A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

New frontiers for intelligent content-based retrieval

NASA Astrophysics Data System (ADS)

Benitez, Ana B.; Smith, John R.

2001-01-01

In this paper, we examine emerging frontiers in the evolution of content-based retrieval systems that rely on an intelligent infrastructure. Here, we refer to intelligence as the capabilities of the systems to build and maintain situational or world models, utilize dynamic knowledge representation, exploit context, and leverage advanced reasoning and learning capabilities. We argue that these elements are essential to producing effective systems for retrieving audio-visual content at semantic levels matching those of human perception and cognition. In this paper, we review relevant research on the understanding of human intelligence and construction of intelligent system in the fields of cognitive psychology, artificial intelligence, semiotics, and computer vision. We also discus how some of the principal ideas form these fields lead to new opportunities and capabilities for content-based retrieval systems. Finally, we describe some of our efforts in these directions. In particular, we present MediaNet, a multimedia knowledge presentation framework, and some MPEG-7 description tools that facilitate and enable intelligent content-based retrieval.

New frontiers for intelligent content-based retrieval

NASA Astrophysics Data System (ADS)

Benitez, Ana B.; Smith, John R.

2000-12-01

In this paper, we examine emerging frontiers in the evolution of content-based retrieval systems that rely on an intelligent infrastructure. Here, we refer to intelligence as the capabilities of the systems to build and maintain situational or world models, utilize dynamic knowledge representation, exploit context, and leverage advanced reasoning and learning capabilities. We argue that these elements are essential to producing effective systems for retrieving audio-visual content at semantic levels matching those of human perception and cognition. In this paper, we review relevant research on the understanding of human intelligence and construction of intelligent system in the fields of cognitive psychology, artificial intelligence, semiotics, and computer vision. We also discus how some of the principal ideas form these fields lead to new opportunities and capabilities for content-based retrieval systems. Finally, we describe some of our efforts in these directions. In particular, we present MediaNet, a multimedia knowledge presentation framework, and some MPEG-7 description tools that facilitate and enable intelligent content-based retrieval.

[A retrieval method of drug molecules based on graph collapsing].

PubMed

Qu, J W; Lv, X Q; Liu, Z M; Liao, Y; Sun, P H; Wang, B; Tang, Z

2018-04-18

To establish a compact and efficient hypergraph representation and a graph-similarity-based retrieval method of molecules to achieve effective and efficient medicine information retrieval. Chemical structural formula (CSF) was a primary search target as a unique and precise identifier for each compound at the molecular level in the research field of medicine information retrieval. To retrieve medicine information effectively and efficiently, a complete workflow of the graph-based CSF retrieval system was introduced. This system accepted the photos taken from smartphones and the sketches drawn on tablet personal computers as CSF inputs, and formalized the CSFs with the corresponding graphs. Then this paper proposed a compact and efficient hypergraph representation for molecules on the basis of analyzing factors that directly affected the efficiency of graph matching. According to the characteristics of CSFs, a hierarchical collapsing method combining graph isomorphism and frequent subgraph mining was adopted. There was yet a fundamental challenge, subgraph overlapping during the collapsing procedure, which hindered the method from establishing the correct compact hypergraph of an original CSF graph. Therefore, a graph-isomorphism-based algorithm was proposed to select dominant acyclic subgraphs on the basis of overlapping analysis. Finally, the spatial similarity among graphical CSFs was evaluated by multi-dimensional measures of similarity. To evaluate the performance of the proposed method, the proposed system was firstly compared with Wikipedia Chemical Structure Explorer (WCSE), the state-of-the-art system that allowed CSF similarity searching within Wikipedia molecules dataset, on retrieval accuracy. The system achieved higher values on mean average precision, discounted cumulative gain, rank-biased precision, and expected reciprocal rank than WCSE from the top-2 to the top-10 retrieved results. Specifically, the system achieved 10%, 1.41, 6.42%, and 1.32% higher than WCSE on these metrics for top-10 retrieval results, respectively. Moreover, several retrieval cases were presented to intuitively compare with WCSE. The results of the above comparative study demonstrated that the proposed method outperformed the existing method with regard to accuracy and effectiveness. This paper proposes a graph-similarity-based retrieval approach for medicine information. To obtain satisfactory retrieval results, an isomorphism-based algorithm is proposed for dominant subgraph selection based on the subgraph overlapping analysis, as well as an effective and efficient hypergraph representation of molecules. Experiment results demonstrate the effectiveness of the proposed approach.

Graph-Based Interactive Bibliographic Information Retrieval Systems

ERIC Educational Resources Information Center

Zhu, Yongjun

2017-01-01

In the big data era, we have witnessed the explosion of scholarly literature. This explosion has imposed challenges to the retrieval of bibliographic information. Retrieval of intended bibliographic information has become challenging due to the overwhelming search results returned by bibliographic information retrieval systems for given input…

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

NASA Astrophysics Data System (ADS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

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

An Intelligent System for Document Retrieval in Distributed Office Environments.

ERIC Educational Resources Information Center

Mukhopadhyay, Uttam; And Others

1986-01-01

MINDS (Multiple Intelligent Node Document Servers) is a distributed system of knowledge-based query engines for efficiently retrieving multimedia documents in an office environment of distributed workstations. By learning document distribution patterns and user interests and preferences during system usage, it customizes document retrievals for…

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

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

Multimodal medical information retrieval with unsupervised rank fusion.

PubMed

Mourão, André; Martins, Flávio; Magalhães, João

2015-01-01

Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. However, the ever-growing heterogeneous information generated in medical environments poses several challenges for retrieval systems. We propose a medical information retrieval system with support for multimodal medical case-based retrieval. The system supports medical information discovery by providing multimodal search, through a novel data fusion algorithm, and term suggestions from a medical thesaurus. Our search system compared favorably to other systems in 2013 ImageCLEFMedical. Copyright © 2014 Elsevier Ltd. All rights reserved.

Document Indexing for Image-Based Optical Information Systems.

ERIC Educational Resources Information Center

Thiel, Thomas J.; And Others

1991-01-01

Discussion of image-based information retrieval systems focuses on indexing. Highlights include computerized information retrieval; multimedia optical systems; optical mass storage and personal computers; and a case study that describes an optical disk system which was developed to preserve, access, and disseminate military documents. (19…

Kingfisher: a system for remote sensing image database management

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

Web Image Retrieval Using Self-Organizing Feature Map.

ERIC Educational Resources Information Center

Wu, Qishi; Iyengar, S. Sitharama; Zhu, Mengxia

2001-01-01

Provides an overview of current image retrieval systems. Describes the architecture of the SOFM (Self Organizing Feature Maps) based image retrieval system, discussing the system architecture and features. Introduces the Kohonen model, and describes the implementation details of SOFM computation and its learning algorithm. Presents a test example…

Image selection system. [computerized data storage and retrieval system

NASA Technical Reports Server (NTRS)

Knutson, M. A.; Hurd, D.; Hubble, L.; Kroeck, R. M.

1974-01-01

An image selection (ISS) was developed for the NASA-Ames Research Center Earth Resources Aircraft Project. The ISS is an interactive, graphics oriented, computer retrieval system for aerial imagery. An analysis of user coverage requests and retrieval strategies is presented, followed by a complete system description. Data base structure, retrieval processors, command language, interactive display options, file structures, and the system's capability to manage sets of selected imagery are described. A detailed example of an area coverage request is graphically presented.

System engineering approach to GPM retrieval algorithms

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

Rose, C. R.; Chandrasekar, V.

2004-01-01

System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Groundmore » validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do calculated at each bin, the rain rate can then be calculated based on a suitable rain-rate model. This paper develops a system engineering interface to the retrieval algorithms while remaining cognizant of system engineering issues so that it can be used to bridge the divide between algorithm physics an d overall mission requirements. Additionally, in line with the systems approach, a methodology is developed such that the measurement requirements pass through the retrieval model and other subsystems and manifest themselves as measurement and other system constraints. A systems model has been developed for the retrieval algorithm that can be evaluated through system-analysis tools such as MATLAB/Simulink.« less

Hypothesis-confirming information search strategies and computerized information-retrieval systems

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

Jacobs, S.M.

A recent trend in information-retrieval systems technology is the development of on-line information retrieval systems. One objective of these systems has been to attempt to enhance decision effectiveness by allowing users to preferentially seek information, thereby facilitating the reduction or elimination of information overload. These systems do not necessarily lead to more-effective decision making, however. Recent research in information-search strategy suggests that when users are seeking information subsequent to forming initial beliefs, they may preferentially seek information to confirm these beliefs. It seems that effective computer-based decision support requires an information retrieval system capable of: (a) retrieving a subset ofmore » all available information, in order to reduce information overload, and (b) supporting an information search strategy that considers all relevant information, rather than merely hypothesis-confirming information. An information retrieval system with an expert component (i.e., a knowledge-based DSS) should be able to provide these capabilities. Results of this study are non conclusive; there was neither strong confirmatory evidence nor strong disconfirmatory evidence regarding the effectiveness of the KBDSS.« less

Semantic-based surveillance video retrieval.

PubMed

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

2007-04-01

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

Unified modeling language and design of a case-based retrieval system in medical imaging.

PubMed Central

LeBozec, C.; Jaulent, M. C.; Zapletal, E.; Degoulet, P.

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users. Images Figure 6 Figure 7 PMID:9929346

Unified modeling language and design of a case-based retrieval system in medical imaging.

PubMed

LeBozec, C; Jaulent, M C; Zapletal, E; Degoulet, P

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users.

Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study

NASA Astrophysics Data System (ADS)

Aljuboori, Ahmed S.; Coenen, Frans; Nsaif, Mohammed; Parsons, David J.

2018-05-01

Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR.

Comparing features sets for content-based image retrieval in a medical-case database

NASA Astrophysics Data System (ADS)

Muller, Henning; Rosset, Antoine; Vallee, Jean-Paul; Geissbuhler, Antoine

2004-04-01

Content-based image retrieval systems (CBIRSs) have frequently been proposed for the use in medical image databases and PACS. Still, only few systems were developed and used in a real clinical environment. It rather seems that medical professionals define their needs and computer scientists develop systems based on data sets they receive with little or no interaction between the two groups. A first study on the diagnostic use of medical image retrieval also shows an improvement in diagnostics when using CBIRSs which underlines the potential importance of this technique. This article explains the use of an open source image retrieval system (GIFT - GNU Image Finding Tool) for the retrieval of medical images in the medical case database system CasImage that is used in daily, clinical routine in the university hospitals of Geneva. Although the base system of GIFT shows an unsatisfactory performance, already little changes in the feature space show to significantly improve the retrieval results. The performance of variations in feature space with respect to color (gray level) quantizations and changes in texture analysis (Gabor filters) is compared. Whereas stock photography relies mainly on colors for retrieval, medical images need a large number of gray levels for successful retrieval, especially when executing feedback queries. The results also show that a too fine granularity in the gray levels lowers the retrieval quality, especially with single-image queries. For the evaluation of the retrieval peformance, a subset of the entire case database of more than 40,000 images is taken with a total of 3752 images. Ground truth was generated by a user who defined the expected query result of a perfect system by selecting images relevant to a given query image. The results show that a smaller number of gray levels (32 - 64) leads to a better retrieval performance, especially when using relevance feedback. The use of more scales and directions for the Gabor filters in the texture analysis also leads to improved results but response time is going up equally due to the larger feature space. CBIRSs can be of great use in managing large medical image databases. They allow to find images that might otherwise be lost for research and publications. They also give students students the possibility to navigate within large image repositories. In the future, CBIR might also become more important in case-based reasoning and evidence-based medicine to support the diagnostics because first studies show good results.

Information Retrieval System Design Issues in a Microcomputer-Based Relational DBMS Environment.

ERIC Educational Resources Information Center

Wolfram, Dietmar

1992-01-01

Outlines the file structure requirements for a microcomputer-based information retrieval system using FoxPro, a relational database management system (DBMS). Issues relating to the design and implementation of such systems are discussed, and two possible designs are examined in terms of space economy and practicality of implementation. (15…

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

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

Trubey, D.K.

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

Three-dimensional spatiotemporal features for fast content-based retrieval of focal liver lesions.

PubMed

Roy, Sharmili; Chi, Yanling; Liu, Jimin; Venkatesh, Sudhakar K; Brown, Michael S

2014-11-01

Content-based image retrieval systems for 3-D medical datasets still largely rely on 2-D image-based features extracted from a few representative slices of the image stack. Most 2 -D features that are currently used in the literature not only model a 3-D tumor incompletely but are also highly expensive in terms of computation time, especially for high-resolution datasets. Radiologist-specified semantic labels are sometimes used along with image-based 2-D features to improve the retrieval performance. Since radiological labels show large interuser variability, are often unstructured, and require user interaction, their use as lesion characterizing features is highly subjective, tedious, and slow. In this paper, we propose a 3-D image-based spatiotemporal feature extraction framework for fast content-based retrieval of focal liver lesions. All the features are computer generated and are extracted from four-phase abdominal CT images. Retrieval performance and query processing times for the proposed framework is evaluated on a database of 44 hepatic lesions comprising of five pathological types. Bull's eye percentage score above 85% is achieved for three out of the five lesion pathologies and for 98% of query lesions, at least one same type of lesion is ranked among the top two retrieved results. Experiments show that the proposed system's query processing is more than 20 times faster than other already published systems that use 2-D features. With fast computation time and high retrieval accuracy, the proposed system has the potential to be used as an assistant to radiologists for routine hepatic tumor diagnosis.

Content-based image retrieval on mobile devices

NASA Astrophysics Data System (ADS)

Ahmad, Iftikhar; Abdullah, Shafaq; Kiranyaz, Serkan; Gabbouj, Moncef

2005-03-01

Content-based image retrieval area possesses a tremendous potential for exploration and utilization equally for researchers and people in industry due to its promising results. Expeditious retrieval of desired images requires indexing of the content in large-scale databases along with extraction of low-level features based on the content of these images. With the recent advances in wireless communication technology and availability of multimedia capable phones it has become vital to enable query operation in image databases and retrieve results based on the image content. In this paper we present a content-based image retrieval system for mobile platforms, providing the capability of content-based query to any mobile device that supports Java platform. The system consists of light-weight client application running on a Java enabled device and a server containing a servlet running inside a Java enabled web server. The server responds to image query using efficient native code from selected image database. The client application, running on a mobile phone, is able to initiate a query request, which is handled by a servlet in the server for finding closest match to the queried image. The retrieved results are transmitted over mobile network and images are displayed on the mobile phone. We conclude that such system serves as a basis of content-based information retrieval on wireless devices and needs to cope up with factors such as constraints on hand-held devices and reduced network bandwidth available in mobile environments.

MorphoSaurus--design and evaluation of an interlingua-based, cross-language document retrieval engine for the medical domain.

PubMed

Markó, K; Schulz, S; Hahn, U

2005-01-01

We propose an interlingua-based indexing approach to account for the particular challenges that arise in the design and implementation of cross-language document retrieval systems for the medical domain. Documents, as well as queries, are mapped to a language-independent conceptual layer on which retrieval operations are performed. We contrast this approach with the direct translation of German queries to English ones which, subsequently, are matched against English documents. We evaluate both approaches, interlingua-based and direct translation, on a large medical document collection, the OHSUMED corpus. A substantial benefit for interlingua-based document retrieval using German queries on English texts is found, which amounts to 93% of the (monolingual) English baseline. Most state-of-the-art cross-language information retrieval systems translate user queries to the language(s) of the target documents. In contra-distinction to this approach, translating both documents and user queries into a language-independent, concept-like representation format is more beneficial to enhance cross-language retrieval performance.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

NASIS data base management system: IBM 360 TSS implementation. Volume 5: Retrieval command system reference manual

NASA Technical Reports Server (NTRS)

1973-01-01

The retrieval command subsystem reference manual for the NASA Aerospace Safety Information System (NASIS) is presented. The command subsystem may be operated conversationally or in the batch mode. Retrieval commands are categorized into search-oriented and output-oriented commands. The characteristics of ancillary commands and their application are reported.

BROWSER: An Automatic Indexing On-Line Text Retrieval System. Annual Progress Report.

ERIC Educational Resources Information Center

Williams, J. H., Jr.

The development and testing of the Browsing On-line With Selective Retrieval (BROWSER) text retrieval system allowing a natural language query statement and providing on-line browsing capabilities through an IBM 2260 display terminal is described. The prototype system contains data bases of 25,000 German language patent abstracts, 9,000 English…

Content-based cell pathology image retrieval by combining different features

NASA Astrophysics Data System (ADS)

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

2004-04-01

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

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

PubMed

Sivakamasundari, J; Natarajan, V

2015-01-01

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

A WWW-Based Archive and Retrieval System for Multimedia

NASA Technical Reports Server (NTRS)

Hyon, J.; Sorensen, S.; Martin, M.; Kawasaki, K.; Takacs, M.

1996-01-01

This paper describes the Data Distribution Laboratory (DDL) and discusses issues involved in building multimedia CD-ROMs. It describes the modeling philosophy for cataloging multimedia products and the worldwide-web (WWW)-based multimedia archive and retrieval system (Webcat) built on that model.

Exploiting the Maximum Entropy Principle to Increase Retrieval Effectiveness.

ERIC Educational Resources Information Center

Cooper, William S.

1983-01-01

Presents information retrieval design approach in which queries of computer-based system consist of sets of terms, either unweighted or weighted with subjective term precision estimates, and retrieval outputs ranked by probability of usefulness estimated by "maximum entropy principle." Boolean and weighted request systems are discussed.…

A passage retrieval method based on probabilistic information retrieval model and UMLS concepts in biomedical question answering.

PubMed

Sarrouti, Mourad; Ouatik El Alaoui, Said

2017-04-01

Passage retrieval, the identification of top-ranked passages that may contain the answer for a given biomedical question, is a crucial component for any biomedical question answering (QA) system. Passage retrieval in open-domain QA is a longstanding challenge widely studied over the last decades. However, it still requires further efforts in biomedical QA. In this paper, we present a new biomedical passage retrieval method based on Stanford CoreNLP sentence/passage length, probabilistic information retrieval (IR) model and UMLS concepts. In the proposed method, we first use our document retrieval system based on PubMed search engine and UMLS similarity to retrieve relevant documents to a given biomedical question. We then take the abstracts from the retrieved documents and use Stanford CoreNLP for sentence splitter to make a set of sentences, i.e., candidate passages. Using stemmed words and UMLS concepts as features for the BM25 model, we finally compute the similarity scores between the biomedical question and each of the candidate passages and keep the N top-ranked ones. Experimental evaluations performed on large standard datasets, provided by the BioASQ challenge, show that the proposed method achieves good performances compared with the current state-of-the-art methods. The proposed method significantly outperforms the current state-of-the-art methods by an average of 6.84% in terms of mean average precision (MAP). We have proposed an efficient passage retrieval method which can be used to retrieve relevant passages in biomedical QA systems with high mean average precision. Copyright © 2017 Elsevier Inc. All rights reserved.

Towards an Intelligent Possibilistic Web Information Retrieval Using Multiagent System

ERIC Educational Resources Information Center

Elayeb, Bilel; Evrard, Fabrice; Zaghdoud, Montaceur; Ahmed, Mohamed Ben

2009-01-01

Purpose: The purpose of this paper is to make a scientific contribution to web information retrieval (IR). Design/methodology/approach: A multiagent system for web IR is proposed based on new technologies: Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). This system is based on a possibilistic qualitative approach which extends the…

Testing of a Natural Language Retrieval System for a Full Text Knowledge Base.

ERIC Educational Resources Information Center

Bernstein, Lionel M.; Williamson, Robert E.

1984-01-01

The Hepatitis Knowledge Base (text of prototype information system) was used for modifying and testing "A Navigator of Natural Language Organized (Textual) Data" (ANNOD), a retrieval system which combines probabilistic, linguistic, and empirical means to rank individual paragraphs of full text for similarity to natural language queries…

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

ERIC Educational Resources Information Center

Wang, James Z.; Du, Yanping

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

Massively parallel support for a case-based planning system

NASA Technical Reports Server (NTRS)

Kettler, Brian P.; Hendler, James A.; Anderson, William A.

1993-01-01

Case-based planning (CBP), a kind of case-based reasoning, is a technique in which previously generated plans (cases) are stored in memory and can be reused to solve similar planning problems in the future. CBP can save considerable time over generative planning, in which a new plan is produced from scratch. CBP thus offers a potential (heuristic) mechanism for handling intractable problems. One drawback of CBP systems has been the need for a highly structured memory to reduce retrieval times. This approach requires significant domain engineering and complex memory indexing schemes to make these planners efficient. In contrast, our CBP system, CaPER, uses a massively parallel frame-based AI language (PARKA) and can do extremely fast retrieval of complex cases from a large, unindexed memory. The ability to do fast, frequent retrievals has many advantages: indexing is unnecessary; very large case bases can be used; memory can be probed in numerous alternate ways; and queries can be made at several levels, allowing more specific retrieval of stored plans that better fit the target problem with less adaptation. In this paper we describe CaPER's case retrieval techniques and some experimental results showing its good performance, even on large case bases.

A Framework for Evaluation and Optimization of Relevance and Novelty-Based Retrieval

ERIC Educational Resources Information Center

Lad, Abhimanyu

2011-01-01

There has been growing interest in building and optimizing retrieval systems with respect to relevance and novelty of information, which together more realistically reflect the usefulness of a system as perceived by the user. How to combine these criteria into a single metric that can be used to measure as well as optimize retrieval systems is an…

The JPL Library Information Retrieval System

ERIC Educational Resources Information Center

Walsh, Josephine

1975-01-01

The development, capabilities, and products of the computer-based retrieval system of the Jet Propulsion Laboratory Library are described. The system handles books and documents, produces a book catalog, and provides a machine search capability. (Author)

Documentation of a spatial data-base management system for monitoring pesticide application in Washington

USGS Publications Warehouse

Schurr, K.M.; Cox, S.E.

1994-01-01

The Pesticide-Application Data-Base Management System was created as a demonstration project and was tested with data submitted to the Washington State Department of Agriculture by pesticide applicators from a small geographic area. These data were entered into the Department's relational data-base system and uploaded into the system's ARC/INFO files. Locations for pesticide applica- tions are assigned within the Public Land Survey System grids, and ARC/INFO programs in the Pesticide-Application Data-Base Management System can subdivide each survey section into sixteen idealized quarter-quarter sections for display map grids. The system provides data retrieval and geographic information system plotting capabilities from a menu of seven basic retrieval options. Additionally, ARC/INFO coverages can be created from the retrieved data when required for particular applications. The Pesticide-Application Data-Base Management System, or the general principles used in the system, could be adapted to other applica- tions or to other states.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

A Usability Survey of a Contents-Based Video Retrieval System by Combining Digital Video and an Electronic Bulletin Board

ERIC Educational Resources Information Center

Haga, Hirohide; Kaneda, Shigeo

2005-01-01

This article describes the survey of the usability of a novel content-based video retrieval system. This system combines video streaming and an electronic bulletin board system (BBS). Comments submitted to the BBS are used to index video data. Following the development of the prototype system an experimental survey with ten subjects was performed.…

Learning Object Retrieval and Aggregation Based on Learning Styles

ERIC Educational Resources Information Center

Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

2017-01-01

The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

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

PubMed

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

2016-06-24

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

Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras

PubMed Central

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

2016-01-01

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

Comparison of Gaussian and non-Gaussian Atmospheric Profile Retrievals from Satellite Microwave Data

NASA Astrophysics Data System (ADS)

Kliewer, A.; Forsythe, J. M.; Fletcher, S. J.; Jones, A. S.

2017-12-01

The Cooperative Institute for Research in the Atmosphere at Colorado State University has recently developed two different versions of a mixed-distribution (lognormal combined with a Gaussian) based microwave temperature and mixing ratio retrieval system as well as the original Gaussian-based approach. These retrieval systems are based upon 1DVAR theory but have been adapted to use different descriptive statistics of the lognormal distribution to minimize the background errors. The input radiance data is from the AMSU-A and MHS instruments on the NOAA series of spacecraft. To help illustrate how the three retrievals are affected by the change in the distribution we are in the process of creating a new website to show the output from the different retrievals. Here we present initial results from different dynamical situations to show how the tool could be used by forecasters as well as for educators. However, as the new retrieved values are from a non-Gaussian based 1DVAR then they will display non-Gaussian behaviors that need to pass a quality control measure that is consistent with this distribution, and these new measures are presented here along with initial results for checking the retrievals.

Visual Semantic Based 3D Video Retrieval System Using HDFS.

PubMed

Kumar, C Ranjith; Suguna, S

2016-08-01

This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose, we intent to hitch on BOVW and Mapreduce in 3D framework. Instead of conventional shape based local descriptors, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based- Predictive Clustering Tree) algorithm is used to generate visual codebook and histogram is produced. Further, matching is performed using soft weighting scheme with L 2 distance function. As a final step, retrieved results are ranked according to the Index value and acknowledged to the user as a feedback .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we future the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

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

NASA Astrophysics Data System (ADS)

Chen, Yi-Chen; Lin, Chao-Hung

2016-06-01

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

Designing a Syntax-Based Retrieval System for Supporting Language Learning

ERIC Educational Resources Information Center

Tsao, Nai-Lung; Kuo, Chin-Hwa; Wible, David; Hung, Tsung-Fu

2009-01-01

In this paper, we propose a syntax-based text retrieval system for on-line language learning and use a fast regular expression search engine as its main component. Regular expression searches provide more scalable querying and search results than keyword-based searches. However, without a well-designed index scheme, the execution time of regular…

AIRS Retrieval Validation During the EAQUATE

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L.; Cuomo, Vincenzo; Taylor, Jonathan P.; Barnet, Christopher D.; DiGirolamo, Paolo; Pappalardo, Gelsomina; Larar, Allen M.; Liu, Xu; Newman, Stuart M.

2006-01-01

Atmospheric and surface thermodynamic parameters retrieved with advanced hyperspectral remote sensors of Earth observing satellites are critical for weather prediction and scientific research. The retrieval algorithms and retrieved parameters from satellite sounders must be validated to demonstrate the capability and accuracy of both observation and data processing systems. The European AQUA Thermodynamic Experiment (EAQUATE) was conducted mainly for validation of the Atmospheric InfraRed Sounder (AIRS) on the AQUA satellite, but also for assessment of validation systems of both ground-based and aircraft-based instruments which will be used for other satellite systems such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) from the NPOESS Preparatory Project and the following NPOESS series of satellites. Detailed inter-comparisons were conducted and presented using different retrieval methodologies: measurements from airborne ultraspectral Fourier transform spectrometers, aircraft in-situ instruments, dedicated dropsondes and radiosondes, and ground based Raman Lidar, as well as from the European Center for Medium range Weather Forecasting (ECMWF) modeled thermal structures. The results of this study not only illustrate the quality of the measurements and retrieval products but also demonstrate the capability of these validation systems which are put in place to validate current and future hyperspectral sounding instruments and their scientific products.

New model for distributed multimedia databases and its application to networking of museums

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1998-02-01

This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.

Content-aware network storage system supporting metadata retrieval

NASA Astrophysics Data System (ADS)

Liu, Ke; Qin, Leihua; Zhou, Jingli; Nie, Xuejun

2008-12-01

Nowadays, content-based network storage has become the hot research spot of academy and corporation[1]. In order to solve the problem of hit rate decline causing by migration and achieve the content-based query, we exploit a new content-aware storage system which supports metadata retrieval to improve the query performance. Firstly, we extend the SCSI command descriptor block to enable system understand those self-defined query requests. Secondly, the extracted metadata is encoded by extensible markup language to improve the universality. Thirdly, according to the demand of information lifecycle management (ILM), we store those data in different storage level and use corresponding query strategy to retrieval them. Fourthly, as the file content identifier plays an important role in locating data and calculating block correlation, we use it to fetch files and sort query results through friendly user interface. Finally, the experiments indicate that the retrieval strategy and sort algorithm have enhanced the retrieval efficiency and precision.

Recent Experiments with INQUERY

DTIC Science & Technology

1995-11-01

were conducted with version of the INQUERY information retrieval system INQUERY is based on the Bayesian inference network retrieval model It is...corpus based query expansion For TREC a subset of of the adhoc document set was used to build the InFinder database None of the...experiments that showed signi cant improvements in retrieval eectiveness when document rankings based on the entire document text are combined with

Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval

ERIC Educational Resources Information Center

Tawfik, Andrew A.; Alhoori, Hamed; Keene, Charles Wayne; Bailey, Christian; Hogan, Maureen

2018-01-01

In case library learning environments, learners are presented with an array of narratives that can be used to guide their problem solving. However, according to theorists, learners struggle to identify and retrieve the optimal case to solve a new problem. Given the challenges novice face during case retrieval, recommender systems can be embedded…

Intelligent web image retrieval system

NASA Astrophysics Data System (ADS)

Hong, Sungyong; Lee, Chungwoo; Nah, Yunmook

2001-07-01

Recently, the web sites such as e-business sites and shopping mall sites deal with lots of image information. To find a specific image from these image sources, we usually use web search engines or image database engines which rely on keyword only retrievals or color based retrievals with limited search capabilities. This paper presents an intelligent web image retrieval system. We propose the system architecture, the texture and color based image classification and indexing techniques, and representation schemes of user usage patterns. The query can be given by providing keywords, by selecting one or more sample texture patterns, by assigning color values within positional color blocks, or by combining some or all of these factors. The system keeps track of user's preferences by generating user query logs and automatically add more search information to subsequent user queries. To show the usefulness of the proposed system, some experimental results showing recall and precision are also explained.

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

NASA Astrophysics Data System (ADS)

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

2008-02-01

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

Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge

PubMed Central

Scerri, Antony; Kuriakose, John; Deshmane, Amit Ajit; Stanger, Mark; Moore, Rebekah; Naik, Raj; de Waard, Anita

2017-01-01

Abstract We developed a two-stream, Apache Solr-based information retrieval system in response to the bioCADDIE 2016 Dataset Retrieval Challenge. One stream was based on the principle of word embeddings, the other was rooted in ontology based indexing. Despite encountering several issues in the data, the evaluation procedure and the technologies used, the system performed quite well. We provide some pointers towards future work: in particular, we suggest that more work in query expansion could benefit future biomedical search engines. Database URL: https://data.mendeley.com/datasets/zd9dxpyybg/1 PMID:29220454

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

NASA Astrophysics Data System (ADS)

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

2005-04-01

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

Knowledge retrieval as one type of knowledge-based decision support in medicine: results of an evaluation study.

PubMed

Haux, R; Grothe, W; Runkel, M; Schackert, H K; Windeler, H J; Winter, A; Wirtz, R; Herfarth, C; Kunze, S

1996-04-01

We report on a prospective, prolective observational study, supplying information on how physicians and other health care professionals retrieve medical knowledge on-line within the Heidelberg University Hospital information system. Within this hospital information system, on-line access to medical knowledge has been realised by installing a medical knowledge server in the range of about 24 GB and by providing access to it by health care professional workstations in wards, physicians' rooms, etc. During the study, we observed about 96 accesses per working day. The main group of health care professionals retrieving medical knowledge were physicians and medical students. Primary reasons for its utilisation were identified as support for the users' scientific work (50%), own clinical cases (19%), general medical problems (14%) and current clinical problems (13%). Health care professionals had accesses to medical knowledge bases such as MEDLINE (79%), drug bases ('Rote Liste', 6%), and to electronic text books and knowledge base systems as well. Sixty-five percent of accesses to medical knowledge were judged to be successful. In our opinion, medical knowledge retrieval can serve as a first step towards knowledge processing in medicine. We point out the consequences for the management of hospital information systems in order to provide the prerequisites for such a type of knowledge retrieval.

Content-Based Image Retrieval System for Pulmonary Nodules: Assisting Radiologists in Self-Learning and Diagnosis of Lung Cancer.

PubMed

Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Dutta, Anirvan; Garg, Mandeep; Khandelwal, Niranjan

2017-02-01

Visual information of similar nodules could assist the budding radiologists in self-learning. This paper presents a content-based image retrieval (CBIR) system for pulmonary nodules, observed in lung CT images. The reported CBIR systems of pulmonary nodules cannot be put into practice as radiologists need to draw the boundary of nodules during query formation and feature database creation. In the proposed retrieval system, the pulmonary nodules are segmented using a semi-automated technique, which requires a seed point on the nodule from the end-user. The involvement of radiologists in feature database creation is also reduced, as only a seed point is expected from radiologists instead of manual delineation of the boundary of the nodules. The performance of the retrieval system depends on the accuracy of the segmentation technique. Several 3D features are explored to improve the performance of the proposed retrieval system. A set of relevant shape and texture features are considered for efficient representation of the nodules in the feature space. The proposed CBIR system is evaluated for three configurations such as configuration-1 (composite rank of malignancy "1","2" as benign and "4","5" as malignant), configuration-2 (composite rank of malignancy "1","2", "3" as benign and "4","5" as malignant), and configuration-3 (composite rank of malignancy "1","2" as benign and "3","4","5" as malignant). Considering top 5 retrieved nodules and Euclidean distance metric, the precision achieved by the proposed method for configuration-1, configuration-2, and configuration-3 are 82.14, 75.91, and 74.27 %, respectively. The performance of the proposed CBIR system is close to the most recent technique, which is dependent on radiologists for manual segmentation of nodules. A computer-aided diagnosis (CAD) system is also developed based on CBIR paradigm. Performance of the proposed CBIR-based CAD system is close to performance of the CAD system using support vector machine.

User-oriented evaluation of a medical image retrieval system for radiologists.

PubMed

Markonis, Dimitrios; Holzer, Markus; Baroz, Frederic; De Castaneda, Rafael Luis Ruiz; Boyer, Célia; Langs, Georg; Müller, Henning

2015-10-01

This article reports the user-oriented evaluation of a text- and content-based medical image retrieval system. User tests with radiologists using a search system for images in the medical literature are presented. The goal of the tests is to assess the usability of the system, identify system and interface aspects that need improvement and useful additions. Another objective is to investigate the system's added value to radiology information retrieval. The study provides an insight into required specifications and potential shortcomings of medical image retrieval systems through a concrete methodology for conducting user tests. User tests with a working image retrieval system of images from the biomedical literature were performed in an iterative manner, where each iteration had the participants perform radiology information seeking tasks and then refining the system as well as the user study design itself. During these tasks the interaction of the users with the system was monitored, usability aspects were measured, retrieval success rates recorded and feedback was collected through survey forms. In total, 16 radiologists participated in the user tests. The success rates in finding relevant information were on average 87% and 78% for image and case retrieval tasks, respectively. The average time for a successful search was below 3 min in both cases. Users felt quickly comfortable with the novel techniques and tools (after 5 to 15 min), such as content-based image retrieval and relevance feedback. User satisfaction measures show a very positive attitude toward the system's functionalities while the user feedback helped identifying the system's weak points. The participants proposed several potentially useful new functionalities, such as filtering by imaging modality and search for articles using image examples. The iterative character of the evaluation helped to obtain diverse and detailed feedback on all system aspects. Radiologists are quickly familiar with the functionalities but have several comments on desired functionalities. The analysis of the results can potentially assist system refinement for future medical information retrieval systems. Moreover, the methodology presented as well as the discussion on the limitations and challenges of such studies can be useful for user-oriented medical image retrieval evaluation, as user-oriented evaluation of interactive system is still only rarely performed. Such interactive evaluations can be limited in effort if done iteratively and can give many insights for developing better systems. Copyright © 2015. Published by Elsevier Ireland Ltd.

Interactive radiographic image retrieval system.

PubMed

Kundu, Malay Kumar; Chowdhury, Manish; Das, Sudeb

2017-02-01

Content based medical image retrieval (CBMIR) systems enable fast diagnosis through quantitative assessment of the visual information and is an active research topic over the past few decades. Most of the state-of-the-art CBMIR systems suffer from various problems: computationally expensive due to the usage of high dimensional feature vectors and complex classifier/clustering schemes. Inability to properly handle the "semantic gap" and the high intra-class versus inter-class variability problem of the medical image database (like radiographic image database). This yields an exigent demand for developing highly effective and computationally efficient retrieval system. We propose a novel interactive two-stage CBMIR system for diverse collection of medical radiographic images. Initially, Pulse Coupled Neural Network based shape features are used to find out the most probable (similar) image classes using a novel "similarity positional score" mechanism. This is followed by retrieval using Non-subsampled Contourlet Transform based texture features considering only the images of the pre-identified classes. Maximal information compression index is used for unsupervised feature selection to achieve better results. To reduce the semantic gap problem, the proposed system uses a novel fuzzy index based relevance feedback mechanism by incorporating subjectivity of human perception in an analytic manner. Extensive experiments were carried out to evaluate the effectiveness of the proposed CBMIR system on a subset of Image Retrieval in Medical Applications (IRMA)-2009 database consisting of 10,902 labeled radiographic images of 57 different modalities. We obtained overall average precision of around 98% after only 2-3 iterations of relevance feedback mechanism. We assessed the results by comparisons with some of the state-of-the-art CBMIR systems for radiographic images. Unlike most of the existing CBMIR systems, in the proposed two-stage hierarchical framework, main importance is given on constructing efficient and compact feature vector representation, search-space reduction and handling the "semantic gap" problem effectively, without compromising the retrieval performance. Experimental results and comparisons show that the proposed system performs efficiently in the radiographic medical image retrieval field. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Enhancing Retrieval with Hyperlinks: A General Model Based on Propositional Argumentation Systems.

ERIC Educational Resources Information Center

Picard, Justin; Savoy, Jacques

2003-01-01

Discusses the use of hyperlinks for improving information retrieval on the World Wide Web and proposes a general model for using hyperlinks based on Probabilistic Argumentation Systems. Topics include propositional logic, knowledge, and uncertainty; assumptions; using hyperlinks to modify document score and rank; and estimating the popularity of a…

An Optical Disk-Based Information Retrieval System.

