Infrared Retrievals of Ice Cloud Properties and Uncertainties with an Optimal Estimation Retrieval Method

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.

2014-12-01

We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.

Linear information retrieval method in X-ray grating-based phase contrast imaging and its interchangeability with tomographic reconstruction

NASA Astrophysics Data System (ADS)

Wu, Z.; Gao, K.; Wang, Z. L.; Shao, Q. G.; Hu, R. F.; Wei, C. X.; Zan, G. B.; Wali, F.; Luo, R. H.; Zhu, P. P.; Tian, Y. C.

2017-06-01

In X-ray grating-based phase contrast imaging, information retrieval is necessary for quantitative research, especially for phase tomography. However, numerous and repetitive processes have to be performed for tomographic reconstruction. In this paper, we report a novel information retrieval method, which enables retrieving phase and absorption information by means of a linear combination of two mutually conjugate images. Thanks to the distributive law of the multiplication as well as the commutative law and associative law of the addition, the information retrieval can be performed after tomographic reconstruction, thus simplifying the information retrieval procedure dramatically. The theoretical model of this method is established in both parallel beam geometry for Talbot interferometer and fan beam geometry for Talbot-Lau interferometer. Numerical experiments are also performed to confirm the feasibility and validity of the proposed method. In addition, we discuss its possibility in cone beam geometry and its advantages compared with other methods. Moreover, this method can also be employed in other differential phase contrast imaging methods, such as diffraction enhanced imaging, non-interferometric imaging, and edge illumination.

Content-based cell pathology image retrieval by combining different features

NASA Astrophysics Data System (ADS)

Zhou, Guangquan; Jiang, Lu; Luo, Limin; Bao, Xudong; Shu, Huazhong

2004-04-01

Content Based Color Cell Pathology Image Retrieval is one of the newest computer image processing applications in medicine. Recently, some algorithms have been developed to achieve this goal. Because of the particularity of cell pathology images, the result of the image retrieval based on single characteristic is not satisfactory. A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed. Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation and mathematics morphology. The features that include color, texture and morphologic features are extracted from single leukocyte to represent main attribute in the search query. The features are then normalized because the numerical value range and physical meaning of extracted features are different. Finally, the relevance feedback system is introduced. So that the system can automatically adjust the weights of different features and improve the results of retrieval system according to the feedback information. Retrieval results using the proposed method fit closely with human perception and are better than those obtained with the methods based on single feature.

Propagation based phase retrieval of simulated intensity measurements using artificial neural networks

NASA Astrophysics Data System (ADS)

Kemp, Z. D. C.

2018-04-01

Determining the phase of a wave from intensity measurements has many applications in fields such as electron microscopy, visible light optics, and medical imaging. Propagation based phase retrieval, where the phase is obtained from defocused images, has shown significant promise. There are, however, limitations in the accuracy of the retrieved phase arising from such methods. Sources of error include shot noise, image misalignment, and diffraction artifacts. We explore the use of artificial neural networks (ANNs) to improve the accuracy of propagation based phase retrieval algorithms applied to simulated intensity measurements. We employ a phase retrieval algorithm based on the transport-of-intensity equation to obtain the phase from simulated micrographs of procedurally generated specimens. We then train an ANN with pairs of retrieved and exact phases, and use the trained ANN to process a test set of retrieved phase maps. The total error in the phase is significantly reduced using this method. We also discuss a variety of potential extensions to this work.

Generating Concise Rules for Human Motion Retrieval

NASA Astrophysics Data System (ADS)

Mukai, Tomohiko; Wakisaka, Ken-Ichi; Kuriyama, Shigeru

This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.

n-Gram-Based Indexing for Korean Text Retrieval.

ERIC Educational Resources Information Center

Lee, Joon Ho; Cho, Hyun Yang; Park, Hyouk Ro

1999-01-01

Discusses indexing methods in Korean text retrieval and proposes a new indexing method based on n-grams which can handle compound nouns effectively without dictionaries and complex linguistic knowledge. Experimental results show that n-gram-based indexing is considerably faster than morpheme-based indexing, and also provides better retrieval…

Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images.

PubMed

Xu, Yingying; Lin, Lanfen; Hu, Hongjie; Wang, Dan; Zhu, Wenchao; Wang, Jian; Han, Xian-Hua; Chen, Yen-Wei

2018-01-01

The bag of visual words (BoVW) model is a powerful tool for feature representation that can integrate various handcrafted features like intensity, texture, and spatial information. In this paper, we propose a novel BoVW-based method that incorporates texture and spatial information for the content-based image retrieval to assist radiologists in clinical diagnosis. This paper presents a texture-specific BoVW method to represent focal liver lesions (FLLs). Pixels in the region of interest (ROI) are classified into nine texture categories using the rotation-invariant uniform local binary pattern method. The BoVW-based features are calculated for each texture category. In addition, a spatial cone matching (SCM)-based representation strategy is proposed to describe the spatial information of the visual words in the ROI. In a pilot study, eight radiologists with different clinical experience performed diagnoses for 20 cases with and without the top six retrieved results. A total of 132 multiphase computed tomography volumes including five pathological types were collected. The texture-specific BoVW was compared to other BoVW-based methods using the constructed dataset of FLLs. The results show that our proposed model outperforms the other three BoVW methods in discriminating different lesions. The SCM method, which adds spatial information to the orderless BoVW model, impacted the retrieval performance. In the pilot trial, the average diagnosis accuracy of the radiologists was improved from 66 to 80% using the retrieval system. The preliminary results indicate that the texture-specific features and the SCM-based BoVW features can effectively characterize various liver lesions. The retrieval system has the potential to improve the diagnostic accuracy and the confidence of the radiologists.

Content-Based Medical Image Retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Deserno, Thomas M.

This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

Brain CT image similarity retrieval method based on uncertain location graph.

PubMed

Pan, Haiwei; Li, Pengyuan; Li, Qing; Han, Qilong; Feng, Xiaoning; Gao, Linlin

2014-03-01

A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases. However, the similarity retrieval for brain CT images requires much higher accuracy than the general images. In this paper, a new model of uncertain location graph (ULG) is presented for brain CT image modeling and similarity retrieval. According to the characteristics of brain CT image, we propose a novel method to model brain CT image to ULG based on brain CT image texture. Then, a scheme for ULG similarity retrieval is introduced. Furthermore, an effective index structure is applied to reduce the searching time. Experimental results reveal that our method functions well on brain CT images similarity retrieval with higher accuracy and efficiency.

An integrated content and metadata based retrieval system for art.

PubMed

Lewis, Paul H; Martinez, Kirk; Abas, Fazly Salleh; Fauzi, Mohammad Faizal Ahmad; Chan, Stephen C Y; Addis, Matthew J; Boniface, Mike J; Grimwood, Paul; Stevenson, Alison; Lahanier, Christian; Stevenson, James

2004-03-01

A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.

A content-based news video retrieval system: NVRS

NASA Astrophysics Data System (ADS)

Liu, Huayong; He, Tingting

2009-10-01

This paper focus on TV news programs and design a content-based news video browsing and retrieval system, NVRS, which is convenient for users to fast browsing and retrieving news video by different categories such as political, finance, amusement, etc. Combining audiovisual features and caption text information, the system automatically segments a complete news program into separate news stories. NVRS supports keyword-based news story retrieval, category-based news story browsing and generates key-frame-based video abstract for each story. Experiments show that the method of story segmentation is effective and the retrieval is also efficient.

An Abstraction-Based Data Model for Information Retrieval

NASA Astrophysics Data System (ADS)

McAllister, Richard A.; Angryk, Rafal A.

Language ontologies provide an avenue for automated lexical analysis that may be used to supplement existing information retrieval methods. This paper presents a method of information retrieval that takes advantage of WordNet, a lexical database, to generate paths of abstraction, and uses them as the basis for an inverted index structure to be used in the retrieval of documents from an indexed corpus. We present this method as a entree to a line of research on using ontologies to perform word-sense disambiguation and improve the precision of existing information retrieval techniques.

Music Retrieval Based on the Relation between Color Association and Lyrics

NASA Astrophysics Data System (ADS)

Nakamur, Tetsuaki; Utsumi, Akira; Sakamoto, Maki

Various methods for music retrieval have been proposed. Recently, many researchers are tackling developing methods based on the relationship between music and feelings. In our previous psychological study, we found that there was a significant correlation between colors evoked from songs and colors evoked only from lyrics, and showed that the music retrieval system using lyrics could be developed. In this paper, we focus on the relationship among music, lyrics and colors, and propose a music retrieval method using colors as queries and analyzing lyrics. This method estimates colors evoked from songs by analyzing lyrics of the songs. On the first step of our method, words associated with colors are extracted from lyrics. We assumed two types of methods to extract words associated with colors. In the one of two methods, the words are extracted based on the result of a psychological experiment. In the other method, in addition to the words extracted based on the result of the psychological experiment, the words from corpora for the Latent Semantic Analysis are extracted. On the second step, colors evoked from the extracted words are compounded, and the compounded colors are regarded as those evoked from the song. On the last step, colors as queries are compared with colors estimated from lyrics, and the list of songs is presented based on similarities. We evaluated the two methods described above and found that the method based on the psychological experiment and corpora performed better than the method only based on the psychological experiment. As a result, we showed that the method using colors as queries and analyzing lyrics is effective for music retrieval.

Selecting relevant 3D image features of margin sharpness and texture for lung nodule retrieval.

PubMed

Ferreira, José Raniery; de Azevedo-Marques, Paulo Mazzoncini; Oliveira, Marcelo Costa

2017-03-01

Lung cancer is the leading cause of cancer-related deaths in the world. Its diagnosis is a challenge task to specialists due to several aspects on the classification of lung nodules. Therefore, it is important to integrate content-based image retrieval methods on the lung nodule classification process, since they are capable of retrieving similar cases from databases that were previously diagnosed. However, this mechanism depends on extracting relevant image features in order to obtain high efficiency. The goal of this paper is to perform the selection of 3D image features of margin sharpness and texture that can be relevant on the retrieval of similar cancerous and benign lung nodules. A total of 48 3D image attributes were extracted from the nodule volume. Border sharpness features were extracted from perpendicular lines drawn over the lesion boundary. Second-order texture features were extracted from a cooccurrence matrix. Relevant features were selected by a correlation-based method and a statistical significance analysis. Retrieval performance was assessed according to the nodule's potential malignancy on the 10 most similar cases and by the parameters of precision and recall. Statistical significant features reduced retrieval performance. Correlation-based method selected 2 margin sharpness attributes and 6 texture attributes and obtained higher precision compared to all 48 extracted features on similar nodule retrieval. Feature space dimensionality reduction of 83 % obtained higher retrieval performance and presented to be a computationaly low cost method of retrieving similar nodules for the diagnosis of lung cancer.

Retrieving the aerosol lidar ratio profile by combining ground- and space-based elastic lidars.

PubMed

Feiyue, Mao; Wei, Gong; Yingying, Ma

2012-02-15

The aerosol lidar ratio is a key parameter for the retrieval of aerosol optical properties from elastic lidar, which changes largely for aerosols with different chemical and physical properties. We proposed a method for retrieving the aerosol lidar ratio profile by combining simultaneous ground- and space-based elastic lidars. The method was tested by a simulated case and a real case at 532 nm wavelength. The results demonstrated that our method is robust and can obtain accurate lidar ratio and extinction coefficient profiles. Our method can be useful for determining the local and global lidar ratio and validating space-based lidar datasets.

A graph-based approach for the retrieval of multi-modality medical images.

PubMed

Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

2014-02-01

In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state-of-the-art methods such as visual words using the scale- invariant feature transform (SIFT) and relational matrices representing the spatial arrangements of objects. Copyright © 2013 Elsevier B.V. All rights reserved.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

PubMed

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm

PubMed Central

Song, Wei; Mei, Haibin

2017-01-01

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient. PMID:28737699

Broadband Phase Retrieval for Image-Based Wavefront Sensing

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A focus-diverse phase-retrieval algorithm has been shown to perform adequately for the purpose of image-based wavefront sensing when (1) broadband light (typically spanning the visible spectrum) is used in forming the images by use of an optical system under test and (2) the assumption of monochromaticity is applied to the broadband image data. Heretofore, it had been assumed that in order to obtain adequate performance, it is necessary to use narrowband or monochromatic light. Some background information, including definitions of terms and a brief description of pertinent aspects of image-based phase retrieval, is prerequisite to a meaningful summary of the present development. Phase retrieval is a general term used in optics to denote estimation of optical imperfections or aberrations of an optical system under test. The term image-based wavefront sensing refers to a general class of algorithms that recover optical phase information, and phase-retrieval algorithms constitute a subset of this class. In phase retrieval, one utilizes the measured response of the optical system under test to produce a phase estimate. The optical response of the system is defined as the image of a point-source object, which could be a star or a laboratory point source. The phase-retrieval problem is characterized as image-based in the sense that a charge-coupled-device camera, preferably of scientific imaging quality, is used to collect image data where the optical system would normally form an image. In a variant of phase retrieval, denoted phase-diverse phase retrieval [which can include focus-diverse phase retrieval (in which various defocus planes are used)], an additional known aberration (or an equivalent diversity function) is superimposed as an aid in estimating unknown aberrations by use of an image-based wavefront-sensing algorithm. Image-based phase-retrieval differs from such other wavefront-sensing methods, such as interferometry, shearing interferometry, curvature wavefront sensing, and Shack-Hartmann sensing, all of which entail disadvantages in comparison with image-based methods. The main disadvantages of these non-image based methods are complexity of test equipment and the need for a wavefront reference.

Web-based multimedia information retrieval for clinical application research

NASA Astrophysics Data System (ADS)

Cao, Xinhua; Hoo, Kent S., Jr.; Zhang, Hong; Ching, Wan; Zhang, Ming; Wong, Stephen T. C.

2001-08-01

We described a web-based data warehousing method for retrieving and analyzing neurological multimedia information. The web-based method supports convenient access, effective search and retrieval of clinical textual and image data, and on-line analysis. To improve the flexibility and efficiency of multimedia information query and analysis, a three-tier, multimedia data warehouse for epilepsy research has been built. The data warehouse integrates clinical multimedia data related to epilepsy from disparate sources and archives them into a well-defined data model.

Research on keyword retrieval method of HBase database based on index structure

NASA Astrophysics Data System (ADS)

Gong, Pijin; Lv, Congmin; Gong, Yongsheng; Ma, Haozhi; Sun, Yang; Wang, Lu

2017-10-01

With the rapid development of manned spaceflight engineering, the scientific experimental data in space application system is increasing rapidly. How to efficiently query the specific data in the mass data volume has become a problem. In this paper, a method of retrieving the object data based on the object attribute as the keyword is proposed. The HBase database is used to store the object data and object attributes, and the secondary index is constructed. The research shows that this method is a good way to retrieve specified data based on object attributes.

Connectionist Interaction Information Retrieval.

ERIC Educational Resources Information Center

Dominich, Sandor

2003-01-01

Discussion of connectionist views for adaptive clustering in information retrieval focuses on a connectionist clustering technique and activation spreading-based information retrieval model using the interaction information retrieval method. Presents theoretical as well as simulation results as regards computational complexity and includes…

The "RED Versa NIR" Plane to Retrieve Broken-Cloud Optical Depth from Ground-Based Measurements"

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Evans, K.; Wiscombe, W.

2003-01-01

A new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (MR) spectral regions is introduced. Because zenith radiance does not have a one-to-one relationship with optical depth, it is absolutely impossible to use a monochromatic retrieval. On the other side, algebraic combinations of spectral radiances such as NDCI while largely removing nouniquiness and the radiative effects of cloud inhomogeneity, can result in poor retrievals due to its insensitivity to cloud fraction. Instead, both RED and NIR radiances as points on the 'RED vs. NIR' plane are proposed to be used for retrieval. The proposed retrieval method is applied to Cimel measurements at the Atmospheric Radiation Measurements (ARM) site in Oklahoma. Cimel, a multi-channel sunphotometer, is a part of AERONET - a ground-based network for monitoring aerosol optical properties. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and Multi-Filter Rotating Shadowband Radiometers (MFRSR) located next to Cimel at the ARM site. In addition, the performance of the retrieval method is assessed using a fractal model of cloud inhomogeneity and broken cloudiness. The preliminary results look very promising both theoretically and from measurements.

Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu

2017-07-01

In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content-based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate, and fast retrieval method for a breast histopathological image. Specifically, the method presents a local statistical feature of nuclei for morphology and distribution of nuclei, and employs the Gabor feature to describe the texture information. The latent Dirichlet allocation model is utilized for high-level semantic mining. Locality-sensitive hashing is used to speed up the search. Experiments on a WSI database with more than 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, and WSI archiving and management.

A humming retrieval system based on music fingerprint

NASA Astrophysics Data System (ADS)

Han, Xingkai; Cao, Baiyu

2011-10-01

In this paper, we proposed an improved music information retrieval method utilizing the music fingerprint. The goal of this method is to represent the music with compressed musical information. Based on the selected MIDI files, which are generated automatically as our music target database, we evaluate the accuracy, effectiveness, and efficiency of this method. In this research we not only extract the feature sequence, which can represent the file effectively, from the query and melody database, but also make it possible for retrieving the results in an innovative way. We investigate on the influence of noise to the performance of our system. As experimental result shows, the retrieval accuracy arriving at up to91% without noise is pretty well

Medical image retrieval system using multiple features from 3D ROIs

NASA Astrophysics Data System (ADS)

Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

2012-02-01

Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

Latent Semantic Analysis as a Method of Content-Based Image Retrieval in Medical Applications

ERIC Educational Resources Information Center

Makovoz, Gennadiy

2010-01-01

The research investigated whether a Latent Semantic Analysis (LSA)-based approach to image retrieval can map pixel intensity into a smaller concept space with good accuracy and reasonable computational cost. From a large set of M computed tomography (CT) images, a retrieval query found all images for a particular patient based on semantic…

Retrieval evaluation and distance learning from perceived similarity between endomicroscopy videos.

PubMed

André, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2011-01-01

Evaluating content-based retrieval (CBR) is challenging because it requires an adequate ground-truth. When the available groundtruth is limited to textual metadata such as pathological classes, retrieval results can only be evaluated indirectly, for example in terms of classification performance. In this study we first present a tool to generate perceived similarity ground-truth that enables direct evaluation of endomicroscopic video retrieval. This tool uses a four-points Likert scale and collects subjective pairwise similarities perceived by multiple expert observers. We then evaluate against the generated ground-truth a previously developed dense bag-of-visual-words method for endomicroscopic video retrieval. Confirming the results of previous indirect evaluation based on classification, our direct evaluation shows that this method significantly outperforms several other state-of-the-art CBR methods. In a second step, we propose to improve the CBR method by learning an adjusted similarity metric from the perceived similarity ground-truth. By minimizing a margin-based cost function that differentiates similar and dissimilar video pairs, we learn a weight vector applied to the visual word signatures of videos. Using cross-validation, we demonstrate that the learned similarity distance is significantly better correlated with the perceived similarity than the original visual-word-based distance.

Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

ERIC Educational Resources Information Center

Wang, James Z.; Du, Yanping

Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

A diagram retrieval method with multi-label learning

NASA Astrophysics Data System (ADS)

Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

2015-01-01

In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

A Wiener-Wavelet-Based filter for de-noising satellite soil moisture retrievals

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Ciabatta, Luca; Moramarco, Tommaso; Su, Chun-Hsu; Ryu, Dongryeol; Wagner, Wolfgang

2014-05-01

The reduction of noise in microwave satellite soil moisture (SM) retrievals is of paramount importance for practical applications especially for those associated with the study of climate changes, droughts, floods and other related hydrological processes. So far, Fourier based methods have been used for de-noising satellite SM retrievals by filtering either the observed emissivity time series (Du, 2012) or the retrieved SM observations (Su et al. 2013). This contribution introduces an alternative approach based on a Wiener-Wavelet-Based filtering (WWB) technique, which uses the Entropy-Based Wavelet de-noising method developed by Sang et al. (2009) to design both a causal and a non-causal version of the filter. WWB is used as a post-retrieval processing tool to enhance the quality of observations derived from the i) Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E), ii) the Advanced SCATterometer (ASCAT), and iii) the Soil Moisture and Ocean Salinity (SMOS) satellite. The method is tested on three pilot sites located in Spain (Remedhus Network), in Greece (Hydrological Observatory of Athens) and in Australia (Oznet network), respectively. Different quantitative criteria are used to judge the goodness of the de-noising technique. Results show that WWB i) is able to improve both the correlation and the root mean squared differences between satellite retrievals and in situ soil moisture observations, and ii) effectively separates random noise from deterministic components of the retrieved signals. Moreover, the use of WWB de-noised data in place of raw observations within a hydrological application confirms the usefulness of the proposed filtering technique. Du, J. (2012), A method to improve satellite soil moisture retrievals based on Fourier analysis, Geophys. Res. Lett., 39, L15404, doi:10.1029/ 2012GL052435 Su,C.-H.,D.Ryu, A. W. Western, and W. Wagner (2013), De-noising of passive and active microwave satellite soil moisture time series, Geophys. Res. Lett., 40,3624-3630, doi:10.1002/grl.50695. Sang Y.-F., D. Wang, J.-C. Wu, Q.-P. Zhu, and L. Wang (2009), Entropy-Based Wavelet De-noising Method for Time Series Analysis, Entropy, 11, pp. 1123-1148, doi:10.3390/e11041123.

A new method of content based medical image retrieval and its applications to CT imaging sign retrieval.

PubMed

Ma, Ling; Liu, Xiabi; Gao, Yan; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu

2017-02-01

This paper proposes a new method of content based medical image retrieval through considering fused, context-sensitive similarity. Firstly, we fuse the semantic and visual similarities between the query image and each image in the database as their pairwise similarities. Then, we construct a weighted graph whose nodes represent the images and edges measure their pairwise similarities. By using the shortest path algorithm over the weighted graph, we obtain a new similarity measure, context-sensitive similarity measure, between the query image and each database image to complete the retrieval process. Actually, we use the fused pairwise similarity to narrow down the semantic gap for obtaining a more accurate pairwise similarity measure, and spread it on the intrinsic data manifold to achieve the context-sensitive similarity for a better retrieval performance. The proposed method has been evaluated on the retrieval of the Common CT Imaging Signs of Lung Diseases (CISLs) and achieved not only better retrieval results but also the satisfactory computation efficiency. Copyright © 2017 Elsevier Inc. All rights reserved.

Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning

NASA Astrophysics Data System (ADS)

Okamura, Rintaro; Iwabuchi, Hironobu; Schmidt, K. Sebastian

2017-12-01

Three-dimensional (3-D) radiative-transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. The challenge is that 3-D effects manifest themselves across multiple satellite pixels, which traditional single-pixel approaches cannot capture. In this study, we present two multi-pixel retrieval approaches based on deep learning, a technique that is becoming increasingly successful for complex problems in engineering and other areas. Specifically, we use deep neural networks (DNNs) to obtain multi-pixel estimates of cloud optical thickness and column-mean cloud droplet effective radius from multispectral, multi-pixel radiances. The first DNN method corrects traditional bispectral retrievals based on the plane-parallel homogeneous cloud assumption using the reflectances at the same two wavelengths. The other DNN method uses so-called convolutional layers and retrieves cloud properties directly from the reflectances at four wavelengths. The DNN methods are trained and tested on cloud fields from large-eddy simulations used as input to a 3-D radiative-transfer model to simulate upward radiances. The second DNN-based retrieval, sidestepping the bispectral retrieval step through convolutional layers, is shown to be more accurate. It reduces 3-D radiative-transfer effects that would otherwise affect the radiance values and estimates cloud properties robustly even for optically thick clouds.

Ground-based remote sensing of thin clouds in the Arctic

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Zhao, C.

2013-05-01

This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" at 862.5 cm-1, 935.8 cm-1, and 988.4 cm-1 where absorption by water vapour is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in the first two of these micro-windows, constrained by the transmission through clouds of primarily stratospheric ozone emission at 1040 cm-1. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius re, visible optical depth τ, number concentration N, and water path WP are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement programme (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with both ground-based microwave radiometer measurements of liquid water path and a method that uses combined shortwave and microwave measurements to retrieve re, τ and N. Compared to other retrieval methods, advantages of this technique include its ability to characterise thin clouds year round, that water vapour is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies and that it relies on a fairly comprehensive suite of ground based measurements.

Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations

NASA Astrophysics Data System (ADS)

Rusli, Stephanie P.; Donovan, David P.; Russchenberg, Herman W. J.

2017-12-01

Despite the importance of radar reflectivity (Z) measurements in the retrieval of liquid water cloud properties, it remains nontrivial to interpret Z due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work that utilizes Z to identify the presence of drizzle above the cloud base in an optimized and a physically consistent manner. In this work, we develop a retrieval technique that exploits the synergy of different remote sensing systems to carry out this task and to subsequently profile the microphysical properties of the cloud and drizzle in a unified framework. This is accomplished by using ground-based measurements of Z, lidar attenuated backscatter below as well as above the cloud base, and microwave brightness temperatures. Fast physical forward models coupled to cloud and drizzle structure parameterization are used in an optimal-estimation-type framework in order to retrieve the best estimate for the cloud and drizzle property profiles. The cloud retrieval is first evaluated using synthetic signals generated from large-eddy simulation (LES) output to verify the forward models used in the retrieval procedure and the vertical parameterization of the liquid water content (LWC). From this exercise it is found that, on average, the cloud properties can be retrieved within 5 % of the mean truth. The full cloud-drizzle retrieval method is then applied to a selected ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign dataset collected in Cabauw, the Netherlands. An assessment of the retrieval products is performed using three independent methods from the literature; each was specifically developed to retrieve only the cloud properties, the drizzle properties below the cloud base, or the drizzle fraction within the cloud. One-to-one comparisons, taking into account the uncertainties or limitations of each retrieval, show that our results are consistent with what is derived using the three independent methods.

A framework based on 2-D Taylor expansion for quantifying the impacts of subpixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method

NASA Astrophysics Data System (ADS)

Zhang, Z.; Werner, F.; Cho, H.-M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, K.

2016-06-01

The bispectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VIS/NIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring subpixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In the literature, the retrievals of τ and re are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on τ is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on re only by the subpixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of subpixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how subpixel cloud reflectance variations impact the τ and re retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from subpixel reflectance variations in operational satellite cloud products and to help understand the differences in τ and re retrievals between two instruments.

A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method

NASA Technical Reports Server (NTRS)

Zhang, Z.; Werner, F.; Cho, H. -M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

2016-01-01

The bi-spectral method retrieves cloud optical thickness and cloud droplet effective radius simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VISNIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved and re. In the literature, the retrievals of and re are often assumed to be independent and considered separately when investigating the impact of sub-pixel cloud reflectance variations on the bi-spectral method. As a result, the impact on is contributed only by the sub-pixel variation of VISNIR band reflectance and the impact on re only by the sub-pixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VISNIR and SWIR cloud reflectances and their covariance on the and re retrievals. This framework takes into account the fact that the retrievals are determined by both VISNIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VISNIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from sub-pixel reflectance variations in operational satellite cloud products and to help understand the differences in and re retrievals between two instruments.

A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Subpixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bispectral Method

NASA Technical Reports Server (NTRS)

Zhang, Z.; Werner, F.; Cho, H.-M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, K.

2016-01-01

The bispectral method retrieves cloud optical thickness (t) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VIS/NIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring subpixel variations of cloud reflectances can lead to a significant bias in the retrieved t and re. In the literature, the retrievals of t and re are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on t is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on re only by the subpixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of subpixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the t and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how subpixel cloud reflectance variations impact the t and re retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from subpixel reflectance variations in operational satellite cloud products and to help understand the differences in t and re retrievals between two instruments.

Spaced-antenna wind estimation using an X-band active phased-array weather radar

NASA Astrophysics Data System (ADS)

Venkatesh, Vijay

Over the past few decades, several single radar methods have been developed to probe the kinematic structure of storms. All these methods trade angular-resolution to retrieve the wind-field. To date, the spaced-antenna method has been employed for profiling the ionosphere and the precipitation free lower atmosphere. This work focuses on applying the spaced-antenna method on an X-band active phased-array radar for high resolution horizontal wind-field retrieval from precipitation echoes. The ability to segment the array face into multiple displaced apertures allows for flexible spaced-antenna implementations. The methodology employed herein comprises of Monte-Carlo simulations to optimize the spaced-antenna system design and analysis of real data collected with the designed phased-array system. The contribution that underpins this dissertation is the demonstration of qualitative agreement between spaced-antenna and Doppler beam swinging retrievals based on real data. First, simulations of backscattered electric fields at the antenna array elements are validated using theoretical expressions. Based on the simulations, the degrees of freedom in the spaced-antenna system design are optimized for retrieval of mean baseline wind. We show that the designed X-band spaced-antenna system has lower retrieval uncertainty than the existing S-band spaced-antenna implementation on the NWRT. This is because of the flexibility to synthesize small overlapping apertures and the ability to obtain statistically independent samples at a faster rate at X-band. We then demonstrate a technique to make relative phase-center displacement measurements based on simulations and real data from the phased-array spaced-antenna system. This simple method uses statistics of precipitation echoes and apriori beamwidth measurements to make field repeatable phase-center displacement measurements. Finally, we test the hypothesis that wind-field curvature effects are common to both the spaced-antenna and Doppler beam swinging methods. Based on a close-range winter storm data set, we find that the spaced-antenna and fine-resolution Doppler beam swinging retrievals are in qualitative agreement. The correlation between the spaced-antenna and fine-resolution Doppler beam swinging retrievals was 0.57. The lowered correlation coefficient was, in part, due to the high standard deviation of the DBS retrievals. At high wind-speeds, the spaced-antenna retrievals significantly departed from variational retrievals of mean baseline wind.

The Community Cloud retrieval for CLimate (CC4CL) - Part 2: The optimal estimation approach

NASA Astrophysics Data System (ADS)

McGarragh, Gregory R.; Poulsen, Caroline A.; Thomas, Gareth E.; Povey, Adam C.; Sus, Oliver; Stapelberg, Stefan; Schlundt, Cornelia; Proud, Simon; Christensen, Matthew W.; Stengel, Martin; Hollmann, Rainer; Grainger, Roy G.

2018-06-01

The Community Cloud retrieval for Climate (CC4CL) is a cloud property retrieval system for satellite-based multispectral imagers and is an important component of the Cloud Climate Change Initiative (Cloud_cci) project. In this paper we discuss the optimal estimation retrieval of cloud optical thickness, effective radius and cloud top pressure based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. Key to this method is the forward model, which includes the clear-sky model, the liquid water and ice cloud models, the surface model including a bidirectional reflectance distribution function (BRDF), and the "fast" radiative transfer solution (which includes a multiple scattering treatment). All of these components and their assumptions and limitations will be discussed in detail. The forward model provides the accuracy appropriate for our retrieval method. The errors are comparable to the instrument noise for cloud optical thicknesses greater than 10. At optical thicknesses less than 10 modeling errors become more significant. The retrieval method is then presented describing optimal estimation in general, the nonlinear inversion method employed, measurement and a priori inputs, the propagation of input uncertainties and the calculation of subsidiary quantities that are derived from the retrieval results. An evaluation of the retrieval was performed using measurements simulated with noise levels appropriate for the MODIS instrument. Results show errors less than 10 % for cloud optical thicknesses greater than 10. Results for clouds of optical thicknesses less than 10 have errors up to 20 %.

Compressed domain indexing of losslessly compressed images

NASA Astrophysics Data System (ADS)

Schaefer, Gerald

2001-12-01

Image retrieval and image compression have been pursued separately in the past. Only little research has been done on a synthesis of the two by allowing image retrieval to be performed directly in the compressed domain of images without the need to uncompress them first. In this paper methods for image retrieval in the compressed domain of losslessly compressed images are introduced. While most image compression techniques are lossy, i.e. discard visually less significant information, lossless techniques are still required in fields like medical imaging or in situations where images must not be changed due to legal reasons. The algorithms in this paper are based on predictive coding methods where a pixel is encoded based on the pixel values of its (already encoded) neighborhood. The first method is based on an understanding that predictively coded data is itself indexable and represents a textural description of the image. The second method operates directly on the entropy encoded data by comparing codebooks of images. Experiments show good image retrieval results for both approaches.

A novel content-based medical image retrieval method based on query topic dependent image features (QTDIF)

NASA Astrophysics Data System (ADS)

Xiong, Wei; Qiu, Bo; Tian, Qi; Mueller, Henning; Xu, Changsheng

2005-04-01

Medical image retrieval is still mainly a research domain with a large variety of applications and techniques. With the ImageCLEF 2004 benchmark, an evaluation framework has been created that includes a database, query topics and ground truth data. Eleven systems (with a total of more than 50 runs) compared their performance in various configurations. The results show that there is not any one feature that performs well on all query tasks. Key to successful retrieval is rather the selection of features and feature weights based on a specific set of input features, thus on the query task. In this paper we propose a novel method based on query topic dependent image features (QTDIF) for content-based medical image retrieval. These feature sets are designed to capture both inter-category and intra-category statistical variations to achieve good retrieval performance in terms of recall and precision. We have used Gaussian Mixture Models (GMM) and blob representation to model medical images and construct the proposed novel QTDIF for CBIR. Finally, trained multi-class support vector machines (SVM) are used for image similarity ranking. The proposed methods have been tested over the Casimage database with around 9000 images, for the given 26 image topics, used for imageCLEF 2004. The retrieval performance has been compared with the medGIFT system, which is based on the GNU Image Finding Tool (GIFT). The experimental results show that the proposed QTDIF-based CBIR can provide significantly better performance than systems based general features only.

A differential optical absorption spectroscopy method for retrieval from ground-based Fourier transform spectrometers measurements of the direct solar beam

NASA Astrophysics Data System (ADS)

Huo, Yanfeng; Duan, Minzheng; Tian, Wenshou; Min, Qilong

2015-08-01

A differential optical absorption spectroscopy (DOAS)-like algorithm is developed to retrieve the column-averaged dryair mole fraction of carbon dioxide from ground-based hyper-spectral measurements of the direct solar beam. Different to the spectral fitting method, which minimizes the difference between the observed and simulated spectra, the ratios of multiple channel-pairs—one weak and one strong absorption channel—are used to retrieve from measurements of the shortwave infrared (SWIR) band. Based on sensitivity tests, a super channel-pair is carefully selected to reduce the effects of solar lines, water vapor, air temperature, pressure, instrument noise, and frequency shift on retrieval errors. The new algorithm reduces computational cost and the retrievals are less sensitive to temperature and H2O uncertainty than the spectral fitting method. Multi-day Total Carbon Column Observing Network (TCCON) measurements under clear-sky conditions at two sites (Tsukuba and Bremen) are used to derive xxxx for the algorithm evaluation and validation. The DOAS-like results agree very well with those of the TCCON algorithm after correction of an airmass-dependent bias.

Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma.

PubMed

Caldas, José; Gehlenborg, Nils; Kettunen, Eeva; Faisal, Ali; Rönty, Mikko; Nicholson, Andrew G; Knuutila, Sakari; Brazma, Alvis; Kaski, Samuel

2012-01-15

Genome-wide measurement of transcript levels is an ubiquitous tool in biomedical research. As experimental data continues to be deposited in public databases, it is becoming important to develop search engines that enable the retrieval of relevant studies given a query study. While retrieval systems based on meta-data already exist, data-driven approaches that retrieve studies based on similarities in the expression data itself have a greater potential of uncovering novel biological insights. We propose an information retrieval method based on differential expression. Our method deals with arbitrary experimental designs and performs competitively with alternative approaches, while making the search results interpretable in terms of differential expression patterns. We show that our model yields meaningful connections between biological conditions from different studies. Finally, we validate a previously unknown connection between malignant pleural mesothelioma and SIM2s suggested by our method, via real-time polymerase chain reaction in an independent set of mesothelioma samples. Supplementary data and source code are available from http://www.ebi.ac.uk/fg/research/rex.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-02-16

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less

Concept-Based Retrieval from Critical Incident Reports.

PubMed

Denecke, Kerstin

2017-01-01

Critical incident reporting systems (CIRS) are used as a means to collect anonymously entered information of incidents that occurred for example in a hospital. Analyzing this information helps to identify among others problems in the workflow, in the infrastructure or in processes. The entire potential of these sources of experiential knowledge remains often unconsidered since retrieval of relevant reports and their analysis is difficult and time-consuming, and the reporting systems often do not provide support for these tasks. The objective of this work is to develop a method for retrieving reports from the CIRS related to a specific user query. atural language processing (NLP) and information retrieval (IR) methods are exploited for realizing the retrieval. We compare standard retrieval methods that rely upon frequency of words with an approach that includes a semantic mapping of natural language to concepts of a medical ontology. By an evaluation, we demonstrate the feasibility of semantic document enrichment to improve recall in incident reporting retrieval. It is shown that a combination of standard keyword-based retrieval with semantic search results in highly satisfactory recall values. In future work, the evaluation should be repeated on a larger data set and real-time user evaluation need to be performed to assess user satisfactory with the system and results.

[Retrieve of red tide distributions from MODIS data based on the characteristics of water spectrum].

PubMed

Qiu, Zhong-Feng; Cui, Ting-Wei; He, Yi-Jun

2011-08-01

After comparing the spectral differences between red tide water and normal water, we developed a method to retrieve red tide distributions from MODIS data based on the characteristics of red tide water spectrum. The authors used the 119 series of in situ observations to validate the method and found that only one observation has not been detected correctly. The authors then applied this method to MODIS data on April 4, 2005. In the research areas three locations of red tide water were apparently detected with the total areas about 2 000 km2. The retrieved red tide distributions are in good agreement with the distributions of high chlorophyll a concentrations. The research suggests that the method is available to eliminating the influence of suspended sediments and can be used to retrieve the locations and areas of red tide water.

A framework for quantifying the impacts of sub-pixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bi-spectral method

NASA Astrophysics Data System (ADS)

Zhang, Z.; Werner, F.; Cho, H.-M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

2017-02-01

The so-called bi-spectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

A Framework for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method.

NASA Technical Reports Server (NTRS)

Zhang, Z; Werner, F.; Cho, H. -M.; Wind, Galina; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

2017-01-01

The so-called bi-spectral method retrieves cloud optical thickness (t) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved t and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the t and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the t and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

Efficient view based 3-D object retrieval using Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jain, Yogendra Kumar; Singh, Roshan Kumar

2013-12-01

Recent research effort has been dedicated to view based 3-D object retrieval, because of highly discriminative property of 3-D object and has multi view representation. The state-of-art method is highly depending on their own camera array setting for capturing views of 3-D object and use complex Zernike descriptor, HAC for representative view selection which limit their practical application and make it inefficient for retrieval. Therefore, an efficient and effective algorithm is required for 3-D Object Retrieval. In order to move toward a general framework for efficient 3-D object retrieval which is independent of camera array setting and avoidance of representative view selection, we propose an Efficient View Based 3-D Object Retrieval (EVBOR) method using Hidden Markov Model (HMM). In this framework, each object is represented by independent set of view, which means views are captured from any direction without any camera array restriction. In this, views are clustered (including query view) to generate the view cluster, which is then used to build the query model with HMM. In our proposed method, HMM is used in twofold: in the training (i.e. HMM estimate) and in the retrieval (i.e. HMM decode). The query model is trained by using these view clusters. The EVBOR query model is worked on the basis of query model combining with HMM. The proposed approach remove statically camera array setting for view capturing and can be apply for any 3-D object database to retrieve 3-D object efficiently and effectively. Experimental results demonstrate that the proposed scheme has shown better performance than existing methods. [Figure not available: see fulltext.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Multi-field query expansion is effective for biomedical dataset retrieval.

PubMed

Bouadjenek, Mohamed Reda; Verspoor, Karin

2017-01-01

In the context of the bioCADDIE challenge addressing information retrieval of biomedical datasets, we propose a method for retrieval of biomedical data sets with heterogenous schemas through query reformulation. In particular, the method proposed transforms the initial query into a multi-field query that is then enriched with terms that are likely to occur in the relevant datasets. We compare and evaluate two query expansion strategies, one based on the Rocchio method and another based on a biomedical lexicon. We then perform a comprehensive comparative evaluation of our method on the bioCADDIE dataset collection for biomedical retrieval. We demonstrate the effectiveness of our multi-field query method compared to two baselines, with MAP improved from 0.2171 and 0.2669 to 0.2996. We also show the benefits of query expansion, where the Rocchio expanstion method improves the MAP for our two baselines from 0.2171 and 0.2669 to 0.335. We show that the Rocchio query expansion method slightly outperforms the one based on the biomedical lexicon as a source of terms, with an improvement of roughly 3% for MAP. However, the query expansion method based on the biomedical lexicon is much less resource intensive since it does not require computation of any relevance feedback set or any initial execution of the query. Hence, in term of trade-off between efficiency, execution time and retrieval accuracy, we argue that the query expansion method based on the biomedical lexicon offers the best performance for a prototype biomedical data search engine intended to be used at a large scale. In the official bioCADDIE challenge results, although our approach is ranked seventh in terms of the infNDCG evaluation metric, it ranks second in term of P@10 and NDCG. Hence, the method proposed here provides overall good retrieval performance in relation to the approaches of other competitors. Consequently, the observations made in this paper should benefit the development of a Data Discovery Index prototype or the improvement of the existing one. © The Author(s) 2017. Published by Oxford University Press.

Multi-field query expansion is effective for biomedical dataset retrieval

PubMed Central

2017-01-01

Abstract In the context of the bioCADDIE challenge addressing information retrieval of biomedical datasets, we propose a method for retrieval of biomedical data sets with heterogenous schemas through query reformulation. In particular, the method proposed transforms the initial query into a multi-field query that is then enriched with terms that are likely to occur in the relevant datasets. We compare and evaluate two query expansion strategies, one based on the Rocchio method and another based on a biomedical lexicon. We then perform a comprehensive comparative evaluation of our method on the bioCADDIE dataset collection for biomedical retrieval. We demonstrate the effectiveness of our multi-field query method compared to two baselines, with MAP improved from 0.2171 and 0.2669 to 0.2996. We also show the benefits of query expansion, where the Rocchio expanstion method improves the MAP for our two baselines from 0.2171 and 0.2669 to 0.335. We show that the Rocchio query expansion method slightly outperforms the one based on the biomedical lexicon as a source of terms, with an improvement of roughly 3% for MAP. However, the query expansion method based on the biomedical lexicon is much less resource intensive since it does not require computation of any relevance feedback set or any initial execution of the query. Hence, in term of trade-off between efficiency, execution time and retrieval accuracy, we argue that the query expansion method based on the biomedical lexicon offers the best performance for a prototype biomedical data search engine intended to be used at a large scale. In the official bioCADDIE challenge results, although our approach is ranked seventh in terms of the infNDCG evaluation metric, it ranks second in term of P@10 and NDCG. Hence, the method proposed here provides overall good retrieval performance in relation to the approaches of other competitors. Consequently, the observations made in this paper should benefit the development of a Data Discovery Index prototype or the improvement of the existing one. PMID:29220457

On the VHF Source Retrieval Errors Associated with Lightning Mapping Arrays (LMAs)

NASA Technical Reports Server (NTRS)

Koshak, W.

2016-01-01

This presentation examines in detail the standard retrieval method: that of retrieving the (x, y, z, t) parameters of a lightning VHF point source from multiple ground-based Lightning Mapping Array (LMA) time-of-arrival (TOA) observations. The solution is found by minimizing a chi-squared function via the Levenberg-Marquardt algorithm. The associated forward problem is examined to illustrate the importance of signal-to-noise ratio (SNR). Monte Carlo simulated retrievals are used to assess the benefits of changing various LMA network properties. A generalized retrieval method is also introduced that, in addition to TOA data, uses LMA electric field amplitude measurements to retrieve a transient VHF dipole moment source.

Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval

PubMed Central

Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

2018-01-01

Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie PMID:29688379

Digital adaptive optics confocal microscopy based on iterative retrieval of optical aberration from a guidestar hologram

PubMed Central

Liu, Changgeng; Thapa, Damber; Yao, Xincheng

2017-01-01

Guidestar hologram based digital adaptive optics (DAO) is one recently emerging active imaging modality. It records each complex distorted line field reflected or scattered from the sample by an off-axis digital hologram, measures the optical aberration from a separate off-axis digital guidestar hologram, and removes the optical aberration from the distorted line fields by numerical processing. In previously demonstrated DAO systems, the optical aberration was directly retrieved from the guidestar hologram by taking its Fourier transform and extracting the phase term. For the direct retrieval method (DRM), when the sample is not coincident with the guidestar focal plane, the accuracy of the optical aberration retrieved by DRM undergoes a fast decay, leading to quality deterioration of corrected images. To tackle this problem, we explore here an image metrics-based iterative method (MIM) to retrieve the optical aberration from the guidestar hologram. Using an aberrated objective lens and scattering samples, we demonstrate that MIM can improve the accuracy of the retrieved aberrations from both focused and defocused guidestar holograms, compared to DRM, to improve the robustness of the DAO. PMID:28380937

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

piscope - A Python based software package for the analysis of volcanic SO2 emissions using UV SO2 cameras

NASA Astrophysics Data System (ADS)

Gliss, Jonas; Stebel, Kerstin; Kylling, Arve; Solvejg Dinger, Anna; Sihler, Holger; Sudbø, Aasmund

2017-04-01

UV SO2 cameras have become a common method for monitoring SO2 emission rates from volcanoes. Scattered solar UV radiation is measured in two wavelength windows, typically around 310 nm and 330 nm (distinct / weak SO2 absorption) using interference filters. The data analysis comprises the retrieval of plume background intensities (to calculate plume optical densities), the camera calibration (to convert optical densities into SO2 column densities) and the retrieval of gas velocities within the plume as well as the retrieval of plume distances. SO2 emission rates are then typically retrieved along a projected plume cross section, for instance a straight line perpendicular to the plume propagation direction. Today, for most of the required analysis steps, several alternatives exist due to ongoing developments and improvements related to the measurement technique. We present piscope, a cross platform, open source software toolbox for the analysis of UV SO2 camera data. The code is written in the Python programming language and emerged from the idea of a common analysis platform incorporating a selection of the most prevalent methods found in literature. piscope includes several routines for plume background retrievals, routines for cell and DOAS based camera calibration including two individual methods to identify the DOAS field of view (shape and position) within the camera images. Gas velocities can be retrieved either based on an optical flow analysis or using signal cross correlation. A correction for signal dilution (due to atmospheric scattering) can be performed based on topographic features in the images. The latter requires distance retrievals to the topographic features used for the correction. These distances can be retrieved automatically on a pixel base using intersections of individual pixel viewing directions with the local topography. The main features of piscope are presented based on dataset recorded at Mt. Etna, Italy in September 2015.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

PubMed

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

Dictionary Pruning with Visual Word Significance for Medical Image Retrieval

PubMed Central

Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G.; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

2016-01-01

Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency. PMID:27688597

Dictionary Pruning with Visual Word Significance for Medical Image Retrieval.

PubMed

Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

2016-02-12

Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency.

Retrieving handwriting by combining word spotting and manifold ranking

NASA Astrophysics Data System (ADS)

Peña Saldarriaga, Sebastián; Morin, Emmanuel; Viard-Gaudin, Christian

2012-01-01

Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequence of points (x, y). As the amount of data available in this form increases, algorithms for retrieval of online data are needed. Word spotting is a common approach used for the retrieval of handwriting. However, from an information retrieval (IR) perspective, word spotting is a primitive keyword based matching and retrieval strategy. We propose a framework for handwriting retrieval where an arbitrary word spotting method is used, and then a manifold ranking algorithm is applied on the initial retrieval scores. Experimental results on a database of more than 2,000 handwritten newswires show that our method can improve the performances of a state-of-the-art word spotting system by more than 10%.

Three-dimensional ordered particulate structures: Method to retrieve characteristics from photonic band gap data

NASA Astrophysics Data System (ADS)

Miskevich, Alexander A.; Loiko, Valery A.

2015-01-01

A method to retrieve characteristics of ordered particulate structures, such as photonic crystals, is proposed. It is based on the solution of the inverse problem using data on the photonic band gap (PBG). The quasicrystalline approximation (QCA) of the theory of multiple scattering of waves and the transfer matrix method (TMM) are used. Retrieval of the refractive index of particles is demonstrated. Refractive indices of the artificial opal particles are estimated using the published experimental data.

Content based image retrieval for matching images of improvised explosive devices in which snake initialization is viewed as an inverse problem

NASA Astrophysics Data System (ADS)

Acton, Scott T.; Gilliam, Andrew D.; Li, Bing; Rossi, Adam

2008-02-01

Improvised explosive devices (IEDs) are common and lethal instruments of terrorism, and linking a terrorist entity to a specific device remains a difficult task. In the effort to identify persons associated with a given IED, we have implemented a specialized content based image retrieval system to search and classify IED imagery. The system makes two contributions to the art. First, we introduce a shape-based matching technique exploiting shape, color, and texture (wavelet) information, based on novel vector field convolution active contours and a novel active contour initialization method which treats coarse segmentation as an inverse problem. Second, we introduce a unique graph theoretic approach to match annotated printed circuit board images for which no schematic or connectivity information is available. The shape-based image retrieval method, in conjunction with the graph theoretic tool, provides an efficacious system for matching IED images. For circuit imagery, the basic retrieval mechanism has a precision of 82.1% and the graph based method has a precision of 98.1%. As of the fall of 2007, the working system has processed over 400,000 case images.

Phase retrieval with the reverse projection method in the presence of object's scattering

NASA Astrophysics Data System (ADS)

Wang, Zhili; Gao, Kun; Wang, Dajiang

2017-08-01

X-ray grating interferometry can provide substantially increased contrast over traditional attenuation-based techniques in biomedical applications, and therefore novel and complementary information. Recently, special attention has been paid to quantitative phase retrieval in X-ray grating interferometry, which is mandatory to perform phase tomography, to achieve material identification, etc. An innovative approach, dubbed ;Reverse Projection; (RP), has been developed for quantitative phase retrieval. The RP method abandons grating scanning completely, and is thus advantageous in terms of higher efficiency and reduced radiation damage. Therefore, it is expected that this novel method would find its potential in preclinical and clinical implementations. Strictly speaking, the reverse projection method is applicable for objects exhibiting only absorption and refraction. In this contribution, we discuss the phase retrieval with the reverse projection method for general objects with absorption, refraction and scattering simultaneously. Especially, we investigate the influence of the object's scattering on the retrieved refraction signal. Both theoretical analysis and numerical experiments are performed. The results show that the retrieved refraction signal is the product of object's refraction and scattering signals for small values. In the case of a strong scattering, the reverse projection method cannot provide reliable phase retrieval. Those presented results will guide the use of the reverse projection method for future practical applications, and help to explain some possible artifacts in the retrieved images and/or reconstructed slices.

Advanced Feedback Methods in Information Retrieval.

ERIC Educational Resources Information Center

Salton, G.; And Others

1985-01-01

In this study, automatic feedback techniques are applied to Boolean query statements in online information retrieval to generate improved query statements based on information contained in previously retrieved documents. Feedback operations are carried out using conventional Boolean logic and extended logic. Experimental output is included to…

Ground-based remote sensing of thin clouds in the Arctic

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Zhao, C.

2012-11-01

This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, visible optical depth, number concentration, and water path are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement program (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with ground-based microwave radiometer measurements of liquid water path. Compared to other retrieval methods, advantages of this technique include its ability to characterize thin clouds year round, that water vapor is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies.

Web image retrieval using an effective topic and content-based technique

NASA Astrophysics Data System (ADS)

Lee, Ching-Cheng; Prabhakara, Rashmi

2005-03-01

There has been an exponential growth in the amount of image data that is available on the World Wide Web since the early development of Internet. With such a large amount of information and image available and its usefulness, an effective image retrieval system is thus greatly needed. In this paper, we present an effective approach with both image matching and indexing techniques that improvise on existing integrated image retrieval methods. This technique follows a two-phase approach, integrating query by topic and query by example specification methods. In the first phase, The topic-based image retrieval is performed by using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. This technique consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. In the second phase, we use query by example specification to perform a low-level content-based image match in order to retrieve smaller and relatively closer results of the example image. From this, information related to the image feature is automatically extracted from the query image. The main objective of our approach is to develop a functional image search and indexing technique and to demonstrate that better retrieval results can be achieved.

COM3/369: Knowledge-based Information Systems: A new approach for the representation and retrieval of medical information

PubMed Central

Mann, G; Birkmann, C; Schmidt, T; Schaeffler, V

1999-01-01

Introduction Present solutions for the representation and retrieval of medical information from online sources are not very satisfying. Either the retrieval process lacks of precision and completeness the representation does not support the update and maintenance of the represented information. Most efforts are currently put into improving the combination of search engines and HTML based documents. However, due to the current shortcomings of methods for natural language understanding there are clear limitations to this approach. Furthermore, this approach does not solve the maintenance problem. At least medical information exceeding a certain complexity seems to afford approaches that rely on structured knowledge representation and corresponding retrieval mechanisms. Methods Knowledge-based information systems are based on the following fundamental ideas. The representation of information is based on ontologies that define the structure of the domain's concepts and their relations. Views on domain models are defined and represented as retrieval schemata. Retrieval schemata can be interpreted as canonical query types focussing on specific aspects of the provided information (e.g. diagnosis or therapy centred views). Based on these retrieval schemata it can be decided which parts of the information in the domain model must be represented explicitly and formalised to support the retrieval process. As representation language propositional logic is used. All other information can be represented in a structured but informal way using text, images etc. Layout schemata are used to assign layout information to retrieved domain concepts. Depending on the target environment HTML or XML can be used. Results Based on this approach two knowledge-based information systems have been developed. The 'Ophthalmologic Knowledge-based Information System for Diabetic Retinopathy' (OKIS-DR) provides information on diagnoses, findings, examinations, guidelines, and reference images related to diabetic retinopathy. OKIS-DR uses combinations of findings to specify the information that must be retrieved. The second system focuses on nutrition related allergies and intolerances. Information on allergies and intolerances of a patient are used to retrieve general information on the specified combination of allergies and intolerances. As a special feature the system generates tables showing food types and products that are tolerated or not tolerated by patients. Evaluation by external experts and user groups showed that the described approach of knowledge-based information systems increases the precision and completeness of knowledge retrieval. Due to the structured and non-redundant representation of information the maintenance and update of the information can be simplified. Both systems are available as WWW based online knowledge bases and CD-ROMs (cf. http://mta.gsf.de topic: products).

Simultaneous retrieval of atmospheric CO2 and light path modification from space-based spectroscopic observations of greenhouse gases: methodology and application to GOSAT measurements over TCCON sites.

PubMed

Oshchepkov, Sergey; Bril, Andrey; Yokota, Tatsuya; Yoshida, Yukio; Blumenstock, Thomas; Deutscher, Nicholas M; Dohe, Susanne; Macatangay, Ronald; Morino, Isamu; Notholt, Justus; Rettinger, Markus; Petri, Christof; Schneider, Matthias; Sussman, Ralf; Uchino, Osamu; Velazco, Voltaire; Wunch, Debra; Belikov, Dmitry

2013-02-20

This paper presents an improved photon path length probability density function method that permits simultaneous retrievals of column-average greenhouse gas mole fractions and light path modifications through the atmosphere when processing high-resolution radiance spectra acquired from space. We primarily describe the methodology and retrieval setup and then apply them to the processing of spectra measured by the Greenhouse gases Observing SATellite (GOSAT). We have demonstrated substantial improvements of the data processing with simultaneous carbon dioxide and light path retrievals and reasonable agreement of the satellite-based retrievals against ground-based Fourier transform spectrometer measurements provided by the Total Carbon Column Observing Network (TCCON).

