Integration of tools for binding archetypes to SNOMED CT

PubMed Central

Sundvall, Erik; Qamar, Rahil; Nyström, Mikael; Forss, Mattias; Petersson, Håkan; Karlsson, Daniel; Åhlfeldt, Hans; Rector, Alan

2008-01-01

Background The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems. Methods Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings. Results An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source. Conclusion Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail. PMID:19007444

Automated encoding of clinical documents based on natural language processing.

PubMed

Friedman, Carol; Shagina, Lyudmila; Lussier, Yves; Hripcsak, George

2004-01-01

The aim of this study was to develop a method based on natural language processing (NLP) that automatically maps an entire clinical document to codes with modifiers and to quantitatively evaluate the method. An existing NLP system, MedLEE, was adapted to automatically generate codes. The method involves matching of structured output generated by MedLEE consisting of findings and modifiers to obtain the most specific code. Recall and precision applied to Unified Medical Language System (UMLS) coding were evaluated in two separate studies. Recall was measured using a test set of 150 randomly selected sentences, which were processed using MedLEE. Results were compared with a reference standard determined manually by seven experts. Precision was measured using a second test set of 150 randomly selected sentences from which UMLS codes were automatically generated by the method and then validated by experts. Recall of the system for UMLS coding of all terms was .77 (95% CI.72-.81), and for coding terms that had corresponding UMLS codes recall was .83 (.79-.87). Recall of the system for extracting all terms was .84 (.81-.88). Recall of the experts ranged from .69 to .91 for extracting terms. The precision of the system was .89 (.87-.91), and precision of the experts ranged from .61 to .91. Extraction of relevant clinical information and UMLS coding were accomplished using a method based on NLP. The method appeared to be comparable to or better than six experts. The advantage of the method is that it maps text to codes along with other related information, rendering the coded output suitable for effective retrieval.

Automatic metro map layout using multicriteria optimization.

PubMed

Stott, Jonathan; Rodgers, Peter; Martínez-Ovando, Juan Carlos; Walker, Stephen G

2011-01-01

This paper describes an automatic mechanism for drawing metro maps. We apply multicriteria optimization to find effective placement of stations with a good line layout and to label the map unambiguously. A number of metrics are defined, which are used in a weighted sum to find a fitness value for a layout of the map. A hill climbing optimizer is used to reduce the fitness value, and find improved map layouts. To avoid local minima, we apply clustering techniques to the map-the hill climber moves both stations and clusters when finding improved layouts. We show the method applied to a number of metro maps, and describe an empirical study that provides some quantitative evidence that automatically-drawn metro maps can help users to find routes more efficiently than either published maps or undistorted maps. Moreover, we have found that, in these cases, study subjects indicate a preference for automatically-drawn maps over the alternatives. © 2011 IEEE Published by the IEEE Computer Society

A computational linguistics motivated mapping of ICPC-2 PLUS to SNOMED CT.

PubMed

Wang, Yefeng; Patrick, Jon; Miller, Graeme; O'Hallaran, Julie

2008-10-27

A great challenge in sharing data across information systems in general practice is the lack of interoperability between different terminologies or coding schema used in the information systems. Mapping of medical vocabularies to a standardised terminology is needed to solve data interoperability problems. We present a system to automatically map an interface terminology ICPC-2 PLUS to SNOMED CT. Three steps of mapping are proposed in this system. The UMLS metathesaurus mapping utilises explicit relationships between ICPC-2 PLUS and SNOMED CT terms in the UMLS library to perform the first stage of the mapping. Computational linguistic mapping uses natural language processing techniques and lexical similarities for the second stage of mapping between terminologies. Finally, the post-coordination mapping allows one ICPC-2 PLUS term to be mapped into an aggregation of two or more SNOMED CT terms. A total 5,971 of all 7,410 ICPC-2 terms (80.58%) were mapped to SNOMED CT using the three stages but with different levels of accuracy. UMLS mapping achieved the mapping of 53.0% ICPC2 PLUS terms to SNOMED CT with the precision rate of 96.46% and overall recall rate of 44.89%. Lexical mapping increased the result to 60.31% and post-coordination mapping gave an increase of 20.27% in mapped terms. A manual review of a part of the mapping shows that the precision of lexical mappings is around 90%. The accuracy of post-coordination has not been evaluated yet. Unmapped terms and mismatched terms are due to the differences in the structures between ICPC-2 PLUS and SNOMED CT. Terms contained in ICPC-2 PLUS but not in SNOMED CT caused a large proportion of the failures in the mappings. Mapping terminologies to a standard vocabulary is a way to facilitate consistent medical data exchange and achieve system interoperability and data standardisation. Broad scale mapping cannot be achieved by any single method and methods based on computational linguistics can be very useful for the task. Automating as much as is possible of this process turns the searching and mapping task into a validation task, which can effectively reduce the cost and increase the efficiency and accuracy of this task over manual methods.

Two-Phase chief complaint mapping to the UMLS metathesaurus in Korean electronic medical records.

PubMed

Kang, Bo-Yeong; Kim, Dae-Won; Kim, Hong-Gee

2009-01-01

The task of automatically determining the concepts referred to in chief complaint (CC) data from electronic medical records (EMRs) is an essential component of many EMR applications aimed at biosurveillance for disease outbreaks. Previous approaches that have been used for this concept mapping have mainly relied on term-level matching, whereby the medical terms in the raw text and their synonyms are matched with concepts in a terminology database. These previous approaches, however, have shortcomings that limit their efficacy in CC concept mapping, where the concepts for CC data are often represented by associative terms rather than by synonyms. Therefore, herein we propose a concept mapping scheme based on a two-phase matching approach, especially for application to Korean CCs, which uses term-level complete matching in the first phase and concept-level matching based on concept learning in the second phase. The proposed concept-level matching suggests the method to learn all the terms (associative terms as well as synonyms) that represent the concept and predict the most probable concept for a CC based on the learned terms. Experiments on 1204 CCs extracted from 15,618 discharge summaries of Korean EMRs showed that the proposed method gave significantly improved F-measure values compared to the baseline system, with improvements of up to 73.57%.

Real-time forecasts of tomorrow's earthquakes in California: a new mapping tool

USGS Publications Warehouse

Gerstenberger, Matt; Wiemer, Stefan; Jones, Lucy

2004-01-01

We have derived a multi-model approach to calculate time-dependent earthquake hazard resulting from earthquake clustering. This file report explains the theoretical background behind the approach, the specific details that are used in applying the method to California, as well as the statistical testing to validate the technique. We have implemented our algorithm as a real-time tool that has been automatically generating short-term hazard maps for California since May of 2002, at http://step.wr.usgs.gov

Functional-to-form mapping for assembly design automation

NASA Astrophysics Data System (ADS)

Xu, Z. G.; Liu, W. M.; Shen, W. D.; Yang, D. Y.; Liu, T. T.

2017-11-01

Assembly-level function-to-form mapping is the most effective procedure towards design automation. The research work mainly includes: the assembly-level function definitions, product network model and the two-step mapping mechanisms. The function-to-form mapping is divided into two steps, i.e. mapping of function-to-behavior, called the first-step mapping, and the second-step mapping, i.e. mapping of behavior-to-structure. After the first step mapping, the three dimensional transmission chain (or 3D sketch) is studied, and the feasible design computing tools are developed. The mapping procedure is relatively easy to be implemented interactively, but, it is quite difficult to finish it automatically. So manual, semi-automatic, automatic and interactive modification of the mapping model are studied. A mechanical hand F-F mapping process is illustrated to verify the design methodologies.

Mapping nursing diagnosis nomenclatures for coordinated care.

PubMed

Zielstorff, R D; Tronni, C; Basque, J; Griffin, L R; Welebob, E M

1998-01-01

To map the problem or diagnosis terms from three nomenclatures, term to term, to determine commonalities and differences; and to determine whether it is possible to develop a single vocabulary that contains the best features of all. When different nomenclatures are used in different settings, continuity of care is hampered by the need to re-state problems and interventions. The sample for this descriptive analysis was 396 terms from three nursing diagnosis and problem nomenclatures recognized by the American Nurses Association: the North American Nursing Diagnosis Association (NANDA) Approved List, the Home Health Care Classification (HHCC), and the Omaha System. Terms from each of the three nomenclatures were mapped to terms in each of the others. Consensus methods were used to resolve differences in mapping decisions. Terms were characterized as "Same," "Similar," "Broader," "Narrower," and "No Match." Validation of consistency and accuracy was done by reverse mapping, use of syllogisms, use of taxonomic groupings, and expert review. Of 396 terms, 21 concepts accounting for 63 terms were found to be the same or similar in all three nomenclatures; 91 terms were unique to the nomenclature in which they were found ("No Match"). The remaining 242 terms had a narrower or broader relationship to at least one term in another nomenclature. In all three nomenclatures, inconsistencies existed in level of abstractness of the diagnosis or problem terms, and in definition and placement of terms within their own taxonomic structure. Because of differences in structure and incompatible taxonomic arrangements, a master list of "preferred terms" taken from the three nomenclatures is not feasible. However, the mappings are useful for determining commonalities and the unique contributions of each nomenclature, which can facilitate the development of a uniform language for nursing diagnoses. The mapping can also form the basis for automatic translation of computer-stored nursing diagnoses from one setting to another when different nomenclatures are used.

Test of a potential link between analytic and nonanalytic category learning and automatic, effortful processing.

PubMed

Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J

2001-08-01

The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.

Mapping of medical acronyms and initialisms to Medical Subject Headings (MeSH) across selected systems

PubMed Central

Shultz, Mary

2006-01-01

Introduction: Given the common use of acronyms and initialisms in the health sciences, searchers may be entering these abbreviated terms rather than full phrases when searching online systems. The purpose of this study is to evaluate how various MEDLINE Medical Subject Headings (MeSH) interfaces map acronyms and initialisms to the MeSH vocabulary. Methods: The interfaces used in this study were: the PubMed MeSH database, the PubMed Automatic Term Mapping feature, the NLM Gateway Term Finder, and Ovid MEDLINE. Acronyms and initialisms were randomly selected from 2 print sources. The test data set included 415 randomly selected acronyms and initialisms whose related meanings were found to be MeSH terms. Each acronym and initialism was entered into each MEDLINE MeSH interface to determine if it mapped to the corresponding MeSH term. Separately, 46 commonly used acronyms and initialisms were tested. Results: While performance differed widely, the success rates were low across all interfaces for the randomly selected terms. The common acronyms and initialisms tested at higher success rates across the interfaces, but the differences between the interfaces remained. Conclusion: Online interfaces do not always map medical acronyms and initialisms to their corresponding MeSH phrases. This may lead to inaccurate results and missed information if acronyms and initialisms are used in search strategies. PMID:17082832

Automated mapping of clinical terms into SNOMED-CT. An application to codify procedures in pathology.

PubMed

Allones, J L; Martinez, D; Taboada, M

2014-10-01

Clinical terminologies are considered a key technology for capturing clinical data in a precise and standardized manner, which is critical to accurately exchange information among different applications, medical records and decision support systems. An important step to promote the real use of clinical terminologies, such as SNOMED-CT, is to facilitate the process of finding mappings between local terms of medical records and concepts of terminologies. In this paper, we propose a mapping tool to discover text-to-concept mappings in SNOMED-CT. Name-based techniques were combined with a query expansion system to generate alternative search terms, and with a strategy to analyze and take advantage of the semantic relationships of the SNOMED-CT concepts. The developed tool was evaluated and compared to the search services provided by two SNOMED-CT browsers. Our tool automatically mapped clinical terms from a Spanish glossary of procedures in pathology with 88.0% precision and 51.4% recall, providing a substantial improvement of recall (28% and 60%) over other publicly accessible mapping services. The improvements reached by the mapping tool are encouraging. Our results demonstrate the feasibility of accurately mapping clinical glossaries to SNOMED-CT concepts, by means a combination of structural, query expansion and named-based techniques. We have shown that SNOMED-CT is a great source of knowledge to infer synonyms for the medical domain. Results show that an automated query expansion system overcomes the challenge of vocabulary mismatch partially.

3D models mapping optimization through an integrated parameterization approach: cases studies from Ravenna

NASA Astrophysics Data System (ADS)

Cipriani, L.; Fantini, F.; Bertacchi, S.

2014-06-01

Image-based modelling tools based on SfM algorithms gained great popularity since several software houses provided applications able to achieve 3D textured models easily and automatically. The aim of this paper is to point out the importance of controlling models parameterization process, considering that automatic solutions included in these modelling tools can produce poor results in terms of texture utilization. In order to achieve a better quality of textured models from image-based modelling applications, this research presents a series of practical strategies aimed at providing a better balance between geometric resolution of models from passive sensors and their corresponding (u,v) map reference systems. This aspect is essential for the achievement of a high-quality 3D representation, since "apparent colour" is a fundamental aspect in the field of Cultural Heritage documentation. Complex meshes without native parameterization have to be "flatten" or "unwrapped" in the (u,v) parameter space, with the main objective to be mapped with a single image. This result can be obtained by using two different strategies: the former automatic and faster, while the latter manual and time-consuming. Reverse modelling applications provide automatic solutions based on splitting the models by means of different algorithms, that produce a sort of "atlas" of the original model in the parameter space, in many instances not adequate and negatively affecting the overall quality of representation. Using in synergy different solutions, ranging from semantic aware modelling techniques to quad-dominant meshes achieved using retopology tools, it is possible to obtain a complete control of the parameterization process.

Automatic crown cover mapping to improve forest inventory

Treesearch

Claude Vidal; Jean-Guy Boureau; Nicolas Robert; Nicolas Py; Josiane Zerubia; Xavier Descombes; Guillaume Perrin

2009-01-01

To automatically analyze near infrared aerial photographs, the French National Institute for Research in Computer Science and Control developed together with the French National Forest Inventory (NFI) a method for automatic crown cover mapping. This method uses a Reverse Jump Monte Carlo Markov Chain algorithm to locate the crowns and describe those using ellipses or...

Semi-automatic mapping of cultural heritage from airborne laser scanning using deep learning

NASA Astrophysics Data System (ADS)

Due Trier, Øivind; Salberg, Arnt-Børre; Holger Pilø, Lars; Tonning, Christer; Marius Johansen, Hans; Aarsten, Dagrun

2016-04-01

This paper proposes to use deep learning to improve semi-automatic mapping of cultural heritage from airborne laser scanning (ALS) data. Automatic detection methods, based on traditional pattern recognition, have been applied in a number of cultural heritage mapping projects in Norway for the past five years. Automatic detection of pits and heaps have been combined with visual interpretation of the ALS data for the mapping of deer hunting systems, iron production sites, grave mounds and charcoal kilns. However, the performance of the automatic detection methods varies substantially between ALS datasets. For the mapping of deer hunting systems on flat gravel and sand sediment deposits, the automatic detection results were almost perfect. However, some false detections appeared in the terrain outside of the sediment deposits. These could be explained by other pit-like landscape features, like parts of river courses, spaces between boulders, and modern terrain modifications. However, these were easy to spot during visual interpretation, and the number of missed individual pitfall traps was still low. For the mapping of grave mounds, the automatic method produced a large number of false detections, reducing the usefulness of the semi-automatic approach. The mound structure is a very common natural terrain feature, and the grave mounds are less distinct in shape than the pitfall traps. Still, applying automatic mound detection on an entire municipality did lead to a new discovery of an Iron Age grave field with more than 15 individual mounds. Automatic mound detection also proved to be useful for a detailed re-mapping of Norway's largest Iron Age grave yard, which contains almost 1000 individual graves. Combined pit and mound detection has been applied to the mapping of more than 1000 charcoal kilns that were used by an iron work 350-200 years ago. The majority of charcoal kilns were indirectly detected as either pits on the circumference, a central mound, or both. However, kilns with a flat interior and a shallow ditch along the circumference were often missed by the automatic detection method. The successfulness of automatic detection seems to depend on two factors: (1) the density of ALS ground hits on the cultural heritage structures being sought, and (2) to what extent these structures stand out from natural terrain structures. The first factor may, to some extent, be improved by using a higher number of ALS pulses per square meter. The second factor is difficult to change, and also highlights another challenge: how to make a general automatic method that is applicable in all types of terrain within a country. The mixed experience with traditional pattern recognition for semi-automatic mapping of cultural heritage led us to consider deep learning as an alternative approach. The main principle is that a general feature detector has been trained on a large image database. The feature detector is then tailored to a specific task by using a modest number of images of true and false examples of the features being sought. Results of using deep learning are compared with previous results using traditional pattern recognition.

Initial Experience With Ultra High-Density Mapping of Human Right Atria.

PubMed

Bollmann, Andreas; Hilbert, Sebastian; John, Silke; Kosiuk, Jedrzej; Hindricks, Gerhard

2016-02-01

Recently, an automatic, high-resolution mapping system has been presented to accurately and quickly identify right atrial geometry and activation patterns in animals, but human data are lacking. This study aims to assess the clinical feasibility and accuracy of high-density electroanatomical mapping of various RA arrhythmias. Electroanatomical maps of the RA (35 partial and 24 complete) were created in 23 patients using a novel mini-basket catheter with 64 electrodes and automatic electrogram annotation. Median acquisition time was 6:43 minutes (0:39-23:05 minutes) with shorter times for partial (4.03 ± 4.13 minutes) than for complete maps (9.41 ± 4.92 minutes). During mapping 3,236 (710-16,306) data points were automatically annotated without manual correction. Maps obtained during sinus rhythm created geometry consistent with CT imaging and demonstrated activation originating at the middle to superior crista terminalis, while maps during CS pacing showed right atrial activation beginning at the infero-septal region. Activation patterns were consistent with cavotricuspid isthmus-dependent atrial flutter (n = 4), complex reentry tachycardia (n = 1), or ectopic atrial tachycardia (n = 2). His bundle and fractionated potentials in the slow pathway region were automatically detected in all patients. Ablation of the cavotricuspid isthmus (n = 9), the atrio-ventricular node (n = 2), atrial ectopy (n = 2), and the slow pathway (n = 3) was successfully and safely performed. RA mapping with this automatic high-density mapping system is fast, feasible, and safe. It is possible to reproducibly identify propagation of atrial activation during sinus rhythm, various tachycardias, and also complex reentrant arrhythmias. © 2015 Wiley Periodicals, Inc.

Semi-Automatic Terminology Generation for Information Extraction from German Chest X-Ray Reports.

PubMed

Krebs, Jonathan; Corovic, Hamo; Dietrich, Georg; Ertl, Max; Fette, Georg; Kaspar, Mathias; Krug, Markus; Stoerk, Stefan; Puppe, Frank

2017-01-01

Extraction of structured data from textual reports is an important subtask for building medical data warehouses for research and care. Many medical and most radiology reports are written in a telegraphic style with a concatenation of noun phrases describing the presence or absence of findings. Therefore a lexico-syntactical approach is promising, where key terms and their relations are recognized and mapped on a predefined standard terminology (ontology). We propose a two-phase algorithm for terminology matching: In the first pass, a local terminology for recognition is derived as close as possible to the terms used in the radiology reports. In the second pass, the local terminology is mapped to a standard terminology. In this paper, we report on an algorithm for the first step of semi-automatic generation of the local terminology and evaluate the algorithm with radiology reports of chest X-ray examinations from Würzburg university hospital. With an effort of about 20 hours work of a radiologist as domain expert and 10 hours for meetings, a local terminology with about 250 attributes and various value patterns was built. In an evaluation with 100 randomly chosen reports it achieved an F1-Score of about 95% for information extraction.

UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text.

PubMed

Demner-Fushman, Dina; Mork, James G; Shooshan, Sonya E; Aronson, Alan R

2010-08-01

Identification of medical terms in free text is a first step in such Natural Language Processing (NLP) tasks as automatic indexing of biomedical literature and extraction of patients' problem lists from the text of clinical notes. Many tools developed to perform these tasks use biomedical knowledge encoded in the Unified Medical Language System (UMLS) Metathesaurus. We continue our exploration of automatic approaches to creation of subsets (UMLS content views) which can support NLP processing of either the biomedical literature or clinical text. We found that suppression of highly ambiguous terms in the conservative AutoFilter content view can partially replace manual filtering for literature applications, and suppression of two character mappings in the same content view achieves 89.5% precision at 78.6% recall for clinical applications. Published by Elsevier Inc.

Assessing the impact of graphical quality on automatic text recognition in digital maps

NASA Astrophysics Data System (ADS)

Chiang, Yao-Yi; Leyk, Stefan; Honarvar Nazari, Narges; Moghaddam, Sima; Tan, Tian Xiang

2016-08-01

Converting geographic features (e.g., place names) in map images into a vector format is the first step for incorporating cartographic information into a geographic information system (GIS). With the advancement in computational power and algorithm design, map processing systems have been considerably improved over the last decade. However, the fundamental map processing techniques such as color image segmentation, (map) layer separation, and object recognition are sensitive to minor variations in graphical properties of the input image (e.g., scanning resolution). As a result, most map processing results would not meet user expectations if the user does not "properly" scan the map of interest, pre-process the map image (e.g., using compression or not), and train the processing system, accordingly. These issues could slow down the further advancement of map processing techniques as such unsuccessful attempts create a discouraged user community, and less sophisticated tools would be perceived as more viable solutions. Thus, it is important to understand what kinds of maps are suitable for automatic map processing and what types of results and process-related errors can be expected. In this paper, we shed light on these questions by using a typical map processing task, text recognition, to discuss a number of map instances that vary in suitability for automatic processing. We also present an extensive experiment on a diverse set of scanned historical maps to provide measures of baseline performance of a standard text recognition tool under varying map conditions (graphical quality) and text representations (that can vary even within the same map sheet). Our experimental results help the user understand what to expect when a fully or semi-automatic map processing system is used to process a scanned map with certain (varying) graphical properties and complexities in map content.

Rheticus Displacement: an Automatic Geo-Information Service Platform for Ground Instabilities Detection and Monitoring

NASA Astrophysics Data System (ADS)

Chiaradia, M. T.; Samarelli, S.; Agrimano, L.; Lorusso, A. P.; Nutricato, R.; Nitti, D. O.; Morea, A.; Tijani, K.

2016-12-01

Rheticus® is an innovative cloud-based data and services hub able to deliver Earth Observation added-value products through automatic complex processes and a minimum interaction with human operators. This target is achieved by means of programmable components working as different software layers in a modern enterprise system which relies on SOA (service-oriented-architecture) model. Due to its architecture, where every functionality is well defined and encapsulated in a standalone component, Rheticus is potentially highly scalable and distributable allowing different configurations depending on the user needs. Rheticus offers a portfolio of services, ranging from the detection and monitoring of geohazards and infrastructural instabilities, to marine water quality monitoring, wildfires detection or land cover monitoring. In this work, we outline the overall cloud-based platform and focus on the "Rheticus Displacement" service, aimed at providing accurate information to monitor movements occurring across landslide features or structural instabilities that could affect buildings or infrastructures. Using Sentinel-1 (S1) open data images and Multi-Temporal SAR Interferometry techniques (i.e., SPINUA), the service is complementary to traditional survey methods, providing a long-term solution to slope instability monitoring. Rheticus automatically browses and accesses (on a weekly basis) the products of the rolling archive of ESA S1 Scientific Data Hub; S1 data are then handled by a mature running processing chain, which is responsible of producing displacement maps immediately usable to measure with sub-centimetric precision movements of coherent points. Examples are provided, concerning the automatic displacement map generation process, as well as the integration of point and distributed scatterers, the integration of multi-sensors displacement maps (e.g., Sentinel-1 IW and COSMO-SkyMed HIMAGE), the combination of displacement rate maps acquired along both ascending and descending passes. ACK: Study carried out in the framework of the FAST4MAP project and co-funded by the Italian Space Agency (Contract n. 2015-020-R.0). Sentinel-1A products provided by ESA. CSK® Products, ASI, provided by ASI under a license to use. Rheticus® is a registered trademark of Planetek Italia srl.

Tools for model-building with cryo-EM maps

DOE PAGES

Terwilliger, Thomas Charles

2018-01-01

There are new tools available to you in Phenix for interpreting cryo-EM maps. You can automatically sharpen (or blur) a map with phenix.auto_sharpen and you can segment a map with phenix.segment_and_split_map. If you have overlapping partial models for a map, you can merge them with phenix.combine_models. If you have a protein-RNA complex and protein chains have been accidentally built in the RNA region, you can try to remove them with phenix.remove_poor_fragments. You can put these together and automatically sharpen, segment and build a map with phenix.map_to_model.

Tools for model-building with cryo-EM maps

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

Terwilliger, Thomas Charles

There are new tools available to you in Phenix for interpreting cryo-EM maps. You can automatically sharpen (or blur) a map with phenix.auto_sharpen and you can segment a map with phenix.segment_and_split_map. If you have overlapping partial models for a map, you can merge them with phenix.combine_models. If you have a protein-RNA complex and protein chains have been accidentally built in the RNA region, you can try to remove them with phenix.remove_poor_fragments. You can put these together and automatically sharpen, segment and build a map with phenix.map_to_model.

Automatic and Controlled Response Inhibition: Associative Learning in the Go/No-Go and Stop-Signal Paradigms

PubMed Central

Verbruggen, Frederick; Logan, Gordon D.

2008-01-01

In five experiments, the authors examined the development of automatic response inhibition in the go/no-go paradigm and a modified version of the stop-signal paradigm. They hypothesized that automatic response inhibition may develop over practice when stimuli are consistently associated with stopping. All five experiments consisted of a training phase and a test phase in which the stimulus mapping was reversed for a subset of the stimuli. Consistent with the automatic-inhibition hypothesis, the authors found that responding in the test phase was slowed when the stimulus had been consistently associated with stopping in the training phase. In addition, they found that response inhibition benefited from consistent stimulus-stop associations. These findings suggest that response inhibition may rely on the retrieval of stimulus-stop associations after practice with consistent stimulus-stop mappings. Stimulus-stop mapping is typically consistent in the go/no-go paradigm, so automatic inhibition is likely to occur. However, stimulus-stop mapping is typically inconsistent in the stop-signal paradigm, so automatic inhibition is unlikely to occur. Thus, the results suggest that the two paradigms are not equivalent because they allow different kinds of response inhibition. PMID:18999358

Automatic Scaffolding and Measurement of Concept Mapping for EFL Students to Write Summaries

ERIC Educational Resources Information Center

Yang, Yu-Fen

2015-01-01

An incorrect concept map may obstruct a student's comprehension when writing summaries if they are unable to grasp key concepts when reading texts. The purpose of this study was to investigate the effects of automatic scaffolding and measurement of three-layer concept maps on improving university students' writing summaries. The automatic…

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

NASA Technical Reports Server (NTRS)

Tarabalka, Y.; Tilton, J. C.; Benediktsson, J. A.; Chanussot, J.

2012-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Using UMLS to construct a generalized hierarchical concept-based dictionary of brain functions for information extraction from the fMRI literature.

PubMed

Hsiao, Mei-Yu; Chen, Chien-Chung; Chen, Jyh-Horng

2009-10-01

With a rapid progress in the field, a great many fMRI studies are published every year, to the extent that it is now becoming difficult for researchers to keep up with the literature, since reading papers is extremely time-consuming and labor-intensive. Thus, automatic information extraction has become an important issue. In this study, we used the Unified Medical Language System (UMLS) to construct a hierarchical concept-based dictionary of brain functions. To the best of our knowledge, this is the first generalized dictionary of this kind. We also developed an information extraction system for recognizing, mapping and classifying terms relevant to human brain study. The precision and recall of our system was on a par with that of human experts in term recognition, term mapping and term classification. Our approach presented in this paper presents an alternative to the more laborious, manual entry approach to information extraction.

Automatic photointerpretation for land use management in Minnesota

NASA Technical Reports Server (NTRS)

Swanlund, G. D. (Principal Investigator); Kirvida, L.; Cheung, M.; Pile, D.; Zirkle, R.

1974-01-01

The author has identified the following significant results. Automatic photointerpretation techniques were utilized to evaluate the feasibility of data for land use management. It was shown that ERTS-1 MSS data can produce thematic maps of adequate resolution and accuracy to update land use maps. In particular, five typical land use areas were mapped with classification accuracies ranging from 77% to over 90%.

Challenges and Opportunities: One Stop Processing of Automatic Large-Scale Base Map Production Using Airborne LIDAR Data Within GIS Environment. Case Study: Makassar City, Indonesia

NASA Astrophysics Data System (ADS)

Widyaningrum, E.; Gorte, B. G. H.

2017-05-01

LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is considered a powerful and efficient approach for the base map provision. The quality of the automated topographic base map is assessed and analysed based on its completeness, correctness, quality, and the confusion matrix.

A semi-automatic 2D-to-3D video conversion with adaptive key-frame selection

NASA Astrophysics Data System (ADS)

Ju, Kuanyu; Xiong, Hongkai

2014-11-01

To compensate the deficit of 3D content, 2D to 3D video conversion (2D-to-3D) has recently attracted more attention from both industrial and academic communities. The semi-automatic 2D-to-3D conversion which estimates corresponding depth of non-key-frames through key-frames is more desirable owing to its advantage of balancing labor cost and 3D effects. The location of key-frames plays a role on quality of depth propagation. This paper proposes a semi-automatic 2D-to-3D scheme with adaptive key-frame selection to keep temporal continuity more reliable and reduce the depth propagation errors caused by occlusion. The potential key-frames would be localized in terms of clustered color variation and motion intensity. The distance of key-frame interval is also taken into account to keep the accumulated propagation errors under control and guarantee minimal user interaction. Once their depth maps are aligned with user interaction, the non-key-frames depth maps would be automatically propagated by shifted bilateral filtering. Considering that depth of objects may change due to the objects motion or camera zoom in/out effect, a bi-directional depth propagation scheme is adopted where a non-key frame is interpolated from two adjacent key frames. The experimental results show that the proposed scheme has better performance than existing 2D-to-3D scheme with fixed key-frame interval.

Automatic categorization of land-water cover types of the Green Swamp, Florida, using Skylab multispectral scanner (S-192) data

NASA Technical Reports Server (NTRS)

Coker, A. E.; Higer, A. L.; Rogers, R. H.; Shah, N. J.; Reed, L. E.; Walker, S.

1975-01-01

The techniques used and the results achieved in the successful application of Skylab Multispectral Scanner (EREP S-192) high-density digital tape data for the automatic categorizing and mapping of land-water cover types in the Green Swamp of Florida were summarized. Data was provided from Skylab pass number 10 on 13 June 1973. Significant results achieved included the automatic mapping of a nine-category and a three-category land-water cover map of the Green Swamp. The land-water cover map was used to make interpretations of a hydrologic condition in the Green Swamp. This type of use marks a significant breakthrough in the processing and utilization of EREP S-192 data.

A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

NASA Astrophysics Data System (ADS)

Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

2013-04-01

There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood, UK and March 2010 Red River flood, US) observed by high-resolution SAR sensors as well as airborne photography highlight advantages and limitations of the online application. A mid-term target is the exploitation of ESA SENTINEL 1 SAR data streams. In the long term it is foreseen to develop a potential extension of the application for systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis. On-going research activities investigate the usefulness of the method for mapping flood hazard at global scale using databases of historic SAR remote sensing-derived flood inundation maps.

Automatic spatiotemporal matching of detected pleural thickenings

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

A multi-part matching strategy for mapping LOINC with laboratory terminologies

PubMed Central

Lee, Li-Hui; Groß, Anika; Hartung, Michael; Liou, Der-Ming; Rahm, Erhard

2014-01-01

Objective To address the problem of mapping local laboratory terminologies to Logical Observation Identifiers Names and Codes (LOINC). To study different ontology matching algorithms and investigate how the probability of term combinations in LOINC helps to increase match quality and reduce manual effort. Materials and methods We proposed two matching strategies: full name and multi-part. The multi-part approach also considers the occurrence probability of combined concept parts. It can further recommend possible combinations of concept parts to allow more local terms to be mapped. Three real-world laboratory databases from Taiwanese hospitals were used to validate the proposed strategies with respect to different quality measures and execution run time. A comparison with the commonly used tool, Regenstrief LOINC Mapping Assistant (RELMA) Lab Auto Mapper (LAM), was also carried out. Results The new multi-part strategy yields the best match quality, with F-measure values between 89% and 96%. It can automatically match 70–85% of the laboratory terminologies to LOINC. The recommendation step can further propose mapping to (proposed) LOINC concepts for 9–20% of the local terminology concepts. On average, 91% of the local terminology concepts can be correctly mapped to existing or newly proposed LOINC concepts. Conclusions The mapping quality of the multi-part strategy is significantly better than that of LAM. It enables domain experts to perform LOINC matching with little manual work. The probability of term combinations proved to be a valuable strategy for increasing the quality of match results, providing recommendations for proposed LOINC conepts, and decreasing the run time for match processing. PMID:24363318

Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search

PubMed Central

Fang, Leyuan; Cunefare, David; Wang, Chong; Guymer, Robyn H.; Li, Shutao; Farsiu, Sina

2017-01-01

We present a novel framework combining convolutional neural networks (CNN) and graph search methods (termed as CNN-GS) for the automatic segmentation of nine layer boundaries on retinal optical coherence tomography (OCT) images. CNN-GS first utilizes a CNN to extract features of specific retinal layer boundaries and train a corresponding classifier to delineate a pilot estimate of the eight layers. Next, a graph search method uses the probability maps created from the CNN to find the final boundaries. We validated our proposed method on 60 volumes (2915 B-scans) from 20 human eyes with non-exudative age-related macular degeneration (AMD), which attested to effectiveness of our proposed technique. PMID:28663902

Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search.

PubMed

Fang, Leyuan; Cunefare, David; Wang, Chong; Guymer, Robyn H; Li, Shutao; Farsiu, Sina

2017-05-01

We present a novel framework combining convolutional neural networks (CNN) and graph search methods (termed as CNN-GS) for the automatic segmentation of nine layer boundaries on retinal optical coherence tomography (OCT) images. CNN-GS first utilizes a CNN to extract features of specific retinal layer boundaries and train a corresponding classifier to delineate a pilot estimate of the eight layers. Next, a graph search method uses the probability maps created from the CNN to find the final boundaries. We validated our proposed method on 60 volumes (2915 B-scans) from 20 human eyes with non-exudative age-related macular degeneration (AMD), which attested to effectiveness of our proposed technique.

Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic stimulation.

PubMed

Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P

2015-09-30

The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.

Segmentation of stereo terrain images

NASA Astrophysics Data System (ADS)

George, Debra A.; Privitera, Claudio M.; Blackmon, Theodore T.; Zbinden, Eric; Stark, Lawrence W.

2000-06-01

We have studied four approaches to segmentation of images: three automatic ones using image processing algorithms and a fourth approach, human manual segmentation. We were motivated toward helping with an important NASA Mars rover mission task -- replacing laborious manual path planning with automatic navigation of the rover on the Mars terrain. The goal of the automatic segmentations was to identify an obstacle map on the Mars terrain to enable automatic path planning for the rover. The automatic segmentation was first explored with two different segmentation methods: one based on pixel luminance, and the other based on pixel altitude generated through stereo image processing. The third automatic segmentation was achieved by combining these two types of image segmentation. Human manual segmentation of Martian terrain images was used for evaluating the effectiveness of the combined automatic segmentation as well as for determining how different humans segment the same images. Comparisons between two different segmentations, manual or automatic, were measured using a similarity metric, SAB. Based on this metric, the combined automatic segmentation did fairly well in agreeing with the manual segmentation. This was a demonstration of a positive step towards automatically creating the accurate obstacle maps necessary for automatic path planning and rover navigation.

Automatic transfer function design for medical visualization using visibility distributions and projective color mapping.

PubMed

Cai, Lile; Tay, Wei-Liang; Nguyen, Binh P; Chui, Chee-Kong; Ong, Sim-Heng

2013-01-01

Transfer functions play a key role in volume rendering of medical data, but transfer function manipulation is unintuitive and can be time-consuming; achieving an optimal visualization of patient anatomy or pathology is difficult. To overcome this problem, we present a system for automatic transfer function design based on visibility distribution and projective color mapping. Instead of assigning opacity directly based on voxel intensity and gradient magnitude, the opacity transfer function is automatically derived by matching the observed visibility distribution to a target visibility distribution. An automatic color assignment scheme based on projective mapping is proposed to assign colors that allow for the visual discrimination of different structures, while also reflecting the degree of similarity between them. When our method was tested on several medical volumetric datasets, the key structures within the volume were clearly visualized with minimal user intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Taxonomic classification of soils using digital information from LANDSAT data. Huayllamarca and eucaliptus areas. M.S. Thesis - Bolivia Univ.

NASA Technical Reports Server (NTRS)

Quiroga, S. Q.

1977-01-01

The applicability of LANDSAT digital information to soil mapping is described. A compilation of all cartographic information and bibliography of the study area is made. LANDSAT MSS images on a scale of 1:250,000 are interpreted and a physiographic map with legend is prepared. The study area is inspected and a selection of the sample areas is made. A digital map of the different soil units is produced and the computer mapping units are checked against the soil units encountered in the field. The soil boundaries obtained by automatic mapping were not substantially changed by field work. The accuracy of the automatic mapping is rather high.

Architecture for Cyber Defense Simulator in Military Applications

DTIC Science & Technology

2013-06-01

ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5977648&isnumber=5977431 [18] Goodall , J.R.; D’Amico, A.; Kopylec, J.K.; , "Camus: Automatically mapping...isnumber=5977431 • [18] Goodall , J.R.; D’Amico, A.; Kopylec, J.K.; , "Camus: Automatically mapping Cyber Assets to Missions and Users," Military

Automatic Texture Mapping of Architectural and Archaeological 3d Models

NASA Astrophysics Data System (ADS)

Kersten, T. P.; Stallmann, D.

2012-07-01

Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage) algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.

The Greek National Observatory of Forest Fires (NOFFi)

NASA Astrophysics Data System (ADS)

Tompoulidou, Maria; Stefanidou, Alexandra; Grigoriadis, Dionysios; Dragozi, Eleni; Stavrakoudis, Dimitris; Gitas, Ioannis Z.

2016-08-01

Efficient forest fire management is a key element for alleviating the catastrophic impacts of wildfires. Overall, the effective response to fire events necessitates adequate planning and preparedness before the start of the fire season, as well as quantifying the environmental impacts in case of wildfires. Moreover, the estimation of fire danger provides crucial information required for the optimal allocation and distribution of the available resources. The Greek National Observatory of Forest Fires (NOFFi)—established by the Greek Forestry Service in collaboration with the Laboratory of Forest Management and Remote Sensing of the Aristotle University of Thessaloniki and the International Balkan Center—aims to develop a series of modern products and services for supporting the efficient forest fire prevention management in Greece and the Balkan region, as well as to stimulate the development of transnational fire prevention and impacts mitigation policies. More specifically, NOFFi provides three main fire-related products and services: a) a remote sensing-based fuel type mapping methodology, b) a semi-automatic burned area mapping service, and c) a dynamically updatable fire danger index providing mid- to long-term predictions. The fuel type mapping methodology was developed and applied across the country, following an object-oriented approach and using Landsat 8 OLI satellite imagery. The results showcase the effectiveness of the generated methodology in obtaining highly accurate fuel type maps on a national level. The burned area mapping methodology was developed as a semi-automatic object-based classification process, carefully crafted to minimize user interaction and, hence, be easily applicable on a near real-time operational level as well as for mapping historical events. NOFFi's products can be visualized through the interactive Fire Forest portal, which allows the involvement and awareness of the relevant stakeholders via the Public Participation GIS (PPGIS) tool.

A State-of-the-Art Assessment of Automatic Name Placement.

DTIC Science & Technology

1986-08-01

develop an automatic name placement system. 11 Balodis, M., "Positioning of typography on maps," Proc. ACSM Pall Con- vention, Salt Lake City, Utah, Sept...1983, pp. 28-44. This article deals with the selection of typography for maps. It describes psycho-visual experiments with groups of individuals to...Polytechnic Institute, Troy, NY 12181, May 1984. (Also available as Tech. Rept. IPL-TR-063.) SBalodis, M., "Positioning of typography on maps," Proc

Accurate and Fully Automatic Hippocampus Segmentation Using Subject-Specific 3D Optimal Local Maps Into a Hybrid Active Contour Model

PubMed Central

Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-01-01

Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866

Automatic Collision Avoidance Technology (ACAT)

NASA Technical Reports Server (NTRS)

Swihart, Donald E.; Skoog, Mark A.

2007-01-01

This document represents two views of the Automatic Collision Avoidance Technology (ACAT). One viewgraph presentation reviews the development and system design of Automatic Collision Avoidance Technology (ACAT). Two types of ACAT exist: Automatic Ground Collision Avoidance (AGCAS) and Automatic Air Collision Avoidance (AACAS). The AGCAS Uses Digital Terrain Elevation Data (DTED) for mapping functions, and uses Navigation data to place aircraft on map. It then scans DTED in front of and around aircraft and uses future aircraft trajectory (5g) to provide automatic flyup maneuver when required. The AACAS uses data link to determine position and closing rate. It contains several canned maneuvers to avoid collision. Automatic maneuvers can occur at last instant and both aircraft maneuver when using data link. The system can use sensor in place of data link. The second viewgraph presentation reviews the development of a flight test and an evaluation of the test. A review of the operation and comparison of the AGCAS and a pilot's performance are given. The same review is given for the AACAS is given.

Normalizing biomedical terms by minimizing ambiguity and variability

PubMed Central

Tsuruoka, Yoshimasa; McNaught, John; Ananiadou, Sophia

2008-01-01

Background One of the difficulties in mapping biomedical named entities, e.g. genes, proteins, chemicals and diseases, to their concept identifiers stems from the potential variability of the terms. Soft string matching is a possible solution to the problem, but its inherent heavy computational cost discourages its use when the dictionaries are large or when real time processing is required. A less computationally demanding approach is to normalize the terms by using heuristic rules, which enables us to look up a dictionary in a constant time regardless of its size. The development of good heuristic rules, however, requires extensive knowledge of the terminology in question and thus is the bottleneck of the normalization approach. Results We present a novel framework for discovering a list of normalization rules from a dictionary in a fully automated manner. The rules are discovered in such a way that they minimize the ambiguity and variability of the terms in the dictionary. We evaluated our algorithm using two large dictionaries: a human gene/protein name dictionary built from BioThesaurus and a disease name dictionary built from UMLS. Conclusions The experimental results showed that automatically discovered rules can perform comparably to carefully crafted heuristic rules in term mapping tasks, and the computational overhead of rule application is small enough that a very fast implementation is possible. This work will help improve the performance of term-concept mapping tasks in biomedical information extraction especially when good normalization heuristics for the target terminology are not fully known. PMID:18426547

Automatic map generalisation from research to production

NASA Astrophysics Data System (ADS)

Nyberg, Rose; Johansson, Mikael; Zhang, Yang

2018-05-01

The manual work of map generalisation is known to be a complex and time consuming task. With the development of technology and societies, the demands for more flexible map products with higher quality are growing. The Swedish mapping, cadastral and land registration authority Lantmäteriet has manual production lines for databases in five different scales, 1 : 10 000 (SE10), 1 : 50 000 (SE50), 1 : 100 000 (SE100), 1 : 250 000 (SE250) and 1 : 1 million (SE1M). To streamline this work, Lantmäteriet started a project to automatically generalise geographic information. Planned timespan for the project is 2015-2022. Below the project background together with the methods for the automatic generalisation are described. The paper is completed with a description of results and conclusions.

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

PubMed Central

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

2009-01-01

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

ActionMap: A web-based software that automates loci assignments to framework maps.

PubMed

Albini, Guillaume; Falque, Matthieu; Joets, Johann

2003-07-01

Genetic linkage computation may be a repetitive and time consuming task, especially when numerous loci are assigned to a framework map. We thus developed ActionMap, a web-based software that automates genetic mapping on a fixed framework map without adding the new markers to the map. Using this tool, hundreds of loci may be automatically assigned to the framework in a single process. ActionMap was initially developed to map numerous ESTs with a small plant mapping population and is limited to inbred lines and backcrosses. ActionMap is highly configurable and consists of Perl and PHP scripts that automate command steps for the MapMaker program. A set of web forms were designed for data import and mapping settings. Results of automatic mapping can be displayed as tables or drawings of maps and may be exported. The user may create personal access-restricted projects to store raw data, settings and mapping results. All data may be edited, updated or deleted. ActionMap may be used either online or downloaded for free (http://moulon.inra.fr/~bioinfo/).

ActionMap: a web-based software that automates loci assignments to framework maps

PubMed Central

Albini, Guillaume; Falque, Matthieu; Joets, Johann

2003-01-01

Genetic linkage computation may be a repetitive and time consuming task, especially when numerous loci are assigned to a framework map. We thus developed ActionMap, a web-based software that automates genetic mapping on a fixed framework map without adding the new markers to the map. Using this tool, hundreds of loci may be automatically assigned to the framework in a single process. ActionMap was initially developed to map numerous ESTs with a small plant mapping population and is limited to inbred lines and backcrosses. ActionMap is highly configurable and consists of Perl and PHP scripts that automate command steps for the MapMaker program. A set of web forms were designed for data import and mapping settings. Results of automatic mapping can be displayed as tables or drawings of maps and may be exported. The user may create personal access-restricted projects to store raw data, settings and mapping results. All data may be edited, updated or deleted. ActionMap may be used either online or downloaded for free (http://moulon.inra.fr/~bioinfo/). PMID:12824426

Implementing automatic LiDAR and supervised mapping methodologies to quantify agricultural terraced landforms at landscape scale: the case of Veneto Region

NASA Astrophysics Data System (ADS)

Eugenio Pappalardo, Salvatore; Ferrarese, Francesco; Tarolli, Paolo; Varotto, Mauro

2016-04-01

Traditional agricultural terraced landscapes presently embody an important cultural value to be deeply investigated, both for their role in local heritage and cultural economy and for their potential geo-hydrological hazard due to abandonment and degradation. Moreover, traditional terraced landscapes are usually based on non-intensive agro-systems and may enhance some important ecosystems services such as agro-biodiversity conservation and cultural services. Due to their unplanned genesis, mapping, quantifying and classifying agricultural terraces at regional scale is often critical as far as they are usually set up on geomorphologically and historically complex landscapes. Hence, traditional mapping methods are generally based on scientific literature and local documentation, historical and cadastral sources, technical cartography and aerial images visual interpretation or, finally, field surveys. By this, limitations and uncertainty in mapping at regional scale are basically related to forest cover and lack in thematic cartography. The Veneto Region (NE of Italy) presents a wide heterogeneity of agricultural terraced landscapes, mainly distributed within the hilly and Prealps areas. Previous studies performed by traditional mapping method quantified 2,688 ha of terraced areas, showing the higher values within the Prealps of Lessinia (1,013 ha, within the Province of Verona) and in the Brenta Valley (421 ha, within the Province of Vicenza); however, terraced features of these case studies show relevant differences in terms of fragmentation and intensity of terraces, highlighting dissimilar degrees of clusterization: 1.7 ha on one hand (Province of Verona) and 1.2 ha per terraced area (Province of Vicenza) on the other one. The aim of this paper is to implement and to compare automatic methodologies with traditional survey methodologies to map and assess agricultural terraces in two representative areas of the Veneto Region. Testing different Remote Sensing analyses such as LiDAR topography survey and visual interpretation from aerial orthophotos (RGB+NIR bands) we performed a territorial analysis in the Lessinia and Brenta Valley case studies. Preliminary results show that terraced feature extraction by automatic LiDAR survey is more efficient both in identifying geometries (walls and terraced surfaces) and in quantifying features under the forest canopy; however, traditional mapping methodology confirms its strength by matching different methods and different data such as aerial photo, visual interpretation, maps and field surveys. Hence, the two methods here compared represent a cross-validation and let us to better know the complexity of this kind of landscape.

Elementary maps on nest algebras

NASA Astrophysics Data System (ADS)

Li, Pengtong

2006-08-01

Let , be algebras and let , be maps. An elementary map of is an ordered pair (M,M*) such that for all , . In this paper, the general form of surjective elementary maps on standard subalgebras of nest algebras is described. In particular, such maps are automatically additive.

An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

PubMed

Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

2017-12-01

The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching.

PubMed

Machado, Inês; Toews, Matthew; Luo, Jie; Unadkat, Prashin; Essayed, Walid; George, Elizabeth; Teodoro, Pedro; Carvalho, Herculano; Martins, Jorge; Golland, Polina; Pieper, Steve; Frisken, Sarah; Golby, Alexandra; Wells, William

2018-06-04

The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.

An object-based image analysis approach for aquaculture ponds precise mapping and monitoring: a case study of Tam Giang-Cau Hai Lagoon, Vietnam.

PubMed

Virdis, Salvatore Gonario Pasquale

2014-01-01

Monitoring and mapping shrimp farms, including their impact on land cover and land use, is critical to the sustainable management and planning of coastal zones. In this work, a methodology was proposed to set up a cost-effective and reproducible procedure that made use of satellite remote sensing, object-based classification approach, and open-source software for mapping aquaculture areas with high planimetric and thematic accuracy between 2005 and 2008. The analysis focused on two characteristic areas of interest of the Tam Giang-Cau Hai Lagoon (in central Vietnam), which have similar farming systems to other coastal aquaculture worldwide: the first was primarily characterised by locally referred "low tide" shrimp ponds, which are partially submerged areas; the second by earthed shrimp ponds, locally referred to as "high tide" ponds, which are non-submerged areas on the lagoon coast. The approach was based on the region-growing segmentation of high- and very high-resolution panchromatic images, SPOT5 and Worldview-1, and the unsupervised clustering classifier ISOSEG embedded on SPRING non-commercial software. The results, the accuracy of which was tested with a field-based aquaculture inventory, showed that in favourable situations (high tide shrimp ponds), the classification results provided high rates of accuracy (>95 %) through a fully automatic object-based classification. In unfavourable situations (low tide shrimp ponds), the performance degraded due to the low contrast between the water and the pond embankments. In these situations, the automatic results were improved by manual delineation of the embankments. Worldview-1 necessarily showed better thematic accuracy, and precise maps have been realised at a scale of up to 1:2,000. However, SPOT5 provided comparable results in terms of number of correctly classified ponds, but less accurate results in terms of the precision of mapped features. The procedure also demonstrated high degrees of reproducibility because it was applied to images with different spatial resolutions in an area that, during the investigated period, did not experience significant land cover changes.

Space-Based Sensorweb Monitoring of Wildfires in Thailand

NASA Technical Reports Server (NTRS)

Chien, Steve; Doubleday, Joshua; Mclaren, David; Davies, Ashley; Tran, Daniel; Tanpipat, Veerachai; Akaakara, Siri; Ratanasuwan, Anuchit; Mandl, Daniel

2011-01-01

We describe efforts to apply sensorweb technologies to the monitoring of forest fires in Thailand. In this approach, satellite data and ground reports are assimilated to assess the current state of the forest system in terms of forest fire risk, active fires, and likely progression of fires and smoke plumes. This current and projected assessment can then be used to actively direct sensors and assets to best acquire further information. This process operates continually with new data updating models of fire activity leading to further sensing and updating of models. As the fire activity is tracked, products such as active fire maps, burn scar severity maps, and alerts are automatically delivered to relevant parties.We describe the current state of the Thailand Fire Sensorweb which utilizes the MODIS-based FIRMS system to track active fires and trigger Earth Observing One / Advanced Land Imager to acquire imagery and produce active fire maps, burn scar severity maps, and alerts. We describe ongoing work to integrate additional sensor sources and generate additional products.

The development of automaticity in short-term memory search: Item-response learning and category learning.

PubMed

Cao, Rui; Nosofsky, Robert M; Shiffrin, Richard M

2017-05-01

In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across trials. In item-response learning, subjects learn long-term mappings between individual items and target versus foil responses. In category learning, subjects learn high-level codes corresponding to separate sets of items and learn to attach old versus new responses to these category codes. To distinguish between these 2 forms of learning, we tested subjects in categorized varied mapping (CV) conditions: There were 2 distinct categories of items, but the assignment of categories to target versus foil responses varied across trials. In cases involving arbitrary categories, CV performance closely resembled standard varied-mapping performance without categories and departed dramatically from CM performance, supporting the item-response-learning hypothesis. In cases involving prelearned categories, CV performance resembled CM performance, as long as there was sufficient practice or steps taken to reduce trial-to-trial category-switching costs. This pattern of results supports the category-coding hypothesis for sufficiently well-learned categories. Thus, item-response learning occurs rapidly and is used early in CM training; category learning is much slower but is eventually adopted and is used to increase the efficiency of search beyond that available from item-response learning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Using novel acoustic and visual mapping tools to predict the small-scale spatial distribution of live biogenic reef framework in cold-water coral habitats

NASA Astrophysics Data System (ADS)

De Clippele, L. H.; Gafeira, J.; Robert, K.; Hennige, S.; Lavaleye, M. S.; Duineveld, G. C. A.; Huvenne, V. A. I.; Roberts, J. M.

2017-03-01

Cold-water corals form substantial biogenic habitats on continental shelves and in deep-sea areas with topographic highs, such as banks and seamounts. In the Atlantic, many reef and mound complexes are engineered by Lophelia pertusa, the dominant framework-forming coral. In this study, a variety of mapping approaches were used at a range of scales to map the distribution of both cold-water coral habitats and individual coral colonies at the Mingulay Reef Complex (west Scotland). The new ArcGIS-based British Geological Survey (BGS) seabed mapping toolbox semi-automatically delineated over 500 Lophelia reef `mini-mounds' from bathymetry data with 2-m resolution. The morphometric and acoustic characteristics of the mini-mounds were also automatically quantified and captured using this toolbox. Coral presence data were derived from high-definition remotely operated vehicle (ROV) records and high-resolution microbathymetry collected by a ROV-mounted multibeam echosounder. With a resolution of 0.35 × 0.35 m, the microbathymetry covers 0.6 km2 in the centre of the study area and allowed identification of individual live coral colonies in acoustic data for the first time. Maximum water depth, maximum rugosity, mean rugosity, bathymetric positioning index and maximum current speed were identified as the environmental variables that contributed most to the prediction of live coral presence. These variables were used to create a predictive map of the likelihood of presence of live cold-water coral colonies in the area of the Mingulay Reef Complex covered by the 2-m resolution data set. Predictive maps of live corals across the reef will be especially valuable for future long-term monitoring surveys, including those needed to understand the impacts of global climate change. This is the first study using the newly developed BGS seabed mapping toolbox and an ROV-based microbathymetric grid to explore the environmental variables that control coral growth on cold-water coral reefs.

Long-term deforestation dynamics in the Brazilian Amazon-Uncovering historic frontier development along the Cuiabá-Santarém highway

NASA Astrophysics Data System (ADS)

Müller, Hannes; Griffiths, Patrick; Hostert, Patrick

2016-02-01

The great success of the Brazilian deforestation programme "PRODES digital" has shown the importance of annual deforestation information for understanding and mitigating deforestation and its consequences in Brazil. However, there is a lack of similar information on deforestation for the 1990s and 1980s. Such maps are essential to understand deforestation frontier development and related carbon emissions. This study aims at extending the deforestation mapping record backwards into the 1990s and 1980s for one of the major deforestation frontiers in the Amazon. We use an image compositing approach to transform 2224 Landsat images in a spatially continuous and cloud free annual time series of Tasseled Cap Wetness metrics from 1984 to 2012. We then employ a random forest classifier to derive annual deforestation patterns. Our final deforestation map has an overall accuracy of 85% with half of the overall deforestation being detected before the year 2000. The results show for the first time detailed patterns of the expanding deforestation frontier before the 2000s. The high degree of automatization exhibits the great potential for mapping the whole Amazon biome using long-term and freely accessible remote sensing collections, such as the Landsat archive and forthcoming Sentinel-2 data.