ERIC Educational Resources Information Center

Bender, Avi

1988-01-01

Discusses a pilot project by the Nuclear Regulatory Commission to apply optical disk technology to the storage and retrieval of documents related to its high level waste management program. Components and features of the microcomputer-based system which provides full-text and image access to documents are described. A sample search is included.…

GPS Radio Occultation as Part of the Global Observing System for Atmosphere

NASA Technical Reports Server (NTRS)

Mannucci, Anthony J.; Ao, C. O.; Iijima, B. A.; Wilson, B. D.; Yunck, T. P.; Kursinski, E. R.

2008-01-01

Topics include: The Measurement (Physical retrievals based on time standards), GPS Retrieval Products, Retrievals and Radiances: CLARREO Mission, GPS RO and AIRS, GPS RO and Microwave, GPS RO and Radiosondes, GPS/GNSS Science, and Conclusions.

Concept-Based Retrieval from Critical Incident Reports.

PubMed

Denecke, Kerstin

2017-01-01

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

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

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

Choo, Jaegul; Kim, Hannah; Clarkson, Edward

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

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

DOE PAGES

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

2018-01-31

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

SLIMMER--A UNIX System-Based Information Retrieval System.

ERIC Educational Resources Information Center

Waldstein, Robert K.

1988-01-01

Describes an information retrieval system developed at Bell Laboratories to create and maintain a variety of different but interrelated databases, and to provide controlled access to these databases. The components discussed include the interfaces, indexing rules, display languages, response time, and updating procedures of the system. (6 notes…

A humming retrieval system based on music fingerprint

NASA Astrophysics Data System (ADS)

Han, Xingkai; Cao, Baiyu

2011-10-01

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

Mobile object retrieval in server-based image databases

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

A novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2005-01-01

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

A novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2004-12-01

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

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

NASA Astrophysics Data System (ADS)

Venkatesh, Vijay

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

MRML: an extensible communication protocol for interoperability and benchmarking of multimedia information retrieval systems

NASA Astrophysics Data System (ADS)

Mueller, Wolfgang; Mueller, Henning; Marchand-Maillet, Stephane; Pun, Thierry; Squire, David M.; Pecenovic, Zoran; Giess, Christoph; de Vries, Arjen P.

2000-10-01

While in the area of relational databases interoperability is ensured by common communication protocols (e.g. ODBC/JDBC using SQL), Content Based Image Retrieval Systems (CBIRS) and other multimedia retrieval systems are lacking both a common query language and a common communication protocol. Besides its obvious short term convenience, interoperability of systems is crucial for the exchange and analysis of user data. In this paper, we present and describe an extensible XML-based query markup language, called MRML (Multimedia Retrieval markup Language). MRML is primarily designed so as to ensure interoperability between different content-based multimedia retrieval systems. Further, MRML allows researchers to preserve their freedom in extending their system as needed. MRML encapsulates multimedia queries in a way that enable multimedia (MM) query languages, MM content descriptions, MM query engines, and MM user interfaces to grow independently from each other, reaching a maximum of interoperability while ensuring a maximum of freedom for the developer. For benefitting from this, only a few simple design principles have to be respected when extending MRML for one's fprivate needs. The design of extensions withing the MRML framework will be described in detail in the paper. MRML has been implemented and tested for the CBIRS Viper, using the user interface Snake Charmer. Both are part of the GNU project and can be downloaded at our site.

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

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

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

1993-09-01

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

World Wide Web Based Image Search Engine Using Text and Image Content Features

NASA Astrophysics Data System (ADS)

Luo, Bo; Wang, Xiaogang; Tang, Xiaoou

2003-01-01

Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. In addition, the images can be re-ranked by the content features according to the user feedback. Such a design makes it truly practical to use both text and image content for image retrieval over the Internet. Experimental results confirm the efficiency of the system.

The JPL Library information retrieval system

NASA Technical Reports Server (NTRS)

Walsh, J.

1975-01-01

The development, capabilities, and products of the computer-based retrieval system of the Jet Propulsion Laboratory Library are described. The system handles books and documents, produces a book catalog, and provides a machine search capability. Programs and documentation are available to the public through NASA's computer software dissemination program.

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

ERIC Educational Resources Information Center

Fox, Edward A.

1987-01-01

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

AEROMETRIC INFORMATION RETRIEVAL SYSTEM (AIRS) - GRAPHICS

EPA Science Inventory

Aerometric Information Retrieval System (AIRS) is a computer-based repository of information about airborne pollution in the United States and various World Health Organization (WHO) member countries. AIRS is administered by the U.S. Environmental Protection Agency, and runs on t...

An XML-based system for the flexible classification and retrieval of clinical practice guidelines.

PubMed Central

Ganslandt, T.; Mueller, M. L.; Krieglstein, C. F.; Senninger, N.; Prokosch, H. U.

2002-01-01

Beneficial effects of clinical practice guidelines (CPGs) have not yet reached expectations due to limited routine adoption. Electronic distribution and reminder systems have the potential to overcome implementation barriers. Existing electronic CPG repositories like the National Guideline Clearinghouse (NGC) provide individual access but lack standardized computer-readable interfaces necessary for automated guideline retrieval. The aim of this paper was to facilitate automated context-based selection and presentation of CPGs. Using attributes from the NGC classification scheme, an XML-based metadata repository was successfully implemented, providing document storage, classification and retrieval functionality. Semi-automated extraction of attributes was implemented for the import of XML guideline documents using XPath. A hospital information system interface was exemplarily implemented for diagnosis-based guideline invocation. Limitations of the implemented system are discussed and possible future work is outlined. Integration of standardized computer-readable search interfaces into existing CPG repositories is proposed. PMID:12463831

NASIS data base management system - IBM 360/370 OS MVT implementation. 5: Retrieval command system reference manual

NASA Technical Reports Server (NTRS)

1973-01-01

The retrieval command subsystem reference manual for the NASA Aerospace Safety Information System (NASIS) is presented. The output oriented classification of retrieval commands provides the user with the ability to review a set of data items for verification or inspection as a typewriter or CRT terminal and to print a set of data on a remote printer. Predefined and user-definable data formatting are available for both output media.

A mathematical model of neuro-fuzzy approximation in image classification

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Users guide for the Water Resources Division bibliographic retrieval and report generation system

USGS Publications Warehouse

Tamberg, Nora

1983-01-01

The WRDBIB Retrieval and Report-generation system has been developed by applying Multitrieve (CSD 1980, Reston) software to bibliographic data files. The WRDBIB data base includes some 9 ,000 records containing bibliographic citations and descriptors of WRD reports released for publication during 1968-1982. The data base is resident in the Reston Multics computer and may be accessed by registered Multics users in the field. The WRDBIB Users Guide provides detailed procedures on how to run retrieval programs using WRDBIB library files, and how to prepare custom bibliographic reports and author indexes. Users may search the WRDBIB data base on the following variable fields as described in the Data Dictionary: Authors, organizational source, title, citation, publication year, descriptors, and the WRSIC (accession) number. The Users Guide provides ample examples of program runs illustrating various retrieval and report generation aspects. Appendices include Multics access and file manipulation procedures; a ' Glossary of Selected Terms'; and a complete ' Retrieval Session ' with step-by-step outlines. (USGS)

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists

PubMed Central

Wiley, Laura K.; Sivley, R. Michael; Bush, William S.

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist PMID:23894185

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

PubMed

Wiley, Laura K; Sivley, R Michael; Bush, William S

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist.

TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury

NASA Astrophysics Data System (ADS)

Li, Shimiao; Gong, Tianxia; Wang, Jie; Liu, Ruizhe; Tan, Chew Lim; Leong, Tze Yun; Pang, Boon Chuan; Lim, C. C. Tchoyoson; Lee, Cheng Kiang; Tian, Qi; Zhang, Zhuo

2010-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction. However, current hospital database system does not provide an efficient and intuitive tool for doctors to search out cases relevant to the current study case. In this paper, we present the TBIdoc system: a content-based image retrieval (CBIR) system which works on the TBI CT images. In this web-based system, user can query by uploading CT image slices from one study, retrieval result is a list of TBI cases ranked according to their 3D visual similarity to the query case. Specifically, cases of TBI CT images often present diffuse or focal lesions. In TBIdoc system, these pathological image features are represented as bin-based binary feature vectors. We use the Jaccard-Needham measure as the similarity measurement. Based on these, we propose a 3D similarity measure for computing the similarity score between two series of CT slices. nDCG is used to evaluate the system performance, which shows the system produces satisfactory retrieval results. The system is expected to improve the current hospital data management in TBI and to give better support for the clinical decision-making process. It may also contribute to the computer-aided education in TBI.

Hypertext Image Retrieval: The Evolution of an Application.

ERIC Educational Resources Information Center

Roberts, G. Louis; Kenney, Carol E.

1991-01-01

Describes the development and implementation of a full-text image retrieval system at the Boeing Commercial Airplane Group. The conversion of card formats to a microcomputer-based system using HyperCard is described; the online system architecture is explained; and future plans are discussed, including conversion to digital images. (LRW)

Interactions between Visual Attention and Episodic Retrieval: Dissociable Contributions of Parietal Regions during Gist-Based False Recognition

PubMed Central

Guerin, Scott A.; Robbins, Clifford A.; Gilmore, Adrian W.; Schacter, Daniel L.

2012-01-01

SUMMARY The interaction between episodic retrieval and visual attention is relatively unexplored. Given that systems mediating attention and episodic memory appear to be segregated, and perhaps even in competition, it is unclear how visual attention is recruited during episodic retrieval. We investigated the recruitment of visual attention during the suppression of gist-based false recognition, the tendency to falsely recognize items that are similar to previously encountered items. Recruitment of visual attention was associated with activity in the dorsal attention network. The inferior parietal lobule, often implicated in episodic retrieval, tracked veridical retrieval of perceptual detail and showed reduced activity during the engagement of visual attention, consistent with a competitive relationship with the dorsal attention network. These findings suggest that the contribution of the parietal cortex to interactions between visual attention and episodic retrieval entails distinct systems that contribute to different components of the task while also suppressing each other. PMID:22998879

User centered and ontology based information retrieval system for life sciences.

PubMed

Sy, Mohameth-François; Ranwez, Sylvie; Montmain, Jacky; Regnault, Armelle; Crampes, Michel; Ranwez, Vincent

2012-01-25

Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help.

User centered and ontology based information retrieval system for life sciences

PubMed Central

2012-01-01

Background Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. Results This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. Conclusions The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help. PMID:22373375

Content-Based Medical Image Retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Deserno, Thomas M.

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

Image/text automatic indexing and retrieval system using context vector approach

NASA Astrophysics Data System (ADS)

Qing, Kent P.; Caid, William R.; Ren, Clara Z.; McCabe, Patrick

1995-11-01

Thousands of documents and images are generated daily both on and off line on the information superhighway and other media. Storage technology has improved rapidly to handle these data but indexing this information is becoming very costly. HNC Software Inc. has developed a technology for automatic indexing and retrieval of free text and images. This technique is demonstrated and is based on the concept of `context vectors' which encode a succinct representation of the associated text and features of sub-image. In this paper, we will describe the Automated Librarian System which was designed for free text indexing and the Image Content Addressable Retrieval System (ICARS) which extends the technique from the text domain into the image domain. Both systems have the ability to automatically assign indices for a new document and/or image based on the content similarities in the database. ICARS also has the capability to retrieve images based on similarity of content using index terms, text description, and user-generated images as a query without performing segmentation or object recognition.

SHRIF, a General-Purpose System for Heuristic Retrieval of Information and Facts, Applied to Medical Knowledge Processing.

ERIC Educational Resources Information Center

Findler, Nicholas V.; And Others

1992-01-01

Describes SHRIF, a System for Heuristic Retrieval of Information and Facts, and the medical knowledge base that was used in its development. Highlights include design decisions; the user-machine interface, including the language processor; and the organization of the knowledge base in an artificial intelligence (AI) project like this one. (57…

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

PubMed

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

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

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

PubMed Central

Song, Wei; Mei, Haibin

2017-01-01

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

Relevance and Retrieval Evaluation: Perspectives from Medicine.

ERIC Educational Resources Information Center

Hersh, William

1994-01-01

Discusses topical relevance and situational relevance, which takes into account the impact of the retrieval system on the user, in the context of medicine. Topics addressed include scientific validity; limitations of current evaluation methodology, including recall and precision; and a framework for future retrieval research based on an…

Knowledge-light adaptation approaches in case-based reasoning for radiotherapy treatment planning.

PubMed

Petrovic, Sanja; Khussainova, Gulmira; Jagannathan, Rupa

2016-03-01

Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which can be difficult to acquire and often is not readily available. In this study, we investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation. We developed two adaptation approaches: adaptation based on machine-learning tools and adaptation-guided retrieval. They were used to adapt the beam number and beam angles suggested in the retrieved case. Two machine-learning tools, neural networks and naive Bayes classifier, were used in the adaptation to learn how the difference in attribute values between the retrieved and new cases affects the output of these two cases. The adaptation-guided retrieval takes into consideration not only the similarity between the new and retrieved cases, but also how to adapt the retrieved case. The research was carried out in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. All experiments were performed using real-world brain cancer patient cases treated with three-dimensional (3D)-conformal radiotherapy. Neural networks-based adaptation improved the success rate of the CBR system with no adaptation by 12%. However, naive Bayes classifier did not improve the current retrieval results as it did not consider the interplay among attributes. The adaptation-guided retrieval of the case for beam number improved the success rate of the CBR system by 29%. However, it did not demonstrate good performance for the beam angle adaptation. Its success rate was 29% versus 39% when no adaptation was performed. The obtained empirical results demonstrate that the proposed adaptation methods improve the performance of the existing CBR system in recommending the number of beams to use. However, we also conclude that to be effective, the proposed adaptation of beam angles requires a large number of relevant cases in the case base. Copyright © 2016 Elsevier B.V. All rights reserved.

Design implications for task-specific search utilities for retrieval and re-engineering of code

NASA Astrophysics Data System (ADS)

Iqbal, Rahat; Grzywaczewski, Adam; Halloran, John; Doctor, Faiyaz; Iqbal, Kashif

2017-05-01

The importance of information retrieval systems is unquestionable in the modern society and both individuals as well as enterprises recognise the benefits of being able to find information effectively. Current code-focused information retrieval systems such as Google Code Search, Codeplex or Koders produce results based on specific keywords. However, these systems do not take into account developers' context such as development language, technology framework, goal of the project, project complexity and developer's domain expertise. They also impose additional cognitive burden on users in switching between different interfaces and clicking through to find the relevant code. Hence, they are not used by software developers. In this paper, we discuss how software engineers interact with information and general-purpose information retrieval systems (e.g. Google, Yahoo!) and investigate to what extent domain-specific search and recommendation utilities can be developed in order to support their work-related activities. In order to investigate this, we conducted a user study and found that software engineers followed many identifiable and repeatable work tasks and behaviours. These behaviours can be used to develop implicit relevance feedback-based systems based on the observed retention actions. Moreover, we discuss the implications for the development of task-specific search and collaborative recommendation utilities embedded with the Google standard search engine and Microsoft IntelliSense for retrieval and re-engineering of code. Based on implicit relevance feedback, we have implemented a prototype of the proposed collaborative recommendation system, which was evaluated in a controlled environment simulating the real-world situation of professional software engineers. The evaluation has achieved promising initial results on the precision and recall performance of the system.

AEROMETRIC INFORMATION RETRIEVAL SYSTEM (AIRS) -GEOGRAPHIC, COMMON, AND MAINTENANCE SUBSYSTEM (GCS)

EPA Science Inventory

Aerometric Information Retrieval System (AIRS) is a computer-based repository of information about airborne pollution in the United States and various World Health Organization (WHO) member countries. AIRS is administered by the U.S. Environmental Protection Agency, and runs on t...

Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography

NASA Astrophysics Data System (ADS)

Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

2015-09-01

In this paper, a novel image encryption system with fingerprint used as a secret key is proposed based on the phase retrieval algorithm and RSA public key algorithm. In the system, the encryption keys include the fingerprint and the public key of RSA algorithm, while the decryption keys are the fingerprint and the private key of RSA algorithm. If the users share the fingerprint, then the system will meet the basic agreement of asymmetric cryptography. The system is also applicable for the information authentication. The fingerprint as secret key is used in both the encryption and decryption processes so that the receiver can identify the authenticity of the ciphertext by using the fingerprint in decryption process. Finally, the simulation results show the validity of the encryption scheme and the high robustness against attacks based on the phase retrieval technique.

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

PubMed Central

Muhammad, Khan; Baik, Sung Wook

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2004-11-01

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

Assessment of Mars Atmospheric Temperature Retrievals from the Thermal Emission Spectrometer Radiances

NASA Technical Reports Server (NTRS)

Hoffman, Matthew J.; Eluszkiewicz, Janusz; Weisenstein, Deborah; Uymin, Gennady; Moncet, Jean-Luc

2012-01-01

Motivated by the needs of Mars data assimilation. particularly quantification of measurement errors and generation of averaging kernels. we have evaluated atmospheric temperature retrievals from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) radiances. Multiple sets of retrievals have been considered in this study; (1) retrievals available from the Planetary Data System (PDS), (2) retrievals based on variants of the retrieval algorithm used to generate the PDS retrievals, and (3) retrievals produced using the Mars 1-Dimensional Retrieval (M1R) algorithm based on the Optimal Spectral Sampling (OSS ) forward model. The retrieved temperature profiles are compared to the MGS Radio Science (RS) temperature profiles. For the samples tested, the M1R temperature profiles can be made to agree within 2 K with the RS temperature profiles, but only after tuning the prior and error statistics. Use of a global prior that does not take into account the seasonal dependence leads errors of up 6 K. In polar samples. errors relative to the RS temperature profiles are even larger. In these samples, the PDS temperature profiles also exhibit a poor fit with RS temperatures. This fit is worse than reported in previous studies, indicating that the lack of fit is due to a bias correction to TES radiances implemented after 2004. To explain the differences between the PDS and Ml R temperatures, the algorithms are compared directly, with the OSS forward model inserted into the PDS algorithm. Factors such as the filtering parameter, the use of linear versus nonlinear constrained inversion, and the choice of the forward model, are found to contribute heavily to the differences in the temperature profiles retrieved in the polar regions, resulting in uncertainties of up to 6 K. Even outside the poles, changes in the a priori statistics result in different profile shapes which all fit the radiances within the specified error. The importance of the a priori statistics prevents reliable global retrievals based a single a priori and strongly implies that a robust science analysis must instead rely on retrievals employing localized a priori information, for example from an ensemble based data assimilation system such as the Local Ensemble Transform Kalman Filter (LETKF).

Impact of Lidar Wind Sounding on Mesoscale Forecast

NASA Technical Reports Server (NTRS)

Miller, Timothy L.; Chou, Shih-Hung; Goodman, H. Michael (Technical Monitor)

2001-01-01

An Observing System Simulation Experiment (OSSE) was conducted to study the impact of airborne lidar wind sounding on mesoscale weather forecast. A wind retrieval scheme, which interpolates wind data from a grid data system, simulates the retrieval of wind profile from a satellite lidar system. A mesoscale forecast system based on the PSU/NCAR MM5 model is developed and incorporated the assimilation of the retrieved line-of-sight wind. To avoid the "identical twin" problem, the NCEP reanalysis data is used as our reference "nature" atmosphere. The simulated space-based lidar wind observations were retrieved by interpolating the NCEP values to the observation locations. A modified dataset obtained by smoothing the NCEP dataset was used as the initial state whose forecast was sought to be improved by assimilating the retrieved lidar observations. Forecasts using wind profiles with various lidar instrument parameters has been conducted. The results show that to significantly improve the mesoscale forecast the satellite should fly near the storm center with large scanning radius. Increasing lidar firing rate also improves the forecast. Cloud cover and lack of aerosol degrade the quality of the lidar wind data and, subsequently, the forecast.

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

NASA Technical Reports Server (NTRS)

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

1974-01-01

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

Navy Medical Information Storage and Retrieval System: Navy MEDISTARS. TR-1-71-Part 2, Manual of Indexing Terms; First Edition.

ERIC Educational Resources Information Center

Ramsey-Klee, Diane M.

A computer-based information storage and retrieval system was designed and implemented for processing Navy neuropsychiatric case history reports. The system design objectives were to produce a dynamic and flexible medical information processing tool. The system that was designed has been given the name NAVY MEDical Information STorage and…

Retrieval-travel-time model for free-fall-flow-rack automated storage and retrieval system

NASA Astrophysics Data System (ADS)

Metahri, Dhiyaeddine; Hachemi, Khalid

2018-03-01

Automated storage and retrieval systems (AS/RSs) are material handling systems that are frequently used in manufacturing and distribution centers. The modelling of the retrieval-travel time of an AS/RS (expected product delivery time) is practically important, because it allows us to evaluate and improve the system throughput. The free-fall-flow-rack AS/RS has emerged as a new technology for drug distribution. This system is a new variation of flow-rack AS/RS that uses an operator or a single machine for storage operations, and uses a combination between the free-fall movement and a transport conveyor for retrieval operations. The main contribution of this paper is to develop an analytical model of the expected retrieval-travel time for the free-fall flow-rack under a dedicated storage assignment policy. The proposed model, which is based on a continuous approach, is compared for accuracy, via simulation, with discrete model. The obtained results show that the maximum deviation between the continuous model and the simulation is less than 5%, which shows the accuracy of our model to estimate the retrieval time. The analytical model is useful to optimise the dimensions of the rack, assess the system throughput, and evaluate different storage policies.

Content-based TV sports video retrieval using multimodal analysis

NASA Astrophysics Data System (ADS)

Yu, Yiqing; Liu, Huayong; Wang, Hongbin; Zhou, Dongru

2003-09-01

In this paper, we propose content-based video retrieval, which is a kind of retrieval by its semantical contents. Because video data is composed of multimodal information streams such as video, auditory and textual streams, we describe a strategy of using multimodal analysis for automatic parsing sports video. The paper first defines the basic structure of sports video database system, and then introduces a new approach that integrates visual stream analysis, speech recognition, speech signal processing and text extraction to realize video retrieval. The experimental results for TV sports video of football games indicate that the multimodal analysis is effective for video retrieval by quickly browsing tree-like video clips or inputting keywords within predefined domain.

Making a Library Catalog Adaptive.

ERIC Educational Resources Information Center

Buckland, Michael K.; And Others

1992-01-01

Describes the design of a prototype adaptive online catalog that was implemented as a transparent workstation-based front end system to MELVYL, the online catalog for the University of California libraries. Problems with searching bibliographic retrieval systems are reviewed, including irrelevant retrievals and the inexperience of most users.…

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

PubMed

Jurling, Alden S; Fienup, James R

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

The MiPACQ clinical question answering system.

PubMed

Cairns, Brian L; Nielsen, Rodney D; Masanz, James J; Martin, James H; Palmer, Martha S; Ward, Wayne H; Savova, Guergana K

2011-01-01

The Multi-source Integrated Platform for Answering Clinical Questions (MiPACQ) is a QA pipeline that integrates a variety of information retrieval and natural language processing systems into an extensible question answering system. We present the system's architecture and an evaluation of MiPACQ on a human-annotated evaluation dataset based on the Medpedia health and medical encyclopedia. Compared with our baseline information retrieval system, the MiPACQ rule-based system demonstrates 84% improvement in Precision at One and the MiPACQ machine-learning-based system demonstrates 134% improvement. Other performance metrics including mean reciprocal rank and area under the precision/recall curves also showed significant improvement, validating the effectiveness of the MiPACQ design and implementation.

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

ERIC Educational Resources Information Center

Hert, Carol A.; Nilan, Michael S.

1991-01-01

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

Gridded Model Information Support System (GMISS) user's guide. Volume 3. Model-concentration data-retrieval subsystem

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

Not Available

The Gridded Model Information Support System (GMISS) is a data base management system for selected Regional Oxidant Model (ROM) input data and species concentrations produced by gridded photochemical air pollution models. The Model Concentration Data Retrieval Subsystem allows State and local air pollution control agencies to retrieve these hourly data for use in support of their regulatory programs. These hourly data may be used to calculate initial and boundary conditions for the Empirical Kinetics Modeling Approach (EKMA). They may be used for other modeling application needs as well as to support evaluation of regional emission controls strategies. Both temporal andmore » spatial subsets of the data may be retrieved. The document describes how to invoke and execute the Model Concentration Data Retrieval Subsystem using the full screen menus.« less

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

ERIC Educational Resources Information Center

Egghe, L.; Michel, Christine

2002-01-01

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

WWW Entrez: A Hypertext Retrieval Tool for Molecular Biology.

ERIC Educational Resources Information Center

Epstein, Jonathan A.; Kans, Jonathan A.; Schuler, Gregory D.

This article describes the World Wide Web (WWW) Entrez server which is based upon the National Center for Biotechnology Information's (NCBI) Entrez retrieval database and software. Entrez is a molecular sequence retrieval system that contains an integrated view of portions of Medline and all publicly available nucleotide and protein databases,…

Coastal and Marine Bird Data Base

USGS Publications Warehouse

Anderson, S.H.; Geissler, P.H.; Dawson, D.K.

1980-01-01

Summary: This report discusses the development of a coastal and marine bird data base at the Migratory Bird and Habitat Research Laboratory. The system is compared with other data bases, and suggestions for future development, such as possible adaptations for other taxonomic groups, are included. The data base is based on the Statistical Analysis System but includes extensions programmed in PL/I. The Appendix shows how the system evolved. Output examples are given for heron data and pelagic bird data which indicate the types of analyses that can be conducted and output figures. The Appendixes include a retrieval language user's guide and description of the retrieval process and listing of translator program.

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows.

PubMed

Depeursinge, Adrien; Vargas, Alejandro; Gaillard, Frédéric; Platon, Alexandra; Geissbuhler, Antoine; Poletti, Pierre-Alexandre; Müller, Henning

2012-01-01

Clinical workflows and user interfaces of image-based computer-aided diagnosis (CAD) for interstitial lung diseases in high-resolution computed tomography are introduced and discussed. Three use cases are implemented to assist students, radiologists, and physicians in the diagnosis workup of interstitial lung diseases. In a first step, the proposed system shows a three-dimensional map of categorized lung tissue patterns with quantification of the diseases based on texture analysis of the lung parenchyma. Then, based on the proportions of abnormal and normal lung tissue as well as clinical data of the patients, retrieval of similar cases is enabled using a multimodal distance aggregating content-based image retrieval (CBIR) and text-based information search. The global system leads to a hybrid detection-CBIR-based CAD, where detection-based and CBIR-based CAD show to be complementary both on the user's side and on the algorithmic side. The proposed approach is in accordance with the classical workflow of clinicians searching for similar cases in textbooks and personal collections. The developed system enables objective and customizable inter-case similarity assessment, and the performance measures obtained with a leave-one-patient-out cross-validation (LOPO CV) are representative of a clinical usage of the system.

Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

PubMed

G Seco de Herrera, Alba; Schaer, Roger; Markonis, Dimitrios; Müller, Henning

2015-01-01

Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches. This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task. Copyright © 2014 Elsevier Ltd. All rights reserved.

An intelligent, free-flying robot

NASA Technical Reports Server (NTRS)

Reuter, G. J.; Hess, C. W.; Rhoades, D. E.; Mcfadin, L. W.; Healey, K. J.; Erickson, J. D.

1988-01-01

The ground-based demonstration of EVA Retriever, a voice-supervised, intelligent, free-flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The major objective of the EVA Retriever Project is to design, develop, and evaluate an integrated robotic hardware and on-board software system which autonomously: (1) performs system activation and check-out, (2) searches for and acquires the target, (3) plans and executes a rendezvous while continuously tracking the target, (4) avoids stationary and moving obstacles, (5) reaches for and grapples the target, (6) returns to transfer the object, and (7) returns to base.

An intelligent, free-flying robot

NASA Technical Reports Server (NTRS)

Reuter, G. J.; Hess, C. W.; Rhoades, D. E.; Mcfadin, L. W.; Healey, K. J.; Erickson, J. D.; Phinney, Dale E.

1989-01-01

The ground based demonstration of the extensive extravehicular activity (EVA) Retriever, a voice-supervised, intelligent, free flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The major objective of the EVA Retriever Project is to design, develop, and evaluate an integrated robotic hardware and on-board software system which autonomously: (1) performs system activation and check-out; (2) searches for and acquires the target; (3) plans and executes a rendezvous while continuously tracking the target; (4) avoids stationary and moving obstacles; (5) reaches for and grapples the target; (6) returns to transfer the object; and (7) returns to base.

The SUNY biomedical communication network: six years of progress in on-line bibiographic retrieval.

PubMed Central

Egeland, J

1975-01-01

The SUNY Biomedical Communication Network became operational in 1968 as the first on-line bibliograhpic retrieval service for biomedical literature. Since 1968, the SUNY/BCN has grown in size from nine to thirty-two medical and university libraries and has expanded its data base coverage to include the ERIC and Psychological Abstracts data bases in addition to the full ten-year retrospective MEDLARS data base. Aside from the continuous provision of an on-line searching system, the SUNY experience over the last six years has yielded valuable information in the following areas of: (1) monograph indexing and retrieval, (2) shared cataloging, (3) user interaction and education in on-line systems, and (4) member participation in Network policy-making processes. The continued success of the SUNY/BCN is evidence that it is possible to provide a high quality on-line bibliographic retrieval system at cost to academic institutions. SUNY's success in this effort is the result of centralized resource sharing and effective regional networking, combined with thoughtful planning by user advisory committees. PMID:1173557

INFORMATION RETRIEVAL EXPERIMENT. FINAL REPORT.

ERIC Educational Resources Information Center

SELYE, HANS

THIS REPORT IS A BRIEF REVIEW OF RESULTS OF AN EXPERIMENT TO DETERMINE THE INFORMATION RETRIEVAL EFFICIENCY OF A MANUAL SPECIALIZED INFORMATION SYSTEM BASED ON 700,000 DOCUMENTS IN THE FIELDS OF ENDOCRINOLOGY, STRESS, MAST CELLS, AND ANAPHYLACTOID REACTIONS. THE SYSTEM RECEIVES 30,000 PUBLICATIONS ANNUALLY. DETAILED INFORMATION IS REPRESENTED BY…

On Inference Rules of Logic-Based Information Retrieval Systems.

ERIC Educational Resources Information Center

Chen, Patrick Shicheng

1994-01-01

Discussion of relevance and the needs of the users in information retrieval focuses on a deductive object-oriented approach and suggests eight inference rules for the deduction. Highlights include characteristics of a deductive object-oriented system, database and data modeling language, implementation, and user interface. (Contains 24…

Retrieval techniques and graphics displays using a computerized stellar data base

NASA Technical Reports Server (NTRS)

Mead, J.; Nagy, T. A.

1977-01-01

The paper describes a stellar data retrieval system for which the data base consists of 28 machine-readable astronomical catalogs. Eleven of these catalogs have been combined into the Goddard Cross Index (GCI), which serves as the computer entry point to these catalogs. The full data entry from any of the GCI catalogs can be retrieved in a single computer run. With this system, it is possible to prepare candidates for observation by searching the data base for stars with given characteristics. Generation of plots of all catalog stars in or near the telescope's field of view to scale of Palomar, other atlases, or to the telescope itself for use as observing charts or to aid in identifying unknown sources, can be accomplished.

Hydrology of lakes in the Minneapolis-Saint Paul Metropolitan Area: A summary of available dat

USGS Publications Warehouse

McBride, Mark S.

1976-01-01

SYSTEM 2000, a generalized computer data-base management system, was used to organize the data and prepare the tables. SYSTEM 2000 provides powerful capabilities for future retrieval and analyses of the data. The data base is available to potential users so that questions not implicitly anticipated in the preparation of the published tables can be answered readily, and the user can retrieve data in tabular or other forms to meet his particular needs.

RIPS: a UNIX-based reference information program for scientists.

PubMed

Klyce, S D; Rózsa, A J

1983-09-01

A set of programs is described which implement a personal reference management and information retrieval system on a UNIX-based minicomputer. The system operates in a multiuser configuration with a host of user-friendly utilities that assist entry of reference material, its retrieval, and formatted printing for associated tasks. A search command language was developed without restriction in keyword vocabulary, number of keywords, or level of parenthetical expression nesting. The system is readily transported, and by design is applicable to any academic specialty.

Implementation of system intelligence in a 3-tier telemedicine/PACS hierarchical storage management system

NASA Astrophysics Data System (ADS)

Chao, Woodrew; Ho, Bruce K. T.; Chao, John T.; Sadri, Reza M.; Huang, Lu J.; Taira, Ricky K.

1995-05-01

Our tele-medicine/PACS archive system is based on a three-tier distributed hierarchical architecture, including magnetic disk farms, optical jukebox, and tape jukebox sub-systems. The hierarchical storage management (HSM) architecture, built around a low cost high performance platform [personal computers (PC) and Microsoft Windows NT], presents a very scaleable and distributed solution ideal for meeting the needs of client/server environments such as tele-medicine, tele-radiology, and PACS. These image based systems typically require storage capacities mirroring those of film based technology (multi-terabyte with 10+ years storage) and patient data retrieval times at near on-line performance as demanded by radiologists. With the scaleable architecture, storage requirements can be easily configured to meet the needs of the small clinic (multi-gigabyte) to those of a major hospital (multi-terabyte). The patient data retrieval performance requirement was achieved by employing system intelligence to manage migration and caching of archived data. Relevant information from HIS/RIS triggers prefetching of data whenever possible based on simple rules. System intelligence embedded in the migration manger allows the clustering of patient data onto a single tape during data migration from optical to tape medium. Clustering of patient data on the same tape eliminates multiple tape loading and associated seek time during patient data retrieval. Optimal tape performance can then be achieved by utilizing the tape drives high performance data streaming capabilities thereby reducing typical data retrieval delays associated with streaming tape devices.

Words, concepts, or both: optimal indexing units for automated information retrieval.

PubMed Central

Hersh, W. R.; Hickam, D. H.; Leone, T. J.

1992-01-01

What is the best way to represent the content of documents in an information retrieval system? This study compares the retrieval effectiveness of five different methods for automated (machine-assigned) indexing using three test collections. The consistently best methods are those that use indexing based on the words that occur in the available text of each document. Methods used to map text into concepts from a controlled vocabulary showed no advantage over the word-based methods. This study also looked at an approach to relevance feedback which showed benefit for both word-based and concept-based methods. PMID:1482951

The MiPACQ Clinical Question Answering System

PubMed Central

Cairns, Brian L.; Nielsen, Rodney D.; Masanz, James J.; Martin, James H.; Palmer, Martha S.; Ward, Wayne H.; Savova, Guergana K.

2011-01-01

The Multi-source Integrated Platform for Answering Clinical Questions (MiPACQ) is a QA pipeline that integrates a variety of information retrieval and natural language processing systems into an extensible question answering system. We present the system’s architecture and an evaluation of MiPACQ on a human-annotated evaluation dataset based on the Medpedia health and medical encyclopedia. Compared with our baseline information retrieval system, the MiPACQ rule-based system demonstrates 84% improvement in Precision at One and the MiPACQ machine-learning-based system demonstrates 134% improvement. Other performance metrics including mean reciprocal rank and area under the precision/recall curves also showed significant improvement, validating the effectiveness of the MiPACQ design and implementation. PMID:22195068

Strategic Help in User Interfaces for Information Retrieval.

ERIC Educational Resources Information Center

Brajnik, Giorgio; Mizzaro, Stefano; Tasso, Carlo; Venuti, Fabio

2002-01-01

Discussion of search strategy in information retrieval by end users focuses on the role played by strategic reasoning and design principles for user interfaces. Highlights include strategic help based on collaborative coaching; a conceptual model for strategic help; and a prototype knowledge-based system named FIRE. (Author/LRW)

A probabilistic Sperner's theorem, with applications to the problem of retrieving information from a data base

NASA Technical Reports Server (NTRS)

Baumert, L. D.; Mceliece, R. J.; Rodemich, E. R.; Rumsey, H., Jr.

1978-01-01

The design of an optimal merged keycode data base information retrieval system is detailed. A probability distribution of n-bit binary words that minimized false drops was developed for the case where the set of desired records was a subset of tagged records.

Information Retrieval Using UMLS-based Structured Queries

PubMed Central

Fagan, Lawrence M.; Berrios, Daniel C.; Chan, Albert; Cucina, Russell; Datta, Anupam; Shah, Maulik; Surendran, Sujith

2001-01-01

During the last three years, we have developed and described components of ELBook, a semantically based information-retrieval system [1-4]. Using these components, domain experts can specify a query model, indexers can use the query model to index documents, and end-users can search these documents for instances of indexed queries.

Requirements for benchmarking personal image retrieval systems

NASA Astrophysics Data System (ADS)

Bouguet, Jean-Yves; Dulong, Carole; Kozintsev, Igor; Wu, Yi

2006-01-01

It is now common to have accumulated tens of thousands of personal ictures. Efficient access to that many pictures can only be done with a robust image retrieval system. This application is of high interest to Intel processor architects. It is highly compute intensive, and could motivate end users to upgrade their personal computers to the next generations of processors. A key question is how to assess the robustness of a personal image retrieval system. Personal image databases are very different from digital libraries that have been used by many Content Based Image Retrieval Systems.1 For example a personal image database has a lot of pictures of people, but a small set of different people typically family, relatives, and friends. Pictures are taken in a limited set of places like home, work, school, and vacation destination. The most frequent queries are searched for people, and for places. These attributes, and many others affect how a personal image retrieval system should be benchmarked, and benchmarks need to be different from existing ones based on art images, or medical images for examples. The attributes of the data set do not change the list of components needed for the benchmarking of such systems as specified in2: - data sets - query tasks - ground truth - evaluation measures - benchmarking events. This paper proposed a way to build these components to be representative of personal image databases, and of the corresponding usage models.