Kingfisher: a system for remote sensing image database management

NASA Astrophysics Data System (ADS)

Bruzzo, Michele; Giordano, Ferdinando; Dellepiane, Silvana G.

2003-04-01

At present retrieval methods in remote sensing image database are mainly based on spatial-temporal information. The increasing amount of images to be collected by the ground station of earth observing systems emphasizes the need for database management with intelligent data retrieval capabilities. The purpose of the proposed method is to realize a new content based retrieval system for remote sensing images database with an innovative search tool based on image similarity. This methodology is quite innovative for this application, at present many systems exist for photographic images, as for example QBIC and IKONA, but they are not able to extract and describe properly remote image content. The target database is set by an archive of images originated from an X-SAR sensor (spaceborne mission, 1994). The best content descriptors, mainly texture parameters, guarantees high retrieval performances and can be extracted without losses independently of image resolution. The latter property allows DBMS (Database Management System) to process low amount of information, as in the case of quick-look images, improving time performance and memory access without reducing retrieval accuracy. The matching technique has been designed to enable image management (database population and retrieval) independently of dimensions (width and height). Local and global content descriptors are compared, during retrieval phase, with the query image and results seem to be very encouraging.

Semantic-based surveillance video retrieval.

PubMed

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)

DTIC Science & Technology

2008-11-01

retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for...estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity...and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach

[Measurements of the concentration of atmospheric CO2 based on OP/FTIR method and infrared reflecting scanning Fourier transform spectrometry].

PubMed

Wei, Ru-Yi; Zhou, Jin-Song; Zhang, Xue-Min; Yu, Tao; Gao, Xiao-Hui; Ren, Xiao-Qiang

2014-11-01

The present paper describes the observations and measurements of the infrared absorption spectra of CO2 on the Earth's surface with OP/FTIR method by employing a mid-infrared reflecting scanning Fourier transform spectrometry, which are the first results produced by the first prototype in China developed by the team of authors. This reflecting scanning Fourier transform spectrometry works in the spectral range 2 100-3 150 cm(-1) with a spectral resolution of 2 cm(-1). Method to measure the atmospheric molecules was described and mathematical proof and quantitative algorithms to retrieve molecular concentration were established. The related models were performed both by a direct method based on the Beer-Lambert Law and by a simulating-fitting method based on HITRAN database and the instrument functions. Concentrations of CO2 were retrieved by the two models. The results of observation and modeling analyses indicate that the concentrations have a distribution of 300-370 ppm, and show tendency that going with the variation of the environment they first decrease slowly and then increase rapidly during the observation period, and reached low points in the afternoon and during the sunset. The concentrations with measuring times retrieved by the direct method and by the simulating-fitting method agree with each other very well, with the correlation of all the data is up to 99.79%, and the relative error is no more than 2.00%. The precision for retrieving is relatively high. The results of this paper demonstrate that, in the field of detecting atmospheric compositions, OP/FTIR method performed by the Infrared reflecting scanning Fourier transform spectrometry is a feasible and effective technical approach, and either the direct method or the simulating-fitting method is capable of retrieving concentrations with high precision.

A Novel Method of Case Representation and Retrieval in CBR for E-Learning

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the…

Using Conceptual Categories of Questions To Measure Differences in Retrieval Performance.

ERIC Educational Resources Information Center

Keyes, John G.

1996-01-01

To investigate the relationship between the retrieval mechanism and the level of question elaboration, this study divided 100 questions from the cystic fibrosis database into five conceptual categories based on their semantic representations. Two retrieval methods were chosen to investigate potential differences in outcomes across conceptual…

Development of the CODER System: A Testbed for Artificial Intelligence Methods in Information Retrieval.

ERIC Educational Resources Information Center

Fox, Edward A.

1987-01-01

Discusses the CODER system, which was developed to investigate the application of artificial intelligence methods to increase the effectiveness of information retrieval systems, particularly those involving heterogeneous documents. Highlights include the use of PROLOG programing, blackboard-based designs, knowledge engineering, lexicological…

A demonstration of adjoint methods for multi-dimensional remote sensing of the atmosphere and surface

NASA Astrophysics Data System (ADS)

Martin, William G. K.; Hasekamp, Otto P.

2018-01-01

In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also possible to retrieve the vertical profile of clouds that are separated by clear regions. The vertical profile retrievals improve for smaller cloud fractions. This leads to the conclusion that cloud edges actually increase the amount of information that is available for retrieving the vertical profile of clouds. However, to exploit this information one must retrieve the horizontally heterogeneous cloud properties with a 2D (or 3D) model. This prototype shows that adjoint methods can efficiently compute the gradient of the misfit function. This work paves the way for the application of similar methods to 3D remote sensing problems.

Triple collocation based merging of satellite soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

We propose a method for merging soil moisture retrievals from space borne active and passive microwave instruments based on weighted averaging taking into account the error characteristics of the individual data sets. The merging scheme is parameterized using error variance estimates obtained from u...

Data augmentation-assisted deep learning of hand-drawn partially colored sketches for visual search

PubMed Central

Muhammad, Khan; Baik, Sung Wook

2017-01-01

In recent years, image databases are growing at exponential rates, making their management, indexing, and retrieval, very challenging. Typical image retrieval systems rely on sample images as queries. However, in the absence of sample query images, hand-drawn sketches are also used. The recent adoption of touch screen input devices makes it very convenient to quickly draw shaded sketches of objects to be used for querying image databases. This paper presents a mechanism to provide access to visual information based on users’ hand-drawn partially colored sketches using touch screen devices. A key challenge for sketch-based image retrieval systems is to cope with the inherent ambiguity in sketches due to the lack of colors, textures, shading, and drawing imperfections. To cope with these issues, we propose to fine-tune a deep convolutional neural network (CNN) using augmented dataset to extract features from partially colored hand-drawn sketches for query specification in a sketch-based image retrieval framework. The large augmented dataset contains natural images, edge maps, hand-drawn sketches, de-colorized, and de-texturized images which allow CNN to effectively model visual contents presented to it in a variety of forms. The deep features extracted from CNN allow retrieval of images using both sketches and full color images as queries. We also evaluated the role of partial coloring or shading in sketches to improve the retrieval performance. The proposed method is tested on two large datasets for sketch recognition and sketch-based image retrieval and achieved better classification and retrieval performance than many existing methods. PMID:28859140

Generating region proposals for histopathological whole slide image retrieval.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu; Shi, Jun

2018-06-01

Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels. This paper presents a novel unsupervised region proposing method for histopathological WSI based on Selective Search. Specifically, the WSI is over-segmented into regions which are hierarchically merged until the WSI becomes a single region. Nucleus-oriented similarity measures for region mergence and Nucleus-Cytoplasm color space for histopathological image are specially defined to generate accurate region proposals. Additionally, we propose a new semi-supervised hashing method for image retrieval. The semantic features of images are extracted with Latent Dirichlet Allocation and transformed into binary hashing codes with Supervised Hashing. The methods are tested on a large-scale multi-class database of breast histopathological WSIs. The results demonstrate that for one WSI, our region proposing method can generate 7.3 thousand contoured regions which fit well with 95.8% of the ROIs annotated by pathologists. The proposed hashing method can retrieve a query image among 136 thousand images in 0.29 s and reach precision of 91% with only 10% of images labeled. The unsupervised region proposing method can generate regions as predictions of lesions in histopathological WSI. The region proposals can also serve as the training samples to train machine-learning models for image retrieval. The proposed hashing method can achieve fast and precise image retrieval with small amount of labels. Furthermore, the proposed methods can be potentially applied in online computer-aided-diagnosis systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Development and application of a probability distribution retrieval scheme to the remote sensing of clouds and precipitation

NASA Astrophysics Data System (ADS)

McKague, Darren Shawn

2001-12-01

The statistical properties of clouds and precipitation on a global scale are important to our understanding of climate. Inversion methods exist to retrieve the needed cloud and precipitation properties from satellite data pixel-by-pixel that can then be summarized over large data sets to obtain the desired statistics. These methods can be quite computationally expensive, and typically don't provide errors on the statistics. A new method is developed to directly retrieve probability distributions of parameters from the distribution of measured radiances. The method also provides estimates of the errors on the retrieved distributions. The method can retrieve joint distributions of parameters that allows for the study of the connection between parameters. A forward radiative transfer model creates a mapping from retrieval parameter space to radiance space. A Monte Carlo procedure uses the mapping to transform probability density from the observed radiance histogram to a two- dimensional retrieval property probability distribution function (PDF). An estimate of the uncertainty in the retrieved PDF is calculated from random realizations of the radiance to retrieval parameter PDF transformation given the uncertainty of the observed radiances, the radiance PDF, the forward radiative transfer, the finite number of prior state vectors, and the non-unique mapping to retrieval parameter space. The retrieval method is also applied to the remote sensing of precipitation from SSM/I microwave data. A method of stochastically generating hydrometeor fields based on the fields from a numerical cloud model is used to create the precipitation parameter radiance space transformation. The impact of vertical and horizontal variability within the hydrometeor fields has a significant impact on algorithm performance. Beamfilling factors are computed from the simulated hydrometeor fields. The beamfilling factors vary quite a bit depending upon the horizontal structure of the rain. The algorithm is applied to SSM/I images from the eastern tropical Pacific and is compared to PDFs of rain rate computed using pixel-by-pixel retrievals from Wilheit and from Liu and Curry. Differences exist between the three methods, but good general agreement is seen between the PDF retrieval algorithm and the algorithm of Liu and Curry. (Abstract shortened by UMI.)

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

A Method for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data

NASA Technical Reports Server (NTRS)

Koshak, William J.

2009-01-01

A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.

Standards-based metadata procedures for retrieving data for display or mining utilizing persistent (data-DOI) identifiers.

PubMed

Harvey, Matthew J; Mason, Nicholas J; McLean, Andrew; Rzepa, Henry S

2015-01-01

We describe three different procedures based on metadata standards for enabling automated retrieval of scientific data from digital repositories utilising the persistent identifier of the dataset with optional specification of the attributes of the data document such as filename or media type. The procedures are demonstrated using the JSmol molecular visualizer as a component of a web page and Avogadro as a stand-alone modelling program. We compare our methods for automated retrieval of data from a standards-compliant data repository with those currently in operation for a selection of existing molecular databases and repositories. Our methods illustrate the importance of adopting a standards-based approach of using metadata declarations to increase access to and discoverability of repository-based data. Graphical abstract.

Cross-Language Information Retrieval: An Analysis of Errors.

ERIC Educational Resources Information Center

Ruiz, Miguel E.; Srinivasan, Padmini

1998-01-01

Investigates an automatic method for Cross Language Information Retrieval (CLIR) that utilizes the multilingual Unified Medical Language System (UMLS) Metathesaurus to translate Spanish natural-language queries into English. Results indicate that for Spanish, the UMLS Metathesaurus-based CLIR method is at least equivalent to if not better than…

Deeply learnt hashing forests for content based image retrieval in prostate MR images

NASA Astrophysics Data System (ADS)

Shah, Amit; Conjeti, Sailesh; Navab, Nassir; Katouzian, Amin

2016-03-01

Deluge in the size and heterogeneity of medical image databases necessitates the need for content based retrieval systems for their efficient organization. In this paper, we propose such a system to retrieve prostate MR images which share similarities in appearance and content with a query image. We introduce deeply learnt hashing forests (DL-HF) for this image retrieval task. DL-HF effectively leverages the semantic descriptiveness of deep learnt Convolutional Neural Networks. This is used in conjunction with hashing forests which are unsupervised random forests. DL-HF hierarchically parses the deep-learnt feature space to encode subspaces with compact binary code words. We propose a similarity preserving feature descriptor called Parts Histogram which is derived from DL-HF. Correlation defined on this descriptor is used as a similarity metric for retrieval from the database. Validations on publicly available multi-center prostate MR image database established the validity of the proposed approach. The proposed method is fully-automated without any user-interaction and is not dependent on any external image standardization like image normalization and registration. This image retrieval method is generalizable and is well-suited for retrieval in heterogeneous databases other imaging modalities and anatomies.

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery.

PubMed

Ni, Zhuoya; Liu, Zhigang; Li, Zhao-Liang; Nerry, Françoise; Huo, Hongyuan; Sun, Rui; Yang, Peiqi; Zhang, Weiwei

2016-04-06

Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators-depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs/radiance-to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value/the base value in the oxygen absorption depth in the O₂-A and O₂-B bands (111.4% and 77.1% in the O₂-A band; and 27.5% and 32.6% in the O₂-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R² = 0.91 for Damm vs. SCOPE SIF; R² = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence.

Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery

PubMed Central

Ni, Zhuoya; Liu, Zhigang; Li, Zhao-Liang; Nerry, Françoise; Huo, Hongyuan; Sun, Rui; Yang, Peiqi; Zhang, Weiwei

2016-01-01

Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators—depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs/radiance—to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value/the base value in the oxygen absorption depth in the O2-A and O2-B bands (111.4% and 77.1% in the O2-A band; and 27.5% and 32.6% in the O2-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R2 = 0.91 for Damm vs. SCOPE SIF; R2 = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence. PMID:27058542

Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval

PubMed Central

Liu, Desheng; Pu, Ruiliang

2008-01-01

Land surface temperature (LST) retrieved from satellite thermal sensors often consists of mixed temperature components. Retrieving subpixel LST is therefore needed in various environmental and ecological studies. In this paper, we developed two methods for downscaling coarse resolution thermal infrared (TIR) radiance for the purpose of subpixel temperature retrieval. The first method was developed on the basis of a scale-invariant physical model on TIR radiance. The second method was based on a statistical relationship between TIR radiance and land cover fraction at high spatial resolution. The two methods were applied to downscale simulated 990-m ASTER TIR data to 90-m resolution. When validated against the original 90-m ASTER TIR data, the results revealed that both downscaling methods were successful in capturing the general patterns of the original data and resolving considerable spatial details. Further quantitative assessments indicated a strong agreement between the true values and the estimated values by both methods. PMID:27879844

Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval.

PubMed

Liu, Desheng; Pu, Ruiliang

2008-04-06

Land surface temperature (LST) retrieved from satellite thermal sensors often consists of mixed temperature components. Retrieving subpixel LST is therefore needed in various environmental and ecological studies. In this paper, we developed two methods for downscaling coarse resolution thermal infrared (TIR) radiance for the purpose of subpixel temperature retrieval. The first method was developed on the basis of a scale-invariant physical model on TIR radiance. The second method was based on a statistical relationship between TIR radiance and land cover fraction at high spatial resolution. The two methods were applied to downscale simulated 990-m ASTER TIR data to 90-m resolution. When validated against the original 90-m ASTER TIR data, the results revealed that both downscaling methods were successful in capturing the general patterns of the original data and resolving considerable spatial details. Further quantitative assessments indicated a strong agreement between the true values and the estimated values by both methods.

Strong Similarity Measures for Ordered Sets of Documents in Information Retrieval.

ERIC Educational Resources Information Center

Egghe, L.; Michel, Christine

2002-01-01

Presents a general method to construct ordered similarity measures in information retrieval based on classical similarity measures for ordinary sets. Describes a test of some of these measures in an information retrieval system that extracted ranked document sets and discuses the practical usability of the ordered similarity measures. (Author/LRW)

Semantics of User Interface for Image Retrieval: Possibility Theory and Learning Techniques.

ERIC Educational Resources Information Center

Crehange, M.; And Others

1989-01-01

Discusses the need for a rich semantics for the user interface in interactive image retrieval and presents two methods for building such interfaces: possibility theory applied to fuzzy data retrieval, and a machine learning technique applied to learning the user's deep need. Prototypes developed using videodisks and knowledge-based software are…

Content Based Image Retrieval based on Wavelet Transform coefficients distribution

PubMed Central

Lamard, Mathieu; Cazuguel, Guy; Quellec, Gwénolé; Bekri, Lynda; Roux, Christian; Cochener, Béatrice

2007-01-01

In this paper we propose a content based image retrieval method for diagnosis aid in medical fields. We characterize images without extracting significant features by using distribution of coefficients obtained by building signatures from the distribution of wavelet transform. The research is carried out by computing signature distances between the query and database images. Several signatures are proposed; they use a model of wavelet coefficient distribution. To enhance results, a weighted distance between signatures is used and an adapted wavelet base is proposed. Retrieval efficiency is given for different databases including a diabetic retinopathy, a mammography and a face database. Results are promising: the retrieval efficiency is higher than 95% for some cases using an optimization process. PMID:18003013

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

Issues associated with manipulator-based waste retrieval from Hanford underground storage tanks with a preliminary review of commercial concepts

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

Berglin, E.J.

1996-09-17

Westinghouse Hanford Company (WHC) is exploring commercial methods for retrieving waste from the underground storage tanks at the Hanford site in south central Washington state. WHC needs data on commercial retrieval systems equipment in order to make programmatic decisions for waste retrieval. Full system testing of retrieval processes is to be demonstrated in phases through September 1997 in support of programs aimed to Acquire Commercial Technology for Retrieval (ACTR) and at the Hanford Tanks Initiative (HTI). One of the important parts of the integrated testing will be the deployment of retrieval tools using manipulator-based systems. WHC requires an assessment ofmore » a number of commercial deployment systems that have been identified by the ACTR program as good candidates to be included in an integrated testing effort. Included in this assessment should be an independent evaluation of manipulator tests performed to date, so that WHC can construct an integrated test based on these systems. The objectives of this document are to provide a description of the need, requirements, and constraints for a manipulator-based retrieval system; to evaluate manipulator-based concepts and testing performed to date by a number of commercial organizations; and to identify issues to be resolved through testing and/or analysis for each concept.« less

Improved image retrieval based on fuzzy colour feature vector

NASA Astrophysics Data System (ADS)

Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

2013-03-01

One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

Soil Moisture Retrieval Using Convolutional Neural Networks: Application to Passive Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Hu, Z.; Xu, L.; Yu, B.

2018-04-01

A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.

Learning semantic and visual similarity for endomicroscopy video retrieval.

PubMed

Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2012-06-01

Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them. In our resulting retrieval system, we decide to use visual signatures for perceived similarity learning and retrieval, and semantic signatures for the output of an additional information, expressed in the endoscopist own language, which provides a relevant semantic translation of the visual retrieval outputs.

Laboratory-Based and Autobiographical Retrieval Tasks Differ Substantially in Their Neural Substrates

ERIC Educational Resources Information Center

McDermott, Kathleen B.; Szpunar, Karl K.; Christ, Shawn E.

2009-01-01

In designing experiments to investigate retrieval of event memory, researchers choose between utilizing laboratory-based methods (in which to-be-remembered materials are presented to participants) and autobiographical approaches (in which the to-be-remembered materials are events from the participant's pre-experimental life). In practice, most…

Retrieval and Validation of Aerosol Optical Depth by using the GF-1 Remote Sensing Data

NASA Astrophysics Data System (ADS)

Zhang, L.; Xu, S.; Wang, L.; Cai, K.; Ge, Q.

2017-05-01

Based on the characteristics of GF-1 remote sensing data, the method and data processing procedure to retrieve the Aerosol Optical Depth (AOD) are developed in this study. The surface contribution over dense vegetation and urban bright target areas are respectively removed by using the dark target and deep blue algorithms. Our method is applied for the three serious polluted Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions. The retrieved AOD are validated by ground-based AERONET data from Beijing, Hangzhou, Hong Kong sites. Our results show that, 1) the heavy aerosol loadings are usually distributed in high industrial emission and dense populated cities, with the AOD value near 1. 2) There is a good agreement between satellite-retrievals and in-site observations, with the coefficient factors of 0.71 (BTH), 0.55 (YRD) and 0.54(PRD). 3) The GF-1 retrieval uncertainties are mainly from the impact of cloud contamination, high surface reflectance and assumed aerosol model.

Interactive content-based image retrieval (CBIR) computer-aided diagnosis (CADx) system for ultrasound breast masses using relevance feedback

NASA Astrophysics Data System (ADS)

Cho, Hyun-chong; Hadjiiski, Lubomir; Sahiner, Berkman; Chan, Heang-Ping; Paramagul, Chintana; Helvie, Mark; Nees, Alexis V.

2012-03-01

We designed a Content-Based Image Retrieval (CBIR) Computer-Aided Diagnosis (CADx) system to assist radiologists in characterizing masses on ultrasound images. The CADx system retrieves masses that are similar to a query mass from a reference library based on computer-extracted features that describe texture, width-to-height ratio, and posterior shadowing of a mass. Retrieval is performed with k nearest neighbor (k-NN) method using Euclidean distance similarity measure and Rocchio relevance feedback algorithm (RRF). In this study, we evaluated the similarity between the query and the retrieved masses with relevance feedback using our interactive CBIR CADx system. The similarity assessment and feedback were provided by experienced radiologists' visual judgment. For training the RRF parameters, similarities of 1891 image pairs obtained from 62 masses were rated by 3 MQSA radiologists using a 9-point scale (9=most similar). A leave-one-out method was used in training. For each query mass, 5 most similar masses were retrieved from the reference library using radiologists' similarity ratings, which were then used by RRF to retrieve another 5 masses for the same query. The best RRF parameters were chosen based on three simulated observer experiments, each of which used one of the radiologists' ratings for retrieval and relevance feedback. For testing, 100 independent query masses on 100 images and 121 reference masses on 230 images were collected. Three radiologists rated the similarity between the query and the computer-retrieved masses. Average similarity ratings without and with RRF were 5.39 and 5.64 on the training set and 5.78 and 6.02 on the test set, respectively. The average Az values without and with RRF were 0.86+/-0.03 and 0.87+/-0.03 on the training set and 0.91+/-0.03 and 0.90+/-0.03 on the test set, respectively. This study demonstrated that RRF improved the similarity of the retrieved masses.

A novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2005-01-01

Ever since the advent of Internet, there has been an immense growth in the amount of image data that is available on the World Wide Web. With such a magnitude of image availability, an efficient and effective image retrieval system is required to make use of this information. This research presents an effective image matching and indexing technique that improvises on existing integrated image retrieval methods. The proposed technique follows a two-phase approach, integrating query by topic and query by example specification methods. The first phase consists of topic-based image retrieval using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. It consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. The second phase uses the query by example specification to perform a low-level content-based image match for the retrieval of smaller and relatively closer results of the example image. Information related to the image feature is automatically extracted from the query image by the image processing system. A technique that is not computationally intensive based on color feature is used to perform content-based matching of images. The main goal is to develop a functional image search and indexing system and to demonstrate that better retrieval results can be achieved with this proposed hybrid search technique.

A novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2004-12-01

Ever since the advent of Internet, there has been an immense growth in the amount of image data that is available on the World Wide Web. With such a magnitude of image availability, an efficient and effective image retrieval system is required to make use of this information. This research presents an effective image matching and indexing technique that improvises on existing integrated image retrieval methods. The proposed technique follows a two-phase approach, integrating query by topic and query by example specification methods. The first phase consists of topic-based image retrieval using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. It consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. The second phase uses the query by example specification to perform a low-level content-based image match for the retrieval of smaller and relatively closer results of the example image. Information related to the image feature is automatically extracted from the query image by the image processing system. A technique that is not computationally intensive based on color feature is used to perform content-based matching of images. The main goal is to develop a functional image search and indexing system and to demonstrate that better retrieval results can be achieved with this proposed hybrid search technique.

Retrieving Liquid Water Path and Precipitable Water Vapor from the Atmospheric Radiation Measurement (ARM) Microwave Radiometers

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

Turner, David D.; Clough, Shepard A.; Liljegren, James C.

2007-11-01

Ground-based two-channel microwave radiometers have been used for over 15 years by the Atmospheric Radiation Measurement (ARM) program to provide observations of downwelling emitted radiance from which precipitable water vapor (PWV) and liquid water path (LWP) – twp geophysical parameters critical for many areas of atmospheric research – are retrieved. An algorithm that utilizes two advanced retrieval techniques, a computationally expensive physical-iterative approach and an efficient statistical method, has been developed to retrieve these parameters. An important component of this Microwave Retrieval (MWRRET) algorithm is the determination of small (< 1K) offsets that are subtracted from the observed brightness temperaturesmore » before the retrievals are performed. Accounting for these offsets removes systematic biases from the observations and/or the model spectroscopy necessary for the retrieval, significantly reducing the systematic biases in the retrieved LWP. The MWRRET algorithm provides significantly more accurate retrievals than the original ARM statistical retrieval which uses monthly retrieval coefficients. By combining the two retrieval methods with the application of brightness temperature offsets to reduce the spurious LWP bias in clear skies, the MWRRET algorithm provides significantly better retrievals of PWV and LWP from the ARM 2-channel microwave radiometers compared to the original ARM product.« less

Novel Fourier-domain constraint for fast phase retrieval in coherent diffraction imaging.

PubMed

Latychevskaia, Tatiana; Longchamp, Jean-Nicolas; Fink, Hans-Werner

2011-09-26

Coherent diffraction imaging (CDI) for visualizing objects at atomic resolution has been realized as a promising tool for imaging single molecules. Drawbacks of CDI are associated with the difficulty of the numerical phase retrieval from experimental diffraction patterns; a fact which stimulated search for better numerical methods and alternative experimental techniques. Common phase retrieval methods are based on iterative procedures which propagate the complex-valued wave between object and detector plane. Constraints in both, the object and the detector plane are applied. While the constraint in the detector plane employed in most phase retrieval methods requires the amplitude of the complex wave to be equal to the squared root of the measured intensity, we propose a novel Fourier-domain constraint, based on an analogy to holography. Our method allows achieving a low-resolution reconstruction already in the first step followed by a high-resolution reconstruction after further steps. In comparison to conventional schemes this Fourier-domain constraint results in a fast and reliable convergence of the iterative reconstruction process. © 2011 Optical Society of America

High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

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

Wu, Zhao; Gao, Kun; Chen, Jian

2015-02-15

Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using themore » error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations.« less

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-07-02

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2.« less

Cluster-based query expansion using external collections in medical information retrieval.

PubMed

Oh, Heung-Seon; Jung, Yuchul

2015-12-01

Utilizing external collections to improve retrieval performance is challenging research because various test collections are created for different purposes. Improving medical information retrieval has also gained much attention as various types of medical documents have become available to researchers ever since they started storing them in machine processable formats. In this paper, we propose an effective method of utilizing external collections based on the pseudo relevance feedback approach. Our method incorporates the structure of external collections in estimating individual components in the final feedback model. Extensive experiments on three medical collections (TREC CDS, CLEF eHealth, and OHSUMED) were performed, and the results were compared with a representative expansion approach utilizing the external collections to show the superiority of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 2: Retrieval method and applications (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.

1990-01-01

A physical retrieval method for estimating precipitating water distributions and other geophysical parameters based upon measurements from the DMSP-F8 SSM/I is developed. Three unique features of the retrieval method are (1) sensor antenna patterns are explicitly included to accommodate varying channel resolution; (2) precipitation-brightness temperature relationships are quantified using the cloud ensemble/radiative parameterization; and (3) spatial constraints are imposed for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The general framework of the method will facilitate the incorporation of measurements from the SSMJT, SSM/T-2 and geostationary infrared measurements, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

Poor readers' retrieval mechanism: efficient access is not dependent on reading skill

PubMed Central

Johns, Clinton L.; Matsuki, Kazunaga; Van Dyke, Julie A.

2015-01-01

A substantial body of evidence points to a cue-based direct-access retrieval mechanism as a crucial component of skilled adult reading. We report two experiments aimed at examining whether poor readers are able to make use of the same retrieval mechanism. This is significant in light of findings that poor readers have difficulty retrieving linguistic information (e.g., Perfetti, 1985). Our experiments are based on a previous demonstration of direct-access retrieval in language processing, presented in McElree et al. (2003). Experiment 1 replicates the original result using an auditory implementation of the Speed-Accuracy Tradeoff (SAT) method. This finding represents a significant methodological advance, as it opens up the possibility of exploring retrieval speeds in non-reading populations. Experiment 2 provides evidence that poor readers do use a direct-access retrieval mechanism during listening comprehension, despite overall poorer accuracy and slower retrieval speeds relative to skilled readers. The findings are discussed with respect to hypotheses about the source of poor reading comprehension. PMID:26528212

Natural texture retrieval based on perceptual similarity measurement

NASA Astrophysics Data System (ADS)

Gao, Ying; Dong, Junyu; Lou, Jianwen; Qi, Lin; Liu, Jun

2018-04-01

A typical texture retrieval system performs feature comparison and might not be able to make human-like judgments of image similarity. Meanwhile, it is commonly known that perceptual texture similarity is difficult to be described by traditional image features. In this paper, we propose a new texture retrieval scheme based on texture perceptual similarity. The key of the proposed scheme is that prediction of perceptual similarity is performed by learning a non-linear mapping from image features space to perceptual texture space by using Random Forest. We test the method on natural texture dataset and apply it on a new wallpapers dataset. Experimental results demonstrate that the proposed texture retrieval scheme with perceptual similarity improves the retrieval performance over traditional image features.

Three methods to retrieve slant total electron content measurements from ground-based GPS receivers and performance assessment

NASA Astrophysics Data System (ADS)

Zhang, Baocheng

2016-07-01

The high sampling rate along with the global coverage of ground-based receivers makes Global Positioning System (GPS) data particularly ideal for sensing the Earth's ionosphere. Retrieval of slant total electron content measurements (TECMs) constitutes a key first step toward extracting various ionospheric parameters from GPS data. Within the ionospheric community, the interpretation of TECM is widely recognized as the slant total electron content along the satellite receiver line of sight, biased by satellite and receiver differential code biases (DCBs). The Carrier-to-Code Leveling (CCL) has long been used as a geometry-free method for retrieving TECM, mainly because of its simplicity and effectiveness. In fact, however, the CCL has proven inaccurate as it may give rise to TECM very susceptible to so-called leveling errors. With the goal of attaining more accurate TECM retrieval, we report in this contribution two other methods than the CCL, namely, the Precise Point Positioning (PPP) and the Array-aided PPP (A-PPP). The PPP further exploits the International GPS Service (IGS) orbit and clock products and turns out to be a geometry-based method. The A-PPP is designed to retrieve TECM from an array of colocated receivers, taking advantage of the broadcast orbit and clock products. Moreover, A-PPP also takes into account the fact that the ionospheric effects measured from one satellite to all colocated receivers ought to be the same, thus leading to the estimability of interreceiver DCB. We perform a comparative study of the formal precision and the empirical accuracy of the TECM that are retrieved, respectively, by three methods from the same set of GPS data. Results of such a study can be used to assess the actual performance of the three methods. In addition, we check the temporal stability in A-PPP-derived interreceiver DCB estimates over time periods ranging from 1 to 3 days.

Cloud Droplet Size and Liquid Water Path Retrievals From Zenith Radiance Measurements: Examples From the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

NASA Technical Reports Server (NTRS)

Chiu, J. C.; Marshak, A.; Huang, C.-H.; Varnai, T.; Hogan, R. J.; Giles, D. M.; Holben, B. N.; Knyazikhin, Y.; O'Connor, E. J.; Wiscombe, W. J.

2012-01-01

The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Design of Content Based Image Retrieval Scheme for Diabetic Retinopathy Images using Harmony Search Algorithm.

PubMed

Sivakamasundari, J; Natarajan, V

2015-01-01

Diabetic Retinopathy (DR) is a disorder that affects the structure of retinal blood vessels due to long-standing diabetes mellitus. Automated segmentation of blood vessel is vital for periodic screening and timely diagnosis. An attempt has been made to generate continuous retinal vasculature for the design of Content Based Image Retrieval (CBIR) application. The typical normal and abnormal retinal images are preprocessed to improve the vessel contrast. The blood vessels are segmented using evolutionary based Harmony Search Algorithm (HSA) combined with Otsu Multilevel Thresholding (MLT) method by best objective functions. The segmentation results are validated with corresponding ground truth images using binary similarity measures. The statistical, textural and structural features are obtained from the segmented images of normal and DR affected retina and are analyzed. CBIR in medical image retrieval applications are used to assist physicians in clinical decision-support techniques and research fields. A CBIR system is developed using HSA based Otsu MLT segmentation technique and the features obtained from the segmented images. Similarity matching is carried out between the features of query and database images using Euclidean Distance measure. Similar images are ranked and retrieved. The retrieval performance of CBIR system is evaluated in terms of precision and recall. The CBIR systems developed using HSA based Otsu MLT and conventional Otsu MLT methods are compared. The retrieval performance such as precision and recall are found to be 96% and 58% for CBIR system using HSA based Otsu MLT segmentation. This automated CBIR system could be recommended for use in computer assisted diagnosis for diabetic retinopathy screening.

Remote sensing of cirrus cloud vertical size profile using MODIS data

NASA Astrophysics Data System (ADS)

Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.

2009-05-01

This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

PubMed

Ashraf, Rehan; Ahmed, Mudassar; Jabbar, Sohail; Khalid, Shehzad; Ahmad, Awais; Din, Sadia; Jeon, Gwangil

2018-01-25

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance. The color, shape and texture are the examples of low-level image features. The feature plays a significant role in image processing. The powerful representation of an image is known as feature vector and feature extraction techniques are applied to get features that will be useful in classifying and recognition of images. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. In this paper, we are going to discuss various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique will be better. The effectiveness of the CBIR approach is fundamentally based on feature extraction. In image processing errands like object recognition and image retrieval feature descriptor is an immense among the most essential step. The main idea of CBIR is that it can search related images to an image passed as query from a dataset got by using distance metrics. The proposed method is explained for image retrieval constructed on YCbCr color with canny edge histogram and discrete wavelet transform. The combination of edge of histogram and discrete wavelet transform increase the performance of image retrieval framework for content based search. The execution of different wavelets is additionally contrasted with discover the suitability of specific wavelet work for image retrieval. The proposed algorithm is prepared and tried to implement for Wang image database. For Image Retrieval Purpose, Artificial Neural Networks (ANN) is used and applied on standard dataset in CBIR domain. The execution of the recommended descriptors is assessed by computing both Precision and Recall values and compared with different other proposed methods with demonstrate the predominance of our method. The efficiency and effectiveness of the proposed approach outperforms the existing research in term of average precision and recall values.

Active learning methods for interactive image retrieval.

PubMed

Gosselin, Philippe Henri; Cord, Matthieu

2008-07-01

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

Advances in simultaneous atmospheric profile and cloud parameter regression based retrieval from high-spectral resolution radiance measurements

NASA Astrophysics Data System (ADS)

Weisz, Elisabeth; Smith, William L.; Smith, Nadia

2013-06-01

The dual-regression (DR) method retrieves information about the Earth surface and vertical atmospheric conditions from measurements made by any high-spectral resolution infrared sounder in space. The retrieved information includes temperature and atmospheric gases (such as water vapor, ozone, and carbon species) as well as surface and cloud top parameters. The algorithm was designed to produce a high-quality product with low latency and has been demonstrated to yield accurate results in real-time environments. The speed of the retrieval is achieved through linear regression, while accuracy is achieved through a series of classification schemes and decision-making steps. These steps are necessary to account for the nonlinearity of hyperspectral retrievals. In this work, we detail the key steps that have been developed in the DR method to advance accuracy in the retrieval of nonlinear parameters, specifically cloud top pressure. The steps and their impact on retrieval results are discussed in-depth and illustrated through relevant case studies. In addition to discussing and demonstrating advances made in addressing nonlinearity in a linear geophysical retrieval method, advances toward multi-instrument geophysical analysis by applying the DR to three different operational sounders in polar orbit are also noted. For any area on the globe, the DR method achieves consistent accuracy and precision, making it potentially very valuable to both the meteorological and environmental user communities.

Digital micromirror device as amplitude diffuser for multiple-plane phase retrieval

NASA Astrophysics Data System (ADS)

Abregana, Timothy Joseph T.; Hermosa, Nathaniel P.; Almoro, Percival F.

2017-06-01

Previous implementations of the phase diffuser used in the multiple-plane phase retrieval method included a diffuser glass plate with fixed optical properties or a programmable yet expensive spatial light modulator. Here a model for phase retrieval based on a digital micromirror device as amplitude diffuser is presented. The technique offers programmable, convenient and low-cost amplitude diffuser for a non-stagnating iterative phase retrieval. The technique is demonstrated in the reconstructions of smooth object wavefronts.

Retrieval of seasonal dynamics of forest understory reflectance from semiarid to boreal forests using MODIS BRDF data

NASA Astrophysics Data System (ADS)

Pisek, Jan; Chen, Jing M.; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael E.; Karnieli, Arnon; Sprinstin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi

2016-03-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional reflectance distribution function (MODIS BRDF)/albedo data. We compared satellite-based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N-31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.

Computer-aided diagnosis of mammographic masses using geometric verification-based image retrieval

NASA Astrophysics Data System (ADS)

Li, Qingliang; Shi, Weili; Yang, Huamin; Zhang, Huimao; Li, Guoxin; Chen, Tao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Computer-Aided Diagnosis of masses in mammograms is an important indicator of breast cancer. The use of retrieval systems in breast examination is increasing gradually. In this respect, the method of exploiting the vocabulary tree framework and the inverted file in the mammographic masse retrieval have been proved high accuracy and excellent scalability. However it just considered the features in each image as a visual word and had ignored the spatial configurations of features. It greatly affect the retrieval performance. To overcome this drawback, we introduce the geometric verification method to retrieval in mammographic masses. First of all, we obtain corresponding match features based on the vocabulary tree framework and the inverted file. After that, we grasps the main point of local similarity characteristic of deformations in the local regions by constructing the circle regions of corresponding pairs. Meanwhile we segment the circle to express the geometric relationship of local matches in the area and generate the spatial encoding strictly. Finally we judge whether the matched features are correct or not, based on verifying the all spatial encoding are whether satisfied the geometric consistency. Experiments show the promising results of our approach.

Comparative evaluation of polarimetric and bi-spectral cloud microphysics retrievals: Retrieval closure experiments and comparisons based on idealized and LES case studies

NASA Astrophysics Data System (ADS)

Miller, D. J.; Zhang, Z.; Ackerman, A. S.; Platnick, S. E.; Cornet, C.

2016-12-01

A remote sensing cloud retrieval simulator, created by coupling an LES cloud model with vector radiative transfer (RT) models is the ideal framework for assessing cloud remote sensing techniques. This simulator serves as a tool for understanding bi-spectral and polarimetric retrievals by comparing them directly to LES cloud properties (retrieval closure comparison) and for comparing the retrieval techniques to one another. Our simulator utilizes the DHARMA LES [Ackerman et al., 2004] with cloud properties based on marine boundary layer (MBL) clouds observed during the DYCOMS-II and ATEX field campaigns. The cloud reflectances are produced by the vectorized RT models based on polarized doubling adding and monte carlo techniques (PDA, MCPOL). Retrievals are performed utilizing techniques as similar as possible to those implemented on their corresponding well known instruments; polarimetric retrievals are based on techniques implemented for polarimeters (POLDER, AirMSPI, and RSP) and bi-spectral retrievals are performed using the Nakajima-King LUT method utilized on a number of spectral instruments (MODIS and VIIRS). Retrieval comparisons focus on cloud droplet effective radius (re), effective variance (ve), and cloud optical thickness (τ). This work explores the sensitivities of these two retrieval techniques to various observation limitations, such as spatial resolution/cloud inhomogeneity, impact of 3D radiative effects, and angular resolution requirements. With future remote sensing missions like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important to understand how these retrieval techniques compare to one another. The cloud retrieval simulator we've developed allows us to probe these important questions in a realistically relevant test bed.

The Continuous Monitoring of Desert Dust using an Infrared-based Dust Detection and Retrieval Method

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick; Trepte, Qing; Sun-Mack, Sunny

2006-01-01

Airborne dust and sand are significant aerosol sources that can impact the atmospheric and surface radiation budgets. Because airborne dust affects visibility and air quality, it is desirable to monitor the location and concentrations of this aerosol for transportation and public health. Although aerosol retrievals have been derived for many years using visible and near-infrared reflectance measurements from satellites, the detection and quantification of dust from these channels is problematic over bright surfaces, or when dust concentrations are large. In addition, aerosol retrievals from polar orbiting satellites lack the ability to monitor the progression and sources of dust storms. As a complement to current aerosol dust retrieval algorithms, multi-spectral thermal infrared (8-12 micron) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI) are used in the development of a prototype dust detection method and dust property retrieval that can monitor the progress of Saharan dust fields continuously, both night and day. The dust detection method is incorporated into the processing of CERES (Clouds and the Earth s Radiant Energy System) aerosol retrievals to produce dust property retrievals. Both MODIS (from Terra and Aqua) and SEVERI data are used to develop the method.

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

Donofrio, David

A method and apparatus for performing stencil computations efficiently are disclosed. In one embodiment, a processor receives an offset, and in response, retrieves a value from a memory via a single instruction, where the retrieving comprises: identifying, based on the offset, one of a plurality of registers of the processor; loading an address stored in the identified register; and retrieving from the memory the value at the address.

Semi-Automated Methods for Refining a Domain-Specific Terminology Base

DTIC Science & Technology

2011-02-01

only as a resource for written and oral translation, but also for Natural Language Processing ( NLP ) applications, text retrieval, document indexing...Natural Language Processing ( NLP ) applications, text retrieval, document indexing, and other knowledge management tasks. The objective of this...also for Natural Language Processing ( NLP ) applications, text retrieval (1), document indexing, and other knowledge management tasks. The National

A new approach to the concept of "relevance" in information retrieval (IR).

PubMed

Kagolovsky, Y; Möhr, J R

2001-01-01

The concept of "relevance" is the fundamental concept of information science in general and information retrieval, in particular. Although "relevance" is extensively used in evaluation of information retrieval, there are considerable problems associated with reaching an agreement on its definition, meaning, evaluation, and application in information retrieval. There are a number of different views on "relevance" and its use for evaluation. Based on a review of the literature the main problems associated with the concept of "relevance" in information retrieval are identified. The authors argue that the proposal for the solution of the problems can be based on the conceptual IR framework built using a systems analytic approach to IR. Using this framework different kinds of "relevance" relationships in the IR process are identified, and a methodology for evaluation of "relevance" based on methods of semantics capturing and comparison is proposed.

Do Family Physicians Retrieve Synopses of Clinical Research Previously Read as Email Alerts?

PubMed Central

Pluye, Pierre; Johnson-Lafleur, Janique; Granikov, Vera; Shulha, Michael; Bartlett, Gillian; Marlow, Bernard

2011-01-01

Background A synopsis of new clinical research highlights important aspects of one study in a brief structured format. When delivered as email alerts, synopses enable clinicians to become aware of new developments relevant for practice. Once read, a synopsis can become a known item of clinical information. In time-pressured situations, remembering a known item may facilitate information retrieval by the clinician. However, exactly how synopses first delivered as email alerts influence retrieval at some later time is not known. Objectives We examined searches for clinical information in which a synopsis previously read as an email alert was retrieved (defined as a dyad). Our study objectives were to (1) examine whether family physicians retrieved synopses they previously read as email alerts and then to (2) explore whether family physicians purposefully retrieved these synopses. Methods We conducted a mixed-methods study in which a qualitative multiple case study explored the retrieval of email alerts within a prospective longitudinal cohort of practicing family physicians. Reading of research-based synopses was tracked in two contexts: (1) push, meaning to read on email and (2) pull, meaning to read after retrieval from one electronic knowledge resource. Dyads, defined as synopses first read as email alerts and subsequently retrieved in a search of a knowledge resource, were prospectively identified. Participants were interviewed about all of their dyads. Outcomes were the total number of dyads and their type. Results Over a period of 341 days, 194 unique synopses delivered to 41 participants resulted in 4937 synopsis readings. In all, 1205 synopses were retrieved over an average of 320 days. Of the 1205 retrieved synopses, 21 (1.7%) were dyads made by 17 family physicians. Of the 1205 retrieved synopses, 6 (0.5%) were known item type dyads. However, dyads also occurred serendipitously. Conclusion In the single knowledge resource we studied, email alerts containing research-based synopses were rarely retrieved. Our findings help us to better understand the effect of push on pull and to improve the integration of research-based information within electronic resources for clinicians. PMID:22130465

Aerosol-type retrieval and uncertainty quantification from OMI data

NASA Astrophysics Data System (ADS)

Kauppi, Anu; Kolmonen, Pekka; Laine, Marko; Tamminen, Johanna

2017-11-01

We discuss uncertainty quantification for aerosol-type selection in satellite-based atmospheric aerosol retrieval. The retrieval procedure uses precalculated aerosol microphysical models stored in look-up tables (LUTs) and top-of-atmosphere (TOA) spectral reflectance measurements to solve the aerosol characteristics. The forward model approximations cause systematic differences between the modelled and observed reflectance. Acknowledging this model discrepancy as a source of uncertainty allows us to produce more realistic uncertainty estimates and assists the selection of the most appropriate LUTs for each individual retrieval.This paper focuses on the aerosol microphysical model selection and characterisation of uncertainty in the retrieved aerosol type and aerosol optical depth (AOD). The concept of model evidence is used as a tool for model comparison. The method is based on Bayesian inference approach, in which all uncertainties are described as a posterior probability distribution. When there is no single best-matching aerosol microphysical model, we use a statistical technique based on Bayesian model averaging to combine AOD posterior probability densities of the best-fitting models to obtain an averaged AOD estimate. We also determine the shared evidence of the best-matching models of a certain main aerosol type in order to quantify how plausible it is that it represents the underlying atmospheric aerosol conditions.The developed method is applied to Ozone Monitoring Instrument (OMI) measurements using a multiwavelength approach for retrieving the aerosol type and AOD estimate with uncertainty quantification for cloud-free over-land pixels. Several larger pixel set areas were studied in order to investigate the robustness of the developed method. We evaluated the retrieved AOD by comparison with ground-based measurements at example sites. We found that the uncertainty of AOD expressed by posterior probability distribution reflects the difficulty in model selection. The posterior probability distribution can provide a comprehensive characterisation of the uncertainty in this kind of problem for aerosol-type selection. As a result, the proposed method can account for the model error and also include the model selection uncertainty in the total uncertainty budget.

Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography.

PubMed

Marschner, Mathias; Birnbacher, Lorenz; Willner, Marian; Chabior, Michael; Herzen, Julia; Noël, Peter B; Pfeiffer, Franz

2017-01-01

Phase-contrast x-ray computed tomography (PCCT) is currently investigated as an interesting extension of conventional CT, providing high soft-tissue contrast even if examining weakly absorbing specimen. Until now, the potential for dose reduction was thought to be limited compared to attenuation CT, since meaningful phase retrieval fails for scans with very low photon counts when using the conventional phase retrieval method via phase stepping. In this work, we examine the statistical behaviour of the reverse projection method, an alternative phase retrieval approach and compare the results to the conventional phase retrieval technique. We investigate the noise levels in the projections as well as the image quality and quantitative accuracy of the reconstructed tomographic volumes. The results of our study show that this method performs better in a low-dose scenario than the conventional phase retrieval approach, resulting in lower noise levels, enhanced image quality and more accurate quantitative values. Overall, we demonstrate that the lower statistical limit of the phase stepping procedure as proposed by recent literature does not apply to this alternative phase retrieval technique. However, further development is necessary to overcome experimental challenges posed by this method which would enable mainstream or even clinical application of PCCT.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2012-09-01

Volcanic ash cloud top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach over 30 km which implies ACTH of more than 12 km in the beginning of the eruption. In the end of April eruption ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2013-03-01

Volcanic ash cloud-top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach 30 km, which implies an ACTH of approximately 12 km at the beginning of the eruption. At the end of April eruption an ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Synergistic method for boreal soil moisture and soil freeze retrievals using active and passive microwave instruments

NASA Astrophysics Data System (ADS)

Smolander, Tuomo; Lemmetyinen, Juha; Rautiainen, Kimmo; Schwank, Mike; Pulliainen, Jouni

2017-04-01

Soil moisture and soil freezing are important for diverse hydrological, biogeochemical, and climatological applications. They affect surface energy balance, surface and subsurface water flow, and exchange rates of carbon with the atmosphere. Soil freezing controls important biogeochemical processes, like photosynthetic activity of plants and microbial activity within soils. Permafrost covers approximately 24% of the land surface in the Northern Hemisphere and seasonal freezing occurs on approximately 51% of the area. The retrieval method presented is based on an inversion technique and applies a semiempirical backscattering model that describes the dependence of radar backscattering of forest as a function of stem volume, soil permittivity, the extinction coefficient of forest canopy, surface roughness, incidence angle, and radar frequency. It gives an estimate of soil permittivity using active microwave measurements. Applying a Bayesian assimilation scheme, it is also possible to use other soil permittivity retrievals to regulate this estimate to combine for example low resolution passive observations with high resolution active observations for a synergistic retrieval. This way the higher variance in the active retrieval can be constricted with the passive retrieval when at the same time the spatial resolution of the product is improved compared to the passive-only retrieval. The retrieved soil permittivity estimate can be used to detect soil freeze/thaw state by considering the soil to be frozen when the estimate is below a threshold value. The permittivity retrieval can also be used to estimate the relative moisture of the soil. The method was tested using SAR (Synthetic Aperture Radar) measurements from ENVISAT ASAR instrument for the years 2010-2012 and from Sentinel-1 satellite for the years 2015-2016 in Sodankylä area in Northern Finland. The synergistic method was tested combining the SAR measurements with a SMOS (Soil Moisture Ocean Salinity) radiometer based retrieval. The results were validated using in situ measurements from automatic soil state observation stations in Sodankylä calibration and validation (CAL-VAL) site, which is a reference site for several EO (Earth Observation) data products.

A comparison of two methods for retrieving ICD-9-CM data: the effect of using an ontology-based method for handling terminology changes.

PubMed

Yu, Alexander C; Cimino, James J

2011-04-01

Most existing controlled terminologies can be characterized as collections of terms, wherein the terms are arranged in a simple list or organized in a hierarchy. These kinds of terminologies are considered useful for standardizing terms and encoding data and are currently used in many existing information systems. However, they suffer from a number of limitations that make data reuse difficult. Relatively recently, it has been proposed that formal ontological methods can be applied to some of the problems of terminological design. Biomedical ontologies organize concepts (embodiments of knowledge about biomedical reality) whereas terminologies organize terms (what is used to code patient data at a certain point in time, based on the particular terminology version). However, the application of these methods to existing terminologies is not straightforward. The use of these terminologies is firmly entrenched in many systems, and what might seem to be a simple option of replacing these terminologies is not possible. Moreover, these terminologies evolve over time in order to suit the needs of users. Any methodology must therefore take these constraints into consideration, hence the need for formal methods of managing changes. Along these lines, we have developed a formal representation of the concept-term relation, around which we have also developed a methodology for management of terminology changes. The objective of this study was to determine whether our methodology would result in improved retrieval of data. Comparison of two methods for retrieving data encoded with terms from the International Classification of Diseases (ICD-9-CM), based on their recall when retrieving data for ICD-9-CM terms whose codes had changed but which had retained their original meaning (code change). Recall and interclass correlation coefficient. Statistically significant differences were detected (p<0.05) with the McNemar test for two terms whose codes had changed. Furthermore, when all the cases are combined in an overall category, our method also performs statistically significantly better (p<0.05). Our study shows that an ontology-based ICD-9-CM data retrieval method that takes into account the effects of terminology changes performs better on recall than one that does not in the retrieval of data for terms whose codes had changed but which retained their original meaning. Copyright © 2011 Elsevier Inc. All rights reserved.

A Comparison of Two Methods for Retrieving ICD-9-CM data: The Effect of Using an Ontology-based Method for Handling Terminology Changes

PubMed Central

Yu, Alexander C.; Cimino, James J.

2012-01-01

Objective Most existing controlled terminologies can be characterized as collections of terms, wherein the terms are arranged in a simple list or organized in a hierarchy. These kinds of terminologies are considered useful for standardizing terms and encoding data and are currently used in many existing information systems. However, they suffer from a number of limitations that make data reuse difficult. Relatively recently, it has been proposed that formal ontological methods can be applied to some of the problems of terminological design. Biomedical ontologies organize concepts (embodiments of knowledge about biomedical reality) whereas terminologies organize terms (what is used to code patient data at a certain point in time, based on the particular terminology version). However, the application of these methods to existing terminologies is not straightforward. The use of these terminologies is firmly entrenched in many systems, and what might seem to be a simple option of replacing these terminologies is not possible. Moreover, these terminologies evolve over time in order to suit the needs of users. Any methodology must therefore take these constraints into consideration, hence the need for formal methods of managing changes. Along these lines, we have developed a formal representation of the concept-term relation, around which we have also developed a methodology for management of terminology changes. The objective of this study was to determine whether our methodology would result in improved retrieval of data. Design Comparison of two methods for retrieving data encoded with terms from the International Classification of Diseases (ICD-9-CM), based on their recall when retrieving data for ICD-9-CM terms whose codes had changed but which had retained their original meaning (code change). Measurements Recall and interclass correlation coefficient. Results Statistically significant differences were detected (p<0.05) with the McNemar test for two terms whose codes had changed. Furthermore, when all the cases are combined in an overall category, our method also performs statistically significantly better (p < 0.05). Conclusion Our study shows that an ontology-based ICD-9-CM data retrieval method that takes into account the effects of terminology changes performs better on recall than one that does not in the retrieval of data for terms whose codes had changed but which retained their original meaning. PMID:21262390

Towards a true aerosol-and-cloud retrieval scheme

NASA Astrophysics Data System (ADS)

Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don

2014-05-01

The Optimal Retrieval of Aerosol and Cloud (ORAC) - formally the Oxford-RAL Aerosol and Cloud retrieval - offers a framework that can provide consistent and well characterised properties of both aerosols and clouds from a range of imaging satellite instruments. Several practical issues stand in the way of achieving the potential of this combined scheme however; in particular the sometimes conflicting priorities and requirements of aerosol and cloud retrieval problems, and the question of the unambiguous identification of aerosol and cloud pixels. This presentation will present recent developments made to the ORAC scheme for both aerosol and cloud, and detail how these are being integrated into a single retrieval framework. The implementation of a probabilistic method for pixel identification will also be presented, for both cloud detection and aerosol/cloud type selection. The method is based on Bayesian methods applied the optimal estimation retrieval output of ORAC and is particularly aimed at providing additional information in the so-called "twilight zone", where pixels can't be unambiguously identified as either aerosol or cloud and traditional cloud or aerosol products do not provide results.

Feasibility study of complex wavefield retrieval in off-axis acoustic holography employing an acousto-optic sensor

PubMed Central

Rodríguez, Guillermo López; Weber, Joshua; Sandhu, Jaswinder Singh; Anastasio, Mark A.