Automatic Computer Mapping of Terrain

NASA Technical Reports Server (NTRS)

Smedes, H. W.

1971-01-01

Computer processing of 17 wavelength bands of visible, reflective infrared, and thermal infrared scanner spectrometer data, and of three wavelength bands derived from color aerial film has resulted in successful automatic computer mapping of eight or more terrain classes in a Yellowstone National Park test site. The tests involved: (1) supervised and non-supervised computer programs; (2) special preprocessing of the scanner data to reduce computer processing time and cost, and improve the accuracy; and (3) studies of the effectiveness of the proposed Earth Resources Technology Satellite (ERTS) data channels in the automatic mapping of the same terrain, based on simulations, using the same set of scanner data. The following terrain classes have been mapped with greater than 80 percent accuracy in a 12-square-mile area with 1,800 feet of relief; (1) bedrock exposures, (2) vegetated rock rubble, (3) talus, (4) glacial kame meadow, (5) glacial till meadow, (6) forest, (7) bog, and (8) water. In addition, shadows of clouds and cliffs are depicted, but were greatly reduced by using preprocessing techniques.

An interoperable standard system for the automatic generation and publication of the fire risk maps based on Fire Weather Index (FWI)

NASA Astrophysics Data System (ADS)

Julià Selvas, Núria; Ninyerola Casals, Miquel

2015-04-01

It has been implemented an automatic system to predict the fire risk in the Principality of Andorra, a small country located in the eastern Pyrenees mountain range, bordered by Catalonia and France, due to its location, his landscape is a set of a rugged mountains with an average elevation around 2000 meters. The system is based on the Fire Weather Index (FWI) that consists on different components, each one, measuring a different aspect of the fire danger calculated by the values of the weather variables at midday. CENMA (Centre d'Estudis de la Neu i de la Muntanya d'Andorra) has a network around 10 automatic meteorological stations, located in different places, peeks and valleys, that measure weather data like relative humidity, wind direction and speed, surface temperature, rainfall and snow cover every ten minutes; this data is sent daily and automatically to the system implemented that will be processed in the way to filter incorrect measurements and to homogenizer measurement units. Then this data is used to calculate all components of the FWI at midday and for the level of each station, creating a database with the values of the homogeneous measurements and the FWI components for each weather station. In order to extend and model this data to all Andorran territory and to obtain a continuous map, an interpolation method based on a multiple regression with spline residual interpolation has been implemented. This interpolation considerer the FWI data as well as other relevant predictors such as latitude, altitude, global solar radiation and sea distance. The obtained values (maps) are validated using a cross-validation leave-one-out method. The discrete and continuous maps are rendered in tiled raster maps and published in a web portal conform to Web Map Service (WMS) Open Geospatial Consortium (OGC) standard. Metadata and other reference maps (fuel maps, topographic maps, etc) are also available from this geoportal.

Automatic delineation of tumor volumes by co-segmentation of combined PET/MR data

NASA Astrophysics Data System (ADS)

Leibfarth, S.; Eckert, F.; Welz, S.; Siegel, C.; Schmidt, H.; Schwenzer, N.; Zips, D.; Thorwarth, D.

2015-07-01

Combined PET/MRI may be highly beneficial for radiotherapy treatment planning in terms of tumor delineation and characterization. To standardize tumor volume delineation, an automatic algorithm for the co-segmentation of head and neck (HN) tumors based on PET/MR data was developed. Ten HN patient datasets acquired in a combined PET/MR system were available for this study. The proposed algorithm uses both the anatomical T2-weighted MR and FDG-PET data. For both imaging modalities tumor probability maps were derived, assigning each voxel a probability of being cancerous based on its signal intensity. A combination of these maps was subsequently segmented using a threshold level set algorithm. To validate the method, tumor delineations from three radiation oncologists were available. Inter-observer variabilities and variabilities between the algorithm and each observer were quantified by means of the Dice similarity index and a distance measure. Inter-observer variabilities and variabilities between observers and algorithm were found to be comparable, suggesting that the proposed algorithm is adequate for PET/MR co-segmentation. Moreover, taking into account combined PET/MR data resulted in more consistent tumor delineations compared to MR information only.

Automatic 3d Building Model Generations with Airborne LiDAR Data

NASA Astrophysics Data System (ADS)

Yastikli, N.; Cetin, Z.

2017-11-01

LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D building models can be generated successfully using raw LiDAR point cloud data.

Mind map learning for advanced engineering study: case study in system dynamics

NASA Astrophysics Data System (ADS)

Woradechjumroen, Denchai

2018-01-01

System Dynamics (SD) is one of the subjects that were use in learning Automatic Control Systems in dynamic and control field. Mathematical modelling and solving skills of students for engineering systems are expecting outcomes of the course which can be further used to efficiently study control systems and mechanical vibration; however, the fundamental of the SD includes strong backgrounds in Dynamics and Differential Equations, which are appropriate to the students in governmental universities that have strong skills in Mathematics and Scientifics. For private universities, students are weak in the above subjects since they obtained high vocational certificate from Technical College or Polytechnic School, which emphasize the learning contents in practice. To enhance their learning for improving their backgrounds, this paper applies mind maps based problem based learning to relate the essential relations of mathematical and physical equations. With the advantages of mind maps, each student is assigned to design individual mind maps for self-leaning development after they attend the class and learn overall picture of each chapter from the class instructor. Four problems based mind maps learning are assigned to each student. Each assignment is evaluated via mid-term and final examinations, which are issued in terms of learning concepts and applications. In the method testing, thirty students are tested and evaluated via student learning backgrounds in the past. The result shows that well-design mind maps can improve learning performance based on outcome evaluation. Especially, mind maps can reduce time-consuming and reviewing for Mathematics and Physics in SD significantly.

Management of natural resources through automatic cartographic inventory

NASA Technical Reports Server (NTRS)

Rey, P. A.; Gourinard, Y.; Cambou, F. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Significant correspondence codes relating ERTS imagery to ground truth from vegetation and geology maps have been established. The use of color equidensity and color composite methods for selecting zones of equal densitometric value on ERTS imagery was perfected. Primary interest of temporal color composite is stressed. A chain of transfer operations from ERTS imagery to the automatic mapping of natural resources was developed.

Automatic Boosted Flood Mapping from Satellite Data

NASA Technical Reports Server (NTRS)

Coltin, Brian; McMichael, Scott; Smith, Trey; Fong, Terrence

2016-01-01

Numerous algorithms have been proposed to map floods from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, most require human input to succeed, either to specify a threshold value or to manually annotate training data. We introduce a new algorithm based on Adaboost which effectively maps floods without any human input, allowing for a truly rapid and automatic response. The Adaboost algorithm combines multiple thresholds to achieve results comparable to state-of-the-art algorithms which do require human input. We evaluate Adaboost, as well as numerous previously proposed flood mapping algorithms, on multiple MODIS flood images, as well as on hundreds of non-flood MODIS lake images, demonstrating its effectiveness across a wide variety of conditions.

Automatic identification of IASLC-defined mediastinal lymph node stations on CT scans using multi-atlas organ segmentation

NASA Astrophysics Data System (ADS)

Hoffman, Joanne; Liu, Jiamin; Turkbey, Evrim; Kim, Lauren; Summers, Ronald M.

2015-03-01

Station-labeling of mediastinal lymph nodes is typically performed to identify the location of enlarged nodes for cancer staging. Stations are usually assigned in clinical radiology practice manually by qualitative visual assessment on CT scans, which is time consuming and highly variable. In this paper, we developed a method that automatically recognizes the lymph node stations in thoracic CT scans based on the anatomical organs in the mediastinum. First, the trachea, lungs, and spines are automatically segmented to locate the mediastinum region. Then, eight more anatomical organs are simultaneously identified by multi-atlas segmentation. Finally, with the segmentation of those anatomical organs, we convert the text definitions of the International Association for the Study of Lung Cancer (IASLC) lymph node map into patient-specific color-coded CT image maps. Thus, a lymph node station is automatically assigned to each lymph node. We applied this system to CT scans of 86 patients with 336 mediastinal lymph nodes measuring equal or greater than 10 mm. 84.8% of mediastinal lymph nodes were correctly mapped to their stations.

Microprocessor-controlled hemodynamics: a step towards improved efficiency and safety.

PubMed

Keogh, B E; Jacobs, J; Royston, D; Taylor, K M

1989-02-01

Manual titration of sodium nitroprusside (SNP) is widely used for treatment of hypertension following cardiac surgery. This study compared conventional manual control with control by a research prototype of an automatic infusion module based on a proportional plus integral plus derivative (PID) negative feedback loop. Two groups of coronary artery bypass patients requiring SNP for postoperative hypertension were studied prospectively. In the first group, hypertension was controlled by manual adjustment of the SNP infusion rate, and in the second, the infusion rate was controlled automatically. The actual and desired mean arterial pressures (MAP) over consecutive ten-second epochs were recorded during the period of infusion. The MAP was maintained within 10% of the desired MAP 45.8% of the time in the manual group, compared with 90.0% in the automatic group, and the mean percent error in the automatic group was significantly less than in the manual group (P less than 0.01). It is concluded that adoption of such systems will result in improved patient safety and may facilitate more effective distribution of nursing staff within intensive care units.

Spectral saliency via automatic adaptive amplitude spectrum analysis

NASA Astrophysics Data System (ADS)

Wang, Xiaodong; Dai, Jialun; Zhu, Yafei; Zheng, Haiyong; Qiao, Xiaoyan

2016-03-01

Suppressing nonsalient patterns by smoothing the amplitude spectrum at an appropriate scale has been shown to effectively detect the visual saliency in the frequency domain. Different filter scales are required for different types of salient objects. We observe that the optimal scale for smoothing amplitude spectrum shares a specific relation with the size of the salient region. Based on this observation and the bottom-up saliency detection characterized by spectrum scale-space analysis for natural images, we propose to detect visual saliency, especially with salient objects of different sizes and locations via automatic adaptive amplitude spectrum analysis. We not only provide a new criterion for automatic optimal scale selection but also reserve the saliency maps corresponding to different salient objects with meaningful saliency information by adaptive weighted combination. The performance of quantitative and qualitative comparisons is evaluated by three different kinds of metrics on the four most widely used datasets and one up-to-date large-scale dataset. The experimental results validate that our method outperforms the existing state-of-the-art saliency models for predicting human eye fixations in terms of accuracy and robustness.

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Conversion of KEGG metabolic pathways to SBGN maps including automatic layout

PubMed Central

2013-01-01

Background Biologists make frequent use of databases containing large and complex biological networks. One popular database is the Kyoto Encyclopedia of Genes and Genomes (KEGG) which uses its own graphical representation and manual layout for pathways. While some general drawing conventions exist for biological networks, arbitrary graphical representations are very common. Recently, a new standard has been established for displaying biological processes, the Systems Biology Graphical Notation (SBGN), which aims to unify the look of such maps. Ideally, online repositories such as KEGG would automatically provide networks in a variety of notations including SBGN. Unfortunately, this is non‐trivial, since converting between notations may add, remove or otherwise alter map elements so that the existing layout cannot be simply reused. Results Here we describe a methodology for automatic translation of KEGG metabolic pathways into the SBGN format. We infer important properties of the KEGG layout and treat these as layout constraints that are maintained during the conversion to SBGN maps. Conclusions This allows for the drawing and layout conventions of SBGN to be followed while creating maps that are still recognizably the original KEGG pathways. This article details the steps in this process and provides examples of the final result. PMID:23953132

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PubMed

Kropat, Georg; Bochud, Francois; Jaboyedoff, Michel; Laedermann, Jean-Pascal; Murith, Christophe; Palacios Gruson, Martha; Baechler, Sébastien

2015-09-01

According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improving fMRI reliability in presurgical mapping for brain tumours.

PubMed

Stevens, M Tynan R; Clarke, David B; Stroink, Gerhard; Beyea, Steven D; D'Arcy, Ryan Cn

2016-03-01

Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Osm Poi Analyzer: a Platform for Assessing Position of POIs in Openstreetmap

NASA Astrophysics Data System (ADS)

Kashian, A.; Rajabifard, A.; Chen, Y.; Richter, K. F.

2017-09-01

In recent years, more and increased participation in Volunteered Geographical Information (VGI) projects provides enough data coverage for most places around the world for ordinary mapping and navigation purposes, however, the positional credibility of contributed data becomes more and more important to bring a long-term trust in VGI data. Today, it is hard to draw a definite traditional boundary between the authoritative map producers and the public map consumers and we observe that more and more volunteers are joining crowdsourcing activities for collecting geodata, which might result in higher rates of man-made mistakes in open map projects such as OpenStreetMap. While there are some methods for monitoring the accuracy and consistency of the created data, there is still a lack of advanced systems to automatically discover misplaced objects on the map. One feature type which is contributed daily to OSM is Point of Interest (POI). In order to understand how likely it is that a newly added POI represents a genuine real-world feature scientific means to calculate a probability of such a POI existing at that specific position is needed. This paper reports on a new analytic tool which dives into OSM data and finds co-existence patterns between one specific POI and its surrounding objects such as roads, parks and buildings. The platform uses a distance-based classification technique to find relationships among objects and tries to identify the high-frequency association patterns among each category of objects. Using such method, for each newly added POI, a probabilistic score would be generated, and the low scored POIs can be highlighted for editors for a manual check. The same scoring method can be used for existing registered POIs to check if they are located correctly. For a sample study, this paper reports on the evaluation of 800 pre-registered ATMs in Paris with associated scores to understand how outliers and fake entries could be detected automatically.

Decision-level fusion of SAR and IR sensor information for automatic target detection

NASA Astrophysics Data System (ADS)

Cho, Young-Rae; Yim, Sung-Hyuk; Cho, Hyun-Woong; Won, Jin-Ju; Song, Woo-Jin; Kim, So-Hyeon

2017-05-01

We propose a decision-level architecture that combines synthetic aperture radar (SAR) and an infrared (IR) sensor for automatic target detection. We present a new size-based feature, called target-silhouette to reduce the number of false alarms produced by the conventional target-detection algorithm. Boolean Map Visual Theory is used to combine a pair of SAR and IR images to generate the target-enhanced map. Then basic belief assignment is used to transform this map into a belief map. The detection results of sensors are combined to build the target-silhouette map. We integrate the fusion mass and the target-silhouette map on the decision level to exclude false alarms. The proposed algorithm is evaluated using a SAR and IR synthetic database generated by SE-WORKBENCH simulator, and compared with conventional algorithms. The proposed fusion scheme achieves higher detection rate and lower false alarm rate than the conventional algorithms.

Open Touch/Sound Maps: A system to convey street data through haptic and auditory feedback

NASA Astrophysics Data System (ADS)

Kaklanis, Nikolaos; Votis, Konstantinos; Tzovaras, Dimitrios

2013-08-01

The use of spatial (geographic) information is becoming ever more central and pervasive in today's internet society but the most of it is currently inaccessible to visually impaired users. However, access in visual maps is severely restricted to visually impaired and people with blindness, due to their inability to interpret graphical information. Thus, alternative ways of a map's presentation have to be explored, in order to enforce the accessibility of maps. Multiple types of sensory perception like touch and hearing may work as a substitute of vision for the exploration of maps. The use of multimodal virtual environments seems to be a promising alternative for people with visual impairments. The present paper introduces a tool for automatic multimodal map generation having haptic and audio feedback using OpenStreetMap data. For a desired map area, an elevation map is being automatically generated and can be explored by touch, using a haptic device. A sonification and a text-to-speech (TTS) mechanism provide also audio navigation information during the haptic exploration of the map.

R-on-1 automatic mapping: A new tool for laser damage testing

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

Hue, J.; Garrec, P.; Dijon, J.

1996-12-31

Laser damage threshold measurement is statistical in nature. For a commercial qualification or for a user, the threshold determined by the weakest point is a satisfactory characterization. When a new coating is designed, threshold mapping is very useful. It enables the technology to be improved and followed more accurately. Different statistical parameters such as the minimum, maximum, average, and standard deviation of the damage threshold as well as spatial parameters such as the threshold uniformity of the coating can be determined. Therefore, in order to achieve a mapping, all the tested sites should give data. This is the major interestmore » of the R-on-1 test in spite of the fact that the laser damage threshold obtained by this method may be different from the 1-on-1 test (smaller or greater). Moreover, on the damage laser test facility, the beam size is smaller (diameters of a few hundred micrometers) than the characteristic sizes of the components in use (diameters of several centimeters up to one meter). Hence, a laser damage threshold mapping appears very interesting, especially for applications linked to large optical components like the Megajoule project or the National Ignition Facility (N.I.F). On the test bench used, damage detection with a Nomarski microscope and scattered light measurement are almost equivalent. Therefore, it becomes possible to automatically detect on line the first defects induced by YAG irradiation. Scattered light mappings and laser damage threshold mappings can therefore be achieved using a X-Y automatic stage (where the test sample is located). The major difficulties due to the automatic capabilities are shown. These characterizations are illustrated at 355 nm. The numerous experiments performed show different kinds of scattering curves, which are discussed in relation with the damage mechanisms.« less

Automated map sharpening by maximization of detail and connectivity

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

Terwilliger, Thomas C.; Sobolev, Oleg V.; Afonine, Pavel V.

An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures inmore » a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a model withBfactors (atomic displacement factors; ADPs) set to zero. Finally, this model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.« less

Automated map sharpening by maximization of detail and connectivity

DOE PAGES

Terwilliger, Thomas C.; Sobolev, Oleg V.; Afonine, Pavel V.; ...

2018-05-18

An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures inmore » a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a model withBfactors (atomic displacement factors; ADPs) set to zero. Finally, this model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.« less

The Influence of Endmember Selection Method in Extracting Impervious Surface from Airborne Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Wang, J.; Feng, B.

2016-12-01

Impervious surface area (ISA) has long been studied as an important input into moisture flux models. In general, ISA impedes groundwater recharge, increases stormflow/flood frequency, and alters in-stream and riparian habitats. Urban area is recognized as one of the richest ISA environment. Urban ISA mapping assists flood prevention and urban planning. Hyperspectral imagery (HI), for its ability to detect subtle spectral signature, becomes an ideal candidate in urban ISA mapping. To map ISA from HI involves endmember (EM) selection. The high degree of spatial and spectral heterogeneity of urban environment puts great difficulty in this task: a compromise point is needed between the automatic degree and the good representativeness of the method. The study tested one manual and two semi-automatic EM selection strategies. The manual and the first semi-automatic methods have been widely used in EM selection. The second semi-automatic EM selection method is rather new and has been only proposed for moderate spatial resolution satellite. The manual method visually selected the EM candidates from eight landcover types in the original image. The first semi-automatic method chose the EM candidates using a threshold over the pixel purity index (PPI) map. The second semi-automatic method used the triangle shape of the HI scatter plot in the n-Dimension visualizer to identify the V-I-S (vegetation-impervious surface-soil) EM candidates: the pixels locate at the triangle points. The initial EM candidates from the three methods were further refined by three indexes (EM average RMSE, minimum average spectral angle, and count based EM selection) and generated three spectral libraries, which were used to classify the test image. Spectral angle mapper was applied. The accuracy reports for the classification results were generated. The overall accuracy are 85% for the manual method, 81% for the PPI method, and 87% for the V-I-S method. The V-I-S EM selection method performs best in this study. This fact proves the value of V-I-S EM selection method in not only moderate spatial resolution satellite image but also the more and more accessible high spatial resolution airborne image. This semi-automatic EM selection method can be adopted into a wide range of remote sensing images and provide ISA map for hydrology analysis.

Development of Generation System of Simplified Digital Maps

NASA Astrophysics Data System (ADS)

Uchimura, Keiichi; Kawano, Masato; Tokitsu, Hiroki; Hu, Zhencheng

In recent years, digital maps have been used in a variety of scenarios, including car navigation systems and map information services over the Internet. These digital maps are formed by multiple layers of maps of different scales; the map data most suitable for the specific situation are used. Currently, the production of map data of different scales is done by hand due to constraints related to processing time and accuracy. We conducted research concerning technologies for automatic generation of simplified map data from detailed map data. In the present paper, the authors propose the following: (1) a method to transform data related to streets, rivers, etc. containing widths into line data, (2) a method to eliminate the component points of the data, and (3) a method to eliminate data that lie below a certain threshold. In addition, in order to evaluate the proposed method, a user survey was conducted; in this survey we compared maps generated using the proposed method with the commercially available maps. From the viewpoint of the amount of data reduction and processing time, and on the basis of the results of the survey, we confirmed the effectiveness of the automatic generation of simplified maps using the proposed methods.

Automatic HDL firmware generation for FPGA-based reconfigurable measurement and control systems with mezzanines in FMC standard

NASA Astrophysics Data System (ADS)

Wojenski, Andrzej; Kasprowicz, Grzegorz; Pozniak, Krzysztof T.; Romaniuk, Ryszard

2013-10-01

The paper describes a concept of automatic firmware generation for reconfigurable measurement systems, which uses FPGA devices and measurement cards in FMC standard. Following sections are described in details: automatic HDL code generation for FPGA devices, automatic communication interfaces implementation, HDL drivers for measurement cards, automatic serial connection between multiple measurement backplane boards, automatic build of memory map (address space), automatic generated firmware management. Presented solutions are required in many advanced measurement systems, like Beam Position Monitors or GEM detectors. This work is a part of a wider project for automatic firmware generation and management of reconfigurable systems. Solutions presented in this paper are based on previous publication in SPIE.

Automatic Evolution of Molecular Nanotechnology Designs

NASA Technical Reports Server (NTRS)

Globus, Al; Lawton, John; Wipke, Todd; Saini, Subhash (Technical Monitor)

1998-01-01

This paper describes strategies for automatically generating designs for analog circuits at the molecular level. Software maps out the edges and vertices of potential nanotechnology systems on graphs, then selects appropriate ones through evolutionary or genetic paradigms.

Automated land-use mapping from spacecraft data. [Oakland County, Michigan

NASA Technical Reports Server (NTRS)

Chase, P. E. (Principal Investigator); Rogers, R. H.; Reed, L. E.

1974-01-01

The author has identified the following significant results. In response to the need for a faster, more economical means of producing land use maps, this study evaluated the suitability of using ERTS-1 computer compatible tape (CCT) data as a basis for automatic mapping. Significant findings are: (1) automatic classification accuracy greater than 90% is achieved on categories of deep and shallow water, tended grass, rangeland, extractive (bare earth), urban, forest land, and nonforested wet lands; (2) computer-generated printouts by target class provide a quantitative measure of land use; and (3) the generation of map overlays showing land use from ERTS-1 CCTs offers a significant breakthrough in the rate at which land use maps are generated. Rather than uncorrected classified imagery or computer line printer outputs, the processing results in geometrically-corrected computer-driven pen drawing of land categories, drawn on a transparent material at a scale specified by the operator. These map overlays are economically produced and provide an efficient means of rapidly updating maps showing land use.

Morphological self-organizing feature map neural network with applications to automatic target recognition

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

Behavioral and electrophysiological evidence for early and automatic detection of phonological equivalence in variable speech inputs.

PubMed

Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina

2011-11-01

Speech sounds are not always perceived in accordance with their acoustic-phonetic content. For example, an early and automatic process of perceptual repair, which ensures conformity of speech inputs to the listener's native language phonology, applies to individual input segments that do not exist in the native inventory or to sound sequences that are illicit according to the native phonotactic restrictions on sound co-occurrences. The present study with Russian and Canadian English speakers shows that listeners may perceive phonetically distinct and licit sound sequences as equivalent when the native language system provides robust evidence for mapping multiple phonetic forms onto a single phonological representation. In Russian, due to an optional but productive t-deletion process that affects /stn/ clusters, the surface forms [sn] and [stn] may be phonologically equivalent and map to a single phonological form /stn/. In contrast, [sn] and [stn] clusters are usually phonologically distinct in (Canadian) English. Behavioral data from identification and discrimination tasks indicated that [sn] and [stn] clusters were more confusable for Russian than for English speakers. The EEG experiment employed an oddball paradigm with nonwords [asna] and [astna] used as the standard and deviant stimuli. A reliable mismatch negativity response was elicited approximately 100 msec postchange in the English group but not in the Russian group. These findings point to a perceptual repair mechanism that is engaged automatically at a prelexical level to ensure immediate encoding of speech inputs in phonological terms, which in turn enables efficient access to the meaning of a spoken utterance.

Automatic drawing for traffic marking with MMS LIDAR intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Shimano, Y.

2014-05-01

Upgrading the database of CYBER JAPAN has been strategically promoted because the "Basic Act on Promotion of Utilization of Geographical Information", was enacted in May 2007. In particular, there is a high demand for road information that comprises a framework in this database. Therefore, road inventory mapping work has to be accurate and eliminate variation caused by individual human operators. Further, the large number of traffic markings that are periodically maintained and possibly changed require an efficient method for updating spatial data. Currently, we apply manual photogrammetry drawing for mapping traffic markings. However, this method is not sufficiently efficient in terms of the required productivity, and data variation can arise from individual operators. In contrast, Mobile Mapping Systems (MMS) and high-density Laser Imaging Detection and Ranging (LIDAR) scanners are rapidly gaining popularity. The aim in this study is to build an efficient method for automatically drawing traffic markings using MMS LIDAR data. The key idea in this method is extracting lines using a Hough transform strategically focused on changes in local reflection intensity along scan lines. However, also note that this method processes every traffic marking. In this paper, we discuss a highly accurate and non-human-operator-dependent method that applies the following steps: (1) Binarizing LIDAR points by intensity and extracting higher intensity points; (2) Generating a Triangulated Irregular Network (TIN) from higher intensity points; (3) Deleting arcs by length and generating outline polygons on the TIN; (4) Generating buffers from the outline polygons; (5) Extracting points from the buffers using the original LIDAR points; (6) Extracting local-intensity-changing points along scan lines using the extracted points; (7) Extracting lines from intensity-changing points through a Hough transform; and (8) Connecting lines to generate automated traffic marking mapping data.

Automatic Summarization of MEDLINE Citations for Evidence–Based Medical Treatment: A Topic-Oriented Evaluation

PubMed Central

Fiszman, Marcelo; Demner-Fushman, Dina; Kilicoglu, Halil; Rindflesch, Thomas C.

2009-01-01

As the number of electronic biomedical textual resources increases, it becomes harder for physicians to find useful answers at the point of care. Information retrieval applications provide access to databases; however, little research has been done on using automatic summarization to help navigate the documents returned by these systems. After presenting a semantic abstraction automatic summarization system for MEDLINE citations, we concentrate on evaluating its ability to identify useful drug interventions for fifty-three diseases. The evaluation methodology uses existing sources of evidence-based medicine as surrogates for a physician-annotated reference standard. Mean average precision (MAP) and a clinical usefulness score developed for this study were computed as performance metrics. The automatic summarization system significantly outperformed the baseline in both metrics. The MAP gain was 0.17 (p < 0.01) and the increase in the overall score of clinical usefulness was 0.39 (p < 0.05). PMID:19022398

A new method for automatic discontinuity traces sampling on rock mass 3D model

NASA Astrophysics Data System (ADS)

Umili, G.; Ferrero, A.; Einstein, H. H.

2013-02-01

A new automatic method for discontinuity traces mapping and sampling on a rock mass digital model is described in this work. The implemented procedure allows one to automatically identify discontinuity traces on a Digital Surface Model: traces are detected directly as surface breaklines, by means of maximum and minimum principal curvature values of the vertices that constitute the model surface. Color influence and user errors, that usually characterize the trace mapping on images, are eliminated. Also trace sampling procedures based on circular windows and circular scanlines have been implemented: they are used to infer trace data and to calculate values of mean trace length, expected discontinuity diameter and intensity of rock discontinuities. The method is tested on a case study: results obtained applying the automatic procedure on the DSM of a rock face are compared to those obtained performing a manual sampling on the orthophotograph of the same rock face.

Acoustic emission source location in complex structures using full automatic delta T mapping technique

NASA Astrophysics Data System (ADS)

Al-Jumaili, Safaa Kh.; Pearson, Matthew R.; Holford, Karen M.; Eaton, Mark J.; Pullin, Rhys

2016-05-01

An easy to use, fast to apply, cost-effective, and very accurate non-destructive testing (NDT) technique for damage localisation in complex structures is key for the uptake of structural health monitoring systems (SHM). Acoustic emission (AE) is a viable technique that can be used for SHM and one of the most attractive features is the ability to locate AE sources. The time of arrival (TOA) technique is traditionally used to locate AE sources, and relies on the assumption of constant wave speed within the material and uninterrupted propagation path between the source and the sensor. In complex structural geometries and complex materials such as composites, this assumption is no longer valid. Delta T mapping was developed in Cardiff in order to overcome these limitations; this technique uses artificial sources on an area of interest to create training maps. These are used to locate subsequent AE sources. However operator expertise is required to select the best data from the training maps and to choose the correct parameter to locate the sources, which can be a time consuming process. This paper presents a new and improved fully automatic delta T mapping technique where a clustering algorithm is used to automatically identify and select the highly correlated events at each grid point whilst the "Minimum Difference" approach is used to determine the source location. This removes the requirement for operator expertise, saving time and preventing human errors. A thorough assessment is conducted to evaluate the performance and the robustness of the new technique. In the initial test, the results showed excellent reduction in running time as well as improved accuracy of locating AE sources, as a result of the automatic selection of the training data. Furthermore, because the process is performed automatically, this is now a very simple and reliable technique due to the prevention of the potential source of error related to manual manipulation.

A comparative study on different methods of automatic mesh generation of human femurs.

PubMed

Viceconti, M; Bellingeri, L; Cristofolini, L; Toni, A

1998-01-01

The aim of this study was to evaluate comparatively five methods for automating mesh generation (AMG) when used to mesh a human femur. The five AMG methods considered were: mapped mesh, which provides hexahedral elements through a direct mapping of the element onto the geometry; tetra mesh, which generates tetrahedral elements from a solid model of the object geometry; voxel mesh which builds cubic 8-node elements directly from CT images; and hexa mesh that automatically generated hexahedral elements from a surface definition of the femur geometry. The various methods were tested against two reference models: a simplified geometric model and a proximal femur model. The first model was useful to assess the inherent accuracy of the meshes created by the AMG methods, since an analytical solution was available for the elastic problem of the simplified geometric model. The femur model was used to test the AMG methods in a more realistic condition. The femoral geometry was derived from a reference model (the "standardized femur") and the finite element analyses predictions were compared to experimental measurements. All methods were evaluated in terms of human and computer effort needed to carry out the complete analysis, and in terms of accuracy. The comparison demonstrated that each tested method deserves attention and may be the best for specific situations. The mapped AMG method requires a significant human effort but is very accurate and it allows a tight control of the mesh structure. The tetra AMG method requires a solid model of the object to be analysed but is widely available and accurate. The hexa AMG method requires a significant computer effort but can also be used on polygonal models and is very accurate. The voxel AMG method requires a huge number of elements to reach an accuracy comparable to that of the other methods, but it does not require any pre-processing of the CT dataset to extract the geometry and in some cases may be the only viable solution.

Wildland resource information system: user's guide

Treesearch

Robert M. Russell; David A. Sharpnack; Elliot L. Amidon

1975-01-01

This user's guide provides detailed information about how to use the computer programs of WRIS, a computer system for storing and manipulating data about land areas. Instructions explain how to prepare maps, digitize by automatic scanners or by hand, produce polygon maps, and combine map layers. Support programs plot maps, store them on tapes, produce summaries,...

Intelligent geocoding system to locate traffic crashes.

PubMed

Qin, Xiao; Parker, Steven; Liu, Yi; Graettinger, Andrew J; Forde, Susie

2013-01-01

State agencies continue to face many challenges associated with new federal crash safety and highway performance monitoring requirements that use data from multiple and disparate systems across different platforms and locations. On a national level, the federal government has a long-term vision for State Departments of Transportation (DOTs) to report state route and off-state route crash data in a single network. In general, crashes occurring on state-owned or state maintained highways are a priority at the Federal and State level; therefore, state-route crashes are being geocoded by state DOTs. On the other hand, crashes occurring on off-state highway system do not always get geocoded due to limited resources and techniques. Creating and maintaining a statewide crash geographic information systems (GIS) map with state route and non-state route crashes is a complicated and expensive task. This study introduces an automatic crash mapping process, Crash-Mapping Automation Tool (C-MAT), where an algorithm translates location information from a police report crash record to a geospatial map and creates a pinpoint map for all crashes. The algorithm has approximate 83 percent mapping rate. An important application of this work is the ability to associate the mapped crash records to underlying business data, such as roadway inventory and traffic volumes. The integrated crash map is the foundation for effective and efficient crash analyzes to prevent highway crashes. Published by Elsevier Ltd.

Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

PubMed

Dos Reis, Julio Cesar; Dinh, Duy; Da Silveira, Marcos; Pruski, Cédric; Reynaud-Delaître, Chantal

2015-03-01

Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappings are highly demanded. The accuracy of such methods relies on the available description about the evolution of ontologies, especially regarding concepts involved in mappings. However, from one ontology version to another, a further understanding of ontology changes relevant for supporting mapping adaptation is typically lacking. This research work defines a set of change patterns at the level of concept attributes, and proposes original methods to automatically recognize instances of these patterns based on the similarity between attributes denoting the evolving concepts. This investigation evaluates the benefits of the proposed methods and the influence of the recognized change patterns to select the strategies for mapping adaptation. The summary of the findings is as follows: (1) the Precision (>60%) and Recall (>35%) achieved by comparing manually identified change patterns with the automatic ones; (2) a set of potential impact of recognized change patterns on the way mappings is adapted. We found that the detected correlations cover ∼66% of the mapping adaptation actions with a positive impact; and (3) the influence of the similarity coefficient calculated between concept attributes on the performance of the recognition algorithms. The experimental evaluations conducted with real life science ontologies showed the effectiveness of our approach to accurately characterize ontology evolution at the level of concept attributes. This investigation confirmed the relevance of the proposed change patterns to support decisions on mapping adaptation. Copyright © 2014 Elsevier B.V. All rights reserved.

Semi-automatic Data Integration using Karma

NASA Astrophysics Data System (ADS)

Garijo, D.; Kejriwal, M.; Pierce, S. A.; Houser, P. I. Q.; Peckham, S. D.; Stanko, Z.; Hardesty Lewis, D.; Gil, Y.; Pennington, D. D.; Knoblock, C.

2017-12-01

Data integration applications are ubiquitous in scientific disciplines. A state-of-the-art data integration system accepts both a set of data sources and a target ontology as input, and semi-automatically maps the data sources in terms of concepts and relationships in the target ontology. Mappings can be both complex and highly domain-specific. Once such a semantic model, expressing the mapping using community-wide standard, is acquired, the source data can be stored in a single repository or database using the semantics of the target ontology. However, acquiring the mapping is a labor-prone process, and state-of-the-art artificial intelligence systems are unable to fully automate the process using heuristics and algorithms alone. Instead, a more realistic goal is to develop adaptive tools that minimize user feedback (e.g., by offering good mapping recommendations), while at the same time making it intuitive and easy for the user to both correct errors and to define complex mappings. We present Karma, a data integration system that has been developed over multiple years in the information integration group at the Information Sciences Institute, a research institute at the University of Southern California's Viterbi School of Engineering. Karma is a state-of-the-art data integration tool that supports an interactive graphical user interface, and has been featured in multiple domains over the last five years, including geospatial, biological, humanities and bibliographic applications. Karma allows a user to import their own ontology and datasets using widely used formats such as RDF, XML, CSV and JSON, can be set up either locally or on a server, supports a native backend database for prototyping queries, and can even be seamlessly integrated into external computational pipelines, including those ingesting data via streaming data sources, Web APIs and SQL databases. We illustrate a Karma workflow at a conceptual level, along with a live demo, and show use cases of Karma specifically for the geosciences. In particular, we show how Karma can be used intuitively to obtain the mapping model between case study data sources and a publicly available and expressive target ontology that has been designed to capture a broad set of concepts in geoscience with standardized, easily searchable names.

Threshold automatic selection hybrid phase unwrapping algorithm for digital holographic microscopy

NASA Astrophysics Data System (ADS)

Zhou, Meiling; Min, Junwei; Yao, Baoli; Yu, Xianghua; Lei, Ming; Yan, Shaohui; Yang, Yanlong; Dan, Dan

2015-01-01

Conventional quality-guided (QG) phase unwrapping algorithm is hard to be applied to digital holographic microscopy because of the long execution time. In this paper, we present a threshold automatic selection hybrid phase unwrapping algorithm that combines the existing QG algorithm and the flood-filled (FF) algorithm to solve this problem. The original wrapped phase map is divided into high- and low-quality sub-maps by selecting a threshold automatically, and then the FF and QG unwrapping algorithms are used in each level to unwrap the phase, respectively. The feasibility of the proposed method is proved by experimental results, and the execution speed is shown to be much faster than that of the original QG unwrapping algorithm.

An attention-gating recurrent working memory architecture for emergent speech representation

NASA Astrophysics Data System (ADS)

Elshaw, Mark; Moore, Roger K.; Klein, Michael

2010-06-01

This paper describes an attention-gating recurrent self-organising map approach for emergent speech representation. Inspired by evidence from human cognitive processing, the architecture combines two main neural components. The first component, the attention-gating mechanism, uses actor-critic learning to perform selective attention towards speech. Through this selective attention approach, the attention-gating mechanism controls access to working memory processing. The second component, the recurrent self-organising map memory, develops a temporal-distributed representation of speech using phone-like structures. Representing speech in terms of phonetic features in an emergent self-organised fashion, according to research on child cognitive development, recreates the approach found in infants. Using this representational approach, in a fashion similar to infants, should improve the performance of automatic recognition systems through aiding speech segmentation and fast word learning.

Enhancing the usability and performance of structured association mapping algorithms using automation, parallelization, and visualization in the GenAMap software system

PubMed Central

2012-01-01

Background Structured association mapping is proving to be a powerful strategy to find genetic polymorphisms associated with disease. However, these algorithms are often distributed as command line implementations that require expertise and effort to customize and put into practice. Because of the difficulty required to use these cutting-edge techniques, geneticists often revert to simpler, less powerful methods. Results To make structured association mapping more accessible to geneticists, we have developed an automatic processing system called Auto-SAM. Auto-SAM enables geneticists to run structured association mapping algorithms automatically, using parallelization. Auto-SAM includes algorithms to discover gene-networks and find population structure. Auto-SAM can also run popular association mapping algorithms, in addition to five structured association mapping algorithms. Conclusions Auto-SAM is available through GenAMap, a front-end desktop visualization tool. GenAMap and Auto-SAM are implemented in JAVA; binaries for GenAMap can be downloaded from http://sailing.cs.cmu.edu/genamap. PMID:22471660

Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR.

PubMed

King, Andrew J; Hochheiser, Harry; Visweswaran, Shyam; Clermont, Gilles; Cooper, Gregory F

2017-01-01

Eye-tracking is a valuable research tool that is used in laboratory and limited field environments. We take steps toward developing methods that enable widespread adoption of eye-tracking and its real-time application in clinical decision support. Eye-tracking will enhance awareness and enable intelligent views, more precise alerts, and other forms of decision support in the Electronic Medical Record (EMR). We evaluated a low-cost eye-tracking device and found the device's accuracy to be non-inferior to a more expensive device. We also developed and evaluated an automatic method for mapping eye-tracking data to interface elements in the EMR (e.g., a displayed laboratory test value). Mapping was 88% accurate across the six participants in our experiment. Finally, we piloted the use of the low-cost device and the automatic mapping method to label training data for a Learning EMR (LEMR) which is a system that highlights the EMR elements a physician is predicted to use.

Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR

PubMed Central

King, Andrew J.; Hochheiser, Harry; Visweswaran, Shyam; Clermont, Gilles; Cooper, Gregory F.

2017-01-01

Eye-tracking is a valuable research tool that is used in laboratory and limited field environments. We take steps toward developing methods that enable widespread adoption of eye-tracking and its real-time application in clinical decision support. Eye-tracking will enhance awareness and enable intelligent views, more precise alerts, and other forms of decision support in the Electronic Medical Record (EMR). We evaluated a low-cost eye-tracking device and found the device’s accuracy to be non-inferior to a more expensive device. We also developed and evaluated an automatic method for mapping eye-tracking data to interface elements in the EMR (e.g., a displayed laboratory test value). Mapping was 88% accurate across the six participants in our experiment. Finally, we piloted the use of the low-cost device and the automatic mapping method to label training data for a Learning EMR (LEMR) which is a system that highlights the EMR elements a physician is predicted to use. PMID:28815151

Using text mining to link journal articles to neuroanatomical databases

PubMed Central

French, Leon; Pavlidis, Paul

2013-01-01

The electronic linking of neuroscience information, including data embedded in the primary literature, would permit powerful queries and analyses driven by structured databases. This task would be facilitated by automated procedures which can identify biological concepts in journals. Here we apply an approach for automatically mapping formal identifiers of neuroanatomical regions to text found in journal abstracts, and apply it to a large body of abstracts from the Journal of Comparative Neurology (JCN). The analyses yield over one hundred thousand brain region mentions which we map to 8,225 brain region concepts in multiple organisms. Based on the analysis of a manually annotated corpus, we estimate mentions are mapped at 95% precision and 63% recall. Our results provide insights into the patterns of publication on brain regions and species of study in the Journal, but also point to important challenges in the standardization of neuroanatomical nomenclatures. We find that many terms in the formal terminologies never appear in a JCN abstract, while conversely, many terms authors use are not reflected in the terminologies. To improve the terminologies we deposited 136 unrecognized brain regions into the Neuroscience Lexicon (NeuroLex). The training data, terminologies, normalizations, evaluations and annotated journal abstracts are freely available at http://www.chibi.ubc.ca/WhiteText/. PMID:22120205

Effective Web and Desktop Retrieval with Enhanced Semantic Spaces

NASA Astrophysics Data System (ADS)

Daoud, Amjad M.

We describe the design and implementation of the NETBOOK prototype system for collecting, structuring and efficiently creating semantic vectors for concepts, noun phrases, and documents from a corpus of free full text ebooks available on the World Wide Web. Automatic generation of concept maps from correlated index terms and extracted noun phrases are used to build a powerful conceptual index of individual pages. To ensure scalabilty of our system, dimension reduction is performed using Random Projection [13]. Furthermore, we present a complete evaluation of the relative effectiveness of the NETBOOK system versus the Google Desktop [8].

Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

NASA Astrophysics Data System (ADS)

Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

2014-06-01

This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

Towards natural language question generation for the validation of ontologies and mappings.

PubMed

Ben Abacha, Asma; Dos Reis, Julio Cesar; Mrabet, Yassine; Pruski, Cédric; Da Silveira, Marcos

2016-08-08

The increasing number of open-access ontologies and their key role in several applications such as decision-support systems highlight the importance of their validation. Human expertise is crucial for the validation of ontologies from a domain point-of-view. However, the growing number of ontologies and their fast evolution over time make manual validation challenging. We propose a novel semi-automatic approach based on the generation of natural language (NL) questions to support the validation of ontologies and their evolution. The proposed approach includes the automatic generation, factorization and ordering of NL questions from medical ontologies. The final validation and correction is performed by submitting these questions to domain experts and automatically analyzing their feedback. We also propose a second approach for the validation of mappings impacted by ontology changes. The method exploits the context of the changes to propose correction alternatives presented as Multiple Choice Questions. This research provides a question optimization strategy to maximize the validation of ontology entities with a reduced number of questions. We evaluate our approach for the validation of three medical ontologies. We also evaluate the feasibility and efficiency of our mappings validation approach in the context of ontology evolution. These experiments are performed with different versions of SNOMED-CT and ICD9. The obtained experimental results suggest the feasibility and adequacy of our approach to support the validation of interconnected and evolving ontologies. Results also suggest that taking into account RDFS and OWL entailment helps reducing the number of questions and validation time. The application of our approach to validate mapping evolution also shows the difficulty of adapting mapping evolution over time and highlights the importance of semi-automatic validation.

User Guide for the Anvil Threat Cooridor Forecast Tool V2.4 for AWIPS

NASA Technical Reports Server (NTRS)

Barett, Joe H., III; Bauman, William H., III

2008-01-01

The Anvil Tool GUI allows users to select a Data Type, toggle the map refresh on/off, place labels, and choose the Profiler Type (source of the KSC 50 MHz profiler data), the Date- Time of the data, the Center of Plot, and the Station (location of the RAOB or 50 MHz profiler). If the Data Type is Models, the user selects a Fcst Hour (forecast hour) instead of Station. There are menus for User Profiles, Circle Label Options, and Frame Label Options. Labels can be placed near the center circle of the plot and/or at a specified distance and direction from the center of the circle (Center of Plot). The default selection for the map refresh is "ON". When the user creates a new Anvil Tool map with Refresh Map "ON, the plot is automatically displayed in the AWIPS frame. If another Anvil Tool map is already displayed and the user does not change the existing map number shown at the bottom of the GUI, the new Anvil Tool map will overwrite the old one. If the user turns the Refresh Map "OFF", the new Anvil Tool map is created but not automatically displayed. The user can still display the Anvil Tool map through the Maps dropdown menu* as shown in Figure 4.

Vegetation survey in Amazonia using LANDSAT data. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Shimabukuro, Y. E.; Dossantos, J. R.; Deaquino, L. C. S.

1982-01-01

Automatic Image-100 analysis of LANDSAT data was performed using the MAXVER classification algorithm. In the pilot area, four vegetation units were mapped automatically in addition to the areas occupied for agricultural activities. The Image-100 classified results together with a soil map and information from RADAR images, permitted the establishment of the final legend with six classes: semi-deciduous tropical forest; low land evergreen tropical forest; secondary vegetation; tropical forest of humid areas, predominant pastureland and flood plains. Two water types were identified based on their sediments indicating different geological and geomorphological aspects.

a Model Study of Small-Scale World Map Generalization

NASA Astrophysics Data System (ADS)

Cheng, Y.; Yin, Y.; Li, C. M.; Wu, W.; Guo, P. P.; Ma, X. L.; Hu, F. M.

2018-04-01

With the globalization and rapid development every filed is taking an increasing interest in physical geography and human economics. There is a surging demand for small scale world map in large formats all over the world. Further study of automated mapping technology, especially the realization of small scale production on a large scale global map, is the key of the cartographic field need to solve. In light of this, this paper adopts the improved model (with the map and data separated) in the field of the mapmaking generalization, which can separate geographic data from mapping data from maps, mainly including cross-platform symbols and automatic map-making knowledge engine. With respect to the cross-platform symbol library, the symbol and the physical symbol in the geographic information are configured at all scale levels. With respect to automatic map-making knowledge engine consists 97 types, 1086 subtypes, 21845 basic algorithm and over 2500 relevant functional modules.In order to evaluate the accuracy and visual effect of our model towards topographic maps and thematic maps, we take the world map generalization in small scale as an example. After mapping generalization process, combining and simplifying the scattered islands make the map more explicit at 1 : 2.1 billion scale, and the map features more complete and accurate. Not only it enhance the map generalization of various scales significantly, but achieve the integration among map-makings of various scales, suggesting that this model provide a reference in cartographic generalization for various scales.

An Investigation of Automatic Change Detection for Topographic Map Updating

NASA Astrophysics Data System (ADS)

Duncan, P.; Smit, J.

2012-08-01

Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa's national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques.

Does training under consistent mapping conditions lead to automatic attention attraction to targets in search tasks?

PubMed

Lefebvre, Christine; Cousineau, Denis; Larochelle, Serge

2008-11-01

Schneider and Shiffrin (1977) proposed that training under consistent stimulus-response mapping (CM) leads to automatic target detection in search tasks. Other theories, such as Treisman and Gelade's (1980) feature integration theory, consider target-distractor discriminability as the main determinant of search performance. The first two experiments pit these two principles against each other. The results show that CM training is neither necessary nor sufficient to achieve optimal search performance. Two other experiments examine whether CM trained targets, presented as distractors in unattended display locations, attract attention away from current targets. The results are again found to vary with target-distractor similarity. Overall, the present study strongly suggests that CM training does not invariably lead to automatic attention attraction in search tasks.

Automated Bone Segmentation and Surface Evaluation of a Small Animal Model of Post-Traumatic Osteoarthritis.

PubMed

Ramme, Austin J; Voss, Kevin; Lesporis, Jurinus; Lendhey, Matin S; Coughlin, Thomas R; Strauss, Eric J; Kennedy, Oran D

2017-05-01

MicroCT imaging allows for noninvasive microstructural evaluation of mineralized bone tissue, and is essential in studies of small animal models of bone and joint diseases. Automatic segmentation and evaluation of articular surfaces is challenging. Here, we present a novel method to create knee joint surface models, for the evaluation of PTOA-related joint changes in the rat using an atlas-based diffeomorphic registration to automatically isolate bone from surrounding tissues. As validation, two independent raters manually segment datasets and the resulting segmentations were compared to our novel automatic segmentation process. Data were evaluated using label map volumes, overlap metrics, Euclidean distance mapping, and a time trial. Intraclass correlation coefficients were calculated to compare methods, and were greater than 0.90. Total overlap, union overlap, and mean overlap were calculated to compare the automatic and manual methods and ranged from 0.85 to 0.99. A Euclidean distance comparison was also performed and showed no measurable difference between manual and automatic segmentations. Furthermore, our new method was 18 times faster than manual segmentation. Overall, this study describes a reliable, accurate, and automatic segmentation method for mineralized knee structures from microCT images, and will allow for efficient assessment of bony changes in small animal models of PTOA.

Apollo: AN Automatic Procedure to Forecast Transport and Deposition of Tephra

NASA Astrophysics Data System (ADS)

Folch, A.; Costa, A.; Macedonio, G.

2007-05-01

Volcanic ash fallout represents a serious threat to communities around active volcanoes. Reliable short term predictions constitute a valuable support for to mitigate the effects of fallout on the surrounding area during an episode of crisis. We present a platform-independent automatic procedure aimed to daily forecast volcanic ash dispersal. The procedure builds on a series of programs and interfaces that allow an automatic data/results flow. Firstly the procedure downloads mesoscale meteorological forecasts for the region and period of interest, filters and converts data from its native format (typically GRIB format files), and sets up the CALMET diagnostic meteorological model to obtain hourly wind field and micro-meteorological variables on a finer mesh. Secondly a 1-D version of the buoyant plume equations assesses the distribution of mass along the eruptive column depending on the obtained wind field and on the conditions at the vent (granulometry, mass flow rate, etc.). All these data are used as input for the ash dispersion model(s). Any model able to face physical complexity and coupling processes with adequate solving times can be plugged into the system by means of an interface. Currently, the procedure contains the models HAZMAP, TEPHRA and FALL3D, the latter in both serial and parallel versions. Parallelization of FALL3D is done at two levels one for particle classes and one for spatial domain. The last step is to post-processes the model(s) outcomes to end up with homogeneous maps written on portable format files. Maps plot relevant quantities such as predicted ground load, expected deposit thickness or visual and flight safety concentration thresholds. Several applications are shown as examples.

A fully automatic three-step liver segmentation method on LDA-based probability maps for multiple contrast MR images.

PubMed

Gloger, Oliver; Kühn, Jens; Stanski, Adam; Völzke, Henry; Puls, Ralf

2010-07-01

Automatic 3D liver segmentation in magnetic resonance (MR) data sets has proven to be a very challenging task in the domain of medical image analysis. There exist numerous approaches for automatic 3D liver segmentation on computer tomography data sets that have influenced the segmentation of MR images. In contrast to previous approaches to liver segmentation in MR data sets, we use all available MR channel information of different weightings and formulate liver tissue and position probabilities in a probabilistic framework. We apply multiclass linear discriminant analysis as a fast and efficient dimensionality reduction technique and generate probability maps then used for segmentation. We develop a fully automatic three-step 3D segmentation approach based upon a modified region growing approach and a further threshold technique. Finally, we incorporate characteristic prior knowledge to improve the segmentation results. This novel 3D segmentation approach is modularized and can be applied for normal and fat accumulated liver tissue properties. Copyright 2010 Elsevier Inc. All rights reserved.

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

PubMed

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

2008-09-01

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

Study of smartphone suitability for mapping of skin chromophores

NASA Astrophysics Data System (ADS)

Kuzmina, Ilona; Lacis, Matiss; Spigulis, Janis; Berzina, Anna; Valeine, Lauma

2015-09-01

RGB (red-green-blue) technique for mapping skin chromophores by smartphones is proposed and studied. Three smartphones of different manufacturers were tested on skin phantoms and in vivo on benign skin lesions using a specially designed light source for illumination. Hemoglobin and melanin indices obtained by these smartphones showed differences in both tests. In vitro tests showed an increment of hemoglobin and melanin indices with the concentration of chromophores in phantoms. In vivo tests indicated higher hemoglobin index in hemangiomas than in nevi and healthy skin, and nevi showed higher melanin index compared to the healthy skin. Smartphones that allow switching off the automatic camera settings provided useful data, while those with "embedded" automatic settings appear to be useless for distant skin chromophore mapping.

Study of smartphone suitability for mapping of skin chromophores.

PubMed

Kuzmina, Ilona; Lacis, Matiss; Spigulis, Janis; Berzina, Anna; Valeine, Lauma

2015-09-01

RGB (red-green-blue) technique for mapping skin chromophores by smartphones is proposed and studied. Three smartphones of different manufacturers were tested on skin phantoms and in vivo on benign skin lesions using a specially designed light source for illumination. Hemoglobin and melanin indices obtained by these smartphones showed differences in both tests. In vitro tests showed an increment of hemoglobin and melanin indices with the concentration of chromophores in phantoms. In vivo tests indicated higher hemoglobin index in hemangiomas than in nevi and healthy skin, and nevi showed higher melanin index compared to the healthy skin. Smartphones that allow switching off the automatic camera settings provided useful data, while those with “embedded” automatic settings appear to be useless for distant skin chromophore mapping.

Basic forest cover mapping using digitized remote sensor data and automated data processing techniques

NASA Technical Reports Server (NTRS)

Coggeshall, M. E.; Hoffer, R. M.

1973-01-01

Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery

PubMed Central

Tamouridou, Afroditi A.; Lagopodi, Anastasia L.; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-01-01

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery. PMID:29019957

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery.

PubMed

Tamouridou, Afroditi A; Alexandridis, Thomas K; Pantazi, Xanthoula E; Lagopodi, Anastasia L; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-10-11

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery.

Automatic concrete cracks detection and mapping of terrestrial laser scan data

NASA Astrophysics Data System (ADS)

Rabah, Mostafa; Elhattab, Ahmed; Fayad, Atef

2013-12-01

Terrestrial laser scanning has become one of the standard technologies for object acquisition in surveying engineering. The high spatial resolution of imaging and the excellent capability of measuring the 3D space by laser scanning bear a great potential if combined for both data acquisition and data compilation. Automatic crack detection from concrete surface images is very effective for nondestructive testing. The crack information can be used to decide the appropriate rehabilitation method to fix the cracked structures and prevent any catastrophic failure. In practice, cracks on concrete surfaces are traced manually for diagnosis. On the other hand, automatic crack detection is highly desirable for efficient and objective crack assessment. The current paper submits a method for automatic concrete cracks detection and mapping from the data that was obtained during laser scanning survey. The method of cracks detection and mapping is achieved by three steps, namely the step of shading correction in the original image, step of crack detection and finally step of crack mapping and processing steps. The detected crack is defined in a pixel coordinate system. To remap the crack into the referred coordinate system, a reverse engineering is used. This is achieved by a hybrid concept of terrestrial laser-scanner point clouds and the corresponding camera image, i.e. a conversion from the pixel coordinate system to the terrestrial laser-scanner or global coordinate system. The results of the experiment show that the mean differences between terrestrial laser scan and the total station are about 30.5, 16.4 and 14.3 mms in x, y and z direction, respectively.