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

PubMed

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

2018-05-01

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

Data management system for USGS/USEPA urban hydrology studies program

USGS Publications Warehouse

Doyle, W.H.; Lorens, J.A.

1982-01-01

A data management system was developed to store, update, and retrieve data collected in urban stormwater studies jointly conducted by the U.S. Geological Survey and U.S. Environmental Protection Agency in 11 cities in the United States. The data management system is used to retrieve and combine data from USGS data files for use in rainfall, runoff, and water-quality models and for data computations such as storm loads. The system is based on the data management aspect of the Statistical Analysis System (SAS) and was used to create all the data files in the data base. SAS is used for storage and retrieval of basin physiography, land-use, and environmental practices inventory data. Also, storm-event water-quality characteristics are stored in the data base. The advantages of using SAS to create and manage a data base are many with a few being that it is simple, easy to use, contains a comprehensive statistical package, and can be used to modify files very easily. Data base system development has progressed rapidly during the last two decades and the data managment system concepts used in this study reflect the advancement made in computer technology during this era. Urban stormwater data is, however, just one application for which the system can be used. (USGS)

Natural texture retrieval based on perceptual similarity measurement

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Modelling Subjectivity in Visual Perception of Orientation for Image Retrieval.

ERIC Educational Resources Information Center

Sanchez, D.; Chamorro-Martinez, J.; Vila, M. A.

2003-01-01

Discussion of multimedia libraries and the need for storage, indexing, and retrieval techniques focuses on the combination of computer vision and data mining techniques to model high-level concepts for image retrieval based on perceptual features of the human visual system. Uses fuzzy set theory to measure users' assessments and to capture users'…

Web information retrieval based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Jian

2013-03-01

The purpose of the Information Retrieval (IR) is to find a set of documents that are relevant for a specific information need of a user. Traditional Information Retrieval model commonly used in commercial search engine is based on keyword indexing system and Boolean logic queries. One big drawback of traditional information retrieval is that they typically retrieve information without an explicitly defined domain of interest to the users so that a lot of no relevance information returns to users, which burden the user to pick up useful answer from these no relevance results. In order to tackle this issue, many semantic web information retrieval models have been proposed recently. The main advantage of Semantic Web is to enhance search mechanisms with the use of Ontology's mechanisms. In this paper, we present our approach to personalize web search engine based on ontology. In addition, key techniques are also discussed in our paper. Compared to previous research, our works concentrate on the semantic similarity and the whole process including query submission and information annotation.

Design of a lattice-based faceted classification system

NASA Technical Reports Server (NTRS)

Eichmann, David A.; Atkins, John

1992-01-01

We describe a software reuse architecture supporting component retrieval by facet classes. The facets are organized into a lattice of facet sets and facet n-tuples. The query mechanism supports precise retrieval and flexible browsing.

Evaluation of the Caravelle litter retrieval system.

DOT National Transportation Integrated Search

1988-01-01

Based on observations, the Caravelle Litter Technologies, Inc's., demonstration of its litter retrieval equipment it was concluded that use of the equipment on highways open to traffic would require extensive and expensive traffic control. The machin...

Implementing and Evaluating a Bibliographic Retrieval System for Print and Non-Print Media Materials.

ERIC Educational Resources Information Center

Buchholz, James L.

This document summarizes the selection, configuration, implementation, and evaluation of BiblioFile, a CD-ROM based bibliographic retrieval system used to catalog and process library materials for 103 school centers in the Palm Beach County Schools (Florida). Technical processing included the production of spine labels, check-out cards and…

Retrieval of the 1964 Laser Literature Using MIT's Project Tip.

ERIC Educational Resources Information Center

Keenan, Stella; Terry, Edward

Reported are the performance characteristics of the Massachusetts Institute of Technology Technical Information Program (TIP) system based on a study involving three search strategies in retrieval o f laser articles published in 1964. The TIP system provides access to (1) title, (2) author(s), (3) bibliographic references, and (4) literature…

Computer-Assisted Search Of Large Textual Data Bases

NASA Technical Reports Server (NTRS)

Driscoll, James R.

1995-01-01

"QA" denotes high-speed computer system for searching diverse collections of documents including (but not limited to) technical reference manuals, legal documents, medical documents, news releases, and patents. Incorporates previously available and emerging information-retrieval technology to help user intelligently and rapidly locate information found in large textual data bases. Technology includes provision for inquiries in natural language; statistical ranking of retrieved information; artificial-intelligence implementation of semantics, in which "surface level" knowledge found in text used to improve ranking of retrieved information; and relevance feedback, in which user's judgements of relevance of some retrieved documents used automatically to modify search for further information.

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

PubMed Central

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

1999-01-01

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

Room Temperature Memory for Few Photon Polarization Qubits

NASA Astrophysics Data System (ADS)

Kupchak, Connor; Mittiga, Thomas; Jordan, Bertus; Nazami, Mehdi; Nolleke, Christian; Figueroa, Eden

2014-05-01

We have developed a room temperature quantum memory device based on Electromagnetically Induced Transparency capable of reliably storing and retrieving polarization qubits on the few photon level. Our system is realized in a vapor of 87Rb atoms utilizing a Λ-type energy level scheme. We create a dual-rail storage scheme mediated by an intense control field to allow storage and retrieval of any arbitrary polarization state. Upon retrieval, we employ a filtering system to sufficiently remove the strong pump field, and subject retrieved light states to polarization tomography. To date, our system has produced signal-to-noise ratios near unity with a memory fidelity of >80 % using coherent state qubits containing four photons on average. Our results thus demonstrate the feasibility of room temperature systems for the storage of single-photon-level photonic qubits. Such room temperature systems will be attractive for future long distance quantum communication schemes.

Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

PubMed

Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

2014-02-01

Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

Information Retrieval Strategies of Millennial Undergraduate Students in Web and Library Database Searches

ERIC Educational Resources Information Center

Porter, Brandi

2009-01-01

Millennial students make up a large portion of undergraduate students attending colleges and universities, and they have a variety of online resources available to them to complete academically related information searches, primarily Web based and library-based online information retrieval systems. The content, ease of use, and required search…

Interactive classification and content-based retrieval of tissue images

NASA Astrophysics Data System (ADS)

Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

2002-11-01

We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

Case-based retrieval framework for gene expression data.

PubMed

Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R; Braytee, Ali; Kennedy, Paul J

2015-01-01

The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process. This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.

Medical Image Retrieval: A Multimodal Approach

PubMed Central

Cao, Yu; Steffey, Shawn; He, Jianbiao; Xiao, Degui; Tao, Cui; Chen, Ping; Müller, Henning

2014-01-01

Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical practice and research. While substantial progress has been made in different areas of content-based image retrieval (CBIR) research, direct applications of existing CBIR techniques to the medical images produced unsatisfactory results, because of the unique characteristics of medical images. In this paper, we develop a new multimodal medical image retrieval approach based on the recent advances in the statistical graphic model and deep learning. Specifically, we first investigate a new extended probabilistic Latent Semantic Analysis model to integrate the visual and textual information from medical images to bridge the semantic gap. We then develop a new deep Boltzmann machine-based multimodal learning model to learn the joint density model from multimodal information in order to derive the missing modality. Experimental results with large volume of real-world medical images have shown that our new approach is a promising solution for the next-generation medical imaging indexing and retrieval system. PMID:26309389

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

PubMed

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

2014-03-01

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

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

PubMed

Kagolovsky, Y; Möhr, J R

2001-01-01

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

AOIPS data base management systems support for GARP data sets

NASA Technical Reports Server (NTRS)

Gary, J. P.

1977-01-01

A data base management system is identified, developed to provide flexible access to data sets produced by GARP during its data systems tests. The content and coverage of the data base are defined and a computer-aided, interactive information storage and retrieval system, implemented to facilitate access to user specified data subsets, is described. The computer programs developed to provide the capability were implemented on the highly interactive, minicomputer-based AOIPS and are referred to as the data retrieval system (DRS). Implemented as a user interactive but menu guided system, the DRS permits users to inventory the data tape library and create duplicate or subset data sets based on a user selected window defined by time and latitude/longitude boundaries. The DRS permits users to select, display, or produce formatted hard copy of individual data items contained within the data records.

Managing biomedical image metadata for search and retrieval of similar images.

PubMed

Korenblum, Daniel; Rubin, Daniel; Napel, Sandy; Rodriguez, Cesar; Beaulieu, Chris

2011-08-01

Radiology images are generally disconnected from the metadata describing their contents, such as imaging observations ("semantic" metadata), which are usually described in text reports that are not directly linked to the images. We developed a system, the Biomedical Image Metadata Manager (BIMM) to (1) address the problem of managing biomedical image metadata and (2) facilitate the retrieval of similar images using semantic feature metadata. Our approach allows radiologists, researchers, and students to take advantage of the vast and growing repositories of medical image data by explicitly linking images to their associated metadata in a relational database that is globally accessible through a Web application. BIMM receives input in the form of standard-based metadata files using Web service and parses and stores the metadata in a relational database allowing efficient data query and maintenance capabilities. Upon querying BIMM for images, 2D regions of interest (ROIs) stored as metadata are automatically rendered onto preview images included in search results. The system's "match observations" function retrieves images with similar ROIs based on specific semantic features describing imaging observation characteristics (IOCs). We demonstrate that the system, using IOCs alone, can accurately retrieve images with diagnoses matching the query images, and we evaluate its performance on a set of annotated liver lesion images. BIMM has several potential applications, e.g., computer-aided detection and diagnosis, content-based image retrieval, automating medical analysis protocols, and gathering population statistics like disease prevalences. The system provides a framework for decision support systems, potentially improving their diagnostic accuracy and selection of appropriate therapies.

Content-based image retrieval from a database of fracture images

NASA Astrophysics Data System (ADS)

Müller, Henning; Do Hoang, Phuong Anh; Depeursinge, Adrien; Hoffmeyer, Pierre; Stern, Richard; Lovis, Christian; Geissbuhler, Antoine

2007-03-01

This article describes the use of a medical image retrieval system on a database of 16'000 fractures, selected from surgical routine over several years. Image retrieval has been a very active domain of research for several years. It was frequently proposed for the medical domain, but only few running systems were ever tested in clinical routine. For the planning of surgical interventions after fractures, x-ray images play an important role. The fractures are classified according to exact fracture location, plus whether and to which degree the fracture is damaging articulations to see how complicated a reparation will be. Several classification systems for fractures exist and the classification plus the experience of the surgeon lead in the end to the choice of surgical technique (screw, metal plate, ...). This choice is strongly influenced by the experience and knowledge of the surgeons with respect to a certain technique. Goal of this article is to describe a prototype that supplies similar cases to an example to help treatment planning and find the most appropriate technique for a surgical intervention. Our database contains over 16'000 fracture images before and after a surgical intervention. We use an image retrieval system (GNU Image Finding Tool, GIFT) to find cases/images similar to an example case currently under observation. Problems encountered are varying illumination of images as well as strong anatomic differences between patients. Regions of interest are usually small and the retrieval system needs to focus on this region. Results show that GIFT is capable of supplying similar cases, particularly when using relevance feedback, on such a large database. Usual image retrieval is based on a single image as search target but for this application we have to select images by case as similar cases need to be found and not images. A few false positive cases often remain in the results but they can be sorted out quickly by the surgeons. Image retrieval can well be used for the planning of operations by supplying similar cases. A variety of challenges has been identified and partly solved (varying luminosity, small region of interested, case-based instead of image-based). This article mainly presents a case study to identify potential benefits and problems. Several steps for improving the system have been identified as well and will be described at the end of the paper.

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

PubMed

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

NASA Technical Reports Server (NTRS)

Taylor, Jaime; Rakoczy, John; Steincamp, James

2003-01-01

Phase retrieval requires calculation of the real-valued phase of the pupil fimction from the image intensity distribution and characteristics of an optical system. Genetic 'algorithms were used to solve two one-dimensional phase retrieval problem. A GA successfully estimated the coefficients of a polynomial expansion of the phase when the number of coefficients was correctly specified. A GA also successfully estimated the multiple p h e s of a segmented optical system analogous to the seven-mirror Systematic Image-Based Optical Alignment (SIBOA) testbed located at NASA s Marshall Space Flight Center. The SIBOA testbed was developed to investigate phase retrieval techniques. Tiphilt and piston motions of the mirrors accomplish phase corrections. A constant phase over each mirror can be achieved by an independent tip/tilt correction: the phase Conection term can then be factored out of the Discrete Fourier Tranform (DFT), greatly reducing computations.

Developing a comprehensive system for content-based retrieval of image and text data from a national survey

NASA Astrophysics Data System (ADS)

Antani, Sameer K.; Natarajan, Mukil; Long, Jonathan L.; Long, L. Rodney; Thoma, George R.

2005-04-01

The article describes the status of our ongoing R&D at the U.S. National Library of Medicine (NLM) towards the development of an advanced multimedia database biomedical information system that supports content-based image retrieval (CBIR). NLM maintains a collection of 17,000 digitized spinal X-rays along with text survey data from the Second National Health and Nutritional Examination Survey (NHANES II). These data serve as a rich data source for epidemiologists and researchers of osteoarthritis and musculoskeletal diseases. It is currently possible to access these through text keyword queries using our Web-based Medical Information Retrieval System (WebMIRS). CBIR methods developed specifically for biomedical images could offer direct visual searching of these images by means of example image or user sketch. We are building a system which supports hybrid queries that have text and image-content components. R&D goals include developing algorithms for robust image segmentation for localizing and identifying relevant anatomy, labeling the segmented anatomy based on its pathology, developing suitable indexing and similarity matching methods for images and image features, and associating the survey text information for query and retrieval along with the image data. Some highlights of the system developed in MATLAB and Java are: use of a networked or local centralized database for text and image data; flexibility to incorporate new research work; provides a means to control access to system components under development; and use of XML for structured reporting. The article details the design, features, and algorithms in this third revision of this prototype system, CBIR3.

The design of PC/MISI, a PC-based common user interface to remote information storage and retrieval systems. Presentation visuals. M.S. Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Hall, Philip P.

1985-01-01

This Working Paper Series entry represents a collection of presentation visuals associated with the companion report entitled, The Design of PC/MISI, a PC-Based Common User Interface to Remote Information Storage and Retrieval Systems, USL/DBMS NASA/RECON Working Paper Series report number DBMS.NASA/RECON-15. The paper discusses the following: problem definition; the PC solution; the goals of system design; the design description; future considerations, the research environment; conclusions.

Estimation of Microphysical and Radiative Parameters of Precipitating Cloud Systems Using mm-Wavelength Radars

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.

2009-03-01

A remote sensing approach is described to retrieve cloud and rainfall parameters within the same precipitating system. This approach is based on mm-wavelength radar signal attenuation effects which are observed in a layer of liquid precipitation containing clouds and rainfall. The parameters of ice clouds in the upper part of startiform precipitating systems are then retrieved using the absolute measurements of radar reflectivity. In case of the ground-based radar location, these measurements are corrected for attenuation in the intervening layer of liquid hydrometers.

Monitoring and Modeling Crop Health and Water Use via in-situ, Airborne and Space-based Platforms

NASA Astrophysics Data System (ADS)

McCabe, M. F.

2014-12-01

The accurate retrieval of plant water use, health and function together with soil state and condition, represent key objectives in the management and monitoring of large-scale agricultural production. In regions of water shortage or stress, understanding the sustainable use of available water supplies is critical. Unfortunately, this need is all too often limited by a lack of reliable observations. Techniques that balance the demand for reliable ground-based data with the rapid retrieval of spatially distributed crop characteristics represent a needed line of research. Data from in-situ monitoring coupled with advances in satellite retrievals of key land surface variables, provide the information necessary to characterize many crop health and water use features, including evaporation, leaf-chlorophyll and other common vegetation indices. With developments in UAV and quadcopter solutions, the opportunity to bridge the spatio-temporal gap between satellite and ground based sensing now exists, along with the capacity for customized retrievals of crop information. While there remain challenges in the routine application of autonomous airborne systems, the state of current technology and sensor developments provide the capacity to explore the operational potential. While this presentation will focus on the multi-scale estimation of crop-water use and crop-health characteristics from satellite-based sensors, the retrieval of high resolution spatially distributed information from near-surface airborne and ground-based systems will also be examined.

Recent Progress on the Second Generation CMORPH: A Prototype Operational Processing System

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert; Wu, Shaorong

2016-04-01

As reported at the EGU General Assembly of 2015, a conceptual test system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05deg lat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include both rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Sub-systems were developed and refined to derive precipitation estimates from the GEO and LEO IR observations and to compute precipitating cloud motion vectors. The results were reported at the EGU of 2014 and the AGU 2015 Fall Meetings. In this presentation, we report our recent work on the construction of a prototype operational processing system for the second generation CMORPH. The second generation CMORPH prototype operational processing system takes in the passive microwave (PMW) retrievals of instantaneous precipitation rates from all available sensors, the full-resolution GEO and LEO IR data, as well as the hourly precipitation fields generated by the NOAA/NCEP Climate Forecast System (CFS) Reanalysis (CFS). First, a combined field of PMW based precipitation retrievals (MWCOMB) is created on a 0.05deg lat/lon grid over the entire globe through inter-calibrating retrievals from various sensors against a common reference. For this experiment, the reference field is the GMI based retrievals with climatological adjustment against the TMI retrievals using data over the overlapping period. Precipitation estimation is then derived from the GEO and LEO IR data through calibration against the global MWCOMB and the CloudSat CPR based estimates. At the meantime, precipitating cloud motion vectors are derived through the combination of vectors computed from the GEO IR based precipitation estimates and the CFSR precipitation with a 2DVAR technique. A prototype system is applied to generate integrated global precipitation estimates over the entire globe for a three-month period from June 1 to August 31 of 2015. Preliminary tests are conducted to optimize the performance of the system. Specific efforts are made to improve the computational efficiency of the system. The second generation CMORPH test products are compared to the first generation CMORPH and ground observations. Detailed results will be reported at the EGU.

Technology for an intelligent, free-flying robot for crew and equipment retrieval in space

NASA Technical Reports Server (NTRS)

Erickson, J. D.; Reuter, G. J.; Healey, Kathleen J.; Phinney, D. E.

1990-01-01

Crew rescue and equipment retrieval is a Space Station Freedom requirement. During Freedom's lifetime, there is a high probability that a number of objects will accidently become separated. Members of the crew, replacement units, and key tools are examples. Retrieval of these objects within a short time is essential. Systems engineering studies were conducted to identify system requirements and candidate approaches. One such approach, based on a voice-supervised, intelligent, free-flying robot was selected for further analysis. A ground-based technology demonstration, now in its second phase, was designed to provide an integrated robotic hardware and software testbed supporting design of a space-borne system. The ground system, known as the EVA Retriever, is examining the problem of autonomously planning and executing a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles. The current prototype is an anthropomorphic manipulator unit with dexterous arms and hands attached to a robot body and latched in a manned maneuvering unit. A precision air-bearing floor is used to simulate space. Sensor data include two vision systems and force/proximity/tactile sensors on the hands and arms. Planning for a shuttle file experiment is underway. A set of scenarios and strawman requirements were defined to support conceptual development. Initial design activities are expected to begin in late 1989 with the flight occurring in 1994. The flight hardware and software will be based on lessons learned from both the ground prototype and computer simulations.

Intelligent distributed medical image management

NASA Astrophysics Data System (ADS)

Garcia, Hong-Mei C.; Yun, David Y.

1995-05-01

The rapid advancements in high performance global communication have accelerated cooperative image-based medical services to a new frontier. Traditional image-based medical services such as radiology and diagnostic consultation can now fully utilize multimedia technologies in order to provide novel services, including remote cooperative medical triage, distributed virtual simulation of operations, as well as cross-country collaborative medical research and training. Fast (efficient) and easy (flexible) retrieval of relevant images remains a critical requirement for the provision of remote medical services. This paper describes the database system requirements, identifies technological building blocks for meeting the requirements, and presents a system architecture for our target image database system, MISSION-DBS, which has been designed to fulfill the goals of Project MISSION (medical imaging support via satellite integrated optical network) -- an experimental high performance gigabit satellite communication network with access to remote supercomputing power, medical image databases, and 3D visualization capabilities in addition to medical expertise anywhere and anytime around the country. The MISSION-DBS design employs a synergistic fusion of techniques in distributed databases (DDB) and artificial intelligence (AI) for storing, migrating, accessing, and exploring images. The efficient storage and retrieval of voluminous image information is achieved by integrating DDB modeling and AI techniques for image processing while the flexible retrieval mechanisms are accomplished by combining attribute- based and content-based retrievals.

The SoRReL papers: Recent publications of the Software Reuse Repository Lab

NASA Technical Reports Server (NTRS)

Eichmann, David A. (Editor)

1992-01-01

The entire publication is presented of some of the papers recently published by the SoRReL. Some typical titles are as follows: Design of a Lattice-Based Faceted Classification System; A Hybrid Approach to Software Reuse Repository Retrieval; Selecting Reusable Components Using Algebraic Specifications; Neural Network-Based Retrieval from Reuse Repositories; and A Neural Net-Based Approach to Software Metrics.

Development of a web-based video management and application processing system

NASA Astrophysics Data System (ADS)

Chan, Shermann S.; Wu, Yi; Li, Qing; Zhuang, Yueting

2001-07-01

How to facilitate efficient video manipulation and access in a web-based environment is becoming a popular trend for video applications. In this paper, we present a web-oriented video management and application processing system, based on our previous work on multimedia database and content-based retrieval. In particular, we extend the VideoMAP architecture with specific web-oriented mechanisms, which include: (1) Concurrency control facilities for the editing of video data among different types of users, such as Video Administrator, Video Producer, Video Editor, and Video Query Client; different users are assigned various priority levels for different operations on the database. (2) Versatile video retrieval mechanism which employs a hybrid approach by integrating a query-based (database) mechanism with content- based retrieval (CBR) functions; its specific language (CAROL/ST with CBR) supports spatio-temporal semantics of video objects, and also offers an improved mechanism to describe visual content of videos by content-based analysis method. (3) Query profiling database which records the `histories' of various clients' query activities; such profiles can be used to provide the default query template when a similar query is encountered by the same kind of users. An experimental prototype system is being developed based on the existing VideoMAP prototype system, using Java and VC++ on the PC platform.

The Challenges Facing Science Data Archiving on Current Mass Storage Systems

NASA Technical Reports Server (NTRS)

Peavey, Bernard; Behnke, Jeanne (Editor)

1996-01-01

This paper discusses the desired characteristics of a tape-based petabyte science data archive and retrieval system required to store and distribute several terabytes (TB) of data per day over an extended period of time, probably more than 115 years, in support of programs such as the Earth Observing System Data and Information System (EOSDIS). These characteristics take into consideration not only cost effective and affordable storage capacity, but also rapid access to selected files, and reading rates that are needed to satisfy thousands of retrieval transactions per day. It seems that where rapid random access to files is not crucial, the tape medium, magnetic or optical, continues to offer cost effective data storage and retrieval solutions, and is likely to do so for many years to come. However, in environments like EOS these tape based archive solutions provide less than full user satisfaction. Therefore, the objective of this paper is to describe the performance and operational enhancements that need to be made to the current tape based archival systems in order to achieve greater acceptance by the EOS and similar user communities.

A data-management system for detailed areal interpretive data

USGS Publications Warehouse

Ferrigno, C.F.

1986-01-01

A data storage and retrieval system has been developed to organize and preserve areal interpretive data. This system can be used by any study where there is a need to store areal interpretive data that generally is presented in map form. This system provides the capability to grid areal interpretive data for input to groundwater flow models at any spacing and orientation. The data storage and retrieval system is designed to be used for studies that cover small areas such as counties. The system is built around a hierarchically structured data base consisting of related latitude-longitude blocks. The information in the data base can be stored at different levels of detail, with the finest detail being a block of 6 sec of latitude by 6 sec of longitude (approximately 0.01 sq mi). This system was implemented on a mainframe computer using a hierarchical data base management system. The computer programs are written in Fortran IV and PL/1. The design and capabilities of the data storage and retrieval system, and the computer programs that are used to implement the system are described. Supplemental sections contain the data dictionary, user documentation of the data-system software, changes that would need to be made to use this system for other studies, and information on the computer software tape. (Lantz-PTT)

Automated information retrieval using CLIPS

NASA Technical Reports Server (NTRS)

Raines, Rodney Doyle, III; Beug, James Lewis

1991-01-01

Expert systems have considerable potential to assist computer users in managing the large volume of information available to them. One possible use of an expert system is to model the information retrieval interests of a human user and then make recommendations to the user as to articles of interest. At Cal Poly, a prototype expert system written in the C Language Integrated Production System (CLIPS) serves as an Automated Information Retrieval System (AIRS). AIRS monitors a user's reading preferences, develops a profile of the user, and then evaluates items returned from the information base. When prompted by the user, AIRS returns a list of items of interest to the user. In order to minimize the impact on system resources, AIRS is designed to run in the background during periods of light system use.

Using the Weighted Keyword Model to Improve Information Retrieval for Answering Biomedical Questions

PubMed Central

Yu, Hong; Cao, Yong-gang

2009-01-01

Physicians ask many complex questions during the patient encounter. Information retrieval systems that can provide immediate and relevant answers to these questions can be invaluable aids to the practice of evidence-based medicine. In this study, we first automatically identify topic keywords from ad hoc clinical questions with a Condition Random Field model that is trained over thousands of manually annotated clinical questions. We then report on a linear model that assigns query weights based on their automatically identified semantic roles: topic keywords, domain specific terms, and their synonyms. Our evaluation shows that this weighted keyword model improves information retrieval from the Text Retrieval Conference Genomics track data. PMID:21347188

Using the weighted keyword model to improve information retrieval for answering biomedical questions.

PubMed

Yu, Hong; Cao, Yong-Gang

2009-03-01

Physicians ask many complex questions during the patient encounter. Information retrieval systems that can provide immediate and relevant answers to these questions can be invaluable aids to the practice of evidence-based medicine. In this study, we first automatically identify topic keywords from ad hoc clinical questions with a Condition Random Field model that is trained over thousands of manually annotated clinical questions. We then report on a linear model that assigns query weights based on their automatically identified semantic roles: topic keywords, domain specific terms, and their synonyms. Our evaluation shows that this weighted keyword model improves information retrieval from the Text Retrieval Conference Genomics track data.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

An intelligent framework for medical image retrieval using MDCT and multi SVM.

PubMed

Balan, J A Alex Rajju; Rajan, S Edward

2014-01-01

Volumes of medical images are rapidly generated in medical field and to manage them effectively has become a great challenge. This paper studies the development of innovative medical image retrieval based on texture features and accuracy. The objective of the paper is to analyze the image retrieval based on diagnosis of healthcare management systems. This paper traces the development of innovative medical image retrieval to estimate both the image texture features and accuracy. The texture features of medical images are extracted using MDCT and multi SVM. Both the theoretical approach and the simulation results revealed interesting observations and they were corroborated using MDCT coefficients and SVM methodology. All attempts to extract the data about the image in response to the query has been computed successfully and perfect image retrieval performance has been obtained. Experimental results on a database of 100 trademark medical images show that an integrated texture feature representation results in 98% of the images being retrieved using MDCT and multi SVM. Thus we have studied a multiclassification technique based on SVM which is prior suitable for medical images. The results show the retrieval accuracy of 98%, 99% for different sets of medical images with respect to the class of image.

Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

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

PubMed Central

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

2018-01-01

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

TRECVID: the utility of a content-based video retrieval evaluation

NASA Astrophysics Data System (ADS)

Hauptmann, Alexander G.

2006-01-01

TRECVID, an annual retrieval evaluation benchmark organized by NIST, encourages research in information retrieval from digital video. TRECVID benchmarking covers both interactive and manual searching by end users, as well as the benchmarking of some supporting technologies including shot boundary detection, extraction of semantic features, and the automatic segmentation of TV news broadcasts. Evaluations done in the context of the TRECVID benchmarks show that generally, speech transcripts and annotations provide the single most important clue for successful retrieval. However, automatically finding the individual images is still a tremendous and unsolved challenge. The evaluations repeatedly found that none of the multimedia analysis and retrieval techniques provide a significant benefit over retrieval using only textual information such as from automatic speech recognition transcripts or closed captions. In interactive systems, we do find significant differences among the top systems, indicating that interfaces can make a huge difference for effective video/image search. For interactive tasks efficient interfaces require few key clicks, but display large numbers of images for visual inspection by the user. The text search finds the right context region in the video in general, but to select specific relevant images we need good interfaces to easily browse the storyboard pictures. In general, TRECVID has motivated the video retrieval community to be honest about what we don't know how to do well (sometimes through painful failures), and has focused us to work on the actual task of video retrieval, as opposed to flashy demos based on technological capabilities.

Optical mass memory system (AMM-13). AMM-13 system segment specification

NASA Technical Reports Server (NTRS)

Bailey, G. A.

1980-01-01

The performance, design, development, and test requirements for an optical mass data storage and retrieval system prototype (AMM-13) are established. This system interfaces to other system segments of the NASA End-to-End Data System via the Data Base Management System segment and is designed to have a storage capacity of 10 to the 13th power bits (10 to the 12th power bits on line). The major functions of the system include control, input and output, recording of ingested data, fiche processing/replication and storage and retrieval.

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

PubMed Central

Liu, Changgeng; Thapa, Damber; Yao, Xincheng

2017-01-01

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

Development of a Graphics Based Automated Emergency Response System (AERS) for Rail Transit Systems

DOT National Transportation Integrated Search

1989-05-01

This report presents an overview of the second generation Automated Emergency Response System (AERS2). Developed to assist transit systems in responding effectively to emergency situations, AERS2 is a microcomputer-based information retrieval system ...

IMIRSEL: a secure music retrieval testing environment

NASA Astrophysics Data System (ADS)

Downie, John S.

2004-10-01

The Music Information Retrieval (MIR) and Music Digital Library (MDL) research communities have long noted the need for formal evaluation mechanisms. Issues concerning the unavailability of freely-available music materials have greatly hindered the creation of standardized test collections with which these communities could scientifically assess the strengths and weaknesses of their various music retrieval techniques. The International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) is being developed at the University of Illinois at Urbana-Champaign (UIUC) specifically to overcome this hindrance to the scientific evaluation of MIR/MDL systems. Together with its subsidiary Human Use of Music Information Retrieval Systems (HUMIRS) project, IMIRSEL will allow MIR/MDL researchers access to the standardized large-scale collection of copyright-sensitive music materials and standardized test queries being housed at UIUC's National Center for Supercomputing Applications (NCSA). Virtual Research Labs (VRL), based upon NCSA's Data-to-Knowledge (D2K) tool set, are being developed through which MIR/MDL researchers will interact with the music materials under a "trusted code" security model.

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

ERIC Educational Resources Information Center

Melton, Jessica S.

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

Using Kintsch's Discourse Comprehension Theory To Model the User's Coding of an Informative Message from an Enabling Information Retrieval System.

ERIC Educational Resources Information Center

Cole, Charles; Mandelblatt, Bertie

2000-01-01

Uses Kintsch's proposition-based construction-integration theory of discourse comprehension to detail the user coding operations that occur in each of the three subsystems (Perception, Comprehension, Application) in which users process an information retrieval systems (IRS) message. Describes an IRS device made up of two separate parts that enable…

Plastic modulation of episodic memory networks in the aging brain with cognitive decline.

PubMed

Bai, Feng; Yuan, Yonggui; Yu, Hui; Zhang, Zhijun

2016-07-15

Social-cognitive processing has been posited to underlie general functions such as episodic memory. Episodic memory impairment is a recognized hallmark of amnestic mild cognitive impairment (aMCI) who is at a high risk for dementia. Three canonical networks, self-referential processing, executive control processing and salience processing, have distinct roles in episodic memory retrieval processing. It remains unclear whether and how these sub-networks of the episodic memory retrieval system would be affected in aMCI. This task-state fMRI study constructed systems-level episodic memory retrieval sub-networks in 28 aMCI and 23 controls using two computational approaches: a multiple region-of-interest based approach and a voxel-level functional connectivity-based approach, respectively. These approaches produced the remarkably similar findings that the self-referential processing network made critical contributions to episodic memory retrieval in aMCI. More conspicuous alterations in self-referential processing of the episodic memory retrieval network were identified in aMCI. In order to complete a given episodic memory retrieval task, increases in cooperation between the self-referential processing network and other sub-networks were mobilized in aMCI. Self-referential processing mediate the cooperation of the episodic memory retrieval sub-networks as it may help to achieve neural plasticity and may contribute to the prevention and treatment of dementia. Copyright © 2016 Elsevier B.V. All rights reserved.

Signal Analysis of Automotive Engine Spark Ignition System using Case-Based Reasoning (CBR) and Case-based Maintenance (CBM)

NASA Astrophysics Data System (ADS)

Huang, H.; Vong, C. M.; Wong, P. K.

2010-05-01

With the development of modern technology, modern vehicles adopt electronic control system for injection and ignition. In traditional way, whenever there is any malfunctioning in an automotive engine, an automotive mechanic usually performs a diagnosis in the ignition system of the engine to check any exceptional symptoms. In this paper, we present a case-based reasoning (CBR) approach to help solve human diagnosis problem. Nevertheless, one drawback of CBR system is that the case library will be expanded gradually after repeatedly running the system, which may cause inaccuracy and longer time for the CBR retrieval. To tackle this problem, case-based maintenance (CBM) framework is employed so that the case library of the CBR system will be compressed by clustering to produce a set of representative cases. As a result, the performance (in retrieval accuracy and time) of the whole CBR system can be improved.

Qualification of a Null Lens Using Image-Based Phase Retrieval

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

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

PubMed

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

2018-01-01

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

DOAS-based total column ozone retrieval from Phaethon system

NASA Astrophysics Data System (ADS)

Gkertsi, F.; Bais, A. F.; Kouremeti, N.; Drosoglou, Th; Fountoulakis, I.; Fragkos, K.

2018-05-01

This study introduces the measurement of the total ozone column using Differential Optical Absorption Spectroscopy (DOAS) analysis of direct-sun spectra recorded by the Phaethon system. This methodology is based on the analysis of spectra relative to a reference spectrum that has been recorded by the same instrument. The slant column density of ozone associated with the reference spectrum is derived by Langley extrapolation. Total ozone data derived by Phaethon over two years in Thessaloniki are compared with those of a collocated, well-maintained and calibrated, Brewer spectrophotometer. When the retrieval of total ozone is based on the absorption cross sections of (Paur and Bass, 1984) at 228 K, Phaethon shows an average overestimation of 1.85 ± 1.86%. Taking into account the effect of the day-to-day variability of stratospheric temperature on total ozone derived by both systems, the bias is reduced to 0.94 ± 1.26%. The sensitivity of the total ozone retrieval to changes in temperature is larger for Phaethon than for Brewer.

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

PubMed

Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

2015-05-15

We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

An introduction to the Marshall information retrieval and display system

NASA Technical Reports Server (NTRS)

1974-01-01

An on-line terminal oriented data storage and retrieval system is presented which allows a user to extract and process information from stored data bases. The use of on-line terminals for extracting and displaying data from the data bases provides a fast and responsive method for obtaining needed information. The system consists of general purpose computer programs that provide the overall capabilities of the total system. The system can process any number of data files via a Dictionary (one for each file) which describes the data format to the system. New files may be added to the system at any time, and reprogramming is not required. Illustrations of the system are shown, and sample inquiries and responses are given.

A searching and reporting system for relational databases using a graph-based metadata representation.

PubMed

Hewitt, Robin; Gobbi, Alberto; Lee, Man-Ling

2005-01-01

Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.

Retrieving handwriting by combining word spotting and manifold ranking

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

Barriers to Retrieving Patient Information from Electronic Health Record Data: Failure Analysis from the TREC Medical Records Track

PubMed Central

Edinger, Tracy; Cohen, Aaron M.; Bedrick, Steven; Ambert, Kyle; Hersh, William

2012-01-01

Objective: Secondary use of electronic health record (EHR) data relies on the ability to retrieve accurate and complete information about desired patient populations. The Text Retrieval Conference (TREC) 2011 Medical Records Track was a challenge evaluation allowing comparison of systems and algorithms to retrieve patients eligible for clinical studies from a corpus of de-identified medical records, grouped by patient visit. Participants retrieved cohorts of patients relevant to 35 different clinical topics, and visits were judged for relevance to each topic. This study identified the most common barriers to identifying specific clinic populations in the test collection. Methods: Using the runs from track participants and judged visits, we analyzed the five non-relevant visits most often retrieved and the five relevant visits most often overlooked. Categories were developed iteratively to group the reasons for incorrect retrieval for each of the 35 topics. Results: Reasons fell into nine categories for non-relevant visits and five categories for relevant visits. Non-relevant visits were most often retrieved because they contained a non-relevant reference to the topic terms. Relevant visits were most often infrequently retrieved because they used a synonym for a topic term. Conclusions: This failure analysis provides insight into areas for future improvement in EHR-based retrieval with techniques such as more widespread and complete use of standardized terminology in retrieval and data entry systems. PMID:23304287

Barriers to retrieving patient information from electronic health record data: failure analysis from the TREC Medical Records Track.

PubMed

Edinger, Tracy; Cohen, Aaron M; Bedrick, Steven; Ambert, Kyle; Hersh, William

2012-01-01

Secondary use of electronic health record (EHR) data relies on the ability to retrieve accurate and complete information about desired patient populations. The Text Retrieval Conference (TREC) 2011 Medical Records Track was a challenge evaluation allowing comparison of systems and algorithms to retrieve patients eligible for clinical studies from a corpus of de-identified medical records, grouped by patient visit. Participants retrieved cohorts of patients relevant to 35 different clinical topics, and visits were judged for relevance to each topic. This study identified the most common barriers to identifying specific clinic populations in the test collection. Using the runs from track participants and judged visits, we analyzed the five non-relevant visits most often retrieved and the five relevant visits most often overlooked. Categories were developed iteratively to group the reasons for incorrect retrieval for each of the 35 topics. Reasons fell into nine categories for non-relevant visits and five categories for relevant visits. Non-relevant visits were most often retrieved because they contained a non-relevant reference to the topic terms. Relevant visits were most often infrequently retrieved because they used a synonym for a topic term. This failure analysis provides insight into areas for future improvement in EHR-based retrieval with techniques such as more widespread and complete use of standardized terminology in retrieval and data entry systems.