2011-01-01

We propose and experimentally demonstrate a new method for complex-valued wavefield retrieval in off-axis acoustic holography. The method involves use of an intensity-sensitive acousto-optic (AO) sensor, optimized for use at 3.3 MHz, to record the acoustic hologram and a computational method for reconstruction of the object wavefield. The proposed method may circumvent limitations of conventional implementations of acoustic holography and may facilitate the development of acoustic-holography-based biomedical imaging methods. PMID:21669451

Content-based video retrieval by example video clip

NASA Astrophysics Data System (ADS)

Dimitrova, Nevenka; Abdel-Mottaleb, Mohamed

1997-01-01

This paper presents a novel approach for video retrieval from a large archive of MPEG or Motion JPEG compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the database for clips with similar contents. Video clips are characterized by a sequence of representative frame signatures, which are constructed from DC coefficients and motion information (`DC+M' signatures). The similarity between two video clips is determined by using their respective signatures. This method facilitates retrieval of clips for the purpose of video editing, broadcast news retrieval, or copyright violation detection.

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

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

Blanchard, Yann; Royer, Alain; O'Neill, Norman T.

Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

NASA Astrophysics Data System (ADS)

Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; Turner, David D.; Eloranta, Edwin W.

2017-06-01

Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

DOE PAGES

Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; ...

2017-06-09

Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less

An automatic method for retrieving and indexing catalogues of biomedical courses.

PubMed

Maojo, Victor; de la Calle, Guillermo; García-Remesal, Miguel; Bankauskaite, Vaida; Crespo, Jose

2008-11-06

Although there is wide information about Biomedical Informatics education and courses in different Websites, information is usually not exhaustive and difficult to update. We propose a new methodology based on information retrieval techniques for extracting, indexing and retrieving automatically information about educational offers. A web application has been developed to make available such information in an inventory of courses and educational offers.

Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

NASA Astrophysics Data System (ADS)

Chen, Yi-Chen; Lin, Chao-Hung

2016-06-01

With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.

The NLM Indexing Initiative.

PubMed Central

Aronson, A. R.; Bodenreider, O.; Chang, H. F.; Humphrey, S. M.; Mork, J. G.; Nelson, S. J.; Rindflesch, T. C.; Wilbur, W. J.

2000-01-01

The objective of NLM's Indexing Initiative (IND) is to investigate methods whereby automated indexing methods partially or completely substitute for current indexing practices. The project will be considered a success if methods can be designed and implemented that result in retrieval performance that is equal to or better than the retrieval performance of systems based principally on humanly assigned index terms. We describe the current state of the project and discuss our plans for the future. PMID:11079836

Fast non-interferometric iterative phase retrieval for holographic data storage.

PubMed

Lin, Xiao; Huang, Yong; Shimura, Tsutomu; Fujimura, Ryushi; Tanaka, Yoshito; Endo, Masao; Nishimoto, Hajimu; Liu, Jinpeng; Li, Yang; Liu, Ying; Tan, Xiaodi

2017-12-11

Fast non-interferometric phase retrieval is a very important technique for phase-encoded holographic data storage and other phase based applications due to its advantage of easy implementation, simple system setup, and robust noise tolerance. Here we present an iterative non-interferometric phase retrieval for 4-level phase encoded holographic data storage based on an iterative Fourier transform algorithm and known portion of the encoded data, which increases the storage code rate to two-times that of an amplitude based method. Only a single image at the Fourier plane of the beam is captured for the iterative reconstruction. Since beam intensity at the Fourier plane of the reconstructed beam is more concentrated than the reconstructed beam itself, the requirement of diffractive efficiency of the recording media is reduced, which will improve the dynamic range of recording media significantly. The phase retrieval only requires 10 iterations to achieve a less than 5% phase data error rate, which is successfully demonstrated by recording and reconstructing a test image data experimentally. We believe our method will further advance the holographic data storage technique in the era of big data.

Qualification of a Null Lens Using Image-Based Phase Retrieval

NASA Technical Reports Server (NTRS)

Bolcar, Matthew R.; Aronstein, David L.; Hill, Peter C.; Smith, J. Scott; Zielinski, Thomas P.

2012-01-01

In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed.

Clinical-decision support based on medical literature: A complex network approach

NASA Astrophysics Data System (ADS)

Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

2016-10-01

In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.

Effectiveness of image features and similarity measures in cluster-based approaches for content-based image retrieval

NASA Astrophysics Data System (ADS)

Du, Hongbo; Al-Jubouri, Hanan; Sellahewa, Harin

2014-05-01

Content-based image retrieval is an automatic process of retrieving images according to image visual contents instead of textual annotations. It has many areas of application from automatic image annotation and archive, image classification and categorization to homeland security and law enforcement. The key issues affecting the performance of such retrieval systems include sensible image features that can effectively capture the right amount of visual contents and suitable similarity measures to find similar and relevant images ranked in a meaningful order. Many different approaches, methods and techniques have been developed as a result of very intensive research in the past two decades. Among many existing approaches, is a cluster-based approach where clustering methods are used to group local feature descriptors into homogeneous regions, and search is conducted by comparing the regions of the query image against those of the stored images. This paper serves as a review of works in this area. The paper will first summarize the existing work reported in the literature and then present the authors' own investigations in this field. The paper intends to highlight not only achievements made by recent research but also challenges and difficulties still remaining in this area.

Technical Note: Synchrotron-based high-energy x-ray phase sensitive microtomography for biomedical research

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

Liu, Huiqiang; Wu, Xizeng, E-mail: xwu@uabmc.edu, E-mail: tqxiao@sinap.ac.cn; Xiao, Tiqiao, E-mail: xwu@uabmc.edu, E-mail: tqxiao@sinap.ac.cn

Purpose: Propagation-based phase-contrast CT (PPCT) utilizes highly sensitive phase-contrast technology applied to x-ray microtomography. Performing phase retrieval on the acquired angular projections can enhance image contrast and enable quantitative imaging. In this work, the authors demonstrate the validity and advantages of a novel technique for high-resolution PPCT by using the generalized phase-attenuation duality (PAD) method of phase retrieval. Methods: A high-resolution angular projection data set of a fish head specimen was acquired with a monochromatic 60-keV x-ray beam. In one approach, the projection data were directly used for tomographic reconstruction. In two other approaches, the projection data were preprocessed bymore » phase retrieval based on either the linearized PAD method or the generalized PAD method. The reconstructed images from all three approaches were then compared in terms of tissue contrast-to-noise ratio and spatial resolution. Results: The authors’ experimental results demonstrated the validity of the PPCT technique based on the generalized PAD-based method. In addition, the results show that the authors’ technique is superior to the direct PPCT technique as well as the linearized PAD-based PPCT technique in terms of their relative capabilities for tissue discrimination and characterization. Conclusions: This novel PPCT technique demonstrates great potential for biomedical imaging, especially for applications that require high spatial resolution and limited radiation exposure.« less

Extended capture range for focus-diverse phase retrieval in segmented aperture systems using geometrical optics.

PubMed

Jurling, Alden S; Fienup, James R

2014-03-01

Extending previous work by Thurman on wavefront sensing for segmented-aperture systems, we developed an algorithm for estimating segment tips and tilts from multiple point spread functions in different defocused planes. We also developed methods for overcoming two common modes for stagnation in nonlinear optimization-based phase retrieval algorithms for segmented systems. We showed that when used together, these methods largely solve the capture range problem in focus-diverse phase retrieval for segmented systems with large tips and tilts. Monte Carlo simulations produced a rate of success better than 98% for the combined approach.

Northeast Artificial Intelligence Consortium (NAIC). Volume 14. Knowledge Base Retrieval Using Plausible Inference

DTIC Science & Technology

1990-12-01

Improvements to Research Environment ............... 6 14.3 Overview of Research ....... .......................... 7 14.3.1 An Experimental Study of...efficient inference methods. The critical issue we have studied is the effectiveness of retrieval. By this, we mean how well the system does at...locating objects that are judged relevant by the user . Designing effective retrieval strategies is difficult because in real environments the query

Biomass Burning Aerosol Absorption Measurements with MODIS Using the Critical Reflectance Method

NASA Technical Reports Server (NTRS)

Zhu, Li; Martins, Vanderlei J.; Remer, Lorraine A.

2010-01-01

This research uses the critical reflectance technique, a space-based remote sensing method, to measure the spatial distribution of aerosol absorption properties over land. Choosing two regions dominated by biomass burning aerosols, a series of sensitivity studies were undertaken to analyze the potential limitations of this method for the type of aerosol to be encountered in the selected study areas, and to show that the retrieved results are relatively insensitive to uncertainties in the assumptions used in the retrieval of smoke aerosol. The critical reflectance technique is then applied to Moderate Resolution Imaging Spectrometer (MODIS) data to retrieve the spectral aerosol single scattering albedo (SSA) in South African and South American 35 biomass burning events. The retrieved results were validated with collocated Aerosol Robotic Network (AERONET) retrievals. One standard deviation of mean MODIS retrievals match AERONET products to within 0.03, the magnitude of the AERONET uncertainty. The overlap of the two retrievals increases to 88%, allowing for measurement variance in the MODIS retrievals as well. The ensemble average of MODIS-derived SSA for the Amazon forest station is 0.92 at 670 nm, and 0.84-0.89 for the southern African savanna stations. The critical reflectance technique allows evaluation of the spatial variability of SSA, and shows that SSA in South America exhibits higher spatial variation than in South Africa. The accuracy of the retrieved aerosol SSA from MODIS data indicates that this product can help to better understand 44 how aerosols affect the regional and global climate.

Cloud Property Retrieval Products for Graciosa Island, Azores

DOE Data Explorer

Dong, Xiquan

2014-05-05

The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.

Document image database indexing with pictorial dictionary

NASA Astrophysics Data System (ADS)

Akbari, Mohammad; Azimi, Reza

2010-02-01

In this paper we introduce a new approach for information retrieval from Persian document image database without using Optical Character Recognition (OCR).At first an attribute called subword upper contour label is defined then, a pictorial dictionary is constructed based on this attribute for the subwords. By this approach we address two issues in document image retrieval: keyword spotting and retrieval according to the document similarities. The proposed methods have been evaluated on a Persian document image database. The results have proved the ability of this approach in document image information retrieval.

Retrieval of the atmospheric compounds using a spectral optical thickness information

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

Ioltukhovski, A.A.

A spectral inversion technique for retrieval of the atmospheric gases and aerosols contents is proposed. This technique based upon the preliminary measurement or retrieval of the spectral optical thickness. The existence of a priori information about the spectral cross sections for some of the atmospheric components allows to retrieve the relative contents of these components in the atmosphere. Method of smooth filtration makes possible to estimate contents of atmospheric aerosols with known cross sections and to filter out other aerosols; this is done independently from their relative contribution to the optical thickness.

Novel Algorithm for Classification of Medical Images

NASA Astrophysics Data System (ADS)

Bhushan, Bharat; Juneja, Monika

2010-11-01

Content-based image retrieval (CBIR) methods in medical image databases have been designed to support specific tasks, such as retrieval of medical images. These methods cannot be transferred to other medical applications since different imaging modalities require different types of processing. To enable content-based queries in diverse collections of medical images, the retrieval system must be familiar with the current Image class prior to the query processing. Further, almost all of them deal with the DICOM imaging format. In this paper a novel algorithm based on energy information obtained from wavelet transform for the classification of medical images according to their modalities is described. For this two types of wavelets have been used and have been shown that energy obtained in either case is quite distinct for each of the body part. This technique can be successfully applied to different image formats. The results are shown for JPEG imaging format.

Snow depth and snow cover retrieval from FengYun3B microwave radiation imagery based on a snow passive microwave unmixing method in Northeast China

NASA Astrophysics Data System (ADS)

Gu, Lingjia; Ren, Ruizhi; Zhao, Kai; Li, Xiaofeng

2014-01-01

The precision of snow parameter retrieval is unsatisfactory for current practical demands. The primary reason is because of the problem of mixed pixels that are caused by low spatial resolution of satellite passive microwave data. A snow passive microwave unmixing method is proposed in this paper, based on land cover type data and the antenna gain function of passive microwaves. The land cover type of Northeast China is partitioned into grass, farmland, bare soil, forest, and water body types. The component brightness temperatures (CBT), namely unmixed data, with 1 km data resolution are obtained using the proposed unmixing method. The snow depth determined by the CBT and three snow depth retrieval algorithms are validated through field measurements taken in forest and farmland areas of Northeast China in January 2012 and 2013. The results show that the overall of the retrieval precision of the snow depth is improved by 17% in farmland areas and 10% in forest areas when using the CBT in comparison with the mixed pixels. The snow cover results based on the CBT are compared with existing MODIS snow cover products. The results demonstrate that more snow cover information can be obtained with up to 86% accuracy.

Parameter retrieval of chiral metamaterials based on the state-space approach.

PubMed

Zarifi, Davoud; Soleimani, Mohammad; Abdolali, Ali

2013-08-01

This paper deals with the introduction of an approach for the electromagnetic characterization of homogeneous chiral layers. The proposed method is based on the state-space approach and properties of a 4×4 state transition matrix. Based on this, first, the forward problem analysis through the state-space method is reviewed and properties of the state transition matrix of a chiral layer are presented and proved as two theorems. The formulation of a proposed electromagnetic characterization method is then presented. In this method, scattering data for a linearly polarized plane wave incident normally on a homogeneous chiral slab are combined with properties of a state transition matrix and provide a powerful characterization method. The main difference with respect to other well-established retrieval procedures based on the use of the scattering parameters relies on the direct computation of the transfer matrix of the slab as opposed to the conventional calculation of the propagation constant and impedance of the modes supported by the medium. The proposed approach allows avoiding nonlinearity of the problem but requires getting enough equations to fulfill the task which was provided by considering some properties of the state transition matrix. To demonstrate the applicability and validity of the method, the constitutive parameters of two well-known dispersive chiral metamaterial structures at microwave frequencies are retrieved. The results show that the proposed method is robust and reliable.

Statistical retrieval of thin liquid cloud microphysical properties using ground-based infrared and microwave observations

NASA Astrophysics Data System (ADS)

Marke, Tobias; Ebell, Kerstin; Löhnert, Ulrich; Turner, David D.

2016-12-01

In this article, liquid water cloud microphysical properties are retrieved by a combination of microwave and infrared ground-based observations. Clouds containing liquid water are frequently occurring in most climate regimes and play a significant role in terms of interaction with radiation. Small perturbations in the amount of liquid water contained in the cloud can cause large variations in the radiative fluxes. This effect is enhanced for thin clouds (liquid water path, LWP <100 g/m2), which makes accurate retrieval information of the cloud properties crucial. Due to large relative errors in retrieving low LWP values from observations in the microwave domain and a high sensitivity for infrared methods when the LWP is low, a synergistic retrieval based on a neural network approach is built to estimate both LWP and cloud effective radius (reff). These statistical retrievals can be applied without high computational demand but imply constraints like prior information on cloud phase and cloud layering. The neural network retrievals are able to retrieve LWP and reff for thin clouds with a mean relative error of 9% and 17%, respectively. This is demonstrated using synthetic observations of a microwave radiometer (MWR) and a spectrally highly resolved infrared interferometer. The accuracy and robustness of the synergistic retrievals is confirmed by a low bias in a radiative closure study for the downwelling shortwave flux, even for marginally invalid scenes. Also, broadband infrared radiance observations, in combination with the MWR, have the potential to retrieve LWP with a higher accuracy than a MWR-only retrieval.

Retrieval and Validation of aerosol optical properties from AHI measurements: impact of surface reflectance assumption

NASA Astrophysics Data System (ADS)

Lim, H.; Choi, M.; Kim, J.; Go, S.; Chan, P.; Kasai, Y.

2017-12-01

This study attempts to retrieve the aerosol optical properties (AOPs) based on the spectral matching method, with using three visible and one near infrared channels (470, 510, 640, 860nm). This method requires the preparation of look-up table (LUT) approach based on the radiative transfer modeling. Cloud detection is one of the most important processes for guaranteed quality of AOPs. Since the AHI has several infrared channels, which are very advantageous for cloud detection, clouds can be removed by using brightness temperature difference (BTD) and spatial variability test. The Yonsei Aerosol Retrieval (YAER) algorithm is basically utilized on a dark surface, therefore a bright surface (e.g., desert, snow) should be removed first. Then we consider the characteristics of the reflectance of land and ocean surface using three visible channels. The known surface reflectivity problem in high latitude area can be solved in this algorithm by selecting appropriate channels through improving tests. On the other hand, we retrieved the AOPs by obtaining the visible surface reflectance using NIR to normalized difference vegetation index short wave infrared (NDVIswir) relationship. ESR tends to underestimate urban and cropland area, we improved the visible surface reflectance considering urban effect. In this version, ocean surface reflectance is using the new cox and munk method which considers ocean bidirectional reflectance distribution function (BRDF). Input of this method has wind speed, chlorophyll, salinity and so on. Based on validation results with the sun-photometer measurement in AErosol Robotic NETwork (AERONET), we confirm that the quality of Aerosol Optical Depth (AOD) from the YAER algorithm is comparable to the product from the Japan Aerospace Exploration Agency (JAXA) retrieval algorithm. Our future update includes a consideration of improvement land surface reflectance by hybrid approach, and non-spherical aerosols. This will improve the quality of YAER algorithm more, particularly retrieval for the dust particle over the bright surface in East Asia.

Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters

NASA Astrophysics Data System (ADS)

Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.

2004-12-01

Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various large heterogeneous spatial-temporal datasets provide evidence that the benefits of the proposed methodology for efficient and accurate learning exist beyond the area of retrieval of geophysical parameters.

Simultaneous Retrieval of Aerosol and Surface Optical Properties from Combined Airborne- and Ground-Based Direct and Diffuse Radiometric Measurements

NASA Technical Reports Server (NTRS)

Gatebe, C. K.; Dubovik, O.; King, M. D.; Sinyuk, A.

2010-01-01

This paper presents a new method for simultaneously retrieving aerosol and surface reflectance properties from combined airborne and ground-based direct and diffuse radiometric measurements. The method is based on the standard Aerosol Robotic Network (AERONET) method for retrieving aerosol size distribution, complex index of refraction, and single scattering albedo, but modified to retrieve aerosol properties in two layers, below and above the aircraft, and parameters on surface optical properties from combined datasets (Cloud Absorption Radiometer (CAR) and AERONET data). A key advantage of this method is the inversion of all available spectral and angular data at the same time, while accounting for the influence of noise in the inversion procedure using statistical optimization. The wide spectral (0.34-2.30 m) and angular range (180 ) of the CAR instrument, combined with observations from an AERONET sunphotometer, provide sufficient measurement constraints for characterizing aerosol and surface properties with minimal assumptions. The robustness of the method was tested on observations made during four different field campaigns: (a) the Southern African Regional Science Initiative 2000 over Mongu, Zambia, (b) the Intercontinental Transport Experiment-Phase B over Mexico City, Mexico (c) Cloud and Land Surface Interaction Campaign over the Atmospheric Radiation Measurement (ARM) Central Facility, Oklahoma, USA, and (d) the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) over Elson Lagoon in Barrow, Alaska, USA. The four areas are dominated by different surface characteristics and aerosol types, and therefore provide good test cases for the new inversion method.

Operational Retrievals of Evapotranspiration: Are we there yet?

NASA Astrophysics Data System (ADS)

Neale, C. M. U.; Anderson, M. C.; Hain, C.; Schull, M.; Isidro, C., Sr.; Goncalves, I. Z.

2017-12-01

Remote sensing based retrievals of evapotranspiration (ET) have progressed significantly over the last two decades with the improvement of methods and algorithms and the availability of multiple satellite sensors with shortwave and thermal infrared bands on polar orbiting platforms. The modeling approaches include simpler vegetation index (VI) based methods such as the reflectance-based crop coefficient approach coupled with surface reference evapotranspiration estimates to derive actual evapotranspiration of crops or, direct inputs to the Penman-Monteith equation through VI relationships with certain input variables. Methods that are more complex include one-layer or two-layer energy balance approaches that make use of both shortwave and longwave spectral band information to estimate different inputs to the energy balance equation. These models mostly differ in the estimation of sensible heat fluxes. For continental and global scale applications, other satellite-based products such as solar radiation, vegetation leaf area and cover are used as inputs, along with gridded re-analysis weather information. This presentation will review the state-of-the-art in satellite-based evapotranspiration estimation, giving examples of existing efforts to obtain operational ET retrievals over continental and global scales and discussing difficulties and challenges.

Combining approaches to on-line handwriting information retrieval

NASA Astrophysics Data System (ADS)

Peña Saldarriaga, Sebastián; Viard-Gaudin, Christian; Morin, Emmanuel

2010-01-01

In this work, we propose to combine two quite different approaches for retrieving handwritten documents. Our hypothesis is that different retrieval algorithms should retrieve different sets of documents for the same query. Therefore, significant improvements in retrieval performances can be expected. The first approach is based on information retrieval techniques carried out on the noisy texts obtained through handwriting recognition, while the second approach is recognition-free using a word spotting algorithm. Results shows that for texts having a word error rate (WER) lower than 23%, the performances obtained with the combined system are close to the performances obtained on clean digital texts. In addition, for poorly recognized texts (WER > 52%), an improvement of nearly 17% can be observed with respect to the best available baseline method.

A minimum albedo aerosol retrieval method for the new-generation geostationary meteorological satellite Himawari-8

NASA Astrophysics Data System (ADS)

Yan, Xing; Li, Zhanqing; Luo, Nana; Shi, Wenzhong; Zhao, Wenji; Yang, Xingchuan; Jin, Jiannan

2018-07-01

Aerosol properties, including aerosol optical thickness (AOT) and fine-mode fraction (FMF), are important physical data and are fundamental for climate studies. A minimum albedo aerosol retrieval method (MAARM) was developed for the retrieval of aerosol properties based on the new-generation geostationary meteorological satellite Himawari-8. This method is based on the albedo data which is directly obtained from the Himawari-8 and can successfully output AOT, FMF, and the Ångström exponent (AE) directly. As part of the MAARM, a modified radiative transfer equation was proposed that considers the impact of aerosol multiple scattering. Through comparisons with output from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer code, the modified radiative transfer equation achieved a high accuracy for the aerosol reflectance calculation ( 5%). Aerosol Robotic Network (AERONET) data from three sites in Beijing and its surrounding area for the year 2016 were used to validate MAARM aerosol retrievals. Fifty-seven percent, 57%, and 56% of derived AOT values fell within the estimated error envelope at the Beijing, the Chinese Academy of Meteorological Sciences (CAMS), and Xianghe AERONET stations, respectively. In addition, 36% (58%) of MAARM-derived FMF values fell within the ±10%AERONET FMF envelope (the ±25%AERONET FMF envelope). Overall, an improvement was achieved by the MAARM in retrieving AOT, FMF, and AE compared with Himawari-8 standard aerosol property retrievals; however, there remains a distinct lack of skills in determining FMF and AE and their use from the MAARM retrieval is not recommended at this time. Given that the Himawari-8 satellite provides observations at 10-min intervals, the MAARM is capable of monitoring the spatial distribution of and variation in AOT with a high temporal resolution.

Penalized maximum likelihood reconstruction for x-ray differential phase-contrast tomography

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

Brendel, Bernhard, E-mail: bernhard.brendel@philips.com; Teuffenbach, Maximilian von; Noël, Peter B.

2016-01-15

Purpose: The purpose of this work is to propose a cost function with regularization to iteratively reconstruct attenuation, phase, and scatter images simultaneously from differential phase contrast (DPC) acquisitions, without the need of phase retrieval, and examine its properties. Furthermore this reconstruction method is applied to an acquisition pattern that is suitable for a DPC tomographic system with continuously rotating gantry (sliding window acquisition), overcoming the severe smearing in noniterative reconstruction. Methods: We derive a penalized maximum likelihood reconstruction algorithm to directly reconstruct attenuation, phase, and scatter image from the measured detector values of a DPC acquisition. The proposed penaltymore » comprises, for each of the three images, an independent smoothing prior. Image quality of the proposed reconstruction is compared to images generated with FBP and iterative reconstruction after phase retrieval. Furthermore, the influence between the priors is analyzed. Finally, the proposed reconstruction algorithm is applied to experimental sliding window data acquired at a synchrotron and results are compared to reconstructions based on phase retrieval. Results: The results show that the proposed algorithm significantly increases image quality in comparison to reconstructions based on phase retrieval. No significant mutual influence between the proposed independent priors could be observed. Further it could be illustrated that the iterative reconstruction of a sliding window acquisition results in images with substantially reduced smearing artifacts. Conclusions: Although the proposed cost function is inherently nonconvex, it can be used to reconstruct images with less aliasing artifacts and less streak artifacts than reconstruction methods based on phase retrieval. Furthermore, the proposed method can be used to reconstruct images of sliding window acquisitions with negligible smearing artifacts.« less

Skin image retrieval using Gabor wavelet texture feature.

PubMed

Ou, X; Pan, W; Zhang, X; Xiao, P

2016-12-01

Skin imaging plays a key role in many clinical studies. We have used many skin imaging techniques, including the recently developed capacitive contact skin imaging based on fingerprint sensors. The aim of this study was to develop an effective skin image retrieval technique using Gabor wavelet transform, which can be used on different types of skin images, but with a special focus on skin capacitive contact images. Content-based image retrieval (CBIR) is a useful technology to retrieve stored images from database by supplying query images. In a typical CBIR, images are retrieved based on colour, shape, texture, etc. In this study, texture feature is used for retrieving skin images, and Gabor wavelet transform is used for texture feature description and extraction. The results show that the Gabor wavelet texture features can work efficiently on different types of skin images. Although Gabor wavelet transform is slower compared with other image retrieval techniques, such as principal component analysis (PCA) and grey-level co-occurrence matrix (GLCM), Gabor wavelet transform is the best for retrieving skin capacitive contact images and facial images with different orientations. Gabor wavelet transform can also work well on facial images with different expressions and skin cancer/disease images. We have developed an effective skin image retrieval method based on Gabor wavelet transform, that it is useful for retrieving different types of images, namely digital colour face images, digital colour skin cancer and skin disease images, and particularly greyscale skin capacitive contact images. Gabor wavelet transform can also be potentially useful for face recognition (with different orientation and expressions) and skin cancer/disease diagnosis. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City.

PubMed

Zhou, Lianjie; Chen, Nengcheng; Yuan, Sai; Chen, Zeqiang

2016-10-29

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems.

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2012-09-01

the Gerchberg-Saxton algorithm in the Fresnel diffraction regime, and is much more robust against image noise than the TIE-based method. For details...developed efficient coding with the software modules for the image registration, flat-filed correction , and phase retrievals. In addition, we...X, Liu H. 2010. Performance analysis of the attenuation-partition based iterative phase retrieval algorithm for in-line phase-contrast imaging

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Corrugated Waveguide Mode Content Analysis Using Irradiance Moments

PubMed Central

Jawla, Sudheer K.; Shapiro, Michael A.; Idei, Hiroshi; Temkin, Richard J.

2015-01-01

We present a novel, relatively simple method for determining the mode content of the linearly polarized modes of a corrugated waveguide using the moments of the intensity pattern of the field radiated from the end of the waveguide. This irradiance moment method is based on calculating the low-order irradiance moments, using measured intensity profiles only, of the radiated field from the waveguide aperture. Unlike the phase retrieval method, this method does not use or determine the phase distribution at the waveguide aperture. The new method was benchmarked numerically by comparison with sample mode mixtures. The results predict less than ±0.7% error bar in the retrieval of the mode content. The method was also tested using high-resolution experimental data from beams radiated from 63.5 mm and 19 mm corrugated waveguides at 170 and 250 GHz, respectively. The results showed a very good agreement of the mode content retrieved using the irradiance moment method versus the phase retrieval technique. The irradiance moment method is most suitable for cases where the modal power is primarily in the fundamental HE11 mode, with <8% of the power in high-order modes. PMID:25821260

Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

NASA Astrophysics Data System (ADS)

Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang

2017-12-01

In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.

Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land

PubMed Central

Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano

2010-01-01

Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. PMID:22163558

Evolutionary Computing Methods for Spectral Retrieval

NASA Technical Reports Server (NTRS)

Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

2009-01-01

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

PubMed

Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

2017-09-21

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Conjugate gradient method for phase retrieval based on the Wirtinger derivative.

PubMed

Wei, Zhun; Chen, Wen; Qiu, Cheng-Wei; Chen, Xudong

2017-05-01

A conjugate gradient Wirtinger flow (CG-WF) algorithm for phase retrieval is proposed in this paper. It is shown that, compared with recently reported Wirtinger flow and its modified methods, the proposed CG-WF algorithm is able to dramatically accelerate the convergence rate while keeping the dominant computational cost of each iteration unchanged. We numerically illustrate the effectiveness of our method in recovering 1D Gaussian signals and 2D natural color images under both Gaussian and coded diffraction pattern models.

Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation

NASA Technical Reports Server (NTRS)

Mandrake, Lukas

2013-01-01

Retrieval algorithms like that used by the Orbiting Carbon Observatory (OCO)-2 mission generate massive quantities of data of varying quality and reliability. A computationally efficient, simple method of labeling problematic datapoints or predicting soundings that will fail is required for basic operation, given that only 6% of the retrieved data may be operationally processed. This method automatically obtains a filter designed to reduce scatter based on a small number of input features. Most machine-learning filter construction algorithms attempt to predict error in the CO2 value. By using a surrogate goal of Mean Monthly STDEV, the goal is to reduce the retrieved CO2 scatter rather than solving the harder problem of reducing CO2 error. This lends itself to improved interpretability and performance. This software reduces the scatter of retrieved CO2 values globally based on a minimum number of input features. It can be used as a prefilter to reduce the number of soundings requested, or as a post-filter to label data quality. The use of the MMS (Mean Monthly Standard deviation) provides a much cleaner, clearer filter than the standard ABS(CO2-truth) metrics previously employed by competitor methods. The software's main strength lies in a clearer (i.e., fewer features required) filter that more efficiently reduces scatter in retrieved CO2 rather than focusing on the more complex (and easily removed) bias issues.

3D object retrieval using salient views

PubMed Central

Shapiro, Linda G.

2013-01-01

This paper presents a method for selecting salient 2D views to describe 3D objects for the purpose of retrieval. The views are obtained by first identifying salient points via a learning approach that uses shape characteristics of the 3D points (Atmosukarto and Shapiro in International workshop on structural, syntactic, and statistical pattern recognition, 2008; Atmosukarto and Shapiro in ACM multimedia information retrieval, 2008). The salient views are selected by choosing views with multiple salient points on the silhouette of the object. Silhouette-based similarity measures from Chen et al. (Comput Graph Forum 22(3):223–232, 2003) are then used to calculate the similarity between two 3D objects. Retrieval experiments were performed on three datasets: the Heads dataset, the SHREC2008 dataset, and the Princeton dataset. Experimental results show that the retrieval results using the salient views are comparable to the existing light field descriptor method (Chen et al. in Comput Graph Forum 22(3):223–232, 2003), and our method achieves a 15-fold speedup in the feature extraction computation time. PMID:23833704

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

NASA Astrophysics Data System (ADS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

A new method for the automatic retrieval of medical cases based on the RadLex ontology.

PubMed

Spanier, A B; Cohen, D; Joskowicz, L

2017-03-01

The goal of medical case-based image retrieval (M-CBIR) is to assist radiologists in the clinical decision-making process by finding medical cases in large archives that most resemble a given case. Cases are described by radiology reports comprised of radiological images and textual information on the anatomy and pathology findings. The textual information, when available in standardized terminology, e.g., the RadLex ontology, and used in conjunction with the radiological images, provides a substantial advantage for M-CBIR systems. We present a new method for incorporating textual radiological findings from medical case reports in M-CBIR. The input is a database of medical cases, a query case, and the number of desired relevant cases. The output is an ordered list of the most relevant cases in the database. The method is based on a new case formulation, the Augmented RadLex Graph and an Anatomy-Pathology List. It uses a new case relatedness metric [Formula: see text] that prioritizes more specific medical terms in the RadLex tree over less specific ones and that incorporates the length of the query case. An experimental study on 8 CT queries from the 2015 VISCERAL 3D Case Retrieval Challenge database consisting of 1497 volumetric CT scans shows that our method has accuracy rates of 82 and 70% on the first 10 and 30 most relevant cases, respectively, thereby outperforming six other methods. The increasing amount of medical imaging data acquired in clinical practice constitutes a vast database of untapped diagnostically relevant information. This paper presents a new hybrid approach to retrieving the most relevant medical cases based on textual and image information.

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

NASA Technical Reports Server (NTRS)

Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.;

Investigating Storage and Retrieval Processes of Directed Forgetting: A Model-Based Approach

ERIC Educational Resources Information Center

Rummel, Jan; Marevic, Ivan; Kuhlmann, Beatrice G.

2016-01-01

Intentional forgetting of previously learned information is an adaptive cognitive capability of humans but its cognitive underpinnings are not yet well understood. It has been argued that it strongly depends on the presentation method whether forgetting instructions alter storage or retrieval stages (Basden, Basden, & Gargano, 1993). In…

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Solar-Induced Plant Fluorescence as seen from space-borne instruments

NASA Astrophysics Data System (ADS)

Khosravi, Narges; Vountas, Marco; Rozanov, Vladimir V.; Bracher, Astrid; Burrows, John P.

2015-04-01

Solar induced chlorophyll fluorescence (SIF) retrieval can be linked to vegetation correspondence to global carbon cycle, and could be useful for terrestrial carbon budget assessment as well as agricultural and environmental purposes. There have been several investigations using space-borne SIF retrieval due to its good spatial coverage and time efficiency. These methods are mainly based on the fact that plant leaves absorb sunlight mainly within the visible spectral range and use it either for photosynthesis and/or release it as heat or fluorescence (in red and Near Infra Red, NIR, spectral region) back to the atmosphere. As a result, SIF can be considered an additive signal on top of the ground reflectance reaching TOA (Top Of the Atmosphere). Chlorophyll fluorescence is mainly emitted in the spectral range of red to the near-infrared with a pronounced peak at 690 and another at 740 nm. Although it is a very weak signal and two orders of magnitude smaller than the received radiance at TOA, it is feasible to retrieve it within spectral wavelength windows in the NIR. We developed a novel SIF retrieval method based on a modeled assumption of the emitted fluorescence spectrum at canopy level as it would be seen at TOA. The application of it to 10 years of SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY) data showed promising results. Comparing our SIF retrieval with results from other studies showed that SIF values of our retrieval are in a general agreement with them. With some variations. As there is no validated SIF retrieval, it is difficult to judge the retrieval quality. Our approach is of generic nature and therefore, could be applied to other data sets as well. Hence, the method is being applied on GOME-2 level 1 data, as the instrument has a better spatial resolution (in the wavelength range needed) and a better global coverage.

Recommending Education Materials for Diabetic Questions Using Information Retrieval Approaches

PubMed Central

Wang, Yanshan; Shen, Feichen; Liu, Sijia; Rastegar-Mojarad, Majid; Wang, Liwei

2017-01-01

Background Self-management is crucial to diabetes care and providing expert-vetted content for answering patients’ questions is crucial in facilitating patient self-management. Objective The aim is to investigate the use of information retrieval techniques in recommending patient education materials for diabetic questions of patients. Methods We compared two retrieval algorithms, one based on Latent Dirichlet Allocation topic modeling (topic modeling-based model) and one based on semantic group (semantic group-based model), with the baseline retrieval models, vector space model (VSM), in recommending diabetic patient education materials to diabetic questions posted on the TuDiabetes forum. The evaluation was based on a gold standard dataset consisting of 50 randomly selected diabetic questions where the relevancy of diabetic education materials to the questions was manually assigned by two experts. The performance was assessed using precision of top-ranked documents. Results We retrieved 7510 diabetic questions on the forum and 144 diabetic patient educational materials from the patient education database at Mayo Clinic. The mapping rate of words in each corpus mapped to the Unified Medical Language System (UMLS) was significantly different (P<.001). The topic modeling-based model outperformed the other retrieval algorithms. For example, for the top-retrieved document, the precision of the topic modeling-based, semantic group-based, and VSM models was 67.0%, 62.8%, and 54.3%, respectively. Conclusions This study demonstrated that topic modeling can mitigate the vocabulary difference and it achieved the best performance in recommending education materials for answering patients’ questions. One direction for future work is to assess the generalizability of our findings and to extend our study to other disease areas, other patient education material resources, and online forums. PMID:29038097

Invalid-point removal based on epipolar constraint in the structured-light method

NASA Astrophysics Data System (ADS)

Qi, Zhaoshuai; Wang, Zhao; Huang, Junhui; Xing, Chao; Gao, Jianmin

2018-06-01

In structured-light measurement, there unavoidably exist many invalid points caused by shadows, image noise and ambient light. According to the property of the epipolar constraint, because the retrieved phase of the invalid point is inaccurate, the corresponding projector image coordinate (PIC) will not satisfy the epipolar constraint. Based on this fact, a new invalid-point removal method based on the epipolar constraint is proposed in this paper. First, the fundamental matrix of the measurement system is calculated, which will be used for calculating the epipolar line. Then, according to the retrieved phase map of the captured fringes, the PICs of each pixel are retrieved. Subsequently, the epipolar line in the projector image plane of each pixel is obtained using the fundamental matrix. The distance between the corresponding PIC and the epipolar line of a pixel is defined as the invalidation criterion, which quantifies the satisfaction degree of the epipolar constraint. Finally, all pixels with a distance larger than a certain threshold are removed as invalid points. Experiments verified that the method is easy to implement and demonstrates better performance than state-of-the-art measurement systems.

Measuring Effective Leaf Area Index, Foliage Profile, and Stand Height in New England Forest Stands Using a Full-Waveform Ground-Based Lidar

NASA Technical Reports Server (NTRS)

Zhao, Feng; Yang, Xiaoyuan; Schull, Mithcell A.; Roman-Colon, Miguel O.; Yao, Tian; Wang, Zhuosen; Zhang, Qingling; Jupp, David L. B.; Lovell, Jenny L.; Culvenor, Darius;

Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach.

PubMed

Abd El Aziz, Mohamed; Selim, I M; Xiong, Shengwu

2017-06-30

This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2000-12-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2001-01-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain.

PubMed

Moen, Hans; Ginter, Filip; Marsi, Erwin; Peltonen, Laura-Maria; Salakoski, Tapio; Salanterä, Sanna

2015-01-01

Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a--possibly unfinished--care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task.

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain

PubMed Central

2015-01-01

Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a - possibly unfinished - care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task. PMID:26099735

A physically-based retrieval of cloud liquid water from SSM/I measurements

NASA Technical Reports Server (NTRS)

Greenwald, Thomas J.; Stephens, Graeme L.; Vonder Haar, Thomas H.

1992-01-01

A simple physical scheme is proposed for retrieving cloud liquid water over the ice-free global oceans from Special Sensor Microwave/Imager (SSM/I) observations. Details of the microwave retrieval scheme are discussed, and the microwave-derived liquid water amounts are compared with the ground radiometer and AVHRR-derived liquid water for stratocumulus clouds off the coast of California. Global distributions of the liquid water path derived by the method proposed here are presented.

Comparisons of Upper Tropospheric Humidity Retrievals from TOVS and METEOSAT

NASA Technical Reports Server (NTRS)

Escoffier, C.; Bates, J.; Chedin, A.; Rossow, W. B.; Schmetz, J.

1999-01-01

Two different methods for retrieving Upper Tropospheric Humidities (UTH) from the TOVS (TIROS Operational Vertical Sounder) instruments aboard NOAA polar orbiting satellites are presented and compared. The first one, from the Environmental Technology Laboratory, computed by J. Bates and D. Jackson (hereafter BJ method), estimates UTH from a simplified radiative transfer analysis of the upper tropospheric infrared water vapor channel at wavelength measured by HIRS (6.3 micrometer). The second one results from a neural network analysis of the TOVS (HIRS and MSU) data developed at, the Laboratoire de Meteorologie Dynamique (hereafter the 3I (Improved Initialization Inversion) method). Although the two methods give very similar retrievals in temperate regions (30-60 N and S), an absolute bias up to 16% appears in the convective zone of the tropics. The two datasets have also been compared with UTH retrievals from infrared radiance measurements in the 6.3 micrometer channel from the geostationary satellite METEOSAT (hereafter MET method). The METEOSAT retrievals are systematically drier than the TOVS-based results by an absolute bias between 5 and 25%. Despite the biases, the spatial and temporal correlations are very good. The purpose of this study is to explain the deviations observed between the three datasets. The sensitivity of UTH to air temperature and humidity profiles is analysed as are the clouds effects. Overall, the comparison of the three retrievals gives an assessment of the current uncertainties in water vapor amounts in the upper troposphere as determined from NOAA and METEOSAT satellites.

Rough case-based reasoning system for continues casting

NASA Astrophysics Data System (ADS)

Su, Wenbin; Lei, Zhufeng

2018-04-01

The continuous casting occupies a pivotal position in the iron and steel industry. The rough set theory and the CBR (case based reasoning, CBR) were combined in the research and implementation for the quality assurance of continuous casting billet to improve the efficiency and accuracy in determining the processing parameters. According to the continuous casting case, the object-oriented method was applied to express the continuous casting cases. The weights of the attributes were calculated by the algorithm which was based on the rough set theory and the retrieval mechanism for the continuous casting cases was designed. Some cases were adopted to test the retrieval mechanism, by analyzing the results, the law of the influence of the retrieval attributes on determining the processing parameters was revealed. A comprehensive evaluation model was established by using the attribute recognition theory. According to the features of the defects, different methods were adopted to describe the quality condition of the continuous casting billet. By using the system, the knowledge was not only inherited but also applied to adjust the processing parameters through the case based reasoning method as to assure the quality of the continuous casting and improve the intelligent level of the continuous casting.

Image Re-Ranking Based on Topic Diversity.

PubMed

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

An optimal-estimation-based aerosol retrieval algorithm using OMI near-UV observations

NASA Astrophysics Data System (ADS)

Jeong, U.; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

2016-01-01

An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional look-up tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OE-based estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

Exploring the Effects of Cloud Vertical Structure on Cloud Microphysical Retrievals based on Polarized Reflectances

NASA Astrophysics Data System (ADS)

Miller, D. J.; Zhang, Z.; Platnick, S. E.; Ackerman, A. S.; Cornet, C.; Baum, B. A.

2013-12-01

A polarized cloud reflectance simulator was developed by coupling an LES cloud model with a polarized radiative transfer model to assess the capabilities of polarimetric cloud retrievals. With future remote sensing campaigns like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important for the cloud remote sensing community to understand the retrievable information available and the related systematic/methodical limitations. The cloud retrieval simulator we have developed allows us to probe these important questions in a realistically relevant test bed. Our simulator utilizes a polarized adding-doubling radiative transfer model and an LES cloud field from a DHARMA simulation (Ackerman et al. 2004) with cloud properties based on the stratocumulus clouds observed during the DYCOMS-II field campaign. In this study we will focus on how the vertical structure of cloud microphysics can influence polarized cloud effective radius retrievals. Numerous previous studies have explored how retrievals based on total reflectance are affected by cloud vertical structure (Platnick 2000, Chang and Li 2002) but no such studies about the effects of vertical structure on polarized retrievals exist. Unlike the total cloud reflectance, which is predominantly multiply scattered light, the polarized reflectance is primarily the result of singly scattered photons. Thus the polarized reflectance is sensitive to only the uppermost region of the cloud (tau~<1) where photons can scatter once and still escape before being scattered again. This means that retrievals based on polarized reflectance have the potential to reveal behaviors specific to the cloud top. For example cloud top entrainment of dry air, a major influencer on the microphysical development of cloud droplets, can be potentially studied with polarimetric retrievals.

Enhanced dual-frequency pattern scheme based on spatial-temporal fringes method

NASA Astrophysics Data System (ADS)

Wang, Minmin; Zhou, Canlin; Si, Shuchun; Lei, Zhenkun; Li, Xiaolei; Li, Hui; Li, YanJie

2018-07-01

One of the major challenges of employing a dual-frequency phase-shifting algorithm for phase retrieval is its sensitivity to noise. Yun et al proposed a dual-frequency method based on the Fourier transform profilometry, yet the low-frequency lobes are close to each other for accurate band-pass filtering. In the light of this problem, a novel dual-frequency pattern based on the spatial-temporal fringes (STF) method is developed in this paper. Three fringe patterns with two different frequencies are required. The low-frequency phase is obtained from two low-frequency fringe patterns by the STF method, so the signal lobes can be extracted accurately as they are far away from each other. The high-frequency phase is retrieved from another fringe pattern without the impact of the DC component. Simulations and experiments are conducted to demonstrate the excellent precision of the proposed method.

Phase retrieval with the transport-of-intensity equation in an arbitrarily-shaped aperture by iterative discrete cosine transforms

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

Huang, Lei; Zuo, Chao; Idir, Mourad

A novel transport-of-intensity equation (TIE) based phase retrieval method is proposed with putting an arbitrarily-shaped aperture into the optical wavefield. In this arbitrarily-shaped aperture, the TIE can be solved under non-uniform illuminations and even non-homogeneous boundary conditions by iterative discrete cosine transforms with a phase compensation mechanism. Simulation with arbitrary phase, arbitrary aperture shape, and non-uniform intensity distribution verifies the effective compensation and high accuracy of the proposed method. Experiment is also carried out to check the feasibility of the proposed method in real measurement. Comparing to the existing methods, the proposed method is applicable for any types of phasemore » distribution under non-uniform illumination and non-homogeneous boundary conditions within an arbitrarily-shaped aperture, which enables the technique of TIE with hard aperture become a more flexible phase retrieval tool in practical measurements.« less

Phase retrieval with the transport-of-intensity equation in an arbitrarily-shaped aperture by iterative discrete cosine transforms

DOE PAGES

Huang, Lei; Zuo, Chao; Idir, Mourad; ...

2015-04-21

A novel transport-of-intensity equation (TIE) based phase retrieval method is proposed with putting an arbitrarily-shaped aperture into the optical wavefield. In this arbitrarily-shaped aperture, the TIE can be solved under non-uniform illuminations and even non-homogeneous boundary conditions by iterative discrete cosine transforms with a phase compensation mechanism. Simulation with arbitrary phase, arbitrary aperture shape, and non-uniform intensity distribution verifies the effective compensation and high accuracy of the proposed method. Experiment is also carried out to check the feasibility of the proposed method in real measurement. Comparing to the existing methods, the proposed method is applicable for any types of phasemore » distribution under non-uniform illumination and non-homogeneous boundary conditions within an arbitrarily-shaped aperture, which enables the technique of TIE with hard aperture become a more flexible phase retrieval tool in practical measurements.« less

Research of image retrieval technology based on color feature

NASA Astrophysics Data System (ADS)

Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

2009-10-01

Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram make rotating and translation does not change. The HSV color space is used to show color characteristic of image, which is suitable to the visual characteristic of human. Taking advance of human's feeling to color, it quantifies color sector with unequal interval, and get characteristic vector. Finally, it matches the similarity of image with the algorithm of the histogram intersection and the partition-overall histogram. Users can choose a demonstration image to show inquired vision require, and also can adjust several right value through the relevance-feedback method to obtain the best result of search.An image retrieval system based on these approaches is presented. The result of the experiments shows that the image retrieval based on partition-overall histogram can keep the space distribution information while abstracting color feature efficiently, and it is superior to the normal color histograms in precision rate while researching. The query precision rate is more than 95%. In addition, the efficient block expression will lower the complicate degree of the images to be searched, and thus the searching efficiency will be increased. The image retrieval algorithms based on the partition-overall histogram proposed in the paper is efficient and effective.

Time series inversion of spectra from ground-based radiometers

NASA Astrophysics Data System (ADS)

Christensen, O. M.; Eriksson, P.

2013-02-01

Retrieving time series of atmospheric constituents from ground-based spectrometers often requires different temporal averaging depending on the altitude region in focus. This can lead to several datasets existing for one instrument which complicates validation and comparisons between instruments. This paper puts forth a possible solution by incorporating the temporal domain into the maximum a posteriori (MAP) retrieval algorithm. The state vector is increased to include measurements spanning a time period, and the temporal correlations between the true atmospheric states are explicitly specified in the a priori uncertainty matrix. This allows the MAP method to effectively select the best temporal smoothing for each altitude, removing the need for several datasets to cover different altitudes. The method is compared to traditional averaging of spectra using a simulated retrieval of water vapour in the mesosphere. The simulations show that the method offers a significant advantage compared to the traditional method, extending the sensitivity an additional 10 km upwards without reducing the temporal resolution at lower altitudes. The method is also tested on the OSO water vapour microwave radiometer confirming the advantages found in the simulation. Additionally, it is shown how the method can interpolate data in time and provide diagnostic values to evaluate the interpolated data.

Applications of Some Artificial Intelligence Methods to Satellite Soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.

1985-01-01

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Accuracy of retrieving temperature and humidity profiles by ground-based microwave radiometry in truly complex terrain

NASA Astrophysics Data System (ADS)

Massaro, G.; Stiperski, I.; Pospichal, B.; Rotach, M. W.

2015-03-01

Within the Innsbruck Box project, a ground-based microwave radiometer (RPG-HATPRO) was operated in the Inn Valley (Austria), in very complex terrain, between September 2012 and May 2013 to obtain temperature and humidity vertical profiles of the full troposphere with a specific focus on the valley boundary layer. The profiles obtained by the radiometer with different retrieval algorithms based on different climatologies, are compared to local radiosonde data. A retrieval that is improved with respect to the one provided by the manufacturer, based on better resolved data, shows a significantly smaller root mean square error (RMSE), both for the temperature and humidity profiles. The improvement is particularly substantial at the heights close to the mountaintop level and in the upper troposphere. Lower level inversions, common in an alpine valley, are resolved to a satisfactory degree. On the other hand, upper level inversions (above 1200 m) still pose a significant challenge for retrieval. For this purpose, specialized retrieval algorithms were developed by classifying the radiosonde climatologies into specialized categories according to different criteria (seasons, daytime, nighttime) and using additional regressors (e.g., measurements from mountain stations). The training and testing on the radiosonde data for these specialized categories suggests that a classification of profiles that reproduces meaningful physical characteristics can yield improved targeted specialized retrievals. A really new and very promising method of improving the profile retrieval in a mountain region is adding further information in the retrieval, such as the surface temperature at fixed levels along a topographic slope or from nearby mountain tops.

Phase retrieval in digital speckle pattern interferometry by application of two-dimensional active contours called snakes.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2006-03-20

We propose a novel approach to retrieving the phase map coded by a single closed-fringe pattern in digital speckle pattern interferometry, which is based on the estimation of the local sign of the quadrature component. We obtain the estimate by calculating the local orientation of the fringes that have previously been denoised by a weighted smoothing spline method. We carry out the procedure of sign estimation by determining the local abrupt jumps of size pi in the orientation field of the fringes and by segmenting the regions defined by these jumps. The segmentation method is based on the application of two-dimensional active contours (snakes), with which one can also estimate absent jumps, i.e., those that cannot be detected from the local orientation of the fringes. The performance of the proposed phase-retrieval technique is evaluated for synthetic and experimental fringes and compared with the results obtained with the spiral-phase- and Fourier-transform methods.

(BARS) -- Bibliographic Retrieval System Sandia Shock Compression (SSC) database Shock Physics Index (SPHINX) database. Volume 1: UNIX version query guide customized application for INGRES

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

Herrmann, W.; von Laven, G.M.; Parker, T.

1993-09-01

The Bibliographic Retrieval System (BARS) is a data base management system specially designed to retrieve bibliographic references. Two databases are available, (i) the Sandia Shock Compression (SSC) database which contains over 5700 references to the literature related to stress waves in solids and their applications, and (ii) the Shock Physics Index (SPHINX) which includes over 8000 further references to stress waves in solids, material properties at intermediate and low rates, ballistic and hypervelocity impact, and explosive or shock fabrication methods. There is some overlap in the information in the two data bases.

Advances in Volcanic Ash Cloud Photogrammetry from Space

NASA Astrophysics Data System (ADS)

Zaksek, K.; von der Lieth, J.; Merucci, L.; Hort, M. K.; Gerst, A.; Carboni, E.; Corradini, S.

2015-12-01

The quality of ash dispersion prediction is limited by the lack of high quality information on eruption source parameters. One of the most important one is the ash cloud top height (ACTH). Because of well-known uncertainties of currently operational methods, photogrammetric methods can be used to improve height estimates. Some satellites have on board multiangular instruments that can be used for photogrammetrical observations. Volcanic ash clouds, however, can move with velocities over several m/s making these instruments inappropriate for accurate ACTH estimation. Thus we propose here two novel methods tested on different case studies (Etna 2013/11/23, Zhupanovsky 2014/09/10). The first method is based on NASA program Crew Earth observations from International Space Station (ISS). ISS has a lower orbit than most operational satellites, resulting in a shorter minimal time between two images required to produce a suitable parallax. In addition, images made by the ISS crew are taken by a full frame sensor and not a line scanner that most operational satellites use. Such data make possible to observe also short time evolution of clouds. The second method is based on the parallax between data retrieved from two geostationary instruments. We implemented a combination of MSG SEVIRI (HRV band; 1000 m nadir spatial resolution, 5 min temporal resolution) and METEOSAT7 MVIRI (VIS band, 2500 m nadir spatial resolution, 30 min temporal resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously. However, MVIRI does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MVIRI retrieval) and interpolate the cloud position from SEVIRI data to the time of MVIRI retrieval.

Retrieving the Polar Mixed-Phase Cloud Liquid Water Path by Combining CALIOP and IIR Measurements

NASA Astrophysics Data System (ADS)

Luo, Tao; Wang, Zhien; Li, Xuebin; Deng, Shumei; Huang, Yong; Wang, Yingjian

2018-02-01

Mixed-phase cloud (MC) is the dominant cloud type over the polar region, and there are challenging conditions for remote sensing and in situ measurements. In this study, a new methodology of retrieving the stratiform MC liquid water path (LWP) by combining Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and infrared imaging radiometer (IIR) measurements was developed and evaluated. This new methodology takes the advantage of reliable cloud-phase discrimination by combining lidar and radar measurements. An improved multiple-scattering effect correction method for lidar signals was implemented to provide reliable cloud extinction near cloud top. Then with the adiabatic cloud assumption, the MC LWP can be retrieved by a lookup-table-based method. Simulations with error-free inputs showed that the mean bias and the root mean squared error of the LWP derived from the new method are -0.23 ± 2.63 g/m2, with the mean absolute relative error of 4%. Simulations with erroneous inputs suggested that the new methodology could provide reliable retrieval of LWP to support the statistical or climatology analysis. Two-month A-train satellite retrievals over Arctic region showed that the new method can produce very similar cloud top temperature (CTT) dependence of LWP to the ground-based microwave radiometer measurements, with a bias of -0.78 g/m2 and a correlation coefficient of 0.95 between the two mean CTT-LWP relationships. The new approach can also produce reasonable pattern and value of LWP in spatial distribution over the Arctic region.

Scalable ranked retrieval using document images

NASA Astrophysics Data System (ADS)

Jain, Rajiv; Oard, Douglas W.; Doermann, David

2013-12-01

Despite the explosion of text on the Internet, hard copy documents that have been scanned as images still play a significant role for some tasks. The best method to perform ranked retrieval on a large corpus of document images, however, remains an open research question. The most common approach has been to perform text retrieval using terms generated by optical character recognition. This paper, by contrast, examines whether a scalable segmentation-free image retrieval algorithm, which matches sub-images containing text or graphical objects, can provide additional benefit in satisfying a user's information needs on a large, real world dataset. Results on 7 million scanned pages from the CDIP v1.0 test collection show that content based image retrieval finds a substantial number of documents that text retrieval misses, and that when used as a basis for relevance feedback can yield improvements in retrieval effectiveness.

