Template‐based field map prediction for rapid whole brain B0 shimming

PubMed Central

Shi, Yuhang; Vannesjo, S. Johanna; Miller, Karla L.

2017-01-01

Purpose In typical MRI protocols, time is spent acquiring a field map to calculate the shim settings for best image quality. We propose a fast template‐based field map prediction method that yields near‐optimal shims without measuring the field. Methods The template‐based prediction method uses prior knowledge of the B0 distribution in the human brain, based on a large database of field maps acquired from different subjects, together with subject‐specific structural information from a quick localizer scan. The shimming performance of using the template‐based prediction is evaluated in comparison to a range of potential fast shimming methods. Results Static B0 shimming based on predicted field maps performed almost as well as shimming based on individually measured field maps. In experimental evaluations at 7 T, the proposed approach yielded a residual field standard deviation in the brain of on average 59 Hz, compared with 50 Hz using measured field maps and 176 Hz using no subject‐specific shim. Conclusions This work demonstrates that shimming based on predicted field maps is feasible. The field map prediction accuracy could potentially be further improved by generating the template from a subset of subjects, based on parameters such as head rotation and body mass index. Magn Reson Med 80:171–180, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:29193340

Interindividual registration and dose mapping for voxelwise population analysis of rectal toxicity in prostate cancer radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dréan, Gaël; Acosta, Oscar, E-mail: Oscar.Acosta@univ-rennes1.fr; Simon, Antoine

2016-06-15

Purpose: Recent studies revealed a trend toward voxelwise population analysis in order to understand the local dose/toxicity relationships in prostate cancer radiotherapy. Such approaches require, however, an accurate interindividual mapping of the anatomies and 3D dose distributions toward a common coordinate system. This step is challenging due to the high interindividual variability. In this paper, the authors propose a method designed for interindividual nonrigid registration of the rectum and dose mapping for population analysis. Methods: The method is based on the computation of a normalized structural description of the rectum using a Laplacian-based model. This description takes advantage of themore » tubular structure of the rectum and its centerline to be embedded in a nonrigid registration-based scheme. The performances of the method were evaluated on 30 individuals treated for prostate cancer in a leave-one-out cross validation. Results: Performance was measured using classical metrics (Dice score and Hausdorff distance), along with new metrics devised to better assess dose mapping in relation with structural deformation (dose-organ overlap). Considering these scores, the proposed method outperforms intensity-based and distance maps-based registration methods. Conclusions: The proposed method allows for accurately mapping interindividual 3D dose distributions toward a single anatomical template, opening the way for further voxelwise statistical analysis.« less

Interval data clustering using self-organizing maps based on adaptive Mahalanobis distances.

PubMed

Hajjar, Chantal; Hamdan, Hani

2013-10-01

The self-organizing map is a kind of artificial neural network used to map high dimensional data into a low dimensional space. This paper presents a self-organizing map for interval-valued data based on adaptive Mahalanobis distances in order to do clustering of interval data with topology preservation. Two methods based on the batch training algorithm for the self-organizing maps are proposed. The first method uses a common Mahalanobis distance for all clusters. In the second method, the algorithm starts with a common Mahalanobis distance per cluster and then switches to use a different distance per cluster. This process allows a more adapted clustering for the given data set. The performances of the proposed methods are compared and discussed using artificial and real interval data sets. Copyright © 2013 Elsevier Ltd. All rights reserved.

A technology mapping based on graph of excitations and outputs for finite state machines

NASA Astrophysics Data System (ADS)

Kania, Dariusz; Kulisz, Józef

2017-11-01

A new, efficient technology mapping method of FSMs, dedicated for PAL-based PLDs is proposed. The essence of the method consists in searching for the minimal set of PAL-based logic blocks that cover a set of multiple-output implicants describing the transition and output functions of an FSM. The method is based on a new concept of graph: the Graph of Excitations and Outputs. The proposed algorithm was tested using the FSM benchmarks. The obtained results were compared with the classical technology mapping of FSM.

Improving estimates of genetic maps: a meta-analysis-based approach.

PubMed

Stewart, William C L

2007-07-01

Inaccurate genetic (or linkage) maps can reduce the power to detect linkage, increase type I error, and distort haplotype and relationship inference. To improve the accuracy of existing maps, I propose a meta-analysis-based method that combines independent map estimates into a single estimate of the linkage map. The method uses the variance of each independent map estimate to combine them efficiently, whether the map estimates use the same set of markers or not. As compared with a joint analysis of the pooled genotype data, the proposed method is attractive for three reasons: (1) it has comparable efficiency to the maximum likelihood map estimate when the pooled data are homogeneous; (2) relative to existing map estimation methods, it can have increased efficiency when the pooled data are heterogeneous; and (3) it avoids the practical difficulties of pooling human subjects data. On the basis of simulated data modeled after two real data sets, the proposed method can reduce the sampling variation of linkage maps commonly used in whole-genome linkage scans. Furthermore, when the independent map estimates are also maximum likelihood estimates, the proposed method performs as well as or better than when they are estimated by the program CRIMAP. Since variance estimates of maps may not always be available, I demonstrate the feasibility of three different variance estimators. Overall, the method should prove useful to investigators who need map positions for markers not contained in publicly available maps, and to those who wish to minimize the negative effects of inaccurate maps. Copyright 2007 Wiley-Liss, Inc.

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners.

PubMed

Poynton, Clare B; Chen, Kevin T; Chonde, Daniel B; Izquierdo-Garcia, David; Gollub, Randy L; Gerstner, Elizabeth R; Batchelor, Tracy T; Catana, Ciprian

2014-01-01

We present a new MRI-based attenuation correction (AC) approach for integrated PET/MRI systems that combines both segmentation- and atlas-based methods by incorporating dual-echo ultra-short echo-time (DUTE) and T1-weighted (T1w) MRI data and a probabilistic atlas. Segmented atlases were constructed from CT training data using a leave-one-out framework and combined with T1w, DUTE, and CT data to train a classifier that computes the probability of air/soft tissue/bone at each voxel. This classifier was applied to segment the MRI of the subject of interest and attenuation maps (μ-maps) were generated by assigning specific linear attenuation coefficients (LACs) to each tissue class. The μ-maps generated with this "Atlas-T1w-DUTE" approach were compared to those obtained from DUTE data using a previously proposed method. For validation of the segmentation results, segmented CT μ-maps were considered to the "silver standard"; the segmentation accuracy was assessed qualitatively and quantitatively through calculation of the Dice similarity coefficient (DSC). Relative change (RC) maps between the CT and MRI-based attenuation corrected PET volumes were also calculated for a global voxel-wise assessment of the reconstruction results. The μ-maps obtained using the Atlas-T1w-DUTE classifier agreed well with those derived from CT; the mean DSCs for the Atlas-T1w-DUTE-based μ-maps across all subjects were higher than those for DUTE-based μ-maps; the atlas-based μ-maps also showed a lower percentage of misclassified voxels across all subjects. RC maps from the atlas-based technique also demonstrated improvement in the PET data compared to the DUTE method, both globally as well as regionally.

Guided filter-based fusion method for multiexposure images

NASA Astrophysics Data System (ADS)

Hou, Xinglin; Luo, Haibo; Qi, Feng; Zhou, Peipei

2016-11-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range camera. A weighted sum-based image fusion (IF) algorithm is proposed so as to express an HDR scene with a high-quality image. This method mainly includes three parts. First, two image features, i.e., gradients and well-exposedness are measured to estimate the initial weight maps. Second, the initial weight maps are refined by a guided filter, in which the source image is considered as the guidance image. This process could reduce the noise in initial weight maps and preserve more texture consistent with the original images. Finally, the fused image is constructed by a weighted sum of source images in the spatial domain. The main contributions of this method are the estimation of the initial weight maps and the appropriate use of the guided filter-based weight maps refinement. It provides accurate weight maps for IF. Compared to traditional IF methods, this algorithm avoids image segmentation, combination, and the camera response curve calibration. Furthermore, experimental results demonstrate the superiority of the proposed method in both subjective and objective evaluations.

Mapping Nearshore Seagrass and Colonized Hard Bottom Spatial Distribution and Percent Biological Cover in Florida, USA Using Object Based Image Analysis of WorldView-2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Baumstark, R. D.; Duffey, R.; Pu, R.

2016-12-01

The offshore extent of seagrass habitat along the West Florida (USA) coast represents an important corridor for inshore-offshore migration of economically important fish and shellfish. Surviving at the fringe of light requirements, offshore seagrass beds are sensitive to changes in water clarity. Beyond and intermingled with the offshore seagrass areas are large swaths of colonized hard bottom. These offshore habitats of the West Florida coast have lacked mapping efforts needed for status and trends monitoring. The objective of this study was to propose an object-based classification method for mapping offshore habitats and to compare results to traditional photo-interpreted maps. Benthic maps depicting the spatial distribution and percent biological cover were created from WorldView-2 satellite imagery using Object Based Image Analysis (OBIA) method and a visual photo-interpretation method. A logistic regression analysis identified depth and distance from shore as significant parameters for discriminating spectrally similar seagrass and colonized hard bottom features. Seagrass, colonized hard bottom and unconsolidated sediment (sand) were mapped with 78% overall accuracy using the OBIA method compared to 71% overall accuracy using the photo-interpretation method. This study presents an alternative for mapping deeper, offshore habitats capable of producing higher thematic (percent biological cover) and spatial resolution maps compared to those created with the traditional photo-interpretation method.

Use of multiple cluster analysis methods to explore the validity of a community outcomes concept map.

PubMed

Orsi, Rebecca

2017-02-01

Concept mapping is now a commonly-used technique for articulating and evaluating programmatic outcomes. However, research regarding validity of knowledge and outcomes produced with concept mapping is sparse. The current study describes quantitative validity analyses using a concept mapping dataset. We sought to increase the validity of concept mapping evaluation results by running multiple cluster analysis methods and then using several metrics to choose from among solutions. We present four different clustering methods based on analyses using the R statistical software package: partitioning around medoids (PAM), fuzzy analysis (FANNY), agglomerative nesting (AGNES) and divisive analysis (DIANA). We then used the Dunn and Davies-Bouldin indices to assist in choosing a valid cluster solution for a concept mapping outcomes evaluation. We conclude that the validity of the outcomes map is high, based on the analyses described. Finally, we discuss areas for further concept mapping methods research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT

PubMed Central

Nelson, Scott D; Parker, Jaqui; Lario, Robert; Winnenburg, Rainer; Erlbaum, Mark S.; Lincoln, Michael J.; Bodenreider, Olivier

2018-01-01

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings. PMID:29295234

Building MapObjects attribute field in cadastral database based on the method of Jackson system development

NASA Astrophysics Data System (ADS)

Chen, Zhu-an; Zhang, Li-ting; Liu, Lu

2009-10-01

ESRI's GIS components MapObjects are applied in many cadastral information system because of its miniaturization and flexibility. Some cadastral information was saved in cadastral database directly by MapObjects's Shape file format in this cadastral information system. However, MapObjects didn't provide the function of building attribute field for map layer's attribute data file in cadastral database and user cann't save the result of analysis. This present paper designed and realized the function of building attribute field in MapObjects based on the method of Jackson's system development.

Mapping of bird distributions from point count surveys

USGS Publications Warehouse

Sauer, J.R.; Pendleton, G.W.; Orsillo, Sandra; Ralph, C.J.; Sauer, J.R.; Droege, S.

1995-01-01

Maps generated from bird survey data are used for a variety of scientific purposes, but little is known about their bias and precision. We review methods for preparing maps from point count data and appropriate sampling methods for maps based on point counts. Maps based on point counts can be affected by bias associated with incomplete counts, primarily due to changes in proportion counted as a function of observer or habitat differences. Large-scale surveys also generally suffer from regional and temporal variation in sampling intensity. A simulated surface is used to demonstrate sampling principles for maps.

Three-dimensional mapping of the local interstellar medium with composite data

NASA Astrophysics Data System (ADS)

Capitanio, L.; Lallement, R.; Vergely, J. L.; Elyajouri, M.; Monreal-Ibero, A.

2017-10-01

Context. Three-dimensional maps of the Galactic interstellar medium are general astrophysical tools. Reddening maps may be based on the inversion of color excess measurements for individual target stars or on statistical methods using stellar surveys. Three-dimensional maps based on diffuse interstellar bands (DIBs) have also been produced. All methods benefit from the advent of massive surveys and may benefit from Gaia data. Aims: All of the various methods and databases have their own advantages and limitations. Here we present a first attempt to combine different datasets and methods to improve the local maps. Methods: We first updated our previous local dust maps based on a regularized Bayesian inversion of individual color excess data by replacing Hipparcos or photometric distances with Gaia Data Release 1 values when available. Secondly, we complemented this database with a series of ≃5000 color excess values estimated from the strength of the λ15273 DIB toward stars possessing a Gaia parallax. The DIB strengths were extracted from SDSS/APOGEE spectra. Third, we computed a low-resolution map based on a grid of Pan-STARRS reddening measurements by means of a new hierarchical technique and used this map as the prior distribution during the inversion of the two other datasets. Results: The use of Gaia parallaxes introduces significant changes in some areas and globally increases the compactness of the structures. Additional DIB-based data make it possible to assign distances to clouds located behind closer opaque structures and do not introduce contradictory information for the close structures. A more realistic prior distribution instead of a plane-parallel homogeneous distribution helps better define the structures. We validated the results through comparisons with other maps and with soft X-ray data. Conclusions: Our study demonstrates that the combination of various tracers is a potential tool for more accurate maps. An online tool makes it possible to retrieve maps and reddening estimations. Our online tool is available at http://stilism.obspm.fr

Evolution of regional to global paddy rice mapping methods

NASA Astrophysics Data System (ADS)

Dong, J.; Xiao, X.

2016-12-01

Paddy rice agriculture plays an important role in various environmental issues including food security, water use, climate change, and disease transmission. However, regional and global paddy rice maps are surprisingly scarce and sporadic despite numerous efforts in paddy rice mapping algorithms and applications. In this presentation we would like to review the existing paddy rice mapping methods from the literatures ranging from the 1980s to 2015. In particular, we illustrated the evolution of these paddy rice mapping efforts, looking specifically at the future trajectory of paddy rice mapping methodologies. The biophysical features and growth phases of paddy rice were analyzed first, and feature selections for paddy rice mapping were analyzed from spectral, polarimetric, temporal, spatial, and textural aspects. We sorted out paddy rice mapping algorithms into four categories: 1) Reflectance data and image statistic-based approaches, 2) vegetation index (VI) data and enhanced image statistic-based approaches, 3) VI or RADAR backscatter-based temporal analysis approaches, and 4) phenology-based approaches through remote sensing recognition of key growth phases. The phenology-based approaches using unique features of paddy rice (e.g., transplanting) for mapping have been increasingly used in paddy rice mapping. Based on the literature review, we discussed a series of issues for large scale operational paddy rice mapping.

Ubiquitous Creation of Bas-Relief Surfaces with Depth-of-Field Effects Using Smartphones.

PubMed

Sohn, Bong-Soo

2017-03-11

This paper describes a new method to automatically generate digital bas-reliefs with depth-of-field effects from general scenes. Most previous methods for bas-relief generation take input in the form of 3D models. However, obtaining 3D models of real scenes or objects is often difficult, inaccurate, and time-consuming. From this motivation, we developed a method that takes as input a set of photographs that can be quickly and ubiquitously captured by ordinary smartphone cameras. A depth map is computed from the input photographs. The value range of the depth map is compressed and used as a base map representing the overall shape of the bas-relief. However, the resulting base map contains little information on details of the scene. Thus, we construct a detail map using pixel values of the input image to express the details. The base and detail maps are blended to generate a new depth map that reflects both overall depth and scene detail information. This map is selectively blurred to simulate the depth-of-field effects. The final depth map is converted to a bas-relief surface mesh. Experimental results show that our method generates a realistic bas-relief surface of general scenes with no expensive manual processing.

Ubiquitous Creation of Bas-Relief Surfaces with Depth-of-Field Effects Using Smartphones

PubMed Central

Sohn, Bong-Soo

2017-01-01

This paper describes a new method to automatically generate digital bas-reliefs with depth-of-field effects from general scenes. Most previous methods for bas-relief generation take input in the form of 3D models. However, obtaining 3D models of real scenes or objects is often difficult, inaccurate, and time-consuming. From this motivation, we developed a method that takes as input a set of photographs that can be quickly and ubiquitously captured by ordinary smartphone cameras. A depth map is computed from the input photographs. The value range of the depth map is compressed and used as a base map representing the overall shape of the bas-relief. However, the resulting base map contains little information on details of the scene. Thus, we construct a detail map using pixel values of the input image to express the details. The base and detail maps are blended to generate a new depth map that reflects both overall depth and scene detail information. This map is selectively blurred to simulate the depth-of-field effects. The final depth map is converted to a bas-relief surface mesh. Experimental results show that our method generates a realistic bas-relief surface of general scenes with no expensive manual processing. PMID:28287487

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

NASA Astrophysics Data System (ADS)

Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel

2017-07-01

Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

Medical Image Fusion Based on Feature Extraction and Sparse Representation

PubMed Central

Wei, Gao; Zongxi, Song

2017-01-01

As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods. PMID:28321246

Volumetric calibration of a plenoptic camera.

PubMed

Hall, Elise Munz; Fahringer, Timothy W; Guildenbecher, Daniel R; Thurow, Brian S

2018-02-01

The volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creation of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.

Recognition of building group patterns in topographic maps based on graph partitioning and random forest

NASA Astrophysics Data System (ADS)

He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

2018-02-01

Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

Computerized mappings of the cerebral cortex: a multiresolution flattening method and a surface-based coordinate system

NASA Technical Reports Server (NTRS)

Drury, H. A.; Van Essen, D. C.; Anderson, C. H.; Lee, C. W.; Coogan, T. A.; Lewis, J. W.

1996-01-01

We present a new method for generating two-dimensional maps of the cerebral cortex. Our computerized, two-stage flattening method takes as its input any well-defined representation of a surface within the three-dimensional cortex. The first stage rapidly converts this surface to a topologically correct two-dimensional map, without regard for the amount of distortion introduced. The second stage reduces distortions using a multiresolution strategy that makes gross shape changes on a coarsely sampled map and further shape refinements on progressively finer resolution maps. We demonstrate the utility of this approach by creating flat maps of the entire cerebral cortex in the macaque monkey and by displaying various types of experimental data on such maps. We also introduce a surface-based coordinate system that has advantages over conventional stereotaxic coordinates and is relevant to studies of cortical organization in humans as well as non-human primates. Together, these methods provide an improved basis for quantitative studies of individual variability in cortical organization.

Identification of an EMS-induced causal mutation in a gene required for boron-mediated root development by low-coverage genome re-sequencing in Arabidopsis

PubMed Central

Tabata, Ryo; Kamiya, Takehiro; Shigenobu, Shuji; Yamaguchi, Katsushi; Yamada, Masashi; Hasebe, Mitsuyasu; Fujiwara, Toru; Sawa, Shinichiro

2013-01-01

Next-generation sequencing (NGS) technologies enable the rapid production of an enormous quantity of sequence data. These powerful new technologies allow the identification of mutations by whole-genome sequencing. However, most reported NGS-based mapping methods, which are based on bulked segregant analysis, are costly and laborious. To address these limitations, we designed a versatile NGS-based mapping method that consists of a combination of low- to medium-coverage multiplex SOLiD (Sequencing by Oligonucleotide Ligation and Detection) and classical genetic rough mapping. Using only low to medium coverage reduces the SOLiD sequencing costs and, since just 10 to 20 mutant F2 plants are required for rough mapping, the operation is simple enough to handle in a laboratory with limited space and funding. As a proof of principle, we successfully applied this method to identify the CTR1, which is involved in boron-mediated root development, from among a population of high boron requiring Arabidopsis thaliana mutants. Our work demonstrates that this NGS-based mapping method is a moderately priced and versatile method that can readily be applied to other model organisms. PMID:23104114

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners

PubMed Central

Poynton, Clare B; Chen, Kevin T; Chonde, Daniel B; Izquierdo-Garcia, David; Gollub, Randy L; Gerstner, Elizabeth R; Batchelor, Tracy T; Catana, Ciprian

2014-01-01

We present a new MRI-based attenuation correction (AC) approach for integrated PET/MRI systems that combines both segmentation- and atlas-based methods by incorporating dual-echo ultra-short echo-time (DUTE) and T1-weighted (T1w) MRI data and a probabilistic atlas. Segmented atlases were constructed from CT training data using a leave-one-out framework and combined with T1w, DUTE, and CT data to train a classifier that computes the probability of air/soft tissue/bone at each voxel. This classifier was applied to segment the MRI of the subject of interest and attenuation maps (μ-maps) were generated by assigning specific linear attenuation coefficients (LACs) to each tissue class. The μ-maps generated with this “Atlas-T1w-DUTE” approach were compared to those obtained from DUTE data using a previously proposed method. For validation of the segmentation results, segmented CT μ-maps were considered to the “silver standard”; the segmentation accuracy was assessed qualitatively and quantitatively through calculation of the Dice similarity coefficient (DSC). Relative change (RC) maps between the CT and MRI-based attenuation corrected PET volumes were also calculated for a global voxel-wise assessment of the reconstruction results. The μ-maps obtained using the Atlas-T1w-DUTE classifier agreed well with those derived from CT; the mean DSCs for the Atlas-T1w-DUTE-based μ-maps across all subjects were higher than those for DUTE-based μ-maps; the atlas-based μ-maps also showed a lower percentage of misclassified voxels across all subjects. RC maps from the atlas-based technique also demonstrated improvement in the PET data compared to the DUTE method, both globally as well as regionally. PMID:24753982

Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.

PubMed

He, Jianbo; Li, Jijie; Huang, Zhongwen; Zhao, Tuanjie; Xing, Guangnan; Gai, Junyi; Guan, Rongzhan

2015-01-01

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively.

Design of an image encryption scheme based on a multiple chaotic map

NASA Astrophysics Data System (ADS)

Tong, Xiao-Jun

2013-07-01

In order to solve the problem that chaos is degenerated in limited computer precision and Cat map is the small key space, this paper presents a chaotic map based on topological conjugacy and the chaotic characteristics are proved by Devaney definition. In order to produce a large key space, a Cat map named block Cat map is also designed for permutation process based on multiple-dimensional chaotic maps. The image encryption algorithm is based on permutation-substitution, and each key is controlled by different chaotic maps. The entropy analysis, differential analysis, weak-keys analysis, statistical analysis, cipher random analysis, and cipher sensibility analysis depending on key and plaintext are introduced to test the security of the new image encryption scheme. Through the comparison to the proposed scheme with AES, DES and Logistic encryption methods, we come to the conclusion that the image encryption method solves the problem of low precision of one dimensional chaotic function and has higher speed and higher security.

Mapping seagrass and colonized hard bottom in Springs Coast, Florida using WorldView-2 satellite imagery

NASA Astrophysics Data System (ADS)

Baumstark, René; Duffey, Renee; Pu, Ruiliang

2016-11-01

The offshore extent of seagrass habitat along the West Florida (USA) coast represents an important corridor for inshore-offshore migration of economically important fish and shellfish. Surviving at the fringe of light requirements, offshore seagrass beds are sensitive to changes in water clarity. Beyond and intermingled with the offshore seagrass areas are large swaths of colonized hard bottom. These offshore habitats of the West Florida coast have lacked mapping efforts needed for status and trends monitoring. The objective of this study was to propose an object-based classification method for mapping offshore habitats and to compare results to traditional photo-interpreted maps. Benthic maps were created from WorldView-2 satellite imagery using an Object Based Image Analysis (OBIA) method and a visual photo-interpretation method. A logistic regression analysis identified depth and distance from shore as significant parameters for discriminating spectrally similar seagrass and colonized hard bottom features. Seagrass, colonized hard bottom and unconsolidated sediment (sand) were mapped with 78% overall accuracy using the OBIA method compared to 71% overall accuracy using the photo-interpretation method. This study suggests an alternative for mapping deeper, offshore habitats capable of producing higher thematic and spatial resolution maps compared to those created with the traditional photo-interpretation method.

Comparing census methods for the endangered Kirtland's Warbler

Treesearch

John R. Probst; Deahn M. Donner; Mike Worland; Jerry Weinrich; Phillip Huber; Kenneth R. Ennis

2005-01-01

We compared transect counts used for the annual official count of male Kirtland`s Warblers (Dendroica kirtlandii) to an observation-based mapping method of individually sighted males in 155 stands over 10 yrs. The annual census count almost tripled from 1990 to 1999. The transect and observation-based mapping method showed the same increasing trend...

An efficient cardiac mapping strategy for radiofrequency catheter ablation with active learning.

PubMed

Feng, Yingjing; Guo, Ziyan; Dong, Ziyang; Zhou, Xiao-Yun; Kwok, Ka-Wai; Ernst, Sabine; Lee, Su-Lin

2017-07-01

A major challenge in radiofrequency catheter ablation procedures is the voltage and activation mapping of the endocardium, given a limited mapping time. By learning from expert interventional electrophysiologists (operators), while also making use of an active-learning framework, guidance on performing cardiac voltage mapping can be provided to novice operators or even directly to catheter robots. A learning from demonstration (LfD) framework, based upon previous cardiac mapping procedures performed by an expert operator, in conjunction with Gaussian process (GP) model-based active learning, was developed to efficiently perform voltage mapping over right ventricles (RV). The GP model was used to output the next best mapping point, while getting updated towards the underlying voltage data pattern as more mapping points are taken. A regularized particle filter was used to keep track of the kernel hyperparameter used by GP. The travel cost of the catheter tip was incorporated to produce time-efficient mapping sequences. The proposed strategy was validated on a simulated 2D grid mapping task, with leave-one-out experiments on 25 retrospective datasets, in an RV phantom using the Stereotaxis Niobe ® remote magnetic navigation system, and on a tele-operated catheter robot. In comparison with an existing geometry-based method, regression error was reduced and was minimized at a faster rate over retrospective procedure data. A new method of catheter mapping guidance has been proposed based on LfD and active learning. The proposed method provides real-time guidance for the procedure, as well as a live evaluation of mapping sufficiency.

Infrared and visible image fusion method based on saliency detection in sparse domain

NASA Astrophysics Data System (ADS)

Liu, C. H.; Qi, Y.; Ding, W. R.

2017-06-01

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion. To better preserve the significant information of the infrared and visible images in the final fused image, the saliency maps of the source images is introduced into the fusion procedure. Firstly, under the framework of the joint sparse representation (JSR) model, the global and local saliency maps of the source images are obtained based on sparse coefficients. Then, a saliency detection model is proposed, which combines the global and local saliency maps to generate an integrated saliency map. Finally, a weighted fusion algorithm based on the integrated saliency map is developed to achieve the fusion progress. The experimental results show that our method is superior to the state-of-the-art methods in terms of several universal quality evaluation indexes, as well as in the visual quality.

An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing

USGS Publications Warehouse

Pelletier, J.D.; Mayer, L.; Pearthree, P.A.; House, P.K.; Demsey, K.A.; Klawon, J.K.; Vincent, K.R.

2005-01-01

Millions of people in the western United States live near the dynamic, distributary channel networks of alluvial fans where flood behavior is complex and poorly constrained. Here we test a new comprehensive approach to alluvial-fan flood hazard assessment that uses four complementary methods: two-dimensional raster-based hydraulic modeling, satellite-image change detection, fieldbased mapping of recent flood inundation, and surficial geologic mapping. Each of these methods provides spatial detail lacking in the standard method and each provides critical information for a comprehensive assessment. Our numerical model simultaneously solves the continuity equation and Manning's equation (Chow, 1959) using an implicit numerical method. It provides a robust numerical tool for predicting flood flows using the large, high-resolution Digital Elevation Models (DEMs) necessary to resolve the numerous small channels on the typical alluvial fan. Inundation extents and flow depths of historic floods can be reconstructed with the numerical model and validated against field- and satellite-based flood maps. A probabilistic flood hazard map can also be constructed by modeling multiple flood events with a range of specified discharges. This map can be used in conjunction with a surficial geologic map to further refine floodplain delineation on fans. To test the accuracy of the numerical model, we compared model predictions of flood inundation and flow depths against field- and satellite-based flood maps for two recent extreme events on the southern Tortolita and Harquahala piedmonts in Arizona. Model predictions match the field- and satellite-based maps closely. Probabilistic flood hazard maps based on the 10 yr, 100 yr, and maximum floods were also constructed for the study areas using stream gage records and paleoflood deposits. The resulting maps predict spatially complex flood hazards that strongly reflect small-scale topography and are consistent with surficial geology. In contrast, FEMA Flood Insurance Rate Maps (FIRMs) based on the FAN model predict uniformly high flood risk across the study areas without regard for small-scale topography and surficial geology. ?? 2005 Geological Society of America.

An Improved Map-Matching Technique Based on the Fréchet Distance Approach for Pedestrian Navigation Services

PubMed Central

Bang, Yoonsik; Kim, Jiyoung; Yu, Kiyun

2016-01-01

Wearable and smartphone technology innovations have propelled the growth of Pedestrian Navigation Services (PNS). PNS need a map-matching process to project a user’s locations onto maps. Many map-matching techniques have been developed for vehicle navigation services. These techniques are inappropriate for PNS because pedestrians move, stop, and turn in different ways compared to vehicles. In addition, the base map data for pedestrians are more complicated than for vehicles. This article proposes a new map-matching method for locating Global Positioning System (GPS) trajectories of pedestrians onto road network datasets. The theory underlying this approach is based on the Fréchet distance, one of the measures of geometric similarity between two curves. The Fréchet distance approach can provide reasonable matching results because two linear trajectories are parameterized with the time variable. Then we improved the method to be adaptive to the positional error of the GPS signal. We used an adaptation coefficient to adjust the search range for every input signal, based on the assumption of auto-correlation between consecutive GPS points. To reduce errors in matching, the reliability index was evaluated in real time for each match. To test the proposed map-matching method, we applied it to GPS trajectories of pedestrians and the road network data. We then assessed the performance by comparing the results with reference datasets. Our proposed method performed better with test data when compared to a conventional map-matching technique for vehicles. PMID:27782091

System and method for generating a deselect mapping for a focal plane array

DOEpatents

Bixler, Jay V; Brandt, Timothy G; Conger, James L; Lawson, Janice K

2013-05-21

A method for generating a deselect mapping for a focal plane array according to one embodiment includes gathering a data set for a focal plane array when exposed to light or radiation from a first known target; analyzing the data set for determining which pixels or subpixels of the focal plane array to add to a deselect mapping; adding the pixels or subpixels to the deselect mapping based on the analysis; and storing the deselect mapping. A method for gathering data using a focal plane array according to another embodiment includes deselecting pixels or subpixels based on a deselect mapping; gathering a data set using pixels or subpixels in a focal plane array that are not deselected upon exposure thereof to light or radiation from a target of interest; and outputting the data set.

Generating Broad-Scale Forest Ownership Maps: A Closest-Neighbor Approach

Treesearch

Brett J. Butler

2005-01-01

A closest-neighbor method for producing a forest ownership map using remotely sensed imagery and point-based ownership information is presented for the Northeastern United States. Based on a validation data set, this method had an accuracy rate of 58 percent.

A Different Web-Based Geocoding Service Using Fuzzy Techniques

NASA Astrophysics Data System (ADS)

Pahlavani, P.; Abbaspour, R. A.; Zare Zadiny, A.

2015-12-01

Geocoding - the process of finding position based on descriptive data such as address or postal code - is considered as one of the most commonly used spatial analyses. Many online map providers such as Google Maps, Bing Maps and Yahoo Maps present geocoding as one of their basic capabilities. Despite the diversity of geocoding services, users usually face some limitations when they use available online geocoding services. In existing geocoding services, proximity and nearness concept is not modelled appropriately as well as these services search address only by address matching based on descriptive data. In addition there are also some limitations in display searching results. Resolving these limitations can enhance efficiency of the existing geocoding services. This paper proposes the idea of integrating fuzzy technique with geocoding process to resolve these limitations. In order to implement the proposed method, a web-based system is designed. In proposed method, nearness to places is defined by fuzzy membership functions and multiple fuzzy distance maps are created. Then these fuzzy distance maps are integrated using fuzzy overlay technique for obtain the results. Proposed methods provides different capabilities for users such as ability to search multi-part addresses, searching places based on their location, non-point representation of results as well as displaying search results based on their priority.

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2012-01-01

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.

Volumetric calibration of a plenoptic camera

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hall, Elise Munz; Fahringer, Timothy W.; Guildenbecher, Daniel Robert

Here, the volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creationmore » of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.« less

Volumetric calibration of a plenoptic camera

DOE PAGES

Hall, Elise Munz; Fahringer, Timothy W.; Guildenbecher, Daniel Robert; ...

2018-02-01

Here, the volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creationmore » of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.« less

Automatic Polyp Detection via A Novel Unified Bottom-up and Top-down Saliency Approach.

PubMed

Yuan, Yixuan; Li, Dengwang; Meng, Max Q-H

2017-07-31

In this paper, we propose a novel automatic computer-aided method to detect polyps for colonoscopy videos. To find the perceptually and semantically meaningful salient polyp regions, we first segment images into multilevel superpixels. Each level corresponds to different sizes of superpixels. Rather than adopting hand-designed features to describe these superpixels in images, we employ sparse autoencoder (SAE) to learn discriminative features in an unsupervised way. Then a novel unified bottom-up and top-down saliency method is proposed to detect polyps. In the first stage, we propose a weak bottom-up (WBU) saliency map by fusing the contrast based saliency and object-center based saliency together. The contrast based saliency map highlights image parts that show different appearances compared with surrounding areas while the object-center based saliency map emphasizes the center of the salient object. In the second stage, a strong classifier with Multiple Kernel Boosting (MKB) is learned to calculate the strong top-down (STD) saliency map based on samples directly from the obtained multi-level WBU saliency maps. We finally integrate these two stage saliency maps from all levels together to highlight polyps. Experiment results achieve 0.818 recall for saliency calculation, validating the effectiveness of our method. Extensive experiments on public polyp datasets demonstrate that the proposed saliency algorithm performs favorably against state-of-the-art saliency methods to detect polyps.

Impervious surface mapping with Quickbird imagery

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio

2010-01-01

This research selects two study areas with different urban developments, sizes, and spatial patterns to explore the suitable methods for mapping impervious surface distribution using Quickbird imagery. The selected methods include per-pixel based supervised classification, segmentation-based classification, and a hybrid method. A comparative analysis of the results indicates that per-pixel based supervised classification produces a large number of “salt-and-pepper” pixels, and segmentation based methods can significantly reduce this problem. However, neither method can effectively solve the spectral confusion of impervious surfaces with water/wetland and bare soils and the impacts of shadows. In order to accurately map impervious surface distribution from Quickbird images, manual editing is necessary and may be the only way to extract impervious surfaces from the confused land covers and the shadow problem. This research indicates that the hybrid method consisting of thresholding techniques, unsupervised classification and limited manual editing provides the best performance. PMID:21643434

Fully Convolutional Network-Based Multifocus Image Fusion.

PubMed

Guo, Xiaopeng; Nie, Rencan; Cao, Jinde; Zhou, Dongming; Qian, Wenhua

2018-07-01

As the optical lenses for cameras always have limited depth of field, the captured images with the same scene are not all in focus. Multifocus image fusion is an efficient technology that can synthesize an all-in-focus image using several partially focused images. Previous methods have accomplished the fusion task in spatial or transform domains. However, fusion rules are always a problem in most methods. In this letter, from the aspect of focus region detection, we propose a novel multifocus image fusion method based on a fully convolutional network (FCN) learned from synthesized multifocus images. The primary novelty of this method is that the pixel-wise focus regions are detected through a learning FCN, and the entire image, not just the image patches, are exploited to train the FCN. First, we synthesize 4500 pairs of multifocus images by repeatedly using a gaussian filter for each image from PASCAL VOC 2012, to train the FCN. After that, a pair of source images is fed into the trained FCN, and two score maps indicating the focus property are generated. Next, an inversed score map is averaged with another score map to produce an aggregative score map, which take full advantage of focus probabilities in two score maps. We implement the fully connected conditional random field (CRF) on the aggregative score map to accomplish and refine a binary decision map for the fusion task. Finally, we exploit the weighted strategy based on the refined decision map to produce the fused image. To demonstrate the performance of the proposed method, we compare its fused results with several start-of-the-art methods not only on a gray data set but also on a color data set. Experimental results show that the proposed method can achieve superior fusion performance in both human visual quality and objective assessment.

Evolution of regional to global paddy rice mapping methods: A review

NASA Astrophysics Data System (ADS)

Dong, Jinwei; Xiao, Xiangming

2016-09-01

Paddy rice agriculture plays an important role in various environmental issues including food security, water use, climate change, and disease transmission. However, regional and global paddy rice maps are surprisingly scarce and sporadic despite numerous efforts in paddy rice mapping algorithms and applications. With the increasing need for regional to global paddy rice maps, this paper reviewed the existing paddy rice mapping methods from the literatures ranging from the 1980s to 2015. In particular, we illustrated the evolution of these paddy rice mapping efforts, looking specifically at the future trajectory of paddy rice mapping methodologies. The biophysical features and growth phases of paddy rice were analyzed first, and feature selections for paddy rice mapping were analyzed from spectral, polarimetric, temporal, spatial, and textural aspects. We sorted out paddy rice mapping algorithms into four categories: (1) Reflectance data and image statistic-based approaches, (2) vegetation index (VI) data and enhanced image statistic-based approaches, (3) VI or RADAR backscatter-based temporal analysis approaches, and (4) phenology-based approaches through remote sensing recognition of key growth phases. The phenology-based approaches using unique features of paddy rice (e.g., transplanting) for mapping have been increasingly used in paddy rice mapping. Current applications of these phenology-based approaches generally use coarse resolution MODIS data, which involves mixed pixel issues in Asia where smallholders comprise the majority of paddy rice agriculture. The free release of Landsat archive data and the launch of Landsat 8 and Sentinel-2 are providing unprecedented opportunities to map paddy rice in fragmented landscapes with higher spatial resolution. Based on the literature review, we discussed a series of issues for large scale operational paddy rice mapping.

Infrared small target detection based on directional zero-crossing measure

NASA Astrophysics Data System (ADS)

Zhang, Xiangyue; Ding, Qinghai; Luo, Haibo; Hui, Bin; Chang, Zheng; Zhang, Junchao

2017-12-01

Infrared small target detection under complex background and low signal-to-clutter ratio (SCR) condition is of great significance to the development on precision guidance and infrared surveillance. In order to detect targets precisely and extract targets from intricate clutters effectively, a detection method based on zero-crossing saliency (ZCS) map is proposed. The original map is first decomposed into different first-order directional derivative (FODD) maps by using FODD filters. Then the ZCS map is obtained by fusing all directional zero-crossing points. At last, an adaptive threshold is adopted to segment targets from the ZCS map. Experimental results on a series of images show that our method is effective and robust for detection under complex backgrounds. Moreover, compared with other five state-of-the-art methods, our method achieves better performance in terms of detection rate, SCR gain and background suppression factor.

Hotspot detection in pancreatic neuroendocrine tumors: density approximation by α-shape maps

NASA Astrophysics Data System (ADS)

Niazi, M. K. K.; Hartman, Douglas J.; Pantanowitz, Liron; Gurcan, Metin N.

2016-03-01

The grading of neuroendocrine tumors of the digestive system is dependent on accurate and reproducible assessment of the proliferation with the tumor, either by counting mitotic figures or counting Ki-67 positive nuclei. At the moment, most pathologists manually identify the hotspots, a practice which is tedious and irreproducible. To better help pathologists, we present an automatic method to detect all potential hotspots in neuroendocrine tumors of the digestive system. The method starts by segmenting Ki-67 positive nuclei by entropy based thresholding, followed by detection of centroids for all Ki-67 positive nuclei. Based on geodesic distance, approximated by the nuclei centroids, we compute two maps: an amoeba map and a weighted amoeba map. These maps are later combined to generate the heat map, the segmentation of which results in the hotspots. The method was trained on three and tested on nine whole slide images of neuroendocrine tumors. When evaluated by two expert pathologists, the method reached an accuracy of 92.6%. The current method does not discriminate between tumor, stromal and inflammatory nuclei. The results show that α-shape maps may represent how hotspots are perceived.

Machine learning-based dual-energy CT parametric mapping

NASA Astrophysics Data System (ADS)

Su, Kuan-Hao; Kuo, Jung-Wen; Jordan, David W.; Van Hedent, Steven; Klahr, Paul; Wei, Zhouping; Helo, Rose Al; Liang, Fan; Qian, Pengjiang; Pereira, Gisele C.; Rassouli, Negin; Gilkeson, Robert C.; Traughber, Bryan J.; Cheng, Chee-Wai; Muzic, Raymond F., Jr.

2018-06-01

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Zeff), relative electron density (ρ e), mean excitation energy (I x ), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 s. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency.

Machine learning-based dual-energy CT parametric mapping.

PubMed

Su, Kuan-Hao; Kuo, Jung-Wen; Jordan, David W; Van Hedent, Steven; Klahr, Paul; Wei, Zhouping; Al Helo, Rose; Liang, Fan; Qian, Pengjiang; Pereira, Gisele C; Rassouli, Negin; Gilkeson, Robert C; Traughber, Bryan J; Cheng, Chee-Wai; Muzic, Raymond F

2018-06-08

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Z eff ), relative electron density (ρ e ), mean excitation energy (I x ), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 s. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency.

Assessing Changes in High School Students' Conceptual Understanding through Concept Maps before and after the Computer-Based Predict-Observe-Explain (CB-POE) Tasks on Acid-Base Chemistry at the Secondary Level

ERIC Educational Resources Information Center

Yaman, Fatma; Ayas, Alipasa

2015-01-01

Although concept maps have been used as alternative assessment methods in education, there has been an ongoing debate on how to evaluate students' concept maps. This study discusses how to evaluate students' concept maps as an assessment tool before and after 15 computer-based Predict-Observe-Explain (CB-POE) tasks related to acid-base chemistry.…

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor.

PubMed

Kim, Heegwang; Park, Jinho; Park, Hasil; Paik, Joonki

2017-12-09

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system.

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor

PubMed Central

Park, Jinho; Park, Hasil

2017-01-01

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system. PMID:29232826

Averaged ratio between complementary profiles for evaluating shape distortions of map projections and spherical hierarchical tessellations

NASA Astrophysics Data System (ADS)

Yan, Jin; Song, Xiao; Gong, Guanghong

2016-02-01

We describe a metric named averaged ratio between complementary profiles to represent the distortion of map projections, and the shape regularity of spherical cells derived from map projections or non-map-projection methods. The properties and statistical characteristics of our metric are investigated. Our metric (1) is a variable of numerical equivalence to both scale component and angular deformation component of Tissot indicatrix, and avoids the invalidation when using Tissot indicatrix and derived differential calculus for evaluating non-map-projection based tessellations where mathematical formulae do not exist (e.g., direct spherical subdivisions), (2) exhibits simplicity (neither differential nor integral calculus) and uniformity in the form of calculations, (3) requires low computational cost, while maintaining high correlation with the results of differential calculus, (4) is a quasi-invariant under rotations, and (5) reflects the distortions of map projections, distortion of spherical cells, and the associated distortions of texels. As an indicator of quantitative evaluation, we investigated typical spherical tessellation methods, some variants of tessellation methods, and map projections. The tessellation methods we evaluated are based on map projections or direct spherical subdivisions. The evaluation involves commonly used Platonic polyhedrons, Catalan polyhedrons, etc. Quantitative analyses based on our metric of shape regularity and an essential metric of area uniformity implied that (1) Uniform Spherical Grids and its variant show good qualities in both area uniformity and shape regularity, and (2) Crusta, Unicube map, and a variant of Unicube map exhibit fairly acceptable degrees of area uniformity and shape regularity.

Aorta modeling with the element-based zero-stress state and isogeometric discretization

NASA Astrophysics Data System (ADS)

Takizawa, Kenji; Tezduyar, Tayfun E.; Sasaki, Takafumi

2017-02-01

Patient-specific arterial fluid-structure interaction computations, including aorta computations, require an estimation of the zero-stress state (ZSS), because the image-based arterial geometries do not come from a ZSS. We have earlier introduced a method for estimation of the element-based ZSS (EBZSS) in the context of finite element discretization of the arterial wall. The method has three main components. 1. An iterative method, which starts with a calculated initial guess, is used for computing the EBZSS such that when a given pressure load is applied, the image-based target shape is matched. 2. A method for straight-tube segments is used for computing the EBZSS so that we match the given diameter and longitudinal stretch in the target configuration and the "opening angle." 3. An element-based mapping between the artery and straight-tube is extracted from the mapping between the artery and straight-tube segments. This provides the mapping from the arterial configuration to the straight-tube configuration, and from the estimated EBZSS of the straight-tube configuration back to the arterial configuration, to be used as the initial guess for the iterative method that matches the image-based target shape. Here we present the version of the EBZSS estimation method with isogeometric wall discretization. With isogeometric discretization, we can obtain the element-based mapping directly, instead of extracting it from the mapping between the artery and straight-tube segments. That is because all we need for the element-based mapping, including the curvatures, can be obtained within an element. With NURBS basis functions, we may be able to achieve a similar level of accuracy as with the linear basis functions, but using larger-size and much fewer elements. Higher-order NURBS basis functions allow representation of more complex shapes within an element. To show how the new EBZSS estimation method performs, we first present 2D test computations with straight-tube configurations. Then we show how the method can be used in a 3D computation where the target geometry is coming from medical image of a human aorta.

Translation from the collaborative OSM database to cartography

NASA Astrophysics Data System (ADS)

Hayat, Flora

2018-05-01

The OpenStreetMap (OSM) database includes original items very useful for geographical analysis and for creating thematic maps. Contributors record in the open database various themes regarding amenities, leisure, transports, buildings and boundaries. The Michelin mapping department develops map prototypes to test the feasibility of mapping based on OSM. To translate the OSM database structure into a database structure fitted with Michelin graphic guidelines a research project is in development. It aims at defining the right structure for the Michelin uses. The research project relies on the analysis of semantic and geometric heterogeneities in OSM data. In that order, Michelin implements methods to transform the input geographical database into a cartographic image dedicated for specific uses (routing and tourist maps). The paper focuses on the mapping tools available to produce a personalised spatial database. Based on processed data, paper and Web maps can be displayed. Two prototypes are described in this article: a vector tile web map and a mapping method to produce paper maps on a regional scale. The vector tile mapping method offers an easy navigation within the map and within graphic and thematic guide- lines. Paper maps can be partly automatically drawn. The drawing automation and data management are part of the mapping creation as well as the final hand-drawing phase. Both prototypes have been set up using the OSM technical ecosystem.

Systems and methods that generate height map models for efficient three dimensional reconstruction from depth information

DOEpatents

Frahm, Jan-Michael; Pollefeys, Marc Andre Leon; Gallup, David Robert

2015-12-08

Methods of generating a three dimensional representation of an object in a reference plane from a depth map including distances from a reference point to pixels in an image of the object taken from a reference point. Weights are assigned to respective voxels in a three dimensional grid along rays extending from the reference point through the pixels in the image based on the distances in the depth map from the reference point to the respective pixels, and a height map including an array of height values in the reference plane is formed based on the assigned weights. An n-layer height map may be constructed by generating a probabilistic occupancy grid for the voxels and forming an n-dimensional height map comprising an array of layer height values in the reference plane based on the probabilistic occupancy grid.

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots

PubMed Central

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-01-01

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed. PMID:29186843

Effectiveness of higher order thinking skills (HOTS) based i-Think map concept towards primary students

NASA Astrophysics Data System (ADS)

Ping, Owi Wei; Ahmad, Azhar; Adnan, Mazlini; Hua, Ang Kean

2017-05-01

Higher Order Thinking Skills (HOTS) is a new concept of education reform based on the Taxonomies Bloom. The concept concentrate on student understanding in learning process based on their own methods. Through the HOTS questions are able to train students to think creatively, critic and innovative. The aim of this study was to identify the student's proficiency in solving HOTS Mathematics question by using i-Think map. This research takes place in Sabak Bernam, Selangor. The method applied is quantitative approach that involves approximately all of the standard five students. Pra-posttest was conduct before and after the intervention using i-Think map in solving the HOTS questions. The result indicates significant improvement for post-test, which prove that applying i-Think map enhance the students ability to solve HOTS question. Survey's analysis showed 90% of the students agree having i-Thinking map in analysis the question carefully and using keywords in the map to solve the questions. As conclusion, this process benefits students to minimize in making the mistake when solving the questions. Therefore, teachers are necessarily to guide students in applying the eligible i-Think map and methods in analyzing the question through finding the keywords.

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots.

PubMed

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-11-25

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed.

A Radio-Map Automatic Construction Algorithm Based on Crowdsourcing

PubMed Central

Yu, Ning; Xiao, Chenxian; Wu, Yinfeng; Feng, Renjian

2016-01-01

Traditional radio-map-based localization methods need to sample a large number of location fingerprints offline, which requires huge amount of human and material resources. To solve the high sampling cost problem, an automatic radio-map construction algorithm based on crowdsourcing is proposed. The algorithm employs the crowd-sourced information provided by a large number of users when they are walking in the buildings as the source of location fingerprint data. Through the variation characteristics of users’ smartphone sensors, the indoor anchors (doors) are identified and their locations are regarded as reference positions of the whole radio-map. The AP-Cluster method is used to cluster the crowdsourced fingerprints to acquire the representative fingerprints. According to the reference positions and the similarity between fingerprints, the representative fingerprints are linked to their corresponding physical locations and the radio-map is generated. Experimental results demonstrate that the proposed algorithm reduces the cost of fingerprint sampling and radio-map construction and guarantees the localization accuracy. The proposed method does not require users’ explicit participation, which effectively solves the resource-consumption problem when a location fingerprint database is established. PMID:27070623

Determination of skeleton and sign map for phase obtaining from a single ESPI image

NASA Astrophysics Data System (ADS)

Yang, Xia; Yu, Qifeng; Fu, Sihua

2009-06-01

A robust method of determining the sign map and skeletons for ESPI images is introduced in this paper. ESPI images have high speckle noise which makes it difficult to obtain the fringe information, especially from a single image. To overcome the effects of high speckle noise, local directional computing windows are designed according to the fringe directions. Then by calculating the gradients from the filtered image in directional windows, sign map and good skeletons can be determined robustly. Based on the sign map, single image phase-extracting methods such as quadrature transform can be improved. And based on skeletons, fringe phases can be obtained directly by normalization methods. Experiments show that this new method is robust and effective for extracting phase from a single ESPI fringe image.

Time-efficient high-resolution whole-brain three-dimensional macromolecular proton fraction mapping

PubMed Central

Yarnykh, Vasily L.

2015-01-01

Purpose Macromolecular proton fraction (MPF) mapping is a quantitative MRI method that reconstructs parametric maps of a relative amount of macromolecular protons causing the magnetization transfer (MT) effect and provides a biomarker of myelination in neural tissues. This study aimed to develop a high-resolution whole-brain MPF mapping technique utilizing a minimal possible number of source images for scan time reduction. Methods The described technique is based on replacement of an actually acquired reference image without MT saturation by a synthetic one reconstructed from R1 and proton density maps, thus requiring only three source images. This approach enabled whole-brain three-dimensional MPF mapping with isotropic 1.25×1.25×1.25 mm3 voxel size and scan time of 20 minutes. The synthetic reference method was validated against standard MPF mapping with acquired reference images based on data from 8 healthy subjects. Results Mean MPF values in segmented white and gray matter appeared in close agreement with no significant bias and small within-subject coefficients of variation (<2%). High-resolution MPF maps demonstrated sharp white-gray matter contrast and clear visualization of anatomical details including gray matter structures with high iron content. Conclusions Synthetic reference method improves resolution of MPF mapping and combines accurate MPF measurements with unique neuroanatomical contrast features. PMID:26102097

Multi-focus image fusion using a guided-filter-based difference image.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

2016-03-20

The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

Predicting "Hot" and "Warm" Spots for Fragment Binding.

PubMed

Rathi, Prakash Chandra; Ludlow, R Frederick; Hall, Richard J; Murray, Christopher W; Mortenson, Paul N; Verdonk, Marcel L

2017-05-11

Computational fragment mapping methods aim to predict hotspots on protein surfaces where small fragments will bind. Such methods are popular for druggability assessment as well as structure-based design. However, to date researchers developing or using such tools have had no clear way of assessing the performance of these methods. Here, we introduce the first diverse, high quality validation set for computational fragment mapping. The set contains 52 diverse examples of fragment binding "hot" and "warm" spots from the Protein Data Bank (PDB). Additionally, we describe PLImap, a novel protocol for fragment mapping based on the Protein-Ligand Informatics force field (PLIff). We evaluate PLImap against the new fragment mapping test set, and compare its performance to that of simple shape-based algorithms and fragment docking using GOLD. PLImap is made publicly available from https://bitbucket.org/AstexUK/pli .

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hub, Martina; Thieke, Christian; Kessler, Marc L.

2012-04-15

Purpose: In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation. Methods: This method accounts formore » the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known. Results: The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected. Conclusions: An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well.« less

A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration

PubMed Central

Hub, Martina; Thieke, Christian; Kessler, Marc L.; Karger, Christian P.

2012-01-01

Purpose: In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation. Methods: This method accounts for the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known. Results: The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected. Conclusions: An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well. PMID:22482640

Maps and navigation methods

NASA Technical Reports Server (NTRS)

Duval, A

1922-01-01

Different maps and scales are discussed with particular emphasis on their use in aviation. The author makes the observation that current navigation methods are slow and dangerous and should be replaced by scientific methods of navigation based on loxodromy and the use of the compass.

Multiresolution saliency map based object segmentation

NASA Astrophysics Data System (ADS)

Yang, Jian; Wang, Xin; Dai, ZhenYou

2015-11-01

Salient objects' detection and segmentation are gaining increasing research interest in recent years. A saliency map can be obtained from different models presented in previous studies. Based on this saliency map, the most salient region (MSR) in an image can be extracted. This MSR, generally a rectangle, can be used as the initial parameters for object segmentation algorithms. However, to our knowledge, all of those saliency maps are represented in a unitary resolution although some models have even introduced multiscale principles in the calculation process. Furthermore, some segmentation methods, such as the well-known GrabCut algorithm, need more iteration time or additional interactions to get more precise results without predefined pixel types. A concept of a multiresolution saliency map is introduced. This saliency map is provided in a multiresolution format, which naturally follows the principle of the human visual mechanism. Moreover, the points in this map can be utilized to initialize parameters for GrabCut segmentation by labeling the feature pixels automatically. Both the computing speed and segmentation precision are evaluated. The results imply that this multiresolution saliency map-based object segmentation method is simple and efficient.

Toward an operational framework for fine-scale urban land-cover mapping in Wallonia using submeter remote sensing and ancillary vector data

NASA Astrophysics Data System (ADS)

Beaumont, Benjamin; Grippa, Tais; Lennert, Moritz; Vanhuysse, Sabine; Stephenne, Nathalie; Wolff, Eléonore

2017-07-01

Encouraged by the EU INSPIRE directive requirements and recommendations, the Walloon authorities, similar to other EU regional or national authorities, want to develop operational land-cover (LC) and land-use (LU) mapping methods using existing geodata. Urban planners and environmental monitoring stakeholders of Wallonia have to rely on outdated, mixed, and incomplete LC and LU information. The current reference map is 10-years old. The two object-based classification methods, i.e., a rule- and a classifier-based method, for detailed regional urban LC mapping are compared. The added value of using the different existing geospatial datasets in the process is assessed. This includes the comparison between satellite and aerial optical data in terms of mapping accuracies, visual quality of the map, costs, processing, data availability, and property rights. The combination of spectral, tridimensional, and vector data provides accuracy values close to 0.90 for mapping the LC into nine categories with a minimum mapping unit of 15 m2. Such a detailed LC map offers opportunities for fine-scale environmental and spatial planning activities. Still, the regional application poses challenges regarding automation, big data handling, and processing time, which are discussed.

a Mapping Method of Slam Based on Look up Table

NASA Astrophysics Data System (ADS)

Wang, Z.; Li, J.; Wang, A.; Wang, J.

2017-09-01

In the last years several V-SLAM(Visual Simultaneous Localization and Mapping) approaches have appeared showing impressive reconstructions of the world. However these maps are built with far more than the required information. This limitation comes from the whole process of each key-frame. In this paper we present for the first time a mapping method based on the LOOK UP TABLE(LUT) for visual SLAM that can improve the mapping effectively. As this method relies on extracting features in each cell divided from image, it can get the pose of camera that is more representative of the whole key-frame. The tracking direction of key-frames is obtained by counting the number of parallax directions of feature points. LUT stored all mapping needs the number of cell corresponding to the tracking direction which can reduce the redundant information in the key-frame, and is more efficient to mapping. The result shows that a better map with less noise is build using less than one-third of the time. We believe that the capacity of LUT efficiently building maps makes it a good choice for the community to investigate in the scene reconstruction problems.

An information hiding method based on LSB and tent chaotic map

NASA Astrophysics Data System (ADS)

Song, Jianhua; Ding, Qun

2011-06-01

In order to protect information security more effectively, a novel information hiding method based on LSB and Tent chaotic map was proposed, first the secret message is Tent chaotic encrypted, and then LSB steganography is executed for the encrypted message in the cover-image. Compared to the traditional image information hiding method, the simulation results indicate that the method greatly improved in imperceptibility and security, and acquired good results.

Line segment confidence region-based string matching method for map conflation

NASA Astrophysics Data System (ADS)

Huh, Yong; Yang, Sungchul; Ga, Chillo; Yu, Kiyun; Shi, Wenzhong

2013-04-01

In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894.

A Fast Approximate Algorithm for Mapping Long Reads to Large Reference Databases.

PubMed

Jain, Chirag; Dilthey, Alexander; Koren, Sergey; Aluru, Srinivas; Phillippy, Adam M

2018-04-30

Emerging single-molecule sequencing technologies from Pacific Biosciences and Oxford Nanopore have revived interest in long-read mapping algorithms. Alignment-based seed-and-extend methods demonstrate good accuracy, but face limited scalability, while faster alignment-free methods typically trade decreased precision for efficiency. In this article, we combine a fast approximate read mapping algorithm based on minimizers with a novel MinHash identity estimation technique to achieve both scalability and precision. In contrast to prior methods, we develop a mathematical framework that defines the types of mapping targets we uncover, establish probabilistic estimates of p-value and sensitivity, and demonstrate tolerance for alignment error rates up to 20%. With this framework, our algorithm automatically adapts to different minimum length and identity requirements and provides both positional and identity estimates for each mapping reported. For mapping human PacBio reads to the hg38 reference, our method is 290 × faster than Burrows-Wheeler Aligner-MEM with a lower memory footprint and recall rate of 96%. We further demonstrate the scalability of our method by mapping noisy PacBio reads (each ≥5 kbp in length) to the complete NCBI RefSeq database containing 838 Gbp of sequence and >60,000 genomes.