A similarity learning approach to content-based image retrieval: application to digital mammography.

PubMed

El-Naqa, Issam; Yang, Yongyi; Galatsanos, Nikolas P; Nishikawa, Robert M; Wernick, Miles N

2004-10-01

In this paper, we describe an approach to content-based retrieval of medical images from a database, and provide a preliminary demonstration of our approach as applied to retrieval of digital mammograms. Content-based image retrieval (CBIR) refers to the retrieval of images from a database using information derived from the images themselves, rather than solely from accompanying text indices. In the medical-imaging context, the ultimate aim of CBIR is to provide radiologists with a diagnostic aid in the form of a display of relevant past cases, along with proven pathology and other suitable information. CBIR may also be useful as a training tool for medical students and residents. The goal of information retrieval is to recall from a database information that is relevant to the user's query. The most challenging aspect of CBIR is the definition of relevance (similarity), which is used to guide the retrieval machine. In this paper, we pursue a new approach, in which similarity is learned from training examples provided by human observers. Specifically, we explore the use of neural networks and support vector machines to predict the user's notion of similarity. Within this framework we propose using a hierarchal learning approach, which consists of a cascade of a binary classifier and a regression module to optimize retrieval effectiveness and efficiency. We also explore how to incorporate online human interaction to achieve relevance feedback in this learning framework. Our experiments are based on a database consisting of 76 mammograms, all of which contain clustered microcalcifications (MCs). Our goal is to retrieve mammogram images containing similar MC clusters to that in a query. The performance of the retrieval system is evaluated using precision-recall curves computed using a cross-validation procedure. Our experimental results demonstrate that: 1) the learning framework can accurately predict the perceptual similarity reported by human observers, thereby serving as a basis for CBIR; 2) the learning-based framework can significantly outperform a simple distance-based similarity metric; 3) the use of the hierarchical two-stage network can improve retrieval performance; and 4) relevance feedback can be effectively incorporated into this learning framework to achieve improvement in retrieval precision based on online interaction with users; and 5) the retrieved images by the network can have predicting value for the disease condition of the query.

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

DTIC Science & Technology

1990-12-01

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

Speech-recognition interfaces for music information retrieval

NASA Astrophysics Data System (ADS)

Goto, Masataka

2005-09-01

This paper describes two hands-free music information retrieval (MIR) systems that enable a user to retrieve and play back a musical piece by saying its title or the artist's name. Although various interfaces for MIR have been proposed, speech-recognition interfaces suitable for retrieving musical pieces have not been studied. Our MIR-based jukebox systems employ two different speech-recognition interfaces for MIR, speech completion and speech spotter, which exploit intentionally controlled nonverbal speech information in original ways. The first is a music retrieval system with the speech-completion interface that is suitable for music stores and car-driving situations. When a user only remembers part of the name of a musical piece or an artist and utters only a remembered fragment, the system helps the user recall and enter the name by completing the fragment. The second is a background-music playback system with the speech-spotter interface that can enrich human-human conversation. When a user is talking to another person, the system allows the user to enter voice commands for music playback control by spotting a special voice-command utterance in face-to-face or telephone conversations. Experimental results from use of these systems have demonstrated the effectiveness of the speech-completion and speech-spotter interfaces. (Video clips: http://staff.aist.go.jp/m.goto/MIR/speech-if.html)

Designing an information search interface for younger and older adults.

PubMed

Pak, Richard; Price, Margaux M

2008-08-01

The present study examined Web-based information retrieval as a function of age for two information organization schemes: hierarchical organization and one organized around tags or keywords. Older adults' performance in information retrieval tasks has traditionally been lower compared with younger adults'. The current study examined the degree to which information organization moderated age-related performance differences on an information retrieval task. The theory of fluid and crystallized intelligence may provide insight into different kinds of information architectures that may reduce age-related differences in computer-based information retrieval performance. Fifty younger (18-23 years of age) and 50 older (55-76 years of age) participants browsed a Web site for answers to specific questions. Half of the participants browsed the hierarchically organized system (taxonomy), which maintained a one-to-one relationship between menu link and page, whereas the other half browsed the tag-based interface, with a many-to-one relationship between menu and page. This difference was expected to interact with age-related differences in fluid and crystallized intelligence. Age-related differences in information retrieval performance persisted; however, a tag-based retrieval interface reduced age-related differences, as compared with a taxonomical interface. Cognitive aging theory can lead to interface interventions that reduce age-related differences in performance with technology. In an information retrieval paradigm, older adults may be able to leverage their increased crystallized intelligence to offset fluid intelligence declines in a computer-based information search task. More research is necessary, but the results suggest that information retrieval interfaces organized around keywords may reduce age-related differences in performance.

Roogle: an information retrieval engine for clinical data warehouse.

PubMed

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

2011-01-01

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

Content-based unconstrained color logo and trademark retrieval with color edge gradient co-occurrence histograms

NASA Astrophysics Data System (ADS)

Phan, Raymond; Androutsos, Dimitrios

2008-01-01

In this paper, we present a logo and trademark retrieval system for unconstrained color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, and as such, we call this the Color Edge Gradient Co-occurrence Histogram (CEGCH). We use this as the main mechanism for our unconstrained color logo and trademark retrieval scheme. Results illustrate that the proposed retrieval system retrieves logos and trademarks with good accuracy, and outperforms the CECH object detection scheme with higher precision and recall.

A Usability Case Study Using TREC and ZPRISE.

ERIC Educational Resources Information Center

Downey, Laura L.; Tice, Dawn M.

1999-01-01

Examines the challenges involved in conducting an informal usability case study based on the introduction of a new information-retrieval system to experienced users. Identifies problems users were having with TREC (Text Retrieval Conference) and examines the usability of the new ZPRISE interface. (Author/LRW)

Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

PubMed

Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

2013-03-01

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

A memory learning framework for effective image retrieval.

PubMed

Han, Junwei; Ngan, King N; Li, Mingjing; Zhang, Hong-Jiang

2005-04-01

Most current content-based image retrieval systems are still incapable of providing users with their desired results. The major difficulty lies in the gap between low-level image features and high-level image semantics. To address the problem, this study reports a framework for effective image retrieval by employing a novel idea of memory learning. It forms a knowledge memory model to store the semantic information by simply accumulating user-provided interactions. A learning strategy is then applied to predict the semantic relationships among images according to the memorized knowledge. Image queries are finally performed based on a seamless combination of low-level features and learned semantics. One important advantage of our framework is its ability to efficiently annotate images and also propagate the keyword annotation from the labeled images to unlabeled images. The presented algorithm has been integrated into a practical image retrieval system. Experiments on a collection of 10,000 general-purpose images demonstrate the effectiveness of the proposed framework.

A Management Information System for Bare Base Civil Engineering Commanders

DTIC Science & Technology

1988-09-01

initial beddown stage. The purpose of this research was to determine the feasibility of developing a microcomputer based management information system (MIS...the software best suited to synthesize four of the categories into a prototype field MIS. Keyword: Management information system , Bare bases, Civil engineering, Data bases, Information retrieval.

The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

2010-01-01

Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

Combining approaches to on-line handwriting information retrieval

NASA Astrophysics Data System (ADS)

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

2010-01-01

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

Intelligent retrieval of medical images from the Internet

NASA Astrophysics Data System (ADS)

Tang, Yau-Kuo; Chiang, Ted T.

1996-05-01

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

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

NASA Astrophysics Data System (ADS)

Lee, Ching-Cheng; Prabhakara, Rashmi

2005-03-01

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

The US-DOE ARM/ASR Effort in Quantifying Uncertainty in Ground-Based Cloud Property Retrievals (Invited)

NASA Astrophysics Data System (ADS)

Xie, S.; Protat, A.; Zhao, C.

2013-12-01

One primary goal of the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program is to obtain and retrieve cloud microphysical properties from detailed cloud observations using ground-based active and passive remote sensors. However, there is large uncertainty in the retrieved cloud property products. Studies have shown that the uncertainty could arise from instrument limitations, measurement errors, sampling errors, retrieval algorithm deficiencies in assumptions, as well as inconsistent input data and constraints used by different algorithms. To quantify the uncertainty in cloud retrievals, a scientific focus group, Quantification of Uncertainties In Cloud Retrievals (QUICR), was recently created by the DOE Atmospheric System Research (ASR) program. This talk will provide an overview of the recent research activities conducted within QUICR and discuss its current collaborations with the European cloud retrieval community and future plans. The goal of QUICR is to develop a methodology for characterizing and quantifying uncertainties in current and future ARM cloud retrievals. The Work at LLNL was performed under the auspices of the U. S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research by Lawrence Livermore National Laboratory under contract No. DE-AC52-07NA27344. LLNL-ABS-641258.

Striatal contributions to declarative memory retrieval

PubMed Central

Scimeca, Jason M.; Badre, David

2012-01-01

Declarative memory is known to depend on the medial temporal lobe memory system. Recently, there has been renewed focus on the relationship between the basal ganglia and declarative memory, including the involvement of striatum. However, the contribution of striatum to declarative memory retrieval remains unknown. Here, we review neuroimaging and neuropsychological evidence for the involvement of the striatum in declarative memory retrieval. From this review, we propose that, along with the prefrontal cortex (PFC), the striatum primarily supports cognitive control of memory retrieval. We conclude by proposing three hypotheses for the specific role of striatum in retrieval: (1) Striatum modulates the re-encoding of retrieved items in accord with their expected utility (adaptive encoding), (2) striatum selectively admits information into working memory that is expected to increase the likelihood of successful retrieval (adaptive gating), and (3) striatum enacts adjustments in cognitive control based on the outcome of retrieval (reinforcement learning). PMID:22884322

Phase Retrieval System for Assessing Diamond Turning and Optical Surface Defects

NASA Technical Reports Server (NTRS)

Dean, Bruce; Maldonado, Alex; Bolcar, Matthew

2011-01-01

An optical design is presented for a measurement system used to assess the impact of surface errors originating from diamond turning artifacts. Diamond turning artifacts are common by-products of optical surface shaping using the diamond turning process (a diamond-tipped cutting tool used in a lathe configuration). Assessing and evaluating the errors imparted by diamond turning (including other surface errors attributed to optical manufacturing techniques) can be problematic and generally requires the use of an optical interferometer. Commercial interferometers can be expensive when compared to the simple optical setup developed here, which is used in combination with an image-based sensing technique (phase retrieval). Phase retrieval is a general term used in optics to describe the estimation of optical imperfections or aberrations. This turnkey system uses only image-based data and has minimal hardware requirements. The system is straightforward to set up, easy to align, and can provide nanometer accuracy on the measurement of optical surface defects.

A Multimodal Search Engine for Medical Imaging Studies.

PubMed

Pinho, Eduardo; Godinho, Tiago; Valente, Frederico; Costa, Carlos

2017-02-01

The use of digital medical imaging systems in healthcare institutions has increased significantly, and the large amounts of data in these systems have led to the conception of powerful support tools: recent studies on content-based image retrieval (CBIR) and multimodal information retrieval in the field hold great potential in decision support, as well as for addressing multiple challenges in healthcare systems, such as computer-aided diagnosis (CAD). However, the subject is still under heavy research, and very few solutions have become part of Picture Archiving and Communication Systems (PACS) in hospitals and clinics. This paper proposes an extensible platform for multimodal medical image retrieval, integrated in an open-source PACS software with profile-based CBIR capabilities. In this article, we detail a technical approach to the problem by describing its main architecture and each sub-component, as well as the available web interfaces and the multimodal query techniques applied. Finally, we assess our implementation of the engine with computational performance benchmarks.

Comprehension and retrieval of failure cases in airborne observatories

NASA Technical Reports Server (NTRS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-01-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

Comprehension and retrieval of failure cases in airborne observatories

NASA Astrophysics Data System (ADS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-05-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

Application of new type of distributed multimedia databases to networked electronic museum

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1999-01-01

Recently, various kinds of multimedia application systems have actively been developed based on the achievement of advanced high sped communication networks, computer processing technologies, and digital contents-handling technologies. Under this background, this paper proposed a new distributed multimedia database system which can effectively perform a new function of cooperative retrieval among distributed databases. The proposed system introduces a new concept of 'Retrieval manager' which functions as an intelligent controller so that the user can recognize a set of distributed databases as one logical database. The logical database dynamically generates and performs a preferred combination of retrieving parameters on the basis of both directory data and the system environment. Moreover, a concept of 'domain' is defined in the system as a managing unit of retrieval. The retrieval can effectively be performed by cooperation of processing among multiple domains. Communication language and protocols are also defined in the system. These are used in every action for communications in the system. A language interpreter in each machine translates a communication language into an internal language used in each machine. Using the language interpreter, internal processing, such internal modules as DBMS and user interface modules can freely be selected. A concept of 'content-set' is also introduced. A content-set is defined as a package of contents. Contents in the content-set are related to each other. The system handles a content-set as one object. The user terminal can effectively control the displaying of retrieved contents, referring to data indicating the relation of the contents in the content- set. In order to verify the function of the proposed system, a networked electronic museum was experimentally built. The results of this experiment indicate that the proposed system can effectively retrieve the objective contents under the control to a number of distributed domains. The result also indicate that the system can effectively work even if the system becomes large.

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

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

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

Case-based fracture image retrieval.

PubMed

Zhou, Xin; Stern, Richard; Müller, Henning

2012-05-01

Case-based fracture image retrieval can assist surgeons in decisions regarding new cases by supplying visually similar past cases. This tool may guide fracture fixation and management through comparison of long-term outcomes in similar cases. A fracture image database collected over 10 years at the orthopedic service of the University Hospitals of Geneva was used. This database contains 2,690 fracture cases associated with 43 classes (based on the AO/OTA classification). A case-based retrieval engine was developed and evaluated using retrieval precision as a performance metric. Only cases in the same class as the query case are considered as relevant. The scale-invariant feature transform (SIFT) is used for image analysis. Performance evaluation was computed in terms of mean average precision (MAP) and early precision (P10, P30). Retrieval results produced with the GNU image finding tool (GIFT) were used as a baseline. Two sampling strategies were evaluated. One used a dense 40 × 40 pixel grid sampling, and the second one used the standard SIFT features. Based on dense pixel grid sampling, three unsupervised feature selection strategies were introduced to further improve retrieval performance. With dense pixel grid sampling, the image is divided into 1,600 (40 × 40) square blocks. The goal is to emphasize the salient regions (blocks) and ignore irrelevant regions. Regions are considered as important when a high variance of the visual features is found. The first strategy is to calculate the variance of all descriptors on the global database. The second strategy is to calculate the variance of all descriptors for each case. A third strategy is to perform a thumbnail image clustering in a first step and then to calculate the variance for each cluster. Finally, a fusion between a SIFT-based system and GIFT is performed. A first comparison on the selection of sampling strategies using SIFT features shows that dense sampling using a pixel grid (MAP = 0.18) outperformed the SIFT detector-based sampling approach (MAP = 0.10). In a second step, three unsupervised feature selection strategies were evaluated. A grid parameter search is applied to optimize parameters for feature selection and clustering. Results show that using half of the regions (700 or 800) obtains the best performance for all three strategies. Increasing the number of clusters in clustering can also improve the retrieval performance. The SIFT descriptor variance in each case gave the best indication of saliency for the regions (MAP = 0.23), better than the other two strategies (MAP = 0.20 and 0.21). Combining GIFT (MAP = 0.23) and the best SIFT strategy (MAP = 0.23) produced significantly better results (MAP = 0.27) than each system alone. A case-based fracture retrieval engine was developed and is available for online demonstration. SIFT is used to extract local features, and three feature selection strategies were introduced and evaluated. A baseline using the GIFT system was used to evaluate the salient point-based approaches. Without supervised learning, SIFT-based systems with optimized parameters slightly outperformed the GIFT system. A fusion of the two approaches shows that the information contained in the two approaches is complementary. Supervised learning on the feature space is foreseen as the next step of this study.

Learning semantic and visual similarity for endomicroscopy video retrieval.

PubMed

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

2012-06-01

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

Autocorrelation and Regularization of Query-Based Information Retrieval Scores

DTIC Science & Technology

2008-02-01

of the most general information retrieval models [ Salton , 1968]. By treating a query as a very short document, documents and queries can be rep... Salton , 1971]. In the context of single link hierarchical clustering, Jardine and van Rijsbergen showed that ranking all k clusters and retrieving a...a document about “dogs”, then the system will always miss this document when a user queries “dog”. Salton recognized that a document’s representation

A Comparison of Three Online Information Retrieval Services.

ERIC Educational Resources Information Center

Zais, Harriet W.

Three firms which offer online information retrieval are compared. The firms are Lockheed Information Service, System Development Corporation and the Western Research Application Center. Comparison tables provide information such as hours accessible, coverage, file update, search elements and cost figures for 15 data bases. In addition, general…

Term-Weighting Approaches in Automatic Text Retrieval.

ERIC Educational Resources Information Center

Salton, Gerard; Buckley, Christopher

1988-01-01

Summarizes the experimental evidence that indicates that text indexing systems based on the assignment of appropriately weighted single terms produce retrieval results superior to those obtained with more elaborate text representations, and provides baseline single term indexing models with which more elaborate content analysis procedures can be…

Recommending Education Materials for Diabetic Questions Using Information Retrieval Approaches

PubMed Central

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

2017-01-01

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

Hippocampal-neocortical functional reorganization underlies children's cognitive development

PubMed Central

Qin, Shaozheng; Cho, Soohyun; Chen, Tianwen; Rosenberg-Lee, Miriam; Geary, David C.; Menon, Vinod

2014-01-01

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development – the transition from procedure-based to memory-based problem solving strategies – are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal fMRI in children, ages 7 to 9, revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Critically, longitudinal improvements in retrieval strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval strategy use continued to improve through adolescence into adulthood, and was associated with decreased activation but more stable inter-problem representations in the hippocampus. Our findings provide novel insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving, and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development. PMID:25129076

Hippocampal-neocortical functional reorganization underlies children's cognitive development.

PubMed

Qin, Shaozheng; Cho, Soohyun; Chen, Tianwen; Rosenberg-Lee, Miriam; Geary, David C; Menon, Vinod

2014-09-01

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development-the transition from procedure-based to memory-based problem-solving strategies-are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal functional magnetic resonance imaging (fMRI) in 7-9-year-old children revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Longitudinal improvements in retrieval-strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval-strategy use continued to improve through adolescence into adulthood and was associated with decreased activation but more stable interproblem representations in the hippocampus. Our findings provide insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development.

Current Standardization and Cooperative Efforts Related to Industrial Information Infrastructures.

DTIC Science & Technology

1993-05-01

Data Management Systems: Components used to store, manage, and retrieve data. Data management includes knowledge bases, database management...Application Development Tools and Methods X/Open and POSIX APIs Integrated Design Support System (IDS) Knowledge -Based Systems (KBS) Application...IDEFlx) Yourdon Jackson System Design (JSD) Knowledge -Based Systems (KBSs) Structured Systems Development (SSD) Semantic Unification Meta-Model

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A Knowledge-based System for Intelligent Support in Pharmacogenomics Evidence Assessment: Ontology-driven Evidence Representation and Retrieval.

PubMed

Lee, Chia-Ju; Devine, Beth; Tarczy-Hornoch, Peter

2017-01-01

Pharmacogenomics holds promise as a critical component of precision medicine. Yet, the use of pharmacogenomics in routine clinical care is minimal, partly due to the lack of efficient and effective use of existing evidence. This paper describes the design, development, implementation and evaluation of a knowledge-based system that fulfills three critical features: a) providing clinically relevant evidence, b) applying an evidence-based approach, and c) using semantically computable formalism, to facilitate efficient evidence assessment to support timely decisions on adoption of pharmacogenomics in clinical care. To illustrate functionality, the system was piloted in the context of clopidogrel and warfarin pharmacogenomics. In contrast to existing pharmacogenomics knowledge bases, the developed system is the first to exploit the expressivity and reasoning power of logic-based representation formalism to enable unambiguous expression and automatic retrieval of pharmacogenomics evidence to support systematic review with meta-analysis.

Theory of the amplitude-phase retrieval in any linear-transform system and its applications

NASA Astrophysics Data System (ADS)

Yang, Guozhen; Gu, Ben-Yuan; Dong, Bi-Zhen

1992-12-01

This paper is a summary of the theory of the amplitude-phase retrieval problem in any linear transform system and its applications based on our previous works in the past decade. We describe the general statement on the amplitude-phase retrieval problem in an imaging system and derive a set of equations governing the amplitude-phase distribution in terms of the rigorous mathematical derivation. We then show that, by using these equations and an iterative algorithm, a variety of amplitude-phase problems can be successfully handled. We carry out the systematic investigations and comprehensive numerical calculations to demonstrate the utilization of this new algorithm in various transform systems. For instance, we have achieved the phase retrieval from two intensity measurements in an imaging system with diffraction loss (non-unitary transform), both theoretically and experimentally, and the recovery of model real image from its Hartley-transform modulus only in one and two dimensional cases. We discuss the achievement of the phase retrieval problem from a single intensity only based on the sampling theorem and our algorithm. We also apply this algorithm to provide an optimal design of the phase-adjusted plate for a phase-adjustment focusing laser accelerator and a design approach of single phase-only element for implementing optical interconnect. In order to closely simulate the really measured data, we examine the reconstruction of image from its spectral modulus corrupted by a random noise in detail. The results show that the convergent solution can always be obtained and the quality of the recovered image is satisfactory. We also indicated the relationship and distinction between our algorithm and the original Gerchberg- Saxton algorithm. From these studies, we conclude that our algorithm shows great capability to deal with the comprehensive phase-retrieval problems in the imaging system and the inverse problem in solid state physics. It may open a new way to solve important inverse source problems extensively appearing in physics.

A concept-based interactive biomedical image retrieval approach using visualness and spatial information

NASA Astrophysics Data System (ADS)

Rahman, Md M.; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.

2015-03-01

This paper presents a novel approach to biomedical image retrieval by mapping image regions to local concepts and represent images in a weighted entropy-based concept feature space. The term concept refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist user in interactively select a Region-Of-Interest (ROI) and search for similar image ROIs. Further, a spatial verification step is used as a post-processing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval, is validated through experiments on a data set of 450 lung CT images extracted from journal articles from four different collections.

Clinician search behaviors may be influenced by search engine design.

PubMed

Lau, Annie Y S; Coiera, Enrico; Zrimec, Tatjana; Compton, Paul

2010-06-30

Searching the Web for documents using information retrieval systems plays an important part in clinicians' practice of evidence-based medicine. While much research focuses on the design of methods to retrieve documents, there has been little examination of the way different search engine capabilities influence clinician search behaviors. Previous studies have shown that use of task-based search engines allows for faster searches with no loss of decision accuracy compared with resource-based engines. We hypothesized that changes in search behaviors may explain these differences. In all, 75 clinicians (44 doctors and 31 clinical nurse consultants) were randomized to use either a resource-based or a task-based version of a clinical information retrieval system to answer questions about 8 clinical scenarios in a controlled setting in a university computer laboratory. Clinicians using the resource-based system could select 1 of 6 resources, such as PubMed; clinicians using the task-based system could select 1 of 6 clinical tasks, such as diagnosis. Clinicians in both systems could reformulate search queries. System logs unobtrusively capturing clinicians' interactions with the systems were coded and analyzed for clinicians' search actions and query reformulation strategies. The most frequent search action of clinicians using the resource-based system was to explore a new resource with the same query, that is, these clinicians exhibited a "breadth-first" search behaviour. Of 1398 search actions, clinicians using the resource-based system conducted 401 (28.7%, 95% confidence interval [CI] 26.37-31.11) in this way. In contrast, the majority of clinicians using the task-based system exhibited a "depth-first" search behavior in which they reformulated query keywords while keeping to the same task profiles. Of 585 search actions conducted by clinicians using the task-based system, 379 (64.8%, 95% CI 60.83-68.55) were conducted in this way. This study provides evidence that different search engine designs are associated with different user search behaviors.

Vision Systems with the Human in the Loop

NASA Astrophysics Data System (ADS)

Bauckhage, Christian; Hanheide, Marc; Wrede, Sebastian; Käster, Thomas; Pfeiffer, Michael; Sagerer, Gerhard

2005-12-01

The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

PubMed

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

Adaptive optics compensation of orbital angular momentum beams with a modified Gerchberg-Saxton-based phase retrieval algorithm

NASA Astrophysics Data System (ADS)

Chang, Huan; Yin, Xiao-li; Cui, Xiao-zhou; Zhang, Zhi-chao; Ma, Jian-xin; Wu, Guo-hua; Zhang, Li-jia; Xin, Xiang-jun

2017-12-01

Practical orbital angular momentum (OAM)-based free-space optical (FSO) communications commonly experience serious performance degradation and crosstalk due to atmospheric turbulence. In this paper, we propose a wave-front sensorless adaptive optics (WSAO) system with a modified Gerchberg-Saxton (GS)-based phase retrieval algorithm to correct distorted OAM beams. We use the spatial phase perturbation (SPP) GS algorithm with a distorted probe Gaussian beam as the only input. The principle and parameter selections of the algorithm are analyzed, and the performance of the algorithm is discussed. The simulation results show that the proposed adaptive optics (AO) system can significantly compensate for distorted OAM beams in single-channel or multiplexed OAM systems, which provides new insights into adaptive correction systems using OAM beams.

Incomplete fuzzy data processing systems using artificial neural network

NASA Technical Reports Server (NTRS)

Patyra, Marek J.

1992-01-01

In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

Cross-Language Information Retrieval: An Analysis of Errors.

ERIC Educational Resources Information Center

Ruiz, Miguel E.; Srinivasan, Padmini

1998-01-01

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

Impact of Physician Education and a Dedicated Inferior Vena Cava Filter Tracking System on Inferior Vena Cava Filter Use and Retrieval Rates Across a Large US Health Care Region.

PubMed

Wang, Stephen L; Cha, Hsien-Hwa A; Lin, James R; Francis, Bolanos; Elizabeth, Wakley; Martin, Porras; Rajan, Sudhir

2016-05-01

To evaluate the effects of physician familiarity with current evidence and guidelines on inferior vena cava (IVC) filter use and the availability of IVC filter tracking infrastructure on retrieval rates. Fourteen continuing medical education-approved in-hospital grand rounds covering evidence-based review of the literature on IVC filter efficacy, patient-centered outcomes, guidelines for IVC filter indications, and complications were performed across a large United States (US) health care region serving more than 3.5 million members. A computer-based IVC filter tracking system was deployed simultaneously. IVC filter use, rates of attempted retrieval, and fulfillment of guidelines for IVC filter indications were retrospectively evaluated at each facility for 12 months before intervention (n = 427) and for 12 months after intervention (n = 347). After education, IVC filter use decreased 18.7%, with a member enrollment-adjusted decrease of 22.2%, despite an increasing IVC filter use trend for 4 years. Reduction in IVC filter use at each facility strongly correlated with physician attendance at grand rounds (r = -0.69; P = .007). Rates of attempted retrieval increased from 38.9% to 54.0% (P = .0006), with similar rates of successful retrieval (82.3% before education and 85.8% after education on first attempt). Improvement in IVC filter retrieval attempts correlated with physician attendance at grand rounds (r = 0.51; P = .051). IVC filter dwell times at first retrieval attempt were similar (10.2 wk before and 10.8 wk after). Physician education dramatically reduced IVC filter use across a large US health care region, and represents a learning opportunity for physicians who request and place them. Education and a novel tracking system improved rates of retrieval for IVC filter devices. Copyright © 2016 SIR. Published by Elsevier Inc. All rights reserved.

Simultenious binary hash and features learning for image retrieval

NASA Astrophysics Data System (ADS)

Frantc, V. A.; Makov, S. V.; Voronin, V. V.; Marchuk, V. I.; Semenishchev, E. A.; Egiazarian, K. O.; Agaian, S.

2016-05-01

Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo-collection management systems, web-scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image-retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel-based image representation to hash-value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine-tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data- dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state-of-the-art methods.

A diagram retrieval method with multi-label learning

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Computer aided fixture design - A case based approach

NASA Astrophysics Data System (ADS)

Tanji, Shekhar; Raiker, Saiesh; Mathew, Arun Tom

2017-11-01

Automated fixture design plays important role in process planning and integration of CAD and CAM. An automated fixture setup design system is developed where when fixturing surfaces and points are described allowing modular fixture components to get automatically select for generating fixture units and placed into position with satisfying assembled conditions. In past, various knowledge based system have been developed to implement CAFD in practice. In this paper, to obtain an acceptable automated machining fixture design, a case-based reasoning method with developed retrieval system is proposed. Visual Basic (VB) programming language is used in integrating with SolidWorks API (Application programming interface) module for better retrieval procedure reducing computational time. These properties are incorporated in numerical simulation to determine the best fit for practical use.

Cloud-assisted mobile-access of health data with privacy and auditability.

PubMed

Tong, Yue; Sun, Jinyuan; Chow, Sherman S M; Li, Pan

2014-03-01

Motivated by the privacy issues, curbing the adoption of electronic healthcare systems and the wild success of cloud service models, we propose to build privacy into mobile healthcare systems with the help of the private cloud. Our system offers salient features including efficient key management, privacy-preserving data storage, and retrieval, especially for retrieval at emergencies, and auditability for misusing health data. Specifically, we propose to integrate key management from pseudorandom number generator for unlinkability, a secure indexing method for privacy-preserving keyword search which hides both search and access patterns based on redundancy, and integrate the concept of attribute-based encryption with threshold signing for providing role-based access control with auditability to prevent potential misbehavior, in both normal and emergency cases.

Variable Sampling Mapping

NASA Technical Reports Server (NTRS)

Smith, Jeffrey, S.; Aronstein, David L.; Dean, Bruce H.; Lyon, Richard G.

2012-01-01

The performance of an optical system (for example, a telescope) is limited by the misalignments and manufacturing imperfections of the optical elements in the system. The impact of these misalignments and imperfections can be quantified by the phase variations imparted on light traveling through the system. Phase retrieval is a methodology for determining these variations. Phase retrieval uses images taken with the optical system and using a light source of known shape and characteristics. Unlike interferometric methods, which require an optical reference for comparison, and unlike Shack-Hartmann wavefront sensors that require special optical hardware at the optical system's exit pupil, phase retrieval is an in situ, image-based method for determining the phase variations of light at the system s exit pupil. Phase retrieval can be used both as an optical metrology tool (during fabrication of optical surfaces and assembly of optical systems) and as a sensor used in active, closed-loop control of an optical system, to optimize performance. One class of phase-retrieval algorithms is the iterative transform algorithm (ITA). ITAs estimate the phase variations by iteratively enforcing known constraints in the exit pupil and at the detector, determined from modeled or measured data. The Variable Sampling Mapping (VSM) technique is a new method for enforcing these constraints in ITAs. VSM is an open framework for addressing a wide range of issues that have previously been considered detrimental to high-accuracy phase retrieval, including undersampled images, broadband illumination, images taken at or near best focus, chromatic aberrations, jitter or vibration of the optical system or detector, and dead or noisy detector pixels. The VSM is a model-to-data mapping procedure. In VSM, fully sampled electric fields at multiple wavelengths are modeled inside the phase-retrieval algorithm, and then these fields are mapped to intensities on the light detector, using the properties of the detector and optical system, for comparison with measured data. Ultimately, this model-to-data mapping procedure enables a more robust and accurate way of incorporating the exit-pupil and image detector constraints, which are fundamental to the general class of ITA phase retrieval algorithms.

Signal Analysis of Automotive Engine Spark Ignition System using Case-Based Reasoning (CBR) and Case-based Maintenance (CBM)

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

Huang, H.; Vong, C. M.; Wong, P. K.

2010-05-21

With the development of modern technology, modern vehicles adopt electronic control system for injection and ignition. In traditional way, whenever there is any malfunctioning in an automotive engine, an automotive mechanic usually performs a diagnosis in the ignition system of the engine to check any exceptional symptoms. In this paper, we present a case-based reasoning (CBR) approach to help solve human diagnosis problem. Nevertheless, one drawback of CBR system is that the case library will be expanded gradually after repeatedly running the system, which may cause inaccuracy and longer time for the CBR retrieval. To tackle this problem, case-based maintenancemore » (CBM) framework is employed so that the case library of the CBR system will be compressed by clustering to produce a set of representative cases. As a result, the performance (in retrieval accuracy and time) of the whole CBR system can be improved.« less

Determination of Ice Water Path in Ice-over-Water Cloud Systems Using Combined MODIS and AMSR-E Measurements

NASA Technical Reports Server (NTRS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-01-01

To provide more accurate ice cloud properties for evaluating climate models, the updated version of multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems over global ocean using combined instrument data from the Aqua satellite. The liquid water path (LWP) of lower layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. With the lower layer LWP known, the properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer measurements by matching simulated radiances from a two-cloud layer radiative transfer model. Comparisons with single-layer cirrus systems and surface-based radar retrievals show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and ice water path retrievals for ice over-water cloud systems. During the period from December 2004 through February 2005, the mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over ocean from Aqua are 7.6 and 146.4 gm(sup -2), respectively, significantly less than the initial single layer retrievals of 17.3 and 322.3 gm(sup -2). The mean IWP for actual single-layer clouds was 128.2 gm(sup -2).

Multiple products management system with sensors array in automated storage and retrieval systems

NASA Astrophysics Data System (ADS)

Vongbunyong, Supachai; Roengritronnachai, Perawat; Kongsanit, Savanut; Chanok-owat, Chawisa; Polchankajorn, Pongsakorn

2018-01-01

Automated Storage and Retrieval Systems (AS/RS) have now been widely used in a number of industries due to its capability to automatically manage the storage of products in effective ways. One of the key features of AS/RS is that each rack is not assigned for a specific product resulting in the benefit of space utilization and logistics related issues. In this research, sensor arrays are equipped at each rack in order to enhance this feature. As a result, various products can be identified and mixed in each rack, so that the space utilization efficiency can be increased. To prove the concept, a prototype system consisting of a Cartesian robot that manages the storage and retrieval of products with 9 variations based on size and color. The concept of Cyber-Physical System and self-awareness of the system are also implemented in this concept prototype.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

A new hybrid case-based reasoning approach for medical diagnosis systems.

PubMed

Sharaf-El-Deen, Dina A; Moawad, Ibrahim F; Khalifa, M E

2014-02-01

Case-Based Reasoning (CBR) has been applied in many different medical applications. Due to the complexities and the diversities of this domain, most medical CBR systems become hybrid. Besides, the case adaptation process in CBR is often a challenging issue as it is traditionally carried out manually by domain experts. In this paper, a new hybrid case-based reasoning approach for medical diagnosis systems is proposed to improve the accuracy of the retrieval-only CBR systems. The approach integrates case-based reasoning and rule-based reasoning, and also applies the adaptation process automatically by exploiting adaptation rules. Both adaptation rules and reasoning rules are generated from the case-base. After solving a new case, the case-base is expanded, and both adaptation and reasoning rules are updated. To evaluate the proposed approach, a prototype was implemented and experimented to diagnose breast cancer and thyroid diseases. The final results show that the proposed approach increases the diagnosing accuracy of the retrieval-only CBR systems, and provides a reliable accuracy comparing to the current breast cancer and thyroid diagnosis systems.

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

PubMed

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

2012-01-15

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

NASIS data base management system: IBM 360 TSS implementation. Volume 8: Data base administrator user's guide

NASA Technical Reports Server (NTRS)

1973-01-01

The Data Base Administrator User's Guide for the NASA Aerospace Safety Information System is presented. The subjects discussed are: (1) multi-terminal tasking, (2) data base executive, (3) utilities, (4) maintenance, (5) terminal support, and (6) retrieval subsystem.

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles

2012-01-01

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms.

PubMed

Tourassi, Georgia D; Harrawood, Brian; Singh, Swatee; Lo, Joseph Y; Floyd, Carey E

2007-01-01

The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrieval precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.

Estimating surface soil moisture from SMAP observations using a Neural Network technique.

PubMed

Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

2018-01-01

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

PubMed

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming distance using the learned binary representation. A boosting algorithm is presented to efficiently learn the distance function. We evaluate the proposed algorithm on a mammographic image reference library with an Interactive Search-Assisted Decision Support (ISADS) system and on the medical image data set from ImageCLEF. Our results show that the boosting framework compares favorably to state-of-the-art approaches for distance metric learning in retrieval accuracy, with much lower computational cost. Additional evaluation with the COREL collection shows that our algorithm works well for regular image data sets.

A new retrieval algorithm for tropospheric temperature, humidity and pressure profiling based on GNSS radio occultation data

NASA Astrophysics Data System (ADS)

Kirchengast, Gottfried; Li, Ying; Scherllin-Pirscher, Barbara; Schwärz, Marc; Schwarz, Jakob; Nielsen, Johannes K.