Simple method based on intensity measurements for characterization of aberrations from micro-optical components.

PubMed

Perrin, Stephane; Baranski, Maciej; Froehly, Luc; Albero, Jorge; Passilly, Nicolas; Gorecki, Christophe

2015-11-01

We report a simple method, based on intensity measurements, for the characterization of the wavefront and aberrations produced by micro-optical focusing elements. This method employs the setup presented earlier in [Opt. Express 22, 13202 (2014)] for measurements of the 3D point spread function, on which a basic phase-retrieval algorithm is applied. This combination allows for retrieval of the wavefront generated by the micro-optical element and, in addition, quantification of the optical aberrations through the wavefront decomposition with Zernike polynomials. The optical setup requires only an in-motion imaging system. The technique, adapted for the optimization of micro-optical component fabrication, is demonstrated by characterizing a planoconvex microlens.

How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yongxiang

2014-01-01

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

Retrieval of reflections from ambient noise using illumination diagnosis

NASA Astrophysics Data System (ADS)

Vidal, C. Almagro; Draganov, D.; van der Neut, J.; Drijkoningen, G.; Wapenaar, K.

2014-09-01

Seismic interferometry (SI) enables the retrieval of virtual sources at the location of receivers. In the case of passive SI, no active sources are used for the retrieval of the reflection response of the subsurface, but ambient-noise recordings only. The resulting retrieved response is determined by the illumination characteristics of the recorded ambient noise. Characteristics like geometrical distribution and signature of the noise sources, together with the complexity of the medium and the length of the noise records, determine the quality of the retrieved virtual-shot events. To retrieve body wave reflections, one needs to correlate body-wave noise. A source of such noise might be regional seismicity. In regions with notable human presence, the dominant noise sources are generally located at or close to the surface. In the latter case, the noise will be dominated by surface waves and consequently also the retrieved virtual common-source panels will contain dominant retrieved surface waves, drowning out possible retrieved reflections. In order to retrieve reflection events, suppression of the surface waves becomes the most important pre-processing goal. Because of the reasons mentioned above, we propose a fast method to evaluate the illumination characteristics of ambient noise using the correlation results from ambient-noise records. The method is based on the analysis of the so-called source function of the retrieved virtual-shot panel, and evaluates the apparent slowness of arrivals in the correlation results that pass through the position of the virtual source and at zero time. The results of the diagnosis are used to suppress the retrieval of surface waves and therefore to improve the quality of the retrieved reflection response. We explain the approach using modelled data from transient and continuous noise sources and an example from a passive field data set recorded at Annerveen, Northern Netherlands.

Cross-Modal Retrieval With CNN Visual Features: A New Baseline.

PubMed

Wei, Yunchao; Zhao, Yao; Lu, Canyi; Wei, Shikui; Liu, Luoqi; Zhu, Zhenfeng; Yan, Shuicheng

2017-02-01

Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than one million images from 1000 object categories, as a generic image representation to tackle cross-modal retrieval. To further enhance the representational ability of CNN visual features, based on the pretrained CNN model on ImageNet, a fine-tuning step is performed by using the open source Caffe CNN library for each target data set. Besides, we propose a deep semantic matching method to address the cross-modal retrieval problem with respect to samples which are annotated with one or multiple labels. Extensive experiments on five popular publicly available data sets well demonstrate the superiority of CNN visual features for cross-modal retrieval.

Fusion of Deep Learning and Compressed Domain features for Content Based Image Retrieval.

PubMed

Liu, Peizhong; Guo, Jing-Ming; Wu, Chi-Yi; Cai, Danlin

2017-08-29

This paper presents an effective image retrieval method by combining high-level features from Convolutional Neural Network (CNN) model and low-level features from Dot-Diffused Block Truncation Coding (DDBTC). The low-level features, e.g., texture and color, are constructed by VQ-indexed histogram from DDBTC bitmap, maximum, and minimum quantizers. Conversely, high-level features from CNN can effectively capture human perception. With the fusion of the DDBTC and CNN features, the extended deep learning two-layer codebook features (DL-TLCF) is generated using the proposed two-layer codebook, dimension reduction, and similarity reweighting to improve the overall retrieval rate. Two metrics, average precision rate (APR) and average recall rate (ARR), are employed to examine various datasets. As documented in the experimental results, the proposed schemes can achieve superior performance compared to the state-of-the-art methods with either low- or high-level features in terms of the retrieval rate. Thus, it can be a strong candidate for various image retrieval related applications.

A Materials Index--Its Storage, Retrieval, and Display

ERIC Educational Resources Information Center

Rosen, Carol Z.

1973-01-01

An experimental procedure for indexing physical materials based on simple syntactical rules was tested by encoding the materials in the journal, Applied Physics Letters,'' to produce a materials index. The syntax and numerous examples together with an indication of the method by which retrieval can be effected are presented. (5 references)…

Innovative approach to retrieve land surface emissivity and land surface temperature in areas of highly dynamic emissivity changes by using thermal infrared data

NASA Astrophysics Data System (ADS)

Heinemann, S.

2015-12-01

The land surface temperature (LST) is an extremely significant parameter in order to understand the processes of energetic interactions between Earth's surface and atmosphere. This knowledge is significant for various environmental research questions, particularly with regard to the recent climate change. This study shows an innovative approach to retrieve land surface emissivity (LSE) and LST by using thermal infrared (TIR) data from satellite sensors, such as SEVIRI and AATSR. So far there are no methods to derive LSE/LST particularly in areas of highly dynamic emissivity changes. Therefore especially for regions with large surface temperature amplitude in the diurnal cycle such as bare and uneven soil surfaces but also for regions with seasonal changes in vegetation cover including various surface areas such as grassland, mixed forests or agricultural land different methods were investigated to identify the most appropriate one. The LSE is retrieved by using the day/night Temperature-Independent Spectral Indices (TISI) method, and the Generalised Split-Window (GSW) method is used to retrieve the LST. Nevertheless different GSW algorithms show that equal LSEs lead to large LST differences. Additionally LSE is also measured using a NDVI-based threshold method (NDVITHM) to distinguish between soil, dense vegetation cover and pixel composed of soil and vegetation. The data used for this analysis were derived from MODIS TIR. The analysis is implemented with IDL and an intercomparison is performed to determine the most effective methods. To compensate temperature differences between derived and ground truth data appropriate correction terms by comparing derived LSE/LST data with ground-based measurements are developed. One way to calibrate LST retrievals is by comparing the canopy leaf temperature of conifers derived from TIR data with the surrounding air temperature (e.g. from synoptic stations). Prospectively, the derived LSE/LST data become validated with near infrared data obtained from an UVA with a TIR camera (TIRC) onboard, and also compared with ground-based measurements. This study aims to generate an appropriate method by integrating developed correction terms to eventually obtain a high correlation between all, LSE/LST, TIRC and ground truth data.

Improving real-time efficiency of case-based reasoning for medical diagnosis.

PubMed

Park, Yoon-Joo

2014-01-01

Conventional case-based reasoning (CBR) does not perform efficiently for high volume dataset because of case-retrieval time. Some previous researches overcome this problem by clustering a case-base into several small groups, and retrieve neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performances than the conventional CBR. This paper suggests a new case-based reasoning method called the Clustering-Merging CBR (CM-CBR) which produces similar level of predictive performances than the conventional CBR with spending significantly less computational cost.

[Atmospheric correction of HJ-1 CCD data for water imagery based on dark object model].

PubMed

Zhou, Li-Guo; Ma, Wei-Chun; Gu, Wan-Hua; Huai, Hong-Yan

2011-08-01

The CCD multi-band data of HJ-1A has great potential in inland water quality monitoring, but the precision of atmospheric correction is a premise and necessary procedure for its application. In this paper, a method based on dark pixel for water-leaving radiance retrieving is proposed. Beside the Rayleigh scattering, the aerosol scattering is important to atmospheric correction, the water quality of inland lakes always are case II water and the value of water leaving radiance is not zero. So the synchronous MODIS shortwave infrared data was used to obtain the aerosol parameters, and in virtue of the characteristic that aerosol scattering is relative stabilized in 560 nm, the water-leaving radiance for each visible and near infrared band were retrieved and normalized, accordingly the remotely sensed reflectance of water was computed. The results show that the atmospheric correction method based on the imagery itself is more effective for the retrieval of water parameters for HJ-1A CCD data.

2D and 3D X-ray phase retrieval of multi-material objects using a single defocus distance.

PubMed

Beltran, M A; Paganin, D M; Uesugi, K; Kitchen, M J

2010-03-29

A method of tomographic phase retrieval is developed for multi-material objects whose components each has a distinct complex refractive index. The phase-retrieval algorithm, based on the Transport-of-Intensity equation, utilizes propagation-based X-ray phase contrast images acquired at a single defocus distance for each tomographic projection. The method requires a priori knowledge of the complex refractive index for each material present in the sample, together with the total projected thickness of the object at each orientation. The requirement of only a single defocus distance per projection simplifies the experimental setup and imposes no additional dose compared to conventional tomography. The algorithm was implemented using phase contrast data acquired at the SPring-8 Synchrotron facility in Japan. The three-dimensional (3D) complex refractive index distribution of a multi-material test object was quantitatively reconstructed using a single X-ray phase-contrast image per projection. The technique is robust in the presence of noise, compared to conventional absorption based tomography.

SU-C-207A-05: Feature Based Water Equivalent Path Length (WEPL) Determination for Proton Radiography by the Technique of Time Resolved Dose Measurement

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

Zhang, R; Jee, K; Sharp, G

Purpose: Studies show that WEPL can be determined from modulated dose rate functions (DRF). However, the previous calibration method based on statistics of the DRF is sensitive to energy mixing of protons due to scattering through different materials (termed as range mixing here), causing inaccuracies in the determination of WEPL. This study intends to explore time-domain features of the DRF to reduce the effect of range mixing in proton radiography (pRG) by this technique. Methods: An amorphous silicon flat panel (PaxScan™ 4030CB, Varian Medical Systems, Inc., Palo Alto, CA) was placed behind phantoms to measure DRFs from a proton beammore » modulated by a specially designed modulator wheel. The performance of two methods, the previously used method based on the root mean square (RMS) and the new approach based on time-domain features of the DRF, are compared for retrieving WEPL and RSP from pRG of a Gammex phantom. Results: Calibration by T{sub 80} (the time point for 80% of the major peak) was more robust to range mixing and produced WEPL with improved accuracy. The error of RSP was reduced from 8.2% to 1.7% for lung equivalent material, with the mean error for all other materials reduced from 1.2% to 0.7%. The mean error of the full width at half maximum (FWHM) of retrieved inserts was decreased from 25.85% to 5.89% for the RMS and T{sub 80} method respectively. Monte Carlo simulations in simplified cases also demonstrated that the T{sub 80} method is less sensitive to range mixing than the RMS method. Conclusion: WEPL images have been retrieved based on single flat panel measured DRFs, with inaccuracies reduced by exploiting time-domain features as the calibration parameter. The T{sub 80} method is validated to be less sensitive to range mixing and can thus retrieve the WEPL values in proximity of interfaces with improved numerical and spatial accuracy for proton radiography.« less

Data-driven Green's function retrieval and application to imaging with multidimensional deconvolution

NASA Astrophysics Data System (ADS)

Broggini, Filippo; Wapenaar, Kees; van der Neut, Joost; Snieder, Roel

2014-01-01

An iterative method is presented that allows one to retrieve the Green's function originating from a virtual source located inside a medium using reflection data measured only at the acquisition surface. In addition to the reflection response, an estimate of the travel times corresponding to the direct arrivals is required. However, no detailed information about the heterogeneities in the medium is needed. The iterative scheme generalizes the Marchenko equation for inverse scattering to the seismic reflection problem. To give insight in the mechanism of the iterative method, its steps for a simple layered medium are analyzed using physical arguments based on the stationary phase method. The retrieved Green's wavefield is shown to correctly contain the multiples due to the inhomogeneities present in the medium. Additionally, a variant of the iterative scheme enables decomposition of the retrieved wavefield into its downgoing and upgoing components. These wavefields then enable creation of a ghost-free image of the medium with either cross correlation or multidimensional deconvolution, presenting an advantage over standard prestack migration.

Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization

PubMed Central

Luo, Jake; Chen, Weiheng; Wu, Min; Weng, Chunhua

2018-01-01

Background Prior studies of clinical trial planning indicate that it is crucial to search and screen recruitment sites before starting to enroll participants. However, currently there is no systematic method developed to support clinical investigators to search candidate recruitment sites according to their interested clinical trial factors. Objective In this study, we aim at developing a new approach to integrating the location data of over one million heterogeneous recruitment sites that are stored in clinical trial documents. The integrated recruitment location data can be searched and visualized using a map-based information retrieval method. The method enables systematic search and analysis of recruitment sites across a large amount of clinical trials. Methods The location data of more than 1.4 million recruitment sites of over 183,000 clinical trials was normalized and integrated using a geocoding method. The integrated data can be used to support geographic information retrieval of recruitment sites. Additionally, the information of over 6000 clinical trial target disease conditions and close to 4000 interventions was also integrated into the system and linked to the recruitment locations. Such data integration enabled the construction of a novel map-based query system. The system will allow clinical investigators to search and visualize candidate recruitment sites for clinical trials based on target conditions and interventions. Results The evaluation results showed that the coverage of the geographic location mapping for the 1.4 million recruitment sites was 99.8%. The evaluation of 200 randomly retrieved recruitment sites showed that the correctness of geographic information mapping was 96.5%. The recruitment intensities of the top 30 countries were also retrieved and analyzed. The data analysis results indicated that the recruitment intensity varied significantly across different countries and geographic areas. Conclusion This study contributed a new data processing framework to extract and integrate the location data of heterogeneous recruitment sites from clinical trial documents. The developed system can support effective retrieval and analysis of potential recruitment sites using target clinical trial factors. PMID:29132636

GOSAT CO2 retrieval results using TANSO-CAI aerosol information over East Asia

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, W.; Jung, Y.; Lee, S.; Kim, J.; Lee, H.; Boesch, H.; Goo, T. Y.

2015-12-01

In the satellite remote sensing of CO2, incorrect aerosol information could induce large errors as previous studies suggested. Many factors, such as, aerosol type, wavelength dependency of AOD, aerosol polarization effect and etc. have been main error sources. Due to these aerosol effects, large number of data retrieved are screened out in quality control, or retrieval errors tend to increase if not screened out, especially in East Asia where aerosol concentrations are fairly high. To reduce these aerosol induced errors, a CO2 retrieval algorithm using the simultaneous TANSO-CAI aerosol information is developed. This algorithm adopts AOD and aerosol type information as a priori information from the CAI aerosol retrieval algorithm. The CO2 retrieval algorithm based on optimal estimation method and VLIDORT, a vector discrete ordinate radiative transfer model. The CO2 algorithm, developed with various state vectors to find accurate CO2 concentration, shows reasonable results when compared with other dataset. This study concentrates on the validation of retrieved results with the ground-based TCCON measurements in East Asia and the comparison with the previous retrieval from ACOS, NIES, and UoL. Although, the retrieved CO2 concentration is lower than previous results by ppm's, it shows similar trend and high correlation with previous results. Retrieved data and TCCON measurements data are compared at three stations of Tsukuba, Saga, Anmyeondo in East Asia, with the collocation criteria of ±2°in latitude/longitude and ±1 hours of GOSAT passing time. Compared results also show similar trend with good correlation. Based on the TCCON comparison results, bias correction equation is calculated and applied to the East Asia data.

Estimating vertical profiles of water-cloud droplet effective radius from SWIR satellite measurements via a statistical model derived from CloudSat observations

NASA Astrophysics Data System (ADS)

Nagao, T. M.; Murakami, H.; Nakajima, T. Y.

2017-12-01

This study proposes an algorithm to estimate vertical profiles of cloud droplet effective radius (CDER-VP) for water clouds from shortwave infrared (SWIR) measurements of Himawari-8/AHI via a statistical model of CDER-VP derived from CloudSat observation. Several similar algorithms in previous studies utilize a spectral radiance matching on the assumption of simultaneous observations of CloudSat and Aqua/MODIS. However, our algorithm does not assume simultaneous observations with CloudSat. First, in advance, a database (DB) of CDER-VP is prepared by the following procedure: TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI are simulated using CDER-VP and cloud optical depth vertical profile (COD-VP) contained in the CloudSat 2B-CWC-RVOD and 2B-TAU products. Cloud optical thickness (COT), Column-CDER and cloud top height (CTH) are retrieved from the simulated radiances using a traditional retrieval algorithm with vertically homogeneous cloud model (1-SWIR VHC method). The CDER-VP is added to the DB by using the COT and Column-CDER retrievals as a key of the DB. Then by using principal component (PC) analysis, up to three PC vectors of the CDER-VPs in the DB are extracted. Next, the algorithm retrieves CDER-VP from actual AHI measurements by the following procedure: First, COT, Column-CDER and CTH are retrieved from TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI using by 1-SWIR VHC method. Then, the PC vectors of CDER-VP is fetched from the DB using the COT and Column-CDER retrievals as the key of the DB. Finally, using coefficients of the PC vectors of CDER-VP as variables for retrieval, CDER-VP, COT and CTH are retrieved from TOA radiances at 0.65, 1.6, 2.3, 3.9 and 10.4-μm bands of the AHI based on optimal estimation method with iterative radiative transfer calculation. The simulation result showed the CDER-VP retrieval errors were almost smaller than 3 - 4 μm. The CDER retrieval errors at the cloud base were almost larger than the others (e.g. CDER at cloud top), especially when COT and CDER was large. The tendency can be explained by less sensitivities of SWIRs to CDER at cloud base. Additionally, as a case study, this study will attempt to apply the algorithm to the AHI's high-frequency observations, and to interpret the time series of the CDER-VP retrievals in terms of temporal evolution of water clouds.

The Influence of Aerosol Hygroscopicity on Retrieving the Aerosol Extincting Coefficient from MPL Data

NASA Astrophysics Data System (ADS)

Zhao, G.; Zhao, C.

2016-12-01

Micro-pulse Lidar (MPL) measurements have been widely used to profile the ambient aerosol extincting coefficient(). Lidar Ratio (LR) ,which highly depends on the particle number size distribution (PNSD) and aerosol hygroscopicity, is the most important factor to retrieve the profile. A constant AOD constrained LR is usually used in current algorithms, which would lead to large bias when the relative humidity (RH) in the mixed layer is high. In this research, the influences of PNSD, aerosol hygroscopicity and RH profiles on the vertical variation of LR were investigated based on the datasets from field measurements in the North China Plain (NCP). Results show that LR can have an enhancement factor of more than 120% when the RH reaches to 92%. A new algorithm of retrieving the profile is proposed based on the variation of LR due to aerosol hygroscopicity. The magnitude and vertical structures of retrieved using this method can be significantly different to that of the fiexed LR method. The relative difference can reach up to 40% when the RH in the mixed layer is higher than 90% . Sensitivity studies show that RH profile and PNSD affect most on the retrieved by fiexed LR method. In view of this, a scheme of LR enhancement factor by RH is proposed in the NCP. The relative differnce of the calculated between using this scheme and the new algorithm with the variable LR can be less than 10%.

Cloud Photogrammetry from Space

NASA Astrophysics Data System (ADS)

Zaksek, K.; Gerst, A.; von der Lieth, J.; Ganci, G.; Hort, M.

2015-04-01

The most commonly used method for satellite cloud top height (CTH) compares brightness temperature of the cloud with the atmospheric temperature profile. Because of the uncertainties of this method, we propose a photogrammetric approach. As clouds can move with high velocities, even instruments with multiple cameras are not appropriate for accurate CTH estimation. Here we present two solutions. The first is based on the parallax between data retrieved from geostationary (SEVIRI, HRV band; 1000 m spatial resolution) and polar orbiting satellites (MODIS, band 1; 250 m spatial resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously. However, MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. CTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The second method is based on NASA program Crew Earth observations from the International Space Station (ISS). The ISS has a lower orbit than most operational satellites, resulting in a shorter minimal time between two images, which is needed to produce a suitable parallax. In addition, images made by the ISS crew are taken by a full frame sensor and not a push broom scanner that most operational satellites use. Such data make it possible to observe also short time evolution of clouds.

A novel UCS memory retrieval-extinction procedure to inhibit relapse to drug seeking.

PubMed

Luo, Yi-xiao; Xue, Yan-xue; Liu, Jian-feng; Shi, Hai-shui; Jian, Min; Han, Ying; Zhu, Wei-li; Bao, Yan-ping; Wu, Ping; Ding, Zeng-bo; Shen, Hao-wei; Shi, Jie; Shaham, Yavin; Lu, Lin

2015-07-14

We recently reported that a conditioned stimulus (CS) memory retrieval-extinction procedure decreases reinstatement of cocaine and heroin seeking in rats and heroin craving in humans. Here we show that non-contingent cocaine or methylphenidate injections (UCS retrieval) 1 h before the extinction sessions decreases cocaine-priming-induced reinstatement, spontaneous recovery, and renewal of cocaine seeking in rats. Unlike the CS-based memory retrieval-extinction procedure, the UCS memory retrieval manipulation decreases renewal and reinstatement of cocaine seeking in the presence of cocaine cues that were not present during extinction training and also decreases cocaine seeking when the procedure commences after 28 days of abstinence. The inhibitory effect of the UCS retrieval manipulation on cocaine-priming-induced reinstatement is mediated by regulation of AMPA-receptor endocytosis in the basolateral amygdala. The UCS memory retrieval-extinction procedure has superior relapse prevention characteristics than the CS memory retrieval-extinction procedure and could be a promising method for decreasing relapse in human addicts.

A novel UCS memory retrieval-extinction procedure to inhibit relapse to drug seeking

PubMed Central

Luo, Yi-xiao; Xue, Yan-xue; Liu, Jian-feng; Shi, Hai-shui; Jian, Min; Han, Ying; Zhu, Wei-li; Bao, Yan-ping; Wu, Ping; Ding, Zeng-bo; Shen, Hao-wei; Shi, Jie; Shaham, Yavin; Lu, Lin

2015-01-01

We recently reported that a conditioned stimulus (CS) memory retrieval-extinction procedure decreases reinstatement of cocaine and heroin seeking in rats and heroin craving in humans. Here we show that non-contingent cocaine or methylphenidate injections (UCS retrieval) 1 h before the extinction sessions decreases cocaine-priming-induced reinstatement, spontaneous recovery, and renewal of cocaine seeking in rats. Unlike the CS-based memory retrieval-extinction procedure, the UCS memory retrieval manipulation decreases renewal and reinstatement of cocaine seeking in the presence of cocaine cues that were not present during extinction training and also decreases cocaine seeking when the procedure commences after 28 days of abstinence. The inhibitory effect of the UCS retrieval manipulation on cocaine-priming-induced reinstatement is mediated by regulation of AMPA-receptor endocytosis in the basolateral amygdala. The UCS memory retrieval-extinction procedure has superior relapse prevention characteristics than the CS memory retrieval-extinction procedure and could be a promising method for decreasing relapse in human addicts. PMID:26169171

Experiments with Cross-Language Information Retrieval on a Health Portal for Psychology and Psychotherapy.

PubMed

Andrenucci, Andrea

2016-01-01

Few studies have been performed within cross-language information retrieval (CLIR) in the field of psychology and psychotherapy. The aim of this paper is to to analyze and assess the quality of available query translation methods for CLIR on a health portal for psychology. A test base of 100 user queries, 50 Multi Word Units (WUs) and 50 Single WUs, was used. Swedish was the source language and English the target language. Query translation methods based on machine translation (MT) and dictionary look-up were utilized in order to submit query translations to two search engines: Google Site Search and Quick Ask. Standard IR evaluation measures and a qualitative analysis were utilized to assess the results. The lexicon extracted with word alignment of the portal's parallel corpus provided better statistical results among dictionary look-ups. Google Translate provided more linguistically correct translations overall and also delivered better retrieval results in MT.

Quantification of signal detection performance degradation induced by phase-retrieval in propagation-based x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

Chou, Cheng-Ying; Anastasio, Mark A.

2016-04-01

In propagation-based X-ray phase-contrast (PB XPC) imaging, the measured image contains a mixture of absorption- and phase-contrast. To obtain separate images of the projected absorption and phase (i.e., refractive) properties of a sample, phase retrieval methods can be employed. It has been suggested that phase-retrieval can always improve image quality in PB XPC imaging. However, when objective (task-based) measures of image quality are employed, this is not necessarily true and phase retrieval can be detrimental. In this work, signal detection theory is utilized to quantify the performance of a Hotelling observer (HO) for detecting a known signal in a known background. Two cases are considered. In the first case, the HO acts directly on the measured intensity data. In the second case, the HO acts on either the retrieved phase or absorption image. We demonstrate that the performance of the HO is superior when acting on the measured intensity data. The loss of task-specific information induced by phase-retrieval is quantified by computing the efficiency of the HO as the ratio of the test statistic signal-to-noise ratio (SNR) for the two cases. The effect of the system geometry on this efficiency is systematically investigated. Our findings confirm that phase-retrieval can impair signal detection performance in XPC imaging.

Textile Retrieval Based on Image Content from CDC and Webcam Cameras in Indoor Environments.

PubMed

García-Olalla, Oscar; Alegre, Enrique; Fernández-Robles, Laura; Fidalgo, Eduardo; Saikia, Surajit

2018-04-25

Textile based image retrieval for indoor environments can be used to retrieve images that contain the same textile, which may indicate that scenes are related. This makes up a useful approach for law enforcement agencies who want to find evidence based on matching between textiles. In this paper, we propose a novel pipeline that allows searching and retrieving textiles that appear in pictures of real scenes. Our approach is based on first obtaining regions containing textiles by using MSER on high pass filtered images of the RGB, HSV and Hue channels of the original photo. To describe the textile regions, we demonstrated that the combination of HOG and HCLOSIB is the best option for our proposal when using the correlation distance to match the query textile patch with the candidate regions. Furthermore, we introduce a new dataset, TextilTube, which comprises a total of 1913 textile regions labelled within 67 classes. We yielded 84.94% of success in the 40 nearest coincidences and 37.44% of precision taking into account just the first coincidence, which outperforms the current deep learning methods evaluated. Experimental results show that this pipeline can be used to set up an effective textile based image retrieval system in indoor environments.

Textile Retrieval Based on Image Content from CDC and Webcam Cameras in Indoor Environments

PubMed Central

García-Olalla, Oscar; Saikia, Surajit

2018-01-01

Textile based image retrieval for indoor environments can be used to retrieve images that contain the same textile, which may indicate that scenes are related. This makes up a useful approach for law enforcement agencies who want to find evidence based on matching between textiles. In this paper, we propose a novel pipeline that allows searching and retrieving textiles that appear in pictures of real scenes. Our approach is based on first obtaining regions containing textiles by using MSER on high pass filtered images of the RGB, HSV and Hue channels of the original photo. To describe the textile regions, we demonstrated that the combination of HOG and HCLOSIB is the best option for our proposal when using the correlation distance to match the query textile patch with the candidate regions. Furthermore, we introduce a new dataset, TextilTube, which comprises a total of 1913 textile regions labelled within 67 classes. We yielded 84.94% of success in the 40 nearest coincidences and 37.44% of precision taking into account just the first coincidence, which outperforms the current deep learning methods evaluated. Experimental results show that this pipeline can be used to set up an effective textile based image retrieval system in indoor environments. PMID:29693590

Lightning Charge Retrievals: Dimensional Reduction, LDAR Constraints, and a First Comparison with LIS Satellite Data

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Krider, E. P.; Murray, N.; Boccippio, D. J.

2007-01-01

A "dimensional reduction" (DR) method is introduced for analyzing lightning field changes (DELTAEs) whereby the number of unknowns in a discrete two-charge model is reduced from the standard eight (x, y, z, Q, x', y', z', Q') to just four (x, y, z, Q). The four unknowns (x, y, z, Q) are found by performing a numerical minimization of a chi-square function. At each step of the minimization, an Overdetermined Fixed Matrix (OFM) method is used to immediately retrieve the best "residual source" (x', y', z', Q'), given the values of (x, y, z, Q). In this way, all 8 parameters (x, y, z, Q, x', y', z', Q') are found, yet a numerical search of only 4 parameters (x, y, z, Q) is required. The DR method has been used to analyze lightning-caused DeltaEs derived from multiple ground-based electric field measurements at the NASA Kennedy Space Center (KSC) and USAF Eastern Range (ER). The accuracy of the DR method has been assessed by comparing retrievals with data provided by the Lightning Detection And Ranging (LDAR) system at the KSC-ER, and from least squares error estimation theory, and the method is shown to be a useful "stand-alone" charge retrieval tool. Since more than one charge distribution describes a finite set of DELTAEs (i.e., solutions are non-unique), and since there can exist appreciable differences in the physical characteristics of these solutions, not all DR solutions are physically acceptable. Hence, an alternative and more accurate method of analysis is introduced that uses LDAR data to constrain the geometry of the charge solutions, thereby removing physically unacceptable retrievals. The charge solutions derived from this method are shown to compare well with independent satellite- and ground-based observations of lightning in several Florida storms.

Evaluation of retrieval methods of daytime convective boundary layer height based on lidar data

NASA Astrophysics Data System (ADS)

Li, Hong; Yang, Yi; Hu, Xiao-Ming; Huang, Zhongwei; Wang, Guoyin; Zhang, Beidou; Zhang, Tiejun

2017-04-01

The atmospheric boundary layer height is a basic parameter in describing the structure of the lower atmosphere. Because of their high temporal resolution, ground-based lidar data are widely used to determine the daytime convective boundary layer height (CBLH), but the currently available retrieval methods have their advantages and drawbacks. In this paper, four methods of retrieving the CBLH (i.e., the gradient method, the idealized backscatter method, and two forms of the wavelet covariance transform method) from lidar normalized relative backscatter are evaluated, using two artificial cases (an idealized profile and a case similar to real profile), to test their stability and accuracy. The results show that the gradient method is suitable for high signal-to-noise ratio conditions. The idealized backscatter method is less sensitive to the first estimate of the CBLH; however, it is computationally expensive. The results obtained from the two forms of the wavelet covariance transform method are influenced by the selection of the initial input value of the wavelet amplitude. Further sensitivity analysis using real profiles under different orders of magnitude of background counts show that when different initial input values are set, the idealized backscatter method always obtains consistent CBLH. For two wavelet methods, the different CBLH are always obtained with the increase in the wavelet amplitude when noise is significant. Finally, the CBLHs as measured by three lidar-based methods are evaluated by as measured from L-band soundings. The boundary layer heights from two instruments coincide with ±200 m in most situations.

High-resolution fluorescence imaging for red and far-red SIF retrieval at leaf and canopy scales

NASA Astrophysics Data System (ADS)

Albert, L.; Alonso, L.; Cushman, K.; Kellner, J. R.

2017-12-01

New commercial-off-the-shelf imaging spectrometers promise the combination of high spatial and spectral resolution needed to retrieve solar induced fluorescence (SIF) at multiple wavelengths for individual plants and even individual leaves from low-altitude airborne or ground-based platforms. Data from these instruments could provide insight into the status of the photosynthetic apparatus at scales of space and time not observable from high-altitude and space-based platforms, and could support calibration and validation activities of current and forthcoming space missions to quantify SIF (OCO-2, OCO-3, FLEX, and GEOCARB). High-spectral resolution enables SIF retrieval from regions of strong telluric absorption by molecular oxygen, and also within numerous solar Fraunhofer lines in atmospheric windows not obscured by oxygen or water absorptions. Here we evaluate algorithms for SIF retrieval using a commercial-off-the-shelf diffraction-grating imaging spectrometer with a spectral sampling interval of 0.05 nm and a FWHM < 0.2 nm throughout the 670 - 780 nm range. We demonstrate the tradeoffs between spatial resolution and signal-to-noise ratio using frame stacking and binning, and evaluate the consequences of these tradeoffs for SIF retrieval using three approaches: (1) oxygen-A and B retrieval; (2) retrieval based exclusively on solar Fraunhofer lines outside regions of telluric gas absorption; and (3) a retrieval based on the combination of these approaches. We evaluate the quality of these methods by comparison with coincident SIF spectra of leaves measured using a hand-held field spectrometer and short-pass filters that block incoming light at wavelengths > 650 or 700 nm. These filters enable a direct measurement of SIF emission > 650 or 700 nm that serves as a benchmark against which retrievals from reflectance spectra can be evaluated. We repeated this comparison between leaf-level SIF emission spectra and retrieved SIF emission spectra for leaves treated with drought stress and an herbicide (DCMU) that inhibits electron transfer from QA to QB of PSII.

Mobile object retrieval in server-based image databases

NASA Astrophysics Data System (ADS)

Manger, D.; Pagel, F.; Widak, H.

2013-05-01

The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.

Analysis of mixing-layer height retrieval methods using backscatter lidar returns and microwave-radiometer temperature observations in the context of synergy

NASA Astrophysics Data System (ADS)

Saeed, Umar; Rocadenbosch, Francesc

2017-04-01

Mixing Layer Height (MLH) is an important parameter in many different atmospheric and meteorological applications. However, there does not exist a single instrument or method which provides accurate and physically consistent estimates of MLH. Instead, there are several methods for MLH estimation based on the measurements of different atmospheric tracers using different instruments [1, 2]. In this work, MLH retrieval methods using backscattered lidar signals and Microwave Radiometer (MWR)-retrieved potential-temperature profiles are compared in terms of their associated uncertainties. The Extended Kalman Filter (EKF) is used for MLH retrieval from backscattered lidar signals [3] and parcel method [4] is used for MLH retrieval from MWR-retrieved potential-temperature profiles. Measurement and retrieval errors are revisited and incorporated into the MLH estimation methods used. Uncertainties on MLH estimates from the two methods are compared along with a combined MLH-retrieval discussion case. The uncertainty analysis is validated using long-term lidar and MWR measurement data, under different atmospheric conditions, from the HD(CP)2 Observational Prototype Experiment (HOPE) campaign at Jülich, Germany [5]. MLH estimates from a Doppler wind lidar and radiosondes are used as reference. This work has received funding from the European Union Seventh Framework Programme, FP7 People, ITN Marie Curie Actions Programme (2012-2016) in the frame of ITaRS project (GA 289923), H2020 programme under ACTRIS-2 project (GA 654109), the Spanish Ministry of Economy and Competitiveness - European Regional Development Funds under TEC2015-63832-P project, and from the Generalitat de Catalunya (Grup de Recerca Consolidat) 2014-SGR-583. [1] S. Emeis, Surface-based Remote Sensing of the Atmospheric Boundary Layer. 978-90-481-9339-4, Springer, 2010. [2] P. Seibert, F. Beyrich, S.-E. Gryning, S. Joffre, A. Rasmussen, and P. Tercier, "Review and intercomparison of operational methods for the determination of the mixing height," Atmospheric Environment, vol. 34, pp. 1352-2310, 2000. [3] D. Lange, J. Tiana-Alsina, U. Saeed, S. Tomás, and F. Rocadenbosch, "Atmospheric-boundary-layer height monitoring using a Kalman filter and backscatter lidar returns," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 8, pp. 4717-4728, 2014. [4] G. Holzworth, "Estimates of mean maximum mixing depths in the contiguous United States," Monthly Weather Review, vol. 92, pp. 235-242, 1964. [5] U. Löhnert, J. H. Schween, C. Acquistapace, K. Ebell, M. Maahn, M. Barrera-Verdejo, A. Hirsikko, B. Bohn, A. Knaps, E. O'Connor, C. Simmer, A. Wahner, and S. Crewell, "JOYCE: Jülich Observatory for Cloud Evolution," Bull. Amer. Meteor. Soc., vol. 96, no. 7, pp. 1157-1174, 2015.

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

PubMed Central

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods. PMID:24349277

Snowfall Rate Retrieval using NPP ATMS Passive Microwave Measurements

NASA Technical Reports Server (NTRS)

Meng, Huan; Ferraro, Ralph; Kongoli, Cezar; Wang, Nai-Yu; Dong, Jun; Zavodsky, Bradley; Yan, Banghua; Zhao, Limin

2014-01-01

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow-on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2014). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two-stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The ATMS SFR product is validated against radar and gauge snowfall data and shows that the ATMS algorithm outperforms the AMSU/MHS SFR.

Plume Tracker: Interactive mapping of volcanic sulfur dioxide emissions with high-performance radiative transfer modeling

NASA Astrophysics Data System (ADS)

Realmuto, Vincent J.; Berk, Alexander

2016-11-01

We describe the development of Plume Tracker, an interactive toolkit for the analysis of multispectral thermal infrared observations of volcanic plumes and clouds. Plume Tracker is the successor to MAP_SO2, and together these flexible and comprehensive tools have enabled investigators to map sulfur dioxide (SO2) emissions from a number of volcanoes with TIR data from a variety of airborne and satellite instruments. Our objective for the development of Plume Tracker was to improve the computational performance of the retrieval procedures while retaining the accuracy of the retrievals. We have achieved a 300 × improvement in the benchmark performance of the retrieval procedures through the introduction of innovative data binning and signal reconstruction strategies, and improved the accuracy of the retrievals with a new method for evaluating the misfit between model and observed radiance spectra. We evaluated the accuracy of Plume Tracker retrievals with case studies based on MODIS and AIRS data acquired over Sarychev Peak Volcano, and ASTER data acquired over Kilauea and Turrialba Volcanoes. In the Sarychev Peak study, the AIRS-based estimate of total SO2 mass was 40% lower than the MODIS-based estimate. This result was consistent with a 45% reduction in the AIRS-based estimate of plume area relative to the corresponding MODIS-based estimate. In addition, we found that our AIRS-based estimate agreed with an independent estimate, based on a competing retrieval technique, within a margin of ± 20%. In the Kilauea study, the ASTER-based concentration estimates from 21 May 2012 were within ± 50% of concurrent ground-level concentration measurements. In the Turrialba study, the ASTER-based concentration estimates on 21 January 2012 were in exact agreement with SO2 concentrations measured at plume altitude on 1 February 2012.

Comparing the quality of accessing medical literature using content-based visual and textual information retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Kalpathy-Cramer, Jayashree; Kahn, Charles E., Jr.; Hersh, William

2009-02-01

Content-based visual information (or image) retrieval (CBIR) has been an extremely active research domain within medical imaging over the past ten years, with the goal of improving the management of visual medical information. Many technical solutions have been proposed, and application scenarios for image retrieval as well as image classification have been set up. However, in contrast to medical information retrieval using textual methods, visual retrieval has only rarely been applied in clinical practice. This is despite the large amount and variety of visual information produced in hospitals every day. This information overload imposes a significant burden upon clinicians, and CBIR technologies have the potential to help the situation. However, in order for CBIR to become an accepted clinical tool, it must demonstrate a higher level of technical maturity than it has to date. Since 2004, the ImageCLEF benchmark has included a task for the comparison of visual information retrieval algorithms for medical applications. In 2005, a task for medical image classification was introduced and both tasks have been run successfully for the past four years. These benchmarks allow an annual comparison of visual retrieval techniques based on the same data sets and the same query tasks, enabling the meaningful comparison of various retrieval techniques. The datasets used from 2004-2007 contained images and annotations from medical teaching files. In 2008, however, the dataset used was made up of 67,000 images (along with their associated figure captions and the full text of their corresponding articles) from two Radiological Society of North America (RSNA) scientific journals. This article describes the results of the medical image retrieval task of the ImageCLEF 2008 evaluation campaign. We compare the retrieval results of both visual and textual information retrieval systems from 15 research groups on the aforementioned data set. The results show clearly that, currently, visual retrieval alone does not achieve the performance necessary for real-world clinical applications. Most of the common visual retrieval techniques have a MAP (Mean Average Precision) of around 2-3%, which is much lower than that achieved using textual retrieval (MAP=29%). Advanced machine learning techniques, together with good training data, have been shown to improve the performance of visual retrieval systems in the past. Multimodal retrieval (basing retrieval on both visual and textual information) can achieve better results than purely visual, but only when carefully applied. In many cases, multimodal retrieval systems performed even worse than purely textual retrieval systems. On the other hand, some multimodal retrieval systems demonstrated significantly increased early precision, which has been shown to be a desirable behavior in real-world systems.

A fast image retrieval method based on SVM and imbalanced samples in filtering multimedia message spam

NASA Astrophysics Data System (ADS)

Chen, Zhang; Peng, Zhenming; Peng, Lingbing; Liao, Dongyi; He, Xin

2011-11-01

With the swift and violent development of the Multimedia Messaging Service (MMS), it becomes an urgent task to filter the Multimedia Message (MM) spam effectively in real-time. For the fact that most MMs contain images or videos, a method based on retrieving images is given in this paper for filtering MM spam. The detection method used in this paper is a combination of skin-color detection, texture detection, and face detection, and the classifier for this imbalanced problem is a very fast multi-classification combining Support vector machine (SVM) with unilateral binary decision tree. The experiments on 3 test sets show that the proposed method is effective, with the interception rate up to 60% and the average detection time for each image less than 1 second.

An Investigation of Differential Encoding and Retrieval in Older Adult College Students.

ERIC Educational Resources Information Center

Shaughnessy, Michael F.; Reif, Laurie

Three experiments were conducted in order to clarify the encoding/retrieval dilemma in older adult students; and the recognition/recall test issue was also explored. First, a mnemonic technique based on the "key word" method of Funk and Tarshis was used; secondly, a semantic processing task was tried; and lastly, a repetition task, based…

User-Based Information Retrieval System Interface Evaluation: An Examination of an On-Line Public Access Catalog.

ERIC Educational Resources Information Center

Hert, Carol A.; Nilan, Michael S.

1991-01-01

Presents preliminary data that characterizes the relationship between what users say they are trying to accomplish when using an online public access catalog (OPAC) and their perceptions of what input to give the system. Human-machine interaction is discussed, and appropriate methods for evaluating information retrieval systems are considered. (18…

Accuracy of retrieving temperature and humidity profiles by ground-based microwave radiometry in truly complex terrain

NASA Astrophysics Data System (ADS)

Massaro, G.; Stiperski, I.; Pospichal, B.; Rotach, M. W.

2015-08-01

Within the Innsbruck Box project, a ground-based microwave radiometer (RPG-HATPRO) was operated in the Inn Valley (Austria), in very complex terrain, between September 2012 and May 2013 to obtain temperature and humidity vertical profiles of the full troposphere with a specific focus on the valley boundary layer. In order to assess its performance in a deep alpine valley, the profiles obtained by the radiometer with different retrieval algorithms based on different climatologies are compared to local radiosonde data. A retrieval that is improved with respect to the one provided by the manufacturer, based on better resolved data, shows a significantly smaller root mean square error (RMSE), both for the temperature and humidity profiles. The improvement is particularly substantial at the heights close to the mountaintop level and in the upper troposphere. Lower-level inversions, common in an alpine valley, are resolved to a satisfactory degree. On the other hand, upper-level inversions (above 1200 m) still pose a significant challenge for retrieval. For this purpose, specialized retrieval algorithms were developed by classifying the radiosonde climatologies into specialized categories according to different criteria (seasons, daytime, nighttime) and using additional regressors (e.g., measurements from mountain stations). The training and testing on the radiosonde data for these specialized categories suggests that a classification of profiles that reproduces meaningful physical characteristics can yield improved targeted specialized retrievals. A novel and very promising method of improving the profile retrieval in a mountainous region is adding further information in the retrieval, such as the surface temperature at fixed levels along a topographic slope or from nearby mountaintops.

Estimation of Cirrus and Stratus Cloud Heights Using Landsat Imagery

NASA Technical Reports Server (NTRS)

Inomata, Yasushi; Feind, R. E.; Welch, R. M.

1996-01-01

A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and anti-sunside of the cloud-shadow pair are apparent. The technique requires some intepretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about +/- 250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semi-automated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals.

A singular value decomposition approach for improved taxonomic classification of biological sequences

PubMed Central

2011-01-01

Background Singular value decomposition (SVD) is a powerful technique for information retrieval; it helps uncover relationships between elements that are not prima facie related. SVD was initially developed to reduce the time needed for information retrieval and analysis of very large data sets in the complex internet environment. Since information retrieval from large-scale genome and proteome data sets has a similar level of complexity, SVD-based methods could also facilitate data analysis in this research area. Results We found that SVD applied to amino acid sequences demonstrates relationships and provides a basis for producing clusters and cladograms, demonstrating evolutionary relatedness of species that correlates well with Linnaean taxonomy. The choice of a reasonable number of singular values is crucial for SVD-based studies. We found that fewer singular values are needed to produce biologically significant clusters when SVD is employed. Subsequently, we developed a method to determine the lowest number of singular values and fewest clusters needed to guarantee biological significance; this system was developed and validated by comparison with Linnaean taxonomic classification. Conclusions By using SVD, we can reduce uncertainty concerning the appropriate rank value necessary to perform accurate information retrieval analyses. In tests, clusters that we developed with SVD perfectly matched what was expected based on Linnaean taxonomy. PMID:22369633

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

Social Image Tag Ranking by Two-View Learning

NASA Astrophysics Data System (ADS)

Zhuang, Jinfeng; Hoi, Steven C. H.

Tags play a central role in text-based social image retrieval and browsing. However, the tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In order to solve this problem, researchers have proposed techniques to rank the annotated tags of a social image according to their relevance to the visual content of the image. In this paper, we aim to overcome the challenge of social image tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the conventional learning approaches that usually assumes some parametric models, our method is completely data-driven and makes no assumption about the underlying models, making the proposed solution practically more effective. We formulate our method as an optimization task and present an efficient algorithm to solve it. To evaluate the efficacy of our method, we conducted an extensive set of experiments by applying our technique to both text-based social image retrieval and automatic image annotation tasks. Our empirical results showed that the proposed method can be more effective than the conventional approaches.

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City

PubMed Central

Zhou, Lianjie; Chen, Nengcheng; Yuan, Sai; Chen, Zeqiang

2016-01-01

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems. PMID:27801869

Fine-Tuning Neural Patient Question Retrieval Model with Generative Adversarial Networks.

PubMed

Tang, Guoyu; Ni, Yuan; Wang, Keqiang; Yong, Qin

2018-01-01

The online patient question and answering (Q&A) system attracts an increasing amount of users in China. Patient will post their questions and wait for doctors' response. To avoid the lag time involved with the waiting and to reduce the workload on the doctors, a better method is to automatically retrieve the semantically equivalent question from the archive. We present a Generative Adversarial Networks (GAN) based approach to automatically retrieve patient question. We apply supervised deep learning based approaches to determine the similarity between patient questions. Then a GAN framework is used to fine-tune the pre-trained deep learning models. The experiment results show that fine-tuning by GAN can improve the performance.

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

NASA Astrophysics Data System (ADS)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

NASA Technical Reports Server (NTRS)

Taylor, Jaime R.

2003-01-01

NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

Photogrammetric retrieval of volcanic ash cloud top height from SEVIRI and MODIS

NASA Astrophysics Data System (ADS)

Zakšek, Klemen; Hort, Matthias; Zaletelj, Janez; Langmann, Bärbel

2013-04-01

Even if erupting in remote areas, volcanoes can have a significant impact on the modern society due to volcanic ash dispersion in the atmosphere. The ash does not affect merely air traffic - its transport in the atmosphere and its deposition on land and in the oceans may also significantly influence the climate through modifications of atmospheric CO2. The emphasis of this contribution is the retrieval of volcanic ash plume height (ACTH). ACTH is important information especially for air traffic but also to predict ash transport and to estimate the mass flux of the ejected material. ACTH is usually estimated from ground measurements, pilot reports, or satellite remote sensing. But ground based instruments are often not available at remote volcanoes and also the pilots reports are a matter of chance. Volcanic ash cloud top height (ACTH) can be monitored on the global level using satellite remote sensing. The most often used method compares brightness temperature of the cloud with the atmospheric temperature profile. Because of uncertainties of this method (unknown emissivity of the ash cloud, tropopause, etc.) we propose photogrammetric methods based on the parallax between data retrieved from geostationary (SEVIRI) and polar orbiting satellites (MODIS). The parallax is estimated using automatic image matching in three level image pyramids. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. ACTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The proposed method was tested using MODIS band 1 and SEVIRI HRV band for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach over 30 km which implies ACTH of more than 12 km. The accuracy of ACTH was estimated to 0.6 km. The limitation of this procedure is that it has difficulties with automatic image matching if the ash cloud is not opaque.

Quantized phase coding and connected region labeling for absolute phase retrieval.

PubMed

Chen, Xiangcheng; Wang, Yuwei; Wang, Yajun; Ma, Mengchao; Zeng, Chunnian

2016-12-12

This paper proposes an absolute phase retrieval method for complex object measurement based on quantized phase-coding and connected region labeling. A specific code sequence is embedded into quantized phase of three coded fringes. Connected regions of different codes are labeled and assigned with 3-digit-codes combining the current period and its neighbors. Wrapped phase, more than 36 periods, can be restored with reference to the code sequence. Experimental results verify the capability of the proposed method to measure multiple isolated objects.

DNA extraction from formalin-fixed, paraffin-embedded tissues: protein digestion as a limiting step for retrieval of high-quality DNA.

PubMed

Díaz-Cano, S J; Brady, S P

1997-12-01

Several DNA extraction methods have been used for formalin-fixed, paraffin-embedded tissues, with variable results being reported regarding the suitability of DNA obtained from such sources to serve as template in polymerase chain reaction (PCR)-based genetic analyses. We present a method routinely used for archival material in our laboratory that reliably yields DNA of sufficient quality for PCR studies. This method is based on extended proteinase K digestion (250 micrograms/ml in an EDTA-free calcium-containing buffer supplemented with mussel glycogen) followed by phenol-chloroform extraction. Agarose gel electrophoresis of both digestion buffer aliquots and PCR amplification of the beta-globin gene tested the suitability of the retrieved DNA for PCR amplification.

New interactive CESAR

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

Fox, P.B.; Yatabe, M.

1987-01-01

The Nuclear Criticality Safety Analytical Methods Resource Center announces the availability of a new interactive version of CESAR, a critical experiments storage and retrieval program available on the Nuclear Criticality Information System (NCIS) data base at Lawrence Livermore National Laboratory. The original version of CESAR did not include interactive search capabilities. The CESAR data base was developed to provide a convenient, readily accessible means of storing and retrieving code input data for the SCALE criticality safety analytical sequences and the codes comprising those sequences. The data base includes data for both cross-section preparation and criticality safety calculations.

Water vapor retrieval from near-IR measurements of polarized scanning atmospheric corrector

NASA Astrophysics Data System (ADS)

Qie, Lili; Ning, Yuanming; Zhang, Yang; Chen, Xingfeng; Ma, Yan; Li, Zhengqiang; Cui, Wenyu

2018-02-01

Water vapor and aerosol are two key atmospheric factors effecting the remote sensing image quality. As water vapor is responsible for most of the solar radiation absorption occurring in the cloudless atmosphere, accurate measurement of water content is important to not only atmospheric correction of remote sensing images, but also many other applications such as the study of energy balance and global climate change, land surface temperature retrieval in thermal remote sensing. A multi-spectral, single-angular, polarized radiometer called Polarized Scanning Atmospheric Corrector (PSAC) were developed in China, which are designed to mount on the same satellite platform with the principle payload and provide essential parameters for principle payload image atmospheric correction. PSAC detect water vapor content via measuring atmosphere reflectance at water vapor absorbing channels (i.e. 0.91 μm) and nearby atmospheric window channel (i.e. 0.865μm). A near-IR channel ratio method was implemented to retrieve column water vapor (CWV) amount from PSAC measurements. Field experiments were performed at Yantai, in Shandong province of China, PSAC aircraft observations were acquired. The comparison between PSAC retrievals and ground-based Sun-sky radiometer measurements of CWV during the experimental flights illustrates that this method retrieves CWV with relative deviations ranging from 4% 13%. This method retrieve CWV more accurate over land than over ocean, as the water reflectance is low.

A Case-Based Reasoning Method with Rank Aggregation

NASA Astrophysics Data System (ADS)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations

NASA Technical Reports Server (NTRS)

Jeong, U; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

2016-01-01

An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional lookup tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OEbased estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

Content based Image Retrieval based on Different Global and Local Color Histogram Methods: A Survey

NASA Astrophysics Data System (ADS)

Suhasini, Pallikonda Sarah; Sri Rama Krishna, K.; Murali Krishna, I. V.

2017-02-01

Different global and local color histogram methods for content based image retrieval (CBIR) are investigated in this paper. Color histogram is a widely used descriptor for CBIR. Conventional method of extracting color histogram is global, which misses the spatial content, is less invariant to deformation and viewpoint changes, and results in a very large three dimensional histogram corresponding to the color space used. To address the above deficiencies, different global and local histogram methods are proposed in recent research. Different ways of extracting local histograms to have spatial correspondence, invariant colour histogram to add deformation and viewpoint invariance and fuzzy linking method to reduce the size of the histogram are found in recent papers. The color space and the distance metric used are vital in obtaining color histogram. In this paper the performance of CBIR based on different global and local color histograms in three different color spaces, namely, RGB, HSV, L*a*b* and also with three distance measures Euclidean, Quadratic and Histogram intersection are surveyed, to choose appropriate method for future research.

Time series inversion of spectra from ground-based radiometers

NASA Astrophysics Data System (ADS)

Christensen, O. M.; Eriksson, P.

2013-07-01

Retrieving time series of atmospheric constituents from ground-based spectrometers often requires different temporal averaging depending on the altitude region in focus. This can lead to several datasets existing for one instrument, which complicates validation and comparisons between instruments. This paper puts forth a possible solution by incorporating the temporal domain into the maximum a posteriori (MAP) retrieval algorithm. The state vector is increased to include measurements spanning a time period, and the temporal correlations between the true atmospheric states are explicitly specified in the a priori uncertainty matrix. This allows the MAP method to effectively select the best temporal smoothing for each altitude, removing the need for several datasets to cover different altitudes. The method is compared to traditional averaging of spectra using a simulated retrieval of water vapour in the mesosphere. The simulations show that the method offers a significant advantage compared to the traditional method, extending the sensitivity an additional 10 km upwards without reducing the temporal resolution at lower altitudes. The method is also tested on the Onsala Space Observatory (OSO) water vapour microwave radiometer confirming the advantages found in the simulation. Additionally, it is shown how the method can interpolate data in time and provide diagnostic values to evaluate the interpolated data.

Ground and satellite-based remote sensing of mineral dust using AERI spectra and MODIS thermal infrared window brightness temperatures

NASA Astrophysics Data System (ADS)

Hansell, Richard Allen, Jr.