A Different Approach to Preparing Novakian Concept Maps: The Indexing Method

ERIC Educational Resources Information Center

Turan Oluk, Nurcan; Ekmekci, Güler

2016-01-01

People who claim that applying Novakian concept maps in Turkish is problematic base their arguments largely upon the structural differences between the English and Turkish languages. This study aims to introduce the indexing method to eliminate problems encountered in Turkish applications of Novakian maps and to share the preliminary results of…

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

Sci—Thur AM: YIS - 08: Constructing an Attenuation map for a PET/MR Breast coil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patrick, John C.; Imaging, Lawson Health Research Institute, Knoxville, TN; London Regional Cancer Program, Knoxville, TN

2014-08-15

In 2013, around 23000 Canadian women and 200 Canadian men were diagnosed with breast cancer. An estimated 5100 women and 55 men died from the disease. Using the sensitivity of MRI with the selectivity of PET, PET/MRI combines anatomical and functional information within the same scan and could help with early detection in high-risk patients. MRI requires radiofrequency coils for transmitting energy and receiving signal but the breast coil attenuates PET signal. To correct for this PET attenuation, a 3-dimensional map of linear attenuation coefficients (μ-map) of the breast coil must be created and incorporated into the PET reconstruction process.more » Several approaches have been proposed for building hardware μ-maps, some of which include the use of conventional kVCT and Dual energy CT. These methods can produce high resolution images based on the electron densities of materials that can be converted into μ-maps. However, imaging hardware containing metal components with photons in the kV range is susceptible to metal artifacts. These artifacts can compromise the accuracy of the resulting μ-map and PET reconstruction; therefore high-Z components should be removed. We propose a method for calculating μ-maps without removing coil components, based on megavoltage (MV) imaging with a linear accelerator that has been detuned for imaging at 1.0MeV. Containers of known geometry with F18 were placed in the breast coil for imaging. A comparison between reconstructions based on the different μ-map construction methods was made. PET reconstructions with our method show a maximum of 6% difference over the existing kVCT-based reconstructions.« less

Modeling a color-rendering operator for high dynamic range images using a cone-response function

NASA Astrophysics Data System (ADS)

Choi, Ho-Hyoung; Kim, Gi-Seok; Yun, Byoung-Ju

2015-09-01

Tone-mapping operators are the typical algorithms designed to produce visibility and the overall impression of brightness, contrast, and color of high dynamic range (HDR) images on low dynamic range (LDR) display devices. Although several new tone-mapping operators have been proposed in recent years, the results of these operators have not matched those of the psychophysical experiments based on the human visual system. A color-rendering model that is a combination of tone-mapping and cone-response functions using an XYZ tristimulus color space is presented. In the proposed method, the tone-mapping operator produces visibility and the overall impression of brightness, contrast, and color in HDR images when mapped onto relatively LDR devices. The tone-mapping resultant image is obtained using chromatic and achromatic colors to avoid well-known color distortions shown in the conventional methods. The resulting image is then processed with a cone-response function wherein emphasis is placed on human visual perception (HVP). The proposed method covers the mismatch between the actual scene and the rendered image based on HVP. The experimental results show that the proposed method yields an improved color-rendering performance compared to conventional methods.

Chaos M-ary modulation and demodulation method based on Hamilton oscillator and its application in communication.

PubMed

Fu, Yongqing; Li, Xingyuan; Li, Yanan; Yang, Wei; Song, Hailiang

2013-03-01

Chaotic communication has aroused general interests in recent years, but its communication effect is not ideal with the restriction of chaos synchronization. In this paper a new chaos M-ary digital modulation and demodulation method is proposed. By using region controllable characteristics of spatiotemporal chaos Hamilton map in phase plane and chaos unique characteristic, which is sensitive to initial value, zone mapping method is proposed. It establishes the map relationship between M-ary digital information and the region of Hamilton map phase plane, thus the M-ary information chaos modulation is realized. In addition, zone partition demodulation method is proposed based on the structure characteristic of Hamilton modulated information, which separates M-ary information from phase trajectory of chaotic Hamilton map, and the theory analysis of zone partition demodulator's boundary range is given. Finally, the communication system based on the two methods is constructed on the personal computer. The simulation shows that in high speed transmission communications and with no chaos synchronization circumstance, the proposed chaotic M-ary modulation and demodulation method has outperformed some conventional M-ary modulation methods, such as quadrature phase shift keying and M-ary pulse amplitude modulation in bit error rate. Besides, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-noise performance, and the system complexity is low and chaos signal is easy to generate.

Mapping landscape corridors

Treesearch

Peter Vogt; Kurt H. Riitters; Marcin Iwanowski; Christine Estreguil; Jacek Kozak; Pierre Soille

2007-01-01

Corridors are important geographic features for biological conservation and biodiversity assessment. The identification and mapping of corridors is usually based on visual interpretations of movement patterns (functional corridors) or habitat maps (structural corridors). We present a method for automated corridor mapping with morphological image processing, and...

Using ancestry matching to combine family-based and unrelated samples for genome-wide association studies‡

PubMed Central

Crossett, Andrew; Kent, Brian P.; Klei, Lambertus; Ringquist, Steven; Trucco, Massimo; Roeder, Kathryn; Devlin, Bernie

2015-01-01

We propose a method to analyze family-based samples together with unrelated cases and controls. The method builds on the idea of matched case–control analysis using conditional logistic regression (CLR). For each trio within the family, a case (the proband) and matched pseudo-controls are constructed, based upon the transmitted and untransmitted alleles. Unrelated controls, matched by genetic ancestry, supplement the sample of pseudo-controls; likewise unrelated cases are also paired with genetically matched controls. Within each matched stratum, the case genotype is contrasted with control pseudo-control genotypes via CLR, using a method we call matched-CLR (mCLR). Eigenanalysis of numerous SNP genotypes provides a tool for mapping genetic ancestry. The result of such an analysis can be thought of as a multidimensional map, or eigenmap, in which the relative genetic similarities and differences amongst individuals is encoded in the map. Once constructed, new individuals can be projected onto the ancestry map based on their genotypes. Successful differentiation of individuals of distinct ancestry depends on having a diverse, yet representative sample from which to construct the ancestry map. Once samples are well-matched, mCLR yields comparable power to competing methods while ensuring excellent control over Type I error. PMID:20862653

Comparing Pixel and Object-Based Approaches to Map an Understorey Invasive Shrub in Tropical Mixed Forests

PubMed Central

Niphadkar, Madhura; Nagendra, Harini; Tarantino, Cristina; Adamo, Maria; Blonda, Palma

2017-01-01

The establishment of invasive alien species in varied habitats across the world is now recognized as a genuine threat to the preservation of biodiversity. Specifically, plant invasions in understory tropical forests are detrimental to the persistence of healthy ecosystems. Monitoring such invasions using Very High Resolution (VHR) satellite remote sensing has been shown to be valuable in designing management interventions for conservation of native habitats. Object-based classification methods are very helpful in identifying invasive plants in various habitats, by their inherent nature of imitating the ability of the human brain in pattern recognition. However, these methods have not been tested adequately in dense tropical mixed forests where invasion occurs in the understorey. This study compares a pixel-based and object-based classification method for mapping the understorey invasive shrub Lantana camara (Lantana) in a tropical mixed forest habitat in the Western Ghats biodiversity hotspot in India. Overall, a hierarchical approach of mapping top canopy at first, and then further processing for the understorey shrub, using measures such as texture and vegetation indices proved effective in separating out Lantana from other cover types. In the first method, we implement a simple parametric supervised classification for mapping cover types, and then process within these types for Lantana delineation. In the second method, we use an object-based segmentation algorithm to map cover types, and then perform further processing for separating Lantana. The improved ability of the object-based approach to delineate structurally distinct objects with characteristic spectral and spatial characteristics of their own, as well as with reference to their surroundings, allows for much flexibility in identifying invasive understorey shrubs among the complex vegetation of the tropical forest than that provided by the parametric classifier. Conservation practices in tropical mixed forests can benefit greatly by adopting methods which use high resolution remotely sensed data and advanced techniques to monitor the patterns and effective functioning of native ecosystems by periodically mapping disturbances such as invasion. PMID:28620400

Development of management information system for land in mine area based on MapInfo

NASA Astrophysics Data System (ADS)

Wang, Shi-Dong; Liu, Chuang-Hua; Wang, Xin-Chuang; Pan, Yan-Yu

2008-10-01

MapInfo is current a popular GIS software. This paper introduces characters of MapInfo and GIS second development methods offered by MapInfo, which include three ones based on MapBasic, OLE automation, and MapX control usage respectively. Taking development of land management information system in mine area for example, in the paper, the method of developing GIS applications based on MapX has been discussed, as well as development of land management information system in mine area has been introduced in detail, including development environment, overall design, design and realization of every function module, and simple application of system, etc. The system uses MapX 5.0 and Visual Basic 6.0 as development platform, takes SQL Server 2005 as back-end database, and adopts Matlab 6.5 to calculate number in back-end. On the basis of integrated design, the system develops eight modules including start-up, layer control, spatial query, spatial analysis, data editing, application model, document management, results output. The system can be used in mine area for cadastral management, land use structure optimization, land reclamation, land evaluation, analysis and forecasting for land in mine area and environmental disruption, thematic mapping, and so on.

Application of the Risk-Based Early Warning Method in a Fracture-Karst Water Source, North China.

PubMed

Guo, Yongli; Wu, Qing; Li, Changsuo; Zhao, Zhenhua; Sun, Bin; He, Shiyi; Jiang, Guanghui; Zhai, Yuanzheng; Guo, Fang

2018-03-01

  The paper proposes a risk-based early warning considering characteristics of fracture-karst aquifer in North China and applied it in a super-large fracture-karst water source. Groundwater vulnerability, types of land use, water abundance, transmissivity and spatial temporal variation of groundwater quality were chosen as indexes of the method. Weights of factors were obtained by using AHP method based on relative importance of factors, maps of factors were zoned by GIS, early warning map was conducted based on extension theory with the help of GIS, ENVI+IDL. The early warning map fused five factors very well, serious and tremendous warning areas are mainly located in northwest and east with high or relatively high transmissivity and groundwater pollutant loading, and obviously deteriorated or deteriorated trend of petroleum. The early warning map warns people where more attention should be paid, and the paper guides decision making to take appropriate protection actions in different warning levels areas.

Relative risk estimation of Chikungunya disease in Malaysia: An analysis based on Poisson-gamma model

NASA Astrophysics Data System (ADS)

Samat, N. A.; Ma'arof, S. H. Mohd Imam

2015-05-01

Disease mapping is a method to display the geographical distribution of disease occurrence, which generally involves the usage and interpretation of a map to show the incidence of certain diseases. Relative risk (RR) estimation is one of the most important issues in disease mapping. This paper begins by providing a brief overview of Chikungunya disease. This is followed by a review of the classical model used in disease mapping, based on the standardized morbidity ratio (SMR), which we then apply to our Chikungunya data. We then fit an extension of the classical model, which we refer to as a Poisson-Gamma model, when prior distributions for the relative risks are assumed known. Both results are displayed and compared using maps and we reveal a smoother map with fewer extremes values of estimated relative risk. The extensions of this paper will consider other methods that are relevant to overcome the drawbacks of the existing methods, in order to inform and direct government strategy for monitoring and controlling Chikungunya disease.

HOTEX: An Approach for Global Mapping of Human Built-Up and Settlement Extent

NASA Technical Reports Server (NTRS)

Wang, Panshi; Huang, Chengquan; Tilton, James C.; Tan, Bin; Brown De Colstoun, Eric C.

2017-01-01

Understanding the impacts of urbanization requires accurate and updatable urban extent maps. Here we present an algorithm for mapping urban extent at global scale using Landsat data. An innovative hierarchical object-based texture (HOTex) classification approach was designed to overcome spectral confusion between urban and nonurban land cover types. VIIRS nightlights data and MODIS vegetation index datasets are integrated as high-level features under an object-based framework. We applied the HOTex method to the GLS-2010 Landsat images to produce a global map of human built-up and settlement extent. As shown by visual assessments, our method could effectively map urban extent and generate consistent results using images with inconsistent acquisition time and vegetation phenology. Using scene-level cross validation for results in Europe, we assessed the performance of HOTex and achieved a kappa coefficient of 0.91, compared to 0.74 from a baseline method using per-pixel classification using spectral information.

Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)

USGS Publications Warehouse

Kokaly, R.F.; King, T.V.V.; Hoefen, T.M.

2011-01-01

Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager), robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral-feature based analysis of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described in this paper. The core concepts and calculations of MICA are presented. A MICA command file has been developed and applied to map minerals in the full-country coverage of the 2007 Afghanistan HyMap hyperspectral data. ?? 2011 IEEE.

Matching biomedical ontologies based on formal concept analysis.

PubMed

Zhao, Mengyi; Zhang, Songmao; Li, Weizhuo; Chen, Guowei

2018-03-19

The goal of ontology matching is to identify correspondences between entities from different yet overlapping ontologies so as to facilitate semantic integration, reuse and interoperability. As a well developed mathematical model for analyzing individuals and structuring concepts, Formal Concept Analysis (FCA) has been applied to ontology matching (OM) tasks since the beginning of OM research, whereas ontological knowledge exploited in FCA-based methods is limited. This motivates the study in this paper, i.e., to empower FCA with as much as ontological knowledge as possible for identifying mappings across ontologies. We propose a method based on Formal Concept Analysis to identify and validate mappings across ontologies, including one-to-one mappings, complex mappings and correspondences between object properties. Our method, called FCA-Map, incrementally generates a total of five types of formal contexts and extracts mappings from the lattices derived. First, the token-based formal context describes how class names, labels and synonyms share lexical tokens, leading to lexical mappings (anchors) across ontologies. Second, the relation-based formal context describes how classes are in taxonomic, partonomic and disjoint relationships with the anchors, leading to positive and negative structural evidence for validating the lexical matching. Third, the positive relation-based context can be used to discover structural mappings. Afterwards, the property-based formal context describes how object properties are used in axioms to connect anchor classes across ontologies, leading to property mappings. Last, the restriction-based formal context describes co-occurrence of classes across ontologies in anonymous ancestors of anchors, from which extended structural mappings and complex mappings can be identified. Evaluation on the Anatomy, the Large Biomedical Ontologies, and the Disease and Phenotype track of the 2016 Ontology Alignment Evaluation Initiative campaign demonstrates the effectiveness of FCA-Map and its competitiveness with the top-ranked systems. FCA-Map can achieve a better balance between precision and recall for large-scale domain ontologies through constructing multiple FCA structures, whereas it performs unsatisfactorily for smaller-sized ontologies with less lexical and semantic expressions. Compared with other FCA-based OM systems, the study in this paper is more comprehensive as an attempt to push the envelope of the Formal Concept Analysis formalism in ontology matching tasks. Five types of formal contexts are constructed incrementally, and their derived concept lattices are used to cluster the commonalities among classes at lexical and structural level, respectively. Experiments on large, real-world domain ontologies show promising results and reveal the power of FCA.

Extracting Lane Geometry and Topology Information from Vehicle Fleet Trajectories in Complex Urban Scenarios Using a Reversible Jump Mcmc Method

NASA Astrophysics Data System (ADS)

Roeth, O.; Zaum, D.; Brenner, C.

2017-05-01

Highly automated driving (HAD) requires maps not only of high spatial precision but also of yet unprecedented actuality. Traditionally small highly specialized fleets of measurement vehicles are used to generate such maps. Nevertheless, for achieving city-wide or even nation-wide coverage, automated map update mechanisms based on very large vehicle fleet data gain importance since highly frequent measurements are only to be obtained using such an approach. Furthermore, the processing of imprecise mass data in contrast to few dedicated highly accurate measurements calls for a high degree of automation. We present a method for the generation of lane-accurate road network maps from vehicle trajectory data (GPS or better). Our approach therefore allows for exploiting today's connected vehicle fleets for the generation of HAD maps. The presented algorithm is based on elementary building blocks which guarantees useful lane models and uses a Reversible Jump Markov chain Monte Carlo method to explore the models parameters in order to reconstruct the one most likely emitting the input data. The approach is applied to a challenging urban real-world scenario of different trajectory accuracy levels and is evaluated against a LIDAR-based ground truth map.

Concept mapping as a method to enhance evidence-based public health.

PubMed

van Bon-Martens, Marja J H; van de Goor, Ien A M; van Oers, Hans A M

2017-02-01

In this paper we explore the suitability of concept mapping as a method for integrating knowledge from science, practice, and policy. In earlier research we described and analysed five cases of concept mapping procedures in the Netherlands, serving different purposes and fields in public health. In the current paper, seven new concept mapping studies of co-produced work are added to extend this analysis. For each of these twelve studies we analysed: (1) how the method was able to integrate knowledge from practice with scientific knowledge by facilitating dialogue and collaboration between different stakeholders in the field of public health, such as academic researchers, practitioners, policy-makers and the public; (2) how the method was able to bring theory development a step further (scientific relevance); and (3) how the method was able to act as a sound basis for practical decision-making (practical relevance). Based on the answers to these research questions, all but one study was considered useful for building more evidence-based public health, even though the extent to which they underpinned actual decision-making varied. The chance of actually being implemented in practice seems strongly related to the extent to which the responsible decision-makers are involved in the way the concept map is prepared and executed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Data-based estimates of the ocean carbon sink variability - results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

NASA Astrophysics Data System (ADS)

Rödenbeck, Christian; Bakker, Dorothee; Gruber, Nicolas; Iida, Yosuke; Jacobson, Andy; Jones, Steve; Landschützer, Peter; Metzl, Nicolas; Nakaoka, Shin-ichiro; Olsen, Are; Park, Geun-Ha; Peylin, Philippe; Rodgers, Keith; Sasse, Tristan; Schuster, Ute; Shutler, James; Valsala, Vinu; Wanninkhof, Rik; Zeng, Jiye

2016-04-01

Using measurements of the surface-ocean COtwo partial pressure (pCOtwo) from the SOCAT and LDEO data bases and 14 different pCOtwo mapping methods recently collated by the Surface Ocean pCOtwo Mapping intercomparison (SOCOM) initiative, variations in regional and global sea-air COtwo fluxes are investigated. Though the available mapping methods use widely different approaches, we find relatively consistent estimates of regional pCOtwo seasonality, in line with previous estimates. In terms of interannual variability (IAV), all mapping methods estimate the largest variations to occur in the Eastern equatorial Pacific. Despite considerable spread in the detailed variations, mapping methods that fit the data more closely also tend to agree more closely with each other in regional averages. Encouragingly, this includes mapping methods belonging to complementary types - taking variability either directly from the pCOtwo data or indirectly from driver data via regression. From a weighted ensemble average, we find an IAV amplitude of the global sea-air COtwo flux of IAVampl (standard deviation over AnalysisPeriod), which is larger than simulated by biogeochemical process models. On a decadal perspective, the global ocean COtwo uptake is estimated to have gradually increased since about 2000, with little decadal change prior to that. The weighted mean net global ocean COtwo sink estimated by the SOCOM ensemble is -1.75 UPgCyr (AnalysisPeriod), consistent within uncertainties with estimates from ocean-interior carbon data or atmospheric oxygen trends. Using data-based sea-air COtwo fluxes in atmospheric COtwo inversions also helps to better constrain land-atmosphere COtwo fluxes.

Saturated linkage map construction in Rubus idaeus using genotyping by sequencing and genome-independent imputation

PubMed Central

2013-01-01

Background Rapid development of highly saturated genetic maps aids molecular breeding, which can accelerate gain per breeding cycle in woody perennial plants such as Rubus idaeus (red raspberry). Recently, robust genotyping methods based on high-throughput sequencing were developed, which provide high marker density, but result in some genotype errors and a large number of missing genotype values. Imputation can reduce the number of missing values and can correct genotyping errors, but current methods of imputation require a reference genome and thus are not an option for most species. Results Genotyping by Sequencing (GBS) was used to produce highly saturated maps for a R. idaeus pseudo-testcross progeny. While low coverage and high variance in sequencing resulted in a large number of missing values for some individuals, a novel method of imputation based on maximum likelihood marker ordering from initial marker segregation overcame the challenge of missing values, and made map construction computationally tractable. The two resulting parental maps contained 4521 and 2391 molecular markers spanning 462.7 and 376.6 cM respectively over seven linkage groups. Detection of precise genomic regions with segregation distortion was possible because of map saturation. Microsatellites (SSRs) linked these results to published maps for cross-validation and map comparison. Conclusions GBS together with genome-independent imputation provides a rapid method for genetic map construction in any pseudo-testcross progeny. Our method of imputation estimates the correct genotype call of missing values and corrects genotyping errors that lead to inflated map size and reduced precision in marker placement. Comparison of SSRs to published R. idaeus maps showed that the linkage maps constructed with GBS and our method of imputation were robust, and marker positioning reliable. The high marker density allowed identification of genomic regions with segregation distortion in R. idaeus, which may help to identify deleterious alleles that are the basis of inbreeding depression in the species. PMID:23324311

Building Interoperable FHIR-Based Vocabulary Mapping Services: A Case Study of OHDSI Vocabularies and Mappings.

PubMed

Jiang, Guoqian; Kiefer, Richard; Prud'hommeaux, Eric; Solbrig, Harold R

2017-01-01

The OHDSI Common Data Model (CDM) is a deep information model, in which its vocabulary component plays a critical role in enabling consistent coding and query of clinical data. The objective of the study is to create methods and tools to expose the OHDSI vocabularies and mappings as the vocabulary mapping services using two HL7 FHIR core terminology resources ConceptMap and ValueSet. We discuss the benefits and challenges in building the FHIR-based terminology services.

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing.

PubMed

Li, Wen; Wei, Dongyan; Lai, Qifeng; Li, Xianghong; Yuan, Hong

2018-05-08

Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy.

Geomagnetism-Aided Indoor Wi-Fi Radio-Map Construction via Smartphone Crowdsourcing

PubMed Central

Li, Wen; Wei, Dongyan; Lai, Qifeng; Li, Xianghong; Yuan, Hong

2018-01-01

Wi-Fi radio-map construction is an important phase in indoor fingerprint localization systems. Traditional methods for Wi-Fi radio-map construction have the problems of being time-consuming and labor-intensive. In this paper, an indoor Wi-Fi radio-map construction method is proposed which utilizes crowdsourcing data contributed by smartphone users. We draw indoor pathway map and construct Wi-Fi radio-map without requiring manual site survey, exact floor layout and extra infrastructure support. The key novelty is that it recognizes road segments from crowdsourcing traces by a cluster based on magnetism sequence similarity and constructs an indoor pathway map with Wi-Fi signal strengths annotated on. Through experiments in real world indoor areas, the method is proved to have good performance on magnetism similarity calculation, road segment clustering and pathway map construction. The Wi-Fi radio maps constructed by crowdsourcing data are validated to provide competitive indoor localization accuracy. PMID:29738454

Research and Practice of the News Map Compilation Service

NASA Astrophysics Data System (ADS)

Zhao, T.; Liu, W.; Ma, W.

2018-04-01

Based on the needs of the news media on the map, this paper researches on the news map compilation service, conducts demand research on the service of compiling news maps, designs and compiles the public authority base map suitable for media publication, and constructs the news base map material library. It studies the compilation of domestic and international news maps with timeliness and strong pertinence and cross-regional characteristics, constructs the hot news thematic gallery and news map customization services, conducts research on types of news maps, establish closer liaison and cooperation methods with news media, and guides news media to use correct maps. Through the practice of the news map compilation service, this paper lists two cases of news map preparation services used by different media, compares and analyses cases, summarizes the research situation of news map compilation service, and at the same time puts forward outstanding problems and development suggestions in the service of news map compilation service.

Quantitative Susceptibility Mapping using Structural Feature based Collaborative Reconstruction (SFCR) in the Human Brain

PubMed Central

Cai, Congbo; Chen, Zhong; van Zijl, Peter C.M.

2017-01-01

The reconstruction of MR quantitative susceptibility mapping (QSM) from local phase measurements is an ill posed inverse problem and different regularization strategies incorporating a priori information extracted from magnitude and phase images have been proposed. However, the anatomy observed in magnitude and phase images does not always coincide spatially with that in susceptibility maps, which could give erroneous estimation in the reconstructed susceptibility map. In this paper, we develop a structural feature based collaborative reconstruction (SFCR) method for QSM including both magnitude and susceptibility based information. The SFCR algorithm is composed of two consecutive steps corresponding to complementary reconstruction models, each with a structural feature based l1 norm constraint and a voxel fidelity based l2 norm constraint, which allows both the structure edges and tiny features to be recovered, whereas the noise and artifacts could be reduced. In the M-step, the initial susceptibility map is reconstructed by employing a k-space based compressed sensing model incorporating magnitude prior. In the S-step, the susceptibility map is fitted in spatial domain using weighted constraints derived from the initial susceptibility map from the M-step. Simulations and in vivo human experiments at 7T MRI show that the SFCR method provides high quality susceptibility maps with improved RMSE and MSSIM. Finally, the susceptibility values of deep gray matter are analyzed in multiple head positions, with the supine position most approximate to the gold standard COSMOS result. PMID:27019480

Tiled vector data model for the geographical features of symbolized maps.

PubMed

Li, Lin; Hu, Wei; Zhu, Haihong; Li, You; Zhang, Hang

2017-01-01

Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and 'addition' (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity.

Network geometry inference using common neighbors

NASA Astrophysics Data System (ADS)

Papadopoulos, Fragkiskos; Aldecoa, Rodrigo; Krioukov, Dmitri

2015-08-01

We introduce and explore a method for inferring hidden geometric coordinates of nodes in complex networks based on the number of common neighbors between the nodes. We compare this approach to the HyperMap method, which is based only on the connections (and disconnections) between the nodes, i.e., on the links that the nodes have (or do not have). We find that for high degree nodes, the common-neighbors approach yields a more accurate inference than the link-based method, unless heuristic periodic adjustments (or "correction steps") are used in the latter. The common-neighbors approach is computationally intensive, requiring O (t4) running time to map a network of t nodes, versus O (t3) in the link-based method. But we also develop a hybrid method with O (t3) running time, which combines the common-neighbors and link-based approaches, and we explore a heuristic that reduces its running time further to O (t2) , without significant reduction in the mapping accuracy. We apply this method to the autonomous systems (ASs) Internet, and we reveal how soft communities of ASs evolve over time in the similarity space. We further demonstrate the method's predictive power by forecasting future links between ASs. Taken altogether, our results advance our understanding of how to efficiently and accurately map real networks to their latent geometric spaces, which is an important necessary step toward understanding the laws that govern the dynamics of nodes in these spaces, and the fine-grained dynamics of network connections.

Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui

PubMed Central

2012-01-01

Background The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. Methods This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Results Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. Conclusions This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an educational role for such applications. PMID:22998945

Investigation of methods to search for the boundaries on the image and their use on lung hardware of methods finding saliency map

NASA Astrophysics Data System (ADS)

Semenishchev, E. A.; Marchuk, V. I.; Fedosov, V. P.; Stradanchenko, S. G.; Ruslyakov, D. V.

2015-05-01

This work aimed to study computationally simple method of saliency map calculation. Research in this field received increasing interest for the use of complex techniques in portable devices. A saliency map allows increasing the speed of many subsequent algorithms and reducing the computational complexity. The proposed method of saliency map detection based on both image and frequency space analysis. Several examples of test image from the Kodak dataset with different detalisation considered in this paper demonstrate the effectiveness of the proposed approach. We present experiments which show that the proposed method providing better results than the framework Salience Toolbox in terms of accuracy and speed.

A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public

PubMed Central

Zhou, Mengjie; Wang, Rui; Tian, Jing; Ye, Ning; Mai, Shumin

2016-01-01

The internet enables the rapid and easy creation, storage, and transfer of knowledge; however, services that transfer geographic knowledge and facilitate the public understanding of geographic knowledge are still underdeveloped to date. Existing online maps (or atlases) can support limited types of geographic knowledge. In this study, we propose a framework for map-based services to represent and transfer different types of geographic knowledge to the public. A map-based service provides tools to ensure the effective transfer of geographic knowledge. We discuss the types of geographic knowledge that should be represented and transferred to the public, and we propose guidelines and a method to represent various types of knowledge through a map-based service. To facilitate the effective transfer of geographic knowledge, tools such as auxiliary background knowledge and auxiliary map-reading tools are provided through interactions with maps. An experiment conducted to illustrate our idea and to evaluate the usefulness of the map-based service is described; the results demonstrate that the map-based service is useful for transferring different types of geographic knowledge. PMID:27045314

A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public.

PubMed

Zhou, Mengjie; Wang, Rui; Tian, Jing; Ye, Ning; Mai, Shumin

2016-01-01

The internet enables the rapid and easy creation, storage, and transfer of knowledge; however, services that transfer geographic knowledge and facilitate the public understanding of geographic knowledge are still underdeveloped to date. Existing online maps (or atlases) can support limited types of geographic knowledge. In this study, we propose a framework for map-based services to represent and transfer different types of geographic knowledge to the public. A map-based service provides tools to ensure the effective transfer of geographic knowledge. We discuss the types of geographic knowledge that should be represented and transferred to the public, and we propose guidelines and a method to represent various types of knowledge through a map-based service. To facilitate the effective transfer of geographic knowledge, tools such as auxiliary background knowledge and auxiliary map-reading tools are provided through interactions with maps. An experiment conducted to illustrate our idea and to evaluate the usefulness of the map-based service is described; the results demonstrate that the map-based service is useful for transferring different types of geographic knowledge.

A self-trained classification technique for producing 30 m percent-water maps from Landsat data

USGS Publications Warehouse

Rover, Jennifer R.; Wylie, Bruce K.; Ji, Lei

2010-01-01

Small bodies of water can be mapped with moderate-resolution satellite data using methods where water is mapped as subpixel fractions using field measurements or high-resolution images as training datasets. A new method, developed from a regression-tree technique, uses a 30 m Landsat image for training the regression tree that, in turn, is applied to the same image to map subpixel water. The self-trained method was evaluated by comparing the percent-water map with three other maps generated from established percent-water mapping methods: (1) a regression-tree model trained with a 5 m SPOT 5 image, (2) a regression-tree model based on endmembers and (3) a linear unmixing classification technique. The results suggest that subpixel water fractions can be accurately estimated when high-resolution satellite data or intensively interpreted training datasets are not available, which increases our ability to map small water bodies or small changes in lake size at a regional scale.

Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

PubMed

Cai, Congbo; Wang, Chao; Zeng, Yiqing; Cai, Shuhui; Liang, Dong; Wu, Yawen; Chen, Zhong; Ding, Xinghao; Zhong, Jianhui

2018-04-24

An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T 2 mapping from single-shot overlapping-echo detachment (OLED) planar imaging. The training dataset was obtained from simulations that were carried out on SPROM (Simulation with PRoduct Operator Matrix) software developed by our group. The relationship between the original OLED image containing two echo signals and the corresponding T 2 mapping was learned by ResNet training. After the ResNet was trained, it was applied to reconstruct the T 2 mapping from simulation and in vivo human brain data. Although the ResNet was trained entirely on simulated data, the trained network was generalized well to real human brain data. The results from simulation and in vivo human brain experiments show that the proposed method significantly outperforms the echo-detachment-based method. Reliable T 2 mapping with higher accuracy is achieved within 30 ms after the network has been trained, while the echo-detachment-based OLED reconstruction method took approximately 2 min. The proposed method will facilitate real-time dynamic and quantitative MR imaging via OLED sequence, and deep convolutional neural network has the potential to reconstruct maps from complex MRI sequences efficiently. © 2018 International Society for Magnetic Resonance in Medicine.

Analysis of spatial distribution of land cover maps accuracy

NASA Astrophysics Data System (ADS)

Khatami, R.; Mountrakis, G.; Stehman, S. V.

2017-12-01

Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain yielded similar AUC; iv) for the larger sample size (i.e., very dense spatial sample) and per-class predictions, the spatial domain yielded larger AUC; v) increasing the sample size improved accuracy predictions with a greater benefit accruing to the spatial domain; and vi) the function used for interpolation had the smallest effect on AUC.

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PubMed

Narayan, Sreenath; Kalhan, Satish C; Wilson, David L

2013-05-01

To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. Copyright © 2012 Wiley Periodicals, Inc.

An improved image non-blind image deblurring method based on FoEs

NASA Astrophysics Data System (ADS)

Zhu, Qidan; Sun, Lei

2013-03-01

Traditional non-blind image deblurring algorithms always use maximum a posterior(MAP). MAP estimates involving natural image priors can reduce the ripples effectively in contrast to maximum likelihood(ML). However, they have been found lacking in terms of restoration performance. Based on this issue, we utilize MAP with KL penalty to replace traditional MAP. We develop an image reconstruction algorithm that minimizes the KL divergence between the reference distribution and the prior distribution. The approximate KL penalty can restrain over-smooth caused by MAP. We use three groups of images and Harris corner detection to prove our method. The experimental results show that our algorithm of non-blind image restoration can effectively reduce the ringing effect and exhibit the state-of-the-art deblurring results.

StructMap: Elastic Distance Analysis of Electron Microscopy Maps for Studying Conformational Changes.

PubMed

Sanchez Sorzano, Carlos Oscar; Alvarez-Cabrera, Ana Lucia; Kazemi, Mohsen; Carazo, Jose María; Jonić, Slavica

2016-04-26

Single-particle electron microscopy (EM) has been shown to be very powerful for studying structures and associated conformational changes of macromolecular complexes. In the context of analyzing conformational changes of complexes, distinct EM density maps obtained by image analysis and three-dimensional (3D) reconstruction are usually analyzed in 3D for interpretation of structural differences. However, graphic visualization of these differences based on a quantitative analysis of elastic transformations (deformations) among density maps has not been done yet due to a lack of appropriate methods. Here, we present an approach that allows such visualization. This approach is based on statistical analysis of distances among elastically aligned pairs of EM maps (one map is deformed to fit the other map), and results in visualizing EM maps as points in a lower-dimensional distance space. The distances among points in the new space can be analyzed in terms of clusters or trajectories of points related to potential conformational changes. The results of the method are shown with synthetic and experimental EM maps at different resolutions. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Drawing road networks with focus regions.

PubMed

Haunert, Jan-Henrik; Sering, Leon

2011-12-01

Mobile users of maps typically need detailed information about their surroundings plus some context information about remote places. In order to avoid that the map partly gets too dense, cartographers have designed mapping functions that enlarge a user-defined focus region--such functions are sometimes called fish-eye projections. The extra map space occupied by the enlarged focus region is compensated by distorting other parts of the map. We argue that, in a map showing a network of roads relevant to the user, distortion should preferably take place in those areas where the network is sparse. Therefore, we do not apply a predefined mapping function. Instead, we consider the road network as a graph whose edges are the road segments. We compute a new spatial mapping with a graph-based optimization approach, minimizing the square sum of distortions at edges. Our optimization method is based on a convex quadratic program (CQP); CQPs can be solved in polynomial time. Important requirements on the output map are expressed as linear inequalities. In particular, we show how to forbid edge crossings. We have implemented our method in a prototype tool. For instances of different sizes, our method generated output maps that were far less distorted than those generated with a predefined fish-eye projection. Future work is needed to automate the selection of roads relevant to the user. Furthermore, we aim at fast heuristics for application in real-time systems. © 2011 IEEE

Mapping of unknown industrial plant using ROS-based navigation mobile robot

NASA Astrophysics Data System (ADS)

Priyandoko, G.; Ming, T. Y.; Achmad, M. S. H.

2017-10-01

This research examines how humans work with teleoperated unmanned mobile robot inspection in industrial plant area resulting 2D/3D map for further critical evaluation. This experiment focuses on two parts, the way human-robot doing remote interactions using robust method and the way robot perceives the environment surround as a 2D/3D perspective map. ROS (robot operating system) as a tool was utilized in the development and implementation during the research which comes up with robust data communication method in the form of messages and topics. RGBD SLAM performs the visual mapping function to construct 2D/3D map using Kinect sensor. The results showed that the mobile robot-based teleoperated system are successful to extend human perspective in term of remote surveillance in large area of industrial plant. It was concluded that the proposed work is robust solution for large mapping within an unknown construction building.

The semantic connectivity map: an adapting self-organising knowledge discovery method in data bases. Experience in gastro-oesophageal reflux disease.

PubMed

Buscema, Massimo; Grossi, Enzo

2008-01-01

We describe here a new mapping method able to find out connectivity traces among variables thanks to an artificial adaptive system, the Auto Contractive Map (AutoCM), able to define the strength of the associations of each variable with all the others in a dataset. After the training phase, the weights matrix of the AutoCM represents the map of the main connections between the variables. The example of gastro-oesophageal reflux disease data base is extremely useful to figure out how this new approach can help to re-design the overall structure of factors related to complex and specific diseases description.

MAPPING SPATIAL ACCURACY AND ESTIMATING LANDSCAPE INDICATORS FROM THEMATIC LAND COVER MAPS USING FUZZY SET THEORY

EPA Science Inventory

This paper presents a fuzzy set-based method of mapping spatial accuracy of thematic map and computing several ecological indicators while taking into account spatial variation of accuracy associated with different land cover types and other factors (e.g., slope, soil type, etc.)...

Next-Generation Sequencing-Based Approaches for Mutation Mapping and Identification in Caenorhabditis elegans

PubMed Central

Doitsidou, Maria; Jarriault, Sophie; Poole, Richard J.

2016-01-01

The use of next-generation sequencing (NGS) has revolutionized the way phenotypic traits are assigned to genes. In this review, we describe NGS-based methods for mapping a mutation and identifying its molecular identity, with an emphasis on applications in Caenorhabditis elegans. In addition to an overview of the general principles and concepts, we discuss the main methods, provide practical and conceptual pointers, and guide the reader in the types of bioinformatics analyses that are required. Owing to the speed and the plummeting costs of NGS-based methods, mapping and cloning a mutation of interest has become straightforward, quick, and relatively easy. Removing this bottleneck previously associated with forward genetic screens has significantly advanced the use of genetics to probe fundamental biological processes in an unbiased manner. PMID:27729495

Multimodal Image Alignment via Linear Mapping between Feature Modalities.

PubMed

Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

2017-01-01

We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

Integrating Terrain Maps Into a Reactive Navigation Strategy

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Werger, Barry; Seraji, Homayoun

2006-01-01

An improved method of processing information for autonomous navigation of a robotic vehicle across rough terrain involves the integration of terrain maps into a reactive navigation strategy. Somewhat more precisely, the method involves the incorporation, into navigation logic, of data equivalent to regional traversability maps. The terrain characteristic is mapped using a fuzzy-logic representation of the difficulty of traversing the terrain. The method is robust in that it integrates a global path-planning strategy with sensor-based regional and local navigation strategies to ensure a high probability of success in reaching a destination and avoiding obstacles along the way. The sensor-based strategies use cameras aboard the vehicle to observe the regional terrain, defined as the area of the terrain that covers the immediate vicinity near the vehicle to a specified distance a few meters away.

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping.

PubMed

Feizizadeh, Bakhtiar; Blaschke, Thomas

2014-03-04

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster-Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster-Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation yielded poor results.

Molecular mapping and breeding with microsatellite markers.

PubMed

Lightfoot, David A; Iqbal, Muhammad J

2013-01-01

In genetics databases for crop plant species across the world, there are thousands of mapped loci that underlie quantitative traits, oligogenic traits, and simple traits recognized by association mapping in populations. The number of loci will increase as new phenotypes are measured in more diverse genotypes and genetic maps based on saturating numbers of markers are developed. A period of locus reevaluation will decrease the number of important loci as those underlying mega-environmental effects are recognized. A second wave of reevaluation of loci will follow from developmental series analysis, especially for harvest traits like seed yield and composition. Breeding methods to properly use the accurate maps of QTL are being developed. New methods to map, fine map, and isolate the genes underlying the loci will be critical to future advances in crop biotechnology. Microsatellite markers are the most useful tool for breeders. They are codominant, abundant in all genomes, highly polymorphic so useful in many populations, and both economical and technically easy to use. The selective genotyping approaches, including genotype ranking (indexing) based on partial phenotype data combined with favorable allele data and bulked segregation event (segregant) analysis (BSA), will be increasingly important uses for microsatellites. Examples of the methods for developing and using microsatellites derived from genomic sequences are presented for monogenic, oligogenic, and polygenic traits. Examples of successful mapping, fine mapping, and gene isolation are given. When combined with high-throughput methods for genotyping and a genome sequence, the use of association mapping with microsatellite markers will provide critical advances in the analysis of crop traits.

Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design

NASA Astrophysics Data System (ADS)

Lerner, Michael G.; Meagher, Kristin L.; Carlson, Heather A.

2008-10-01

Use of solvent mapping, based on multiple-copy minimization (MCM) techniques, is common in structure-based drug discovery. The minima of small-molecule probes define locations for complementary interactions within a binding pocket. Here, we present improved methods for MCM. In particular, a Jarvis-Patrick (JP) method is outlined for grouping the final locations of minimized probes into physical clusters. This algorithm has been tested through a study of protein-protein interfaces, showing the process to be robust, deterministic, and fast in the mapping of protein "hot spots." Improvements in the initial placement of probe molecules are also described. A final application to HIV-1 protease shows how our automated technique can be used to partition data too complicated to analyze by hand. These new automated methods may be easily and quickly extended to other protein systems, and our clustering methodology may be readily incorporated into other clustering packages.

Surface-Constrained Volumetric Brain Registration Using Harmonic Mappings

PubMed Central

Joshi, Anand A.; Shattuck, David W.; Thompson, Paul M.; Leahy, Richard M.

2015-01-01

In order to compare anatomical and functional brain imaging data across subjects, the images must first be registered to a common coordinate system in which anatomical features are aligned. Intensity-based volume registration methods can align subcortical structures well, but the variability in sulcal folding patterns typically results in misalignment of the cortical surface. Conversely, surface-based registration using sulcal features can produce excellent cortical alignment but the mapping between brains is restricted to the cortical surface. Here we describe a method for volumetric registration that also produces an accurate one-to-one point correspondence between cortical surfaces. This is achieved by first parameterizing and aligning the cortical surfaces using sulcal landmarks. We then use a constrained harmonic mapping to extend this surface correspondence to the entire cortical volume. Finally, this mapping is refined using an intensity-based warp. We demonstrate the utility of the method by applying it to T1-weighted magnetic resonance images (MRI). We evaluate the performance of our proposed method relative to existing methods that use only intensity information; for this comparison we compute the inter-subject alignment of expert-labeled sub-cortical structures after registration. PMID:18092736

Exploration of a Capability-Focused Aerospace System of Systems Architecture Alternative with Bilayer Design Space, Based on RST-SOM Algorithmic Methods

PubMed Central

Li, Zhifei; Qin, Dongliang

2014-01-01

In defense related programs, the use of capability-based analysis, design, and acquisition has been significant. In order to confront one of the most challenging features of a huge design space in capability based analysis (CBA), a literature review of design space exploration was first examined. Then, in the process of an aerospace system of systems design space exploration, a bilayer mapping method was put forward, based on the existing experimental and operating data. Finally, the feasibility of the foregoing approach was demonstrated with an illustrative example. With the data mining RST (rough sets theory) and SOM (self-organized mapping) techniques, the alternative to the aerospace system of systems architecture was mapping from P-space (performance space) to C-space (configuration space), and then from C-space to D-space (design space), respectively. Ultimately, the performance space was mapped to the design space, which completed the exploration and preliminary reduction of the entire design space. This method provides a computational analysis and implementation scheme for large-scale simulation. PMID:24790572

Exploration of a capability-focused aerospace system of systems architecture alternative with bilayer design space, based on RST-SOM algorithmic methods.

PubMed

Li, Zhifei; Qin, Dongliang; Yang, Feng

2014-01-01

In defense related programs, the use of capability-based analysis, design, and acquisition has been significant. In order to confront one of the most challenging features of a huge design space in capability based analysis (CBA), a literature review of design space exploration was first examined. Then, in the process of an aerospace system of systems design space exploration, a bilayer mapping method was put forward, based on the existing experimental and operating data. Finally, the feasibility of the foregoing approach was demonstrated with an illustrative example. With the data mining RST (rough sets theory) and SOM (self-organized mapping) techniques, the alternative to the aerospace system of systems architecture was mapping from P-space (performance space) to C-space (configuration space), and then from C-space to D-space (design space), respectively. Ultimately, the performance space was mapped to the design space, which completed the exploration and preliminary reduction of the entire design space. This method provides a computational analysis and implementation scheme for large-scale simulation.

Comparison of Pixel-Based and Object-Based Classification Using Parameters and Non-Parameters Approach for the Pattern Consistency of Multi Scale Landcover

NASA Astrophysics Data System (ADS)

Juniati, E.; Arrofiqoh, E. N.

2017-09-01

Information extraction from remote sensing data especially land cover can be obtained by digital classification. In practical some people are more comfortable using visual interpretation to retrieve land cover information. However, it is highly influenced by subjectivity and knowledge of interpreter, also takes time in the process. Digital classification can be done in several ways, depend on the defined mapping approach and assumptions on data distribution. The study compared several classifiers method for some data type at the same location. The data used Landsat 8 satellite imagery, SPOT 6 and Orthophotos. In practical, the data used to produce land cover map in 1:50,000 map scale for Landsat, 1:25,000 map scale for SPOT and 1:5,000 map scale for Orthophotos, but using visual interpretation to retrieve information. Maximum likelihood Classifiers (MLC) which use pixel-based and parameters approach applied to such data, and also Artificial Neural Network classifiers which use pixel-based and non-parameters approach applied too. Moreover, this study applied object-based classifiers to the data. The classification system implemented is land cover classification on Indonesia topographic map. The classification applied to data source, which is expected to recognize the pattern and to assess consistency of the land cover map produced by each data. Furthermore, the study analyse benefits and limitations the use of methods.

Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

NASA Astrophysics Data System (ADS)

Kohira, K.; Masuda, H.

2017-09-01

A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui.

PubMed

Newton, Richard; Deonarine, Andrew; Wernisch, Lorenz

2012-09-24

The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an educational role for such applications.

Retinotopic Maps, Spatial Tuning, and Locations of Human Visual Areas in Surface Coordinates Characterized with Multifocal and Blocked fMRI Designs

PubMed Central

Henriksson, Linda; Karvonen, Juha; Salminen-Vaparanta, Niina; Railo, Henry; Vanni, Simo

2012-01-01

The localization of visual areas in the human cortex is typically based on mapping the retinotopic organization with functional magnetic resonance imaging (fMRI). The most common approach is to encode the response phase for a slowly moving visual stimulus and to present the result on an individual's reconstructed cortical surface. The main aims of this study were to develop complementary general linear model (GLM)-based retinotopic mapping methods and to characterize the inter-individual variability of the visual area positions on the cortical surface. We studied 15 subjects with two methods: a 24-region multifocal checkerboard stimulus and a blocked presentation of object stimuli at different visual field locations. The retinotopic maps were based on weighted averaging of the GLM parameter estimates for the stimulus regions. In addition to localizing visual areas, both methods could be used to localize multiple retinotopic regions-of-interest. The two methods yielded consistent retinotopic maps in the visual areas V1, V2, V3, hV4, and V3AB. In the higher-level areas IPS0, VO1, LO1, LO2, TO1, and TO2, retinotopy could only be mapped with the blocked stimulus presentation. The gradual widening of spatial tuning and an increase in the responses to stimuli in the ipsilateral visual field along the hierarchy of visual areas likely reflected the increase in the average receptive field size. Finally, after registration to Freesurfer's surface-based atlas of the human cerebral cortex, we calculated the mean and variability of the visual area positions in the spherical surface-based coordinate system and generated probability maps of the visual areas on the average cortical surface. The inter-individual variability in the area locations decreased when the midpoints were calculated along the spherical cortical surface compared with volumetric coordinates. These results can facilitate both analysis of individual functional anatomy and comparisons of visual cortex topology across studies. PMID:22590626

A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

NASA Astrophysics Data System (ADS)

Sun, Li-Sha; Kang, Xiao-Yun; Zhang, Qiong; Lin, Lan-Xin

2011-12-01

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.

Decoding 2D-PAGE complex maps: relevance to proteomics.

PubMed

Pietrogrande, Maria Chiara; Marchetti, Nicola; Dondi, Francesco; Righetti, Pier Giorgio

2006-03-20

This review describes two mathematical approaches useful for decoding the complex signal of 2D-PAGE maps of protein mixtures. These methods are helpful for interpreting the large amount of data of each 2D-PAGE map by extracting all the analytical information hidden therein by spot overlapping. Here the basic theory and application to 2D-PAGE maps are reviewed: the means for extracting information from the experimental data and their relevance to proteomics are discussed. One method is based on the quantitative theory of statistical model of peak overlapping (SMO) using the spot experimental data (intensity and spatial coordinates). The second method is based on the study of the 2D-autocovariance function (2D-ACVF) computed on the experimental digitised map. They are two independent methods that are able to extract equal and complementary information from the 2D-PAGE map. Both methods permit to obtain fundamental information on the sample complexity and the separation performance and to single out ordered patterns present in spot positions: the availability of two independent procedures to compute the same separation parameters is a powerful tool to estimate the reliability of the obtained results. The SMO procedure is an unique tool to quantitatively estimate the degree of spot overlapping present in the map, while the 2D-ACVF method is particularly powerful in simply singling out the presence of order in the spot position from the complexity of the whole 2D map, i.e., spot trains. The procedures were validated by extensive numerical computation on computer-generated maps describing experimental 2D-PAGE gels of protein mixtures. Their applicability to real samples was tested on reference maps obtained from literature sources. The review describes the most relevant information for proteomics: sample complexity, separation performance, overlapping extent, identification of spot trains related to post-translational modifications (PTMs).

An efficient hole-filling method based on depth map in 3D view generation

NASA Astrophysics Data System (ADS)

Liang, Haitao; Su, Xiu; Liu, Yilin; Xu, Huaiyuan; Wang, Yi; Chen, Xiaodong

2018-01-01

New virtual view is synthesized through depth image based rendering(DIBR) using a single color image and its associated depth map in 3D view generation. Holes are unavoidably generated in the 2D to 3D conversion process. We propose a hole-filling method based on depth map to address the problem. Firstly, we improve the process of DIBR by proposing a one-to-four (OTF) algorithm. The "z-buffer" algorithm is used to solve overlap problem. Then, based on the classical patch-based algorithm of Criminisi et al., we propose a hole-filling algorithm using the information of depth map to handle the image after DIBR. In order to improve the accuracy of the virtual image, inpainting starts from the background side. In the calculation of the priority, in addition to the confidence term and the data term, we add the depth term. In the search for the most similar patch in the source region, we define the depth similarity to improve the accuracy of searching. Experimental results show that the proposed method can effectively improve the quality of the 3D virtual view subjectively and objectively.

Participatory mapping in low-resource settings: Three novel methods used to engage Kenyan youth and other community members in community-based HIV prevention research

PubMed Central

Green, Eric P.; Warren, Virginia Rieck; Broverman, Sherryl; Ogwang, Benson; Puffer, Eve S.

2017-01-01

Understanding the link between health and place can strengthen the design of health interventions, particularly in the context of HIV prevention. Individuals who might one day participate in such interventions—including youth—may further improve the design if engaged in a meaningful way in the formative research process. Increasingly, participatory mapping methods are being used to achieve both aims. We describe the development of three innovative mapping methods for engaging youth in formative community-based research: ‘dot map’ focus groups, geocaching games, and satellite imagery assisted daily activity logs. We demonstrate that these methods are feasible and acceptable in a low-resource, rural African setting. The discussion outlines the merits of each method and considers possible limitations. PMID:27064073

A concept mapping approach to guide and understand dissemination and implementation.

PubMed

Green, Amy E; Fettes, Danielle L; Aarons, Gregory A

2012-10-01

Many efforts to implement evidence-based programs do not reach their full potential or fail due to the variety of challenges inherent in dissemination and implementation. This article describes the use of concept mapping-a mixed method strategy-to study implementation of behavioral health innovations and evidence-based practice (EBP). The application of concept mapping to implementation research represents a practical and concise way to identify and quantify factors affecting implementation, develop conceptual models of implementation, target areas to address as part of implementation readiness and active implementation, and foster communication among stakeholders. Concept mapping is described and a case example is provided to illustrate its use in an implementation study. Implications for the use of concept mapping methods in both research and applied settings towards the dissemination and implementation of behavioral health services are discussed.

Application of remote sensing to reconnaissance geologic mapping and mineral exploration

NASA Technical Reports Server (NTRS)

Birnie, R. W.; Dykstra, J. D.

1978-01-01

A method of mapping geology at a reconnaissance scale and locating zones of possible hydrothermal alteration has been developed. This method is based on principal component analysis of Landsat digital data and is applied to the desert area of the Chagai Hills, Baluchistan, Pakistan. A method for airborne spectrometric detection of geobotanical anomalies associated with prophyry Cu-Mo mineralization at Heddleston, Montana has also been developed. This method is based on discriminants in the 0.67 micron and 0.79 micron region of the spectrum.

Salient region detection by fusing bottom-up and top-down features extracted from a single image.

PubMed

Tian, Huawei; Fang, Yuming; Zhao, Yao; Lin, Weisi; Ni, Rongrong; Zhu, Zhenfeng

2014-10-01

Recently, some global contrast-based salient region detection models have been proposed based on only the low-level feature of color. It is necessary to consider both color and orientation features to overcome their limitations, and thus improve the performance of salient region detection for images with low-contrast in color and high-contrast in orientation. In addition, the existing fusion methods for different feature maps, like the simple averaging method and the selective method, are not effective sufficiently. To overcome these limitations of existing salient region detection models, we propose a novel salient region model based on the bottom-up and top-down mechanisms: the color contrast and orientation contrast are adopted to calculate the bottom-up feature maps, while the top-down cue of depth-from-focus from the same single image is used to guide the generation of final salient regions, since depth-from-focus reflects the photographer's preference and knowledge of the task. A more general and effective fusion method is designed to combine the bottom-up feature maps. According to the degree-of-scattering and eccentricities of feature maps, the proposed fusion method can assign adaptive weights to different feature maps to reflect the confidence level of each feature map. The depth-from-focus of the image as a significant top-down feature for visual attention in the image is used to guide the salient regions during the fusion process; with its aid, the proposed fusion method can filter out the background and highlight salient regions for the image. Experimental results show that the proposed model outperforms the state-of-the-art models on three public available data sets.

An ellipsometric approach towards the description of inhomogeneous polymer-based Langmuir layers

PubMed Central

Rottke, Falko O; Schulz, Burkhard; Richau, Klaus; Kratz, Karl

2016-01-01

Summary The applicability of nulling-based ellipsometric mapping as a complementary method next to Brewster angle microscopy (BAM) and imaging ellipsometry (IE) is presented for the characterization of ultrathin films at the air–water interface. First, the methodology is demonstrated for a vertically nonmoving Langmuir layer of star-shaped, 4-arm poly(ω-pentadecalactone) (PPDL-D4). Using nulling-based ellipsometric mapping, PPDL-D4-based inhomogeneously structured morphologies with a vertical dimension in the lower nm range could be mapped. In addition to the identification of these structures, the differentiation between a monolayer and bare water was possible. Second, the potential and limitations of this method were verified by applying it to more versatile Langmuir layers of telechelic poly[(rac-lactide)-co-glycolide]-diol (PLGA). All ellipsometric maps were converted into thickness maps by introduction of the refractive index that was derived from independent ellipsometric experiments, and the result was additionally evaluated in terms of the root mean square roughness, R q. Thereby, a three-dimensional view into the layers was enabled and morphological inhomogeneity could be quantified. PMID:27826490

Applying parallel factor analysis and Tucker-3 methods on sensory and instrumental data to establish preference maps: case study on sweet corn varieties.

PubMed

Gere, Attila; Losó, Viktor; Györey, Annamária; Kovács, Sándor; Huzsvai, László; Nábrádi, András; Kókai, Zoltán; Sipos, László

2014-12-01

Traditional internal and external preference mapping methods are based on principal component analysis (PCA). However, parallel factor analysis (PARAFAC) and Tucker-3 methods could be a better choice. To evaluate the methods, preference maps of sweet corn varieties will be introduced. A preference map of eight sweet corn varieties was established using PARAFAC and Tucker-3 methods. Instrumental data were also integrated into the maps. The triplot created by the PARAFAC model explains better how odour is separated from texture or appearance, and how some varieties are separated from others. Internal and external preference maps were created using parallel factor analysis (PARAFAC) and Tucker-3 models employing both sensory (trained panel and consumers) and instrumental parameters simultaneously. Triplots of the applied three-way models have a competitive advantage compared to the traditional biplots of the PCA-based external preference maps. The solution of PARAFAC and Tucker-3 is very similar regarding the interpretation of the first and third factors. The main difference is due to the second factor as it differentiated the attributes better. Consumers who prefer 'super sweet' varieties (they place great emphasis especially on taste) are much younger and have significantly higher incomes, and buy sweet corn products rarely (once a month). Consumers who consume sweet corn products mainly because of their texture and appearance are significantly older and include a higher ratio of men. © 2014 Society of Chemical Industry.

sscMap: an extensible Java application for connecting small-molecule drugs using gene-expression signatures.

PubMed

Zhang, Shu-Dong; Gant, Timothy W

2009-07-31

Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap.

A flood map based DOI decoding method for block detector: a GATE simulation study.

PubMed

Shi, Han; Du, Dong; Su, Zhihong; Peng, Qiyu

2014-01-01

Positron Emission Tomography (PET) systems using detectors with Depth of Interaction (DOI) capabilities could achieve higher spatial resolution and better image quality than those without DOI. Up till now, most DOI methods developed are not cost-efficient for a whole body PET system. In this paper, we present a DOI decoding method based on flood map for low-cost conventional block detector with four-PMT readout. Using this method, the DOI information can be directly extracted from the DOI-related crystal spot deformation in the flood map. GATE simulations are then carried out to validate the method, confirming a DOI sorting accuracy of 85.27%. Therefore, we conclude that this method has the potential to be applied in conventional detectors to achieve a reasonable DOI measurement without dramatically increasing their complexity and cost of an entire PET system.