2017-04-01

The GNSS radio occultation (RO) technique is an important remote sensing technique for obtaining thermodynamic profiles of temperature, humidity, and pressure in the Earth's troposphere. However, due to refraction effects of both dry ambient air and water vapor in the troposphere, retrieval of accurate thermodynamic profiles at these lower altitudes is challenging and requires suitable background information in addition to the RO refractivity information. Here we introduce a new moist air retrieval algorithm aiming to improve the quality and robustness of retrieving temperature, humidity and pressure profiles in moist air tropospheric conditions. The new algorithm consists of four steps: (1) use of prescribed specific humidity and its uncertainty to retrieve temperature and its associated uncertainty; (2) use of prescribed temperature and its uncertainty to retrieve specific humidity and its associated uncertainty; (3) use of the previous results to estimate final temperature and specific humidity profiles through optimal estimation; (4) determination of air pressure and density profiles from the results obtained before. The new algorithm does not require elaborated matrix inversions which are otherwise widely used in 1D-Var retrieval algorithms, and it allows a transparent uncertainty propagation, whereby the uncertainties of prescribed variables are dynamically estimated accounting for their spatial and temporal variations. Estimated random uncertainties are calculated by constructing error covariance matrices from co-located ECMWF short-range forecast and corresponding analysis profiles. Systematic uncertainties are estimated by empirical modeling. The influence of regarding or disregarding vertical error correlations is quantified. The new scheme is implemented with static input uncertainty profiles in WEGC's current OPSv5.6 processing system and with full scope in WEGC's next-generation system, the Reference Occultation Processing System (rOPS). Results from both WEGC systems, current OPSv5.6 and next-generation rOPS, are shown and discussed, based on both insights from individual profiles and statistical ensembles, and compared to moist air retrieval results from the UCAR Boulder and ROM-SAF Copenhagen centers. The results show that the new algorithmic scheme improves the temperature, humidity and pressure retrieval performance, in particular also the robustness including for integrated uncertainty estimation for large-scale applications, over the previous algorithms. The new rOPS-implemented algorithm will therefore be used in the first large-scale reprocessing towards a tropospheric climate data record 2001-2016 by the rOPS, including its integrated uncertainty propagation.

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

NASA Astrophysics Data System (ADS)

Chou, Cheng-Ying; Anastasio, Mark A.

2016-04-01

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

On the retrieval efficiency of light storage in an EIT medium

NASA Astrophysics Data System (ADS)

Chough, Young-Tak

2016-08-01

We investigate the retrieval efficiency of light slowed and/or stored in a medium with electromagnetically-induced transparency (an EIT medium) by numerical simulations based on first principles. Starting from the master equation formulation, we derive the full dynamics of the system and then show how the approximations are applied to reduce the number of dynamical equations. While operating the system as an optical "retarder," a "reflector," and a "beam-splitter," we find that the total retrieval efficiency in the case of the "beam-splitter" operation is lower than that in either of the other two operations. Nevertheless, we find that (1) when an appropriate value of detuning is applied between the two counter-propagating " read"-fields, the retrieval efficiency in the latter case can be significantly improved, (2) storing the signal in the form of the atomic spin wave is more advantageous than storing it in the form of a stationary light pulse (SLP), and (3) the retrieval efficiency can be augmented by increasing the strengths of the " read"-fields.

Natural language information retrieval in digital libraries

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

Strzalkowski, T.; Perez-Carballo, J.; Marinescu, M.

In this paper we report on some recent developments in joint NYU and GE natural language information retrieval system. The main characteristic of this system is the use of advanced natural language processing to enhance the effectiveness of term-based document retrieval. The system is designed around a traditional statistical backbone consisting of the indexer module, which builds inverted index files from pre-processed documents, and a retrieval engine which searches and ranks the documents in response to user queries. Natural language processing is used to (1) preprocess the documents in order to extract content-carrying terms, (2) discover inter-term dependencies and buildmore » a conceptual hierarchy specific to the database domain, and (3) process user`s natural language requests into effective search queries. This system has been used in NIST-sponsored Text Retrieval Conferences (TREC), where we worked with approximately 3.3 GBytes of text articles including material from the Wall Street Journal, the Associated Press newswire, the Federal Register, Ziff Communications`s Computer Library, Department of Energy abstracts, U.S. Patents and the San Jose Mercury News, totaling more than 500 million words of English. The system have been designed to facilitate its scalability to deal with ever increasing amounts of data. In particular, a randomized index-splitting mechanism has been installed which allows the system to create a number of smaller indexes that can be independently and efficiently searched.« less

Topic Models in Information Retrieval

DTIC Science & Technology

2007-08-01

Information Processing Systems, Cambridge, MA, MIT Press, 2004. Brown, P.F., Della Pietra, V.J., deSouza, P.V., Lai, J.C. and Mercer, R.L., Class-based...2003. http://www.wkap.nl/prod/b/1-4020-1216-0. Croft, W.B., Lucia , T.J., Cringean, J., and Willett, P., Retrieving Documents By Plausible Inference

A Semantic Rule-Based Framework for Efficient Retrieval of Educational Materials

ERIC Educational Resources Information Center

Mahmoudi, Maryam Tayefeh; Taghiyareh, Fattaneh; Badie, Kambiz

2013-01-01

Retrieving resources in an appropriate manner has a promising role in increasing the performance of educational support systems. A variety of works have been done to organize materials for educational purposes using tagging techniques. Despite the effectiveness of these techniques within certain domains, organizing resources in a way being…

Simulation of snow and soil water content as a basis for satellite retrievals

USDA-ARS?s Scientific Manuscript database

It is not yet possible to determine whether the snow has changed over time despite collection of passive microwave data for more than thirty years. Physically-based, but computationally simple snow and soil models have been coupled to form the basis of a data assimilation system for retrievals of sn...

Desktop Social Science: Coming of Age.

ERIC Educational Resources Information Center

Dwyer, David C.; And Others

Beginning in 1985, Apple Computer, Inc. and several school districts began a collaboration to examine the impact of intensive computer use on instruction and learning in K-12 classrooms. This paper follows the development of a Macintosh II-based management and retrieval system for text data undertaken to store and retrieve oral reflections of…

Single-intensity-recording optical encryption technique based on phase retrieval algorithm and QR code

NASA Astrophysics Data System (ADS)

Wang, Zhi-peng; Zhang, Shuai; Liu, Hong-zhao; Qin, Yi

2014-12-01

Based on phase retrieval algorithm and QR code, a new optical encryption technology that only needs to record one intensity distribution is proposed. In this encryption process, firstly, the QR code is generated from the information to be encrypted; and then the generated QR code is placed in the input plane of 4-f system to have a double random phase encryption. For only one intensity distribution in the output plane is recorded as the ciphertext, the encryption process is greatly simplified. In the decryption process, the corresponding QR code is retrieved using phase retrieval algorithm. A priori information about QR code is used as support constraint in the input plane, which helps solve the stagnation problem. The original information can be recovered without distortion by scanning the QR code. The encryption process can be implemented either optically or digitally, and the decryption process uses digital method. In addition, the security of the proposed optical encryption technology is analyzed. Theoretical analysis and computer simulations show that this optical encryption system is invulnerable to various attacks, and suitable for harsh transmission conditions.

Technology test results from an intelligent, free-flying robot for crew and equipment retrieval in space

NASA Technical Reports Server (NTRS)

Erickson, J.; Goode, R.; Grimm, K.; Hess, C.; Norsworthy, R.; Anderson, G.; Merkel, L.; Phinney, D.

1992-01-01

The ground-based demonstrations of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, are designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles with subsequent object handover. The software architecture incorporates a heirarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: sensing, perception, world model, reasoning, and acting. The design provides for supervised autonomy as the primary mode of operation. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable and safe operation. This paper gives an overview of the hardware, a focus on software, and a summary of results achieved recently from both computer simulations and air bearing floor demonstrations. Limitations of the technology used are evaluated. Plans for the next phase, during which moving targets and obstacles drive realtime behavior requirements, are discussed.

Technology test results from an intelligent, free-flying robot for crew and equipment retrieval in space

NASA Astrophysics Data System (ADS)

Erickson, Jon D.; Goode, R.; Grimm, K. A.; Hess, Clifford W.; Norsworthy, Robert S.; Anderson, Greg D.; Merkel, L.; Phinney, Dale E.

1992-03-01

The ground-based demonstrations of Extra Vehicular Activity (EVA) Retriever, a voice- supervised, intelligent, free-flying robot, are designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the space station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles with subsequent object handover. The software architecture incorporates a hierarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: sensing, perception, world model, reasoning, and acting. The design provides for supervised autonomy as the primary mode of operation. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable and safe operation. This paper gives an overview of the hardware, a focus on software, and a summary of results achieved recently from both computer simulations and air bearing floor demonstrations. Limitations of the technology used are evaluated. Plans for the next phase, during which moving targets and obstacles drive realtime behavior requirements, are discussed.

'SON-GO-KU' : a dream of automated library

NASA Astrophysics Data System (ADS)

Sato, Mamoru; Kishimoto, Juji

In the process of automating libraries, the retrieval of books through the browsing of shelves is being overlooked. The telematic library is a document based DBMS which can deliver the content of books by simulating the browsing process. The retrieval actually simulates the process a person would use in selecting a book in a real library, where a visual presentation using a graphic display is substituted. The characteristics of prototype system "Son-Go-Ku" for such retrieval implemented in 1988 are mentioned.

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

PubMed

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

2018-04-25

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

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

PubMed Central

García-Olalla, Oscar; Saikia, Surajit

2018-01-01

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

Improving data management and dissemination in web based information systems by semantic enrichment of descriptive data aspects

NASA Astrophysics Data System (ADS)

Gebhardt, Steffen; Wehrmann, Thilo; Klinger, Verena; Schettler, Ingo; Huth, Juliane; Künzer, Claudia; Dech, Stefan

2010-10-01

The German-Vietnamese water-related information system for the Mekong Delta (WISDOM) project supports business processes in Integrated Water Resources Management in Vietnam. Multiple disciplines bring together earth and ground based observation themes, such as environmental monitoring, water management, demographics, economy, information technology, and infrastructural systems. This paper introduces the components of the web-based WISDOM system including data, logic and presentation tier. It focuses on the data models upon which the database management system is built, including techniques for tagging or linking metadata with the stored information. The model also uses ordered groupings of spatial, thematic and temporal reference objects to semantically tag datasets to enable fast data retrieval, such as finding all data in a specific administrative unit belonging to a specific theme. A spatial database extension is employed by the PostgreSQL database. This object-oriented database was chosen over a relational database to tag spatial objects to tabular data, improving the retrieval of census and observational data at regional, provincial, and local areas. While the spatial database hinders processing raster data, a "work-around" was built into WISDOM to permit efficient management of both raster and vector data. The data model also incorporates styling aspects of the spatial datasets through styled layer descriptions (SLD) and web mapping service (WMS) layer specifications, allowing retrieval of rendered maps. Metadata elements of the spatial data are based on the ISO19115 standard. XML structured information of the SLD and metadata are stored in an XML database. The data models and the data management system are robust for managing the large quantity of spatial objects, sensor observations, census and document data. The operational WISDOM information system prototype contains modules for data management, automatic data integration, and web services for data retrieval, analysis, and distribution. The graphical user interfaces facilitate metadata cataloguing, data warehousing, web sensor data analysis and thematic mapping.

Performance analysis of algorithms for retrieval of magnetic resonance images for interactive teleradiology

NASA Astrophysics Data System (ADS)

Atkins, M. Stella; Hwang, Robert; Tang, Simon

2001-05-01

We have implemented a prototype system consisting of a Java- based image viewer and a web server extension component for transmitting Magnetic Resonance Images (MRI) to an image viewer, to test the performance of different image retrieval techniques. We used full-resolution images, and images compressed/decompressed using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm. We examined the SPIHT decompression algorithm using both non- progressive and progressive transmission, focusing on the running times of the algorithm, client memory usage and garbage collection. We also compared the Java implementation with a native C++ implementation of the non- progressive SPIHT decompression variant. Our performance measurements showed that for uncompressed image retrieval using a 10Mbps Ethernet, a film of 16 MR images can be retrieved and displayed almost within interactive times. The native C++ code implementation of the client-side decoder is twice as fast as the Java decoder. If the network bandwidth is low, the high communication time for retrieving uncompressed images may be reduced by use of SPIHT-compressed images, although the image quality is then degraded. To provide diagnostic quality images, we also investigated the retrieval of up to 3 images on a MR film at full-resolution, using progressive SPIHT decompression. The Java-based implementation of progressive decompression performed badly, mainly due to the memory requirements for maintaining the image states, and the high cost of execution of the Java garbage collector. Hence, in systems where the bandwidth is high, such as found in a hospital intranet, SPIHT image compression does not provide advantages for image retrieval performance.

Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis.

PubMed

Welter, Petra; Riesmeier, Jörg; Fischer, Benedikt; Grouls, Christoph; Kuhl, Christiane; Deserno, Thomas M

2011-01-01

It is widely accepted that content-based image retrieval (CBIR) can be extremely useful for computer-aided diagnosis (CAD). However, CBIR has not been established in clinical practice yet. As a widely unattended gap of integration, a unified data concept for CBIR-based CAD results and reporting is lacking. Picture archiving and communication systems and the workflow of radiologists must be considered for successful data integration to be achieved. We suggest that CBIR systems applied to CAD should integrate their results in a picture archiving and communication systems environment such as Digital Imaging and Communications in Medicine (DICOM) structured reporting documents. A sample DICOM structured reporting template adaptable to CBIR and an appropriate integration scheme is presented. The proposed CBIR data concept may foster the promulgation of CBIR systems in clinical environments and, thereby, improve the diagnostic process.

Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis

PubMed Central

Riesmeier, Jörg; Fischer, Benedikt; Grouls, Christoph; Kuhl, Christiane; Deserno (né Lehmann), Thomas M

2011-01-01

It is widely accepted that content-based image retrieval (CBIR) can be extremely useful for computer-aided diagnosis (CAD). However, CBIR has not been established in clinical practice yet. As a widely unattended gap of integration, a unified data concept for CBIR-based CAD results and reporting is lacking. Picture archiving and communication systems and the workflow of radiologists must be considered for successful data integration to be achieved. We suggest that CBIR systems applied to CAD should integrate their results in a picture archiving and communication systems environment such as Digital Imaging and Communications in Medicine (DICOM) structured reporting documents. A sample DICOM structured reporting template adaptable to CBIR and an appropriate integration scheme is presented. The proposed CBIR data concept may foster the promulgation of CBIR systems in clinical environments and, thereby, improve the diagnostic process. PMID:21672913

An ECG storage and retrieval system embedded in client server HIS utilizing object-oriented DB.

PubMed

Wang, C; Ohe, K; Sakurai, T; Nagase, T; Kaihara, S

1996-02-01

In the University of Tokyo Hospital, the improved client server HIS has been applied to clinical practice and physicians can order prescription, laboratory examination, ECG examination and radiographic examination, etc. directly by themselves and read results of these examinations, except medical signal waves, schema and image, on UNIX workstations. Recently, we designed and developed an ECG storage and retrieval system embedded in the client server HIS utilizing object-oriented database to take the first step in dealing with digitized signal, schema and image data and show waves, graphics, and images directly to physicians by the client server HIS. The system was developed based on object-oriented analysis and design, and implemented with object-oriented database management system (OODMS) and C++ programming language. In this paper, we describe the ECG data model, functions of the storage and retrieval system, features of user interface and the result of its implementation in the HIS.

Characterizing region of interest in image using MPEG-7 visual descriptors

NASA Astrophysics Data System (ADS)

Ryu, Min-Sung; Park, Soo-Jun; Won, Chee Sun

2005-08-01

In this paper, we propose a region-based image retrieval system using EHD (Edge Histogram Descriptor) and CLD (Color Layout Descriptor) of MPEG-7 descriptors. The combined descriptor can efficiently describe edge and color features in terms of sub-image regions. That is, the basic unit for the selection of the region-of-interest (ROI) in the image is the sub-image block of the EHD, which corresponds to 16 (i.e., 4x4) non-overlapping image blocks in the image space. This implies that, to have a one-to-one region correspondence between EHD and CLD, we need to take an 8x8 inverse DCT (IDCT) for the CLD. Experimental results show that the proposed retrieval scheme can be used for image retrieval with the ROI based image retrieval for MPEG-7 indexed images.

iHelp: an intelligent online helpdesk system.

PubMed

Wang, Dingding; Li, Tao; Zhu, Shenghuo; Gong, Yihong

2011-02-01

Due to the importance of high-quality customer service, many companies use intelligent helpdesk systems (e.g., case-based systems) to improve customer service quality. However, these systems face two challenges: 1) Case retrieval measures: most case-based systems use traditional keyword-matching-based ranking schemes for case retrieval and have difficulty to capture the semantic meanings of cases and 2) result representation: most case-based systems return a list of past cases ranked by their relevance to a new request, and customers have to go through the list and examine the cases one by one to identify their desired cases. To address these challenges, we develop iHelp, an intelligent online helpdesk system, to automatically find problem-solution patterns from the past customer-representative interactions. When a new customer request arrives, iHelp searches and ranks the past cases based on their semantic relevance to the request, groups the relevant cases into different clusters using a mixture language model and symmetric matrix factorization, and summarizes each case cluster to generate recommended solutions. Case and user studies have been conducted to show the full functionality and the effectiveness of iHelp.

On Building an Ontological Knowledge Base for Managing Patient Safety Events.

PubMed

Liang, Chen; Gong, Yang

2015-01-01

Over the past decade, improving healthcare quality and safety through patient safety event reporting systems has drawn much attention. Unfortunately, such systems are suffering from low data quality, inefficient data entry and ineffective information retrieval. For improving the systems, we develop a semantic web ontology based on the WHO International Classification for Patient Safety (ICPS) and AHRQ Common Formats for patient safety event reporting. The ontology holds potential in enhancing knowledge management and information retrieval, as well as providing flexible data entry and case analysis for both reporters and reviewers of patient safety events. In this paper, we detailed our efforts in data acquisition, transformation, implementation and initial evaluation of the ontology.

Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

NASA Technical Reports Server (NTRS)

Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

2014-01-01

Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

Mineral Resources Data System (MRDS)

USGS Publications Warehouse

Mason, G.T.; Arndt, R.E.

1996-01-01

The U.S. Geological Survey (USGS) operates the Mineral Resources Data System (MRDS), a digital system that contained 111,955 records on Sept. 1, 1995. Records describe metallic and industrial commodity deposits, mines, prospects, and occurrences in the United States and selected other countries. These records have been created over the years by USGS commodity specialists and through cooperative agreements with geological surveys of U.S. States and other countries. This CD-ROM contains the complete MRDS data base, several subsets of it, and software to allow data retrieval and display. Data retrievals are made by using GSSEARCH, a program that is included on this CD-ROM. Retrievals are made by specifying fields or any combination of the fields that provide information on deposit name, location, commodity, deposit model type, geology, mineral production, reserves, and references. A tutorial is included. Retrieved records may be printed or written to a hard disk file in four different formats: ascii, fixed, comma delimited, and DBASE compatible.

Data engineering systems: Computerized modeling and data bank capabilities for engineering analysis

NASA Technical Reports Server (NTRS)

Kopp, H.; Trettau, R.; Zolotar, B.

1984-01-01

The Data Engineering System (DES) is a computer-based system that organizes technical data and provides automated mechanisms for storage, retrieval, and engineering analysis. The DES combines the benefits of a structured data base system with automated links to large-scale analysis codes. While the DES provides the user with many of the capabilities of a computer-aided design (CAD) system, the systems are actually quite different in several respects. A typical CAD system emphasizes interactive graphics capabilities and organizes data in a manner that optimizes these graphics. On the other hand, the DES is a computer-aided engineering system intended for the engineer who must operationally understand an existing or planned design or who desires to carry out additional technical analysis based on a particular design. The DES emphasizes data retrieval in a form that not only provides the engineer access to search and display the data but also links the data automatically with the computer analysis codes.

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

PubMed

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

1996-02-01

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

An evaluation of information retrieval accuracy with simulated OCR output

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

Croft, W.B.; Harding, S.M.; Taghva, K.

Optical Character Recognition (OCR) is a critical part of many text-based applications. Although some commercial systems use the output from OCR devices to index documents without editing, there is very little quantitative data on the impact of OCR errors on the accuracy of a text retrieval system. Because of the difficulty of constructing test collections to obtain this data, we have carried out evaluation using simulated OCR output on a variety of databases. The results show that high quality OCR devices have little effect on the accuracy of retrieval, but low quality devices used with databases of short documents canmore » result in significant degradation.« less

45 CFR 205.35 - Mechanized claims processing and information retrieval systems; definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... claims processing and information retrieval systems; definitions. Section 205.35 through 205.38 contain...: (a) A mechanized claims processing and information retrieval system, hereafter referred to as an automated application processing and information retrieval system (APIRS), or the system, means a system of...

45 CFR 205.35 - Mechanized claims processing and information retrieval systems; definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... claims processing and information retrieval systems; definitions. Section 205.35 through 205.38 contain...: (a) A mechanized claims processing and information retrieval system, hereafter referred to as an automated application processing and information retrieval system (APIRS), or the system, means a system of...

45 CFR 205.35 - Mechanized claims processing and information retrieval systems; definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... claims processing and information retrieval systems; definitions. Section 205.35 through 205.38 contain...: (a) A mechanized claims processing and information retrieval system, hereafter referred to as an automated application processing and information retrieval system (APIRS), or the system, means a system of...

Where's My Data - WMD

NASA Technical Reports Server (NTRS)

Quach, William L.; Sesplaukis, Tadas; Owen-Mankovich, Kyran J.; Nakamura, Lori L.

2012-01-01

WMD provides a centralized interface to access data stored in the Mission Data Processing and Control System (MPCS) GDS (Ground Data Systems) databases during MSL (Mars Science Laboratory) Testbeds and ATLO (Assembly, Test, and Launch Operations) test sessions. The MSL project organizes its data based on venue (Testbed, ATLO, Ops), with each venue's data stored on a separate database, making it cumbersome for users to access data across the various venues. WMD allows sessions to be retrieved through a Web-based search using several criteria: host name, session start date, or session ID number. Sessions matching the search criteria will be displayed and users can then select a session to obtain and analyze the associated data. The uniqueness of this software comes from its collection of data retrieval and analysis features provided through a single interface. This allows users to obtain their data and perform the necessary analysis without having to worry about where and how to get the data, which may be stored in various locations. Additionally, this software is a Web application that only requires a standard browser without additional plug-ins, providing a cross-platform, lightweight solution for users to retrieve and analyze their data. This software solves the problem of efficiently and easily finding and retrieving data from thousands of MSL Testbed and ATLO sessions. WMD allows the user to retrieve their session in as little as one mouse click, and then to quickly retrieve additional data associated with the session.

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval.

PubMed

Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R

2015-10-01

This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval

PubMed Central

Rahman, Md. Mahmudur; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.

2015-01-01

Abstract. This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term “concept” refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature. PMID:26730398

Recommending Education Materials for Diabetic Questions Using Information Retrieval Approaches.

PubMed

Zeng, Yuqun; Liu, Xusheng; Wang, Yanshan; Shen, Feichen; Liu, Sijia; Rastegar-Mojarad, Majid; Wang, Liwei; Liu, Hongfang

2017-10-16

Self-management is crucial to diabetes care and providing expert-vetted content for answering patients' questions is crucial in facilitating patient self-management. The aim is to investigate the use of information retrieval techniques in recommending patient education materials for diabetic questions of patients. We compared two retrieval algorithms, one based on Latent Dirichlet Allocation topic modeling (topic modeling-based model) and one based on semantic group (semantic group-based model), with the baseline retrieval models, vector space model (VSM), in recommending diabetic patient education materials to diabetic questions posted on the TuDiabetes forum. The evaluation was based on a gold standard dataset consisting of 50 randomly selected diabetic questions where the relevancy of diabetic education materials to the questions was manually assigned by two experts. The performance was assessed using precision of top-ranked documents. We retrieved 7510 diabetic questions on the forum and 144 diabetic patient educational materials from the patient education database at Mayo Clinic. The mapping rate of words in each corpus mapped to the Unified Medical Language System (UMLS) was significantly different (P<.001). The topic modeling-based model outperformed the other retrieval algorithms. For example, for the top-retrieved document, the precision of the topic modeling-based, semantic group-based, and VSM models was 67.0%, 62.8%, and 54.3%, respectively. This study demonstrated that topic modeling can mitigate the vocabulary difference and it achieved the best performance in recommending education materials for answering patients' questions. One direction for future work is to assess the generalizability of our findings and to extend our study to other disease areas, other patient education material resources, and online forums. ©Yuqun Zeng, Xusheng Liu, Yanshan Wang, Feichen Shen, Sijia Liu, Majid Rastegar Mojarad, Liwei Wang, Hongfang Liu. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.10.2017.

A biomedical information system for retrieval and manipulation of NHANES data.

PubMed

Mukherjee, Sukrit; Martins, David; Norris, Keith C; Jenders, Robert A

2013-01-01

The retrieval and manipulation of data from large public databases like the U.S. National Health and Nutrition Examination Survey (NHANES) may require sophisticated statistical software and significant expertise that may be unavailable in the university setting. In response, we have developed the Data Retrieval And Manipulation System (DReAMS), an automated information system to handle all processes of data extraction and cleaning and then joining different subsets to produce analysis-ready output. The system is a browser-based data warehouse application in which the input data from flat files or operational systems are aggregated in a structured way so that the desired data can be read, recoded, queried and extracted efficiently. The current pilot implementation of the system provides access to a limited amount of NHANES database. We plan to increase the amount of data available through the system in the near future and to extend the techniques to other large databases from CDU archive with a current holding of about 53 databases.

An Exploratory Data Analysis System for Support in Medical Decision-Making

PubMed Central

Copeland, J. A.; Hamel, B.; Bourne, J. R.

1979-01-01

An experimental system was developed to allow retrieval and analysis of data collected during a study of neurobehavioral correlates of renal disease. After retrieving data organized in a relational data base, simple bivariate statistics of parametric and nonparametric nature could be conducted. An “exploratory” mode in which the system provided guidance in selection of appropriate statistical analyses was also available to the user. The system traversed a decision tree using the inherent qualities of the data (e.g., the identity and number of patients, tests, and time epochs) to search for the appropriate analyses to employ.

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

PubMed

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

2018-01-01

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

A high throughput geocomputing system for remote sensing quantitative retrieval and a case study

NASA Astrophysics Data System (ADS)

Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting

2011-12-01

The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.

Design of a graphical user interface for an intelligent multimedia information system for radiology research

NASA Astrophysics Data System (ADS)

Taira, Ricky K.; Wong, Clement; Johnson, David; Bhushan, Vikas; Rivera, Monica; Huang, Lu J.; Aberle, Denise R.; Cardenas, Alfonso F.; Chu, Wesley W.

1995-05-01

With the increase in the volume and distribution of images and text available in PACS and medical electronic health-care environments it becomes increasingly important to maintain indexes that summarize the content of these multi-media documents. Such indices are necessary to quickly locate relevant patient cases for research, patient management, and teaching. The goal of this project is to develop an intelligent document retrieval system that allows researchers to request for patient cases based on document content. Thus we wish to retrieve patient cases from electronic information archives that could include a combined specification of patient demographics, low level radiologic findings (size, shape, number), intermediate-level radiologic findings (e.g., atelectasis, infiltrates, etc.) and/or high-level pathology constraints (e.g., well-differentiated small cell carcinoma). The cases could be distributed among multiple heterogeneous databases such as PACS, RIS, and HIS. Content- based retrieval systems go beyond the capabilities of simple key-word or string-based retrieval matching systems. These systems require a knowledge base to comprehend the generality/specificity of a concept (thus knowing the subclasses or related concepts to a given concept) and knowledge of the various string representations for each concept (i.e., synonyms, lexical variants, etc.). We have previously reported on a data integration mediation layer that allows transparent access to multiple heterogeneous distributed medical databases (HIS, RIS, and PACS). The data access layer of our architecture currently has limited query processing capabilities. Given a patient hospital identification number, the access mediation layer collects all documents in RIS and HIS and returns this information to a specified workstation location. In this paper we report on our efforts to extend the query processing capabilities of the system by creation of custom query interfaces, an intelligent query processing engine, and a document-content index that can be generated automatically (i.e., no manual authoring or changes to the normal clinical protocols).

A Computer-Based System Integrating Instruction and Information Retrieval: A Description of Some Methodological Considerations.

ERIC Educational Resources Information Center

Selig, Judith A.; And Others

This report, summarizing the activities of the Vision Information Center (VIC) in the field of computer-assisted instruction from December, 1966 to August, 1967, describes the methodology used to load a large body of information--a programed text on basic opthalmology--onto a computer for subsequent information retrieval and computer-assisted…

An Evaluation of the Interactive Query Expansion in an Online Library Catalogue with a Graphical User Interface.

ERIC Educational Resources Information Center

Hancock-Beaulieu, Micheline; And Others

1995-01-01

An online library catalog was used to evaluate an interactive query expansion facility based on relevance feedback for the Okapi, probabilistic, term weighting, retrieval system. A graphical user interface allowed searchers to select candidate terms extracted from relevant retrieved items to reformulate queries. Results suggested that the…

Task-Oriented Access to Data Files: An Evaluation.

ERIC Educational Resources Information Center

Watters, Carolyn; And Others

1994-01-01

Discussion of information retrieval highlights DalText, a prototype information retrieval system that provides access to nonindexed textual data files where the mode of access is determined by the user based on the task at hand. A user study is described that was conducted at Dalhousie University (Nova Scotia) to test DalText. (Contains 23…

The GLOBAL Learning and Observations to Benefit the Environment (GLOBE) Data Visualization and Retrieval System. Building a robust system for scientists and students.

NASA Astrophysics Data System (ADS)

Overoye, D.; Lewis, C.; Butler, D. M.; Andersen, T. J.

2016-12-01

The Global Learning and Observations to Benefit the Environment (GLOBE) Program is a worldwide hands-on, primary and secondary school-based science and education program founded on Earth Day 1995. Implemented in 117 countries, GLOBE promotes the teaching and learning of science, supporting students, teachers and scientists worldwide to collaborate with each other on inquiry-based investigations of the Earth system. The GLOBE Data Information System (DIS) currently supports users with the ability to enter data from over 50 different science protocols. GLOBE's Data Access and Visualization tools have been developed to accommodate the need to display and retrieve data from this large number of protocols. The community of users is also diverse, including NASA scientists, citizen scientists and grade school students. The challenge for GLOBE is to meet the needs from this diverse set of users with protocol specific displays that are simple enough for a GLOBE school to use, but also provide enough features for a NASA Scientist to retrieve data sets they are interested in. During the last 3 years, the GLOBE visualization system has evolved to meet the needs of these various users, leveraging user feedback and technological advances. Further refinements and enhancements continue. In this session we review the design and capabilities of the GLOBE visualization and data retrieval tool set, discuss the evolution of these tools, and discuss coming directions.

Is there a need for biomedical CBIR systems in clinical practice? Outcomes from a usability study

NASA Astrophysics Data System (ADS)

Antani, Sameer; Xue, Zhiyun; Long, L. Rodney; Bennett, Deborah; Ward, Sarah; Thoma, George R.

2011-03-01

Articles in the literature routinely describe advances in Content Based Image Retrieval (CBIR) and its potential for improving clinical practice, biomedical research and education. Several systems have been developed to address particular needs, however, surprisingly few are found to be in routine practical use. Our collaboration with the National Cancer Institute (NCI) has identified a need to develop tools to annotate and search a collection of over 100,000 cervigrams and related, anonymized patient data. One such tool developed for a projected need for retrieving similar patient images is the prototype CBIR system, called CervigramFinder, which retrieves images based on the visual similarity of particular regions on the cervix. In this article we report the outcomes from a usability study conducted at a primary meeting of practicing experts. We used the study to not only evaluate the system for software errors and ease of use, but also to explore its "user readiness", and to identify obstacles that hamper practical use of such systems, in general. Overall, the participants in the study found the technology interesting and bearing great potential; however, several challenges need to be addressed before the technology can be adopted.

A requirement for memory retrieval during and after long-term extinction learning

PubMed Central

Ouyang, Ming; Thomas, Steven A.

2005-01-01

Current learning theories are based on the idea that learning is driven by the difference between expectations and experience (the delta rule). In extinction, one learns that certain expectations no longer apply. Here, we test the potential validity of the delta rule by manipulating memory retrieval (and thus expectations) during extinction learning. Adrenergic signaling is critical for the time-limited retrieval (but not acquisition or consolidation) of contextual fear. Using genetic and pharmacologic approaches to manipulate adrenergic signaling, we find that long-term extinction requires memory retrieval but not conditioned responding. Identical manipulations of the adrenergic system that do not affect memory retrieval do not alter extinction. The results provide substantial support for the delta rule of learning theory. In addition, the timing over which extinction is sensitive to adrenergic manipulation suggests a model whereby memory retrieval occurs during, and several hours after, extinction learning to consolidate long-term extinction memory. PMID:15947076

New interactive CESAR

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

Fox, P.B.; Yatabe, M.

1987-01-01

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

The ESA Cloud CCI project: Generation of Multi Sensor consistent Cloud Properties with an Optimal Estimation Based Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Jerg, M.; Stengel, M.; Hollmann, R.; Poulsen, C.

2012-04-01

The ultimate objective of the ESA Climate Change Initiative (CCI) Cloud project is to provide long-term coherent cloud property data sets exploiting and improving on the synergetic capabilities of past, existing, and upcoming European and American satellite missions. The synergetic approach allows not only for improved accuracy and extended temporal and spatial sampling of retrieved cloud properties better than those provided by single instruments alone but potentially also for improved (inter-)calibration and enhanced homogeneity and stability of the derived time series. Such advances are required by the scientific community to facilitate further progress in satellite-based climate monitoring, which leads to a better understanding of climate. Some of the primary objectives of ESA Cloud CCI Cloud are (1) the development of inter-calibrated radiance data sets, so called Fundamental Climate Data Records - for ESA and non ESA instruments through an international collaboration, (2) the development of an optimal estimation based retrieval framework for cloud related essential climate variables like cloud cover, cloud top height and temperature, liquid and ice water path, and (3) the development of two multi-annual global data sets for the mentioned cloud properties including uncertainty estimates. These two data sets are characterized by different combinations of satellite systems: the AVHRR heritage product comprising (A)ATSR, AVHRR and MODIS and the novel (A)ATSR - MERIS product which is based on a synergetic retrieval using both instruments. Both datasets cover the years 2007-2009 in the first project phase. ESA Cloud CCI will also carry out a comprehensive validation of the cloud property products and provide a common data base as in the framework of the Global Energy and Water Cycle Experiment (GEWEX). The presentation will give an overview of the ESA Cloud CCI project and its goals and approaches and then continue with results from the Round Robin algorithm comparison exercise carried out at the beginning of the project which included three algorithms. The purpose of the exercise was to assess and compare existing cloud retrieval algorithms in order to chose one of them as backbone of the retrieval system and also identify areas of potential improvement and general strengths and weaknesses of the algorithm. Furthermore the presentation will elaborate on the optimal estimation algorithm subsequently chosen to derive the heritage product and which is presently further developed and will be employed for the AVHRR heritage product. The algorithm's capabilities to coherently and simultaneously process all radiative input and yield retrieval parameters together with associated uncertainty estimates will be presented together with first results for the heritage product. In the course of the project the algorithm is being developed into a freely and publicly available community retrieval system for interested scientists.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Research on lunar and planet development and utilization

NASA Astrophysics Data System (ADS)

Iwata, Tsutomu; Etou, Takao; Imai, Ryouichi; Oota, Kazuo; Kaneko, Yutaka; Maeda, Toshihide; Takano, Yutaka

1992-08-01

Status of the study on unmanned and manned lunar missions, unmanned Mars missions, lunar resource development and utilization missions, remote sensing exploration missions, survey and review to elucidate the problems of research and development for lunar resource development and utilization, and the techniques and equipment for lunar and planet exploration are presented. Following items were studied respectively: (1) spacecraft systems for unmanned lunar missions, such as lunar observation satellites, lunar landing vehicles, lunar surface rovers, lunar surface hoppers, and lunar sample retrieval; (2) spacecraft systems for manned lunar missions, such as manned lunar bases, lunar surface operation robots, lunar surface experiment systems, manned lunar take-off and landing vehicles, and lunar freight transportation ships; (3) spacecraft systems for Mars missions, such as Mars satellites, Phobos and Deimos sample retrieval vehicles, Mars landing explorers, Mars rovers, Mars sample retrieval; (4) lunar resource development and utilization; and (5) remote sensing exploration technologies.

Characterizing the Vertical Distribution of Aerosols using Ground-based Multiwavelength Lidar Data

NASA Astrophysics Data System (ADS)

Ferrare, R. A.; Thorsen, T. J.; Clayton, M.; Mueller, D.; Chemyakin, E.; Burton, S. P.; Goldsmith, J.; Holz, R.; Kuehn, R.; Eloranta, E. W.; Marais, W.; Newsom, R. K.; Liu, X.; Sawamura, P.; Holben, B. N.; Hostetler, C. A.

2016-12-01

Observations of aerosol optical and microphysical properties are critical for developing and evaluating aerosol transport model parameterizations and assessing global aerosol-radiation impacts on climate. During the Combined HSRL And Raman lidar Measurement Study (CHARMS), we investigated the synergistic use of ground-based Raman lidar and High Spectral Resolution Lidar (HSRL) measurements to retrieve aerosol properties aloft. Continuous (24/7) operation of these co-located lidars during the ten-week CHARMS mission (mid-July through September 2015) allowed the acquisition of a unique, multiwavelength ground-based lidar dataset for studying aerosol properties above the Southern Great Plains (SGP) site. The ARM Raman lidar measured profiles of aerosol backscatter, extinction and depolarization at 355 nm as well as profiles of water vapor mixing ratio and temperature. The University of Wisconsin HSRL simultaneously measured profiles of aerosol backscatter, extinction and depolarization at 532 nm and aerosol backscatter at 1064 nm. Recent advances in both lidar retrieval theory and algorithm development demonstrate that vertically-resolved retrievals using such multiwavelength lidar measurements of aerosol backscatter and extinction can help constrain both the aerosol optical (e.g. complex refractive index, scattering, etc.) and microphysical properties (e.g. effective radius, concentrations) as well as provide qualitative aerosol classification. Based on this work, the NASA Langley Research Center (LaRC) HSRL group developed automated algorithms for classifying and retrieving aerosol optical and microphysical properties, demonstrated these retrievals using data from the unique NASA/LaRC airborne multiwavelength HSRL-2 system, and validated the results using coincident airborne in situ data. We apply these algorithms to the CHARMS multiwavelength (Raman+HSRL) lidar dataset to retrieve aerosol properties above the SGP site. We present some profiles of aerosol effective radius and concentration retrieved from the CHARMS data and compare column-average aerosol properties derived from the multiwavelength lidar aerosol retrievals to corresponding values retrieved from AERONET measurements.