The radiative effects of dust aerosol on our climate system have yet to be fully understood and remain a topic of contemporary research. To investigate these effects, detection/retrieval methods for dust events over major dust outbreak and transport areas have been developed using satellite and ground-based approaches. To this end, both the shortwave and longwave surface radiative forcing of dust aerosol were investigated. The ground-based remote sensing approach uses the Atmospheric Emitted Radiance Interferometer brightness temperature spectra to detect mineral dust events and to retrieve their properties. Taking advantage of the high spectral resolution of the AERI instrument, absorptive differences in prescribed thermal IR window sub-band channels were exploited to differentiate dust from cirrus clouds. AERI data collected during the UAE2 at Al-Ain UAE was employed for dust retrieval. Assuming a specified dust composition model a priori and using the light scattering programs of T-matrix and the finite difference time domain methods for oblate spheroids and hexagonal plates, respectively, dust optical depths have been retrieved and compared to those inferred from a collocated and coincident AERONET sun-photometer dataset. The retrieved optical depths were then used to determine the dust longwave surface forcing during the UAE2. Likewise, dust shortwave surface forcing is investigated employing a differential technique from previous field studies. The satellite-based approach uses MODIS thermal infrared brightness temperature window data for the simultaneous detection/separation of mineral dust and cirrus clouds. Based on the spectral variability of dust emissivity at the 3.75, 8.6, 11 and 12 mum wavelengths, the D*-parameter, BTD-slope and BTD3-11 tests are combined to identify dust and cirrus. MODIS data for the three dust-laden scenes have been analyzed to demonstrate the effectiveness of this detection/separation method. Detected daytime dust and cloud coverage for the Persian Gulf case compare reasonably well to those from the "Deep Blue" algorithm developed at NASA-GSFC. The nighttime dust/cloud detection for the cases surrounding Cape Verde and Niger, West Africa has been validated by comparing to coincident and collocated ground-based micro-pulse lidar measurements.

Improved MODIS aerosol retrieval in urban areas using a land classification approach and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Levitan, Nathaniel; Gross, Barry

2016-10-01

New, high-resolution aerosol products are required in urban areas to improve the spatial coverage of the products, in terms of both resolution and retrieval frequency. These new products will improve our understanding of the spatial variability of aerosols in urban areas and will be useful in the detection of localized aerosol emissions. Urban aerosol retrieval is challenging for existing algorithms because of the high spatial variability of the surface reflectance, indicating the need for improved urban surface reflectance models. This problem can be stated in the language of novelty detection as the problem of selecting aerosol parameters whose effective surface reflectance spectrum is not an outlier in some space. In this paper, empirical orthogonal functions, a reconstruction-based novelty detection technique, is used to perform single-pixel aerosol retrieval using the single angular and temporal sample provided by the MODIS sensor. The empirical orthogonal basis functions are trained for different land classes using the MODIS BRDF MCD43 product. Existing land classification products are used in training and aerosol retrieval. The retrieval is compared against the existing operational MODIS 3 KM Dark Target (DT) aerosol product and co-located AERONET data. Based on the comparison, our method allows for a significant increase in retrieval frequency and a moderate decrease in the known biases of MODIS urban aerosol retrievals.

Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras.

PubMed

Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki

2016-06-24

Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system.

Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras

PubMed Central

Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki

2016-01-01

Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system. PMID:27347961

JANE, A new information retrieval system for the Radiation Shielding Information Center

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

Trubey, D.K.

A new information storage and retrieval system has been developed for the Radiation Shielding Information Center (RSIC) at Oak Ridge National Laboratory to replace mainframe systems that have become obsolete. The database contains citations and abstracts of literature which were selected by RSIC analysts and indexed with terms from a controlled vocabulary. The database, begun in 1963, has been maintained continuously since that time. The new system, called JANE, incorporates automatic indexing techniques and on-line retrieval using the RSIC Data General Eclipse MV/4000 minicomputer, Automatic indexing and retrieval techniques based on fuzzy-set theory allow the presentation of results in ordermore » of Retrieval Status Value. The fuzzy-set membership function depends on term frequency in the titles and abstracts and on Term Discrimination Values which indicate the resolving power of the individual terms. These values are determined by the Cover Coefficient method. The use of a commercial database base to store and retrieve the indexing information permits rapid retrieval of the stored documents. Comparisons of the new and presently-used systems for actual searches of the literature indicate that it is practical to replace the mainframe systems with a minicomputer system similar to the present version of JANE. 18 refs., 10 figs.« less

Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval.

PubMed

Dai, Guoxian; Xie, Jin; Fang, Yi

2018-07-01

How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape. In this paper, we proposed a novel deep correlated holistic metric learning (DCHML) method to mitigate the discrepancy between sketch and 3D shape domains. The proposed DCHML trains two distinct deep neural networks (one for each domain) jointly, which learns two deep nonlinear transformations to map features from both domains into a new feature space. The proposed loss, including discriminative loss and correlation loss, aims to increase the discrimination of features within each domain as well as the correlation between different domains. In the new feature space, the discriminative loss minimizes the intra-class distance of the deep transformed features and maximizes the inter-class distance of the deep transformed features to a large margin within each domain, while the correlation loss focused on mitigating the distribution discrepancy across different domains. Different from existing deep metric learning methods only with loss at the output layer, our proposed DCHML is trained with loss at both hidden layer and output layer to further improve the performance by encouraging features in the hidden layer also with desired properties. Our proposed method is evaluated on three benchmarks, including 3D Shape Retrieval Contest 2013, 2014, and 2016 benchmarks, and the experimental results demonstrate the superiority of our proposed method over the state-of-the-art methods.

Retrieval feedback in MEDLINE.

PubMed Central

Srinivasan, P

1996-01-01

OBJECTIVE: To investigate a new approach for query expansion based on retrieval feedback. The first objective in this study was to examine alternative query-expansion methods within the same retrieval-feedback framework. The three alternatives proposed are: expansion on the MeSH query field alone, expansion on the free-text field alone, and expansion on both the MeSH and the free-text fields. The second objective was to gain further understanding of retrieval feedback by examining possible dependencies on relevant documents during the feedback cycle. DESIGN: Comparative study of retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a MEDLINE test collection of 75 queries and 2,334 MEDLINE citations. MEASUREMENTS: Retrieval effectivenesses of the original unexpanded and the alternative expanded queries were compared using 11-point-average precision scores (11-AvgP). These are averages of precision scores obtained at 11 standard recall points. RESULTS: All three expansion strategies significantly improved the original queries in terms of retrieval effectiveness. Expansion on MeSH alone was equivalent to expansion on both MeSH and the free-text fields. Expansion on the free-text field alone improved the queries significantly less than did the other two strategies. The second part of the study indicated that retrieval-feedback-based expansion yields significant performance improvements independent of the availability of relevant documents for feedback information. CONCLUSIONS: Retrieval feedback offers a robust procedure for query expansion that is most effective for MEDLINE when applied to the MeSH field. PMID:8653452

Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization.

PubMed

Luo, Jake; Chen, Weiheng; Wu, Min; Weng, Chunhua

2017-12-01

Prior studies of clinical trial planning indicate that it is crucial to search and screen recruitment sites before starting to enroll participants. However, currently there is no systematic method developed to support clinical investigators to search candidate recruitment sites according to their interested clinical trial factors. In this study, we aim at developing a new approach to integrating the location data of over one million heterogeneous recruitment sites that are stored in clinical trial documents. The integrated recruitment location data can be searched and visualized using a map-based information retrieval method. The method enables systematic search and analysis of recruitment sites across a large amount of clinical trials. The location data of more than 1.4 million recruitment sites of over 183,000 clinical trials was normalized and integrated using a geocoding method. The integrated data can be used to support geographic information retrieval of recruitment sites. Additionally, the information of over 6000 clinical trial target disease conditions and close to 4000 interventions was also integrated into the system and linked to the recruitment locations. Such data integration enabled the construction of a novel map-based query system. The system will allow clinical investigators to search and visualize candidate recruitment sites for clinical trials based on target conditions and interventions. The evaluation results showed that the coverage of the geographic location mapping for the 1.4 million recruitment sites was 99.8%. The evaluation of 200 randomly retrieved recruitment sites showed that the correctness of geographic information mapping was 96.5%. The recruitment intensities of the top 30 countries were also retrieved and analyzed. The data analysis results indicated that the recruitment intensity varied significantly across different countries and geographic areas. This study contributed a new data processing framework to extract and integrate the location data of heterogeneous recruitment sites from clinical trial documents. The developed system can support effective retrieval and analysis of potential recruitment sites using target clinical trial factors. Copyright © 2017 Elsevier B.V. All rights reserved.

A New Antigen Retrieval Technique for Human Brain Tissue

PubMed Central

Byne, William; Haroutunian, Vahram; García-Villanueva, Mercedes; Rábano, Alberto; García-Amado, María; Prensa, Lucía; Giménez-Amaya, José Manuel

2008-01-01

Immunohistochemical staining of tissues is a powerful tool used to delineate the presence or absence of an antigen. During the last 30 years, antigen visualization in human brain tissue has been significantly limited by the masking effect of fixatives. In the present study, we have used a new method for antigen retrieval in formalin-fixed human brain tissue and examined the effectiveness of this protocol to reveal masked antigens in tissues with both short and long formalin fixation times. This new method, which is based on the use of citraconic acid, has not been previously utilized in brain tissue although it has been employed in various other tissues such as tonsil, ovary, skin, lymph node, stomach, breast, colon, lung and thymus. Thus, we reported here a novel method to carry out immunohistochemical studies in free-floating human brain sections. Since fixation of brain tissue specimens in formaldehyde is a commonly method used in brain banks, this new antigen retrieval method could facilitate immunohistochemical studies of brains with prolonged formalin fixation times. PMID:18852880

Phase retrieval in annulus sector domain by non-iterative methods

NASA Astrophysics Data System (ADS)

Wang, Xiao; Mao, Heng; Zhao, Da-zun

2008-03-01

Phase retrieval could be achieved by solving the intensity transport equation (ITE) under the paraxial approximation. For the case of uniform illumination, Neumann boundary condition is involved and it makes the solving process more complicated. The primary mirror is usually designed segmented in the telescope with large aperture, and the shape of a segmented piece is often like an annulus sector. Accordingly, It is necessary to analyze the phase retrieval in the annulus sector domain. Two non-iterative methods are considered for recovering the phase. The matrix method is based on the decomposition of the solution into a series of orthogonalized polynomials, while the frequency filtering method depends on the inverse computation process of ITE. By the simulation, it is found that both methods can eliminate the effect of Neumann boundary condition, save a lot of computation time and recover the distorted phase well. The wavefront error (WFE) RMS can be less than 0.05 wavelength, even when some noise is added.

Noniterative approach to the missing data problem in coherent diffraction imaging by phase retrieval.

PubMed

Nakajima, Nobuharu

2010-07-20

When a very intense beam is used for illuminating an object in coherent x-ray diffraction imaging, the intensities at the center of the diffraction pattern for the object are cut off by a beam stop that is utilized to block the intense beam. Until now, only iterative phase-retrieval methods have been applied to object reconstruction from a single diffraction pattern with a deficiency of central data due to a beam stop. As an alternative method, I present a noniterative solution in which an interpolation method based on the sampling theorem for the missing data is used for object reconstruction with our previously proposed phase-retrieval method using an aperture-array filter. Computer simulations demonstrate the reconstruction of a complex-amplitude object from a single diffraction pattern with a missing data area, which is generally difficult to treat with the iterative methods because a nonnegativity constraint cannot be used for such an object.

Mining knowledge from corpora: an application to retrieval and indexing.

PubMed

Soualmia, Lina F; Dahamna, Badisse; Darmoni, Stéfan

2008-01-01

The present work aims at discovering new associations between medical concepts to be exploited as input in retrieval and indexing. Association rules method is applied to documents. The process is carried out on three major document categories referring to e-health information consumers: health professionals, students and lay people. Association rules evaluation is founded on statistical measures combined with domain knowledge. Association rules represent existing relations between medical concepts (60.62%) and new knowledge (54.21%). Based on observations, 463 expert rules are defined by medical librarians for retrieval and indexing. Association rules bear out existing relations, produce new knowledge and support users and indexers in document retrieval and indexing.

VIRTIS on Venus Express: retrieval of real surface emissivity on global scales

NASA Astrophysics Data System (ADS)

Arnold, Gabriele E.; Kappel, David; Haus, Rainer; Telléz Pedroza, Laura; Piccioni, Giuseppe; Drossart, Pierre

2015-09-01

The extraction of surface emissivity data provides the data base for surface composition analyses and enables to evaluate Venus' geology. The Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS) aboard ESA's Venus Express mission measured, inter alia, the nightside thermal emission of Venus in the near infrared atmospheric windows between 1.0 and 1.2 μm. These data can be used to determine information about surface properties on global scales. This requires a sophisticated approach to understand and consider the effects and interferences of different atmospheric and surface parameters influencing the retrieved values. In the present work, results of a new technique for retrieval of the 1.0 - 1.2 μm - surface emissivity are summarized. It includes a Multi-Window Retrieval Technique, a Multi-Spectrum Retrieval technique (MSR), and a detailed reliability analysis. The MWT bases on a detailed radiative transfer model making simultaneous use of information from different atmospheric windows of an individual spectrum. MSR regularizes the retrieval by incorporating available a priori mean values, standard deviations as well as spatial-temporal correlations of parameters to be retrieved. The capability of this method is shown for a selected surface target area. Implications for geologic investigations are discussed. Based on these results, the work draws conclusions for future Venus surface composition analyses on global scales using spectral remote sensing techniques. In that context, requirements for observational scenarios and instrumental performances are investigated, and recommendations are derived to optimize spectral measurements for Venus' surface studies.

A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval

NASA Astrophysics Data System (ADS)

You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-01-01

Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

Do family physicians retrieve synopses of clinical research previously read as email alerts?

PubMed

Grad, Roland; Pluye, Pierre; Johnson-Lafleur, Janique; Granikov, Vera; Shulha, Michael; Bartlett, Gillian; Marlow, Bernard

2011-11-30

A synopsis of new clinical research highlights important aspects of one study in a brief structured format. When delivered as email alerts, synopses enable clinicians to become aware of new developments relevant for practice. Once read, a synopsis can become a known item of clinical information. In time-pressured situations, remembering a known item may facilitate information retrieval by the clinician. However, exactly how synopses first delivered as email alerts influence retrieval at some later time is not known. We examined searches for clinical information in which a synopsis previously read as an email alert was retrieved (defined as a dyad). Our study objectives were to (1) examine whether family physicians retrieved synopses they previously read as email alerts and then to (2) explore whether family physicians purposefully retrieved these synopses. We conducted a mixed-methods study in which a qualitative multiple case study explored the retrieval of email alerts within a prospective longitudinal cohort of practicing family physicians. Reading of research-based synopses was tracked in two contexts: (1) push, meaning to read on email and (2) pull, meaning to read after retrieval from one electronic knowledge resource. Dyads, defined as synopses first read as email alerts and subsequently retrieved in a search of a knowledge resource, were prospectively identified. Participants were interviewed about all of their dyads. Outcomes were the total number of dyads and their type. Over a period of 341 days, 194 unique synopses delivered to 41 participants resulted in 4937 synopsis readings. In all, 1205 synopses were retrieved over an average of 320 days. Of the 1205 retrieved synopses, 21 (1.7%) were dyads made by 17 family physicians. Of the 1205 retrieved synopses, 6 (0.5%) were known item type dyads. However, dyads also occurred serendipitously. In the single knowledge resource we studied, email alerts containing research-based synopses were rarely retrieved. Our findings help us to better understand the effect of push on pull and to improve the integration of research-based information within electronic resources for clinicians.

A novel class sensitive hashing technique for large-scale content-based remote sensing image retrieval

NASA Astrophysics Data System (ADS)

Reato, Thomas; Demir, Begüm; Bruzzone, Lorenzo

2017-10-01

This paper presents a novel class sensitive hashing technique in the framework of large-scale content-based remote sensing (RS) image retrieval. The proposed technique aims at representing each image with multi-hash codes, each of which corresponds to a primitive (i.e., land cover class) present in the image. To this end, the proposed method consists of a three-steps algorithm. The first step is devoted to characterize each image by primitive class descriptors. These descriptors are obtained through a supervised approach, which initially extracts the image regions and their descriptors that are then associated with primitives present in the images. This step requires a set of annotated training regions to define primitive classes. A correspondence between the regions of an image and the primitive classes is built based on the probability of each primitive class to be present at each region. All the regions belonging to the specific primitive class with a probability higher than a given threshold are highly representative of that class. Thus, the average value of the descriptors of these regions is used to characterize that primitive. In the second step, the descriptors of primitive classes are transformed into multi-hash codes to represent each image. This is achieved by adapting the kernel-based supervised locality sensitive hashing method to multi-code hashing problems. The first two steps of the proposed technique, unlike the standard hashing methods, allow one to represent each image by a set of primitive class sensitive descriptors and their hash codes. Then, in the last step, the images in the archive that are very similar to a query image are retrieved based on a multi-hash-code-matching scheme. Experimental results obtained on an archive of aerial images confirm the effectiveness of the proposed technique in terms of retrieval accuracy when compared to the standard hashing methods.

Content Based Lecture Video Retrieval Using Speech and Video Text Information

ERIC Educational Resources Information Center

Yang, Haojin; Meinel, Christoph

2014-01-01

In the last decade e-lecturing has become more and more popular. The amount of lecture video data on the "World Wide Web" (WWW) is growing rapidly. Therefore, a more efficient method for video retrieval in WWW or within large lecture video archives is urgently needed. This paper presents an approach for automated video indexing and video…

Automatic Processing of Metallurgical Abstracts for the Purpose of Information Retrieval. Final Report.

ERIC Educational Resources Information Center

Melton, Jessica S.

Objectives of this project were to develop and test a method for automatically processing the text of abstracts for a document retrieval system. The test corpus consisted of 768 abstracts from the metallurgical section of Chemical Abstracts (CA). The system, based on a subject indexing rational, had two components: (1) a stored dictionary of words…

Information retrieval for systematic reviews in food and feed topics: A narrative review.

PubMed

Wood, Hannah; O'Connor, Annette; Sargeant, Jan; Glanville, Julie

2018-01-09

Systematic review methods are now being used for reviews of food production, food safety and security, plant health, and animal health and welfare. Information retrieval methods in this context have been informed by human health-care approaches and ideally should be based on relevant research and experience. This narrative review seeks to identify and summarize current research-based evidence and experience on information retrieval for systematic reviews in food and feed topics. MEDLINE (Ovid), Science Citation Index (Web of Science), and ScienceDirect (http://www.sciencedirect.com/) were searched in 2012 and 2016. We also contacted topic experts and undertook citation searches. We selected and summarized studies reporting research on information retrieval, as well as published guidance and experience. There is little published evidence on the most efficient way to conduct searches for food and feed topics. There are few available study design search filters, and their use may be problematic given poor or inconsistent reporting of study methods. Food and feed research makes use of a wide range of study designs so it might be best to focus strategy development on capturing study populations, although this also has challenges. There is limited guidance on which resources should be searched and whether publication bias in disciplines relevant to food and feed necessitates extensive searching of the gray literature. There is some limited evidence on information retrieval approaches, but more research is required to inform effective and efficient approaches to searching to populate food and feed reviews. Copyright © 2018 John Wiley & Sons, Ltd.

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

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

Choo, Jaegul; Kim, Hannah; Clarkson, Edward

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE PAGES

Choo, Jaegul; Kim, Hannah; Clarkson, Edward; ...

2018-01-31

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

Multi-clues image retrieval based on improved color invariants

NASA Astrophysics Data System (ADS)

Liu, Liu; Li, Jian-Xun

2012-05-01

At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

Application of the LSQR algorithm in non-parametric estimation of aerosol size distribution

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Lew, Zhongyuan; Ruan, Liming; Tan, Heping; Luo, Kun

2016-05-01

Based on the Least Squares QR decomposition (LSQR) algorithm, the aerosol size distribution (ASD) is retrieved in non-parametric approach. The direct problem is solved by the Anomalous Diffraction Approximation (ADA) and the Lambert-Beer Law. An optimal wavelength selection method is developed to improve the retrieval accuracy of the ASD. The proposed optimal wavelength set is selected by the method which can make the measurement signals sensitive to wavelength and decrease the degree of the ill-condition of coefficient matrix of linear systems effectively to enhance the anti-interference ability of retrieval results. Two common kinds of monomodal and bimodal ASDs, log-normal (L-N) and Gamma distributions, are estimated, respectively. Numerical tests show that the LSQR algorithm can be successfully applied to retrieve the ASD with high stability in the presence of random noise and low susceptibility to the shape of distributions. Finally, the experimental measurement ASD over Harbin in China is recovered reasonably. All the results confirm that the LSQR algorithm combined with the optimal wavelength selection method is an effective and reliable technique in non-parametric estimation of ASD.

Multiple search methods for similarity-based virtual screening: analysis of search overlap and precision

PubMed Central

2011-01-01

Background Data fusion methods are widely used in virtual screening, and make the implicit assumption that the more often a molecule is retrieved in multiple similarity searches, the more likely it is to be active. This paper tests the correctness of this assumption. Results Sets of 25 searches using either the same reference structure and 25 different similarity measures (similarity fusion) or 25 different reference structures and the same similarity measure (group fusion) show that large numbers of unique molecules are retrieved by just a single search, but that the numbers of unique molecules decrease very rapidly as more searches are considered. This rapid decrease is accompanied by a rapid increase in the fraction of those retrieved molecules that are active. There is an approximately log-log relationship between the numbers of different molecules retrieved and the number of searches carried out, and a rationale for this power-law behaviour is provided. Conclusions Using multiple searches provides a simple way of increasing the precision of a similarity search, and thus provides a justification for the use of data fusion methods in virtual screening. PMID:21824430

Retrieval of land cover information under thin fog in Landsat TM image

NASA Astrophysics Data System (ADS)

Wei, Yuchun

2008-04-01

Thin fog, which often appears in remote sensing image of subtropical climate region, has resulted in the low image quantity and bad image mapping. Therefore, it is necessary to develop the image processing method to retrieve land cover information under thin fog. In this paper, the Landsat TM image near the Taihu Lake that is in the subtropical climate zone of China was used as an example, and the workflow and method used to retrieve the land cover information under thin fog have been built based on ENVI software and a single TM image. The basic step covers three parts: 1) isolating the thin fog area in image according to the spectral difference of different bands; 2) retrieving the visible band information of different land cover types under thin fog from the near-infrared bands according to the relationships between near-infrared bands and visible bands of different land cover types in the area without fog; 3) image post-process. The result showed that the method in the paper is easy and suitable, and can be used to improve the quantity of TM image mapping more effectively.

Experiments on sparsity assisted phase retrieval of phase objects

NASA Astrophysics Data System (ADS)

Gaur, Charu; Lochab, Priyanka; Khare, Kedar

2017-05-01

Iterative phase retrieval algorithms such as the Gerchberg-Saxton method and the Fienup hybrid input-output method are known to suffer from the twin image stagnation problem, particularly when the solution to be recovered is complex valued and has centrosymmetric support. Recently we showed that the twin image stagnation problem can be addressed using image sparsity ideas (Gaur et al 2015 J. Opt. Soc. Am. A 32 1922). In this work we test this sparsity assisted phase retrieval method with experimental single shot Fourier transform intensity data frames corresponding to phase objects displayed on a spatial light modulator. The standard iterative phase retrieval algorithms are combined with an image sparsity based penalty in an adaptive manner. Illustrations for both binary and continuous phase objects are provided. It is observed that image sparsity constraint has an important role to play in obtaining meaningful phase recovery without encountering the well-known stagnation problems. The results are valuable for enabling single shot coherent diffraction imaging of phase objects for applications involving illumination wavelengths over a wide range of electromagnetic spectrum.

Random forest regression modelling for forest aboveground biomass estimation using RISAT-1 PolSAR and terrestrial LiDAR data

NASA Astrophysics Data System (ADS)

Mangla, Rohit; Kumar, Shashi; Nandy, Subrata

2016-05-01

SAR and LiDAR remote sensing have already shown the potential of active sensors for forest parameter retrieval. SAR sensor in its fully polarimetric mode has an advantage to retrieve scattering property of different component of forest structure and LiDAR has the capability to measure structural information with very high accuracy. This study was focused on retrieval of forest aboveground biomass (AGB) using Terrestrial Laser Scanner (TLS) based point clouds and scattering property of forest vegetation obtained from decomposition modelling of RISAT-1 fully polarimetric SAR data. TLS data was acquired for 14 plots of Timli forest range, Uttarakhand, India. The forest area is dominated by Sal trees and random sampling with plot size of 0.1 ha (31.62m*31.62m) was adopted for TLS and field data collection. RISAT-1 data was processed to retrieve SAR data based variables and TLS point clouds based 3D imaging was done to retrieve LiDAR based variables. Surface scattering, double-bounce scattering, volume scattering, helix and wire scattering were the SAR based variables retrieved from polarimetric decomposition. Tree heights and stem diameters were used as LiDAR based variables retrieved from single tree vertical height and least square circle fit methods respectively. All the variables obtained for forest plots were used as an input in a machine learning based Random Forest Regression Model, which was developed in this study for forest AGB estimation. Modelled output for forest AGB showed reliable accuracy (RMSE = 27.68 t/ha) and a good coefficient of determination (0.63) was obtained through the linear regression between modelled AGB and field-estimated AGB. The sensitivity analysis showed that the model was more sensitive for the major contributed variables (stem diameter and volume scattering) and these variables were measured from two different remote sensing techniques. This study strongly recommends the integration of SAR and LiDAR data for forest AGB estimation.

Retrievals of methane from IASI radiance spectra and comparisons with ground-based FTIR measurements

NASA Astrophysics Data System (ADS)

Kerzenmacher, T.; Kumps, N.; de Mazière, M.; Kruglanski, M.; Senten, C.; Vanhaelewyn, G.; Vandaele, A. C.; Vigouroux, C.

2009-04-01

The Infrared Atmospheric Sounding Interferometer (IASI), launched on 19 October 2006, is a Fourier transform spectrometer onboard METOP-1, observing the radiance of the Earth's surface and atmosphere in nadir mode. The spectral range covers the 645 to 2760 cm-1 region with a resolution of 0.35 to 0.5 cm-1. A line-by-line spectral simulation and inversion code, ASIMUT, has been developed for the retrieval of chemical species from infrared spectra. The code includes an analytical calculation of the Jacobians for use in the inversion part of the algorithm based on the Optimal Estimation Method. In 2007 we conducted a measurement campaign at St Denis, Île de la Réunion where we performed ground-based solar absorption observations with a infrared Fourier transform spectrometer. ASIMUT has been used to retrieve methane from the ground-based and collocated satellite measurements. For the latter we selected pixels that are situated over the sea. In this presentation we will show the retrieval strategies, the resulting methane column time series above St Denis and the comparisons of the satellite data with the ground-based data sets. Vertical profile information in these data sets will also be discussed.

View subspaces for indexing and retrieval of 3D models

NASA Astrophysics Data System (ADS)

Dutagaci, Helin; Godil, Afzal; Sankur, Bülent; Yemez, Yücel

2010-02-01

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.

The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

NASA Technical Reports Server (NTRS)

Welch, Ronald M.

1993-01-01

A series of cloud and sea ice retrieval algorithms are being developed in support of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Science Team objectives. These retrievals include the following: cloud fractional area, cloud optical thickness, cloud phase (water or ice), cloud particle effective radius, cloud top heights, cloud base height, cloud top temperature, cloud emissivity, cloud 3-D structure, cloud field scales of organization, sea ice fractional area, sea ice temperature, sea ice albedo, and sea surface temperature. Due to the problems of accurately retrieving cloud properties over bright surfaces, an advanced cloud classification method was developed which is based upon spectral and textural features and artificial intelligence classifiers.

Semantic concept-enriched dependence model for medical information retrieval.

PubMed

Choi, Sungbin; Choi, Jinwook; Yoo, Sooyoung; Kim, Heechun; Lee, Youngho

2014-02-01

In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance. Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method. We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research. Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query. By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance. Copyright © 2013 Elsevier Inc. All rights reserved.

Surface Reflectance of Mars Observed by CRISM-MRO: 1. Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (mars-reco)

NASA Technical Reports Server (NTRS)

Ceamanos, Xavier; Doute, S.; Fernando, J.; Pinet, P.; Lyapustin, A.

2013-01-01

This article addresses the correction for aerosol effects in near-simultaneous multiangle observations acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter. In the targeted mode, CRISM senses the surface of Mars using 11 viewing angles, which allow it to provide unique information on the scattering properties of surface materials. In order to retrieve these data, however, appropriate strategies must be used to compensate the signal sensed by CRISM for aerosol contribution. This correction is particularly challenging as the photometric curve of these suspended particles is often correlated with the also anisotropic photometric curve of materials at the surface. This article puts forward an innovative radiative transfer based method named Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS-ReCO). The proposed method retrieves photometric curves of surface materials in reflectance units after removing aerosol contribution. MARS-ReCO represents a substantial improvement regarding previous techniques as it takes into consideration the anisotropy of the surface, thus providing more realistic surface products. Furthermore, MARS-ReCO is fast and provides error bars on the retrieved surface reflectance. The validity and accuracy of MARS-ReCO is explored in a sensitivity analysis based on realistic synthetic data. According to experiments, MARS-ReCO provides accurate results (up to 10 reflectance error) under favorable acquisition conditions. In the companion article, photometric properties of Martian materials are retrieved using MARS-ReCO and validated using in situ measurements acquired during the Mars Exploration Rovers mission.

Assessment of imaging quality in magnified phase CT of human bone tissue at the nanoscale

NASA Astrophysics Data System (ADS)

Yu, Boliang; Langer, Max; Pacureanu, Alexandra; Gauthier, Remy; Follet, Helene; Mitton, David; Olivier, Cecile; Cloetens, Peter; Peyrin, Francoise

2017-10-01

Bone properties at all length scales have a major impact on the fracture risk in disease such as osteoporosis. However, quantitative 3D data on bone tissue at the cellular scale are still rare. Here we propose to use magnified X-ray phase nano-CT to quantify bone ultra-structure in human bone, on the new setup developed on the beamline ID16A at the ESRF, Grenoble. Obtaining 3D images requires the application of phase retrieval prior to tomographic reconstruction. Phase retrieval is an ill-posed problem for which various approaches have been developed. Since image quality has a strong impact on the further quantification of bone tissue, our aim here is to evaluate different phase retrieval methods for imaging bone samples at the cellular scale. Samples from femurs of female donors were scanned using magnified phase nano-CT at voxel sizes of 120 and 30 nm with an energy of 33 keV. Four CT scans at varying sample-to-detector distances were acquired for each sample. We evaluated three phase retrieval methods adapted to these conditions: Paganin's method at single distance, Paganin's method extended to multiple distances, and the contrast transfer function (CTF) approach for pure phase objects. These methods were used as initialization to an iterative refinement step. Our results based on visual and quantitative assessment show that the use of several distances (as opposed to single one) clearly improves image quality and the two multi-distance phase retrieval methods give similar results. First results on the segmentation of osteocyte lacunae and canaliculi from such images are presented.

Information recovery in propagation-based imaging with decoherence effects

NASA Astrophysics Data System (ADS)

Froese, Heinrich; Lötgering, Lars; Wilhein, Thomas

2017-05-01

During the past decades the optical imaging community witnessed a rapid emergence of novel imaging modalities such as coherent diffraction imaging (CDI), propagation-based imaging and ptychography. These methods have been demonstrated to recover complex-valued scalar wave fields from redundant data without the need for refractive or diffractive optical elements. This renders these techniques suitable for imaging experiments with EUV and x-ray radiation, where the use of lenses is complicated by fabrication, photon efficiency and cost. However, decoherence effects can have detrimental effects on the reconstruction quality of the numerical algorithms involved. Here we demonstrate propagation-based optical phase retrieval from multiple near-field intensities with decoherence effects such as partially coherent illumination, detector point spread, binning and position uncertainties of the detector. Methods for overcoming these systematic experimental errors - based on the decomposition of the data into mutually incoherent modes - are proposed and numerically tested. We believe that the results presented here open up novel algorithmic methods to accelerate detector readout rates and enable subpixel resolution in propagation-based phase retrieval. Further the techniques are straightforward to be extended to methods such as CDI, ptychography and holography.

Discovering relevance knowledge in data: a growing cell structures approach.

PubMed

Azuaje, F; Dubitzky, W; Black, N; Adamson, K

2000-01-01

Both information retrieval and case-based reasoning systems rely on effective and efficient selection of relevant data. Typically, relevance in such systems is approximated by similarity or indexing models. However, the definition of what makes data items similar or how they should be indexed is often nontrivial and time-consuming. Based on growing cell structure artificial neural networks, this paper presents a method that automatically constructs a case retrieval model from existing data. Within the case-based reasoning (CBR) framework, the method is evaluated for two medical prognosis tasks, namely, colorectal cancer survival and coronary heart disease risk prognosis. The results of the experiments suggest that the proposed method is effective and robust. To gain a deeper insight and understanding of the underlying mechanisms of the proposed model, a detailed empirical analysis of the models structural and behavioral properties is also provided.

Information verification and encryption based on phase retrieval with sparsity constraints and optical inference

NASA Astrophysics Data System (ADS)

Zhong, Shenlu; Li, Mengjiao; Tang, Xiajie; He, Weiqing; Wang, Xiaogang

2017-01-01

A novel optical information verification and encryption method is proposed based on inference principle and phase retrieval with sparsity constraints. In this method, a target image is encrypted into two phase-only masks (POMs), which comprise sparse phase data used for verification. Both of the two POMs need to be authenticated before being applied for decrypting. The target image can be optically reconstructed when the two authenticated POMs are Fourier transformed and convolved by the correct decryption key, which is also generated in encryption process. No holographic scheme is involved in the proposed optical verification and encryption system and there is also no problem of information disclosure in the two authenticable POMs. Numerical simulation results demonstrate the validity and good performance of this new proposed method.

A mathematical model of neuro-fuzzy approximation in image classification

NASA Astrophysics Data System (ADS)

Gopalan, Sasi; Pinto, Linu; Sheela, C.; Arun Kumar M., N.

2016-06-01

Image digitization and explosion of World Wide Web has made traditional search for image, an inefficient method for retrieval of required grassland image data from large database. For a given input query image Content-Based Image Retrieval (CBIR) system retrieves the similar images from a large database. Advances in technology has increased the use of grassland image data in diverse areas such has agriculture, art galleries, education, industry etc. In all the above mentioned diverse areas it is necessary to retrieve grassland image data efficiently from a large database to perform an assigned task and to make a suitable decision. A CBIR system based on grassland image properties and it uses the aid of a feed-forward back propagation neural network for an effective image retrieval is proposed in this paper. Fuzzy Memberships plays an important role in the input space of the proposed system which leads to a combined neural fuzzy approximation in image classification. The CBIR system with mathematical model in the proposed work gives more clarity about fuzzy-neuro approximation and the convergence of the image features in a grassland image.

Supervised graph hashing for histopathology image retrieval and classification.

PubMed

Shi, Xiaoshuang; Xing, Fuyong; Xu, KaiDi; Xie, Yuanpu; Su, Hai; Yang, Lin

2017-12-01

In pathology image analysis, morphological characteristics of cells are critical to grade many diseases. With the development of cell detection and segmentation techniques, it is possible to extract cell-level information for further analysis in pathology images. However, it is challenging to conduct efficient analysis of cell-level information on a large-scale image dataset because each image usually contains hundreds or thousands of cells. In this paper, we propose a novel image retrieval based framework for large-scale pathology image analysis. For each image, we encode each cell into binary codes to generate image representation using a novel graph based hashing model and then conduct image retrieval by applying a group-to-group matching method to similarity measurement. In order to improve both computational efficiency and memory requirement, we further introduce matrix factorization into the hashing model for scalable image retrieval. The proposed framework is extensively validated with thousands of lung cancer images, and it achieves 97.98% classification accuracy and 97.50% retrieval precision with all cells of each query image used. Copyright © 2017 Elsevier B.V. All rights reserved.

The prediction of tropopause height from clusters of brightness temperatures and its application in the stratified regression temperature retrievals using microwave and infrared satellite measurements

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Piraino, P.; Jakubowicz, O.

1984-01-01

A total of 1575 radiosondes and the corresponding simulated brightness temperatures were used in an effort to derive a temperature retrieval based on the clusters of brightness temperatures. The 8 simulated channels, namely, 3 MSU and 5 IR of the TIROS-N satellite are used by the GLAS temperature retrieval method. The 3 MSU and 5 IR brightness temperatures were clustered into 17 cluster groups and a regression for the prediction of the tropopause height in mb was generated. The overall r.m.s. for the tropopause prediction is excellent, namely, around 16 mb for the summer and 23 mb for the winter. The correct cluster of brightness temperatures can be identified 98% of the time by the method of discriminatory classification if it is approximately a normal distribution or, in general, by the method of the nearest neighbor.

Method for utilizing properties of the sinc(x) function for phase retrieval on nyquist-under-sampled data

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor); Smith, Jeffrey Scott (Inventor); Aronstein, David L. (Inventor)

2012-01-01

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for simulating propagation of an electromagnetic field, performing phase retrieval, or sampling a band-limited function. A system practicing the method generates transformed data using a discrete Fourier transform which samples a band-limited function f(x) without interpolating or modifying received data associated with the function f(x), wherein an interval between repeated copies in a periodic extension of the function f(x) obtained from the discrete Fourier transform is associated with a sampling ratio Q, defined as a ratio of a sampling frequency to a band-limited frequency, and wherein Q is assigned a value between 1 and 2 such that substantially no aliasing occurs in the transformed data, and retrieves a phase in the received data based on the transformed data, wherein the phase is used as feedback to an optical system.

Improve Biomedical Information Retrieval using Modified Learning to Rank Methods.

PubMed

Xu, Bo; Lin, Hongfei; Lin, Yuan; Ma, Yunlong; Yang, Liang; Wang, Jian; Yang, Zhihao

2016-06-14

In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the problem automatically, providing users with the needed information. However, it is a great challenge to apply these technologies directly for biomedical retrieval, because of the abundance of domain specific terminologies. To enhance biomedical retrieval, we propose a novel framework based on learning to rank. Learning to rank is a series of state-of-the-art information retrieval techniques, and has been proved effective in many information retrieval tasks. In the proposed framework, we attempt to tackle the problem of the abundance of terminologies by constructing ranking models, which focus on not only retrieving the most relevant documents, but also diversifying the searching results to increase the completeness of the resulting list for a given query. In the model training, we propose two novel document labeling strategies, and combine several traditional retrieval models as learning features. Besides, we also investigate the usefulness of different learning to rank approaches in our framework. Experimental results on TREC Genomics datasets demonstrate the effectiveness of our framework for biomedical information retrieval.

Application of an Optimal Estimation Method to the Retrieval of Aerosol Properties Using Multispectral, Multiangle Polarimetric Measurements From the Research Scanning Polarimeter.

NASA Astrophysics Data System (ADS)

Waquet, F.; Cairns, B.; Chowdhary, J.; Knobelspiesse, K.; Mishchenko, M. I.; Travis, L. D.

2006-12-01

Aerosols affect the climate directly by means of reflecting and absorbing sunlight, and indirectly by means of changing the formation and evolution of clouds. The uncertainties associated with these forcing are however highly uncertain, and may add up to be equal in magnitude but opposite in sign to the climate forcing caused by greenhouse gasses. To reduce these uncertainties, accurate retrievals of the effective size of the particles, their complex refractive index and the column number density are required. Intensity-based techniques for aerosol remote sensing from space only partially meet these requirements because they provide reasonable estimates of only the aerosol size distribution and optical thickness, and only over ocean. Laboratory and theoretical studies, on the other hand, show that the multi-angle, multi-spectral behavior of polarization of light scattered by aerosol particles contains sufficient information to provide all the relevant properties of these particles. The Research Scanning Polarimeter (RSP) instrument provides an opportunity to extend such studies to the polarimetric retrieval of aerosol properties from actual remote sensing data. This instrument provides photo-polarimetric measurements of a scene in 152 viewing angles covering an angular range of 120 degrees, and in 9 spectral bands covering a spectral range of 0.41 to 2.25 micrometers. It was recently deployed in the ALIVE field experiment in Oklahoma and the MILAGRO field experiment near Mexico City, in conjunction with many other space-, air-, and ground-based sensors, to study aerosols over land and ocean. The purpose of this study is to use data acquired during these field experiments by the RSP instrument and various other sensors to evaluate a new method for aerosol polarimetry over land. Our approach follows one of the so-called optimal methods described by Rodger (2004) with a few modifications. We describe the optimal method selected and modified for RSP-type data sets, and also how to include the noise and accuracy (including relative angular and relative spectral accuracy) of RSP measurements in the optimal estimate. This approach has been used for aerosol retrievals over ocean, and is now being extended to aerosol retrievals over land since multi-spectral polarized measurements allow the surface and aerosol properties to be retrieved simultaneously, as recently shown in Waquet et al. (2006). We present results of our RSP-based aerosol retrievals and compare them with independent retrievals for various atmospheric conditions that span from low aerosols loads dominated by spherical particles to high aerosol loads dominated by wind blown non-spherical soil particles. This study constitutes an important step in the validation of new algorithms for aerosol remote sensing using polarization measurements in preparation for the GLORY mission.

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Aires, F.; Prigent, C.; Rossow, W. B.; Rothstein, M.; Hansen, James E. (Technical Monitor)

2000-01-01

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Vertical Photon Transport in Cloud Remote Sensing Problems

NASA Technical Reports Server (NTRS)

Platnick, S.

1999-01-01

Photon transport in plane-parallel, vertically inhomogeneous clouds is investigated and applied to cloud remote sensing techniques that use solar reflectance or transmittance measurements for retrieving droplet effective radius. Transport is couched in terms of weighting functions which approximate the relative contribution of individual layers to the overall retrieval. Two vertical weightings are investigated, including one based on the average number of scatterings encountered by reflected and transmitted photons in any given layer. A simpler vertical weighting based on the maximum penetration of reflected photons proves useful for solar reflectance measurements. These weighting functions are highly dependent on droplet absorption and solar/viewing geometry. A superposition technique, using adding/doubling radiative transfer procedures, is derived to accurately determine both weightings, avoiding time consuming Monte Carlo methods. Superposition calculations are made for a variety of geometries and cloud models, and selected results are compared with Monte Carlo calculations. Effective radius retrievals from modeled vertically inhomogeneous liquid water clouds are then made using the standard near-infrared bands, and compared with size estimates based on the proposed weighting functions. Agreement between the two methods is generally within several tenths of a micrometer, much better than expected retrieval accuracy. Though the emphasis is on photon transport in clouds, the derived weightings can be applied to any multiple scattering plane-parallel radiative transfer problem, including arbitrary combinations of cloud, aerosol, and gas layers.

Multivariate Analysis, Retrieval, and Storage System (MARS). Volume 1: MARS System and Analysis Techniques

NASA Technical Reports Server (NTRS)

Hague, D. S.; Vanderberg, J. D.; Woodbury, N. W.

1974-01-01

A method for rapidly examining the probable applicability of weight estimating formulae to a specific aerospace vehicle design is presented. The Multivariate Analysis Retrieval and Storage System (MARS) is comprised of three computer programs which sequentially operate on the weight and geometry characteristics of past aerospace vehicles designs. Weight and geometric characteristics are stored in a set of data bases which are fully computerized. Additional data bases are readily added to the MARS system and/or the existing data bases may be easily expanded to include additional vehicles or vehicle characteristics.

Ontology-Based Retrieval of Spatially Related Objects for Location Based Services

NASA Astrophysics Data System (ADS)

Haav, Hele-Mai; Kaljuvee, Aivi; Luts, Martin; Vajakas, Toivo

Advanced Location Based Service (LBS) applications have to integrate information stored in GIS, information about users' preferences (profile) as well as contextual information and information about application itself. Ontology engineering provides methods to semantically integrate several data sources. We propose an ontology-driven LBS development framework: the paper describes the architecture of ontologies and their usage for retrieval of spatially related objects relevant to the user. Our main contribution is to enable personalised ontology driven LBS by providing a novel approach for defining personalised semantic spatial relationships by means of ontologies. The approach is illustrated by an industrial case study.

Comparison of different methods to retrieve optical-equivalent snow grain size in central Antarctica

NASA Astrophysics Data System (ADS)

Carlsen, Tim; Birnbaum, Gerit; Ehrlich, André; Freitag, Johannes; Heygster, Georg; Istomina, Larysa; Kipfstuhl, Sepp; Orsi, Anaïs; Schäfer, Michael; Wendisch, Manfred

2017-11-01

The optical-equivalent snow grain size affects the reflectivity of snow surfaces and, thus, the local surface energy budget in particular in polar regions. Therefore, the specific surface area (SSA), from which the optical snow grain size is derived, was observed for a 2-month period in central Antarctica (Kohnen research station) during austral summer 2013/14. The data were retrieved on the basis of ground-based spectral surface albedo measurements collected by the COmpact RAdiation measurement System (CORAS) and airborne observations with the Spectral Modular Airborne Radiation measurement sysTem (SMART). The snow grain size and pollution amount (SGSP) algorithm, originally developed to analyze spaceborne reflectance measurements by the MODerate Resolution Imaging Spectroradiometer (MODIS), was modified in order to reduce the impact of the solar zenith angle on the retrieval results and to cover measurements in overcast conditions. Spectral ratios of surface albedo at 1280 and 1100 nm wavelength were used to reduce the retrieval uncertainty. The retrieval was applied to the ground-based and airborne observations and validated against optical in situ observations of SSA utilizing an IceCube device. The SSA retrieved from CORAS observations varied between 27 and 89 m2 kg-1. Snowfall events caused distinct relative maxima of the SSA which were followed by a gradual decrease in SSA due to snow metamorphism and wind-induced transport of freshly fallen ice crystals. The ability of the modified algorithm to include measurements in overcast conditions improved the data coverage, in particular at times when precipitation events occurred and the SSA changed quickly. SSA retrieved from measurements with CORAS and MODIS agree with the in situ observations within the ranges given by the measurement uncertainties. However, SSA retrieved from the airborne SMART data slightly underestimated the ground-based results.

Opinions in Federated Search: University of Lugano at TREC 2014 Federated Web Search Track

DTIC Science & Technology

2014-11-01

Opinions in Federated Search : University of Lugano at TREC 2014 Federated Web Search Track Anastasia Giachanou 1 , Ilya Markov 2 and Fabio Crestani 1...ranking based on sentiment using the retrieval-interpolated diversification method. Keywords: federated search , resource selection, vertical selection...performance. Federated search , also known as Distributed Information Retrieval (DIR), o↵ers the means of simultaneously searching multiple information

Retrieval of an ice water path over the ocean from ISMAR and MARSS millimeter and submillimeter brightness temperatures

NASA Astrophysics Data System (ADS)

Brath, Manfred; Fox, Stuart; Eriksson, Patrick; Chawn Harlow, R.; Burgdorf, Martin; Buehler, Stefan A.

2018-02-01

A neural-network-based retrieval method to determine the snow ice water path (SIWP), liquid water path (LWP), and integrated water vapor (IWV) from millimeter and submillimeter brightness temperatures, measured by using airborne radiometers (ISMAR and MARSS), is presented. The neural networks were trained by using atmospheric profiles from the ICON numerical weather prediction (NWP) model and by radiative transfer simulations using the Atmospheric Radiative Transfer Simulator (ARTS). The basic performance of the retrieval method was analyzed in terms of offset (bias) and the median fractional error (MFE), and the benefit of using submillimeter channels was studied in comparison to pure microwave retrievals. The retrieval is offset-free for SIWP > 0.01 kg m-2, LWP > 0.1 kg m-2, and IWV > 3 kg m-2. The MFE of SIWP decreases from 100 % at SIWP = 0.01 kg m-2 to 20 % at SIWP = 1 kg m-2 and the MFE of LWP from 100 % at LWP = 0.05 kg m-2 to 30 % at LWP = 1 kg m-2. The MFE of IWV for IWV > 3 kg m-2 is 5 to 8 %. The SIWP retrieval strongly benefits from submillimeter channels, which reduce the MFE by a factor of 2, compared to pure microwave retrievals. The IWV and the LWP retrievals also benefit from submillimeter channels, albeit to a lesser degree. The retrieval was applied to ISMAR and MARSS brightness temperatures from FAAM flight B897 on 18 March 2015 of a precipitating frontal system west of the coast of Iceland. Considering the given uncertainties, the retrieval is in reasonable agreement with the SIWP, LWP, and IWV values simulated by the ICON NWP model for that flight. A comparison of the retrieved IWV with IWV from 12 dropsonde measurements shows an offset of 0.5 kg m-2 and an RMS difference of 0.8 kg m-2, showing that the retrieval of IWV is highly effective even under cloudy conditions.

Unsupervised symmetrical trademark image retrieval in soccer telecast using wavelet energy and quadtree decomposition

NASA Astrophysics Data System (ADS)

Ong, Swee Khai; Lim, Wee Keong; Soo, Wooi King

2013-04-01

Trademark, a distinctive symbol, is used to distinguish products or services provided by a particular person, group or organization from other similar entries. As trademark represents the reputation and credit standing of the owner, it is important to differentiate one trademark from another. Many methods have been proposed to identify, classify and retrieve trademarks. However, most methods required features database and sample sets for training prior to recognition and retrieval process. In this paper, a new feature on wavelet coefficients, the localized wavelet energy, is introduced to extract features of trademarks. With this, unsupervised content-based symmetrical trademark image retrieval is proposed without the database and prior training set. The feature analysis is done by an integration of the proposed localized wavelet energy and quadtree decomposed regional symmetrical vector. The proposed framework eradicates the dependence on query database and human participation during the retrieval process. In this paper, trademarks for soccer games sponsors are the intended trademark category. Video frames from soccer telecast are extracted and processed for this study. Reasonably good localization and retrieval results on certain categories of trademarks are achieved. A distinctive symbol is used to distinguish products or services provided by a particular person, group or organization from other similar entries.

Intelligent retrieval of medical images from the Internet

NASA Astrophysics Data System (ADS)

Tang, Yau-Kuo; Chiang, Ted T.

1996-05-01

The object of this study is using Internet resources to provide a cost-effective, user-friendly method to access the medical image archive system and to provide an easy method for the user to identify the images required. This paper describes the prototype system architecture, the implementation, and results. In the study, we prototype the Intelligent Medical Image Retrieval (IMIR) system as a Hypertext Transport Prototype server and provide Hypertext Markup Language forms for user, as an Internet client, using browser to enter image retrieval criteria for review. We are developing the intelligent retrieval engine, with the capability to map the free text search criteria to the standard terminology used for medical image identification. We evaluate retrieved records based on the number of the free text entries matched and their relevance level to the standard terminology. We are in the integration and testing phase. We have collected only a few different types of images for testing and have trained a few phrases to map the free text to the standard medical terminology. Nevertheless, we are able to demonstrate the IMIR's ability to search, retrieve, and review medical images from the archives using general Internet browser. The prototype also uncovered potential problems in performance, security, and accuracy. Additional studies and enhancements will make the system clinically operational.

Towards an Optimal Noise Versus Resolution Trade-Off in Wind Scatterometry

NASA Technical Reports Server (NTRS)

Williams, Brent A.

2011-01-01

A scatterometer is a radar that measures the normalized radar cross section sigma(sup 0) of the Earth's surface. Over the ocean this signal is related to the wind via the geophysical model function (GMF). The objective of wind scatterometry is to estimate the wind vector field from sigma(sup 0) measurements; however, there are many subtleties that complicate this problem-making it difficult to obtain a unique wind field estimate. Conventionally, wind estimation is split into two stages: a wind retrieval stage in which several ambiguous solutions are obtained, and an ambiguity removal stage in which ambiguities are chosen to produce an appropriate wind vector field estimate. The most common approach to wind field estimation is to grid the scatterometer swath into wind vector cells and estimate wind vector ambiguities independently for each cell. Then, field wise structure is imposed on the solution by an ambiguity selection routine. Although this approach is simple and practical, it neglects field wise structure in the retrieval step and does not account for the spatial correlation imposed by the sampling. This makes it difficult to develop a theoretically appropriate noise versus resolution trade-off using pointwise retrieval. Fieldwise structure may be imposed in the retrieval step using a model-based approach. However, this approach is generally only practical if a low order wind field model is applied, which may discard more information than is desired. Furthermore, model-based approaches do not account for the structure imposed by the sampling. A more general fieldwise approach is to estimate all the wind vectors for all the WVCs simultaneously from all the measurements. This approach can account for structure of the wind field as well as structure imposed by the sampling in the wind retrieval step. Williams and Long in 2010 developed a fieldwise retrieval method based on maximum a posteriori estimation (MAP). This MAP approach can be extended to perform a noise versus resolution trade-off, and deal with ambiguity selection. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed.

Applications of cluster analysis to satellite soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.; Kalnay, E.; Piraino, P.

1984-01-01

The advantages of the use of cluster analysis in the improvement of satellite temperature retrievals were evaluated since the use of natural clusters, which are associated with atmospheric temperature soundings characteristic of different types of air masses, has the potential for improving stratified regression schemes in comparison with currently used methods which stratify soundings based on latitude, season, and land/ocean. The method of discriminatory analysis was used. The correct cluster of temperature profiles from satellite measurements was located in 85% of the cases. Considerable improvement was observed at all mandatory levels using regression retrievals derived in the clusters of temperature (weighted and nonweighted) in comparison with the control experiment and with the regression retrievals derived in the clusters of brightness temperatures of 3 MSU and 5 IR channels.

Redundant array of independent disks: practical on-line archiving of nuclear medicine image data.

PubMed

Lear, J L; Pratt, J P; Trujillo, N

1996-02-01

While various methods for long-term archiving of nuclear medicine image data exist, none support rapid on-line search and retrieval of information. We assembled a 90-Gbyte redundant array of independent disks (RAID) system using 10-, 9-Gbyte disk drives. The system was connected to a personal computer and software was used to partition the array into 4-Gbyte sections. All studies (50,000) acquired over a 7-year period were archived in the system. Based on patient name/number and study date, information could be located within 20 seconds and retrieved for display and analysis in less than 5 seconds. RAID offers a practical, redundant method for long-term archiving of nuclear medicine studies that supports rapid on-line retrieval.

The Potential of Clear Sky Carbon Dioxide Satellite Retrievals

NASA Astrophysics Data System (ADS)

Nelson, R.; O'Dell, C.

2013-12-01

It has been shown that neglecting scattering and absorption by aerosols and thin clouds can lead to significant errors in retrievals of the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from space-based measurements of near-infrared reflected sunlight. These clear sky retrievals, which assume no aerosol effects, are desirable because of their high computational efficiency relative to common full physics retrievals. Further, clear sky retrievals may be able to make higher quality measurements relative to the full physics approach because they may introduce fewer potential biases under certain circumstances. These biases can appear when we try to retrieve clouds and aerosols in the full physics methods when there are none actually present. Recent work has shown that intelligent pre-screening can remove soundings with large light-path modifications over ocean surfaces. In this work, we test the hypothesis that intelligent pre-screening of soundings may be successfully used over land surfaces as well as oceans, which would allow clear sky retrievals to be applicable over all surfaces. We also test the hypothesis that major light path modification effects associated with aerosols can be identified based on spectral tests at 0.76, 1.6, and 2 microns. This presentation summarizes our study of both simulated data and satellite observations from the GOSAT instrument in order to assess the effectiveness of using a clear sky retrieval algorithm coupled with intelligent pre-screening to accurately measure carbon dioxide from space-borne instruments.

Creating and indexing teaching files from free-text patient reports.