WRIS: a resource information system for wildland management

Treesearch

Robert M. Russell; David A. Sharpnack; Elliot Amidon

1975-01-01

WRIS (Wildland Resource Information System) is a computer system for processing, storing, retrieving, updating, and displaying geographic data. The polygon, representing a land area boundary, forms the building block of WRIS. Polygons form a map. Maps are digitized manually or by automatic scanning. Computer programs can extract and produce polygon maps and can overlay...

A Radio-Map Automatic Construction Algorithm Based on Crowdsourcing

PubMed Central

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

2016-01-01

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

Application of nonlinear transformations to automatic flight control

NASA Technical Reports Server (NTRS)

Meyer, G.; Su, R.; Hunt, L. R.

1984-01-01

The theory of transformations of nonlinear systems to linear ones is applied to the design of an automatic flight controller for the UH-1H helicopter. The helicopter mathematical model is described and it is shown to satisfy the necessary and sufficient conditions for transformability. The mapping is constructed, taking the nonlinear model to canonical form. The performance of the automatic control system in a detailed simulation on the flight computer is summarized.

Automatic detection of artifacts in converted S3D video

NASA Astrophysics Data System (ADS)

Bokov, Alexander; Vatolin, Dmitriy; Zachesov, Anton; Belous, Alexander; Erofeev, Mikhail

2014-03-01

In this paper we present algorithms for automatically detecting issues specific to converted S3D content. When a depth-image-based rendering approach produces a stereoscopic image, the quality of the result depends on both the depth maps and the warping algorithms. The most common problem with converted S3D video is edge-sharpness mismatch. This artifact may appear owing to depth-map blurriness at semitransparent edges: after warping, the object boundary becomes sharper in one view and blurrier in the other, yielding binocular rivalry. To detect this problem we estimate the disparity map, extract boundaries with noticeable differences, and analyze edge-sharpness correspondence between views. We pay additional attention to cases involving a complex background and large occlusions. Another problem is detection of scenes that lack depth volume: we present algorithms for detecting at scenes and scenes with at foreground objects. To identify these problems we analyze the features of the RGB image as well as uniform areas in the depth map. Testing of our algorithms involved examining 10 Blu-ray 3D releases with converted S3D content, including Clash of the Titans, The Avengers, and The Chronicles of Narnia: The Voyage of the Dawn Treader. The algorithms we present enable improved automatic quality assessment during the production stage.

Potential and limitations of webcam images for snow cover monitoring in the Swiss Alps

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2017-04-01

In Switzerland, several thousands of outdoor webcams are currently connected to the Internet. They deliver freely available images that can be used to analyze snow cover variability on a high spatio-temporal resolution. To make use of this big data source, we have implemented a webcam-based snow cover mapping procedure, which allows to almost automatically derive snow cover maps from such webcam images. As there is mostly no information about the webcams and its parameters available, our registration approach automatically resolves these parameters (camera orientation, principal point, field of view) by using an estimate of the webcams position, the mountain silhouette, and a high-resolution digital elevation model (DEM). Combined with an automatic snow classification and an image alignment using SIFT features, our procedure can be applied to arbitrary images to generate snow cover maps with a minimum of effort. Resulting snow cover maps have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or hidden from webcams' positions. Up to now, we processed images of about 290 webcams from our archive, and evaluated images of 20 webcams using manually selected ground control points (GCPs) to evaluate the mapping accuracy of our procedure. We present methodological limitations and ongoing improvements, show some applications of our snow cover maps, and demonstrate that webcams not only offer a great opportunity to complement satellite-derived snow retrieval under cloudy conditions, but also serve as a reference for improved validation of satellite-based approaches.

Fast Quantitative Susceptibility Mapping with L1-Regularization and Automatic Parameter Selection

PubMed Central

Bilgic, Berkin; Fan, Audrey P.; Polimeni, Jonathan R.; Cauley, Stephen F.; Bianciardi, Marta; Adalsteinsson, Elfar; Wald, Lawrence L.; Setsompop, Kawin

2014-01-01

Purpose To enable fast reconstruction of quantitative susceptibility maps with Total Variation penalty and automatic regularization parameter selection. Methods ℓ1-regularized susceptibility mapping is accelerated by variable-splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and FFTs. This fast algorithm also renders automatic regularization parameter estimation practical. A weighting mask derived from the magnitude signal can be incorporated to allow edge-aware regularization. Results Compared to the nonlinear Conjugate Gradient (CG) solver, the proposed method offers 20× speed-up in reconstruction time. A complete pipeline including Laplacian phase unwrapping, background phase removal with SHARP filtering and ℓ1-regularized dipole inversion at 0.6 mm isotropic resolution is completed in 1.2 minutes using Matlab on a standard workstation compared to 22 minutes using the Conjugate Gradient solver. This fast reconstruction allows estimation of regularization parameters with the L-curve method in 13 minutes, which would have taken 4 hours with the CG algorithm. Proposed method also permits magnitude-weighted regularization, which prevents smoothing across edges identified on the magnitude signal. This more complicated optimization problem is solved 5× faster than the nonlinear CG approach. Utility of the proposed method is also demonstrated in functional BOLD susceptibility mapping, where processing of the massive time-series dataset would otherwise be prohibitive with the CG solver. Conclusion Online reconstruction of regularized susceptibility maps may become feasible with the proposed dipole inversion. PMID:24259479

Significantly Reduced Blood Pressure Measurement Variability for Both Normotensive and Hypertensive Subjects: Effect of Polynomial Curve Fitting of Oscillometric Pulses

PubMed Central

Zhu, Mingping; Chen, Aiqing

2017-01-01

This study aimed to compare within-subject blood pressure (BP) variabilities from different measurement techniques. Cuff pressures from three repeated BP measurements were obtained from 30 normotensive and 30 hypertensive subjects. Automatic BPs were determined from the pulses with normalised peak amplitude larger than a threshold (0.5 for SBP, 0.7 for DBP, and 1.0 for MAP). They were also determined from cuff pressures associated with the above thresholds on a fitted curve polynomial curve of the oscillometric pulse peaks. Finally, the standard deviation (SD) of three repeats and its coefficient of variability (CV) were compared between the two automatic techniques. For the normotensive group, polynomial curve fitting significantly reduced SD of repeats from 3.6 to 2.5 mmHg for SBP and from 3.7 to 2.1 mmHg for MAP and reduced CV from 3.0% to 2.2% for SBP and from 4.3% to 2.4% for MAP (all P < 0.01). For the hypertensive group, SD of repeats decreased from 6.5 to 5.5 mmHg for SBP and from 6.7 to 4.2 mmHg for MAP, and CV decreased from 4.2% to 3.6% for SBP and from 5.8% to 3.8% for MAP (all P < 0.05). In conclusion, polynomial curve fitting of oscillometric pulses had the ability to reduce automatic BP measurement variability. PMID:28785580

Rheticus: a cloud-based Geo-Information Service for the Detection and Monitoring of Geohazards and Infrastructural Instabilities

NASA Astrophysics Data System (ADS)

Chiaradia, M. T.; Samarelli, S.; Massimi, V.; Nutricato, R.; Nitti, D. O.; Morea, A.; Tijani, K.

2017-12-01

Geospatial information is today essential for organizations and professionals working in several industries. More and more, huge information is collected from multiple data sources and is freely available to anyone as open data. Rheticus® is an innovative cloud-based data and services hub able to deliver Earth Observation added-value products through automatic complex processes and, if appropriate, a minimum interaction with human operators. This target is achieved by means of programmable components working as different software layers in a modern enterprise system which relies on SOA (Service-Oriented-Architecture) model. Due to its spread architecture, where every functionality is defined and encapsulated in a standalone component, Rheticus is potentially highly scalable and distributable allowing different configurations depending on the user needs. This approach makes the system very flexible with respect to the services implementation, ensuring the ability to rethink and redesign the whole process with little effort. In this work, we outline the overall cloud-based platform and focus on the "Rheticus Displacement" service, aimed at providing accurate information to monitor movements occurring across landslide features or structural instabilities that could affect buildings or infrastructures. Using Sentinel-1 (S1) open data images and Multi-Temporal SAR Interferometry techniques (MTInSAR), the service is complementary to traditional survey methods, providing a long-term solution to slope instability monitoring. Rheticus automatically browses and accesses (on a weekly basis) the products of the rolling archive of ESA S1 Scientific Data Hub. S1 data are then processed by SPINUA (Stable Point Interferometry even in Unurbanized Areas), a robust MTInSAR algorithm, which is responsible of producing displacement maps immediately usable to measure movements of point and distributed scatterers, with sub-centimetric precision. We outline the automatic generation process of displacement maps and we provide examples of the detection and monitoring of geohazard and infrastructure instabilities. ACK: Rheticus® is a registered trademark of Planetek Italia srl. Study carried out in the framework of the FAST4MAP project (ASI Contract n. 2015-020-R.0). Sentinel-1A products provided by ESA.

A Graphics System for Pole-Zero Map Analysis.

ERIC Educational Resources Information Center

Beyer, William Fred, III

Computer scientists have developed an interactive, graphical display system for pole-zero map analysis. They designed it for use as an educational tool in teaching introductory courses in automatic control systems. The facilities allow the user to specify a control system and an input function in the form of a pole-zero map and then examine the…

Improving Critical Thinking Using Web Based Argument Mapping Exercises with Automated Feedback

ERIC Educational Resources Information Center

Butchart, Sam; Forster, Daniella; Gold, Ian; Bigelow, John; Korb, Kevin; Oppy, Graham; Serrenti, Alexandra

2009-01-01

In this paper we describe a simple software system that allows students to practise their critical thinking skills by constructing argument maps of natural language arguments. As the students construct their maps of an argument, the system provides automatic, real time feedback on their progress. We outline the background and theoretical framework…

Near-real-time simulation and internet-based delivery of forecast-flood inundation maps using two-dimensional hydraulic modeling--A pilot study for the Snoqualmie River, Washington

USGS Publications Warehouse

Jones, Joseph L.; Fulford, Janice M.; Voss, Frank D.

2002-01-01

A system of numerical hydraulic modeling, geographic information system processing, and Internet map serving, supported by new data sources and application automation, was developed that generates inundation maps for forecast floods in near real time and makes them available through the Internet. Forecasts for flooding are generated by the National Weather Service (NWS) River Forecast Center (RFC); these forecasts are retrieved automatically by the system and prepared for input to a hydraulic model. The model, TrimR2D, is a new, robust, two-dimensional model capable of simulating wide varieties of discharge hydrographs and relatively long stream reaches. TrimR2D was calibrated for a 28-kilometer reach of the Snoqualmie River in Washington State, and is used to estimate flood extent, depth, arrival time, and peak time for the RFC forecast. The results of the model are processed automatically by a Geographic Information System (GIS) into maps of flood extent, depth, and arrival and peak times. These maps subsequently are processed into formats acceptable by an Internet map server (IMS). The IMS application is a user-friendly interface to access the maps over the Internet; it allows users to select what information they wish to see presented and allows the authors to define scale-dependent availability of map layers and their symbology (appearance of map features). For example, the IMS presents a background of a digital USGS 1:100,000-scale quadrangle at smaller scales, and automatically switches to an ortho-rectified aerial photograph (a digital photograph that has camera angle and tilt distortions removed) at larger scales so viewers can see ground features that help them identify their area of interest more effectively. For the user, the option exists to select either background at any scale. Similar options are provided for both the map creator and the viewer for the various flood maps. This combination of a robust model, emerging IMS software, and application interface programming should allow the technology developed in the pilot study to be applied to other river systems where NWS forecasts are provided routinely.

ShakeCast Manual

USGS Publications Warehouse

Lin, Kuo-Wan; Wald, David J.

2008-01-01

ShakeCast is a freely available, post-earthquake situational awareness application that automatically retrieves earthquake shaking data from ShakeMap, compares intensity measures against users? facilities, and generates potential damage assessment notifications, facility damage maps, and other Web-based products for emergency managers and responders.

QuickMap: a public tool for large-scale gene therapy vector insertion site mapping and analysis.

PubMed

Appelt, J-U; Giordano, F A; Ecker, M; Roeder, I; Grund, N; Hotz-Wagenblatt, A; Opelz, G; Zeller, W J; Allgayer, H; Fruehauf, S; Laufs, S

2009-07-01

Several events of insertional mutagenesis in pre-clinical and clinical gene therapy studies have created intense interest in assessing the genomic insertion profiles of gene therapy vectors. For the construction of such profiles, vector-flanking sequences detected by inverse PCR, linear amplification-mediated-PCR or ligation-mediated-PCR need to be mapped to the host cell's genome and compared to a reference set. Although remarkable progress has been achieved in mapping gene therapy vector insertion sites, public reference sets are lacking, as are the possibilities to quickly detect non-random patterns in experimental data. We developed a tool termed QuickMap, which uniformly maps and analyzes human and murine vector-flanking sequences within seconds (available at www.gtsg.org). Besides information about hits in chromosomes and fragile sites, QuickMap automatically determines insertion frequencies in +/- 250 kb adjacency to genes, cancer genes, pseudogenes, transcription factor and (post-transcriptional) miRNA binding sites, CpG islands and repetitive elements (short interspersed nuclear elements (SINE), long interspersed nuclear elements (LINE), Type II elements and LTR elements). Additionally, all experimental frequencies are compared with the data obtained from a reference set, containing 1 000 000 random integrations ('random set'). Thus, for the first time a tool allowing high-throughput profiling of gene therapy vector insertion sites is available. It provides a basis for large-scale insertion site analyses, which is now urgently needed to discover novel gene therapy vectors with 'safe' insertion profiles.

Using airborne LiDAR in geoarchaeological contexts: Assessment of an automatic tool for the detection and the morphometric analysis of grazing archaeological structures (French Massif Central).

NASA Astrophysics Data System (ADS)

Roussel, Erwan; Toumazet, Jean-Pierre; Florez, Marta; Vautier, Franck; Dousteyssier, Bertrand

2014-05-01

Airborne laser scanning (ALS) of archaeological regions of interest is nowadays a widely used and established method for accurate topographic and microtopographic survey. The penetration of the vegetation cover by the laser beam allows the reconstruction of reliable digital terrain models (DTM) of forested areas where traditional prospection methods are inefficient, time-consuming and non-exhaustive. The ALS technology provides the opportunity to discover new archaeological features hidden by vegetation and provides a comprehensive survey of cultural heritage sites within their environmental context. However, the post-processing of LiDAR points clouds produces a huge quantity of data in which relevant archaeological features are not easily detectable with common visualizing and analysing tools. Undoubtedly, there is an urgent need for automation of structures detection and morphometric extraction techniques, especially for the "archaeological desert" in densely forested areas. This presentation deals with the development of automatic detection procedures applied to archaeological structures located in the French Massif Central, in the western forested part of the Puy-de-Dôme volcano between 950 and 1100 m a.s.l.. These unknown archaeological sites were discovered by the March 2011 ALS mission and display a high density of subcircular depressions with a corridor access. The spatial organization of these depressions vary from isolated to aggregated or aligned features. Functionally, they appear to be former grazing constructions built from the medieval to the modern period. Similar grazing structures are known in other locations of the French Massif Central (Sancy, Artense, Cézallier) where the ground is vegetation-free. In order to develop a reliable process of automatic detection and mapping of these archaeological structures, a learning zone has been delineated within the ALS surveyed area. The grazing features were mapped and typical morphometric attributes were calculated based on 2 methods: (i) The mapping of the archaeological structures by a human operator using common visualisation tools (DTM, multi-direction hillshading & local relief models) within a GIS environment; (ii) The automatic detection and mapping performed by a recognition algorithm based on a user defined geometric pattern of the grazing structures. The efficiency of the automatic tool has been assessed by comparing the number of structures detected and the morphometric attributes calculated by the two methods. Our results indicate that the algorithm is efficient for the detection and the location of grazing structures. Concerning the morphometric results, there is still a discrepancy between automatic and expert calculations, due to both the expert mapping choices and the algorithm calibration.

Ultramap: the all in One Photogrammetric Solution

NASA Astrophysics Data System (ADS)

Wiechert, A.; Gruber, M.; Karner, K.

2012-07-01

This paper describes in detail the dense matcher developed since years by Vexcel Imaging in Graz for Microsoft's Bing Maps project. This dense matcher was exclusively developed for and used by Microsoft for the production of the 3D city models of Virtual Earth. It will now be made available to the public with the UltraMap software release mid-2012. That represents a revolutionary step in digital photogrammetry. The dense matcher generates digital surface models (DSM) and digital terrain models (DTM) automatically out of a set of overlapping UltraCam images. The models have an outstanding point density of several hundred points per square meter and sub-pixel accuracy and are generated automatically. The dense matcher consists of two steps. The first step rectifies overlapping image areas to speed up the dense image matching process. This rectification step ensures a very efficient processing and detects occluded areas by applying a back-matching step. In this dense image matching process a cost function consisting of a matching score as well as a smoothness term is minimized. In the second step the resulting range image patches are fused into a DSM by optimizing a global cost function. The whole process is optimized for multi-core CPUs and optionally uses GPUs if available. UltraMap 3.0 features also an additional step which is presented in this paper, a complete automated true-ortho and ortho workflow. For this, the UltraCam images are combined with the DSM or DTM in an automated rectification step and that results in high quality true-ortho or ortho images as a result of a highly automated workflow. The paper presents the new workflow and first results.

30 CFR 75.1103-5 - Automatic fire warning devices; actions and response.

Code of Federal Regulations, 2010 CFR

2010-07-01

... level reaches 10 parts per million above the established ambient level at any sensor location, automatic fire sensor and warning device systems shall provide an effective warning signal at the following... endangered and (ii) A map or schematic that shows the locations of sensors, and the intended air flow...

Comparison of Landsat-8, ASTER and Sentinel 1 satellite remote sensing data in automatic lineaments extraction: A case study of Sidi Flah-Bouskour inlier, Moroccan Anti Atlas

NASA Astrophysics Data System (ADS)

Adiri, Zakaria; El Harti, Abderrazak; Jellouli, Amine; Lhissou, Rachid; Maacha, Lhou; Azmi, Mohamed; Zouhair, Mohamed; Bachaoui, El Mostafa

2017-12-01

Certainly, lineament mapping occupies an important place in several studies, including geology, hydrogeology and topography etc. With the help of remote sensing techniques, lineaments can be better identified due to strong advances in used data and methods. This allowed exceeding the usual classical procedures and achieving more precise results. The aim of this work is the comparison of ASTER, Landsat-8 and Sentinel 1 data sensors in automatic lineament extraction. In addition to image data, the followed approach includes the use of the pre-existing geological map, the Digital Elevation Model (DEM) as well as the ground truth. Through a fully automatic approach consisting of a combination of edge detection algorithm and line-linking algorithm, we have found the optimal parameters for automatic lineament extraction in the study area. Thereafter, the comparison and the validation of the obtained results showed that the Sentinel 1 data are more efficient in restitution of lineaments. This indicates the performance of the radar data compared to those optical in this kind of study.

Single-Frame Terrain Mapping Software for Robotic Vehicles

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.

2011-01-01

This software is a component in an unmanned ground vehicle (UGV) perception system that builds compact, single-frame terrain maps for distribution to other systems, such as a world model or an operator control unit, over a local area network (LAN). Each cell in the map encodes an elevation value, terrain classification, object classification, terrain traversability, terrain roughness, and a confidence value into four bytes of memory. The input to this software component is a range image (from a lidar or stereo vision system), and optionally a terrain classification image and an object classification image, both registered to the range image. The single-frame terrain map generates estimates of the support surface elevation, ground cover elevation, and minimum canopy elevation; generates terrain traversability cost; detects low overhangs and high-density obstacles; and can perform geometry-based terrain classification (ground, ground cover, unknown). A new origin is automatically selected for each single-frame terrain map in global coordinates such that it coincides with the corner of a world map cell. That way, single-frame terrain maps correctly line up with the world map, facilitating the merging of map data into the world map. Instead of using 32 bits to store the floating-point elevation for a map cell, the vehicle elevation is assigned to the map origin elevation and reports the change in elevation (from the origin elevation) in terms of the number of discrete steps. The single-frame terrain map elevation resolution is 2 cm. At that resolution, terrain elevation from 20.5 to 20.5 m (with respect to the vehicle's elevation) is encoded into 11 bits. For each four-byte map cell, bits are assigned to encode elevation, terrain roughness, terrain classification, object classification, terrain traversability cost, and a confidence value. The vehicle s current position and orientation, the map origin, and the map cell resolution are all included in a header for each map. The map is compressed into a vector prior to delivery to another system.

Structural Validation of Nursing Terminologies

PubMed Central

Hardiker, Nicholas R.; Rector, Alan L.

2001-01-01

Objective: The purpose of the study is twofold: 1) to explore the applicability of combinatorial terminologies as the basis for building enumerated classifications, and 2) to investigate the usefulness of formal terminological systems for performing such classification and for assisting in the refinement of both combinatorial terminologies and enumerated classifications. Design: A formal model of the beta version of the International Classification for Nursing Practice (ICNP) was constructed in the compositional terminological language GRAIL (GALEN Representation and Integration Language). Terms drawn from the North American Nursing Diagnosis Association Taxonomy I (NANDA taxonomy) were mapped into the model and classified automatically using GALEN technology. Measurements: The resulting generated hierarchy was compared with the NANDA taxonomy to assess coverage and accuracy of classification. Results: In terms of coverage, in this study ICNP was able to capture 77 percent of NANDA terms using concepts drawn from five of its eight axes. Three axes—Body Site, Topology, and Frequency—were not needed. In terms of accuracy, where hierarchic relationships existed in the generated hierarchy or the NANDA taxonomy, or both, 6 were identical, 19 existed in the generated hierarchy alone (2 of these were considered suitable for incorporation into the NANDA taxonomy and 17 were considered inaccurate), and 23 appeared in the NANDA taxonomy alone (8 of these were considered suitable for incorporation into ICNP, 9 were considered inaccurate, and 6 reflected different, equally valid perspectives). Sixty terms appeared at the top level, with no indenting, in both the generated hierarchy and the NANDA taxonomy. Conclusions: With appropriate refinement, combinatorial terminologies such as ICNP have the potential to provide a useful foundation for representing enumerated classifications such as NANDA. Technologies such as GALEN make possible the process of building automatically enumerated classifications while providing a useful means of validating and refining both combinatorial terminologies and enumerated classifications. PMID:11320066

Technical Note: A 3-D rendering algorithm for electromechanical wave imaging of a beating heart.

PubMed

Nauleau, Pierre; Melki, Lea; Wan, Elaine; Konofagou, Elisa

2017-09-01

Arrhythmias can be treated by ablating the heart tissue in the regions of abnormal contraction. The current clinical standard provides electroanatomic 3-D maps to visualize the electrical activation and locate the arrhythmogenic sources. However, the procedure is time-consuming and invasive. Electromechanical wave imaging is an ultrasound-based noninvasive technique that can provide 2-D maps of the electromechanical activation of the heart. In order to fully visualize the complex 3-D pattern of activation, several 2-D views are acquired and processed separately. They are then manually registered with a 3-D rendering software to generate a pseudo-3-D map. However, this last step is operator-dependent and time-consuming. This paper presents a method to generate a full 3-D map of the electromechanical activation using multiple 2-D images. Two canine models were considered to illustrate the method: one in normal sinus rhythm and one paced from the lateral region of the heart. Four standard echographic views of each canine heart were acquired. Electromechanical wave imaging was applied to generate four 2-D activation maps of the left ventricle. The radial positions and activation timings of the walls were automatically extracted from those maps. In each slice, from apex to base, these values were interpolated around the circumference to generate a full 3-D map. In both cases, a 3-D activation map and a cine-loop of the propagation of the electromechanical wave were automatically generated. The 3-D map showing the electromechanical activation timings overlaid on realistic anatomy assists with the visualization of the sources of earlier activation (which are potential arrhythmogenic sources). The earliest sources of activation corresponded to the expected ones: septum for the normal rhythm and lateral for the pacing case. The proposed technique provides, automatically, a 3-D electromechanical activation map with a realistic anatomy. This represents a step towards a noninvasive tool to efficiently localize arrhythmias in 3-D. © 2017 American Association of Physicists in Medicine.

A New Automatic Method of Urban Areas Mapping in East Asia from LANDSAT Data

NASA Astrophysics Data System (ADS)

XU, R.; Jia, G.

2012-12-01

Cities, as places where human activities are concentrated, account for a small percent of global land cover but are frequently cited as the chief causes of, and solutions to, climate, biogeochemistry, and hydrology processes at local, regional, and global scales. Accompanying with uncontrolled economic growth, urban sprawl has been attributed to the accelerating integration of East Asia into the world economy and involved dramatic changes in its urban form and land use. To understand the impact of urban extent on biogeophysical processes, reliable mapping of built-up areas is particularly essential in eastern cities as a result of their characteristics of smaller patches, more fragile, and a lower fraction of the urban landscape which does not have natural than in the West. Segmentation of urban land from other land-cover types using remote sensing imagery can be done by standard classification processes as well as a logic rule calculation based on spectral indices and their derivations. Efforts to establish such a logic rule with no threshold for automatically mapping are highly worthwhile. Existing automatic methods are reviewed, and then a proposed approach is introduced including the calculation of the new index and the improved logic rule. Following this, existing automatic methods as well as the proposed approach are compared in a common context. Afterwards, the proposed approach is tested separately in cities of large, medium, and small scale in East Asia selected from different LANDSAT images. The results are promising as the approach can efficiently segment urban areas, even in the presence of more complex eastern cities. Key words: Urban extraction; Automatic Method; Logic Rule; LANDSAT images; East AisaThe Proposed Approach of Extraction of Urban Built-up Areas in Guangzhou, China

[The automatic iris map overlap technology in computer-aided iridiagnosis].

PubMed

He, Jia-feng; Ye, Hu-nian; Ye, Miao-yuan

2002-11-01

In the paper, iridology and computer-aided iridiagnosis technologies are briefly introduced and the extraction method of the collarette contour is then investigated. The iris map can be overlapped on the original iris image based on collarette contour extraction. The research on collarette contour extraction and iris map overlap is of great importance to computer-aided iridiagnosis technologies.

An effective self-assessment based on concept map extraction from test-sheet for personalized learning

NASA Astrophysics Data System (ADS)

Liew, Keng-Hou; Lin, Yu-Shih; Chang, Yi-Chun; Chu, Chih-Ping

2013-12-01

Examination is a traditional way to assess learners' learning status, progress and performance after a learning activity. Except the test grade, a test sheet hides some implicit information such as test concepts, their relationships, importance, and prerequisite. The implicit information can be extracted and constructed a concept map for considering (1) the test concepts covered in the same question means these test concepts have strong relationships, and (2) questions in the same test sheet means the test concepts are relative. Concept map has been successfully employed in many researches to help instructors and learners organize relationships among concepts. However, concept map construction depends on experts who need to take effort and time for the organization of the domain knowledge. In addition, the previous researches regarding to automatic concept map construction are limited to consider all learners of a class, which have not considered personalized learning. To cope with this problem, this paper proposes a new approach to automatically extract and construct concept map based on implicit information in a test sheet. Furthermore, the proposed approach also can help learner for self-assessment and self-diagnosis. Finally, an example is given to depict the effectiveness of proposed approach.

Adaptive Registration of Varying Contrast-Weighted Images for Improved Tissue Characterization (ARCTIC): Application to T1 Mapping

PubMed Central

Roujol, Sébastien; Foppa, Murilo; Weingartner, Sebastian; Manning, Warren J.; Nezafat, Reza

2014-01-01

Purpose To propose and evaluate a novel non-rigid image registration approach for improved myocardial T1 mapping. Methods Myocardial motion is estimated as global affine motion refined by a novel local non-rigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient (DSC) and the myocardial boundary error (MBE) in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion”. Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-non diagnostic/severe motion artifact, 4-excellent/no motion artifact). Results Increased DSC (0.78±0.14 to 0.87±0.03, p<0.001), reduced MBE (1.29±0.72mm to 0.84±0.20mm, p<0.001), improved overall T1 map quality (2.86±1.04 to 3.49±0.77, p<0.001), and reduced T1 map motion artifacts (2.51±0.84 to 3.61±0.64, p<0.001) were obtained after motion correction of “with motion” data (~56% of data). Conclusion The proposed non-rigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. PMID:24798588

Terminologies for text-mining; an experiment in the lipoprotein metabolism domain

PubMed Central

Alexopoulou, Dimitra; Wächter, Thomas; Pickersgill, Laura; Eyre, Cecilia; Schroeder, Michael

2008-01-01

Background The engineering of ontologies, especially with a view to a text-mining use, is still a new research field. There does not yet exist a well-defined theory and technology for ontology construction. Many of the ontology design steps remain manual and are based on personal experience and intuition. However, there exist a few efforts on automatic construction of ontologies in the form of extracted lists of terms and relations between them. Results We share experience acquired during the manual development of a lipoprotein metabolism ontology (LMO) to be used for text-mining. We compare the manually created ontology terms with the automatically derived terminology from four different automatic term recognition (ATR) methods. The top 50 predicted terms contain up to 89% relevant terms. For the top 1000 terms the best method still generates 51% relevant terms. In a corpus of 3066 documents 53% of LMO terms are contained and 38% can be generated with one of the methods. Conclusions Given high precision, automatic methods can help decrease development time and provide significant support for the identification of domain-specific vocabulary. The coverage of the domain vocabulary depends strongly on the underlying documents. Ontology development for text mining should be performed in a semi-automatic way; taking ATR results as input and following the guidelines we described. Availability The TFIDF term recognition is available as Web Service, described at PMID:18460175

Automating the selection of standard parallels for conic map projections

NASA Astrophysics Data System (ADS)

Šavriǒ, Bojan; Jenny, Bernhard

2016-05-01

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

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

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

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Automatic mapping of event landslides at basin scale in Taiwan using a Montecarlo approach and synthetic land cover fingerprints

NASA Astrophysics Data System (ADS)

Mondini, Alessandro C.; Chang, Kang-Tsung; Chiang, Shou-Hao; Schlögel, Romy; Notarnicola, Claudia; Saito, Hitoshi

2017-12-01

We propose a framework to systematically generate event landslide inventory maps from satellite images in southern Taiwan, where landslides are frequent and abundant. The spectral information is used to assess the pixel land cover class membership probability through a Maximum Likelihood classifier trained with randomly generated synthetic land cover spectral fingerprints, which are obtained from an independent training images dataset. Pixels are classified as landslides when the calculated landslide class membership probability, weighted by a susceptibility model, is higher than membership probabilities of other classes. We generated synthetic fingerprints from two FORMOSAT-2 images acquired in 2009 and tested the procedure on two other images, one in 2005 and the other in 2009. We also obtained two landslide maps through manual interpretation. The agreement between the two sets of inventories is given by the Cohen's k coefficients of 0.62 and 0.64, respectively. This procedure can now classify a new FORMOSAT-2 image automatically facilitating the production of landslide inventory maps.

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

DOE PAGES

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.; ...

2015-10-09

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Semi-automatic mapping of linear-trending bedforms using 'Self-Organizing Maps' algorithm

NASA Astrophysics Data System (ADS)

Foroutan, M.; Zimbelman, J. R.

2017-09-01

Increased application of high resolution spatial data such as high resolution satellite or Unmanned Aerial Vehicle (UAV) images from Earth, as well as High Resolution Imaging Science Experiment (HiRISE) images from Mars, makes it necessary to increase automation techniques capable of extracting detailed geomorphologic elements from such large data sets. Model validation by repeated images in environmental management studies such as climate-related changes as well as increasing access to high-resolution satellite images underline the demand for detailed automatic image-processing techniques in remote sensing. This study presents a methodology based on an unsupervised Artificial Neural Network (ANN) algorithm, known as Self Organizing Maps (SOM), to achieve the semi-automatic extraction of linear features with small footprints on satellite images. SOM is based on competitive learning and is efficient for handling huge data sets. We applied the SOM algorithm to high resolution satellite images of Earth and Mars (Quickbird, Worldview and HiRISE) in order to facilitate and speed up image analysis along with the improvement of the accuracy of results. About 98% overall accuracy and 0.001 quantization error in the recognition of small linear-trending bedforms demonstrate a promising framework.

Proceeding of the ACM/IEEE-CS Joint Conference on Digital Libraries (1st, Roanoke, Virginia, June 24-28, 2001).

ERIC Educational Resources Information Center

Association for Computing Machinery, New York, NY.

Papers in this Proceedings of the ACM/IEEE-CS Joint Conference on Digital Libraries (Roanoke, Virginia, June 24-28, 2001) discuss: automatic genre analysis; text categorization; automated name authority control; automatic event generation; linked active content; designing e-books for legal research; metadata harvesting; mapping the…

Cross-terminology mapping challenges: a demonstration using medication terminological systems.

PubMed

Saitwal, Himali; Qing, David; Jones, Stephen; Bernstam, Elmer V; Chute, Christopher G; Johnson, Todd R

2012-08-01

Standardized terminological systems for biomedical information have provided considerable benefits to biomedical applications and research. However, practical use of this information often requires mapping across terminological systems-a complex and time-consuming process. This paper demonstrates the complexity and challenges of mapping across terminological systems in the context of medication information. It provides a review of medication terminological systems and their linkages, then describes a case study in which we mapped proprietary medication codes from an electronic health record to SNOMED CT and the UMLS Metathesaurus. The goal was to create a polyhierarchical classification system for querying an i2b2 clinical data warehouse. We found that three methods were required to accurately map the majority of actively prescribed medications. Only 62.5% of source medication codes could be mapped automatically. The remaining codes were mapped using a combination of semi-automated string comparison with expert selection, and a completely manual approach. Compound drugs were especially difficult to map: only 7.5% could be mapped using the automatic method. General challenges to mapping across terminological systems include (1) the availability of up-to-date information to assess the suitability of a given terminological system for a particular use case, and to assess the quality and completeness of cross-terminology links; (2) the difficulty of correctly using complex, rapidly evolving, modern terminologies; (3) the time and effort required to complete and evaluate the mapping; (4) the need to address differences in granularity between the source and target terminologies; and (5) the need to continuously update the mapping as terminological systems evolve. Copyright © 2012 Elsevier Inc. All rights reserved.

Cross-terminology mapping challenges: A demonstration using medication terminological systems

PubMed Central

Saitwal, Himali; Qing, David; Jones, Stephen; Bernstam, Elmer; Chute, Christopher G.; Johnson, Todd R.

2015-01-01

Standardized terminological systems for biomedical information have provided considerable benefits to biomedical applications and research. However, practical use of this information often requires mapping across terminological systems—a complex and time-consuming process. This paper demonstrates the complexity and challenges of mapping across terminological systems in the context of medication information. It provides a review of medication terminological systems and their linkages, then describes a case study in which we mapped proprietary medication codes from an electronic health record to SNOMED-CT and the UMLS Metathesaurus. The goal was to create a polyhierarchical classification system for querying an i2b2 clinical data warehouse. We found that three methods were required to accurately map the majority of actively prescribed medications. Only 62.5% of source medication codes could be mapped automatically. The remaining codes were mapped using a combination of semi-automated string comparison with expert selection, and a completely manual approach. Compound drugs were especially difficult to map: only 7.5% could be mapped using the automatic method. General challenges to mapping across terminological systems include (1) the availability of up-to-date information to assess the suitability of a given terminological system for a particular use case, and to assess the quality and completeness of cross-terminology links; (2) the difficulty of correctly using complex, rapidly evolving, modern terminologies; (3) the time and effort required to complete and evaluate the mapping; (4) the need to address differences in granularity between the source and target terminologies; and (5) the need to continuously update the mapping as terminological systems evolve. PMID:22750536

Mapping gullies, dunes, lava fields, and landslides via surface roughness

NASA Astrophysics Data System (ADS)

Korzeniowska, Karolina; Pfeifer, Norbert; Landtwing, Stephan

2018-01-01

Gully erosion is a widespread and significant process involved in soil and land degradation. Mapping gullies helps to quantify past, and anticipate future, soil losses. Digital terrain models offer promising data for automatically detecting and mapping gullies especially in vegetated areas, although methods vary widely measures of local terrain roughness are the most varied and debated among these methods. Rarely do studies test the performance of roughness metrics for mapping gullies, limiting their applicability to small training areas. To this end, we systematically explored how local terrain roughness derived from high-resolution Light Detection And Ranging (LiDAR) data can aid in the unsupervised detection of gullies over a large area. We also tested expanding this method for other landforms diagnostic of similarly abrupt land-surface changes, including lava fields, dunes, and landslides, as well as investigating the influence of different roughness thresholds, resolutions of kernels, and input data resolution, and comparing our method with previously published roughness algorithms. Our results show that total curvature is a suitable metric for recognising analysed gullies and lava fields from LiDAR data, with comparable success to that of more sophisticated roughness metrics. Tested dunes or landslides remain difficult to distinguish from the surrounding landscape, partly because they are not easily defined in terms of their topographic signature.

Cortical surface registration using spherical thin-plate spline with sulcal lines and mean curvature as features.

PubMed

Park, Hyunjin; Park, Jun-Sung; Seong, Joon-Kyung; Na, Duk L; Lee, Jong-Min

2012-04-30

Analysis of cortical patterns requires accurate cortical surface registration. Many researchers map the cortical surface onto a unit sphere and perform registration of two images defined on the unit sphere. Here we have developed a novel registration framework for the cortical surface based on spherical thin-plate splines. Small-scale composition of spherical thin-plate splines was used as the geometric interpolant to avoid folding in the geometric transform. Using an automatic algorithm based on anisotropic skeletons, we extracted seven sulcal lines, which we then incorporated as landmark information. Mean curvature was chosen as an additional feature for matching between spherical maps. We employed a two-term cost function to encourage matching of both sulcal lines and the mean curvature between the spherical maps. Application of our registration framework to fifty pairwise registrations of T1-weighted MRI scans resulted in improved registration accuracy, which was computed from sulcal lines. Our registration approach was tested as an additional procedure to improve an existing surface registration algorithm. Our registration framework maintained an accurate registration over the sulcal lines while significantly increasing the cross-correlation of mean curvature between the spherical maps being registered. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2013-05-01

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

Collaboration spotting for dental science.

PubMed

Leonardi, E; Agocs, A; Fragkiskos, S; Kasfikis, N; Le Goff, J M; Cristalli, M P; Luzzi, V; Polimeni, A

2014-10-06

The goal of the Collaboration Spotting project is to create an automatic system to collect information about publications and patents related to a given technology, to identify the key players involved, and to highlight collaborations and related technologies. The collected information can be visualized in a web browser as interactive graphical maps showing in an intuitive way the players and their collaborations (Sociogram) and the relations among the technologies (Technogram). We propose to use the system to study technologies related to Dental Science. In order to create a Sociogram, we create a logical filter based on a set of keywords related to the technology under study. This filter is used to extract a list of publications from the Web of Science™ database. The list is validated by an expert in the technology and sent to CERN where it is inserted in the Collaboration Spotting database. Here, an automatic software system uses the data to generate the final maps. We studied a set of recent technologies related to bone regeneration procedures of oro--maxillo--facial critical size defects, namely the use of Porous HydroxyApatite (HA) as a bone substitute alone (bone graft) or as a tridimensional support (scaffold) for insemination and differentiation ex--vivo of Mesenchymal Stem Cells. We produced the Sociograms for these technologies and the resulting maps are now accessible on--line. The Collaboration Spotting system allows the automatic creation of interactive maps to show the current and historical state of research on a specific technology. These maps are an ideal tool both for researchers who want to assess the state--of--the--art in a given technology, and for research organizations who want to evaluate their contribution to the technological development in a given field. We demonstrated that the system can be used for Dental Science and produced the maps for an initial set of technologies in this field. We now plan to enlarge the set of mapped technologies in order to make the Collaboration Spotting system a useful reference tool for Dental Science research.

Collaboration Spotting for oral medicine.

PubMed

Leonardi, E; Agocs, A; Fragkiskos, S; Kasfikis, N; Le Goff, J M; Cristalli, M P; Luzzi, V; Polimeni, A

2014-09-01

The goal of the Collaboration Spotting project is to create an automatic system to collect information about publications and patents related to a given technology, to identify the key players involved, and to highlight collaborations and related technologies. The collected information can be visualized in a web browser as interactive graphical maps showing in an intuitive way the players and their collaborations (Sociogram) and the relations among the technologies (Technogram). We propose to use the system to study technologies related to oral medicine. In order to create a sociogram, we create a logical filter based on a set of keywords related to the technology under study. This filter is used to extract a list of publications from the Web of Science™ database. The list is validated by an expert in the technology and sent to CERN where it is inserted in the Collaboration Spotting database. Here, an automatic software system uses the data to generate the final maps. We studied a set of recent technologies related to bone regeneration procedures of oro-maxillo-facial critical size defects, namely the use of porous hydroxyapatite (HA) as a bone substitute alone (bone graft) or as a tridimensional support (scaffold) for insemination and differentiation ex vivo of mesenchymal stem cells. We produced the sociograms for these technologies and the resulting maps are now accessible on-line. The Collaboration Spotting system allows the automatic creation of interactive maps to show the current and historical state of research on a specific technology. These maps are an ideal tool both for researchers who want to assess the state-of-the-art in a given technology, and for research organizations who want to evaluate their contribution to the technological development in a given field. We demonstrated that the system can be used in oral medicine as is produced the maps for an initial set of technologies in this field. We now plan to enlarge the set of mapped technologies in order to make the Collaboration Spotting system a useful reference tool for oral medicine research.

Semantic similarity-based alignment between clinical archetypes and SNOMED CT: an application to observations.

PubMed

Meizoso García, María; Iglesias Allones, José Luis; Martínez Hernández, Diego; Taboada Iglesias, María Jesús

2012-08-01

One of the main challenges of eHealth is semantic interoperability of health systems. But, this will only be possible if the capture, representation and access of patient data is standardized. Clinical data models, such as OpenEHR Archetypes, define data structures that are agreed by experts to ensure the accuracy of health information. In addition, they provide an option to normalize clinical data by means of binding terms used in the model definition to standard medical vocabularies. Nevertheless, the effort needed to establish the association between archetype terms and standard terminology concepts is considerable. Therefore, the purpose of this study is to provide an automated approach to bind OpenEHR archetypes terms to the external terminology SNOMED CT, with the capability to do it at a semantic level. This research uses lexical techniques and external terminological tools in combination with context-based techniques, which use information about structural and semantic proximity to identify similarities between terms and so, to find alignments between them. The proposed approach exploits both the structural context of archetypes and the terminology context, in which concepts are logically defined through the relationships (hierarchical and definitional) to other concepts. A set of 25 OBSERVATION archetypes with 477 bound terms was used to test the method. Of these, 342 terms (74.6%) were linked with 96.1% precision, 71.7% recall and 1.23 SNOMED CT concepts on average for each mapping. It has been detected that about one third of the archetype clinical information is grouped logically. Context-based techniques take advantage of this to increase the recall and to validate a 30.4% of the bindings produced by lexical techniques. This research shows that it is possible to automatically map archetype terms to a standard terminology with a high precision and recall, with the help of appropriate contextual and semantic information of both models. Moreover, the semantic-based methods provide a means of validating and disambiguating the resulting bindings. Therefore, this work is a step forward to reduce the human participation in the mapping process. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Automatic segmentation of multimodal brain tumor images based on classification of super-voxels.

PubMed

Kadkhodaei, M; Samavi, S; Karimi, N; Mohaghegh, H; Soroushmehr, S M R; Ward, K; All, A; Najarian, K

2016-08-01

Despite the rapid growth in brain tumor segmentation approaches, there are still many challenges in this field. Automatic segmentation of brain images has a critical role in decreasing the burden of manual labeling and increasing robustness of brain tumor diagnosis. We consider segmentation of glioma tumors, which have a wide variation in size, shape and appearance properties. In this paper images are enhanced and normalized to same scale in a preprocessing step. The enhanced images are then segmented based on their intensities using 3D super-voxels. Usually in images a tumor region can be regarded as a salient object. Inspired by this observation, we propose a new feature which uses a saliency detection algorithm. An edge-aware filtering technique is employed to align edges of the original image to the saliency map which enhances the boundaries of the tumor. Then, for classification of tumors in brain images, a set of robust texture features are extracted from super-voxels. Experimental results indicate that our proposed method outperforms a comparable state-of-the-art algorithm in term of dice score.

Global spectral UV-radiometer with automatic shadow band.

PubMed

Rosales, Alejandro; Pedroni, Jorge V; Tocho, Jorge O

2006-01-01

A solar radiometer (GUV-511 C, Biospherical Instruments Inc., San Diego, CA) with four UV channels has been operating at Trelew (43.2 degrees S, 65.3 degrees W), Argentina, since the austral spring of 1997. The instrument provides global (direct + diffuse) irradiance on the horizontal plane year-round, with a 1 min period. On 1 January 1999, an automatic shadow band was added to calculate diffuse and direct radiation. The period of the measurements was increased to 2 min to keep the same signal to noise (S:N) ratio. Once the direct radiation values were available for the 305 nm and 320 nm spectral bands, the total ozone value was calculated and results were compared with data provided by the U.S. National Aeronautics and Space Administration for the Total Ozone Mapping Spectrometer (TOMS) on the Earth Probe satellite. Results show a root-mean-square (RMS) deviation within 4% compared with that of TOMS, so the quality of results is considered to be quite good. The importance of regular calibration to maintain long-term accuracy is stressed.

Oil Spill Disasters Detection and Monitoring by RST Analysis of Optical Satellite Radiances: the Case of Deepwater Horizon Platform in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Pergola, N.; Grimaldi, S. C.; Coviello, I.; Faruolo, M.; Lacava, T.; Tramutoli, V.

2010-12-01

Marine oil spill disasters may have devastating effects on the marine and coastal environment. For monitoring and mitigation purposes, timely detection and continuously updated information on polluted areas are required. Satellite remote sensing can give a significant contribution in such a direction. Nowadays, SAR (Synthetic Aperture Radar) technology has been recognized as the most efficient for oil spill detection and mapping, thanks to the high spatial resolution and all-time/all-weather capability of the present operational sensors. Anyway, the present SARs revisiting time does not allow for a rapid detection and a near real-time monitoring of these phenomena at global scale. Passive optical sensors, on board meteorological satellites, thanks to their high temporal resolution (from a few hours to 15 minutes, depending on the characteristics of the platform/sensor), may represent, at this moment, a suitable SAR alternative/complement for oil spill detection and monitoring. Up to now, some techniques, based on optical satellite data, have been proposed for “a posteriori” mapping of already known oil spill discharges. On the other hand, reliable satellite methods for an automatic and timely detection of oil spills, for surveillance and warning purposes, are still currently missing. Recently, an innovative technique for automatic and near real time oil spill detection and monitoring has been proposed. The technique is based on the general RST (Robust Satellite Technique) approach which exploits multi-temporal satellite records in order to obtain a former characterization of the measured signal, in terms of expected value and natural variability, providing a further identification of signal anomalies by an automatic, unsupervised change detection step. Results obtained by using AVHRR (Advanced Very High Resolution Radiometer) Thermal Infrared data, in different geographic areas and observational conditions, demonstrated excellent detection capabilities both in term of sensitivity (to the presence even of thin/old oil films) and reliability (up to zero occurrence of false alarms), mainly due to the RST invariance regardless of local and environmental conditions. Exploiting its complete independence on the specific satellite platform, RST approach has been successfully exported to the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites. In this paper, results obtained applying the proposed methodology to the recent oil spill disaster of Deepwater Horizon Platform in the gulf of Mexico, that discharged over 5 million barrels (550 million litres) in the ocean, will be shown. A dense temporal series of RST-based oil spill maps, obtained by using MODIS TIR records, are commented, emphasizing and discussing main peculiarities and specific characteristics of this event. Preliminary findings, possible residual limits and future perspectives will be also presented and discussed.

Research on the Intensity Analysis and Result Visualization of Construction Land in Urban Planning

NASA Astrophysics Data System (ADS)

Cui, J.; Dong, B.; Li, J.; Li, L.

2017-09-01

As a fundamental work of urban planning, the intensity analysis of construction land involves many repetitive data processing works that are prone to cause errors or data precision loss, and the lack of efficient methods and tools to visualizing the analysis results in current urban planning. In the research a portable tool is developed by using the Model Builder technique embedded in ArcGIS to provide automatic data processing and rapid result visualization for the works. A series of basic modules provided by ArcGIS are linked together to shape a whole data processing chain in the tool. Once the required data is imported, the analysis results and related maps and graphs including the intensity values and zoning map, the skyline analysis map etc. are produced automatically. Finally the tool is installation-free and can be dispatched quickly between planning teams.

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

NASA Technical Reports Server (NTRS)

Messmore, J.; Copeland, G. E.; Levy, G. F.

1975-01-01

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95%), and progress is being made towards identifying the mapped spectral classes.

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

NASA Technical Reports Server (NTRS)

Messmore, J.; Copeland, G. E.; Levy, G. F.

1975-01-01

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95 percent), and progress is being made towards identifying the mapped spectral classes.

EXIF Custom: Automatic image metadata extraction for Scratchpads and Drupal.

PubMed

Baker, Ed

2013-01-01

Many institutions and individuals use embedded metadata to aid in the management of their image collections. Many deskop image management solutions such as Adobe Bridge and online tools such as Flickr also make use of embedded metadata to describe, categorise and license images. Until now Scratchpads (a data management system and virtual research environment for biodiversity) have not made use of these metadata, and users have had to manually re-enter this information if they have wanted to display it on their Scratchpad site. The Drupal described here allows users to map metadata embedded in their images to the associated field in the Scratchpads image form using one or more customised mappings. The module works seamlessly with the bulk image uploader used on Scratchpads and it is therefore possible to upload hundreds of images easily with automatic metadata (EXIF, XMP and IPTC) extraction and mapping.

The NavTrax fleet management system

NASA Astrophysics Data System (ADS)

McLellan, James F.; Krakiwsky, Edward J.; Schleppe, John B.; Knapp, Paul L.

The NavTrax System, a dispatch-type automatic vehicle location and navigation system, is discussed. Attention is given to its positioning, communication, digital mapping, and dispatch center components. The positioning module is a robust GPS (Global Positioning System)-based system integrated with dead reckoning devices by a decentralized-federated filter, making the module fault tolerant. The error behavior and characteristics of GPS, rate gyro, compass, and odometer sensors are discussed. The communications module, as presently configured, utilizes UHF radio technology, and plans are being made to employ a digital cellular telephone system. Polling and automatic smart vehicle reporting are also discussed. The digital mapping component is an intelligent digital single line road network database stored in vector form with full connectivity and address ranges. A limited form of map matching is performed for the purposes of positioning, but its main purpose is to define location once position is determined.

Edge map analysis in chest X-rays for automatic pulmonary abnormality screening.

PubMed

Santosh, K C; Vajda, Szilárd; Antani, Sameer; Thoma, George R

2016-09-01

Our particular motivator is the need for screening HIV+ populations in resource-constrained regions for the evidence of tuberculosis, using posteroanterior chest radiographs (CXRs). The proposed method is motivated by the observation that abnormal CXRs tend to exhibit corrupted and/or deformed thoracic edge maps. We study histograms of thoracic edges for all possible orientations of gradients in the range [Formula: see text] at different numbers of bins and different pyramid levels, using five different regions-of-interest selection. We have used two CXR benchmark collections made available by the U.S. National Library of Medicine and have achieved a maximum abnormality detection accuracy (ACC) of 86.36 % and area under the ROC curve (AUC) of 0.93 at 1 s per image, on average. We have presented an automatic method for screening pulmonary abnormalities using thoracic edge map in CXR images. The proposed method outperforms previously reported state-of-the-art results.

EXIF Custom: Automatic image metadata extraction for Scratchpads and Drupal

PubMed Central

2013-01-01

Abstract Many institutions and individuals use embedded metadata to aid in the management of their image collections. Many deskop image management solutions such as Adobe Bridge and online tools such as Flickr also make use of embedded metadata to describe, categorise and license images. Until now Scratchpads (a data management system and virtual research environment for biodiversity) have not made use of these metadata, and users have had to manually re-enter this information if they have wanted to display it on their Scratchpad site. The Drupal described here allows users to map metadata embedded in their images to the associated field in the Scratchpads image form using one or more customised mappings. The module works seamlessly with the bulk image uploader used on Scratchpads and it is therefore possible to upload hundreds of images easily with automatic metadata (EXIF, XMP and IPTC) extraction and mapping. PMID:24723768

Automatic face recognition in HDR imaging

NASA Astrophysics Data System (ADS)

Pereira, Manuela; Moreno, Juan-Carlos; Proença, Hugo; Pinheiro, António M. G.

2014-05-01

The gaining popularity of the new High Dynamic Range (HDR) imaging systems is raising new privacy issues caused by the methods used for visualization. HDR images require tone mapping methods for an appropriate visualization on conventional and non-expensive LDR displays. These visualization methods might result in completely different visualization raising several issues on privacy intrusion. In fact, some visualization methods result in a perceptual recognition of the individuals, while others do not even show any identity. Although perceptual recognition might be possible, a natural question that can rise is how computer based recognition will perform using tone mapping generated images? In this paper, a study where automatic face recognition using sparse representation is tested with images that result from common tone mapping operators applied to HDR images. Its ability for the face identity recognition is described. Furthermore, typical LDR images are used for the face recognition training.

Automatic Term Class Construction Using Relevance--A Summary of Work in Automatic Pseudoclassification.

ERIC Educational Resources Information Center

Salton, G.

1980-01-01

Summarizes studies of pseudoclassification, a process of utilizing user relevance assessments of certain documents with respect to certain queries to build term classes designed to retrieve relevant documents. Conclusions are reached concerning the effectiveness and feasibility of constructing term classifications based on human relevance…

Chocolate equals stop. Chocolate-specific inhibition training reduces chocolate intake and go associations with chocolate.

PubMed

Houben, Katrijn; Jansen, Anita

2015-04-01

Earlier research has demonstrated that food-specific inhibition training wherein food cues are repeatedly and consistently mapped onto stop signals decreases food intake and bodyweight. The mechanisms underlying these training effects, however, remain unclear. It has been suggested that consistently pairing stimuli with stop signals induces automatic stop associations with those stimuli, thereby facilitating automatic, bottom-up inhibition. This study examined this hypothesis with respect to food-inhibition training. Participants performed a training that consistently paired chocolate with no go cues (chocolate/no-go) or with go cues (chocolate/go). Following training, we measured automatic associations between chocolate and stop versus go, as well as food intake and desire to eat. As expected, food that was consistently mapped onto stopping was indeed more associated with stopping versus going afterwards. In replication of previous results, participants in the no-go condition also showed less desire to eat and reduced food intake relative to the go condition. Together these findings support the idea that food-specific inhibition training prompts the development of automatic inhibition associations, which subsequently facilitate inhibitory control over unwanted food-related urges. Copyright © 2015 Elsevier Ltd. All rights reserved.

Recognition of surface lithologic and topographic patterns in southwest Colorado with ADP techniques

NASA Technical Reports Server (NTRS)

Melhorn, W. N.; Sinnock, S.