On-Line Retrieval System Design; Part V of Scientific Report No. ISR-18, Information Storage and Retrieval...

ERIC Educational Resources Information Center

Cornell Univ., Ithaca, NY. Dept. of Computer Science.

On-line retrieval system design is discussed in the two papers which make up Part Five of this report on Salton's Magical Automatic Retriever of Texts (SMART) project report. The first paper: "A Prototype On-Line Document Retrieval System" by D. Williamson and R. Williamson outlines a design for a SMART on-line document retrieval system…

A novel architecture for information retrieval system based on semantic web

NASA Astrophysics Data System (ADS)

Zhang, Hui

2011-12-01

Nowadays, the web has enabled an explosive growth of information sharing (there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhead. The challenge that is now before us is not only to help people locating relevant information precisely but also to access and aggregate a variety of information from different resources automatically. Current web document are in human-oriented formats and they are suitable for the presentation, but machines cannot understand the meaning of document. To address this issue, Berners-Lee proposed a concept of semantic web. With semantic web technology, web information can be understood and processed by machine. It provides new possibilities for automatic web information processing. A main problem of semantic web information retrieval is that when these is not enough knowledge to such information retrieval system, the system will return to a large of no sense result to uses due to a huge amount of information results. In this paper, we present the architecture of information based on semantic web. In addiction, our systems employ the inference Engine to check whether the query should pose to Keyword-based Search Engine or should pose to the Semantic Search Engine.

Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-02-01

From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an intercomparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT), and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products (Goddard Space Flight Center (GSFC)-MODIS and Clouds and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

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

KIRKBRIDE, R.A.

The Tank Waste Remediation System Operation and Utilization Plan updates the operating scenario and plans for the delivery of feed to BNFL Inc., retrieval of waste from single-shell tanks, and the overall process flowsheets for Phases I and II of the privatization of the Tank Waste Remediation System. The plans and flowsheets are updated with the most recent tank-by-tank inventory and sludge washing data. Sensitivity cases were run to evaluate the impact or benefits of proposed changes to the BNFL Inc. contract and to evaluate a risk-based SST retrieval strategy.

Design criteria for a PC-based common user interface to remote information systems

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Hall, Philip P.

1984-01-01

A set of design criteria are presented which will allow the implementation of an interface to multiple remote information systems on a microcomputer. The focus of the design description is on providing the user with the functionality required to retrieve, store and manipulate data residing in remote information systems through the utilization of a standardized interface system. The intent is to spare the user from learning the details of retrieval from specific systems while retaining the full capabilities of each system. The system design includes multi-level capabilities to enhance usability by a wide range of users and utilizes microcomputer graphics capabilities where applicable. A data collection subsystem for evaluation purposes is also described.

Representation and alignment of sung queries for music information retrieval

NASA Astrophysics Data System (ADS)

Adams, Norman H.; Wakefield, Gregory H.

2005-09-01

The pursuit of robust and rapid query-by-humming systems, which search melodic databases using sung queries, is a common theme in music information retrieval. The retrieval aspect of this database problem has received considerable attention, whereas the front-end processing of sung queries and the data structure to represent melodies has been based on musical intuition and historical momentum. The present work explores three time series representations for sung queries: a sequence of notes, a ``smooth'' pitch contour, and a sequence of pitch histograms. The performance of the three representations is compared using a collection of naturally sung queries. It is found that the most robust performance is achieved by the representation with highest dimension, the smooth pitch contour, but that this representation presents a formidable computational burden. For all three representations, it is necessary to align the query and target in order to achieve robust performance. The computational cost of the alignment is quadratic, hence it is necessary to keep the dimension small for rapid retrieval. Accordingly, iterative deepening is employed to achieve both robust performance and rapid retrieval. Finally, the conventional iterative framework is expanded to adapt the alignment constraints based on previous iterations, further expediting retrieval without degrading performance.

Experimental Studies on a Compact Storage Scheme for Wavelet-based Multiresolution Subregion Retrieval

NASA Technical Reports Server (NTRS)

Poulakidas, A.; Srinivasan, A.; Egecioglu, O.; Ibarra, O.; Yang, T.

1996-01-01

Wavelet transforms, when combined with quantization and a suitable encoding, can be used to compress images effectively. In order to use them for image library systems, a compact storage scheme for quantized coefficient wavelet data must be developed with a support for fast subregion retrieval. We have designed such a scheme and in this paper we provide experimental studies to demonstrate that it achieves good image compression ratios, while providing a natural indexing mechanism that facilitates fast retrieval of portions of the image at various resolutions.

Comparing the performance of two CBIRS indexing schemes

NASA Astrophysics Data System (ADS)

Mueller, Wolfgang; Robbert, Guenter; Henrich, Andreas

2003-01-01

Content based image retrieval (CBIR) as it is known today has to deal with a number of challenges. Quickly summarized, the main challenges are firstly, to bridge the semantic gap between high-level concepts and low-level features using feedback, secondly to provide performance under adverse conditions. High-dimensional spaces, as well as a demanding machine learning task make the right way of indexing an important issue. When indexing multimedia data, most groups opt for extraction of high-dimensional feature vectors from the data, followed by dimensionality reduction like PCA (Principal Components Analysis) or LSI (Latent Semantic Indexing). The resulting vectors are indexed using spatial indexing structures such as kd-trees or R-trees, for example. Other projects, such as MARS and Viper propose the adaptation of text indexing techniques, notably the inverted file. Here, the Viper system is the most direct adaptation of text retrieval techniques to quantized vectors. However, while the Viper query engine provides decent performance together with impressive user-feedback behavior, as well as the possibility for easy integration of long-term learning algorithms, and support for potentially infinite feature vectors, there has been no comparison of vector-based methods and inverted-file-based methods under similar conditions. In this publication, we compare a CBIR query engine that uses inverted files (Bothrops, a rewrite of the Viper query engine based on a relational database), and a CBIR query engine based on LSD (Local Split Decision) trees for spatial indexing using the same feature sets. The Benchathlon initiative works on providing a set of images and ground truth for simulating image queries by example and corresponding user feedback. When performing the Benchathlon benchmark on a CBIR system (the System Under Test, SUT), a benchmarking harness connects over internet to the SUT, performing a number of queries using an agreed-upon protocol, the multimedia retrieval markup language (MRML). Using this benchmark one can measure the quality of retrieval, as well as the overall (speed) performance of the benchmarked system. Our Benchmarks will draw on the Benchathlon"s work for documenting the retrieval performance of both inverted file-based and LSD tree based techniques. However in addition to these results, we will present statistics, that can be obtained only inside the system under test. These statistics will include the number of complex mathematical operations, as well as the amount of data that has to be read from disk during operation of a query.

Comparison of global cloud liquid water path derived from microwave measurements with CERES-MODIS

NASA Astrophysics Data System (ADS)

Yi, Y.; Minnis, P.; Huang, J.; Lin, B.; Ayers, K.; Sun-Mack, S.; Fan, A.

Cloud liquid water path LWP is a crucial parameter for climate studies due to the link that it provides between the atmospheric hydrological and radiative budgets Satellite-based visible infrared techniques such as the Visible Infrared Solar Split-Window Technique VISST can retrieve LWP for water clouds assumes single-layer over a variety of surfaces If the water clouds are overlapped by ice clouds the LWP of the underlying clouds can not be retrieved by such techniques However microwave techniques may be used to retrieve the LWP underneath ice clouds due to the microwave s insensitivity to cloud ice particles LWP is typically retrieved from satellite-observed microwave radiances only over ocean due to variations of land surface temperature and emissivity Recently Deeter and Vivekanandan 2006 developed a new technique for retrieving LWP over land In order to overcome the sensitivity to land surface temperature and emissivity their technique is based on a parameterization of microwave polarization-difference signals In this study a similar regression-based technique for retrieving LWP over land and ocean using Advanced Microwave Scanning Radiometer - EOS AMSR-E measurements is developed Furthermore the microwave surface emissivities are also derived using clear-sky fields of view based on the Clouds and Earth s Radiant Energy System Moderate-resolution Imaging Spectroradiometer CERES-MODIS cloud mask These emissivities are used in an alternate form of the technique The results are evaluated using independent measurements such

A Logic Basis for Information Retrieval.

ERIC Educational Resources Information Center

Watters, C. R.; Shepherd, M. A.

1987-01-01

Discusses the potential of recent work in artificial intelligence, especially expert systems, for the development of more effective information retrieval systems. Highlights include the role of an expert bibliographic retrieval system and a prototype expert retrieval system, PROBIB-2, that uses MicroProlog to provide deductive reasoning…

An Evaluation of On-Line Information Retrieval System Techniques.

ERIC Educational Resources Information Center

Wolfe, Theodore

This report presents a review and evaluation of three remote access on-line information retrieval systems and some ideas on what the capabilities of an ideal on-line information retrieval system should be. The three systems reviewed are the DDC Remote On-Line Retrieval System, the National Aeronautics and Space Administration RECON System, and the…

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Content-based image retrieval for interstitial lung diseases using classification confidence

NASA Astrophysics Data System (ADS)

Dash, Jatindra Kumar; Mukhopadhyay, Sudipta; Prabhakar, Nidhi; Garg, Mandeep; Khandelwal, Niranjan

2013-02-01

Content Based Image Retrieval (CBIR) system could exploit the wealth of High-Resolution Computed Tomography (HRCT) data stored in the archive by finding similar images to assist radiologists for self learning and differential diagnosis of Interstitial Lung Diseases (ILDs). HRCT findings of ILDs are classified into several categories (e.g. consolidation, emphysema, ground glass, nodular etc.) based on their texture like appearances. Therefore, analysis of ILDs is considered as a texture analysis problem. Many approaches have been proposed for CBIR of lung images using texture as primitive visual content. This paper presents a new approach to CBIR for ILDs. The proposed approach makes use of a trained neural network (NN) to find the output class label of query image. The degree of confidence of the NN classifier is analyzed using Naive Bayes classifier that dynamically takes a decision on the size of the search space to be used for retrieval. The proposed approach is compared with three simple distance based and one classifier based texture retrieval approaches. Experimental results show that the proposed technique achieved highest average percentage precision of 92.60% with lowest standard deviation of 20.82%.

The Design of PC/MISI, a PC-Based Common User Interface to Remote Information Storage and Retrieval Systems. M.S. ThesisFinal Report, 1 Jul. 1985 - 31 Dec. 1987

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Hall, Philip P.

1985-01-01

The amount of information contained in the data bases of large-scale information storage and retrieval systems is very large and growing at a rapid rate. The methods available for assessing this information have not been successful in making the information easily available to the people who have the greatest need for it. This thesis describes the design of a personal computer based system which will provide a means for these individuals to retrieve this data through one standardized interface. The thesis identifies each of the major problems associated with providing access to casual users of IS and R systems and describes the manner in which these problems are to be solved by the utilization of the local processing power of a PC. Additional capabilities, not available with standard access methods, are also provided to improve the user's ability to make use of this information. The design of PC/MISI is intended to facilitate its use as a research vehicle. Evaluation mechanisms and possible areas of future research are described. The PC/MISI development effort is part of a larger research effort directed at improving access to remote IS and R systems. This research effort, supported in part by NASA, is also reviewed.

Controlling conflict from interfering long-term memory representations.

PubMed

Jost, Kerstin; Khader, Patrick H; Düsel, Peter; Richter, Franziska R; Rohde, Kristina B; Bien, Siegfried; Rösler, Frank

2012-05-01

Remembering is more than an activation of a memory trace. As retrieval cues are often not uniquely related to one specific memory, cognitive control should come into play to guide selective memory retrieval by focusing on relevant while ignoring irrelevant information. Here, we investigated, by means of EEG and fMRI, how the memory system deals with retrieval interference arising when retrieval cues are associated with two material types (faces and spatial positions), but only one is task-relevant. The topography of slow EEG potentials and the fMRI BOLD signal in posterior storage areas indicated that in such situations not only the relevant but also the irrelevant material becomes activated. This results in retrieval interference that triggers control processes mediated by the medial and lateral PFC, which are presumably involved in biasing target representations by boosting the task-relevant material. Moreover, memory-based conflict was found to be dissociable from response conflict that arises when the relevant and irrelevant materials imply different responses. The two types of conflict show different activations in the medial frontal cortex, supporting the claim of domain-specific prefrontal control systems.

Displaying Geographically-Based Domestic Statistics

NASA Technical Reports Server (NTRS)

Quann, J.; Dalton, J.; Banks, M.; Helfer, D.; Szczur, M.; Winkert, G.; Billingsley, J.; Borgstede, R.; Chen, J.; Chen, L.;

Web-based OPACs: Between Tradition and Innovation.

ERIC Educational Resources Information Center

Moscoso, Purificacion; Ortiz-Repiso, Virginia

1999-01-01

Analyzes the change that Internet-based OPACs (Online Public Access Catalogs) have represented to the structure, administration, and maintenance of the catalogs, retrieval systems, and user interfaces. Examines the structure of databases and traditional principles that have governed systems development. Discusses repercussions of the application…

Rotation-robust math symbol recognition and retrieval using outer contours and image subsampling

NASA Astrophysics Data System (ADS)

Zhu, Siyu; Hu, Lei; Zanibbi, Richard

2013-01-01

This paper presents an unified recognition and retrieval system for isolated offline printed mathematical symbols for the first time. The system is based on nearest neighbor scheme and uses modified Turning Function and Grid Features to calculate the distance between two symbols based on Sum of Squared Difference. An unwrap process and an alignment process are applied to modify Turning Function to deal with the horizontal and vertical shift caused by the changing of staring point and rotation. This modified Turning Function make our system robust against rotation of the symbol image. The system obtains top-1 recognition rate of 96.90% and 47.27% Area Under Curve (AUC) of precision/recall plot on the InftyCDB-3 dataset. Experiment result shows that the system with modified Turning Function performs significantly better than the system with original Turning Function on the rotated InftyCDB-3 dataset.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2017-12-01

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

How I do it: a practical database management system to assist clinical research teams with data collection, organization, and reporting.

PubMed

Lee, Howard; Chapiro, Julius; Schernthaner, Rüdiger; Duran, Rafael; Wang, Zhijun; Gorodetski, Boris; Geschwind, Jean-François; Lin, MingDe

2015-04-01

The objective of this study was to demonstrate that an intra-arterial liver therapy clinical research database system is a more workflow efficient and robust tool for clinical research than a spreadsheet storage system. The database system could be used to generate clinical research study populations easily with custom search and retrieval criteria. A questionnaire was designed and distributed to 21 board-certified radiologists to assess current data storage problems and clinician reception to a database management system. Based on the questionnaire findings, a customized database and user interface system were created to perform automatic calculations of clinical scores including staging systems such as the Child-Pugh and Barcelona Clinic Liver Cancer, and facilitates data input and output. Questionnaire participants were favorable to a database system. The interface retrieved study-relevant data accurately and effectively. The database effectively produced easy-to-read study-specific patient populations with custom-defined inclusion/exclusion criteria. The database management system is workflow efficient and robust in retrieving, storing, and analyzing data. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Archetype relational mapping - a practical openEHR persistence solution.

PubMed

Wang, Li; Min, Lingtong; Wang, Rui; Lu, Xudong; Duan, Huilong

2015-11-05

One of the primary obstacles to the widespread adoption of openEHR methodology is the lack of practical persistence solutions for future-proof electronic health record (EHR) systems as described by the openEHR specifications. This paper presents an archetype relational mapping (ARM) persistence solution for the archetype-based EHR systems to support healthcare delivery in the clinical environment. First, the data requirements of the EHR systems are analysed and organized into archetype-friendly concepts. The Clinical Knowledge Manager (CKM) is queried for matching archetypes; when necessary, new archetypes are developed to reflect concepts that are not encompassed by existing archetypes. Next, a template is designed for each archetype to apply constraints related to the local EHR context. Finally, a set of rules is designed to map the archetypes to data tables and provide data persistence based on the relational database. A comparison study was conducted to investigate the differences among the conventional database of an EHR system from a tertiary Class A hospital in China, the generated ARM database, and the Node + Path database. Five data-retrieving tests were designed based on clinical workflow to retrieve exams and laboratory tests. Additionally, two patient-searching tests were designed to identify patients who satisfy certain criteria. The ARM database achieved better performance than the conventional database in three of the five data-retrieving tests, but was less efficient in the remaining two tests. The time difference of query executions conducted by the ARM database and the conventional database is less than 130 %. The ARM database was approximately 6-50 times more efficient than the conventional database in the patient-searching tests, while the Node + Path database requires far more time than the other two databases to execute both the data-retrieving and the patient-searching tests. The ARM approach is capable of generating relational databases using archetypes and templates for archetype-based EHR systems, thus successfully adapting to changes in data requirements. ARM performance is similar to that of conventionally-designed EHR systems, and can be applied in a practical clinical environment. System components such as ARM can greatly facilitate the adoption of openEHR architecture within EHR systems.

Video Information Communication and Retrieval/Image Based Information System (VICAR/IBIS)

NASA Technical Reports Server (NTRS)

Wherry, D. B.

1981-01-01

The acquisition, operation, and planning stages of installing a VICAR/IBIS system are described. The system operates in an IBM mainframe environment, and provides image processing of raster data. System support problems with software and documentation are discussed.

Integration of CBIR in radiological routine in accordance with IHE

NASA Astrophysics Data System (ADS)

Welter, Petra; Deserno, Thomas M.; Fischer, Benedikt; Wein, Berthold B.; Ott, Bastian; Günther, Rolf W.

2009-02-01

Increasing use of digital imaging processing leads to an enormous amount of imaging data. The access to picture archiving and communication systems (PACS), however, is solely textually, leading to sparse retrieval results because of ambiguous or missing image descriptions. Content-based image retrieval (CBIR) systems can improve the clinical diagnostic outcome significantly. However, current CBIR systems are not able to integrate their results with clinical workflow and PACS. Existing communication standards like DICOM and HL7 leave many options for implementation and do not ensure full interoperability. We present a concept of the standardized integration of a CBIR system for the radiology workflow in accordance with the Integrating the Healthcare Enterprise (IHE) framework. This is based on the IHE integration profile 'Post-Processing Workflow' (PPW) defining responsibilities as well as standardized communication and utilizing the DICOM Structured Report (DICOM SR). Because nowadays most of PACS and RIS systems are not yet fully IHE compliant to PPW, we also suggest an intermediate approach with the concepts of the CAD-PACS Toolkit. The integration is independent of the particular PACS and RIS system. Therefore, it supports the widespread application of CBIR in radiological routine. As a result, the approach is exemplarily applied to the Image Retrieval in Medical Applications (IRMA) framework.

Combining semantic technologies with a content-based image retrieval system - Preliminary considerations

NASA Astrophysics Data System (ADS)

Chmiel, P.; Ganzha, M.; Jaworska, T.; Paprzycki, M.

2017-10-01

Nowadays, as a part of systematic growth of volume, and variety, of information that can be found on the Internet, we observe also dramatic increase in sizes of available image collections. There are many ways to help users browsing / selecting images of interest. One of popular approaches are Content-Based Image Retrieval (CBIR) systems, which allow users to search for images that match their interests, expressed in the form of images (query by example). However, we believe that image search and retrieval could take advantage of semantic technologies. We have decided to test this hypothesis. Specifically, on the basis of knowledge captured in the CBIR, we have developed a domain ontology of residential real estate (detached houses, in particular). This allows us to semantically represent each image (and its constitutive architectural elements) represented within the CBIR. The proposed ontology was extended to capture not only the elements resulting from image segmentation, but also "spatial relations" between them. As a result, a new approach to querying the image database (semantic querying) has materialized, thus extending capabilities of the developed system.

Content Classification and Context-Based Retrieval System for E-Learning

ERIC Educational Resources Information Center

Mittal, Ankush; Krishnan, Pagalthivarthi V.; Altman, Edward

2006-01-01

A recent focus in web based learning systems has been the development of reusable learning materials that can be delivered as personalized courses depending of a number of factors such as the user's background, his/her learning preferences, current knowledge based on previous assessments, or previous browsing patterns. The student is often…

DICOM-compliant PACS with CD-based image archival

NASA Astrophysics Data System (ADS)

Cox, Robert D.; Henri, Christopher J.; Rubin, Richard K.; Bret, Patrice M.

1998-07-01

This paper describes the design and implementation of a low- cost PACS conforming to the DICOM 3.0 standard. The goal was to provide an efficient image archival and management solution on a heterogeneous hospital network as a basis for filmless radiology. The system follows a distributed, client/server model and was implemented at a fraction of the cost of a commercial PACS. It provides reliable archiving on recordable CD and allows access to digital images throughout the hospital and on the Internet. Dedicated servers have been designed for short-term storage, CD-based archival, data retrieval and remote data access or teleradiology. The short-term storage devices provide DICOM storage and query/retrieve services to scanners and workstations and approximately twelve weeks of 'on-line' image data. The CD-based archival and data retrieval processes are fully automated with the exception of CD loading and unloading. The system employs lossless compression on both short- and long-term storage devices. All servers communicate via the DICOM protocol in conjunction with both local and 'master' SQL-patient databases. Records are transferred from the local to the master database independently, ensuring that storage devices will still function if the master database server cannot be reached. The system features rules-based work-flow management and WWW servers to provide multi-platform remote data access. The WWW server system is distributed on the storage, retrieval and teleradiology servers allowing viewing of locally stored image data directly in a WWW browser without the need for data transfer to a central WWW server. An independent system monitors disk usage, processes, network and CPU load on each server and reports errors to the image management team via email. The PACS was implemented using a combination of off-the-shelf hardware, freely available software and applications developed in-house. The system has enabled filmless operation in CT, MR and ultrasound within the radiology department and throughout the hospital. The use of WWW technology has enabled the development of an intuitive we- based teleradiology and image management solution that provides complete access to image data.

42 CFR 433.116 - FFP for operation of mechanized claims processing and information retrieval systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... and information retrieval systems. 433.116 Section 433.116 Public Health CENTERS FOR MEDICARE... FISCAL ADMINISTRATION Mechanized Claims Processing and Information Retrieval Systems § 433.116 FFP for operation of mechanized claims processing and information retrieval systems. (a) Subject to paragraph (j) of...

7 CFR 277.18 - Establishment of an Automated Data Processing (ADP) and Information Retrieval System.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) and Information Retrieval System. 277.18 Section 277.18 Agriculture Regulations of the Department of... Data Processing (ADP) and Information Retrieval System. (a) Scope and application. This section... costs of planning, design, development or installation of ADP and information retrieval systems if the...

42 CFR 433.116 - FFP for operation of mechanized claims processing and information retrieval systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... and information retrieval systems. 433.116 Section 433.116 Public Health CENTERS FOR MEDICARE... FISCAL ADMINISTRATION Mechanized Claims Processing and Information Retrieval Systems § 433.116 FFP for operation of mechanized claims processing and information retrieval systems. (a) Subject to paragraph (j) of...

7 CFR 277.18 - Establishment of an Automated Data Processing (ADP) and Information Retrieval System.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) and Information Retrieval System. 277.18 Section 277.18 Agriculture Regulations of the Department of... Data Processing (ADP) and Information Retrieval System. (a) Scope and application. This section... costs of planning, design, development or installation of ADP and information retrieval systems if the...

42 CFR 433.116 - FFP for operation of mechanized claims processing and information retrieval systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... and information retrieval systems. 433.116 Section 433.116 Public Health CENTERS FOR MEDICARE... FISCAL ADMINISTRATION Mechanized Claims Processing and Information Retrieval Systems § 433.116 FFP for operation of mechanized claims processing and information retrieval systems. (a) Subject to paragraph (j) of...

7 CFR 277.18 - Establishment of an Automated Data Processing (ADP) and Information Retrieval System.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) and Information Retrieval System. 277.18 Section 277.18 Agriculture Regulations of the Department of... Data Processing (ADP) and Information Retrieval System. (a) Scope and application. This section... costs of planning, design, development or installation of ADP and information retrieval systems if the...

42 CFR 433.116 - FFP for operation of mechanized claims processing and information retrieval systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... and information retrieval systems. 433.116 Section 433.116 Public Health CENTERS FOR MEDICARE... FISCAL ADMINISTRATION Mechanized Claims Processing and Information Retrieval Systems § 433.116 FFP for operation of mechanized claims processing and information retrieval systems. (a) Subject to paragraph (j) of...

7 CFR 277.18 - Establishment of an Automated Data Processing (ADP) and Information Retrieval System.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) and Information Retrieval System. 277.18 Section 277.18 Agriculture Regulations of the Department of... Data Processing (ADP) and Information Retrieval System. (a) Scope and application. This section... costs of planning, design, development or installation of ADP and information retrieval systems if the...

Hydrogeologic correlations for selected wells on Long Island, New York; a data base with retrieval program

USGS Publications Warehouse

Buxton, H.T.; Shernoff, P.K.; Smolensky, D.A.

1989-01-01

Accurate delineation of the internal hydrogeologic structure of Long Island, NY is integral to the understanding and management of the groundwater system. This report presents a computerized data base of hydrogeologic correlations for 3,146 wells on Long Island and adjacent parts of New York City. The data base includes the well identification number, the latitude-longitude of the well location, the altitude of land surface at the well and of the bottom of the drilled hole, and the altitude of the top of the major hydrogeologic units penetrated by the well. A computer program is included that allows retrieval of selected types of data for all of, or any local area of, Long Island. These data retrievals are a valuable aid to the construction of hydrogeologic surface maps. (USGS)

First retrievals of MLT sodium profiles based on satellite sodium nightglow observations

NASA Astrophysics Data System (ADS)

Von Savigny, Christian; Zilker, Bianca; Langowski, Martin

2016-07-01

The Na D lines are a well known feature of the terrestrial airglow and have been identified for the first time in 1929. During the daytime the Na airglow emission is caused by resonance fluorescence, while during the night the excitation occurs by chemiluminescent reactions. Knowledge of Na in the mesopause region is of interest, because the Na layer is thought to be maintained by meteoric ablation and Na measurements allow constraining the meteoric mass influx into the Earth system. In this contribution we employ SCIAMACHY/Envisat nighttime limb measurements of the Na D-line airglow from fall 2002 to spring 2012 - in combination with photochemical models - in order to retrieve Na concentration profiles in the 75 - 100 km altitude range. The Na profiles show realistic peak altitudes, number densities and seasonal variations. The retrieval scheme, sample results and comparisons to ground-based LIDAR measurements of Na as well as SCIAMACHY daytime retrievals will be presented. Moreover, uncertainties in the assumed photochemical scheme and their impact on the Na retrievals will be discussed.

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Information content and sensitivity of the 3β + 2α lidar measurement system for aerosol microphysical retrievals

NASA Astrophysics Data System (ADS)

Burton, Sharon P.; Chemyakin, Eduard; Liu, Xu; Knobelspiesse, Kirk; Stamnes, Snorre; Sawamura, Patricia; Moore, Richard H.; Hostetler, Chris A.; Ferrare, Richard A.

2016-11-01

There is considerable interest in retrieving profiles of aerosol effective radius, total number concentration, and complex refractive index from lidar measurements of extinction and backscatter at several wavelengths. The combination of three backscatter channels plus two extinction channels (3β + 2α) is particularly important since it is believed to be the minimum configuration necessary for the retrieval of aerosol microphysical properties and because the technological readiness of lidar systems permits this configuration on both an airborne and future spaceborne instrument. The second-generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) has been making 3β + 2α measurements since 2012. The planned NASA Aerosol/Clouds/Ecosystems (ACE) satellite mission also recommends the 3β + 2α combination.Here we develop a deeper understanding of the information content and sensitivities of the 3β + 2α system in terms of aerosol microphysical parameters of interest. We use a retrieval-free methodology to determine the basic sensitivities of the measurements independent of retrieval assumptions and constraints. We calculate information content and uncertainty metrics using tools borrowed from the optimal estimation methodology based on Bayes' theorem, using a simplified forward model look-up table, with no explicit inversion. The forward model is simplified to represent spherical particles, monomodal log-normal size distributions, and wavelength-independent refractive indices. Since we only use the forward model with no retrieval, the given simplified aerosol scenario is applicable as a best case for all existing retrievals in the absence of additional constraints. Retrieval-dependent errors due to mismatch between retrieval assumptions and true atmospheric aerosols are not included in this sensitivity study, and neither are retrieval errors that may be introduced in the inversion process. The choice of a simplified model adds clarity to the understanding of the uncertainties in such retrievals, since it allows for separately assessing the sensitivities and uncertainties of the measurements alone that cannot be corrected by any potential or theoretical improvements to retrieval methodology but must instead be addressed by adding information content.The sensitivity metrics allow for identifying (1) information content of the measurements vs. a priori information; (2) error bars on the retrieved parameters; and (3) potential sources of cross-talk or "compensating" errors wherein different retrieval parameters are not independently captured by the measurements. The results suggest that the 3β + 2α measurement system is underdetermined with respect to the full suite of microphysical parameters considered in this study and that additional information is required, in the form of additional coincident measurements (e.g., sun-photometer or polarimeter) or a priori retrieval constraints. A specific recommendation is given for addressing cross-talk between effective radius and total number concentration.

Wavelet optimization for content-based image retrieval in medical databases.

PubMed

Quellec, G; Lamard, M; Cazuguel, G; Cochener, B; Roux, C

2010-04-01

We propose in this article a content-based image retrieval (CBIR) method for diagnosis aid in medical fields. In the proposed system, images are indexed in a generic fashion, without extracting domain-specific features: a signature is built for each image from its wavelet transform. These image signatures characterize the distribution of wavelet coefficients in each subband of the decomposition. A distance measure is then defined to compare two image signatures and thus retrieve the most similar images in a database when a query image is submitted by a physician. To retrieve relevant images from a medical database, the signatures and the distance measure must be related to the medical interpretation of images. As a consequence, we introduce several degrees of freedom in the system so that it can be tuned to any pathology and image modality. In particular, we propose to adapt the wavelet basis, within the lifting scheme framework, and to use a custom decomposition scheme. Weights are also introduced between subbands. All these parameters are tuned by an optimization procedure, using the medical grading of each image in the database to define a performance measure. The system is assessed on two medical image databases: one for diabetic retinopathy follow up and one for screening mammography, as well as a general purpose database. Results are promising: a mean precision of 56.50%, 70.91% and 96.10% is achieved for these three databases, when five images are returned by the system. Copyright 2009 Elsevier B.V. All rights reserved.

Selecting Data-Base Management Software for Microcomputers in Libraries and Information Units.

ERIC Educational Resources Information Center

Pieska, K. A. O.

1986-01-01

Presents a model for the evaluation of database management systems software from the viewpoint of librarians and information specialists. The properties of data management systems, database management systems, and text retrieval systems are outlined and compared. (10 references) (CLB)

Rough case-based reasoning system for continues casting

NASA Astrophysics Data System (ADS)

Su, Wenbin; Lei, Zhufeng

2018-04-01

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

42 CFR 433.116 - FFP for operation of mechanized claims processing and information retrieval systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... and information retrieval systems. 433.116 Section 433.116 Public Health CENTERS FOR MEDICARE... FISCAL ADMINISTRATION Mechanized Claims Processing and Information Retrieval Systems § 433.116 FFP for operation of mechanized claims processing and information retrieval systems. (a) Subject to 42 CFR 433.113(c...

SPIRES (Stanford Public Information Retrieval System) 1970-71 Annual Report.

ERIC Educational Resources Information Center

Parker, Edwin B.

SPIRES (Stanford Public Information REtrieval System) is a computer information storage and retrieval system being developed at Stanford University with funding from the National Science Foundation. SPIRES has two major goals: to provide a user-oriented, interactive, on-line retrieval system for a variety of researchers at Stanford; and to support…

Implementing a distributed intranet-based information system.

PubMed

O'Kane, K C; McColligan, E E; Davis, G A

1996-11-01

The article discusses Internet and intranet technologies and describes how to install an intranet-based information system using the Merle language facility and other readily available components. Merle is a script language designed to support decentralized medical record information retrieval applications on the World Wide Web. The goal of this work is to provide a script language tool to facilitate construction of efficient, fully functional, multipoint medical record information systems that can be accessed anywhere by low-cost Web browsers to search, retrieve, and analyze patient information. The language allows legacy MUMPS applications to function in a Web environment and to make use of the Web graphical, sound, and video presentation services. It also permits downloading of script applets for execution on client browsers, and it can be used in standalone mode with the Unix, Windows 95, Windows NT, and OS/2 operating systems.

Implementation of a thesaurus in an electronic photograph imaging system

NASA Astrophysics Data System (ADS)

Partlow, Denise

1995-11-01

A photograph imaging system presents a unique set of requirements for indexing and retrieving images, unlike a standard imaging system for written documents. This paper presents the requirements, technical design, and development results for a hierarchical ANSI standard thesaurus embedded into a photograph archival system. The thesaurus design incorporates storage reduction techniques, permits fast searches, and contains flexible indexing methods. It can be extended to many applications other than the retrieval of photographs. When photographic images are indexed into an electronic system, they are subject to a variety of indexing problems based on what the indexer `sees.' For instance, the indexer may categorize an image as a boat when others might refer to it as a ship, sailboat, or raft. The thesaurus will allow a user to locate images containing any synonym for boat, regardless of how the image was actually indexed. In addition to indexing problems, photos may need to be retrieved based on a broad category, for instance, flowers. The thesaurus allows a search for `flowers' to locate all images containing a rose, hibiscus, or daisy, yet still allow a specific search for an image containing only a rose. The technical design and method of implementation for such a thesaurus is presented. The thesaurus is implemented using an SQL relational data base management system that supports blobs, binary large objects. The design incorporates unique compression methods for storing the thesaurus words. Words are indexed to photographs using the compressed word and allow for very rapid searches, eliminating lengthy string matches.

Multiple capture locations for 3D ultrasound-guided robotic retrieval of moving bodies from a beating heart

NASA Astrophysics Data System (ADS)

Thienphrapa, Paul; Ramachandran, Bharat; Elhawary, Haytham; Taylor, Russell H.; Popovic, Aleksandra

2012-02-01

Free moving bodies in the heart pose a serious health risk as they may be released in the arteries causing blood flow disruption. These bodies may be the result of various medical conditions and trauma. The conventional approach to removing these objects involves open surgery with sternotomy, the use of cardiopulmonary bypass, and a wide resection of the heart muscle. We advocate a minimally invasive surgical approach using a flexible robotic end effector guided by 3D transesophageal echocardiography. In a phantom study, we track a moving body in a beating heart using a modified normalized cross-correlation method, with mean RMS errors of 2.3 mm. We previously found the foreign body motion to be fast and abrupt, rendering infeasible a retrieval method based on direct tracking. We proposed a strategy based on guiding a robot to the most spatially probable location of the fragment and securing it upon its reentry to said location. To improve efficacy in the context of a robotic retrieval system, we extend this approach by exploring multiple candidate capture locations. Salient locations are identified based on spatial probability, dwell time, and visit frequency; secondary locations are also examined. Aggregate results indicate that the location of highest spatial probability (50% occupancy) is distinct from the longest-dwelled location (0.84 seconds). Such metrics are vital in informing the design of a retrieval system and capture strategies, and they can be computed intraoperatively to select the best capture location based on constraints such as workspace, time, and device manipulability. Given the complex nature of fragment motion, the ability to analyze multiple capture locations is a desirable capability in an interventional system.

A General Uncertainty Quantification Methodology for Cloud Microphysical Property Retrievals

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

The Earth System Science Pathfinder Orbiting Carbon Observatory (OCO) Mission

NASA Technical Reports Server (NTRS)

Crisp, David

2003-01-01

A viewgraph presentation describing the Earth System Science Pathfinder Orbiting Carbon Observatory (OCO) Mission is shown. The contents include: 1) Why CO2?; 2) What Processes Control CO2 Sinks?; 3) OCO Science Team; 4) Space-Based Measurements of CO2; 5) Driving Requirement: Precise, Bias-Free Global Measurements; 6) Making Precise CO2 Measurements from Space; 7) OCO Spatial Sampling Strategy; 8) OCO Observing Modes; 9) Implementation Approach; 10) The OCO Instrument; 11) The OCO Spacecraft; 12) OCO Will Fly in the A-Train; 13) Validation Program Ensures Accuracy and Minimizes Spatially Coherent Biases; 14) Can OCO Provide the Required Precision?; 15) O2 Column Retrievals with Ground-based FTS; 16) X(sub CO2) Retrieval Simulations; 17) Impact of Albedo and Aerosol Uncertainty on X(sub CO2) Retrievals; 18) Carbon Cycle Modeling Studies: Seasonal Cycle; 19) Carbon Cycle Modeling Studies: The North-South Gradient in CO2; 20) Carbon Cycle Modeling Studies: Effect of Diurnal Biases; 21) Project Status and Schedule; and 22) Summary.

Quantifying the sensitivity of aerosol optical depths retrieved from MSG SEVIRI to a priori data

NASA Astrophysics Data System (ADS)

Bulgin, C. E.; Palmer, P. I.; Merchant, C. J.; Siddans, R.; Poulsen, C.; Grainger, R. G.; Thomas, G.; Carboni, E.; McConnell, C.; Highwood, E.