Analyzing the Scientific Evolution of Social Work Using Science Mapping

ERIC Educational Resources Information Center

Martínez, Ma Angeles; Cobo, Manuel Jesús; Herrera, Manuel; Herrera-Viedma, Enrique

2015-01-01

Objectives: This article reports the first science mapping analysis of the social work field, which shows its conceptual structure and scientific evolution. Methods: Science Mapping Analysis Software Tool, a bibliometric science mapping tool based on co-word analysis and h-index, is applied using a sample of 18,794 research articles published from…

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

PubMed Central

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery.

PubMed

Huang, Huasheng; Deng, Jizhong; Lan, Yubin; Yang, Aqing; Deng, Xiaoling; Zhang, Lei

2018-01-01

Appropriate Site Specific Weed Management (SSWM) is crucial to ensure the crop yields. Within SSWM of large-scale area, remote sensing is a key technology to provide accurate weed distribution information. Compared with satellite and piloted aircraft remote sensing, unmanned aerial vehicle (UAV) is capable of capturing high spatial resolution imagery, which will provide more detailed information for weed mapping. The objective of this paper is to generate an accurate weed cover map based on UAV imagery. The UAV RGB imagery was collected in 2017 October over the rice field located in South China. The Fully Convolutional Network (FCN) method was proposed for weed mapping of the collected imagery. Transfer learning was used to improve generalization capability, and skip architecture was applied to increase the prediction accuracy. After that, the performance of FCN architecture was compared with Patch_based CNN algorithm and Pixel_based CNN method. Experimental results showed that our FCN method outperformed others, both in terms of accuracy and efficiency. The overall accuracy of the FCN approach was up to 0.935 and the accuracy for weed recognition was 0.883, which means that this algorithm is capable of generating accurate weed cover maps for the evaluated UAV imagery.

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

PubMed

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

The effects of using concept mapping as an artifact to engender metacognitive thinking in first-year medical students' problem-based learning discussions: A mixed-methods investigation

NASA Astrophysics Data System (ADS)

Shoop, Glenda Hostetter

Attention in medical education is turning toward instruction that not only focuses on knowledge acquisition, but on developing the medical students' clinical problem-solving skills, and their ability to critically think through complex diseases. Metacognition is regarded as an important consideration in how we teach medical students these higher-order, critical thinking skills. This study used a mixed-methods research design to investigate if concept mapping as an artifact may engender metacognitive thinking in the medical student population. Specifically the purpose of the study is twofold: (1) to determine if concept mapping, functioning as an artifact during problem-based learning, improves learning as measured by scores on test questions; and (2) to explore if the process of concept mapping alters the problem-based learning intragroup discussion in ways that show medical students are engaged in metacognitive thinking. The results showed that students in the problem-based learning concept-mapping groups used more metacognitive thinking patterns than those in the problem-based learning discussion-only group, particularly in the monitoring component. These groups also engaged in a higher level of cognitive thinking associated with reasoning through mechanisms-of-action and breaking down complex biochemical and physiologic principals. The students disclosed in focus-group interviews that concept mapping was beneficial to help them understand how discrete pieces of information fit together in a bigger structure of knowledge. They also stated that concept mapping gave them some time to think through these concepts in a larger conceptual framework. There was no significant difference in the exam-question scores between the problem-based learning concept-mapping groups and the problem-based learning discussion-only group.

Slope, Scarp and Sea Cliff Instability Susceptibility Mapping for Planning Regulations in Almada County, Portugal

NASA Astrophysics Data System (ADS)

Marques, Fernando; Queiroz, Sónia; Gouveia, Luís; Vasconcelos, Manuel

2017-12-01

In Portugal, the modifications introduced in 2008 and 2012 in the National Ecological Reserve law (REN) included the mandatory study of slope instability, including slopes, natural scarps, and sea cliffs, at municipal or regional scale, with the purpose of avoiding the use of hazardous zones with buildings and other structures. The law also indicates specific methods to perform these studies, with different approaches for slope instability, natural scarps and sea cliffs. The methods used to produce the maps required by REN law, with modifications and improvements to the law specified methods, were applied to the 71 km2 territory of Almada County, and included: 1) Slope instability mapping using the statistically based Information Value method validated with the landslide inventory using ROC curves, which provided an AAC=0.964, with the higher susceptibility zones which cover at least 80% of the landslides of the inventory to be included in REN map. The map was object of a generalization process to overcome the inconveniences of the use of a pixel based approach. 2) Natural scarp mapping including setback areas near the top, defined according to the law and setback areas near the toe defined by the application of the shadow angle calibrated with the major rockfalls which occurred in the study area; 3) Sea cliffs mapping including two levels of setback zones near the top, and one setback zone at the cliffs toe, which were based on systematic inventories of cliff failures occurred between 1947 and 2010 in a large scale regional littoral monitoring project. In the paper are described the methods used and the results obtained in this study, which correspond to the final maps of areas to include in REN. The results obtained in this study may be considered as an example of good practice of the municipal authorities in terms of solid, technical and scientifically supported regulation definitions, hazard prevention and safe and sustainable land use management.

Bedrock topography of western Cape Cod, Massachusetts, based on bedrock altitudes from geologic borings and analysis of ambient seismic noise by the horizontal-to-vertical spectral-ratio method

USGS Publications Warehouse

Fairchild, Gillian M.; Lane, John W.; Voytek, Emily B.; LeBlanc, Denis R.

2013-01-01

This report presents a topographic map of the bedrock surface beneath western Cape Cod, Massachusetts, that was prepared for use in groundwater-flow models of the Sagamore lens of the Cape Cod aquifer. The bedrock surface of western Cape Cod had been characterized previously through seismic refraction surveys and borings drilled to bedrock. The borings were mostly on and near the Massachusetts Military Reservation (MMR). The bedrock surface was first mapped by Oldale (1969), and mapping was updated in 2006 by the Air Force Center for Environmental Excellence (AFCEE, 2006). This report updates the bedrock-surface map with new data points collected by using a passive seismic technique based on the horizontal-to-vertical spectral ratio (HVSR) of ambient seismic noise (Lane and others, 2008) and from borings drilled to bedrock since the 2006 map was prepared. The HVSR method is based on a relationship between the resonance frequency of ambient seismic noise as measured at land surface and the thickness of the unconsolidated sediments that overlie consolidated bedrock. The HVSR method was shown by Lane and others (2008) to be an effective method for determining sediment thickness on Cape Cod owing to the distinct difference in the acoustic impedance between the sediments and the underlying bedrock. The HVSR data for 164 sites were combined with data from 559 borings to bedrock in the study area to create a spatially distributed dataset that was manually contoured to prepare a topographic map of the bedrock surface. The interpreted bedrock surface generally slopes downward to the southeast as was shown on the earlier maps by Oldale (1969) and AFCEE (2006). The surface also has complex small-scale topography characteristic of a glacially eroded surface. More information about the methods used to prepare the map is given in the pamphlet that accompanies this plate.

Progress toward scalable tomography of quantum maps using twirling-based methods and information hierarchies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lopez, Cecilia C.; Theoretische Physik, Universitaet des Saarlandes, D-66041 Saarbruecken; Departament de Fisica, Universitat Autonoma de Barcelona, E-08193 Bellaterra

2010-06-15

We present in a unified manner the existing methods for scalable partial quantum process tomography. We focus on two main approaches: the one presented in Bendersky et al. [Phys. Rev. Lett. 100, 190403 (2008)] and the ones described, respectively, in Emerson et al. [Science 317, 1893 (2007)] and Lopez et al. [Phys. Rev. A 79, 042328 (2009)], which can be combined together. The methods share an essential feature: They are based on the idea that the tomography of a quantum map can be efficiently performed by studying certain properties of a twirling of such a map. From this perspective, inmore » this paper we present extensions, improvements, and comparative analyses of the scalable methods for partial quantum process tomography. We also clarify the significance of the extracted information, and we introduce interesting and useful properties of the {chi}-matrix representation of quantum maps that can be used to establish a clearer path toward achieving full tomography of quantum processes in a scalable way.« less

Flexible, reconfigurable, power efficient transmitter and method

NASA Technical Reports Server (NTRS)

Bishop, James W. (Inventor); Zaki, Nazrul H. Mohd (Inventor); Newman, David Childress (Inventor); Bundick, Steven N. (Inventor)

2011-01-01

A flexible, reconfigurable, power efficient transmitter device and method is provided. In one embodiment, the method includes receiving outbound data and determining a mode of operation. When operating in a first mode the method may include modulation mapping the outbound data according a modulation scheme to provide first modulation mapped digital data, converting the first modulation mapped digital data to an analog signal that comprises an intermediate frequency (IF) analog signal, upconverting the IF analog signal to produce a first modulated radio frequency (RF) signal based on a local oscillator signal, amplifying the first RF modulated signal to produce a first RF output signal, and outputting the first RF output signal via an isolator. In a second mode of operation method may include modulation mapping the outbound data according a modulation scheme to provide second modulation mapped digital data, converting the second modulation mapped digital data to a first digital baseband signal, conditioning the first digital baseband signal to provide a first analog baseband signal, modulating one or more carriers with the first analog baseband signal to produce a second modulated RF signal based on a local oscillator signal, amplifying the second RF modulated signal to produce a second RF output signal, and outputting the second RF output signal via the isolator. The digital baseband signal may comprise an in-phase (I) digital baseband signal and a quadrature (Q) baseband signal.

Power maps and wavefront for progressive addition lenses in eyeglass frames.

PubMed

Mejía, Yobani; Mora, David A; Díaz, Daniel E

2014-10-01

To evaluate a method for measuring the cylinder, sphere, and wavefront of progressive addition lenses (PALs) in eyeglass frames. We examine the contour maps of cylinder, sphere, and wavefront of a PAL assembled in an eyeglass frame using an optical system based on a Hartmann test. To reduce the data noise, particularly in the border of the eyeglass frame, we implement a method based on the Fourier analysis to extrapolate spots outside the eyeglass frame. The spots are extrapolated up to a circular pupil that circumscribes the eyeglass frame and compared with data obtained from a circular uncut PAL. By using the Fourier analysis to extrapolate spots outside the eyeglass frame, we can remove the edge artifacts of the PAL within its frame and implement the modal method to fit wavefront data with Zernike polynomials within a circular aperture that circumscribes the frame. The extrapolated modal maps from framed PALs accurately reflect maps obtained from uncut PALs and provide smoothed maps for the cylinder and sphere inside the eyeglass frame. The proposed method for extrapolating spots outside the eyeglass frame removes edge artifacts of the contour maps (wavefront, cylinder, and sphere), which may be useful to facilitate measurements such as the length and width of the progressive corridor for a PAL in its frame. The method can be applied to any shape of eyeglass frame.

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

AEKF-SLAM: A New Algorithm for Robotic Underwater Navigation

PubMed Central

Yuan, Xin; Martínez-Ortega, José-Fernán; Fernández, José Antonio Sánchez; Eckert, Martina

2017-01-01

In this work, we focus on key topics related to underwater Simultaneous Localization and Mapping (SLAM) applications. Moreover, a detailed review of major studies in the literature and our proposed solutions for addressing the problem are presented. The main goal of this paper is the enhancement of the accuracy and robustness of the SLAM-based navigation problem for underwater robotics with low computational costs. Therefore, we present a new method called AEKF-SLAM that employs an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-based SLAM approach stores the robot poses and map landmarks in a single state vector, while estimating the state parameters via a recursive and iterative estimation-update process. Hereby, the prediction and update state (which exist as well in the conventional EKF) are complemented by a newly proposed augmentation stage. Applied to underwater robot navigation, the AEKF-SLAM has been compared with the classic and popular FastSLAM 2.0 algorithm. Concerning the dense loop mapping and line mapping experiments, it shows much better performances in map management with respect to landmark addition and removal, which avoid the long-term accumulation of errors and clutters in the created map. Additionally, the underwater robot achieves more precise and efficient self-localization and a mapping of the surrounding landmarks with much lower processing times. Altogether, the presented AEKF-SLAM method achieves reliably map revisiting, and consistent map upgrading on loop closure. PMID:28531135

Performance comparison of LUR and OK in PM2.5 concentration mapping: a multidimensional perspective

PubMed Central

Zou, Bin; Luo, Yanqing; Wan, Neng; Zheng, Zhong; Sternberg, Troy; Liao, Yilan

2015-01-01

Methods of Land Use Regression (LUR) modeling and Ordinary Kriging (OK) interpolation have been widely used to offset the shortcomings of PM2.5 data observed at sparse monitoring sites. However, traditional point-based performance evaluation strategy for these methods remains stagnant, which could cause unreasonable mapping results. To address this challenge, this study employs ‘information entropy’, an area-based statistic, along with traditional point-based statistics (e.g. error rate, RMSE) to evaluate the performance of LUR model and OK interpolation in mapping PM2.5 concentrations in Houston from a multidimensional perspective. The point-based validation reveals significant differences between LUR and OK at different test sites despite the similar end-result accuracy (e.g. error rate 6.13% vs. 7.01%). Meanwhile, the area-based validation demonstrates that the PM2.5 concentrations simulated by the LUR model exhibits more detailed variations than those interpolated by the OK method (i.e. information entropy, 7.79 vs. 3.63). Results suggest that LUR modeling could better refine the spatial distribution scenario of PM2.5 concentrations compared to OK interpolation. The significance of this study primarily lies in promoting the integration of point- and area-based statistics for model performance evaluation in air pollution mapping. PMID:25731103

Salient target detection based on pseudo-Wigner-Ville distribution and Rényi entropy.

PubMed

Xu, Yuannan; Zhao, Yuan; Jin, Chenfei; Qu, Zengfeng; Liu, Liping; Sun, Xiudong

2010-02-15

We present what we believe to be a novel method based on pseudo-Wigner-Ville distribution (PWVD) and Rényi entropy for salient targets detection. In the foundation of studying the statistical property of Rényi entropy via PWVD, the residual entropy-based saliency map of an input image can be obtained. From the saliency map, target detection is completed by the simple and convenient threshold segmentation. Experimental results demonstrate the proposed method can detect targets effectively in complex ground scenes.

exocartographer: Constraining surface maps orbital parameters of exoplanets

NASA Astrophysics Data System (ADS)

Farr, Ben; Farr, Will M.; Cowan, Nicolas B.; Haggard, Hal M.; Robinson, Tyler

2018-05-01

exocartographer solves the exo-cartography inverse problem. This flexible forward-modeling framework, written in Python, retrieves the albedo map and spin geometry of a planet based on time-resolved photometry; it uses a Markov chain Monte Carlo method to extract albedo maps and planet spin and their uncertainties. Gaussian Processes use the data to fit for the characteristic length scale of the map and enforce smooth maps.

Conformal mapping for multiple terminals

PubMed Central

Wang, Weimin; Ma, Wenying; Wang, Qiang; Ren, Hao

2016-01-01

Conformal mapping is an important mathematical tool that can be used to solve various physical and engineering problems in many fields, including electrostatics, fluid mechanics, classical mechanics, and transformation optics. It is an accurate and convenient way to solve problems involving two terminals. However, when faced with problems involving three or more terminals, which are more common in practical applications, existing conformal mapping methods apply assumptions or approximations. A general exact method does not exist for a structure with an arbitrary number of terminals. This study presents a conformal mapping method for multiple terminals. Through an accurate analysis of boundary conditions, additional terminals or boundaries are folded into the inner part of a mapped region. The method is applied to several typical situations, and the calculation process is described for two examples of an electrostatic actuator with three electrodes and of a light beam splitter with three ports. Compared with previously reported results, the solutions for the two examples based on our method are more precise and general. The proposed method is helpful in promoting the application of conformal mapping in analysis of practical problems. PMID:27830746

Mixture model based joint-MAP reconstruction of attenuation and activity maps in TOF-PET

NASA Astrophysics Data System (ADS)

Hemmati, H.; Kamali-Asl, A.; Ghafarian, P.; Ay, M. R.

2018-06-01

A challenge to have quantitative positron emission tomography (PET) images is to provide an accurate and patient-specific photon attenuation correction. In PET/MR scanners, the nature of MR signals and hardware limitations have led to a real challenge on the attenuation map extraction. Except for a constant factor, the activity and attenuation maps from emission data on TOF-PET system can be determined by the maximum likelihood reconstruction of attenuation and activity approach (MLAA) from emission data. The aim of the present study is to constrain the joint estimations of activity and attenuation approach for PET system using a mixture model prior based on the attenuation map histogram. This novel prior enforces non-negativity and its hyperparameters can be estimated using a mixture decomposition step from the current estimation of the attenuation map. The proposed method can also be helpful on the solving of scaling problem and is capable to assign the predefined regional attenuation coefficients with some degree of confidence to the attenuation map similar to segmentation-based attenuation correction approaches. The performance of the algorithm is studied with numerical and Monte Carlo simulations and a phantom experiment and was compared with MLAA algorithm with and without the smoothing prior. The results demonstrate that the proposed algorithm is capable of producing the cross-talk free activity and attenuation images from emission data. The proposed approach has potential to be a practical and competitive method for joint reconstruction of activity and attenuation maps from emission data on PET/MR and can be integrated on the other methods.

Computed tomography landmark-based semi-automated mesh morphing and mapping techniques: generation of patient specific models of the human pelvis without segmentation.

PubMed

Salo, Zoryana; Beek, Maarten; Wright, David; Whyne, Cari Marisa

2015-04-13

Current methods for the development of pelvic finite element (FE) models generally are based upon specimen specific computed tomography (CT) data. This approach has traditionally required segmentation of CT data sets, which is time consuming and necessitates high levels of user intervention due to the complex pelvic anatomy. The purpose of this research was to develop and assess CT landmark-based semi-automated mesh morphing and mapping techniques to aid the generation and mechanical analysis of specimen-specific FE models of the pelvis without the need for segmentation. A specimen-specific pelvic FE model (source) was created using traditional segmentation methods and morphed onto a CT scan of a different (target) pelvis using a landmark-based method. The morphed model was then refined through mesh mapping by moving the nodes to the bone boundary. A second target model was created using traditional segmentation techniques. CT intensity based material properties were assigned to the morphed/mapped model and to the traditionally segmented target models. Models were analyzed to evaluate their geometric concurrency and strain patterns. Strains generated in a double-leg stance configuration were compared to experimental strain gauge data generated from the same target cadaver pelvis. CT landmark-based morphing and mapping techniques were efficiently applied to create a geometrically multifaceted specimen-specific pelvic FE model, which was similar to the traditionally segmented target model and better replicated the experimental strain results (R(2)=0.873). This study has shown that mesh morphing and mapping represents an efficient validated approach for pelvic FE model generation without the need for segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies.

PubMed

Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

2017-05-07

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18 F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans-each containing 1/8th of the total number of events-were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18 F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of [Formula: see text], the tracer transport rate (ml · min -1 · ml -1 ), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced [Formula: see text] maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced [Formula: see text] estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in-vivo studies

PubMed Central

Petibon, Yoann; Rakvongthai, Yothin; Fakhri, Georges El; Ouyang, Jinsong

2017-01-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves -TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in-vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans - each containing 1/8th of the total number of events - were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard Ordered Subset Expectation Maximization (OSEM) reconstruction algorithm on one side, and the One-Step Late Maximum a Posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of K1, the tracer transport rate (mL.min−1.mL−1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced K1 maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced K1 estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in-vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance. PMID:28379843

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

NASA Astrophysics Data System (ADS)

Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

2017-05-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of {{K}1} , the tracer transport rate (ml · min-1 · ml-1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced {{K}1} maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced {{K}1} estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

PubMed

Waldner, François; Hansen, Matthew C; Potapov, Peter V; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information

PubMed Central

Hansen, Matthew C.; Potapov, Peter V.; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring. PMID:28817618

A fusion algorithm for infrared and visible based on guided filtering and phase congruency in NSST domain

NASA Astrophysics Data System (ADS)

Liu, Zhanwen; Feng, Yan; Chen, Hang; Jiao, Licheng

2017-10-01

A novel and effective image fusion method is proposed for creating a highly informative and smooth surface of fused image through merging visible and infrared images. Firstly, a two-scale non-subsampled shearlet transform (NSST) is employed to decompose the visible and infrared images into detail layers and one base layer. Then, phase congruency is adopted to extract the saliency maps from the detail layers and a guided filtering is proposed to compute the filtering output of base layer and saliency maps. Next, a novel weighted average technique is used to make full use of scene consistency for fusion and obtaining coefficients map. Finally the fusion image was acquired by taking inverse NSST of the fused coefficients map. Experiments show that the proposed approach can achieve better performance than other methods in terms of subjective visual effect and objective assessment.

Mapping functional connectivity

Treesearch

Peter Vogt; Joseph R. Ferrari; Todd R. Lookingbill; Robert H. Gardner; Kurt H. Riitters; Katarzyna Ostapowicz

2009-01-01

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible,...

Distance-Based Phylogenetic Methods Around a Polytomy.

PubMed

Davidson, Ruth; Sullivant, Seth

2014-01-01

Distance-based phylogenetic algorithms attempt to solve the NP-hard least-squares phylogeny problem by mapping an arbitrary dissimilarity map representing biological data to a tree metric. The set of all dissimilarity maps is a Euclidean space properly containing the space of all tree metrics as a polyhedral fan. Outputs of distance-based tree reconstruction algorithms such as UPGMA and neighbor-joining are points in the maximal cones in the fan. Tree metrics with polytomies lie at the intersections of maximal cones. A phylogenetic algorithm divides the space of all dissimilarity maps into regions based upon which combinatorial tree is reconstructed by the algorithm. Comparison of phylogenetic methods can be done by comparing the geometry of these regions. We use polyhedral geometry to compare the local nature of the subdivisions induced by least-squares phylogeny, UPGMA, and neighbor-joining when the true tree has a single polytomy with exactly four neighbors. Our results suggest that in some circumstances, UPGMA and neighbor-joining poorly match least-squares phylogeny.

Proposal of Classification Method of Time Series Data in International Emissions Trading Market Using Agent-based Simulation

NASA Astrophysics Data System (ADS)

Nakada, Tomohiro; Takadama, Keiki; Watanabe, Shigeyoshi

This paper proposes the classification method using Bayesian analytical method to classify the time series data in the international emissions trading market depend on the agent-based simulation and compares the case with Discrete Fourier transform analytical method. The purpose demonstrates the analytical methods mapping time series data such as market price. These analytical methods have revealed the following results: (1) the classification methods indicate the distance of mapping from the time series data, it is easier the understanding and inference than time series data; (2) these methods can analyze the uncertain time series data using the distance via agent-based simulation including stationary process and non-stationary process; and (3) Bayesian analytical method can show the 1% difference description of the emission reduction targets of agent.

Long-time uncertainty propagation using generalized polynomial chaos and flow map composition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luchtenburg, Dirk M., E-mail: dluchten@cooper.edu; Brunton, Steven L.; Rowley, Clarence W.

2014-10-01

We present an efficient and accurate method for long-time uncertainty propagation in dynamical systems. Uncertain initial conditions and parameters are both addressed. The method approximates the intermediate short-time flow maps by spectral polynomial bases, as in the generalized polynomial chaos (gPC) method, and uses flow map composition to construct the long-time flow map. In contrast to the gPC method, this approach has spectral error convergence for both short and long integration times. The short-time flow map is characterized by small stretching and folding of the associated trajectories and hence can be well represented by a relatively low-degree basis. The compositionmore » of these low-degree polynomial bases then accurately describes the uncertainty behavior for long integration times. The key to the method is that the degree of the resulting polynomial approximation increases exponentially in the number of time intervals, while the number of polynomial coefficients either remains constant (for an autonomous system) or increases linearly in the number of time intervals (for a non-autonomous system). The findings are illustrated on several numerical examples including a nonlinear ordinary differential equation (ODE) with an uncertain initial condition, a linear ODE with an uncertain model parameter, and a two-dimensional, non-autonomous double gyre flow.« less

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

PubMed

Khalifé, Maya; Fernandez, Brice; Jaubert, Olivier; Soussan, Michael; Brulon, Vincent; Buvat, Irène; Comtat, Claude

2017-09-21

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units ([Formula: see text]) in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous μ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into [Formula: see text] was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of [Formula: see text] corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

NASA Astrophysics Data System (ADS)

Khalifé, Maya; Fernandez, Brice; Jaubert, Olivier; Soussan, Michael; Brulon, Vincent; Buvat, Irène; Comtat, Claude

2017-10-01

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units (HU ) in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous μ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into HU was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of 4~mm corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

Validation and application of Acoustic Mapping Velocimetry

NASA Astrophysics Data System (ADS)

Baranya, Sandor; Muste, Marian

2016-04-01

The goal of this paper is to introduce a novel methodology to estimate bedload transport in rivers based on an improved bedform tracking procedure. The measurement technique combines components and processing protocols from two contemporary nonintrusive instruments: acoustic and image-based. The bedform mapping is conducted with acoustic surveys while the estimation of the velocity of the bedforms is obtained with processing techniques pertaining to image-based velocimetry. The technique is therefore called Acoustic Mapping Velocimetry (AMV). The implementation of this technique produces a whole-field velocity map associated with the multi-directional bedform movement. Based on the calculated two-dimensional bedform migration velocity field, the bedload transport estimation is done using the Exner equation. A proof-of-concept experiment was performed to validate the AMV based bedload estimation in a laboratory flume at IIHR-Hydroscience & Engineering (IIHR). The bedform migration was analysed at three different flow discharges. Repeated bed geometry mapping, using a multiple transducer array (MTA), provided acoustic maps, which were post-processed with a particle image velocimetry (PIV) method. Bedload transport rates were calculated along longitudinal sections using the streamwise components of the bedform velocity vectors and the measured bedform heights. The bulk transport rates were compared with the results from concurrent direct physical samplings and acceptable agreement was found. As a first field implementation of the AMV an attempt was made to estimate bedload transport for a section of the Ohio river in the United States, where bed geometry maps, resulted by repeated multibeam echo sounder (MBES) surveys, served as input data. Cross-sectional distributions of bedload transport rates from the AMV based method were compared with the ones obtained from another non-intrusive technique (due to the lack of direct samplings), ISSDOTv2, developed by the US Army Corps of Engineers. The good agreement between the results from the two different methods is encouraging and suggests further field tests in varying hydro-morphological situations.

Dynamic spatial filtering using a digital micromirror device for high-speed optical diffraction tomography.

PubMed

Jin, Di; Zhou, Renjie; Yaqoob, Zahid; So, Peter T C

2018-01-08

Optical diffraction tomography (ODT) is an emerging microscopy technique for three-dimensional (3D) refractive index (RI) mapping of transparent specimens. Recently, the digital micromirror device (DMD) based scheme for angle-controlled plane wave illumination has been proposed to improve the imaging speed and stability of ODT. However, undesired diffraction noise always exists in the reported DMD-based illumination scheme, which leads to a limited contrast ratio of the measurement fringe and hence inaccurate RI mapping. Here we present a novel spatial filtering method, based on a second DMD, to dynamically remove the diffraction noise. The reported results illustrate significantly enhanced image quality of the obtained interferograms and the subsequently derived phase maps. And moreover, with this method, we demonstrate mapping of 3D RI distribution of polystyrene beads as well as biological cells with high accuracy. Importantly, with the proper hardware configuration, our method does not compromise the 3D imaging speed advantage promised by the DMD-based illumination scheme. Specifically, we have been able to successfully obtain interferograms at over 1 kHz speed, which is critical for potential high-throughput label-free 3D image cytometry applications.

Paper-Based and Computer-Based Concept Mappings: The Effects on Computer Achievement, Computer Anxiety and Computer Attitude

ERIC Educational Resources Information Center

Erdogan, Yavuz

2009-01-01

The purpose of this paper is to compare the effects of paper-based and computer-based concept mappings on computer hardware achievement, computer anxiety and computer attitude of the eight grade secondary school students. The students were randomly allocated to three groups and were given instruction on computer hardware. The teaching methods used…

Computer-based self-organized tectonic zoning: a tentative pattern recognition for Iran

NASA Astrophysics Data System (ADS)

Zamani, Ahmad; Hashemi, Naser

2004-08-01

Conventional methods of tectonic zoning are frequently characterized by two deficiencies. The first one is the large uncertainty involved in tectonic zoning based on non-quantitative and subjective analysis. Failure to interpret accurately a large amount of data "by eye" is the second. In order to alleviate each of these deficiencies, the multivariate statistical method of cluster analysis has been utilized to seek and separate zones with similar tectonic pattern and construct automated self-organized multivariate tectonic zoning maps. This analytical method of tectonic regionalization is particularly useful for showing trends in tectonic evolution of a region that could not be discovered by any other means. To illustrate, this method has been applied for producing a general-purpose numerical tectonic zoning map of Iran. While there are some similarities between the self-organized multivariate numerical maps and the conventional maps, the cluster solution maps reveal some remarkable features that cannot be observed on the current tectonic maps. The following specific examples need to be noted: (1) The much disputed extent and rigidity of the Lut Rigid Block, described as the microplate of east Iran, is clearly revealed on the self-organized numerical maps. (2) The cluster solution maps reveal a striking similarity between this microplate and the northern Central Iran—including the Great Kavir region. (3) Contrary to the conventional map, the cluster solution maps make a clear distinction between the East Iranian Ranges and the Makran Mountains. (4) Moreover, an interesting similarity between the Azarbaijan region in the northwest and the Makran Mountains in the southeast and between the Kopet Dagh Ranges in the northeast and the Zagros Folded Belt in the southwest of Iran are revealed in the clustering process. This new approach to tectonic zoning is a starting point and is expected to be improved and refined by collection of new data. The method is also a useful tool in studying neotectonics, seismotectonics, seismic zoning, and hazard estimation of the seismogenic regions.

Digital Mapping Techniques '09-Workshop Proceedings, Morgantown, West Virginia, May 10-13, 2009

USGS Publications Warehouse

Soller, David R.

2011-01-01

As in the previous years' meetings, the objective was to foster informal discussion and exchange of technical information, principally in order to develop more efficient methods for digital mapping, cartography, GIS analysis, and information management. At this meeting, oral and poster presentations and special discussion sessions emphasized (1) methods for creating and publishing map products (here, "publishing" includes Web-based release); (2) field data capture software and techniques, including the use of LiDAR; (3) digital cartographic techniques; (4) migration of digital maps into ArcGIS Geodatabase format; (5) analytical GIS techniques; and (6) continued development of the National Geologic Map Database.

Mapping protein-RNA interactions by RCAP, RNA-cross-linking and peptide fingerprinting.

PubMed

Vaughan, Robert C; Kao, C Cheng

2015-01-01

RNA nanotechnology often feature protein RNA complexes. The interaction between proteins and large RNAs are difficult to study using traditional structure-based methods like NMR or X-ray crystallography. RCAP, an approach that uses reversible-cross-linking affinity purification method coupled with mass spectrometry, has been developed to map regions within proteins that contact RNA. This chapter details how RCAP is applied to map protein-RNA contacts within virions.

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

2016-10-01

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

Apprehensions and Expectations of the Adoption of Systematically Planned, Outcome-Oriented Practice

ERIC Educational Resources Information Center

Savaya, Riki; Altschuler, Dorit; Melamed, Sharon

2013-01-01

Objectives: The study examined social workers' apprehensions and expectations of the impending adoption of systematically planned, empirically based, outcome-oriented practice (SEOP). Method: Employing a mixed methods longitudinal design, the study used concept mapping to identify and map workers' apprehensions and expectations and a self-reported…

Lithology and aggregate quality attributes for the digital geologic map of Colorado

USGS Publications Warehouse

Knepper, Daniel H.; Green, Gregory N.; Langer, William H.

1999-01-01

This geologic map was prepared as a part of a study of digital methods and techniques as applied to complex geologic maps. The geologic map was digitized from the original scribe sheets used to prepare the published Geologic Map of Colorado (Tweto 1979). Consequently the digital version is at 1:500,000 scale using the Lambert Conformal Conic map projection parameters of the state base map. Stable base contact prints of the scribe sheets were scanned on a Tektronix 4991 digital scanner. The scanner automatically converts the scanned image to an ASCII vector format. These vectors were transferred to a VAX minicomputer, where they were then loaded into ARC/INFO. Each vector and polygon was given attributes derived from the original 1979 geologic map.

Segmentation of singularity maps in the context of soil porosity

NASA Astrophysics Data System (ADS)

Martin-Sotoca, Juan J.; Saa-Requejo, Antonio; Grau, Juan; Tarquis, Ana M.

2016-04-01

Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, including concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012) and concentration-volume (C-V) model (Afzal et al., 2011) just to name a few examples. These methods are based on the singularity maps of a measure that at each point define areas with self-similar properties that are shown in power-law relationships in Concentration-Area plots (C-A method). The C-A method together with the singularity map ("Singularity-CA" method) define thresholds that can be applied to segment the map. Recently, the "Singularity-CA" method has been applied to binarize 2D grayscale Computed Tomography (CT) soil images (Martin-Sotoca et al, 2015). Unlike image segmentation based on global thresholding methods, the "Singularity-CA" method allows to quantify the local scaling property of the grayscale value map in the space domain and determinate the intensity of local singularities. It can be used as a high-pass-filter technique to enhance high frequency patterns usually regarded as anomalies when applied to maps. In this work we will put special attention on how to select the singularity thresholds in the C-A plot to segment the image. We will compare two methods: 1) cross point of linear regressions and 2) Wavelets Transform Modulus Maxima (WTMM) singularity function detection. REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Afzal, P., Fadakar Alghalandis, Y., Khakzad, A., Moarefvand, P. and Rashidnejad Omran, N. (2011) Delineation of mineralization zones in porphyry Cu deposits by fractal concentration-volume modeling. Journal of Geochemical Exploration, 108, 220-232. Martín-Sotoca, J. J., Tarquis, A. M., Saa-Requejo, A. and Grau, J. B. (2015). Pore detection in Computed Tomography (CT) soil images through singularity map analysis. Oral Presentation in PedoFract VIII Congress (June, La Coruña - Spain).

Voxel-based lesion mapping of meningioma: a comprehensive lesion location mapping of 260 lesions.

PubMed

Hirayama, Ryuichi; Kinoshita, Manabu; Arita, Hideyuki; Kagawa, Naoki; Kishima, Haruhiko; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki

2018-06-01

OBJECTIVE In the present study the authors aimed to determine preferred locations of meningiomas by avoiding descriptive analysis and instead using voxel-based lesion mapping and 3D image-rendering techniques. METHODS Magnetic resonance images obtained in 248 treatment-naïve meningioma patients with 260 lesions were retrospectively and consecutively collected. All images were registered to a 1-mm isotropic, high-resolution, T1-weighted brain atlas provided by the Montreal Neurological Institute (the MNI152), and a lesion frequency map was created, followed by 3D volume rendering to visualize the preferred locations of meningiomas in 3D. RESULTS The 3D lesion frequency map clearly showed that skull base structures such as parasellar, sphenoid wing, and petroclival regions were commonly affected by the tumor. The middle one-third of the superior sagittal sinus was most commonly affected in parasagittal tumors. Substantial lesion accumulation was observed around the leptomeninges covering the central sulcus and the sylvian fissure, with very few lesions observed at the frontal, parietal, and occipital convexities. CONCLUSIONS Using an objective visualization method, meningiomas were shown to be located around the middle third of the superior sagittal sinus, the perisylvian convexity, and the skull base. These observations, which are in line with previous descriptive analyses, justify further use of voxel-based lesion mapping techniques to help understand the biological nature of this disease.

Solving the Helmholtz equation in conformal mapped ARROW structures using homotopy perturbation method.

PubMed

Reck, Kasper; Thomsen, Erik V; Hansen, Ole

2011-01-31

The scalar wave equation, or Helmholtz equation, describes within a certain approximation the electromagnetic field distribution in a given system. In this paper we show how to solve the Helmholtz equation in complex geometries using conformal mapping and the homotopy perturbation method. The solution of the mapped Helmholtz equation is found by solving an infinite series of Poisson equations using two dimensional Fourier series. The solution is entirely based on analytical expressions and is not mesh dependent. The analytical results are compared to a numerical (finite element method) solution.

Topography- and nightlight-based national flood risk assessment in Canada

NASA Astrophysics Data System (ADS)

Elshorbagy, Amin; Bharath, Raja; Lakhanpal, Anchit; Ceola, Serena; Montanari, Alberto; Lindenschmidt, Karl-Erich

2017-04-01

In Canada, flood analysis and water resource management, in general, are tasks conducted at the provincial level; therefore, unified national-scale approaches to water-related problems are uncommon. In this study, a national-scale flood risk assessment approach is proposed and developed. The study focuses on using global and national datasets available with various resolutions to create flood risk maps. First, a flood hazard map of Canada is developed using topography-based parameters derived from digital elevation models, namely, elevation above nearest drainage (EAND) and distance from nearest drainage (DFND). This flood hazard mapping method is tested on a smaller area around the city of Calgary, Alberta, against a flood inundation map produced by the city using hydraulic modelling. Second, a flood exposure map of Canada is developed using a land-use map and the satellite-based nightlight luminosity data as two exposure parameters. Third, an economic flood risk map is produced, and subsequently overlaid with population density information to produce a socioeconomic flood risk map for Canada. All three maps of hazard, exposure, and risk are classified into five classes, ranging from very low to severe. A simple way to include flood protection measures in hazard estimation is also demonstrated using the example of the city of Winnipeg, Manitoba. This could be done for the entire country if information on flood protection across Canada were available. The evaluation of the flood hazard map shows that the topography-based method adopted in this study is both practical and reliable for large-scale analysis. Sensitivity analysis regarding the resolution of the digital elevation model is needed to identify the resolution that is fine enough for reliable hazard mapping, but coarse enough for computational tractability. The nightlight data are found to be useful for exposure and risk mapping in Canada; however, uncertainty analysis should be conducted to investigate the effect of the overglow phenomenon on flood risk mapping.

On testing for spatial correspondence between maps of human brain structure and function.

PubMed

Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D; Glahn, David C; Shinohara, Russell T; Vandekar, Simon N; Raznahan, Armin

2018-06-01

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data. Copyright © 2018 Elsevier Inc. All rights reserved.

A Novel Bit-level Image Encryption Method Based on Chaotic Map and Dynamic Grouping

NASA Astrophysics Data System (ADS)

Zhang, Guo-Ji; Shen, Yan

2012-10-01

In this paper, a novel bit-level image encryption method based on dynamic grouping is proposed. In the proposed method, the plain-image is divided into several groups randomly, then permutation-diffusion process on bit level is carried out. The keystream generated by logistic map is related to the plain-image, which confuses the relationship between the plain-image and the cipher-image. The computer simulation results of statistical analysis, information entropy analysis and sensitivity analysis show that the proposed encryption method is secure and reliable enough to be used for communication application.

Phenotypic mapping of metabolic profiles using self-organizing maps of high-dimensional mass spectrometry data.

PubMed

Goodwin, Cody R; Sherrod, Stacy D; Marasco, Christina C; Bachmann, Brian O; Schramm-Sapyta, Nicole; Wikswo, John P; McLean, John A

2014-07-01

A metabolic system is composed of inherently interconnected metabolic precursors, intermediates, and products. The analysis of untargeted metabolomics data has conventionally been performed through the use of comparative statistics or multivariate statistical analysis-based approaches; however, each falls short in representing the related nature of metabolic perturbations. Herein, we describe a complementary method for the analysis of large metabolite inventories using a data-driven approach based upon a self-organizing map algorithm. This workflow allows for the unsupervised clustering, and subsequent prioritization of, correlated features through Gestalt comparisons of metabolic heat maps. We describe this methodology in detail, including a comparison to conventional metabolomics approaches, and demonstrate the application of this method to the analysis of the metabolic repercussions of prolonged cocaine exposure in rat sera profiles.

Global localization of 3D point clouds in building outline maps of urban outdoor environments.

PubMed

Landsiedel, Christian; Wollherr, Dirk

2017-01-01

This paper presents a method to localize a robot in a global coordinate frame based on a sparse 2D map containing outlines of building and road network information and no location prior information. Its input is a single 3D laser scan of the surroundings of the robot. The approach extends the generic chamfer matching template matching technique from image processing by including visibility analysis in the cost function. Thus, the observed building planes are matched to the expected view of the corresponding map section instead of to the entire map, which makes a more accurate matching possible. Since this formulation operates on generic edge maps from visual sensors, the matching formulation can be expected to generalize to other input data, e.g., from monocular or stereo cameras. The method is evaluated on two large datasets collected in different real-world urban settings and compared to a baseline method from literature and to the standard chamfer matching approach, where it shows considerable performance benefits, as well as the feasibility of global localization based on sparse building outline data.

Single-shot real-time three dimensional measurement based on hue-height mapping

NASA Astrophysics Data System (ADS)

Wan, Yingying; Cao, Yiping; Chen, Cheng; Fu, Guangkai; Wang, Yapin; Li, Chengmeng

2018-06-01

A single-shot three-dimensional (3D) measurement based on hue-height mapping is proposed. The color fringe pattern is encoded by three sinusoidal fringes with the same frequency but different shifting phase into red (R), green (G) and blue (B) color channels, respectively. It is found that the hue of the captured color fringe pattern on the reference plane maintains monotonic in one period even it has the color crosstalk. Thus, unlike the traditional color phase shifting technique, the hue information is utilized to decode the color fringe pattern and map to the pixels of the fringe displacement in the proposed method. Because the monotonicity of the hue is limited within one period, displacement unwrapping is proposed to obtain the continuous displacement that is finally used to map to the height distribution. This method directly utilizes the hue under the effect of color crosstalk for mapping the height so that no color calibration is involved. Also, as it requires only single shot deformed color fringe pattern, this method can be applied into the real-time or dynamic 3D measurements.

Global Ionospheric Perturbations Monitored by the Worldwide GPS Network

NASA Technical Reports Server (NTRS)

Ho, C. M.; Mannucci, A. T.; Lindqwister, U. J.; Pi, X. Q.

1996-01-01

Based on the delays of these (Global Positioning System-GPS)signals, we have generated high resolution global ionospheric TEC (Total Electronic Changes) maps at 15-minute intervals. Using a differential method comparing storm time maps with quiet time maps, we find that the ionopshere during this time storm has increased significantly (the percentage change relative to quiet times is greater than 150 percent) ...These preliminary results (those mentioned above plus other in the paper)indicate that the differential maping method, which is based on GPS network measurements appears to be a useful tool for studying the global pattern and evolution process of the entire ionospheric perturbation.

The Salient Map Analysis for Research and Teaching (SMART) method: Powerful potential as a formative assessment in the biomedical sciences

NASA Astrophysics Data System (ADS)

Cathcart, Laura Anne

This dissertation consists of two studies: 1) development and characterization of the Salient Map Analysis for Research and Teaching (SMART) method as a formative assessment tool and 2) a case study exploring how a paramedic instructor's beliefs about learners affect her utilization of the SMART method and vice versa. The first study explored: How can a novel concept map analysis method be designed as an effective formative assessment tool? The SMART method improves upon existing concept map analysis methods because it does not require hierarchically structured concept maps and it preserves the rich content of the maps instead of reducing each map down to a numerical score. The SMART method is performed by comparing a set of students' maps to each other and to an instructor's map. The resulting composite map depicts, in percentages and highlighted colors, the similarities and differences between all of the maps. Some advantages of the SMART method as a formative assessment tool include its ability to highlight changes across time, problematic or alternative conceptions, and patterns of student responses at a glance. Study two explored: How do a paramedic instructor's beliefs about students and learning affect---and become affected by---her use of the SMART method as a formative assessment tool? This case study of Angel, an expert paramedic instructor, begins to address a gap in the emergency medical services (EMS) education literature, which contains almost no research on teachers or pedagogy. Angel and I worked together as participant co-researchers (Heron & Reason, 1997) exploring the affordances of the SMART method. This study, based on those interactions with Angel, involved using open coding to identify themes (Strauss & Corbin, 1998) from Angel's views of students and use of the SMART method. Angel views learning as a sense-making process. She has a multi-faceted view of her students as novices and invests substantial time trying to understand their concept maps. Not only do these beliefs affect her use of the SMART method; in addition, her beliefs are refined through the use of the SMART method.

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

PubMed

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Project Loon based augmentation for global ionospheric modeling over Southern Hemisphere

NASA Astrophysics Data System (ADS)

Wang, Cheng; Shi, Chuang; Zhang, Hongping

2017-04-01

Global ionospheric products of vertical total electron content (VTEC) derived from GNSS measurements may have low accuracy over oceans and southern latitudes where there are not rich observations. Project Loon provides a great opportunity to enhance the measurements over those areas. In this contribution, a simulation of Project Loon based augmentation for global ionospheric modeling is performed by using the international reference ionosphere (IRI) which could simulate VTEC measurements for the balloons. The performance of the enhanced method based on simulation of Project Loon is investigated by comparing with VTEC maps from Ionosphere Associate Analysis Centers (IAACs) as well as IGS final GIMs. The comparison indicates that there is a better consistency between the VTEC maps by the enhanced method and IGS final GIMs. Also, obvious improvements of RMS maps in GIMs for the middle latitudes and southern latitudes are enabled by the augmentation of Project Loon. Additionally, JASON data are used to validate the specific improvement of the VTEC maps. The results show that the performance of VTEC maps is improved slightly, especially in southern latitudes. It is possible that the VTEC maps could be improved significantly by using real GPS measurements from balloons of Project Loon in the near future.

Project Loon based augmentation for global ionospheric modeling over Southern Hemisphere.

PubMed

Wang, Cheng; Shi, Chuang; Zhang, Hongping

2017-04-06

Global ionospheric products of vertical total electron content (VTEC) derived from GNSS measurements may have low accuracy over oceans and southern latitudes where there are not rich observations. Project Loon provides a great opportunity to enhance the measurements over those areas. In this contribution, a simulation of Project Loon based augmentation for global ionospheric modeling is performed by using the international reference ionosphere (IRI) which could simulate VTEC measurements for the balloons. The performance of the enhanced method based on simulation of Project Loon is investigated by comparing with VTEC maps from Ionosphere Associate Analysis Centers (IAACs) as well as IGS final GIMs. The comparison indicates that there is a better consistency between the VTEC maps by the enhanced method and IGS final GIMs. Also, obvious improvements of RMS maps in GIMs for the middle latitudes and southern latitudes are enabled by the augmentation of Project Loon. Additionally, JASON data are used to validate the specific improvement of the VTEC maps. The results show that the performance of VTEC maps is improved slightly, especially in southern latitudes. It is possible that the VTEC maps could be improved significantly by using real GPS measurements from balloons of Project Loon in the near future.

Project Loon based augmentation for global ionospheric modeling over Southern Hemisphere

PubMed Central

Wang, Cheng; Shi, Chuang; Zhang, Hongping

2017-01-01

Global ionospheric products of vertical total electron content (VTEC) derived from GNSS measurements may have low accuracy over oceans and southern latitudes where there are not rich observations. Project Loon provides a great opportunity to enhance the measurements over those areas. In this contribution, a simulation of Project Loon based augmentation for global ionospheric modeling is performed by using the international reference ionosphere (IRI) which could simulate VTEC measurements for the balloons. The performance of the enhanced method based on simulation of Project Loon is investigated by comparing with VTEC maps from Ionosphere Associate Analysis Centers (IAACs) as well as IGS final GIMs. The comparison indicates that there is a better consistency between the VTEC maps by the enhanced method and IGS final GIMs. Also, obvious improvements of RMS maps in GIMs for the middle latitudes and southern latitudes are enabled by the augmentation of Project Loon. Additionally, JASON data are used to validate the specific improvement of the VTEC maps. The results show that the performance of VTEC maps is improved slightly, especially in southern latitudes. It is possible that the VTEC maps could be improved significantly by using real GPS measurements from balloons of Project Loon in the near future. PMID:28383058

Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map

PubMed Central

Kafieh, Raheleh; Rabbani, Hossein; Abramoff, Michael D.; Sonka, Milan

2013-01-01

Optical coherence tomography (OCT) is a powerful and noninvasive method for retinal imaging. In this paper, we introduce a fast segmentation method based on a new variant of spectral graph theory named diffusion maps. The research is performed on spectral domain (SD) OCT images depicting macular and optic nerve head appearance. The presented approach does not require edge-based image information in localizing most of boundaries and relies on regional image texture. Consequently, the proposed method demonstrates robustness in situations of low image contrast or poor layer-to-layer image gradients. Diffusion mapping applied to 2D and 3D OCT datasets is composed of two steps, one for partitioning the data into important and less important sections, and another one for localization of internal layers. In the first step, the pixels/voxels are grouped in rectangular/cubic sets to form a graph node. The weights of the graph are calculated based on geometric distances between pixels/voxels and differences of their mean intensity. The first diffusion map clusters the data into three parts, the second of which is the area of interest. The other two sections are eliminated from the remaining calculations. In the second step, the remaining area is subjected to another diffusion map assessment and the internal layers are localized based on their textural similarities. The proposed method was tested on 23 datasets from two patient groups (glaucoma and normals). The mean unsigned border positioning errors (mean ± SD) was 8.52 ± 3.13 and 7.56 ± 2.95 μm for the 2D and 3D methods, respectively. PMID:23837966

A Computer-Aided Diagnosis System for Measuring Carotid Artery Intima-Media Thickness (IMT) Using Quaternion Vectors.

PubMed

Kutbay, Uğurhan; Hardalaç, Fırat; Akbulut, Mehmet; Akaslan, Ünsal; Serhatlıoğlu, Selami

2016-06-01

This study aims investigating adjustable distant fuzzy c-means segmentation on carotid Doppler images, as well as quaternion-based convolution filters and saliency mapping procedures. We developed imaging software that will simplify the measurement of carotid artery intima-media thickness (IMT) on saliency mapping images. Additionally, specialists evaluated the present images and compared them with saliency mapping images. In the present research, we conducted imaging studies of 25 carotid Doppler images obtained by the Department of Cardiology at Fırat University. After implementing fuzzy c-means segmentation and quaternion-based convolution on all Doppler images, we obtained a model that can be analyzed easily by the doctors using a bottom-up saliency model. These methods were applied to 25 carotid Doppler images and then interpreted by specialists. In the present study, we used color-filtering methods to obtain carotid color images. Saliency mapping was performed on the obtained images, and the carotid artery IMT was detected and interpreted on the obtained images from both methods and the raw images are shown in Results. Also these results were investigated by using Mean Square Error (MSE) for the raw IMT images and the method which gives the best performance is the Quaternion Based Saliency Mapping (QBSM). 0,0014 and 0,000191 mm(2) MSEs were obtained for artery lumen diameters and plaque diameters in carotid arteries respectively. We found that computer-based image processing methods used on carotid Doppler could aid doctors' in their decision-making process. We developed software that could ease the process of measuring carotid IMT for cardiologists and help them to evaluate their findings.

Probabilistic drug connectivity mapping

PubMed Central

2014-01-01

Background The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines. This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug. We infer the relevance for retrieval by data-driven probabilistic modeling of the drug responses, resulting in probabilistic connectivity mapping, and further consider the available cell lines as different data sources. We use a special type of probabilistic model to separate what is shared and specific between the sources, in contrast to earlier connectivity mapping methods that have intentionally aggregated all available data, neglecting information about the differences between the cell lines. Results We show that the probabilistic multi-source connectivity mapping method is superior to alternatives in finding functionally and chemically similar drugs from the Connectivity Map data set. We also demonstrate that an extension of the method is capable of retrieving combinations of drugs that match different relevant parts of the query drug response profile. Conclusions The probabilistic modeling-based connectivity mapping method provides a promising alternative to earlier methods. Principled integration of data from different cell lines helps to identify relevant responses for specific drug repositioning applications. PMID:24742351

ERTS-1 imagery as an aid to the understanding of the regional setting of base metal deposits in the North West Cape Province, South Africa. [mineral exploration

NASA Technical Reports Server (NTRS)

Viljoen, R. P.

1974-01-01

A number of base metal finds have recently focussed attention on the North Western Cape Province of South Africa as an area of great potential mineral wealth. From the point of view of competitive mineral exploration it was essential that an insight into the regional geological controls of the base metal mineralization of the area be obtained as rapidly as possible. Conventional methods of producing a suitable regional geological map were considered to be too time-consuming and ERTS-1 imagery was consequently examined. This imagery has made a significant contribution in the compilation of a suitable map on which to base further mineral exploration programmes. The time involved in the compilation of maps of this nature was found to be only a fraction of the time necessary for the production of similar maps using other methods. ERTS imagery is therefore considered to be valuable in producing accurate regional maps in areas where little or no geological data are available, or in areas of poor access. Furthermore, these images have great potential for rapidly defining the regional extent of metallogenic provinces.

Cross-disciplinary Undergraduate Research: A Case Study in Digital Mapping, western Ireland

NASA Astrophysics Data System (ADS)

Whitmeyer, S. J.; de Paor, D. G.; Nicoletti, J.; Rivera, M.; Santangelo, B.; Daniels, J.

2008-12-01

As digital mapping technology becomes ever more advanced, field geologists spend a greater proportion of time learning digital methods relative to analyzing rocks and structures. To explore potential solutions to the time commitment implicit in learning digital field methods, we paired James Madison University (JMU) geology majors (experienced in traditional field techniques) with Worcester Polytechnic Institute (WPI) engineering students (experienced in computer applications) during a four week summer mapping project in Connemara, western Ireland. The project consisted of approximately equal parts digital field mapping (directed by the geology students), and lab-based map assembly, evaluation and formatting for virtual 3D terrains (directed by the engineering students). Students collected geologic data in the field using ruggedized handheld computers (Trimble GeoExplorer® series) with ArcPAD® software. Lab work initially focused on building geologic maps in ArcGIS® from the digital field data and then progressed to developing Google Earth-based visualizations of field data and maps. Challenges included exporting GIS data, such as locations and attributes, to KML tags for viewing in Google Earth, which we accomplished using a Linux bash script written by one of our engineers - a task outside the comfort zone of the average geology major. We also attempted to expand the scope of Google Earth by using DEMs of present-day geologically-induced landforms as representative models for paleo-geographic reconstructions of the western Ireland field area. As our integrated approach to digital field work progressed, we found that our digital field mapping produced data at a faster rate than could be effectively managed during our allotted time for lab work. This likely reflected the more developed methodology for digital field data collection, as compared with our lab-based attempts to develop new methods for 3D visualization of geologic maps. However, this experiment in cross-disciplinary undergraduate research was a big success, with an enthusiastic interchange of expertise between undergraduate geology and engineering students that produced new, cutting-edge methods for visualizing geologic data and maps.

A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications

PubMed Central

Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser

2017-01-01

In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service. PMID:28574471

A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications.

PubMed

Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser

2017-06-02

In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service.

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

PubMed Central

Feizizadeh, Bakhtiar; Blaschke, Thomas

2014-01-01

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation yielded poor results. PMID:27019609

Communicating Earth Observation (EO)-based landslide mapping capabilities to practitioners

NASA Astrophysics Data System (ADS)

Albrecht, Florian; Hölbling, Daniel; Eisank, Clemens; Weinke, Elisabeth; Vecchiotti, Filippo; Kociu, Arben

2016-04-01

Current remote sensing methods and the available Earth Observation (EO) data for landslide mapping already can support practitioners in their processes for gathering and for using landslide information. Information derived from EO data can support emergency services and authorities in rapid mapping after landslide-triggering events, in landslide monitoring and can serve as a relevant basis for hazard and risk mapping. These applications also concern owners, maintainers and insurers of infrastructure. Most often practitioners have a rough overview of the potential and limits of EO-based methods for landslide mapping. However, semi-automated image analysis techniques are still rarely used in practice. This limits the opportunity for user feedback, which would contribute to improve the methods for delivering fully adequate results in terms of accuracy, applicability and reliability. Moreover, practitioners miss information on the best way of integrating the methods in their daily processes. Practitioners require easy-to-grasp interfaces for testing new methods, which in turn would provide researchers with valuable user feedback. We introduce ongoing work towards an innovative web service which will allow for fast and efficient provision of EO-based landslide information products and that supports online processing. We investigate the applicability of various very high resolution (VHR), e.g. WorldView-2/3, Pleiades, and high resolution (HR), e.g. Landsat, Sentinel-2, optical EO data for semi-automated mapping based on object-based image analysis (OBIA). The methods, i.e. knowledge-based and statistical OBIA routines, are evaluated regarding their suitability for inclusion in a web service that is easy to use with the least amount of necessary training. The pre-operational web service will be implemented for selected study areas in the Alps (Austria, Italy), where weather-induced landslides have happened in the past. We will test the service on its usability together with potential users from the Geological Survey of Austria (GBA), various geological services of provinces of Austria, Germany and Italy, the Austrian Service for Torrent and Avalanche Control (WLV), the Austrian Federal Forestry Office (ÖBf), the Austrian Mountaineering Club (ÖAV) and infrastructure owners like the Austrian Road Maintenance Agency (ASFINAG). The results will show how EO-based landslide information products can be made accessible to responsible authorities in an innovative and easy manner and how new analysis methods can be promoted among a broad audience. Thus, the communication and knowledge exchange between researchers, the public, stakeholders and practitioners can be improved.

Recursive approach to the moment-based phase unwrapping method.

PubMed

Langley, Jason A; Brice, Robert G; Zhao, Qun

2010-06-01

The moment-based phase unwrapping algorithm approximates the phase map as a product of Gegenbauer polynomials, but the weight function for the Gegenbauer polynomials generates artificial singularities along the edge of the phase map. A method is presented to remove the singularities inherent to the moment-based phase unwrapping algorithm by approximating the phase map as a product of two one-dimensional Legendre polynomials and applying a recursive property of derivatives of Legendre polynomials. The proposed phase unwrapping algorithm is tested on simulated and experimental data sets. The results are then compared to those of PRELUDE 2D, a widely used phase unwrapping algorithm, and a Chebyshev-polynomial-based phase unwrapping algorithm. It was found that the proposed phase unwrapping algorithm provides results that are comparable to those obtained by using PRELUDE 2D and the Chebyshev phase unwrapping algorithm.

Direct and accelerated parameter mapping using the unscented Kalman filter.

PubMed

Zhao, Li; Feng, Xue; Meyer, Craig H

2016-05-01

To accelerate parameter mapping using a new paradigm that combines image reconstruction and model regression as a parameter state-tracking problem. In T2 mapping, the T2 map is first encoded in parameter space by multi-TE measurements and then encoded by Fourier transformation with readout/phase encoding gradients. Using a state transition function and a measurement function, the unscented Kalman filter can describe T2 mapping as a dynamic system and directly estimate the T2 map from the k-space data. The proposed method was validated with a numerical brain phantom and volunteer experiments with a multiple-contrast spin echo sequence. Its performance was compared with a conjugate-gradient nonlinear inversion method at undersampling factors of 2 to 8. An accelerated pulse sequence was developed based on this method to achieve prospective undersampling. Compared with the nonlinear inversion reconstruction, the proposed method had higher precision, improved structural similarity and reduced normalized root mean squared error, with acceleration factors up to 8 in numerical phantom and volunteer studies. This work describes a new perspective on parameter mapping by state tracking. The unscented Kalman filter provides a highly accelerated and efficient paradigm for T2 mapping. © 2015 Wiley Periodicals, Inc.