1973-01-01

Analysis of ERTS-1 multispectral data by automatic pattern recognition procedures is applicable toward grappling with current and future resource stresses by providing a means for refining existing geologic maps. The procedures used in the current analysis already yield encouraging results toward the eventual machine recognition of extensive surface lithologic and topographic patterns. Automatic mapping of a series of hogbacks, strike valleys, and alluvial surfaces along the northwest flank of the San Juan Basin in Colorado can be obtained by minimal man-machine interaction. The determination of causes for separable spectral signatures is dependent upon extensive correlation of micro- and macro field based ground truth observations and aircraft underflight data with the satellite data.

Automatic Generation of Building Models with Levels of Detail 1-3

NASA Astrophysics Data System (ADS)

Nguatem, W.; Drauschke, M.; Mayer, H.

2016-06-01

We present a workflow for the automatic generation of building models with levels of detail (LOD) 1 to 3 according to the CityGML standard (Gröger et al., 2012). We start with orienting unsorted image sets employing (Mayer et al., 2012), we compute depth maps using semi-global matching (SGM) (Hirschmüller, 2008), and fuse these depth maps to reconstruct dense 3D point clouds (Kuhn et al., 2014). Based on planes segmented from these point clouds, we have developed a stochastic method for roof model selection (Nguatem et al., 2013) and window model selection (Nguatem et al., 2014). We demonstrate our workflow up to the export into CityGML.

Towards an Automatic Framework for Urban Settlement Mapping from Satellite Images: Applications of Geo-referenced Social Media and One Class Classification

NASA Astrophysics Data System (ADS)

Miao, Zelang

2017-04-01

Currently, urban dwellers comprise more than half of the world's population and this percentage is still dramatically increasing. The explosive urban growth over the next two decades poses long-term profound impact on people as well as the environment. Accurate and up-to-date delineation of urban settlements plays a fundamental role in defining planning strategies and in supporting sustainable development of urban settlements. In order to provide adequate data about urban extents and land covers, classifying satellite data has become a common practice, usually with accurate enough results. Indeed, a number of supervised learning methods have proven effective in urban area classification, but they usually depend on a large amount of training samples, whose collection is a time and labor expensive task. This issue becomes particularly serious when classifying large areas at the regional/global level. As an alternative to manual ground truth collection, in this work we use geo-referenced social media data. Cities and densely populated areas are an extremely fertile land for the production of individual geo-referenced data (such as GPS and social network data). Training samples derived from geo-referenced social media have several advantages: they are easy to collect, usually they are freely exploitable; and, finally, data from social media are spatially available in many locations, and with no doubt in most urban areas around the world. Despite these advantages, the selection of training samples from social media meets two challenges: 1) there are many duplicated points; 2) method is required to automatically label them as "urban/non-urban". The objective of this research is to validate automatic sample selection from geo-referenced social media and its applicability in one class classification for urban extent mapping from satellite images. The findings in this study shed new light on social media applications in the field of remote sensing.

Modeling shape and topology of low-resolution density maps of biological macromolecules.

PubMed Central

De-Alarcón, Pedro A; Pascual-Montano, Alberto; Gupta, Amarnath; Carazo, Jose M

2002-01-01

In the present work we develop an efficient way of representing the geometry and topology of volumetric datasets of biological structures from medium to low resolution, aiming at storing and querying them in a database framework. We make use of a new vector quantization algorithm to select the points within the macromolecule that best approximate the probability density function of the original volume data. Connectivity among points is obtained with the use of the alpha shapes theory. This novel data representation has a number of interesting characteristics, such as 1) it allows us to automatically segment and quantify a number of important structural features from low-resolution maps, such as cavities and channels, opening the possibility of querying large collections of maps on the basis of these quantitative structural features; 2) it provides a compact representation in terms of size; 3) it contains a subset of three-dimensional points that optimally quantify the densities of medium resolution data; and 4) a general model of the geometry and topology of the macromolecule (as opposite to a spatially unrelated bunch of voxels) is easily obtained by the use of the alpha shapes theory. PMID:12124252

The prepared emotional reflex: intentional preparation of automatic approach and avoidance tendencies as a means to regulate emotional responding.

PubMed

Eder, Andreas B; Rothermund, Klaus; Proctor, Robert W

2010-08-01

Advance preparation of action courses toward emotional stimuli is an effective means to regulate impulsive emotional behavior. Our experiment shows that performing intentional acts of approach and avoidance in an evaluation task influences the unintended activation of approach and avoidance tendencies in another task in which stimulus valence is irrelevant. For the evaluation-relevant blocks, participants received either congruent (positive-approach, negative-avoidance) or incongruent (positive-avoidance, negative-approach) mapping instructions. In the evaluation-irrelevant blocks, approach- and avoidance-related lever movements were selected in response to a stimulus feature other than valence (affective Simon task). Response mapping in the evaluation task influenced performance in the evaluation-irrelevant task: An enhanced affective Simon effect was observed with congruent mapping instructions; in contrast, the effect was reversed when the evaluation task required incongruent responses. Thus, action instructions toward affective stimuli received in one task determined affective response tendencies in another task where these instructions were not in effect. These findings suggest that intentionally prepared short-term links between affective valence and motor responses elicit associated responses without a deliberate act of will, operating like a "prepared reflex." Copyright 2010 APA

Automated Deployment of Advanced Controls and Analytics in Buildings

NASA Astrophysics Data System (ADS)

Pritoni, Marco

Buildings use 40% of primary energy in the US. Recent studies show that developing energy analytics and enhancing control strategies can significantly improve their energy performance. However, the deployment of advanced control software applications has been mostly limited to academic studies. Larger-scale implementations are prevented by the significant engineering time and customization required, due to significant differences among buildings. This study demonstrates how physics-inspired data-driven models can be used to develop portable analytics and control applications for buildings. Specifically, I demonstrate application of these models in all phases of the deployment of advanced controls and analytics in buildings: in the first phase, "Site Preparation and Interface with Legacy Systems" I used models to discover or map relationships among building components, automatically gathering metadata (information about data points) necessary to run the applications. During the second phase: "Application Deployment and Commissioning", models automatically learn system parameters, used for advanced controls and analytics. In the third phase: "Continuous Monitoring and Verification" I utilized models to automatically measure the energy performance of a building that has implemented advanced control strategies. In the conclusions, I discuss future challenges and suggest potential strategies for these innovative control systems to be widely deployed in the market. This dissertation provides useful new tools in terms of procedures, algorithms, and models to facilitate the automation of deployment of advanced controls and analytics and accelerate their wide adoption in buildings.

Distributed and Collaborative Software Analysis

NASA Astrophysics Data System (ADS)

Ghezzi, Giacomo; Gall, Harald C.

Throughout the years software engineers have come up with a myriad of specialized tools and techniques that focus on a certain type of software analysissoftware analysis such as source code analysis, co-change analysis or bug prediction. However, easy and straight forward synergies between these analyses and tools rarely exist because of their stand-alone nature, their platform dependence, their different input and output formats and the variety of data to analyze. As a consequence, distributed and collaborative software analysiscollaborative software analysis scenarios and in particular interoperability are severely limited. We describe a distributed and collaborative software analysis platform that allows for a seamless interoperability of software analysis tools across platform, geographical and organizational boundaries. We realize software analysis tools as services that can be accessed and composed over the Internet. These distributed analysis services shall be widely accessible in our incrementally augmented Software Analysis Broker software analysis broker where organizations and tool providers can register and share their tools. To allow (semi-) automatic use and composition of these tools, they are classified and mapped into a software analysis taxonomy and adhere to specific meta-models and ontologiesontologies for their category of analysis.

Automated Glacier Mapping using Object Based Image Analysis. Case Studies from Nepal, the European Alps and Norway

NASA Astrophysics Data System (ADS)

Vatle, S. S.

2015-12-01

Frequent and up-to-date glacier outlines are needed for many applications of glaciology, not only glacier area change analysis, but also for masks in volume or velocity analysis, for the estimation of water resources and as model input data. Remote sensing offers a good option for creating glacier outlines over large areas, but manual correction is frequently necessary, especially in areas containing supraglacial debris. We show three different workflows for mapping clean ice and debris-covered ice within Object Based Image Analysis (OBIA). By working at the object level as opposed to the pixel level, OBIA facilitates using contextual, spatial and hierarchical information when assigning classes, and additionally permits the handling of multiple data sources. Our first example shows mapping debris-covered ice in the Manaslu Himalaya, Nepal. SAR Coherence data is used in combination with optical and topographic data to classify debris-covered ice, obtaining an accuracy of 91%. Our second example shows using a high-resolution LiDAR derived DEM over the Hohe Tauern National Park in Austria. Breaks in surface morphology are used in creating image objects; debris-covered ice is then classified using a combination of spectral, thermal and topographic properties. Lastly, we show a completely automated workflow for mapping glacier ice in Norway. The NDSI and NIR/SWIR band ratio are used to map clean ice over the entire country but the thresholds are calculated automatically based on a histogram of each image subset. This means that in theory any Landsat scene can be inputted and the clean ice can be automatically extracted. Debris-covered ice can be included semi-automatically using contextual and morphological information.

Automatic Generation of Cycle-Approximate TLMs with Timed RTOS Model Support

NASA Astrophysics Data System (ADS)

Hwang, Yonghyun; Schirner, Gunar; Abdi, Samar

This paper presents a technique for automatically generating cycle-approximate transaction level models (TLMs) for multi-process applications mapped to embedded platforms. It incorporates three key features: (a) basic block level timing annotation, (b) RTOS model integration, and (c) RTOS overhead delay modeling. The inputs to TLM generation are application C processes and their mapping to processors in the platform. A processor data model, including pipelined datapath, memory hierarchy and branch delay model is used to estimate basic block execution delays. The delays are annotated to the C code, which is then integrated with a generated SystemC RTOS model. Our abstract RTOS provides dynamic scheduling and inter-process communication (IPC) with processor- and RTOS-specific pre-characterized timing. Our experiments using a MP3 decoder and a JPEG encoder show that timed TLMs, with integrated RTOS models, can be automatically generated in less than a minute. Our generated TLMs simulated three times faster than real-time and showed less than 10% timing error compared to board measurements.

Beyond left and right: Automaticity and flexibility of number-space associations.

PubMed

Antoine, Sophie; Gevers, Wim

2016-02-01

Close links exist between the processing of numbers and the processing of space: relatively small numbers are preferentially associated with a left-sided response while relatively large numbers are associated with a right-sided response (the SNARC effect). Previous work demonstrated that the SNARC effect is triggered in an automatic manner and is highly flexible. Besides the left-right dimension, numbers associate with other spatial response mappings such as close/far responses, where small numbers are associated with a close response and large numbers with a far response. In two experiments we investigate the nature of this association. Associations between magnitude and close/far responses were observed using a magnitude-irrelevant task (Experiment 1: automaticity) and using a variable referent task (Experiment 2: flexibility). While drawing a strong parallel between both response mappings, the present results are also informative with regard to the question about what type of processing mechanism underlies both the SNARC effect and the association between numerical magnitude and close/far response locations.

Mapping landslide source and transport areas in VHR images with Object-Based Analysis and Support Vector Machines

NASA Astrophysics Data System (ADS)

Heleno, Sandra; Matias, Magda; Pina, Pedro

2015-04-01

Visual interpretation of satellite imagery remains extremely demanding in terms of resources and time, especially when dealing with numerous multi-scale landslides affecting wide areas, such as is the case of rainfall-induced shallow landslides. Applying automated methods can contribute to more efficient landslide mapping and updating of existing inventories, and in recent years the number and variety of approaches is rapidly increasing. Very High Resolution (VHR) images, acquired by space-borne sensors with sub-metric precision, such as Ikonos, Quickbird, Geoeye and Worldview, are increasingly being considered as the best option for landslide mapping, but these new levels of spatial detail also present new challenges to state of the art image analysis tools, asking for automated methods specifically suited to map landslide events on VHR optical images. In this work we develop and test a methodology for semi-automatic landslide recognition and mapping of landslide source and transport areas. The method combines object-based image analysis and a Support Vector Machine supervised learning algorithm, and was tested using a GeoEye-1 multispectral image, sensed 3 days after a damaging landslide event in Madeira Island, together with a pre-event LiDAR DEM. Our approach has proved successful in the recognition of landslides on a 15 Km2-wide study area, with 81 out of 85 landslides detected in its validation regions. The classifier also showed reasonable performance (false positive rate 60% and false positive rate below 36% in both validation regions) in the internal mapping of landslide source and transport areas, in particular in the sunnier east-facing slopes. In the less illuminated areas the classifier is still able to accurately map the source areas, but performs poorly in the mapping of landslide transport areas.

Exploration of Web Users' Search Interests through Automatic Subject Categorization of Query Terms.

ERIC Educational Resources Information Center

Pu, Hsiao-tieh; Yang, Chyan; Chuang, Shui-Lung

2001-01-01

Proposes a mechanism that carefully integrates human and machine efforts to explore Web users' search interests. The approach consists of a four-step process: extraction of core terms; construction of subject taxonomy; automatic subject categorization of query terms; and observation of users' search interests. Research findings are proved valuable…

Automatic and robust extrinsic camera calibration for high-accuracy mobile mapping

NASA Astrophysics Data System (ADS)

Goeman, Werner; Douterloigne, Koen; Bogaert, Peter; Pires, Rui; Gautama, Sidharta

2012-10-01

A mobile mapping system (MMS) is the answer of the geoinformation community to the exponentially growing demand for various geospatial data with increasingly higher accuracies and captured by multiple sensors. As the mobile mapping technology is pushed to explore its use for various applications on water, rail, or road, the need emerges to have an external sensor calibration procedure which is portable, fast and easy to perform. This way, sensors can be mounted and demounted depending on the application requirements without the need for time consuming calibration procedures. A new methodology is presented to provide a high quality external calibration of cameras which is automatic, robust and fool proof.The MMS uses an Applanix POSLV420, which is a tightly coupled GPS/INS positioning system. The cameras used are Point Grey color video cameras synchronized with the GPS/INS system. The method uses a portable, standard ranging pole which needs to be positioned on a known ground control point. For calibration a well studied absolute orientation problem needs to be solved. Here, a mutual information based image registration technique is studied for automatic alignment of the ranging pole. Finally, a few benchmarking tests are done under various lighting conditions which proves the methodology's robustness, by showing high absolute stereo measurement accuracies of a few centimeters.

Perfusion CT in acute stroke: effectiveness of automatically-generated colour maps.

PubMed

Ukmar, Maja; Degrassi, Ferruccio; Pozzi Mucelli, Roberta Antea; Neri, Francesca; Mucelli, Fabio Pozzi; Cova, Maria Assunta

2017-04-01

To evaluate the accuracy of perfusion CT (pCT) in the definition of the infarcted core and the penumbra, comparing the data obtained from the evaluation of parametric maps [cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT)] with software-generated colour maps. A retrospective analysis was performed to identify patients with suspected acute ischaemic strokes and who had undergone unenhanced CT and pCT carried out within 4.5 h from the onset of the symptoms. A qualitative evaluation of the CBV, CBF and MTT maps was performed, followed by an analysis of the colour maps automatically generated by the software. 26 patients were identified, but a direct CT follow-up was performed only on 19 patients after 24-48 h. In the qualitative analysis, 14 patients showed perfusion abnormalities. Specifically, 29 perfusion deficit areas were detected, of which 15 areas suggested the penumbra and the remaining 14 areas suggested the infarct. As for automatically software-generated maps, 12 patients showed perfusion abnormalities. 25 perfusion deficit areas were identified, 15 areas of which suggested the penumbra and the other 10 areas the infarct. The McNemar's test showed no statistically significant difference between the two methods of evaluation in highlighting infarcted areas proved later at CT follow-up. We demonstrated how pCT provides good diagnostic accuracy in the identification of acute ischaemic lesions. The limits of identification of the lesions mainly lie at the pons level and in the basal ganglia area. Qualitative analysis has proven to be more efficient in identification of perfusion lesions in comparison with software-generated maps. However, software-generated maps have proven to be very useful in the emergency setting. Advances in knowledge: The use of CT perfusion is requested in increasingly more patients in order to optimize the treatment, thanks also to the technological evolution of CT, which now allows a whole-brain study. The need for performing CT perfusion study also in the emergency setting could represent a problem for physicians who are not used to interpreting the parametric maps (CBV, MTT etc.). The software-generated maps could be of value in these settings, helping the less expert physician in the differentiation between different areas.

Automatic query formulations in information retrieval.

PubMed

Salton, G; Buckley, C; Fox, E A

1983-07-01

Modern information retrieval systems are designed to supply relevant information in response to requests received from the user population. In most retrieval environments the search requests consist of keywords, or index terms, interrelated by appropriate Boolean operators. Since it is difficult for untrained users to generate effective Boolean search requests, trained search intermediaries are normally used to translate original statements of user need into useful Boolean search formulations. Methods are introduced in this study which reduce the role of the search intermediaries by making it possible to generate Boolean search formulations completely automatically from natural language statements provided by the system patrons. Frequency considerations are used automatically to generate appropriate term combinations as well as Boolean connectives relating the terms. Methods are covered to produce automatic query formulations both in a standard Boolean logic system, as well as in an extended Boolean system in which the strict interpretation of the connectives is relaxed. Experimental results are supplied to evaluate the effectiveness of the automatic query formulation process, and methods are described for applying the automatic query formulation process in practice.

Automatic Rock Detection and Mapping from HiRISE Imagery

NASA Technical Reports Server (NTRS)

Huertas, Andres; Adams, Douglas S.; Cheng, Yang

2008-01-01

This system includes a C-code software program and a set of MATLAB software tools for statistical analysis and rock distribution mapping. The major functions include rock detection and rock detection validation. The rock detection code has been evolved into a production tool that can be used by engineers and geologists with minor training.

Automatic Aircraft Collision Avoidance System and Method

NASA Technical Reports Server (NTRS)

Skoog, Mark (Inventor); Hook, Loyd (Inventor); McWherter, Shaun (Inventor); Willhite, Jaimie (Inventor)

2014-01-01

The invention is a system and method of compressing a DTM to be used in an Auto-GCAS system using a semi-regular geometric compression algorithm. In general, the invention operates by first selecting the boundaries of the three dimensional map to be compressed and dividing the three dimensional map data into regular areas. Next, a type of free-edged, flat geometric surface is selected which will be used to approximate terrain data of the three dimensional map data. The flat geometric surface is used to approximate terrain data for each regular area. The approximations are checked to determine if they fall within selected tolerances. If the approximation for a specific regular area is within specified tolerance, the data is saved for that specific regular area. If the approximation for a specific area falls outside the specified tolerances, the regular area is divided and a flat geometric surface approximation is made for each of the divided areas. This process is recursively repeated until all of the regular areas are approximated by flat geometric surfaces. Finally, the compressed three dimensional map data is provided to the automatic ground collision system for an aircraft.

Harvesting geographic features from heterogeneous raster maps

NASA Astrophysics Data System (ADS)

Chiang, Yao-Yi

2010-11-01

Raster maps offer a great deal of geospatial information and are easily accessible compared to other geospatial data. However, harvesting geographic features locked in heterogeneous raster maps to obtain the geospatial information is challenging. This is because of the varying image quality of raster maps (e.g., scanned maps with poor image quality and computer-generated maps with good image quality), the overlapping geographic features in maps, and the typical lack of metadata (e.g., map geocoordinates, map source, and original vector data). Previous work on map processing is typically limited to a specific type of map and often relies on intensive manual work. In contrast, this thesis investigates a general approach that does not rely on any prior knowledge and requires minimal user effort to process heterogeneous raster maps. This approach includes automatic and supervised techniques to process raster maps for separating individual layers of geographic features from the maps and recognizing geographic features in the separated layers (i.e., detecting road intersections, generating and vectorizing road geometry, and recognizing text labels). The automatic technique eliminates user intervention by exploiting common map properties of how road lines and text labels are drawn in raster maps. For example, the road lines are elongated linear objects and the characters are small connected-objects. The supervised technique utilizes labels of road and text areas to handle complex raster maps, or maps with poor image quality, and can process a variety of raster maps with minimal user input. The results show that the general approach can handle raster maps with varying map complexity, color usage, and image quality. By matching extracted road intersections to another geospatial dataset, we can identify the geocoordinates of a raster map and further align the raster map, separated feature layers from the map, and recognized features from the layers with the geospatial dataset. The road vectorization and text recognition results outperform state-of-art commercial products, and with considerably less user input. The approach in this thesis allows us to make use of the geospatial information of heterogeneous maps locked in raster format.

Bibliometric mapping: eight decades of analytical chemistry, with special focus on the use of mass spectrometry.

PubMed

Waaijer, Cathelijn J F; Palmblad, Magnus

2015-01-01

In this Feature we use automatic bibliometric mapping tools to visualize the history of analytical chemistry from the 1920s until the present. In particular, we have focused on the application of mass spectrometry in different fields. The analysis shows major shifts in research focus and use of mass spectrometry. We conclude by discussing the application of bibliometric mapping and visualization tools in analytical chemists' research.

Automatic Indexing Using Term Discrimination and Term Precision Measurements

ERIC Educational Resources Information Center

Salton, G.; And Others

1976-01-01

These two indexing systems are briefly described and experimental evidence is cited showing that a combination of both theories produces better retrieval performance than either one alone. Appropriate conclusions are reached concerning viable automatic indexing procedures usable in practice. (Author)

Evaluation of Apache Hadoop for parallel data analysis with ROOT

NASA Astrophysics Data System (ADS)

Lehrack, S.; Duckeck, G.; Ebke, J.

2014-06-01

The Apache Hadoop software is a Java based framework for distributed processing of large data sets across clusters of computers, using the Hadoop file system (HDFS) for data storage and backup and MapReduce as a processing platform. Hadoop is primarily designed for processing large textual data sets which can be processed in arbitrary chunks, and must be adapted to the use case of processing binary data files which cannot be split automatically. However, Hadoop offers attractive features in terms of fault tolerance, task supervision and control, multi-user functionality and job management. For this reason, we evaluated Apache Hadoop as an alternative approach to PROOF for ROOT data analysis. Two alternatives in distributing analysis data were discussed: either the data was stored in HDFS and processed with MapReduce, or the data was accessed via a standard Grid storage system (dCache Tier-2) and MapReduce was used only as execution back-end. The focus in the measurements were on the one hand to safely store analysis data on HDFS with reasonable data rates and on the other hand to process data fast and reliably with MapReduce. In the evaluation of the HDFS, read/write data rates from local Hadoop cluster have been measured and compared to standard data rates from the local NFS installation. In the evaluation of MapReduce, realistic ROOT analyses have been used and event rates have been compared to PROOF.

Enhancing the Characterization of Epistemic Uncertainties in PM2.5 Risk Analyses.

PubMed

Smith, Anne E; Gans, Will

2015-03-01

The Environmental Benefits Mapping and Analysis Program (BenMAP) is a software tool developed by the U.S. Environmental Protection Agency (EPA) that is widely used inside and outside of EPA to produce quantitative estimates of public health risks from fine particulate matter (PM2.5 ). This article discusses the purpose and appropriate role of a risk analysis tool to support risk management deliberations, and evaluates the functions of BenMAP in this context. It highlights the importance in quantitative risk analyses of characterization of epistemic uncertainty, or outright lack of knowledge, about the true risk relationships being quantified. This article describes and quantitatively illustrates sensitivities of PM2.5 risk estimates to several key forms of epistemic uncertainty that pervade those calculations: the risk coefficient, shape of the risk function, and the relative toxicity of individual PM2.5 constituents. It also summarizes findings from a review of U.S.-based epidemiological evidence regarding the PM2.5 risk coefficient for mortality from long-term exposure. That review shows that the set of risk coefficients embedded in BenMAP substantially understates the range in the literature. We conclude that BenMAP would more usefully fulfill its role as a risk analysis support tool if its functions were extended to better enable and prompt its users to characterize the epistemic uncertainties in their risk calculations. This requires expanded automatic sensitivity analysis functions and more recognition of the full range of uncertainty in risk coefficients. © 2014 Society for Risk Analysis.

Querying XML Data with SPARQL

NASA Astrophysics Data System (ADS)

Bikakis, Nikos; Gioldasis, Nektarios; Tsinaraki, Chrisa; Christodoulakis, Stavros

SPARQL is today the standard access language for Semantic Web data. In the recent years XML databases have also acquired industrial importance due to the widespread applicability of XML in the Web. In this paper we present a framework that bridges the heterogeneity gap and creates an interoperable environment where SPARQL queries are used to access XML databases. Our approach assumes that fairly generic mappings between ontology constructs and XML Schema constructs have been automatically derived or manually specified. The mappings are used to automatically translate SPARQL queries to semantically equivalent XQuery queries which are used to access the XML databases. We present the algorithms and the implementation of SPARQL2XQuery framework, which is used for answering SPARQL queries over XML databases.

Automatic recognition of seismic intensity based on RS and GIS: a case study in Wenchuan Ms8.0 earthquake of China.

PubMed

Zhang, Qiuwen; Zhang, Yan; Yang, Xiaohong; Su, Bin

2014-01-01

In recent years, earthquakes have frequently occurred all over the world, which caused huge casualties and economic losses. It is very necessary and urgent to obtain the seismic intensity map timely so as to master the distribution of the disaster and provide supports for quick earthquake relief. Compared with traditional methods of drawing seismic intensity map, which require many investigations in the field of earthquake area or are too dependent on the empirical formulas, spatial information technologies such as Remote Sensing (RS) and Geographical Information System (GIS) can provide fast and economical way to automatically recognize the seismic intensity. With the integrated application of RS and GIS, this paper proposes a RS/GIS-based approach for automatic recognition of seismic intensity, in which RS is used to retrieve and extract the information on damages caused by earthquake, and GIS is applied to manage and display the data of seismic intensity. The case study in Wenchuan Ms8.0 earthquake in China shows that the information on seismic intensity can be automatically extracted from remotely sensed images as quickly as possible after earthquake occurrence, and the Digital Intensity Model (DIM) can be used to visually query and display the distribution of seismic intensity.

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

PubMed

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

2017-07-31

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

Intraventricular vector flow mapping—a Doppler-based regularized problem with automatic model selection

NASA Astrophysics Data System (ADS)

Assi, Kondo Claude; Gay, Etienne; Chnafa, Christophe; Mendez, Simon; Nicoud, Franck; Abascal, Juan F. P. J.; Lantelme, Pierre; Tournoux, François; Garcia, Damien

2017-09-01

We propose a regularized least-squares method for reconstructing 2D velocity vector fields within the left ventricular cavity from single-view color Doppler echocardiographic images. Vector flow mapping is formulated as a quadratic optimization problem based on an {{\\ell }2} -norm minimization of a cost function composed of a Doppler data-fidelity term and a regularizer. The latter contains three physically interpretable expressions related to 2D mass conservation, Dirichlet boundary conditions, and smoothness. A finite difference discretization of the continuous problem was adopted in a polar coordinate system, leading to a sparse symmetric positive-definite system. The three regularization parameters were determined automatically by analyzing the L-hypersurface, a generalization of the L-curve. The performance of the proposed method was numerically evaluated using (1) a synthetic flow composed of a mixture of divergence-free and curl-free flow fields and (2) simulated flow data from a patient-specific CFD (computational fluid dynamics) model of a human left heart. The numerical evaluations showed that the vector flow fields reconstructed from the Doppler components were in good agreement with the original velocities, with a relative error less than 20%. It was also demonstrated that a perturbation of the domain contour has little effect on the rebuilt velocity fields. The capability of our intraventricular vector flow mapping (iVFM) algorithm was finally illustrated on in vivo echocardiographic color Doppler data acquired in patients. The vortex that forms during the rapid filling was clearly deciphered. This improved iVFM algorithm is expected to have a significant clinical impact in the assessment of diastolic function.

Medicare and Medicaid programs; fire safety requirements for long term care facilities, automatic sprinkler systems. Final rule.

PubMed

2008-08-13

This final rule requires all long term care facilities to be equipped with sprinkler systems by August 13, 2013. Additionally, this final rule requires affected facilities to maintain their automatic sprinkler systems once they are installed.

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

PubMed Central

Zheng, Jiaping; Yu, Hong

2016-01-01

Background Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients’ notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them. Interventions can then be developed by giving them targeted education to improve their EHR comprehension and the quality of care. Objective We aimed to develop a supervised natural language processing (NLP) system called Finding impOrtant medical Concepts most Useful to patientS (FOCUS) that automatically identifies and ranks medical terms in EHR notes based on their importance to the patients. Methods First, we built an expert-annotated corpus. For each EHR note, 2 physicians independently identified medical terms important to the patient. Using the physicians’ agreement as the gold standard, we developed and evaluated FOCUS. FOCUS first identifies candidate terms from each EHR note using MetaMap and then ranks the terms using a support vector machine-based learn-to-rank algorithm. We explored rich learning features, including distributed word representation, Unified Medical Language System semantic type, topic features, and features derived from consumer health vocabulary. We compared FOCUS with 2 strong baseline NLP systems. Results Physicians annotated 90 EHR notes and identified a mean of 9 (SD 5) important terms per note. The Cohen’s kappa annotation agreement was .51. The 10-fold cross-validation results show that FOCUS achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.940 for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FOCUS for identifying important terms from EHR notes was 0.866 AUC-ROC. Both performance scores significantly exceeded the corresponding baseline system scores (P<.001). Rich learning features contributed to FOCUS’s performance substantially. Conclusions FOCUS can automatically rank terms from EHR notes based on their importance to patients. It may help develop future interventions that improve quality of care. PMID:27903489

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations.

PubMed

Chen, Jinying; Zheng, Jiaping; Yu, Hong

2016-11-30

Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients' notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them. Interventions can then be developed by giving them targeted education to improve their EHR comprehension and the quality of care. We aimed to develop a supervised natural language processing (NLP) system called Finding impOrtant medical Concepts most Useful to patientS (FOCUS) that automatically identifies and ranks medical terms in EHR notes based on their importance to the patients. First, we built an expert-annotated corpus. For each EHR note, 2 physicians independently identified medical terms important to the patient. Using the physicians' agreement as the gold standard, we developed and evaluated FOCUS. FOCUS first identifies candidate terms from each EHR note using MetaMap and then ranks the terms using a support vector machine-based learn-to-rank algorithm. We explored rich learning features, including distributed word representation, Unified Medical Language System semantic type, topic features, and features derived from consumer health vocabulary. We compared FOCUS with 2 strong baseline NLP systems. Physicians annotated 90 EHR notes and identified a mean of 9 (SD 5) important terms per note. The Cohen's kappa annotation agreement was .51. The 10-fold cross-validation results show that FOCUS achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.940 for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FOCUS for identifying important terms from EHR notes was 0.866 AUC-ROC. Both performance scores significantly exceeded the corresponding baseline system scores (P<.001). Rich learning features contributed to FOCUS's performance substantially. FOCUS can automatically rank terms from EHR notes based on their importance to patients. It may help develop future interventions that improve quality of care. ©Jinying Chen, Jiaping Zheng, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 30.11.2016.

Measurable realistic image-based 3D mapping

NASA Astrophysics Data System (ADS)

Liu, W.; Wang, J.; Wang, J. J.; Ding, W.; Almagbile, A.

2011-12-01

Maps with 3D visual models are becoming a remarkable feature of 3D map services. High-resolution image data is obtained for the construction of 3D visualized models.The3D map not only provides the capabilities of 3D measurements and knowledge mining, but also provides the virtual experienceof places of interest, such as demonstrated in the Google Earth. Applications of 3D maps are expanding into the areas of architecture, property management, and urban environment monitoring. However, the reconstruction of high quality 3D models is time consuming, and requires robust hardware and powerful software to handle the enormous amount of data. This is especially for automatic implementation of 3D models and the representation of complicated surfacesthat still need improvements with in the visualisation techniques. The shortcoming of 3D model-based maps is the limitation of detailed coverage since a user can only view and measure objects that are already modelled in the virtual environment. This paper proposes and demonstrates a 3D map concept that is realistic and image-based, that enables geometric measurements and geo-location services. Additionally, image-based 3D maps provide more detailed information of the real world than 3D model-based maps. The image-based 3D maps use geo-referenced stereo images or panoramic images. The geometric relationships between objects in the images can be resolved from the geometric model of stereo images. The panoramic function makes 3D maps more interactive with users but also creates an interesting immersive circumstance. Actually, unmeasurable image-based 3D maps already exist, such as Google street view, but only provide virtual experiences in terms of photos. The topographic and terrain attributes, such as shapes and heights though are omitted. This paper also discusses the potential for using a low cost land Mobile Mapping System (MMS) to implement realistic image 3D mapping, and evaluates the positioning accuracy that a measureable realistic image-based (MRI) system can produce. The major contribution here is the implementation of measurable images on 3D maps to obtain various measurements from real scenes.

A design for the geoinformatics system

NASA Astrophysics Data System (ADS)

Allison, M. L.

2002-12-01

Informatics integrates and applies information technologies with scientific and technical disciplines. A geoinformatics system targets the spatially based sciences. The system is not a master database, but will collect pertinent information from disparate databases distributed around the world. Seamless interoperability of databases promises quantum leaps in productivity not only for scientific researchers but also for many areas of society including business and government. The system will incorporate: acquisition of analog and digital legacy data; efficient information and data retrieval mechanisms (via data mining and web services); accessibility to and application of visualization, analysis, and modeling capabilities; online workspace, software, and tutorials; GIS; integration with online scientific journal aggregates and digital libraries; access to real time data collection and dissemination; user-defined automatic notification and quality control filtering for selection of new resources; and application to field techniques such as mapping. In practical terms, such a system will provide the ability to gather data over the Web from a variety of distributed sources, regardless of computer operating systems, database formats, and servers. Search engines will gather data about any geographic location, above, on, or below ground, covering any geologic time, and at any scale or detail. A distributed network of digital geolibraries can archive permanent copies of databases at risk of being discontinued and those that continue to be maintained by the data authors. The geoinformatics system will generate results from widely distributed sources to function as a dynamic data network. Instead of posting a variety of pre-made tables, charts, or maps based on static databases, the interactive dynamic system creates these products on the fly, each time an inquiry is made, using the latest information in the appropriate databases. Thus, in the dynamic system, a map generated today may differ from one created yesterday and one to be created tomorrow, because the databases used to make it are constantly (and sometimes automatically) being updated.

Automatic public access to documents and maps stored on and internal secure system.

NASA Astrophysics Data System (ADS)

Trench, James; Carter, Mary

2013-04-01

The Geological Survey of Ireland operates a Document Management System for providing documents and maps stored internally in high resolution and in a high level secure environment, to an external service where the documents are automatically presented in a lower resolution to members of the public. Security is devised through roles and Individual Users where role level and folder level can be set. The application is an electronic document/data management (EDM) system which has a Geographical Information System (GIS) component integrated to allow users to query an interactive map of Ireland for data that relates to a particular area of interest. The data stored in the database consists of Bedrock Field Sheets, Bedrock Notebooks, Bedrock Maps, Geophysical Surveys, Geotechnical Maps & Reports, Groundwater, GSI Publications, Marine, Mine Records, Mineral Localities, Open File, Quaternary and Unpublished Reports. The Konfig application Tool is both an internal and public facing application. It acts as a tool for high resolution data entry which are stored in a high resolution vault. The public facing application is a mirror of the internal application and differs only in that the application furnishes high resolution data into low resolution format which is stored in a low resolution vault thus, making the data web friendly to the end user for download.

DiffNet: automatic differential functional summarization of dE-MAP networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes

2014-10-01

The study of genetic interaction networks that respond to changing conditions is an emerging research problem. Recently, Bandyopadhyay et al. (2010) proposed a technique to construct a differential network (dE-MAPnetwork) from two static gene interaction networks in order to map the interaction differences between them under environment or condition change (e.g., DNA-damaging agent). This differential network is then manually analyzed to conclude that DNA repair is differentially effected by the condition change. Unfortunately, manual construction of differential functional summary from a dE-MAP network that summarizes all pertinent functional responses is time-consuming, laborious and error-prone, impeding large-scale analysis on it. To this end, we propose DiffNet, a novel data-driven algorithm that leverages Gene Ontology (go) annotations to automatically summarize a dE-MAP network to obtain a high-level map of functional responses due to condition change. We tested DiffNet on the dynamic interaction networks following MMS treatment and demonstrated the superiority of our approach in generating differential functional summaries compared to state-of-the-art graph clustering methods. We studied the effects of parameters in DiffNet in controlling the quality of the summary. We also performed a case study that illustrates its utility. Copyright © 2014 Elsevier Inc. All rights reserved.

Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

PubMed

Emadzadeh, Ehsan; Sarker, Abeed; Nikfarjam, Azadeh; Gonzalez, Graciela

2017-01-01

Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extraction of ADR information can be crucial for healthcare providers, drug manufacturers, and consumers. However, because of the non-standard nature of social media language, automatically extracted ADR mentions need to be mapped to standard forms before they can be used by operational pharmacovigilance systems. We propose a modular natural language processing pipeline for mapping (normalizing) colloquial mentions of ADRs to their corresponding standardized identifiers. We seek to accomplish this task and enable customization of the pipeline so that distinct unlabeled free text resources can be incorporated to use the system for other normalization tasks. Our approach, which we call Hybrid Semantic Analysis (HSA), sequentially employs rule-based and semantic matching algorithms for mapping user-generated mentions to concept IDs in the Unified Medical Language System vocabulary. The semantic matching component of HSA is adaptive in nature and uses a regression model to combine various measures of semantic relatedness and resources to optimize normalization performance on the selected data source. On a publicly available corpus, our normalization method achieves 0.502 recall and 0.823 precision (F-measure: 0.624). Our proposed method outperforms a baseline based on latent semantic analysis and another that uses MetaMap.

Mapping urban climate zones and quantifying climate behaviors--an application on Toulouse urban area (France).

PubMed

Houet, Thomas; Pigeon, Grégoire

2011-01-01

Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The use of climatic maps, such Urban Climate Zone‑UCZ, is adapted for this kind of application. The objective of this paper is to demonstrate that the UCZ classification, integrated in the World Meteorological Organization guidelines, first can be automatically determined for sample areas and second is meaningful according to climatic variables. The analysis presented is applied on Toulouse urban area (France). Results show first that UCZ differentiate according to air and surface temperature. It has been possible to determine the membership of sample areas to an UCZ using landscape descriptors automatically computed with GIS and remote sensed data. It also emphasizes that climate behavior and magnitude of UCZ may vary from winter to summer. Finally we discuss the influence of climate data and scale of observation on UCZ mapping and climate characterization. Copyright © 2011 Elsevier Ltd. All rights reserved.

Automatic co-registration of 3D multi-sensor point clouds

NASA Astrophysics Data System (ADS)

Persad, Ravi Ancil; Armenakis, Costas

2017-08-01

We propose an approach for the automatic coarse alignment of 3D point clouds which have been acquired from various platforms. The method is based on 2D keypoint matching performed on height map images of the point clouds. Initially, a multi-scale wavelet keypoint detector is applied, followed by adaptive non-maxima suppression. A scale, rotation and translation-invariant descriptor is then computed for all keypoints. The descriptor is built using the log-polar mapping of Gabor filter derivatives in combination with the so-called Rapid Transform. In the final step, source and target height map keypoint correspondences are determined using a bi-directional nearest neighbour similarity check, together with a threshold-free modified-RANSAC. Experiments with urban and non-urban scenes are presented and results show scale errors ranging from 0.01 to 0.03, 3D rotation errors in the order of 0.2° to 0.3° and 3D translation errors from 0.09 m to 1.1 m.

Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

2017-05-01

Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

Use of scientific social networking to improve the research strategies of PubMed readers.

PubMed

Evdokimov, Pavel; Kudryavtsev, Alexey; Ilgisonis, Ekaterina; Ponomarenko, Elena; Lisitsa, Andrey

2016-02-18

Keeping up with journal articles on a daily basis is an important activity of scientists engaged in biomedical research. Usually, journal articles and papers in the field of biomedicine are accessed through the Medline/PubMed electronic library. In the process of navigating PubMed, researchers unknowingly generate user-specific reading profiles that can be shared within a social networking environment. This paper examines the structure of the social networking environment generated by PubMed users. A web browser plugin was developed to map [in Medical Subject Headings (MeSH) terms] the reading patterns of individual PubMed users. We developed a scientific social network based on the personal research profiles of readers of biomedical articles. A browser plugin is used to record the digital object identifier or PubMed ID of web pages. Recorded items are posted on the activity feed and automatically mapped to PubMed abstract. Within the activity feed a user can trace back previously browsed articles and insert comments. By calculating the frequency with which specific MeSH occur, the research interests of PubMed users can be visually represented with a tag cloud. Finally, research profiles can be searched for matches between network users. A social networking environment was created using MeSH terms to map articles accessed through the Medline/PubMed online library system. In-network social communication is supported by the recommendation of articles and by matching users with similar scientific interests. The system is available at http://bioknol.org/en/.

Method for Stereo Mapping Based on Objectarx and Pipeline Technology

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

Automatic circuit interrupter

NASA Technical Reports Server (NTRS)

Dwinell, W. S.

1979-01-01

In technique, voice circuits connecting crew's cabin to launch station through umbilical connector disconnect automatically unused, or deadened portion of circuits immediately after vehicle is launched, eliminating possibility that unused wiring interferes with voice communications inside vehicle or need for manual cutoff switch and its associated wiring. Technique is applied to other types of electrical actuation circuits, also launch of mapped vehicles, such as balloons, submarines, test sleds, and test chambers-all requiring assistance of ground crew.

Use of an automatic earth resistivity system for detection of abandoned mine workings

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

Peters, W.R.; Burdick, R.

1982-04-01

Under the sponsorship of the US Bureau of Mines, a surface-operated automatic high resolution earth resistivity system and associated computer data processing techniques have been designed and constructed for use as a potential means of detecting abandoned coal mine workings. The hardware and software aspects of the new system are described together with applications of the method to the survey and mapping of abandoned mine workings.

Open-Source Programming for Automated Generation of Graphene Raman Spectral Maps

NASA Astrophysics Data System (ADS)

Vendola, P.; Blades, M.; Pierre, W.; Jedlicka, S.; Rotkin, S. V.

Raman microscopy is a useful tool for studying the structural characteristics of graphene deposited onto substrates. However, extracting useful information from the Raman spectra requires data processing and 2D map generation. An existing home-built confocal Raman microscope was optimized for graphene samples and programmed to automatically generate Raman spectral maps across a specified area. In particular, an open source data collection scheme was generated to allow the efficient collection and analysis of the Raman spectral data for future use. NSF ECCS-1509786.

Near Real-Time Photometric Data Processing for the Solar Mass Ejection Imager (SMEI)

NASA Astrophysics Data System (ADS)

Hick, P. P.; Buffington, A.; Jackson, B. V.

2004-12-01

The Solar Mass Ejection Imager (SMEI) records a photometric white-light response of the interplanetary medium from Earth over most of the sky in near real time. In the first two years of operation the instrument has recorded the inner heliospheric response to several hundred CMEs, including the May 28, 2003 and the October 28, 2003 halo CMEs. In this preliminary work we present the techniques required to process the SMEI data from the time the raw CCD images become available to their final assembly in photometrically accurate maps of the sky brightness relative to a long-term time base. Processing of the SMEI data includes integration of new data into the SMEI data base; a conditioning program that removes from the raw CCD images an electronic offset ("pedestal") and a temperature-dependent dark current pattern; an "indexing" program that places these CCD images onto a high-resolution sidereal grid using known spacecraft pointing information. At this "indexing" stage further conditioning removes the bulk of the the effects of high-energy-particle hits ("cosmic rays"), space debris inside the field of view, and pixels with a sudden state change ("flipper pixels"). Once the high-resolution grid is produced, it is reformatted to a lower-resolution set of sidereal maps of sky brightness. From these sidereal maps we remove bright stars, background stars, and a zodiacal cloud model (their brightnesses are retained as additional data products). The final maps can be represented in any convenient sky coordinate system. Common formats are Sun-centered Hammer-Aitoff or "fisheye" maps. Time series at selected locations on these maps are extracted and processed further to remove aurorae, variable stars and other unwanted signals. These time series (with a long-term base removed) are used in 3D tomographic reconstructions. The data processing is distributed over multiple PCs running Linux, and, runs as much as possible automatically using recurring batch jobs ('cronjobs'). The batch scrips are controlled by Python scripts. The core data processing routines are written in several computer languages: Fortran, C++ and IDL.

Automatic Correction Algorithm of Hyfrology Feature Attribute in National Geographic Census

NASA Astrophysics Data System (ADS)

Li, C.; Guo, P.; Liu, X.

2017-09-01

A subset of the attributes of hydrologic features data in national geographic census are not clear, the current solution to this problem was through manual filling which is inefficient and liable to mistakes. So this paper proposes an automatic correction algorithm of hydrologic features attribute. Based on the analysis of the structure characteristics and topological relation, we put forward three basic principles of correction which include network proximity, structure robustness and topology ductility. Based on the WJ-III map workstation, we realize the automatic correction of hydrologic features. Finally, practical data is used to validate the method. The results show that our method is highly reasonable and efficient.

An automatic locating system for cloud-to-ground lightning. [which utilizes a microcomputer

NASA Technical Reports Server (NTRS)

Krider, E. P.; Pifer, A. E.; Uman, M. A.

1980-01-01

Automatic locating systems which respond to cloud to ground lightning and which discriminate against cloud discharges and background noise are described. Subsystems of the locating system, which include the direction finder and the position analyzer, are discussed. The direction finder senses the electromagnetic fields radiated by lightning on two orthogonal magnetic loop antennas and on a flat plate electric antenna. The position analyzer is a preprogrammed microcomputer system which automatically computes, maps, and records lightning locations in real time using data inputs from the direction finder. The use of the locating systems for wildfire management and fire weather forecasting is discussed.

A partial differential equation-based general framework adapted to Rayleigh's, Rician's and Gaussian's distributed noise for restoration and enhancement of magnetic resonance image.

PubMed

Yadav, Ram Bharos; Srivastava, Subodh; Srivastava, Rajeev

2016-01-01

The proposed framework is obtained by casting the noise removal problem into a variational framework. This framework automatically identifies the various types of noise present in the magnetic resonance image and filters them by choosing an appropriate filter. This filter includes two terms: the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimizing the negative log likelihood of the corresponding probability density functions: Gaussian or Rayleigh or Rician. Further, due to the ill-posedness of the likelihood term, a prior function is needed. This paper examines three partial differential equation based priors which include total variation based prior, anisotropic diffusion based prior, and a complex diffusion (CD) based prior. A regularization parameter is used to balance the trade-off between data fidelity term and prior. The finite difference scheme is used for discretization of the proposed method. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of peak signal-to-noise ratio, mean square error, structure similarity index map, and correlation parameter. From the simulation results, it is observed that the proposed framework with CD based prior is performing better in comparison to other priors in consideration.

Automatic localization of landmark sets in head CT images with regression forests for image registration initialization

NASA Astrophysics Data System (ADS)

Zhang, Dongqing; Liu, Yuan; Noble, Jack H.; Dawant, Benoit M.

2016-03-01

Cochlear Implants (CIs) are electrode arrays that are surgically inserted into the cochlea. Individual contacts stimulate frequency-mapped nerve endings thus replacing the natural electro-mechanical transduction mechanism. CIs are programmed post-operatively by audiologists but this is currently done using behavioral tests without imaging information that permits relating electrode position to inner ear anatomy. We have recently developed a series of image processing steps that permit the segmentation of the inner ear anatomy and the localization of individual contacts. We have proposed a new programming strategy that uses this information and we have shown in a study with 68 participants that 78% of long term recipients preferred the programming parameters determined with this new strategy. A limiting factor to the large scale evaluation and deployment of our technique is the amount of user interaction still required in some of the steps used in our sequence of image processing algorithms. One such step is the rough registration of an atlas to target volumes prior to the use of automated intensity-based algorithms when the target volumes have very different fields of view and orientations. In this paper we propose a solution to this problem. It relies on a random forest-based approach to automatically localize a series of landmarks. Our results obtained from 83 images with 132 registration tasks show that automatic initialization of an intensity-based algorithm proves to be a reliable technique to replace the manual step.

A Theory of Term Importance in Automatic Text Analysis.

ERIC Educational Resources Information Center

Salton, G.; And Others

Most existing automatic content analysis and indexing techniques are based on work frequency characteristics applied largely in an ad hoc manner. Contradictory requirements arise in this connection, in that terms exhibiting high occurrence frequencies in individual documents are often useful for high recall performance (to retrieve many relevant…

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

USGS Publications Warehouse

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

1999-01-01

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

Statewide Cellular Coverage Map

DOT National Transportation Integrated Search

2002-02-01

The role of wireless communications in transportation is becoming increasingly important. Wireless communications are critical for many applications of Intelligent Transportation Systems (ITS) such as Automatic Vehicle Location (AVL) and Automated Co...

Automated reconstruction of standing posture panoramas from multi-sector long limb x-ray images

NASA Astrophysics Data System (ADS)

Miller, Linzey; Trier, Caroline; Ben-Zikri, Yehuda K.; Linte, Cristian A.

2016-03-01

Due to the digital X-ray imaging system's limited field of view, several individual sector images are required to capture the posture of an individual in standing position. These images are then "stitched together" to reconstruct the standing posture. We have created an image processing application that automates the stitching, therefore minimizing user input, optimizing workflow, and reducing human error. The application begins with pre-processing the input images by removing artifacts, filtering out isolated noisy regions, and amplifying a seamless bone edge. The resulting binary images are then registered together using a rigid-body intensity based registration algorithm. The identified registration transformations are then used to map the original sector images into the panorama image. Our method focuses primarily on the use of the anatomical content of the images to generate the panoramas as opposed to using external markers employed to aid with the alignment process. Currently, results show robust edge detection prior to registration and we have tested our approach by comparing the resulting automatically-stitched panoramas to the manually stitched panoramas in terms of registration parameters, target registration error of homologous markers, and the homogeneity of the digitally subtracted automatically- and manually-stitched images using 26 patient datasets.

Derivation of groundwater flow-paths based on semi-automatic extraction of lineaments from remote sensing data

NASA Astrophysics Data System (ADS)

Mallast, U.; Gloaguen, R.; Geyer, S.; Rödiger, T.; Siebert, C.

2011-08-01

In this paper we present a semi-automatic method to infer groundwater flow-paths based on the extraction of lineaments from digital elevation models. This method is especially adequate in remote and inaccessible areas where in-situ data are scarce. The combined method of linear filtering and object-based classification provides a lineament map with a high degree of accuracy. Subsequently, lineaments are differentiated into geological and morphological lineaments using auxiliary information and finally evaluated in terms of hydro-geological significance. Using the example of the western catchment of the Dead Sea (Israel/Palestine), the orientation and location of the differentiated lineaments are compared to characteristics of known structural features. We demonstrate that a strong correlation between lineaments and structural features exists. Using Euclidean distances between lineaments and wells provides an assessment criterion to evaluate the hydraulic significance of detected lineaments. Based on this analysis, we suggest that the statistical analysis of lineaments allows a delineation of flow-paths and thus significant information on groundwater movements. To validate the flow-paths we compare them to existing results of groundwater models that are based on well data.

3D model assisted fully automated scanning laser Doppler vibrometer measurements

NASA Astrophysics Data System (ADS)

Sels, Seppe; Ribbens, Bart; Bogaerts, Boris; Peeters, Jeroen; Vanlanduit, Steve

2017-12-01

In this paper, a new fully automated scanning laser Doppler vibrometer (LDV) measurement technique is presented. In contrast to existing scanning LDV techniques which use a 2D camera for the manual selection of sample points, we use a 3D Time-of-Flight camera in combination with a CAD file of the test object to automatically obtain measurements at pre-defined locations. The proposed procedure allows users to test prototypes in a shorter time because physical measurement locations are determined without user interaction. Another benefit from this methodology is that it incorporates automatic mapping between a CAD model and the vibration measurements. This mapping can be used to visualize measurements directly on a 3D CAD model. The proposed method is illustrated with vibration measurements of an unmanned aerial vehicle

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

An Innovative Approach to Automatically Detect and Interpret Salient Spatiotemporal Features of a Numeric Field: A Case Study in Electrocardiographic Imaging

NASA Astrophysics Data System (ADS)

Ironi, Liliana; Tentoni, Stefania

2009-08-01

The last decade has witnessed major advancements in the direct application of functional imaging techniques to several clinical contexts. Unfortunately, this is not the case of Electrocardiology. As a matter of fact, epicardial maps, which can hit electrical conduction pathologies that routine surface ECG's analysis may miss, can be obtained non invasively from body surface data through mathematical model-based reconstruction methods. But, their interpretation still requires highly specialized skills that belong to few experts. The automated detection of salient patterns in the map, grounded on the existing interpretation rationale, would therefore represent a major contribution towards the clinical use of such valuable tools, whose diagnostic potential is still largely unexploited. We focus on epicardial activation isochronal maps, which convey information about the heart electric function in terms of the depolarization wavefront kinematics. An approach grounded on the integration of a Spatial Aggregation (SA) method with concepts borrowed from Computational Geometry provides a computational framework to extract, from the given activation data, a few basic features that characterize the wavefront propagation, as well as a more specific set of features that identify an important class of heart rhythm pathologies, namely reentry arrhythmias due to block of conduction.

Automatic Query Formulations in Information Retrieval.

ERIC Educational Resources Information Center

Salton, G.; And Others

1983-01-01

Introduces methods designed to reduce role of search intermediaries by generating Boolean search formulations automatically using term frequency considerations from natural language statements provided by system patrons. Experimental results are supplied and methods are described for applying automatic query formulation process in practice.…

46 CFR 62.10-1 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... control means a function of an automatic control system to restrict operation to a specified operating... automatic or manual control. Safety trip control system means a manually or automatically operated system... GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING VITAL SYSTEM AUTOMATION Terms Used...

46 CFR 62.10-1 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... control means a function of an automatic control system to restrict operation to a specified operating... automatic or manual control. Safety trip control system means a manually or automatically operated system... GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING VITAL SYSTEM AUTOMATION Terms Used...

46 CFR 62.10-1 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... control means a function of an automatic control system to restrict operation to a specified operating... automatic or manual control. Safety trip control system means a manually or automatically operated system... GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING VITAL SYSTEM AUTOMATION Terms Used...

46 CFR 62.10-1 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... control means a function of an automatic control system to restrict operation to a specified operating... automatic or manual control. Safety trip control system means a manually or automatically operated system... GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING VITAL SYSTEM AUTOMATION Terms Used...

46 CFR 62.10-1 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... control means a function of an automatic control system to restrict operation to a specified operating... automatic or manual control. Safety trip control system means a manually or automatically operated system... GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING VITAL SYSTEM AUTOMATION Terms Used...

Where do students struggle in the field? Computer-aided evaluation of mapping errors from an undergraduate Field Geology summer course

NASA Astrophysics Data System (ADS)

Lang, K. A.; Petrie, G.