2009-12-01

Radiative forcing contributions from aerosol direct and indirect effects remain one of the most uncertain components of the climate system. Satellite observations of aerosol optical properties offer important constraints on atmospheric aerosols but their sensitivity to prior assumptions must be better characterized before they are used effectively to reduce uncertainty in aerosol radiative forcing. We assess the sensitivity of the Oxford-RAL Aerosol and Cloud (ORAC) optimal estimation retrieval of aerosol optical depth (AOD) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) to a priori aerosol data. SEVIRI is a geostationary satellite instrument centred over Africa and the neighbouring Atlantic Ocean, routinely sampling desert dust and biomass burning outflow from Africa. We quantify the uncertainty in SEVIRI AOD retrievals in the presence of desert dust by comparing retrievals that use prior information from the Optical Properties of Aerosol and Cloud (OPAC) database, with those that use measured aerosol properties during the Dust Outflow and Deposition to the Ocean (DODO) aircraft campaign (August, 2006). We also assess the sensitivity of retrieved AODs to changes in solar zenith angle, and the vertical profile of aerosol effective radius and extinction coefficient input into the retrieval forward model. Currently the ORAC retrieval scheme retrieves AODs for five aerosol types (desert dust, biomass burning, maritime, urban and continental) and chooses the most appropriate AOD based on the cost functions. We generate an improved prior aerosol speciation database for SEVIRI based on a statistical analysis of a Saharan Dust Index (SDI) determined using variances of different brightness temperatures, and organic and black carbon tracers from the GEOS-Chem chemistry transport model. This database is described as a function of season and time of day. We quantify the difference in AODs between those chosen based on prior information from the SDI and GEOS-Chem and those chosen based on the smallest cost function.

Potential for Hospital Based Corneal Retreival in Hassan District Hospital

PubMed Central

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

2015-01-01

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

Audio-guided audiovisual data segmentation, indexing, and retrieval

NASA Astrophysics Data System (ADS)

Zhang, Tong; Kuo, C.-C. Jay

1998-12-01

While current approaches for video segmentation and indexing are mostly focused on visual information, audio signals may actually play a primary role in video content parsing. In this paper, we present an approach for automatic segmentation, indexing, and retrieval of audiovisual data, based on audio content analysis. The accompanying audio signal of audiovisual data is first segmented and classified into basic types, i.e., speech, music, environmental sound, and silence. This coarse-level segmentation and indexing step is based upon morphological and statistical analysis of several short-term features of the audio signals. Then, environmental sounds are classified into finer classes, such as applause, explosions, bird sounds, etc. This fine-level classification and indexing step is based upon time- frequency analysis of audio signals and the use of the hidden Markov model as the classifier. On top of this archiving scheme, an audiovisual data retrieval system is proposed. Experimental results show that the proposed approach has an accuracy rate higher than 90 percent for the coarse-level classification, and higher than 85 percent for the fine-level classification. Examples of audiovisual data segmentation and retrieval are also provided.

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

PubMed

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

2017-12-11

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

An object-oriented programming system for the integration of internet-based bioinformatics resources.

PubMed

Beveridge, Allan

2006-01-01

The Internet consists of a vast inhomogeneous reservoir of data. Developing software that can integrate a wide variety of different data sources is a major challenge that must be addressed for the realisation of the full potential of the Internet as a scientific research tool. This article presents a semi-automated object-oriented programming system for integrating web-based resources. We demonstrate that the current Internet standards (HTML, CGI [common gateway interface], Java, etc.) can be exploited to develop a data retrieval system that scans existing web interfaces and then uses a set of rules to generate new Java code that can automatically retrieve data from the Web. The validity of the software has been demonstrated by testing it on several biological databases. We also examine the current limitations of the Internet and discuss the need for the development of universal standards for web-based data.

Efficient Caption-Based Retrieval of Multimedia Information

DTIC Science & Technology

1993-10-09

in the design of transportable natural language interfaces. Artifcial Intelligence , 32 (1987), 173-243. - 13- (101 Jones, M. and Eisner, J. A...systems for multimedia data . They exploit captions on the data and perform natural-language processing of them and English retrieval requests. Some...content analysis of the data is also performed to obtain additional descriptive information. The key to getting this approach to work is sufficiently

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Three dimensional single molecule localization using a phase retrieved pupilfunction

PubMed Central

Liu, Sheng; Kromann, Emil B.; Krueger, Wesley D.; Bewersdorf, Joerg; Lidke, Keith A.

2013-01-01

Localization-based superresolution imaging is dependent on finding the positions of individualfluorophores in a sample by fitting the observed single-molecule intensity pattern to the microscopepoint spread function (PSF). For three-dimensional imaging, system-specific aberrations of theoptical system can lead to inaccurate localizations when the PSF model does not account for theseaberrations. Here we describe the use of phase-retrieved pupil functions to generate a more accuratePSF and therefore more accurate 3D localizations. The complex-valued pupil function containsinformation about the system-specific aberrations and can thus be used to generate the PSF forarbitrary defocus. Further, it can be modified to include depth dependent aberrations. We describethe phase retrieval process, the method for including depth dependent aberrations, and a fastfitting algorithm using graphics processing units. The superior localization accuracy of the pupilfunction generated PSF is demonstrated with dual focal plane 3D superresolution imaging ofbiological structures. PMID:24514501

An Intelligent Pictorial Information System

NASA Astrophysics Data System (ADS)

Lee, Edward T.; Chang, B.

1987-05-01

In examining the history of computer application, we discover that early computer systems were developed primarily for applications related to scientific computation, as in weather prediction, aerospace applications, and nuclear physics applications. At this stage, the computer system served as a big calculator to perform, in the main, manipulation of numbers. Then it was found that computer systems could also be used for business applications, information storage and retrieval, word processing, and report generation. The history of computer application is summarized in Table I. The complexity of pictures makes picture processing much more difficult than number and alphanumerical processing. Therefore, new techniques, new algorithms, and above all, new pictorial knowledge, [1] are needed to overcome the limitatins of existing computer systems. New frontiers in designing computer systems are the ways to handle the representation,[2,3] classification, manipulation, processing, storage, and retrieval of pictures. Especially, the ways to deal with similarity measures and the meaning of the word "approximate" and the phrase "approximate reasoning" are an important and an indispensable part of an intelligent pictorial information system. [4,5] The main objective of this paper is to investigate the mathematical foundation for the effective organization and efficient retrieval of pictures in similarity-directed pictorial databases, [6] based on similarity retrieval techniques [7] and fuzzy languages [8]. The main advantage of this approach is that similar pictures are stored logically close to each other by using quantitative similarity measures. Thus, for answering queries, the amount of picture data needed to be searched can be reduced and the retrieval time can be improved. In addition, in a pictorial database, very often it is desired to find pictures (or feature vectors, histograms, etc.) that are most similar to or most dissimilar [9] to a test picture (or feature vector). Using similarity measures, one can not only store similar pictures logically or physically close to each other in order to improve retrieval or updating efficiency, one can also use such similarity measures to answer fuzzy queries involving nonexact retrieval conditions. In this paper, similarity directed pictorial databases involving geometric figures, chromosome images, [10] leukocyte images, cardiomyopathy images, and satellite images [11] are presented as illustrative examples.

Requirements for SPIRES II. An External Specification for the Stanford Public Information Retrieval System.

ERIC Educational Resources Information Center

Parker, Edwin B.

SPIRES (Stanford Public Information Retrieval System) is a computerized information storage and retrieval system intended for use by students and faculty members who have little knowledge of computers but who need rapid and sophisticated retrieval and analysis. The functions and capabilities of the system from the user's point of view are…

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

MPEG-7 audio-visual indexing test-bed for video retrieval

NASA Astrophysics Data System (ADS)

Gagnon, Langis; Foucher, Samuel; Gouaillier, Valerie; Brun, Christelle; Brousseau, Julie; Boulianne, Gilles; Osterrath, Frederic; Chapdelaine, Claude; Dutrisac, Julie; St-Onge, Francis; Champagne, Benoit; Lu, Xiaojian

2003-12-01

This paper reports on the development status of a Multimedia Asset Management (MAM) test-bed for content-based indexing and retrieval of audio-visual documents within the MPEG-7 standard. The project, called "MPEG-7 Audio-Visual Document Indexing System" (MADIS), specifically targets the indexing and retrieval of video shots and key frames from documentary film archives, based on audio-visual content like face recognition, motion activity, speech recognition and semantic clustering. The MPEG-7/XML encoding of the film database is done off-line. The description decomposition is based on a temporal decomposition into visual segments (shots), key frames and audio/speech sub-segments. The visible outcome will be a web site that allows video retrieval using a proprietary XQuery-based search engine and accessible to members at the Canadian National Film Board (NFB) Cineroute site. For example, end-user will be able to ask to point on movie shots in the database that have been produced in a specific year, that contain the face of a specific actor who tells a specific word and in which there is no motion activity. Video streaming is performed over the high bandwidth CA*net network deployed by CANARIE, a public Canadian Internet development organization.

iSMART: Ontology-based Semantic Query of CDA Documents

PubMed Central

Liu, Shengping; Ni, Yuan; Mei, Jing; Li, Hanyu; Xie, Guotong; Hu, Gang; Liu, Haifeng; Hou, Xueqiao; Pan, Yue

2009-01-01

The Health Level 7 Clinical Document Architecture (CDA) is widely accepted as the format for electronic clinical document. With the rich ontological references in CDA documents, the ontology-based semantic query could be performed to retrieve CDA documents. In this paper, we present iSMART (interactive Semantic MedicAl Record reTrieval), a prototype system designed for ontology-based semantic query of CDA documents. The clinical information in CDA documents will be extracted into RDF triples by a declarative XML to RDF transformer. An ontology reasoner is developed to infer additional information by combining the background knowledge from SNOMED CT ontology. Then an RDF query engine is leveraged to enable the semantic queries. This system has been evaluated using the real clinical documents collected from a large hospital in southern China. PMID:20351883

CONTRACT ADMINISTRATIVE TRACKING SYSTEM (CATS)

EPA Science Inventory

The Contract Administrative Tracking System (CATS) was developed in response to an ORD NHEERL, Mid-Continent Ecology Division (MED)-recognized need for an automated tracking and retrieval system for Cost Reimbursable Level of Effort (CR/LOE) Contracts. CATS is an Oracle-based app...

Towards case-based medical learning in radiological decision making using content-based image retrieval

PubMed Central

2011-01-01

Background Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. Methods We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. Results We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. Conclusions The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer. PMID:22032775

Towards case-based medical learning in radiological decision making using content-based image retrieval.

PubMed

Welter, Petra; Deserno, Thomas M; Fischer, Benedikt; Günther, Rolf W; Spreckelsen, Cord

2011-10-27

Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer.

Schematic memory components converge within angular gyrus during retrieval

PubMed Central

Wagner, Isabella C; van Buuren, Mariët; Kroes, Marijn CW; Gutteling, Tjerk P; van der Linden, Marieke; Morris, Richard G; Fernández, Guillén

2015-01-01

Mental schemas form associative knowledge structures that can promote the encoding and consolidation of new and related information. Schemas are facilitated by a distributed system that stores components separately, presumably in the form of inter-connected neocortical representations. During retrieval, these components need to be recombined into one representation, but where exactly such recombination takes place is unclear. Thus, we asked where different schema components are neuronally represented and converge during retrieval. Subjects acquired and retrieved two well-controlled, rule-based schema structures during fMRI on consecutive days. Schema retrieval was associated with midline, medial-temporal, and parietal processing. We identified the multi-voxel representations of different schema components, which converged within the angular gyrus during retrieval. Critically, convergence only happened after 24-hour-consolidation and during a transfer test where schema material was applied to novel but related trials. Therefore, the angular gyrus appears to recombine consolidated schema components into one memory representation. DOI: http://dx.doi.org/10.7554/eLife.09668.001 PMID:26575291

Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

1999-01-01

This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Adaptation of reference volumes for correlation-based digital holographic particle tracking

NASA Astrophysics Data System (ADS)

Hesseling, Christina; Peinke, Joachim; Gülker, Gerd

2018-04-01

Numerically reconstructed reference volumes tailored to particle images are used for particle position detection by means of three-dimensional correlation. After a first tracking of these positions, the experimentally recorded particle images are retrieved as a posteriori knowledge about the particle images in the system. This knowledge is used for a further refinement of the detected positions. A transparent description of the individual algorithm steps including the results retrieved with experimental data complete the paper. The work employs extraordinarily small particles, smaller than the pixel pitch of the camera sensor. It is the first approach known to the authors that combines numerical knowledge about particle images and particle images retrieved from the experimental system to an iterative particle tracking approach for digital holographic particle tracking velocimetry.

Global Interior Robot Localisation by a Colour Content Image Retrieval System

NASA Astrophysics Data System (ADS)

Chaari, A.; Lelandais, S.; Montagne, C.; Ahmed, M. Ben

2007-12-01

We propose a new global localisation approach to determine a coarse position of a mobile robot in structured indoor space using colour-based image retrieval techniques. We use an original method of colour quantisation based on the baker's transformation to extract a two-dimensional colour pallet combining as well space and vicinity-related information as colourimetric aspect of the original image. We conceive several retrieving approaches bringing to a specific similarity measure [InlineEquation not available: see fulltext.] integrating the space organisation of colours in the pallet. The baker's transformation provides a quantisation of the image into a space where colours that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image. Whereas the distance [InlineEquation not available: see fulltext.] provides for partial invariance to translation, sight point small changes, and scale factor. In addition to this study, we developed a hierarchical search module based on the logic classification of images following rooms. This hierarchical module reduces the searching indoor space and ensures an improvement of our system performances. Results are then compared with those brought by colour histograms provided with several similarity measures. In this paper, we focus on colour-based features to describe indoor images. A finalised system must obviously integrate other type of signature like shape and texture.

Novel Algorithm for Classification of Medical Images

NASA Astrophysics Data System (ADS)

Bhushan, Bharat; Juneja, Monika

2010-11-01

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

Proper name retrieval in temporal lobe epilepsy: naming of famous faces and landmarks.

PubMed

Benke, Thomas; Kuen, Eva; Schwarz, Michael; Walser, Gerald

2013-05-01

The objective of this study was to further explore proper name (PN) retrieval and conceptual knowledge in patients with left and right temporal lobe epilepsy (69 patients with LTLE and 62 patients with RTLE) using a refined assessment procedure. Based on the performance of a large group of age- and education-matched normals, a new test of famous faces and famous landmarks was designed. Recognition, naming, and semantic knowledge were assessed consecutively, allowing for a better characterization of deficient levels in the naming system. Impairment in PN retrieval was common in the cohort with TLE. Furthermore, side of seizure onset impaired stages of name retrieval differently: LTLE impaired the lexico-phonological processing, whereas RTLE mainly impaired the perceptual-semantic stage of object recognition. In addition to deficient PN retrieval, patients with TLE had reduced conceptual knowledge regarding famous persons and landmarks. Copyright © 2013 Elsevier Inc. All rights reserved.

Video PATSEARCH: A Mixed-Media System.

ERIC Educational Resources Information Center

Schulman, Jacque-Lynne

1982-01-01

Describes a videodisc-based information display system in which a computer terminal is used to search the online PATSEARCH database from a remote host with local microcomputer control to select and display drawings from the retrieved records. System features and system components are discussed and criteria for system evaluation are presented.…

Ontology-guided organ detection to retrieve web images of disease manifestation: towards the construction of a consumer-based health image library.

PubMed

Chen, Yang; Ren, Xiaofeng; Zhang, Guo-Qiang; Xu, Rong

2013-01-01

Visual information is a crucial aspect of medical knowledge. Building a comprehensive medical image base, in the spirit of the Unified Medical Language System (UMLS), would greatly benefit patient education and self-care. However, collection and annotation of such a large-scale image base is challenging. To combine visual object detection techniques with medical ontology to automatically mine web photos and retrieve a large number of disease manifestation images with minimal manual labeling effort. As a proof of concept, we first learnt five organ detectors on three detection scales for eyes, ears, lips, hands, and feet. Given a disease, we used information from the UMLS to select affected body parts, ran the pretrained organ detectors on web images, and combined the detection outputs to retrieve disease images. Compared with a supervised image retrieval approach that requires training images for every disease, our ontology-guided approach exploits shared visual information of body parts across diseases. In retrieving 2220 web images of 32 diseases, we reduced manual labeling effort to 15.6% while improving the average precision by 3.9% from 77.7% to 81.6%. For 40.6% of the diseases, we improved the precision by 10%. The results confirm the concept that the web is a feasible source for automatic disease image retrieval for health image database construction. Our approach requires a small amount of manual effort to collect complex disease images, and to annotate them by standard medical ontology terms.

Techniques for Soundscape Retrieval and Synthesis

NASA Astrophysics Data System (ADS)

Mechtley, Brandon Michael

The study of acoustic ecology is concerned with the manner in which life interacts with its environment as mediated through sound. As such, a central focus is that of the soundscape: the acoustic environment as perceived by a listener. This dissertation examines the application of several computational tools in the realms of digital signal processing, multimedia information retrieval, and computer music synthesis to the analysis of the soundscape. Namely, these tools include a) an open source software library, Sirens, which can be used for the segmentation of long environmental field recordings into individual sonic events and compare these events in terms of acoustic content, b) a graph-based retrieval system that can use these measures of acoustic similarity and measures of semantic similarity using the lexical database WordNet to perform both text-based retrieval and automatic annotation of environmental sounds, and c) new techniques for the dynamic, realtime parametric morphing of multiple field recordings, informed by the geographic paths along which they were recorded.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Multi-view information fusion for automatic BI-RADS description of mammographic masses

NASA Astrophysics Data System (ADS)

Narvaez, Fabián; Díaz, Gloria; Romero, Eduardo

2011-03-01

Most CBIR-based CAD systems (Content Based Image Retrieval systems for Computer Aided Diagnosis) identify lesions that are eventually relevant. These systems base their analysis upon a single independent view. This article presents a CBIR framework which automatically describes mammographic masses with the BI-RADS lexicon, fusing information from the two mammographic views. After an expert selects a Region of Interest (RoI) at the two views, a CBIR strategy searches similar masses in the database by automatically computing the Mahalanobis distance between shape and texture feature vectors of the mammography. The strategy was assessed in a set of 400 cases, for which the suggested descriptions were compared with the ground truth provided by the data base. Two information fusion strategies were evaluated, allowing a retrieval precision rate of 89.6% in the best scheme. Likewise, the best performance obtained for shape, margin and pathology description, using a ROC methodology, was reported as AUC = 0.86, AUC = 0.72 and AUC = 0.85, respectively.

Development of an Automated Emergency Response System (AERS) for Rail Transit Systems

DOT National Transportation Integrated Search

1984-10-01

As a result of a fire in 1979 at the Bay Area Rapid Transit District (BART), a microprocessor-based information retrieval system was developed to aid in the emergency decision-making process. This system was proposed, designed and programmed by a sup...

Toward an Episodic Context Account of Retrieval-Based Learning: Dissociating Retrieval Practice and Elaboration

ERIC Educational Resources Information Center

Lehman, Melissa; Smith, Megan A.; Karpicke, Jeffrey D.

2014-01-01

We tested the predictions of 2 explanations for retrieval-based learning; while the elaborative retrieval hypothesis assumes that the retrieval of studied information promotes the generation of semantically related information, which aids in later retrieval (Carpenter, 2009), the episodic context account proposed by Karpicke, Lehman, and Aue (in…

Web Mining for Web Image Retrieval.

ERIC Educational Resources Information Center

Chen, Zheng; Wenyin, Liu; Zhang, Feng; Li, Mingjing; Zhang, Hongjiang

2001-01-01

Presents a prototype system for image retrieval from the Internet using Web mining. Discusses the architecture of the Web image retrieval prototype; document space modeling; user log mining; and image retrieval experiments to evaluate the proposed system. (AEF)

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

2013-01-01

Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

Psychophysical experiments on the PicHunter image retrieval system

NASA Astrophysics Data System (ADS)

Papathomas, Thomas V.; Cox, Ingemar J.; Yianilos, Peter N.; Miller, Matt L.; Minka, Thomas P.; Conway, Tiffany E.; Ghosn, Joumana

2001-01-01

Psychophysical experiments were conducted on PicHunter, a content-based image retrieval (CBIR) experimental prototype with the following properties: (1) Based on a model of how users respond, it uses Bayes's rule to predict what target users want, given their actions. (2) It possesses an extremely simple user interface. (3) It employs an entropy- based scheme to improve convergence. (4) It introduces a paradigm for assessing the performance of CBIR systems. Experiments 1-3 studied human judgment of image similarity to obtain data for the model. Experiment 4 studied the importance of using: (a) semantic information, (b) memory of earlier input, and (c) relative and absolute judgments of similarity. Experiment 5 tested an approach that we propose for comparing performances of CBIR systems objectively. Finally, experiment 6 evaluated the most informative display-updating scheme that is based on entropy minimization, and confirmed earlier simulation results. These experiments represent one of the first attempts to quantify CBIR performance based on psychophysical studies, and they provide valuable data for improving CBIR algorithms. Even though they were designed with PicHunter in mind, their results can be applied to any CBIR system and, more generally, to any system that involves judgment of image similarity by humans.

Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM

NASA Astrophysics Data System (ADS)

Beltrán-Abaunza, J. M.; Kratzer, S.; Brockmann, C.

2013-11-01

In this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using 4 different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system (http.vattenkvalitet.se). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improve the retrieval of spectral reflectance for all processors, Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18-26.5%, dependent on the compared pairs, were obtained. At low chlorophyll concentrations (< 2.5 mg m-3), random errors dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and random errors were obtained with MEGS for suspended particulate matter, for which overestimations in te range of 8-16% were found. Only the FUB retrieved CDOM (Coloured Dissolved Organic Matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a~local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjärden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in presence of high CDOM attenuation.

Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM

NASA Astrophysics Data System (ADS)

Beltrán-Abaunza, J. M.; Kratzer, S.; Brockmann, C.

2014-05-01

In this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using four different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system (http://vattenkvalitet.se). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improves the retrieval of spectral reflectance for all processors. Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18-26.5%, dependent on the compared pairs, were obtained. At low chlorophyll concentrations (< 2.5 mg m-3), data dispersion dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and data dispersion were obtained with MEGS for suspended particulate matter, for which overestimations in the range of 8-16% were found. Only the FUB retrieved CDOM (coloured dissolved organic matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjärden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in the presence of high CDOM attenuation.

Retrieval System for Calcined Waste for the Idaho Cleanup Project - 12104

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

Eastman, Randy L.; Johnston, Beau A.; Lower, Danielle E.

This paper describes the conceptual approach to retrieve radioactive calcine waste, hereafter called calcine, from stainless steel storage bins contained within concrete vaults. The retrieval system will allow evacuation of the granular solids (calcine) from the storage bins through the use of stationary vacuum nozzles. The nozzles will use air jets for calcine fluidization and will be able to rotate and direct the fluidization or displacement of the calcine within the bin. Each bin will have a single retrieval system installed prior to operation to prevent worker exposure to the high radiation fields. The addition of an articulated camera armmore » will allow for operations monitoring and will be equipped with contingency tools to aid in calcine removal. Possible challenges (calcine bridging and rat-holing) associated with calcine retrieval and transport, including potential solutions for bin pressurization, calcine fluidization and waste confinement, are also addressed. The Calcine Disposition Project has the responsibility to retrieve, treat, and package HLW calcine. The calcine retrieval system has been designed to incorporate the functions and technical characteristics as established by the retrieval system functional analysis. By adequately implementing the highest ranking technical characteristics into the design of the retrieval system, the system will be able to satisfy the functional requirements. The retrieval system conceptual design provides the means for removing bulk calcine from the bins of the CSSF vaults. Top-down vacuum retrieval coupled with an articulating camera arm will allow for a robust, contained process capable of evacuating bulk calcine from bins and transporting it to the processing facility. The system is designed to fluidize, vacuum, transport and direct the calcine from its current location to the CSSF roof-top transport lines. An articulating camera arm, deployed through an adjacent access riser, will work in conjunction with the retrieval nozzle to aid in calcine fluidization, remote viewing, clumped calcine breaking and recovery from off-normal conditions. As the design of the retrieval system progresses from conceptual to preliminary, increasing attention will be directed toward detailed design and proof-of- concept testing. (authors)« less

Enhancing the Retrieval Effectiveness of Large Information Systems. Final Report for the Period 1 June 1975-31 December 1976.

ERIC Educational Resources Information Center

Becker, David S.; Pyrce, Sharon R.

The goal of this project was to find ways of enhancing the efficiency of searching machine readable data bases. Ways are sought to transfer to the computer some of the tasks that are normally performed by the user, i.e., to further automate information retrieval. Four experiments were conducted to test the feasibility of a sequential processing…

Large Scale Hierarchical K-Means Based Image Retrieval With MapReduce

DTIC Science & Technology

2014-03-27

hadoop distributed file system: Architecture and design, 2007. [10] G. Bradski. Dr. Dobb’s Journal of Software Tools, 2000. [11] Terry Costlow. Big data ...million images running on 20 virtual machines are shown. 15. SUBJECT TERMS Image Retrieval, MapReduce, Hierarchical K-Means, Big Data , Hadoop U U U UU 87...13 2.1.1.2 HDFS Data Representation . . . . . . . . . . . . . . . . 14 2.1.1.3 Hadoop Engine

Multisensor Retrieval of Atmospheric Properties.

NASA Astrophysics Data System (ADS)

Boba Stankov, B.

1998-09-01

A new method, Multisensor Retrieval of Atmospheric Properties (MRAP), is presented for deriving vertical profiles of atmospheric parameters throughout the troposphere. MRAP integrates measurements from multiple, diverse, remote sensing, and in situ instruments, the combination of which provides better capabilities than any instrument alone. Since remote sensors can deliver measurements automatically and continuously with high time resolution, MRAP provides better coverage than traditional rawinsondes. MRAP's design is flexible, being capable of incorporating measurements from different instruments in order to take advantage of new or developing advanced sensor technology. Furthermore, new or alternative atmospheric parameters for a variety of applications may be easily added as products of MRAP.A combination of passive radiometric, active radar, and in situ observations provide the best temperature and humidity profile measurements. Therefore, MRAP starts with a traditional, radiometer-based, physical retrieval algorithm provided by the International TOVS (TIROS-N Operational Vertical Sounder) Processing Package (ITPP) that constrains the retrieved profiles to agree with brightness temperature measurements. The first-guess profiles required by the ITPP's iterative retrieval algorithm are obtained by using a statistical inversion technique and ground-based remote sensing measurements. Because the individual ground-based remote sensing measurements are usually of sufficiently high quality, the first-guess profiles by themselves provide a satisfactory solution to establish the atmospheric water vapor and temperature state, and the TOVS data are included to provide profiles with better accuracy at higher levels, MRAP provides a physically consistent mechanism for combining the ground- and space-based humidity and temperature profiles.Data that have been used successfully to retrieve humidity and temperature profiles with MRAP are the following: temperature profiles in the lower troposphere from the ground-based Radio Acoustic Sounding System (RASS); total water vapor measurements from the Global Positioning System; specific humidity gradient profiles from the wind-profiling radar/RASS system; surface meteorological observations from standard instruments; cloud-base heights from a lidar ceilometer; temperature from the Aeronautical Radio, Incorporated Communication, Addressing and Reporting System aboard commercial airlines; and brightness temperature observations from TOVS.Data from the experiment conducted in the late summer of 1995 at Point Loma, California, were used for comparisons of MRAP results and 20 nearby rawinsonde releases to assess the statistical error estimates of MRAP. The temperature profiles had a bias of -0.27°C and a standard deviation of 1.56°C for the entire troposphere. Dewpoint profile retrievals did not have an overall accuracy as high as that of the temperature profiles but they exhibited a markedly improved standard deviation and bias in the lower atmosphere when the wind profiler/RASS specific humidity gradient information was available as a further constraint on the process. The European Centre for Medium-Range Weather Forecasts (ECMWF) model profiles of humidity and temperature for the grid point nearest to the Point Loma site were also used for comparison with the rawinsonde soundings to establish the usefulness of MRAP profiles to the weather forecasting community. The comparison showed that the vertical resolution of the ECMWF model profiles within the planetary boundary layer is not capable of detecting sharp gradients.

Coherent Evaluation of Aerosol Data Products from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Ichoku, Charles

2011-01-01

Aerosol retrieval from satellite has practically become routine, especially during the last decade. However, there is often disagreement between similar aerosol parameters retrieved from different sensors, thereby leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus, and the inconsistencies are not well characterized and understood, there will be no way of developing reliable model inputs and climate data records from satellite aerosol measurements. Fortunately, the Aerosol Robotic Network (AERONET) is providing well-calibrated globally representative ground-based aerosol measurements corresponding to the satellite-retrieved products. Through a recently developed web-based Multi-sensor Aerosol Products Sampling System (MAPSS), we are utilizing the advantages offered by collocated AERONET and satellite products to characterize and evaluate aerosol retrieval from multiple sensors. Indeed, MAPSS and its companion statistical tool AeroStat are facilitating detailed comparative uncertainty analysis of satellite aerosol measurements from Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Enhancements in medicine by integrating content based image retrieval in computer-aided diagnosis

NASA Astrophysics Data System (ADS)

Aggarwal, Preeti; Sardana, H. K.

2010-02-01

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. With cad, radiologists use the computer output as a "second opinion" and make the final decisions. Retrieving images is a useful tool to help radiologist to check medical image and diagnosis. The impact of contentbased access to medical images is frequently reported but existing systems are designed for only a particular context of diagnosis. The challenge in medical informatics is to develop tools for analyzing the content of medical images and to represent them in a way that can be efficiently searched and compared by the physicians. CAD is a concept established by taking into account equally the roles of physicians and computers. To build a successful computer aided diagnostic system, all the relevant technologies, especially retrieval need to be integrated in such a manner that should provide effective and efficient pre-diagnosed cases with proven pathology for the current case at the right time. In this paper, it is suggested that integration of content-based image retrieval (CBIR) in cad can bring enormous results in medicine especially in diagnosis. This approach is also compared with other approaches by highlighting its advantages over those approaches.

Overlap in the functional neural systems involved in semantic and episodic memory retrieval.

PubMed

Rajah, M N; McIntosh, A R

2005-03-01

Neuroimaging and neuropsychological data suggest that episodic and semantic memory may be mediated by distinct neural systems. However, an alternative perspective is that episodic and semantic memory represent different modes of processing within a single declarative memory system. To examine whether the multiple or the unitary system view better represents the data we conducted a network analysis using multivariate partial least squares (PLS ) activation analysis followed by covariance structural equation modeling (SEM) of positron emission tomography data obtained while healthy adults performed episodic and semantic verbal retrieval tasks. It is argued that if performance of episodic and semantic retrieval tasks are mediated by different memory systems, then there should differences in both regional activations and interregional correlations related to each type of retrieval task, respectively. The PLS results identified brain regions that were differentially active during episodic retrieval versus semantic retrieval. Regions that showed maximal differences in regional activity between episodic retrieval tasks were used to construct separate functional models for episodic and semantic retrieval. Omnibus tests of these functional models failed to find a significant difference across tasks for both functional models. The pattern of path coefficients for the episodic retrieval model were not different across tasks, nor were the path coefficients for the semantic retrieval model. The SEM results suggest that the same memory network/system was engaged across tasks, given the similarities in path coefficients. Therefore, activation differences between episodic and semantic retrieval may ref lect variation along a continuum of processing during task performance within the context of a single memory system.

Pilot study of the domestic information display system in state and local government

NASA Technical Reports Server (NTRS)

1982-01-01

An interactive computer based system that can retrieve a wide range of data (demographic, environmental, socio-economic, etc.,) from a large data base and display these data for different geographic units in the form of choropleth maps was developed. The system was designed to display statistical information in a geographic format for national policy makers.

Using Induction to Refine Information Retrieval Strategies

NASA Technical Reports Server (NTRS)

Baudin, Catherine; Pell, Barney; Kedar, Smadar

1994-01-01

Conceptual information retrieval systems use structured document indices, domain knowledge and a set of heuristic retrieval strategies to match user queries with a set of indices describing the document's content. Such retrieval strategies increase the set of relevant documents retrieved (increase recall), but at the expense of returning additional irrelevant documents (decrease precision). Usually in conceptual information retrieval systems this tradeoff is managed by hand and with difficulty. This paper discusses ways of managing this tradeoff by the application of standard induction algorithms to refine the retrieval strategies in an engineering design domain. We gathered examples of query/retrieval pairs during the system's operation using feedback from a user on the retrieved information. We then fed these examples to the induction algorithm and generated decision trees that refine the existing set of retrieval strategies. We found that (1) induction improved the precision on a set of queries generated by another user, without a significant loss in recall, and (2) in an interactive mode, the decision trees pointed out flaws in the retrieval and indexing knowledge and suggested ways to refine the retrieval strategies.

42 CFR 433.110 - Basis, purpose, and applicability.

Code of Federal Regulations, 2010 CFR

2010-10-01

... and Information Retrieval Systems § 433.110 Basis, purpose, and applicability. (a) This subpart... information retrieval systems and for the operation of certain systems. Additional HHS regulations and CMS... mechanized claims processing and information retrieval system or if the system fails to meet certain...

On combining image-based and ontological semantic dissimilarities for medical image retrieval applications

PubMed Central

Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F.; Rubin, Daniel L.

2014-01-01

Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic “soft” prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs of images on a 25-images dataset, and evaluation relative to the diagnoses of the retrieved images on a 72-images dataset. A normalized discounted cumulative gain (NDCG) score of more than 0.92 was obtained with the first protocol, while AUC scores of more than 0.77 were obtained with the second protocol. This automatical approach could provide real-time decision support to radiologists by showing them similar images with associated diagnoses and, where available, responses to therapies. PMID:25036769

An 8-year, high-resolution reanalysis of atmospheric carbon dioxide mixing ratios based on OCO-2 and GOSAT-ACOS retrievals

NASA Astrophysics Data System (ADS)

Weir, B.; Chatterjee, A.; Ott, L. E.; Pawson, S.

2017-12-01

This talk presents an overview of results from the GEOS-Carb reanalysis of retrievals of average-column carbon dioxide (XCO2) from the Orbiting Carbon Observatory 2 (OCO-2) and Greenhouse Gases Observing Satellite (GOSAT) satellite missions. The reanalysis is a Level 3 (L3) product: a collection of 3D fields of carbon dioxide (CO2) mixing ratios every 6 hours beginning in April 2009 going until the present on a grid with a 0.5 degree horizontal resolution and 72 vertical levels from the surface to 0.01 hPa. Using an assimilation methodology based on the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS), the L3 fields are weighted averages of the two satellite retrievals and predictions from the GEOS general circulation model driven by assimilated meteorology from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). In places and times where there are a dense number of soundings, the observations dominate the predicted mixing ratios, while the model is used to fill in locations with fewer soundings, e.g., high latitudes and the Amazon. Blending the satellite observations with model predictions has at least two notable benefits. First, it provides a bridge for evaluating the satellite retrievals and their uncertainties against a heterogeneous collection of observations including those from surface sites, towers, aircraft, and soundings from the Total Carbon Column Observing Network (TCCON). Extensive evaluations of the L3 reanalysis clearly demonstrate both the strength and the deficiency of the satellite retrievals. Second, it is possible to estimate variables from the reanalysis without introducing bias due to spatiotemporal variability in sounding coverage. For example, the assimilated product provides robust estimates of the monthly CO2 global growth rate. These monthly growth rate estimates show significant differences from estimates based on in situ observations, which have sparse coverage, and those based on model surface fluxes, which imperfectly represent key processes. This presentation discusses the implications of this finding as well as ongoing strategies to extract more information from the satellite retrievals in future L3 reanalyses.

VidCat: an image and video analysis service for personal media management

NASA Astrophysics Data System (ADS)

Begeja, Lee; Zavesky, Eric; Liu, Zhu; Gibbon, David; Gopalan, Raghuraman; Shahraray, Behzad

2013-03-01

Cloud-based storage and consumption of personal photos and videos provides increased accessibility, functionality, and satisfaction for mobile users. One cloud service frontier that is recently growing is that of personal media management. This work presents a system called VidCat that assists users in the tagging, organization, and retrieval of their personal media by faces and visual content similarity, time, and date information. Evaluations for the effectiveness of the copy detection and face recognition algorithms on standard datasets are also discussed. Finally, the system includes a set of application programming interfaces (API's) allowing content to be uploaded, analyzed, and retrieved on any client with simple HTTP-based methods as demonstrated with a prototype developed on the iOS and Android mobile platforms.

RESEARCH AND TECHNOLOGY DIVISION REPORT FOR 1966.

ERIC Educational Resources Information Center

BAUM, C.

THE WORK OF THE RESEARCH AND TECHNOLOGY DIVISION OF SYSTEM DEVELOPMENT CORPORATION DURING 1966 IS REPORTED. THE PROGRESS OF VARIOUS STUDIES AND ACTIVITIES DISCUSSED IN THE REPORT WERE ADVANCED PROGRAMING, INFORMATION PROCESSING RESEARCH, PROGRAMING SYSTEMS, DATA BASE SYSTEMS. LANGUAGE PROCESSING AND RETRIEVAL, BEHAVIORAL GAMING AND SIMULATION…

RDFBuilder: a tool to automatically build RDF-based interfaces for MAGE-OM microarray data sources.

PubMed

Anguita, Alberto; Martin, Luis; Garcia-Remesal, Miguel; Maojo, Victor

2013-07-01

This paper presents RDFBuilder, a tool that enables RDF-based access to MAGE-ML-compliant microarray databases. We have developed a system that automatically transforms the MAGE-OM model and microarray data stored in the ArrayExpress database into RDF format. Additionally, the system automatically enables a SPARQL endpoint. This allows users to execute SPARQL queries for retrieving microarray data, either from specific experiments or from more than one experiment at a time. Our system optimizes response times by caching and reusing information from previous queries. In this paper, we describe our methods for achieving this transformation. We show that our approach is complementary to other existing initiatives, such as Bio2RDF, for accessing and retrieving data from the ArrayExpress database. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Rapid automatic keyword extraction for information retrieval and analysis

DOEpatents

Rose, Stuart J [Richland, WA; Cowley,; E, Wendy [Richland, WA; Crow, Vernon L [Richland, WA; Cramer, Nicholas O [Richland, WA

2012-03-06

Methods and systems for rapid automatic keyword extraction for information retrieval and analysis. Embodiments can include parsing words in an individual document by delimiters, stop words, or both in order to identify candidate keywords. Word scores for each word within the candidate keywords are then calculated based on a function of co-occurrence degree, co-occurrence frequency, or both. Based on a function of the word scores for words within the candidate keyword, a keyword score is calculated for each of the candidate keywords. A portion of the candidate keywords are then extracted as keywords based, at least in part, on the candidate keywords having the highest keyword scores.