Object-based image analysis for cadastral mapping using satellite images

NASA Astrophysics Data System (ADS)

Kohli, D.; Crommelinck, S.; Bennett, R.; Koeva, M.; Lemmen, C.

2017-10-01

Cadasters together with land registry form a core ingredient of any land administration system. Cadastral maps comprise of the extent, ownership and value of land which are essential for recording and updating land records. Traditional methods for cadastral surveying and mapping often prove to be labor, cost and time intensive: alternative approaches are thus being researched for creating such maps. With the advent of very high resolution (VHR) imagery, satellite remote sensing offers a tremendous opportunity for (semi)-automation of cadastral boundaries detection. In this paper, we explore the potential of object-based image analysis (OBIA) approach for this purpose by applying two segmentation methods, i.e. MRS (multi-resolution segmentation) and ESP (estimation of scale parameter) to identify visible cadastral boundaries. Results show that a balance between high percentage of completeness and correctness is hard to achieve: a low error of commission often comes with a high error of omission. However, we conclude that the resulting segments/land use polygons can potentially be used as a base for further aggregation into tenure polygons using participatory mapping.

Exploration and implementation of ontology-based cultural relic knowledge map integration platform

NASA Astrophysics Data System (ADS)

Yang, Weiqiang; Dong, Yiqiang

2018-05-01

To help designers to better carry out creative design and improve the ability of searching traditional cultural relic information, the ontology-based knowledge map construction method was explored and an integrated platform for cultural relic knowledge map was developed. First of all, the construction method of the ontology of cultural relics was put forward, and the construction of the knowledge map of cultural relics was completed based on the constructed cultural relic otology. Then, a personalized semantic retrieval framework for creative design was proposed. Finally, the integrated platform of the knowledge map of cultural relics was designed and realized. The platform was divided into two parts. One was the foreground display system, which was used for designers to search and browse cultural relics. The other was the background management system, which was for cultural experts to manage cultural relics' knowledge. The research results showed that the platform designed could improve the retrieval ability of cultural relic information. To sum up, the platform can provide a good support for the designer's creative design.

Evaluation of a Moderate Resolution, Satellite-Based Impervious Surface Map Using an Independent, High-Resolution Validation Dataset

EPA Science Inventory

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data ...

Method for Stereo Mapping Based on Objectarx and Pipeline Technology

NASA Astrophysics Data System (ADS)

Liu, F.; Chen, T.; Lin, Z.; Yang, Y.

2012-07-01

Stereo mapping is an important way to acquire 4D production. Based on the development of the stereo mapping and the characteristics of ObjectARX and pipeline technology, a new stereo mapping scheme which can realize the interaction between the AutoCAD and digital photogrammetry system is offered by ObjectARX and pipeline technology. An experiment is made in order to make sure the feasibility with the example of the software MAP-AT (Modern Aerial Photogrammetry Automatic Triangulation), the experimental results show that this scheme is feasible and it has very important meaning for the realization of the acquisition and edit integration.

Mapping seabed sediments: Comparison of manual, geostatistical, object-based image analysis and machine learning approaches

NASA Astrophysics Data System (ADS)

Diesing, Markus; Green, Sophie L.; Stephens, David; Lark, R. Murray; Stewart, Heather A.; Dove, Dayton

2014-08-01

Marine spatial planning and conservation need underpinning with sufficiently detailed and accurate seabed substrate and habitat maps. Although multibeam echosounders enable us to map the seabed with high resolution and spatial accuracy, there is still a lack of fit-for-purpose seabed maps. This is due to the high costs involved in carrying out systematic seabed mapping programmes and the fact that the development of validated, repeatable, quantitative and objective methods of swath acoustic data interpretation is still in its infancy. We compared a wide spectrum of approaches including manual interpretation, geostatistics, object-based image analysis and machine-learning to gain further insights into the accuracy and comparability of acoustic data interpretation approaches based on multibeam echosounder data (bathymetry, backscatter and derivatives) and seabed samples with the aim to derive seabed substrate maps. Sample data were split into a training and validation data set to allow us to carry out an accuracy assessment. Overall thematic classification accuracy ranged from 67% to 76% and Cohen's kappa varied between 0.34 and 0.52. However, these differences were not statistically significant at the 5% level. Misclassifications were mainly associated with uncommon classes, which were rarely sampled. Map outputs were between 68% and 87% identical. To improve classification accuracy in seabed mapping, we suggest that more studies on the effects of factors affecting the classification performance as well as comparative studies testing the performance of different approaches need to be carried out with a view to developing guidelines for selecting an appropriate method for a given dataset. In the meantime, classification accuracy might be improved by combining different techniques to hybrid approaches and multi-method ensembles.

Mesh versus bathtub - effects of flood models on exposure analysis in Switzerland

NASA Astrophysics Data System (ADS)

Röthlisberger, Veronika; Zischg, Andreas; Keiler, Margreth

2016-04-01

In Switzerland, mainly two types of maps that indicate potential flood zones are available for flood exposure analyses: 1) Aquaprotect, a nationwide overview provided by the Federal Office for the Environment and 2) communal flood hazard maps available from the 26 cantons. The model used to produce Aquaprotect can be described as a bathtub approach or linear superposition method with three main parameters, namely the horizontal and vertical distance of a point to water features and the size of the river sub-basin. Whereas the determination of flood zones in Aquaprotect is based on a uniform, nationwide model, the communal flood hazard maps are less homogenous, as they have been elaborated either at communal or cantonal levels. Yet their basic content (i.e. indication of potential flood zones for three recurrence periods, with differentiation of at least three inundation depths) is described in national directives and the vast majority of communal flood hazard maps are based on 2D inundation simulations using meshes. Apart from the methodical differences between Aquaprotect and the communal flood hazard maps (and among different communal flood hazard maps), all of these maps include a layer with a similar recurrence period (i.e. Aquaprotect 250 years, flood hazard maps 300 years) beyond the intended protection level of installed structural systems. In our study, we compare the resulting exposure by overlaying the two types of flood maps with a complete, harmonized, and nationwide dataset of building polygons. We assess the different exposure at the national level, and also consider differences among the 26 cantons and the six biogeographically unique regions, respectively. It was observed that while the nationwide exposure rates for both types of flood maps are similar, the differences within certain cantons and biogeographical regions are remarkable. We conclude that flood maps based on bathtub models are appropriate for assessments at national levels, while maps based on 2D simulations are preferable at sub-national levels.

Reconnaissance geologic map of part of the San Isidro Quadrangle, Baja California Sur, Mexico

USGS Publications Warehouse

McLean, Hugh; Hausback, B.P.; Knapp, J.H.

1985-01-01

Mapping was done on aerial photographs and transferred, where possible, to 1:50,000-scale topographic base maps. Areas with roads were field checked; however, in the northeast part of the map area, lack of roads prevented field checks. Previous geologic surveys of parts of the map area were made by horseback in the early 1920's; reports were published by Darton (1921), Heim (1922), and Beal (1948). Subsurface data from petroleum exploration and a geologic map were incorporated in a regional study by Mina (1957). The first radiometric ages of rocks from the map area were published by Gastil and others (1979). Recently determined radiometric ages and chemical analysis of volcanic rocks were reported by Hausback (1984) and by Sawlan and Smith (1984). Our study incorporates geologic mapping with age control based on new radiometric ages as well as paleontology, Flows and tuffs were dated by the K-Ar method. Fossil ages are based on diatom and mollusk assemblages.

Reasoning Maps: A Generally Applicable Method for Characterizing Hypothesis-Testing Behaviour. Research Report

ERIC Educational Resources Information Center

White, Brian

2004-01-01

This paper presents a generally applicable method for characterizing subjects' hypothesis-testing behaviour based on a synthesis that extends on previous work. Beginning with a transcript of subjects' speech and videotape of their actions, a Reasoning Map is created that depicts the flow of their hypotheses, tests, predictions, results, and…

Performance analysis of mineral mapping method to delineate mineralization zones under tropical region

NASA Astrophysics Data System (ADS)

Wakila, M. H.; Saepuloh, A.; Heriawan, M. N.; Susanto, A.

2016-09-01

Geothermal explorations and productions are currently being intensively conducted at certain areas in Indonesia such as Wayang Windu Geothermal Field (WWGF) in West Java, Indonesia. The WWGF is located at wide area covering about 40 km2. An accurate method to map the distribution of heterogeneity minerals is necessary for wide areas such as WWGF. Mineral mapping is an important method in geothermal explorations to determine the distribution of minerals which indicate the surface manifestations of geothermal system. This study is aimed to determine the most precise and accurate methods for minerals mapping at geothermal field. Field measurements were performed to assess the accuracy of three proposed methods: 1) Minimum Noise Fraction (MNF), utilizing the linear transformation method to eliminate the correlation among the spectra bands and to reduce the noise in the data, 2) Pixel Purity Index (PPI), a designed method to find the most extreme spectrum pixels and their characteristics due to end-members mixing, 3) Spectral Angle Mapper (SAM), an image classification technique by measuring the spectral similarity between an unknown object with spectral reference in n- dimension. The output of those methods were mineral distribution occurrence. The performance of each mapping method was analyzed based on the ground truth data. Among the three proposed method, the SAM classification method is the most appropriate and accurate for mineral mapping related to spatial distribution of alteration minerals.

Novel method for measuring a dense 3D strain map of robotic flapping wings

NASA Astrophysics Data System (ADS)

Li, Beiwen; Zhang, Song

2018-04-01

Measuring dense 3D strain maps of the inextensible membranous flapping wings of robots is of vital importance to the field of bio-inspired engineering. Conventional high-speed 3D videography methods typically reconstruct the wing geometries through measuring sparse points with fiducial markers, and thus cannot obtain the full-field mechanics of the wings in detail. In this research, we propose a novel system to measure a dense strain map of inextensible membranous flapping wings by developing a superfast 3D imaging system and a computational framework for strain analysis. Specifically, first we developed a 5000 Hz 3D imaging system based on the digital fringe projection technique using the defocused binary patterns to precisely measure the dynamic 3D geometries of rapidly flapping wings. Then, we developed a geometry-based algorithm to perform point tracking on the precisely measured 3D surface data. Finally, we developed a dense strain computational method using the Kirchhoff-Love shell theory. Experiments demonstrate that our method can effectively perform point tracking and measure a highly dense strain map of the wings without many fiducial markers.

An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph

NASA Astrophysics Data System (ADS)

Zagouras, Athanassios; Argiriou, Athanassios A.; Flocas, Helena A.; Economou, George; Fotopoulos, Spiros

2012-11-01

Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850 hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters.

Accurate and reproducible functional maps in 127 human cell types via 2D genome segmentation

PubMed Central

Hardison, Ross C.

2017-01-01

Abstract The Roadmap Epigenomics Consortium has published whole-genome functional annotation maps in 127 human cell types by integrating data from studies of multiple epigenetic marks. These maps have been widely used for studying gene regulation in cell type-specific contexts and predicting the functional impact of DNA mutations on disease. Here, we present a new map of functional elements produced by applying a method called IDEAS on the same data. The method has several unique advantages and outperforms existing methods, including that used by the Roadmap Epigenomics Consortium. Using five categories of independent experimental datasets, we compared the IDEAS and Roadmap Epigenomics maps. While the overall concordance between the two maps is high, the maps differ substantially in the prediction details and in their consistency of annotation of a given genomic position across cell types. The annotation from IDEAS is uniformly more accurate than the Roadmap Epigenomics annotation and the improvement is substantial based on several criteria. We further introduce a pipeline that improves the reproducibility of functional annotation maps. Thus, we provide a high-quality map of candidate functional regions across 127 human cell types and compare the quality of different annotation methods in order to facilitate biomedical research in epigenomics. PMID:28973456

Investigation of contrast-enhanced subtracted breast CT images with MAP-EM based on projection-based weighting imaging.

PubMed

Zhou, Zhengdong; Guan, Shaolin; Xin, Runchao; Li, Jianbo

2018-06-01

Contrast-enhanced subtracted breast computer tomography (CESBCT) images acquired using energy-resolved photon counting detector can be helpful to enhance the visibility of breast tumors. In such technology, one challenge is the limited number of photons in each energy bin, thereby possibly leading to high noise in separate images from each energy bin, the projection-based weighted image, and the subtracted image. In conventional low-dose CT imaging, iterative image reconstruction provides a superior signal-to-noise compared with the filtered back projection (FBP) algorithm. In this paper, maximum a posteriori expectation maximization (MAP-EM) based on projection-based weighting imaging for reconstruction of CESBCT images acquired using an energy-resolving photon counting detector is proposed, and its performance was investigated in terms of contrast-to-noise ratio (CNR). The simulation study shows that MAP-EM based on projection-based weighting imaging can improve the CNR in CESBCT images by 117.7%-121.2% compared with FBP based on projection-based weighting imaging method. When compared with the energy-integrating imaging that uses the MAP-EM algorithm, projection-based weighting imaging that uses the MAP-EM algorithm can improve the CNR of CESBCT images by 10.5%-13.3%. In conclusion, MAP-EM based on projection-based weighting imaging shows significant improvement the CNR of the CESBCT image compared with FBP based on projection-based weighting imaging, and MAP-EM based on projection-based weighting imaging outperforms MAP-EM based on energy-integrating imaging for CESBCT imaging.

The development of an adolescent smoking cessation intervention--an Intervention Mapping approach to planning.

PubMed

Dalum, Peter; Schaalma, Herman; Kok, Gerjo

2012-02-01

The objective of this project was to develop a theory- and evidence-based adolescent smoking cessation intervention using both new and existing materials. We used the Intervention Mapping framework for planning health promotion programmes. Based on a needs assessment, we identified important and changeable determinants of cessation behaviour, specified change objectives for the intervention programme, selected theoretical change methods for accomplishing intervention objectives and finally operationalized change methods into practical intervention strategies. We found that guided practice, modelling, self-monitoring, coping planning, consciousness raising, dramatic relief and decisional balance were suitable methods for adolescent smoking cessation. We selected behavioural journalism, guided practice and Motivational Interviewing as strategies in our intervention. Intervention Mapping helped us to develop as systematic adolescent smoking cessation intervention with a clear link between behavioural goals, theoretical methods, practical strategies and materials and with a strong focus on implementation and recruitment. This paper does not present evaluation data.

Personal sleep pattern visualization using sequence-based kernel self-organizing map on sound data.

PubMed

Wu, Hongle; Kato, Takafumi; Yamada, Tomomi; Numao, Masayuki; Fukui, Ken-Ichi

2017-07-01

We propose a method to discover sleep patterns via clustering of sound events recorded during sleep. The proposed method extends the conventional self-organizing map algorithm by kernelization and sequence-based technologies to obtain a fine-grained map that visualizes the distribution and changes of sleep-related events. We introduced features widely applied in sound processing and popular kernel functions to the proposed method to evaluate and compare performance. The proposed method provides a new aspect of sleep monitoring because the results demonstrate that sound events can be directly correlated to an individual's sleep patterns. In addition, by visualizing the transition of cluster dynamics, sleep-related sound events were found to relate to the various stages of sleep. Therefore, these results empirically warrant future study into the assessment of personal sleep quality using sound data. Copyright © 2017 Elsevier B.V. All rights reserved.

A natural-color mapping for single-band night-time image based on FPGA

NASA Astrophysics Data System (ADS)

Wang, Yilun; Qian, Yunsheng

2018-01-01

A natural-color mapping for single-band night-time image method based on FPGA can transmit the color of the reference image to single-band night-time image, which is consistent with human visual habits and can help observers identify the target. This paper introduces the processing of the natural-color mapping algorithm based on FPGA. Firstly, the image can be transformed based on histogram equalization, and the intensity features and standard deviation features of reference image are stored in SRAM. Then, the real-time digital images' intensity features and standard deviation features are calculated by FPGA. At last, FPGA completes the color mapping through matching pixels between images using the features in luminance channel.

Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

NASA Astrophysics Data System (ADS)

Rokni Deilmai, B.; Ahmad, B. Bin; Zabihi, H.

2014-06-01

Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Yuyu; Smith, Steven J.; Elvidge, Christopher

Accurate information of urban areas at regional and global scales is important for both the science and policy-making communities. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime stable light data (NTL) provide a potential way to map urban area and its dynamics economically and timely. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the DMSP/OLS NTL data in five major steps, including data preprocessing, urban cluster segmentation, logistic model development, threshold estimation, and urban extent delineation. Different from previous fixed threshold method with over- and under-estimation issues, in ourmore » method the optimal thresholds are estimated based on cluster size and overall nightlight magnitude in the cluster, and they vary with clusters. Two large countries of United States and China with different urbanization patterns were selected to map urban extents using the proposed method. The result indicates that the urbanized area occupies about 2% of total land area in the US ranging from lower than 0.5% to higher than 10% at the state level, and less than 1% in China, ranging from lower than 0.1% to about 5% at the province level with some municipalities as high as 10%. The derived thresholds and urban extents were evaluated using high-resolution land cover data at the cluster and regional levels. It was found that our method can map urban area in both countries efficiently and accurately. Compared to previous threshold techniques, our method reduces the over- and under-estimation issues, when mapping urban extent over a large area. More important, our method shows its potential to map global urban extents and temporal dynamics using the DMSP/OLS NTL data in a timely, cost-effective way.« less

Reliability of confidence intervals calculated by bootstrap and classical methods using the FIA 1-ha plot design

Treesearch

H. T. Schreuder; M. S. Williams

2000-01-01

In simulation sampling from forest populations using sample sizes of 20, 40, and 60 plots respectively, confidence intervals based on the bootstrap (accelerated, percentile, and t-distribution based) were calculated and compared with those based on the classical t confidence intervals for mapped populations and subdomains within those populations. A 68.1 ha mapped...

A Ranking Analysis/An Interlinking Approach of New Triangular Fuzzy Cognitive Maps and Combined Effective Time Dependent Matrix

NASA Astrophysics Data System (ADS)

Adiga, Shreemathi; Saraswathi, A.; Praveen Prakash, A.

2018-04-01

This paper aims an interlinking approach of new Triangular Fuzzy Cognitive Maps (TrFCM) and Combined Effective Time Dependent (CETD) matrix to find the ranking of the problems of Transgenders. Section one begins with an introduction that briefly describes the scope of Triangular Fuzzy Cognitive Maps (TrFCM) and CETD Matrix. Section two provides the process of causes of problems faced by Transgenders using Fuzzy Triangular Fuzzy Cognitive Maps (TrFCM) method and performs the calculations using the collected data among the Transgender. In Section 3, the reasons for the main causes for the problems of the Transgenders. Section 4 describes the Charles Spearmans coefficients of rank correlation method by interlinking of Triangular Fuzzy Cognitive Maps (TrFCM) Method and CETD Matrix. Section 5 shows the results based on our study.

Space moving target detection using time domain feature

NASA Astrophysics Data System (ADS)

Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu

2018-01-01

The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.

Digital Mapping Techniques '11–12 workshop proceedings

USGS Publications Warehouse

Soller, David R.

2014-01-01

At these meetings, oral and poster presentations and special discussion sessions emphasized: (1) methods for creating and publishing map products (here, "publishing" includes Web-based release); (2) field data capture software and techniques, including the use of LiDAR; (3) digital cartographic techniques; (4) migration of digital maps into ArcGIS Geodatabase formats; (5) analytical GIS techniques; and (6) continued development of the National Geologic Map Database.

Optically Mapping Multiple Bacterial Genomes Simultaneously in a Single Run

DTIC Science & Technology

2011-11-21

sequence orientation. We have demonstrated mapping of Shigella dysenteriae and Escherichia coli simultaneously, despite their very close phylogenetic...relationship ( Shigella and Escherichia coli are generally considered to be within a single species, but are segregated at the genus level for historical...reasons [4]); two clones of Shigella would likely not map together successfully using the mixed DNA method. Similarly, based on reference maps being

Quantitative Methods Based on Twisted Nematic Liquid Crystals for Mapping Surfaces Patterned with Bio/Chemical Functionality Relevant to Bioanalytical Assays

PubMed Central

Lowe, Aaron M.; Bertics, Paul J.; Abbott, Nicholas L.

2009-01-01

We report methods for the acquisition and analysis of optical images formed by thin films of twisted nematic liquid crystals (LCs) placed into contact with surfaces patterned with bio/chemical functionality relevant to surface-based assays. The methods are simple to implement and are shown to provide easily interpreted maps of chemical transformations on surfaces that are widely exploited in the preparation of analytic devices. The methods involve acquisition of multiple images of the LC as a function of the orientation of a polarizer; data analysis condenses the information present in the stack of images into a spatial map of the twist angle of the LC on the analytic surface. The potential utility of the methods is illustrated by mapping (i) the displacement of a monolayer formed from one alkanethiol on a gold film by a second thiol in solution, (ii) coadsorption of mixtures of amine-terminated and ethyleneglycol-terminated alkanethiols on gold films, which leads to a type of mixed monolayer that is widely exploited for immobilization of proteins on analytic surfaces, and (iii) patterns of antibodies printed onto surfaces. These results show that maps of the twist angle of the LC constructed from families of optical images can be used to reveal surface features that are not apparent in a single image of the LC film. Furthermore, the twist angles of the LC can be used to quantify the energy of interaction of the LC with the surface with a spatial resolution of <10 µm. When combined, the results described in this paper suggest non-destructive methods to monitor and validate chemical transformations on surfaces of the type that are routinely employed in the preparation of surface-based analytic technologies. PMID:18355089

Participatory three dimensional mapping for the preparation of landslide disaster risk reduction program

NASA Astrophysics Data System (ADS)

Kusratmoko, Eko; Wibowo, Adi; Cholid, Sofyan; Pin, Tjiong Giok

2017-07-01

This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng' village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of the village. Based on the results P3DM, the ability of the communities in understanding the village environment spatially well-tested and honed, so as to facilitate the preparation of the CBDRR programs. Furthermore, the P3DM method can be applied to another disaster areas, due to it becomes a medium of effective dialogue between all levels of involved communities.

Application of terrestrial laser scanning to the development and updating of the base map

NASA Astrophysics Data System (ADS)

Klapa, Przemysław; Mitka, Bartosz

2017-06-01

The base map provides basic information about land to individuals, companies, developers, design engineers, organizations, and government agencies. Its contents include spatial location data for control network points, buildings, land lots, infrastructure facilities, and topographic features. As the primary map of the country, it must be developed in accordance with specific laws and regulations and be continuously updated. The base map is a data source used for the development and updating of derivative maps and other large scale cartographic materials such as thematic or topographic maps. Thanks to the advancement of science and technology, the quality of land surveys carried out by means of terrestrial laser scanning (TLS) matches that of traditional surveying methods in many respects. This paper discusses the potential application of output data from laser scanners (point clouds) to the development and updating of cartographic materials, taking Poland's base map as an example. A few research sites were chosen to present the method and the process of conducting a TLS land survey: a fragment of a residential area, a street, the surroundings of buildings, and an undeveloped area. The entire map that was drawn as a result of the survey was checked by comparing it to a map obtained from PODGiK (pol. Powiatowy Ośrodek Dokumentacji Geodezyjnej i Kartograficznej - Regional Centre for Geodetic and Cartographic Records) and by conducting a field inspection. An accuracy and quality analysis of the conducted fieldwork and deskwork yielded very good results, which provide solid grounds for predicating that cartographic materials based on a TLS point cloud are a reliable source of information about land. The contents of the map that had been created with the use of the obtained point cloud were very accurately located in space (x, y, z). The conducted accuracy analysis and the inspection of the performed works showed that high quality is characteristic of TLS surveys. The accuracy of determining the location of the various map contents has been estimated at 0.02-0.03 m. The map was developed in conformity with the applicable laws and regulations as well as with best practice requirements.

A Concept Mapping Approach to Guide and Understand Dissemination and Implementation

PubMed Central

Green, Amy E.; Fettes, Danielle L.; Aarons, Gregory A.

2013-01-01

Many efforts to implement evidence-based programs do not reach their full potential or fail due to the variety of challenges inherent in dissemination and implementation. This article describes the use of concept mapping—a mixed method strategy—to study implementation of behavioral health innovations and evidence-based practice (EBP). The application of concept mapping to implementation research represents a practical and concise way to identify and quantify factors affecting implementation, develop conceptual models of implementation, target areas to address as part of implementation readiness and active implementation, and foster communication among stakeholders. Concept mapping is described and a case example is provided to illustrate its use in an implementation study. Implications for the use of concept mapping methods in both research and applied settings towards the dissemination and implementation of behavioral health services are discussed. PMID:22892987

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

New segmentation-based tone mapping algorithm for high dynamic range image

NASA Astrophysics Data System (ADS)

Duan, Weiwei; Guo, Huinan; Zhou, Zuofeng; Huang, Huimin; Cao, Jianzhong

2017-07-01

The traditional tone mapping algorithm for the display of high dynamic range (HDR) image has the drawback of losing the impression of brightness, contrast and color information. To overcome this phenomenon, we propose a new tone mapping algorithm based on dividing the image into different exposure regions in this paper. Firstly, the over-exposure region is determined using the Local Binary Pattern information of HDR image. Then, based on the peak and average gray of the histogram, the under-exposure and normal-exposure region of HDR image are selected separately. Finally, the different exposure regions are mapped by differentiated tone mapping methods to get the final result. The experiment results show that the proposed algorithm achieve the better performance both in visual quality and objective contrast criterion than other algorithms.

Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited.

PubMed

Thomas, Cibu; Ye, Frank Q; Irfanoglu, M Okan; Modi, Pooja; Saleem, Kadharbatcha S; Leopold, David A; Pierpaoli, Carlo

2014-11-18

Tractography based on diffusion-weighted MRI (DWI) is widely used for mapping the structural connections of the human brain. Its accuracy is known to be limited by technical factors affecting in vivo data acquisition, such as noise, artifacts, and data undersampling resulting from scan time constraints. It generally is assumed that improvements in data quality and implementation of sophisticated tractography methods will lead to increasingly accurate maps of human anatomical connections. However, assessing the anatomical accuracy of DWI tractography is difficult because of the lack of independent knowledge of the true anatomical connections in humans. Here we investigate the future prospects of DWI-based connectional imaging by applying advanced tractography methods to an ex vivo DWI dataset of the macaque brain. The results of different tractography methods were compared with maps of known axonal projections from previous tracer studies in the macaque. Despite the exceptional quality of the DWI data, none of the methods demonstrated high anatomical accuracy. The methods that showed the highest sensitivity showed the lowest specificity, and vice versa. Additionally, anatomical accuracy was highly dependent upon parameters of the tractography algorithm, with different optimal values for mapping different pathways. These results suggest that there is an inherent limitation in determining long-range anatomical projections based on voxel-averaged estimates of local fiber orientation obtained from DWI data that is unlikely to be overcome by improvements in data acquisition and analysis alone.

Gradient-based Electrical Properties Tomography (gEPT): a Robust Method for Mapping Electrical Properties of Biological Tissues In Vivo Using Magnetic Resonance Imaging

PubMed Central

Liu, Jiaen; Zhang, Xiaotong; Schmitter, Sebastian; Van de Moortele, Pierre-Francois; He, Bin

2014-01-01

Purpose To develop high-resolution electrical properties tomography (EPT) methods and investigate a gradient-based EPT (gEPT) approach which aims to reconstruct the electrical properties (EP), including conductivity and permittivity, of an imaged sample from experimentally measured B1 maps with improved boundary reconstruction and robustness against measurement noise. Theory and Methods Using a multi-channel transmit/receive stripline head coil, with acquired B1 maps for each coil element, by assuming negligible Bz component compared to transverse B1 components, a theory describing the relationship between B1 field, EP value and their spatial gradient has been proposed. The final EP images were obtained through spatial integration over the reconstructed EP gradient. Numerical simulation, physical phantom and in vivo human experiments at 7 T have been conducted to evaluate the performance of the proposed methods. Results Reconstruction results were compared with target EP values in both simulations and phantom experiments. Human experimental results were compared with EP values in literature. Satisfactory agreement was observed with improved boundary reconstruction. Importantly, the proposed gEPT method proved to be more robust against noise when compared to previously described non-gradient-based EPT approaches. Conclusion The proposed gEPT approach holds promises to improve EP mapping quality by recovering the boundary information and enhancing robustness against noise. PMID:25213371

The Systematic Development of an Internet-Based Smoking Cessation Intervention for Adults.

PubMed

Dalum, Peter; Brandt, Caroline Lyng; Skov-Ettrup, Lise; Tolstrup, Janne; Kok, Gerjo

2016-07-01

Objectives The objective of this project was to determine whether intervention mapping is a suitable strategy for developing an Internet- and text message-based smoking cessation intervention. Method We used the Intervention Mapping framework for planning health promotion programs. After a needs assessment, we identified important changeable determinants of cessation behavior, specified objectives for the intervention, selected theoretical methods for meeting our objectives, and operationalized change methods into practical intervention strategies. Results We found that "social cognitive theory," the "transtheoretical model/stages of change," "self-regulation theory," and "appreciative inquiry" were relevant theories for smoking cessation interventions. From these theories, we selected modeling/behavioral journalism, feedback, planning coping responses/if-then statements, gain frame/positive imaging, consciousness-raising, helping relationships, stimulus control, and goal-setting as suitable methods for an Internet- and text-based adult smoking cessation program. Furthermore, we identified computer tailoring as a useful strategy for adapting the intervention to individual users. Conclusion The Intervention Mapping method, with a clear link between behavioral goals, theoretical methods, and practical strategies and materials, proved useful for systematic development of a digital smoking cessation intervention for adults. © 2016 Society for Public Health Education.

PCA-based groupwise image registration for quantitative MRI.

PubMed

Huizinga, W; Poot, D H J; Guyader, J-M; Klaassen, R; Coolen, B F; van Kranenburg, M; van Geuns, R J M; Uitterdijk, A; Polfliet, M; Vandemeulebroucke, J; Leemans, A; Niessen, W J; Klein, S

2016-04-01

Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as competing methods, while avoiding the need to choose a reference image. It is also shown that the results of the conventional pairwise approach do depend on the choice of this reference image. We therefore conclude that our groupwise registration method with a similarity measure based on PCA is the preferred technique for compensating misalignments in qMRI. Copyright © 2015 Elsevier B.V. All rights reserved.

Urban local climate zone mapping and apply in urban environment study

NASA Astrophysics Data System (ADS)

He, Shan; Zhang, Yunwei; Zhang, Jili

2018-02-01

The city’s local climate zone (LCZ) was considered to be a powerful tool for urban climate mapping. But for cities in different countries and regions, the LCZ division methods and results were different, thus targeted researches should be performed. In the current work, a LCZ mapping method was proposed, which is convenient in operation and city planning oriented. In this proposed method, the local climate zoning types were adjusted firstly, according to the characteristics of Chinese city, that more tall buildings and high density. Then the classification method proposed by WUDAPT based on remote sensing data was performed on Xi’an city, as an example, for LCZ mapping. Combined with the city road network, a reasonable expression of the dividing results was provided, to adapt to the characteristics in city planning that land parcels are usually recognized as the basic unit. The proposed method was validated against the actual land use and construction data that surveyed in Xi’an, with results indicating the feasibility of the proposed method for urban LCZ mapping in China.

Finger Vein Recognition Based on a Personalized Best Bit Map

PubMed Central

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Finger vein recognition based on a personalized best bit map.

PubMed

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps.

PubMed

Singharoy, Abhishek; Teo, Ivan; McGreevy, Ryan; Stone, John E; Zhao, Jianhua; Schulten, Klaus

2016-07-07

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

Visual Fast Mapping in School-Aged Children with Specific Language Impairment

ERIC Educational Resources Information Center

Alt, Mary

2013-01-01

Purpose: To determine whether children with specific language impairment (SLI) demonstrate impaired visual fast mapping skills compared with unimpaired peers and to test components of visual working memory that may contribute to a visual working memory deficit. Methods: Fifty children (25 SLI) played 2 computer-based visual fast mapping games…

Community Mapping in Action: Uncovering Resources and Assets for Young Children and Their Families

ERIC Educational Resources Information Center

Ordonez-Jasis, Rosario; Myck-Wayne, Janice

2012-01-01

Community mapping is a promising practice that can assist early intervention/early childhood special education (EI/ECSE) professionals uncover the depth and diversity of community needs, resources, and learning opportunities, in the neighborhoods surrounding their schools. Community mapping is an inquiry-based method that situates learning in the…

Perceptual Mapping Software as a Tool for Facilitating School-Based Consultation

ERIC Educational Resources Information Center

Rush, S. Craig; Kalish, Ashley; Wheeler, Joanna

2013-01-01

Perceptual mapping is a systematic method for collecting, analyzing, and presenting group perceptions that is potentially useful in consultation. With input and feedback from a consultee group, perceptual mapping allows the consultant to capture the group's collective perceptions and display them as an organized image that may foster…

Development of a Mapped Diabetes Community Program Guide for a Safety Net Population

PubMed Central

Zallman, Leah; Ibekwe, Lynn; Thompson, Jennifer W.; Ross-Degnan, Dennis; Oken, Emily

2014-01-01

Purpose Enhancing linkages between patients and community programs is increasingly recognized as a method for improving physical activity, nutrition and weight management. Although interactive mapped community program guides may be beneficial, there remains a dearth of articles that describe the processes and practicalities of creating such guides. This article describes the development of an interactive, web-based mapped community program guide at a safety net institution and the lessons learned from that process. Conclusions This project demonstrated the feasibility of creating two maps – a program guide and a population health map. It also revealed some key challenges and lessons for future work in this area, particularly within safety-net institutions. Our work underscores the need for developing partnerships outside of the health care system and the importance of employing community-based participatory methods. In addition to facilitating improvements in individual wellness, mapping community programs also has the potential to improve population health management by healthcare delivery systems such as hospitals, health centers, or public health systems, including city and state departments of health. PMID:24752180

Compensated geothermal gradient: new map of old data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibrahim, M.W.

1986-05-01

Bottom-hole temperature measurement is one of the oldest forms of downhole information acquired by the oil industry. Old and new geothermal maps that are based on these measurements have invariably been drawn with an assumed constant or average ground surface temperature over the mapped areas. However, near ground-surface equilibrium temperature is a variable rather than a constant over any region; therefore, old and current geothermal gradient mapping methods give a false impression of the true thermal level of subsurface strata, and may lead to erroneous results of temperature-based calculations, such as the TTI. In this paper, a geothermal mapping methodmore » is presented in which extrapolated surface temperature is coupled with the corresponding geothermal gradient over the mapped area. The method was tested on areas in the Middle East and Africa. Results indicate that it is especially effective in delineating loci of vertical geothermal heat flux carried upwards by ascending subsurface fluids; such areas are preferential sites for hydrocarbon entrapment, especially in young sedimentary basins where migration is still in progress.« less

The Use of Intervention Mapping to Develop a Tailored Web-Based Intervention, Condom-HIM

PubMed Central

2017-01-01

Background Many HIV (human immunodeficiency virus) prevention interventions are currently being implemented and evaluated, with little information published on their development. A framework highlighting the method of development of an intervention can be used by others wanting to replicate interventions or develop similar interventions to suit other contexts and settings. It provides researchers with a comprehensive development process of the intervention. Objective The objective of this paper was to describe how a systematic approach, intervention mapping, was used to develop a tailored Web-based intervention to increase condom use among HIV-positive men who have sex with men. Methods The intervention was developed in consultation with a multidisciplinary team composed of academic researchers, community members, Web designers, and the target population. Intervention mapping involved a systematic process of 6 steps: (1) needs assessment; (2) identification of proximal intervention objectives; (3) selection of theory-based intervention methods and practical strategies; (4) development of intervention components and materials; (5) adoption, implementation, and maintenance; and (6) evaluation planning. Results The application of intervention mapping resulted in the development of a tailored Web-based intervention for HIV-positive men who have sex with men, called Condom-HIM. Conclusions Using intervention mapping as a systematic process to develop interventions is a feasible approach that specifically integrates the use of theory and empirical findings. Outlining the process used to develop a particular intervention provides clarification on the conceptual use of experimental interventions in addition to potentially identifying reasons for intervention failures. PMID:28428162

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

NASA Astrophysics Data System (ADS)

Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter

2017-05-01

The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.

Calibration and accuracy analysis of a focused plenoptic camera

NASA Astrophysics Data System (ADS)

Zeller, N.; Quint, F.; Stilla, U.

2014-08-01

In this article we introduce new methods for the calibration of depth images from focused plenoptic cameras and validate the results. We start with a brief description of the concept of a focused plenoptic camera and how from the recorded raw image a depth map can be estimated. For this camera, an analytical expression of the depth accuracy is derived for the first time. In the main part of the paper, methods to calibrate a focused plenoptic camera are developed and evaluated. The optical imaging process is calibrated by using a method which is already known from the calibration of traditional cameras. For the calibration of the depth map two new model based methods, which make use of the projection concept of the camera are developed. These new methods are compared to a common curve fitting approach, which is based on Taylor-series-approximation. Both model based methods show significant advantages compared to the curve fitting method. They need less reference points for calibration than the curve fitting method and moreover, supply a function which is valid in excess of the range of calibration. In addition the depth map accuracy of the plenoptic camera was experimentally investigated for different focal lengths of the main lens and is compared to the analytical evaluation.

Automated segmentation of dental CBCT image with prior-guided sequential random forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Li; Gao, Yaozong; Shi, Feng

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT. Methods: In this paper, the authors present a new automatic segmentation method to address these problems. Specifically, the authors first employ a majority voting method to estimatemore » the initial segmentation probability maps of both mandible and maxilla based on multiple aligned expert-segmented CBCT images. These probability maps provide an important prior guidance for CBCT segmentation. The authors then extract both the appearance features from CBCTs and the context features from the initial probability maps to train the first-layer of random forest classifier that can select discriminative features for segmentation. Based on the first-layer of trained classifier, the probability maps are updated, which will be employed to further train the next layer of random forest classifier. By iteratively training the subsequent random forest classifier using both the original CBCT features and the updated segmentation probability maps, a sequence of classifiers can be derived for accurate segmentation of CBCT images. Results: Segmentation results on CBCTs of 30 subjects were both quantitatively and qualitatively validated based on manually labeled ground truth. The average Dice ratios of mandible and maxilla by the authors’ method were 0.94 and 0.91, respectively, which are significantly better than the state-of-the-art method based on sparse representation (p-value < 0.001). Conclusions: The authors have developed and validated a novel fully automated method for CBCT segmentation.« less

MS lesion segmentation using a multi-channel patch-based approach with spatial consistency

NASA Astrophysics Data System (ADS)

Mechrez, Roey; Goldberger, Jacob; Greenspan, Hayit

2015-03-01

This paper presents an automatic method for segmentation of Multiple Sclerosis (MS) in Magnetic Resonance Images (MRI) of the brain. The approach is based on similarities between multi-channel patches (T1, T2 and FLAIR). An MS lesion patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching labels for these k patches are then combined to produce an initial segmentation map for the test case. Finally a novel iterative patch-based label refinement process based on the initial segmentation map is performed to ensure spatial consistency of the detected lesions. A leave-one-out evaluation is done for each testing image in the MS lesion segmentation challenge of MICCAI 2008. Results are shown to compete with the state-of-the-art methods on the MICCAI 2008 challenge.

National-scale crop type mapping and area estimation using multi-resolution remote sensing and field survey

NASA Astrophysics Data System (ADS)

Song, X. P.; Potapov, P.; Adusei, B.; King, L.; Khan, A.; Krylov, A.; Di Bella, C. M.; Pickens, A. H.; Stehman, S. V.; Hansen, M.

2016-12-01

Reliable and timely information on agricultural production is essential for ensuring world food security. Freely available medium-resolution satellite data (e.g. Landsat, Sentinel) offer the possibility of improved global agriculture monitoring. Here we develop and test a method for estimating in-season crop acreage using a probability sample of field visits and producing wall-to-wall crop type maps at national scales. The method is first illustrated for soybean cultivated area in the US for 2015. A stratified, two-stage cluster sampling design was used to collect field data to estimate national soybean area. The field-based estimate employed historical soybean extent maps from the U.S. Department of Agriculture (USDA) Cropland Data Layer to delineate and stratify U.S. soybean growing regions. The estimated 2015 U.S. soybean cultivated area based on the field sample was 341,000 km2 with a standard error of 23,000 km2. This result is 1.0% lower than USDA's 2015 June survey estimate and 1.9% higher than USDA's 2016 January estimate. Our area estimate was derived in early September, about 2 months ahead of harvest. To map soybean cover, the Landsat image archive for the year 2015 growing season was processed using an active learning approach. Overall accuracy of the soybean map was 84%. The field-based sample estimated area was then used to calibrate the map such that the soybean acreage of the map derived through pixel counting matched the sample-based area estimate. The strength of the sample-based area estimation lies in the stratified design that takes advantage of the spatially explicit cropland layers to construct the strata. The success of the mapping was built upon an automated system which transforms Landsat images into standardized time-series metrics. The developed method produces reliable and timely information on soybean area in a cost-effective way and could be implemented in an operational mode. The approach has also been applied for other crops in other regions, such as winter wheat in Pakistan, soybean in Argentina and soybean in the entire South America. Similar levels of accuracy and timeliness were achieved as in the US.

Conformal mapping for the Helmholtz equation: acoustic wave scattering by a two dimensional inclusion with irregular shape in an ideal fluid.

PubMed

Liu, Gang; Jayathilake, Pahala G; Khoo, Boo Cheong; Han, Feng; Liu, Dian Kui

2012-02-01

The complex variables method with mapping function was extended to solve the linear acoustic wave scattering by an inclusion with sharp/smooth corners in an infinite ideal fluid domain. The improved solutions of Helmholtz equation, shown as Bessel function with mapping function as the argument and fractional order Bessel function, were analytically obtained. Based on the mapping function, the initial geometry as well as the original physical vector can be transformed into the corresponding expressions inside the mapping plane. As all the physical vectors are calculated in the mapping plane (η,η), this method can lead to potential vast savings of computational resources and memory. In this work, the results are validated against several published works in the literature. The different geometries of the inclusion with sharp corners based on the proposed mapping functions for irregular polygons are studied and discussed. The findings show that the variation of angles and frequencies of the incident waves have significant influence on the bistatic scattering pattern and the far-field form factor for the pressure in the fluid. © 2012 Acoustical Society of America

Neural network-based multiple robot simultaneous localization and mapping.

PubMed

Saeedi, Sajad; Paull, Liam; Trentini, Michael; Li, Howard

2011-12-01

In this paper, a decentralized platform for simultaneous localization and mapping (SLAM) with multiple robots is developed. Each robot performs single robot view-based SLAM using an extended Kalman filter to fuse data from two encoders and a laser ranger. To extend this approach to multiple robot SLAM, a novel occupancy grid map fusion algorithm is proposed. Map fusion is achieved through a multistep process that includes image preprocessing, map learning (clustering) using neural networks, relative orientation extraction using norm histogram cross correlation and a Radon transform, relative translation extraction using matching norm vectors, and then verification of the results. The proposed map learning method is a process based on the self-organizing map. In the learning phase, the obstacles of the map are learned by clustering the occupied cells of the map into clusters. The learning is an unsupervised process which can be done on the fly without any need to have output training patterns. The clusters represent the spatial form of the map and make further analyses of the map easier and faster. Also, clusters can be interpreted as features extracted from the occupancy grid map so the map fusion problem becomes a task of matching features. Results of the experiments from tests performed on a real environment with multiple robots prove the effectiveness of the proposed solution.

The multiscale coarse-graining method. XI. Accurate interactions based on the centers of charge of coarse-grained sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Zhen; Voth, Gregory A., E-mail: gavoth@uchicago.edu

It is essential to be able to systematically construct coarse-grained (CG) models that can efficiently and accurately reproduce key properties of higher-resolution models such as all-atom. To fulfill this goal, a mapping operator is needed to transform the higher-resolution configuration to a CG configuration. Certain mapping operators, however, may lose information related to the underlying electrostatic properties. In this paper, a new mapping operator based on the centers of charge of CG sites is proposed to address this issue. Four example systems are chosen to demonstrate this concept. Within the multiscale coarse-graining framework, CG models that use this mapping operatormore » are found to better reproduce the structural correlations of atomistic models. The present work also demonstrates the flexibility of the mapping operator and the robustness of the force matching method. For instance, important functional groups can be isolated and emphasized in the CG model.« less

Using gradient-based ray and candidate shadow maps for environmental illumination distribution estimation

NASA Astrophysics Data System (ADS)

Eem, Changkyoung; Kim, Iksu; Hong, Hyunki

2015-07-01

A method to estimate the environmental illumination distribution of a scene with gradient-based ray and candidate shadow maps is presented. In the shadow segmentation stage, we apply a Canny edge detector to the shadowed image by using a three-dimensional (3-D) augmented reality (AR) marker of a known size and shape. Then the hierarchical tree of the connected edge components representing the topological relation is constructed, and the connected components are merged, taking their hierarchical structures into consideration. A gradient-based ray that is perpendicular to the gradient of the edge pixel in the shadow image can be used to extract the shadow regions. In the light source detection stage, shadow regions with both a 3-D AR marker and the light sources are partitioned into candidate shadow maps. A simple logic operation between each candidate shadow map and the segmented shadow is used to efficiently compute the area ratio between them. The proposed method successively extracts the main light sources according to their relative contributions on the segmented shadows. The proposed method can reduce unwanted effects due to the sampling positions in the shadow region and the threshold values in the shadow edge detection.

Automating the selection of standard parallels for conic map projections

NASA Astrophysics Data System (ADS)

Šavriǒ, Bojan; Jenny, Bernhard

2016-05-01

Conic map projections are appropriate for mapping regions at medium and large scales with east-west extents at intermediate latitudes. Conic projections are appropriate for these cases because they show the mapped area with less distortion than other projections. In order to minimize the distortion of the mapped area, the two standard parallels of conic projections need to be selected carefully. Rules of thumb exist for placing the standard parallels based on the width-to-height ratio of the map. These rules of thumb are simple to apply, but do not result in maps with minimum distortion. There also exist more sophisticated methods that determine standard parallels such that distortion in the mapped area is minimized. These methods are computationally expensive and cannot be used for real-time web mapping and GIS applications where the projection is adjusted automatically to the displayed area. This article presents a polynomial model that quickly provides the standard parallels for the three most common conic map projections: the Albers equal-area, the Lambert conformal, and the equidistant conic projection. The model defines the standard parallels with polynomial expressions based on the spatial extent of the mapped area. The spatial extent is defined by the length of the mapped central meridian segment, the central latitude of the displayed area, and the width-to-height ratio of the map. The polynomial model was derived from 3825 maps-each with a different spatial extent and computationally determined standard parallels that minimize the mean scale distortion index. The resulting model is computationally simple and can be used for the automatic selection of the standard parallels of conic map projections in GIS software and web mapping applications.

Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure.

PubMed

Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu; Scheuermann, Richard H

2016-01-01

Flow cytometry (FCM) is a fluorescence-based single-cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap-FR, a novel method for cell population mapping across FCM samples. FlowMap-FR is based on the Friedman-Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap-FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap-FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap-FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap-FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap-FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback-Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL-distance in distinguishing equivalent from nonequivalent cell populations. FlowMap-FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F-measure of 0.88 was obtained, indicating high precision and recall of the FR-based population matching results. FlowMap-FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © The Authors. Published by Wiley Periodicals, Inc. on behalf of ISAC.

Eddy current loss analysis of open-slot fault-tolerant permanent-magnet machines based on conformal mapping method

NASA Astrophysics Data System (ADS)

Ji, Jinghua; Luo, Jianhua; Lei, Qian; Bian, Fangfang

2017-05-01

This paper proposed an analytical method, based on conformal mapping (CM) method, for the accurate evaluation of magnetic field and eddy current (EC) loss in fault-tolerant permanent-magnet (FTPM) machines. The aim of modulation function, applied in CM method, is to change the open-slot structure into fully closed-slot structure, whose air-gap flux density is easy to calculate analytically. Therefore, with the help of Matlab Schwarz-Christoffel (SC) Toolbox, both the magnetic flux density and EC density of FTPM machine are obtained accurately. Finally, time-stepped transient finite-element method (FEM) is used to verify the theoretical analysis, showing that the proposed method is able to predict the magnetic flux density and EC loss precisely.

Group-regularized individual prediction: theory and application to pain.

PubMed

Lindquist, Martin A; Krishnan, Anjali; López-Solà, Marina; Jepma, Marieke; Woo, Choong-Wan; Koban, Leonie; Roy, Mathieu; Atlas, Lauren Y; Schmidt, Liane; Chang, Luke J; Reynolds Losin, Elizabeth A; Eisenbarth, Hedwig; Ashar, Yoni K; Delk, Elizabeth; Wager, Tor D

2017-01-15

Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or 'decode' psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction-based on population-level predictive maps from prior groups-and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N=180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker-in this case, the Neurologic Pain Signature (NPS)-improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study. Copyright © 2015 Elsevier Inc. All rights reserved.

Infrared small target enhancement: grey level mapping based on improved sigmoid transformation and saliency histogram

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian

2018-06-01

Infrared (IR) small target enhancement plays a significant role in modern infrared search and track (IRST) systems and is the basic technique of target detection and tracking. In this paper, a coarse-to-fine grey level mapping method using improved sigmoid transformation and saliency histogram is designed to enhance IR small targets under different backgrounds. For the stage of rough enhancement, the intensity histogram is modified via an improved sigmoid function so as to narrow the regular intensity range of background as much as possible. For the part of further enhancement, a linear transformation is accomplished based on a saliency histogram constructed by averaging the cumulative saliency values provided by a saliency map. Compared with other typical methods, the presented method can achieve both better visual performances and quantitative evaluations.

Method for determining waveguide temperature for acoustic transceiver used in a gas turbine engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeSilva, Upul P.; Claussen, Heiko; Ragunathan, Karthik

A method for determining waveguide temperature for at least one waveguide of a transceiver utilized for generating a temperature map. The transceiver generates an acoustic signal that travels through a measurement space in a hot gas flow path defined by a wall such as in a combustor. The method includes calculating a total time of flight for the acoustic signal and subtracting a waveguide travel time from the total time of flight to obtain a measurement space travel time. A temperature map is calculated based on the measurement space travel time. An estimated wall temperature is obtained from the temperaturemore » map. An estimated waveguide temperature is then calculated based on the estimated wall temperature wherein the estimated waveguide temperature is determined without the use of a temperature sensing device.« less

Single-step scanner-based digital image correlation (SB-DIC) method for large deformation mapping in rubber

NASA Astrophysics Data System (ADS)

Goh, C. P.; Ismail, H.; Yen, K. S.; Ratnam, M. M.

2017-01-01

The incremental digital image correlation (DIC) method has been applied in the past to determine strain in large deformation materials like rubber. This method is, however, prone to cumulative errors since the total displacement is determined by combining the displacements in numerous stages of the deformation. In this work, a method of mapping large strains in rubber using DIC in a single-step without the need for a series of deformation images is proposed. The reference subsets were deformed using deformation factors obtained from the fitted mean stress-axial stretch ratio curve obtained experimentally and the theoretical Poisson function. The deformed reference subsets were then correlated with the deformed image after loading. The recently developed scanner-based digital image correlation (SB-DIC) method was applied on dumbbell rubber specimens to obtain the in-plane displacement fields up to 350% axial strain. Comparison of the mean axial strains determined from the single-step SB-DIC method with those from the incremental SB-DIC method showed an average difference of 4.7%. Two rectangular rubber specimens containing circular and square holes were deformed and analysed using the proposed method. The resultant strain maps from the single-step SB-DIC method were compared with the results of finite element modeling (FEM). The comparison shows that the proposed single-step SB-DIC method can be used to map the strain distribution accurately in large deformation materials like rubber at much shorter time compared to the incremental DIC method.

A method for mapping topsoil field-saturated hydraulic conductivity in the Cévennes-Vivarais region using infiltration tests conducted with different techniques

NASA Astrophysics Data System (ADS)

Braud, Isabelle; Desprats, Jean-François; Ayral, Pierre-Alain; Bouvier, Christophe; Vandervaere, Jean-Pierre

2017-04-01

Topsoil field-saturated hydraulic conductivity, Kfs, is a parameter that controls the partition of rainfall between infiltration and runoff. It is a key parameter in most distributed hydrological models. However, there is a mismatch between the scale of local in situ measurements and the scale at which the parameter is required in models. Therefore it is necessary to design methods to regionally map this parameter at the model scale. The paper propose a method for mapping Kfs in the Cévennes-Vivarais region, south-east France, using more easily available GIS data: geology and land cover. The mapping is based on a data set gathering infiltration tests performed in the area or close to it for more than ten years. The data set is composed of infiltration tests performed using various techniques: Guelph permeameter, double ring and single ring infiltration tests, infiltrometers with multiple suctions. The different methods lead to different orders of magnitude for Kfs rendering the pooling of all the data challenging. Therefore, a method is first proposed to pool the data from the different infiltration methods, leading to a homogenized set of Kfs, based on an equivalent double ring/tension disk infiltration value. Statistical tests showed significant differences in distributions among different geologies and land covers. Thus those variables were retained as proxy for mapping Kfs at the regional scale. This map was compared to a map based on the Rawls and Brakensiek (RB) pedo-transfer function (Manus et al., 2009, Vannier et al., 2016), showing very different patterns between both maps. In addition, RB values did not fit observed values at the plot scale, highlighting that soil texture only is not a good predictor of Kfs. References Manus, C., Anquetin, S., Braud, I., Vandervaere, J.P., Viallet, P., Creutin, J.D., Gaume, E., 2009. A modelling approach to assess the hydrological response of small Mediterranean catchments to the variability of soil characteristics in a context of extreme events. Hydrology and Earth System Sciences, 13: 79-87. Vannier, O., Anquetin, S., Braud, I., 2016. Investigating the role of geology in the hydrological response of Mediterranean catchments prone to flash-floods: regional modelling study and process understanding. Journal of Hydrology, 541 Part A, 158-172.

A High-throughput AFLP-based Method for Constructing Integrated Genetic and Physical Maps: Progress Toward a Sorghum Genome Map

PubMed Central

Klein, Patricia E.; Klein, Robert R.; Cartinhour, Samuel W.; Ulanch, Paul E.; Dong, Jianmin; Obert, Jacque A.; Morishige, Daryl T.; Schlueter, Shannon D.; Childs, Kevin L.; Ale, Melissa; Mullet, John E.

2000-01-01

Sorghum is an important target for plant genomic mapping because of its adaptation to harsh environments, diverse germplasm collection, and value for comparing the genomes of grass species such as corn and rice. The construction of an integrated genetic and physical map of the sorghum genome (750 Mbp) is a primary goal of our sorghum genome project. To help accomplish this task, we have developed a new high-throughput PCR-based method for building BAC contigs and locating BAC clones on the sorghum genetic map. This task involved pooling 24,576 sorghum BAC clones (∼4× genome equivalents) in six different matrices to create 184 pools of BAC DNA. DNA fragments from each pool were amplified using amplified fragment length polymorphism (AFLP) technology, resolved on a LI-COR dual-dye DNA sequencing system, and analyzed using Bionumerics software. On average, each set of AFLP primers amplified 28 single-copy DNA markers that were useful for identifying overlapping BAC clones. Data from 32 different AFLP primer combinations identified ∼2400 BACs and ordered ∼700 BAC contigs. Analysis of a sorghum RIL mapping population using the same primer pairs located ∼200 of the BAC contigs on the sorghum genetic map. Restriction endonuclease fingerprinting of the entire collection of sorghum BAC clones was applied to test and extend the contigs constructed using this PCR-based methodology. Analysis of the fingerprint data allowed for the identification of 3366 contigs each containing an average of 5 BACs. BACs in ∼65% of the contigs aligned by AFLP analysis had sufficient overlap to be confirmed by DNA fingerprint analysis. In addition, 30% of the overlapping BACs aligned by AFLP analysis provided information for merging contigs and singletons that could not be joined using fingerprint data alone. Thus, the combination of fingerprinting and AFLP-based contig assembly and mapping provides a reliable, high-throughput method for building an integrated genetic and physical map of the sorghum genome. [The sequence data described in this paper have been submitted to the GenBank data library under accession no. AF218263.] PMID:10854411

In Preparation of the Nationwide Dissemination of the School-Based Obesity Prevention Program DOiT: Stepwise Development Applying the Intervention Mapping Protocol

ERIC Educational Resources Information Center

van Nassau, Femke; Singh, Amika S.; van Mechelen, Willem; Brug, Johannes; Chin A. Paw, Mai J. M.

2014-01-01

Background: The school-based Dutch Obesity Intervention in Teenagers (DOiT) program is an evidence-based obesity prevention program. In preparation for dissemination throughout the Netherlands, this study aimed to adapt the initial program and to develop an implementation strategy and materials. Methods: We revisited the Intervention Mapping (IM)…

A Electronic Map Data Model Based on PDF

NASA Astrophysics Data System (ADS)

Zhou, Xiaodong; Yang, Chuncheng; Meng, Nina; Peng, Peng

2018-05-01

In this paper, we proposed the PDFEMAP (PDF electronic map) that is a kind of new electronic map products aiming at the current situation and demand of the use of electronic map products. Firstly gives the definition and characteristics of PDFEMAP, followed by a detailed description of the data model and method for generating PDFEMAP, and finally expounds application modes of the PDFEMAP which feasibility and effectiveness are verified.

Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methods

PubMed Central

2014-01-01

Automatic reconstruction of metabolic pathways for an organism from genomics and transcriptomics data has been a challenging and important problem in bioinformatics. Traditionally, known reference pathways can be mapped into an organism-specific ones based on its genome annotation and protein homology. However, this simple knowledge-based mapping method might produce incomplete pathways and generally cannot predict unknown new relations and reactions. In contrast, ab initio metabolic network construction methods can predict novel reactions and interactions, but its accuracy tends to be low leading to a lot of false positives. Here we combine existing pathway knowledge and a new ab initio Bayesian probabilistic graphical model together in a novel fashion to improve automatic reconstruction of metabolic networks. Specifically, we built a knowledge database containing known, individual gene / protein interactions and metabolic reactions extracted from existing reference pathways. Known reactions and interactions were then used as constraints for Bayesian network learning methods to predict metabolic pathways. Using individual reactions and interactions extracted from different pathways of many organisms to guide pathway construction is new and improves both the coverage and accuracy of metabolic pathway construction. We applied this probabilistic knowledge-based approach to construct the metabolic networks from yeast gene expression data and compared its results with 62 known metabolic networks in the KEGG database. The experiment showed that the method improved the coverage of metabolic network construction over the traditional reference pathway mapping method and was more accurate than pure ab initio methods. PMID:25374614

Concept mapping as a promising method to bring practice into science.