2014-12-01

Extended field-based summer courses provide an invaluable field experience for undergraduate majors in the geosciences. These courses often utilize the construction of geological maps and structural cross sections as the primary pedagogical tool to teach basic map orientation, rock identification and structural interpretation. However, advances in the usability and ubiquity of Geographic Information Systems in these courses presents new opportunities to evaluate student work. In particular, computer-based quantification of systematic mapping errors elucidates the factors influencing student success in the field. We present a case example from a mapping exercise conducted in a summer Field Geology course at a popular field location near Dillon, Montana. We use a computer algorithm to automatically compare the placement and attribution of unit contacts with spatial variables including topographic slope, aspect, bedding attitude, ground cover and distance from starting location. We compliment analyses with anecdotal and survey data that suggest both physical factors (e.g. steep topographic slope) as well as structural nuance (e.g. low angle bedding) may dominate student frustration, particularly in courses with a high student to instructor ratio. We propose mechanisms to improve student experience by allowing students to practice skills with orientation games and broadening student background with tangential lessons (e.g. on colluvial transport processes). As well, we suggest low-cost ways to decrease the student to instructor ratio by supporting returning undergraduates from previous years or staging mapping over smaller areas. Future applications of this analysis might include a rapid and objective system for evaluation of student maps (including point-data, such as attitude measurements) and quantification of temporal trends in student work as class sizes, pedagogical approaches or environmental variables change. Long-term goals include understanding and characterizing stochasticity in geological mapping beyond the undergraduate classroom, and better quantifying uncertainty in published map products.

Deep SOMs for automated feature extraction and classification from big data streaming

NASA Astrophysics Data System (ADS)

Sakkari, Mohamed; Ejbali, Ridha; Zaied, Mourad

2017-03-01

In this paper, we proposed a deep self-organizing map model (Deep-SOMs) for automated features extracting and learning from big data streaming which we benefit from the framework Spark for real time streams and highly parallel data processing. The SOMs deep architecture is based on the notion of abstraction (patterns automatically extract from the raw data, from the less to more abstract). The proposed model consists of three hidden self-organizing layers, an input and an output layer. Each layer is made up of a multitude of SOMs, each map only focusing at local headmistress sub-region from the input image. Then, each layer trains the local information to generate more overall information in the higher layer. The proposed Deep-SOMs model is unique in terms of the layers architecture, the SOMs sampling method and learning. During the learning stage we use a set of unsupervised SOMs for feature extraction. We validate the effectiveness of our approach on large data sets such as Leukemia dataset and SRBCT. Results of comparison have shown that the Deep-SOMs model performs better than many existing algorithms for images classification.

Standard cell electrical and physical variability analysis based on automatic physical measurement for design-for-manufacturing purposes

NASA Astrophysics Data System (ADS)

Shauly, Eitan; Parag, Allon; Khmaisy, Hafez; Krispil, Uri; Adan, Ofer; Levi, Shimon; Latinski, Sergey; Schwarzband, Ishai; Rotstein, Israel

2011-04-01

A fully automated system for process variability analysis of high density standard cell was developed. The system consists of layout analysis with device mapping: device type, location, configuration and more. The mapping step was created by a simple DRC run-set. This database was then used as an input for choosing locations for SEM images and for specific layout parameter extraction, used by SPICE simulation. This method was used to analyze large arrays of standard cell blocks, manufactured using Tower TS013LV (Low Voltage for high-speed applications) Platforms. Variability of different physical parameters like and like Lgate, Line-width-roughness and more as well as of electrical parameters like drive current (Ion), off current (Ioff) were calculated and statistically analyzed, in order to understand the variability root cause. Comparison between transistors having the same W/L but with different layout configurations and different layout environments (around the transistor) was made in terms of performances as well as process variability. We successfully defined "robust" and "less-robust" transistors configurations, and updated guidelines for Design-for-Manufacturing (DfM).

40 CFR 1065.510 - Engine mapping.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... Configure any auxiliary work inputs and outputs such as hybrid, turbo-compounding, or thermoelectric systems... intended primarily for propulsion of a vehicle with an automatic transmission where that engine is subject...

Glacier Surface Lowering and Stagnation in the Manaslu Region of Nepal

NASA Astrophysics Data System (ADS)

Robson, B. A.; Nuth, C.; Nielsen, P. R.; Hendrickx, M.; Dahl, S. O.

2015-12-01

Frequent and up-to-date glacier outlines are needed for many applications of glaciology, not only glacier area change analysis, but also for masks in volume or velocity analysis, for the estimation of water resources and as model input data. Remote sensing offers a good option for creating glacier outlines over large areas, but manual correction is frequently necessary, especially in areas containing supraglacial debris. We show three different workflows for mapping clean ice and debris-covered ice within Object Based Image Analysis (OBIA). By working at the object level as opposed to the pixel level, OBIA facilitates using contextual, spatial and hierarchical information when assigning classes, and additionally permits the handling of multiple data sources. Our first example shows mapping debris-covered ice in the Manaslu Himalaya, Nepal. SAR Coherence data is used in combination with optical and topographic data to classify debris-covered ice, obtaining an accuracy of 91%. Our second example shows using a high-resolution LiDAR derived DEM over the Hohe Tauern National Park in Austria. Breaks in surface morphology are used in creating image objects; debris-covered ice is then classified using a combination of spectral, thermal and topographic properties. Lastly, we show a completely automated workflow for mapping glacier ice in Norway. The NDSI and NIR/SWIR band ratio are used to map clean ice over the entire country but the thresholds are calculated automatically based on a histogram of each image subset. This means that in theory any Landsat scene can be inputted and the clean ice can be automatically extracted. Debris-covered ice can be included semi-automatically using contextual and morphological information.

Computer vision-based diameter maps to study fluoroscopic recordings of small intestinal motility from conscious experimental animals.

PubMed

Ramírez, I; Pantrigo, J J; Montemayor, A S; López-Pérez, A E; Martín-Fontelles, M I; Brookes, S J H; Abalo, R

2017-08-01

When available, fluoroscopic recordings are a relatively cheap, non-invasive and technically straightforward way to study gastrointestinal motility. Spatiotemporal maps have been used to characterize motility of intestinal preparations in vitro, or in anesthetized animals in vivo. Here, a new automated computer-based method was used to construct spatiotemporal motility maps from fluoroscopic recordings obtained in conscious rats. Conscious, non-fasted, adult, male Wistar rats (n=8) received intragastric administration of barium contrast, and 1-2 hours later, when several loops of the small intestine were well-defined, a 2 minutes-fluoroscopic recording was obtained. Spatiotemporal diameter maps (Dmaps) were automatically calculated from the recordings. Three recordings were also manually analyzed for comparison. Frequency analysis was performed in order to calculate relevant motility parameters. In each conscious rat, a stable recording (17-20 seconds) was analyzed. The Dmaps manually and automatically obtained from the same recording were comparable, but the automated process was faster and provided higher resolution. Two frequencies of motor activity dominated; lower frequency contractions (15.2±0.9 cpm) had an amplitude approximately five times greater than higher frequency events (32.8±0.7 cpm). The automated method developed here needed little investigator input, provided high-resolution results with short computing times, and automatically compensated for breathing and other small movements, allowing recordings to be made without anesthesia. Although slow and/or infrequent events could not be detected in the short recording periods analyzed to date (17-20 seconds), this novel system enhances the analysis of in vivo motility in conscious animals. © 2017 John Wiley & Sons Ltd.

Portability issues for a structured clinical vocabulary: mapping from Yale to the Columbia medical entities dictionary.

PubMed Central

Kannry, J L; Wright, L; Shifman, M; Silverstein, S; Miller, P L

1996-01-01

OBJECTIVE: To examine the issues involved in mapping an existing structured controlled vocabulary, the Medical Entities Dictionary (MED) developed at Columbia University, to an institutional vocabulary, the laboratory and pharmacy vocabularies of the Yale New Haven Medical Center. DESIGN: 200 Yale pharmacy terms and 200 Yale laboratory terms were randomly selected from database files containing all of the Yale laboratory and pharmacy terms. These 400 terms were then mapped to the MED in three phases: mapping terms, mapping relationships between terms, and mapping attributes that modify terms. RESULTS: 73% of the Yale pharmacy terms mapped to MED terms. 49% of the Yale laboratory terms mapped to MED terms. After certain obsolete and otherwise inappropriate laboratory terms were eliminated, the latter rate improved to 59%. 23% of the unmatched Yale laboratory terms failed to match because of differences in granularity with MED terms. The Yale and MED pharmacy terms share 12 of 30 distinct attributes. The Yale and MED laboratory terms share 14 of 23 distinct attributes. CONCLUSION: The mapping of an institutional vocabulary to a structured controlled vocabulary requires that the mapping be performed at the level of terms, relationships, and attributes. The mapping process revealed the importance of standardization of local vocabulary subsets, standardization of attribute representation, and term granularity. PMID:8750391

Potentiality of SENTINEL-1 for landslide detection: first results in the Molise Region (Italy)

NASA Astrophysics Data System (ADS)

Barra, Anna; Monserrat, Oriol; Mazzanti, Paolo; Esposito, Carlo; Crosetto, Michele; Scarascia Mugnozza, Gabriele

2016-04-01

A detailed inventory map, including information on landslide activity, is one of the most important input to landslide susceptibility and hazard analyses. The contribution of satellite SAR Interferometry in landslide risk mitigation is well-known within the scientific community. In fact, many encouraging results have been obtained, principally, in areas characterized by high coherence of the images (e.g. due to rock lithology or urban environment setting). In terms of coherence, the expected increased capabilities of Sentinel-1 for landslide mapping and monitoring are connected to both wavelength (55.5 mm) and short temporal baseline (12 days). The latter one is expected to be a key feature for increasing coherence and for defining monitoring and updating plans. With the aim of assessing these potentialities, we processed a set of 14 Sentinel-1 SLC images, acquired during a temporal span of 7 months, over the Molise region (Southern Italy), a critical area geologically susceptible to landslides. Even though Molise is mostly covered by crops and forested areas (63% and 35% respectively), that means a non-optimal coherence condition for SAR interferometry, promising results have been obtained. This has been achieved by integrating differential interferometric SAR techniques (12-days interferograms and time series) with GIS multilayer analysis (optical, geological, geomorphological, etc.). Specifically, analyzing a single burst of a Sentinel-1 frame (approximately 1875 km2), 62 landslides have been detected, thus allowing to improve the pre-existing inventory maps both in terms of landslide boundaries and state of activity. The results of our ongoing research show that Sentinel-1 can give a significant improvement in terms of exploitation of SAR data for landslide mapping and monitoring. As a matter of fact, by analyzing longer periods, it is expected to achieve a better understanding of landslide behavior and its relationship with triggering factors. This will be key to perform hazard analyses. Further research will be focused in finding algorithms to automatically detect and extract patterns and in developing a more reliable methodology. This will be done by integrating the Sentinel-1 data with other types of data and, in particular, with Sentinel-2 imagery.

Towards SWOT data assimilation for hydrology : automatic calibration of global flow routing model parameters in the Amazon basin

NASA Astrophysics Data System (ADS)

Mouffe, M.; Getirana, A.; Ricci, S. M.; Lion, C.; Biancamaria, S.; Boone, A.; Mognard, N. M.; Rogel, P.

2011-12-01

The Surface Water and Ocean Topography (SWOT) mission is a swath mapping radar interferometer that will provide global measurements of water surface elevation (WSE). The revisit time depends upon latitude and varies from two (low latitudes) to ten (high latitudes) per 22-day orbit repeat period. The high resolution and the global coverage of the SWOT data open the way for new hydrology studies. Here, the aim is to investigate the use of virtually generated SWOT data to improve discharge simulation using data assimilation techniques. In the framework of the SWOT virtual mission (VM), this study presents the first results of the automatic calibration of a global flow routing (GFR) scheme using SWOT VM measurements for the Amazon basin. The Hydrological Modeling and Analysis Platform (HyMAP) is used along with the MOCOM-UA multi-criteria global optimization algorithm. HyMAP has a 0.25-degree spatial resolution and runs at the daily time step to simulate discharge, water levels and floodplains. The surface runoff and baseflow drainage derived from the Interactions Sol-Biosphère-Atmosphère (ISBA) model are used as inputs for HyMAP. Previous works showed that the use of ENVISAT data enables the reduction of the uncertainty on some of the hydrological model parameters, such as river width and depth, Manning roughness coefficient and groundwater time delay. In the framework of the SWOT preparation work, the automatic calibration procedure was applied using SWOT VM measurements. For this Observing System Experiment (OSE), the synthetical data were obtained applying an instrument simulator (representing realistic SWOT errors) for one hydrological year to HYMAP simulated WSE using a "true" set of parameters. Only pixels representing rivers larger than 100 meters within the Amazon basin are considered to produce SWOT VM measurements. The automatic calibration procedure leads to the estimation of optimal parametersminimizing objective functions that formulate the difference between SWOT observations and modeled WSE using a perturbed set of parameters. Different formulations of the objective function were used, especially to account for SWOT observation errors, as well as various sets of calibration parameters.

Feasibility study ASCS remote sensing/compliance determination system

NASA Technical Reports Server (NTRS)

Duggan, I. E.; Minter, T. C., Jr.; Moore, B. H.; Nosworthy, C. T.

1973-01-01

A short-term technical study was performed by the MSC Earth Observations Division to determine the feasibility of the proposed Agricultural Stabilization and Conservation Service Automatic Remote Sensing/Compliance Determination System. For the study, the term automatic was interpreted as applying to an automated remote-sensing system that includes data acquisition, processing, and management.

Automatic Text Analysis Based on Transition Phenomena of Word Occurrences

ERIC Educational Resources Information Center

Pao, Miranda Lee

1978-01-01

Describes a method of selecting index terms directly from a word frequency list, an idea originally suggested by Goffman. Results of the analysis of word frequencies of two articles seem to indicate that the automated selection of index terms from a frequency list holds some promise for automatic indexing. (Author/MBR)

Automatic and Controlled Processing in Sentence Recall: The Role of Long-Term and Working Memory

ERIC Educational Resources Information Center

Jefferies, E.; Lambon Ralph, M.A.; Baddeley, A.D.

2004-01-01

Immediate serial recall is better for sentences than word lists presumably because of the additional support that meaningful material receives from long-term memory. This may occur automatically, without the involvement of attention, or may require additional attentionally demanding processing. For example, the episodic buffer model (Baddeley,…

Satellite image based methods for fuels maps updating

NASA Astrophysics Data System (ADS)

Alonso-Benito, Alfonso; Hernandez-Leal, Pedro A.; Arbelo, Manuel; Gonzalez-Calvo, Alejandro; Moreno-Ruiz, Jose A.; Garcia-Lazaro, Jose R.

2016-10-01

Regular updating of fuels maps is important for forest fire management. Nevertheless complex and time consuming field work is usually necessary for this purpose, which prevents a more frequent update. That is why the assessment of the usefulness of satellite data and the development of remote sensing techniques that enable the automatic updating of these maps, is of vital interest. In this work, we have tested the use of the spectral bands of OLI (Operational Land Imager) sensor on board Landsat 8 satellite, for updating the fuels map of El Hierro Island (Spain). From previously digitized map, a set of 200 reference plots for different fuel types was created. A 50% of the plots were randomly used as a training set and the rest were considered for validation. Six supervised and 2 unsupervised classification methods were applied, considering two levels of detail. A first level with only 5 classes (Meadow, Brushwood, Undergrowth canopy cover >50%, Undergrowth canopy cover <15%, and Xeric formations), and the second one containing 19 fuel types. The level 1 classification methods yielded an overall accuracy ranging from 44% for Parellelepided to an 84% for Maximun Likelihood. Meanwhile, level 2 results showed at best, an unacceptable overall accuracy of 34%, which prevents the use of this data for such a detailed characterization. Anyway it has been demonstrated that in some conditions, images of medium spatial resolution, like Landsat 8-OLI, could be a valid tool for an automatic upgrade of fuels maps, minimizing costs and complementing traditional methodologies.

eWaterCycle visualisation. combining the strength of NetCDF and Web Map Service: ncWMS

NASA Astrophysics Data System (ADS)

Hut, R.; van Meersbergen, M.; Drost, N.; Van De Giesen, N.

2016-12-01

As a result of the eWatercycle global hydrological forecast we have created Cesium-ncWMS, a web application based on ncWMS and Cesium. ncWMS is a server side application capable of reading any NetCDF file written using the Climate and Forecasting (CF) conventions, and making the data available as a Web Map Service(WMS). ncWMS automatically determines available variables in a file, and creates maps colored according to map data and a user selected color scale. Cesium is a Javascript 3D virtual Globe library. It uses WebGL for rendering, which makes it very fast, and it is capable of displaying a wide variety of data types such as vectors, 3D models, and 2D maps. The forecast results are automatically uploaded to our web server running ncWMS. In turn, the web application can be used to change the settings for color maps and displayed data. The server uses the settings provided by the web application, together with the data in NetCDF to provide WMS image tiles, time series data and legend graphics to the Cesium-NcWMS web application. The user can simultaneously zoom in to the very high resolution forecast results anywhere on the world, and get time series data for any point on the globe. The Cesium-ncWMS visualisation combines a global overview with local relevant information in any browser. See the visualisation live at forecast.ewatercycle.org

IntegratedMap: a Web interface for integrating genetic map data.

PubMed

Yang, Hongyu; Wang, Hongyu; Gingle, Alan R

2005-05-01

IntegratedMap is a Web application and database schema for storing and interactively displaying genetic map data. Its Web interface includes a menu for direct chromosome/linkage group selection, a search form for selection based on mapped object location and linkage group displays. An overview display provides convenient access to the full range of mapped and anchored object types with genetic locus details, such as numbers, types and names of mapped/anchored objects displayed in a compact scrollable list box that automatically updates based on selected map location and object type. Also, multilinkage group and localized map views are available along with links that can be configured for integration with other Web resources. IntegratedMap is implemented in C#/ASP.NET and the package, including a MySQL schema creation script, is available from http://cggc.agtec.uga.edu/Data/download.asp

a Conceptual Framework for Indoor Mapping by Using Grammars

NASA Astrophysics Data System (ADS)

Hu, X.; Fan, H.; Zipf, A.; Shang, J.; Gu, F.

2017-09-01

Maps are the foundation of indoor location-based services. Many automatic indoor mapping approaches have been proposed, but they rely highly on sensor data, such as point clouds and users' location traces. To address this issue, this paper presents a conceptual framework to represent the layout principle of research buildings by using grammars. This framework can benefit the indoor mapping process by improving the accuracy of generated maps and by dramatically reducing the volume of the sensor data required by traditional reconstruction approaches. In addition, we try to present more details of partial core modules of the framework. An example using the proposed framework is given to show the generation process of a semantic map. This framework is part of an ongoing research for the development of an approach for reconstructing semantic maps.

Automatic generation of stop word lists for information retrieval and analysis

DOEpatents

Rose, Stuart J

2013-01-08

Methods and systems for automatically generating lists of stop words for information retrieval and analysis. Generation of the stop words can include providing a corpus of documents and a plurality of keywords. From the corpus of documents, a term list of all terms is constructed and both a keyword adjacency frequency and a keyword frequency are determined. If a ratio of the keyword adjacency frequency to the keyword frequency for a particular term on the term list is less than a predetermined value, then that term is excluded from the term list. The resulting term list is truncated based on predetermined criteria to form a stop word list.

Integration and segregation of large-scale brain networks during short-term task automatization

PubMed Central

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F.; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-01-01

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes. PMID:27808095

Neural Bases of Automaticity

ERIC Educational Resources Information Center

Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.

2018-01-01

Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…

Precision about the automatic emotional brain.

PubMed

Vuilleumier, Patrik

2015-01-01

The question of automaticity in emotion processing has been debated under different perspectives in recent years. Satisfying answers to this issue will require a better definition of automaticity in terms of relevant behavioral phenomena, ecological conditions of occurrence, and a more precise mechanistic account of the underlying neural circuits.

Extraction of Greenhouse Areas with Image Processing Methods in Karabuk Province

NASA Astrophysics Data System (ADS)

Yildirima, M. Z.; Ozcan, C.

2017-11-01

Greenhouses provide the environmental conditions to be controlled and regulated as desired while allowing agricultural products to be produced without being affected by external environmental conditions. High quality and a wide variety of agricultural products can be produced throughout the year. In addition, mapping and detection of these areas has great importance in terms of factors such as yield analysis, natural resource management and environmental impact. Various remote sensing techniques are currently available for extraction of greenhouse areas. These techniques are based on the automatic detection and interpretation of objects on remotely sensed images. In this study, greenhouse areas were determined from optical images obtained from Landsat. The study was carried out in the greenhouse areas in Karabuk province. The obtained results are presented with figures and tables.

An Approach to Extract Moving Objects from Mls Data Using a Volumetric Background Representation

NASA Astrophysics Data System (ADS)

Gehrung, J.; Hebel, M.; Arens, M.; Stilla, U.

2017-05-01

Data recorded by mobile LiDAR systems (MLS) can be used for the generation and refinement of city models or for the automatic detection of long-term changes in the public road space. Since for this task only static structures are of interest, all mobile objects need to be removed. This work presents a straightforward but powerful approach to remove the subclass of moving objects. A probabilistic volumetric representation is utilized to separate MLS measurements recorded by a Velodyne HDL-64E into mobile objects and static background. The method was subjected to a quantitative and a qualitative examination using multiple datasets recorded by a mobile mapping platform. The results show that depending on the chosen octree resolution 87-95% of the measurements are labeled correctly.

Rapid Mapping Of Floods Using SAR Data: Opportunities And Critical Aspects

NASA Astrophysics Data System (ADS)

Pulvirenti, Luca; Pierdicca, Nazzareno; Chini, Marco

2013-04-01

The potentiality of spaceborne Synthetic Aperture Radar (SAR) for flood mapping was demonstrated by several past investigations. The synoptic view, the capability to operate in almost all-weather conditions and during both day time and night time and the sensitivity of the microwave band to water are the key features that make SAR data useful for monitoring inundation events. In addition, their high spatial resolution, which can reach 1m with the new generation of X-band instruments such as TerraSAR-X and COSMO-SkyMed (CSK), allows emergency managers to use flood maps at very high spatial resolution. CSK gives also the possibility of performing frequent observations of regions hit by floods, thanks to the four-satellite constellation. Current research on flood mapping using SAR is focused on the development of automatic algorithms to be used in near real time applications. The approaches are generally based on the low radar return from smooth open water bodies that behave as specular reflectors and appear dark in SAR images. The major advantage of automatic algorithms is the computational efficiency that makes them suitable for rapid mapping purposes. The choice of the threshold value that, in this kind of algorithms, separates flooded from non-flooded areas is a critical aspect because it depends on the characteristics of the observed scenario and on system parameters. To deal with this aspect an algorithm for automatic detection of the regions of low backscatter has been developed. It basically accomplishes three steps: 1) division of the SAR image in a set of non-overlapping sub-images or splits; 2) selection of inhomogeneous sub-images that contain (at least) two populations of pixels, one of which is formed by dark pixels; 3) the application in sequence of an automatic thresholding algorithm and a region growing algorithm in order to produce a homogeneous map of flooded areas. Besides the aforementioned choice of the threshold, rapid mapping of floods may present other critical aspects. Searching for low SAR backscatter areas only may cause inaccuracies because flooded soils do not always act as smooth open water bodies. The presence of wind or of vegetation emerging above the water surface may give rise to an increase of the radar backscatter. In particular, mapping flooded vegetation using SAR data may represent a difficult task since backscattering phenomena in the volume between canopy, trunks and floodwater are quite complex in the presence of vegetation. A typical phenomenon is the double-bounce effect involving soil and stems or trunks, which is generally enhanced by the floodwater, so that flooded vegetation may appear very bright in a SAR image. Even in the absence of dense vegetation or wind, some regions may appear dark because of artefacts due to topography (shadowing), absorption caused by wet snow, and attenuation caused by heavy precipitating clouds (X-band SARs). Examples of the aforementioned effects that may limit the reliability of flood maps will be presented at the conference and some indications to deal with these effects (e.g. presence of vegetation and of artefacts) will be provided.

Fusion of multi-source remote sensing data for agriculture monitoring tasks

NASA Astrophysics Data System (ADS)

Skakun, S.; Franch, B.; Vermote, E.; Roger, J. C.; Becker Reshef, I.; Justice, C. O.; Masek, J. G.; Murphy, E.

2016-12-01

Remote sensing data is essential source of information for enabling monitoring and quantification of crop state at global and regional scales. Crop mapping, state assessment, area estimation and yield forecasting are the main tasks that are being addressed within GEO-GLAM. Efficiency of agriculture monitoring can be improved when heterogeneous multi-source remote sensing datasets are integrated. Here, we present several case studies of utilizing MODIS, Landsat-8 and Sentinel-2 data along with meteorological data (growing degree days - GDD) for winter wheat yield forecasting, mapping and area estimation. Archived coarse spatial resolution data, such as MODIS, VIIRS and AVHRR, can provide daily global observations that coupled with statistical data on crop yield can enable the development of empirical models for timely yield forecasting at national level. With the availability of high-temporal and high spatial resolution Landsat-8 and Sentinel-2A imagery, course resolution empirical yield models can be downscaled to provide yield estimates at regional and field scale. In particular, we present the case study of downscaling the MODIS CMG based generalized winter wheat yield forecasting model to high spatial resolution data sets, namely harmonized Landsat-8 - Sentinel-2A surface reflectance product (HLS). Since the yield model requires corresponding in season crop masks, we propose an automatic approach to extract winter crop maps from MODIS NDVI and MERRA2 derived GDD using Gaussian mixture model (GMM). Validation for the state of Kansas (US) and Ukraine showed that the approach can yield accuracies > 90% without using reference (ground truth) data sets. Another application of yearly derived winter crop maps is their use for stratification purposes within area frame sampling for crop area estimation. In particular, one can simulate the dependence of error (coefficient of variation) on the number of samples and strata size. This approach was used for estimating the area of winter crops in Ukraine for 2013-2016. The GMM-GDD approach is further extended for HLS data to provide automatic winter crop mapping at 30 m resolution for crop yield model and area estimation. In case of persistent cloudiness, addition of Sentinel-1A synthetic aperture radar (SAR) images is explored for automatic winter crop mapping.

Towards the Optimal Pixel Size of dem for Automatic Mapping of Landslide Areas

NASA Astrophysics Data System (ADS)

Pawłuszek, K.; Borkowski, A.; Tarolli, P.

2017-05-01

Determining appropriate spatial resolution of digital elevation model (DEM) is a key step for effective landslide analysis based on remote sensing data. Several studies demonstrated that choosing the finest DEM resolution is not always the best solution. Various DEM resolutions can be applicable for diverse landslide applications. Thus, this study aims to assess the influence of special resolution on automatic landslide mapping. Pixel-based approach using parametric and non-parametric classification methods, namely feed forward neural network (FFNN) and maximum likelihood classification (ML), were applied in this study. Additionally, this allowed to determine the impact of used classification method for selection of DEM resolution. Landslide affected areas were mapped based on four DEMs generated at 1 m, 2 m, 5 m and 10 m spatial resolution from airborne laser scanning (ALS) data. The performance of the landslide mapping was then evaluated by applying landslide inventory map and computation of confusion matrix. The results of this study suggests that the finest scale of DEM is not always the best fit, however working at 1 m DEM resolution on micro-topography scale, can show different results. The best performance was found at 5 m DEM-resolution for FFNN and 1 m DEM resolution for results. The best performance was found to be using 5 m DEM-resolution for FFNN and 1 m DEM resolution for ML classification.

A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

PubMed

Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

2016-01-01

This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

Evaluation of the Clinical Data Dictionary (CiDD)

PubMed Central

Lee, Myung Kyung; Min, Yul Ha; Kim, Younglan; Min, Hyo Ki; Ham, Sung Woo

2010-01-01

Objectives The purpose of the study was to evaluate content coverage and data quality of the Clinical Data Dictionary (CiDD) developed by the Center for Interoperable EHR (CiEHR). Methods A total of 12,994 terms were collected from 98 clinical forms of a tertiary cancer center hospital with 500 beds. After data cleaning, 9,418 terms were mapped with the data items of the CiDD by the research team, and validated by 30 doctors and nurses at the research hospital. Results Mapping results were classified into five categories: lexically mapped; semantically mapped; mapped to either a broader term or a narrower term; mapped to more than one term and not mapped. In terms of coverage, out of 9,418 terms, 6,750 (71.7%) terms were mapped; 4,319 (45.9%) terms were lexically mapped; 2,431 (25.8%) were semantically mapped; 281 (3.0%) terms were mapped to a broader term; 43 (0.5%) were mapped to a narrower term; and 550 (5.8%) were mapped to more than one term. In terms of data quality, the CiDD has problems such as errors in concept namingand representation, redundancy in synonyms, inadequate synonyms, and ambiguity in meaning. Conclusions Although the CiDD has terms covering 72% of local clinical terms, the CiDD can be improved by cleaning up errors and redundancies, adding textual definitions or use cases of the concept, and arranging the concepts in a hierarchy. PMID:21818428

Automatic Thesaurus Generation for an Electronic Community System.

ERIC Educational Resources Information Center

Chen, Hsinchun; And Others

1995-01-01

This research reports an algorithmic approach to the automatic generation of thesauri for electronic community systems. The techniques used include term filtering, automatic indexing, and cluster analysis. The Worm Community System, used by molecular biologists studying the nematode worm C. elegans, was used as the testbed for this research.…

47 CFR 25.161 - Automatic termination of station authorization.

Code of Federal Regulations, 2014 CFR

2014-10-01

...(e) or, in the case of a space station license, an application for extension of the license term has... 47 Telecommunication 2 2014-10-01 2014-10-01 false Automatic termination of station authorization... Station Authorization § 25.161 Automatic termination of station authorization. A station authorization...

Enhancing Automaticity through Task-Based Language Learning

ERIC Educational Resources Information Center

De Ridder, Isabelle; Vangehuchten, Lieve; Gomez, Marta Sesena

2007-01-01

In general terms automaticity could be defined as the subconscious condition wherein "we perform a complex series of tasks very quickly and efficiently, without having to think about the various components and subcomponents of action involved" (DeKeyser 2001: 125). For language learning, Segalowitz (2003) characterised automaticity as a…

Overview of long-term field experiments in Germany - metadata visualization

NASA Astrophysics Data System (ADS)

Muqit Zoarder, Md Abdul; Heinrich, Uwe; Svoboda, Nikolai; Grosse, Meike; Hierold, Wilfried

2017-04-01

BonaRes ("soil as a sustainable resource for the bioeconomy") is conducting to collect data and metadata of agricultural long-term field experiments (LTFE) of Germany. It is funded by the German Federal Ministry of Education and Research (BMBF) under the umbrella of the National Research Strategy BioEconomy 2030. BonaRes consists of ten interdisciplinary research project consortia and the 'BonaRes - Centre for Soil Research'. BonaRes Data Centre is responsible for collecting all LTFE data and regarding metadata into an enterprise database upon higher level of security and visualization of the data and metadata through data portal. In the frame of the BonaRes project, we are compiling an overview of long-term field experiments in Germany that is based on a literature review, the results of the online survey and direct contacts with LTFE operators. Information about research topic, contact person, website, experiment setup and analyzed parameters are collected. Based on the collected LTFE data, an enterprise geodatabase is developed and a GIS-based web-information system about LTFE in Germany is also settled. Various aspects of the LTFE, like experiment type, land-use type, agricultural category and duration of experiment, are presented in thematic maps. This information system is dynamically linked to the database, which means changes in the data directly affect the presentation. An easy data searching option using LTFE name, -location or -operators and the dynamic layer selection ensure a user-friendly web application. Dispersion and visualization of the overlapping LTFE points on the overview map are also challenging and we make it automatized at very zoom level which is also a consistent part of this application. The application provides both, spatial location and meta-information of LTFEs, which is backed-up by an enterprise geodatabase, GIS server for hosting map services and Java script API for web application development.

Automated crystallographic ligand building using the medial axis transform of an electron-density isosurface.

PubMed

Aishima, Jun; Russel, Daniel S; Guibas, Leonidas J; Adams, Paul D; Brunger, Axel T

2005-10-01

Automatic fitting methods that build molecules into electron-density maps usually fail below 3.5 A resolution. As a first step towards addressing this problem, an algorithm has been developed using an approximation of the medial axis to simplify an electron-density isosurface. This approximation captures the central axis of the isosurface with a graph which is then matched against a graph of the molecular model. One of the first applications of the medial axis to X-ray crystallography is presented here. When applied to ligand fitting, the method performs at least as well as methods based on selecting peaks in electron-density maps. Generalization of the method to recognition of common features across multiple contour levels could lead to powerful automatic fitting methods that perform well even at low resolution.

Automatic Detection and Evaluation of Solar Cell Micro-Cracks in Electroluminescence Images Using Matched Filters

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

Spataru, Sergiu; Hacke, Peter; Sera, Dezso

A method for detecting micro-cracks in solar cells using two dimensional matched filters was developed, derived from the electroluminescence intensity profile of typical micro-cracks. We describe the image processing steps to obtain a binary map with the location of the micro-cracks. Finally, we show how to automatically estimate the total length of each micro-crack from these maps, and propose a method to identify severe types of micro-cracks, such as parallel, dendritic, and cracks with multiple orientations. With an optimized threshold parameter, the technique detects over 90 % of cracks larger than 3 cm in length. The method shows great potentialmore » for quantifying micro-crack damage after manufacturing or module transportation for the determination of a module quality criterion for cell cracking in photovoltaic modules.« less

Zebra Crossing Spotter: Automatic Population of Spatial Databases for Increased Safety of Blind Travelers

PubMed Central

Ahmetovic, Dragan; Manduchi, Roberto; Coughlan, James M.; Mascetti, Sergio

2016-01-01

In this paper we propose a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Knowing the location of crosswalks is critical for a blind person planning a trip that includes street crossing. By augmenting existing spatial databases (such as Google Maps or OpenStreetMap) with this information, a blind traveler may make more informed routing decisions, resulting in greater safety during independent travel. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm could also be complemented by a final crowdsourcing validation stage for increased accuracy. PMID:26824080

A CityGML extension for traffic-sign objects that guides the automatic processing of data collected using Mobile Mapping technology

NASA Astrophysics Data System (ADS)

Varela-González, M.; Riveiro, B.; Arias-Sánchez, P.; González-Jorge, H.; Martínez-Sánchez, J.

2014-11-01

The rapid evolution of integral schemes, accounting for geometric and semantic data, has been importantly motivated by the advances in the last decade in mobile laser scanning technology; automation in data processing has also recently influenced the expansion of the new model concepts. This paper reviews some important issues involved in the new paradigms of city 3D modelling: an interoperable schema for city 3D modelling (cityGML) and mobile mapping technology to provide the features that composing the city model. This paper focuses in traffic signs, discussing their characterization using cityGML in order to ease the implementation of LiDAR technology in road management software, as well as analysing some limitations of the current technology in the labour of automatic detection and classification.

Automated kidney detection for 3D ultrasound using scan line searching

NASA Astrophysics Data System (ADS)

Noll, Matthias; Nadolny, Anne; Wesarg, Stefan

2016-04-01

Ultrasound (U/S) is a fast and non-expensive imaging modality that is used for the examination of various anatomical structures, e.g. the kidneys. One important task for automatic organ tracking or computer-aided diagnosis is the identification of the organ region. During this process the exact information about the transducer location and orientation is usually unavailable. This renders the implementation of such automatic methods exceedingly challenging. In this work we like to introduce a new automatic method for the detection of the kidney in 3D U/S images. This novel technique analyses the U/S image data along virtual scan lines. Here, characteristic texture changes when entering and leaving the symmetric tissue regions of the renal cortex are searched for. A subsequent feature accumulation along a second scan direction produces a 2D heat map of renal cortex candidates, from which the kidney location is extracted in two steps. First, the strongest candidate as well as its counterpart are extracted by heat map intensity ranking and renal cortex size analysis. This process exploits the heat map gap caused by the renal pelvis region. Substituting the renal pelvis detection with this combined cortex tissue feature increases the detection robustness. In contrast to model based methods that generate characteristic pattern matches, our method is simpler and therefore faster. An evaluation performed on 61 3D U/S data sets showed, that in 55 cases showing none or minor shadowing the kidney location could be correctly identified.

Automatic Texture Reconstruction of 3d City Model from Oblique Images

NASA Astrophysics Data System (ADS)

Kang, Junhua; Deng, Fei; Li, Xinwei; Wan, Fang

2016-06-01

In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data

NASA Astrophysics Data System (ADS)

Gloger, Oliver; Tönnies, Klaus; Mensel, Birger; Völzke, Henry

2015-11-01

In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches.

Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data.

PubMed

Gloger, Oliver; Tönnies, Klaus; Mensel, Birger; Völzke, Henry

2015-11-21

In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches.

Automatic classification and detection of clinically relevant images for diabetic retinopathy

NASA Astrophysics Data System (ADS)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Automatic Registration of Scanned Satellite Imagery with a Digital Map Data Base.

DTIC Science & Technology

1980-11-01

define the corresponding map window (mW)(procedure TRANSFORMWINDOW MAP A-- S4S Araofms Cpo iin et Serc Area deiatl compAr tal _______________ T...to a LIST-item). LIN: = ( ® code 2621431 ; ® pointer LA to the line list, © pointer PRI; pointer PR2), LIST: = ( Q pointer PL to a LIN-item; n pointer...items where PL -pointers are replaced by a code for the beginning (the number 262140 in our case) and end (the number 26241). Figure 3.2 illustra- tes a

Intelligent process mapping through systematic improvement of heuristics

NASA Technical Reports Server (NTRS)

Ieumwananonthachai, Arthur; Aizawa, Akiko N.; Schwartz, Steven R.; Wah, Benjamin W.; Yan, Jerry C.

1992-01-01

The present system for automatic learning/evaluation of novel heuristic methods applicable to the mapping of communication-process sets on a computer network has its basis in the testing of a population of competing heuristic methods within a fixed time-constraint. The TEACHER 4.1 prototype learning system implemented or learning new postgame analysis heuristic methods iteratively generates and refines the mappings of a set of communicating processes on a computer network. A systematic exploration of the space of possible heuristic methods is shown to promise significant improvement.

Adaptive optimization of reference intensity for optical coherence imaging using galvanometric mirror tilting method

NASA Astrophysics Data System (ADS)

Kim, Ji-hyun; Han, Jae-Ho; Jeong, Jichai

2015-09-01

Integration time and reference intensity are important factors for achieving high signal-to-noise ratio (SNR) and sensitivity in optical coherence tomography (OCT). In this context, we present an adaptive optimization method of reference intensity for OCT setup. The reference intensity is automatically controlled by tilting a beam position using a Galvanometric scanning mirror system. Before sample scanning, the OCT system acquires two dimensional intensity map with normalized intensity and variables in color spaces using false-color mapping. Then, the system increases or decreases reference intensity following the map data for optimization with a given algorithm. In our experiments, the proposed method successfully corrected the reference intensity with maintaining spectral shape, enabled to change integration time without manual calibration of the reference intensity, and prevented image degradation due to over-saturation and insufficient reference intensity. Also, SNR and sensitivity could be improved by increasing integration time with automatic adjustment of the reference intensity. We believe that our findings can significantly aid in the optimization of SNR and sensitivity for optical coherence tomography systems.

Automatic Gleason grading of prostate cancer using SLIM and machine learning

NASA Astrophysics Data System (ADS)

Nguyen, Tan H.; Sridharan, Shamira; Marcias, Virgilia; Balla, Andre K.; Do, Minh N.; Popescu, Gabriel

2016-03-01

In this paper, we present an updated automatic diagnostic procedure for prostate cancer using quantitative phase imaging (QPI). In a recent report [1], we demonstrated the use of Random Forest for image segmentation on prostate cores imaged using QPI. Based on these label maps, we developed an algorithm to discriminate between regions with Gleason grade 3 and 4 prostate cancer in prostatectomy tissue. The Area-Under-Curve (AUC) of 0.79 for the Receiver Operating Curve (ROC) can be obtained for Gleason grade 4 detection in a binary classification between Grade 3 and Grade 4. Our dataset includes 280 benign cases and 141 malignant cases. We show that textural features in phase maps have strong diagnostic values since they can be used in combination with the label map to detect presence or absence of basal cells, which is a strong indicator for prostate carcinoma. A support vector machine (SVM) classifier trained on this new feature vector can classify cancer/non-cancer with an error rate of 0.23 and an AUC value of 0.83.

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images

PubMed Central

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections. PMID:29875639

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images.

PubMed

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections.

Autonomous mental development with selective attention, object perception, and knowledge representation

NASA Astrophysics Data System (ADS)

Ban, Sang-Woo; Lee, Minho

2008-04-01

Knowledge-based clustering and autonomous mental development remains a high priority research topic, among which the learning techniques of neural networks are used to achieve optimal performance. In this paper, we present a new framework that can automatically generate a relevance map from sensory data that can represent knowledge regarding objects and infer new knowledge about novel objects. The proposed model is based on understating of the visual what pathway in our brain. A stereo saliency map model can selectively decide salient object areas by additionally considering local symmetry feature. The incremental object perception model makes clusters for the construction of an ontology map in the color and form domains in order to perceive an arbitrary object, which is implemented by the growing fuzzy topology adaptive resonant theory (GFTART) network. Log-polar transformed color and form features for a selected object are used as inputs of the GFTART. The clustered information is relevant to describe specific objects, and the proposed model can automatically infer an unknown object by using the learned information. Experimental results with real data have demonstrated the validity of this approach.

Approach of automatic 3D geological mapping: the case of the Kovdor phoscorite-carbonatite complex, NW Russia.

PubMed

Kalashnikov, A O; Ivanyuk, G Yu; Mikhailova, J A; Sokharev, V A

2017-07-31

We have developed an approach for automatic 3D geological mapping based on conversion of chemical composition of rocks to mineral composition by logical computation. It allows to calculate mineral composition based on bulk rock chemistry, interpolate the mineral composition in the same way as chemical composition, and, finally, build a 3D geological model. The approach was developed for the Kovdor phoscorite-carbonatite complex containing the Kovdor baddeleyite-apatite-magnetite deposit. We used 4 bulk rock chemistry analyses - Fe magn , P 2 O 5 , CO 2 and SiO 2 . We used four techniques for prediction of rock types - calculation of normative mineral compositions (norms), multiple regression, artificial neural network and developed by logical evaluation. The two latter became the best. As a result, we distinguished 14 types of phoscorites (forsterite-apatite-magnetite-carbonate rock), carbonatite and host rocks. The results show good convergence with our petrographical studies of the deposit, and recent manually built maps. The proposed approach can be used as a tool of a deposit genesis reconstruction and preliminary geometallurgical modelling.

Stacked Multilayer Self-Organizing Map for Background Modeling.

PubMed

Zhao, Zhenjie; Zhang, Xuebo; Fang, Yongchun

2015-09-01

In this paper, a new background modeling method called stacked multilayer self-organizing map background model (SMSOM-BM) is proposed, which presents several merits such as strong representative ability for complex scenarios, easy to use, and so on. In order to enhance the representative ability of the background model and make the parameters learned automatically, the recently developed idea of representative learning (or deep learning) is elegantly employed to extend the existing single-layer self-organizing map background model to a multilayer one (namely, the proposed SMSOM-BM). As a consequence, the SMSOM-BM gains several merits including strong representative ability to learn background model of challenging scenarios, and automatic determination for most network parameters. More specifically, every pixel is modeled by a SMSOM, and spatial consistency is considered at each layer. By introducing a novel over-layer filtering process, we can train the background model layer by layer in an efficient manner. Furthermore, for real-time performance consideration, we have implemented the proposed method using NVIDIA CUDA platform. Comparative experimental results show superior performance of the proposed approach.

Small passenger car transmission test; Ford C4 transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1980-01-01

A 1979 Ford C4 automatic transmission was tested per a passenger car automatic transmission test code (SAE J651b) which required drive performance, coast performance, and no load test conditions. Under these test conditions, the transmission attained maximum efficiencies in the mid-eighty percent range for both drive performance tests and coast performance tests. The major results of this test (torque, speed, and efficiency curves) are presented. Graphs map the complete performance characteristics for the Ford C4 transmission.

Classifying forest and nonforest land on space photographs

NASA Technical Reports Server (NTRS)

Aldrich, R. C.

1970-01-01

Although the research reported is in its preliminary stages, results show that: (1) infrared color film is the best single multiband sensor available; (2) there is a good possibility that forest can be separated from all nonforest land uses by microimage evaluation techniques on IR color film coupled with B/W infrared and panchromatic films; and (3) discrimination of forest and nonforest classes is possible by either of two methods: interpreters with appropriate viewing and mapping instruments, or programmable automatic scanning microdensitometers and automatic data processing.

Citrus Inventory

NASA Technical Reports Server (NTRS)

1994-01-01

An aerial color infrared (CIR) mapping system developed by Kennedy Space Center enables Florida's Charlotte County to accurately appraise its citrus groves while reducing appraisal costs. The technology was further advanced by development of a dual video system making it possible to simultaneously view images of the same area and detect changes. An image analysis system automatically surveys and photo interprets grove images as well as automatically counts trees and reports totals. The system, which saves both time and money, has potential beyond citrus grove valuation.

Use of an automatic resistivity system for detecting abandoned mine workings

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

Peters, W.R.; Burdick, R.G.

1983-01-01

A high-resolution earth resistivity system has been designed and constructed for use as a means of detecting abandoned coal mine workings. The automatic pole-dipole earth resistivity technique has already been applied to the detection of subsurface voids for military applications. The hardware and software of the system are described, together with applications for surveying and mapping abandoned coal mine workings. Field tests are presented to illustrate the detection of both air-filled and water-filled mine workings.

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

Yuan, Jiangye

Up-to-date maps of installed solar photovoltaic panels are a critical input for policy and financial assessment of solar distributed generation. However, such maps for large areas are not available. With high coverage and low cost, aerial images enable large-scale mapping, bit it is highly difficult to automatically identify solar panels from images, which are small objects with varying appearances dispersed in complex scenes. We introduce a new approach based on deep convolutional networks, which effectively learns to delineate solar panels in aerial scenes. The approach has successfully mapped solar panels in imagery covering 200 square kilometers in two cities, usingmore » only 12 square kilometers of training data that are manually labeled.« less

LANDSAT and radar mapping of intrusive rocks in SE-Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dossantos, A. R.; Dosanjos, C. E.; Moreira, J. C.; Barbosa, M. P.; Veneziani, P.

1982-01-01

The feasibility of intrusive rock mapping was investigated and criteria for regional geological mapping established at the scale of 1:500,00 in polycyclic and polymetamorphic areas using the logic method of photointerpretation of LANDSAT imagery and radar from the RADAMBRASIL project. The spectral behavior of intrusive rocks, was evaluated using the interactive multispectral image analysis system (Image-100). The region of Campos (city) in northern Rio de Janeiro State was selected as the study area and digital imagery processing and pattern recognition techniques were applied. Various maps at the 2:250,000 scale were obtained to evaluate the results of automatic data processing.

Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories

NASA Astrophysics Data System (ADS)

Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.

2016-06-01

For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

Calculation of three-dimensional, inviscid, supersonic, steady flows

NASA Technical Reports Server (NTRS)

Moretti, G.

1981-01-01

A detailed description of a computational program for the evaluation of three dimensional supersonic, inviscid, steady flow past airplanes is presented. Emphasis was put on how a powerful, automatic mapping technique is coupled to the fluid mechanical analysis. Each of the three constituents of the analysis (body geometry, mapping technique, and gas dynamical effects) was carefully coded and described. Results of computations based on sample geometrics and discussions are also presented.

Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps.

PubMed

Fernández-Esparrach, Glòria; Bernal, Jorge; López-Cerón, Maria; Córdova, Henry; Sánchez-Montes, Cristina; Rodríguez de Miguel, Cristina; Sánchez, Francisco Javier

2016-09-01

Polyp miss-rate is a drawback of colonoscopy that increases significantly for small polyps. We explored the efficacy of an automatic computer-vision method for polyp detection. Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps that represent the likelihood of the presence of a polyp. In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. The mean of the maximum values on the energy map was higher for frames with polyps than without (P < 0.001). Performance improved in high quality frames (AUC = 0.79 [95 %CI 0.70 - 0.87] vs. 0.75 [95 %CI 0.66 - 0.83]). With 3.75 set as the maximum threshold value, sensitivity and specificity for the detection of polyps were 70.4 % (95 %CI 60.3 % - 80.8 %) and 72.4 % (95 %CI 61.6 % - 84.6 %), respectively. Energy maps performed well for colonic polyp detection, indicating their potential applicability in clinical practice. © Georg Thieme Verlag KG Stuttgart · New York.

Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, Y.; Li, Q.

2017-09-01

Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

Polarization transformation as an algorithm for automatic generalization and quality assessment

NASA Astrophysics Data System (ADS)

Qian, Haizhong; Meng, Liqiu

2007-06-01

Since decades it has been a dream of cartographers to computationally mimic the generalization processes in human brains for the derivation of various small-scale target maps or databases from a large-scale source map or database. This paper addresses in a systematic way the polarization transformation (PT) - a new algorithm that serves both the purpose of automatic generalization of discrete features and the quality assurance. By means of PT, two dimensional point clusters or line networks in the Cartesian system can be transformed into a polar coordinate system, which then can be unfolded as a single spectrum line r = f(α), where r and a stand for the polar radius and the polar angle respectively. After the transformation, the original features will correspond to nodes on the spectrum line delimited between 0° and 360° along the horizontal axis, and between the minimum and maximum polar radius along the vertical axis. Since PT is a lossless transformation, it allows a straighforward analysis and comparison of the original and generalized distributions, thus automatic generalization and quality assurance can be down in this way. Examples illustrate that PT algorithm meets with the requirement of generalization of discrete spatial features and is more scientific.

Adaptive video-based vehicle classification technique for monitoring traffic : [executive summary].

DOT National Transportation Integrated Search

2015-08-01

Federal Highway Administration (FHWA) recommends axle-based classification standards to map : passenger vehicles, single unit trucks, and multi-unit trucks, at Automatic Traffic Recorder (ATR) stations : statewide. Many state Departments of Transport...

Clustering of color map pixels: an interactive approach

NASA Astrophysics Data System (ADS)

Moon, Yiu Sang; Luk, Franklin T.; Yuen, K. N.; Yeung, Hoi Wo

2003-12-01

The demand for digital maps continues to arise as mobile electronic devices become more popular nowadays. Instead of creating the entire map from void, we may convert a scanned paper map into a digital one. Color clustering is the very first step of the conversion process. Currently, most of the existing clustering algorithms are fully automatic. They are fast and efficient but may not work well in map conversion because of the numerous ambiguous issues associated with printed maps. Here we introduce two interactive approaches for color clustering on the map: color clustering with pre-calculated index colors (PCIC) and color clustering with pre-calculated color ranges (PCCR). We also introduce a memory model that could enhance and integrate different image processing techniques for fine-tuning the clustering results. Problems and examples of the algorithms are discussed in the paper.

The Masked Semantic Priming Effect Is Task Dependent: Reconsidering the Automatic Spreading Activation Process

ERIC Educational Resources Information Center

de Wit, Bianca; Kinoshita, Sachiko

2015-01-01

Semantic priming effects are popularly explained in terms of an automatic spreading activation process, according to which the activation of a node in a semantic network spreads automatically to interconnected nodes, preactivating a semantically related word. It is expected from this account that semantic priming effects should be routinely…

Impact of translation on named-entity recognition in radiology texts

PubMed Central

Pedro, Vasco

2017-01-01

Abstract Radiology reports describe the results of radiography procedures and have the potential of being a useful source of information which can bring benefits to health care systems around the world. One way to automatically extract information from the reports is by using Text Mining tools. The problem is that these tools are mostly developed for English and reports are usually written in the native language of the radiologist, which is not necessarily English. This creates an obstacle to the sharing of Radiology information between different communities. This work explores the solution of translating the reports to English before applying the Text Mining tools, probing the question of what translation approach should be used. We created MRRAD (Multilingual Radiology Research Articles Dataset), a parallel corpus of Portuguese research articles related to Radiology and a number of alternative translations (human, automatic and semi-automatic) to English. This is a novel corpus which can be used to move forward the research on this topic. Using MRRAD we studied which kind of automatic or semi-automatic translation approach is more effective on the Named-entity recognition task of finding RadLex terms in the English version of the articles. Considering the terms extracted from human translations as our gold standard, we calculated how similar to this standard were the terms extracted using other translations. We found that a completely automatic translation approach using Google leads to F-scores (between 0.861 and 0.868, depending on the extraction approach) similar to the ones obtained through a more expensive semi-automatic translation approach using Unbabel (between 0.862 and 0.870). To better understand the results we also performed a qualitative analysis of the type of errors found in the automatic and semi-automatic translations. Database URL: https://github.com/lasigeBioTM/MRRAD PMID:29220455

Development of a Global Agricultural Hotspot Detection and Early Warning System

NASA Astrophysics Data System (ADS)

Lemoine, G.; Rembold, F.; Urbano, F.; Csak, G.

2015-12-01

The number of web based platforms for crop monitoring has grown rapidly over the last years and anomaly maps and time profiles of remote sensing derived indicators can be accessed online thanks to a number of web based portals. However, while these systems make available a large amount of crop monitoring data to the agriculture and food security analysts, there is no global platform which provides agricultural production hotspot warning in a highly automatic and timely manner. Therefore a web based system providing timely warning evidence as maps and short narratives is currently under development by the Joint Research Centre. The system (called "HotSpot Detection System of Agriculture Production Anomalies", HSDS) will focus on water limited agricultural systems worldwide. The automatic analysis of relevant meteorological and vegetation indicators at selected administrative units (Gaul 1 level) will trigger warning messages for the areas where anomalous conditions are observed. The level of warning (ranging from "watch" to "alert") will depend on the nature and number of indicators for which an anomaly is detected. Information regarding the extent of the agricultural areas concerned by the anomaly and the progress of the agricultural season will complement the warning label. In addition, we are testing supplementary detailed information from other sources for the areas triggering a warning. These regard the automatic web-based and food security-tailored analysis of media (using the JRC Media Monitor semantic search engine) and the automatic detection of active crop area using Sentinel 1, upcoming Sentinel-2 and Landsat 8 imagery processed in Google Earth Engine. The basic processing will be fully automated and updated every 10 days exploiting low resolution rainfall estimates and satellite vegetation indices. Maps, trend graphs and statistics accompanied by short narratives edited by a team of crop monitoring experts, will be made available on the website on a monthly basis.

Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature

NASA Astrophysics Data System (ADS)

Akay, S. S.; Sertel, E.

2016-06-01

Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was conducted by creating a confusion matrix to illustrate the thematic accuracy of each class.

fMRat: an extension of SPM for a fully automatic analysis of rodent brain functional magnetic resonance series.

PubMed

Chavarrías, Cristina; García-Vázquez, Verónica; Alemán-Gómez, Yasser; Montesinos, Paula; Pascau, Javier; Desco, Manuel

2016-05-01

The purpose of this study was to develop a multi-platform automatic software tool for full processing of fMRI rodent studies. Existing tools require the usage of several different plug-ins, a significant user interaction and/or programming skills. Based on a user-friendly interface, the tool provides statistical parametric brain maps (t and Z) and percentage of signal change for user-provided regions of interest. The tool is coded in MATLAB (MathWorks(®)) and implemented as a plug-in for SPM (Statistical Parametric Mapping, the Wellcome Trust Centre for Neuroimaging). The automatic pipeline loads default parameters that are appropriate for preclinical studies and processes multiple subjects in batch mode (from images in either Nifti or raw Bruker format). In advanced mode, all processing steps can be selected or deselected and executed independently. Processing parameters and workflow were optimized for rat studies and assessed using 460 male-rat fMRI series on which we tested five smoothing kernel sizes and three different hemodynamic models. A smoothing kernel of FWHM = 1.2 mm (four times the voxel size) yielded the highest t values at the somatosensorial primary cortex, and a boxcar response function provided the lowest residual variance after fitting. fMRat offers the features of a thorough SPM-based analysis combined with the functionality of several SPM extensions in a single automatic pipeline with a user-friendly interface. The code and sample images can be downloaded from https://github.com/HGGM-LIM/fmrat .