PubMed Central

Johnson, D. B.; Chu, W. W.; Dionisio, J. D.; Taira, R. K.; Kangarloo, H.

1999-01-01

Teaching files based on real patient data can enhance the education of students, staff and other colleagues. Although information retrieval system can index free-text documents using keywords, these systems do not work well where content bearing terms (e.g., anatomy descriptions) frequently appears. This paper describes a system that uses multi-word indexing terms to provide access to free-text patient reports. The utilization of multi-word indexing allows better modeling of the content of medical reports, thus improving retrieval performance. The method used to select indexing terms as well as early evaluation of retrieval performance is discussed. PMID:10566473

Roogle: an information retrieval engine for clinical data warehouse.

PubMed

Cuggia, Marc; Garcelon, Nicolas; Campillo-Gimenez, Boris; Bernicot, Thomas; Laurent, Jean-François; Garin, Etienne; Happe, André; Duvauferrier, Régis

2011-01-01

High amount of relevant information is contained in reports stored in the electronic patient records and associated metadata. R-oogle is a project aiming at developing information retrieval engines adapted to these reports and designed for clinicians. The system consists in a data warehouse (full-text reports and structured data) imported from two different hospital information systems. Information retrieval is performed using metadata-based semantic and full-text search methods (as Google). Applications may be biomarkers identification in a translational approach, search of specific cases, and constitution of cohorts, professional practice evaluation, and quality control assessment.

Applying CBR to machine tool product configuration design oriented to customer requirements

NASA Astrophysics Data System (ADS)

Wang, Pengjia; Gong, Yadong; Xie, Hualong; Liu, Yongxian; Nee, Andrew Yehching

2017-01-01

Product customization is a trend in the current market-oriented manufacturing environment. However, deduction from customer requirements to design results and evaluation of design alternatives are still heavily reliant on the designer's experience and knowledge. To solve the problem of fuzziness and uncertainty of customer requirements in product configuration, an analysis method based on the grey rough model is presented. The customer requirements can be converted into technical characteristics effectively. In addition, an optimization decision model for product planning is established to help the enterprises select the key technical characteristics under the constraints of cost and time to serve the customer to maximal satisfaction. A new case retrieval approach that combines the self-organizing map and fuzzy similarity priority ratio method is proposed in case-based design. The self-organizing map can reduce the retrieval range and increase the retrieval efficiency, and the fuzzy similarity priority ratio method can evaluate the similarity of cases comprehensively. To ensure that the final case has the best overall performance, an evaluation method of similar cases based on grey correlation analysis is proposed to evaluate similar cases to select the most suitable case. Furthermore, a computer-aided system is developed using MATLAB GUI to assist the product configuration design. The actual example and result on an ETC series machine tool product show that the proposed method is effective, rapid and accurate in the process of product configuration. The proposed methodology provides a detailed instruction for the product configuration design oriented to customer requirements.

Retrieval of NO2 stratospheric profiles from ground-based zenith-sky uv-visible measurements at 60°N

NASA Astrophysics Data System (ADS)

Hendrick, F.; van Roozendael, M.; Lambert, J.-C.; Fayt, C.; Hermans, C.; de Mazière, M.

2003-04-01

Nitrogen dioxide (NO_2) plays an important role in controlling ozone abundances in the stratosphere, either directly through the NOx (NO+NO_2) catalytic cycle, either indirectly by reaction with the radical ClO to form the reservoir species ClONO_2. In this presentation, NO_2 stratospheric profiles are retrieved from ground-based UV-visible NO_2 slant column abundances measured since 1998 at the complementary NDSC station of Harestua (Norway, 60^oN). The retrieval algorithm is based on the Rodgers optimal estimation inversion method and a forward model consisting in the IASB-BIRA stacked box photochemical model PSCBOX coupled to the radiative transfer package UVspec/DISORT. This algorithm has been applied to a set of about 50 sunrises and sunsets for which spatially and temporally coincident NO_2 measurements made by the HALOE (Halogen Occultation Experiment) instrument on board the Upper Atmosphere Research Satellite (UARS) are available. The consistency between retrieved and HALOE profiles is discussed in term of the different seasonal conditions investigated which are spring with and without chlorine activation, summer, and fall.

Information operator approach applied to the retrieval of vertical distributions of atmospheric constituents from ground-based FTIR measurements

NASA Astrophysics Data System (ADS)

Senten, Cindy; de Mazière, Martine; Vanhaelewyn, Gauthier; Vigouroux, Corinne; Delmas, Robert

2010-05-01

The retrieval of information about the vertical distribution of an atmospheric absorber from high spectral resolution ground-based Fourier Transform infrared (FTIR) solar absorption spectra is an important issue in remote sensing. A frequently used technique at present is the optimal estimation method. This work introduces the application of an alternative method, namely the information operator approach (Doicu et al., 2007; Hoogen et al., 1999), for extracting the available information from such FTIR measurements. This approach has been implemented within the well-known retrieval code SFIT2, by adapting the optimal estimation method such as to take into account only the significant contributions to the solution. In particular, we demonstrate the feasibility of the method when applied to ground-based FTIR spectra taken at the southern (sub)tropical site Ile de La Réunion (21° S, 55° E) in 2007. A thorough comparison has been made between the retrieval results obtained with the original optimal estimation method and the ones obtained with the information operator approach, regarding profile and column stability, information content and corresponding full error budget evaluation. This has been done for the target species ozone (O3), methane (CH4), nitrous oxide (N2O), and carbon monoxide (CO). It is shown that the information operator approach performs well and is capable of achieving the same accuracy as optimal estimation, with a gain of stability and with the additional advantage of being less sensitive to the choice of a priori information as well as to the actual signal-to-noise ratio. Keywords: ground-based FTIR, solar absorption spectra, greenhouse gases, information operator approach References Doicu, A., Hilgers, S., von Bargen, A., Rozanov, A., Eichmann, K.-U., von Savigny, C., and Burrows, J.P.: Information operator approach and iterative regularization methods for atmospheric remote sensing, J. Quant. Spectrosc. Radiat. Transfer, 103, 340-350, 2007. Hoogen, R., Rozanov, V.V., and Burrows, J.P.: Ozone profiles from GOME satellite data: description and first validation, J. Geophys. Res., 104(D7), 8263-8280, 1999.

The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds.

PubMed

Miller, Daniel J; Zhang, Zhibo; Ackerman, Andrew S; Platnick, Steven; Baum, Bryan A

2016-04-27

Passive optical retrievals of cloud liquid water path (LWP), like those implemented for Moderate Resolution Imaging Spectroradiometer (MODIS), rely on cloud vertical profile assumptions to relate optical thickness ( τ ) and effective radius ( r e ) retrievals to LWP. These techniques typically assume that shallow clouds are vertically homogeneous; however, an adiabatic cloud model is plausibly more realistic for shallow marine boundary layer cloud regimes. In this study a satellite retrieval simulator is used to perform MODIS-like satellite retrievals, which in turn are compared directly to the large-eddy simulation (LES) output. This satellite simulator creates a framework for rigorous quantification of the impact that vertical profile features have on LWP retrievals, and it accomplishes this while also avoiding sources of bias present in previous observational studies. The cloud vertical profiles from the LES are often more complex than either of the two standard assumptions, and the favored assumption was found to be sensitive to cloud regime (cumuliform/stratiform). Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias LWP retrievals away from adiabatic and toward homogeneous assumptions. The mean bias induced by drizzle-influenced profiles was shown to be on the order of 5-10 g/m 2 . In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is developed to explain variability in LWP retrievals by introducing modifications to the adiabatic r e profile. In addition to analyzing bispectral retrievals, we also compare results with the vertical profile sensitivity of passive polarimetric retrieval techniques.

The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds

PubMed Central

Miller, Daniel J.; Zhang, Zhibo; Ackerman, Andrew S.; Platnick, Steven; Baum, Bryan A.

2018-01-01

Passive optical retrievals of cloud liquid water path (LWP), like those implemented for Moderate Resolution Imaging Spectroradiometer (MODIS), rely on cloud vertical profile assumptions to relate optical thickness (τ) and effective radius (re) retrievals to LWP. These techniques typically assume that shallow clouds are vertically homogeneous; however, an adiabatic cloud model is plausibly more realistic for shallow marine boundary layer cloud regimes. In this study a satellite retrieval simulator is used to perform MODIS-like satellite retrievals, which in turn are compared directly to the large-eddy simulation (LES) output. This satellite simulator creates a framework for rigorous quantification of the impact that vertical profile features have on LWP retrievals, and it accomplishes this while also avoiding sources of bias present in previous observational studies. The cloud vertical profiles from the LES are often more complex than either of the two standard assumptions, and the favored assumption was found to be sensitive to cloud regime (cumuliform/stratiform). Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias LWP retrievals away from adiabatic and toward homogeneous assumptions. The mean bias induced by drizzle-influenced profiles was shown to be on the order of 5–10 g/m2. In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is developed to explain variability in LWP retrievals by introducing modifications to the adiabatic re profile. In addition to analyzing bispectral retrievals, we also compare results with the vertical profile sensitivity of passive polarimetric retrieval techniques. PMID:29637042

Multispectral information for gas and aerosol retrieval from TANSO-FTS instrument

NASA Astrophysics Data System (ADS)

Herbin, H.; Labonnote, L. C.; Dubuisson, P.

2012-11-01

The Greenhouse gases Observing SATellite (GOSAT) mission and in particular TANSO-FTS instrument has the advantage to measure simultaneously the same field of view in different spectral ranges with a high spectral resolution. These features are promising to improve, not only, gaseous retrieval in clear sky or scattering atmosphere, but also to retrieve aerosol parameters. Therefore, this paper is dedicated to an Information Content (IC) analysis of potential synergy between thermal infrared, shortwave infrared and visible, in order to obtain a more accurate retrieval of gas and aerosol. The latter is based on Shannon theory and used a sophisticated radiative transfer algorithm developed at "Laboratoire d'Optique Atmosphérique", dealing with multiple scattering. This forward model can be relied to an optimal estimation method, which allows simultaneously retrieving gases profiles and aerosol granulometry and concentration. The analysis of the information provided by the spectral synergy is based on climatology of dust, volcanic ash and biomass burning aerosols. This work was conducted in order to develop a powerful tool that allows retrieving simultaneously not only the gas concentrations but also the aerosol characteristics by selecting the so called "best channels", i.e. the channels that bring most of the information concerning gas and aerosol. The methodology developed in this paper could also be used to define the specifications of future high spectral resolution mission to reach a given accuracy on retrieved parameters.

A General Uncertainty Quantification Methodology for Cloud Microphysical Property Retrievals

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Chen, X.; Zhao, C.

2014-12-01

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program provides long-term (~20 years) ground-based cloud remote sensing observations. However, there are large uncertainties in the retrieval products of cloud microphysical properties based on the active and/or passive remote-sensing measurements. To address this uncertainty issue, a DOE Atmospheric System Research scientific focus study, Quantification of Uncertainties in Cloud Retrievals (QUICR), has been formed. In addition to an overview of recent progress of QUICR, we will demonstrate the capacity of an observation-based general uncertainty quantification (UQ) methodology via the ARM Climate Research Facility baseline cloud microphysical properties (MICROBASE) product. This UQ method utilizes the Karhunen-Loéve expansion (KLE) and Central Limit Theorems (CLT) to quantify the retrieval uncertainties from observations and algorithm parameters. The input perturbations are imposed on major modes to take into account the cross correlations between input data, which greatly reduces the dimension of random variables (up to a factor of 50) and quantifies vertically resolved full probability distribution functions of retrieved quantities. Moreover, this KLE/CLT approach has the capability of attributing the uncertainties in the retrieval output to individual uncertainty source and thus sheds light on improving the retrieval algorithm and observations. We will present the results of a case study for the ice water content at the Southern Great Plains during an intensive observing period on March 9, 2000. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2001-01-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2000-12-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Spatial Pyramid Covariance based Compact Video Code for Robust Face Retrieval in TV-series.

PubMed

Li, Yan; Wang, Ruiping; Cui, Zhen; Shan, Shiguang; Chen, Xilin

2016-10-10

We address the problem of face video retrieval in TV-series which searches video clips based on the presence of specific character, given one face track of his/her. This is tremendously challenging because on one hand, faces in TV-series are captured in largely uncontrolled conditions with complex appearance variations, and on the other hand retrieval task typically needs efficient representation with low time and space complexity. To handle this problem, we propose a compact and discriminative representation for the huge body of video data, named Compact Video Code (CVC). Our method first models the face track by its sample (i.e., frame) covariance matrix to capture the video data variations in a statistical manner. To incorporate discriminative information and obtain more compact video signature suitable for retrieval, the high-dimensional covariance representation is further encoded as a much lower-dimensional binary vector, which finally yields the proposed CVC. Specifically, each bit of the code, i.e., each dimension of the binary vector, is produced via supervised learning in a max margin framework, which aims to make a balance between the discriminability and stability of the code. Besides, we further extend the descriptive granularity of covariance matrix from traditional pixel-level to more general patchlevel, and proceed to propose a novel hierarchical video representation named Spatial Pyramid Covariance (SPC) along with a fast calculation method. Face retrieval experiments on two challenging TV-series video databases, i.e., the Big Bang Theory and Prison Break, demonstrate the competitiveness of the proposed CVC over state-of-the-art retrieval methods. In addition, as a general video matching algorithm, CVC is also evaluated in traditional video face recognition task on a standard Internet database, i.e., YouTube Celebrities, showing its quite promising performance by using an extremely compact code with only 128 bits.

A method of solving tilt illumination for multiple distance phase retrieval

NASA Astrophysics Data System (ADS)

Guo, Cheng; Li, Qiang; Tan, Jiubin; Liu, Shutian; Liu, Zhengjun

2018-07-01

Multiple distance phase retrieval is a technique of using a series of intensity patterns to reconstruct a complex-valued image of object. However, tilt illumination originating from the off-axis displacement of incident light significantly impairs its imaging quality. To eliminate this affection, we use cross-correlation calibration to estimate oblique angle of incident light and a Fourier-based strategy to correct tilted illumination effect. Compared to other methods, binary and biological object are both stably reconstructed in simulation and experiment. This work provides a simple but beneficial method to solve the problem of tilt illumination for lens-free multi-distance system.

Cloud-property retrieval using merged HIRS and AVHRR data

NASA Technical Reports Server (NTRS)

Baum, Bryan A.; Wielicki, Bruce A.; Minnis, Patrick; Parker, Lindsay

1992-01-01

A technique is developed that uses a multispectral, multiresolution method to improve the overall retrieval of mid- to high-level cloud properties by combining HIRS sounding channel data with higher spatial resolution AVHRR radiometric data collocated with the HIRS footprint. Cirrus cloud radiative and physical properties are determined using satellite data, surface-based measurements provided by rawinsondes and lidar, and aircraft-based lidar data collected during the First International Satellite Cloud Climatology Program Regional Experiment in Wisconsin during the months of October and November 1986. HIRS cloud-height retrievals are compared to ground-based lidar and aircraft lidar when possible. Retrieved cloud heights are found to have close agreement with lidar for thin cloud, but are higher than lidar for optically thick cloud. The results of the reflectance-emittance relationships derived are compared to theoretical scattering model results for both water-droplet spheres and randomly oriented hexagonal ice crystals. It is found that the assumption of 10-micron water droplets is inadequate to describe the reflectance-emittance relationship for the ice clouds seen here. Use of this assumption would lead to lower cloud heights using the ISCCP approach. The theoretical results show that use of hexagonal ice crystal phase functions could lead to much improved results for cloud retrieval algorithms using a bispectral approach.

Potential for Hospital Based Corneal Retreival in Hassan District Hospital

PubMed Central

Melsakkare, Suresh Ramappa; Manipur, Sahana R.; Acharya, Pavana; Ramamurthy, Lakshmi Bomalapura

2015-01-01

Context In developing countries, corneal diseases are the second leading cause of blindness. This corneal blindness can be treated through corneal transplantation. Though the present infrastructure is strong enough to increase keratoplasty numbers at a required rate, India has largest corneal blind population in the world. So a constant supply of high quality donor corneal tissue is the key factor for reduction of prevalence of corneal blindness. Considering the magnitude of corneal blindness and shortage of donor cornea, there is a huge gap in the demand and supply. Aim To study the potential for hospital based retrieval of donor corneal tissue in Hassan district hospital after analysing the indicated and contraindicated causes of deaths, so that hospital corneal retrieval program in Hassan district hospital can be planned. Materials and Methods The cross-sectional, retrospective and record-based study included all hospital deaths with age group more than two years occurred during one year period (January 2014 to December 2014). Data regarding demographic profile, cause of death, treatment given and presence of any systemic diseases were collected. The causes of deaths which are contraindicated for the retrieval of corneas were analysed and noted. The contraindications were based on the NPCB guidelines for standard of eye banking in India 2009. Results Out of 855 deaths, number of deaths in males (565) was greater than females (290). Numbers of deaths were highest between 41-60 years age group (343). Deaths due to HIV, septicaemia, meningitis, encephalitis, disseminated malignancies were contraindicated for corneal retrieval. Corneas could be retrieved from 736 deaths out of 855. Potential for corneal retrieval in a period of one year in Hassan District hospital was 86%. Conclusion Hospital corneal retrieval program has got a great potential to bridge the gap between the need for the cornea and actually collected corneas which will contribute enormously in eliminating corneal blindness. In present study there was 86% potential for corneal retrieval among the hospital deaths. PMID:26435976

The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm: theoretical basis

NASA Astrophysics Data System (ADS)

Loughman, Robert; Bhartia, Pawan K.; Chen, Zhong; Xu, Philippe; Nyaku, Ernest; Taha, Ghassan

2018-05-01

The theoretical basis of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm is presented. The algorithm uses an assumed bimodal lognormal aerosol size distribution to retrieve aerosol extinction profiles at 675 nm from OMPS LP radiance measurements. A first-guess aerosol extinction profile is updated by iteration using the Chahine nonlinear relaxation method, based on comparisons between the measured radiance profile at 675 nm and the radiance profile calculated by the Gauss-Seidel limb-scattering (GSLS) radiative transfer model for a spherical-shell atmosphere. This algorithm is discussed in the context of previous limb-scattering aerosol extinction retrieval algorithms, and the most significant error sources are enumerated. The retrieval algorithm is limited primarily by uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction, which violate the spherical-shell atmosphere assumed in the version 1 algorithm, may also limit the quality of the retrieved aerosol extinction profiles significantly.

Effective material parameter retrieval of anisotropic elastic metamaterials with inherent nonlocality

NASA Astrophysics Data System (ADS)

Lee, Hyung Jin; Lee, Heung Son; Ma, Pyung Sik; Kim, Yoon Young

2016-09-01

In this paper, the scattering (S-) parameter retrieval method is presented specifically for anisotropic elastic metamaterials; so far, no retrieval has been accomplished when elastic metamaterials exhibit fully anisotropic behavior. Complex constitutive property and intrinsic scattering behavior of elastic metamaterials make their characterization far more complicated than that for acoustic and electromagnetic metamaterials. In particular, elastic metamaterials generally exhibit anisotropic scattering behavior due to higher scattering modes associated with shear deformation. They also exhibit nonlocal responses to some degrees, which originate from strong multiple scattering interactions even in the long wavelength limit. Accordingly, the conventional S-parameter retrieval methods cannot be directly used for elastic metamaterials, because they determine only the diagonal components in effective tensor property. Also, the conventional methods simply use the analytic inversion formulae for the material characterization so that inherent nonlocality cannot be taken into account. To establish a retrieval method applicable to anisotropic elastic metamaterials, we propose an alternative S-parameter method to deal with full anisotropy of elastic metamaterials. To retrieve the whole effective anisotropic parameter, we utilize not only normal but also oblique wave incidences. For the retrieval, we first retrieve the ratio of the effective stiffness tensor to effective density and then determine the effective density. The proposed retrieval method is validated by characterizing the effective material parameters of various types of non-resonant anisotropic metamaterials. It is found that the whole effective parameters are retrieved consistently regardless of used retrieval conditions in spite of inherent nonlocality.

Ethnographic Methods in Academic Libraries: A Review

ERIC Educational Resources Information Center

Ramsden, Bryony

2016-01-01

Research in academic libraries has recently seen an increase in the use of ethnographic-based methods to collect data. Primarily used to learn about library users and their interaction with spaces and resources, the methods are proving particularly useful to academic libraries. The data ethnographic methods retrieve is rich, context specific, and…

Similarity estimation for reference image retrieval in mammograms using convolutional neural network

NASA Astrophysics Data System (ADS)

Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

2018-02-01

Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

Testing the MODIS Satellite Retrieval of Aerosol Fine-Mode Fraction

NASA Technical Reports Server (NTRS)

Anderson, Theodore L.; Wu, Yonghua; Chu, D. Allen; Schmid, Beat; Redemann, Jens; Dubovik, Oleg

2005-01-01

Satellite retrievals of the fine-mode fraction (FMF) of midvisible aerosol optical depth, tau, are potentially valuable for constraining chemical transport models and for assessing the global distribution of anthropogenic aerosols. Here we compare satellite retrievals of FMF from the Moderate Resolution Imaging Spectroradiometer (MODIS) to suborbital data on the submicrometer fraction (SMF) of tau. SMF is a closely related parameter that is directly measurable by in situ techniques. The primary suborbital method uses in situ profiling of SMF combined with airborne Sun photometry both to validate the in situ estimate of ambient extinction and to take into account the aerosol above the highest flight level. This method is independent of the satellite retrieval and has well-known accuracy but entails considerable logistical and technical difficulties. An alternate method uses Sun photometer measurements near the surface and an empirical relation between SMF and the Angstrom exponent, A, a measure of the wavelength dependence of optical depth or extinction. Eleven primary and fifteen alternate comparisons are examined involving varying mixtures of dust, sea salt, and pollution in the vicinity of Korea and Japan. MODIS ocean retrievals of FMF are shown to be systematically higher than suborbital estimates of SMF by about 0.2. The most significant cause of this discrepancy involves the relationship between 5 and fine-mode partitioning; in situ measurements indicate a systematically different relationship from what is assumed in the satellite retrievals. Based on these findings, we recommend: (1) satellite programs should concentrate on retrieving and validating since an excellent validation program is in place for doing this, and (2) suborbital measurements should be used to derive relationships between A and fine-mode partitioning to allow interpretation of the satellite data in terms of fine-mode aerosol optical depth.

A rapid place name locating algorithm based on ontology qualitative retrieval, ranking and recommendation

NASA Astrophysics Data System (ADS)

Fan, Hong; Zhu, Anfeng; Zhang, Weixia

2015-12-01

In order to meet the rapid positioning of 12315 complaints, aiming at the natural language expression of telephone complaints, a semantic retrieval framework is proposed which is based on natural language parsing and geographical names ontology reasoning. Among them, a search result ranking and recommended algorithms is proposed which is regarding both geo-name conceptual similarity and spatial geometry relation similarity. The experiments show that this method can assist the operator to quickly find location of 12,315 complaints, increased industry and commerce customer satisfaction.

Case retrieval in medical databases by fusing heterogeneous information.

PubMed

Quellec, Gwénolé; Lamard, Mathieu; Cazuguel, Guy; Roux, Christian; Cochener, Béatrice

2011-01-01

A novel content-based heterogeneous information retrieval framework, particularly well suited to browse medical databases and support new generation computer aided diagnosis (CADx) systems, is presented in this paper. It was designed to retrieve possibly incomplete documents, consisting of several images and semantic information, from a database; more complex data types such as videos can also be included in the framework. The proposed retrieval method relies on image processing, in order to characterize each individual image in a document by their digital content, and information fusion. Once the available images in a query document are characterized, a degree of match, between the query document and each reference document stored in the database, is defined for each attribute (an image feature or a metadata). A Bayesian network is used to recover missing information if need be. Finally, two novel information fusion methods are proposed to combine these degrees of match, in order to rank the reference documents by decreasing relevance for the query. In the first method, the degrees of match are fused by the Bayesian network itself. In the second method, they are fused by the Dezert-Smarandache theory: the second approach lets us model our confidence in each source of information (i.e., each attribute) and take it into account in the fusion process for a better retrieval performance. The proposed methods were applied to two heterogeneous medical databases, a diabetic retinopathy database and a mammography screening database, for computer aided diagnosis. Precisions at five of 0.809 ± 0.158 and 0.821 ± 0.177, respectively, were obtained for these two databases, which is very promising.

Cloud parameters from zenith transmittances measured by sky radiometer at surface: Method development and satellite product validation

NASA Astrophysics Data System (ADS)

Khatri, Pradeep; Hayasaka, Tadahiro; Iwabuchi, Hironobu; Takamura, Tamio; Irie, Hitoshi; Nakajima, Takashi Y.; Letu, Husi; Kai, Qin

2017-04-01

Clouds are known to have profound impacts on atmospheric radiation and water budget, climate change, atmosphere-surface interaction, and so on. Cloud optical thickness (COT) and effective radius (Re) are two fundamental cloud parameters required to study clouds from climatological and hydrological point of view. Large spatial-temporal coverages of those cloud parameters from space observation have proved to be very useful for cloud research; however, validation of space-based products is still a challenging task due to lack of reliable data. Ground-based remote sensing instruments, such as sky radiometers distributed around the world through international observation networks of SKYNET (http://atmos2.cr.chiba-u.jp/skynet/) and AERONET (https://aeronet.gsfc.nasa.gov/) have a great potential to produce ground-truth cloud parameters at different parts of the globe to validate satellite products. Focusing to the sky radiometers of SKYNET and AERONET, a few cloud retrieval methods exists, but those methods have some difficulties to address the problem when cloud is optically thin. It is because the observed transmittances at two wavelengths can be originated from more than one set of COD and Re, and the choice of the most plausible set is difficult. At the same time, calibration issue, especially for the wavelength of near infrared (NIR) region, which is important to retrieve Re, is also a difficult task at present. As a result, instruments need to be calibrated at a high mountain or calibration terms need to be transferred from a standard instrument. Taking those points on account, we developed a new retrieval method emphasizing to overcome above-mentioned difficulties. We used observed transmittances of multiple wavelengths to overcome the first problem. We further proposed a method to obtain calibration constant of NIR wavelength channel using observation data. Our cloud retrieval method is found to produce relatively accurate COD and Re when validated them using data of a narrow field of view radiometer of collocated observation in one SKYNET site. Though the method is developed for the sky radiometer of SKYNET, it can be still used for the sky radiometer of AERONET and other instruments observing spectral zenith transmittances. The proposed retrieval method is then applied to retrieve cloud parameters at key sites of SKYNET within Japan, which are then used to validate cloud products obtained from space observations by MODIS sensors onboard TERRA/AQUA satellites and Himawari 8, a Japanese geostationary satellite. Our analyses suggest the underestimation (overestimation) of COD (Re) from space observations.

Barriers to Retrieving Patient Information from Electronic Health Record Data: Failure Analysis from the TREC Medical Records Track

PubMed Central

Edinger, Tracy; Cohen, Aaron M.; Bedrick, Steven; Ambert, Kyle; Hersh, William

2012-01-01

Objective: Secondary use of electronic health record (EHR) data relies on the ability to retrieve accurate and complete information about desired patient populations. The Text Retrieval Conference (TREC) 2011 Medical Records Track was a challenge evaluation allowing comparison of systems and algorithms to retrieve patients eligible for clinical studies from a corpus of de-identified medical records, grouped by patient visit. Participants retrieved cohorts of patients relevant to 35 different clinical topics, and visits were judged for relevance to each topic. This study identified the most common barriers to identifying specific clinic populations in the test collection. Methods: Using the runs from track participants and judged visits, we analyzed the five non-relevant visits most often retrieved and the five relevant visits most often overlooked. Categories were developed iteratively to group the reasons for incorrect retrieval for each of the 35 topics. Results: Reasons fell into nine categories for non-relevant visits and five categories for relevant visits. Non-relevant visits were most often retrieved because they contained a non-relevant reference to the topic terms. Relevant visits were most often infrequently retrieved because they used a synonym for a topic term. Conclusions: This failure analysis provides insight into areas for future improvement in EHR-based retrieval with techniques such as more widespread and complete use of standardized terminology in retrieval and data entry systems. PMID:23304287

Retrieval of volcanic ash height from satellite-based infrared measurements

NASA Astrophysics Data System (ADS)

Zhu, Lin; Li, Jun; Zhao, Yingying; Gong, He; Li, Wenjie

2017-05-01

A new algorithm for retrieving volcanic ash cloud height from satellite-based measurements is presented. This algorithm, which was developed in preparation for China's next-generation meteorological satellite (FY-4), is based on volcanic ash microphysical property simulation and statistical optimal estimation theory. The MSG satellite's main payload, a 12-channel Spinning Enhanced Visible and Infrared Imager, was used as proxy data to test this new algorithm. A series of eruptions of Iceland's Eyjafjallajökull volcano during April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruption in the Chilean Andes on 16 June 2011 were selected as two typical cases for evaluating the algorithm under various meteorological backgrounds. Independent volcanic ash simulation training samples and satellite-based Cloud-Aerosol Lidar with Orthogonal Polarization data were used as validation data. It is demonstrated that the statistically based volcanic ash height algorithm is able to rapidly retrieve volcanic ash heights, globally. The retrieved ash heights show comparable accuracy with both independent training data and the lidar measurements, which is consistent with previous studies. However, under complicated background, with multilayers in vertical scale, underlying stratus clouds tend to have detrimental effects on the final retrieval accuracy. This is an unresolved problem, like many other previously published methods using passive satellite sensors. Compared with previous studies, the FY-4 ash height algorithm is independent of simultaneous atmospheric profiles, providing a flexible way to estimate volcanic ash height using passive satellite infrared measurements.

An ionospheric occultation inversion technique based on epoch difference

NASA Astrophysics Data System (ADS)

Lin, Jian; Xiong, Jing; Zhu, Fuying; Yang, Jian; Qiao, Xuejun

2013-09-01

Of the ionospheric radio occultation (IRO) electron density profile (EDP) retrievals, the Abel based calibrated TEC inversion (CTI) is the most widely used technique. In order to eliminate the contribution from the altitude above the RO satellite, it is necessary to utilize the calibrated TEC to retrieve the EDP, which introduces the error due to the coplanar assumption. In this paper, a new technique based on the epoch difference inversion (EDI) is firstly proposed to eliminate this error. The comparisons between CTI and EDI have been done, taking advantage of the simulated and real COSMIC data. The following conclusions can be drawn: the EDI technique can successfully retrieve the EDPs without non-occultation side measurements and shows better performance than the CTI method, especially for lower orbit mission; no matter which technique is used, the inversion results at the higher altitudes are better than those at the lower altitudes, which could be explained theoretically.

The contribution of mediator-based deficiencies to age differences in associative learning.

PubMed

Dunlosky, John; Hertzog, Christopher; Powell-Moman, Amy

2005-03-01

Production, mediational, and utilization deficiencies, which describe how strategy use may contribute to developmental trends in episodic memory, have been intensively investigated. Using a mediator report-and-retrieval method, the authors present evidence concerning the degree to which 2 previously unexplored mediator-based deficits--retrieval and decoding deficiencies--account for age deficits in learning. During study, older and younger adults were instructed to use a strategy (imagery or sentence generation) to associate words within paired associates. They also reported each mediator and later attempted to retrieve each response and the mediator produced at study. Substantial deficits occurred in mediator recall, and small differences were observed in decoding mediators. Mediator recall also accounted for a substantial proportion of the age deficits in criterion recall independently of fluid or crystallized intelligence. Discussion focuses on mediator-based deficiencies and their implications for theories of age deficits in episodic memory. Copyright 2005 APA, all rights reserved.

An imager-based multispectral retrieval of above-cloud absorbing aerosol optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2014-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into imager-based cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced for cloud optical thickness retrievals, which are typically derived from the visible or near-IR wavelength channels (effective particle size retrievals are derived from short and mid-wave IR channels that are less affected by aerosol absorption). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple spectral channels in the visible and near- and shortwave-IR. The technique has been applied to MODIS, and retrieval results and statistics, as well as comparisons with other A-Train sensors, are shown.

Content-based unconstrained color logo and trademark retrieval with color edge gradient co-occurrence histograms

NASA Astrophysics Data System (ADS)

Phan, Raymond; Androutsos, Dimitrios

2008-01-01

In this paper, we present a logo and trademark retrieval system for unconstrained color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, and as such, we call this the Color Edge Gradient Co-occurrence Histogram (CEGCH). We use this as the main mechanism for our unconstrained color logo and trademark retrieval scheme. Results illustrate that the proposed retrieval system retrieves logos and trademarks with good accuracy, and outperforms the CECH object detection scheme with higher precision and recall.

Aerosol Optical Depths over Oceans: a View from MISR Retrievals and Collocated MAN and AERONET in Situ Observations

NASA Technical Reports Server (NTRS)

Witek, Marcin L.; Garay, Michael J.; Diner, David J.; Smirnov, Alexander

2013-01-01

In this study, aerosol optical depths over oceans are analyzed from satellite and surface perspectives. Multiangle Imaging SpectroRadiometer (MISR) aerosol retrievals are investigated and validated primarily against Maritime Aerosol Network (MAN) observations. Furthermore, AErosol RObotic NETwork (AERONET) data from 19 island and coastal sites is incorporated in this study. The 270 MISRMAN comparison points scattered across all oceans were identified. MISR on average overestimates aerosol optical depths (AODs) by 0.04 as compared to MAN; the correlation coefficient and root-mean-square error are 0.95 and 0.06, respectively. A new screening procedure based on retrieval region characterization is proposed, which is capable of substantially reducing MISR retrieval biases. Over 1000 additional MISRAERONET comparison points are added to the analysis to confirm the validity of the method. The bias reduction is effective within all AOD ranges. Setting a clear flag fraction threshold to 0.6 reduces the bias to below 0.02, which is close to a typical ground-based measurement uncertainty. Twelve years of MISR data are analyzed with the new screening procedure. The average over ocean AOD is reduced by 0.03, from 0.15 to 0.12. The largest AOD decrease is observed in high latitudes of both hemispheres, regions with climatologically high cloud cover. It is postulated that the screening procedure eliminates spurious retrieval errors associated with cloud contamination and cloud adjacency effects. The proposed filtering method can be used for validating aerosol and chemical transport models.

Multispectral Wavefronts Retrieval in Digital Holographic Three-Dimensional Imaging Spectrometry

NASA Astrophysics Data System (ADS)

Yoshimori, Kyu

2010-04-01

This paper deals with a recently developed passive interferometric technique for retrieving a set of spectral components of wavefronts that are propagating from a spatially incoherent, polychromatic object. The technique is based on measurement of 5-D spatial coherence function using a suitably designed interferometer. By applying signal processing, including aperture synthesis and spectral decomposition, one may obtains a set of wavefronts of different spectral bands. Since each wavefront is equivalent to the complex Fresnel hologram at a particular spectrum of the polychromatic object, application of the conventional Fresnel transform yields 3-D image of different spectrum. Thus, this technique of multispectral wavefronts retrieval provides a new type of 3-D imaging spectrometry based on a fully passive interferometry. Experimental results are also shown to demonstrate the validity of the method.

Developing an A Priori Database for Passive Microwave Snow Water Retrievals Over Ocean

NASA Astrophysics Data System (ADS)

Yin, Mengtao; Liu, Guosheng

2017-12-01

A physically optimized a priori database is developed for Global Precipitation Measurement Microwave Imager (GMI) snow water retrievals over ocean. The initial snow water content profiles are derived from CloudSat Cloud Profiling Radar (CPR) measurements. A radiative transfer model in which the single-scattering properties of nonspherical snowflakes are based on the discrete dipole approximate results is employed to simulate brightness temperatures and their gradients. Snow water content profiles are then optimized through a one-dimensional variational (1D-Var) method. The standard deviations of the difference between observed and simulated brightness temperatures are in a similar magnitude to the observation errors defined for observation error covariance matrix after the 1D-Var optimization, indicating that this variational method is successful. This optimized database is applied in a Bayesian retrieval snow water algorithm. The retrieval results indicated that the 1D-Var approach has a positive impact on the GMI retrieved snow water content profiles by improving the physical consistency between snow water content profiles and observed brightness temperatures. Global distribution of snow water contents retrieved from the a priori database is compared with CloudSat CPR estimates. Results showed that the two estimates have a similar pattern of global distribution, and the difference of their global means is small. In addition, we investigate the impact of using physical parameters to subset the database on snow water retrievals. It is shown that using total precipitable water to subset the database with 1D-Var optimization is beneficial for snow water retrievals.

The influence of learning methods on collaboration: prior repeated retrieval enhances retrieval organization, abolishes collaborative inhibition, and promotes post-collaborative memory.

PubMed

Congleton, Adam R; Rajaram, Suparna

2011-11-01

Research on collaborative memory has unveiled the counterintuitive yet robust phenomenon that collaboration impairs group recall. A candidate explanation for this collaborative inhibition effect is the disruption of people's idiosyncratic retrieval strategies during collaboration, and it is hypothesized that employing methods that improve one's organization protects against retrieval disruption. Here it is investigated how one's learning method during the study phase--defined as either repeatedly studying or repeatedly retrieving information--influences retrieval organization and what effects this has on collaborative recall and post-collaborative individual recall. Results show that repeated retrieval consistently eliminated collaborative inhibition. This enabled participants to gain the most from re-exposure to materials recalled by their partners that they themselves did not recall and led to improvements in their individual memory following collaboration. This repeated retrieval advantage stemmed from the preferential manner in which this learning method strengthened retrieval organization. Findings are also discussed that reveal a relationship between retrieval organization and the interaction observed between learning method and short versus long delay seen in the testing effect literature. Finally, results show that the elusive benefits of cross-cuing during collaboration may be best detected with a longer study-test delay. Together, these findings illuminate when and how collaboration can enhance memory.

Feature hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

Bag-of-features based medical image retrieval via multiple assignment and visual words weighting.

PubMed

Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

2011-11-01

Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights.

Hybrid ontology for semantic information retrieval model using keyword matching indexing system.

PubMed

Uthayan, K R; Mala, G S Anandha

2015-01-01

Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.

Indexing and retrieving motions of characters in close contact.

PubMed

Ho, Edmond S L; Komura, Taku

2009-01-01

Human motion indexing and retrieval are important for animators due to the need to search for motions in the database which can be blended and concatenated. Most of the previous researches of human motion indexing and retrieval compute the Euclidean distance of joint angles or joint positions. Such approaches are difficult to apply for cases in which multiple characters are closely interacting with each other, as the relationships of the characters are not encoded in the representation. In this research, we propose a topology-based approach to index the motions of two human characters in close contact. We compute and encode how the two bodies are tangled based on the concept of rational tangles. The encoded relationships, which we define as TangleList, are used to determine the similarity of the pairs of postures. Using our method, we can index and retrieve motions such as one person piggy-backing another, one person assisting another in walking, and two persons dancing / wrestling. Our method is useful to manage a motion database of multiple characters. We can also produce motion graph structures of two characters closely interacting with each other by interpolating and concatenating topologically similar postures and motion clips, which are applicable to 3D computer games and computer animation.

Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System

PubMed Central

Uthayan, K. R.; Anandha Mala, G. S.

2015-01-01

Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology. PMID:25922851

Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

2017-01-01

Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

Cross Validation of Rain Drop Size Distribution between GPM and Ground Based Polarmetric radar

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Biswas, S.; Le, M.; Chen, H.

2017-12-01

Dual-frequency precipitation radar (DPR) on board the Global Precipitation Measurement (GPM) core satellite has reflectivity measurements at two independent frequencies, Ku- and Ka- band. Dual-frequency retrieval algorithms have been developed traditionally through forward, backward, and recursive approaches. However, these algorithms suffer from "dual-value" problem when they retrieve medium volume diameter from dual-frequency ratio (DFR) in rain region. To this end, a hybrid method has been proposed to perform raindrop size distribution (DSD) retrieval for GPM using a linear constraint of DSD along rain profile to avoid "dual-value" problem (Le and Chandrasekar, 2015). In the current GPM level 2 algorithm (Iguchi et al. 2017- Algorithm Theoretical Basis Document) the Solver module retrieves a vertical profile of drop size distributionn from dual-frequency observations and path integrated attenuations. The algorithm details can be found in Seto et al. (2013) . On the other hand, ground based polarimetric radars have been used for a long time to estimate drop size distributions (e.g., Gorgucci et al. 2002 ). In addition, coincident GPM and ground based observations have been cross validated using careful overpass analysis. In this paper, we perform cross validation on raindrop size distribution retrieval from three sources, namely the hybrid method, the standard products from the solver module and DSD retrievals from ground polarimetric radars. The results are presented from two NEXRAD radars located in Dallas -Fort Worth, Texas (i.e., KFWS radar) and Melbourne, Florida (i.e., KMLB radar). The results demonstrate the ability of DPR observations to produce DSD estimates, which can be used subsequently to generate global DSD maps. References: Seto, S., T. Iguchi, T. Oki, 2013: The basic performance of a precipitation retrieval algorithm for the Global Precipitation Measurement mission's single/dual-frequency radar measurements. IEEE Transactions on Geoscience and Remote Sensing, 51(12), 5239-5251. Gorgucci, E., Chandrasekar, V., Bringi, V. N., and Scarchilli, G.: Estimation of Raindrop Size Distribution Parameters from Polarimetric Radar Measurements, J. Atmos. Sci., 59, 2373-2384, doi:10.1175/1520-0469(2002)0592.0.CO;2, 2002.

Exploiting the synergy between SMAP and SMOS to improve brightness temperature simulations and soil moisture retrievals in arid regions

NASA Astrophysics Data System (ADS)

Ebrahimi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-02-01

The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world. In the current operational algorithm of SMAP (level 2), vegetation water content (VWC) is considered as a proxy to compute VOD which is calculated by an empirical conversion function of NDVI. Avoiding the empirical estimation of VOD, the SMOS algorithm is used to retrieve simultaneously SM and VOD from TB observations. The present study attempted to improve SMAP TB simulations and SM retrievals by benefiting from the advantages of the SMOS (L-MEB) algorithm. This was achieved by using a synergy method based on replacing the default value of SMAP VOD with the retrieved value of VOD from the SMOS multi angular and bi-polarization observations of TB. The insitu SM measurements, used as reference SM in this study, were obtained from the International Soil Moisture Network (ISMN) over 180 stations located in arid regions of the world. Furthermore, four stations were randomly selected to analyze the temporal variations in VOD and SM. Results of the synergy method showed that the accuracy of the TB simulations and SM retrievals was respectively improved at 144 and 124 stations (out of a total of 180 stations) in terms of coefficient of determination (R2) and unbiased root mean squared error (UbRMSE). Analyzing the temporal variations in VOD showed that the SMOS VOD, conversely to the SMAP VOD, can better illustrate the presence of herbaceous plants and may be a better indicator of the seasonal changes in the vegetation density and biomass over the year.

Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

2017-01-01

The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

A joint method to retrieve directional ocean wave spectra from SAR and wave spectrometer data

NASA Astrophysics Data System (ADS)

Ren, Lin; Yang, Jingsong; Zheng, Gang; Wang, Juan

2016-07-01

This paper proposes a joint method to simultaneously retrieve wave spectra at different scales from spaceborne Synthetic Aperture Radar (SAR) and wave spectrometer data. The method combines the output from the two different sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coefficient is estimated using an effective significant wave height (SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coefficient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as first guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length (PWL), and peak wave direction (PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR (ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting (ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.

Improving Lightning and Precipitation Prediction of Severe Convection Using Lightning Data Assimilation With NCAR WRF-RTFDDA

NASA Astrophysics Data System (ADS)

Wang, Haoliang; Liu, Yubao; Cheng, William Y. Y.; Zhao, Tianliang; Xu, Mei; Liu, Yuewei; Shen, Si; Calhoun, Kristin M.; Fierro, Alexandre O.

2017-11-01

In this study, a lightning data assimilation (LDA) scheme was developed and implemented in the National Center for Atmospheric Research Weather Research and Forecasting-Real-Time Four-Dimensional Data Assimilation system. In this LDA method, graupel mixing ratio (qg) is retrieved from observed total lightning. To retrieve qg on model grid boxes, column-integrated graupel mass is first calculated using an observation-based linear formula between graupel mass and total lightning rate. Then the graupel mass is distributed vertically according to the empirical qg vertical profiles constructed from model simulations. Finally, a horizontal spread method is utilized to consider the existence of graupel in the adjacent regions of the lightning initiation locations. Based on the retrieved qg fields, latent heat is adjusted to account for the latent heat releases associated with the formation of the retrieved graupel and to promote convection at the observed lightning locations, which is conceptually similar to the method developed by Fierro et al. Three severe convection cases were studied to evaluate the LDA scheme for short-term (0-6 h) lightning and precipitation forecasts. The simulation results demonstrated that the LDA was effective in improving the short-term lightning and precipitation forecasts by improving the model simulation of the qg fields, updrafts, cold pool, and front locations. The improvements were most notable in the first 2 h, indicating a highly desired benefit of the LDA in lightning and convective precipitation nowcasting (0-2 h) applications.

Quantification of CO emissions from the city of Madrid using MOPITT satellite retrievals and WRF simulations

NASA Astrophysics Data System (ADS)

Dekker, Iris N.; Houweling, Sander; Aben, Ilse; Röckmann, Thomas; Krol, Maarten; Martínez-Alonso, Sara; Deeter, Merritt N.; Worden, Helen M.

2017-12-01

The growth of mega-cities leads to air quality problems directly affecting the citizens. Satellite measurements are becoming of higher quality and quantity, which leads to more accurate satellite retrievals of enhanced air pollutant concentrations over large cities. In this paper, we compare and discuss both an existing and a new method for estimating urban-scale trends in CO emissions using multi-year retrievals from the MOPITT satellite instrument. The first method is mainly based on satellite data, and has the advantage of fewer assumptions, but also comes with uncertainties and limitations as shown in this paper. To improve the reliability of urban-to-regional scale emission trend estimation, we simulate MOPITT retrievals using the Weather Research and Forecast model with chemistry core (WRF-Chem). The difference between model and retrieval is used to optimize CO emissions in WRF-Chem, focusing on the city of Madrid, Spain. This method has the advantage over the existing method in that it allows both a trend analysis of CO concentrations and a quantification of CO emissions. Our analysis confirms that MOPITT is capable of detecting CO enhancements over Madrid, although significant differences remain between the yearly averaged model output and satellite measurements (R2 = 0.75) over the city. After optimization, we find Madrid CO emissions to be lower by 48 % for 2002 and by 17 % for 2006 compared with the EdgarV4.2 emission inventory. The MOPITT-derived emission adjustments lead to better agreement with the European emission inventory TNO-MAC-III for both years. This suggests that the downward trend in CO emissions over Madrid is overestimated in EdgarV4.2 and more realistically represented in TNO-MACC-III. However, our satellite and model based emission estimates have large uncertainties, around 20 % for 2002 and 50 % for 2006.

Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.

PubMed

Hsieh, Jui-Hua; Yin, Shuangye; Wang, Xiang S; Liu, Shubin; Dokholyan, Nikolay V; Tropsha, Alexander

2012-01-23

Poor performance of scoring functions is a well-known bottleneck in structure-based virtual screening (VS), which is most frequently manifested in the scoring functions' inability to discriminate between true ligands vs known nonbinders (therefore designated as binding decoys). This deficiency leads to a large number of false positive hits resulting from VS. We have hypothesized that filtering out or penalizing docking poses recognized as non-native (i.e., pose decoys) should improve the performance of VS in terms of improved identification of true binders. Using several concepts from the field of cheminformatics, we have developed a novel approach to identifying pose decoys from an ensemble of poses generated by computational docking procedures. We demonstrate that the use of target-specific pose (scoring) filter in combination with a physical force field-based scoring function (MedusaScore) leads to significant improvement of hit rates in VS studies for 12 of the 13 benchmark sets from the clustered version of the Database of Useful Decoys (DUD). This new hybrid scoring function outperforms several conventional structure-based scoring functions, including XSCORE::HMSCORE, ChemScore, PLP, and Chemgauss3, in 6 out of 13 data sets at early stage of VS (up 1% decoys of the screening database). We compare our hybrid method with several novel VS methods that were recently reported to have good performances on the same DUD data sets. We find that the retrieved ligands using our method are chemically more diverse in comparison with two ligand-based methods (FieldScreen and FLAP::LBX). We also compare our method with FLAP::RBLB, a high-performance VS method that also utilizes both the receptor and the cognate ligand structures. Interestingly, we find that the top ligands retrieved using our method are highly complementary to those retrieved using FLAP::RBLB, hinting effective directions for best VS applications. We suggest that this integrative VS approach combining cheminformatics and molecular mechanics methodologies may be applied to a broad variety of protein targets to improve the outcome of structure-based drug discovery studies.

Global Contrast Based Salient Region Detection.

PubMed

Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

2015-03-01

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

Secret shared multiple-image encryption based on row scanning compressive ghost imaging and phase retrieval in the Fresnel domain

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2017-09-01

A multiple-image encryption method is proposed that is based on row scanning compressive ghost imaging, (t, n) threshold secret sharing, and phase retrieval in the Fresnel domain. In the encryption process, after wavelet transform and Arnold transform of the target image, the ciphertext matrix can be first detected using a bucket detector. Based on a (t, n) threshold secret sharing algorithm, the measurement key used in the row scanning compressive ghost imaging can be decomposed and shared into two pairs of sub-keys, which are then reconstructed using two phase-only mask (POM) keys with fixed pixel values, placed in the input plane and transform plane 2 of the phase retrieval scheme, respectively; and the other POM key in the transform plane 1 can be generated and updated by the iterative encoding of each plaintext image. In each iteration, the target image acts as the input amplitude constraint in the input plane. During decryption, each plaintext image possessing all the correct keys can be successfully decrypted by measurement key regeneration, compression algorithm reconstruction, inverse wavelet transformation, and Fresnel transformation. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

Analyser-based phase contrast image reconstruction using geometrical optics.

PubMed

Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A

2007-07-21

Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (<100 microm), whilst quantitative phase and attenuation information can be extracted using just two images when the approximations of geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser.

Sensitivity of the RMI's MAGIC/Heliosat-2 method to relevant input data

NASA Astrophysics Data System (ADS)

Demain, C.; Journée, M.; Bertrand, C.

2013-01-01

Appropriate information on solar resources is very important for a variety of technological areas. Based on the potential of retrieving global horizontal irradiance from satellite data, an enhanced version of the Heliosat-2 method has been implemented at the Royal Meteorological Institute of Belgium to estimate surface solar irradiance over Belgium from Meteosat Second Generation at the SEVIRI spatial and temporal resolution. In this contribution, sensitivity of our retrieval scheme to surface albedo, atmospheric aerosol and water vapor contents is investigated. Results indicate that while the use of real-time information instead of climatological values can help to reduce to some extent the RMS error between satellite-retrieved and ground-measured solar irradiance, only the correction of the satellite-derived data with in situ measurements allows to significantly reduce the overall model bias.

Tropospheric nitrogen dioxide column retrieval from ground-based zenith-sky DOAS observations

NASA Astrophysics Data System (ADS)

Tack, F.; Hendrick, F.; Goutail, F.; Fayt, C.; Merlaud, A.; Pinardi, G.; Hermans, C.; Pommereau, J.-P.; Van Roozendael, M.

2015-01-01

We present an algorithm for retrieving tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) from ground-based zenith-sky (ZS) measurements of scattered sunlight. The method is based on a four-step approach consisting of (1) the Differential Optical Absorption Spectroscopy (DOAS) analysis of ZS radiance spectra using a fixed reference spectrum corresponding to low NO2 absorption, (2) the determination of the residual amount in the reference spectrum using a Langley-plot-type method, (3) the removal of the stratospheric content from the daytime total measured slant column based on stratospheric VCDs measured at sunrise and sunset, and simulation of the rapid NO2 diurnal variation, (4) the retrieval of tropospheric VCDs by dividing the resulting tropospheric slant columns by appropriate air mass factors (AMFs). These steps are fully characterized and recommendations are given for each of them. The retrieval algorithm is applied on a ZS dataset acquired with a Multi-AXis (MAX-) DOAS instrument during the Cabauw (51.97° N, 4.93° E, sea level) Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI) held from the 10 June to the 21 July 2009 in the Netherlands. A median value of 7.9 × 1015 molec cm-2 is found for the retrieved tropospheric NO2 VCDs, with maxima up to 6.0 × 1016 molec cm-2. The error budget assessment indicates that the overall error σTVCD on the column values is less than 28%. In case of low tropospheric contribution, σTVCD is estimated to be around 39% and is dominated by uncertainties in the determination of the residual amount in the reference spectrum. For strong tropospheric pollution events, σTVCD drops to approximately 22% with the largest uncertainties on the determination of the stratospheric NO2 abundance and tropospheric AMFs. The tropospheric VCD amounts derived from ZS observations are compared to VCDs retrieved from off-axis and direct-sun measurements of the same MAX-DOAS instrument as well as to data from a co-located Système d'Analyse par Observations Zénithales (SAOZ) spectrometer. The retrieved tropospheric VCDs are in good agreement with the different datasets with correlation coefficients and slopes close to or larger than 0.9. The potential of the presented ZS retrieval algorithm is further demonstrated by its successful application on a 2 year dataset, acquired at the NDACC (Network for the Detection of Atmospheric Composition Change) station Observatoire de Haute Provence (OHP; Southern France).

Tropospheric nitrogen dioxide column retrieval from ground-based zenith-sky DOAS observations

NASA Astrophysics Data System (ADS)

Tack, F.; Hendrick, F.; Goutail, F.; Fayt, C.; Merlaud, A.; Pinardi, G.; Hermans, C.; Pommereau, J.-P.; Van Roozendael, M.

2015-06-01

We present an algorithm for retrieving tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) from ground-based zenith-sky (ZS) measurements of scattered sunlight. The method is based on a four-step approach consisting of (1) the differential optical absorption spectroscopy (DOAS) analysis of ZS radiance spectra using a fixed reference spectrum corresponding to low NO2 absorption, (2) the determination of the residual amount in the reference spectrum using a Langley-plot-type method, (3) the removal of the stratospheric content from the daytime total measured slant column based on stratospheric VCDs measured at sunrise and sunset, and simulation of the rapid NO2 diurnal variation, (4) the retrieval of tropospheric VCDs by dividing the resulting tropospheric slant columns by appropriate air mass factors (AMFs). These steps are fully characterized and recommendations are given for each of them. The retrieval algorithm is applied on a ZS data set acquired with a multi-axis (MAX-) DOAS instrument during the Cabauw (51.97° N, 4.93° E, sea level) Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI) held from 10 June to 21 July 2009 in the Netherlands. A median value of 7.9 × 1015 molec cm-2 is found for the retrieved tropospheric NO2 VCDs, with maxima up to 6.0 × 1016 molec cm-2. The error budget assessment indicates that the overall error σTVCD on the column values is less than 28%. In the case of low tropospheric contribution, σTVCD is estimated to be around 39% and is dominated by uncertainties in the determination of the residual amount in the reference spectrum. For strong tropospheric pollution events, σTVCD drops to approximately 22% with the largest uncertainties on the determination of the stratospheric NO2 abundance and tropospheric AMFs. The tropospheric VCD amounts derived from ZS observations are compared to VCDs retrieved from off-axis and direct-sun measurements of the same MAX-DOAS instrument as well as to data from a co-located Système d'Analyse par Observations Zénithales (SAOZ) spectrometer. The retrieved tropospheric VCDs are in good agreement with the different data sets with correlation coefficients and slopes close to or larger than 0.9. The potential of the presented ZS retrieval algorithm is further demonstrated by its successful application on a 2-year data set, acquired at the NDACC (Network for the Detection of Atmospheric Composition Change) station Observatoire de Haute Provence (OHP; Southern France).