PubMed

van Bon-Martens, M J H; van de Goor, L A M; Holsappel, J C; Kuunders, T J M; Jacobs-van der Bruggen, M A M; te Brake, J H M; van Oers, J A M

2014-06-01

Concept mapping is a method for developing a conceptual framework of a complex topic for use as a guide to evaluation or planning. In concept mapping, thoughts and ideas are represented in the form of a picture or map, the content of which is determined by a group of stakeholders. This study aimed to explore the suitability of this method as a tool to integrate practical knowledge with scientific knowledge in order to improve theory development as a sound basis for practical decision-making. Following a short introduction to the method of concept mapping, five Dutch studies, serving different purposes and fields in public health, will be described. The aim of these studies was: to construct a theoretical framework for good regional public health reporting; to design an implementation strategy for a guideline for integral local health policy; to guide the evaluation of a local integral approach of overweight and obesity in youth; to guide the construction of a questionnaire to measure the quality of postdisaster psychosocial care; and to conceptualize an integral base for formulation of ambitions and targets for the new youth healthcare programme of a regional health service. The studies showed that concept mapping is a way to integrate practical and scientific knowledge with careful selection of participants that represent the different perspectives. Theory development can be improved through concept mapping; not by formulating new theories, but by highlighting the key issues and defining perceived relationships between topics. In four of the five studies, the resulting concept map was received as a sound basis for practical decision-making. Concept mapping is a valuable method for evidence-based public health policy, and a powerful instrument for facilitating dialogue, coherence and collaboration between researchers, practitioners, policy makers and the public. Development of public health theory was realized by a step-by-step approach, considering both scientific and practical knowledge. However, the external validity of the concept maps in place and time is of importance. Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera.

PubMed

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-08-31

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments.

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

PubMed Central

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-01-01

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments. PMID:26404284

A batch sliding window method for local singularity mapping and its application for geochemical anomaly identification

NASA Astrophysics Data System (ADS)

Xiao, Fan; Chen, Zhijun; Chen, Jianguo; Zhou, Yongzhang

2016-05-01

In this study, a novel batch sliding window (BSW) based singularity mapping approach was proposed. Compared to the traditional sliding window (SW) technique with disadvantages of the empirical predetermination of a fixed maximum window size and outliers sensitivity of least-squares (LS) linear regression method, the BSW based singularity mapping approach can automatically determine the optimal size of the largest window for each estimated position, and utilizes robust linear regression (RLR) which is insensitive to outlier values. In the case study, tin geochemical data in Gejiu, Yunnan, have been processed by BSW based singularity mapping approach. The results show that the BSW approach can improve the accuracy of the calculation of singularity exponent values due to the determination of the optimal maximum window size. The utilization of RLR method in the BSW approach can smoothen the distribution of singularity index values with few or even without much high fluctuate values looking like noise points that usually make a singularity map much roughly and discontinuously. Furthermore, the student's t-statistic diagram indicates a strong spatial correlation between high geochemical anomaly and known tin polymetallic deposits. The target areas within high tin geochemical anomaly could probably have much higher potential for the exploration of new tin polymetallic deposits than other areas, particularly for the areas that show strong tin geochemical anomalies whereas no tin polymetallic deposits have been found in them.

Mapping the Indonesian territory, based on pollution, social demography and geographical data, using self organizing feature map

NASA Astrophysics Data System (ADS)

Hernawati, Kuswari; Insani, Nur; Bambang S. H., M.; Nur Hadi, W.; Sahid

2017-08-01

This research aims to mapping the 33 (thirty-three) provinces in Indonesia, based on the data on air, water and soil pollution, as well as social demography and geography data, into a clustered model. The method used in this study was unsupervised method that combines the basic concept of Kohonen or Self-Organizing Feature Maps (SOFM). The method is done by providing the design parameters for the model based on data related directly/ indirectly to pollution, which are the demographic and social data, pollution levels of air, water and soil, as well as the geographical situation of each province. The parameters used consists of 19 features/characteristics, including the human development index, the number of vehicles, the availability of the plant's water absorption and flood prevention, as well as geographic and demographic situation. The data used were secondary data from the Central Statistics Agency (BPS), Indonesia. The data are mapped into SOFM from a high-dimensional vector space into two-dimensional vector space according to the closeness of location in term of Euclidean distance. The resulting outputs are represented in clustered grouping. Thirty-three provinces are grouped into five clusters, where each cluster has different features/characteristics and level of pollution. The result can used to help the efforts on prevention and resolution of pollution problems on each cluster in an effective and efficient way.

Integration of data-driven and physically-based methods to assess shallow landslides susceptibility

NASA Astrophysics Data System (ADS)

Lajas, Sara; Oliveira, Sérgio C.; Zêzere, José Luis

2016-04-01

Approaches used to assess shallow landslides susceptibility at the basin scale are conceptually different depending on the use of statistic or deterministic methods. The data-driven methods are sustained in the assumption that the same causes are likely to produce the same effects and for that reason a present/past landslide inventory and a dataset of factors assumed as predisposing factors are crucial for the landslide susceptibility assessment. The physically-based methods are based on a system controlled by physical laws and soil mechanics, where the forces which tend to promote movement are compared with forces that tend to promote resistance to movement. In this case, the evaluation of susceptibility is supported by the calculation of the Factor of safety (FoS), and dependent of the availability of detailed data related with the slope geometry and hydrological and geotechnical properties of the soils and rocks. Within this framework, this work aims to test two hypothesis: (i) although conceptually distinct and based on contrasting procedures, statistic and deterministic methods generate similar shallow landslides susceptibility results regarding the predictive capacity and spatial agreement; and (ii) the integration of the shallow landslides susceptibility maps obtained with data-driven and physically-based methods, for the same study area, generate a more reliable susceptibility model for shallow landslides occurrence. To evaluate these two hypotheses, we select the Information Value data-driven method and the physically-based Infinite Slope model to evaluate shallow landslides in the study area of Monfalim and Louriceira basins (13.9 km2), which is located in the north of Lisbon region (Portugal). The landslide inventory is composed by 111 shallow landslides and was divide in two independent groups based on temporal criteria (age ≤ 1983 and age > 1983): (i) the modelling group (51 cases) was used to define the weights for each predisposing factor (lithology, land use, slope, aspect, curvature, topographic position index and the slope over area ratio) with the Information Value method and was used also to calibrate the strength parameters (cohesion and friction angle) of the different lithological units considered in the Infinity Slope model; and (ii) the validation group (60 cases) was used to independent validate and define the predictive capacity of the shallow landslides susceptibility maps produced with the Information Value method and the Infinite Slope method. The comparison of both landslide susceptibility maps was supported by: (i) the computation of the Receiver Operator Characteristic (ROC) curves; (ii) the calculation of the Area Under the Curve (AUC); and (iii) the evaluation of the spatial agreement between the landslide susceptibility classes. Finally, the susceptibility maps produced with the Information Value and the Infinite Slope methods are integrated into a single landslide susceptibility map based on a set of integration rules define by cross-validation of the susceptibility classes of both maps and analysis of the corresponding contingency table. This work was supported by the FCT - Portuguese Foundation for Science and Technology and is within the framework of the FORLAND Project. Sérgio Oliveira was funded by a postdoctoral grant (SFRH/BPD/85827/2012) from the Portuguese Foundation for Science and Technology (FCT).

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

A statistical approach for validating eSOTER and digital soil maps in front of traditional soil maps

NASA Astrophysics Data System (ADS)

Bock, Michael; Baritz, Rainer; Köthe, Rüdiger; Melms, Stephan; Günther, Susann

2015-04-01

During the European research project eSOTER, three different Digital Soil Maps (DSM) were developed for the pilot area Chemnitz 1:250,000 (FP7 eSOTER project, grant agreement nr. 211578). The core task of the project was to revise the SOTER method for the interpretation of soil and terrain data. It was one of the working hypothesis that eSOTER does not only provide terrain data with typical soil profiles, but that the new products actually perform like a conceptual soil map. The three eSOTER maps for the pilot area considerably differed in spatial representation and content of soil classes. In this study we compare the three eSOTER maps against existing reconnaissance soil maps keeping in mind that traditional soil maps have many subjective issues and intended bias regarding the overestimation and emphasize of certain features. Hence, a true validation of the proper representation of modeled soil maps is hardly possible; rather a statistical comparison between modeled and empirical approaches is possible. If eSOTER data represent conceptual soil maps, then different eSOTER, DSM and conventional maps from various sources and different regions could be harmonized towards consistent new data sets for large areas including the whole European continent. One of the eSOTER maps has been developed closely to the traditional SOTER method: terrain classification data (derived from SRTM DEM) were combined with lithology data (re-interpreted geological map); the corresponding terrain units were then extended with soil information: a very dense regional soil profile data set was used to define soil mapping units based on a statistical grouping of terrain units. The second map is a pure DSM map using continuous terrain parameters instead of terrain classification; radiospectrometric data were used to supplement parent material information from geology maps. The classification method Random Forest was used. The third approach predicts soil diagnostic properties based on covariates similar to DSM practices; in addition, multi-temporal MODIS data were used; the resulting soil map is the product of these diagnostic layers producing a map of soil reference groups (classified according to WRB). Because the third approach was applied to a larger test area in central Europe, and compared to the first two approaches, has worked with coarser input data, comparability is only partly fulfilled. To evaluate the usability of the three eSOTER maps, and to make a comparison among them, traditional soil maps 1:200,000 and 1:50,000 were used as reference data sets. Three statistical methods were applied: (i) in a moving window the distribution of the soil classes of each DSM product was compared to that of the soil maps by calculating the corrected coefficient of contingency, (ii) the value of predictive power for each of the eSOTER maps was determined, and (iii) the degree of consistency was derived. The latter is based on a weighting of the match of occurring class combinations via expert knowledge and recalculating the proportions of map appearance with these weights. To re-check the validation results a field study by local soil experts was conducted. The results show clearly that the first eSOTER approach based on the terrain classification / reinterpreted parent material information has the greatest similarity with traditional soil maps. The spatial differentiation offered by such an approach is well suitable to serve as a conceptual soil map. Therefore, eSOTER can be a tool for soil mappers to generate conceptual soil maps in a faster and more consistent way. This conclusion is at least valid for overview scales such as 1.250,000.

Enhancing sparsity of Hermite polynomial expansions by iterative rotations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiu; Lei, Huan; Baker, Nathan A.

2016-02-01

Compressive sensing has become a powerful addition to uncertainty quantification in recent years. This paper identifies new bases for random variables through linear mappings such that the representation of the quantity of interest is more sparse with new basis functions associated with the new random variables. This sparsity increases both the efficiency and accuracy of the compressive sensing-based uncertainty quantification method. Specifically, we consider rotation- based linear mappings which are determined iteratively for Hermite polynomial expansions. We demonstrate the effectiveness of the new method with applications in solving stochastic partial differential equations and high-dimensional (O(100)) problems.

Temporal similarity perfusion mapping: A standardized and model-free method for detecting perfusion deficits in stroke

PubMed Central

Song, Sunbin; Luby, Marie; Edwardson, Matthew A.; Brown, Tyler; Shah, Shreyansh; Cox, Robert W.; Saad, Ziad S.; Reynolds, Richard C.; Glen, Daniel R.; Cohen, Leonardo G.; Latour, Lawrence L.

2017-01-01

Introduction Interpretation of the extent of perfusion deficits in stroke MRI is highly dependent on the method used for analyzing the perfusion-weighted signal intensity time-series after gadolinium injection. In this study, we introduce a new model-free standardized method of temporal similarity perfusion (TSP) mapping for perfusion deficit detection and test its ability and reliability in acute ischemia. Materials and methods Forty patients with an ischemic stroke or transient ischemic attack were included. Two blinded readers compared real-time generated interactive maps and automatically generated TSP maps to traditional TTP/MTT maps for presence of perfusion deficits. Lesion volumes were compared for volumetric inter-rater reliability, spatial concordance between perfusion deficits and healthy tissue and contrast-to-noise ratio (CNR). Results Perfusion deficits were correctly detected in all patients with acute ischemia. Inter-rater reliability was higher for TSP when compared to TTP/MTT maps and there was a high similarity between the lesion volumes depicted on TSP and TTP/MTT (r(18) = 0.73). The Pearson's correlation between lesions calculated on TSP and traditional maps was high (r(18) = 0.73, p<0.0003), however the effective CNR was greater for TSP compared to TTP (352.3 vs 283.5, t(19) = 2.6, p<0.03.) and MTT (228.3, t(19) = 2.8, p<0.03). Discussion TSP maps provide a reliable and robust model-free method for accurate perfusion deficit detection and improve lesion delineation compared to traditional methods. This simple method is also computationally faster and more easily automated than model-based methods. This method can potentially improve the speed and accuracy in perfusion deficit detection for acute stroke treatment and clinical trial inclusion decision-making. PMID:28973000

High-density genetic map construction and comparative genome analysis in asparagus bean.

PubMed

Huang, Haitao; Tan, Huaqiang; Xu, Dongmei; Tang, Yi; Niu, Yisong; Lai, Yunsong; Tie, Manman; Li, Huanxiu

2018-03-19

Genetic maps are a prerequisite for quantitative trait locus (QTL) analysis, marker-assisted selection (MAS), fine gene mapping, and assembly of genome sequences. So far, several asparagus bean linkage maps have been established using various kinds of molecular markers. However, these maps were all constructed by gel- or array-based markers. No maps based on sequencing method have been reported. In this study, an NGS-based strategy, SLAF-seq, was applied to create a high-density genetic map for asparagus bean. Through SLAF library construction and Illumina sequencing of two parents and 100 F2 individuals, a total of 55,437 polymorphic SLAF markers were developed and mined for SNP markers. The map consisted of 5,225 SNP markers in 11 LGs, spanning a total distance of 1,850.81 cM, with an average distance between markers of 0.35 cM. Comparative genome analysis with four other legume species, soybean, common bean, mung bean and adzuki bean showed that asparagus bean is genetically more related to adzuki bean. The results will provide a foundation for future genomic research, such as QTL fine mapping, comparative mapping in pulses, and offer support for assembling asparagus bean genome sequence.

Basin boundaries and focal points in a map coming from Bairstow's method.

PubMed

Gardini, Laura; Bischi, Gian-Italo; Fournier-Prunaret, Daniele

1999-06-01

This paper is devoted to the study of the global dynamical properties of a two-dimensional noninvertible map, with a denominator which can vanish, obtained by applying Bairstow's method to a cubic polynomial. It is shown that the complicated structure of the basins of attraction of the fixed points is due to the existence of singularities such as sets of nondefinition, focal points, and prefocal curves, which are specific to maps with a vanishing denominator, and have been recently introduced in the literature. Some global bifurcations that change the qualitative structure of the basin boundaries, are explained in terms of contacts among these singularities. The techniques used in this paper put in evidence some new dynamic behaviors and bifurcations, which are peculiar of maps with denominator; hence they can be applied to the analysis of other classes of maps coming from iterative algorithms (based on Newton's method, or others). (c) 1999 American Institute of Physics.

Interpretation of fingerprint image quality features extracted by self-organizing maps

NASA Astrophysics Data System (ADS)

Danov, Ivan; Olsen, Martin A.; Busch, Christoph

2014-05-01

Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

LIFTING THE DUSTY VEIL WITH NEAR- AND MID-INFRARED PHOTOMETRY. III. TWO-DIMENSIONAL EXTINCTION MAPS OF THE GALACTIC MIDPLANE USING THE RAYLEIGH-JEANS COLOR EXCESS METHOD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nidever, David L.; Zasowski, Gail; Majewski, Steven R., E-mail: dln5q@virginia.edu, E-mail: gz2n@virginia.edu, E-mail: srm4n@virginia.edu

We provide new, high-resolution A(K{sub s} ) extinction maps of the heavily reddened Galactic midplane based on the Rayleigh-Jeans Color Excess ({sup R}JCE{sup )} method. RJCE determines star-by-star reddening based on a combination of near- and mid-infrared photometry. The new RJCE-generated maps have 2' Multiplication-Sign 2' pixels and span some of the most severely extinguished regions of the Galaxy-those covered with Spitzer/IRAC imaging by the GLIMPSE-I, -II, -3D, and Vela-Carina surveys, from 256 Degree-Sign < l < 65 Degree-Sign and, in general, for |b| {<=} 1 Degree-Sign -1.{sup 0}5 (extending up to |b| {<=} 4 Degree-Sign in the bulge). Usingmore » RJCE extinction measurements, we generate dereddened color-magnitude diagrams and, in turn, create maps based on main sequence, red clump, and red giant star tracers, each probing different distances and thereby providing coarse three-dimensional information on the relative placement of dust cloud structures. The maps generated from red giant stars, which reach to {approx}18-20 kpc, probe beyond most of the Milky Way extinction in most directions and provide close to a 'total Galactic extinction' map-at minimum they provide high angular resolution maps of lower limits on A(K{sub s} ). Because these maps are generated directly from measurements of reddening by the very dust being mapped, rather than inferred on the basis of some less direct means, they are likely the most accurate to date for charting in detail the highly patchy differential extinction in the Galactic midplane. We provide downloadable FITS files and an IDL tool for retrieving extinction values for any line of sight within our mapped regions.« less

Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line.

PubMed

Teo, Audrey S M; Verzotto, Davide; Yao, Fei; Nagarajan, Niranjan; Hillmer, Axel M

2015-01-01

Next-generation sequencing (NGS) technologies have changed our understanding of the variability of the human genome. However, the identification of genome structural variations based on NGS approaches with read lengths of 35-300 bases remains a challenge. Single-molecule optical mapping technologies allow the analysis of DNA molecules of up to 2 Mb and as such are suitable for the identification of large-scale genome structural variations, and for de novo genome assemblies when combined with short-read NGS data. Here we present optical mapping data for two human genomes: the HapMap cell line GM12878 and the colorectal cancer cell line HCT116. High molecular weight DNA was obtained by embedding GM12878 and HCT116 cells, respectively, in agarose plugs, followed by DNA extraction under mild conditions. Genomic DNA was digested with KpnI and 310,000 and 296,000 DNA molecules (≥ 150 kb and 10 restriction fragments), respectively, were analyzed per cell line using the Argus optical mapping system. Maps were aligned to the human reference by OPTIMA, a new glocal alignment method. Genome coverage of 6.8× and 5.7× was obtained, respectively; 2.9× and 1.7× more than the coverage obtained with previously available software. Optical mapping allows the resolution of large-scale structural variations of the genome, and the scaffold extension of NGS-based de novo assemblies. OPTIMA is an efficient new alignment method; our optical mapping data provide a resource for genome structure analyses of the human HapMap reference cell line GM12878, and the colorectal cancer cell line HCT116.

Optimal Mass Transport for Shape Matching and Comparison

PubMed Central

Su, Zhengyu; Wang, Yalin; Shi, Rui; Zeng, Wei; Sun, Jian; Luo, Feng; Gu, Xianfeng

2015-01-01

Surface based 3D shape analysis plays a fundamental role in computer vision and medical imaging. This work proposes to use optimal mass transport map for shape matching and comparison, focusing on two important applications including surface registration and shape space. The computation of the optimal mass transport map is based on Monge-Brenier theory, in comparison to the conventional method based on Monge-Kantorovich theory, this method significantly improves the efficiency by reducing computational complexity from O(n2) to O(n). For surface registration problem, one commonly used approach is to use conformal map to convert the shapes into some canonical space. Although conformal mappings have small angle distortions, they may introduce large area distortions which are likely to cause numerical instability thus resulting failures of shape analysis. This work proposes to compose the conformal map with the optimal mass transport map to get the unique area-preserving map, which is intrinsic to the Riemannian metric, unique, and diffeomorphic. For shape space study, this work introduces a novel Riemannian framework, Conformal Wasserstein Shape Space, by combing conformal geometry and optimal mass transport theory. In our work, all metric surfaces with the disk topology are mapped to the unit planar disk by a conformal mapping, which pushes the area element on the surface to a probability measure on the disk. The optimal mass transport provides a map from the shape space of all topological disks with metrics to the Wasserstein space of the disk and the pullback Wasserstein metric equips the shape space with a Riemannian metric. We validate our work by numerous experiments and comparisons with prior approaches and the experimental results demonstrate the efficiency and efficacy of our proposed approach. PMID:26440265

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics

PubMed Central

Chen, Wenan; Larrabee, Beth R.; Ovsyannikova, Inna G.; Kennedy, Richard B.; Haralambieva, Iana H.; Poland, Gregory A.; Schaid, Daniel J.

2015-01-01

Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. PMID:25948564

Mapping Human Cortical Areas in vivo Based on Myelin Content as Revealed by T1- and T2-weighted MRI

PubMed Central

Glasser, Matthew F.; Van Essen, David C.

2011-01-01

Non-invasively mapping the layout of cortical areas in humans is a continuing challenge for neuroscience. We present a new method of mapping cortical areas based on myelin content as revealed by T1-weighted (T1w) and T2-weighted (T2w) MRI. The method is generalizable across different 3T scanners and pulse sequences. We use the ratio of T1w/T2w image intensities to eliminate the MR-related image intensity bias and enhance the contrast to noise ratio for myelin. Data from each subject was mapped to the cortical surface and aligned across individuals using surface-based registration. The spatial gradient of the group average myelin map provides an observer-independent measure of sharp transitions in myelin content across the surface—i.e. putative cortical areal borders. We found excellent agreement between the gradients of the myelin maps and the gradients of published probabilistic cytoarchitectonically defined cortical areas that were registered to the same surface-based atlas. For other cortical regions, we used published anatomical and functional information to make putative identifications of dozens of cortical areas or candidate areas. In general, primary and early unimodal association cortices are heavily myelinated and higher, multi-modal, association cortices are more lightly myelinated, but there are notable exceptions in the literature that are confirmed by our results. The overall pattern in the myelin maps also has important correlations with the developmental onset of subcortical white matter myelination, evolutionary cortical areal expansion in humans compared to macaques, postnatal cortical expansion in humans, and maps of neuronal density in non-human primates. PMID:21832190

Exploiting Surroundedness for Saliency Detection: A Boolean Map Approach.

PubMed

Zhang, Jianming; Sclaroff, Stan

2016-05-01

We demonstrate the usefulness of surroundedness for eye fixation prediction by proposing a Boolean Map based Saliency model (BMS). In our formulation, an image is characterized by a set of binary images, which are generated by randomly thresholding the image's feature maps in a whitened feature space. Based on a Gestalt principle of figure-ground segregation, BMS computes a saliency map by discovering surrounded regions via topological analysis of Boolean maps. Furthermore, we draw a connection between BMS and the Minimum Barrier Distance to provide insight into why and how BMS can properly captures the surroundedness cue via Boolean maps. The strength of BMS is verified by its simplicity, efficiency and superior performance compared with 10 state-of-the-art methods on seven eye tracking benchmark datasets.

Fast and robust generation of feature maps for region-based visual attention.

PubMed

Aziz, Muhammad Zaheer; Mertsching, Bärbel

2008-05-01

Visual attention is one of the important phenomena in biological vision which can be followed to achieve more efficiency, intelligence, and robustness in artificial vision systems. This paper investigates a region-based approach that performs pixel clustering prior to the processes of attention in contrast to late clustering as done by contemporary methods. The foundation steps of feature map construction for the region-based attention model are proposed here. The color contrast map is generated based upon the extended findings from the color theory, the symmetry map is constructed using a novel scanning-based method, and a new algorithm is proposed to compute a size contrast map as a formal feature channel. Eccentricity and orientation are computed using the moments of obtained regions and then saliency is evaluated using the rarity criteria. The efficient design of the proposed algorithms allows incorporating five feature channels while maintaining a processing rate of multiple frames per second. Another salient advantage over the existing techniques is the reusability of the salient regions in the high-level machine vision procedures due to preservation of their shapes and precise locations. The results indicate that the proposed model has the potential to efficiently integrate the phenomenon of attention into the main stream of machine vision and systems with restricted computing resources such as mobile robots can benefit from its advantages.

Regional Lung Ventilation Analysis Using Temporally Resolved Magnetic Resonance Imaging.

PubMed

Kolb, Christoph; Wetscherek, Andreas; Buzan, Maria Teodora; Werner, René; Rank, Christopher M; Kachelrie, Marc; Kreuter, Michael; Dinkel, Julien; Heuel, Claus Peter; Maier-Hein, Klaus

We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI). A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference). Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior. The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.

Quantile rank maps: a new tool for understanding individual brain development.

PubMed

Chen, Huaihou; Kelly, Clare; Castellanos, F Xavier; He, Ye; Zuo, Xi-Nian; Reiss, Philip T

2015-05-01

We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample. Copyright © 2015 Elsevier Inc. All rights reserved.

Infrastructure-Free Mapping and Localization for Tunnel-Based Rail Applications Using 2D Lidar

NASA Astrophysics Data System (ADS)

Daoust, Tyler

This thesis presents an infrastructure-free mapping and localization framework for rail vehicles using only a lidar sensor. The method was designed to handle modern underground tunnels: narrow, parallel, and relatively smooth concrete walls. A sliding-window algorithm was developed to estimate the train's motion, using a Renyi's Quadratic Entropy (RQE)-based point-cloud alignment system. The method was tested with datasets gathered on a subway train travelling at high speeds, with 75 km of data across 14 runs, simulating 500 km of localization. The system was capable of mapping with an average error of less than 0.6 % by distance. It was capable of continuously localizing, relative to the map, to within 10 cm in stations and at crossovers, and 2.3 m in pathological sections of tunnel. This work has the potential to improve train localization in a tunnel, which can be used to increase capacity and for automation purposes.

ACCELERATING MR PARAMETER MAPPING USING SPARSITY-PROMOTING REGULARIZATION IN PARAMETRIC DIMENSION

PubMed Central

Velikina, Julia V.; Alexander, Andrew L.; Samsonov, Alexey

2013-01-01

MR parameter mapping requires sampling along additional (parametric) dimension, which often limits its clinical appeal due to a several-fold increase in scan times compared to conventional anatomic imaging. Data undersampling combined with parallel imaging is an attractive way to reduce scan time in such applications. However, inherent SNR penalties of parallel MRI due to noise amplification often limit its utility even at moderate acceleration factors, requiring regularization by prior knowledge. In this work, we propose a novel regularization strategy, which utilizes smoothness of signal evolution in the parametric dimension within compressed sensing framework (p-CS) to provide accurate and precise estimation of parametric maps from undersampled data. The performance of the method was demonstrated with variable flip angle T1 mapping and compared favorably to two representative reconstruction approaches, image space-based total variation regularization and an analytical model-based reconstruction. The proposed p-CS regularization was found to provide efficient suppression of noise amplification and preservation of parameter mapping accuracy without explicit utilization of analytical signal models. The developed method may facilitate acceleration of quantitative MRI techniques that are not suitable to model-based reconstruction because of complex signal models or when signal deviations from the expected analytical model exist. PMID:23213053

Optimization with artificial neural network systems - A mapping principle and a comparison to gradient based methods

NASA Technical Reports Server (NTRS)

Leong, Harrison Monfook

1988-01-01

General formulae for mapping optimization problems into systems of ordinary differential equations associated with artificial neural networks are presented. A comparison is made to optimization using gradient-search methods. The performance measure is the settling time from an initial state to a target state. A simple analytical example illustrates a situation where dynamical systems representing artificial neural network methods would settle faster than those representing gradient-search. Settling time was investigated for a more complicated optimization problem using computer simulations. The problem was a simplified version of a problem in medical imaging: determining loci of cerebral activity from electromagnetic measurements at the scalp. The simulations showed that gradient based systems typically settled 50 to 100 times faster than systems based on current neural network optimization methods.

Back analysis of Swiss flood danger map to define local flood hazards

NASA Astrophysics Data System (ADS)

Choffet, Marc; Derron, Marc-Henri; Jaboyedoff, Michel; Leroi, Eric; Mayis, Arnaud

2010-05-01

The flood hazard maps for the entire Switzerland will be available at the end of 2011. Furthermore, the Swiss territory has been covered by aerial laser scanning (ALS) providing high resolution digital elevation model (DEM). This paper describes the development of a method for analyzing the local flood hazard based on Swiss hazard maps and HR-DEM. In their original state, Swiss hazard maps are constructed on the basis of an aggregation of information, a matrix intensity, and frequency. The degree of danger represented by the yellow, blue and red zones gives no information on the water level at each point of the territory. The developed method is based on a superposition of the danger map with the HR-DEM to determine the water level in a hazard area. To perform this method, (1) a triangulation is based on the intersection of the hazard map with the HR-DEM. It uses the limits of area where information is contrain. The hazard map perimeter and the boundaries of hazard areas give information on the widest possible overflow in case of flooding. It is also possible to associate it with a return period. (2) Based on these areas and the difference with the DEM, it is possible to calibrate the highest flood level and the extract water levels for the entire area. This analysis of existing documents opens up interesting perspectives for understanding how infrastructures are threatened by flood hazard by predicting water levels and potential damages to buildings while proposing remedial measures. Indeed, this method allows estimating the water level at each point of a building in case of flooding. It is designed to provide spatial information on water height levels; this offers a different approach of buildings in danger zones. Indeed, it is possible to discern several elements, such as areas of water accumulation involving longer flood duration, possible structural damages to buildings due to high hydrostatic pressure, determination of a local hazard, or the display of water levels in 3D.

Concept Map Engineering: Methods and Tools Based on the Semantic Relation Approach

ERIC Educational Resources Information Center

Kim, Minkyu

2013-01-01

The purpose of this study is to develop a better understanding of technologies that use natural language as the basis for concept map construction. In particular, this study focuses on the semantic relation (SR) approach to drawing rich and authentic concept maps that reflect students' internal representations of a problem situation. The…

From Open Geographical Data to Tangible Maps: Improving the Accessibility of Maps for Visually Impaired People

NASA Astrophysics Data System (ADS)

Ducasse, J.; Macé, M.; Jouffrais, C.

2015-08-01

Visual maps must be transcribed into (interactive) raised-line maps to be accessible for visually impaired people. However, these tactile maps suffer from several shortcomings: they are long and expensive to produce, they cannot display a large amount of information, and they are not dynamically modifiable. A number of methods have been developed to automate the production of raised-line maps, but there is not yet any tactile map editor on the market. Tangible interactions proved to be an efficient way to help a visually impaired user manipulate spatial representations. Contrary to raised-line maps, tangible maps can be autonomously constructed and edited. In this paper, we present the scenarios and the main expected contributions of the AccessiMap project, which is based on the availability of many sources of open spatial data: 1/ facilitating the production of interactive tactile maps with the development of an open-source web-based editor; 2/ investigating the use of tangible interfaces for the autonomous construction and exploration of a map by a visually impaired user.

Application of IS1311 locus 2 PCR-REA assay for the specific detection of 'Bison type' Mycobacterium avium subspecies paratuberculosis isolates of Indian origin.

PubMed

Singh, Ajay Vir; Chauhan, Devendra Singh; Singh, Abhinendra; Singh, Pravin Kumar; Sohal, Jagdip Singh; Singh, Shoor Vir

2015-01-01

Of the three major genotypes of Mycobacterium avium subspecies paratuberculosis (MAP), 'Bison type' is most prevalent genotype in the domestic livestock species of the country, and has also been recovered from patients suffering from Crohn's disease. Recently, a new assay based on IS1311 locus 2 PCR- restriction endonuclease analysis (REA) was designed to distinguish between 'Indian Bison type' and non-Indian genotypes. The present study investigated discriminatory potential of this new assay while screening of a panel of MAP isolates of diverse genotypes and from different geographical regions. A total of 53 mycobacterial isolates (41 MAP and 12 mycobacterium other than MAP), three MAP genomic DNA and 36 MAP positive faecal DNA samples from different livestock species (cattle, buffaloes, goat, sheep and bison) and geographical regions (India, Canada, USA, Spain and Portugal) were included in the study. The extracted DNA samples (n=92) were analyzed for the presence of MAP specific sequences (IS900, ISMav 2 and HspX) using PCR. DNA samples were further subjected to genotype differentiation using IS1311 PCR-REA and IS1311 L2 PCR-REA methods. All the DNA samples (except DNA from non-MAP mycobacterial isolates) were positive for all the three MAP specific sequences based PCRs. IS1311 PCR-REA showed that MAP DNA samples of Indian origin belonged to 'Bison type'. Whereas, of the total 19 non-Indian MAP DNA samples, 2, 15 and 2 were genotyped as 'Bison type', 'Cattle type' and 'Sheep type', respectively. IS1311 L2 PCR-REA method showed different restriction profiles of 'Bison type' genotype as compared to non-Indian DNA samples. IS1311 L2 PCR-REA method successfully discriminated 'Indian Bison type' from other non-Indian genotypes and showed potential to be future epidemiological tool and for genotyping of MAP isolates.

Robust visual object tracking with interleaved segmentation

NASA Astrophysics Data System (ADS)

Abel, Peter; Kieritz, Hilke; Becker, Stefan; Arens, Michael

2017-10-01

In this paper we present a new approach for tracking non-rigid, deformable objects by means of merging an on-line boosting-based tracker and a fast foreground background segmentation. We extend an on-line boosting- based tracker, which uses axes-aligned bounding boxes with fixed aspect-ratio as tracking states. By constructing a confidence map from the on-line boosting-based tracker and unifying this map with a confidence map, which is obtained from a foreground background segmentation algorithm, we build a superior confidence map. For constructing a rough confidence map of a new frame based on on-line boosting, we employ the responses of the strong classifier as well as the single weak classifier responses that were built before during the updating step. This confidence map provides a rough estimation of the object's position and dimension. In order to refine this confidence map, we build a fine, pixel-wisely segmented confidence map and merge both maps together. Our segmentation method is color-histogram-based and provides a fine and fast image segmentation. By means of back-projection and the Bayes' rule, we obtain a confidence value for every pixel. The rough and the fine confidence maps are merged together by building an adaptively weighted sum of both maps. The weights are obtained by utilizing the variances of both confidence maps. Further, we apply morphological operators in the merged confidence map in order to reduce the noise. In the resulting map we estimate the object localization and dimension via continuous adaptive mean shift. Our approach provides a rotated rectangle as tracking states, which enables a more precise description of non-rigid, deformable objects than axes-aligned bounding boxes. We evaluate our tracker on the visual object tracking (VOT) benchmark dataset 2016.

A method of genotyping by pedigree-based training-set for identification of QTLs associated with cucumber fruit size

USDA-ARS?s Scientific Manuscript database

Large sets of genomic data are becoming available for cucumber (Cucumis sativus), yet there is no tool for whole genome genotyping. Creation of saturated genetic maps depends on development of good markers. The present cucumber genetic maps are based on several hundreds of markers. However they are ...

Mapping Fuels on the Okanogan and Wenatchee National Forests

Treesearch

Crystal L. Raymond; Lara-Karena B. Kellogg; Donald McKenzie

2006-01-01

Resource managers need spatially explicit fuels data to manage fire hazard and evaluate the ecological effects of wildland fires and fuel treatments. For this study, fuels were mapped on the Okanogan and Wenatchee National Forests (OWNF) using a rule-based method and the Fuels Characteristic Classification System (FCCS). The FCCS classifies fuels based on their...

Large-scale virtual screening on public cloud resources with Apache Spark.

PubMed

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

2017-01-01

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

A comparative analysis of chaotic particle swarm optimizations for detecting single nucleotide polymorphism barcodes.

PubMed

Chuang, Li-Yeh; Moi, Sin-Hua; Lin, Yu-Da; Yang, Cheng-Hong

2016-10-01

Evolutionary algorithms could overcome the computational limitations for the statistical evaluation of large datasets for high-order single nucleotide polymorphism (SNP) barcodes. Previous studies have proposed several chaotic particle swarm optimization (CPSO) methods to detect SNP barcodes for disease analysis (e.g., for breast cancer and chronic diseases). This work evaluated additional chaotic maps combined with the particle swarm optimization (PSO) method to detect SNP barcodes using a high-dimensional dataset. Nine chaotic maps were used to improve PSO method results and compared the searching ability amongst all CPSO methods. The XOR and ZZ disease models were used to compare all chaotic maps combined with PSO method. Efficacy evaluations of CPSO methods were based on statistical values from the chi-square test (χ 2 ). The results showed that chaotic maps could improve the searching ability of PSO method when population are trapped in the local optimum. The minor allele frequency (MAF) indicated that, amongst all CPSO methods, the numbers of SNPs, sample size, and the highest χ 2 value in all datasets were found in the Sinai chaotic map combined with PSO method. We used the simple linear regression results of the gbest values in all generations to compare the all methods. Sinai chaotic map combined with PSO method provided the highest β values (β≥0.32 in XOR disease model and β≥0.04 in ZZ disease model) and the significant p-value (p-value<0.001 in both the XOR and ZZ disease models). The Sinai chaotic map was found to effectively enhance the fitness values (χ 2 ) of PSO method, indicating that the Sinai chaotic map combined with PSO method is more effective at detecting potential SNP barcodes in both the XOR and ZZ disease models. Copyright © 2016 Elsevier B.V. All rights reserved.

Potential mapping with charged-particle beams

NASA Technical Reports Server (NTRS)

Robinson, J. W.; Tillery, D. G.

1979-01-01

Experimental methods of mapping the equipotential surfaces near some structure of interest rely on the detection of charged particles which have traversed the regions of interest and are detected remotely. One method is the measurement of ion energies for ions created at a point of interest and expelled from the region by the fields. The ion energy at the detector in eV corresponds to the potential where the ion was created. An ionizing beam forms the ions from background neutrals. The other method is to inject charged particles into the region of interest and to locate their exit points. A set of several trajectories becomes a data base for a systematic mapping technique. An iterative solution of a boundary value problem establishes concepts and limitations pertaining to the mapping problem.

Interpreting the Externalised Images of Pupils' Conceptions of ICT: Methods for the Analysis of Concept Maps.

ERIC Educational Resources Information Center

Mavers, Diane; Somekh, Bridget; Restorick, Jane

2002-01-01

Describes the ImpacT2 evaluation of students aged ten to 16 in the United Kingdom that uses image-based concept mapping to explore the impact of networked technologies on students' learning. Explains a method for interviewing young students and discusses implications for the way that information and communication technologies (ICT) are used in…

Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping.

PubMed

Jaakkola, Anttoni; Hyyppä, Juha; Hyyppä, Hannu; Kukko, Antero

2008-09-01

Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehiclebased laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively.

Mapping snow depth distribution in forested terrain using unmanned aerial vehicles and structure-from-motion

NASA Astrophysics Data System (ADS)

Webster, C.; Bühler, Y.; Schirmer, M.; Stoffel, A.; Giulia, M.; Jonas, T.

2017-12-01

Snow depth distribution in forests exhibits strong spatial heterogeneity compared to adjacent open sites. Measurement of snow depths in forests is currently limited to a) manual point measurements, which are sparse and time-intensive, b) ground-penetrating radar surveys, which have limited spatial coverage, or c) airborne LiDAR acquisition, which are expensive and may deteriorate in denser forests. We present the application of unmanned aerial vehicles in combination with structure-from-motion (SfM) methods to photogrammetrically map snow depth distribution in forested terrain. Two separate flights were carried out 10 days apart across a heterogeneous forested area of 900 x 500 m. Corresponding snow depth maps were derived using both, LiDAR-based and SfM-based DTM data, obtained during snow-off conditions. Manual measurements collected following each flight were used to validate the snow depth maps. Snow depths were resolved at 5cm resolution and forest snow depth distribution structures such as tree wells and other areas of preferential melt were represented well. Differential snow depth maps showed maximum ablation in the exposed south sides of trees and smaller differences in the centre of gaps and on the north side of trees. This new application of SfM to map snow depth distribution in forests demonstrates a straightforward method for obtaining information that was previously only available through manual spatially limited ground-based measurements. These methods could therefore be extended to more frequent observation of snow depths in forests as well as estimating snow accumulation and depletion rates.

Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management

NASA Astrophysics Data System (ADS)

Reyes-Gonzalez, Arturo

Irrigation water is scarce. Hence, accurate estimation of crop water use is necessary for proper irrigation managements and water conservation. Satellite-based remote sensing is a tool that can estimate crop water use efficiently. Several models have been developed to estimate crop water requirement or actual evapotranspiration (ETa) using remote sensing. One of them is the Mapping EvapoTranspiration at High Resolution using Internalized Calibration (METRIC) model. This model has been compared with other methods for ET estimations including weighing lysimeters, pan evaporation, Bowen Ratio Energy Balance System (BREBS), Eddy Covariance (EC), and sap flow. However, comparison of METRIC model outputs to an atmometer for ETa estimation has not yet been attempted in eastern South Dakota. The results showed a good relationship between ETa estimated by the METRIC model and estimated with atmometer (r2 = 0.87 and RMSE = 0.65 mm day-1). However, ETa values from atmometer were consistently lower than ET a values from METRIC. The verification of remotely sensed estimates of surface variables is essential for any remote-sensing study. The relationships between LAI, Ts, and ETa estimated using the remote sensing-based METRIC model and in-situ measurements were established. The results showed good agreement between the variables measured in situ and estimated by the METRIC model. LAI showed r2 = 0.76, and RMSE = 0.59 m2 m -2, Ts had r2 = 0.87 and RMSE 1.24 °C and ETa presented r2= 0.89 and RMSE = 0.71 mm day -1. Estimation of ETa using energy balance method can be challenging and time consuming. Thus, there is a need to develop a simple and fast method to estimate ETa using minimum input parameters. Two methods were used, namely 1) an energy balance method (EB method) that used input parameters of the Landsat image, weather data, a digital elevation map, and a land cover map and 2) a Kc-NDVI method that use two input parameters: the Landsat image and weather data. A strong relationship was found between the two methods with r2 of 0.97 and RMSE of 0.37 mm day -1. Hence, the Kc-NDVI method performed well for ET a estimations, indicating that Kc-NDVI method can be a robust and reliable method to estimate ETa in a short period of time. Estimation of crop evapotranspiration (ETc) using satellite remote sensing-based vegetation index such as the Normalized Difference Vegetation Index (NDVI). The NDVI was calculated using near-infrared and red wavebands. The relationship between NDVI and tabulated Kc's was used to generate Kc maps. ETc maps were developed as an output of Kc maps multiplied by reference evapotranspiration (ETr). Daily ETc maps helped to explain the variability of crop water use during the growing season. Based on the results we can conclude that ETc maps developed from remotely sensed multispectral vegetation indices are a useful tool for quantifying crop water use at regional and field scales.

Mapping from multiple-control Toffoli circuits to linear nearest neighbor quantum circuits

NASA Astrophysics Data System (ADS)

Cheng, Xueyun; Guan, Zhijin; Ding, Weiping

2018-07-01

In recent years, quantum computing research has been attracting more and more attention, but few studies on the limited interaction distance between quantum bits (qubit) are deeply carried out. This paper presents a mapping method for transforming multiple-control Toffoli (MCT) circuits into linear nearest neighbor (LNN) quantum circuits instead of traditional decomposition-based methods. In order to reduce the number of inserted SWAP gates, a novel type of gate with the optimal LNN quantum realization was constructed, namely NNTS gate. The MCT gate with multiple control bits could be better cascaded by the NNTS gates, in which the arrangement of the input lines was LNN arrangement of the MCT gate. Then, the communication overhead measurement model on inserted SWAP gate count from the original arrangement to the new arrangement was put forward, and we selected one of the LNN arrangements with the minimum SWAP gate count. Moreover, the LNN arrangement-based mapping algorithm was given, and it dealt with the MCT gates in turn and mapped each MCT gate into its LNN form by inserting the minimum number of SWAP gates. Finally, some simplification rules were used, which can further reduce the final quantum cost of the LNN quantum circuit. Experiments on some benchmark MCT circuits indicate that the direct mapping algorithm results in fewer additional SWAP gates in about 50%, while the average improvement rate in quantum cost is 16.95% compared to the decomposition-based method. In addition, it has been verified that the proposed method has greater superiority for reversible circuits cascaded by MCT gates with more control bits.

Interactive remote data processing using Pixelize Wavelet Filtration (PWF-method) and PeriodMap analysis

NASA Astrophysics Data System (ADS)

Sych, Robert; Nakariakov, Valery; Anfinogentov, Sergey

Wavelet analysis is suitable for investigating waves and oscillating in solar atmosphere, which are limited in both time and frequency. We have developed an algorithms to detect this waves by use the Pixelize Wavelet Filtration (PWF-method). This method allows to obtain information about the presence of propagating and non-propagating waves in the data observation (cube images), and localize them precisely in time as well in space. We tested the algorithm and found that the results of coronal waves detection are consistent with those obtained by visual inspection. For fast exploration of the data cube, in addition, we applied early-developed Period- Map analysis. This method based on the Fast Fourier Transform and allows on initial stage quickly to look for "hot" regions with the peak harmonic oscillations and determine spatial distribution at the significant harmonics. We propose the detection procedure of coronal waves separate on two parts: at the first part, we apply the PeriodMap analysis (fast preparation) and than, at the second part, use information about spatial distribution of oscillation sources to apply the PWF-method (slow preparation). There are two possible algorithms working with the data: in automatic and hands-on operation mode. Firstly we use multiply PWF analysis as a preparation narrowband maps at frequency subbands multiply two and/or harmonic PWF analysis for separate harmonics in a spectrum. Secondly we manually select necessary spectral subband and temporal interval and than construct narrowband maps. For practical implementation of the proposed methods, we have developed the remote data processing system at Institute of Solar-Terrestrial Physics, Irkutsk. The system based on the data processing server - http://pwf.iszf.irk.ru. The main aim of this resource is calculation in remote access through the local and/or global network (Internet) narrowband maps of wave's sources both in whole spectral band and at significant harmonics. In addition, we can obtain temporal dynamics (mpeg- files) of the main oscillation characteristics: amplitude, power and phase as a spatial-temporal coordinates. For periodogram mapping of data cubes as a method for the pre-analysis, we developed preparation of the color maps where the pixel's colour corresponds to the frequency of the power spectrum maximum. The computer system based on applications ION-scripts, algorithmic languages IDL and PHP, and Apache WEB server. The IDL ION-scripts use for preparation and configuration of network requests at the central data server with subsequent connection to IDL run-unit software and graphic output on FTP-server and screen. Web page is constructed using PHP language.

Positive Contrast Visualization of Nitinol Devices using Susceptibility Gradient Mapping

PubMed Central

Vonken, Evert-jan P.A.; Schär, Michael; Stuber, Matthias

2008-01-01

MRI visualization of devices is traditionally based on the signal loss due to T2* effects originating from the local susceptibility differences. To visualize nitinol devices with positive contrast a recently introduced post processing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center of mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualization of a nitinol wire and two stents are shown for illustration. PMID:18727096

A methodology for small scale rural land use mapping in semi-arid developing countries using orbital imagery. Part 6: A low-cost method for land use mapping using simple visual techniques of interpretation. [Spain

NASA Technical Reports Server (NTRS)

Vangenderen, J. L. (Principal Investigator); Lock, B. F.

1976-01-01

The author has identified the following significant results. It was found that color composite transparencies and monocular magnification provided the best base for land use interpretation. New methods for determining optimum sample sizes and analyzing interpretation accuracy levels were developed. All stages of the methodology were assessed, in the operational sense, during the production of a 1:250,000 rural land use map of Murcia Province, Southeast Spain.

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Roberts, Dar A.; Adams, John B.; Smith, Milton O.

1993-01-01

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa

PubMed Central

Tran, Annelise; Trevennec, Carlène; Lutwama, Julius; Sserugga, Joseph; Gély, Marie; Pittiglio, Claudia; Pinto, Julio; Chevalier, Véronique

2016-01-01

Rift Valley fever (RVF), a mosquito-borne disease affecting ruminants and humans, is one of the most important viral zoonoses in Africa. The objective of the present study was to develop a geographic knowledge-based method to map the areas suitable for RVF amplification and RVF spread in four East African countries, namely, Kenya, Tanzania, Uganda and Ethiopia, and to assess the predictive accuracy of the model using livestock outbreak data from Kenya and Tanzania. Risk factors and their relative importance regarding RVF amplification and spread were identified from a literature review. A numerical weight was calculated for each risk factor using an analytical hierarchy process. The corresponding geographic data were collected, standardized and combined based on a weighted linear combination to produce maps of the suitability for RVF transmission. The accuracy of the resulting maps was assessed using RVF outbreak locations in livestock reported in Kenya and Tanzania between 1998 and 2012 and the ROC curve analysis. Our results confirmed the capacity of the geographic information system-based multi-criteria evaluation method to synthesize available scientific knowledge and to accurately map (AUC = 0.786; 95% CI [0.730–0.842]) the spatial heterogeneity of RVF suitability in East Africa. This approach provides users with a straightforward and easy update of the maps according to data availability or the further development of scientific knowledge. PMID:27631374

High-efficient Extraction of Drainage Networks from Digital Elevation Model Data Constrained by Enhanced Flow Enforcement from Known River Map

NASA Astrophysics Data System (ADS)

Wu, T.; Li, T.; Li, J.; Wang, G.

2017-12-01

Improved drainage network extraction can be achieved by flow enforcement whereby information of known river maps is imposed to the flow-path modeling process. However, the common elevation-based stream burning method can sometimes cause unintended topological errors and misinterpret the overall drainage pattern. We presented an enhanced flow enforcement method to facilitate accurate and efficient process of drainage network extraction. Both the topology of the mapped hydrography and the initial landscape of the DEM are well preserved and fully utilized in the proposed method. An improved stream rasterization is achieved here, yielding continuous, unambiguous and stream-collision-free raster equivalent of stream vectors for flow enforcement. By imposing priority-based enforcement with a complementary flow direction enhancement procedure, the drainage patterns of the mapped hydrography are fully represented in the derived results. The proposed method was tested over the Rogue River Basin, using DEMs with various resolutions. As indicated by the visual and statistical analyses, the proposed method has three major advantages: (1) it significantly reduces the occurrences of topological errors, yielding very accurate watershed partition and channel delineation, (2) it ensures scale-consistent performance at DEMs of various resolutions, and (3) the entire extraction process is well-designed to achieve great computational efficiency.

Applying multibeam sonar and mathematical modeling for mapping seabed substrate and biota of offshore shallows

NASA Astrophysics Data System (ADS)

Herkül, Kristjan; Peterson, Anneliis; Paekivi, Sander

2017-06-01

Both basic science and marine spatial planning are in a need of high resolution spatially continuous data on seabed habitats and biota. As conventional point-wise sampling is unable to cover large spatial extents in high detail, it must be supplemented with remote sensing and modeling in order to fulfill the scientific and management needs. The combined use of in situ sampling, sonar scanning, and mathematical modeling is becoming the main method for mapping both abiotic and biotic seabed features. Further development and testing of the methods in varying locations and environmental settings is essential for moving towards unified and generally accepted methodology. To fill the relevant research gap in the Baltic Sea, we used multibeam sonar and mathematical modeling methods - generalized additive models (GAM) and random forest (RF) - together with underwater video to map seabed substrate and epibenthos of offshore shallows. In addition to testing the general applicability of the proposed complex of techniques, the predictive power of different sonar-based variables and modeling algorithms were tested. Mean depth, followed by mean backscatter, were the most influential variables in most of the models. Generally, mean values of sonar-based variables had higher predictive power than their standard deviations. The predictive accuracy of RF was higher than that of GAM. To conclude, we found the method to be feasible and with predictive accuracy similar to previous studies of sonar-based mapping.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii.

PubMed

Shen, Bang; Powell, Robin H; Behnke, Michael S

2017-06-22

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

PubMed Central

Shen, Bang; Powell, Robin H.; Behnke, Michael S.

2017-01-01

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites. PMID:28671645

Mass spectrometric-based stable isotopic 2-aminobenzoic acid glycan mapping for rapid glycan screening of biotherapeutics.

PubMed

Prien, Justin M; Prater, Bradley D; Qin, Qiang; Cockrill, Steven L

2010-02-15

Fast, sensitive, robust methods for "high-level" glycan screening are necessary during various stages of a biotherapeutic product's lifecycle, including clone selection, process changes, and quality control for lot release testing. Traditional glycan screening involves chromatographic or electrophoretic separation-based methods, and, although reproducible, these methods can be time-consuming. Even ultrahigh-performance chromatographic and microfluidic integrated LC/MS systems, which work on the tens of minute time scale, become lengthy when hundreds of samples are to be analyzed. Comparatively, a direct infusion mass spectrometry (MS)-based glycan screening method acquires data on a millisecond time scale, exhibits exquisite sensitivity and reproducibility, and is amenable to automated peak annotation. In addition, characterization of glycan species via sequential mass spectrometry can be performed simultaneously. Here, we demonstrate a quantitative high-throughput MS-based mapping approach using stable isotope 2-aminobenzoic acid (2-AA) for rapid "high-level" glycan screening.

Alaska Interim Land Cover Mapping Program; final report

USGS Publications Warehouse

Fitzpatrick-Lins, Katherine; Doughty, E.F.; Shasby, Mark; Benjamin, Susan

1989-01-01

In 1985, the U.S. Geological Survey initiated a research project to develop an interim land cover data base for Alaska as an alternative to the nationwide Land Use and Land Cover Mapping Program. The Alaska Interim Land Cover Mapping Program was subsequently created to develop methods for producing a series of land cover maps that utilized the existing Landsat digital land cover classifications produced by and for the major land management agencies for mapping the vegetation of Alaska. The program was successful in producing digital land cover classifications and statistical summaries using a common statewide classification and in reformatting these data to produce l:250,000-scale quadrangle-based maps directly from the Scitex laser plotter. A Federal and State agency review of these products found considerable user support for the maps. Presently the Geological Survey is committed to digital processing of six to eight quadrangles each year.

Comparison of landmark-based and automatic methods for cortical surface registration

PubMed Central

Pantazis, Dimitrios; Joshi, Anand; Jiang, Jintao; Shattuck, David; Bernstein, Lynne E.; Damasio, Hanna; Leahy, Richard M.

2009-01-01

Group analysis of structure or function in cerebral cortex typically involves as a first step the alignment of the cortices. A surface based approach to this problem treats the cortex as a convoluted surface and coregisters across subjects so that cortical landmarks or features are aligned. This registration can be performed using curves representing sulcal fundi and gyral crowns to constrain the mapping. Alternatively, registration can be based on the alignment of curvature metrics computed over the entire cortical surface. The former approach typically involves some degree of user interaction in defining the sulcal and gyral landmarks while the latter methods can be completely automated. Here we introduce a cortical delineation protocol consisting of 26 consistent landmarks spanning the entire cortical surface. We then compare the performance of a landmark-based registration method that uses this protocol with that of two automatic methods implemented in the software packages FreeSurfer and BrainVoyager. We compare performance in terms of discrepancy maps between the different methods, the accuracy with which regions of interest are aligned, and the ability of the automated methods to correctly align standard cortical landmarks. Our results show similar performance for ROIs in the perisylvian region for the landmark based method and FreeSurfer. However, the discrepancy maps showed larger variability between methods in occipital and frontal cortex and also that automated methods often produce misalignment of standard cortical landmarks. Consequently, selection of the registration approach should consider the importance of accurate sulcal alignment for the specific task for which coregistration is being performed. When automatic methods are used, the users should ensure that sulci in regions of interest in their studies are adequately aligned before proceeding with subsequent analysis. PMID:19796696

Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

NASA Astrophysics Data System (ADS)

Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

2014-10-01

The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

A CLEAN-based method for mosaic deconvolution

NASA Astrophysics Data System (ADS)

Gueth, F.; Guilloteau, S.; Viallefond, F.

1995-03-01

Mosaicing may be used in aperture synthesis to map large fields of view. So far, only MEM techniques have been used to deconvolve mosaic images (Cornwell (1988)). A CLEAN-based method has been developed, in which the components are located in a modified expression. This allows a better utilization of the information and consequent noise reduction in the overlapping regions. Simulations show that this method gives correct clean maps and recovers most of the flux of the sources. The introduction of the short-spacing visibilities in the data set is strongly required. Their absence actually introduces artificial lack of structures on the corresponding scale in the mosaic images. The formation of ``stripes'' in clean maps may also occur, but this phenomenon can be significantly reduced by using the Steer-Dewdney-Ito algorithm (Steer, Dewdney & Ito (1984)) to identify the CLEAN components. Typical IRAM interferometer pointing errors do not have a significant effect on the reconstructed images.

No-reference image quality assessment based on statistics of convolution feature maps

NASA Astrophysics Data System (ADS)

Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo

2018-04-01

We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.

Empty tracks optimization based on Z-Map model

NASA Astrophysics Data System (ADS)

Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao

2017-12-01

For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.

A Voronoi interior adjacency-based approach for generating a contour tree

NASA Astrophysics Data System (ADS)

Chen, Jun; Qiao, Chaofei; Zhao, Renliang

2004-05-01

A contour tree is a good graphical tool for representing the spatial relations of contour lines and has found many applications in map generalization, map annotation, terrain analysis, etc. A new approach for generating contour trees by introducing a Voronoi-based interior adjacency set concept is proposed in this paper. The immediate interior adjacency set is employed to identify all of the children contours of each contour without contour elevations. It has advantages over existing methods such as the point-in-polygon method and the region growing-based method. This new approach can be used for spatial data mining and knowledge discovering, such as the automatic extraction of terrain features and construction of multi-resolution digital elevation model.

Accuracy Improvement of Multi-Axis Systems Based on Laser Correction of Volumetric Geometric Errors

NASA Astrophysics Data System (ADS)

Teleshevsky, V. I.; Sokolov, V. A.; Pimushkin, Ya I.

2018-04-01

The article describes a volumetric geometric errors correction method for CNC- controlled multi-axis systems (machine-tools, CMMs etc.). The Kalman’s concept of “Control and Observation” is used. A versatile multi-function laser interferometer is used as Observer in order to measure machine’s error functions. A systematic error map of machine’s workspace is produced based on error functions measurements. The error map results into error correction strategy. The article proposes a new method of error correction strategy forming. The method is based on error distribution within machine’s workspace and a CNC-program postprocessor. The postprocessor provides minimal error values within maximal workspace zone. The results are confirmed by error correction of precision CNC machine-tools.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

Multimodal Deep Autoencoder for Human Pose Recovery.