Weakly supervised automatic segmentation and 3D modeling of the knee joint from MR images

NASA Astrophysics Data System (ADS)

Amami, Amal; Ben Azouz, Zouhour

2013-12-01

Automatic segmentation and 3D modeling of the knee joint from MR images, is a challenging task. Most of the existing techniques require the tedious manual segmentation of a training set of MRIs. We present an approach that necessitates the manual segmentation of one MR image. It is based on a volumetric active appearance model. First, a dense tetrahedral mesh is automatically created on a reference MR image that is arbitrary selected. Second, a pairwise non-rigid registration between each MRI from a training set and the reference MRI is computed. The non-rigid registration is based on a piece-wise affine deformation using the created tetrahedral mesh. The minimum description length is then used to bring all the MR images into a correspondence. An average image and tetrahedral mesh, as well as a set of main modes of variations, are generated using the established correspondence. Any manual segmentation of the average MRI can be mapped to other MR images using the AAM. The proposed approach has the advantage of simultaneously generating 3D reconstructions of the surface as well as a 3D solid model of the knee joint. The generated surfaces and tetrahedral meshes present the interesting property of fulfilling a correspondence between different MR images. This paper shows preliminary results of the proposed approach. It demonstrates the automatic segmentation and 3D reconstruction of a knee joint obtained by mapping a manual segmentation of a reference image.

The effort to close the gap: Tracking the development of illusory contour processing from childhood to adulthood with high-density electrical mapping

PubMed Central

Altschuler, Ted S.; Molholm, Sophie; Butler, John S.; Mercier, Manuel R.; Brandwein, Alice B.; Foxe, John J.

2014-01-01

The adult human visual system can efficiently fill-in missing object boundaries when low-level information from the retina is incomplete, but little is known about how these processes develop across childhood. A decade of visual-evoked potential (VEP) studies has produced a theoretical model identifying distinct phases of contour completion in adults. The first, termed a perceptual phase, occurs from approximately 100-200 ms and is associated with automatic boundary completion. The second is termed a conceptual phase occurring between 230-400 ms. The latter has been associated with the analysis of ambiguous objects which seem to require more effort to complete. The electrophysiological markers of these phases have both been localized to the lateral occipital complex, a cluster of ventral visual stream brain regions associated with object-processing. We presented Kanizsa-type illusory contour stimuli, often used for exploring contour completion processes, to neurotypical persons ages 6-31 (N= 63), while parametrically varying the spatial extent of these induced contours, in order to better understand how filling-in processes develop across childhood and adolescence. Our results suggest that, while adults complete contour boundaries in a single discrete period during the automatic perceptual phase, children display an immature response pattern - engaging in more protracted processing across both timeframes and appearing to recruit more widely distributed regions which resemble those evoked during adult processing of higher-order ambiguous figures. However, children older than 5 years of age were remarkably like adults in that the effects of contour processing were invariant to manipulation of contour extent. PMID:24365674

Combining Quantitative Susceptibility Mapping with Automatic Zero Reference (QSM0) and Myelin Water Fraction Imaging to Quantify Iron-Related Myelin Damage in Chronic Active MS Lesions.

PubMed

Yao, Y; Nguyen, T D; Pandya, S; Zhang, Y; Hurtado Rúa, S; Kovanlikaya, I; Kuceyeski, A; Liu, Z; Wang, Y; Gauthier, S A

2018-02-01

A hyperintense rim on susceptibility in chronic MS lesions is consistent with iron deposition, and the purpose of this study was to quantify iron-related myelin damage within these lesions as compared with those without rim. Forty-six patients had 2 longitudinal quantitative susceptibility mapping with automatic zero reference scans with a mean interval of 28.9 ± 11.4 months. Myelin water fraction mapping by using fast acquisition with spiral trajectory and T2 prep was obtained at the second time point to measure myelin damage. Mixed-effects models were used to assess lesion quantitative susceptibility mapping and myelin water fraction values. Quantitative susceptibility mapping scans were on average 6.8 parts per billion higher in 116 rim-positive lesions compared with 441 rim-negative lesions ( P < .001). All rim-positive lesions retained a hyperintense rim over time, with increasing quantitative susceptibility mapping values of both the rim and core regions ( P < .001). Quantitative susceptibility mapping scans and myelin water fraction in rim-positive lesions decreased from rim to core, which is consistent with rim iron deposition. Whole lesion myelin water fractions for rim-positive and rim-negative lesions were 0.055 ± 0.07 and 0.066 ± 0.04, respectively. In the mixed-effects model, rim-positive lesions had on average 0.01 lower myelin water fraction compared with rim-negative lesions ( P < .001). The volume of the rim at the initial quantitative susceptibility mapping scan was negatively associated with follow-up myelin water fraction ( P < .01). Quantitative susceptibility mapping rim-positive lesions maintained a hyperintense rim, increased in susceptibility, and had more myelin damage compared with rim-negative lesions. Our results are consistent with the identification of chronic active MS lesions and may provide a target for therapeutic interventions to reduce myelin damage. © 2018 by American Journal of Neuroradiology.

RCrane: semi-automated RNA model building.

PubMed

Keating, Kevin S; Pyle, Anna Marie

2012-08-01

RNA crystals typically diffract to much lower resolutions than protein crystals. This low-resolution diffraction results in unclear density maps, which cause considerable difficulties during the model-building process. These difficulties are exacerbated by the lack of computational tools for RNA modeling. Here, RCrane, a tool for the partially automated building of RNA into electron-density maps of low or intermediate resolution, is presented. This tool works within Coot, a common program for macromolecular model building. RCrane helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RCrane then allows the crystallographer to review the newly built structure and select alternative backbone conformations where desired. This tool can also be used to automatically correct the backbone structure of previously built nucleotides. These automated corrections can fix incorrect sugar puckers, steric clashes and other structural problems.

larvalign: Aligning Gene Expression Patterns from the Larval Brain of Drosophila melanogaster.

PubMed

Muenzing, Sascha E A; Strauch, Martin; Truman, James W; Bühler, Katja; Thum, Andreas S; Merhof, Dorit

2018-01-01

The larval brain of the fruit fly Drosophila melanogaster is a small, tractable model system for neuroscience. Genes for fluorescent marker proteins can be expressed in defined, spatially restricted neuron populations. Here, we introduce the methods for 1) generating a standard template of the larval central nervous system (CNS), 2) spatial mapping of expression patterns from different larvae into a reference space defined by the standard template. We provide a manually annotated gold standard that serves for evaluation of the registration framework involved in template generation and mapping. A method for registration quality assessment enables the automatic detection of registration errors, and a semi-automatic registration method allows one to correct registrations, which is a prerequisite for a high-quality, curated database of expression patterns. All computational methods are available within the larvalign software package: https://github.com/larvalign/larvalign/releases/tag/v1.0.

Wheat cultivation: Identification and estimation of areas using LANDSAT data

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Mendonca, F. J.; Cottrell, D. A.; Tardin, A. T.; Lee, D. C. L.; Shimabukuro, Y. E.; Moreira, M. A.; Delimaefernandocelsosoaresmaia, A. M.

1981-01-01

The feasibility of using automatically processed multispectral data obtained from LANDSAT to identify wheat and estimate the areas planted with this grain was investigated. Three 20 km by 40 km segments in a wheat growing region of Rio Grande do Sul were aerially photographed using type 2443 Aerochrome film. Three maps corresponding to each segment were obtained from the analysis of the photographs which identified wheat, barley, fallow land, prepared soil, forests, and reforested land. Using basic information about the fields and maps made from the photographed areas, an automatic classification of wheat was made using MSS data from two different periods: July to September and July to October 1979. Results show that orbital data is not only useful in characterizing the growth of wheat, but also provides information of the intensity and extent of adverse climate which affects cultivation. The temporal and spatial characteristics of LANDSAR data are also demonstrated.

Different Manhattan project: automatic statistical model generation

NASA Astrophysics Data System (ADS)

Yap, Chee Keng; Biermann, Henning; Hertzmann, Aaron; Li, Chen; Meyer, Jon; Pao, Hsing-Kuo; Paxia, Salvatore

2002-03-01

We address the automatic generation of large geometric models. This is important in visualization for several reasons. First, many applications need access to large but interesting data models. Second, we often need such data sets with particular characteristics (e.g., urban models, park and recreation landscape). Thus we need the ability to generate models with different parameters. We propose a new approach for generating such models. It is based on a top-down propagation of statistical parameters. We illustrate the method in the generation of a statistical model of Manhattan. But the method is generally applicable in the generation of models of large geographical regions. Our work is related to the literature on generating complex natural scenes (smoke, forests, etc) based on procedural descriptions. The difference in our approach stems from three characteristics: modeling with statistical parameters, integration of ground truth (actual map data), and a library-based approach for texture mapping.

Automatic analysis and classification of surface electromyography.

PubMed

Abou-Chadi, F E; Nashar, A; Saad, M

2001-01-01

In this paper, parametric modeling of surface electromyography (EMG) algorithms that facilitates automatic SEMG feature extraction and artificial neural networks (ANN) are combined for providing an integrated system for the automatic analysis and diagnosis of myopathic disorders. Three paradigms of ANN were investigated: the multilayer backpropagation algorithm, the self-organizing feature map algorithm and a probabilistic neural network model. The performance of the three classifiers was compared with that of the old Fisher linear discriminant (FLD) classifiers. The results have shown that the three ANN models give higher performance. The percentage of correct classification reaches 90%. Poorer diagnostic performance was obtained from the FLD classifier. The system presented here indicates that surface EMG, when properly processed, can be used to provide the physician with a diagnostic assist device.

Validation of the "HAMP" mapping algorithm: a tool for long-term trauma research studies in the conversion of AIS 2005 to AIS 98.

PubMed

Adams, Derk; Schreuder, Astrid B; Salottolo, Kristin; Settell, April; Goss, J Richard

2011-07-01

There are significant changes in the abbreviated injury scale (AIS) 2005 system, which make it impractical to compare patients coded in AIS version 98 with patients coded in AIS version 2005. Harborview Medical Center created a computer algorithm "Harborview AIS Mapping Program (HAMP)" to automatically convert AIS 2005 to AIS 98 injury codes. The mapping was validated using 6 months of double-coded patient injury records from a Level I Trauma Center. HAMP was used to determine how closely individual AIS and injury severity scores (ISS) were converted from AIS 2005 to AIS 98 versions. The kappa statistic was used to measure the agreement between manually determined codes and HAMP-derived codes. Seven hundred forty-nine patient records were used for validation. For the conversion of AIS codes, the measure of agreement between HAMP and manually determined codes was [kappa] = 0.84 (95% confidence interval, 0.82-0.86). The algorithm errors were smaller in magnitude than the manually determined coding errors. For the conversion of ISS, the agreement between HAMP versus manually determined ISS was [kappa] = 0.81 (95% confidence interval, 0.78-0.84). The HAMP algorithm successfully converted injuries coded in AIS 2005 to AIS 98. This algorithm will be useful when comparing trauma patient clinical data across populations coded in different versions, especially for longitudinal studies.

Relationships among Rapid Digit Naming, Phonological Processing, Motor Automaticity, and Speech Perception in Poor, Average, and Good Readers and Spellers

ERIC Educational Resources Information Center

Savage, Robert S.; Frederickson, Norah; Goodwin, Roz; Patni, Ulla; Smith, Nicola; Tuersley, Louise

2005-01-01

In this article, we explore the relationship between rapid automatized naming (RAN) and other cognitive processes among below-average, average, and above-average readers and spellers. Nonsense word reading, phonological awareness, RAN, automaticity of balance, speech perception, and verbal short-term and working memory were measured. Factor…

Resolving Quasi-Synonym Relationships in Automatic Thesaurus Construction Using Fuzzy Rough Sets and an Inverse Term Frequency Similarity Function

ERIC Educational Resources Information Center

Davault, Julius M., III.

2009-01-01

One of the problems associated with automatic thesaurus construction is with determining the semantic relationship between word pairs. Quasi-synonyms provide a type of equivalence relationship: words are similar only for purposes of information retrieval. Determining such relationships in a thesaurus is hard to achieve automatically. The term…

Lockheed L-1101 avionic flight control redundant systems

NASA Technical Reports Server (NTRS)

Throndsen, E. O.

1976-01-01

The Lockheed L-1011 automatic flight control systems - yaw stability augmentation and automatic landing - are described in terms of their redundancies. The reliability objectives for these systems are discussed and related to in-service experience. In general, the availability of the stability augmentation system is higher than the original design requirement, but is commensurate with early estimates. The in-service experience with automatic landing is not sufficient to provide verification of Category 3 automatic landing system estimated availability.

Automatic learning-based beam angle selection for thoracic IMRT

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

Amit, Guy; Marshall, Andrea; Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca

Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationallymore » efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume coverage and organ at risk sparing and were superior over plans produced with fixed sets of common beam angles. The great majority of the automatic plans (93%) were approved as clinically acceptable by three radiation therapy specialists. Conclusions: The results demonstrated the feasibility of utilizing a learning-based approach for automatic selection of beam angles in thoracic IMRT planning. The proposed method may assist in reducing the manual planning workload, while sustaining plan quality.« less

Management of natural resources through automatic cartographic inventory

NASA Technical Reports Server (NTRS)

Rey, P. (Principal Investigator); Gourinard, Y.; Cambou, F.

1972-01-01

The author has identified the following significant results. Return beam vidicon and multispectral band scanner imagery will be correlated with existing vegetation and geologic maps of southern France and northern Spain to develop correspondence codes between map units and space data. Microclimate data from six stations, spectral measurements from a few meters to 2 km using ERTS-type filter and spectrometers, and leaf reflectance measurements will be obtained to assist in correlation studies.

SPARK: Adapting Keyword Query to Semantic Search

NASA Astrophysics Data System (ADS)

Zhou, Qi; Wang, Chong; Xiong, Miao; Wang, Haofen; Yu, Yong

Semantic search promises to provide more accurate result than present-day keyword search. However, progress with semantic search has been delayed due to the complexity of its query languages. In this paper, we explore a novel approach of adapting keywords to querying the semantic web: the approach automatically translates keyword queries into formal logic queries so that end users can use familiar keywords to perform semantic search. A prototype system named 'SPARK' has been implemented in light of this approach. Given a keyword query, SPARK outputs a ranked list of SPARQL queries as the translation result. The translation in SPARK consists of three major steps: term mapping, query graph construction and query ranking. Specifically, a probabilistic query ranking model is proposed to select the most likely SPARQL query. In the experiment, SPARK achieved an encouraging translation result.

Elliptic generation of composite three-dimensional grids about realistic aircraft

NASA Technical Reports Server (NTRS)

Sorenson, R. L.

1986-01-01

An elliptic method for generating composite grids about realistic aircraft is presented. A body-conforming grid is first generated about the entire aircraft by the solution of Poisson's differential equation. This grid has relatively coarse spacing, and it covers the entire physical domain. At boundary surfaces, cell size is controlled and cell skewness is nearly eliminated by inhomogeneous terms, which are found automatically by the program. Certain regions of the grid in which high gradients are expected, and which map into rectangular solids in the computational domain, are then designated for zonal refinement. Spacing in the zonal grids is reduced by adding points with a simple, algebraic scheme. Details of the grid generation method are presented along with results of the present application, a wing-body configuration based on the F-16 fighter aircraft.

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

Peffer, Therese; Blumstein, Carl; Culler, David

The Project uses state-of-the-art computer science to extend the benefits of Building Automation Systems (BAS) typically found in large buildings (>100,000 square foot) to medium-sized commercial buildings (<50,000 sq ft). The BAS developed in this project, termed OpenBAS, uses an open-source and open software architecture platform, user interface, and plug-and-play control devices to facilitate adoption of energy efficiency strategies in the commercial building sector throughout the United States. At the heart of this “turn key” BAS is the platform with three types of controllers—thermostat, lighting controller, and general controller—that are easily “discovered” by the platform in a plug-and-play fashion. Themore » user interface showcases the platform and provides the control system set-up, system status display and means of automatically mapping the control points in the system.« less

Anomaly Detection for Beam Loss Maps in the Large Hadron Collider

NASA Astrophysics Data System (ADS)

Valentino, Gianluca; Bruce, Roderik; Redaelli, Stefano; Rossi, Roberto; Theodoropoulos, Panagiotis; Jaster-Merz, Sonja

2017-07-01

In the LHC, beam loss maps are used to validate collimator settings for cleaning and machine protection. This is done by monitoring the loss distribution in the ring during infrequent controlled loss map campaigns, as well as in standard operation. Due to the complexity of the system, consisting of more than 50 collimators per beam, it is difficult to identify small changes in the collimation hierarchy, which may be due to setting errors or beam orbit drifts with such methods. A technique based on Principal Component Analysis and Local Outlier Factor is presented to detect anomalies in the loss maps and therefore provide an automatic check of the collimation hierarchy.

Automatic detection and decoding of honey bee waggle dances.

PubMed

Wario, Fernando; Wild, Benjamin; Rojas, Raúl; Landgraf, Tim

2017-01-01

The waggle dance is one of the most popular examples of animal communication. Forager bees direct their nestmates to profitable resources via a complex motor display. Essentially, the dance encodes the polar coordinates to the resource in the field. Unemployed foragers follow the dancer's movements and then search for the advertised spots in the field. Throughout the last decades, biologists have employed different techniques to measure key characteristics of the waggle dance and decode the information it conveys. Early techniques involved the use of protractors and stopwatches to measure the dance orientation and duration directly from the observation hive. Recent approaches employ digital video recordings and manual measurements on screen. However, manual approaches are very time-consuming. Most studies, therefore, regard only small numbers of animals in short periods of time. We have developed a system capable of automatically detecting, decoding and mapping communication dances in real-time. In this paper, we describe our recording setup, the image processing steps performed for dance detection and decoding and an algorithm to map dances to the field. The proposed system performs with a detection accuracy of 90.07%. The decoded waggle orientation has an average error of -2.92° (± 7.37°), well within the range of human error. To evaluate and exemplify the system's performance, a group of bees was trained to an artificial feeder, and all dances in the colony were automatically detected, decoded and mapped. The system presented here is the first of this kind made publicly available, including source code and hardware specifications. We hope this will foster quantitative analyses of the honey bee waggle dance.

Project of Near-Real-Time Generation of ShakeMaps and a New Hazard Map in Austria

NASA Astrophysics Data System (ADS)

Jia, Yan; Weginger, Stefan; Horn, Nikolaus; Hausmann, Helmut; Lenhardt, Wolfgang

2016-04-01

Target-orientated prevention and effective crisis management can reduce or avoid damage and save lives in case of a strong earthquake. To achieve this goal, a project for automatic generated ShakeMaps (maps of ground motion and shaking intensity) and updating the Austrian hazard map was started at ZAMG (Zentralanstalt für Meteorologie und Geodynamik) in 2015. The first goal of the project is set for a near-real-time generation of ShakeMaps following strong earthquakes in Austria to provide rapid, accurate and official information to support the governmental crisis management. Using newly developed methods and software by SHARE (Seismic Hazard Harmonization in Europe) and GEM (Global Earthquake Model), which allows a transnational analysis at European level, a new generation of Austrian hazard maps will be ultimately calculated. More information and a status of our project will be given by this presentation.

KEGGParser: parsing and editing KEGG pathway maps in Matlab.

PubMed

Arakelyan, Arsen; Nersisyan, Lilit

2013-02-15

KEGG pathway database is a collection of manually drawn pathway maps accompanied with KGML format files intended for use in automatic analysis. KGML files, however, do not contain the required information for complete reproduction of all the events indicated in the static image of a pathway map. Several parsers and editors of KEGG pathways exist for processing KGML files. We introduce KEGGParser-a MATLAB based tool for KEGG pathway parsing, semiautomatic fixing, editing, visualization and analysis in MATLAB environment. It also works with Scilab. The source code is available at http://www.mathworks.com/matlabcentral/fileexchange/37561.

GenomeVx: simple web-based creation of editable circular chromosome maps.

PubMed

Conant, Gavin C; Wolfe, Kenneth H

2008-03-15

We describe GenomeVx, a web-based tool for making editable, publication-quality, maps of mitochondrial and chloroplast genomes and of large plasmids. These maps show the location of genes and chromosomal features as well as a position scale. The program takes as input either raw feature positions or GenBank records. In the latter case, features are automatically extracted and colored, an example of which is given. Output is in the Adobe Portable Document Format (PDF) and can be edited by programs such as Adobe Illustrator. GenomeVx is available at http://wolfe.gen.tcd.ie/GenomeVx

MO-F-CAMPUS-J-04: Tissue Segmentation-Based MR Electron Density Mapping Method for MR-Only Radiation Treatment Planning of Brain

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

Yu, H; Lee, Y; Ruschin, M

2015-06-15

Purpose: Automatically derive electron density of tissues using MR images and generate a pseudo-CT for MR-only treatment planning of brain tumours. Methods: 20 stereotactic radiosurgery (SRS) patients’ T1-weighted MR images and CT images were retrospectively acquired. First, a semi-automated tissue segmentation algorithm was developed to differentiate tissues with similar MR intensities and large differences in electron densities. The method started with approximately 12 slices of manually contoured spatial regions containing sinuses and airways, then air, bone, brain, cerebrospinal fluid (CSF) and eyes were automatically segmented using edge detection and anatomical information including location, shape, tissue uniformity and relative intensity distribution.more » Next, soft tissues - muscle and fat were segmented based on their relative intensity histogram. Finally, intensities of voxels in each segmented tissue were mapped into their electron density range to generate pseudo-CT by linearly fitting their relative intensity histograms. Co-registered CT was used as a ground truth. The bone segmentations of pseudo-CT were compared with those of co-registered CT obtained by using a 300HU threshold. The average distances between voxels on external edges of the skull of pseudo-CT and CT in three axial, coronal and sagittal slices with the largest width of skull were calculated. The mean absolute electron density (in Hounsfield unit) difference of voxels in each segmented tissues was calculated. Results: The average of distances between voxels on external skull from pseudo-CT and CT were 0.6±1.1mm (mean±1SD). The mean absolute electron density differences for bone, brain, CSF, muscle and fat are 78±114 HU, and 21±8 HU, 14±29 HU, 57±37 HU, and 31±63 HU, respectively. Conclusion: The semi-automated MR electron density mapping technique was developed using T1-weighted MR images. The generated pseudo-CT is comparable to that of CT in terms of anatomical position of tissues and similarity of electron density assignment. This method can allow MR-only treatment planning.« less

Automatic intersection map generation task 10 report.

DOT National Transportation Integrated Search

2016-02-29

This report describes the work conducted in Task 10 of the V2I Safety Applications Development Project. The work was performed by the University of Michigan Transportation Research Institute (UMTRI) under contract to the Crash Avoidance Metrics Partn...

Mission Assurance: Issues and Challenges

DTIC Science & Technology

2010-07-15

JFQ), Summer 1995. [9] Alberts , C.J. & Dorofee, A.J., “Mission Assurance Analysis Protocol (MAAP): Assessing Risk in Complex Environments... CAMUS : Automatically Mapping Cyber Assets to Missions and Users,” Proc. of the 2010 Military Communications Conference (MILCOM 2009), 2009. [23

TU-F-BRF-03: Effect of Radiation Therapy Planning Scan Registration On the Dose in Lung Cancer Patient CT Scans

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

Cunliffe, A; Contee, C; White, B

Purpose: To characterize the effect of deformable registration of serial computed tomography (CT) scans on the radiation dose calculated from a treatment planning scan. Methods: Eighteen patients who received curative doses (≥60Gy, 2Gy/fraction) of photon radiation therapy for lung cancer treatment were retrospectively identified. For each patient, a diagnostic-quality pre-therapy (4–75 days) CT scan and a treatment planning scan with an associated dose map calculated in Pinnacle were collected. To establish baseline correspondence between scan pairs, a researcher manually identified anatomically corresponding landmark point pairs between the two scans. Pre-therapy scans were co-registered with planning scans (and associated dose maps)more » using the Plastimatch demons and Fraunhofer MEVIS deformable registration algorithms. Landmark points in each pretherapy scan were automatically mapped to the planning scan using the displacement vector field output from both registration algorithms. The absolute difference in planned dose (|ΔD|) between manually and automatically mapped landmark points was calculated. Using regression modeling, |ΔD| was modeled as a function of the distance between manually and automatically matched points (registration error, E), the dose standard deviation (SD-dose) in the eight-pixel neighborhood, and the registration algorithm used. Results: 52–92 landmark point pairs (median: 82) were identified in each patient's scans. Average |ΔD| across patients was 3.66Gy (range: 1.2–7.2Gy). |ΔD| was significantly reduced by 0.53Gy using Plastimatch demons compared with Fraunhofer MEVIS. |ΔD| increased significantly as a function of E (0.39Gy/mm) and SD-dose (2.23Gy/Gy). Conclusion: An average error of <4Gy in radiation dose was introduced when points were mapped between CT scan pairs using deformable registration. Dose differences following registration were significantly increased when the Fraunhofer MEVIS registration algorithm was used, spatial registration errors were larger, and dose gradient was higher (i.e., higher SD-dose). To our knowledge, this is the first study to directly compute dose errors following deformable registration of lung CT scans.« less

Observed and forecast flood-inundation mapping application-A pilot study of an eleven-mile reach of the White River, Indianapolis, Indiana

USGS Publications Warehouse

Kim, Moon H.; Morlock, Scott E.; Arihood, Leslie D.; Kiesler, James L.

2011-01-01

Near-real-time and forecast flood-inundation mapping products resulted from a pilot study for an 11-mile reach of the White River in Indianapolis. The study was done by the U.S. Geological Survey (USGS), Indiana Silver Jackets hazard mitigation taskforce members, the National Weather Service (NWS), the Polis Center, and Indiana University, in cooperation with the City of Indianapolis, the Indianapolis Museum of Art, the Indiana Department of Homeland Security, and the Indiana Department of Natural Resources, Division of Water. The pilot project showed that it is technically feasible to create a flood-inundation map library by means of a two-dimensional hydraulic model, use a map from the library to quickly complete a moderately detailed local flood-loss estimate, and automatically run the hydraulic model during a flood event to provide the maps and flood-damage information through a Web graphical user interface. A library of static digital flood-inundation maps was created by means of a calibrated two-dimensional hydraulic model. Estimated water-surface elevations were developed for a range of river stages referenced to a USGS streamgage and NWS flood forecast point colocated within the study reach. These maps were made available through the Internet in several formats, including geographic information system, Keyhole Markup Language, and Portable Document Format. A flood-loss estimate was completed for part of the study reach by using one of the flood-inundation maps from the static library. The Federal Emergency Management Agency natural disaster-loss estimation program HAZUS-MH, in conjunction with local building information, was used to complete a level 2 analysis of flood-loss estimation. A Service-Oriented Architecture-based dynamic flood-inundation application was developed and was designed to start automatically during a flood, obtain near real-time and forecast data (from the colocated USGS streamgage and NWS flood forecast point within the study reach), run the two-dimensional hydraulic model, and produce flood-inundation maps. The application used local building data and depth-damage curves to estimate flood losses based on the maps, and it served inundation maps and flood-loss estimates through a Web-based graphical user interface.

Augmented paper maps: Exploring the design space of a mixed reality system

NASA Astrophysics Data System (ADS)

Paelke, Volker; Sester, Monika

Paper maps and mobile electronic devices have complementary strengths and shortcomings in outdoor use. In many scenarios, like small craft sailing or cross-country trekking, a complete replacement of maps is neither useful nor desirable. Paper maps are fail-safe, relatively cheap, offer superior resolution and provide large scale overview. In uses like open-water sailing it is therefore mandatory to carry adequate maps/charts. GPS based mobile devices, on the other hand, offer useful features like automatic positioning and plotting, real-time information update and dynamic adaptation to user requirements. While paper maps are now commonly used in combination with mobile GPS devices, there is no meaningful integration between the two, and the combined use leads to a number of interaction problems and potential safety issues. In this paper we explore the design space of augmented paper maps in which maps are augmented with additional functionality through a mobile device to achieve a meaningful integration between device and map that combines their respective strengths.

MultiElec: A MATLAB Based Application for MEA Data Analysis.

PubMed

Georgiadis, Vassilis; Stephanou, Anastasis; Townsend, Paul A; Jackson, Thomas R

2015-01-01

We present MultiElec, an open source MATLAB based application for data analysis of microelectrode array (MEA) recordings. MultiElec displays an extremely user-friendly graphic user interface (GUI) that allows the simultaneous display and analysis of voltage traces for 60 electrodes and includes functions for activation-time determination, the production of activation-time heat maps with activation time and isoline display. Furthermore, local conduction velocities are semi-automatically calculated along with their corresponding vector plots. MultiElec allows ad hoc signal suppression, enabling the user to easily and efficiently handle signal artefacts and for incomplete data sets to be analysed. Voltage traces and heat maps can be simply exported for figure production and presentation. In addition, our platform is able to produce 3D videos of signal progression over all 60 electrodes. Functions are controlled entirely by a single GUI with no need for command line input or any understanding of MATLAB code. MultiElec is open source under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. Both the program and source code are available to download from http://www.cancer.manchester.ac.uk/MultiElec/.

Potential Energy Surface-Based Automatic Deduction of Conformational Transition Networks and Its Application on Quantum Mechanical Landscapes of d-Glucose Conformers.

PubMed

Satoh, Hiroko; Oda, Tomohiro; Nakakoji, Kumiyo; Uno, Takeaki; Tanaka, Hiroaki; Iwata, Satoru; Ohno, Koichi

2016-11-08

This paper describes our approach that is built upon the potential energy surface (PES)-based conformational analysis. This approach automatically deduces a conformational transition network, called a conformational reaction route map (r-map), by using the Scaled Hypersphere Search of the Anharmonic Downward Distortion Following method (SHS-ADDF). The PES-based conformational search has been achieved by using large ADDF, which makes it possible to trace only low transition state (TS) barriers while restraining bond lengths and structures with high free energy. It automatically performs sampling the minima and TS structures by simply taking into account the mathematical feature of PES without requiring any a priori specification of variable internal coordinates. An obtained r-map is composed of equilibrium (EQ) conformers connected by reaction routes via TS conformers, where all of the reaction routes are already confirmed during the process of the deduction using the intrinsic reaction coordinate (IRC) method. The postcalculation analysis of the deduced r-map is interactively carried out using the RMapViewer software we have developed. This paper presents computational details of the PES-based conformational analysis and its application to d-glucose. The calculations have been performed for an isolated glucose molecule in the gas phase at the RHF/6-31G level. The obtained conformational r-map for α-d-glucose is composed of 201 EQ and 435 TS conformers and that for β-d-glucose is composed of 202 EQ and 371 TS conformers. For the postcalculation analysis of the conformational r-maps by using the RMapViewer software program we have found multiple minimum energy paths (MEPs) between global minima of 1 C 4 and 4 C 1 chair conformations. The analysis using RMapViewer allows us to confirm the thermodynamic and kinetic predominance of 4 C 1 conformations; that is, the potential energy of the global minimum of 4 C 1 is lower than that of 1 C 4 (thermodynamic predominance) and that the highest energy of those of all the TS structures along a route from 4 C 1 to 1 C 4 is lower than that of 1 C 4 to 4 C 1 (kinetic predominance).

Toward fully automated processing of dynamic susceptibility contrast perfusion MRI for acute ischemic cerebral stroke.

PubMed

Kim, Jinsuh; Leira, Enrique C; Callison, Richard C; Ludwig, Bryan; Moritani, Toshio; Magnotta, Vincent A; Madsen, Mark T

2010-05-01

We developed fully automated software for dynamic susceptibility contrast (DSC) MR perfusion-weighted imaging (PWI) to efficiently and reliably derive critical hemodynamic information for acute stroke treatment decisions. Brain MR PWI was performed in 80 consecutive patients with acute nonlacunar ischemic stroke within 24h after onset of symptom from January 2008 to August 2009. These studies were automatically processed to generate hemodynamic parameters that included cerebral blood flow and cerebral blood volume, and the mean transit time (MTT). To develop reliable software for PWI analysis, we used computationally robust algorithms including the piecewise continuous regression method to determine bolus arrival time (BAT), log-linear curve fitting, arrival time independent deconvolution method and sophisticated motion correction methods. An optimal arterial input function (AIF) search algorithm using a new artery-likelihood metric was also developed. Anatomical locations of the automatically determined AIF were reviewed and validated. The automatically computed BAT values were statistically compared with estimated BAT by a single observer. In addition, gamma-variate curve-fitting errors of AIF and inter-subject variability of AIFs were analyzed. Lastly, two observes independently assessed the quality and area of hypoperfusion mismatched with restricted diffusion area from motion corrected MTT maps and compared that with time-to-peak (TTP) maps using the standard approach. The AIF was identified within an arterial branch and enhanced areas of perfusion deficit were visualized in all evaluated cases. Total processing time was 10.9+/-2.5s (mean+/-s.d.) without motion correction and 267+/-80s (mean+/-s.d.) with motion correction on a standard personal computer. The MTT map produced with our software adequately estimated brain areas with perfusion deficit and was significantly less affected by random noise of the PWI when compared with the TTP map. Results of image quality assessment by two observers revealed that the MTT maps exhibited superior quality over the TTP maps (88% good rating of MTT as compared to 68% of TTP). Our software allowed fully automated deconvolution analysis of DSC PWI using proven efficient algorithms that can be applied to acute stroke treatment decisions. Our streamlined method also offers promise for further development of automated quantitative analysis of the ischemic penumbra. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

An Anomalous Noise Events Detector for Dynamic Road Traffic Noise Mapping in Real-Life Urban and Suburban Environments.

PubMed

Socoró, Joan Claudi; Alías, Francesc; Alsina-Pagès, Rosa Ma

2017-10-12

One of the main aspects affecting the quality of life of people living in urban and suburban areas is their continued exposure to high Road Traffic Noise (RTN) levels. Until now, noise measurements in cities have been performed by professionals, recording data in certain locations to build a noise map afterwards. However, the deployment of Wireless Acoustic Sensor Networks (WASN) has enabled automatic noise mapping in smart cities. In order to obtain a reliable picture of the RTN levels affecting citizens, Anomalous Noise Events (ANE) unrelated to road traffic should be removed from the noise map computation. To this aim, this paper introduces an Anomalous Noise Event Detector (ANED) designed to differentiate between RTN and ANE in real time within a predefined interval running on the distributed low-cost acoustic sensors of a WASN. The proposed ANED follows a two-class audio event detection and classification approach, instead of multi-class or one-class classification schemes, taking advantage of the collection of representative acoustic data in real-life environments. The experiments conducted within the DYNAMAP project, implemented on ARM-based acoustic sensors, show the feasibility of the proposal both in terms of computational cost and classification performance using standard Mel cepstral coefficients and Gaussian Mixture Models (GMM). The two-class GMM core classifier relatively improves the baseline universal GMM one-class classifier F1 measure by 18.7% and 31.8% for suburban and urban environments, respectively, within the 1-s integration interval. Nevertheless, according to the results, the classification performance of the current ANED implementation still has room for improvement.

Forest Stand Segmentation Using Airborne LIDAR Data and Very High Resolution Multispectral Imagery

NASA Astrophysics Data System (ADS)

Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet, Valérie; Hervieu, Alexandre

2016-06-01

Forest stands are the basic units for forest inventory and mapping. Stands are large forested areas (e.g., ≥ 2 ha) of homogeneous tree species composition. The accurate delineation of forest stands is usually performed by visual analysis of human operators on very high resolution (VHR) optical images. This work is highly time consuming and should be automated for scalability purposes. In this paper, a method based on the fusion of airborne laser scanning data (or lidar) and very high resolution multispectral imagery for automatic forest stand delineation and forest land-cover database update is proposed. The multispectral images give access to the tree species whereas 3D lidar point clouds provide geometric information on the trees. Therefore, multi-modal features are computed, both at pixel and object levels. The objects are individual trees extracted from lidar data. A supervised classification is performed at the object level on the computed features in order to coarsely discriminate the existing tree species in the area of interest. The analysis at tree level is particularly relevant since it significantly improves the tree species classification. A probability map is generated through the tree species classification and inserted with the pixel-based features map in an energetical framework. The proposed energy is then minimized using a standard graph-cut method (namely QPBO with α-expansion) in order to produce a segmentation map with a controlled level of details. Comparison with an existing forest land cover database shows that our method provides satisfactory results both in terms of stand labelling and delineation (matching ranges between 94% and 99%).

TriNet "ShakeMaps": Rapid generation of peak ground motion and intensity maps for earthquakes in southern California

USGS Publications Warehouse

Wald, D.J.; Quitoriano, V.; Heaton, T.H.; Kanamori, H.; Scrivner, C.W.; Worden, C.B.

1999-01-01

Rapid (3-5 minutes) generation of maps of instrumental ground-motion and shaking intensity is accomplished through advances in real-time seismographic data acquisition combined with newly developed relationships between recorded ground-motion parameters and expected shaking intensity values. Estimation of shaking over the entire regional extent of southern California is obtained by the spatial interpolation of the measured ground motions with geologically based frequency and amplitude-dependent site corrections. Production of the maps is automatic, triggered by any significant earthquake in southern California. Maps are now made available within several minutes of the earthquake for public and scientific consumption via the World Wide Web; they will be made available with dedicated communications for emergency response agencies and critical users.

Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations

PubMed Central

Wang, Nancy X. R.; Olson, Jared D.; Ojemann, Jeffrey G.; Rao, Rajesh P. N.; Brunton, Bingni W.

2016-01-01

Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Implementing Brain Computer Interfaces (BCIs) outside carefully controlled experiments in laboratory settings requires adaptive and scalable strategies with minimal supervision. Here we describe an unsupervised approach to decoding neural states from naturalistic human brain recordings. We analyzed continuous, long-term electrocorticography (ECoG) data recorded over many days from the brain of subjects in a hospital room, with simultaneous audio and video recordings. We discovered coherent clusters in high-dimensional ECoG recordings using hierarchical clustering and automatically annotated them using speech and movement labels extracted from audio and video. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Interpretable behaviors were decoded from ECoG data, including moving, speaking and resting; the results were assessed by comparison with manual annotation. Discovered clusters were projected back onto the brain revealing features consistent with known functional areas, opening the door to automated functional brain mapping in natural settings. PMID:27148018

A system of regional agricultural land use mapping tested against small scale Apollo 9 color infrared photography of the Imperial Valley (California)

USGS Publications Warehouse

Johnson, Claude W.; Browden, Leonard W.; Pease, Robert W.

1969-01-01

Interpretation results of the small scale ClR photography of the Imperial Valley (California) taken on March 12, 1969 by the Apollo 9 earth orbiting satellite have shown that world wide agricultural land use mapping can be accomplished from satellite ClR imagery if sufficient a priori information is available for the region being mapped. Correlation of results with actual data is encouraging although the accuracy of identification of specific crops from the single image is poor. The poor results can be partly attributed to only one image taken during mid-season when the three major crops were reflecting approximately the same and their ClR image appears to indicate the same crop type. However, some incapacity can be attributed to lack of understanding of the subtle variations of visual and infrared color reflectance of vegetation and surrounding environment. Analysis of integrated color variations of the vegetation and background environment recorded on ClR imagery is discussed. Problems associated with the color variations may be overcome by development of a semi-automatic processing system which considers individual field units or cells. Design criteria for semi-automatic processing system are outlined.

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

Semi-Automatic Building Models and FAÇADE Texture Mapping from Mobile Phone Images

NASA Astrophysics Data System (ADS)

Jeong, J.; Kim, T.

2016-06-01

Research on 3D urban modelling has been actively carried out for a long time. Recently the need of 3D urban modelling research is increased rapidly due to improved geo-web services and popularized smart devices. Nowadays 3D urban models provided by, for example, Google Earth use aerial photos for 3D urban modelling but there are some limitations: immediate update for the change of building models is difficult, many buildings are without 3D model and texture, and large resources for maintaining and updating are inevitable. To resolve the limitations mentioned above, we propose a method for semi-automatic building modelling and façade texture mapping from mobile phone images and analyze the result of modelling with actual measurements. Our method consists of camera geometry estimation step, image matching step, and façade mapping step. Models generated from this method were compared with actual measurement value of real buildings. Ratios of edge length of models and measurements were compared. Result showed 5.8% average error of length ratio. Through this method, we could generate a simple building model with fine façade textures without expensive dedicated tools and dataset.

Standardized unfold mapping: a technique to permit left atrial regional data display and analysis.

PubMed

Williams, Steven E; Tobon-Gomez, Catalina; Zuluaga, Maria A; Chubb, Henry; Butakoff, Constantine; Karim, Rashed; Ahmed, Elena; Camara, Oscar; Rhode, Kawal S

2017-10-01

Left atrial arrhythmia substrate assessment can involve multiple imaging and electrical modalities, but visual analysis of data on 3D surfaces is time-consuming and suffers from limited reproducibility. Unfold maps (e.g., the left ventricular bull's eye plot) allow 2D visualization, facilitate multimodal data representation, and provide a common reference space for inter-subject comparison. The aim of this work is to develop a method for automatic representation of multimodal information on a left atrial standardized unfold map (LA-SUM). The LA-SUM technique was developed and validated using 18 electroanatomic mapping (EAM) LA geometries before being applied to ten cardiac magnetic resonance/EAM paired geometries. The LA-SUM was defined as an unfold template of an average LA mesh, and registration of clinical data to this mesh facilitated creation of new LA-SUMs by surface parameterization. The LA-SUM represents 24 LA regions on a flattened surface. Intra-observer variability of LA-SUMs for both EAM and CMR datasets was minimal; root-mean square difference of 0.008 ± 0.010 and 0.007 ± 0.005 ms (local activation time maps), 0.068 ± 0.063 gs (force-time integral maps), and 0.031 ± 0.026 (CMR LGE signal intensity maps). Following validation, LA-SUMs were used for automatic quantification of post-ablation scar formation using CMR imaging, demonstrating a weak but significant relationship between ablation force-time integral and scar coverage (R 2  = 0.18, P < 0.0001). The proposed LA-SUM displays an integrated unfold map for multimodal information. The method is applicable to any LA surface, including those derived from imaging and EAM systems. The LA-SUM would facilitate standardization of future research studies involving segmental analysis of the LA.

Besides Precision & Recall: Exploring Alternative Approaches to Evaluating an Automatic Indexing Tool for MEDLINE

PubMed Central

Névéol, Aurélie; Zeng, Kelly; Bodenreider, Olivier

2006-01-01

Objective This paper explores alternative approaches for the evaluation of an automatic indexing tool for MEDLINE, complementing the traditional precision and recall method. Materials and methods The performance of MTI, the Medical Text Indexer used at NLM to produce MeSH recommendations for biomedical journal articles is evaluated on a random set of MEDLINE citations. The evaluation examines semantic similarity at the term level (indexing terms). In addition, the documents retrieved by queries resulting from MTI index terms for a given document are compared to the PubMed related citations for this document. Results Semantic similarity scores between sets of index terms are higher than the corresponding Dice similarity scores. Overall, 75% of the original documents and 58% of the top ten related citations are retrieved by queries based on the automatic indexing. Conclusions The alternative measures studied in this paper confirm previous findings and may be used to select particular documents from the test set for a more thorough analysis. PMID:17238409

Besides precision & recall: exploring alternative approaches to evaluating an automatic indexing tool for MEDLINE.

PubMed

Neveol, Aurélie; Zeng, Kelly; Bodenreider, Olivier

2006-01-01

This paper explores alternative approaches for the evaluation of an automatic indexing tool for MEDLINE, complementing the traditional precision and recall method. The performance of MTI, the Medical Text Indexer used at NLM to produce MeSH recommendations for biomedical journal articles is evaluated on a random set of MEDLINE citations. The evaluation examines semantic similarity at the term level (indexing terms). In addition, the documents retrieved by queries resulting from MTI index terms for a given document are compared to the PubMed related citations for this document. Semantic similarity scores between sets of index terms are higher than the corresponding Dice similarity scores. Overall, 75% of the original documents and 58% of the top ten related citations are retrieved by queries based on the automatic indexing. The alternative measures studied in this paper confirm previous findings and may be used to select particular documents from the test set for a more thorough analysis.

Fragman: an R package for fragment analysis.

PubMed

Covarrubias-Pazaran, Giovanny; Diaz-Garcia, Luis; Schlautman, Brandon; Salazar, Walter; Zalapa, Juan

2016-04-21

Determination of microsatellite lengths or other DNA fragment types is an important initial component of many genetic studies such as mutation detection, linkage and quantitative trait loci (QTL) mapping, genetic diversity, pedigree analysis, and detection of heterozygosity. A handful of commercial and freely available software programs exist for fragment analysis; however, most of them are platform dependent and lack high-throughput applicability. We present the R package Fragman to serve as a freely available and platform independent resource for automatic scoring of DNA fragment lengths diversity panels and biparental populations. The program analyzes DNA fragment lengths generated in Applied Biosystems® (ABI) either manually or automatically by providing panels or bins. The package contains additional tools for converting the allele calls to GenAlEx, JoinMap® and OneMap software formats mainly used for genetic diversity and generating linkage maps in plant and animal populations. Easy plotting functions and multiplexing friendly capabilities are some of the strengths of this R package. Fragment analysis using a unique set of cranberry (Vaccinium macrocarpon) genotypes based on microsatellite markers is used to highlight the capabilities of Fragman. Fragman is a valuable new tool for genetic analysis. The package produces equivalent results to other popular software for fragment analysis while possessing unique advantages and the possibility of automation for high-throughput experiments by exploiting the power of R.

Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

NASA Astrophysics Data System (ADS)

Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

2016-06-01

High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

Crowd-sourced data collection to support automatic classification of building footprint data

NASA Astrophysics Data System (ADS)

Hecht, Robert; Kalla, Matthias; Krüger, Tobias

2018-05-01

Human settlements are mainly formed by buildings with their different characteristics and usage. Despite the importance of buildings for the economy and society, complete regional or even national figures of the entire building stock and its spatial distribution are still hardly available. Available digital topographic data sets created by National Mapping Agencies or mapped voluntarily through a crowd via Volunteered Geographic Information (VGI) platforms (e.g. OpenStreetMap) contain building footprint information but often lack additional information on building type, usage, age or number of floors. For this reason, predictive modeling is becoming increasingly important in this context. The capabilities of machine learning allow for the prediction of building types and other building characteristics and thus, the efficient classification and description of the entire building stock of cities and regions. However, such data-driven approaches always require a sufficient amount of ground truth (reference) information for training and validation. The collection of reference data is usually cost-intensive and time-consuming. Experiences from other disciplines have shown that crowdsourcing offers the possibility to support the process of obtaining ground truth data. Therefore, this paper presents the results of an experimental study aiming at assessing the accuracy of non-expert annotations on street view images collected from an internet crowd. The findings provide the basis for a future integration of a crowdsourcing component into the process of land use mapping, particularly the automatic building classification.

Digital Map Requirements For Automatic Vehicle Location

DOT National Transportation Integrated Search

1998-12-01

New Jersey Transit (NJT) is currently investigating acquisition of an automated vehicle locator (AVL) system. The purpose of the AVL system is to monitor the location of buses. Knowing the location of a bus enables the agency to manage the bus fleet ...

Automated analysis of individual sperm cells using stain-free interferometric phase microscopy and machine learning.

PubMed

Mirsky, Simcha K; Barnea, Itay; Levi, Mattan; Greenspan, Hayit; Shaked, Natan T

2017-09-01

Currently, the delicate process of selecting sperm cells to be used for in vitro fertilization (IVF) is still based on the subjective, qualitative analysis of experienced clinicians using non-quantitative optical microscopy techniques. In this work, a method was developed for the automated analysis of sperm cells based on the quantitative phase maps acquired through use of interferometric phase microscopy (IPM). Over 1,400 human sperm cells from 8 donors were imaged using IPM, and an algorithm was designed to digitally isolate sperm cell heads from the quantitative phase maps while taking into consideration both the cell 3D morphology and contents, as well as acquire features describing sperm head morphology. A subset of these features was used to train a support vector machine (SVM) classifier to automatically classify sperm of good and bad morphology. The SVM achieves an area under the receiver operating characteristic curve of 88.59% and an area under the precision-recall curve of 88.67%, as well as precisions of 90% or higher. We believe that our automatic analysis can become the basis for objective and automatic sperm cell selection in IVF. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Arraycount, an algorithm for automatic cell counting in microwell arrays.

PubMed

Kachouie, Nezamoddin; Kang, Lifeng; Khademhosseini, Ali

2009-09-01

Microscale technologies have emerged as a powerful tool for studying and manipulating biological systems and miniaturizing experiments. However, the lack of software complementing these techniques has made it difficult to apply them for many high-throughput experiments. This work establishes Arraycount, an approach to automatically count cells in microwell arrays. The procedure consists of fluorescent microscope imaging of cells that are seeded in microwells of a microarray system and then analyzing images via computer to recognize the array and count cells inside each microwell. To start counting, green and red fluorescent images (representing live and dead cells, respectively) are extracted from the original image and processed separately. A template-matching algorithm is proposed in which pre-defined well and cell templates are matched against the red and green images to locate microwells and cells. Subsequently, local maxima in the correlation maps are determined and local maxima maps are thresholded. At the end, the software records the cell counts for each detected microwell on the original image in high-throughput. The automated counting was shown to be accurate compared with manual counting, with a difference of approximately 1-2 cells per microwell: based on cell concentration, the absolute difference between manual and automatic counting measurements was 2.5-13%.

Optimal guidance with obstacle avoidance for nap-of-the-earth flight

NASA Technical Reports Server (NTRS)

Pekelsma, Nicholas J.

1988-01-01

The development of automatic guidance is discussed for helicopter Nap-of-the-Earth (NOE) and near-NOE flight. It deals with algorithm refinements relating to automated real-time flight path planning and to mission planning. With regard to path planning, it relates rotorcraft trajectory characteristics to the NOE computation scheme and addresses real-time computing issues and both ride quality issues and pilot-vehicle interfaces. The automated mission planning algorithm refinements include route optimization, automatic waypoint generation, interactive applications, and provisions for integrating the results into the real-time path planning software. A microcomputer based mission planning workstation was developed and is described. Further, the application of Defense Mapping Agency (DMA) digital terrain to both the mission planning workstation and to automatic guidance is both discussed and illustrated.

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

PubMed Central

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

2018-01-01

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

Characterizing semantic mappings adaptation via biomedical KOS evolution: a case study investigating SNOMED CT and ICD.

PubMed

Dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2013-01-01

Mappings established between Knowledge Organization Systems (KOS) increase semantic interoperability between biomedical information systems. However, biomedical knowledge is highly dynamic and changes affecting KOS entities can potentially invalidate part or the totality of existing mappings. Understanding how mappings evolve and what the impacts of KOS evolution on mappings are is therefore crucial for the definition of an automatic approach to maintain mappings valid and up-to-date over time. In this article, we study variations of a specific KOS complex change (split) for two biomedical KOS (SNOMED CT and ICD-9-CM) through a rigorous method of investigation for identifying and refining complex changes, and for selecting representative cases. We empirically analyze and explain their influence on the evolution of associated mappings. Results point out the importance of considering various dimensions of the information described in KOS, like the semantic structure of concepts, the set of relevant information used to define the mappings and the change operations interfering with this set of information.

Characterizing Semantic Mappings Adaptation via Biomedical KOS Evolution: A Case Study Investigating SNOMED CT and ICD

PubMed Central

Reis, Julio Cesar Dos; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2013-01-01

Mappings established between Knowledge Organization Systems (KOS) increase semantic interoperability between biomedical information systems. However, biomedical knowledge is highly dynamic and changes affecting KOS entities can potentially invalidate part or the totality of existing mappings. Understanding how mappings evolve and what the impacts of KOS evolution on mappings are is therefore crucial for the definition of an automatic approach to maintain mappings valid and up-to-date over time. In this article, we study variations of a specific KOS complex change (split) for two biomedical KOS (SNOMED CT and ICD-9-CM) through a rigorous method of investigation for identifying and refining complex changes, and for selecting representative cases. We empirically analyze and explain their influence on the evolution of associated mappings. Results point out the importance of considering various dimensions of the information described in KOS, like the semantic structure of concepts, the set of relevant information used to define the mappings and the change operations interfering with this set of information. PMID:24551341

Real-time mapping of the corneal sub-basal nerve plexus by in vivo laser scanning confocal microscopy

NASA Astrophysics Data System (ADS)

Guthoff, Rudolf F.; Zhivov, Andrey; Stachs, Oliver

2010-02-01

The aim of the study was to produce two-dimensional reconstruction maps of the living corneal sub-basal nerve plexus by in vivo laser scanning confocal microscopy in real time. CLSM source data (frame rate 30Hz, 384x384 pixel) were used to create large-scale maps of the scanned area by selecting the Automatic Real Time (ART) composite mode. The mapping algorithm is based on an affine transformation. Microscopy of the sub-basal nerve plexus was performed on normal and LASIK eyes as well as on rabbit eyes. Real-time mapping of the sub-basal nerve plexus was performed in large-scale up to a size of 3.2mm x 3.2mm. The developed method enables a real-time in vivo mapping of the sub-basal nerve plexus which is stringently necessary for statistically firmed conclusions about morphometric plexus alterations.

Experiments to Distribute Map Generalization Processes

NASA Astrophysics Data System (ADS)

Berli, Justin; Touya, Guillaume; Lokhat, Imran; Regnauld, Nicolas

2018-05-01

Automatic map generalization requires the use of computationally intensive processes often unable to deal with large datasets. Distributing the generalization process is the only way to make them scalable and usable in practice. But map generalization is a highly contextual process, and the surroundings of a generalized map feature needs to be known to generalize the feature, which is a problem as distribution might partition the dataset and parallelize the processing of each part. This paper proposes experiments to evaluate the past propositions to distribute map generalization, and to identify the main remaining issues. The past propositions to distribute map generalization are first discussed, and then the experiment hypotheses and apparatus are described. The experiments confirmed that regular partitioning was the quickest strategy, but also the less effective in taking context into account. The geographical partitioning, though less effective for now, is quite promising regarding the quality of the results as it better integrates the geographical context.

Towards a Copernicus Service for Monitoring Polar Ice Sheet Velocity and Discharge using Sentinel-1A and 1B SAR

NASA Astrophysics Data System (ADS)

Wuite, Jan; Nagler, Thomas; Hetzenecker, Markus; Blumthaler, Ursula; Ossowska, Joanna; Rott, Helmut

2017-04-01

The enhanced imaging capabilities of Sentinel-1A and 1B and the systematic acquisition planning of polar regions by ESA form the basis for the development and implementation of an operational system for monitoring ice dynamics and discharge of Antarctica, Greenland and other polar ice caps. Within the framework of the ESA CCI and the Austrian ASAP/FFG programs we implemented an automatic system for generation of ice velocity maps from repeat pass Sentinel-1 Terrain Observation by Progressive Scans (TOPS) mode data applying iterative offset tracking using both coherent and incoherent image cross-correlation. Greenland's margins are monitored by 6 tracks continuously since mid of 2015 with 12 days repeat observations using Sentinel-1A. With the twin satellite Sentinel-1B, launched in April 2016, the repeat acquisition period is reduced to only 6 days allowing frequent velocity retrievals - even in regions with high accumulation rates and very fast flow - and providing insight for studying short-term variations of ice flow and discharge. The Sentinel-1 ice velocity products continue the sparse coverage in time and space of previous velocity mapping efforts. The annual Greenland wide winter acquisition campaigns of 4 to 6 repeat track observations, acquired within a few weeks, provide nearly gapless and seamless ice sheet wide flow velocity maps on a yearly basis which are important for ice sheet modelling purposes and accurate mass balance assessments. An Antarctic ice sheet wide ice velocity map (with polar gap) was generated from Sentinel-1A data, acquired within 8 months, providing an important benchmark for gauging future changes in ice dynamics. For regions with significant warming continuous monitoring of ice streams with 6 to 12-day repeat intervals, exploiting both satellites, is ongoing to detect changes of ice flow as indicators of climate change. We present annual ice sheet wide velocity maps of Greenland from 2014/15 to 2016/17 and Antarctica from 2015/16 as well as dense time series of short-term velocity changes of outlet glaciers since 2014. We will highlight the improvements of the dual satellite constellation of Sentinel-1A and 1B, in particular for fast moving glaciers and regions with high accumulation rates. Derived surface velocities are combined with ice thickness from airborne Radio Echo Sounding data to compute ice discharge and its short-term variation across flux gates of major outlet glaciers in Greenland and Antarctica. Ice velocity maps, including dense time series for outlet glaciers, and ice discharge products are made available to registered users through our webtool at cryoportal.enveo.at.