Developing a comprehensive system for content-based retrieval of image and text data from a national survey

NASA Astrophysics Data System (ADS)

Antani, Sameer K.; Natarajan, Mukil; Long, Jonathan L.; Long, L. Rodney; Thoma, George R.

2005-04-01

The article describes the status of our ongoing R&D at the U.S. National Library of Medicine (NLM) towards the development of an advanced multimedia database biomedical information system that supports content-based image retrieval (CBIR). NLM maintains a collection of 17,000 digitized spinal X-rays along with text survey data from the Second National Health and Nutritional Examination Survey (NHANES II). These data serve as a rich data source for epidemiologists and researchers of osteoarthritis and musculoskeletal diseases. It is currently possible to access these through text keyword queries using our Web-based Medical Information Retrieval System (WebMIRS). CBIR methods developed specifically for biomedical images could offer direct visual searching of these images by means of example image or user sketch. We are building a system which supports hybrid queries that have text and image-content components. R&D goals include developing algorithms for robust image segmentation for localizing and identifying relevant anatomy, labeling the segmented anatomy based on its pathology, developing suitable indexing and similarity matching methods for images and image features, and associating the survey text information for query and retrieval along with the image data. Some highlights of the system developed in MATLAB and Java are: use of a networked or local centralized database for text and image data; flexibility to incorporate new research work; provides a means to control access to system components under development; and use of XML for structured reporting. The article details the design, features, and algorithms in this third revision of this prototype system, CBIR3.

Rapid automatic keyword extraction for information retrieval and analysis

DOEpatents

Rose, Stuart J [Richland, WA; Cowley,; E, Wendy [Richland, WA; Crow, Vernon L [Richland, WA; Cramer, Nicholas O [Richland, WA

2012-03-06

Methods and systems for rapid automatic keyword extraction for information retrieval and analysis. Embodiments can include parsing words in an individual document by delimiters, stop words, or both in order to identify candidate keywords. Word scores for each word within the candidate keywords are then calculated based on a function of co-occurrence degree, co-occurrence frequency, or both. Based on a function of the word scores for words within the candidate keyword, a keyword score is calculated for each of the candidate keywords. A portion of the candidate keywords are then extracted as keywords based, at least in part, on the candidate keywords having the highest keyword scores.

Application of the Markov Chain Monte Carlo method for snow water equivalent retrieval based on passive microwave measurements

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Vanderjagt, B. J.

2015-12-01

Markov Chain Monte Carlo (MCMC) method is a retrieval algorithm based on Bayes' rule, which starts from an initial state of snow/soil parameters, and updates it to a series of new states by comparing the posterior probability of simulated snow microwave signals before and after each time of random walk. It is a realization of the Bayes' rule, which gives an approximation to the probability of the snow/soil parameters in condition of the measured microwave TB signals at different bands. Although this method could solve all snow parameters including depth, density, snow grain size and temperature at the same time, it still needs prior information of these parameters for posterior probability calculation. How the priors will influence the SWE retrieval is a big concern. Therefore, in this paper at first, a sensitivity test will be carried out to study how accurate the snow emission models and how explicit the snow priors need to be to maintain the SWE error within certain amount. The synthetic TB simulated from the measured snow properties plus a 2-K observation error will be used for this purpose. It aims to provide a guidance on the MCMC application under different circumstances. Later, the method will be used for the snowpits at different sites, including Sodankyla, Finland, Churchill, Canada and Colorado, USA, using the measured TB from ground-based radiometers at different bands. Based on the previous work, the error in these practical cases will be studied, and the error sources will be separated and quantified.

Wind Shear Identification with the Retrieval Wind of Doppler Wearth Radar

NASA Astrophysics Data System (ADS)

Zhou, S.; Cui, Y.; Zheng, H.; Zhang, T.

2018-05-01

A new method, which based on the wind field retrieval algorithm of Volume Velocity Process (VVP), has been used to identified the intensity of wind shear occurred in a severe convection process in Guangzhou. The intensity of wind shear's strength shown that new cells would be more likely to generate in areas where the magnitude generally larger than 3.0 m/(s*km). Moreover, in the areas of potential areas of rainfall, the wind shear's strength would larger than 4.5 m/(s*km). This wind shear identify method is very helpful to forecasting severe convections' moving and developments.

A scattering-based over-land rainfall retrieval algorithm for South Korea using GCOM-W1/AMSR-2 data

NASA Astrophysics Data System (ADS)

Kwon, Young-Joo; Shin, Hayan; Ban, Hyunju; Lee, Yang-Won; Park, Kyung-Ae; Cho, Jaeil; Park, No-Wook; Hong, Sungwook

2017-08-01

Heavy summer rainfall is a primary natural disaster affecting lives and properties in the Korean Peninsula. This study presents a satellite-based rainfall rate retrieval algorithm for the South Korea combining polarization-corrected temperature ( PCT) and scattering index ( SI) data from the 36.5 and 89.0 GHz channels of the Advanced microwave Scanning Radiometer 2 (AMSR-2) onboard the Global Change Observation Mission (GCOM)-W1 satellite. The coefficients for the algorithm were obtained from spatial and temporal collocation data from the AMSR-2 and groundbased automatic weather station rain gauges from 1 July - 30 August during the years, 2012-2015. There were time delays of about 25 minutes between the AMSR-2 observations and the ground raingauge measurements. A new linearly-combined rainfall retrieval algorithm focused on heavy rain for the PCT and SI was validated using ground-based rainfall observations for the South Korea from 1 July - 30 August, 2016. The validation presented PCT and SI methods showed slightly improved results for rainfall > 5 mm h-1 compared to the current ASMR-2 level 2 data. The best bias and root mean square error (RMSE) for the PCT method at AMSR-2 36.5 GHz were 2.09 mm h-1 and 7.29 mm h-1, respectively, while the current official AMSR-2 rainfall rates show a larger bias and RMSE (4.80 mm h-1 and 9.35 mm h-1, respectively). This study provides a scatteringbased over-land rainfall retrieval algorithm for South Korea affected by stationary front rain and typhoons with the advantages of the previous PCT and SI methods to be applied to a variety of spaceborne passive microwave radiometers.

Relative humidity vertical profiling using lidar-based synergistic methods in the framework of the Hygra-CD campaign

NASA Astrophysics Data System (ADS)

Labzovskii, Lev D.; Papayannis, Alexandros; Binietoglou, Ioannis; Banks, Robert F.; Baldasano, Jose M.; Toanca, Florica; Tzanis, Chris G.; Christodoulakis, John

2018-02-01

Accurate continuous measurements of relative humidity (RH) vertical profiles in the lower troposphere have become a significant scientific challenge. In recent years a synergy of various ground-based remote sensing instruments have been successfully used for RH vertical profiling, which has resulted in the improvement of spatial resolution and, in some cases, of the accuracy of the measurement. Some studies have also suggested the use of high-resolution model simulations as input datasets into RH vertical profiling techniques. In this paper we apply two synergetic methods for RH profiling, including the synergy of lidar with a microwave radiometer and high-resolution atmospheric modeling. The two methods are employed for RH retrieval between 100 and 6000 m with increased spatial resolution, based on datasets from the HygrA-CD (Hygroscopic Aerosols to Cloud Droplets) campaign conducted in Athens, Greece from May to June 2014. RH profiles from synergetic methods are then compared with those retrieved using single instruments or as simulated by high-resolution models. Our proposed technique for RH profiling provides improved statistical agreement with reference to radiosoundings by 27 % when the lidar-radiometer (in comparison with radiometer measurements) approach is used and by 15 % when a lidar model is used (in comparison with WRF-model simulations). Mean uncertainty of RH due to temperature bias in RH profiling was ˜ 4.34 % for the lidar-radiometer and ˜ 1.22 % for the lidar-model methods. However, maximum uncertainty in RH retrievals due to temperature bias showed that lidar-model method is more reliable at heights greater than 2000 m. Overall, our results have demonstrated the capability of both combined methods for daytime measurements in heights between 100 and 6000 m when lidar-radiometer or lidar-WRF combined datasets are available.

Joint aerosol and water-leaving radiance retrieval from Airborne Multi-angle SpectroPolarimeter Imager

NASA Astrophysics Data System (ADS)

Xu, F.; Dubovik, O.; Zhai, P.; Kalashnikova, O. V.; Diner, D. J.

2015-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) [1] has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI typically acquires observations of a target area at 9 view angles between ±67° off the nadir. Its spectral channels are centered at 355, 380, 445, 470*, 555, 660*, and 865* nm, where the asterisk denotes the polarimetric bands. In order to retrieve information from the AirMSPI observations, we developed a efficient and flexible retrieval code that can jointly retrieve aerosol and water leaving radiance simultaneously. The forward model employs a coupled Markov Chain (MC) [2] and adding/doubling [3] radiative transfer method which is fully linearized and integrated with a multi-patch retrieval algorithm to obtain aerosol and water leaving radiance/Chl-a information. Various constraints are imposed to improve convergence and retrieval stability. We tested the aerosol and water leaving radiance retrievals using the AirMSPI radiance and polarization measurements by comparing to the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration to the values reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California. In addition, the MC-based retrievals of aerosol properties were compared with GRASP ([4-5]) retrievals for selected cases. The MC-based retrieval approach was then used to systematically explore the benefits of AirMSPI's ultraviolet and polarimetric channels, the use of multiple view angles, and constraints provided by inclusion of bio-optical models of the water-leaving radiance. References [1]. D. J. Diner, et al. Atmos. Meas. Tech. 6, 1717 (2013). [2]. F. Xu et al. Opt. Lett. 36, 2083 (2011). [3]. J. E. Hansen and L.D. Travis. Space Sci. Rev. 16, 527 (1974). [4]. O. Dubovik et al. Atmos. Meas. Tech., 4, 975 (2011). [5]. O. Dubovik et al. SPIE: Newsroom, DOI:10.1117/2.1201408.005558 (2014).

An oil film information retrieval method overcoming the influence of sun glitter, based on AISA+ airborne hyper-spectral image

NASA Astrophysics Data System (ADS)

Zhan, Yuanzeng; Mao, Tianming; Gong, Fang; Wang, Difeng; Chen, Jianyu

2010-10-01

As an effective survey tool for oil spill detection, the airborne hyper-spectral sensor affords the potentiality for retrieving the quantitative information of oil slick which is useful for the cleanup of spilled oil. But many airborne hyper-spectral images are affected by sun glitter which distorts radiance values and spectral ratios used for oil slick detection. In 2005, there's an oil spill event leaking at oil drilling platform in The South China Sea, and an AISA+ airborne hyper-spectral image recorded this event will be selected for studying in this paper, which is affected by sun glitter terribly. Through a spectrum analysis of the oil and water samples, two features -- "spectral rotation" and "a pair of fixed points" can be found in spectral curves between crude oil film and water. Base on these features, an oil film information retrieval method which can overcome the influence of sun glitter is presented. Firstly, the radiance of the image is converted to normal apparent reflectance (NormAR). Then, based on the features of "spectral rotation" (used for distinguishing oil film and water) and "a pair of fixed points" (used for overcoming the effect of sun glitter), NormAR894/NormAR516 is selected as an indicator of oil film. Finally, by using a threshold combined with the technologies of image filter and mathematic morphology, the distribution and relative thickness of oil film are retrieved.

Two Improved Access Methods on Compact Binary (CB) Trees.

ERIC Educational Resources Information Center

Shishibori, Masami; Koyama, Masafumi; Okada, Makoto; Aoe, Jun-ichi

2000-01-01

Discusses information retrieval and the use of binary trees as a fast access method for search strategies such as hashing. Proposes new methods based on compact binary trees that provide faster access and more compact storage, explains the theoretical basis, and confirms the validity of the methods through empirical observations. (LRW)

Mathematical, Logical, and Formal Methods in Information Retrieval: An Introduction to the Special Issue.

ERIC Educational Resources Information Center

Crestani, Fabio; Dominich, Sandor; Lalmas, Mounia; van Rijsbergen, Cornelis Joost

2003-01-01

Discusses the importance of research on the use of mathematical, logical, and formal methods in information retrieval to help enhance retrieval effectiveness and clarify underlying concepts of information retrieval. Highlights include logic; probability; spaces; and future research needs. (Author/LRW)

Exploring personalized searches using tag-based user profiles and resource profiles in folksonomy.

PubMed

Cai, Yi; Li, Qing; Xie, Haoran; Min, Huaqin

2014-10-01

With the increase in resource-sharing websites such as YouTube and Flickr, many shared resources have arisen on the Web. Personalized searches have become more important and challenging since users demand higher retrieval quality. To achieve this goal, personalized searches need to take users' personalized profiles and information needs into consideration. Collaborative tagging (also known as folksonomy) systems allow users to annotate resources with their own tags, which provides a simple but powerful way for organizing, retrieving and sharing different types of social resources. In this article, we examine the limitations of previous tag-based personalized searches. To handle these limitations, we propose a new method to model user profiles and resource profiles in collaborative tagging systems. We use a normalized term frequency to indicate the preference degree of a user on a tag. A novel search method using such profiles of users and resources is proposed to facilitate the desired personalization in resource searches. In our framework, instead of the keyword matching or similarity measurement used in previous works, the relevance measurement between a resource and a user query (termed the query relevance) is treated as a fuzzy satisfaction problem of a user's query requirements. We implement a prototype system called the Folksonomy-based Multimedia Retrieval System (FMRS). Experiments using the FMRS data set and the MovieLens data set show that our proposed method outperforms baseline methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

The performance of Yonsei CArbon Retrieval (YCAR) algorithm with improved aerosol information using GOSAT measurements over East Asia

NASA Astrophysics Data System (ADS)

Jung, Y.; Kim, J.; Kim, W.; Boesch, H.; Yoshida, Y.; Cho, C.; Lee, H.; Goo, T. Y.

2016-12-01

The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space that can able to improve our knowledge about carbon cycle. Several studies have performed to develop the CO2 retrieval algorithms using GOSAT measurements, but limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. In this study, we develop the Yonsei CArbon Retrieval (YCAR) algorithm based on optimal estimation method to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) and the aerosol top height used to cause significant errors in retrieved XCO2 up to 2.5 ppm. Since this bias comes from a rough assumption of aerosol information in the forward model used in CO2 retrieval process, the YCAR algorithm improves the process to take into account AOPs as well as aerosol vertical distribution; total AOD and the fine mode fraction (FMF) are obtained from the ground-based measurements closely located, and other parameters are obtained from a priori information. Comparing to ground-based XCO2 measurements, the YCAR XCO2 product has a bias of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, showing lower biases and higher correlations rather than the GOSAT standard products. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties.

Photogrammetric Retrieval of Etna's Plume Height from SEVIRI and MODIS

NASA Astrophysics Data System (ADS)

Zaksek, K.; Ganci, G.; Hort, M. K.

2013-12-01

Even remote volcanoes can impact the modern society due to volcanic ash dispersion in the atmosphere. A lot of research is currently dedicated to minimizing the impact of volcanic ash on air traffic. But the ash transport in the atmosphere and its deposition on land and in the oceans may also significantly influence the climate through modifications of atmospheric CO2. The emphasis of this contribution is the retrieval of volcanic ash plume height. This is important information for air traffic, to predict ash transport and to estimate the mass flux of the ejected material. The best way to monitor volcanic ash cloud top height (ACTH) on the global level is using satellite remote sensing. The most commonly used method for satellite ACTH compares brightness temperature of the cloud with the atmospheric temperature profile. Because of well-known uncertainties of this method we propose photogrammetric methods based on the parallax between data retrieved from geostationary (SEVIRI, HRV band; 1000 m spatial resolution) and polar orbiting satellites (MODIS, band 1; 250 m spatial resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously butMODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. ACTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The proposed method has already been tested for the case of the Eyjafjallajökull eruption in April 2010. This case study had almost perfect conditions as the plume was vast and stretching over a homogeneous background - ocean. Here we show results of ACTH estimation during lava fountaining activity of Mount Etna in years 2011-2013. This activity resulted in volcanic ash plumes that are much smaller than the plume observed at Eyjafjallajökull eruption. Challenges and problems occurring while applying the photogrammetric method to small and medium sized plumes will be discussed and solutions to those challenges will be shown.

The absolute radiometric calibration of the advanced very high resolution radiometer

NASA Technical Reports Server (NTRS)

Slater, P. N.; Teillet, P. M.; Ding, Y.

1988-01-01

The need for independent, redundant absolute radiometric calibration methods is discussed with reference to the Thematic Mapper. Uncertainty requirements for absolute calibration of between 0.5 and 4 percent are defined based on the accuracy of reflectance retrievals at an agricultural site. It is shown that even very approximate atmospheric corrections can reduce the error in reflectance retrieval to 0.02 over the reflectance range 0 to 0.4.

Efficient Methods to Assimilate Satellite Retrievals Based on Information Content. Part 2; Suboptimal Retrieval Assimilation

NASA Technical Reports Server (NTRS)

Joiner, J.; Dee, D. P.

1998-01-01

One of the outstanding problems in data assimilation has been and continues to be how best to utilize satellite data while balancing the tradeoff between accuracy and computational cost. A number of weather prediction centers have recently achieved remarkable success in improving their forecast skill by changing the method by which satellite data are assimilated into the forecast model from the traditional approach of assimilating retrievals to the direct assimilation of radiances in a variational framework. The operational implementation of such a substantial change in methodology involves a great number of technical details, e.g., pertaining to quality control procedures, systematic error correction techniques, and tuning of the statistical parameters in the analysis algorithm. Although there are clear theoretical advantages to the direct radiance assimilation approach, it is not obvious at all to what extent the improvements that have been obtained so far can be attributed to the change in methodology, or to various technical aspects of the implementation. The issue is of interest because retrieval assimilation retains many practical and logistical advantages which may become even more significant in the near future when increasingly high-volume data sources become available. The central question we address here is: how much improvement can we expect from assimilating radiances rather than retrievals, all other things being equal? We compare the two approaches in a simplified one-dimensional theoretical framework, in which problems related to quality control and systematic error correction are conveniently absent. By assuming a perfect radiative transfer model and perfect knowledge of radiance and background error covariances, we are able to formulate a nonlinear local error analysis for each assimilation method. Direct radiance assimilation is optimal in this idealized context, while the traditional method of assimilating retrievals is suboptimal because it ignores the cross-covariances between background errors and retrieval errors. We show that interactive retrieval assimilation (where the same background used for assimilation is also used in the retrieval step) is equivalent to direct assimilation of radiances with suboptimal analysis weights. We illustrate and extend these theoretical arguments with several one-dimensional assimilation experiments, where we estimate vertical atmospheric profiles using simulated data from both the High-resolution InfraRed Sounder 2 (HIRS2) and the future Atmospheric InfraRed Sounder (AIRS).

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Marshak, Alexander; Chiu, J. Christine; Wiscombe, Warren J.; Palm, Stephen P.; Davis, Anthony B.; Spangenberg, Douglas A.; Nguyen, Louis; Spinhirne, James D.; Minnis, Patrick

2008-01-01

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

A new randomized Kaczmarz based kernel canonical correlation analysis algorithm with applications to information retrieval.

PubMed

Cai, Jia; Tang, Yi

2018-02-01

Canonical correlation analysis (CCA) is a powerful statistical tool for detecting the linear relationship between two sets of multivariate variables. Kernel generalization of it, namely, kernel CCA is proposed to describe nonlinear relationship between two variables. Although kernel CCA can achieve dimensionality reduction results for high-dimensional data feature selection problem, it also yields the so called over-fitting phenomenon. In this paper, we consider a new kernel CCA algorithm via randomized Kaczmarz method. The main contributions of the paper are: (1) A new kernel CCA algorithm is developed, (2) theoretical convergence of the proposed algorithm is addressed by means of scaled condition number, (3) a lower bound which addresses the minimum number of iterations is presented. We test on both synthetic dataset and several real-world datasets in cross-language document retrieval and content-based image retrieval to demonstrate the effectiveness of the proposed algorithm. Numerical results imply the performance and efficiency of the new algorithm, which is competitive with several state-of-the-art kernel CCA methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Shape Measurement by Means of Phase Retrieval using a Spatial Light Modulator

NASA Astrophysics Data System (ADS)

Agour, Mostafa; Huke, Philipp; Kopylow, Christoph V.; Falldorf, Claas

2010-04-01

We present a novel approach to investigate the shape of a diffusely reflecting technical object. It is based on a combination of a multiple-illumination contouring procedure and phase retrieval from a set of intensity measurements. Special consideration is given to the design of the experimental configuration for phase retrieval and the iterative algorithm to extract the 3D phase map. It is mainly based on a phase-only spatial light modulator (SLM) in the Fourier domain of a 4f-imaging system. The SLM is used to modulate the light incident in the Fourier plane with the transfer function of propagation. Thus, a set of consecutive intensity measurements of the wave field scattered by the investigated object in various propagation states can be realized in a common recording plane. In contrast to already existing methods, no mechanical adjustment is required during the recording process and thus the measuring time is considerably reduced. The method is applied to investigate the shape of micro-objects obtained from a metalforming process. Finally, the experimental results are compared to those provided by a standard interferometric contouring procedure.

[Modeling continuous scaling of NDVI based on fractal theory].

PubMed

Luan, Hai-Jun; Tian, Qing-Jiu; Yu, Tao; Hu, Xin-Li; Huang, Yan; Du, Ling-Tong; Zhao, Li-Min; Wei, Xi; Han, Jie; Zhang, Zhou-Wei; Li, Shao-Peng

2013-07-01

Scale effect was one of the very important scientific problems of remote sensing. The scale effect of quantitative remote sensing can be used to study retrievals' relationship between different-resolution images, and its research became an effective way to confront the challenges, such as validation of quantitative remote sensing products et al. Traditional up-scaling methods cannot describe scale changing features of retrievals on entire series of scales; meanwhile, they are faced with serious parameters correction issues because of imaging parameters' variation of different sensors, such as geometrical correction, spectral correction, etc. Utilizing single sensor image, fractal methodology was utilized to solve these problems. Taking NDVI (computed by land surface radiance) as example and based on Enhanced Thematic Mapper Plus (ETM+) image, a scheme was proposed to model continuous scaling of retrievals. Then the experimental results indicated that: (a) For NDVI, scale effect existed, and it could be described by fractal model of continuous scaling; (2) The fractal method was suitable for validation of NDVI. All of these proved that fractal was an effective methodology of studying scaling of quantitative remote sensing.

Selectively Encrypted Pull-Up Based Watermarking of Biometric data

NASA Astrophysics Data System (ADS)

Shinde, S. A.; Patel, Kushal S.

2012-10-01

Biometric authentication systems are becoming increasingly popular due to their potential usage in information security. However, digital biometric data (e.g. thumb impression) are themselves vulnerable to security attacks. There are various methods are available to secure biometric data. In biometric watermarking the data are embedded in an image container and are only retrieved if the secrete key is available. This container image is encrypted to have more security against the attack. As wireless devices are equipped with battery as their power supply, they have limited computational capabilities; therefore to reduce energy consumption we use the method of selective encryption of container image. The bit pull-up-based biometric watermarking scheme is based on amplitude modulation and bit priority which reduces the retrieval error rate to great extent. By using selective Encryption mechanism we expect more efficiency in time at the time of encryption as well as decryption. Significant reduction in error rate is expected to be achieved by the bit pull-up method.

Novel citation-based search method for scientific literature: application to meta-analyses.

PubMed

Janssens, A Cecile J W; Gwinn, M

2015-10-13

Finding eligible studies for meta-analysis and systematic reviews relies on keyword-based searching as the gold standard, despite its inefficiency. Searching based on direct citations is not sufficiently comprehensive. We propose a novel strategy that ranks articles on their degree of co-citation with one or more "known" articles before reviewing their eligibility. In two independent studies, we aimed to reproduce the results of literature searches for sets of published meta-analyses (n = 10 and n = 42). For each meta-analysis, we extracted co-citations for the randomly selected 'known' articles from the Web of Science database, counted their frequencies and screened all articles with a score above a selection threshold. In the second study, we extended the method by retrieving direct citations for all selected articles. In the first study, we retrieved 82% of the studies included in the meta-analyses while screening only 11% as many articles as were screened for the original publications. Articles that we missed were published in non-English languages, published before 1975, published very recently, or available only as conference abstracts. In the second study, we retrieved 79% of included studies while screening half the original number of articles. Citation searching appears to be an efficient and reasonably accurate method for finding articles similar to one or more articles of interest for meta-analysis and reviews.

Measuring Gap Fraction, Element Clumping Index and LAI in Sierra Forest Stands Using a Full-Waveform Ground-Based Lidar

NASA Technical Reports Server (NTRS)

Zhao, Feng; Strahler, Alan H.; Crystal L. Schaaf; Yao, Tian; Yang, Xiaoyuan; Wang, Zhuosen; Schull, Mitchell A.; Roman, Miguel O.; Woodcock, Curtis E.; Olofsson, Pontus;

Simultaneous retrieval of the solar EUV flux and neutral thermospheric O, O2, N2, and temperature from twilight airglow

NASA Technical Reports Server (NTRS)

Fennelly, J. A.; Torr, D. G.; Richards, P. G.; Torr, M. R.

1994-01-01

We present a method to retrieve neutral thermospheric composition and the solar EUV flux from ground-based twilight optical measurements of the O(+) ((exp 2)P) 7320 A and O((exp 1)D) 6300 A airglow emissions. The parameters retrieved are the neutral temperature, the O, O2, N2 density profiles, and a scaling factor for the solar EUV flux spectrum. The temperature, solar EUV flux scaling factor, and atomic oxygen density are first retrieved from the 7320-A emission, which are then used with the 6300-A emission to retrieve the O2 and N2 densities. The retrieval techniques have been verified by computer simulations. We have shown that the retrieval technique is able to statistically retrieve values, between 200 and 400 km, within an average error of 3.1 + or - 0.6% for thermospheric temperature, 3.3 + or - 2.0% for atomic oxygen, 2.3 + or - 1.3% for molecular oxygen, and 2.4 + or - 1.3% for molecular nitrogen. The solar EUV flux scaling factor was found to have a retrieval error of 5.1 + or - 2.3%. All the above errors have a confidence level of 95%. The purpose of this paper is to prove the viability and usefulness of the retrieval technique by demonstrating the ability to retrieve known quantities under a realistic simulation of the measurement process, excluding systematic effects.

Triple-frequency radar retrievals of snowfall properties from the OLYMPEX field campaign

NASA Astrophysics Data System (ADS)

Leinonen, J. S.; Lebsock, M. D.; Sy, O. O.; Tanelli, S.

2017-12-01

Retrieval of snowfall properties with radar is subject to significant errors arising from the uncertainties in the size and structure of snowflakes. Recent modeling and theoretical studies have shown that multi-frequency radars can potentially constrain the microphysical properties and thus reduce the uncertainties in the retrieved snow water content. So far, there have only been limited efforts to leverage the theoretical advances in actual snowfall retrievals. In this study, we have implemented an algorithm that retrieves the snowfall properties from triple-frequency radar data using the radar scattering properties from a combination of snowflake scattering databases, which were derived using numerical scattering methods. Snowflake number concentration, characteristic size and density are derived using a combination of optimal estimation and Kalman smoothing; the snow water content and other bulk properties are then derived from these. The retrieval framework is probabilistic and thus naturally provides error estimates for the retrieved quantities. We tested the retrieval algorithm using data from the APR3 airborne radar flown onboard the NASA DC-8 aircraft during the Olympic Mountain Experiment (OLYMPEX) in late 2015. We demonstrated consistent retrieval of snow properties and smooth transition from single- and dual-frequency retrievals to using all three frequencies simultaneously. The error analysis shows that the retrieval accuracy is improved when additional frequencies are introduced. We also compare the findings to in situ measurements of snow properties as well as measurements by polarimetric ground-based radar.

3D model retrieval method based on mesh segmentation

NASA Astrophysics Data System (ADS)

Gan, Yuanchao; Tang, Yan; Zhang, Qingchen

2012-04-01

In the process of feature description and extraction, current 3D model retrieval algorithms focus on the global features of 3D models but ignore the combination of global and local features of the model. For this reason, they show less effective performance to the models with similar global shape and different local shape. This paper proposes a novel algorithm for 3D model retrieval based on mesh segmentation. The key idea is to exact the structure feature and the local shape feature of 3D models, and then to compares the similarities of the two characteristics and the total similarity between the models. A system that realizes this approach was built and tested on a database of 200 objects and achieves expected results. The results show that the proposed algorithm improves the precision and the recall rate effectively.

Content based image retrieval using local binary pattern operator and data mining techniques.

PubMed

Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

2015-01-01

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

Practical quantum retrieval games

NASA Astrophysics Data System (ADS)

Arrazola, Juan Miguel; Karasamanis, Markos; Lütkenhaus, Norbert

2016-06-01

Complex cryptographic protocols are often constructed from simpler building blocks. In order to advance quantum cryptography, it is important to study practical building blocks that can be used to develop new protocols. An example is quantum retrieval games (QRGs), which have broad applicability and have already been used to construct quantum money schemes. In this work, we introduce a general construction of quantum retrieval games based on the hidden matching problem and show how they can be implemented in practice using available technology. More precisely, we provide a general method to construct (1-out-of-k ) QRGs, proving that their cheating probabilities decrease exponentially in k . In particular, we define QRGs based on coherent states of light, which can be implemented even in the presence of experimental imperfections. Our results constitute a tool in the arsenal of the practical quantum cryptographer.

Coupled binary embedding for large-scale image retrieval.

PubMed

Zheng, Liang; Wang, Shengjin; Tian, Qi

2014-08-01

Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

Characterization of freshly retrieved preantral follicles using a low-invasive, mechanical isolation method extended to different ruminant species.

PubMed

Langbeen, A; Jorssen, E P A; Fransen, E; Rodriguez, A P A; García, M Chong; Leroy, J L M R; Bols, P E J

2015-10-01

Due to the increased interest in preantral follicular physiology, non-invasive retrieval and morphological classification are crucial. Therefore, this study aimed: (1) to standardize a minimally invasive isolation protocol, applicable to three ruminant species; (2) to morphologically classify preantral follicles upon retrieval; and (3) to describe morphological features of freshly retrieved follicles compared with follicle characteristics using invasive methods. Bovine, caprine and ovine ovarian cortex strips were retrieved from slaughterhouse ovaries and dispersed. This suspension was filtered, centrifuged, re-suspended and transferred to a Petri dish, to which 0.025 mg/ml neutral red (NR) was added to assess the viability of the isolated follicles. Between 59 and 191 follicles per follicle class and per species were collected and classified by light microscopy, based on follicular cell morphology. Subsequently, follicle diameters were measured. The proposed isolation protocol was applicable to all three species and showed a significant, expected increase in diameter with developmental stage. With an average diameter of 37 ± 5 μm for primordial follicles, 47 ± 6.3 μm for primary follicles and 67.1 ± 13.1 μm for secondary follicles, no significant difference in diameter among the three species was observed. Bovine, caprine and ovine follicles (63, 59 and 50% respectively) were graded as viable upon retrieval. Using the same morphological characteristics as determined by invasive techniques [e.g. haematoxylin-eosin (HE) sections], cumulus cell morphology and follicle diameter could be used routinely to classify freshly retrieved follicles. Finally, we applied a mechanical, minimally invasive, follicle isolation protocol and extended it to three ruminant species, yielding viable preantral follicles without compromising further in vitro processing and allowing routine follicle characterization upon retrieval.

Retrievals of Surface Air Temperature Using Multiple Satellite Data Combinations over Complex Terrain in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Jang, K.; Won, M.; Yoon, S.; Lim, J.

2016-12-01

Surface air temperature (Tair) is a fundamental factor for terrestrial environments and plays a major role in the fields of applied meteorology, climatology, and ecology. The satellite remotely sensed data offers the opportunity to estimate Tair on the earth's surface with high spatial and temporal resolutions. The Moderate Resolution Imaging Spectroradiometer (MODIS) provides effective Tair retrievals although restricted to clear sky condition. MODIS Tair over complex terrain can result in significant retrieval errors due to the retrieval height mismatch to the elevation of local weather stations. In this study, we propose the methodology to estimate Tair over complex terrain for all sky conditions using multiple satellite data fusion based on the pixel-wise regression method. The combination of synergistic information from MODIS Tair and the brightness temperature (Tb) retrievals at 37 GHz frequency from the satellite microwave sensor were used for analysis. The air temperature lapse rate was applied to estimate the near-surface Tair considering the complex terrain such as mountainous regions. The retrieval results produced from this study showed a good agreement (RMSE < 2.5 K) with weather measurements from the Korea Forest Service (KFS) for mountain regions and the Korea Meteorology Administration (KMA). The gaps in the MODIS Tair data due to cloud contamination were successfully filled using the proposed method which yielded similar accuracy as retrievals of clear sky. The results of this study indicate that the satellite data fusion can continuously produce Tair retrievals with reasonable accuracy and that the application of the temperature lapse rate can lead to improvement of the reliability over complex terrains such as the Korean Peninsula.

The influence of sea fog inhomogeneity on its microphysical characteristics retrieval

NASA Astrophysics Data System (ADS)

Hao, Zengzhou; Pan, Delu; Gong, Fang; He, Xianqiang

2008-10-01

A study on the effect of sea fog inhomogeneity on its microphysical parameters retrieval is presented. On the condition that the average liquid water content is linear vertically and the power spectrum spectral index sets 2.0, we generate a 3D sea fog fields by controlling the total liquid water contents greater than 0.04g/m3 based on the iterative method for generating scaling log-normal random field with an energy spectrum and a fragmentized cloud algorithm. Based on the fog field, the radiance at the wavelengths of 0.67 and 1.64 μm are simulated with 3D radiative transfer model SHDOM, and then the fog optical thickness and effective particle radius are simultaneously retrieved using the generic look-up-table AVHRR cloud algorithm. By comparing those fog optical thickness and effective particle radius, the influence of sea fog inhomogeneity on its properties retrieval is discussed. It exhibits the system bias when inferring sea fog physical properties from satellite measurements based on the assumption of plane parallel homogeneous atmosphere. And the bias depends on the solar zenith angel. The optical thickness is overrated while the effective particle radius is under-estimated at two solar zenith angle 30° and 60°. Those results show that it is necessary for sea fog true characteristics retrieval to develop a new algorithm using the 3D radiative transfer.

Treelets Binary Feature Retrieval for Fast Keypoint Recognition.

PubMed

Zhu, Jianke; Wu, Chenxia; Chen, Chun; Cai, Deng

2015-10-01

Fast keypoint recognition is essential to many vision tasks. In contrast to the classification-based approaches, we directly formulate the keypoint recognition as an image patch retrieval problem, which enjoys the merit of finding the matched keypoint and its pose simultaneously. To effectively extract the binary features from each patch surrounding the keypoint, we make use of treelets transform that can group the highly correlated data together and reduce the noise through the local analysis. Treelets is a multiresolution analysis tool, which provides an orthogonal basis to reflect the geometry of the noise-free data. To facilitate the real-world applications, we have proposed two novel approaches. One is the convolutional treelets that capture the image patch information locally and globally while reducing the computational cost. The other is the higher-order treelets that reflect the relationship between the rows and columns within image patch. An efficient sub-signature-based locality sensitive hashing scheme is employed for fast approximate nearest neighbor search in patch retrieval. Experimental evaluations on both synthetic data and the real-world Oxford dataset have shown that our proposed treelets binary feature retrieval methods outperform the state-of-the-art feature descriptors and classification-based approaches.

Latent Heating Retrieval from TRMM Observations Using a Simplified Thermodynamic Model

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Olson, William S.

2003-01-01

A procedure for the retrieval of hydrometeor latent heating from TRMM active and passive observations is presented. The procedure is based on current methods for estimating multiple-species hydrometeor profiles from TRMM observations. The species include: cloud water, cloud ice, rain, and graupel (or snow). A three-dimensional wind field is prescribed based on the retrieved hydrometeor profiles, and, assuming a steady-state, the sources and sinks in the hydrometeor conservation equations are determined. Then, the momentum and thermodynamic equations, in which the heating and cooling are derived from the hydrometeor sources and sinks, are integrated one step forward in time. The hydrometeor sources and sinks are reevaluated based on the new wind field, and the momentum and thermodynamic equations are integrated one more step. The reevalution-integration process is repeated until a steady state is reached. The procedure is tested using cloud model simulations. Cloud-model derived fields are used to synthesize TRMM observations, from which hydrometeor profiles are derived. The procedure is applied to the retrieved hydrometeor profiles, and the latent heating estimates are compared to the actual latent heating produced by the cloud model. Examples of procedure's applications to real TRMM data are also provided.

Toward an Episodic Context Account of Retrieval-Based Learning: Dissociating Retrieval Practice and Elaboration

ERIC Educational Resources Information Center

Lehman, Melissa; Smith, Megan A.; Karpicke, Jeffrey D.

2014-01-01

We tested the predictions of 2 explanations for retrieval-based learning; while the elaborative retrieval hypothesis assumes that the retrieval of studied information promotes the generation of semantically related information, which aids in later retrieval (Carpenter, 2009), the episodic context account proposed by Karpicke, Lehman, and Aue (in…

Evaluation of a simple method for the automatic assignment of MeSH descriptors to health resources in a French online catalogue.

PubMed

Névéol, Aurélie; Pereira, Suzanne; Kerdelhué, Gaetan; Dahamna, Badisse; Joubert, Michel; Darmoni, Stéfan J

2007-01-01

The growing number of resources to be indexed in the catalogue of online health resources in French (CISMeF) calls for curating strategies involving automatic indexing tools while maintaining the catalogue's high indexing quality standards. To develop a simple automatic tool that retrieves MeSH descriptors from documents titles. In parallel to research on advanced indexing methods, a bag-of-words tool was developed for timely inclusion in CISMeF's maintenance system. An evaluation was carried out on a corpus of 99 documents. The indexing sets retrieved by the automatic tool were compared to manual indexing based on the title and on the full text of resources. 58% of the major main headings were retrieved by the bag-of-words algorithm and the precision on main heading retrieval was 69%. Bag-of-words indexing has effectively been used on selected resources to be included in CISMeF since August 2006. Meanwhile, on going work aims at improving the current version of the tool.

Sensitivity Analysis for Atmospheric Infrared Sounder (AIRS) CO2 Retrieval

NASA Technical Reports Server (NTRS)

Gat, Ilana

2012-01-01

The Atmospheric Infrared Sounder (AIRS) is a thermal infrared sensor able to retrieve the daily atmospheric state globally for clear as well as partially cloudy field-of-views. The AIRS spectrometer has 2378 channels sensing from 15.4 micrometers to 3.7 micrometers, of which a small subset in the 15 micrometers region has been selected, to date, for CO2 retrieval. To improve upon the current retrieval method, we extended the retrieval calculations to include a prior estimate component and developed a channel ranking system to optimize the channels and number of channels used. The channel ranking system uses a mathematical formalism to rapidly process and assess the retrieval potential of large numbers of channels. Implementing this system, we identifed a larger optimized subset of AIRS channels that can decrease retrieval errors and minimize the overall sensitivity to other iridescent contributors, such as water vapor, ozone, and atmospheric temperature. This methodology selects channels globally by accounting for the latitudinal, longitudinal, and seasonal dependencies of the subset. The new methodology increases accuracy in AIRS CO2 as well as other retrievals and enables the extension of retrieved CO2 vertical profiles to altitudes ranging from the lower troposphere to upper stratosphere. The extended retrieval method for CO2 vertical profile estimation using a maximum-likelihood estimation method. We use model data to demonstrate the beneficial impact of the extended retrieval method using the new channel ranking system on CO2 retrieval.

Complex dark-field contrast and its retrieval in x-ray phase contrast imaging implemented with Talbot interferometry.

PubMed

Yang, Yi; Tang, Xiangyang

2014-10-01

Under the existing theoretical framework of x-ray phase contrast imaging methods implemented with Talbot interferometry, the dark-field contrast refers to the reduction in interference fringe visibility due to small-angle x-ray scattering of the subpixel microstructures of an object to be imaged. This study investigates how an object's subpixel microstructures can also affect the phase of the intensity oscillations. Instead of assuming that the object's subpixel microstructures distribute in space randomly, the authors' theoretical derivation starts by assuming that an object's attenuation projection and phase shift vary at a characteristic size that is not smaller than the period of analyzer grating G₂ and a characteristic length dc. Based on the paraxial Fresnel-Kirchhoff theory, the analytic formulae to characterize the zeroth- and first-order Fourier coefficients of the x-ray irradiance recorded at each detector cell are derived. Then the concept of complex dark-field contrast is introduced to quantify the influence of the object's microstructures on both the interference fringe visibility and the phase of intensity oscillations. A method based on the phase-attenuation duality that holds for soft tissues and high x-ray energies is proposed to retrieve the imaginary part of the complex dark-field contrast for imaging. Through computer simulation study with a specially designed numerical phantom, they evaluate and validate the derived analytic formulae and the proposed retrieval method. Both theoretical analysis and computer simulation study show that the effect of an object's subpixel microstructures on x-ray phase contrast imaging method implemented with Talbot interferometry can be fully characterized by a complex dark-field contrast. The imaginary part of complex dark-field contrast quantifies the influence of the object's subpixel microstructures on the phase of intensity oscillations. Furthermore, at relatively high energies, for soft tissues it can be retrieved for imaging with a method based on the phase-attenuation duality. The analytic formulae derived in this work to characterize the complex dark-field contrast in x-ray phase contrast imaging method implemented with Talbot interferometry are of significance, which may initiate more activities in the research and development of x-ray differential phase contrast imaging for extensive biomedical applications.

Retrieval of Understory NDVI in Sparse Boreal Forests By MODIS Brdf Data

NASA Astrophysics Data System (ADS)

Yang, W.; Kobayashi, H.; Suzuki, R.; Nasahara, K. N.

2014-12-01

Global products of leaf area index (LAI) usually show large uncertainties in sparsely vegetated areas. The reason is that the understory contribution is not negligible in reflectance modeling for the case of low to intermediate canopy cover. Therefore many efforts have been carried out on inclusion of understory properties in the LAI estimation algorithms. Compared with conventional data bank method, estimation of forest understory property from satellite data is superior in the studies at global or continental scale during a long periods. However, the existing remote sensing method based on multi-angular observations is very complicated to implement. Alternatively, a simple method to retrieve understory NDVI (NDVIu) for sparse boreal forests was proposed in this study. The method is based on the property that the bi-directional variation of NDVIu is much smaller than that of the canopy-level NDVI. To retrieve NDVIu for a certain pixel, linear extrapolation was applied using the pixels within a 5×5 target-pixel-centered window. The NDVI values were reconstructed from the MODIS BRDF data corresponding to eight different solar-view angles. NDVIu was estimated as the average of the NDVI values corresponding to the position where the stand NDVI has the smallest angular variation. Validation by noise-free simulation dataset yielded high agreement between estimated and true NDVIu with R2 and RMSE of 0.99 and 0.03, respectively. By the MODIS BRDF data, we got the estimate of NDVIu close to the in situ measured value (0.61 vs. 0.66 for estimate and measurement, respectively), and also reasonable seasonal patterns of NDVIu in 2010-2013. The results imply a potential application of the retrieved NDVIu to improve the estimation of overstory LAI for sparse boreal forests.

System engineering approach to GPM retrieval algorithms

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

Rose, C. R.; Chandrasekar, V.

2004-01-01

System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Groundmore » validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do calculated at each bin, the rain rate can then be calculated based on a suitable rain-rate model. This paper develops a system engineering interface to the retrieval algorithms while remaining cognizant of system engineering issues so that it can be used to bridge the divide between algorithm physics an d overall mission requirements. Additionally, in line with the systems approach, a methodology is developed such that the measurement requirements pass through the retrieval model and other subsystems and manifest themselves as measurement and other system constraints. A systems model has been developed for the retrieval algorithm that can be evaluated through system-analysis tools such as MATLAB/Simulink.« less

Retrieval of Snow and Rain From Combined X- and W-B and Airborne Radar Measurements

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert; Tian, Lin; Heymsfield, Gerald M.

2008-01-01

Two independent airborne dual-wavelength techniques, based on nadir measurements of radar reflectivity factors and Doppler velocities, respectively, are investigated with respect to their capability of estimating microphysical properties of hydrometeors. The data used to investigate the methods are taken from the ER-2 Doppler radar (X-band) and Cloud Radar System (W-band) airborne Doppler radars during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment campaign in 2002. Validity is assessed by the degree to which the methods produce consistent retrievals of the microphysics. For deriving snow parameters, the reflectivity-based technique has a clear advantage over the Doppler-velocity-based approach because of the large dynamic range in the dual-frequency ratio (DFR) with respect to the median diameter Do and the fact that the difference in mean Doppler velocity at the two frequencies, i.e., the differential Doppler velocity (DDV), in snow is small relative to the measurement errors and is often not uniquely related to Do. The DFR and DDV can also be used to independently derive Do in rain. At W-band, the DFR-based algorithms are highly sensitive to attenuation from rain, cloud water, and water vapor. Thus, the retrieval algorithms depend on various assumptions regarding these components, whereas the DDV-based approach is unaffected by attenuation. In view of the difficulties and ambiguities associated with the attenuation correction at W-band, the DDV approach in rain is more straightforward and potentially more accurate than the DFR method.

New Technique for Retrieving Liquid Water Path over Land using Satellite Microwave Observations

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

Deeter, M.N.; Vivekanandan, J.

2005-03-18

We present a new methodology for retrieving liquid water path over land using satellite microwave observations. As input, the technique exploits the Advanced Microwave Scanning Radiometer for earth observing plan (EOS) (AMSR-E) polarization-difference signals at 37 and 89 GHz. Regression analysis performed on model simulations indicates that over variable atmospheric and surface conditions the polarization-difference signals can be simply parameterized in terms of the surface emissivity polarization difference ({Delta}{var_epsilon}), surface temperature, liquid water path (LWP), and precipitable water vapor (PWV). The resulting polarization-difference parameterization (PDP) enables fast and direct (noniterative) retrievals of LWP with minimal requirements for ancillary data. Single-more » and dual-channel retrieval methods are described and demonstrated. Data gridding is used to reduce the effects of instrumental noise. The methodology is demonstrated using AMSR-E observations over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site during a six day period in November and December, 2003. Single- and dual-channel retrieval results mostly agree with ground-based microwave retrievals of LWP to within approximately 0.04 mm.« less

Inversion method based on stochastic optimization for particle sizing.

PubMed

Sánchez-Escobar, Juan Jaime; Barbosa-Santillán, Liliana Ibeth; Vargas-Ubera, Javier; Aguilar-Valdés, Félix

2016-08-01

A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46≤α≤150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem.

[Satellite remote sensing retrieval of canopy nitrogen nutritional status of apple trees at blossom stage].

PubMed

Wang, Ling; Zhao, Geng-Xing; Zhu, Xi-Cun; Wang, Rui-Yan; Chang, Chun-Yan

2013-10-01

Taking Qixia City of Shandong, China as the study area, and based on the Landsat-5 TM and ALOS AVNIR-2 images, the canopy retrieval reflectance of apple trees at blossom stage was acquired. In combining with the measured reflectance of sample trees, the nitrogen-sensitive spectral indices were constructed and selected. By using the sensitive spectral indices as the independent variables, the nitrogen retrieval models were established, and the model with the best accuracy was used for spatial retrieve. The correlations between the spectral indices and the nitrogen nutritional status were in the order of canopy > leaf > flower. The sensitive indices were mainly composed of green, red, and near infrared bands. The accuracy of the retrieval models was in the order of support vector regression > multi-variable stepwise regression > one-variable regression. The retrieval results based on different images were similar, and showed that the leaf nitrogen content was mainly of grades 3-4 (27-33 g x kg(-1)), and the canopy nitrogen nutrient indices were mainly of grades 2-4 (TM: 38-47 g x kg(-1); ALOS: 32-41 g x kg(-1)). The spatial distribution of the retrieval nitrogen nutritional status based on different images also showed the similar trend, i. e., the nitrogen nutritional status was higher in the north and south than that in the middle part of the study area, and the areas with the high grades of leaf nitrogen and canopy nitrogen were mainly located in Sujiadian Town and Songshan subdistrict in the northwest, Zangjiazhuang Town and Tingkou Town in the northeast, and Shewopo Town in the south, which were consistent with the distribution of the key towns for apple production in Qixia City. This study provided a feasible method for the acquisition of nitrogen nutritional status of apple trees on macroscopic scale, and also, provided reference for other similar remote sensing retrievals.

Inferring Cirrus Size Distributions Through Satellite Remote Sensing and Microphysical Databases

NASA Technical Reports Server (NTRS)

Mitchell, David; D'Entremont, Robert P.; Lawson, R. Paul

2010-01-01

Since cirrus clouds have a substantial influence on the global energy balance that depends on their microphysical properties, climate models should strive to realistically characterize the cirrus ice particle size distribution (PSD), at least in a climatological sense. To date, the airborne in situ measurements of the cirrus PSD have contained large uncertainties due to errors in measuring small ice crystals (D<60 m). This paper presents a method to remotely estimate the concentration of the small ice crystals relative to the larger ones using the 11- and 12- m channels aboard several satellites. By understanding the underlying physics producing the emissivity difference between these channels, this emissivity difference can be used to infer the relative concentration of small ice crystals. This is facilitated by enlisting temperature-dependent characterizations of the PSD (i.e., PSD schemes) based on in situ measurements. An average cirrus emissivity relationship between 12 and 11 m is developed here using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and is used to retrieve the PSD based on six different PSD schemes. The PSDs from the measurement-based PSD schemes are compared with corresponding retrieved PSDs to evaluate differences in small ice crystal concentrations. The retrieved PSDs generally had lower concentrations of small ice particles, with total number concentration independent of temperature. In addition, the temperature dependence of the PSD effective diameter De and fall speed Vf for these retrieved PSD schemes exhibited less variability relative to the unmodified PSD schemes. The reduced variability in the retrieved De and Vf was attributed to the lower concentrations of small ice crystals in the retrieved PSD.

Optical properties of aerosol contaminated cloud derived from MODIS instrument

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Lelli, Luca; Vountas, Marco; Burrows, John P.

2016-04-01

The presence of absorbing aerosols above/within cloud can reduce the amount of up-welling radiation in visible (VIS) and short-wave infrared and darken the spectral reflectance when compared with a spectrum of a clean cloud observed by satellite instruments (Jethva et al., 2013). Cloud properties retrieval for aerosol contaminated cases is a great challenge. Even small additional injection of aerosol particles into clouds in the cleanest regions of Earth's atmosphere will cause significant effect on those clouds and on climate forcing (Koren et al., 2014; Rosenfeld et al., 2014) because the micro-physical cloud process are non-linear with respect to the aerosol loading. The current cloud products like Moderate Resolution Imaging Spectroradiometer (MODIS) ignoring the aerosol effect for the retrieval, which may cause significant error in the satellite-derived cloud properties. In this paper, a new cloud properties retrieval method, considering aerosol effect, based on the weighting-function (WF) method, is presented. The retrieval results shows that the WF retrieved cloud properties (e.g COT) agrees quite well with MODIS COT product for relative clear atmosphere (AOT ≤ 0.4) while there is a large difference for large aerosol loading. The MODIS COT product is underestimated for at least 2 - 3 times for AOT>0.4, and this underestimation increases with the increase of AOT.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content.

PubMed

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-27

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness ( τ ), effective radius ( r eff ), and cloud-top height ( h ). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Comparison of methods for measurement and retrieval of SIF with tower based sensors

NASA Astrophysics Data System (ADS)

Kornfeld, A.; Berry, J. A.

2017-12-01

As the popularity of solar induced fluorescence (SIF) measurement increases, the number of ways to measure and process the data has also increased, leaving a bewildering array of choices for the practitioner. To help clarify the advantages and disadvantages of several methods, we modified our foreoptic, Rotaprism, to measure spectra using either bi-hemispheric (cosine correcting diffusers on both upward and downward views) or hemispherical-conical views (only the upward view is cosine corrected). To test spatial sensitivity of each optic, we recorded data after moving the device relatively short distances - 1-2x the sensor's height above the canopy. When using conical measurements, measured SIF varied by as much as 100% across locations, whereas bi-hemispherical measurements were nearly unaffected by the moves. Reflectance indexes such as NDVI, PRI, NIRv were also spatially sensitive for the conical measurements. We also compared retrievals using either the O2A band or the adjacent Fraunhofer band to examine the relative advantages of each retrieval band for full-day retrievals. Finally, we investigated how choice of retrieval algorithm (SVD, FLD, SFM) affects the computed results. The primary site for this experiment was a California bunchgrass/tallgrass field. Additional data from the Brazilian Amazon will also be used, where appropriate, to support our conclusions.

Clinical guideline representation in a CDS: a human information processing method.

PubMed

Kilsdonk, Ellen; Riezebos, Rinke; Kremer, Leontien; Peute, Linda; Jaspers, Monique

2012-01-01

The Dutch Childhood Oncology Group (DCOG) has developed evidence-based guidelines for screening childhood cancer survivors for possible late complications of treatment. These paper-based guidelines appeared to not suit clinicians' information retrieval strategies; it was thus decided to communicate the guidelines through a Computerized Decision Support (CDS) tool. To ensure high usability of this tool, an analysis of clinicians' cognitive strategies in retrieving information from the paper-based guidelines was used as requirements elicitation method. An information processing model was developed through an analysis of think aloud protocols and used as input for the design of the CDS user interface. Usability analysis of the user interface showed that the navigational structure of the CDS tool fitted well with the clinicians' mental strategies employed in deciding on survivors screening protocols. Clinicians were more efficient and more complete in deciding on patient-tailored screening procedures when supported by the CDS tool than by the paper-based guideline booklet. The think-aloud method provided detailed insight into users' clinical work patterns that supported the design of a highly usable CDS system.

The validation of the Yonsei CArbon Retrieval algorithm with improved aerosol information using GOSAT measurements

NASA Astrophysics Data System (ADS)

Jung, Yeonjin; Kim, Jhoon; Kim, Woogyung; Boesch, Hartmut; Goo, Tae-Young; Cho, Chunho

2017-04-01

Although several CO2 retrieval algorithms have been developed to improve our understanding about carbon cycle, limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. Based on an optimal estimation method, the Yonsei CArbon Retrieval (YCAR) algorithm was developed to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) using the Greenhouse Gases Observing SATellite (GOSAT) measurements with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) are the most important factors in CO2 retrievals since AOPs are assumed as fixed parameters during retrieval process, resulting in significant XCO2 retrieval error up to 2.5 ppm. In this study, to reduce these errors caused by inaccurate aerosol optical information, the YCAR algorithm improved with taking into account aerosol optical properties as well as aerosol vertical distribution simultaneously. The CO2 retrievals with two difference aerosol approaches have been analyzed using the GOSAT spectra and have been evaluated throughout the comparison with collocated ground-based observations at several Total Carbon Column Observing Network (TCCON) sites. The improved YCAR algorithm has biases of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, with smaller biases and higher correlation coefficients compared to the GOSAT operational algorithm. In addition, the XCO2 retrievals will be validated at other TCCON sites and error analysis will be evaluated. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties. This study would be expected to provide useful information in estimating carbon sources and sinks.