PubMed

Hong, Chaoqun; Yu, Jun; Wan, Jian; Tao, Dacheng; Wang, Meng

2015-12-01

Video-based human pose recovery is usually conducted by retrieving relevant poses using image features. In the retrieving process, the mapping between 2D images and 3D poses is assumed to be linear in most of the traditional methods. However, their relationships are inherently non-linear, which limits recovery performance of these methods. In this paper, we propose a novel pose recovery method using non-linear mapping with multi-layered deep neural network. It is based on feature extraction with multimodal fusion and back-propagation deep learning. In multimodal fusion, we construct hypergraph Laplacian with low-rank representation. In this way, we obtain a unified feature description by standard eigen-decomposition of the hypergraph Laplacian matrix. In back-propagation deep learning, we learn a non-linear mapping from 2D images to 3D poses with parameter fine-tuning. The experimental results on three data sets show that the recovery error has been reduced by 20%-25%, which demonstrates the effectiveness of the proposed method.

Reducing the Dynamical Degradation by Bi-Coupling Digital Chaotic Maps

NASA Astrophysics Data System (ADS)

Liu, Lingfeng; Liu, Bocheng; Hu, Hanping; Miao, Suoxia

A chaotic map which is realized on a computer will suffer dynamical degradation. Here, a coupled chaotic model is proposed to reduce the dynamical degradation. In this model, the state variable of one digital chaotic map is used to control the parameter of the other digital map. This coupled model is universal and can be used for all chaotic maps. In this paper, two coupled models (one is coupled by two logistic maps, the other is coupled by Chebyshev map and Baker map) are performed, and the numerical experiments show that the performances of these two coupled chaotic maps are greatly improved. Furthermore, a simple pseudorandom bit generator (PRBG) based on coupled digital logistic maps is proposed as an application for our method.

Design and application of star map simulation system for star sensors

NASA Astrophysics Data System (ADS)

Wu, Feng; Shen, Weimin; Zhu, Xifang; Chen, Yuheng; Xu, Qinquan

2013-12-01

Modern star sensors are powerful to measure attitude automatically which assure a perfect performance of spacecrafts. They achieve very accurate attitudes by applying algorithms to process star maps obtained by the star camera mounted on them. Therefore, star maps play an important role in designing star cameras and developing procession algorithms. Furthermore, star maps supply significant supports to exam the performance of star sensors completely before their launch. However, it is not always convenient to supply abundant star maps by taking pictures of the sky. Thus, star map simulation with the aid of computer attracts a lot of interests by virtue of its low price and good convenience. A method to simulate star maps by programming and extending the function of the optical design program ZEMAX is proposed. The star map simulation system is established. Firstly, based on analyzing the working procedures of star sensors to measure attitudes and the basic method to design optical system by ZEMAX, the principle of simulating star sensor imaging is given out in detail. The theory about adding false stars and noises, and outputting maps is discussed and the corresponding approaches are proposed. Then, by external programming, the star map simulation program is designed and produced. Its user interference and operation are introduced. Applications of star map simulation method in evaluating optical system, star image extraction algorithm and star identification algorithm, and calibrating system errors are presented completely. It was proved that the proposed simulation method provides magnificent supports to the study on star sensors, and improves the performance of star sensors efficiently.

Mapping from Space - Ontology Based Map Production Using Satellite Imageries

NASA Astrophysics Data System (ADS)

Asefpour Vakilian, A.; Momeni, M.

2013-09-01

Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83%. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7%. Results showed that vegetation cover and water features have been extracted completely (100%) and about 71% of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.

Mapping from Space - Ontology Based Map Production Using Satellite Imageries

NASA Astrophysics Data System (ADS)

Asefpour Vakilian, A.; Momeni, M.

2013-09-01

Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83 %. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7 %. Results showed that vegetation cover and water features have been extracted completely (100 %) and about 71 % of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.

Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data.

PubMed

Dalponte, Michele; Coomes, David A

2016-10-01

Forests are a major component of the global carbon cycle, and accurate estimation of forest carbon stocks and fluxes is important in the context of anthropogenic global change. Airborne laser scanning (ALS) data sets are increasingly recognized as outstanding data sources for high-fidelity mapping of carbon stocks at regional scales.We develop a tree-centric approach to carbon mapping, based on identifying individual tree crowns (ITCs) and species from airborne remote sensing data, from which individual tree carbon stocks are calculated. We identify ITCs from the laser scanning point cloud using a region-growing algorithm and identifying species from airborne hyperspectral data by machine learning. For each detected tree, we predict stem diameter from its height and crown-width estimate. From that point on, we use well-established approaches developed for field-based inventories: above-ground biomasses of trees are estimated using published allometries and summed within plots to estimate carbon density.We show this approach is highly reliable: tests in the Italian Alps demonstrated a close relationship between field- and ALS-based estimates of carbon stocks ( r 2  = 0·98). Small trees are invisible from the air, and a correction factor is required to accommodate this effect.An advantage of the tree-centric approach over existing area-based methods is that it can produce maps at any scale and is fundamentally based on field-based inventory methods, making it intuitive and transparent. Airborne laser scanning, hyperspectral sensing and computational power are all advancing rapidly, making it increasingly feasible to use ITC approaches for effective mapping of forest carbon density also inside wider carbon mapping programs like REDD++.

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI.

PubMed

Mehranian, Abolfazl; Arabi, Hossein; Zaidi, Habib

2016-04-15

In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlas-registration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI. Fourteen patients referred for diagnostic MRI and (18)F-FDG PET/CT brain scans were included in this comparative study. For each study, PET images were reconstructed using four different attenuation maps derived from CT-based AC (CTAC) serving as reference, standard 3-class MR-segmentation, atlas-registration and emission-based AC methods. To generate 3-class attenuation maps, T1-weighted MRI images were segmented into background air, fat and soft-tissue classes followed by assignment of constant linear attenuation coefficients of 0, 0.0864 and 0.0975 cm(-1) to each class, respectively. A robust atlas-registration based AC method was developed for pseudo-CT generation using local weighted fusion of atlases based on their morphological similarity to target MR images. Our recently proposed MRI-guided maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm was employed to estimate the attenuation map from TOF emission data. The performance of the different AC algorithms in terms of prediction of bones and quantification of PET tracer uptake was objectively evaluated with respect to reference CTAC maps and CTAC-PET images. Qualitative evaluation showed that the MLAA-AC method could sparsely estimate bones and accurately differentiate them from air cavities. It was found that the atlas-AC method can accurately predict bones with variable errors in defining air cavities. Quantitative assessment of bone extraction accuracy based on Dice similarity coefficient (DSC) showed that MLAA-AC and atlas-AC resulted in DSC mean values of 0.79 and 0.92, respectively, in all patients. The MLAA-AC and atlas-AC methods predicted mean linear attenuation coefficients of 0.107 and 0.134 cm(-1), respectively, for the skull compared to reference CTAC mean value of 0.138cm(-1). The evaluation of the relative change in tracer uptake within 32 distinct regions of the brain with respect to CTAC PET images showed that the 3-class MRAC, MLAA-AC and atlas-AC methods resulted in quantification errors of -16.2 ± 3.6%, -13.3 ± 3.3% and 1.0 ± 3.4%, respectively. Linear regression and Bland-Altman concordance plots showed that both 3-class MRAC and MLAA-AC methods result in a significant systematic bias in PET tracer uptake, while the atlas-AC method results in a negligible bias. The standard 3-class MRAC method significantly underestimated cerebral PET tracer uptake. While current state-of-the-art MLAA-AC methods look promising, they were unable to noticeably reduce quantification errors in the context of brain imaging. Conversely, the proposed atlas-AC method provided the most accurate attenuation maps, and thus the lowest quantification bias. Copyright © 2016 Elsevier Inc. All rights reserved.

Rapid genotyping by low-coverage resequencing to construct genetic linkage maps of fungi: a case study in Lentinula edodes

PubMed Central

2013-01-01

Background Genetic linkage maps are important tools in breeding programmes and quantitative trait analyses. Traditional molecular markers used for genotyping are limited in throughput and efficiency. The advent of next-generation sequencing technologies has facilitated progeny genotyping and genetic linkage map construction in the major grains. However, the applicability of the approach remains untested in the fungal system. Findings Shiitake mushroom, Lentinula edodes, is a basidiomycetous fungus that represents one of the most popular cultivated edible mushrooms. Here, we developed a rapid genotyping method based on low-coverage (~0.5 to 1.5-fold) whole-genome resequencing. We used the approach to genotype 20 single-spore isolates derived from L. edodes strain L54 and constructed the first high-density sequence-based genetic linkage map of L. edodes. The accuracy of the proposed genotyping method was verified experimentally with results from mating compatibility tests and PCR-single-strand conformation polymorphism on a few known genes. The linkage map spanned a total genetic distance of 637.1 cM and contained 13 linkage groups. Two hundred sequence-based markers were placed on the map, with an average marker spacing of 3.4 cM. The accuracy of the map was confirmed by comparing with previous maps the locations of known genes such as matA and matB. Conclusions We used the shiitake mushroom as an example to provide a proof-of-principle that low-coverage resequencing could allow rapid genotyping of basidiospore-derived progenies, which could in turn facilitate the construction of high-density genetic linkage maps of basidiomycetous fungi for quantitative trait analyses and improvement of genome assembly. PMID:23915543

Usability Evaluation of Public Web Mapping Sites

NASA Astrophysics Data System (ADS)

Wang, C.

2014-04-01

Web mapping sites are interactive maps that are accessed via Webpages. With the rapid development of Internet and Geographic Information System (GIS) field, public web mapping sites are not foreign to people. Nowadays, people use these web mapping sites for various reasons, in that increasing maps and related map services of web mapping sites are freely available for end users. Thus, increased users of web mapping sites led to more usability studies. Usability Engineering (UE), for instance, is an approach for analyzing and improving the usability of websites through examining and evaluating an interface. In this research, UE method was employed to explore usability problems of four public web mapping sites, analyze the problems quantitatively and provide guidelines for future design based on the test results. Firstly, the development progress for usability studies were described, and simultaneously several usability evaluation methods such as Usability Engineering (UE), User-Centered Design (UCD) and Human-Computer Interaction (HCI) were generally introduced. Then the method and procedure of experiments for the usability test were presented in detail. In this usability evaluation experiment, four public web mapping sites (Google Maps, Bing maps, Mapquest, Yahoo Maps) were chosen as the testing websites. And 42 people, who having different GIS skills (test users or experts), gender (male or female), age and nationality, participated in this test to complete the several test tasks in different teams. The test comprised three parts: a pretest background information questionnaire, several test tasks for quantitative statistics and progress analysis, and a posttest questionnaire. The pretest and posttest questionnaires focused on gaining the verbal explanation of their actions qualitatively. And the design for test tasks targeted at gathering quantitative data for the errors and problems of the websites. Then, the results mainly from the test part were analyzed. The success rate from different public web mapping sites was calculated and compared, and displayed by the means of diagram. And the answers from questionnaires were also classified and organized in this part. Moreover, based on the analysis, this paper expands the discussion about the layout, map visualization, map tools, search logic and etc. Finally, this paper closed with some valuable guidelines and suggestions for the design of public web mapping sites. Also, limitations for this research stated in the end.

Direct estimation of tracer-kinetic parameter maps from highly undersampled brain dynamic contrast enhanced MRI.

PubMed

Guo, Yi; Lingala, Sajan Goud; Zhu, Yinghua; Lebel, R Marc; Nayak, Krishna S

2017-10-01

The purpose of this work was to develop and evaluate a T 1 -weighted dynamic contrast enhanced (DCE) MRI methodology where tracer-kinetic (TK) parameter maps are directly estimated from undersampled (k,t)-space data. The proposed reconstruction involves solving a nonlinear least squares optimization problem that includes explicit use of a full forward model to convert parameter maps to (k,t)-space, utilizing the Patlak TK model. The proposed scheme is compared against an indirect method that creates intermediate images by parallel imaging and compressed sensing before to TK modeling. Thirteen fully sampled brain tumor DCE-MRI scans with 5-second temporal resolution are retrospectively undersampled at rates R = 20, 40, 60, 80, and 100 for each dynamic frame. TK maps are quantitatively compared based on root mean-squared-error (rMSE) and Bland-Altman analysis. The approach is also applied to four prospectively R = 30 undersampled whole-brain DCE-MRI data sets. In the retrospective study, the proposed method performed statistically better than indirect method at R ≥ 80 for all 13 cases. This approach provided restoration of TK parameter values with less errors in tumor regions of interest, an improvement compared to a state-of-the-art indirect method. Applied prospectively, the proposed method provided whole-brain, high-resolution TK maps with good image quality. Model-based direct estimation of TK maps from k,t-space DCE-MRI data is feasible and is compatible up to 100-fold undersampling. Magn Reson Med 78:1566-1578, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Object-oriented classification of drumlins from digital elevation models

NASA Astrophysics Data System (ADS)

Saha, Kakoli

Drumlins are common elements of glaciated landscapes which are easily identified by their distinct morphometric characteristics including shape, length/width ratio, elongation ratio, and uniform direction. To date, most researchers have mapped drumlins by tracing contours on maps, or through on-screen digitization directly on top of hillshaded digital elevation models (DEMs). This paper seeks to utilize the unique morphometric characteristics of drumlins and investigates automated extraction of the landforms as objects from DEMs by Definiens Developer software (V.7), using the 30 m United States Geological Survey National Elevation Dataset DEM as input. The Chautauqua drumlin field in Pennsylvania and upstate New York, USA was chosen as a study area. As the study area is huge (approximately covers 2500 sq.km. of area), small test areas were selected for initial testing of the method. Individual polygons representing the drumlins were extracted from the elevation data set by automated recognition, using Definiens' Multiresolution Segmentation tool, followed by rule-based classification. Subsequently parameters such as length, width and length-width ratio, perimeter and area were measured automatically. To test the accuracy of the method, a second base map was produced by manual on-screen digitization of drumlins from topographic maps and the same morphometric parameters were extracted from the mapped landforms using Definiens Developer. Statistical comparison showed a high agreement between the two methods confirming that object-oriented classification for extraction of drumlins can be used for mapping these landforms. The proposed method represents an attempt to solve the problem by providing a generalized rule-set for mass extraction of drumlins. To check that the automated extraction process was next applied to a larger area. Results showed that the proposed method is as successful for the bigger area as it was for the smaller test areas.

Mapping cell-specific functional connections in the mouse brain using ChR2-evoked hemodynamics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael; Lee, Jin-Moo; Culver, Joseph P.

2017-02-01

Functional magnetic resonance imaging (fMRI) has transformed our understanding of the brain's functional organization. However, mapping subunits of a functional network using hemoglobin alone presents several disadvantages. Evoked and spontaneous hemodynamic fluctuations reflect ensemble activity from several populations of neurons making it difficult to discern excitatory vs inhibitory network activity. Still, blood-based methods of brain mapping remain powerful because hemoglobin provides endogenous contrast in all mammalian brains. To add greater specificity to hemoglobin assays, we integrated optical intrinsic signal(OIS) imaging with optogenetic stimulation to create an Opto-OIS mapping tool that combines the cell-specificity of optogenetics with label-free, hemoglobin imaging. Before mapping, titrated photostimuli determined which stimulus parameters elicited linear hemodynamic responses in the cortex. Optimized stimuli were then scanned over the left hemisphere to create a set of optogenetically-defined effective connectivity (Opto-EC) maps. For many sites investigated, Opto-EC maps exhibited higher spatial specificity than those determined using spontaneous hemodynamic fluctuations. For example, resting-state functional connectivity (RS-FC) patterns exhibited widespread ipsilateral connectivity while Opto-EC maps contained distinct short- and long-range constellations of ipsilateral connectivity. Further, RS-FC maps were usually symmetric about midline while Opto-EC maps displayed more heterogeneous contralateral homotopic connectivity. Both Opto-EC and RS-FC patterns were compared to mouse connectivity data from the Allen Institute. Unlike RS-FC maps, Thy1-based maps collected in awake, behaving mice closely recapitulated the connectivity structure derived using ex vivo anatomical tracer methods. Opto-OIS mapping could be a powerful tool for understanding cellular and molecular contributions to network dynamics and processing in the mouse brain.

Big Science, Nano Science?: Mapping the Evolution and Socio-Cognitive Structure of Nanoscience/Nanotechnology Using Mixed Methods

ERIC Educational Resources Information Center

Milojevic, Stasa

2009-01-01

This study examines the development of nanoscience/nanotechnology over a 35 year period (1970-2004) by mapping its social and cognitive structures using social network analysis, bibliometrics and document analysis, and following their changes in time. Mapping is performed based on 580,000 journal articles, 240,000 patents and 53,000 research…

[The automatic iris map overlap technology in computer-aided iridiagnosis].

PubMed

He, Jia-feng; Ye, Hu-nian; Ye, Miao-yuan

2002-11-01

In the paper, iridology and computer-aided iridiagnosis technologies are briefly introduced and the extraction method of the collarette contour is then investigated. The iris map can be overlapped on the original iris image based on collarette contour extraction. The research on collarette contour extraction and iris map overlap is of great importance to computer-aided iridiagnosis technologies.

Texture mapping via optimal mass transport.

PubMed

Dominitz, Ayelet; Tannenbaum, Allen

2010-01-01

In this paper, we present a novel method for texture mapping of closed surfaces. Our method is based on the technique of optimal mass transport (also known as the "earth-mover's metric"). This is a classical problem that concerns determining the optimal way, in the sense of minimal transportation cost, of moving a pile of soil from one site to another. In our context, the resulting mapping is area preserving and minimizes angle distortion in the optimal mass sense. Indeed, we first begin with an angle-preserving mapping (which may greatly distort area) and then correct it using the mass transport procedure derived via a certain gradient flow. In order to obtain fast convergence to the optimal mapping, we incorporate a multiresolution scheme into our flow. We also use ideas from discrete exterior calculus in our computations.

Thermal Spray Maps: Material Genomics of Processing Technologies

NASA Astrophysics Data System (ADS)

Ang, Andrew Siao Ming; Sanpo, Noppakun; Sesso, Mitchell L.; Kim, Sun Yung; Berndt, Christopher C.

2013-10-01

There is currently no method whereby material properties of thermal spray coatings may be predicted from fundamental processing inputs such as temperature-velocity correlations. The first step in such an important understanding would involve establishing a foundation that consolidates the thermal spray literature so that known relationships could be documented and any trends identified. This paper presents a method to classify and reorder thermal spray data so that relationships and correlations between competing processes and materials can be identified. Extensive data mining of published experimental work was performed to create thermal spray property-performance maps, known as "TS maps" in this work. Six TS maps will be presented. The maps are based on coating characteristics of major importance; i.e., porosity, microhardness, adhesion strength, and the elastic modulus of thermal spray coatings.

GIS based optimal impervious surface map generation using various spatial data for urban nonpoint source management.

PubMed

Lee, Cholyoung; Kim, Kyehyun; Lee, Hyuk

2018-01-15

Impervious surfaces are mainly artificial structures such as rooftops, roads, and parking lots that are covered by impenetrable materials. These surfaces are becoming the major causes of nonpoint source (NPS) pollution in urban areas. The rapid progress of urban development is increasing the total amount of impervious surfaces and NPS pollution. Therefore, many cities worldwide have adopted a stormwater utility fee (SUF) that generates funds needed to manage NPS pollution. The amount of SUF is estimated based on the impervious ratio, which is calculated by dividing the total impervious surface area by the net area of an individual land parcel. Hence, in order to identify the exact impervious ratio, large-scale impervious surface maps (ISMs) are necessary. This study proposes and assesses various methods for generating large-scale ISMs for urban areas by using existing GIS data. Bupyeong-gu, a district in the city of Incheon, South Korea, was selected as the study area. Spatial data that were freely offered by national/local governments in S. Korea were collected. First, three types of ISMs were generated by using the land-cover map, digital topographic map, and orthophotographs, to validate three methods that had been proposed conceptually by Korea Environment Corporation. Then, to generate an ISM of higher accuracy, an integration method using all data was proposed. Error matrices were made and Kappa statistics were calculated to evaluate the accuracy. Overlay analyses were performed to examine the distribution of misclassified areas. From the results, the integration method delivered the highest accuracy (Kappa statistic of 0.99) compared to the three methods that use a single type of spatial data. However, a longer production time and higher cost were limiting factors. Among the three methods using a single type of data, the land-cover map showed the highest accuracy with a Kappa statistic of 0.91. Thus, it was judged that the mapping method using the land-cover map is more appropriate than the others. In conclusion, it is desirable to apply the integration method when generating the ISM with the highest accuracy. However, if time and cost are constrained, it would be effective to primarily use the land-cover map. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visual attention based bag-of-words model for image classification

NASA Astrophysics Data System (ADS)

Wang, Qiwei; Wan, Shouhong; Yue, Lihua; Wang, Che

2014-04-01

Bag-of-words is a classical method for image classification. The core problem is how to count the frequency of the visual words and what visual words to select. In this paper, we propose a visual attention based bag-of-words model (VABOW model) for image classification task. The VABOW model utilizes visual attention method to generate a saliency map, and uses the saliency map as a weighted matrix to instruct the statistic process for the frequency of the visual words. On the other hand, the VABOW model combines shape, color and texture cues and uses L1 regularization logistic regression method to select the most relevant and most efficient features. We compare our approach with traditional bag-of-words based method on two datasets, and the result shows that our VABOW model outperforms the state-of-the-art method for image classification.

Regional geochemical maps of the Tonopah 1 degree by 2 degrees Quadrangle, Nevada, based on samples of stream sediment and nonmagnetic heavy-mineral concentrate

USGS Publications Warehouse

Nash, J.T.; Siems, D.F.

1988-01-01

The geochemical maps in this report are based on analytical results reported by Fairfield and others (1985), Hill and others (1986), and Siems and others (1986). These reports also describe the sample preparation and analytical methods and provide information on the location of the sample sites.

Mapping a Strategic Plan for Health: Community-Based Participatory Research with Underserved, Low-Income, Urban Neighborhoods

ERIC Educational Resources Information Center

Zandee, Gail

2012-01-01

Since 2002, community-based participatory research methods have been used by the Calvin College Nursing Department to map out a strategic health plan for three urban, low-income, underserved neighborhoods. Nine focus groups and 449 door-to-door health surveys were completed across the three urban neighborhoods between 2002 and 2004. Neighborhood…

Signal digitizing system and method based on amplitude-to-time optical mapping

DOEpatents

Chou, Jason; Bennett, Corey V; Hernandez, Vince

2015-01-13

A signal digitizing system and method based on analog-to-time optical mapping, optically maps amplitude information of an analog signal of interest first into wavelength information using an amplitude tunable filter (ATF) to impress spectral changes induced by the amplitude of the analog signal onto a carrier signal, i.e. a train of optical pulses, and next from wavelength information to temporal information using a dispersive element so that temporal information representing the amplitude information is encoded in the time domain in the carrier signal. Optical-to-electrical conversion of the optical pulses into voltage waveforms and subsequently digitizing the voltage waveforms into a digital image enables the temporal information to be resolved and quantized in the time domain. The digital image may them be digital signal processed to digitally reconstruct the analog signal based on the temporal information with high fidelity.

Systems and Methods for Data Visualization Using Three-Dimensional Displays

NASA Technical Reports Server (NTRS)

Davidoff, Scott (Inventor); Djorgovski, Stanislav G. (Inventor); Estrada, Vicente (Inventor); Donalek, Ciro (Inventor)

2017-01-01

Data visualization systems and methods for generating 3D visualizations of a multidimensional data space are described. In one embodiment a 3D data visualization application directs a processing system to: load a set of multidimensional data points into a visualization table; create representations of a set of 3D objects corresponding to the set of data points; receive mappings of data dimensions to visualization attributes; determine the visualization attributes of the set of 3D objects based upon the selected mappings of data dimensions to 3D object attributes; update a visibility dimension in the visualization table for each of the plurality of 3D object to reflect the visibility of each 3D object based upon the selected mappings of data dimensions to visualization attributes; and interactively render 3D data visualizations of the 3D objects within the virtual space from viewpoints determined based upon received user input.

Characterization of a subwavelength-scale 3D void structure using the FDTD-based confocal laser scanning microscopic image mapping technique.

PubMed

Choi, Kyongsik; Chon, James W; Gu, Min; Lee, Byoungho

2007-08-20

In this paper, a simple confocal laser scanning microscopic (CLSM) image mapping technique based on the finite-difference time domain (FDTD) calculation has been proposed and evaluated for characterization of a subwavelength-scale three-dimensional (3D) void structure fabricated inside polymer matrix. The FDTD simulation method adopts a focused Gaussian beam incident wave, Berenger's perfectly matched layer absorbing boundary condition, and the angular spectrum analysis method. Through the well matched simulation and experimental results of the xz-scanned 3D void structure, we first characterize the exact position and the topological shape factor of the subwavelength-scale void structure, which was fabricated by a tightly focused ultrashort pulse laser. The proposed CLSM image mapping technique based on the FDTD can be widely applied from the 3D near-field microscopic imaging, optical trapping, and evanescent wave phenomenon to the state-of-the-art bio- and nanophotonics.

Bladder cancer mapping in Libya based on standardized morbidity ratio and log-normal model

NASA Astrophysics Data System (ADS)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-05-01

Disease mapping contains a set of statistical techniques that detail maps of rates based on estimated mortality, morbidity, and prevalence. A traditional approach to measure the relative risk of the disease is called Standardized Morbidity Ratio (SMR). It is the ratio of an observed and expected number of accounts in an area, which has the greatest uncertainty if the disease is rare or if geographical area is small. Therefore, Bayesian models or statistical smoothing based on Log-normal model are introduced which might solve SMR problem. This study estimates the relative risk for bladder cancer incidence in Libya from 2006 to 2007 based on the SMR and log-normal model, which were fitted to data using WinBUGS software. This study starts with a brief review of these models, starting with the SMR method and followed by the log-normal model, which is then applied to bladder cancer incidence in Libya. All results are compared using maps and tables. The study concludes that the log-normal model gives better relative risk estimates compared to the classical method. The log-normal model has can overcome the SMR problem when there is no observed bladder cancer in an area.

Flood Extent Mapping Using Dual-Polarimetric SENTINEL-1 Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

Jo, M.-J.; Osmanoglu, B.; Zhang, B.; Wdowinski, S.

2018-04-01

Rapid generation of synthetic aperture radar (SAR) based flood extent maps provide valuable data in disaster response efforts thanks to the cloud penetrating ability of microwaves. We present a method using dual-polarimetric SAR imagery acquired on Sentinel-1a/b satellites. A false-colour map is generated using pre- and post- disaster imagery, allowing operators to distinguish between existing standing water pre-flooding, and recently flooded areas. The method works best in areas of standing water and provides mixed results in urban areas. A flood depth map is also estimated by using an external DEM. We will present the methodology, it's estimated accuracy as well as investigations into improving the response in urban areas.

Mapping yeast origins of replication via single-stranded DNA detection.

PubMed

Feng, Wenyi; Raghuraman, M K; Brewer, Bonita J

2007-02-01

Studies in th Saccharomyces cerevisiae have provided a framework for understanding how eukaryotic cells replicate their chromosomal DNA to ensure faithful transmission of genetic information to their daughter cells. In particular, S. cerevisiae is the first eukaryote to have its origins of replication mapped on a genomic scale, by three independent groups using three different microarray-based approaches. Here we describe a new technique of origin mapping via detection of single-stranded DNA in yeast. This method not only identified the majority of previously discovered origins, but also detected new ones. We have also shown that this technique can identify origins in Schizosaccharomyces pombe, illustrating the utility of this method for origin mapping in other eukaryotes.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps

PubMed Central

Singharoy, Abhishek; Teo, Ivan; McGreevy, Ryan; Stone, John E; Zhao, Jianhua; Schulten, Klaus

2016-01-01

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services. DOI: http://dx.doi.org/10.7554/eLife.16105.001 PMID:27383269

Acoustic methods for cavitation mapping in biomedical applications

NASA Astrophysics Data System (ADS)

Wan, M.; Xu, S.; Ding, T.; Hu, H.; Liu, R.; Bai, C.; Lu, S.

2015-12-01

In recent years, cavitation is increasingly utilized in a wide range of applications in biomedical field. Monitoring the spatial-temporal evolution of cavitation bubbles is of great significance for efficiency and safety in biomedical applications. In this paper, several acoustic methods for cavitation mapping proposed or modified on the basis of existing work will be presented. The proposed novel ultrasound line-by-line/plane-by-plane method can depict cavitation bubbles distribution with high spatial and temporal resolution and may be developed as a potential standard 2D/3D cavitation field mapping method. The modified ultrafast active cavitation mapping based upon plane wave transmission and reception as well as bubble wavelet and pulse inversion technique can apparently enhance the cavitation to tissue ratio in tissue and further assist in monitoring the cavitation mediated therapy with good spatial and temporal resolution. The methods presented in this paper will be a foundation to promote the research and development of cavitation imaging in non-transparent medium.

Navigating 3D electron microscopy maps with EM-SURFER.

PubMed

Esquivel-Rodríguez, Juan; Xiong, Yi; Han, Xusi; Guang, Shuomeng; Christoffer, Charles; Kihara, Daisuke

2015-05-30

The Electron Microscopy DataBank (EMDB) is growing rapidly, accumulating biological structural data obtained mainly by electron microscopy and tomography, which are emerging techniques for determining large biomolecular complex and subcellular structures. Together with the Protein Data Bank (PDB), EMDB is becoming a fundamental resource of the tertiary structures of biological macromolecules. To take full advantage of this indispensable resource, the ability to search the database by structural similarity is essential. However, unlike high-resolution structures stored in PDB, methods for comparing low-resolution electron microscopy (EM) density maps in EMDB are not well established. We developed a computational method for efficiently searching low-resolution EM maps. The method uses a compact fingerprint representation of EM maps based on the 3D Zernike descriptor, which is derived from a mathematical series expansion for EM maps that are considered as 3D functions. The method is implemented in a web server named EM-SURFER, which allows users to search against the entire EMDB in real-time. EM-SURFER compares the global shapes of EM maps. Examples of search results from different types of query structures are discussed. We developed EM-SURFER, which retrieves structurally relevant matches for query EM maps from EMDB within seconds. The unique capability of EM-SURFER to detect 3D shape similarity of low-resolution EM maps should prove invaluable in structural biology.

Depth estimation and camera calibration of a focused plenoptic camera for visual odometry

NASA Astrophysics Data System (ADS)

Zeller, Niclas; Quint, Franz; Stilla, Uwe

2016-08-01

This paper presents new and improved methods of depth estimation and camera calibration for visual odometry with a focused plenoptic camera. For depth estimation we adapt an algorithm previously used in structure-from-motion approaches to work with images of a focused plenoptic camera. In the raw image of a plenoptic camera, scene patches are recorded in several micro-images under slightly different angles. This leads to a multi-view stereo-problem. To reduce the complexity, we divide this into multiple binocular stereo problems. For each pixel with sufficient gradient we estimate a virtual (uncalibrated) depth based on local intensity error minimization. The estimated depth is characterized by the variance of the estimate and is subsequently updated with the estimates from other micro-images. Updating is performed in a Kalman-like fashion. The result of depth estimation in a single image of the plenoptic camera is a probabilistic depth map, where each depth pixel consists of an estimated virtual depth and a corresponding variance. Since the resulting image of the plenoptic camera contains two plains: the optical image and the depth map, camera calibration is divided into two separate sub-problems. The optical path is calibrated based on a traditional calibration method. For calibrating the depth map we introduce two novel model based methods, which define the relation of the virtual depth, which has been estimated based on the light-field image, and the metric object distance. These two methods are compared to a well known curve fitting approach. Both model based methods show significant advantages compared to the curve fitting method. For visual odometry we fuse the probabilistic depth map gained from one shot of the plenoptic camera with the depth data gained by finding stereo correspondences between subsequent synthesized intensity images of the plenoptic camera. These images can be synthesized totally focused and thus finding stereo correspondences is enhanced. In contrast to monocular visual odometry approaches, due to the calibration of the individual depth maps, the scale of the scene can be observed. Furthermore, due to the light-field information better tracking capabilities compared to the monocular case can be expected. As result, the depth information gained by the plenoptic camera based visual odometry algorithm proposed in this paper has superior accuracy and reliability compared to the depth estimated from a single light-field image.

A two-dimensional matrix image based feature extraction method for classification of sEMG: A comparative analysis based on SVM, KNN and RBF-NN.

PubMed

Wen, Tingxi; Zhang, Zhongnan; Qiu, Ming; Zeng, Ming; Luo, Weizhen

2017-01-01

The computer mouse is an important human-computer interaction device. But patients with physical finger disability are unable to operate this device. Surface EMG (sEMG) can be monitored by electrodes on the skin surface and is a reflection of the neuromuscular activities. Therefore, we can control limbs auxiliary equipment by utilizing sEMG classification in order to help the physically disabled patients to operate the mouse. To develop a new a method to extract sEMG generated by finger motion and apply novel features to classify sEMG. A window-based data acquisition method was presented to extract signal samples from sEMG electordes. Afterwards, a two-dimensional matrix image based feature extraction method, which differs from the classical methods based on time domain or frequency domain, was employed to transform signal samples to feature maps used for classification. In the experiments, sEMG data samples produced by the index and middle fingers at the click of a mouse button were separately acquired. Then, characteristics of the samples were analyzed to generate a feature map for each sample. Finally, the machine learning classification algorithms (SVM, KNN, RBF-NN) were employed to classify these feature maps on a GPU. The study demonstrated that all classifiers can identify and classify sEMG samples effectively. In particular, the accuracy of the SVM classifier reached up to 100%. The signal separation method is a convenient, efficient and quick method, which can effectively extract the sEMG samples produced by fingers. In addition, unlike the classical methods, the new method enables to extract features by enlarging sample signals' energy appropriately. The classical machine learning classifiers all performed well by using these features.

Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets

PubMed Central

Cha, Kenny H.; Hadjiiski, Lubomir; Samala, Ravi K.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.

2016-01-01

Purpose: The authors are developing a computerized system for bladder segmentation in CT urography (CTU) as a critical component for computer-aided detection of bladder cancer. Methods: A deep-learning convolutional neural network (DL-CNN) was trained to distinguish between the inside and the outside of the bladder using 160 000 regions of interest (ROI) from CTU images. The trained DL-CNN was used to estimate the likelihood of an ROI being inside the bladder for ROIs centered at each voxel in a CTU case, resulting in a likelihood map. Thresholding and hole-filling were applied to the map to generate the initial contour for the bladder, which was then refined by 3D and 2D level sets. The segmentation performance was evaluated using 173 cases: 81 cases in the training set (42 lesions, 21 wall thickenings, and 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, and 13 normal bladders). The computerized segmentation accuracy using the DL likelihood map was compared to that using a likelihood map generated by Haar features and a random forest classifier, and that using our previous conjoint level set analysis and segmentation system (CLASS) without using a likelihood map. All methods were evaluated relative to the 3D hand-segmented reference contours. Results: With DL-CNN-based likelihood map and level sets, the average volume intersection ratio, average percent volume error, average absolute volume error, average minimum distance, and the Jaccard index for the test set were 81.9% ± 12.1%, 10.2% ± 16.2%, 14.0% ± 13.0%, 3.6 ± 2.0 mm, and 76.2% ± 11.8%, respectively. With the Haar-feature-based likelihood map and level sets, the corresponding values were 74.3% ± 12.7%, 13.0% ± 22.3%, 20.5% ± 15.7%, 5.7 ± 2.6 mm, and 66.7% ± 12.6%, respectively. With our previous CLASS with local contour refinement (LCR) method, the corresponding values were 78.0% ± 14.7%, 16.5% ± 16.8%, 18.2% ± 15.0%, 3.8 ± 2.3 mm, and 73.9% ± 13.5%, respectively. Conclusions: The authors demonstrated that the DL-CNN can overcome the strong boundary between two regions that have large difference in gray levels and provides a seamless mask to guide level set segmentation, which has been a problem for many gradient-based segmentation methods. Compared to our previous CLASS with LCR method, which required two user inputs to initialize the segmentation, DL-CNN with level sets achieved better segmentation performance while using a single user input. Compared to the Haar-feature-based likelihood map, the DL-CNN-based likelihood map could guide the level sets to achieve better segmentation. The results demonstrate the feasibility of our new approach of using DL-CNN in combination with level sets for segmentation of the bladder. PMID:27036584

Semi-automatic mapping of geological Structures using UAV-based photogrammetric data: An image analysis approach

NASA Astrophysics Data System (ADS)

Vasuki, Yathunanthan; Holden, Eun-Jung; Kovesi, Peter; Micklethwaite, Steven

2014-08-01

Recent advances in data acquisition technologies, such as Unmanned Aerial Vehicles (UAVs), have led to a growing interest in capturing high-resolution rock surface images. However, due to the large volumes of data that can be captured in a short flight, efficient analysis of this data brings new challenges, especially the time it takes to digitise maps and extract orientation data. We outline a semi-automated method that allows efficient mapping of geological faults using photogrammetric data of rock surfaces, which was generated from aerial photographs collected by a UAV. Our method harnesses advanced automated image analysis techniques and human data interaction to rapidly map structures and then calculate their dip and dip directions. Geological structures (faults, joints and fractures) are first detected from the primary photographic dataset and the equivalent three dimensional (3D) structures are then identified within a 3D surface model generated by structure from motion (SfM). From this information the location, dip and dip direction of the geological structures are calculated. A structure map generated by our semi-automated method obtained a recall rate of 79.8% when compared against a fault map produced using expert manual digitising and interpretation methods. The semi-automated structure map was produced in 10 min whereas the manual method took approximately 7 h. In addition, the dip and dip direction calculation, using our automated method, shows a mean±standard error of 1.9°±2.2° and 4.4°±2.6° respectively with field measurements. This shows the potential of using our semi-automated method for accurate and efficient mapping of geological structures, particularly from remote, inaccessible or hazardous sites.

Sub-pixel flood inundation mapping from multispectral remotely sensed images based on discrete particle swarm optimization

NASA Astrophysics Data System (ADS)

Li, Linyi; Chen, Yun; Yu, Xin; Liu, Rui; Huang, Chang

2015-03-01

The study of flood inundation is significant to human life and social economy. Remote sensing technology has provided an effective way to study the spatial and temporal characteristics of inundation. Remotely sensed images with high temporal resolutions are widely used in mapping inundation. However, mixed pixels do exist due to their relatively low spatial resolutions. One of the most popular approaches to resolve this issue is sub-pixel mapping. In this paper, a novel discrete particle swarm optimization (DPSO) based sub-pixel flood inundation mapping (DPSO-SFIM) method is proposed to achieve an improved accuracy in mapping inundation at a sub-pixel scale. The evaluation criterion for sub-pixel inundation mapping is formulated. The DPSO-SFIM algorithm is developed, including particle discrete encoding, fitness function designing and swarm search strategy. The accuracy of DPSO-SFIM in mapping inundation at a sub-pixel scale was evaluated using Landsat ETM + images from study areas in Australia and China. The results show that DPSO-SFIM consistently outperformed the four traditional SFIM methods in these study areas. A sensitivity analysis of DPSO-SFIM was also carried out to evaluate its performances. It is hoped that the results of this study will enhance the application of medium-low spatial resolution images in inundation detection and mapping, and thereby support the ecological and environmental studies of river basins.

Universal map for cellular automata

NASA Astrophysics Data System (ADS)

García-Morales, V.

2012-08-01

A universal map is derived for all deterministic 1D cellular automata (CAs) containing no freely adjustable parameters and valid for any alphabet size and any neighborhood range (including non-symmetrical neighborhoods). The map can be extended to an arbitrary number of dimensions and topologies and to arbitrary order in time. Specific CA maps for the famous Conway's Game of Life and Wolfram's 256 elementary CAs are given. An induction method for CAs, based in the universal map, allows mathematical expressions for the orbits of a wide variety of elementary CAs to be systematically derived.

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds.

PubMed

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-06-17

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data.

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds†

PubMed Central

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-01-01

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data. PMID:27322279

Fractal-Based Lightning Channel Length Estimation from Convex-Hull Flash Areas for DC3 Lightning Mapping Array Data

NASA Technical Reports Server (NTRS)

Bruning, Eric C.; Thomas, Ronald J.; Krehbiel, Paul R.; Rison, William; Carey, Larry D.; Koshak, William; Peterson, Harold; MacGorman, Donald R.

2013-01-01

We will use VHF Lightning Mapping Array data to estimate NOx per flash and per unit channel length, including the vertical distribution of channel length. What s the best way to find channel length from VHF sources? This paper presents the rationale for the fractal method, which is closely related to the box-covering method.

Audio Tracking in Noisy Environments by Acoustic Map and Spectral Signature.

PubMed

Crocco, Marco; Martelli, Samuele; Trucco, Andrea; Zunino, Andrea; Murino, Vittorio

2018-05-01

A novel method is proposed for generic target tracking by audio measurements from a microphone array. To cope with noisy environments characterized by persistent and high energy interfering sources, a classification map (CM) based on spectral signatures is calculated by means of a machine learning algorithm. Next, the CM is combined with the acoustic map, describing the spatial distribution of sound energy, in order to obtain a cleaned joint map in which contributions from the disturbing sources are removed. A likelihood function is derived from this map and fed to a particle filter yielding the target location estimation on the acoustic image. The method is tested on two real environments, addressing both speaker and vehicle tracking. The comparison with a couple of trackers, relying on the acoustic map only, shows a sharp improvement in performance, paving the way to the application of audio tracking in real challenging environments.

Improving Signal-to-Noise Ratio in Scanning Transmission Electron Microscopy Energy-Dispersive X-Ray (STEM-EDX) Spectrum Images Using Single-Atomic-Column Cross-Correlation Averaging.

PubMed

Jeong, Jong Seok; Mkhoyan, K Andre

2016-06-01

Acquiring an atomic-resolution compositional map of crystalline specimens has become routine practice, thus opening possibilities for extracting subatomic information from such maps. A key challenge for achieving subatomic precision is the improvement of signal-to-noise ratio (SNR) of compositional maps. Here, we report a simple and reliable solution for achieving high-SNR energy-dispersive X-ray (EDX) spectroscopy spectrum images for individual atomic columns. The method is based on standard cross-correlation aided by averaging of single-column EDX maps with modifications in the reference image. It produces EDX maps with minimal specimen drift, beam drift, and scan distortions. Step-by-step procedures to determine a self-consistent reference map with a discussion on the reliability, stability, and limitations of the method are presented here.

An SPM8-based Approach for Attenuation Correction Combining Segmentation and Non-rigid Template Formation: Application to Simultaneous PET/MR Brain Imaging

PubMed Central

Izquierdo-Garcia, David; Hansen, Adam E.; Förster, Stefan; Benoit, Didier; Schachoff, Sylvia; Fürst, Sebastian; Chen, Kevin T.; Chonde, Daniel B.; Catana, Ciprian

2014-01-01

We present an approach for head MR-based attenuation correction (MR-AC) based on the Statistical Parametric Mapping (SPM8) software that combines segmentation- and atlas-based features to provide a robust technique to generate attenuation maps (µ-maps) from MR data in integrated PET/MR scanners. Methods Coregistered anatomical MR and CT images acquired in 15 glioblastoma subjects were used to generate the templates. The MR images from these subjects were first segmented into 6 tissue classes (gray and white matter, cerebro-spinal fluid, bone and soft tissue, and air), which were then non-rigidly coregistered using a diffeomorphic approach. A similar procedure was used to coregister the anatomical MR data for a new subject to the template. Finally, the CT-like images obtained by applying the inverse transformations were converted to linear attenuation coefficients (LACs) to be used for AC of PET data. The method was validated on sixteen new subjects with brain tumors (N=12) or mild cognitive impairment (N=4) who underwent CT and PET/MR scans. The µ-maps and corresponding reconstructed PET images were compared to those obtained using the gold standard CT-based approach and the Dixon-based method available on the Siemens Biograph mMR scanner. Relative change (RC) images were generated in each case and voxel- and region of interest (ROI)-based analyses were performed. Results The leave-one-out cross-validation analysis of the data from the 15 atlas-generation subjects showed small errors in brain LACs (RC=1.38%±4.52%) compared to the gold standard. Similar results (RC=1.86±4.06%) were obtained from the analysis of the atlas-validation datasets. The voxel- and ROI-based analysis of the corresponding reconstructed PET images revealed quantification errors of 3.87±5.0% and 2.74±2.28%, respectively. The Dixon-based method performed substantially worse (the mean RC values were 13.0±10.25% and 9.38±4.97%, respectively). Areas closer to skull showed the largest improvement. Conclusion We have presented an SPM8-based approach for deriving the head µ-map from MR data to be used for PET AC in integrated PET/MR scanners. Its implementation is straightforward and only requires the morphological data acquired with a single MR sequence. The method is very accurate and robust, combining the strengths of both segmentation- and atlas-based approaches while minimizing their drawbacks. PMID:25278515

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm.

PubMed

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-24

Indoor occupants' positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans' position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization.

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm

PubMed Central

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-01

Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization. PMID:29364188

Forward and backward tone mapping of high dynamic range images based on subband architecture

NASA Astrophysics Data System (ADS)

Bouzidi, Ines; Ouled Zaid, Azza

2015-01-01

This paper presents a novel High Dynamic Range (HDR) tone mapping (TM) system based on sub-band architecture. Standard wavelet filters of Daubechies, Symlets, Coiflets and Biorthogonal were used to estimate the proposed system performance in terms of Low Dynamic Range (LDR) image quality and reconstructed HDR image fidelity. During TM stage, the HDR image is firstly decomposed in sub-bands using symmetrical analysis-synthesis filter bank. The transform coefficients are then rescaled using a predefined gain map. The inverse Tone Mapping (iTM) stage is straightforward. Indeed, the LDR image passes through the same sub-band architecture. But, instead of reducing the dynamic range, the LDR content is boosted to an HDR representation. Moreover, in our TM sheme, we included an optimization module to select the gain map components that minimize the reconstruction error, and consequently resulting in high fidelity HDR content. Comparisons with recent state-of-the-art methods have shown that our method provides better results in terms of visual quality and HDR reconstruction fidelity using objective and subjective evaluations.

Behavior Analysis of Novel Wearable Indoor Mapping System Based on 3D-SLAM.

PubMed

Lagüela, Susana; Dorado, Iago; Gesto, Manuel; Arias, Pedro; González-Aguilera, Diego; Lorenzo, Henrique

2018-03-02

This paper presents a Wearable Prototype for indoor mapping developed by the University of Vigo. The system is based on a Velodyne LiDAR, acquiring points with 16 rays for a simplistic or low-density 3D representation of reality. With this, a Simultaneous Localization and Mapping (3D-SLAM) method is developed for the mapping and generation of 3D point clouds of scenarios deprived from GNSS signal. The quality of the system presented is validated through the comparison with a commercial indoor mapping system, Zeb-Revo, from the company GeoSLAM and with a terrestrial LiDAR, Faro Focus 3D X330. The first is considered as a relative reference with other mobile systems and is chosen due to its use of the same principle for mapping: SLAM techniques based on Robot Operating System (ROS), while the second is taken as ground-truth for the determination of the final accuracy of the system regarding reality. Results show that the accuracy of the system is mainly determined by the accuracy of the sensor, with little increment in the error introduced by the mapping algorithm.

Derivation and application of an analytical rock displacement solution on rectangular cavern wall using the inverse mapping method.

PubMed

Gao, Mingzhong; Yu, Bin; Qiu, Zhiqiang; Yin, Xiangang; Li, Shengwei; Liu, Qiang

2017-01-01

Rectangular caverns are increasingly used in underground engineering projects, the failure mechanism of rectangular cavern wall rock is significantly different as a result of the cross-sectional shape and variations in wall stress distributions. However, the conventional computational method always results in a long-winded computational process and multiple displacement solutions of internal rectangular wall rock. This paper uses a Laurent series complex method to obtain a mapping function expression based on complex variable function theory and conformal transformation. This method is combined with the Schwarz-Christoffel method to calculate the mapping function coefficient and to determine the rectangular cavern wall rock deformation. With regard to the inverse mapping concept, the mapping relation between the polar coordinate system within plane ς and a corresponding unique plane coordinate point inside the cavern wall rock is discussed. The disadvantage of multiple solutions when mapping from the plane to the polar coordinate system is addressed. This theoretical formula is used to calculate wall rock boundary deformation and displacement field nephograms inside the wall rock for a given cavern height and width. A comparison with ANSYS numerical software results suggests that the theoretical solution and numerical solution exhibit identical trends, thereby demonstrating the method's validity. This method greatly improves the computing accuracy and reduces the difficulty in solving for cavern boundary and internal wall rock displacements. The proposed method provides a theoretical guide for controlling cavern wall rock deformation failure.

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.

PubMed

Chen, Wenan; Larrabee, Beth R; Ovsyannikova, Inna G; Kennedy, Richard B; Haralambieva, Iana H; Poland, Gregory A; Schaid, Daniel J

2015-07-01

Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. Copyright © 2015 by the Genetics Society of America.

A stable downward continuation of airborne magnetic data: A case study for mineral prospectivity mapping in Central Iran

NASA Astrophysics Data System (ADS)

Abedi, Maysam; Gholami, Ali; Norouzi, Gholam-Hossain

2013-03-01

Previous studies have shown that a well-known multi-criteria decision making (MCDM) technique called Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE II) to explore porphyry copper deposits can prioritize the ground-based exploratory evidential layers effectively. In this paper, the PROMETHEE II method is applied to airborne geophysical (potassium radiometry and magnetometry) data, geological layers (fault and host rock zones), and various extracted alteration layers from remote sensing images. The central Iranian volcanic-sedimentary belt is chosen for this study. A stable downward continuation method as an inverse problem in the Fourier domain using Tikhonov and edge-preserving regularizations is proposed to enhance magnetic data. Numerical analysis of synthetic models show that the reconstructed magnetic data at the ground surface exhibits significant enhancement compared to the airborne data. The reduced-to-pole (RTP) and the analytic signal filters are applied to the magnetic data to show better maps of the magnetic anomalies. Four remote sensing evidential layers including argillic, phyllic, propylitic and hydroxyl alterations are extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images in order to map the altered areas associated with porphyry copper deposits. Principal component analysis (PCA) based on six Enhanced Thematic Mapper Plus (ETM+) images is implemented to map iron oxide layer. The final mineral prospectivity map based on desired geo-data set indicates adequately matching of high potential zones with previous working mines and copper deposits.

On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates

USGS Publications Warehouse

Singh, Ramesh K.; Senay, Gabriel B.; Velpuri, Naga Manohar; Bohms, Stefanie; Verdin, James P.

2014-01-01

 Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.

Multirisk analysis along the Road 7, Mendoza Province, Argentina

NASA Astrophysics Data System (ADS)

Wick, Emmanuel; Baumann, Valérie; Michoud, Clément; Derron, Marc-Henri; Jaboyedoff, Michel; Rune Lauknes, Tom; Marengo, Hugo; Rosas, Mario

2010-05-01

The National Road 7 crosses Argentina from East to West, linking Buenos Aires to the Chile border. This road is an extremely important corridor crossing the Andes Cordillera, but it is exposed to numerous natural hazards, such as rockfalls, debris flows and snow avalanches. The study area is located in the Mendoza Province, between Potrerillos and Las Cuevas in the Chilean border. This study has for main goals to achieve a regional mapping of geohazards susceptibility along the Road 7 corridor using modern remote sensing and numerical modelling techniques completed by field investigations. The main topics are: - Detection and monitoring of deep-seated gravitational slope deformations by time-series satellite radar interferometry (InSAR) methods. The area of interest is mountainous with almost no vegetation permitting an optimized InSAR processing. Our results are based on applying the small-baseline subset (SBAS) method to a time-series of Envisat ASAR images. - Rockfalls susceptibility mapping is realized using statistical analysis of the slope angle distribution, including external knowledge on the geology and land cover, to detect the potential source areas (quantitative DEM analysis). The run-outs are assessed with numerical methods based on the shallow angle method with Conefall. A second propagation is performed using the alpha-beta methodology (3D numerical modelling) with RAS and is compared to the first one. - Debris flow susceptibility mapping is realized using DF-IGAR to detect starting and spreading areas. Slope, flow accumulations, contributive surfaces, plan curvature, geological and land use dataset are used. The spreading is simulated by a multiple flow algorithm (rules the path that the debris flow will follow) coupled to a run-out distance calculation (energy-based). - Snow avalanches susceptibility mapping is realized using DF-IGAR to map sources areas and propagations. To detect the sources areas, slope, altitude, land-use and minimum surfaces are needed. DF-IGAR simulates the spreading by means of the "Perla" methodology. Furthermore, RAS performs the spreading based on the "alpha-beta" method. All these methods are based on Aster and SRTM DEM (grid 30 m) and observations of both optical and radar satellite imagery (Aster, Quickbird, Worldview, Ikonos, Envisat ASAR) and aerial photographs. Several field campaigns are performed to calibrate the regional models with adapted parameters. Susceptibility maps of the entire area for rockfalls, debris flows and snow avalanches at a scale of 1:100'000 are created. Those maps and the field investigations are cross-checked to identify and prioritize hotspots. It appears that numerous road sectors are subject to highly active phenomena. Some mitigation works already exist but they are often under-dimensioned, inadequate or neglected. Recommendations for priority and realistic mitigation measures along the endangered road sectors identified are proposed.

Usage of Data-Encoded Web Maps with Client Side Color Rendering for Combined Data Access, Visualization and Modeling Purposes

NASA Technical Reports Server (NTRS)

Pliutau, Denis; Prasad, Narashimha S.

2013-01-01

Current approaches to satellite observation data storage and distribution implement separate visualization and data access methodologies which often leads to the need in time consuming data ordering and coding for applications requiring both visual representation as well as data handling and modeling capabilities. We describe an approach we implemented for a data-encoded web map service based on storing numerical data within server map tiles and subsequent client side data manipulation and map color rendering. The approach relies on storing data using the lossless compression Portable Network Graphics (PNG) image data format which is natively supported by web-browsers allowing on-the-fly browser rendering and modification of the map tiles. The method is easy to implement using existing software libraries and has the advantage of easy client side map color modifications, as well as spatial subsetting with physical parameter range filtering. This method is demonstrated for the ASTER-GDEM elevation model and selected MODIS data products and represents an alternative to the currently used storage and data access methods. One additional benefit includes providing multiple levels of averaging due to the need in generating map tiles at varying resolutions for various map magnification levels. We suggest that such merged data and mapping approach may be a viable alternative to existing static storage and data access methods for a wide array of combined simulation, data access and visualization purposes.

Cadastral Positioning Accuracy Improvement: a Case Study in Malaysia

NASA Astrophysics Data System (ADS)

Hashim, N. M.; Omar, A. H.; Omar, K. M.; Abdullah, N. M.; Yatim, M. H. M.

2016-09-01

Cadastral map is a parcel-based information which is specifically designed to define the limitation of boundaries. In Malaysia, the cadastral map is under authority of the Department of Surveying and Mapping Malaysia (DSMM). With the growth of spatial based technology especially Geographical Information System (GIS), DSMM decided to modernize and reform its cadastral legacy datasets by generating an accurate digital based representation of cadastral parcels. These legacy databases usually are derived from paper parcel maps known as certified plan. The cadastral modernization will result in the new cadastral database no longer being based on single and static parcel paper maps, but on a global digital map. Despite the strict process of the cadastral modernization, this reform has raised unexpected queries that remain essential to be addressed. The main focus of this study is to review the issues that have been generated by this transition. The transformed cadastral database should be additionally treated to minimize inherent errors and to fit them to the new satellite based coordinate system with high positional accuracy. This review result will be applied as a foundation for investigation to study the systematic and effectiveness method for Positional Accuracy Improvement (PAI) in cadastral database modernization.

Depth-Based Selective Blurring in Stereo Images Using Accelerated Framework

NASA Astrophysics Data System (ADS)

Mukherjee, Subhayan; Guddeti, Ram Mohana Reddy

2014-09-01

We propose a hybrid method for stereo disparity estimation by combining block and region-based stereo matching approaches. It generates dense depth maps from disparity measurements of only 18 % image pixels (left or right). The methodology involves segmenting pixel lightness values using fast K-Means implementation, refining segment boundaries using morphological filtering and connected components analysis; then determining boundaries' disparities using sum of absolute differences (SAD) cost function. Complete disparity maps are reconstructed from boundaries' disparities. We consider an application of our method for depth-based selective blurring of non-interest regions of stereo images, using Gaussian blur to de-focus users' non-interest regions. Experiments on Middlebury dataset demonstrate that our method outperforms traditional disparity estimation approaches using SAD and normalized cross correlation by up to 33.6 % and some recent methods by up to 6.1 %. Further, our method is highly parallelizable using CPU-GPU framework based on Java Thread Pool and APARAPI with speed-up of 5.8 for 250 stereo video frames (4,096 × 2,304).

Winter wheat mapping combining variations before and after estimated heading dates

NASA Astrophysics Data System (ADS)

Qiu, Bingwen; Luo, Yuhan; Tang, Zhenghong; Chen, Chongcheng; Lu, Difei; Huang, Hongyu; Chen, Yunzhi; Chen, Nan; Xu, Weiming

2017-01-01

Accurate and updated information on winter wheat distribution is vital for food security. The intra-class variability of the temporal profiles of vegetation indices presents substantial challenges to current time series-based approaches. This study developed a new method to identify winter wheat over large regions through a transformation and metric-based approach. First, the trend surfaces were established to identify key phenological parameters of winter wheat based on altitude and latitude with references to crop calendar data from the agro-meteorological stations. Second, two phenology-based indicators were developed based on the EVI2 differences between estimated heading and seedling/harvesting dates and the change amplitudes. These two phenology-based indicators revealed variations during the estimated early and late growth stages. Finally, winter wheat data were extracted based on these two metrics. The winter wheat mapping method was applied to China based on the 250 m 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) 2-band Enhanced Vegetation Index (EVI2) time series datasets. Accuracy was validated with field survey data, agricultural census data, and Landsat-interpreted results in test regions. When evaluated with 653 field survey sites and Landsat image interpreted data, the overall accuracy of MODIS-derived images in 2012-2013 was 92.19% and 88.86%, respectively. The MODIS-derived winter wheat areas accounted for over 82% of the variability at the municipal level when compared with agricultural census data. The winter wheat mapping method developed in this study demonstrates great adaptability to intra-class variability of the vegetation temporal profiles and has great potential for further applications to broader regions and other types of agricultural crop mapping.

Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships.