Automatic Control of Personal Rapid Transit Vehicles

NASA Technical Reports Server (NTRS)

Smith, P. D.

1972-01-01

The requirements for automatic longitudinal control of a string of closely packed personal vehicles are outlined. Optimal control theory is used to design feedback controllers for strings of vehicles. An important modification of the usual optimal control scheme is the inclusion of jerk in the cost functional. While the inclusion of the jerk term was considered, the effect of its inclusion was not sufficiently studied. Adding the jerk term will increase passenger comfort.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

PubMed Central

Robinson, Jennifer; Calhoun, Vince

2018-01-01

Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

Metadata mapping and reuse in caBIG.

PubMed

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-02-05

This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG framework or other frameworks that use metadata repositories. The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG framework and potentially any framework that uses a metadata repository. This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG. This effort contributes to facilitating the development of interoperable systems within caBIG as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies.

Mapping and localization for extraterrestrial robotic explorations

NASA Astrophysics Data System (ADS)

Xu, Fengliang

In the exploration of an extraterrestrial environment such as Mars, orbital data, such as high-resolution imagery Mars Orbital Camera-Narrow Angle (MOC-NA), laser ranging data Mars Orbital Laser Altimeter (MOLA), and multi-spectral imagery Thermal Emission Imaging System (THEMIS), play more and more important roles. However, these remote sensing techniques can never replace the role of landers and rovers, which can provide a close up and inside view. Similarly, orbital mapping can not compete with ground-level close-range mapping in resolution, precision, and speed. This dissertation addresses two tasks related to robotic extraterrestrial exploration: mapping and rover localization. Image registration is also discussed as an important aspect for both of them. Techniques from computer vision and photogrammetry are applied for automation and precision. Image registration is classified into three sub-categories: intra-stereo, inter-stereo, and cross-site, according to the relationship between stereo images. In the intra-stereo registration, which is the most fundamental sub-category, interest point-based registration and verification by parallax continuity in the principal direction are proposed. Two other techniques, inter-scanline search with constrained dynamic programming for far range matching and Markov Random Field (MRF) based registration for big terrain variation, are explored as possible improvements. Creating using rover ground images mainly involves the generation of Digital Terrain Model (DTM) and ortho-rectified map (orthomap). The first task is to derive the spatial distribution statistics from the first panorama and model the DTM with a dual polynomial model. This model is used for interpolation of the DTM, using Kriging in the close range and Triangular Irregular Network (TIN) in the far range. To generate a uniformly illuminated orthomap from the DTM, a least-squares-based automatic intensity balancing method is proposed. Finally a seamless orthomap is constructed by a split-and-merge technique: the mapped area is split or subdivided into small regions of image overlap, and then each small map piece was processed and all of the pieces are merged together to form a seamless map. Rover localization has three stages, all of which use a least-squares adjustment procedure: (1) an initial localization which is accomplished by adjustment over features common to rover images and orbital images, (2) an adjustment of image pointing angles at a single site through inter and intra-stereo tie points, and (3) an adjustment of the rover traverse through manual cross-site tie points. The first stage is based on adjustment of observation angles of features. The second stage and third stage are based on bundle-adjustment. In the third-stage an incremental adjustment method was proposed. Automation in rover localization includes automatic intra/inter-stereo tie point selection, computer-assisted cross-site tie point selection, and automatic verification of accuracy. (Abstract shortened by UMI.)

Facilitating Analysis of Multiple Partial Data Streams

NASA Technical Reports Server (NTRS)

Maimone, Mark W.; Liebersbach, Robert R.

2008-01-01

Robotic Operations Automation: Mechanisms, Imaging, Navigation report Generation (ROAMING) is a set of computer programs that facilitates and accelerates both tactical and strategic analysis of time-sampled data especially the disparate and often incomplete streams of Mars Explorer Rover (MER) telemetry data described in the immediately preceding article. As used here, tactical refers to the activities over a relatively short time (one Martian day in the original MER application) and strategic refers to a longer time (the entire multi-year MER missions in the original application). Prior to installation, ROAMING must be configured with the types of data of interest, and parsers must be modified to understand the format of the input data (many example parsers are provided, including for general CSV files). Thereafter, new data from multiple disparate sources are automatically resampled into a single common annotated spreadsheet stored in a readable space-separated format, and these data can be processed or plotted at any time scale. Such processing or plotting makes it possible to study not only the details of a particular activity spanning only a few seconds, but also longer-term trends. ROAMING makes it possible to generate mission-wide plots of multiple engineering quantities [e.g., vehicle tilt as in Figure 1(a), motor current, numbers of images] that, heretofore could be found only in thousands of separate files. ROAMING also supports automatic annotation of both images and graphs. In the MER application, labels given to terrain features by rover scientists and engineers are automatically plotted in all received images based on their associated camera models (see Figure 2), times measured in seconds are mapped to Mars local time, and command names or arbitrary time-labeled events can be used to label engineering plots, as in Figure 1(b).

On the automaticity of response inhibition in individuals with alcoholism.

PubMed

Noël, Xavier; Brevers, Damien; Hanak, Catherine; Kornreich, Charles; Verbanck, Paul; Verbruggen, Frederick

2016-06-01

Response inhibition is usually considered a hallmark of executive control. However, recent work indicates that stop performance can become associatively mediated ('automatic') over practice. This study investigated automatic response inhibition in sober and recently detoxified individuals with alcoholism.. We administered to forty recently detoxified alcoholics and forty healthy participants a modified stop-signal task that consisted of a training phase in which a subset of the stimuli was consistently associated with stopping or going, and a test phase in which this mapping was reversed. In the training phase, stop performance improved for the consistent stop stimuli, compared with control stimuli that were not associated with going or stopping. In the test phase, go performance tended to be impaired for old stop stimuli. Combined, these findings support the automatic inhibition hypothesis. Importantly, performance was similar in both groups, which indicates that automatic inhibitory control develops normally in individuals with alcoholism.. This finding is specific to individuals with alcoholism without other psychiatric disorders, which is rather atypical and prevents generalization. Personalized stimuli with a stronger affective content should be used in future studies. These results advance our understanding of behavioral inhibition in individuals with alcoholism. Furthermore, intact automatic inhibitory control may be an important element of successful cognitive remediation of addictive behaviors.. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cadastral Map Assembling Using Generalized Hough Transformation

NASA Astrophysics Data System (ADS)

Liu, Fei; Ohyama, Wataru; Wakabayashi, Tetsushi; Kimura, Fumitaka

There are numerous cadastral maps generated by the past land surveying. The raster digitization of these paper maps is in progress. For effective and efficient use of these maps, we have to assemble the set of maps to make them superimposable on other geographic information in a GIS. The problem can be seen as a complex jigsaw puzzle where the pieces are the cadastral sections extracted from the map. We present an automatic solution to this geographic jigsaw puzzle, based on the generalized Hough transformation that detects the longest common boundary between every piece and its neighbors. The experiments have been conducted using the map of Mie Prefecture, Japan and the French cadastral map. The results of the experiments with the French cadastral maps showed that the proposed method, which consists of a flood filling procedure of internal area and detection and normalization of the north arrow direction, is suitable for assembling the cadastral map. The final goal of the process is to integrate every piece of the puzzle into a national geographic reference frame and database.

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

Wetlands delineation by spectral signature analysis and legal implications

NASA Technical Reports Server (NTRS)

Anderon, R. R.; Carter, V.

1972-01-01

High altitude analysis of wetland resources and the use of such information in an operational mode to address specific problems of wetland preservation at a state level are discussed. Work efforts were directed toward: (1) developing techniques for using large scale color IR photography in state wetlands mapping program, (2) developing methods for obtaining wetlands ecology information from high altitude photography, (3) developing means by which spectral data can be more accurately analyzed visually, and (4) developing spectral data for automatic mapping of wetlands.

A multi-resolution approach for optimal mass transport

NASA Astrophysics Data System (ADS)

Dominitz, Ayelet; Angenent, Sigurd; Tannenbaum, Allen

2007-09-01

Optimal mass transport is an important technique with numerous applications in econometrics, fluid dynamics, automatic control, statistical physics, shape optimization, expert systems, and meteorology. Motivated by certain problems in image registration and medical image visualization, in this note, we describe a simple gradient descent methodology for computing the optimal L2 transport mapping which may be easily implemented using a multiresolution scheme. We also indicate how the optimal transport map may be computed on the sphere. A numerical example is presented illustrating our ideas.

Mapping soil types from multispectral scanner data.

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Zachary, A. L.

1971-01-01

Multispectral remote sensing and computer-implemented pattern recognition techniques were used for automatic ?mapping' of soil types. This approach involves subjective selection of a set of reference samples from a gray-level display of spectral variations which was generated by a computer. Each resolution element is then classified using a maximum likelihood ratio. Output is a computer printout on which the researcher assigns a different symbol to each class. Four soil test areas in Indiana were experimentally examined using this approach, and partially successful results were obtained.

Image Processing

NASA Technical Reports Server (NTRS)

1987-01-01

A new spinoff product was derived from Geospectra Corporation's expertise in processing LANDSAT data in a software package. Called ATOM (for Automatic Topographic Mapping), it's capable of digitally extracting elevation information from stereo photos taken by spaceborne cameras. ATOM offers a new dimension of realism in applications involving terrain simulations, producing extremely precise maps of an area's elevations at a lower cost than traditional methods. ATOM has a number of applications involving defense training simulations and offers utility in architecture, urban planning, forestry, petroleum and mineral exploration.

Department of Defense Strategy to Support Multi-Agency Bat Conservation Initiative within the State of Utah

DTIC Science & Technology

2008-02-28

Range, and Section are entered. Datum: Geometric reference surface. Original Site Location datum is defined by user’s map datum; e.g. NAD27...Section are entered. Datum: Geometric reference surface. Original Site Location datum is defined by user’s map datum; e.g. NAD27 Conus or NAD83...Calculated and recorded automatically if the fields UTM_N and UTM_E or Township, Range, and Section are entered. 41 Datum: Geometric reference surface

Application of LANDSAT images in the Minas Gerais tectonic division

NASA Technical Reports Server (NTRS)

Dacunha, R. P.; Demattos, J. T.

1978-01-01

The interpretation of LANDSAT data for a regional geological investigation of Brazil is provided. Radar imagery, aerial photographs and aeromagnetic maps were also used. Automatic interpretation, using LANDSAT OCT's was carried out by the 1-100 equipment. As a primary result a tectonic map was obtained, at 1:1,000,000 scale, of an area of about 143,000 square kilometers, in the central portion of Minas Gerais and Eastern Goias States, known as regions potentially rich in mineral resources.

Comparison of SAM and OBIA as Tools for Lava Morphology Classification - A Case Study in Krafla, NE Iceland

NASA Astrophysics Data System (ADS)

Aufaristama, Muhammad; Hölbling, Daniel; Höskuldsson, Ármann; Jónsdóttir, Ingibjörg

2017-04-01

The Krafla volcanic system is part of the Icelandic North Volcanic Zone (NVZ). During Holocene, two eruptive events occurred in Krafla, 1724-1729 and 1975-1984. The last eruptive episode (1975-1984), known as the "Krafla Fires", resulted in nine volcanic eruption episodes. The total area covered by the lavas from this eruptive episode is 36 km2 and the volume is about 0.25-0.3 km3. Lava morphology is related to the characteristics of the surface morphology of a lava flow after solidification. The typical morphology of lava can be used as primary basis for the classification of lava flows when rheological properties cannot be directly observed during emplacement, and also for better understanding the behavior of lava flow models. Although mapping of lava flows in the field is relatively accurate such traditional methods are time consuming, especially when the lava covers large areas such as it is the case in Krafla. Semi-automatic mapping methods that make use of satellite remote sensing data allow for an efficient and fast mapping of lava morphology. In this study, two semi-automatic methods for lava morphology classification are presented and compared using Landsat 8 (30 m spatial resolution) and SPOT-5 (10 m spatial resolution) satellite images. For assessing the classification accuracy, the results from semi-automatic mapping were compared to the respective results from visual interpretation. On the one hand, the Spectral Angle Mapper (SAM) classification method was used. With this method an image is classified according to the spectral similarity between the image reflectance spectrums and the reference reflectance spectra. SAM successfully produced detailed lava surface morphology maps. However, the pixel-based approach partly leads to a salt-and-pepper effect. On the other hand, we applied the Random Forest (RF) classification method within an object-based image analysis (OBIA) framework. This statistical classifier uses a randomly selected subset of training samples to produce multiple decision trees. For final classification of pixels or - in the present case - image objects, the average of the class assignments probability predicted by the different decision trees is used. While the resulting OBIA classification of lava morphology types shows a high coincidence with the reference data, the approach is sensitive to the segmentation-derived image objects that constitute the base units for classification. Both semi-automatic methods produce reasonable results in the Krafla lava field, even if the identification of different pahoehoe and aa types of lava appeared to be difficult. The use of satellite remote sensing data shows a high potential for fast and efficient classification of lava morphology, particularly over large and inaccessible areas.

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

Bridging data models and terminologies to support adverse drug event reporting using EHR data.

PubMed

Declerck, G; Hussain, S; Daniel, C; Yuksel, M; Laleci, G B; Twagirumukiza, M; Jaulent, M-C

2015-01-01

This article is part of the Focus Theme of METHODs of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". SALUS project aims at building an interoperability platform and a dedicated toolkit to enable secondary use of electronic health records (EHR) data for post marketing drug surveillance. An important component of this toolkit is a drug-related adverse events (AE) reporting system designed to facilitate and accelerate the reporting process using automatic prepopulation mechanisms. To demonstrate SALUS approach for establishing syntactic and semantic interoperability for AE reporting. Standard (e.g. HL7 CDA-CCD) and proprietary EHR data models are mapped to the E2B(R2) data model via SALUS Common Information Model. Terminology mapping and terminology reasoning services are designed to ensure the automatic conversion of source EHR terminologies (e.g. ICD-9-CM, ICD-10, LOINC or SNOMED-CT) to the target terminology MedDRA which is expected in AE reporting forms. A validated set of terminology mappings is used to ensure the reliability of the reasoning mechanisms. The percentage of data elements of a standard E2B report that can be completed automatically has been estimated for two pilot sites. In the best scenario (i.e. the available fields in the EHR have actually been filled), only 36% (pilot site 1) and 38% (pilot site 2) of E2B data elements remain to be filled manually. In addition, most of these data elements shall not be filled in each report. SALUS platform's interoperability solutions enable partial automation of the AE reporting process, which could contribute to improve current spontaneous reporting practices and reduce under-reporting, which is currently one major obstacle in the process of acquisition of pharmacovigilance data.

Automatic detection and decoding of honey bee waggle dances

PubMed Central

Wild, Benjamin; Rojas, Raúl; Landgraf, Tim

2017-01-01

The waggle dance is one of the most popular examples of animal communication. Forager bees direct their nestmates to profitable resources via a complex motor display. Essentially, the dance encodes the polar coordinates to the resource in the field. Unemployed foragers follow the dancer’s movements and then search for the advertised spots in the field. Throughout the last decades, biologists have employed different techniques to measure key characteristics of the waggle dance and decode the information it conveys. Early techniques involved the use of protractors and stopwatches to measure the dance orientation and duration directly from the observation hive. Recent approaches employ digital video recordings and manual measurements on screen. However, manual approaches are very time-consuming. Most studies, therefore, regard only small numbers of animals in short periods of time. We have developed a system capable of automatically detecting, decoding and mapping communication dances in real-time. In this paper, we describe our recording setup, the image processing steps performed for dance detection and decoding and an algorithm to map dances to the field. The proposed system performs with a detection accuracy of 90.07%. The decoded waggle orientation has an average error of -2.92° (± 7.37°), well within the range of human error. To evaluate and exemplify the system’s performance, a group of bees was trained to an artificial feeder, and all dances in the colony were automatically detected, decoded and mapped. The system presented here is the first of this kind made publicly available, including source code and hardware specifications. We hope this will foster quantitative analyses of the honey bee waggle dance. PMID:29236712

Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.

PubMed

Meyer, C R; Boes, J L; Kim, B; Bland, P H; Zasadny, K R; Kison, P V; Koral, K; Frey, K A; Wahl, R L

1997-04-01

This paper applies and evaluates an automatic mutual information-based registration algorithm across a broad spectrum of multimodal volume data sets. The algorithm requires little or no pre-processing, minimal user input and easily implements either affine, i.e. linear or thin-plate spline (TPS) warped registrations. We have evaluated the algorithm in phantom studies as well as in selected cases where few other algorithms could perform as well, if at all, to demonstrate the value of this new method. Pairs of multimodal gray-scale volume data sets were registered by iteratively changing registration parameters to maximize mutual information. Quantitative registration errors were assessed in registrations of a thorax phantom using PET/CT and in the National Library of Medicine's Visible Male using MRI T2-/T1-weighted acquisitions. Registrations of diverse clinical data sets were demonstrated including rotate-translate mapping of PET/MRI brain scans with significant missing data, full affine mapping of thoracic PET/CT and rotate-translate mapping of abdominal SPECT/CT. A five-point thin-plate spline (TPS) warped registration of thoracic PET/CT is also demonstrated. The registration algorithm converged in times ranging between 3.5 and 31 min for affine clinical registrations and 57 min for TPS warping. Mean error vector lengths for rotate-translate registrations were measured to be subvoxel in phantoms. More importantly the rotate-translate algorithm performs well even with missing data. The demonstrated clinical fusions are qualitatively excellent at all levels. We conclude that such automatic, rapid, robust algorithms significantly increase the likelihood that multimodality registrations will be routinely used to aid clinical diagnoses and post-therapeutic assessment in the near future.

Georectification and snow classification of webcam images: potential for complementing satellite-derrived snow maps over Switzerland

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2016-04-01

The spatial and temporal variability of snow cover has a significant impact on climate and environment and is of great socio-economic importance for the European Alps. Satellite remote sensing data is widely used to study snow cover variability and can provide spatially comprehensive information on snow cover extent. However, cloud cover strongly impedes the surface view and hence limits the number of useful snow observations. Outdoor webcam images not only offer unique potential for complementing satellite-derived snow retrieval under cloudy conditions but could also serve as a reference for improved validation of satellite-based approaches. Thousands of webcams are currently connected to the Internet and deliver freely available images with high temporal and spatial resolutions. To exploit the untapped potential of these webcams, a semi-automatic procedure was developed to generate snow cover maps based on webcam images. We used daily webcam images of the Swiss alpine region to apply, improve, and extend existing approaches dealing with the positioning of photographs within a terrain model, appropriate georectification, and the automatic snow classification of such photographs. In this presentation, we provide an overview of the implemented procedure and demonstrate how our registration approach automatically resolves the orientation of a webcam by using a high-resolution digital elevation model and the webcam's position. This allows snow-classified pixels of webcam images to be related to their real-world coordinates. We present several examples of resulting snow cover maps, which have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or not visible from webcams' positions. The procedure is expected to work under almost any weather condition and demonstrates the feasibility of using webcams for the retrieval of high-resolution snow cover information.

Finding complex biological relationships in recent PubMed articles using Bio-LDA.

PubMed

Wang, Huijun; Ding, Ying; Tang, Jie; Dong, Xiao; He, Bing; Qiu, Judy; Wild, David J

2011-03-23

The overwhelming amount of available scholarly literature in the life sciences poses significant challenges to scientists wishing to keep up with important developments related to their research, but also provides a useful resource for the discovery of recent information concerning genes, diseases, compounds and the interactions between them. In this paper, we describe an algorithm called Bio-LDA that uses extracted biological terminology to automatically identify latent topics, and provides a variety of measures to uncover putative relations among topics and bio-terms. Relationships identified using those approaches are combined with existing data in life science datasets to provide additional insight. Three case studies demonstrate the utility of the Bio-LDA model, including association predication, association search and connectivity map generation. This combined approach offers new opportunities for knowledge discovery in many areas of biology including target identification, lead hopping and drug repurposing.

Finding Complex Biological Relationships in Recent PubMed Articles Using Bio-LDA

PubMed Central

Wang, Huijun; Ding, Ying; Tang, Jie; Dong, Xiao; He, Bing; Qiu, Judy; Wild, David J.

2011-01-01

The overwhelming amount of available scholarly literature in the life sciences poses significant challenges to scientists wishing to keep up with important developments related to their research, but also provides a useful resource for the discovery of recent information concerning genes, diseases, compounds and the interactions between them. In this paper, we describe an algorithm called Bio-LDA that uses extracted biological terminology to automatically identify latent topics, and provides a variety of measures to uncover putative relations among topics and bio-terms. Relationships identified using those approaches are combined with existing data in life science datasets to provide additional insight. Three case studies demonstrate the utility of the Bio-LDA model, including association predication, association search and connectivity map generation. This combined approach offers new opportunities for knowledge discovery in many areas of biology including target identification, lead hopping and drug repurposing. PMID:21448266

Using multi-terminology indexing for the assignment of MeSH descriptors to health resources in a French online catalogue.

PubMed

Pereira, Suzanne; Névéol, Aurélie; Kerdelhué, Gaétan; Serrot, Elisabeth; Joubert, Michel; Darmoni, Stéfan J

2008-11-06

To assist with the development of a French online quality-controlled health gateway(CISMeF), an automatic indexing tool assigning MeSH descriptors to medical text in French was created. The French Multi-Terminology Indexer (FMTI) relies on a multi-terminology approach involving four prominent medical terminologies and the mappings between them. In this paper,we compare lemmatization and stemming as methods to process French medical text for indexing. We also evaluate the multi-terminology approach implemented in F-MTI. The indexing strategies were assessed on a corpus of 18,814 resources indexed manually. There is little difference in the indexing performance when lemmatization or stemming is used. However, the multi-terminology approach outperforms indexing relying on a single terminology in terms of recall. F-MTI will soon be used in the CISMeF production environment and in a Health MultiTerminology Server in French.

The (De-)evolution of Evolution Games: A Content Analysis of the Representation of Evolution Through Natural Selection in Digital Games

NASA Astrophysics Data System (ADS)

Leith, Alex P.; Ratan, Rabindra A.; Wohn, Donghee Yvette

2016-08-01

Given the diversity and complexity of education game mechanisms and topics, this article contributes to a theoretical understanding of how game mechanisms "map" to educational topics through inquiry-based learning. Namely, the article examines the presence of evolution through natural selection (ENS) in digital games. ENS is a fundamentally important and widely misunderstood theory. This analysis of ENS portrayal in digital games provides insight into the use of games in teaching ENS. Systematic database search results were coded for the three principles of ENS: phenotypic variation, differential fitness, and fitness heritability. Though thousands of games use the term evolution, few presented elements of evolution, and even fewer contained all principles of ENS. Games developed to specifically teach evolution were difficult to find through Web searches. These overall deficiencies in ENS games reflect the inherent incompatibility between game control elements and the automatic process of ENS.

The effort to close the gap: tracking the development of illusory contour processing from childhood to adulthood with high-density electrical mapping.

PubMed

Altschuler, Ted S; Molholm, Sophie; Butler, John S; Mercier, Manuel R; Brandwein, Alice B; Foxe, John J

2014-04-15

The adult human visual system can efficiently fill-in missing object boundaries when low-level information from the retina is incomplete, but little is known about how these processes develop across childhood. A decade of visual-evoked potential (VEP) studies has produced a theoretical model identifying distinct phases of contour completion in adults. The first, termed a perceptual phase, occurs from approximately 100-200 ms and is associated with automatic boundary completion. The second is termed a conceptual phase occurring between 230 and 400 ms. The latter has been associated with the analysis of ambiguous objects which seem to require more effort to complete. The electrophysiological markers of these phases have both been localized to the lateral occipital complex, a cluster of ventral visual stream brain regions associated with object-processing. We presented Kanizsa-type illusory contour stimuli, often used for exploring contour completion processes, to neurotypical persons ages 6-31 (N=63), while parametrically varying the spatial extent of these induced contours, in order to better understand how filling-in processes develop across childhood and adolescence. Our results suggest that, while adults complete contour boundaries in a single discrete period during the automatic perceptual phase, children display an immature response pattern-engaging in more protracted processing across both timeframes and appearing to recruit more widely distributed regions which resemble those evoked during adult processing of higher-order ambiguous figures. However, children older than 5years of age were remarkably like adults in that the effects of contour processing were invariant to manipulation of contour extent. Copyright © 2013 Elsevier Inc. All rights reserved.

Variations in Medical Subject Headings (MeSH) mapping: from the natural language of patron terms to the controlled vocabulary of mapped lists*

PubMed Central

Gault, Lora V.; Shultz, Mary; Davies, Kathy J.

2002-01-01

Objectives: This study compared the mapping of natural language patron terms to the Medical Subject Headings (MeSH) across six MeSH interfaces for the MEDLINE database. Methods: Test data were obtained from search requests submitted by patrons to the Library of the Health Sciences, University of Illinois at Chicago, over a nine-month period. Search request statements were parsed into separate terms or phrases. Using print sources from the National Library of Medicine, Each parsed patron term was assigned corresponding MeSH terms. Each patron term was entered into each of the selected interfaces to determine how effectively they mapped to MeSH. Data were collected for mapping success, accessibility of MeSH term within mapped list, and total number of MeSH choices within each list. Results: The selected MEDLINE interfaces do not map the same patron term in the same way, nor do they consistently lead to what is considered the appropriate MeSH term. Conclusions: If searchers utilize the MEDLINE database to its fullest potential by mapping to MeSH, the results of the mapping will vary between interfaces. This variance may ultimately impact the search results. These differences should be considered when choosing a MEDLINE interface and when instructing end users. PMID:11999175

Variations in Medical Subject Headings (MeSH) mapping: from the natural language of patron terms to the controlled vocabulary of mapped lists.

PubMed

Gault, Lora V; Shultz, Mary; Davies, Kathy J

2002-04-01

This study compared the mapping of natural language patron terms to the Medical Subject Headings (MeSH) across six MeSH interfaces for the MEDLINE database. Test data were obtained from search requests submitted by patrons to the Library of the Health Sciences, University of Illinois at Chicago, over a nine-month period. Search request statements were parsed into separate terms or phrases. Using print sources from the National Library of Medicine, Each parsed patron term was assigned corresponding MeSH terms. Each patron term was entered into each of the selected interfaces to determine how effectively they mapped to MeSH. Data were collected for mapping success, accessibility of MeSH term within mapped list, and total number of MeSH choices within each list. The selected MEDLINE interfaces do not map the same patron term in the same way, nor do they consistently lead to what is considered the appropriate MeSH term. If searchers utilize the MEDLINE database to its fullest potential by mapping to MeSH, the results of the mapping will vary between interfaces. This variance may ultimately impact the search results. These differences should be considered when choosing a MEDLINE interface and when instructing end users.

Automatic violence detection in digital movies

NASA Astrophysics Data System (ADS)

Fischer, Stephan

1996-11-01

Research on computer-based recognition of violence is scant. We are working on the automatic recognition of violence in digital movies, a first step towards the goal of a computer- assisted system capable of protecting children against TV programs containing a great deal of violence. In the video domain a collision detection and a model-mapping to locate human figures are run, while the creation and comparison of fingerprints to find certain events are run int he audio domain. This article centers on the recognition of fist- fights in the video domain and on the recognition of shots, explosions and cries in the audio domain.

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring in large area and high resolution image sequences. The change detection and analysis algorithm developed could be adapted to many potential image change scenarios to perform automatic large scale analysis of change.

WE-AB-BRA-05: Fully Automatic Segmentation of Male Pelvic Organs On CT Without Manual Intervention

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

Gao, Y; Lian, J; Chen, R

Purpose: We aim to develop a fully automatic tool for accurate contouring of major male pelvic organs in CT images for radiotherapy without any manual initialization, yet still achieving superior performance than the existing tools. Methods: A learning-based 3D deformable shape model was developed for automatic contouring. Specifically, we utilized a recent machine learning method, random forest, to jointly learn both image regressor and classifier for each organ. In particular, the image regressor is trained to predict the 3D displacement from each vertex of the 3D shape model towards the organ boundary based on the local image appearance around themore » location of this vertex. The predicted 3D displacements are then used to drive the 3D shape model towards the target organ. Once the shape model is deformed close to the target organ, it is further refined by an organ likelihood map estimated by the learned classifier. As the organ likelihood map provides good guideline for the organ boundary, the precise contouring Result could be achieved, by deforming the 3D shape model locally to fit boundaries in the organ likelihood map. Results: We applied our method to 29 previously-treated prostate cancer patients, each with one planning CT scan. Compared with manually delineated pelvic organs, our method obtains overlap ratios of 85.2%±3.74% for the prostate, 94.9%±1.62% for the bladder, and 84.7%±1.97% for the rectum, respectively. Conclusion: This work demonstrated feasibility of a novel machine-learning based approach for accurate and automatic contouring of major male pelvic organs. It shows the potential to replace the time-consuming and inconsistent manual contouring in the clinic. Also, compared with the existing works, our method is more accurate and also efficient since it does not require any manual intervention, such as manual landmark placement. Moreover, our method obtained very similar contouring results as the clinical experts. Project is partially support by a grant from NCI 1R01CA140413.« less

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

The role of surgery in the treatment of post-infarction ventricular tachycardia. A 5 year experience.

PubMed

Martinelli, L; Goggi, C; Graffigna, A; Salerno, J A; Chimienti, M; Klersy, C; Viganò, M

1987-01-01

The purpose of this report is to present a 5 year experience in electrophysiologically guided surgical treatment of post-infarction ventricular tachycardia (VT) in a consecutive series of 39 patients. In every case the arrhythmia was not responsive to pluripharmacological therapy. The diagnostic steps included preoperative endocardial, intraoperative epi- and endocardial mapping, automatically carried out when possible. Surgical techniques were: classic Guiraudon's encircling endocardial ventriculotomy (EEV), partial EEV, endocardial resection (ER), cryoablation or combined procedures. The hospital mortality was of 4 patients (10%). During the follow-up period (1-68 mo), 4 patients (11%) died of cardiac non-VT related causes. Among the survivors, 90% are in sinus rhythm. The authors consider electrophysiologically guided surgery a safe and reliable method for the treatment of post-infarction VT and suggest more extensive indications. They stress the importance of automatic mapping in pleomorphic and non-sustained VT, and the necessity of tailoring the surgical technique to the characteristics of each case.

Ventricular tachycardia in post-myocardial infarction patients. Results of surgical therapy.

PubMed

Viganò, M; Martinelli, L; Salerno, J A; Minzioni, G; Chimienti, M; Graffigna, A; Goggi, C; Klersy, C; Montemartini, C

1986-05-01

This report addresses the problems related to surgical treatment of post-infarction ventricular tachycardia (VT) and is based on a 5 year experience of 36 consecutive patients. In every case the arrhythmia was unresponsive to pharmacological therapy. All patients were operated on after the completion of a diagnostic protocol including preoperative endocardial, intra-operative epi-endocardial mapping, the latter performed automatically when possible. Surgical techniques were: classical Guiraudon's encircling endocardial ventriculotomy (EEV); partial EEV, endocardial resection (ER); cryoablation or a combination of these procedures. The in-hospital mortality (30 days) was 8.3% (3 patients). During the follow-up period (1-68 months), 3 patients (9%) died of cardiac but not VT related causes. Of the survivors, 92% are VT-free. We consider electrophysiologically guided surgery a safe and reliable method for the treatment of post-infarction VT and suggest its more extensive use. We stress the importance of automatic mapping in pleomorphic and non-sustained VT, and the necessity of tailoring the surgical technique to the characteristics of each case.

Glacier Frontal Line Extraction from SENTINEL-1 SAR Imagery in Prydz Area

NASA Astrophysics Data System (ADS)

Li, F.; Wang, Z.; Zhang, S.; Zhang, Y.

2018-04-01

Synthetic Aperture Radar (SAR) can provide all-day and all-night observation of the earth in all-weather conditions with high resolution, and it is widely used in polar research including sea ice, sea shelf, as well as the glaciers. For glaciers monitoring, the frontal position of a calving glacier at different moments of time is of great importance, which indicates the estimation of the calving rate and flux of the glaciers. In this abstract, an automatic algorithm for glacier frontal extraction using time series Sentinel-1 SAR imagery is proposed. The technique transforms the amplitude imagery of Sentinel-1 SAR into a binary map using SO-CFAR method, and then frontal points are extracted using profile method which reduces the 2D binary map to 1D binary profiles, the final frontal position of a calving glacier is the optimal profile selected from the different average segmented profiles. The experiment proves that the detection algorithm for SAR data can automatically extract the frontal position of glacier with high efficiency.

Geometrical and topological issues in octree based automatic meshing

NASA Technical Reports Server (NTRS)

Saxena, Mukul; Perucchio, Renato

1987-01-01

Finite element meshes derived automatically from solid models through recursive spatial subdivision schemes (octrees) can be made to inherit the hierarchical structure and the spatial addressability intrinsic to the underlying grid. These two properties, together with the geometric regularity that can also be built into the mesh, make octree based meshes ideally suited for efficient analysis and self-adaptive remeshing and reanalysis. The element decomposition of the octal cells that intersect the boundary of the domain is discussed. The problem, central to octree based meshing, is solved by combining template mapping and element extraction into a procedure that utilizes both constructive solid geometry and boundary representation techniques. Boundary cells that are not intersected by the edge of the domain boundary are easily mapped to predefined element topology. Cells containing edges (and vertices) are first transformed into a planar polyhedron and then triangulated via element extractor. The modeling environments required for the derivation of planar polyhedra and for element extraction are analyzed.

Octree based automatic meshing from CSG models

NASA Technical Reports Server (NTRS)

Perucchio, Renato

1987-01-01

Finite element meshes derived automatically from solid models through recursive spatial subdivision schemes (octrees) can be made to inherit the hierarchical structure and the spatial addressability intrinsic to the underlying grid. These two properties, together with the geometric regularity that can also be built into the mesh, make octree based meshes ideally suited for efficient analysis and self-adaptive remeshing and reanalysis. The element decomposition of the octal cells that intersect the boundary of the domain is emphasized. The problem, central to octree based meshing, is solved by combining template mapping and element extraction into a procedure that utilizes both constructive solid geometry and boundary respresentation techniques. Boundary cells that are not intersected by the edge of the domain boundary are easily mapped to predefined element topology. Cells containing edges (and vertices) are first transformed into a planar polyhedron and then triangulated via element extractors. The modeling environments required for the derivation of planar polyhedra and for element extraction are analyzed.

High-order space charge effects using automatic differentiation

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

Reusch, Michael F.; Bruhwiler, David L.; Computer Accelerator Physics Conference Williamsburg, Virginia 1996

1997-02-01

The Northrop Grumman Topkark code has been upgraded to Fortran 90, making use of operator overloading, so the same code can be used to either track an array of particles or construct a Taylor map representation of the accelerator lattice. We review beam optics and beam dynamics simulations conducted with TOPKARK in the past and we present a new method for modeling space charge forces to high-order with automatic differentiation. This method generates an accurate, high-order, 6-D Taylor map of the phase space variable trajectories for a bunched, high-current beam. The spatial distribution is modeled as the product of amore » Taylor Series times a Gaussian. The variables in the argument of the Gaussian are normalized to the respective second moments of the distribution. This form allows for accurate representation of a wide range of realistic distributions, including any asymmetries, and allows for rapid calculation of the space charge fields with free space boundary conditions. An example problem is presented to illustrate our approach.« less

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

PubMed Central

2012-01-01

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

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

PubMed

Newton, Richard; Deonarine, Andrew; Wernisch, Lorenz

2012-09-24

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

Black hole thermodynamics from a variational principle: asymptotically conical backgrounds

DOE PAGES

An, Ok Song; Cvetič, Mirjam; Papadimitriou, Ioannis

2016-03-14

The variational problem of gravity theories is directly related to black hole thermodynamics. For asymptotically locally AdS backgrounds it is known that holographic renormalization results in a variational principle in terms of equivalence classes of boundary data under the local asymptotic symmetries of the theory, which automatically leads to finite conserved charges satisfying the first law of thermodynamics. We show that this connection holds well beyond asymptotically AdS black holes. In particular, we formulate the variational problem for N = 2 STU supergravity in four dimensions with boundary conditions corresponding to those obeyed by the so called ‘subtracted geometries’. Wemore » show that such boundary conditions can be imposed covariantly in terms of a set of asymptotic second class constraints, and we derive the appropriate boundary terms that render the variational problem well posed in two different duality frames of the STU model. This allows us to define finite conserved charges associated with any asymptotic Killing vector and to demonstrate that these charges satisfy the Smarr formula and the first law of thermodynamics. Moreover, by uplifting the theory to five dimensions and then reducing on a 2-sphere, we provide a precise map between the thermodynamic observables of the subtracted geometries and those of the BTZ black hole. Finally, surface terms play a crucial role in this identification.« less

Black hole thermodynamics from a variational principle: asymptotically conical backgrounds

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

An, Ok Song; Cvetič, Mirjam; Papadimitriou, Ioannis

The variational problem of gravity theories is directly related to black hole thermodynamics. For asymptotically locally AdS backgrounds it is known that holographic renormalization results in a variational principle in terms of equivalence classes of boundary data under the local asymptotic symmetries of the theory, which automatically leads to finite conserved charges satisfying the first law of thermodynamics. We show that this connection holds well beyond asymptotically AdS black holes. In particular, we formulate the variational problem for N = 2 STU supergravity in four dimensions with boundary conditions corresponding to those obeyed by the so called ‘subtracted geometries’. Wemore » show that such boundary conditions can be imposed covariantly in terms of a set of asymptotic second class constraints, and we derive the appropriate boundary terms that render the variational problem well posed in two different duality frames of the STU model. This allows us to define finite conserved charges associated with any asymptotic Killing vector and to demonstrate that these charges satisfy the Smarr formula and the first law of thermodynamics. Moreover, by uplifting the theory to five dimensions and then reducing on a 2-sphere, we provide a precise map between the thermodynamic observables of the subtracted geometries and those of the BTZ black hole. Finally, surface terms play a crucial role in this identification.« less

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN

PubMed Central

2018-01-01

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μController-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 16 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection. PMID:29677147

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN.

PubMed

Alsina-Pagès, Rosa Ma; Alías, Francesc; Socoró, Joan Claudi; Orga, Ferran

2018-04-20

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 1 6 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.

Photogrammetric Accuracy and Modeling of Rolling Shutter Cameras

NASA Astrophysics Data System (ADS)

Ye, W.; Qiao, G.; Kong, F.; Guo, S.; Ma, X.; Tong, X.; Li, R.

2016-06-01

Global climate change is one of the major challenges that all nations are commonly facing. Long-term observations of the Antarctic ice sheet have been playing a critical role in quantitatively estimating and predicting effects resulting from the global changes. The film-based ARGON reconnaissance imagery provides a remarkable data source for studying the Antarctic ice-sheet in 1960s, thus greatly extending the time period of Antarctica surface observations. To deal with the low-quality images and the unavailability of camera poses, a systematic photogrammetric approach is proposed to reconstruct the interior and exterior orientation information for further glacial mapping applications, including ice flow velocity mapping and mass balance estimation. Some noteworthy details while performing geometric modelling using the ARGON images were introduced, including methods and results for handling specific effects of film deformation, damaged or missing fiducial marks and calibration report, automatic fiducial mark detection, control point selection through Antarctic shadow and ice surface terrain analysis, and others. Several sites in East Antarctica were tested. As an example, four images in the Byrd glacier region were used to assess the accuracy of the geometric modelling. A digital elevation model (DEM) and an orthophoto map of Byrd glacier were generated. The accuracy of the ground positions estimated by using independent check points is within one nominal pixel of 140 m of ARGON imagery. Furthermore, a number of significant features, such as ice flow velocity and regional change patterns, will be extracted and analysed.

EuroPhenome: a repository for high-throughput mouse phenotyping data

PubMed Central

Morgan, Hugh; Beck, Tim; Blake, Andrew; Gates, Hilary; Adams, Niels; Debouzy, Guillaume; Leblanc, Sophie; Lengger, Christoph; Maier, Holger; Melvin, David; Meziane, Hamid; Richardson, Dave; Wells, Sara; White, Jacqui; Wood, Joe; de Angelis, Martin Hrabé; Brown, Steve D. M.; Hancock, John M.; Mallon, Ann-Marie

2010-01-01

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies. PMID:19933761

Reduced age-related degeneration of the hippocampal subiculum in long-term meditators.

PubMed

Kurth, Florian; Cherbuin, Nicolas; Luders, Eileen

2015-06-30

Normal aging is known to result in a reduction of gray matter within the hippocampal complex, particularly in the subiculum. The present study was designed to address the question whether the practice of meditation can amend this age-related subicular atrophy. For this purpose, we established the correlations between subicular volume and chronological age within 50 long-term meditators and 50 control subjects. High-resolution magnetic resonance imaging (MRI) scans were automatically processed combining cytoarchitectonically defined probabilistic maps with advanced tissue segmentation and registration methods. Overall, we observed steeper negative regression slopes in controls. The analysis further revealed a significant group-by-age interaction for the left subiculum with a significant negative correlation between age and subicular volume in controls, but no significant correlation in meditators. Altogether, these findings seem to suggest a reduced age-related atrophy of the left subiculum in meditators compared to healthy controls. Possible explanations might be a relative increase of subicular tissue over time through long-term training as meditation is a process that incorporates regular and ongoing mental efforts. Alternatively, because meditation is an established form of reducing stress, our observation might reflect an overall preservation of subicular tissue through a reduced neuronal vulnerability to negative effects of stress. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

NASA Astrophysics Data System (ADS)

Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

2015-03-01

Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of the ratio algorithm. The differences in the characteristics of the two satellite imageries in terms of spatial and spectral resolution can play an important role in the estimation and detection of the shadow of urban objects.

Extending gene ontology with gene association networks.

PubMed

Peng, Jiajie; Wang, Tao; Wang, Jixuan; Wang, Yadong; Chen, Jin

2016-04-15

Gene ontology (GO) is a widely used resource to describe the attributes for gene products. However, automatic GO maintenance remains to be difficult because of the complex logical reasoning and the need of biological knowledge that are not explicitly represented in the GO. The existing studies either construct whole GO based on network data or only infer the relations between existing GO terms. None is purposed to add new terms automatically to the existing GO. We proposed a new algorithm 'GOExtender' to efficiently identify all the connected gene pairs labeled by the same parent GO terms. GOExtender is used to predict new GO terms with biological network data, and connect them to the existing GO. Evaluation tests on biological process and cellular component categories of different GO releases showed that GOExtender can extend new GO terms automatically based on the biological network. Furthermore, we applied GOExtender to the recent release of GO and discovered new GO terms with strong support from literature. Software and supplementary document are available at www.msu.edu/%7Ejinchen/GOExtender jinchen@msu.edu or ydwang@hit.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Updating National Topographic Data Base Using Change Detection Methods

NASA Astrophysics Data System (ADS)

Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

2016-06-01

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

An automatic approach for rice mapping in temperate region using time series of MODIS imagery: first results for Mediterranean environment

NASA Astrophysics Data System (ADS)

Boschetti, M.; Nelson, A.; Manfrom, G.; Brivio, P. A.

2012-04-01

Timely and accurate information on crop typology and status are required to support suitable action to better manage agriculture production and reduce food insecurity. More specifically, regional crop masking and phenological information are important inputs for spatialized crop growth models for yield forecasting systems. Digital cartographic data available at global/regional scale, such as GLC2000, GLOBCOVER or MODIS land cover products (MOD12), are often not adequate for this crop modeling application. For this reason, there is a need to develop and test methods that can provide such information for specific cropsusing automated classification techniques.. In this framework we focused our analysis on the rice cultivation area detection due to the importance of this crop. Rice is a staple food for half of the world's population (FAO 2004). Over 90% of the world's rice is produced and consumed in Asia and the region is home to 70% of the world's poor, most of whom depend on rice for their livelihoods andor food security. Several initiatives are being promoted at the international level to provide maps of rice cultivated areas in South and South East Asia using different approaches available in literature for rice mapping in tropical regions. We contribute to these efforts by proposing an automatic method to detect rice cultivated areas in temperate regions exploiting MODIS 8-Day composite of Surface Reflectance at 500m spatial resolution (MOD09A1product). Temperate rice is cultivated worldwide in more than 20 countries covering around 16M ha for a total production of about 65M tons of paddy per year. The proposed method is based on a common approach available in literature that first identifies flood condition that can be related to rice agronomic practice and then checks for vegetation growth. The method presents innovative aspects related both to the flood detection, exploiting Short Wave Infrared spectral information, and to the crop grow monitoring analyzing vegetation index seasonal trend. Tests conducted in European Mediterranean environment demonstrated that our approach is able to provide accurate rice map (User Accuracy > 80%) when compared to available Corine Land Cover land use map (1:100.000 scale, MMU 25 ha). Map accuracy in term of omission and commission error has been analyzed in north of Italy where about 60 % of total European riceis produced. For this study area thematic cartography at 1:10.000scale allowed to analyze the type of commission errors and evaluate the entity of omission errors in relation to low resolution bias and/or algorithm performance. Pareto boundary method has been used to assess the level of accuracy of the method respect a maximum achievable accuracy with medium resolution MODIS data. Results demonstrate that the proposed approach outperform the method developed for tropical and sub-tropical environment.

Presentation video retrieval using automatically recovered slide and spoken text

NASA Astrophysics Data System (ADS)

Cooper, Matthew

2013-03-01

Video is becoming a prevalent medium for e-learning. Lecture videos contain text information in both the presentation slides and lecturer's speech. This paper examines the relative utility of automatically recovered text from these sources for lecture video retrieval. To extract the visual information, we automatically detect slides within the videos and apply optical character recognition to obtain their text. Automatic speech recognition is used similarly to extract spoken text from the recorded audio. We perform controlled experiments with manually created ground truth for both the slide and spoken text from more than 60 hours of lecture video. We compare the automatically extracted slide and spoken text in terms of accuracy relative to ground truth, overlap with one another, and utility for video retrieval. Results reveal that automatically recovered slide text and spoken text contain different content with varying error profiles. Experiments demonstrate that automatically extracted slide text enables higher precision video retrieval than automatically recovered spoken text.

Automated, on-board terrain analysis for precision landings

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.; Hines, Glenn D.

2006-01-01

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform|multi-scale retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the vs produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the msr has proven to be a very strong enhancement engine, the other elements of the approach|the vs, terrain map generation, and smoothness-based segmentation|are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown.

An Anomalous Noise Events Detector for Dynamic Road Traffic Noise Mapping in Real-Life Urban and Suburban Environments

PubMed Central

2017-01-01

One of the main aspects affecting the quality of life of people living in urban and suburban areas is their continued exposure to high Road Traffic Noise (RTN) levels. Until now, noise measurements in cities have been performed by professionals, recording data in certain locations to build a noise map afterwards. However, the deployment of Wireless Acoustic Sensor Networks (WASN) has enabled automatic noise mapping in smart cities. In order to obtain a reliable picture of the RTN levels affecting citizens, Anomalous Noise Events (ANE) unrelated to road traffic should be removed from the noise map computation. To this aim, this paper introduces an Anomalous Noise Event Detector (ANED) designed to differentiate between RTN and ANE in real time within a predefined interval running on the distributed low-cost acoustic sensors of a WASN. The proposed ANED follows a two-class audio event detection and classification approach, instead of multi-class or one-class classification schemes, taking advantage of the collection of representative acoustic data in real-life environments. The experiments conducted within the DYNAMAP project, implemented on ARM-based acoustic sensors, show the feasibility of the proposal both in terms of computational cost and classification performance using standard Mel cepstral coefficients and Gaussian Mixture Models (GMM). The two-class GMM core classifier relatively improves the baseline universal GMM one-class classifier F1 measure by 18.7% and 31.8% for suburban and urban environments, respectively, within the 1-s integration interval. Nevertheless, according to the results, the classification performance of the current ANED implementation still has room for improvement. PMID:29023397

A new tool for rapid and automatic estimation of earthquake source parameters and generation of seismic bulletins

NASA Astrophysics Data System (ADS)

Zollo, Aldo

2016-04-01

RISS S.r.l. is a Spin-off company recently born from the initiative of the research group constituting the Seismology Laboratory of the Department of Physics of the University of Naples Federico II. RISS is an innovative start-up, based on the decade-long experience in earthquake monitoring systems and seismic data analysis of its members and has the major goal to transform the most recent innovations of the scientific research into technological products and prototypes. With this aim, RISS has recently started the development of a new software, which is an elegant solution to manage and analyse seismic data and to create automatic earthquake bulletins. The software has been initially developed to manage data recorded at the ISNet network (Irpinia Seismic Network), which is a network of seismic stations deployed in Southern Apennines along the active fault system responsible for the 1980, November 23, MS 6.9 Irpinia earthquake. The software, however, is fully exportable and can be used to manage data from different networks, with any kind of station geometry or network configuration and is able to provide reliable estimates of earthquake source parameters, whichever is the background seismicity level of the area of interest. Here we present the real-time automated procedures and the analyses performed by the software package, which is essentially a chain of different modules, each of them aimed at the automatic computation of a specific source parameter. The P-wave arrival times are first detected on the real-time streaming of data and then the software performs the phase association and earthquake binding. As soon as an event is automatically detected by the binder, the earthquake location coordinates and the origin time are rapidly estimated, using a probabilistic, non-linear, exploration algorithm. Then, the software is able to automatically provide three different magnitude estimates. First, the local magnitude (Ml) is computed, using the peak-to-peak amplitude of the equivalent Wood-Anderson displacement recordings. The moment magnitude (Mw) is then estimated from the inversion of displacement spectra. The duration magnitude (Md) is rapidly computed, based on a simple and automatic measurement of the seismic wave coda duration. Starting from the magnitude estimates, other relevant pieces of information are also computed, such as the corner frequency, the seismic moment, the source radius and the seismic energy. The ground-shaking maps on a Google map are produced, for peak ground acceleration (PGA), peak ground velocity (PGV) and instrumental intensity (in SHAKEMAP® format), or a plot of the measured peak ground values. Furthermore, based on a specific decisional scheme, the automatic discrimination between local earthquakes occurred within the network and regional/teleseismic events occurred outside the network is performed. Finally, for largest events, if a consistent number of P-wave polarity reading are available, the focal mechanism is also computed. For each event, all of the available pieces of information are stored in a local database and the results of the automatic analyses are published on an interactive web page. "The Bulletin" shows a map with event location and stations, as well as a table listing all the events, with the associated parameters. The catalogue fields are the event ID, the origin date and time, latitude, longitude, depth, Ml, Mw, Md, the number of triggered stations, the S-displacement spectra, and shaking maps. Some of these entries also provide additional information, such as the focal mechanism (when available). The picked traces are uploaded in the database and from the web interface of the Bulletin the traces can be download for more specific analysis. This innovative software represents a smart solution, with a friendly and interactive interface, for high-level analysis of seismic data analysis and it may represent a relevant tool not only for seismologists, but also for non-expert external users who are interested in the seismological data. The software is a valid tool for the automatic analysis of the background seismicity at different time scales and can be a relevant tool for the monitoring of both natural and induced seismicity.

Biomedical Terminology Mapper for UML projects.

PubMed

Thibault, Julien C; Frey, Lewis

2013-01-01

As the biomedical community collects and generates more and more data, the need to describe these datasets for exchange and interoperability becomes crucial. This paper presents a mapping algorithm that can help developers expose local implementations described with UML through standard terminologies. The input UML class or attribute name is first normalized and tokenized, then lookups in a UMLS-based dictionary are performed. For the evaluation of the algorithm 142 UML projects were extracted from caGrid and automatically mapped to National Cancer Institute (NCI) terminology concepts. Resulting mappings at the UML class and attribute levels were compared to the manually curated annotations provided in caGrid. Results are promising and show that this type of algorithm could speed-up the tedious process of mapping local implementations to standard biomedical terminologies.

Biomedical Terminology Mapper for UML projects

PubMed Central

Thibault, Julien C.; Frey, Lewis

As the biomedical community collects and generates more and more data, the need to describe these datasets for exchange and interoperability becomes crucial. This paper presents a mapping algorithm that can help developers expose local implementations described with UML through standard terminologies. The input UML class or attribute name is first normalized and tokenized, then lookups in a UMLS-based dictionary are performed. For the evaluation of the algorithm 142 UML projects were extracted from caGrid and automatically mapped to National Cancer Institute (NCI) terminology concepts. Resulting mappings at the UML class and attribute levels were compared to the manually curated annotations provided in caGrid. Results are promising and show that this type of algorithm could speed-up the tedious process of mapping local implementations to standard biomedical terminologies. PMID:24303278

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

PubMed

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-09-11

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

Automatic Text Decomposition and Structuring.

ERIC Educational Resources Information Center

Salton, Gerard; And Others

1996-01-01

Text similarity measurements are used to determine relationships between natural-language texts and text excerpts. The resulting linked hypertext maps can be broken down into text segments and themes used to identify different text types and structures, leading to improved information access and utilization. Examples are provided for text…

Pavement type and wear condition classification from tire cavity acoustic measurements with artificial neural networks.

PubMed

Masino, Johannes; Foitzik, Michael-Jan; Frey, Michael; Gauterin, Frank

2017-06-01

Tire road noise is the major contributor to traffic noise, which leads to general annoyance, speech interference, and sleep disturbances. Standardized methods to measure tire road noise are expensive, sophisticated to use, and they cannot be applied comprehensively. This paper presents a method to automatically classify different types of pavement and the wear condition to identify noisy road surfaces. The methods are based on spectra of time series data of the tire cavity sound, acquired under normal vehicle operation. The classifier, an artificial neural network, correctly predicts three pavement types, whereas there are few bidirectional mis-classifications for two pavements, which have similar physical characteristics. The performance measures of the classifier to predict a new or worn out condition are over 94.6%. One could create a digital map with the output of the presented method. On the basis of these digital maps, road segments with a strong impact on tire road noise could be automatically identified. Furthermore, the method can estimate the road macro-texture, which has an impact on the tire road friction especially on wet conditions. Overall, this digital map would have a great benefit for civil engineering departments, road infrastructure operators, and for advanced driver assistance systems.

Visual Uav Trajectory Plan System Based on Network Map

NASA Astrophysics Data System (ADS)

Li, X. L.; Lin, Z. J.; Su, G. Z.; Wu, B. Y.