Sea Ice Freeboard and Thickness from the 2013 IceBridge ATM and DMS Data in Ross Sea, Antarctica

NASA Astrophysics Data System (ADS)

Xie, H.; Tian, L.; Tang, J.; Ackley, S. F.

2016-12-01

In November (20, 21, 27, and 28) 2013, NASA's IceBridge mission flew over the Ross Sea, Antarctica and collected important sea ice data with the ATM and DMS for the first time. We will present our methods to derive the local sea level and total freeboard for ice thickness retrieval from these two datasets. The methods include (1) leads classification from DMS data using an automated lead detection method, (2) potential leads from the reflectance of less than 0.25 from the ATM laser shots of L1B data, (3) local sea level retrieval based on these qualified ATM laser shots (L1B) within the DMS-derived leads (after outliers removal from the mean ± 2 standard deviation of these ATM elevations), (4) establishment of an empirical equation of local sea level as a function of distance from the starting point of each IceBridge flight, (5) total freeboard retrieval from the ATM L2 elevations by subtracting the local sea level derived from the empirical equation, and (6) ice thickness retrieval. The ice thickness derived from this method will be analyzed and compared with ICESat data (2003-2009) and other available data for the same region at the similar time period. Possible change and potential reasons will be identified and discussed.

Automated semantic indexing of figure captions to improve radiology image retrieval.

PubMed

Kahn, Charles E; Rubin, Daniel L

2009-01-01

We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Estimated precision was 0.897 (95% confidence interval, 0.857-0.937). Estimated recall was 0.930 (95% confidence interval, 0.838-1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval.

A new retrieval method for the ice water content of cirrus using data from the CloudSat and CALIPSO

NASA Astrophysics Data System (ADS)

Pan, Honglin; Bu, Lingbing; Kumar, K. Raghavendra; Gao, Haiyang; Huang, Xingyou; Zhang, Wentao

2017-08-01

The CloudSat and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) are the members of satellite observation system of A-train to achieve the quasi-synchronization observation on the same orbit. With the help of active (CALIOP and CPR) and passive payloads from these two satellites, respectively, unprecedented detailed information of microphysical properties of ice cloud can be retrieved. The ice water content (IWC) is regarded as one of the most important microphysical characteristics of cirrus for its prominent role in cloud radiative forcing. In this paper, we proposed a new joint (Combination) retrieval method using the full advantages of different well established retrieval methods, namely the LIDAR method (for the region Lidar-only), the MWCR method (for the region Radar-only), and Wang method (for the region Lidar-Radar) proposed by Wang et al. (2002). In retrieval of cirrus IWC, empirical formulas of the exponential type were used for both thinner cirrus (detected by Lidar-only), thicker cirrus (detected by radar-only), and the part of cirrus detected by both, respectively. In the present study, the comparison of various methods verified that our proposed new joint method is more comprehensive, rational and reliable. Further, the retrieval information of cirrus is complete and accurate for the region that Lidar cannot penetrate and Radar is insensitive. On the whole, the retrieval results of IWC showed certain differences retrieved from the joint method, Ca&Cl, and ICARE which can be interpreted from the different hypothesis of microphysical characteristics and parameters used in the retrieval method. In addition, our joint method only uses the extinction coefficient and the radar reflectivity factor to calculate the IWC, which is simpler and reduces to some extent the accumulative error. In future studies, we will not only compare the value of IWC but also explore the detailed macrophysical and microphysical characteristics of cirrus.

Forward and inverse models of electromagnetic scattering from layered media with rough interfaces

NASA Astrophysics Data System (ADS)

Tabatabaeenejad, Seyed Alireza

This work addresses the problem of electromagnetic scattering from layered dielectric structures with rough boundaries and the associated inverse problem of retrieving the subsurface parameters of the structure using the scattered field. To this end, a forward scattering model based on the Small Perturbation Method (SPM) is developed to calculate the first-order spectral-domain bistatic scattering coefficients of a two-layer rough surface structure. SPM requires the boundaries to be slightly rough compared to the wavelength, but to understand the range of applicability of this method in scattering from two-layer rough surfaces, its region of validity is investigated by comparing its output with that of a first principle solver that does not impose roughness restrictions. The Method of Moments (MoM) is used for this purpose. Finally, for retrieval of the model parameters of the layered structure using scattered field, an inversion scheme based on the Simulated Annealing method is investigated and a strategy is proposed to address convergence to local minimum.

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.

A single-image method for x-ray refractive index CT.

PubMed

Mittone, A; Gasilov, S; Brun, E; Bravin, A; Coan, P

2015-05-07

X-ray refraction-based computer tomography imaging is a well-established method for nondestructive investigations of various objects. In order to perform the 3D reconstruction of the index of refraction, two or more raw computed tomography phase-contrast images are usually acquired and combined to retrieve the refraction map (i.e. differential phase) signal within the sample. We suggest an approximate method to extract the refraction signal, which uses a single raw phase-contrast image. This method, here applied to analyzer-based phase-contrast imaging, is employed to retrieve the index of refraction map of a biological sample. The achieved accuracy in distinguishing the different tissues is comparable with the non-approximated approach. The suggested procedure can be used for precise refraction computer tomography with the advantage of a reduction of at least a factor of two of both the acquisition time and the dose delivered to the sample with respect to any of the other algorithms in the literature.

Neural correlates of retrieval-based memory enhancement: An fMRI study of the testing effect

PubMed Central

Wing, Erik A.; Marsh, Elizabeth J.; Cabeza, Roberto

2013-01-01

Restudying material is a common method for learning new information, but not necessarily an effective one. Research on the testing effect shows that practice involving retrieval from memory can facilitate later memory in contrast to passive restudy. Despite extensive behavioral work, the brain processes that make retrieval an effective learning strategy remain unclear. In the present experiment, we explored how initially retrieving items affected memory a day later as compared to a condition involving traditional restudy. In contrast to restudy, initial testing that contributed to future memory success was associated with engagement of several regions including the anterior hippocampus, lateral temporal cortices, and medial prefrontal cortex (PFC). Additionally, testing enhanced hippocampal connectivity with ventrolateral PFC and midline regions. These findings indicate that the testing effect may be contingent on processes that are typically thought to support memory success at encoding (e.g. relational binding, selection and elaboration of semantically-related information) in addition to those more often associated with retrieval (e.g. memory search). PMID:23607935

Fast, axis-agnostic, dynamically summarized storage and retrieval for mass spectrometry data.

PubMed

Handy, Kyle; Rosen, Jebediah; Gillan, André; Smith, Rob

2017-01-01

Mass spectrometry, a popular technique for elucidating the molecular contents of experimental samples, creates data sets comprised of millions of three-dimensional (m/z, retention time, intensity) data points that correspond to the types and quantities of analyzed molecules. Open and commercial MS data formats are arranged by retention time, creating latency when accessing data across multiple m/z. Existing MS storage and retrieval methods have been developed to overcome the limitations of retention time-based data formats, but do not provide certain features such as dynamic summarization and storage and retrieval of point meta-data (such as signal cluster membership), precluding efficient viewing applications and certain data-processing approaches. This manuscript describes MzTree, a spatial database designed to provide real-time storage and retrieval of dynamically summarized standard and augmented MS data with fast performance in both m/z and RT directions. Performance is reported on real data with comparisons against related published retrieval systems.

The Next-generation Berkeley High Resolution NO2 (BEHR NO2) Retrieval: Design and Preliminary Emissions Constraints

NASA Astrophysics Data System (ADS)

Laughner, J.; Cohen, R. C.

2017-12-01

Recent work has identified a number of assumptions made in NO2 retrievals that lead to biases in the retrieved NO2 column density. These include the treatment of the surface as an isotropic reflector, the absence of lightning NO2 in high resolution a priori profiles, and the use of monthly averaged a priori profiles. We present a new release of the Berkeley High Resolution (BEHR) OMI NO2 retrieval based on the new NASA Standard Product (version 3) that addresses these assumptions by: accounting for surface anisotropy by using a BRDF albedo product, using an updated method of regridding NO2 data, and revised NO2 a priori profiles that better account for lightning NO2 and daily variation in the profile shape. We quantify the effect these changes have on the retrieved NO2 column densities and the resultant impact these updates have on constraints of urban NOx emissions for select cities throughout the United States.

The effect of cloud screening on MAX-DOAS aerosol retrievals.

NASA Astrophysics Data System (ADS)

Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; De Backer, Hugo; De Bock, Veerle; Laffineur, Quentin; Vlemmix, Tim

2014-05-01

In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under strong non-clear-sky conditions, causing strong data quality degradation and uncertainties on the retrievals. Here we present the result of our cloud-screening method, using the colour index (CI), on aerosol retrievals from MAX-DOAS measurements (AOD and vertical profiles). We focus on two large data sets, from the Brussels and Beijing area. Using the CI we define 3 different sky conditions: bad (=full thick cloud cover/extreme aerosols), mediocre (=thin clouds/aerosols) and good (=clear sky). We also flag the presence of broken/scattered clouds. We further compare our cloud-screening method with results from cloud-cover fractions derived from thermic infrared measurements. In general, our method shows good results to qualify the sky and cloud conditions of MAX-DOAS measurements, without the need for other external cloud-detection systems. Removing data under bad-sky and broken-cloud conditions results in a strongly improved agreement, in both correlation and slope, between the MAX-DOAS aerosol retrievals and data from other instruments (e.g. AERONET, Brewer). With the improved AOD retrievals, the seasonal and diurnal variations of the aerosol content and vertical distribution at both sites can be investigated in further detail. By combining with additional information derived by other instruments (Brewer, lidar, ...) operated at the stations, we will further study the observed aerosol characteristics, and their influence on and by meteorological conditions such as clouds and/or the boundary layer height.

Search and retrieval of office files using dBASE 3

NASA Technical Reports Server (NTRS)

Breazeale, W. L.; Talley, C. R.

1986-01-01

Described is a method of automating the office files retrieval process using a commercially available software package (dBASE III). The resulting product is a menu-driven computer program which requires no computer skills to operate. One part of the document is written for the potential user who has minimal computer experience and uses sample menu screens to explain the program; while a second part is oriented towards the computer literate individual and includes rather detailed descriptions of the methodology and search routines. Although much of the programming techniques are explained, this document is not intended to be a tutorial on dBASE III. It is hoped that the document will serve as a stimulus for other applications of dBASE III.

On iterative algorithms for quantitative photoacoustic tomography in the radiative transport regime

NASA Astrophysics Data System (ADS)

Wang, Chao; Zhou, Tie

2017-11-01

In this paper, we present a numerical reconstruction method for quantitative photoacoustic tomography (QPAT), based on the radiative transfer equation (RTE), which models light propagation more accurately than diffusion approximation (DA). We investigate the reconstruction of absorption coefficient and scattering coefficient of biological tissues. An improved fixed-point iterative method to retrieve the absorption coefficient, given the scattering coefficient, is proposed for its cheap computational cost; the convergence of this method is also proved. The Barzilai-Borwein (BB) method is applied to retrieve two coefficients simultaneously. Since the reconstruction of optical coefficients involves the solutions of original and adjoint RTEs in the framework of optimization, an efficient solver with high accuracy is developed from Gao and Zhao (2009 Transp. Theory Stat. Phys. 38 149-92). Simulation experiments illustrate that the improved fixed-point iterative method and the BB method are competitive methods for QPAT in the relevant cases.

Estimating surface soil moisture from SMAP observations using a Neural Network technique.

PubMed

Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

2018-01-01

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

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

Item-method directed forgetting: Effects at retrieval?

PubMed

Taylor, Tracy L; Cutmore, Laura; Pries, Lotta

2018-02-01

In an item-method directed forgetting paradigm, words are presented one at a time, each followed by an instruction to Remember or Forget; a directed forgetting effect is measured as better subsequent memory for Remember words than Forget words. The dominant view is that the directed forgetting effect arises during encoding due to selective rehearsal of Remember over Forget items. In three experiments we attempted to falsify a strong view that directed forgetting effects in recognition are due only to encoding mechanisms when an item method is used. Across 3 experiments we tested for retrieval-based processes by colour-coding the recognition test items. Black colour provided no information; green colour cued a potential Remember item; and, red colour cued a potential Forget item. Recognition cues were mixed within-blocks in Experiment 1 and between-blocks in Experiments 2 and 3; Experiment 3 added explicit feedback on the accuracy of the recognition decision. Although overall recognition improved with cuing when explicit test performance feedback was added in Experiment 3, in no case was the magnitude of the directed forgetting effect influenced by recognition cueing. Our results argue against a role for retrieval-based strategies that limit recognition of Forget items at test and posit a role for encoding intentions only. Copyright © 2017 Elsevier B.V. All rights reserved.

BlastNeuron for Automated Comparison, Retrieval and Clustering of 3D Neuron Morphologies.

PubMed

Wan, Yinan; Long, Fuhui; Qu, Lei; Xiao, Hang; Hawrylycz, Michael; Myers, Eugene W; Peng, Hanchuan

2015-10-01

Characterizing the identity and types of neurons in the brain, as well as their associated function, requires a means of quantifying and comparing 3D neuron morphology. Presently, neuron comparison methods are based on statistics from neuronal morphology such as size and number of branches, which are not fully suitable for detecting local similarities and differences in the detailed structure. We developed BlastNeuron to compare neurons in terms of their global appearance, detailed arborization patterns, and topological similarity. BlastNeuron first compares and clusters 3D neuron reconstructions based on global morphology features and moment invariants, independent of their orientations, sizes, level of reconstruction and other variations. Subsequently, BlastNeuron performs local alignment between any pair of retrieved neurons via a tree-topology driven dynamic programming method. A 3D correspondence map can thus be generated at the resolution of single reconstruction nodes. We applied BlastNeuron to three datasets: (1) 10,000+ neuron reconstructions from a public morphology database, (2) 681 newly and manually reconstructed neurons, and (3) neurons reconstructions produced using several independent reconstruction methods. Our approach was able to accurately and efficiently retrieve morphologically and functionally similar neuron structures from large morphology database, identify the local common structures, and find clusters of neurons that share similarities in both morphology and molecular profiles.

Retrieving Storm Electric Fields From Aircraft Field Mill Data. Part 2; Applications

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Mach, D. M.; Christian, H. J.; Stewart, M. F.; Bateman, M. G.

2005-01-01

The Lagrange multiplier theory and "pitch down method" developed in Part I of this study are applied to complete the calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the method performs well in computer simulations. For mill measurement errors of 1 V/m and a 5 V/m error in the mean fair weather field function, the 3-D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair weather field was also tested using computer simulations. For mill measurement errors of 1 V/m, the method retrieves the 3-D storm field to within an error of about 8% if the fair weather field estimate is typically within 1 V/m of the true fair weather field. Using this side constraint and data from fair weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. The resulting calibration matrix was then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably with the results obtained from earlier calibration analyses that were based on iterative techniques.

Single-intensity-recording optical encryption technique based on phase retrieval algorithm and QR code

NASA Astrophysics Data System (ADS)

Wang, Zhi-peng; Zhang, Shuai; Liu, Hong-zhao; Qin, Yi

2014-12-01

Based on phase retrieval algorithm and QR code, a new optical encryption technology that only needs to record one intensity distribution is proposed. In this encryption process, firstly, the QR code is generated from the information to be encrypted; and then the generated QR code is placed in the input plane of 4-f system to have a double random phase encryption. For only one intensity distribution in the output plane is recorded as the ciphertext, the encryption process is greatly simplified. In the decryption process, the corresponding QR code is retrieved using phase retrieval algorithm. A priori information about QR code is used as support constraint in the input plane, which helps solve the stagnation problem. The original information can be recovered without distortion by scanning the QR code. The encryption process can be implemented either optically or digitally, and the decryption process uses digital method. In addition, the security of the proposed optical encryption technology is analyzed. Theoretical analysis and computer simulations show that this optical encryption system is invulnerable to various attacks, and suitable for harsh transmission conditions.

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

Content-based image retrieval in medical applications for picture archiving and communication systems

NASA Astrophysics Data System (ADS)

Lehmann, Thomas M.; Guld, Mark O.; Thies, Christian; Fischer, Benedikt; Keysers, Daniel; Kohnen, Michael; Schubert, Henning; Wein, Berthold B.

2003-05-01

Picture archiving and communication systems (PACS) aim to efficiently provide the radiologists with all images in a suitable quality for diagnosis. Modern standards for digital imaging and communication in medicine (DICOM) comprise alphanumerical descriptions of study, patient, and technical parameters. Currently, this is the only information used to select relevant images within PACS. Since textual descriptions insufficiently describe the great variety of details in medical images, content-based image retrieval (CBIR) is expected to have a strong impact when integrated into PACS. However, existing CBIR approaches usually are limited to a distinct modality, organ, or diagnostic study. In this state-of-the-art report, we present first results implementing a general approach to content-based image retrieval in medical applications (IRMA) and discuss its integration into PACS environments. Usually, a PACS consists of a DICOM image server and several DICOM-compliant workstations, which are used by radiologists for reading the images and reporting the findings. Basic IRMA components are the relational database, the scheduler, and the web server, which all may be installed on the DICOM image server, and the IRMA daemons running on distributed machines, e.g., the radiologists" workstations. These workstations can also host the web-based front-ends of IRMA applications. Integrating CBIR and PACS, a special focus is put on (a) location and access transparency for data, methods, and experiments, (b) replication transparency for methods in development, (c) concurrency transparency for job processing and feature extraction, (d) system transparency at method implementation time, and (e) job distribution transparency when issuing a query. Transparent integration will have a certain impact on diagnostic quality supporting both evidence-based medicine and case-based reasoning.

Multiple capture locations for 3D ultrasound-guided robotic retrieval of moving bodies from a beating heart

NASA Astrophysics Data System (ADS)

Thienphrapa, Paul; Ramachandran, Bharat; Elhawary, Haytham; Taylor, Russell H.; Popovic, Aleksandra

2012-02-01

Free moving bodies in the heart pose a serious health risk as they may be released in the arteries causing blood flow disruption. These bodies may be the result of various medical conditions and trauma. The conventional approach to removing these objects involves open surgery with sternotomy, the use of cardiopulmonary bypass, and a wide resection of the heart muscle. We advocate a minimally invasive surgical approach using a flexible robotic end effector guided by 3D transesophageal echocardiography. In a phantom study, we track a moving body in a beating heart using a modified normalized cross-correlation method, with mean RMS errors of 2.3 mm. We previously found the foreign body motion to be fast and abrupt, rendering infeasible a retrieval method based on direct tracking. We proposed a strategy based on guiding a robot to the most spatially probable location of the fragment and securing it upon its reentry to said location. To improve efficacy in the context of a robotic retrieval system, we extend this approach by exploring multiple candidate capture locations. Salient locations are identified based on spatial probability, dwell time, and visit frequency; secondary locations are also examined. Aggregate results indicate that the location of highest spatial probability (50% occupancy) is distinct from the longest-dwelled location (0.84 seconds). Such metrics are vital in informing the design of a retrieval system and capture strategies, and they can be computed intraoperatively to select the best capture location based on constraints such as workspace, time, and device manipulability. Given the complex nature of fragment motion, the ability to analyze multiple capture locations is a desirable capability in an interventional system.

Comparison of cloud top heights derived from FY-2 meteorological satellites with heights derived from ground-based millimeter wavelength cloud radar

NASA Astrophysics Data System (ADS)

Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa

2018-01-01

Clouds are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic cloud measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their cloud top temperature product can be processed to retrieve the cloud top height (CTH). The ground-based millimeter wavelength cloud radar can acquire information about the vertical structure of clouds-such as the cloud base height (CBH), CTH and the cloud thickness-and can continuously monitor changes in the vertical profiles of clouds. The CTHs were retrieved using both cloud top temperature data from the FY-2 satellites and the cloud radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of cloud detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker clouds with larger echo intensity and for more continuous clouds. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level clouds was less than that for high-level clouds. An attenuation threshold of the cloud radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the cloud radar data.

Fast DCNN based on FWT, intelligent dropout and layer skipping for image retrieval.

PubMed

ElAdel, Asma; Zaied, Mourad; Amar, Chokri Ben

2017-11-01

Deep Convolutional Neural Network (DCNN) can be marked as a powerful tool for object and image classification and retrieval. However, the training stage of such networks is highly consuming in terms of storage space and time. Also, the optimization is still a challenging subject. In this paper, we propose a fast DCNN based on Fast Wavelet Transform (FWT), intelligent dropout and layer skipping. The proposed approach led to improve the image retrieval accuracy as well as the searching time. This was possible thanks to three key advantages: First, the rapid way to compute the features using FWT. Second, the proposed intelligent dropout method is based on whether or not a unit is efficiently and not randomly selected. Third, it is possible to classify the image using efficient units of earlier layer(s) and skipping all the subsequent hidden layers directly to the output layer. Our experiments were performed on CIFAR-10 and MNIST datasets and the obtained results are very promising. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biomedical information retrieval across languages.

PubMed

Daumke, Philipp; Markü, Kornél; Poprat, Michael; Schulz, Stefan; Klar, Rüdiger

2007-06-01

This work presents a new dictionary-based approach to biomedical cross-language information retrieval (CLIR) that addresses many of the general and domain-specific challenges in current CLIR research. Our method is based on a multilingual lexicon that was generated partly manually and partly automatically, and currently covers six European languages. It contains morphologically meaningful word fragments, termed subwords. Using subwords instead of entire words significantly reduces the number of lexical entries necessary to sufficiently cover a specific language and domain. Mediation between queries and documents is based on these subwords as well as on lists of word-n-grams that are generated from large monolingual corpora and constitute possible translation units. The translations are then sent to a standard Internet search engine. This process makes our approach an effective tool for searching the biomedical content of the World Wide Web in different languages. We evaluate this approach using the OHSUMED corpus, a large medical document collection, within a cross-language retrieval setting.

Retrieval of constituent mixing ratios from limb thermal emission spectra

NASA Technical Reports Server (NTRS)

Shaffer, William A.; Kunde, Virgil G.; Conrath, Barney J.

1988-01-01

An onion-peeling iterative, least-squares relaxation method to retrieve mixing ratio profiles from limb thermal emission spectra is presented. The method has been tested on synthetic data, containing various amounts of added random noise for O3, HNO3, and N2O. The retrieval method is used to obtain O3 and HNO3 mixing ratio profiles from high-resolution thermal emission spectra. Results of the retrievals compare favorably with those obtained previously.

Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

NASA Astrophysics Data System (ADS)

Tang, Hong; Lin, Jian-Zhong

2013-01-01

An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

2014-12-01

Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various datasets available, the methods employed to utilize them in the cloud property retrieval validation process, and the results and how they aid future development of the retrieval algorithms. Future needs are also discussed.

Topography of hidden objects using THz digital holography with multi-beam interferences.

PubMed

Valzania, Lorenzo; Zolliker, Peter; Hack, Erwin

2017-05-15

We present a method for the separation of the signal scattered from an object hidden behind a THz-transparent sample in the framework of THz digital holography in reflection. It combines three images of different interference patterns to retrieve the amplitude and phase distribution of the object beam. Comparison of simulated with experimental images obtained from a metallic resolution target behind a Teflon plate demonstrates that the interference patterns can be described in the simple form of three-beam interference. Holographic reconstructions after the application of the method show a considerable improvement compared to standard reconstructions exclusively based on Fourier transform phase retrieval.

Image retrieval for identifying house plants

NASA Astrophysics Data System (ADS)

Kebapci, Hanife; Yanikoglu, Berrin; Unal, Gozde

2010-02-01

We present a content-based image retrieval system for plant identification which is intended for providing users with a simple method to locate information about their house plants. A plant image consists of a collection of overlapping leaves and possibly flowers, which makes the problem challenging. We studied the suitability of various well-known color, texture and shape features for this problem, as well as introducing some new ones. The features are extracted from the general plant region that is segmented from the background using the max-flow min-cut technique. Results on a database of 132 different plant images show promise (in about 72% of the queries, the correct plant image is retrieved among the top-15 results).

Knowledge Acquisition of Generic Queries for Information Retrieval

PubMed Central

Seol, Yoon-Ho; Johnson, Stephen B.; Cimino, James J.

2002-01-01

Several studies have identified clinical questions posed by health care professionals to understand the nature of information needs during clinical practice. To support access to digital information sources, it is necessary to integrate the information needs with a computer system. We have developed a conceptual guidance approach in information retrieval, based on a knowledge base that contains the patterns of information needs. The knowledge base uses a formal representation of clinical questions based on the UMLS knowledge sources, called the Generic Query model. To improve the coverage of the knowledge base, we investigated a method for extracting plausible clinical questions from the medical literature. This poster presents the Generic Query model, shows how it is used to represent the patterns of clinical questions, and describes the framework used to extract knowledge from the medical literature.

Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method

PubMed Central

Zhong, Xinke; Huo, Xing; Ren, Chao; Labed, Jelila; Li, Zhao-Liang

2016-01-01

Land Surface Temperature (LST) is a key parameter in climate systems. The methods for retrieving LST from hyperspectral thermal infrared data either require accurate atmospheric profile data or require thousands of continuous channels. We aim to retrieve LST for natural land surfaces from hyperspectral thermal infrared data using an adapted multi-channel method taking Land Surface Emissivity (LSE) properly into consideration. In the adapted method, LST can be retrieved by a linear function of 36 brightness temperatures at Top of Atmosphere (TOA) using channels where LSE has high values. We evaluated the adapted method using simulation data at nadir and satellite data near nadir. The Root Mean Square Error (RMSE) of the LST retrieved from the simulation data is 0.90 K. Compared with an LST product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat, the error in the LST retrieved from the Infared Atmospheric Sounding Interferometer (IASI) is approximately 1.6 K. The adapted method can be used for the near-real-time production of an LST product and to provide the physical method to simultaneously retrieve atmospheric profiles, LST, and LSE with a first-guess LST value. The limitations of the adapted method are that it requires the minimum LSE in the spectral interval of 800–950 cm−1 larger than 0.95 and it has not been extended for off-nadir measurements. PMID:27187408

Retrieval of the Nitrous Oxide Profiles using the AIRS Data in China

NASA Astrophysics Data System (ADS)

Chen, L.; Ma, P.; Tao, J.; Li, X.; Zhang, Y.; Wang, Z.; Li, S.; Xiong, X.

2014-12-01

As an important greenhouse gas and ozone-depleting substance, the 100-year global warming potential of Nitrous Oxide (N2O) is almost 300 times higher than that of carbon dioxide. However, there are still large uncertainties about the quantitative N2O emission and its feedback to climate change due to the coarse ground-based network. This approach attempts to retrieve the N2O profiles from the Atmospheric InfraRed Sounder (AIRS) data. First, the sensitivity of atmospheric temperature and humidity profiles and surface parameters between two spectral absorption bands were simulated by using the radiative transfer model. Second, the eigenvector regression algorithm is used to construct a priori state. Third, an optimal estimate method was developed based on the band selection of N2O. Finally, we compared our retrieved AIRS profiles with HIPPO data, and analyzed the seasonal and annual N2O distribution in China from 2004 to 2013.

An improvement of the retrieval of temperature and relative humidity profiles from a combination of active and passive remote sensing

NASA Astrophysics Data System (ADS)

Che, Yunfei; Ma, Shuqing; Xing, Fenghua; Li, Siteng; Dai, Yaru

2018-03-01

This paper focuses on an improvement of the retrieval of atmospheric temperature and relative humidity profiles through combining active and passive remote sensing. Ground-based microwave radiometer and millimeter-wavelength cloud radar were used to acquire the observations. Cloud base height and cloud thickness determinations from cloud radar were added into the atmospheric profile retrieval process, and a back-propagation neural network method was used as the retrieval tool. Because a substantial amount of data are required to train a neural network, and as microwave radiometer data are insufficient for this purpose, 8 years of radiosonde data from Beijing were used as the database. The monochromatic radiative transfer model was used to calculate the brightness temperatures in the same channels as the microwave radiometer. Parts of the cloud base heights and cloud thicknesses in the training data set were also estimated using the radiosonde data. The accuracy of the results was analyzed through a comparison with L-band sounding radar data and quantified using the mean bias, root-mean-square error (RMSE), and correlation coefficient. The statistical results showed that an inversion with cloud information was the optimal method. Compared with the inversion profiles without cloud information, the RMSE values after adding cloud information reduced to varying degrees for the vast majority of height layers. These reductions were particularly clear in layers with clouds. The maximum reduction in the RMSE for the temperature profile was 2.2 K, while that for the humidity profile was 16%.

NPP ATMS Snowfall Rate Product

NASA Technical Reports Server (NTRS)

Meng, Huan; Ferraro, Ralph; Kongoli, Cezar; Wang, Nai-Yu; Dong, Jun; Zavodsky, Bradley; Yan, Banghua

2015-01-01

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow-on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2015). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two-stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. NCEP CMORPH analysis has shown that integration of ATMS SFR has improved the performance of CMORPH-Snow. The ATMS SFR product is also being assessed at several NWS Weather Forecast Offices for its usefulness in weather forecast.

Recent Improvements in AMSR2 Ground-Based RFI Filtering

NASA Astrophysics Data System (ADS)

Scott, J. P.; Gentemann, C. L.; Wentz, F. J.

2015-12-01

Passive satellite radiometer measurements in the microwave frequencies (6-89 GHz) are useful in providing geophysical retrievals of sea surface temperature (SST), atmospheric water vapor, wind speed, rain rate, and more. However, radio frequency interference (RFI) is one of the fastest growing sources of error in these retrievals. RFI can originate from broadcasting satellites, as well as from ground-based instrumentation that makes use of the microwave range. The microwave channel bandwidths used by passive satellite radiometers are often wider than the protected bands allocated for this type of remote sensing, a common practice in microwave radiometer design used to reduce the effect of instrument noise in the observed signal. However, broad channel bandwidths allow greater opportunity for RFI to affect these observations and retrievals. For ground-based RFI, a signal is broadcast directly into the atmosphere which may interfere with the radiometer - its antenna, cold mirror, hot load or the internal workings of the radiometer itself. It is relatively easy to identify and flag RFI from large sources, but more difficult to do so from small, sporadic sources. Ground-based RFI has high spatial and temporal variability, requiring constant, automated detection and removal to avoid spurious trends leaching into the geophysical retrievals. Ascension Island in the South Atlantic Ocean has been one of these notorious ground-based RFI sources, affecting many microwave radiometers, including the AMSR2 radiometer onboard JAXA's GCOM-W1 satellite. Ascension Island RFI mainly affects AMSR2's lower frequency channels (6.9, 7.3, and 10.65 GHz) over a broad spatial region in the South Atlantic Ocean, which makes it challenging to detect and flag this RFI using conventional channel and geophysical retrieval differencing techniques. The authors have developed a new method of using the radiometer's earth counts and hot counts, for the affected channels, to detect an Ascension Island RFI event and flag the data efficiently and accurately, thereby reducing false detections and optimizing retrieval quality and data preservation.

Applications of Land Surface Temperature from Microwave Observations

USDA-ARS?s Scientific Manuscript database

Land surface temperature (LST) is a key input for physically-based retrieval algorithms of hydrological states and fluxes. Yet, it remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observation...

Radiation characteristics and effective optical properties of dumbbell-shaped cyanobacterium Synechocystis sp.

NASA Astrophysics Data System (ADS)

Heng, Ri-Liang; Pilon, Laurent

2016-05-01

This study presents experimental measurements of the radiation characteristics of unicellular freshwater cyanobacterium Synechocystis sp. during their exponential growth in F medium. Their scattering phase function at 633 nm average spectral absorption and scattering cross-sections between 400 and 750 nm were measured. In addition, an inverse method was used for retrieving the spectral effective complex index of refraction of overlapping or touching bispheres and quadspheres from their absorption and scattering cross-sections. The inverse method combines a genetic algorithm and a forward model based on Lorenz-Mie theory, treating bispheres and quadspheres as projected area and volume-equivalent coated spheres. The inverse method was successfully validated with numerically predicted average absorption and scattering cross-sections of suspensions consisting of bispheres and quadspheres, with realistic size distributions, using the T-matrix method. It was able to retrieve the monomers' complex index of refraction with size parameter up to 11, relative refraction index less than 1.3, and absorption index less than 0.1. Then, the inverse method was applied to retrieve the effective spectral complex index of refraction of Synechocystis sp. approximated as randomly oriented aggregates consisting of two overlapping homogeneous spheres. Both the measured absorption cross-section and the retrieved absorption index featured peaks at 435 and 676 nm corresponding to chlorophyll a, a peak at 625 nm corresponding to phycocyanin, and a shoulder around 485 nm corresponding to carotenoids. These results can be used to optimize and control light transfer in photobioreactors. The inverse method and the equivalent coated sphere model could be applied to other optically soft particles of similar morphologies.

Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval.

PubMed

Wang, Yang; Lin, Xuemin; Wu, Lin; Zhang, Wenjie

2017-03-01

Given a query photo issued by a user (q-user), the landmark retrieval is to return a set of photos with their landmarks similar to those of the query, while the existing studies on the landmark retrieval focus on exploiting geometries of landmarks for similarity matches between candidate photos and a query photo. We observe that the same landmarks provided by different users over social media community may convey different geometry information depending on the viewpoints and/or angles, and may, subsequently, yield very different results. In fact, dealing with the landmarks with low quality shapes caused by the photography of q-users is often nontrivial and has seldom been studied. In this paper, we propose a novel framework, namely, multi-query expansions, to retrieve semantically robust landmarks by two steps. First, we identify the top- k photos regarding the latent topics of a query landmark to construct multi-query set so as to remedy its possible low quality shape. For this purpose, we significantly extend the techniques of Latent Dirichlet Allocation. Then, motivated by the typical collaborative filtering methods, we propose to learn a collaborative deep networks-based semantically, nonlinear, and high-level features over the latent factor for landmark photo as the training set, which is formed by matrix factorization over collaborative user-photo matrix regarding the multi-query set. The learned deep network is further applied to generate the features for all the other photos, meanwhile resulting into a compact multi-query set within such space. Then, the final ranking scores are calculated over the high-level feature space between the multi-query set and all other photos, which are ranked to serve as the final ranking list of landmark retrieval. Extensive experiments are conducted on real-world social media data with both landmark photos together with their user information to show the superior performance over the existing methods, especially our recently proposed multi-query based mid-level pattern representation method [1].

On the Simulation of Sea States with High Significant Wave Height for the Validation of Parameter Retrieval Algorithms for Future Altimetry Missions

NASA Astrophysics Data System (ADS)

Kuschenerus, Mieke; Cullen, Robert

2016-08-01

To ensure reliability and precision of wave height estimates for future satellite altimetry missions such as Sentinel 6, reliable parameter retrieval algorithms that can extract significant wave heights up to 20 m have to be established. The retrieved parameters, i.e. the retrieval methods need to be validated extensively on a wide range of possible significant wave heights. Although current missions require wave height retrievals up to 20 m, there is little evidence of systematic validation of parameter retrieval methods for sea states with wave heights above 10 m. This paper provides a definition of a set of simulated sea states with significant wave height up to 20 m, that allow simulation of radar altimeter response echoes for extreme sea states in SAR and low resolution mode. The simulated radar responses are used to derive significant wave height estimates, which can be compared with the initial models, allowing precision estimations of the applied parameter retrieval methods. Thus we establish a validation method for significant wave height retrieval for sea states causing high significant wave heights, to allow improved understanding and planning of future satellite altimetry mission validation.

Automated Semantic Indexing of Figure Captions to Improve Radiology Image Retrieval

PubMed Central

Kahn, Charles E.; Rubin, Daniel L.

2009-01-01

Objective We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. Design The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Measurements Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Results Estimated precision was 0.897 (95% confidence interval, 0.857–0.937). Estimated recall was 0.930 (95% confidence interval, 0.838–1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Conclusion Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval. PMID:19261938

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

NASA Technical Reports Server (NTRS)

Miernecki, Maciej; Wigneron, Jean-Pierre; Lopez-Baeza, Ernesto; Kerr, Yann; DeJeu, Richard; DeLannoy, Gabielle J. M.; Jackson, Tom J.; O'Neill, Peggy E.; Shwank, Mike; Moran, Roberto Fernandez;

The Dependence of Homo- and Heterogeneously Formed Cirrus Clouds on Latitude, Season and Surface-type based on a New CALIPSO Remote Sensing Method

NASA Astrophysics Data System (ADS)

Mitchell, D. L.; Garnier, A.; Mejia, J.; Avery, M. A.; Erfani, E.

2016-12-01

A new CALIPSO infrared retrieval method sensitive to small ice crystals has been developed to measure the temperature dependence of the layer-average number concentration N, effective diameter De and ice water content in single-layer cirrus clouds (one cloud layer in the atmospheric column) that have optical depths between 0.3 and 3.0 and cloud base temperature T < 235 K. While retrievals of low N are not accurate, mid-to-high N can be retrieved with much lower uncertainty. This enables the retrieval to estimate the dominant ice nucleation mechanism (homo- or heterogeneous, henceforth hom and het) though which the cirrus formed. Based on N, hom or het cirrus can be estimated as a function of temperature, season, latitude and surface type. The retrieved properties noted above compare favorably with spatial-temporal coincident cirrus cloud in situ measurements from SPARTICUS case studies as well as the extensive in situ cirrus data set of Krämer et al. (2009, ACP). For our cirrus cloud selection, these retrievals show a pronounced seasonal cycle in the N. Hemisphere over land north of 30°N latitude in terms of both cloud amount and microphysics, with greater cloud cover, higher N and smaller De during the winter season. We postulate that this is partially due to the seasonal cycle of deep convection that replenishes the supply of ice nuclei (IN) at cirrus levels, with hom more likely when deep convection is absent. Over oceans, heterogeneous ice nucleation appears to prevail based on the lower N and higher De observed. Due to the relatively smooth ocean surface, lower amplitude atmospheric waves at cirrus cloud levels are expected. Over land outside the tropics during winter, hom cirrus tend to occur over mountainous terrain, possibly due to lower IN concentrations and stronger, more sustained updrafts in mountain-induced waves. Over pristine Antarctica, IN concentrations are minimal and the terrain near the coast is often high and rugged, allowing hom to dominate. Accordingly, over Antarctica cirrus clouds exhibit relatively high N and small De throughout the year. These retrievals allow us to parameterize De and the ice fall speed in CAM5 as a function of T, season, latitude and surface-type. Our goal is to estimate the radiative impact of hom cirrus north of 30°N latitude in winter relative to het cirrus before the AGU Fall Meeting.

Development of a generalized multi-pixel and multi-parameter satellite remote sensing algorithm for aerosol properties

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Takenaka, H.; Higurashi, A.

2013-12-01

We develop a new satellite remote sensing algorithm to retrieve the properties of aerosol particles in the atmosphere. In late years, high resolution and multi-wavelength, and multiple-angle observation data have been obtained by grand-based spectral radiometers and imaging sensors on board the satellite. With this development, optimized multi-parameter remote sensing methods based on the Bayesian theory have become popularly used (Turchin and Nozik, 1969; Rodgers, 2000; Dubovik et al., 2000). Additionally, a direct use of radiation transfer calculation has been employed for non-linear remote sensing problems taking place of look up table methods supported by the progress of computing technology (Dubovik et al., 2011; Yoshida et al., 2011). We are developing a flexible multi-pixel and multi-parameter remote sensing algorithm for aerosol optical properties. In this algorithm, the inversion method is a combination of the MAP method (Maximum a posteriori method, Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, we include a radiation transfer calculation code, Rstar (Nakajima and Tanaka, 1986, 1988), numerically solved each time in iteration for solution search. The Rstar-code has been directly used in the AERONET operational processing system (Dubovik and King, 2000). Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine mode, sea salt, and dust particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area. We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. In this test, we simulated satellite-observed radiances for a sub-domain consisting of 5 by 5 pixels by the Rstar code assuming wavelengths of 380, 674, 870 and 1600 [nm], atmospheric condition of the US standard atmosphere, and the several aerosol and ground surface conditions. The result of the experiment showed that AOTs of fine mode and dust particles, soot fraction and ground surface albedo at the wavelength of 674 [nm] are retrieved within absolute value differences of 0.04, 0.01, 0.06 and 0.006 from the true value, respectively, for the case of dark surface, and also, for the case of blight surface, 0.06, 0.03, 0.04 and 0.10 from the true value, respectively. We will conduct more tests to study the information contents of parameters needed for aerosol and land surface remote sensing with different boundary conditions among sub-domains.

Satellite-based estimation of cloud-base updrafts for convective clouds and stratocumulus

NASA Astrophysics Data System (ADS)

Zheng, Y.; Rosenfeld, D.; Li, Z.

2017-12-01

Updraft speeds of thermals have always been notoriously difficult to measure, despite significant roles they play in transporting pollutants and in cloud formation and precipitation. To our knowledge, no attempt to date has been made to estimate updraft speed from satellite information. In this study, we introduce three methods of retrieving updraft speeds at cloud base () for convective clouds and marine stratocumulus with VIIRS onboard Suomi-NPP satellite. The first method uses ground-air temperature difference to characterize the surface sensible heat flux, which is found to be correlated with updraft speeds measured by the Doppler lidar over the Southern Great Plains (SGP). Based on the relationship, we use the satellite-retrieved surface skin temperature and reanalysis surface air temperature to estimate the updrafts. The second method is based on a good linear correlation between cloud base height and updrafts, which was found over the SGP, the central Amazon, and on board a ship sailing between Honolulu and Los Angeles. We found a universal relationship for both land and ocean. The third method is for marine stratocumulus. A statistically significant relationship between Wb and cloud-top radiative cooling rate (CTRC) is found from measurements over northeastern Pacific and Atlantic. Based on this relation, satellite- and reanalysis-derived CTRC is utilized to infer the Wb of stratocumulus clouds. Evaluations against ground-based Doppler lidar measurements show estimation errors of 24%, 21% and 22% for the three methods, respectively.

A neural network to retrieve the mesoscale instantaneous latent heat flux over oceans from SSM/I observations

NASA Technical Reports Server (NTRS)

Bourras, D.; Eymard, L.; Liu, W. T.

2000-01-01

The turbulent latent and sensible heat fluxes are necessary to study heat budget of the upper ocean or initialize ocean general circulation models. In order to retrieve the latent heat flux from satellite observations authors mostly use a bulk approximation of the flux whose parameters are derived from different instrument. In this paper, an approach based on artificial neural networks is proposed and compared to the bulk method on a global data set and 3 local data sets.

Unified Pairwise Spatial Relations: An Application to Graphical Symbol Retrieval

NASA Astrophysics Data System (ADS)

Santosh, K. C.; Wendling, Laurent; Lamiroy, Bart

In this paper, we present a novel unifying concept of pairwise spatial relations. We develop two way directional relations with respect to a unique point set, based on topology of the studied objects and thus avoids problems related to erroneous choices of reference objects while preserving symmetry. The method is robust to any type of image configuration since the directional relations are topologically guided. An automatic prototype graphical symbol retrieval is presented in order to establish its expressiveness.

Competitive retrieval is not a prerequisite for forgetting in the retrieval practice paradigm.

PubMed

Camp, Gino; Dalm, Sander

2016-09-01

Retrieving information from memory can lead to forgetting of other, related information. The inhibition account of this retrieval-induced forgetting effect predicts that this form of forgetting occurs when competition arises between the practiced information and the related information, leading to inhibition of the related information. In the standard retrieval practice paradigm, a retrieval practice task is used in which participants retrieve the items based on a category-plus-stem cue (e.g., FRUIT-or___). In the current experiment, participants instead generated the target based on a cue in which the first 2 letters of the target were transposed (e.g., FRUIT-roange). This noncompetitive task also induced forgetting of unpracticed items from practiced categories. This finding is inconsistent with the inhibition account, which asserts that the forgetting effect depends on competitive retrieval. We argue that interference-based accounts of forgetting and the context-based account of retrieval-induced forgetting can account for this result. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features

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

Ahmed, Fiaz; Schumacher, Courtney; Feng, Zhe

Traditionally, radar-based latent heating retrievals use rainfall to estimate the total column-integrated latent heating and then distribute that heating in the vertical using a model-based look-up table (LUT). In this study, we develop a new method that uses size characteristics of radar-observed precipitating echo (i.e., area and mean echo-top height) to estimate the vertical structure of latent heating. This technique (named the Convective-Stratiform Area [CSA] algorithm) builds on the fact that the shape and magnitude of latent heating profiles are dependent on the organization of convective systems and aims to avoid some of the pitfalls involved in retrieving accurate rainfallmore » amounts and microphysical information from radars and models. The CSA LUTs are based on a high-resolution Weather Research and Forecasting model (WRF) simulation whose domain spans much of the near-equatorial Indian Ocean. When applied to S-PolKa radar observations collected during the DYNAMO/CINDY2011/AMIE field campaign, the CSA retrieval compares well to heating profiles from a sounding-based budget analysis and improves upon a simple rain-based latent heating retrieval. The CSA LUTs also highlight the fact that convective latent heating increases in magnitude and height as cluster area and echo-top heights grow, with a notable congestus signature of cooling at mid levels. Stratiform latent heating is less dependent on echo-top height, but is strongly linked to area. Unrealistic latent heating profiles in the stratiform LUT, viz., a low-level heating spike, an elevated melting layer, and net column cooling were identified and corrected for. These issues highlight the need for improvement in model parameterizations, particularly in linking microphysical phase changes to larger mesoscale processes.« less

SSM/I Rain Retrievals Within a Unified All-Weather Ocean Algorithm

NASA Technical Reports Server (NTRS)

Wentz, Frank J.; Spencer, Roy W.

1996-01-01

A new method for the physical retrieval of rain rates from satellite microwave radiometers is presented and compared to two other rainfall climatologies derived from satellites. The method is part of a unified ocean parameter retrieval algorithm that is based on the fundamental principles of radiative transfer. The algorithm simultaneously finds near-surface wind speed W, columnar water vapor V, columnar cloud liquid water L, rain rate R, and effective radiating temperature T(sub U) for the upwelling radiation. The performance of the algorithm in the absence of rain is discussed in Wentz, and this paper focuses on the rain component of the algorithm. A particular strength of the unified algorithm is its ability to 'orthogonalize' the retrievals so that there is minimum cross-talk between the retrieved parameters. For example, comparisons of the retrieved water vapor with radiosonde observations show that there is very little correlation between the water vapor retrieval error and rain rate. For rain rates from 1 to 15 mm/h, the rms difference between the retrieved water vapor and the radiosonde value is 5 mm. A novel feature of the rain retrieval method is a beamfilling correction that is based upon the ratio of the retrieved liquid water absorption coefficients at 37 GHz and 19.35 GHz. This ratio decreases by about 40% when heavy and light rain co-exist within the SSM/I footprint as compared to the case of uniform rain. This correction has the effect of increasing the rain rate when the spectral ratio of the absorption coefficients is small. Even with this beamfilling correction, tropical rainfall is still unrealistically low when the freezing level in the tropics (approx. 5 km) is used to specify the rain layer thickness. We restore realism by reducing the assumed averaged tropical rain layer thickness to 3 km, thereby accounting for the existence of warm rain processes in which the rain layer does not extend to the freezing level. Global rain rates are produced for the 1991 through 1994 period from observations taken by microwave radiometers (SSM/I) that are aboard two polar-orbiting satellites. We find that approximately 6% of the SSM/I observations detect measurable rain rates (R greater than 0.2 mm/h). Zonal averages of the rain rates show the peak at the intertropical convergence zone (ITCZ) is quite narrow in meridional extent and varies from about 7 mm/day in the winter to a maximum 11 mm/day in the summer. Very low precipitation rates (less than 0.3 mm/day) are observed in those areas of subsidence influenced by the large semipermanent anticyclones. In general, these features are similar to those reported in previously published rain climatologies. However, significant differences do exists between our rain rates and those produced by Spencer. These differences seem to be related to non-precipitating cloud water.

Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection

PubMed Central

Huang, Jidong; Emery, Sherry

2016-01-01

Background Social media have transformed the communications landscape. People increasingly obtain news and health information online and via social media. Social media platforms also serve as novel sources of rich observational data for health research (including infodemiology, infoveillance, and digital disease detection detection). While the number of studies using social data is growing rapidly, very few of these studies transparently outline their methods for collecting, filtering, and reporting those data. Keywords and search filters applied to social data form the lens through which researchers may observe what and how people communicate about a given topic. Without a properly focused lens, research conclusions may be biased or misleading. Standards of reporting data sources and quality are needed so that data scientists and consumers of social media research can evaluate and compare methods and findings across studies. Objective We aimed to develop and apply a framework of social media data collection and quality assessment and to propose a reporting standard, which researchers and reviewers may use to evaluate and compare the quality of social data across studies. Methods We propose a conceptual framework consisting of three major steps in collecting social media data: develop, apply, and validate search filters. This framework is based on two criteria: retrieval precision (how much of retrieved data is relevant) and retrieval recall (how much of the relevant data is retrieved). We then discuss two conditions that estimation of retrieval precision and recall rely on—accurate human coding and full data collection—and how to calculate these statistics in cases that deviate from the two ideal conditions. We then apply the framework on a real-world example using approximately 4 million tobacco-related tweets collected from the Twitter firehose. Results We developed and applied a search filter to retrieve e-cigarette–related tweets from the archive based on three keyword categories: devices, brands, and behavior. The search filter retrieved 82,205 e-cigarette–related tweets from the archive and was validated. Retrieval precision was calculated above 95% in all cases. Retrieval recall was 86% assuming ideal conditions (no human coding errors and full data collection), 75% when unretrieved messages could not be archived, 86% assuming no false negative errors by coders, and 93% allowing both false negative and false positive errors by human coders. Conclusions This paper sets forth a conceptual framework for the filtering and quality evaluation of social data that addresses several common challenges and moves toward establishing a standard of reporting social data. Researchers should clearly delineate data sources, how data were accessed and collected, and the search filter building process and how retrieval precision and recall were calculated. The proposed framework can be adapted to other public social media platforms. PMID:26920122

Variable Sampling Mapping

NASA Technical Reports Server (NTRS)

Smith, Jeffrey, S.; Aronstein, David L.; Dean, Bruce H.; Lyon, Richard G.

2012-01-01

The performance of an optical system (for example, a telescope) is limited by the misalignments and manufacturing imperfections of the optical elements in the system. The impact of these misalignments and imperfections can be quantified by the phase variations imparted on light traveling through the system. Phase retrieval is a methodology for determining these variations. Phase retrieval uses images taken with the optical system and using a light source of known shape and characteristics. Unlike interferometric methods, which require an optical reference for comparison, and unlike Shack-Hartmann wavefront sensors that require special optical hardware at the optical system's exit pupil, phase retrieval is an in situ, image-based method for determining the phase variations of light at the system s exit pupil. Phase retrieval can be used both as an optical metrology tool (during fabrication of optical surfaces and assembly of optical systems) and as a sensor used in active, closed-loop control of an optical system, to optimize performance. One class of phase-retrieval algorithms is the iterative transform algorithm (ITA). ITAs estimate the phase variations by iteratively enforcing known constraints in the exit pupil and at the detector, determined from modeled or measured data. The Variable Sampling Mapping (VSM) technique is a new method for enforcing these constraints in ITAs. VSM is an open framework for addressing a wide range of issues that have previously been considered detrimental to high-accuracy phase retrieval, including undersampled images, broadband illumination, images taken at or near best focus, chromatic aberrations, jitter or vibration of the optical system or detector, and dead or noisy detector pixels. The VSM is a model-to-data mapping procedure. In VSM, fully sampled electric fields at multiple wavelengths are modeled inside the phase-retrieval algorithm, and then these fields are mapped to intensities on the light detector, using the properties of the detector and optical system, for comparison with measured data. Ultimately, this model-to-data mapping procedure enables a more robust and accurate way of incorporating the exit-pupil and image detector constraints, which are fundamental to the general class of ITA phase retrieval algorithms.

Assessment of Snared-Loop Technique When Standard Retrieval of Inferior Vena Cava Filters Fails

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

Doody, Orla, E-mail: orla_doody@hotmail.com; Noe, Geertje; Given, Mark F.

Purpose To identify the success and complications related to a variant technique used to retrieve inferior vena cava filters when simple snare approach has failed. Methods A retrospective review of all Cook Guenther Tulip filters and Cook Celect filters retrieved between July 2006 and February 2008 was performed. During this period, 130 filter retrievals were attempted. In 33 cases, the standard retrieval technique failed. Retrieval was subsequently attempted with our modified retrieval technique. Results The retrieval was successful in 23 cases (mean dwell time, 171.84 days; range, 5-505 days) and unsuccessful in 10 cases (mean dwell time, 162.2 days; range,more » 94-360 days). Our filter retrievability rates increased from 74.6% with the standard retrieval method to 92.3% when the snared-loop technique was used. Unsuccessful retrieval was due to significant endothelialization (n = 9) and caval penetration by the filter (n = 1). A single complication occurred in the group, in a patient developing pulmonary emboli after attempted retrieval. Conclusion The technique we describe increased the retrievability of the two filters studied. Hook endothelialization is the main factor resulting in failed retrieval and continues to be a limitation with these filters.« less

1975 Automotive Characteristics Data Base

DOT National Transportation Integrated Search

1976-10-01

A study of automobile characteristics as a supportive tool for auto energy consumption, fuel economy monitoring, and fleet analysis studies is presented. This report emphasizes the utility of efficient data retrieval methods in fuel economy analysis,...

A searching and reporting system for relational databases using a graph-based metadata representation.

PubMed

Hewitt, Robin; Gobbi, Alberto; Lee, Man-Ling

2005-01-01

Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.

Method for indexing and retrieving manufacturing-specific digital imagery based on image content

DOEpatents

Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

2004-06-15

A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

Implementation of a thesaurus in an electronic photograph imaging system

NASA Astrophysics Data System (ADS)

Partlow, Denise

1995-11-01

A photograph imaging system presents a unique set of requirements for indexing and retrieving images, unlike a standard imaging system for written documents. This paper presents the requirements, technical design, and development results for a hierarchical ANSI standard thesaurus embedded into a photograph archival system. The thesaurus design incorporates storage reduction techniques, permits fast searches, and contains flexible indexing methods. It can be extended to many applications other than the retrieval of photographs. When photographic images are indexed into an electronic system, they are subject to a variety of indexing problems based on what the indexer `sees.' For instance, the indexer may categorize an image as a boat when others might refer to it as a ship, sailboat, or raft. The thesaurus will allow a user to locate images containing any synonym for boat, regardless of how the image was actually indexed. In addition to indexing problems, photos may need to be retrieved based on a broad category, for instance, flowers. The thesaurus allows a search for `flowers' to locate all images containing a rose, hibiscus, or daisy, yet still allow a specific search for an image containing only a rose. The technical design and method of implementation for such a thesaurus is presented. The thesaurus is implemented using an SQL relational data base management system that supports blobs, binary large objects. The design incorporates unique compression methods for storing the thesaurus words. Words are indexed to photographs using the compressed word and allow for very rapid searches, eliminating lengthy string matches.