PubMed

Zhang, Qianqian; Guldbrandtsen, Bernt; Calus, Mario P L; Lund, Mogens Sandø; Sahana, Goutam

2016-08-17

There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared to LMM. Therefore, it is recommended to use rare variant association mapping methods to map rare genetic variants that affect quantitative traits in livestock, such as bovine populations.

Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population

PubMed Central

Serin, Elise A. R.; Snoek, L. B.; Nijveen, Harm; Willems, Leo A. J.; Jiménez-Gómez, Jose M.; Hilhorst, Henk W. M.; Ligterink, Wilco

2017-01-01

High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches. PMID:29259624

Identifying online user reputation in terms of user preference

NASA Astrophysics Data System (ADS)

Dai, Lu; Guo, Qiang; Liu, Xiao-Lu; Liu, Jian-Guo; Zhang, Yi-Cheng

2018-03-01

Identifying online user reputation is significant for online social systems. In this paper, taking into account the preference physics of online user collective behaviors, we present an improved group-based rating method for ranking online user reputation based on the user preference (PGR). All the ratings given by each specific user are mapped to the same rating criteria. By grouping users according to their mapped ratings, the online user reputation is calculated based on the corresponding group sizes. Results for MovieLens and Netflix data sets show that the AUC values of the PGR method can reach 0.9842 (0.9493) and 0.9995 (0.9987) for malicious (random) spammers, respectively, outperforming the results generated by the traditional group-based method, which indicates that the online preference plays an important role for measuring user reputation.

Full-Field Calibration of Color Camera Chromatic Aberration using Absolute Phase Maps.

PubMed

Liu, Xiaohong; Huang, Shujun; Zhang, Zonghua; Gao, Feng; Jiang, Xiangqian

2017-05-06

The refractive index of a lens varies for different wavelengths of light, and thus the same incident light with different wavelengths has different outgoing light. This characteristic of lenses causes images captured by a color camera to display chromatic aberration (CA), which seriously reduces image quality. Based on an analysis of the distribution of CA, a full-field calibration method based on absolute phase maps is proposed in this paper. Red, green, and blue closed sinusoidal fringe patterns are generated, consecutively displayed on an LCD (liquid crystal display), and captured by a color camera from the front viewpoint. The phase information of each color fringe is obtained using a four-step phase-shifting algorithm and optimum fringe number selection method. CA causes the unwrapped phase of the three channels to differ. These pixel deviations can be computed by comparing the unwrapped phase data of the red, blue, and green channels in polar coordinates. CA calibration is accomplished in Cartesian coordinates. The systematic errors introduced by the LCD are analyzed and corrected. Simulated results show the validity of the proposed method and experimental results demonstrate that the proposed full-field calibration method based on absolute phase maps will be useful for practical software-based CA calibration.

Multiband tangent space mapping and feature selection for classification of EEG during motor imagery.

PubMed

Islam, Md Rabiul; Tanaka, Toshihisa; Molla, Md Khademul Islam

2018-05-08

When designing multiclass motor imagery-based brain-computer interface (MI-BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of covariance matrices is an effective technique. This paper aims to introduce a method using TSM for finding accurate operational frequency bands related brain activities associated with MI tasks. A multichannel electroencephalogram (EEG) signal is decomposed into multiple subbands, and tangent features are then estimated on each subband. A mutual information analysis-based effective algorithm is implemented to select subbands containing features capable of improving motor imagery classification accuracy. Thus obtained features of selected subbands are combined to get feature space. A principal component analysis-based approach is employed to reduce the features dimension and then the classification is accomplished by a support vector machine (SVM). Offline analysis demonstrates the proposed multiband tangent space mapping with subband selection (MTSMS) approach outperforms state-of-the-art methods. It acheives the highest average classification accuracy for all datasets (BCI competition dataset 2a, IIIa, IIIb, and dataset JK-HH1). The increased classification accuracy of MI tasks with the proposed MTSMS approach can yield effective implementation of BCI. The mutual information-based subband selection method is implemented to tune operation frequency bands to represent actual motor imagery tasks.

Epitope mapping: the first step in developing epitope-based vaccines.

PubMed

Gershoni, Jonathan M; Roitburd-Berman, Anna; Siman-Tov, Dror D; Tarnovitski Freund, Natalia; Weiss, Yael

2007-01-01

Antibodies are an effective line of defense in preventing infectious diseases. Highly potent neutralizing antibodies can intercept a virus before it attaches to its target cell and, thus, inactivate it. This ability is based on the antibodies' specific recognition of epitopes, the sites of the antigen to which antibodies bind. Thus, understanding the antibody/epitope interaction provides a basis for the rational design of preventive vaccines. It is assumed that immunization with the precise epitope, corresponding to an effective neutralizing antibody, would elicit the generation of similarly potent antibodies in the vaccinee. Such a vaccine would be a 'B-cell epitope-based vaccine', the implementation of which requires the ability to backtrack from a desired antibody to its corresponding epitope. In this article we discuss a range of methods that enable epitope discovery based on a specific antibody. Such a reversed immunological approach is the first step in the rational design of an epitope-based vaccine. Undoubtedly, the gold standard for epitope definition is x-ray analyses of crystals of antigen:antibody complexes. This method provides atomic resolution of the epitope; however, it is not readily applicable to many antigens and antibodies, and requires a very high degree of sophistication and expertise. Most other methods rely on the ability to monitor the binding of the antibody to antigen fragments or mutated variations. In mutagenesis of the antigen, loss of binding due to point modification of an amino acid residue is often considered an indication of an epitope component. In addition, computational combinatorial methods for epitope mapping are also useful. These methods rely on the ability of the antibody of interest to affinity isolate specific short peptides from combinatorial phage display peptide libraries. The peptides are then regarded as leads for the definition of the epitope corresponding to the antibody used to screen the peptide library. For epitope mapping, computational algorithms have been developed, such as Mapitope, which has recently been found to be effective in mapping conformational discontinuous epitopes. The pros and cons of various approaches towards epitope mapping are also discussed.

Spectrally based bathymetric mapping of a dynamic, sand‐bedded channel: Niobrara River, Nebraska, USA

USGS Publications Warehouse

Dilbone, Elizabeth; Legleiter, Carl; Alexander, Jason S.; McElroy, Brandon

2018-01-01

Methods for spectrally based mapping of river bathymetry have been developed and tested in clear‐flowing, gravel‐bed channels, with limited application to turbid, sand‐bed rivers. This study used hyperspectral images and field surveys from the dynamic, sandy Niobrara River to evaluate three depth retrieval methods. The first regression‐based approach, optimal band ratio analysis (OBRA), paired in situ depth measurements with image pixel values to estimate depth. The second approach used ground‐based field spectra to calibrate an OBRA relationship. The third technique, image‐to‐depth quantile transformation (IDQT), estimated depth by linking the cumulative distribution function (CDF) of depth to the CDF of an image‐derived variable. OBRA yielded the lowest depth retrieval mean error (0.005 m) and highest observed versus predicted R2 (0.817). Although misalignment between field and image data did not compromise the performance of OBRA in this study, poor georeferencing could limit regression‐based approaches such as OBRA in dynamic, sand‐bedded rivers. Field spectroscopy‐based depth maps exhibited a mean error with a slight shallow bias (0.068 m) but provided reliable estimates for most of the study reach. IDQT had a strong deep bias but provided informative relative depth maps. Overprediction of depth by IDQT highlights the need for an unbiased sampling strategy to define the depth CDF. Although each of the techniques we tested demonstrated potential to provide accurate depth estimates in sand‐bed rivers, each method also was subject to certain constraints and limitations.

A reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

USGS Publications Warehouse

Raines, G.L.; Mihalasky, M.J.

2002-01-01

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. ?? 2002 International Association for Mathematical Geology.

Stress field modeling of the Carpathian Basin based on compiled tectonic maps

NASA Astrophysics Data System (ADS)

Albert, Gáspár; Ungvári, Zsuzsanna; Szentpéteri, Krisztián

2014-05-01

The estimation of the stress field in the Carpathian Basin is tackled by several authors. Their modeling methods usually based on measurements (borehole-, focal mechanism- and geodesic data) and the result is a possible structural pattern of the region. Our method works indirectly: the analysis is aimed to project a possible 2D stress field over the already mapped/known/compiled lineament pattern. This includes a component-wise interpolation of the tensor-field, which is based on the generated irregular point cloud in the puffer zone of the mapped lineaments. The interpolated values appear on contour and tensor maps, and show the relative stress field of the area. In 2006 Horváth et al. compiled the 'Atlas of the present-day geodynamics of the Pannonian basin'. To test our method we processed the lineaments of the 1:1 500 000 scale 'Map of neotectonic (active) structures' published in this atlas. The geodynamic parameters (i.e. normal, reverse, right- and left lateral strike-slip faults, etc.) of the lines on this map were mostly explained in the legend. We classified the linear elements according to these parameters and created a geo-referenced mapping database. This database contains the polyline sections of the map lineaments as vectors (i.e. line sections), and the directions of the stress field as attributes of these vectors. The directions of the dip-parallel-, strike-parallel- and vertical stress-vectors are calculated from the geodynamical parameters of the line section. Since we created relative stress field properties, the eigenvalues of the vectors were maximized to one. Each point in the point cloud inherits the stress property of the line section, from which it was derived. During the modeling we tried several point-cloud generating- and interpolation methods. The analysis of the interpolated tensor fields revealed that the model was able to reproduce a geodynamic synthesis of the Carpathian Basin, which can be correlated with the synthesis of the Atlas published in 2006. The method was primarily aimed to reconstruct paleo-stress fields. References Horváth, F., Bada, G., Windhoffer, G., Csontos, L., Dombrádi, E., Dövényi, P., Fodor, L., Grenerczy, G., Síkhegyi, F., Szafián, P., Székely, B., Timár, G., Tóth, L., Tóth, T. 2006: Atlas of the present-day geodynamics of the Pannonian basin: Euroconform maps with explanatory text. Magyar Geofizika 47, 133-137.

Representation of DNA sequences in genetic codon context with applications in exon and intron prediction.

PubMed

Yin, Changchuan

2015-04-01

To apply digital signal processing (DSP) methods to analyze DNA sequences, the sequences first must be specially mapped into numerical sequences. Thus, effective numerical mappings of DNA sequences play key roles in the effectiveness of DSP-based methods such as exon prediction. Despite numerous mappings of symbolic DNA sequences to numerical series, the existing mapping methods do not include the genetic coding features of DNA sequences. We present a novel numerical representation of DNA sequences using genetic codon context (GCC) in which the numerical values are optimized by simulation annealing to maximize the 3-periodicity signal to noise ratio (SNR). The optimized GCC representation is then applied in exon and intron prediction by Short-Time Fourier Transform (STFT) approach. The results show the GCC method enhances the SNR values of exon sequences and thus increases the accuracy of predicting protein coding regions in genomes compared with the commonly used 4D binary representation. In addition, this study offers a novel way to reveal specific features of DNA sequences by optimizing numerical mappings of symbolic DNA sequences.

An RBF-based reparameterization method for constrained texture mapping.

PubMed

Yu, Hongchuan; Lee, Tong-Yee; Yeh, I-Cheng; Yang, Xiaosong; Li, Wenxi; Zhang, Jian J

2012-07-01

Texture mapping has long been used in computer graphics to enhance the realism of virtual scenes. However, to match the 3D model feature points with the corresponding pixels in a texture image, surface parameterization must satisfy specific positional constraints. However, despite numerous research efforts, the construction of a mathematically robust, foldover-free parameterization that is subject to positional constraints continues to be a challenge. In the present paper, this foldover problem is addressed by developing radial basis function (RBF)-based reparameterization. Given initial 2D embedding of a 3D surface, the proposed method can reparameterize 2D embedding into a foldover-free 2D mesh, satisfying a set of user-specified constraint points. In addition, this approach is mesh free. Therefore, generating smooth texture mapping results is possible without extra smoothing optimization.

Comparing and Reconciling Traditional Field and Photogeologic Mapping Techniques: Lessons from the San Francisco Volcanic Field, Arizona

NASA Technical Reports Server (NTRS)

Skinner, J. A., Jr.; Eppler, D. B.; Bleacher, J. E.; Evans, C. A.; Feng, W.; Gruener, J.; Hurwitz, D. M.; Janoiko, B.; Whitson, P.

2014-01-01

Cartographic products and - specifically - geologic maps provide critical assistance for establishing physical and temporal frameworks of planetary surfaces. The technical methods that result in the creation of geologic maps vary depending on how observations are made as well as the overall intent of the final products [1-3]. These methods tend to follow a common linear work flow, including the identification and delineation of spatially and temporally discrete materials (units), the documentation of their primary (emplacement) and secondary (erosional) characteristics, analysis of the relative and absolute age relationships between these materials, and the collation of observations and interpretations into an objective map product. The "objectivity" of a map is critical cross comparison with overlapping maps and topical studies as well as its relevance to scientific posterity. However, the "accuracy" and "correctness" of a geologic map is very subject to debate. This can be evidenced by comparison of existing geologic maps at various scales, particularly those compiled through field- and remote-based mapped efforts. Our study focuses on comparing the fidelity of (1) "Apollo-style" geologic investigations, where typically non-geologist crew members follow static traverse routes established through pre-mission planning, and (2) "traditional" field-based investigations, where geologists are given free rein to observe without preplanned routes. This abstract summarizes the regional geology wherein our study was conducted, presents the geologic map created from traditional field mapping techniques, and offers basic insights into how geologic maps created from different tactics can be reconciled in support of exploratory missions. Additional abstracts [4-6] from this study discuss various exploration and science results of these efforts.

A new method for mapping multidimensional data to lower dimensions

NASA Technical Reports Server (NTRS)

Gowda, K. C.

1983-01-01

A multispectral mapping method is proposed which is based on the new concept of BEND (Bidimensional Effective Normalised Difference). The method, which involves taking one sample point at a time and finding the interrelationships between its features, is found very economical from the point of view of storage and processing time. It has good dimensionality reduction and clustering properties, and is highly suitable for computer analysis of large amounts of data. The transformed values obtained by this procedure are suitable for either a planar 2-space mapping of geological sample points or for making grayscale and color images of geo-terrains. A few examples are given to justify the efficacy of the proposed procedure.

The use of interactive graphical maps for browsing medical/health Internet information resources

PubMed Central

Boulos, Maged N Kamel

2003-01-01

As online information portals accumulate metadata descriptions of Web resources, it becomes necessary to develop effective ways for visualising and navigating the resultant huge metadata repositories as well as the different semantic relationships and attributes of described Web resources. Graphical maps provide a good method to visualise, understand and navigate a world that is too large and complex to be seen directly like the Web. Several examples of maps designed as a navigational aid for Web resources are presented in this review with an emphasis on maps of medical and health-related resources. The latter include HealthCyberMap maps , which can be classified as conceptual information space maps, and the very abstract and geometric Visual Net maps of PubMed (for demos). Information resources can be also organised and navigated based on their geographic attributes. Some of the maps presented in this review use a Kohonen Self-Organising Map algorithm, and only HealthCyberMap uses a Geographic Information System to classify Web resource data and render the maps. Maps based on familiar metaphors taken from users' everyday life are much easier to understand. Associative and pictorial map icons that enable instant recognition and comprehension are preferred to geometric ones and are key to successful maps for browsing medical/health Internet information resources. PMID:12556244

Mapping landslide source and transport areas in VHR images with Object-Based Analysis and Support Vector Machines

NASA Astrophysics Data System (ADS)

Heleno, Sandra; Matias, Magda; Pina, Pedro

2015-04-01

Visual interpretation of satellite imagery remains extremely demanding in terms of resources and time, especially when dealing with numerous multi-scale landslides affecting wide areas, such as is the case of rainfall-induced shallow landslides. Applying automated methods can contribute to more efficient landslide mapping and updating of existing inventories, and in recent years the number and variety of approaches is rapidly increasing. Very High Resolution (VHR) images, acquired by space-borne sensors with sub-metric precision, such as Ikonos, Quickbird, Geoeye and Worldview, are increasingly being considered as the best option for landslide mapping, but these new levels of spatial detail also present new challenges to state of the art image analysis tools, asking for automated methods specifically suited to map landslide events on VHR optical images. In this work we develop and test a methodology for semi-automatic landslide recognition and mapping of landslide source and transport areas. The method combines object-based image analysis and a Support Vector Machine supervised learning algorithm, and was tested using a GeoEye-1 multispectral image, sensed 3 days after a damaging landslide event in Madeira Island, together with a pre-event LiDAR DEM. Our approach has proved successful in the recognition of landslides on a 15 Km2-wide study area, with 81 out of 85 landslides detected in its validation regions. The classifier also showed reasonable performance (false positive rate 60% and false positive rate below 36% in both validation regions) in the internal mapping of landslide source and transport areas, in particular in the sunnier east-facing slopes. In the less illuminated areas the classifier is still able to accurately map the source areas, but performs poorly in the mapping of landslide transport areas.

Equidistant map projections of a triaxial ellipsoid with the use of reduced coordinates

NASA Astrophysics Data System (ADS)

Pędzich, Paweł

2017-12-01

The paper presents a new method of constructing equidistant map projections of a triaxial ellipsoid as a function of reduced coordinates. Equations for x and y coordinates are expressed with the use of the normal elliptic integral of the second kind and Jacobian elliptic functions. This solution allows to use common known and widely described in literature methods of solving such integrals and functions. The main advantage of this method is the fact that the calculations of x and y coordinates are practically based on a single algorithm that is required to solve the elliptic integral of the second kind. Equations are provided for three types of map projections: cylindrical, azimuthal and pseudocylindrical. These types of projections are often used in planetary cartography for presentation of entire and polar regions of extraterrestrial objects. The paper also contains equations for the calculation of the length of a meridian and a parallel of a triaxial ellipsoid in reduced coordinates. Moreover, graticules of three coordinates systems (planetographic, planetocentric and reduced) in developed map projections are presented. The basic properties of developed map projections are also described. The obtained map projections may be applied in planetary cartography in order to create maps of extraterrestrial objects.

Methodological considerations for the evaluation of EEG mapping data: a practical example based on a placebo/diazepam crossover trial.

PubMed

Jähnig, P; Jobert, M

1995-01-01

Quantitative EEG is a sensitive method for measuring pharmacological effects on the central nervous system. Nowadays, computers enable EEG data to be stored and spectral parameters to be computed for signals obtained from a large number of electrode locations. However, the statistical analysis of such vast amounts of EEG data is complicated due to the limited number of subjects usually involved in pharmacological studies. In the present study, data from a trial aimed at comparing diazepam and placebo were used to investigate different properties of EEG mapping data and to compare different methods of data analysis. Both the topography and the temporal changes of EEG activity were investigated using descriptive data analysis, which is based on an inspection of patterns of pd values (descriptive p values) assessed for all pair-wise tests for differences in time or treatment. An empirical measure (tri-mean) for the computation of group maps is suggested, allowing a better description of group effects with skewed data of small samples size. Finally, both the investigation of maps based on principal component analysis and the notion of distance between maps are discussed and applied to the analysis of the data collected under diazepam treatment, exemplifying the evaluation of pharmacodynamic drug effects.

Aerosol Extinction Profile Mapping with Lognormal Distribution Based on MPL Data

NASA Astrophysics Data System (ADS)

Lin, T. H.; Lee, T. T.; Chang, K. E.; Lien, W. H.; Liu, G. R.; Liu, C. Y.

2017-12-01

This study intends to challenge the profile mapping of aerosol vertical distribution by mathematical function. With the similarity in distribution pattern, lognormal distribution is examined for mapping the aerosol extinction profile based on MPL (Micro Pulse LiDAR) in situ measurements. The variables of lognormal distribution are log mean (μ) and log standard deviation (σ), which will be correlated with the parameters of aerosol optical depht (AOD) and planetary boundary layer height (PBLH) associated with the altitude of extinction peak (Mode) defined in this study. On the base of 10 years MPL data with single peak, the mapping results showed that the mean error of Mode and σ retrievals are 16.1% and 25.3%, respectively. The mean error of σ retrieval can be reduced to 16.5% under the cases of larger distance between PBLH and Mode. The proposed method is further applied to MODIS AOD product in mapping extinction profile for the retrieval of PM2.5 in terms of satellite observations. The results indicated well agreement between retrievals and ground measurements when aerosols under 525 meters are well-mixed. The feasibility of proposed method to satellite remote sensing is also suggested by the case study. Keyword: Aerosol extinction profile, Lognormal distribution, MPL, Planetary boundary layer height (PBLH), Aerosol optical depth (AOD), Mode

Experimental mapping of DNA duplex shape enabled by global lineshape analyses of a nucleotide-independent nitroxide probe

PubMed Central

Ding, Yuan; Zhang, Xiaojun; Tham, Kenneth W.; Qin, Peter Z.

2014-01-01

Sequence-dependent variation in structure and dynamics of a DNA duplex, collectively referred to as ‘DNA shape’, critically impacts interactions between DNA and proteins. Here, a method based on the technique of site-directed spin labeling was developed to experimentally map shapes of two DNA duplexes that contain response elements of the p53 tumor suppressor. An R5a nitroxide spin label, which was covalently attached at a specific phosphate group, was scanned consecutively through the DNA duplex. X-band continuous-wave electron paramagnetic resonance spectroscopy was used to monitor rotational motions of R5a, which report on DNA structure and dynamics at the labeling site. An approach based on Pearson's coefficient analysis was developed to collectively examine the degree of similarity among the ensemble of R5a spectra. The resulting Pearson's coefficients were used to generate maps representing variation of R5a mobility along the DNA duplex. The R5a mobility maps were found to correlate with maps of certain DNA helical parameters, and were capable of revealing similarity and deviation in the shape of the two closely related DNA duplexes. Collectively, the R5a probe and the Pearson's coefficient-based lineshape analysis scheme yielded a generalizable method for examining sequence-dependent DNA shapes. PMID:25092920

Object-based landslide mapping on satellite images from different sensors

NASA Astrophysics Data System (ADS)

Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens; Blaschke, Thomas

2015-04-01

Several studies have proven that object-based image analysis (OBIA) is a suitable approach for landslide mapping using remote sensing data. Mostly, optical satellite images are utilized in combination with digital elevation models (DEMs) for semi-automated mapping. The ability of considering spectral, spatial, morphometric and contextual features in OBIA constitutes a significant advantage over pixel-based methods, especially when analysing non-uniform natural phenomena such as landslides. However, many of the existing knowledge-based OBIA approaches for landslide mapping are rather complex and are tailored to specific data sets. These restraints lead to a lack of transferability of OBIA mapping routines. The objective of this study is to develop an object-based approach for landslide mapping that is robust against changing input data with different resolutions, i.e. optical satellite imagery from various sensors. Two study sites in Taiwan were selected for developing and testing the landslide mapping approach. One site is located around the Baolai village in the Huaguoshan catchment in the southern-central part of the island, the other one is a sub-area of the Taimali watershed in Taitung County near the south-eastern Pacific coast. Both areas are regularly affected by severe landslides and debris flows. A range of very high resolution (VHR) optical satellite images was used for the object-based mapping of landslides and for testing the transferability across different sensors and resolutions: (I) SPOT-5, (II) Formosat-2, (III) QuickBird, and (IV) WorldView-2. Additionally, a digital elevation model (DEM) with 5 m spatial resolution and its derived products (e.g. slope, plan curvature) were used for supporting the semi-automated mapping, particularly for differentiating source areas and accumulation areas according to their morphometric characteristics. A focus was put on the identification of comparatively stable parameters (e.g. relative indices), which could be transferred to the different satellite images. The presence of bare ground was assumed to be an evidence for the occurrence of landslides. For separating vegetated from non-vegetated areas the Normalized Difference Vegetation Index (NDVI) was primarily used. Each image was divided into two respective parts based on an automatically calculated NDVI threshold value in eCognition (Trimble) software by combining the homogeneity criterion of multiresolution segmentation and histogram-based methods, so that heterogeneity is increased to a maximum. Expert knowledge models, which depict features and thresholds that are usually used by experts for digital landslide mapping, were considered for refining the classification. The results were compared to the respective results from visual image interpretation (i.e. manually digitized reference polygons for each image), which were produced by an independent local expert. By that, the spatial overlaps as well as under- and over-estimated areas were identified and the performance of the approach in relation to each sensor was evaluated. The presented method can complement traditional manual mapping efforts. Moreover, it contributes to current developments for increasing the transferability of semi-automated OBIA approaches and for improving the efficiency of change detection approaches across multi-sensor imagery.

Image Restoration in Cryo-electron Microscopy

PubMed Central

Penczek, Pawel A.

2011-01-01

Image restoration techniques are used to obtain, given experimental measurements, the best possible approximation of the original object within the limits imposed by instrumental conditions and noise level in the data. In molecular electron microscopy, we are mainly interested in linear methods that preserve the respective relationships between mass densities within the restored map. Here, we describe the methodology of image restoration in structural electron microscopy, and more specifically, we will focus on the problem of the optimum recovery of Fourier amplitudes given electron microscope data collected under various defocus settings. We discuss in detail two classes of commonly used linear methods, the first of which consists of methods based on pseudoinverse restoration, and which is further subdivided into mean-square error, chi-square error, and constrained based restorations, where the methods in the latter two subclasses explicitly incorporates non-white distribution of noise in the data. The second class of methods is based on the Wiener filtration approach. We show that the Wiener filter-based methodology can be used to obtain a solution to the problem of amplitude correction (or “sharpening”) of the electron microscopy map that makes it visually comparable to maps determined by X-ray crystallography, and thus amenable to comparable interpretation. Finally, we present a semi-heuristic Wiener filter-based solution to the problem of image restoration given sets of heterogeneous solutions. We conclude the chapter with a discussion of image restoration protocols implemented in commonly used single particle software packages. PMID:20888957

A GIS based method for soil mapping in Sardinia, Italy: a geomatic approach.

PubMed

Vacca, A; Loddo, S; Melis, M T; Funedda, A; Puddu, R; Verona, M; Fanni, S; Fantola, F; Madrau, S; Marrone, V A; Serra, G; Tore, C; Manca, D; Pasci, S; Puddu, M R; Schirru, P

2014-06-01

A new project was recently initiated for the realization of the "Land Unit and Soil Capability Map of Sardinia" at a scale of 1:50,000 to support land use planning. In this study, we outline the general structure of the project and the methods used in the activities that have been thus far conducted. A GIS approach was used. We used the soil-landscape paradigm for the prediction of soil classes and their spatial distribution or the prediction of soil properties based on landscape features. The work is divided into two main phases. In the first phase, the available digital data on land cover, geology and topography were processed and classified according to their influence on weathering processes and soil properties. The methods used in the interpretation are based on consolidated and generalized knowledge about the influence of geology, topography and land cover on soil properties. The existing soil data (areal and point data) were collected, reviewed, validated and standardized according to international and national guidelines. Point data considered to be usable were input into a specific database created for the project. Using expert interpretation, all digital data were merged to produce a first draft of the Land Unit Map. During the second phase, this map will be implemented with the existing soil data and verified in the field if also needed with new soil data collection, and the final Land Unit Map will be produced. The Land Unit and Soil Capability Map will be produced by classifying the land units using a reference matching table of land capability classes created for this project. Copyright © 2013 Elsevier Ltd. All rights reserved.

Research on the Application of Rapid Surveying and Mapping for Large Scare Topographic Map by Uav Aerial Photography System

NASA Astrophysics Data System (ADS)

Gao, Z.; Song, Y.; Li, C.; Zeng, F.; Wang, F.

2017-08-01

Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.

Sea-Floor Images and Data from Multibeam Surveys in San Francisco Bay, Southern California, Hawaii, the Gulf of Mexico, and Lake Tahoe, California-Nevada

USGS Publications Warehouse

Dartnell, Peter; Gardiner, James V.

1999-01-01

Accurate base maps are a prerequisite for any geologic study, regardless of the objectives. Land-based studies commonly utilize aerial photographs, USGS 7.5-minute quadrangle maps, and satellite images as base maps. Until now, studies that involve the ocean floor have been at a disadvantage due to an almost complete lack of accurate marine base maps. Many base maps of the sea floor have been constructed over the past century but with a wide range in navigational and depth accuracies. Only in the past few years has marine surveying technology advanced far enough to produce navigational accuracy of 1 meter and depth resolutions of 50 centimeters. The Pacific Seafloor Mapping Project of the U.S. Geological Survey's, Western Coastal and Marine Geology Program, Menlo Park, California, U.S.A., in cooperation with the Ocean Mapping Group, University of New Brunswick, Fredericton, Canada, is using this new technology to systematically map the ocean floor and lakes. This type of marine surveying, called multibeam surveying, collects high-resolution bathymetric and backscatter data that can be used for various base maps, GIS coverages, and scientific visualization methods. This is an interactive CD-ROM that contains images, movies, and data of all the surveys the Pacific Seafloor Mapping Project has completed up to January 1999. The images and movies on this CD-ROM, such as shaded relief of the bathymetry, backscatter, oblique views, 3-D views, and QuickTime movies help the viewer to visualize the multibeam data. This CD-ROM also contains ARC/INFO export (.e00) files and full-resolution TIFF images of all the survey sites that can be downloaded and used in many GIS packages.

Optimal contact definition for reconstruction of contact maps.

PubMed

Duarte, Jose M; Sathyapriya, Rajagopal; Stehr, Henning; Filippis, Ioannis; Lappe, Michael

2010-05-27

Contact maps have been extensively used as a simplified representation of protein structures. They capture most important features of a protein's fold, being preferred by a number of researchers for the description and study of protein structures. Inspired by the model's simplicity many groups have dedicated a considerable amount of effort towards contact prediction as a proxy for protein structure prediction. However a contact map's biological interest is subject to the availability of reliable methods for the 3-dimensional reconstruction of the structure. We use an implementation of the well-known distance geometry protocol to build realistic protein 3-dimensional models from contact maps, performing an extensive exploration of many of the parameters involved in the reconstruction process. We try to address the questions: a) to what accuracy does a contact map represent its corresponding 3D structure, b) what is the best contact map representation with regard to reconstructability and c) what is the effect of partial or inaccurate contact information on the 3D structure recovery. Our results suggest that contact maps derived from the application of a distance cutoff of 9 to 11A around the Cbeta atoms constitute the most accurate representation of the 3D structure. The reconstruction process does not provide a single solution to the problem but rather an ensemble of conformations that are within 2A RMSD of the crystal structure and with lower values for the pairwise average ensemble RMSD. Interestingly it is still possible to recover a structure with partial contact information, although wrong contacts can lead to dramatic loss in reconstruction fidelity. Thus contact maps represent a valid approximation to the structures with an accuracy comparable to that of experimental methods. The optimal contact definitions constitute key guidelines for methods based on contact maps such as structure prediction through contacts and structural alignments based on maximum contact map overlap.

Optimal contact definition for reconstruction of Contact Maps

PubMed Central

2010-01-01

Background Contact maps have been extensively used as a simplified representation of protein structures. They capture most important features of a protein's fold, being preferred by a number of researchers for the description and study of protein structures. Inspired by the model's simplicity many groups have dedicated a considerable amount of effort towards contact prediction as a proxy for protein structure prediction. However a contact map's biological interest is subject to the availability of reliable methods for the 3-dimensional reconstruction of the structure. Results We use an implementation of the well-known distance geometry protocol to build realistic protein 3-dimensional models from contact maps, performing an extensive exploration of many of the parameters involved in the reconstruction process. We try to address the questions: a) to what accuracy does a contact map represent its corresponding 3D structure, b) what is the best contact map representation with regard to reconstructability and c) what is the effect of partial or inaccurate contact information on the 3D structure recovery. Our results suggest that contact maps derived from the application of a distance cutoff of 9 to 11Å around the Cβ atoms constitute the most accurate representation of the 3D structure. The reconstruction process does not provide a single solution to the problem but rather an ensemble of conformations that are within 2Å RMSD of the crystal structure and with lower values for the pairwise average ensemble RMSD. Interestingly it is still possible to recover a structure with partial contact information, although wrong contacts can lead to dramatic loss in reconstruction fidelity. Conclusions Thus contact maps represent a valid approximation to the structures with an accuracy comparable to that of experimental methods. The optimal contact definitions constitute key guidelines for methods based on contact maps such as structure prediction through contacts and structural alignments based on maximum contact map overlap. PMID:20507547

Reliable aerial thermography for energy conservation

NASA Technical Reports Server (NTRS)

Jack, J. R.; Bowman, R. L.

1981-01-01

A method for energy conservation, the aerial thermography survey, is discussed. It locates sources of energy losses and wasteful energy management practices. An operational map is presented for clear sky conditions. The map outlines the key environmental conditions conductive to obtaining reliable aerial thermography. The map is developed from defined visual and heat loss discrimination criteria which are quantized based on flat roof heat transfer calculations.

Using image mapping towards biomedical and biological data sharing

PubMed Central

2013-01-01

Image-based data integration in eHealth and life sciences is typically concerned with the method used for anatomical space mapping, needed to retrieve, compare and analyse large volumes of biomedical data. In mapping one image onto another image, a mechanism is used to match and find the corresponding spatial regions which have the same meaning between the source and the matching image. Image-based data integration is useful for integrating data of various information structures. Here we discuss a broad range of issues related to data integration of various information structures, review exemplary work on image representation and mapping, and discuss the challenges that these techniques may bring. PMID:24059352

EMSAR: estimation of transcript abundance from RNA-seq data by mappability-based segmentation and reclustering.

PubMed

Lee, Soohyun; Seo, Chae Hwa; Alver, Burak Han; Lee, Sanghyuk; Park, Peter J

2015-09-03

RNA-seq has been widely used for genome-wide expression profiling. RNA-seq data typically consists of tens of millions of short sequenced reads from different transcripts. However, due to sequence similarity among genes and among isoforms, the source of a given read is often ambiguous. Existing approaches for estimating expression levels from RNA-seq reads tend to compromise between accuracy and computational cost. We introduce a new approach for quantifying transcript abundance from RNA-seq data. EMSAR (Estimation by Mappability-based Segmentation And Reclustering) groups reads according to the set of transcripts to which they are mapped and finds maximum likelihood estimates using a joint Poisson model for each optimal set of segments of transcripts. The method uses nearly all mapped reads, including those mapped to multiple genes. With an efficient transcriptome indexing based on modified suffix arrays, EMSAR minimizes the use of CPU time and memory while achieving accuracy comparable to the best existing methods. EMSAR is a method for quantifying transcripts from RNA-seq data with high accuracy and low computational cost. EMSAR is available at https://github.com/parklab/emsar.

Pixel-based parametric source depth map for Cerenkov luminescence imaging

NASA Astrophysics Data System (ADS)

Altabella, L.; Boschi, F.; Spinelli, A. E.

2016-01-01

Optical tomography represents a challenging problem in optical imaging because of the intrinsically ill-posed inverse problem due to photon diffusion. Cerenkov luminescence tomography (CLT) for optical photons produced in tissues by several radionuclides (i.e.: 32P, 18F, 90Y), has been investigated using both 3D multispectral approach and multiviews methods. Difficult in convergence of 3D algorithms can discourage to use this technique to have information of depth and intensity of source. For these reasons, we developed a faster 2D corrected approach based on multispectral acquisitions, to obtain source depth and its intensity using a pixel-based fitting of source intensity. Monte Carlo simulations and experimental data were used to develop and validate the method to obtain the parametric map of source depth. With this approach we obtain parametric source depth maps with a precision between 3% and 7% for MC simulation and 5-6% for experimental data. Using this method we are able to obtain reliable information about the source depth of Cerenkov luminescence with a simple and flexible procedure.

Detecting spatial regimes in ecosystems | Science Inventory ...

EPA Pesticide Factsheets

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

Analysis of terrain map matching using multisensing techniques for applications to autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Page, Lance; Shen, C. N.

1991-01-01

This paper describes skyline-based terrain matching, a new method for locating the vantage point of laser range-finding measurements on a global map previously prepared by satellite or aerial mapping. Skylines can be extracted from the range-finding measurements and modelled from the global map, and are represented in parametric, cylindrical form with azimuth angle as the independent variable. The three translational parameters of the vantage point are determined with a three-dimensional matching of these two sets of skylines.

Analysis of the BEV Technology Progress of America, Europe, Japan and Korea Based on Patent Map

NASA Astrophysics Data System (ADS)

Yurong, Huang; Yuanyuan, Hou; Jingyan, Zhou; Ru, Liu

2018-02-01

The paper analyzed the Battery Electric Vehicle patent application trend, major country distribution, main technology layout and patentee of America, Europe, Japan and Korea based on patent information from 2006 to 2016 by using patent map method, and visualized the Battery Electric Vehicle technology progress conditions of the four countries and regions in the last decade.

Usefulness of the Poincaré maps in detection of T-wave alternans in precordial leads of standard ECG--a comparison with the spectral method.

PubMed

Ruta, J; Strumiłło, P

2001-01-01

T-wave alternans (TWA) at microvolt level is considered as an important non-invasive risk factor for sudden death. Several methods are used to measure such repolarization variations, but each of them has some limitations. The purpose of our study is to assess the usefulness of Poincaré maps, a method based on nonlinear dynamics theory, in detection of repolarization abnormalities. In 30 postinfarction patients presence of TWA in precordial ECG leads was assessed by the spectral method (SM) and by the Poincaré maps (PM). Quantitative measures of both methods: alternans voltage (AV) and alternans distance (AD) were compared using linear regression. Significant correlation between both measures (r = 0.92, p < 0.01) was found. The value of AD > or = 10 microV was accepted as significant for the presence of T-wave alternans. Poincaré mapping seems to be a useful and simple method for detection of TWA. The alternans distance equal or greater than 10 microV can be considered as a level determinative for the presence of TWA.

Ultra-high density intra-specific genetic linkage maps accelerate identification of functionally relevant molecular tags governing important agronomic traits in chickpea

PubMed Central

Kujur, Alice; Upadhyaya, Hari D.; Shree, Tanima; Bajaj, Deepak; Das, Shouvik; Saxena, Maneesha S.; Badoni, Saurabh; Kumar, Vinod; Tripathi, Shailesh; Gowda, C. L. L.; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

2015-01-01

We discovered 26785 and 16573 high-quality SNPs differentiating two parental genotypes of a RIL mapping population using reference desi and kabuli genome-based GBS assay. Of these, 3625 and 2177 SNPs have been integrated into eight desi and kabuli chromosomes, respectively in order to construct ultra-high density (0.20–0.37 cM) intra-specific chickpea genetic linkage maps. One of these constructed high-resolution genetic map has potential to identify 33 major genomic regions harbouring 35 robust QTLs (PVE: 17.9–39.7%) associated with three agronomic traits, which were mapped within <1 cM mean marker intervals on desi chromosomes. The extended LD (linkage disequilibrium) decay (~15 cM) in chromosomes of genetic maps have encouraged us to use a rapid integrated approach (comparative QTL mapping, QTL-region specific haplotype/LD-based trait association analysis, expression profiling and gene haplotype-based association mapping) rather than a traditional QTL map-based cloning method to narrow-down one major seed weight (SW) robust QTL region. It delineated favourable natural allelic variants and superior haplotype-containing one seed-specific candidate embryo defective gene regulating SW in chickpea. The ultra-high-resolution genetic maps, QTLs/genes and alleles/haplotypes-related genomic information generated and integrated strategy for rapid QTL/gene identification developed have potential to expedite genomics-assisted breeding applications in crop plants, including chickpea for their genetic enhancement. PMID:25942004

Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction.

PubMed

Dziadek, Juliusz; Henriksson, Aron; Duneld, Martin

2017-01-01

The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes. Here, we apply several spelling correction methods to Swedish medical text and evaluate their impact on SNOMED CT mapping; first in a controlled evaluation using medical literature text with induced errors, followed by a partial evaluation on clinical notes. It is shown that the best-performing method is context-sensitive, taking into account trigram frequencies and utilizing a corpus-based dictionary.

An Isometric Mapping Based Co-Location Decision Tree Algorithm

NASA Astrophysics Data System (ADS)

Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

2018-05-01

Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

Grid-based mapping: A method for rapidly determining the spatial distributions of small features over very large areas

NASA Astrophysics Data System (ADS)

Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Séjourné, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas

2017-06-01

The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than ;mapping; with points and polygons, grid-based mapping uses a ;tick box; approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping provides an efficient solution to the problems of mapping small landforms over large areas, by providing a consistent and standardised approach to spatial data collection. The simplicity of the grid-based mapping approach makes it extremely scalable and workable for group efforts, requiring minimal user experience and producing consistent and repeatable results. The discrete nature of the datasets, simplicity of approach, and divisibility of tasks, open up the possibility for citizen science in which crowdsourcing large grid-based mapping areas could be applied.

Derivation and application of an analytical rock displacement solution on rectangular cavern wall using the inverse mapping method

PubMed Central

Gao, Mingzhong; Qiu, Zhiqiang; Yin, Xiangang; Li, Shengwei; Liu, Qiang

2017-01-01

Rectangular caverns are increasingly used in underground engineering projects, the failure mechanism of rectangular cavern wall rock is significantly different as a result of the cross-sectional shape and variations in wall stress distributions. However, the conventional computational method always results in a long-winded computational process and multiple displacement solutions of internal rectangular wall rock. This paper uses a Laurent series complex method to obtain a mapping function expression based on complex variable function theory and conformal transformation. This method is combined with the Schwarz-Christoffel method to calculate the mapping function coefficient and to determine the rectangular cavern wall rock deformation. With regard to the inverse mapping concept, the mapping relation between the polar coordinate system within plane ς and a corresponding unique plane coordinate point inside the cavern wall rock is discussed. The disadvantage of multiple solutions when mapping from the plane to the polar coordinate system is addressed. This theoretical formula is used to calculate wall rock boundary deformation and displacement field nephograms inside the wall rock for a given cavern height and width. A comparison with ANSYS numerical software results suggests that the theoretical solution and numerical solution exhibit identical trends, thereby demonstrating the method’s validity. This method greatly improves the computing accuracy and reduces the difficulty in solving for cavern boundary and internal wall rock displacements. The proposed method provides a theoretical guide for controlling cavern wall rock deformation failure. PMID:29155892

Aerial images visual localization on a vector map using color-texture segmentation

NASA Astrophysics Data System (ADS)

Kunina, I. A.; Teplyakov, L. M.; Gladkov, A. P.; Khanipov, T. M.; Nikolaev, D. P.

2018-04-01

In this paper we study the problem of combining UAV obtained optical data and a coastal vector map in absence of satellite navigation data. The method is based on presenting the territory as a set of segments produced by color-texture image segmentation. We then find such geometric transform which gives the best match between these segments and land and water areas of the georeferenced vector map. We calculate transform consisting of an arbitrary shift relatively to the vector map and bound rotation and scaling. These parameters are estimated using the RANSAC algorithm which matches the segments contours and the contours of land and water areas of the vector map. To implement this matching we suggest computing shape descriptors robust to rotation and scaling. We performed numerical experiments demonstrating the practical applicability of the proposed method.

Mapping debris-flow hazard in Honolulu using a DEM

USGS Publications Warehouse

Ellen, Stephen D.; Mark, Robert K.; ,

1993-01-01

A method for mapping hazard posed by debris flows has been developed and applied to an area near Honolulu, Hawaii. The method uses studies of past debris flows to characterize sites of initiation, volume at initiation, and volume-change behavior during flow. Digital simulations of debris flows based on these characteristics are then routed through a digital elevation model (DEM) to estimate degree of hazard over the area.

Three Reading Comprehension Strategies: TELLS, Story Mapping, and QARs.

ERIC Educational Resources Information Center

Sorrell, Adrian L.

1990-01-01

Three reading comprehension strategies are presented to assist learning-disabled students: an advance organizer technique called "TELLS Fact or Fiction" used before reading a passage, a schema-based technique called "Story Mapping" used while reading, and a postreading method of categorizing questions called…

Generating Multi-Destination Maps.

PubMed

Zhang, Junsong; Fan, Jiepeng; Luo, Zhenshan

2017-08-01

Multi-destination maps are a kind of navigation maps aimed to guide visitors to multiple destinations within a region, which can be of great help to urban visitors. However, they have not been developed in the current online map service. To address this issue, we introduce a novel layout model designed especially for generating multi-destination maps, which considers the global and local layout of a multi-destination map. We model the layout problem as a graph drawing that satisfies a set of hard and soft constraints. In the global layout phase, we balance the scale factor between ROIs. In the local layout phase, we make all edges have good visibility and optimize the map layout to preserve the relative length and angle of roads. We also propose a perturbation-based optimization method to find an optimal layout in the complex solution space. The multi-destination maps generated by our system are potential feasible on the modern mobile devices and our result can show an overview and a detail view of the whole map at the same time. In addition, we perform a user study to evaluate the effectiveness of our method, and the results prove that the multi-destination maps achieve our goals well.

Mapping detailed 3D information onto high resolution SAR signatures

NASA Astrophysics Data System (ADS)

Anglberger, H.; Speck, R.

2017-05-01

Due to challenges in the visual interpretation of radar signatures or in the subsequent information extraction, a fusion with other data sources can be beneficial. The most accurate basis for a fusion of any kind of remote sensing data is the mapping of the acquired 2D image space onto the true 3D geometry of the scenery. In the case of radar images this is a challenging task because the coordinate system is based on the measured range which causes ambiguous regions due to layover effects. This paper describes a method that accurately maps the detailed 3D information of a scene to the slantrange-based coordinate system of imaging radars. Due to this mapping all the contributing geometrical parts of one resolution cell can be determined in 3D space. The proposed method is highly efficient, because computationally expensive operations can be directly performed on graphics card hardware. The described approach builds a perfect basis for sophisticated methods to extract data from multiple complimentary sensors like from radar and optical images, especially because true 3D information from whole cities will be available in the near future. The performance of the developed methods will be demonstrated with high resolution radar data acquired by the space-borne SAR-sensor TerraSAR-X.

Dissecting enzyme function with microfluidic-based deep mutational scanning.

PubMed

Romero, Philip A; Tran, Tuan M; Abate, Adam R

2015-06-09

Natural enzymes are incredibly proficient catalysts, but engineering them to have new or improved functions is challenging due to the complexity of how an enzyme's sequence relates to its biochemical properties. Here, we present an ultrahigh-throughput method for mapping enzyme sequence-function relationships that combines droplet microfluidic screening with next-generation DNA sequencing. We apply our method to map the activity of millions of glycosidase sequence variants. Microfluidic-based deep mutational scanning provides a comprehensive and unbiased view of the enzyme function landscape. The mapping displays expected patterns of mutational tolerance and a strong correspondence to sequence variation within the enzyme family, but also reveals previously unreported sites that are crucial for glycosidase function. We modified the screening protocol to include a high-temperature incubation step, and the resulting thermotolerance landscape allowed the discovery of mutations that enhance enzyme thermostability. Droplet microfluidics provides a general platform for enzyme screening that, when combined with DNA-sequencing technologies, enables high-throughput mapping of enzyme sequence space.

A Scheme for Obtaining Secure S-Boxes Based on Chaotic Baker's Map

NASA Astrophysics Data System (ADS)

Gondal, Muhammad Asif; Abdul Raheem; Hussain, Iqtadar

2014-09-01

In this paper, a method for obtaining cryptographically strong 8 × 8 substitution boxes (S-boxes) is presented. The method is based on chaotic baker's map and a "mini version" of a new block cipher with block size 8 bits and can be easily and efficiently performed on a computer. The cryptographic strength of some 8 × 8 S-boxes randomly produced by the method is analyzed. The results show (1) all of them are bijective; (2) the nonlinearity of each output bit of them is usually about 100; (3) all of them approximately satisfy the strict avalanche criterion and output bits independence criterion; (4) they all have an almost equiprobable input/output XOR distribution.

Method and system for progressive mesh storage and reconstruction using wavelet-encoded height fields

NASA Technical Reports Server (NTRS)

Baxes, Gregory A. (Inventor); Linger, Timothy C. (Inventor)

2011-01-01

Systems and methods are provided for progressive mesh storage and reconstruction using wavelet-encoded height fields. A method for progressive mesh storage includes reading raster height field data, and processing the raster height field data with a discrete wavelet transform to generate wavelet-encoded height fields. In another embodiment, a method for progressive mesh storage includes reading texture map data, and processing the texture map data with a discrete wavelet transform to generate wavelet-encoded texture map fields. A method for reconstructing a progressive mesh from wavelet-encoded height field data includes determining terrain blocks, and a level of detail required for each terrain block, based upon a viewpoint. Triangle strip constructs are generated from vertices of the terrain blocks, and an image is rendered utilizing the triangle strip constructs. Software products that implement these methods are provided.

Method and system for progressive mesh storage and reconstruction using wavelet-encoded height fields

NASA Technical Reports Server (NTRS)

Baxes, Gregory A. (Inventor)

2010-01-01

Systems and methods are provided for progressive mesh storage and reconstruction using wavelet-encoded height fields. A method for progressive mesh storage includes reading raster height field data, and processing the raster height field data with a discrete wavelet transform to generate wavelet-encoded height fields. In another embodiment, a method for progressive mesh storage includes reading texture map data, and processing the texture map data with a discrete wavelet transform to generate wavelet-encoded texture map fields. A method for reconstructing a progressive mesh from wavelet-encoded height field data includes determining terrain blocks, and a level of detail required for each terrain block, based upon a viewpoint. Triangle strip constructs are generated from vertices of the terrain blocks, and an image is rendered utilizing the triangle strip constructs. Software products that implement these methods are provided.

Clearance detector and method for motion and distance

DOEpatents

Xavier, Patrick G [Albuquerque, NM

2011-08-09

A method for correct and efficient detection of clearances between three-dimensional bodies in computer-based simulations, where one or both of the volumes is subject to translation and/or rotations. The method conservatively determines of the size of such clearances and whether there is a collision between the bodies. Given two bodies, each of which is undergoing separate motions, the method utilizes bounding-volume hierarchy representations for the two bodies and, mappings and inverse mappings for the motions of the two bodies. The method uses the representations, mappings and direction vectors to determine the directionally furthest locations of points on the convex hulls of the volumes virtually swept by the bodies and hence the clearance between the bodies, without having to calculate the convex hulls of the bodies. The method includes clearance detection for bodies comprising convex geometrical primitives and more specific techniques for bodies comprising convex polyhedra.

Object-based change detection method using refined Markov random field

NASA Astrophysics Data System (ADS)

Peng, Daifeng; Zhang, Yongjun

2017-01-01

In order to fully consider the local spatial constraints between neighboring objects in object-based change detection (OBCD), an OBCD approach is presented by introducing a refined Markov random field (MRF). First, two periods of images are stacked and segmented to produce image objects. Second, object spectral and textual histogram features are extracted and G-statistic is implemented to measure the distance among different histogram distributions. Meanwhile, object heterogeneity is calculated by combining spectral and textual histogram distance using adaptive weight. Third, an expectation-maximization algorithm is applied for determining the change category of each object and the initial change map is then generated. Finally, a refined change map is produced by employing the proposed refined object-based MRF method. Three experiments were conducted and compared with some state-of-the-art unsupervised OBCD methods to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method obtains the highest accuracy among the methods used in this paper, which confirms its validness and effectiveness in OBCD.

An efficient depth map preprocessing method based on structure-aided domain transform smoothing for 3D view generation

PubMed Central

Ma, Liyan; Qiu, Bo; Cui, Mingyue; Ding, Jianwei

2017-01-01

Depth image-based rendering (DIBR), which is used to render virtual views with a color image and the corresponding depth map, is one of the key techniques in the 2D to 3D conversion process. Due to the absence of knowledge about the 3D structure of a scene and its corresponding texture, DIBR in the 2D to 3D conversion process, inevitably leads to holes in the resulting 3D image as a result of newly-exposed areas. In this paper, we proposed a structure-aided depth map preprocessing framework in the transformed domain, which is inspired by recently proposed domain transform for its low complexity and high efficiency. Firstly, our framework integrates hybrid constraints including scene structure, edge consistency and visual saliency information in the transformed domain to improve the performance of depth map preprocess in an implicit way. Then, adaptive smooth localization is cooperated and realized in the proposed framework to further reduce over-smoothness and enhance optimization in the non-hole regions. Different from the other similar methods, the proposed method can simultaneously achieve the effects of hole filling, edge correction and local smoothing for typical depth maps in a united framework. Thanks to these advantages, it can yield visually satisfactory results with less computational complexity for high quality 2D to 3D conversion. Numerical experimental results demonstrate the excellent performances of the proposed method. PMID:28407027

Near-Infrared Coloring via a Contrast-Preserving Mapping Model.

PubMed

Chang-Hwan Son; Xiao-Ping Zhang

2017-11-01

Near-infrared gray images captured along with corresponding visible color images have recently proven useful for image restoration and classification. This paper introduces a new coloring method to add colors to near-infrared gray images based on a contrast-preserving mapping model. A naive coloring method directly adds the colors from the visible color image to the near-infrared gray image. However, this method results in an unrealistic image because of the discrepancies in the brightness and image structure between the captured near-infrared gray image and the visible color image. To solve the discrepancy problem, first, we present a new contrast-preserving mapping model to create a new near-infrared gray image with a similar appearance in the luminance plane to the visible color image, while preserving the contrast and details of the captured near-infrared gray image. Then, we develop a method to derive realistic colors that can be added to the newly created near-infrared gray image based on the proposed contrast-preserving mapping model. Experimental results show that the proposed new method not only preserves the local contrast and details of the captured near-infrared gray image, but also transfers the realistic colors from the visible color image to the newly created near-infrared gray image. It is also shown that the proposed near-infrared coloring can be used effectively for noise and haze removal, as well as local contrast enhancement.

Geological analysis of parts of the southern Arabian Shield based on Landsat imagery

NASA Astrophysics Data System (ADS)

Qari, Mohammed Yousef Hedaytullah T.

This thesis examines the capability and applicability of Landsat multispectral remote sensing data for geological analysis in the arid southern Arabian Shield, which is the eastern segment of the Nubian-Arabian Shield surrounding the Red Sea. The major lithologies in the study area are Proterozoic metavolcanics, metasediments, gneisses and granites. Three test-sites within the study area, located within two tectonic assemblages, the Asir Terrane and the Nabitah Mobile Belt, were selected for detailed comparison of remote sensing methods and ground geological studies. Selected digital image processing techniques were applied to full-resolution Landsat TM imagery and the results are interpreted and discussed. Methods included: image contrast improvement, edge enhancement for detecting lineaments and spectral enhancement for geological mapping. The last method was based on two principles, statistical analysis of the data and the use of arithmetical operators. New and detailed lithological and structural maps were constructed and compared with previous maps of these sites. Examples of geological relations identified using TM imagery include: recognition and mapping of migmatites for the first time in the Arabian Shield; location of the contact between the Asir Terrane and the Nabitah Mobile Belt; and mapping of lithologies, some of which were not identified on previous geological maps. These and other geological features were confirmed by field checking. Methods of lineament enhancement implemented in this study revealed structural lineaments, mostly mapped for the first time, which can be related to regional tectonics. Structural analysis showed that the southern Arabian Shield has been affected by at least three successive phases of deformation. The third phase is the most dominant and widespread. A crustal evolutionary model in the vicinity of the study area is presented showing four stages, these are: arc stage, accretion stage, collision stage and post-collision stage. The results of this study demonstrate that Landsat TM data can be used reliably for geological investigations in the Arabian Shield and comparable areas, particularly to generate detailed geological maps over large areas by using quantitative remote sensing methods, providing there is prior knowledge of part of the area.

Object detection system based on multimodel saliency maps

NASA Astrophysics Data System (ADS)

Guo, Ya'nan; Luo, Chongfan; Ma, Yide

2017-03-01

Detection of visually salient image regions is extensively applied in computer vision and computer graphics, such as object detection, adaptive compression, and object recognition, but any single model always has its limitations to various images, so in our work, we establish a method based on multimodel saliency maps to detect the object, which intelligently absorbs the merits of various individual saliency detection models to achieve promising results. The method can be roughly divided into three steps: in the first step, we propose a decision-making system to evaluate saliency maps obtained by seven competitive methods and merely select the three most valuable saliency maps; in the second step, we introduce heterogeneous PCNN algorithm to obtain three prime foregrounds; and then a self-designed nonlinear fusion method is proposed to merge these saliency maps; at last, the adaptive improved and simplified PCNN model is used to detect the object. Our proposed method can constitute an object detection system for different occasions, which requires no training, is simple, and highly efficient. The proposed saliency fusion technique shows better performance over a broad range of images and enriches the applicability range by fusing different individual saliency models, this proposed system is worthy enough to be called a strong model. Moreover, the proposed adaptive improved SPCNN model is stemmed from the Eckhorn's neuron model, which is skilled in image segmentation because of its biological background, and in which all the parameters are adaptive to image information. We extensively appraise our algorithm on classical salient object detection database, and the experimental results demonstrate that the aggregation of saliency maps outperforms the best saliency model in all cases, yielding highest precision of 89.90%, better recall rates of 98.20%, greatest F-measure of 91.20%, and lowest mean absolute error value of 0.057, the value of proposed saliency evaluation EHA reaches to 215.287. We deem our method can be wielded to diverse applications in the future.

Regional snow-avalanche detection using object-based image analysis of near-infrared aerial imagery

NASA Astrophysics Data System (ADS)

Korzeniowska, Karolina; Bühler, Yves; Marty, Mauro; Korup, Oliver

2017-10-01

Snow avalanches are destructive mass movements in mountain regions that continue to claim lives and cause infrastructural damage and traffic detours. Given that avalanches often occur in remote and poorly accessible steep terrain, their detection and mapping is extensive and time consuming. Nonetheless, systematic avalanche detection over large areas could help to generate more complete and up-to-date inventories (cadastres) necessary for validating avalanche forecasting and hazard mapping. In this study, we focused on automatically detecting avalanches and classifying them into release zones, tracks, and run-out zones based on 0.25 m near-infrared (NIR) ADS80-SH92 aerial imagery using an object-based image analysis (OBIA) approach. Our algorithm takes into account the brightness, the normalised difference vegetation index (NDVI), the normalised difference water index (NDWI), and its standard deviation (SDNDWI) to distinguish avalanches from other land-surface elements. Using normalised parameters allows applying this method across large areas. We trained the method by analysing the properties of snow avalanches at three 4 km-2 areas near Davos, Switzerland. We compared the results with manually mapped avalanche polygons and obtained a user's accuracy of > 0.9 and a Cohen's kappa of 0.79-0.85. Testing the method for a larger area of 226.3 km-2, we estimated producer's and user's accuracies of 0.61 and 0.78, respectively, with a Cohen's kappa of 0.67. Detected avalanches that overlapped with reference data by > 80 % occurred randomly throughout the testing area, showing that our method avoids overfitting. Our method has potential for large-scale avalanche mapping, although further investigations into other regions are desirable to verify the robustness of our selected thresholds and the transferability of the method.