2012-07-01

The base map of the current software UP-30 using in trajectory plan for Unmanned Aircraft Vehicle is vector diagram. UP-30 draws navigation points manually. But in the field of operation process, the efficiency and the quality of work is influenced because of insufficient information, screen reflection, calculate inconveniently and other factors. If we do this work in indoor, the effect of external factors on the results would be eliminated, the network earth users can browse the free world high definition satellite images through downloading a client software, and can export the high resolution image by standard file format. This brings unprecedented convenient of trajectory plan. But the images must be disposed by coordinate transformation, geometric correction. In addition, according to the requirement of mapping scale ,camera parameters and overlap degree we can calculate exposure hole interval and trajectory distance between the adjacent trajectory automatically . This will improve the degree of automation of data collection. Software will judge the position of next point according to the intersection of the trajectory and the survey area and ensure the position of point according to trajectory distance. We can undertake the points artificially. So the trajectory plan is automatic and flexible. Considering safety, the date can be used in flying after simulating flight. Finally we can export all of the date using a key

Structural knowledge learning from maps for supervised land cover/use classification: Application to the monitoring of land cover/use maps in French Guiana

NASA Astrophysics Data System (ADS)

Bayoudh, Meriam; Roux, Emmanuel; Richard, Gilles; Nock, Richard

2015-03-01

The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.

Semi-automatic mapping for identifying complex geobodies in seismic images

NASA Astrophysics Data System (ADS)

Domínguez-C, Raymundo; Romero-Salcedo, Manuel; Velasquillo-Martínez, Luis G.; Shemeretov, Leonid

2017-03-01

Seismic images are composed of positive and negative seismic wave traces with different amplitudes (Robein 2010 Seismic Imaging: A Review of the Techniques, their Principles, Merits and Limitations (Houten: EAGE)). The association of these amplitudes together with a color palette forms complex visual patterns. The color intensity of such patterns is directly related to impedance contrasts: the higher the contrast, the higher the color intensity. Generally speaking, low impedance contrasts are depicted with low tone colors, creating zones with different patterns whose features are not evident for a 3D automated mapping option available on commercial software. In this work, a workflow for a semi-automatic mapping of seismic images focused on those areas with low-intensity colored zones that may be associated with geobodies of petroleum interest is proposed. The CIE L*A*B* color space was used to perform the seismic image processing, which helped find small but significant differences between pixel tones. This process generated binary masks that bound color regions to low-intensity colors. The three-dimensional-mask projection allowed the construction of 3D structures for such zones (geobodies). The proposed method was applied to a set of digital images from a seismic cube and tested on four representative study cases. The obtained results are encouraging because interesting geobodies are obtained with a minimum of information.

An overview of animal science research 1945-2011 through science mapping analysis.

PubMed

Rodriguez-Ledesma, A; Cobo, M J; Lopez-Pujalte, C; Herrera-Viedma, E

2015-12-01

The conceptual structure of the field of Animal Science (AS) research is examined by means of a longitudinal science mapping analysis. The whole of the AS research field is analysed, revealing its conceptual evolution. To this end, an automatic approach to detecting and visualizing hidden themes or topics and their evolution across a consecutive span of years was applied to AS publications of the JCR category 'Agriculture, Dairy & Animal Science' during the period 1945-2011. This automatic approach was based on a coword analysis and combines performance analysis and science mapping. To observe the conceptual evolution of AS, six consecutive periods were defined: 1945-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2005 and 2006-2011. Research in AS was identified as having focused on ten main thematic areas: ANIMAL-FEEDING, SMALL-RUMINANTS, ANIMAL-REPRODUCTION, DAIRY-PRODUCTION, MEAT-QUALITY, SWINE-PRODUCTION, GENETICS-AND-ANIMAL-BREEDING, POULTRY, ANIMAL-WELFARE and GROWTH-FACTORS-AND-FATTY-ACIDS. The results show how genomic studies gain in weight and integrate with other thematic areas. The whole of AS research has become oriented towards an overall framework in which animal welfare, sustainable management and human health play a major role. All this would affect the future structure and management of livestock farming. © 2014 Blackwell Verlag GmbH.

Change detection and classification in brain MR images using change vector analysis.

PubMed

Simões, Rita; Slump, Cornelis

2011-01-01

The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases--such as Alzheimer's--focus on large-scale brain deformations. However, such patients often have other brain impairments, such as infarcts, white matter lesions and hemorrhages, which are typically overlooked by the deformation-based methods. Other unsupervised change detection algorithms have been proposed to detect tissue intensity changes. The outcome of these methods is typically a binary change map, which identifies changed brain regions. However, understanding what types of changes these regions underwent is likely to provide equally important information about lesion evolution. In this paper, we present an unsupervised 3D change detection method based on Change Vector Analysis. We compute and automatically threshold the Generalized Likelihood Ratio map to obtain a binary change map. Subsequently, we perform histogram-based clustering to classify the change vectors. We obtain a Kappa Index of 0.82 using various types of simulated lesions. The classification error is 2%. Finally, we are able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients.

Progress satellite: An automatic cargo spacecraft. [for resupplying orbital space stations

NASA Technical Reports Server (NTRS)

Novikov, N.

1978-01-01

The requirement for resupplying long term orbital space stations is discussed. The operation of Progress (an unmanned automatic resupply spacecraft) is described. It concludes that the development of Progress is a major contribution of Soviet science to domestic and world aeronautics.

Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

PubMed

Hu, Peijun; Wu, Fa; Peng, Jialin; Bao, Yuanyuan; Chen, Feng; Kong, Dexing

2017-03-01

Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images. The proposed method employs deep fully convolutional neural networks (CNNs) for organ detection and segmentation, which is further refined by a time-implicit multi-phase evolution method. Firstly, a 3D CNN is trained to automatically localize and delineate the organs of interest with a probability prediction map. The learned probability map provides both subject-specific spatial priors and initialization for subsequent fine segmentation. Then, for the refinement of the multi-organ segmentation, image intensity models, probability priors as well as a disjoint region constraint are incorporated into an unified energy functional. Finally, a novel time-implicit multi-phase level-set algorithm is utilized to efficiently optimize the proposed energy functional model. Our method has been evaluated on 140 abdominal CT scans for the segmentation of four organs (liver, spleen and both kidneys). With respect to the ground truth, average Dice overlap ratios for the liver, spleen and both kidneys are 96.0, 94.2 and 95.4%, respectively, and average symmetric surface distance is less than 1.3 mm for all the segmented organs. The computation time for a CT volume is 125 s in average. The achieved accuracy compares well to state-of-the-art methods with much higher efficiency. A fully automatic method for multi-organ segmentation from abdominal CT images was developed and evaluated. The results demonstrated its potential in clinical usage with high effectiveness, robustness and efficiency.

Route learning in Korsakoff's syndrome: Residual acquisition of spatial memory despite profound amnesia.

PubMed

Oudman, Erik; Van der Stigchel, Stefan; Nijboer, Tanja C W; Wijnia, Jan W; Seekles, Maaike L; Postma, Albert

2016-03-01

Korsakoff's syndrome (KS) is characterized by explicit amnesia, but relatively spared implicit memory. The aim of this study was to assess to what extent KS patients can acquire spatial information while performing a spatial navigation task. Furthermore, we examined whether residual spatial acquisition in KS was based on automatic or effortful coding processes. Therefore, 20 KS patients and 20 matched healthy controls performed six tasks on spatial navigation after they navigated through a residential area. Ten participants per group were instructed to pay close attention (intentional condition), while 10 received mock instructions (incidental condition). KS patients showed hampered performance on a majority of tasks, yet their performance was superior to chance level on a route time and distance estimation tasks, a map drawing task and a route walking task. Performance was relatively spared on the route distance estimation task, but there were large variations between participants. Acquisition in KS was automatic rather than effortful, since no significant differences were obtained between the intentional and incidental condition on any task, whereas for the healthy controls, the intention to learn was beneficial for the map drawing task and the route walking task. The results of this study suggest that KS patients are still able to acquire spatial information during navigation on multiple domains despite the presence of the explicit amnesia. Residual acquisition is most likely based on automatic coding processes. © 2014 The British Psychological Society.

Water Mapping Using Multispectral Airborne LIDAR Data

NASA Astrophysics Data System (ADS)

Yan, W. Y.; Shaker, A.; LaRocque, P. E.

2018-04-01

This study investigates the use of the world's first multispectral airborne LiDAR sensor, Optech Titan, manufactured by Teledyne Optech to serve the purpose of automatic land-water classification with a particular focus on near shore region and river environment. Although there exist recent studies utilizing airborne LiDAR data for shoreline detection and water surface mapping, the majority of them only perform experimental testing on clipped data subset or rely on data fusion with aerial/satellite image. In addition, most of the existing approaches require manual intervention or existing tidal/datum data for sample collection of training data. To tackle the drawbacks of previous approaches, we propose and develop an automatic data processing workflow for land-water classification using multispectral airborne LiDAR data. Depending on the nature of the study scene, two methods are proposed for automatic training data selection. The first method utilizes the elevation/intensity histogram fitted with Gaussian mixture model (GMM) to preliminarily split the land and water bodies. The second method mainly relies on the use of a newly developed scan line elevation intensity ratio (SLIER) to estimate the water surface data points. Regardless of the training methods being used, feature spaces can be constructed using the multispectral LiDAR intensity, elevation and other features derived from these parameters. The comprehensive workflow was tested with two datasets collected for different near shore region and river environment, where the overall accuracy yielded better than 96 %.

What Iswebmapping Anyway?

NASA Astrophysics Data System (ADS)

Veenendaal, B.; Brovelli, M. A.; Li, S.; Ivánová, I.

2017-09-01

Although maps have been around for a very long time, web maps are yet very young in their origin. Despite their relatively short history, web maps have been developing very rapidly over the past few decades. The use, users and usability of web maps have rapidly expanded along with developments in web technologies and new ways of mapping. In the process of these developments, the terms and terminology surrounding web mapping have also changed and evolved, often relating to the new technologies or new uses. Examples include web mapping, web GIS, cloud mapping, internet mapping, internet GIS, geoweb, map mashup, online mapping etc., not to mention those with prefixes such as "web-based" and "internet-based". So, how do we keep track of these terms, relate them to each other and have common understandings of their meanings so that references to them are not ambiguous, misunderstood or even different? This paper explores the terms surrounding web mapping and web GIS, and the development of their meaning over time. The paper then suggests the current context in which these terms are used and provides meanings that may assist in better understanding and communicating using these terms in the future.

Metadata mapping and reuse in caBIG™

PubMed Central

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-01-01

Background This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG™). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG™ framework or other frameworks that use metadata repositories. Results The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG™ framework and potentially any framework that uses a metadata repository. Conclusion This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG™. This effort contributes to facilitating the development of interoperable systems within caBIG™ as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies. PMID:19208192

Advanced Ecosystem Mapping Techniques for Large Arctic Study Domains Using Calibrated High-Resolution Imagery

NASA Astrophysics Data System (ADS)

Macander, M. J.; Frost, G. V., Jr.

2015-12-01

Regional-scale mapping of vegetation and other ecosystem properties has traditionally relied on medium-resolution remote sensing such as Landsat (30 m) and MODIS (250 m). Yet, the burgeoning availability of high-resolution (<=2 m) imagery and ongoing advances in computing power and analysis tools raises the prospect of performing ecosystem mapping at fine spatial scales over large study domains. Here we demonstrate cutting-edge mapping approaches over a ~35,000 km² study area on Alaska's North Slope using calibrated and atmospherically-corrected mosaics of high-resolution WorldView-2 and GeoEye-1 imagery: (1) an a priori spectral approach incorporating the Satellite Imagery Automatic Mapper (SIAM) algorithms; (2) image segmentation techniques; and (3) texture metrics. The SIAM spectral approach classifies radiometrically-calibrated imagery to general vegetation density categories and non-vegetated classes. The SIAM classes were developed globally and their applicability in arctic tundra environments has not been previously evaluated. Image segmentation, or object-based image analysis, automatically partitions high-resolution imagery into homogeneous image regions that can then be analyzed based on spectral, textural, and contextual information. We applied eCognition software to delineate waterbodies and vegetation classes, in combination with other techniques. Texture metrics were evaluated to determine the feasibility of using high-resolution imagery to algorithmically characterize periglacial surface forms (e.g., ice-wedge polygons), which are an important physical characteristic of permafrost-dominated regions but which cannot be distinguished by medium-resolution remote sensing. These advanced mapping techniques provide products which can provide essential information supporting a broad range of ecosystem science and land-use planning applications in northern Alaska and elsewhere in the circumpolar Arctic.

Flood hazards studies in the Mississippi River basin using remote sensing

NASA Technical Reports Server (NTRS)

Rango, A.; Anderson, A. T.

1974-01-01

The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicated that ERTS-1 is extremely useful as a regional tool for flood mamagement. Quantitative estimates of area flooded were made in St. Charles County, Missouri and Arkansas. Flood hazard mapping was conducted in three study areas along the Mississippi River using pre-flood ERTS-1 imagery enlarged to 1:250,000 and 1:100,000 scale. Initial results indicate that ERTS-1 digital mapping of flood prone areas can be performed at 1:62,500 which is comparable to some conventional flood hazard map scales.

Simultaneous orientation and thickness mapping in transmission electron microscopy

DOE PAGES

Tyutyunnikov, Dmitry; Özdöl, V. Burak; Koch, Christoph T.

2014-12-04

In this paper we introduce an approach for simultaneous thickness and orientation mapping of crystalline samples by means of transmission electron microscopy. We show that local thickness and orientation values can be extracted from experimental dark-field (DF) image data acquired at different specimen tilts. The method has been implemented to automatically acquire the necessary data and then map thickness and crystal orientation for a given region of interest. We have applied this technique to a specimen prepared from a commercial semiconductor device, containing multiple 22 nm technology transistor structures. The performance and limitations of our method are discussed and comparedmore » to those of other techniques available.« less

Application of remote sensing to the photogeologic mapping of the region of the Itatiaia alkaline complex. M.S. Thesis; [Minas Gerais, Rio De Janeiro, Sao Paulo, and Itatiaia, Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Rodrigues, J. E.

1981-01-01

Remote sensing methods applied to geologically complex areas, through interaction of ground truth and information obtained from multispectral LANDSAT images and radar mosaics were evaluated. The test area covers parts of Minos Gerais, Rio De Janeiro and Sao Paulo states and contains the alkaline complex of Itatiaia and surrounding Precambrian terrains. Geological and structural mapping was satisfactory; however, lithological varieties which form the massif's could not be identified. Photogeological lineaments were mapped, some of which represent the boundaries of stratigraphic units. Automatic processing was used to classify sedimentary areas, which includes the talus deposits of the alkaline massifs.

Spectral mapping of soil organic matter

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Baumgardner, M. F.; Johannsen, C. J.

1974-01-01

Multispectral remote sensing data were examined for use in the mapping of soil organic matter content. Computer-implemented pattern recognition techniques were used to analyze data collected in May 1969 and May 1970 by an airborne multispectral scanner over a 40-km flightline. Two fields within the flightline were selected for intensive study. Approximately 400 surface soil samples from these fields were obtained for organic matter analysis. The analytical data were used as training sets for computer-implemented analysis of the spectral data. It was found that within the geographical limitations included in this study, multispectral data and automatic data processing techniques could be used very effectively to delineate and map surface soils areas containing different levels of soil organic matter.

Sentinel-2 for rapid operational landslide inventory mapping

NASA Astrophysics Data System (ADS)

Stumpf, André; Marc, Odin; Malet, Jean-Philippe; Michea, David

2017-04-01

Landslide inventory mapping after major triggering events such as heavy rainfalls or earthquakes is crucial for disaster response, the assessment of hazards, and the quantification of sediment budgets and empirical scaling laws. Numerous studies have already demonstrated the utility of very-high resolution satellite and aerial images for the elaboration of inventories based on semi-automatic methods or visual image interpretation. Nevertheless, such semi-automatic methods are rarely used in an operational context after major triggering events; this is partly due to access limitations on the required input datasets (i.e. VHR satellite images) and to the absence of dedicated services (i.e. processing chain) available for the landslide community. Several on-going initiatives allow to overcome these limitations. First, from a data perspective, the launch of the Sentinel-2 mission offers opportunities for the design of an operational service that can be deployed for landslide inventory mapping at any time and everywhere on the globe. Second, from an implementation perspective, the Geohazards Exploitation Platform (GEP) of the European Space Agency (ESA) allows the integration and diffusion of on-line processing algorithms in a high computing performance environment. Third, from a community perspective, the recently launched Landslide Pilot of the Committee on Earth Observation Satellites (CEOS), has targeted the take-off of such service as a main objective for the landslide community. Within this context, this study targets the development of a largely automatic, supervised image processing chain for landslide inventory mapping from bi-temporal (before and after a given event) Sentinel-2 optical images. The processing chain combines change detection methods, image segmentation, higher-level image features (e.g. texture, shape) and topographic variables. Based on a few representative examples provided by a human operator, a machine learning model is trained and subsequently used to distinguish newly triggered landslides from other landscape elements. The final map product is provided along with an uncertainty map that allows identifying areas which might require further considerations. The processing chain is tested for two recent and contrasted triggering events in New Zealand and Taiwan. A Mw 7.8 earthquake in New Zealand in November 2016 triggered tens of thousands of landslides in a complex environment, with important textural variations with elevations, due to vegetation change and snow cover. In contrast a large but unexceptional typhoon in July 2016 in Taiwan triggered a moderate amount of relatively small landslides in a lushly vegetated, more homogenous terrain. Based on the obtained results we discuss the potential and limitations of Sentinel-2 bi-temporal images and time-series for operational landslide inventory mapping This work is part of the General Studies Program (GSP) ALCANTARA of ESA.

Multiresolution saliency map based object segmentation

NASA Astrophysics Data System (ADS)

Yang, Jian; Wang, Xin; Dai, ZhenYou

2015-11-01

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

Markov random field based automatic image alignment for electron tomography.

PubMed

Amat, Fernando; Moussavi, Farshid; Comolli, Luis R; Elidan, Gal; Downing, Kenneth H; Horowitz, Mark

2008-03-01

We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.

NREL Transportation Project to Reduce Fuel Usage

Science.gov Websites

and communication software was developed by NREL researchers to display a vehicle's location automatically and transmit a map of the its location over the Internet. After developing the communication vehicle location and communication technology to track and direct vehicle fleet movements," said the

Wireless tracking of cotton modules Part II: automatic machine identification and system testing

USDA-ARS?s Scientific Manuscript database

Mapping the harvest location of cotton modules is essential to practical understanding and utilization of spatial-variability information in fiber quality. A wireless module-tracking system was recently developed, but automation of the system is required before it will find practical use on the far...

Enabling the Interoperability of Large-Scale Legacy Systems

DTIC Science & Technology

2008-01-01

information retrieval systems ( Salton and McGill 1983). We use this method because, in the schema mapping task, only one instance per class is...2001). A survey of approaches to automatic schema matching. The VLDB Journal, 10, 334-350. Salton , G., & McGill, M.J. (1983). Introduction to

HelpfulMed: Intelligent Searching for Medical Information over the Internet.

ERIC Educational Resources Information Center

Chen, Hsinchun; Lally, Ann M.; Zhu, Bin; Chau, Michael

2003-01-01

Discussion of the information needs of medical professionals and researchers focuses on the architecture of a Web portal designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, and self-organizing map technologies to provide searchers with fine-grained results. Reports results of evaluation of spider algorithms…

The Measurement of Term Importance in Automatic Indexing.

ERIC Educational Resources Information Center

Salton, G.; And Others

1981-01-01

Reviews major term-weighting theories, presents methods for estimating the relevance properties of terms based on their frequency characteristics in a document collection, and compares weighting systems using term relevance properties with more conventional frequency-based methodologies. Eighteen references are cited. (Author/FM)

Automatic Generation of Issue Maps: Structured, Interactive Outputs for Complex Information Needs

DTIC Science & Technology

2012-09-01

much can result in behaviour similar to the shortest-path chains. 24 Ronald Goldman Neil Lewis Judge Lance Ito 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 jury...Connecting the Dots has also been explored in non-textual domains. The authors of [ Heath et al., 2010] propose building graphs, called Image Webs, to...could imagine a metro map summarizing a dataset of medical records. 2. Images: In [ Heath et al., 2010], Heath et al build graphs called Image Webs to rep

Analysis of 2D Phase Contrast MRI in Renal Arteries by Self Organizing Maps

NASA Astrophysics Data System (ADS)

Zöllner, Frank G.; Schad, Lothar R.

We present an approach based on self organizing maps to segment renal arteries from 2D PC Cine MR, images to measure blood velocity and flow. Such information are important in grading renal artery stenosis and support the decision on surgical interventions like percu-tan transluminal angioplasty. Results show that the renal arteries could be extracted automatically. The corresponding velocity profiles show high correlation (r=0.99) compared those from manual delineated vessels. Furthermore, the method could detect possible blood flow patterns within the vessel.

Skylab-EREP studies in computer mapping of terrain in the Cripple Creek-Canon City area of Colorado

NASA Technical Reports Server (NTRS)

Smedes, H. W.; Ranson, K. J.; Holstrom, R. L.

1975-01-01

Multispectral-scanner data from satellites are used as input to computers for automatically mapping terrain classes of ground cover. Some major problems faced in this remote-sensing task include: (1) the effect of mixtures of classes and, primarily because of mixtures, the problem of what constitutes accurate control data, and (2) effects of the atmosphere on spectral responses. The fundamental principles of these problems are presented along with results of studies of them for a test site of Colorado, using LANDSAT-1 data.

Ecoregions and ecodistricts: Ecological regionalizations for the Netherlands' environmental policy

NASA Astrophysics Data System (ADS)

Klijn, Frans; de Waal, Rein W.; Oude Voshaar, Jan H.

1995-11-01

For communicating data on the state of the environment to policy makers, various integrative frameworks are used, including regional integration. For this kind of integration we have developed two related ecological regionalizations, ecoregions and ecodistricts, which are two levels in a series of classifications for hierarchically nested ecosystems at different spatial scale levels. We explain the compilation of the maps from existing geographical data, demonstrating the relatively holistic, a priori integrated approach. The resulting maps are submitted to discriminant analysis to test the consistancy of the use of mapping characteristics, using data on individual abiotic ecosystem components from a national database on a 1-km2 grid. This reveals that the spatial patterns of soil, groundwater, and geomorphology correspond with the ecoregion and ecodistrict maps. Differences between the original maps and maps formed by automatically reclassifying 1-km2 cells with these discriminant components are found to be few. These differences are discussed against the background of the principal dilemma between deductive, a priori integrated, and inductive, a posteriori, classification.

Automated strip-mine and reclamation mapping from ERTS

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Reed, L. E.; Pettyjohn, W. A.

1974-01-01

The author has identified the following significant results. Computer processing techniques were applied to ERTS-1 computer-compatible tape (CCT) data acquired in August 1972 on the Ohio Power Company's coal mining operation in Muskingum County, Ohio. Processing results succeeded in automatically classifying, with an accuracy greater than 90%: (1) stripped earth and major sources of erosion; (2) partially reclaimed areas and minor sources of erosion; (3) water with sedimentation; (4) water without sedimentation; and (5) vegetation. Computer-generated tables listing the area in acres and square kilometers were produced for each target category. Processing results also included geometrically corrected map overlays, one for each target category, drawn on a transparent material by a pen under computer control. Each target category is assigned a distinctive color on the overlay to facilitate interpretation. The overlays, drawn at a scale of 1:250,000 when placed over an AMS map of the same area, immediately provided map locations for each target. These mapping products were generated at a tenth of the cost of conventional mapping techniques.

Automated Robot Movement in the Mapped Area Using Fuzzy Logic for Wheel Chair Application

NASA Astrophysics Data System (ADS)

Siregar, B.; Efendi, S.; Ramadhana, H.; Andayani, U.; Fahmi, F.

2018-03-01

The difficulties of the disabled to move make them unable to live independently. People with disabilities need supporting device to move from place to place. For that, we proposed a solution that can help people with disabilities to move from one room to another automatically. This study aims to create a wheelchair prototype in the form of a wheeled robot as a means to learn the automatic mobilization. The fuzzy logic algorithm was used to determine motion direction based on initial position, ultrasonic sensors reading in avoiding obstacles, infrared sensors reading as a black line reader for the wheeled robot to move smooth and smartphone as a mobile controller. As a result, smartphones with the Android operating system can control the robot using Bluetooth. Here Bluetooth technology can be used to control the robot from a maximum distance of 15 meters. The proposed algorithm was able to work stable for automatic motion determination based on initial position, and also able to modernize the wheelchair movement from one room to another automatically.

Diffraction phase microscopy realized with an automatic digital pinhole

NASA Astrophysics Data System (ADS)

Zheng, Cheng; Zhou, Renjie; Kuang, Cuifang; Zhao, Guangyuan; Zhang, Zhimin; Liu, Xu

2017-12-01

We report a novel approach to diffraction phase microscopy (DPM) with automatic pinhole alignment. The pinhole, which serves as a spatial low-pass filter to generate a uniform reference beam, is made out of a liquid crystal display (LCD) device that allows for electrical control. We have made DPM more accessible to users, while maintaining high phase measurement sensitivity and accuracy, through exploring low cost optical components and replacing the tedious pinhole alignment process with an automatic pinhole optical alignment procedure. Due to its flexibility in modifying the size and shape, this LCD device serves as a universal filter, requiring no future replacement. Moreover, a graphic user interface for real-time phase imaging has been also developed by using a USB CMOS camera. Experimental results of height maps of beads sample and live red blood cells (RBCs) dynamics are also presented, making this system ready for broad adaption to biological imaging and material metrology.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

PubMed

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

Automatic limb identification and sleeping parameters assessment for pressure ulcer prevention.

PubMed

Baran Pouyan, Maziyar; Birjandtalab, Javad; Nourani, Mehrdad; Matthew Pompeo, M D

2016-08-01

Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Natural language processing of spoken diet records (SDRs).

PubMed

Lacson, Ronilda; Long, William

2006-01-01

Dietary assessment is a fundamental aspect of nutritional evaluation that is essential for management of obesity as well as for assessing dietary impact on chronic diseases. Various methods have been used for dietary assessment including written records, 24-hour recalls, and food frequency questionnaires. The use of mobile phones to provide real-time dietary records provides potential advantages for accessibility, ease of use and automated documentation. However, understanding even a perfect transcript of spoken dietary records (SDRs) is challenging for people. This work presents a first step towards automatic analysis of SDRs. Our approach consists of four steps - identification of food items, identification of food quantifiers, classification of food quantifiers and temporal annotation. Our method enables automatic extraction of dietary information from SDRs, which in turn allows automated mapping to a Diet History Questionnaire dietary database. Our model has an accuracy of 90%. This work demonstrates the feasibility of automatically processing SDRs.

SA-SOM algorithm for detecting communities in complex networks

NASA Astrophysics Data System (ADS)

Chen, Luogeng; Wang, Yanran; Huang, Xiaoming; Hu, Mengyu; Hu, Fang

2017-10-01

Currently, community detection is a hot topic. This paper, based on the self-organizing map (SOM) algorithm, introduced the idea of self-adaptation (SA) that the number of communities can be identified automatically, a novel algorithm SA-SOM of detecting communities in complex networks is proposed. Several representative real-world networks and a set of computer-generated networks by LFR-benchmark are utilized to verify the accuracy and the efficiency of this algorithm. The experimental findings demonstrate that this algorithm can identify the communities automatically, accurately and efficiently. Furthermore, this algorithm can also acquire higher values of modularity, NMI and density than the SOM algorithm does.

MICRA: an automatic pipeline for fast characterization of microbial genomes from high-throughput sequencing data.

PubMed

Caboche, Ségolène; Even, Gaël; Loywick, Alexandre; Audebert, Christophe; Hot, David

2017-12-19

The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data.

Automatic Estimation of Volcanic Ash Plume Height using WorldView-2 Imagery

NASA Technical Reports Server (NTRS)

McLaren, David; Thompson, David R.; Davies, Ashley G.; Gudmundsson, Magnus T.; Chien, Steve

2012-01-01

We explore the use of machine learning, computer vision, and pattern recognition techniques to automatically identify volcanic ash plumes and plume shadows, in WorldView-2 imagery. Using information of the relative position of the sun and spacecraft and terrain information in the form of a digital elevation map, classification, the height of the ash plume can also be inferred. We present the results from applying this approach to six scenes acquired on two separate days in April and May of 2010 of the Eyjafjallajokull eruption in Iceland. These results show rough agreement with ash plume height estimates from visual and radar based measurements.

Eliminating the Simon Effect by Instruction

ERIC Educational Resources Information Center

Theeuwes, Marijke; Liefooghe, Baptist; De Houwer, Jan

2014-01-01

A growing body of research demonstrates that instructions can elicit automatic response activations. The results of the present study indicate that instruction-based response activations can also counteract automatic response activations based on long-term associations. To this end, we focused on the Simon effect, which is the observation that…

Automatic and continuous landslide monitoring: the Rotolon Web-based platform

NASA Astrophysics Data System (ADS)

Frigerio, Simone; Schenato, Luca; Mantovani, Matteo; Bossi, Giulia; Marcato, Gianluca; Cavalli, Marco; Pasuto, Alessandro

2013-04-01

Mount Rotolon (Eastern Italian Alps) is affected by a complex landslide that, since 1985, is threatening the nearby village of Recoaro Terme. The first written proof of a landslide occurrence dated back to 1798. After the last re-activation on November 2010 (637 mm of intense rainfall recorded in the 12 days prior the event), a mass of approximately 320.000 m3 detached from the south flank of Mount Rotolon and evolved into a fast debris flow that ran for about 3 km along the stream bed. A real-time monitoring system was required to detect early indication of rapid movements, potentially saving lives and property. A web-based platform for automatic and continuous monitoring was designed as a first step in the implementation of an early-warning system. Measurements collected by the automated geotechnical and topographic instrumentation, deployed over the landslide body, are gathered in a central box station. After the calibration process, they are transmitted by web services on a local server, where graphs, maps, reports and alert announcement are automatically generated and updated. All the processed information are available by web browser with different access rights. The web environment provides the following advantages: 1) data is collected from different data sources and matched on a single server-side frame 2) a remote user-interface allows regular technical maintenance and direct access to the instruments 3) data management system is synchronized and automatically tested 4) a graphical user interface on browser provides a user-friendly tool for decision-makers to interact with a system continuously updated. On this site two monitoring systems are actually on course: 1) GB-InSAR radar interferometer (University of Florence - Department of Earth Science) and 2) Automated Total Station (ATS) combined with extensometers network in a Web-based solution (CNR-IRPI Padova). This work deals with details on methodology, services and techniques adopted for the second monitoring solution. The activity directly interfaces with local Civil Protection agency, Regional Geological Service and local authorities with integrated roles and aims.

A tool for the estimation of the distribution of landslide area in R

NASA Astrophysics Data System (ADS)

Rossi, M.; Cardinali, M.; Fiorucci, F.; Marchesini, I.; Mondini, A. C.; Santangelo, M.; Ghosh, S.; Riguer, D. E. L.; Lahousse, T.; Chang, K. T.; Guzzetti, F.

2012-04-01

We have developed a tool in R (the free software environment for statistical computing, http://www.r-project.org/) to estimate the probability density and the frequency density of landslide area. The tool implements parametric and non-parametric approaches to the estimation of the probability density and the frequency density of landslide area, including: (i) Histogram Density Estimation (HDE), (ii) Kernel Density Estimation (KDE), and (iii) Maximum Likelihood Estimation (MLE). The tool is available as a standard Open Geospatial Consortium (OGC) Web Processing Service (WPS), and is accessible through the web using different GIS software clients. We tested the tool to compare Double Pareto and Inverse Gamma models for the probability density of landslide area in different geological, morphological and climatological settings, and to compare landslides shown in inventory maps prepared using different mapping techniques, including (i) field mapping, (ii) visual interpretation of monoscopic and stereoscopic aerial photographs, (iii) visual interpretation of monoscopic and stereoscopic VHR satellite images and (iv) semi-automatic detection and mapping from VHR satellite images. Results show that both models are applicable in different geomorphological settings. In most cases the two models provided very similar results. Non-parametric estimation methods (i.e., HDE and KDE) provided reasonable results for all the tested landslide datasets. For some of the datasets, MLE failed to provide a result, for convergence problems. The two tested models (Double Pareto and Inverse Gamma) resulted in very similar results for large and very large datasets (> 150 samples). Differences in the modeling results were observed for small datasets affected by systematic biases. A distinct rollover was observed in all analyzed landslide datasets, except for a few datasets obtained from landslide inventories prepared through field mapping or by semi-automatic mapping from VHR satellite imagery. The tool can also be used to evaluate the probability density and the frequency density of landslide volume.

Automatic identification of artifacts in electrodermal activity data.

PubMed

Taylor, Sara; Jaques, Natasha; Chen, Weixuan; Fedor, Szymon; Sano, Akane; Picard, Rosalind

2015-01-01

Recently, wearable devices have allowed for long term, ambulatory measurement of electrodermal activity (EDA). Despite the fact that ambulatory recording can be noisy, and recording artifacts can easily be mistaken for a physiological response during analysis, to date there is no automatic method for detecting artifacts. This paper describes the development of a machine learning algorithm for automatically detecting EDA artifacts, and provides an empirical evaluation of classification performance. We have encoded our results into a freely available web-based tool for artifact and peak detection.

Projection Mapping User Interface for Disabled People

PubMed Central

Simutis, Rimvydas; Maskeliūnas, Rytis

2018-01-01

Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities. PMID:29686827

Application of LANDSAT and Skylab data for land use mapping in Italy. [emphasizing the Alps Mountains

NASA Technical Reports Server (NTRS)

Bodechtel, J.; Nithack, J.; Dibernardo, G.; Hiller, K.; Jaskolla, F.; Smolka, A.

1975-01-01

Utilizing LANDSAT and Skylab multispectral imagery of 1972 and 1973, a land use map of the mountainous regions of Italy was evaluated at a scale of 1:250,000. Seven level I categories were identified by conventional methods of photointerpretation. Images of multispectral scanner (MSS) bands 5 and 7, or equivalents were mainly used. Areas of less than 200 by 200 m were classified and standard procedures were established for interpretation of multispectral satellite imagery. Land use maps were produced for central and southern Europe indicating that the existing land use maps could be updated and optimized. The complexity of European land use patterns, the intensive morphology of young mountain ranges, and time-cost calculations are the reasons that the applied conventional techniques are superior to automatic evaluation.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

PubMed Central

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-01-01

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

Projection Mapping User Interface for Disabled People.

PubMed

Gelšvartas, Julius; Simutis, Rimvydas; Maskeliūnas, Rytis

2018-01-01

Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities.

Assessment of disease named entity recognition on a corpus of annotated sentences.

PubMed

Jimeno, Antonio; Jimenez-Ruiz, Ernesto; Lee, Vivian; Gaudan, Sylvain; Berlanga, Rafael; Rebholz-Schuhmann, Dietrich

2008-04-11

In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other semantic types like diseases have not received the same level of attention. Different solutions have been proposed to identify disease named entities in the scientific literature. While matching the terminology with language patterns suffers from low recall (e.g., Whatizit) other solutions make use of morpho-syntactic features to better cover the full scope of terminological variability (e.g., MetaMap). Currently, MetaMap that is provided from the National Library of Medicine (NLM) is the state of the art solution for the annotation of concepts from UMLS (Unified Medical Language System) in the literature. Nonetheless, its performance has not yet been assessed on an annotated corpus. In addition, little effort has been invested so far to generate an annotated dataset that links disease entities in text to disease entries in a database, thesaurus or ontology and that could serve as a gold standard to benchmark text mining solutions. As part of our research work, we have taken a corpus that has been delivered in the past for the identification of associations of genes to diseases based on the UMLS Metathesaurus and we have reprocessed and re-annotated the corpus. We have gathered annotations for disease entities from two curators, analyzed their disagreement (0.51 in the kappa-statistic) and composed a single annotated corpus for public use. Thereafter, three solutions for disease named entity recognition including MetaMap have been applied to the corpus to automatically annotate it with UMLS Metathesaurus concepts. The resulting annotations have been benchmarked to compare their performance. The annotated corpus is publicly available at ftp://ftp.ebi.ac.uk/pub/software/textmining/corpora/diseases and can serve as a benchmark to other systems. In addition, we found that dictionary look-up already provides competitive results indicating that the use of disease terminology is highly standardized throughout the terminologies and the literature. MetaMap generates precise results at the expense of insufficient recall while our statistical method obtains better recall at a lower precision rate. Even better results in terms of precision are achieved by combining at least two of the three methods leading, but this approach again lowers recall. Altogether, our analysis gives a better understanding of the complexity of disease annotations in the literature. MetaMap and the dictionary based approach are available through the Whatizit web service infrastructure (Rebholz-Schuhmann D, Arregui M, Gaudan S, Kirsch H, Jimeno A: Text processing through Web services: Calling Whatizit. Bioinformatics 2008, 24:296-298).

Improved spatial coverage for brain 3D PRESS MRSI by automatic placement of outer-volume suppression saturation bands.

PubMed

Ozhinsky, Eugene; Vigneron, Daniel B; Nelson, Sarah J

2011-04-01

To develop a technique for optimizing coverage of brain 3D (1) H magnetic resonance spectroscopic imaging (MRSI) by automatic placement of outer-volume suppression (OVS) saturation bands (sat bands) and to compare the performance for point-resolved spectroscopic sequence (PRESS) MRSI protocols with manual and automatic placement of sat bands. The automated OVS procedure includes the acquisition of anatomic images from the head, obtaining brain and lipid tissue maps, calculating optimal sat band placement, and then using those optimized parameters during the MRSI acquisition. The data were analyzed to quantify brain coverage volume and data quality. 3D PRESS MRSI data were acquired from three healthy volunteers and 29 patients using protocols that included either manual or automatic sat band placement. On average, the automatic sat band placement allowed the acquisition of PRESS MRSI data from 2.7 times larger brain volumes than the conventional method while maintaining data quality. The technique developed helps solve two of the most significant problems with brain PRESS MRSI acquisitions: limited brain coverage and difficulty in prescription. This new method will facilitate routine clinical brain 3D MRSI exams and will be important for performing serial evaluation of response to therapy in patients with brain tumors and other neurological diseases. Copyright © 2011 Wiley-Liss, Inc.

Translation from the collaborative OSM database to cartography

NASA Astrophysics Data System (ADS)

Hayat, Flora

2018-05-01

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

ShakeMap manual: technical manual, user's guide, and software guide

USGS Publications Warehouse

Wald, David J.; Worden, Bruce C.; Quitoriano, Vincent; Pankow, Kris L.

2005-01-01

ShakeMap (http://earthquake.usgs.gov/shakemap) --rapidly, automatically generated shaking and intensity maps--combines instrumental measurements of shaking with information about local geology and earthquake location and magnitude to estimate shaking variations throughout a geographic area. The results are rapidly available via the Web through a variety of map formats, including Geographic Information System (GIS) coverages. These maps have become a valuable tool for emergency response, public information, loss estimation, earthquake planning, and post-earthquake engineering and scientific analyses. With the adoption of ShakeMap as a standard tool for a wide array of users and uses came an impressive demand for up-to-date technical documentation and more general guidelines for users and software developers. This manual is meant to address this need. ShakeMap, and associated Web and data products, are rapidly evolving as new advances in communications, earthquake science, and user needs drive improvements. As such, this documentation is organic in nature. We will make every effort to keep it current, but undoubtedly necessary changes in operational systems take precedence over producing and making documentation publishable.

Development of a microcontroller-based automatic control system for the electrohydraulic total artificial heart.

PubMed

Kim, H C; Khanwilkar, P S; Bearnson, G B; Olsen, D B

1997-01-01

An automatic physiological control system for the actively filled, alternately pumped ventricles of the volumetrically coupled, electrohydraulic total artificial heart (EHTAH) was developed for long-term use. The automatic control system must ensure that the device: 1) maintains a physiological response of cardiac output, 2) compensates for an nonphysiological condition, and 3) is stable, reliable, and operates at a high power efficiency. The developed automatic control system met these requirements both in vitro, in week-long continuous mock circulation tests, and in vivo, in acute open-chested animals (calves). Satisfactory results were also obtained in a series of chronic animal experiments, including 21 days of continuous operation of the fully automatic control mode, and 138 days of operation in a manual mode, in a 159-day calf implant.

Testing interactive effects of automatic and conflict control processes during response inhibition - A system neurophysiological study.

PubMed

Chmielewski, Witold X; Beste, Christian

2017-02-01

In everyday life successful acting often requires to inhibit automatic responses that might not be appropriate in the current situation. These response inhibition processes have been shown to become aggravated with increasing automaticity of pre-potent response tendencies. Likewise, it has been shown that inhibitory processes are complicated by a concurrent engagement in additional cognitive control processes (e.g. conflicting monitoring). Therefore, opposing processes (i.e. automaticity and cognitive control) seem to strongly impact response inhibition. However, possible interactive effects of automaticity and cognitive control for the modulation of response inhibition processes have yet not been examined. In the current study we examine this question using a novel experimental paradigm combining a Go/NoGo with a Simon task in a system neurophysiological approach combining EEG recordings with source localization analyses. The results show that response inhibition is less accurate in non-conflicting than in conflicting stimulus-response mappings. Thus it seems that conflicts and the resulting engagement in conflict monitoring processes, as reflected in the N2 amplitude, may foster response inhibition processes. This engagement in conflict monitoring processes leads to an increase in cognitive control, as reflected by an increased activity in the anterior and posterior cingulate areas, while simultaneously the automaticity of response tendencies is decreased. Most importantly, this study suggests that the quality of conflict processes in anterior cingulate areas and especially the resulting interaction of cognitive control and automaticity of pre-potent response tendencies are important factors to consider, when it comes to the modulation of response inhibition processes. Copyright © 2016 Elsevier Inc. All rights reserved.

Semi-automatic knee cartilage segmentation

NASA Astrophysics Data System (ADS)

Dam, Erik B.; Folkesson, Jenny; Pettersen, Paola C.; Christiansen, Claus

2006-03-01

Osteo-Arthritis (OA) is a very common age-related cause of pain and reduced range of motion. A central effect of OA is wear-down of the articular cartilage that otherwise ensures smooth joint motion. Quantification of the cartilage breakdown is central in monitoring disease progression and therefore cartilage segmentation is required. Recent advances allow automatic cartilage segmentation with high accuracy in most cases. However, the automatic methods still fail in some problematic cases. For clinical studies, even if a few failing cases will be averaged out in the overall results, this reduces the mean accuracy and precision and thereby necessitates larger/longer studies. Since the severe OA cases are often most problematic for the automatic methods, there is even a risk that the quantification will introduce a bias in the results. Therefore, interactive inspection and correction of these problematic cases is desirable. For diagnosis on individuals, this is even more crucial since the diagnosis will otherwise simply fail. We introduce and evaluate a semi-automatic cartilage segmentation method combining an automatic pre-segmentation with an interactive step that allows inspection and correction. The automatic step consists of voxel classification based on supervised learning. The interactive step combines a watershed transformation of the original scan with the posterior probability map from the classification step at sub-voxel precision. We evaluate the method for the task of segmenting the tibial cartilage sheet from low-field magnetic resonance imaging (MRI) of knees. The evaluation shows that the combined method allows accurate and highly reproducible correction of the segmentation of even the worst cases in approximately ten minutes of interaction.

The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data

NASA Astrophysics Data System (ADS)

Le Bihan, Guillaume; Payrastre, Olivier; Gaume, Eric; Moncoulon, David; Pons, Frédéric

2017-11-01

Up to now, flash flood monitoring and forecasting systems, based on rainfall radar measurements and distributed rainfall-runoff models, generally aimed at estimating flood magnitudes - typically discharges or return periods - at selected river cross sections. The approach presented here goes one step further by proposing an integrated forecasting chain for the direct assessment of flash flood possible impacts on inhabited areas (number of buildings at risk in the presented case studies). The proposed approach includes, in addition to a distributed rainfall-runoff model, an automatic hydraulic method suited for the computation of flood extent maps on a dense river network and over large territories. The resulting catalogue of flood extent maps is then combined with land use data to build a flood impact curve for each considered river reach, i.e. the number of inundated buildings versus discharge. These curves are finally used to compute estimated impacts based on forecasted discharges. The approach has been extensively tested in the regions of Alès and Draguignan, located in the south of France, where well-documented major flash floods recently occurred. The article presents two types of validation results. First, the automatically computed flood extent maps and corresponding water levels are tested against rating curves at available river gauging stations as well as against local reference or observed flood extent maps. Second, a rich and comprehensive insurance claim database is used to evaluate the relevance of the estimated impacts for some recent major floods.

Automatic Depth Extraction from 2D Images Using a Cluster-Based Learning Framework.

PubMed

Herrera, Jose L; Del-Blanco, Carlos R; Garcia, Narciso

2018-07-01

There has been a significant increase in the availability of 3D players and displays in the last years. Nonetheless, the amount of 3D content has not experimented an increment of such magnitude. To alleviate this problem, many algorithms for converting images and videos from 2D to 3D have been proposed. Here, we present an automatic learning-based 2D-3D image conversion approach, based on the key hypothesis that color images with similar structure likely present a similar depth structure. The presented algorithm estimates the depth of a color query image using the prior knowledge provided by a repository of color + depth images. The algorithm clusters this database attending to their structural similarity, and then creates a representative of each color-depth image cluster that will be used as prior depth map. The selection of the appropriate prior depth map corresponding to one given color query image is accomplished by comparing the structural similarity in the color domain between the query image and the database. The comparison is based on a K-Nearest Neighbor framework that uses a learning procedure to build an adaptive combination of image feature descriptors. The best correspondences determine the cluster, and in turn the associated prior depth map. Finally, this prior estimation is enhanced through a segmentation-guided filtering that obtains the final depth map estimation. This approach has been tested using two publicly available databases, and compared with several state-of-the-art algorithms in order to prove its efficiency.

Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model.

PubMed

Martin, Sébastien; Troccaz, Jocelyne; Daanenc, Vincent

2010-04-01

The authors present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. The approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a probabilistic segmentation is obtained by mapping the probabilistic map of the atlas to the patient's anatomy. In the second stage, a deformable surface evolves toward the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model. During the evolution of the surface, the probabilistic segmentation allows the introduction of a spatial constraint that prevents the deformable surface from leaking in an unlikely configuration. The proposed method is evaluated on 36 exams that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. By merging prior knowledge, the presented method achieves a robust and completely automatic segmentation of the prostate in MR images. Results show that the use of a spatial constraint is useful to increase the robustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.

MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data

NASA Astrophysics Data System (ADS)

Gafurov, Abror; Lüdtke, Stefan; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Schöne, Tilo; Schmidt, Sebastian; Kalashnikova, Olga; Merz, Bruno

2017-04-01

Spatially distributed snow cover information in mountain areas is extremely important for water storage estimations, seasonal water availability forecasting, or the assessment of snow-related hazards (e.g. enhanced snow-melt following intensive rains, or avalanche events). Moreover, spatially distributed snow cover information can be used to calibrate and/or validate hydrological models. We present the MODSNOW-Tool - an operational monitoring tool offers a user-friendly application which can be used for catchment-based operational snow cover monitoring. The application automatically downloads and processes freely available daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data. The MODSNOW-Tool uses a step-wise approach for cloud removal and delivers cloud-free snow cover maps for the selected river basins including basin specific snow cover extent statistics. The accuracy of cloud-eliminated MODSNOW snow cover maps was validated for 84 almost cloud-free days in the Karadarya river basin in Central Asia, and an average accuracy of 94 % was achieved. The MODSNOW-Tool can be used in operational and non-operational mode. In the operational mode, the tool is set up as a scheduled task on a local computer allowing automatic execution without user interaction and delivers snow cover maps on a daily basis. In the non-operational mode, the tool can be used to process historical time series of snow cover maps. The MODSNOW-Tool is currently implemented and in use at the national hydrometeorological services of four Central Asian states - Kazakhstan, Kyrgyzstan, Uzbekistan and Turkmenistan and used for seasonal water availability forecast.

On the role of conflict and control in social cognition: event-related brain potential investigations.

PubMed

Bartholow, Bruce D

2010-03-01

Numerous social-cognitive models posit that social behavior largely is driven by links between constructs in long-term memory that automatically become activated when relevant stimuli are encountered. Various response biases have been understood in terms of the influence of such "implicit" processes on behavior. This article reviews event-related potential (ERP) studies investigating the role played by cognitive control and conflict resolution processes in social-cognitive phenomena typically deemed automatic. Neurocognitive responses associated with response activation and conflict often are sensitive to the same stimulus manipulations that produce differential behavioral responses on social-cognitive tasks and that often are attributed to the role of automatic associations. Findings are discussed in the context of an overarching social cognitive neuroscience model in which physiological data are used to constrain social-cognitive theories.

Automatic multimodal detection for long-term seizure documentation in epilepsy.

PubMed

Fürbass, F; Kampusch, S; Kaniusas, E; Koren, J; Pirker, S; Hopfengärtner, R; Stefan, H; Kluge, T; Baumgartner, C

2017-08-01

This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Wireless tracking of cotton modules. Part I: Automatic message triggering

USDA-ARS?s Scientific Manuscript database

The ability to map profit across a cotton field would enable producers to see where money is being made or lost on their farms and to implement precise field management practices to ensure the highest return possible on each portion of a field. To this end, a wireless module-tracking system was rec...

CAMUS: Automatically Mapping Cyber Assets to Mission and Users (PREPRINT)

DTIC Science & Technology

2009-10-01

which machines regularly use a particular mail server. Armed with these basic data sources – LDAP, NetFlow traffic and user logs – fuselets were created... NetFlow traffic used in the demonstration has over ten thousand unique IP Addresses and is over one gigabyte in size. A number of high performance

RFID: A Revolution in Automatic Data Recognition

ERIC Educational Resources Information Center

Deal, Walter F., III

2004-01-01

Radio frequency identification, or RFID, is a generic term for technologies that use radio waves to automatically identify people or objects. There are several methods of identification, but the most common is to store a serial number that identifies a person or object, and perhaps other information, on a microchip that is attached to an antenna…

Automatic Identification and Organization of Index Terms for Interactive Browsing.

ERIC Educational Resources Information Center

Wacholder, Nina; Evans, David K.; Klavans, Judith L.

The potential of automatically generated indexes for information access has been recognized for several decades, but the quantity of text and the ambiguity of natural language processing have made progress at this task more difficult than was originally foreseen. Recently, a body of work on development of interactive systems to support phrase…

Improving the Learning Experience of Business Subjects in Engineering Studies Using Automatic Spreadsheet Correctors

ERIC Educational Resources Information Center

Rafart Serra, Maria Assumpció; Bikfalvi, Andrea; Soler Masó, Josep; Prados Carrasco, Ferran; Poch Garcia, Jordi

2017-01-01

The combination of two macro trends, Information and Communication Technologies' (ICT) proliferation and novel approaches in education, has resulted in a series of opportunities with no precedent in terms of content, channels and methods in education. The present contribution aims to describe the experience of using an automatic spreadsheet…

Resolving carbonate platform geometries on the Island of Bonaire, Caribbean Netherlands through semi-automatic GPR facies classification

NASA Astrophysics Data System (ADS)

Bowling, R. D.; Laya, J. C.; Everett, M. E.

2018-07-01

The study of exposed carbonate platforms provides observational constraints on regional tectonics and sea-level history. In this work Miocene-aged carbonate platform units of the Seroe Domi Formation are investigated on the island of Bonaire, located in the Southern Caribbean. Ground penetrating radar (GPR) was used to probe near-surface structural geometries associated with these lithologies. The single cross-island transect described herein allowed for continuous mapping of geologic structures on kilometre length scales. Numerical analysis was applied to the data in the form of k-means clustering of structure-parallel vectors derived from image structure tensors. This methodology enables radar facies along the survey transect to be semi-automatically mapped. The results provide subsurface evidence to support previous surficial and outcrop observations, and reveal complex stratigraphy within the platform. From the GPR data analysis, progradational clinoform geometries were observed on the northeast side of the island which support the tectonics and depositional trends of the region. Furthermore, several leeward-side radar facies are identified which correlate to environments of deposition conducive to dolomitization via reflux mechanisms.

Discrete range clustering using Monte Carlo methods

NASA Technical Reports Server (NTRS)

Chatterji, G. B.; Sridhar, B.

1993-01-01

For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.

Automatized Photometric Monitoring of Active Galactic Nuclei with the 46cm Telescope of the Wise Observatory

NASA Astrophysics Data System (ADS)

Pozo Nuñez, Francisco; Chelouche, Doron; Kaspi, Shai; Niv, Saar

2017-09-01

We present the first results of an ongoing variability monitoring program of active galactic nuclei (AGNs) using the 46 cm telescope of the Wise Observatory in Israel. The telescope has a field of view of 1.25^\\circ × 0.84^\\circ and is specially equipped with five narrowband filters at 4300, 5200, 5700, 6200, and 7000 Å to perform photometric reverberation mapping studies of the central engine of AGNs. The program aims to observe a sample of 27 AGNs (V < 17 mag) selected according to tentative continuum and line time delay measurements obtained in previous works. We describe the autonomous operation of the telescope together with the fully automatic pipeline used to achieve high-performance unassisted observations, data reduction, and light curves extraction using different photometric methods. The science verification data presented here demonstrates the performance of the monitoring program in particular for efficiently photometric reverberation mapping of AGNs with additional capabilities to carry out complementary studies of other transient and variable phenomena such as variable stars studies.

Man-Made Object Extraction from Remote Sensing Imagery by Graph-Based Manifold Ranking

NASA Astrophysics Data System (ADS)

He, Y.; Wang, X.; Hu, X. Y.; Liu, S. H.

2018-04-01

The automatic extraction of man-made objects from remote sensing imagery is useful in many applications. This paper proposes an algorithm for extracting man-made objects automatically by integrating a graph model with the manifold ranking algorithm. Initially, we estimate a priori value of the man-made objects with the use of symmetric and contrast features. The graph model is established to represent the spatial relationships among pre-segmented superpixels, which are used as the graph nodes. Multiple characteristics, namely colour, texture and main direction, are used to compute the weights of the adjacent nodes. Manifold ranking effectively explores the relationships among all the nodes in the feature space as well as initial query assignment; thus, it is applied to generate a ranking map, which indicates the scores of the man-made objects. The man-made objects are then segmented on the basis of the ranking map. Two typical segmentation algorithms are compared with the proposed algorithm. Experimental results show that the proposed algorithm can extract man-made objects with high recognition rate and low omission rate.

Generalized Self-Organizing Maps for Automatic Determination of the Number of Clusters and Their Multiprototypes in Cluster Analysis.

PubMed

Gorzalczany, Marian B; Rudzinski, Filip

2017-06-07

This paper presents a generalization of self-organizing maps with 1-D neighborhoods (neuron chains) that can be effectively applied to complex cluster analysis problems. The essence of the generalization consists in introducing mechanisms that allow the neuron chain--during learning--to disconnect into subchains, to reconnect some of the subchains again, and to dynamically regulate the overall number of neurons in the system. These features enable the network--working in a fully unsupervised way (i.e., using unlabeled data without a predefined number of clusters)--to automatically generate collections of multiprototypes that are able to represent a broad range of clusters in data sets. First, the operation of the proposed approach is illustrated on some synthetic data sets. Then, this technique is tested using several real-life, complex, and multidimensional benchmark data sets available from the University of California at Irvine (UCI) Machine Learning repository and the Knowledge Extraction based on Evolutionary Learning data set repository. A sensitivity analysis of our approach to changes in control parameters and a comparative analysis with an alternative approach are also performed.