Data-based estimates of the ocean carbon sink variability - first results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

NASA Astrophysics Data System (ADS)

Rödenbeck, C.; Bakker, D. C. E.; Gruber, N.; Iida, Y.; Jacobson, A. R.; Jones, S.; Landschützer, P.; Metzl, N.; Nakaoka, S.; Olsen, A.; Park, G.-H.; Peylin, P.; Rodgers, K. B.; Sasse, T. P.; Schuster, U.; Shutler, J. D.; Valsala, V.; Wanninkhof, R.; Zeng, J.

2015-08-01

Using measurements of the surface-ocean CO2 partial pressure (pCO2) and 14 different pCO2 mapping methods recently collated by the Surface Ocean pCO2 Mapping intercomparison (SOCOM) initiative, variations in regional and global sea-air CO2 fluxes have been investigated. Though the available mapping methods use widely different approaches, we find relatively consistent estimates of regional pCO2 seasonality, in line with previous estimates. In terms of interannual variability (IAV), all mapping methods estimate the largest variations to occur in the Eastern equatorial Pacific. Despite considerable spead in the detailed variations, mapping methods with closer match to the data also tend to be more consistent with each other. Encouragingly, this includes mapping methods belonging to complementary types - taking variability either directly from the pCO2 data or indirectly from driver data via regression. From a weighted ensemble average, we find an IAV amplitude of the global sea-air CO2 flux of 0.31 PgC yr-1 (standard deviation over 1992-2009), which is larger than simulated by biogeochemical process models. On a decadal perspective, the global CO2 uptake is estimated to have gradually increased since about 2000, with little decadal change prior to 2000. The weighted mean total ocean CO2 sink estimated by the SOCOM ensemble is consistent within uncertainties with estimates from ocean-interior carbon data or atmospheric oxygen trends.

Covariance approximation for fast and accurate computation of channelized Hotelling observer statistics

NASA Astrophysics Data System (ADS)

Bonetto, P.; Qi, Jinyi; Leahy, R. M.

2000-08-01

Describes a method for computing linear observer statistics for maximum a posteriori (MAP) reconstructions of PET images. The method is based on a theoretical approximation for the mean and covariance of MAP reconstructions. In particular, the authors derive here a closed form for the channelized Hotelling observer (CHO) statistic applied to 2D MAP images. The theoretical analysis models both the Poission statistics of PET data and the inhomogeneity of tracer uptake. The authors show reasonably good correspondence between these theoretical results and Monte Carlo studies. The accuracy and low computational cost of the approximation allow the authors to analyze the observer performance over a wide range of operating conditions and parameter settings for the MAP reconstruction algorithm.

Clustering self-organizing maps (SOM) method for human papillomavirus (HPV) DNA as the main cause of cervical cancer disease

NASA Astrophysics Data System (ADS)

Bustamam, A.; Aldila, D.; Fatimah, Arimbi, M. D.

2017-07-01

One of the most widely used clustering method, since it has advantage on its robustness, is Self-Organizing Maps (SOM) method. This paper discusses the application of SOM method on Human Papillomavirus (HPV) DNA which is the main cause of cervical cancer disease, the most dangerous cancer in developing countries. We use 18 types of HPV DNA-based on the newest complete genome. By using open-source-based program R, clustering process can separate 18 types of HPV into two different clusters. There are two types of HPV in the first cluster while 16 others in the second cluster. The analyzing result of 18 types HPV based on the malignancy of the virus (the difficultness to cure). Two of HPV types the first cluster can be classified as tame HPV, while 16 others in the second cluster are classified as vicious HPV.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

Improving the extraction of crisis information in the context of flood, fire, and landslide rapid mapping using SAR and optical remote sensing data

NASA Astrophysics Data System (ADS)

Martinis, Sandro; Clandillon, Stephen; Twele, André; Huber, Claire; Plank, Simon; Maxant, Jérôme; Cao, Wenxi; Caspard, Mathilde; May, Stéphane

2016-04-01

Optical and radar satellite remote sensing have proven to provide essential crisis information in case of natural disasters, humanitarian relief activities and civil security issues in a growing number of cases through mechanisms such as the Copernicus Emergency Management Service (EMS) of the European Commission or the International Charter 'Space and Major Disasters'. The aforementioned programs and initiatives make use of satellite-based rapid mapping services aimed at delivering reliable and accurate crisis information after natural hazards. Although these services are increasingly operational, they need to be continuously updated and improved through research and development (R&D) activities. The principal objective of ASAPTERRA (Advancing SAR and Optical Methods for Rapid Mapping), the ESA-funded R&D project being described here, is to improve, automate and, hence, speed-up geo-information extraction procedures in the context of natural hazards response. This is performed through the development, implementation, testing and validation of novel image processing methods using optical and Synthetic Aperture Radar (SAR) data. The methods are mainly developed based on data of the German radar satellites TerraSAR-X and TanDEM-X, the French satellite missions Pléiades-1A/1B as well as the ESA missions Sentinel-1/2 with the aim to better characterize the potential and limitations of these sensors and their synergy. The resulting algorithms and techniques are evaluated in real case applications during rapid mapping activities. The project is focussed on three types of natural hazards: floods, landslides and fires. Within this presentation an overview of the main methodological developments in each topic is given and demonstrated in selected test areas. The following developments are presented in the context of flood mapping: a fully automated Sentinel-1 based processing chain for detecting open flood surfaces, a method for the improved detection of flooded vegetation in Sentinel-1data using Entropy/Alpha decomposition, unsupervised Wishart Classification, and object-based post-classification as well as semi-automatic approaches for extracting inundated areas and flood traces in rural and urban areas from VHR and HR optical imagery using machine learning techniques. Methodological developments related to fires are the implementation of fast and robust methods for mapping burnt scars using change detection procedures using SAR (Sentinel-1, TerraSAR-X) and HR optical (e.g. SPOT, Sentinel-2) data as well as the extraction of 3D surface and volume change information from Pléiades stereo-pairs. In the context of landslides, fast and transferable change detection procedures based on SAR (TerraSAR-X) and optical (SPOT) data as well methods for extracting the extent of landslides only based on polarimetric VHR SAR (TerraSAR-X) data are presented.

Hepatic fat quantification using the two-point Dixon method and fat color maps based on non-alcoholic fatty liver disease activity score.

PubMed

Hayashi, Tatsuya; Saitoh, Satoshi; Takahashi, Junji; Tsuji, Yoshinori; Ikeda, Kenji; Kobayashi, Masahiro; Kawamura, Yusuke; Fujii, Takeshi; Inoue, Masafumi; Miyati, Tosiaki; Kumada, Hiromitsu

2017-04-01

The two-point Dixon method for magnetic resonance imaging (MRI) is commonly used to non-invasively measure fat deposition in the liver. The aim of the present study was to assess the usefulness of MRI-fat fraction (MRI-FF) using the two-point Dixon method based on the non-alcoholic fatty liver disease activity score. This retrospective study included 106 patients who underwent liver MRI and MR spectroscopy, and 201 patients who underwent liver MRI and histological assessment. The relationship between MRI-FF and MR spectroscopy-fat fraction was used to estimate the corrected MRI-FF for hepatic multi-peaks of fat. Then, a color FF map was generated with the corrected MRI-FF based on the non-alcoholic fatty liver disease activity score. We defined FF variability as the standard deviation of FF in regions of interest. Uniformity of hepatic fat was visually graded on a three-point scale using both gray-scale and color FF maps. Confounding effects of histology (iron, inflammation and fibrosis) on corrected MRI-FF were assessed by multiple linear regression. The linear correlations between MRI-FF and MR spectroscopy-fat fraction, and between corrected MRI-FF and histological steatosis were strong (R 2  = 0.90 and R 2  = 0.88, respectively). Liver fat variability significantly increased with visual fat uniformity grade using both of the maps (ρ = 0.67-0.69, both P < 0.001). Hepatic iron, inflammation and fibrosis had no significant confounding effects on the corrected MRI-FF (all P > 0.05). The two-point Dixon method and the gray-scale or color FF maps based on the non-alcoholic fatty liver disease activity score were useful for fat quantification in the liver of patients without severe iron deposition. © 2016 The Japan Society of Hepatology.

Three-dimensional dominant frequency mapping using autoregressive spectral analysis of atrial electrograms of patients in persistent atrial fibrillation.

PubMed

Salinet, João L; Masca, Nicholas; Stafford, Peter J; Ng, G André; Schlindwein, Fernando S

2016-03-08

Areas with high frequency activity within the atrium are thought to be 'drivers' of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in eliminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electrophysiology (EP) procedures but literature is restricted on using alternative spectral estimation techniques that can have a better frequency resolution that FFT-based spectral estimation. Autoregressive (AR) model-based spectral estimation techniques, with emphasis on selection of appropriate sampling rate and AR model order, were implemented to generate high-density 3D DF maps of atrial electrograms (AEGs) in persistent atrial fibrillation (persAF). For each patient, 2048 simultaneous AEGs were recorded for 20.478 s-long segments in the left atrium (LA) and exported for analysis, together with their anatomical locations. After the DFs were identified using AR-based spectral estimation, they were colour coded to produce sequential 3D DF maps. These maps were systematically compared with maps found using the Fourier-based approach. 3D DF maps can be obtained using AR-based spectral estimation after AEGs downsampling (DS) and the resulting maps are very similar to those obtained using FFT-based spectral estimation (mean 90.23 %). There were no significant differences between AR techniques (p = 0.62). The processing time for AR-based approach was considerably shorter (from 5.44 to 5.05 s) when lower sampling frequencies and model order values were used. Higher levels of DS presented higher rates of DF agreement (sampling frequency of 37.5 Hz). We have demonstrated the feasibility of using AR spectral estimation methods for producing 3D DF maps and characterised their differences to the maps produced using the FFT technique, offering an alternative approach for 3D DF computation in human persAF studies.

A method for detecting IBD regions simultaneously in multiple individuals—with applications to disease genetics

PubMed Central

Moltke, Ida; Albrechtsen, Anders; Hansen, Thomas v.O.; Nielsen, Finn C.; Nielsen, Rasmus

2011-01-01

All individuals in a finite population are related if traced back long enough and will, therefore, share regions of their genomes identical by descent (IBD). Detection of such regions has several important applications—from answering questions about human evolution to locating regions in the human genome containing disease-causing variants. However, IBD regions can be difficult to detect, especially in the common case where no pedigree information is available. In particular, all existing non-pedigree based methods can only infer IBD sharing between two individuals. Here, we present a new Markov Chain Monte Carlo method for detection of IBD regions, which does not rely on any pedigree information. It is based on a probabilistic model applicable to unphased SNP data. It can take inbreeding, allele frequencies, genotyping errors, and genomic distances into account. And most importantly, it can simultaneously infer IBD sharing among multiple individuals. Through simulations, we show that the simultaneous modeling of multiple individuals makes the method more powerful and accurate than several other non-pedigree based methods. We illustrate the potential of the method by applying it to data from individuals with breast and/or ovarian cancer, and show that a known disease-causing mutation can be mapped to a 2.2-Mb region using SNP data from only five seemingly unrelated affected individuals. This would not be possible using classical linkage mapping or association mapping. PMID:21493780

Extinction Map of Baade's Window

NASA Astrophysics Data System (ADS)

Stanek, K. Z.

1996-03-01

Recently Wozniak & Stanek proposed a new method to investigate interstellar extinction, based on two-band photometry, which uses red clump stars as a means to construct the reddening curve. I apply this method to the color-magnitude diagrams obtained by the Optical Gravitational Lensing Experiment to construct an extinction map of a 40' x 40' region of Baade's window, with resolution of ~30". Such a map should be useful for studies of this frequently observed region of the Galactic bulge. The map and software useful for its applications are available via anonymous ftp. The total extinction AV varies from 1.26 to 2.79 mag within the 40' x 40' field of view centered on ( alpha 2000, delta 2000) = (18:03:20.9, -30:02:06), i.e., (l, b) = (1.001, -3.885). The ratio AV/E(V - I) = 2.49 +/- 0.02 is determined with this new method.

Depth profile measurement with lenslet images of the plenoptic camera

NASA Astrophysics Data System (ADS)

Yang, Peng; Wang, Zhaomin; Zhang, Wei; Zhao, Hongying; Qu, Weijuan; Zhao, Haimeng; Asundi, Anand; Yan, Lei

2018-03-01

An approach for carrying out depth profile measurement of an object with the plenoptic camera is proposed. A single plenoptic image consists of multiple lenslet images. To begin with, these images are processed directly with a refocusing technique to obtain the depth map, which does not need to align and decode the plenoptic image. Then, a linear depth calibration is applied based on the optical structure of the plenoptic camera for depth profile reconstruction. One significant improvement of the proposed method concerns the resolution of the depth map. Unlike the traditional method, our resolution is not limited by the number of microlenses inside the camera, and the depth map can be globally optimized. We validated the method with experiments on depth map reconstruction, depth calibration, and depth profile measurement, with the results indicating that the proposed approach is both efficient and accurate.

Shear wave mapping of skeletal muscle using shear wave wavefront reconstruction based on ultrasound color flow imaging

NASA Astrophysics Data System (ADS)

Yamakoshi, Yoshiki; Yamamoto, Atsushi; Kasahara, Toshihiro; Iijima, Tomohiro; Yuminaka, Yasushi

2015-07-01

We have proposed a quantitative shear wave imaging technique for continuous shear wave excitation. Shear wave wavefront is observed directly by color flow imaging using a general-purpose ultrasonic imaging system. In this study, the proposed method is applied to experiments in vivo, and shear wave maps, namely, the shear wave phase map, which shows the shear wave propagation inside the medium, and the shear wave velocity map, are observed for the skeletal muscle in the shoulder. To excite the shear wave inside the skeletal muscle of the shoulder, a hybrid ultrasonic wave transducer, which combines a small vibrator with an ultrasonic wave probe, is adopted. The shear wave velocity of supraspinatus muscle, which is measured by the proposed method, is 4.11 ± 0.06 m/s (N = 4). This value is consistent with those obtained by the acoustic radiation force impulse method.

Preferred reporting items for studies mapping onto preference-based outcome measures: The MAPS statement.

PubMed

Petrou, Stavros; Rivero-Arias, Oliver; Dakin, Helen; Longworth, Louise; Oppe, Mark; Froud, Robert; Gray, Alastair

2015-01-01

'Mapping' onto generic preference-based outcome measures is increasingly being used as a means of generating health utilities for use within health economic evaluations. Despite publication of technical guides for the conduct of mapping research, guidance for the reporting of mapping studies is currently lacking. The MAPS (MApping onto Preference-based measures reporting Standards) statement is a new checklist, which aims to promote complete and transparent reporting of mapping studies. The primary audiences for the MAPS statement are researchers reporting mapping studies, the funders of the research, and peer reviewers and editors involved in assessing mapping studies for publication. A de novo list of 29 candidate reporting items and accompanying explanations was created by a working group comprised of six health economists and one Delphi methodologist. Following a two-round, modified Delphi survey with representatives from academia, consultancy, health technology assessment agencies and the biomedical journal editorial community, a final set of 23 items deemed essential for transparent reporting, and accompanying explanations, was developed. The items are contained in a user friendly 23 item checklist. They are presented numerically and categorised within six sections, namely: (i) title and abstract; (ii) introduction; (iii) methods; (iv) results; (v) discussion; and (vi) other. The MAPS statement is best applied in conjunction with the accompanying MAPS explanation and elaboration document. It is anticipated that the MAPS statement will improve the clarity, transparency and completeness of reporting of mapping studies. To facilitate dissemination and uptake, the MAPS statement is being co-published by seven health economics and quality of life journals, and broader endorsement is encouraged. The MAPS working group plans to assess the need for an update of the reporting checklist in five years' time.

Preferred Reporting Items for Studies Mapping onto Preference-Based Outcome Measures: The MAPS Statement.

PubMed

Petrou, Stavros; Rivero-Arias, Oliver; Dakin, Helen; Longworth, Louise; Oppe, Mark; Froud, Robert; Gray, Alastair

2015-10-01

'Mapping' onto generic preference-based outcome measures is increasingly being used as a means of generating health utilities for use within health economic evaluations. Despite the publication of technical guides for the conduct of mapping research, guidance for the reporting of mapping studies is currently lacking. The MAPS (MApping onto Preference-based measures reporting Standards) statement is a new checklist, which aims to promote complete and transparent reporting of mapping studies. The primary audiences for the MAPS statement are researchers reporting mapping studies, the funders of the research, and peer reviewers and editors involved in assessing mapping studies for publication. A de novo list of 29 candidate reporting items and accompanying explanations was created by a working group comprising six health economists and one Delphi methodologist. Following a two-round modified Delphi survey with representatives from academia, consultancy, health technology assessment agencies and the biomedical journal editorial community, a final set of 23 items deemed essential for transparent reporting, and accompanying explanations, was developed. The items are contained in a user-friendly 23-item checklist. They are presented numerically and categorised within six sections, namely: (1) title and abstract; (2) introduction; (3) methods; (4) results; (5) discussion; and (6) other. The MAPS statement is best applied in conjunction with the accompanying MAPS explanation and elaboration document. It is anticipated that the MAPS statement will improve the clarity, transparency and completeness of reporting of mapping studies. To facilitate dissemination and uptake, the MAPS statement is being co-published by seven health economics and quality-of-life journals, and broader endorsement is encouraged. The MAPS working group plans to assess the need for an update of the reporting checklist in 5 years' time.

Improving acoustic beamforming maps in a reverberant environment by modifying the cross-correlation matrix

NASA Astrophysics Data System (ADS)

Fischer, J.; Doolan, C.

2017-12-01

A method to improve the quality of acoustic beamforming in reverberant environments is proposed in this paper. The processing is based on a filtering of the cross-correlation matrix of the microphone signals obtained using a microphone array. The main advantage of the proposed method is that it does not require information about the geometry of the reverberant environment and thus it can be applied to any configuration. The method is applied to the particular example of aeroacoustic testing in a hard-walled low-speed wind tunnel; however, the technique can be used in any reverberant environment. Two test cases demonstrate the technique. The first uses a speaker placed in the hard-walled working section with no wind tunnel flow. In the second test case, an airfoil is placed in a flow and acoustic beamforming maps are obtained. The acoustic maps have been improved, as the reflections observed in the conventional maps have been removed after application of the proposed method.

Regional gene mapping using mixed radiation hybrids and reverse chromosome painting.

PubMed

Lin, J Y; Bedford, J S

1997-11-01

We describe a new approach for low-resolution physical mapping using pooled DNA probe from mixed (non-clonal) populations of human-CHO cell hybrids and reverse chromosome painting. This mapping method is based on a process in which the human chromosome fragments bearing a complementing gene were selectively retained in a large non-clonal population of CHO-human hybrid cells during a series of 12- to 15-Gy gamma irradiations each followed by continuous growth selection. The location of the gene could then be identified by reverse chromosome painting on normal human metaphase spreads using biotinylated DNA from this population of "enriched" hybrid cells. We tested the validity of this method by correctly mapping the complementing human HPRT gene, whose location is well established. We then demonstrated the method's usefulness by mapping the chromosome location of a human gene which complemented the defect responsible for the hypersensitivity to ionizing radiation in CHO irs-20 cells. This method represents an efficient alternative to conventional concordance analysis in somatic cell hybrids where detailed chromosome analysis of numerous hybrid clones is necessary. Using this approach, it is possible to localize a gene for which there is no prior sequence or linkage information to a subchromosomal region, thus facilitating association with known mapping landmarks (e.g. RFLP, YAC or STS contigs) for higher-resolution mapping.

Inverse full state hybrid projective synchronization for chaotic maps with different dimensions

NASA Astrophysics Data System (ADS)

Ouannas, Adel; Grassi, Giuseppe

2016-09-01

A new synchronization scheme for chaotic (hyperchaotic) maps with different dimensions is presented. Specifically, given a drive system map with dimension n and a response system with dimension m, the proposed approach enables each drive system state to be synchronized with a linear response combination of the response system states. The method, based on the Lyapunov stability theory and the pole placement technique, presents some useful features: (i) it enables synchronization to be achieved for both cases of n < m and n > m; (ii) it is rigorous, being based on theorems; (iii) it can be readily applied to any chaotic (hyperchaotic) maps defined to date. Finally, the capability of the approach is illustrated by synchronization examples between the two-dimensional Hénon map (as the drive system) and the three-dimensional hyperchaotic Wang map (as the response system), and the three-dimensional Hénon-like map (as the drive system) and the two-dimensional Lorenz discrete-time system (as the response system).

Language Mapping with Navigated Repetitive TMS: Proof of Technique and Validation

PubMed Central

Tarapore, Phiroz E.; Findlay, Anne M.; Honma, Susanne M.; Mizuiri, Danielle; Houde, John F.; Berger, Mitchel S.; Nagarajan, Srikantan S.

2013-01-01

Objective Lesion-based mapping of speech pathways has been possible only during invasive neurosurgical procedures using direct cortical stimulation (DCS). However, navigated transcranial magnetic stimulation (nTMS) may allow for lesion-based interrogation of language pathways noninvasively. Although not lesion-based, magnetoencephalographic imaging (MEGI) is another noninvasive modality for language mapping. In this study, we compare the accuracy of nTMS and MEGI with DCS. Methods Subjects with lesions around cortical language areas underwent preoperative nTMS and MEGI for language mapping. nTMS maps were generated using a repetitive TMS protocol to deliver trains of stimulations during a picture naming task. MEGI activation maps were derived from adaptive spatial filtering of beta-band power decreases prior to overt speech during picture naming and verb generation tasks. The subjects subsequently underwent awake language mapping via intraoperative DCS. The language maps obtained from each of the 3 modalities were recorded and compared. Results nTMS and MEGI were performed on 12 subjects. nTMS yielded 21 positive language disruption sites (11 speech arrest, 5 anomia, and 5 other) while DCS yielded 10 positive sites (2 speech arrest, 5 anomia, and 3 other). MEGI isolated 32 sites of peak activation with language tasks. Positive language sites were most commonly found in the pars opercularis for all three modalities. In 9 instances the positive DCS site corresponded to a positive nTMS site, while in 1 instance it did not. In 4 instances, a positive nTMS site corresponded to a negative DCS site, while 169 instances of negative nTMS and DCS were recorded. The sensitivity of nTMS was therefore 90%, specificity was 98%, the positive predictive value was 69% and the negative predictive value was 99% as compared with intraoperative DCS. MEGI language sites for verb generation and object naming correlated with nTMS sites in 5 subjects, and with DCS sites in 2 subjects. Conclusion Maps of language function generated with nTMS correlate well with those generated by DCS. Negative nTMS mapping also correlates with negative DCS mapping. In our study, MEGI lacks the same level of correlation with intraoperative mapping; nevertheless it provides useful adjunct information in some cases. nTMS may offer a lesion-based method for noninvasively interrogating language pathways and be valuable in managing patients with peri-eloquent lesions. PMID:23702420

Bayesian B-spline mapping for dynamic quantitative traits.

PubMed

Xing, Jun; Li, Jiahan; Yang, Runqing; Zhou, Xiaojing; Xu, Shizhong

2012-04-01

Owing to their ability and flexibility to describe individual gene expression at different time points, random regression (RR) analyses have become a popular procedure for the genetic analysis of dynamic traits whose phenotypes are collected over time. Specifically, when modelling the dynamic patterns of gene expressions in the RR framework, B-splines have been proved successful as an alternative to orthogonal polynomials. In the so-called Bayesian B-spline quantitative trait locus (QTL) mapping, B-splines are used to characterize the patterns of QTL effects and individual-specific time-dependent environmental errors over time, and the Bayesian shrinkage estimation method is employed to estimate model parameters. Extensive simulations demonstrate that (1) in terms of statistical power, Bayesian B-spline mapping outperforms the interval mapping based on the maximum likelihood; (2) for the simulated dataset with complicated growth curve simulated by B-splines, Legendre polynomial-based Bayesian mapping is not capable of identifying the designed QTLs accurately, even when higher-order Legendre polynomials are considered and (3) for the simulated dataset using Legendre polynomials, the Bayesian B-spline mapping can find the same QTLs as those identified by Legendre polynomial analysis. All simulation results support the necessity and flexibility of B-spline in Bayesian mapping of dynamic traits. The proposed method is also applied to a real dataset, where QTLs controlling the growth trajectory of stem diameters in Populus are located.

Towards an EO-based Landslide Web Mapping and Monitoring Service

NASA Astrophysics Data System (ADS)

Hölbling, Daniel; Weinke, Elisabeth; Albrecht, Florian; Eisank, Clemens; Vecchiotti, Filippo; Friedl, Barbara; Kociu, Arben

2017-04-01

National and regional authorities and infrastructure maintainers in mountainous regions require accurate knowledge of the location and spatial extent of landslides for hazard and risk management. Information on landslides is often collected by a combination of ground surveying and manual image interpretation following landslide triggering events. However, the high workload and limited time for data acquisition result in a trade-off between completeness, accuracy and detail. Remote sensing data offers great potential for mapping and monitoring landslides in a fast and efficient manner. While facing an increased availability of high-quality Earth Observation (EO) data and new computational methods, there is still a lack in science-policy interaction and in providing innovative tools and methods that can easily be used by stakeholders and users to support their daily work. Taking up this issue, we introduce an innovative and user-oriented EO-based web service for landslide mapping and monitoring. Three central design components of the service are presented: (1) the user requirements definition, (2) the semi-automated image analysis methods implemented in the service, and (3) the web mapping application with its responsive user interface. User requirements were gathered during semi-structured interviews with regional authorities. The potential users were asked if and how they employ remote sensing data for landslide investigation and what their expectations to a landslide web mapping service regarding reliability and usability are. The interviews revealed the capability of our service for landslide documentation and mapping as well as monitoring of selected landslide sites, for example to complete and update landslide inventory maps. In addition, the users see a considerable potential for landslide rapid mapping. The user requirements analysis served as basis for the service concept definition. Optical satellite imagery from different high resolution (HR) and very high resolution (VHR) sensors, e.g. Landsat, Sentinel-2, SPOT-5, WorldView-2/3, was acquired for different study areas in the Alps. Object-based image analysis (OBIA) methods were used for semi-automated mapping of landslides. Selected mapping routines and results, including a step-by-step guidance, are integrated in the service by means of a web processing chain. This allows the user to gain insights into the service idea, the potential of semi-automated mapping methods, and the applicability of various satellite data for specific landslide mapping tasks. Moreover, an easy-to use and guided classification workflow, which includes image segmentation, statistical classification and manual editing options, enables the user to perform his/her own analyses. For validation, the classification results can be downloaded or compared against uploaded reference data using the implemented tools. Furthermore, users can compare the classification results to freely available data such as OpenStreetMap to identify landslide-affected infrastructure (e.g. roads, buildings). They also can upload infrastructure data available at their organization for specific assessments or monitor the evolution of selected landslides over time. Further actions will include the validation of the service in collaboration with stakeholders, decision makers and experts, which is essential to produce landslide information products that can assist the targeted management of natural hazards, and the evaluation of the potential towards the development of an operational Copernicus downstream service.

Artificial-epitope mapping for CK-MB assay.

PubMed

Tai, Dar-Fu; Ho, Yi-Fang; Wu, Cheng-Hsin; Lin, Tzu-Chieh; Lu, Kuo-Hao; Lin, Kun-Shian

2011-06-07

A quantitative method using artificial antibody to detect creatine kinases was developed. Linear epitope sequences were selected based on an artificial-epitope mapping strategy. Nine different MIPs corresponding to the selected peptides were then fabricated on QCM chips. The subtle conformational changes were also recognized by these chips.

Teaching science with technology: Using EPA’s EnviroAtlas in the classroom

EPA Science Inventory

Background/Question/Methods U.S. EPA’s EnviroAtlas provides a collection of web-based, interactive tools and resources for exploring ecosystem goods and services. EnviroAtlas contains two primary tools: An Interactive Map, which provides access to 300+ maps at multiple exte...

Preferred Reporting Items for Studies Mapping onto Preference-Based Outcome Measures: The MAPS Statement.

PubMed

Petrou, Stavros; Rivero-Arias, Oliver; Dakin, Helen; Longworth, Louise; Oppe, Mark; Froud, Robert; Gray, Alastair

2015-10-01

'Mapping' onto generic preference-based outcome measures is increasingly being used as a means of generating health utilities for use within health economic evaluations. Despite publication of technical guides for the conduct of mapping research, guidance for the reporting of mapping studies is currently lacking. The MAPS (MApping onto Preference-based measures reporting Standards) statement is a new checklist, which aims to promote complete and transparent reporting of mapping studies. In the absence of previously published reporting checklists or reporting guidance documents, a de novo list of reporting items was created by a working group comprising six health economists and one Delphi methodologist. A two-round, modified Delphi survey, with representatives from academia, consultancy, health technology assessment agencies and the biomedical journal editorial community, was used to identify a list of essential reporting items from this larger list. From the initial de novo list of 29 candidate items, a set of 23 essential reporting items was developed. The items are presented numerically and categorized within six sections: (1) title and abstract; (2) introduction; (3) methods; (4) results; (5) discussion; and (6) other. The MAPS statement is best applied in conjunction with the accompanying MAPS Explanation and Elaboration paper. It is anticipated that the MAPS statement will improve the clarity, transparency and completeness of the reporting of mapping studies. To facilitate dissemination and uptake, the MAPS statement is being co-published by seven health economics and quality-of-life journals, and broader endorsement is encouraged. The MAPS working group plans to assess the need for an update of the reporting checklist in 5 years' time.

Preferred Reporting Items for Studies Mapping onto Preference-Based Outcome Measures: The MAPS Statement.

PubMed

Petrou, Stavros; Rivero-Arias, Oliver; Dakin, Helen; Longworth, Louise; Oppe, Mark; Froud, Robert; Gray, Alastair

2015-08-01

"Mapping" onto generic preference-based outcome measures is increasingly being used as a means of generating health utilities for use within health economic evaluations. Despite the publication of technical guides for the conduct of mapping research, guidance for the reporting of mapping studies is currently lacking. The MAPS (MApping onto Preference-based measures reporting Standards) statement is a new checklist that aims to promote complete and transparent reporting of mapping studies. In the absence of previously published reporting checklists or reporting guidance documents, a de novo list of reporting items was created by a working group comprised of 6 health economists and 1 Delphi methodologist. A 2-round, modified Delphi survey with representatives from academia, consultancy, health technology assessment agencies, and the biomedical journal editorial community was used to identify a list of essential reporting items from this larger list. From the initial de novo list of 29 candidate items, a set of 23 essential reporting items was developed. The items are presented numerically and categorized within 6 sections, namely: (i) title and abstract; (ii) introduction; (iii) methods; (iv) results; (v) discussion; and (vi) other. The MAPS statement is best applied in conjunction with the accompanying MAPS explanation and elaboration document. It is anticipated that the MAPS statement will improve the clarity, transparency, and completeness of reporting of mapping studies. To facilitate dissemination and uptake, the MAPS statement is being co-published by 7 health economics and quality-of-life journals, and broader endorsement is encouraged. The MAPS working group plans to assess the need for an update of the reporting checklist in 5 years.

Planetary Geologic Mapping Handbook - 2010. Appendix

NASA Technical Reports Server (NTRS)

Tanaka, K. L.; Skinner, J. A., Jr.; Hare, T. M.

2010-01-01

Geologic maps present, in an historical context, fundamental syntheses of interpretations of the materials, landforms, structures, and processes that characterize planetary surfaces and shallow subsurfaces. Such maps also provide a contextual framework for summarizing and evaluating thematic research for a given region or body. In planetary exploration, for example, geologic maps are used for specialized investigations such as targeting regions of interest for data collection and for characterizing sites for landed missions. Whereas most modern terrestrial geologic maps are constructed from regional views provided by remote sensing data and supplemented in detail by field-based observations and measurements, planetary maps have been largely based on analyses of orbital photography. For planetary bodies in particular, geologic maps commonly represent a snapshot of a surface, because they are based on available information at a time when new data are still being acquired. Thus the field of planetary geologic mapping has been evolving rapidly to embrace the use of new data and modern technology and to accommodate the growing needs of planetary exploration. Planetary geologic maps have been published by the U.S. Geological Survey (USGS) since 1962. Over this time, numerous maps of several planetary bodies have been prepared at a variety of scales and projections using the best available image and topographic bases. Early geologic map bases commonly consisted of hand-mosaicked photographs or airbrushed shaded-relief views and geologic linework was manually drafted using mylar bases and ink drafting pens. Map publishing required a tedious process of scribing, color peel-coat preparation, typesetting, and photo-laboratory work. Beginning in the 1990s, inexpensive computing, display capability and user-friendly illustration software allowed maps to be drawn using digital tools rather than pen and ink, and mylar bases became obsolete. Terrestrial geologic maps published by the USGS now are primarily digital products using geographic information system (GIS) software and file formats. GIS mapping tools permit easy spatial comparison, generation, importation, manipulation, and analysis of multiple raster image, gridded, and vector data sets. GIS software has also permitted the development of projectspecific tools and the sharing of geospatial products among researchers. GIS approaches are now being used in planetary geologic mapping as well. Guidelines or handbooks on techniques in planetary geologic mapping have been developed periodically. As records of the heritage of mapping methods and data, these remain extremely useful guides. However, many of the fundamental aspects of earlier mapping handbooks have evolved significantly, and a comprehensive review of currently accepted mapping methodologies is now warranted. As documented in this handbook, such a review incorporates additional guidelines developed in recent years for planetary geologic mapping by the NASA Planetary Geology and Geophysics (PGG) Program's Planetary Cartography and Geologic Mapping Working Group's (PCGMWG) Geologic Mapping Subcommittee (GEMS) on the selection and use of map bases as well as map preparation, review, publication, and distribution. In light of the current boom in planetary exploration and the ongoing rapid evolution of available data for planetary mapping, this handbook is especially timely.

A perturbation method to the tent map based on Lyapunov exponent and its application

NASA Astrophysics Data System (ADS)

Cao, Lv-Chen; Luo, Yu-Ling; Qiu, Sen-Hui; Liu, Jun-Xiu

2015-10-01

Perturbation imposed on a chaos system is an effective way to maintain its chaotic features. A novel parameter perturbation method for the tent map based on the Lyapunov exponent is proposed in this paper. The pseudo-random sequence generated by the tent map is sent to another chaos function — the Chebyshev map for the post processing. If the output value of the Chebyshev map falls into a certain range, it will be sent back to replace the parameter of the tent map. As a result, the parameter of the tent map keeps changing dynamically. The statistical analysis and experimental results prove that the disturbed tent map has a highly random distribution and achieves good cryptographic properties of a pseudo-random sequence. As a result, it weakens the phenomenon of strong correlation caused by the finite precision and effectively compensates for the digital chaos system dynamics degradation. Project supported by the Guangxi Provincial Natural Science Foundation, China (Grant No. 2014GXNSFBA118271), the Research Project of Guangxi University, China (Grant No. ZD2014022), the Fund from Guangxi Provincial Key Laboratory of Multi-source Information Mining & Security, China (Grant No. MIMS14-04), the Fund from the Guangxi Provincial Key Laboratory of Wireless Wideband Communication & Signal Processing, China (Grant No. GXKL0614205), the Education Development Foundation and the Doctoral Research Foundation of Guangxi Normal University, the State Scholarship Fund of China Scholarship Council (Grant No. [2014]3012), and the Innovation Project of Guangxi Graduate Education, China (Grant No. YCSZ2015102).

A simple method for serving Web hypermaps with dynamic database drill-down

PubMed Central

Boulos, Maged N Kamel; Roudsari, Abdul V; Carson, Ewart R

2002-01-01

Background HealthCyberMap aims at mapping parts of health information cyberspace in novel ways to deliver a semantically superior user experience. This is achieved through "intelligent" categorisation and interactive hypermedia visualisation of health resources using metadata, clinical codes and GIS. HealthCyberMap is an ArcView 3.1 project. WebView, the Internet extension to ArcView, publishes HealthCyberMap ArcView Views as Web client-side imagemaps. The basic WebView set-up does not support any GIS database connection, and published Web maps become disconnected from the original project. A dedicated Internet map server would be the best way to serve HealthCyberMap database-driven interactive Web maps, but is an expensive and complex solution to acquire, run and maintain. This paper describes HealthCyberMap simple, low-cost method for "patching" WebView to serve hypermaps with dynamic database drill-down functionality on the Web. Results The proposed solution is currently used for publishing HealthCyberMap GIS-generated navigational information maps on the Web while maintaining their links with the underlying resource metadata base. Conclusion The authors believe their map serving approach as adopted in HealthCyberMap has been very successful, especially in cases when only map attribute data change without a corresponding effect on map appearance. It should be also possible to use the same solution to publish other interactive GIS-driven maps on the Web, e.g., maps of real world health problems. PMID:12437788

Coastal flood inundation monitoring with Satellite C-band and L-band Synthetic Aperture Radar data

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, Amina; Bannister, Terri

2013-01-01

Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm- and tidal-related flooding of spatially extensive coastal marshes within the north-central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L-Band SAR (PALSAR) (L-band) (21 scenes with HH polarizations in Wide Beam [100 m]) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C-band) data (24 scenes with VV and HH polarizations in Wide Swath [150 m]) during 2006-2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels. Both PALSAR- and ASAR-based mapping at times were based on suboptimal reference scenes; however, ASAR performance seemed more sensitive to reference-scene quality and other types of scene variability. Related to water depth, PALSAR and ASAR mapping accuracies tended to be lower when water depths were shallow and increased as water levels decreased below or increased above the ground surface, but this pattern was more pronounced with ASAR. Overall, PALSAR-based inundation accuracies averaged 84% (n = 160), while ASAR-based mapping accuracies averaged 62% (n = 245).

Mapping Partners Master Drug Dictionary to RxNorm using an NLP-based approach.

PubMed

Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Chang, Frank Y; DiMaggio, Dana; Rocha, Roberto A

2012-08-01

To develop an automated method based on natural language processing (NLP) to facilitate the creation and maintenance of a mapping between RxNorm and a local medication terminology for interoperability and meaningful use purposes. We mapped 5961 terms from Partners Master Drug Dictionary (MDD) and 99 of the top prescribed medications to RxNorm. The mapping was conducted at both term and concept levels using an NLP tool, called MTERMS, followed by a manual review conducted by domain experts who created a gold standard mapping. The gold standard was used to assess the overall mapping between MDD and RxNorm and evaluate the performance of MTERMS. Overall, 74.7% of MDD terms and 82.8% of the top 99 terms had an exact semantic match to RxNorm. Compared to the gold standard, MTERMS achieved a precision of 99.8% and a recall of 73.9% when mapping all MDD terms, and a precision of 100% and a recall of 72.6% when mapping the top prescribed medications. The challenges and gaps in mapping MDD to RxNorm are mainly due to unique user or application requirements for representing drug concepts and the different modeling approaches inherent in the two terminologies. An automated approach based on NLP followed by human expert review is an efficient and feasible way for conducting dynamic mapping. Copyright © 2011 Elsevier Inc. All rights reserved.

Production of high-resolution forest-ecosite maps based on model predictions of soil moisture and nutrient regimes over a large forested area.

PubMed

Yang, Qi; Meng, Fan-Rui; Bourque, Charles P-A; Zhao, Zhengyong

2017-09-08

Forest ecosite reflects the local site conditions that are meaningful to forest productivity as well as basic ecological functions. Field assessments of vegetation and soil types are often used to identify forest ecosites. However, the production of high-resolution ecosite maps for large areas from interpolating field data is difficult because of high spatial variation and associated costs and time requirements. Indices of soil moisture and nutrient regimes (i.e., SMR and SNR) introduced in this study reflect the combined effects of biogeochemical and topographic factors on forest growth. The objective of this research is to present a method for creating high-resolution forest ecosite maps based on computer-generated predictions of SMR and SNR for an area in Atlantic Canada covering about 4.3 × 10 6 hectares (ha) of forestland. Field data from 1,507 forest ecosystem classification plots were used to assess the accuracy of the ecosite maps produced. Using model predictions of SMR and SNR alone, ecosite maps were 61 and 59% correct in identifying 10 Acadian- and Maritime-Boreal-region ecosite types, respectively. This method provides an operational framework for the production of high-resolution maps of forest ecosites over large areas without the need for data from expensive, supplementary field surveys.

Accelerating parallel transmit array B1 mapping in high field MRI with slice undersampling and interpolation by kriging.

PubMed

Ferrand, Guillaume; Luong, Michel; Cloos, Martijn A; Amadon, Alexis; Wackernagel, Hans

2014-08-01

Transmit arrays have been developed to mitigate the RF field inhomogeneity commonly observed in high field magnetic resonance imaging (MRI), typically above 3T. To this end, the knowledge of the RF complex-valued B1 transmit-sensitivities of each independent radiating element has become essential. This paper details a method to speed up a currently available B1-calibration method. The principle relies on slice undersampling, slice and channel interleaving and kriging, an interpolation method developed in geostatistics and applicable in many domains. It has been demonstrated that, under certain conditions, kriging gives the best estimator of a field in a region of interest. The resulting accelerated sequence allows mapping a complete set of eight volumetric field maps of the human head in about 1 min. For validation, the accuracy of kriging is first evaluated against a well-known interpolation technique based on Fourier transform as well as to a B1-maps interpolation method presented in the literature. This analysis is carried out on simulated and decimated experimental B1 maps. Finally, the accelerated sequence is compared to the standard sequence on a phantom and a volunteer. The new sequence provides B1 maps three times faster with a loss of accuracy limited potentially to about 5%.

Assessment of Three Flood Hazard Mapping Methods: A Case Study of Perlis

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan Mohd Sabki Wan

2018-03-01

Flood is a common natural disaster and also affect the all state in Malaysia. Regarding to Drainage and Irrigation Department (DID) in 2007, about 29, 270 km2 or 9 percent of region of the country is prone to flooding. Flood can be such devastating catastrophic which can effected to people, economy and environment. Flood hazard mapping can be used is an important part in flood assessment to define those high risk area prone to flooding. The purposes of this study are to prepare a flood hazard mapping in Perlis and to evaluate flood hazard using frequency ratio, statistical index and Poisson method. The six factors affecting the occurrence of flood including elevation, distance from the drainage network, rainfall, soil texture, geology and erosion were created using ArcGIS 10.1 software. Flood location map in this study has been generated based on flooded area in year 2010 from DID. These parameters and flood location map were analysed to prepare flood hazard mapping in representing the probability of flood area. The results of the analysis were verified using flood location data in year 2013, 2014, 2015. The comparison result showed statistical index method is better in prediction of flood area rather than frequency ratio and Poisson method.

An accelerated photo-magnetic imaging reconstruction algorithm based on an analytical forward solution and a fast Jacobian assembly method

NASA Astrophysics Data System (ADS)

Nouizi, F.; Erkol, H.; Luk, A.; Marks, M.; Unlu, M. B.; Gulsen, G.

2016-10-01

We previously introduced photo-magnetic imaging (PMI), an imaging technique that illuminates the medium under investigation with near-infrared light and measures the induced temperature increase using magnetic resonance thermometry (MRT). Using a multiphysics solver combining photon migration and heat diffusion, PMI models the spatiotemporal distribution of temperature variation and recovers high resolution optical absorption images using these temperature maps. In this paper, we present a new fast non-iterative reconstruction algorithm for PMI. This new algorithm uses analytic methods during the resolution of the forward problem and the assembly of the sensitivity matrix. We validate our new analytic-based algorithm with the first generation finite element method (FEM) based reconstruction algorithm previously developed by our team. The validation is performed using, first synthetic data and afterwards, real MRT measured temperature maps. Our new method accelerates the reconstruction process 30-fold when compared to a single iteration of the FEM-based algorithm.

A Physics-Based Deep Learning Approach to Shadow Invariant Representations of Hyperspectral Images.

PubMed

Windrim, Lloyd; Ramakrishnan, Rishi; Melkumyan, Arman; Murphy, Richard J

2018-02-01

This paper proposes the Relit Spectral Angle-Stacked Autoencoder, a novel unsupervised feature learning approach for mapping pixel reflectances to illumination invariant encodings. This work extends the Spectral Angle-Stacked Autoencoder so that it can learn a shadow-invariant mapping. The method is inspired by a deep learning technique, Denoising Autoencoders, with the incorporation of a physics-based model for illumination such that the algorithm learns a shadow invariant mapping without the need for any labelled training data, additional sensors, a priori knowledge of the scene or the assumption of Planckian illumination. The method is evaluated using datasets captured from several different cameras, with experiments to demonstrate the illumination invariance of the features and how they can be used practically to improve the performance of high-level perception algorithms that operate on images acquired outdoors.

Weighted augmented Jacobian matrix with a variable coefficient method for kinematics mapping of space teleoperation based on human-robot motion similarity

NASA Astrophysics Data System (ADS)

Shi, Zhong; Huang, Xuexiang; Hu, Tianjian; Tan, Qian; Hou, Yuzhuo

2016-10-01

Space teleoperation is an important space technology, and human-robot motion similarity can improve the flexibility and intuition of space teleoperation. This paper aims to obtain an appropriate kinematics mapping method of coupled Cartesian-joint space for space teleoperation. First, the coupled Cartesian-joint similarity principles concerning kinematics differences are defined. Then, a novel weighted augmented Jacobian matrix with a variable coefficient (WAJM-VC) method for kinematics mapping is proposed. The Jacobian matrix is augmented to achieve a global similarity of human-robot motion. A clamping weighted least norm scheme is introduced to achieve local optimizations, and the operating ratio coefficient is variable to pursue similarity in the elbow joint. Similarity in Cartesian space and the property of joint constraint satisfaction is analysed to determine the damping factor and clamping velocity. Finally, a teleoperation system based on human motion capture is established, and the experimental results indicate that the proposed WAJM-VC method can improve the flexibility and intuition of space teleoperation to complete complex space tasks.

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data.

PubMed

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-12

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

NASA Astrophysics Data System (ADS)

Lee, Sanggyun; Kim, Hyun-cheol; Im, Jungho

2018-05-01

We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m) MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0), as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011-2016, excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data

NASA Astrophysics Data System (ADS)

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-01

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Introducing students to digital geological mapping: A workflow based on cheap hardware and free software

NASA Astrophysics Data System (ADS)

Vrabec, Marko; Dolžan, Erazem

2016-04-01

The undergraduate field course in Geological Mapping at the University of Ljubljana involves 20-40 students per year, which precludes the use of specialized rugged digital field equipment as the costs would be way beyond the capabilities of the Department. A different mapping area is selected each year with the aim to provide typical conditions that a professional geologist might encounter when doing fieldwork in Slovenia, which includes rugged relief, dense tree cover, and moderately-well- to poorly-exposed bedrock due to vegetation and urbanization. It is therefore mandatory that the digital tools and workflows are combined with classical methods of fieldwork, since, for example, full-time precise GNSS positioning is not viable under such circumstances. Additionally, due to the prevailing combination of complex geological structure with generally poor exposure, students cannot be expected to produce line (vector) maps of geological contacts on the go, so there is no need for such functionality in hardware and software that we use in the field. Our workflow therefore still relies on paper base maps, but is strongly complemented with digital tools to provide robust positioning, track recording, and acquisition of various point-based data. Primary field hardware are students' Android-based smartphones and optionally tablets. For our purposes, the built-in GNSS chips provide adequate positioning precision most of the time, particularly if they are GLONASS-capable. We use Oruxmaps, a powerful free offline map viewer for the Android platform, which facilitates the use of custom-made geopositioned maps. For digital base maps, which we prepare in free Windows QGIS software, we use scanned topographic maps provided by the National Geodetic Authority, but also other maps such as aerial imagery, processed Digital Elevation Models, scans of existing geological maps, etc. Point data, like important outcrop locations or structural measurements, are entered into Oruxmaps as waypoints. Students are also encouraged to directly measure structural data with specialized Android apps such as the MVE FieldMove Clino. Digital field data is exported from Oruxmaps to Windows computers primarily in the ubiquitous GPX data format and then integrated in the QGIS environment. Recorded GPX tracks are also used with the free Geosetter Windows software to geoposition and tag any digital photographs taken in the field. With minimal expenses, our workflow provides the students with basic familiarity and experience in using digital field tools and methods. The workflow is also practical enough for the prevailing field conditions of Slovenia that the faculty staff is using it in geological mapping for scientific research and consultancy work.

Adaptive filtering with the self-organizing map: a performance comparison.

PubMed

Barreto, Guilherme A; Souza, Luís Gustavo M

2006-01-01

In this paper we provide an in-depth evaluation of the SOM as a feasible tool for nonlinear adaptive filtering. A comprehensive survey of existing SOM-based and related architectures for learning input-output mappings is carried out and the application of these architectures to nonlinear adaptive filtering is formulated. Then, we introduce two simple procedures for building RBF-based nonlinear filters using the Vector-Quantized Temporal Associative Memory (VQTAM), a recently proposed method for learning dynamical input-output mappings using the SOM. The aforementioned SOM-based adaptive filters are compared with standard FIR/LMS and FIR/LMS-Newton linear transversal filters, as well as with powerful MLP-based filters in nonlinear channel equalization and inverse modeling tasks. The obtained results in both tasks indicate that SOM-based filters can consistently outperform powerful MLP-based ones.

A novel structure-based multimode QSAR method affords predictive models for phosphodiesterase inhibitors.

PubMed

Dong, Xialan; Ebalunode, Jerry O; Cho, Sung Jin; Zheng, Weifan

2010-02-22

Quantitative structure-activity relationship (QSAR) methods aim to build quantitatively predictive models for the discovery of new molecules. It has been widely used in medicinal chemistry for drug discovery. Many QSAR techniques have been developed since Hansch's seminal work, and more are still being developed. Motivated by Hopfinger's receptor-dependent QSAR (RD-QSAR) formalism and the Lukacova-Balaz scheme to treat multimode issues, we have initiated studies that focus on a structure-based multimode QSAR (SBMM QSAR) method, where the structure of the target protein is used in characterizing the ligand, and the multimode issue of ligand binding is systematically treated with a modified Lukacova-Balaz scheme. All ligand molecules are first docked to the target binding pocket to obtain a set of aligned ligand poses. A structure-based pharmacophore concept is adopted to characterize the binding pocket. Specifically, we represent the binding pocket as a geometric grid labeled by pharmacophoric features. Each pose of the ligand is also represented as a labeled grid, where each grid point is labeled according to the atom types of nearby ligand atoms. These labeled grids or three-dimensional (3D) maps (both the receptor map (R-map) and the ligand map (L-map)) are compared to each other to derive descriptors for each pose of the ligand, resulting in a multimode structure-activity relationship (SAR) table. Iterative partial least-squares (PLS) is employed to build the QSAR models. When we applied this method to analyze PDE-4 inhibitors, predictive models have been developed, obtaining models with excellent training correlation (r(2) = 0.65-0.66), as well as test correlation (R(2) = 0.64-0.65). A comparative analysis with 4 other QSAR techniques demonstrates that this new method affords better models, in terms of the prediction power for the test set.

Development and Evaluation of a Web Map Mind Tool Environment with the Theory of Spatial Thinking and Project-Based Learning Strategy

ERIC Educational Resources Information Center

Hou, Huei-Tse; Yu, Tsai-Fang; Wu, Yi-Xuan; Sung, Yao-Ting; Chang, Kuo-En

2016-01-01

The theory of spatial thinking is relevant to the learning and teaching of many academic domains. One promising method to facilitate learners' higher-order thinking is to utilize a web map mind tool to assist learners in applying spatial thinking to cooperative problem solving. In this study, an environment is designed based on the theory of…

The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

USGS Publications Warehouse

Ackers, Steven H.; Davis, Raymond J.; Olsen, K.; Dugger, Catherine

2015-01-01

Wildlife habitat mapping has evolved at a rapid pace over the last few decades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often essential for producing range wide maps. Habitat monitoring for northern spotted owls (Strix occidentalis caurina), whose geographic covers about 23 million ha, is based on SDMs that use Landsat Thematic Mapper imagery to create forest vegetation data layers using gradient nearest neighbor (GNN) methods. Vegetation data layers derived from GNN are modeled relationships between forest inventory plot data, climate and topographic data, and the spectral signatures acquired by the satellite. When used as predictor variables for SDMs, there is some transference of the GNN modeling error to the final habitat map.Recent increases in the use of light detection and ranging (lidar) data, coupled with the need to produce spatially accurate and detailed forest vegetation maps have spurred interest in its use for SDMs and habitat mapping. Instead of modeling predictor variables from remotely sensed spectral data, lidar provides direct measurements of vegetation height for use in SDMs. We expect a SDM habitat map produced from directly measured predictor variables to be more accurate than one produced from modeled predictors.We used maximum entropy (Maxent) SDM modeling software to compare predictive performance and estimates of habitat area between Landsat-based and lidar-based northern spotted owl SDMs and habitat maps. We explored the differences and similarities between these maps, and to a pre-existing aerial photo-interpreted habitat map produced by local wildlife biologists. The lidar-based map had the highest predictive performance based on 10 bootstrapped replicate models (AUC = 0.809 ± 0.011), but the performance of the Landsat-based map was within acceptable limits (AUC = 0.717 ± 0.021). As is common with photo-interpreted maps, there was no accuracy assessment available for comparison. The photo-interpreted map produced the highest and lowest estimates of habitat area, depending on which habitat classes were included (nesting, roosting, and foraging habitat = 9962 ha, nesting habitat only = 6036 ha). The Landsat-based map produced an estimate of habitat area that was within this range (95% CI: 6679–9592 ha), while the lidar-based map produced an area estimate similar to what was interpreted by local wildlife biologists as nesting (i.e., high quality) habitat using aerial imagery (95% CI: 5453–7216). Confidence intervals of habitat area estimates from the SDMs based on Landsat and lidar overlapped.We concluded that both Landsat- and lidar-based SDMs produced reasonable maps and area estimates for northern spotted owl habitat within the study area. The lidar-based map was more precise and spatially similar to what local wildlife biologists considered spotted owl nesting habitat. The Landsat-based map provided a less precise spatial representation of habitat within the relatively small geographic confines of the study area, but habitat area estimates were similar to both the photo-interpreted and lidar-based maps.Photo-interpreted maps are time consuming to produce, subjective in nature, and difficult to replicate. SDMs provide a framework for efficiently producing habitat maps that can be replicated as habitat conditions change over time, provided that comparable remotely sensed data are available. When the SDM uses predictor variables extracted from lidar data, it can produce a habitat map that is both accurate and useful at large and small spatial scales. In comparison, SDMs using Landsat-based data are more appropriate for large scale analyses of amounts and general spatial patterns of habitat at regional scales.

Ladar imaging detection of salient map based on PWVD and Rényi entropy

NASA Astrophysics Data System (ADS)

Xu, Yuannan; Zhao, Yuan; Deng, Rong; Dong, Yanbing

2013-10-01

Spatial-frequency information of a given image can be extracted by associating the grey-level spatial data with one of the well-known spatial/spatial-frequency distributions. The Wigner-Ville distribution (WVD) has a good characteristic that the images can be represented in spatial/spatial-frequency domains. For intensity and range images of ladar, through the pseudo Wigner-Ville distribution (PWVD) using one or two dimension window, the statistical property of Rényi entropy is studied. We also analyzed the change of Rényi entropy's statistical property in the ladar intensity and range images when the man-made objects appear. From this foundation, a novel method for generating saliency map based on PWVD and Rényi entropy is proposed. After that, target detection is completed when the saliency map is segmented using a simple and convenient threshold method. For the ladar intensity and range images, experimental results show the proposed method can effectively detect the military vehicles from complex earth background with low false alarm.

A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

PubMed

Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

2015-03-15

This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Action recognition using multi-scale histograms of oriented gradients based depth motion trail Images

NASA Astrophysics Data System (ADS)

Wang, Guanxi; Tie, Yun; Qi, Lin

2017-07-01

In this paper, we propose a novel approach based on Depth Maps and compute Multi-Scale Histograms of Oriented Gradient (MSHOG) from sequences of depth maps to recognize actions. Each depth frame in a depth video sequence is projected onto three orthogonal Cartesian planes. Under each projection view, the absolute difference between two consecutive projected maps is accumulated through a depth video sequence to form a Depth Map, which is called Depth Motion Trail Images (DMTI). The MSHOG is then computed from the Depth Maps for the representation of an action. In addition, we apply L2-Regularized Collaborative Representation (L2-CRC) to classify actions. We evaluate the proposed approach on MSR Action3D dataset and MSRGesture3D dataset. Promising experimental result demonstrates the effectiveness of our proposed method.

Transmission imaging for integrated PET-MR systems.

PubMed

Bowen, Spencer L; Fuin, Niccolò; Levine, Michael A; Catana, Ciprian

2016-08-07

Attenuation correction for PET-MR systems continues to be a challenging problem, particularly for body regions outside the head. The simultaneous acquisition of transmission scan based μ-maps and MR images on integrated PET-MR systems may significantly increase the performance of and offer validation for new MR-based μ-map algorithms. For the Biograph mMR (Siemens Healthcare), however, use of conventional transmission schemes is not practical as the patient table and relatively small diameter scanner bore significantly restrict radioactive source motion and limit source placement. We propose a method for emission-free coincidence transmission imaging on the Biograph mMR. The intended application is not for routine subject imaging, but rather to improve and validate MR-based μ-map algorithms; particularly for patient implant and scanner hardware attenuation correction. In this study we optimized source geometry and assessed the method's performance with Monte Carlo simulations and phantom scans. We utilized a Bayesian reconstruction algorithm, which directly generates μ-map estimates from multiple bed positions, combined with a robust scatter correction method. For simulations with a pelvis phantom a single torus produced peak noise equivalent count rates (34.8 kcps) dramatically larger than a full axial length ring (11.32 kcps) and conventional rotating source configurations. Bias in reconstructed μ-maps for head and pelvis simulations was  ⩽4% for soft tissue and  ⩽11% for bone ROIs. An implementation of the single torus source was filled with (18)F-fluorodeoxyglucose and the proposed method quantified for several test cases alone or in comparison with CT-derived μ-maps. A volume average of 0.095 cm(-1) was recorded for an experimental uniform cylinder phantom scan, while a bias of  <2% was measured for the cortical bone equivalent insert of the multi-compartment phantom. Single torus μ-maps of a hip implant phantom showed significantly less artifacts and improved dynamic range, and differed greatly for highly attenuating materials in the case of the patient table, compared to CT results. Use of a fixed torus geometry, in combination with translation of the patient table to perform complete tomographic sampling, generated highly quantitative measured μ-maps and is expected to produce images with significantly higher SNR than competing fixed geometries at matched total acquisition time.