Automated semantic indexing of figure captions to improve radiology image retrieval.

PubMed

Kahn, Charles E; Rubin, Daniel L

2009-01-01

We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Estimated precision was 0.897 (95% confidence interval, 0.857-0.937). Estimated recall was 0.930 (95% confidence interval, 0.838-1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval.

Ground-based microwave radar and optical lidar signatures of volcanic ash plumes: models, observations and retrievals

NASA Astrophysics Data System (ADS)

Mereu, Luigi; Marzano, Frank; Mori, Saverio; Montopoli, Mario; Cimini, Domenico; Martucci, Giovanni

2013-04-01

The detection and quantitative retrieval of volcanic ash clouds is of significant interest due to its environmental, climatic and socio-economic effects. Real-time monitoring of such phenomena is crucial, also for the initialization of dispersion models. Satellite visible-infrared radiometric observations from geostationary platforms are usually exploited for long-range trajectory tracking and for measuring low level eruptions. Their imagery is available every 15-30 minutes and suffers from a relatively poor spatial resolution. Moreover, the field-of-view of geostationary radiometric measurements may be blocked by water and ice clouds at higher levels and their overall utility is reduced at night. Ground-based microwave radars may represent an important tool to detect and, to a certain extent, mitigate the hazard from the ash clouds. Ground-based weather radar systems can provide data for determining the ash volume, total mass and height of eruption clouds. Methodological studies have recently investigated the possibility of using ground-based single-polarization and dual-polarization radar system for the remote sensing of volcanic ash cloud. A microphysical characterization of volcanic ash was carried out in terms of dielectric properties, size distribution and terminal fall speed, assuming spherically-shaped particles. A prototype of volcanic ash radar retrieval (VARR) algorithm for single-polarization systems was proposed and applied to S-band and C-band weather radar data. The sensitivity of the ground-based radar measurements decreases as the ash cloud is farther so that for distances greater than about 50 kilometers fine ash might be not detected anymore by microwave radars. In this respect, radar observations can be complementary to satellite, lidar and aircraft observations. Active remote sensing retrieval from ground, in terms of detection, estimation and sensitivity, of volcanic ash plumes is not only dependent on the sensor specifications, but also on the range and ash cloud distribution. The minimum detectable signal can be increased, for a given system and ash plume scenario, by decreasing the observation range and increasing the operational frequency using a multi-sensor approach, but also exploiting possible polarimetric capabilities. In particular, multi-wavelengths lidars can be complementary systems useful to integrate radar-based ash particle measurement. This work, starting from the results of a previous study and from above mentioned issues, is aimed at quantitatively assessing the optimal choices for microwave and millimeter-wave radar systems with a dual-polarization capability for real-time ash cloud remote sensing to be used in combination with an optical lidar. The physical-electromagnetic model of ash particle distributions is systematically reviewed and extended to include non-spherical particle shapes, vesicular composition, silicate content and orientation phenomena. The radar and lidar scattering and absorption response is simulated and analyzed in terms of self-consistent polarimetric signatures for ash classification purposes and correlation with ash concentration and mean diameter for quantitative retrieval aims. A sensitivity analysis to ash concentration, as a function of sensor specifications, range and ash category, is carried out trying to assess the expected multi-sensor multi-spectral system performances and limitations. The multi-sensor multi-wavelength polarimetric model-based approach can be used within a particle classification and estimation scheme, based on the VARR Bayesian metrics. As an application, the ground-based observation of the Eyjafjallajökull volcanic ash plume on 15-16 May 2010, carried out at the Atmospheric Research Station at Mace Head, Carna (Ireland) with MIRA36 35-GHz Ka-Band Doppler cloud radar and CHM15K lidar/ceilometer at 1064-nm wavelength, has been considered. Results are discussed in terms of retrievals and intercomparison with other ground-based and satellite-based sensors.

Gaps in content-based image retrieval

NASA Astrophysics Data System (ADS)

Deserno, Thomas M.; Antani, Sameer; Long, Rodney

2007-03-01

Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potentially strong impact in diagnostics, research, and education. Research successes that are increasingly reported in the scientific literature, however, have not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed without sufficient analytical reasoning to the inability of these applications in overcoming the "semantic gap". The semantic gap divides the high-level scene analysis of humans from the low-level pixel analysis of computers. In this paper, we suggest a more systematic and comprehensive view on the concept of gaps in medical CBIR research. In particular, we define a total of 13 gaps that address the image content and features, as well as the system performance and usability. In addition to these gaps, we identify 6 system characteristics that impact CBIR applicability and performance. The framework we have created can be used a posteriori to compare medical CBIR systems and approaches for specific biomedical image domains and goals and a priori during the design phase of a medical CBIR application. To illustrate the a posteriori use of our conceptual system, we apply it, initially, to the classification of three medical CBIR implementations: the content-based PACS approach (cbPACS), the medical GNU image finding tool (medGIFT), and the image retrieval in medical applications (IRMA) project. We show that systematic analysis of gaps provides detailed insight in system comparison and helps to direct future research.

42 CFR 433.110 - Basis, purpose, and applicability.

Code of Federal Regulations, 2011 CFR

2011-10-01

... and Information Retrieval Systems § 433.110 Basis, purpose, and applicability. (a) This subpart... information retrieval systems and for the operation of certain systems. Additional HHS regulations and CMS... conditions on mechanized claims processing and information retrieval systems (including eligibility...

42 CFR 433.110 - Basis, purpose, and applicability.

Code of Federal Regulations, 2012 CFR

2012-10-01

... and Information Retrieval Systems § 433.110 Basis, purpose, and applicability. (a) This subpart... information retrieval systems and for the operation of certain systems. Additional HHS regulations and CMS... conditions on mechanized claims processing and information retrieval systems (including eligibility...

42 CFR 433.110 - Basis, purpose, and applicability.

Code of Federal Regulations, 2014 CFR

2014-10-01

... and Information Retrieval Systems § 433.110 Basis, purpose, and applicability. (a) This subpart... information retrieval systems and for the operation of certain systems. Additional HHS regulations and CMS... conditions on mechanized claims processing and information retrieval systems (including eligibility...

42 CFR 433.110 - Basis, purpose, and applicability.

Code of Federal Regulations, 2013 CFR

2013-10-01

... and Information Retrieval Systems § 433.110 Basis, purpose, and applicability. (a) This subpart... information retrieval systems and for the operation of certain systems. Additional HHS regulations and CMS... conditions on mechanized claims processing and information retrieval systems (including eligibility...

Math expression retrieval using an inverted index over symbol pairs

NASA Astrophysics Data System (ADS)

Stalnaker, David; Zanibbi, Richard

2015-01-01

We introduce a new method for indexing and retrieving mathematical expressions, and a new protocol for evaluating math formula retrieval systems. The Tangent search engine uses an inverted index over pairs of symbols in math expressions. Each key in the index is a pair of symbols along with their relative distance and vertical displacement within an expression. Matched expressions are ranked by the harmonic mean of the percentage of symbol pairs matched in the query, and the percentage of symbol pairs matched in the candidate expression. We have found that our method is fast enough for use in real time and finds partial matches well, such as when subexpressions are re-arranged (e.g. expressions moved from the left to the right of an equals sign) or when individual symbols (e.g. variables) differ from a query expression. In an experiment using expressions from English Wikipedia, student and faculty participants (N=20) found expressions returned by Tangent significantly more similar than those from a text-based retrieval system (Lucene) adapted for mathematical expressions. Participants provided similarity ratings using a 5-point Likert scale, evaluating expressions from both algorithms one-at-a-time in a randomized order to avoid bias from the position of hits in search result lists. For the Lucene-based system, precision for the top 1 and 10 hits averaged 60% and 39% across queries respectively, while for Tangent mean precision at 1 and 10 were 99% and 60%. A demonstration and source code are publicly available.

High-spatial-resolution passive microwave sounding systems

NASA Technical Reports Server (NTRS)

Staelin, D. H.; Rosenkranz, P. W.

1994-01-01

The principal contributions of this combined theoretical and experimental effort were to advance and demonstrate new and more accurate techniques for sounding atmospheric temperature, humidity, and precipitation profiles at millimeter wavelengths, and to improve the scientific basis for such soundings. Some of these techniques are being incorporated in both research and operational systems. Specific results include: (1) development of the MIT Microwave Temperature Sounder (MTS), a 118-GHz eight-channel imaging spectrometer plus a switched-frequency spectrometer near 53 GHz, for use on the NASA ER-2 high-altitude aircraft, (2) conduct of ER-2 MTS missions in multiple seasons and locations in combination with other instruments, mapping with unprecedented approximately 2-km lateral resolution atmospheric temperature and precipitation profiles, atmospheric transmittances (at both zenith and nadir), frontal systems, and hurricanes, (3) ground based 118-GHz 3-D spectral images of wavelike structure within clouds passing overhead, (4) development and analysis of approaches to ground- and space-based 5-mm wavelength sounding of the upper stratosphere and mesosphere, which supported the planning of improvements to operational weather satellites, (5) development of improved multidimensional and adaptive retrieval methods for atmospheric temperature and humidity profiles, (6) development of combined nonlinear and statistical retrieval techniques for 183-GHz humidity profile retrievals, (7) development of nonlinear statistical retrieval techniques for precipitation cell-top altitudes, and (8) numerical analyses of the impact of remote sensing data on the accuracy of numerical weather predictions; a 68-km gridded model was used to study the spectral properties of error growth.

Music Retrieval Based on the Relation between Color Association and Lyrics

NASA Astrophysics Data System (ADS)

Nakamur, Tetsuaki; Utsumi, Akira; Sakamoto, Maki

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

Seasonal to Decadal-Scale Variability in Satellite Ocean Color and Sea Surface Temperature for the California Current System

NASA Technical Reports Server (NTRS)

Mitchell, B. Greg; Kahru, Mati; Marra, John (Technical Monitor)

2002-01-01

Support for this project was used to develop satellite ocean color and temperature indices (SOCTI) for the California Current System (CCS) using the historic record of CZCS West Coast Time Series (WCTS), OCTS, WiFS and AVHRR SST. The ocean color satellite data have been evaluated in relation to CalCOFI data sets for chlorophyll (CZCS) and ocean spectral reflectance and chlorophyll OCTS and SeaWiFS. New algorithms for the three missions have been implemented based on in-water algorithm data sets, or in the case of CZCS, by comparing retrieved pigments with ship-based observations. New algorithms for absorption coefficients, diffuse attenuation coefficients and primary production have also been evaluated. Satellite retrievals are being evaluated based on our large data set of pigments and optics from CalCOFI.

The remains of the day in dissociative amnesia.

PubMed

Staniloiu, Angelica; Markowitsch, Hans J

2012-04-10

Memory is not a unity, but is divided along a content axis and a time axis, respectively. Along the content dimension, five long-term memory systems are described, according to their hierarchical ontogenetic and phylogenetic organization. These memory systems are assumed to be accompanied by different levels of consciousness. While encoding is based on a hierarchical arrangement of memory systems from procedural to episodic-autobiographical memory, retrieval allows independence in the sense that no matter how information is encoded, it can be retrieved in any memory system. Thus, we illustrate the relations between various long-term memory systems by reviewing the spectrum of abnormalities in mnemonic processing that may arise in the dissociative amnesia-a condition that is usually characterized by a retrieval blockade of episodic-autobiographical memories and occurs in the context of psychological trauma, without evidence of brain damage on conventional structural imaging. Furthermore, we comment on the functions of implicit memories in guiding and even adaptively molding the behavior of patients with dissociative amnesia and preserving, in the absence of autonoetic consciousness, the so-called "internal coherence of life".

The Remains of the Day in Dissociative Amnesia

PubMed Central

Staniloiu, Angelica; Markowitsch, Hans J.

2012-01-01

Memory is not a unity, but is divided along a content axis and a time axis, respectively. Along the content dimension, five long-term memory systems are described, according to their hierarchical ontogenetic and phylogenetic organization. These memory systems are assumed to be accompanied by different levels of consciousness. While encoding is based on a hierarchical arrangement of memory systems from procedural to episodic-autobiographical memory, retrieval allows independence in the sense that no matter how information is encoded, it can be retrieved in any memory system. Thus, we illustrate the relations between various long-term memory systems by reviewing the spectrum of abnormalities in mnemonic processing that may arise in the dissociative amnesia—a condition that is usually characterized by a retrieval blockade of episodic-autobiographical memories and occurs in the context of psychological trauma, without evidence of brain damage on conventional structural imaging. Furthermore, we comment on the functions of implicit memories in guiding and even adaptively molding the behavior of patients with dissociative amnesia and preserving, in the absence of autonoetic consciousness, the so-called “internal coherence of life”. PMID:24962768

CAESAR : an expert system for evaluation of scour and stream stability

DOT National Transportation Integrated Search

1999-01-01

This report documents the development and testing of a field-deployable, knowledge-based decision support system that assists bridge inspectors by acquiring, cataloging, storing, and retrieving information necessary for the evaluation of a bridge for...

Development of an Automated Security Incident Reporting System (SIRS) for Bus Transit

DOT National Transportation Integrated Search

1986-12-01

The security incident reporting system (sirs) is a microcomputer-based software program demonstrated at the metropolitan transit commission (mtc) in Minneapolis, mn. Sirs is designed to provide convenient storage, update and retrieval of security inc...

Development of geotechnical analysis and design modules for the Virginia Department of Transportation's geotechnical database.

DOT National Transportation Integrated Search

2005-01-01

In 2003, an Internet-based Geotechnical Database Management System (GDBMS) was developed for the Virginia Department of Transportation (VDOT) using distributed Geographic Information System (GIS) methodology for data management, archival, retrieval, ...

Project W-211 Initial Tank Retrieval Systems (ITRS) Description of Operations for 241-AZ-102

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

BRIGGS, S.R.

2000-02-25

The primary purpose of the Initial Tank Retrieval Systems (ITRS) is to provide systems for retrieval of radioactive wastes stored in underground double-shell tanks (DSTs) for transfer to alternate storage, evaporation, pretreatment or treatment, while concurrently reducing risks associated with safety watch list and other DSTs. This Description of Operation (DOO) defines the control philosophy for the waste retrieval system for Tank 241-AZ-102 (AZ-102). This DOO provides a basis for the detailed design of the Project W-211 Retrieval Control System (RCS) for AZ-102 and also establishes test criteria for the RCS.

Lightweight Active Object Retrieval with Weak Classifiers.

PubMed

Czúni, László; Rashad, Metwally

2018-03-07

In the last few years, there has been a steadily growing interest in autonomous vehicles and robotic systems. While many of these agents are expected to have limited resources, these systems should be able to dynamically interact with other objects in their environment. We present an approach where lightweight sensory and processing techniques, requiring very limited memory and processing power, can be successfully applied to the task of object retrieval using sensors of different modalities. We use the Hough framework to fuse optical and orientation information of the different views of the objects. In the presented spatio-temporal perception technique, we apply active vision, where, based on the analysis of initial measurements, the direction of the next view is determined to increase the hit-rate of retrieval. The performance of the proposed methods is shown on three datasets loaded with heavy noise.

Lightweight Active Object Retrieval with Weak Classifiers

PubMed Central

2018-01-01

In the last few years, there has been a steadily growing interest in autonomous vehicles and robotic systems. While many of these agents are expected to have limited resources, these systems should be able to dynamically interact with other objects in their environment. We present an approach where lightweight sensory and processing techniques, requiring very limited memory and processing power, can be successfully applied to the task of object retrieval using sensors of different modalities. We use the Hough framework to fuse optical and orientation information of the different views of the objects. In the presented spatio-temporal perception technique, we apply active vision, where, based on the analysis of initial measurements, the direction of the next view is determined to increase the hit-rate of retrieval. The performance of the proposed methods is shown on three datasets loaded with heavy noise. PMID:29518902

Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

NASA Technical Reports Server (NTRS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Perez Garcia-Pando, Carlos

2017-01-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0

NASA Astrophysics Data System (ADS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Pérez García-Pando, Carlos

2017-03-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets. The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

ACMES: fast multiple-genome searches for short repeat sequences with concurrent cross-species information retrieval

PubMed Central

Reneker, Jeff; Shyu, Chi-Ren; Zeng, Peiyu; Polacco, Joseph C.; Gassmann, Walter

2004-01-01

We have developed a web server for the life sciences community to use to search for short repeats of DNA sequence of length between 3 and 10 000 bases within multiple species. This search employs a unique and fast hash function approach. Our system also applies information retrieval algorithms to discover knowledge of cross-species conservation of repeat sequences. Furthermore, we have incorporated a part of the Gene Ontology database into our information retrieval algorithms to broaden the coverage of the search. Our web server and tutorial can be found at http://acmes.rnet.missouri.edu. PMID:15215469

Transparent Information Systems through Gateways, Front Ends, Intermediaries, and Interfaces.

ERIC Educational Resources Information Center

Williams, Martha E.

1986-01-01

Provides overview of design requirements for transparent information retrieval (implies that user sees through complexity of retrieval activities sequence). Highlights include need for transparent systems; history of transparent retrieval research; information retrieval functions (automated converters, routers, selectors, evaluators/analyzers);…

45 CFR 205.38 - Federal financial participation (FFP) for establishing a statewide mechanized system.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., development or installation of a statewide automated application processing and information retrieval system.... (2) The system is compatible with the claims processing and information retrieval systems used in the... in the title IV-A (AFDC) Automated Application Processing and Information Retrieval System Guide...

45 CFR 205.38 - Federal financial participation (FFP) for establishing a statewide mechanized system.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., development or installation of a statewide automated application processing and information retrieval system.... (2) The system is compatible with the claims processing and information retrieval systems used in the... in the title IV-A (AFDC) Automated Application Processing and Information Retrieval System Guide...

45 CFR 205.38 - Federal financial participation (FFP) for establishing a statewide mechanized system.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., development or installation of a statewide automated application processing and information retrieval system.... (2) The system is compatible with the claims processing and information retrieval systems used in the... in the title IV-A (AFDC) Automated Application Processing and Information Retrieval System Guide...

45 CFR 205.38 - Federal financial participation (FFP) for establishing a statewide mechanized system.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., development or installation of a statewide automated application processing and information retrieval system.... (2) The system is compatible with the claims processing and information retrieval systems used in the... in the title IV-A (AFDC) Automated Application Processing and Information Retrieval System Guide...

45 CFR 205.38 - Federal financial participation (FFP) for establishing a statewide mechanized system.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., development or installation of a statewide automated application processing and information retrieval system.... (2) The system is compatible with the claims processing and information retrieval systems used in the... in the title IV-A (AFDC) Automated Application Processing and Information Retrieval System Guide...

The influence of sea fog inhomogeneity on its microphysical characteristics retrieval

NASA Astrophysics Data System (ADS)

Hao, Zengzhou; Pan, Delu; Gong, Fang; He, Xianqiang

2008-10-01

A study on the effect of sea fog inhomogeneity on its microphysical parameters retrieval is presented. On the condition that the average liquid water content is linear vertically and the power spectrum spectral index sets 2.0, we generate a 3D sea fog fields by controlling the total liquid water contents greater than 0.04g/m3 based on the iterative method for generating scaling log-normal random field with an energy spectrum and a fragmentized cloud algorithm. Based on the fog field, the radiance at the wavelengths of 0.67 and 1.64 μm are simulated with 3D radiative transfer model SHDOM, and then the fog optical thickness and effective particle radius are simultaneously retrieved using the generic look-up-table AVHRR cloud algorithm. By comparing those fog optical thickness and effective particle radius, the influence of sea fog inhomogeneity on its properties retrieval is discussed. It exhibits the system bias when inferring sea fog physical properties from satellite measurements based on the assumption of plane parallel homogeneous atmosphere. And the bias depends on the solar zenith angel. The optical thickness is overrated while the effective particle radius is under-estimated at two solar zenith angle 30° and 60°. Those results show that it is necessary for sea fog true characteristics retrieval to develop a new algorithm using the 3D radiative transfer.

Retrieval and Validation of Zenith and Slant Path Delays From the Irish GPS Network

NASA Astrophysics Data System (ADS)

Hanafin, Jennifer; Jennings, S. Gerard; O'Dowd, Colin; McGrath, Ray; Whelan, Eoin

2010-05-01

Retrieval of atmospheric integrated water vapour (IWV) from ground-based GPS receivers and provision of this data product for meteorological applications has been the focus of a number of Europe-wide networks and projects, most recently the EUMETNET GPS water vapour programme. The results presented here are from a project to provide such information about the state of the atmosphere around Ireland for climate monitoring and improved numerical weather prediction. Two geodetic reference GPS receivers have been deployed at Valentia Observatory in Co. Kerry and Mace Head Atmospheric Research Station in Co. Galway, Ireland. These two receivers supplement the existing Ordnance Survey Ireland active network of 17 permanent ground-based receivers. A system to retrieve column-integrated atmospheric water vapour from the data provided by this network has been developed, based on the GPS Analysis at MIT (GAMIT) software package. The data quality of the zenith retrievals has been assessed using co-located radiosondes at the Valentia site and observations from a microwave profiling radiometer at the Mace Head site. Validation of the slant path retrievals requires a numerical weather prediction model and HIRLAM (High-Resolution Limited Area Model) version 7.2, the current operational forecast model in use at Met Éireann for the region, has been used for this validation work. Results from the data processing and comparisons with the independent observations and model will be presented.

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Marshak, Alexander; Chiu, J. Christine; Wiscombe, Warren J.; Palm, Stephen P.; Davis, Anthony B.; Spangenberg, Douglas A.; Nguyen, Louis; Spinhirne, James D.; Minnis, Patrick

2008-01-01

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Occam's razor: supporting visual query expression for content-based image queries

NASA Astrophysics Data System (ADS)

Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.

2005-01-01

This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).

3D model retrieval method based on mesh segmentation

NASA Astrophysics Data System (ADS)

Gan, Yuanchao; Tang, Yan; Zhang, Qingchen

2012-04-01

In the process of feature description and extraction, current 3D model retrieval algorithms focus on the global features of 3D models but ignore the combination of global and local features of the model. For this reason, they show less effective performance to the models with similar global shape and different local shape. This paper proposes a novel algorithm for 3D model retrieval based on mesh segmentation. The key idea is to exact the structure feature and the local shape feature of 3D models, and then to compares the similarities of the two characteristics and the total similarity between the models. A system that realizes this approach was built and tested on a database of 200 objects and achieves expected results. The results show that the proposed algorithm improves the precision and the recall rate effectively.

Occam"s razor: supporting visual query expression for content-based image queries

NASA Astrophysics Data System (ADS)

Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.

2004-12-01

This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).

The NLM Indexing Initiative.

PubMed Central

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

2000-01-01

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

Information Retrieval Systems Retrieved? An Alternative to Present Dial Access Systems

ERIC Educational Resources Information Center

Hofmann, Norbert

1976-01-01

The expense of a dial access information retrieval system (DIARS) is weighed against its benefits. Problems of usage and efficacy for the student are outlined. A fully automated system is proposed instead, and its cost-saving features are pointed out. (MS)

Desktop Access to Full-Text NACA and NASA Reports: Systems Developed by NASA Langley Technical Library

NASA Technical Reports Server (NTRS)

Ambur, Manjula Y.; Adams, David L.; Trinidad, P. Paul

1997-01-01

NASA Langley Technical Library has been involved in developing systems for full-text information delivery of NACA/NASA technical reports since 1991. This paper will describe the two prototypes it has developed and the present production system configuration. The prototype systems are a NACA CD-ROM of thirty-three classic paper NACA reports and a network-based Full-text Electronic Reports Documents System (FEDS) constructed from both paper and electronic formats of NACA and NASA reports. The production system is the DigiDoc System (DIGItal Documents) presently being developed based on the experiences gained from the two prototypes. DigiDoc configuration integrates the on-line catalog database World Wide Web interface and PDF technology to provide a powerful and flexible search and retrieval system. It describes in detail significant achievements and lessons learned in terms of data conversion, storage technologies, full-text searching and retrieval, and image databases. The conclusions from the experiences of digitization and full- text access and future plans for DigiDoc system implementation are discussed.

On the Use of Adaptive Instructional Images Based on the Sequential-Global Dimension of the Felder-Silverman Learning Style Theory

ERIC Educational Resources Information Center

Filippidis, Stavros K.; Tsoukalas, Ioannis A.

2009-01-01

An adaptive educational system that uses adaptive presentation is presented. In this system fragments of different images present the same content and the system can choose the one most relevant to the user based on the sequential-global dimension of Felder-Silverman's learning style theory. In order to retrieve the learning style of each student…

A knowledgebase system to enhance scientific discovery: Telemakus

PubMed Central

Fuller, Sherrilynne S; Revere, Debra; Bugni, Paul F; Martin, George M

2004-01-01

Background With the rapid expansion of scientific research, the ability to effectively find or integrate new domain knowledge in the sciences is proving increasingly difficult. Efforts to improve and speed up scientific discovery are being explored on a number of fronts. However, much of this work is based on traditional search and retrieval approaches and the bibliographic citation presentation format remains unchanged. Methods Case study. Results The Telemakus KnowledgeBase System provides flexible new tools for creating knowledgebases to facilitate retrieval and review of scientific research reports. In formalizing the representation of the research methods and results of scientific reports, Telemakus offers a potential strategy to enhance the scientific discovery process. While other research has demonstrated that aggregating and analyzing research findings across domains augments knowledge discovery, the Telemakus system is unique in combining document surrogates with interactive concept maps of linked relationships across groups of research reports. Conclusion Based on how scientists conduct research and read the literature, the Telemakus KnowledgeBase System brings together three innovations in analyzing, displaying and summarizing research reports across a domain: (1) research report schema, a document surrogate of extracted research methods and findings presented in a consistent and structured schema format which mimics the research process itself and provides a high-level surrogate to facilitate searching and rapid review of retrieved documents; (2) research findings, used to index the documents, allowing searchers to request, for example, research studies which have studied the relationship between neoplasms and vitamin E; and (3) visual exploration interface of linked relationships for interactive querying of research findings across the knowledgebase and graphical displays of what is known as well as, through gaps in the map, what is yet to be tested. The rationale and system architecture are described and plans for the future are discussed. PMID:15507158

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

NASA Astrophysics Data System (ADS)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

Exploring personalized searches using tag-based user profiles and resource profiles in folksonomy.

PubMed

Cai, Yi; Li, Qing; Xie, Haoran; Min, Huaqin

2014-10-01

With the increase in resource-sharing websites such as YouTube and Flickr, many shared resources have arisen on the Web. Personalized searches have become more important and challenging since users demand higher retrieval quality. To achieve this goal, personalized searches need to take users' personalized profiles and information needs into consideration. Collaborative tagging (also known as folksonomy) systems allow users to annotate resources with their own tags, which provides a simple but powerful way for organizing, retrieving and sharing different types of social resources. In this article, we examine the limitations of previous tag-based personalized searches. To handle these limitations, we propose a new method to model user profiles and resource profiles in collaborative tagging systems. We use a normalized term frequency to indicate the preference degree of a user on a tag. A novel search method using such profiles of users and resources is proposed to facilitate the desired personalization in resource searches. In our framework, instead of the keyword matching or similarity measurement used in previous works, the relevance measurement between a resource and a user query (termed the query relevance) is treated as a fuzzy satisfaction problem of a user's query requirements. We implement a prototype system called the Folksonomy-based Multimedia Retrieval System (FMRS). Experiments using the FMRS data set and the MovieLens data set show that our proposed method outperforms baseline methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Enhanced Information Retrieval Using AJAX

NASA Astrophysics Data System (ADS)

Kachhwaha, Rajendra; Rajvanshi, Nitin

2010-11-01

Information Retrieval deals with the representation, storage, organization of, and access to information items. The representation and organization of information items should provide the user with easy access to the information with the rapid development of Internet, large amounts of digitally stored information is readily available on the World Wide Web. This information is so huge that it becomes increasingly difficult and time consuming for the users to find the information relevant to their needs. The explosive growth of information on the Internet has greatly increased the need for information retrieval systems. However, most of the search engines are using conventional information retrieval systems. An information system needs to implement sophisticated pattern matching tools to determine contents at a faster rate. AJAX has recently emerged as the new tool such the of information retrieval process of information retrieval can become fast and information reaches the use at a faster pace as compared to conventional retrieval systems.

Automated Semantic Indexing of Figure Captions to Improve Radiology Image Retrieval

PubMed Central

Kahn, Charles E.; Rubin, Daniel L.

2009-01-01

Objective We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. Design The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Measurements Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Results Estimated precision was 0.897 (95% confidence interval, 0.857–0.937). Estimated recall was 0.930 (95% confidence interval, 0.838–1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Conclusion Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval. PMID:19261938

Development of bilateral data transferability in the Virginia Department of Transportation's Geotechnical Database Management System Framework.

DOT National Transportation Integrated Search

2006-01-01

An Internet-based, spatiotemporal Geotechnical Database Management System (GDBMS) Framework was designed, developed, and implemented at the Virginia Department of Transportation (VDOT) in 2002 to retrieve, manage, archive, and analyze geotechnical da...

Data Compression in Full-Text Retrieval Systems.

ERIC Educational Resources Information Center

Bell, Timothy C.; And Others

1993-01-01

Describes compression methods for components of full-text systems such as text databases on CD-ROM. Topics discussed include storage media; structures for full-text retrieval, including indexes, inverted files, and bitmaps; compression tools; memory requirements during retrieval; and ranking and information retrieval. (Contains 53 references.)…

A semi-automated workflow for biodiversity data retrieval, cleaning, and quality control

PubMed Central

Mathew, Cherian; Obst, Matthias; Vicario, Saverio; Haines, Robert; Williams, Alan R.; de Jong, Yde; Goble, Carole

2014-01-01

Abstract The compilation and cleaning of data needed for analyses and prediction of species distributions is a time consuming process requiring a solid understanding of data formats and service APIs provided by biodiversity informatics infrastructures. We designed and implemented a Taverna-based Data Refinement Workflow which integrates taxonomic data retrieval, data cleaning, and data selection into a consistent, standards-based, and effective system hiding the complexity of underlying service infrastructures. The workflow can be freely used both locally and through a web-portal which does not require additional software installations by users. PMID:25535486

General specifications for the development of a USL/DBMS NASA/PC R and D distributed workstation

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Chum, Frank Y.

1984-01-01

The general specifications for the development of a PC-based distributed workstation (PCDWS) for an information storage and retrieval systems environment are defined. This research proposes the development of a PCDWS prototype as part of the University of Southwestern Louisiana Data Base Management System (USL/DBMS) NASA/PC R and D project in the PC-based workstation environment.

Query Expansion for Noisy Legal Documents

DTIC Science & Technology

2008-11-01

9] G. Salton (ed). The SMART retrieval system experiments in automatic document processing. 1971. [10] H. Schutze and J . Pedersen. A cooccurrence...Language Modeling and Information Retrieval. http://www.lemurproject.org. [2] J . Baron, D. Lewis, and D. Oard. TREC 2006 legal track overview. In...Retrieval, 1993. [8] J . Rocchio. Relevance feedback in information retrieval. In The SMART retrieval system experiments in automatic document processing, 1971

A prototype feature system for feature retrieval using relationships

USGS Publications Warehouse

Choi, J.; Usery, E.L.

2009-01-01

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

Competitive retrieval is not a prerequisite for forgetting in the retrieval practice paradigm.

PubMed

Camp, Gino; Dalm, Sander

2016-09-01

Retrieving information from memory can lead to forgetting of other, related information. The inhibition account of this retrieval-induced forgetting effect predicts that this form of forgetting occurs when competition arises between the practiced information and the related information, leading to inhibition of the related information. In the standard retrieval practice paradigm, a retrieval practice task is used in which participants retrieve the items based on a category-plus-stem cue (e.g., FRUIT-or___). In the current experiment, participants instead generated the target based on a cue in which the first 2 letters of the target were transposed (e.g., FRUIT-roange). This noncompetitive task also induced forgetting of unpracticed items from practiced categories. This finding is inconsistent with the inhibition account, which asserts that the forgetting effect depends on competitive retrieval. We argue that interference-based accounts of forgetting and the context-based account of retrieval-induced forgetting can account for this result. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms

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

Tourassi, Georgia D.; Harrawood, Brian; Singh, Swatee

The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrievalmore » precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.« less

Ground-based retrieval of atmospheric temperature, moisture, cloud properties, and aerosols using the Atmospheric Emitted Radiance Interferometer (AERI)

NASA Astrophysics Data System (ADS)

Feltz, W.; Turner, D.; Knuteson, R.; Revercomb, H.; Best, F.; Dedecker, R.; Li, J.; Buijs, H.; Clateauneuf, F.; Roy, C.

The Atmospheric Emitted Radiance Interferometer AERI system measures infrared downwelling radiances at one wavenumber resolution from 3-20 mu m with better than 10-minute temporal resolution The robust and fully automated AERI instruments are monitored in the field via the Internet in near real-time The AERI absolute radiometric accuracy is better than 1 of ambient radiance The calibrated AERI radiances are used to validate high spectral resolution line-by-line model calculations retrieve profiles of atmospheric constituents derive cloud aerosol properties and surface oceanic skin properties The University of Wisconsin -- Madison Space Science and Engineering Center SSEC developed the AERI for use within the United States Department of Energy DOE Atmospheric Radiation Measurement ARM research program DOE ARM has funded the development and installation of eight ground-based AERI systems based in several international locations including Darwin Australia Niger Africa Barrow Alaska and Nauru Island in the South Pacific The AERI systems have shown high reliability including over ten years of continuous operation at Lamont Oklahoma USA The AERI technology has been licensed to ABB Bomem of Quebec City Canada and plans are underway to provide commercial versions of a variety of atmospheric measurement capabilities The most mature and demonstrated capability allows direct retrieval of meteorological information about the vertical structure of temperature and water vapor in the planetary boundary layer PBL 0-3 km New

Computer-generated mineral commodity deposit maps

USGS Publications Warehouse

Schruben, Paul G.; Hanley, J. Thomas

1983-01-01

This report describes an automated method of generating deposit maps of mineral commodity information. In addition, it serves as a user's manual for the authors' mapping system. Procedures were developed which allow commodity specialists to enter deposit information, retrieve selected data, and plot deposit symbols in any geographic area within the conterminous United States. The mapping system uses both micro- and mainframe computers. The microcomputer is used to input and retrieve information, thus minimizing computing charges. The mainframe computer is used to generate map plots which are printed by a Calcomp plotter. Selector V data base system is employed for input and retrieval on the microcomputer. A general mapping program (Genmap) was written in FORTRAN for use on the mainframe computer. Genmap can plot fifteen symbol types (for point locations) in three sizes. The user can assign symbol types to data items interactively. Individual map symbols can be labeled with a number or the deposit name. Genmap also provides several geographic boundary file and window options.

Current Status and Future Plan of Arctic Sea Ice monitoring in South Korea

NASA Astrophysics Data System (ADS)

Shin, J.; Park, J.

2016-12-01

Arctic sea ice is one of the most important parameters in climate. For monitoring of sea ice changes, the National Meteorological Satellite Center (NMSC) of Korea Metrological Administration has developed the "Arctic sea ice monitoring system" to retrieve the sea ice extent and surface roughness using microwave sensor data, and statistical prediction model for Arctic sea ice extent. This system has been implemented to the web site for real-time public service. The sea ice information can be retrieved using the spaceborne microwave sensor-Special Sensor Microwave Imager/Sounder (SSMI/S). The sea ice information like sea ice extent, sea ice surface roughness, and predictive sea ice extent are produced weekly base since 2007. We also publish the "Analysis report of the Arctic sea ice" twice a year. We are trying to add more sea ice information into this system. Details of current status and future plan of Arctic sea ice monitoring and the methodology of the sea ice information retrievals will be presented in the meeting.

Intelligent Text Retrieval and Knowledge Acquisition from Texts for NASA Applications: Preprocessing Issues

NASA Technical Reports Server (NTRS)

2002-01-01

A system that retrieves problem reports from a NASA database is described. The database is queried with natural language questions. Part-of-speech tags are first assigned to each word in the question using a rule based tagger. A partial parse of the question is then produced with independent sets of deterministic finite state a utomata. Using partial parse information, a look up strategy searches the database for problem reports relevant to the question. A bigram stemmer and irregular verb conjugates have been incorporated into the system to improve accuracy. The system is evaluated by a set of fifty five questions posed by NASA engineers. A discussion of future research is also presented.

The Improved Dual-view Field Goniometer System FIGOS

PubMed Central

Schopfer, Jürg; Dangel, Stefan; Kneubühler, Mathias; Itten, Klaus I.

2008-01-01

In spectrodirectional Remote Sensing (RS) the Earth's surface reflectance characteristics are studied by means of their angular dimensions. Almost all natural surfaces exhibit an individual anisotropic reflectance behaviour due to the contrast between the optical properties of surface elements and background and the geometric surface properties of the observed scene. The underlying concept, which describes the reflectance characteristic of a specific surface area, is called the bidirectional reflectance distribution function (BRDF). BRDF knowledge is essential for both correction of directional effects in RS data and quantitative retrieval of surface parameters. Ground-based spectrodirectional measurements are usually performed with goniometer systems. An accurate retrieval of the bidirectional reflectance factors (BRF) from field goniometer measurements requires hyperspectral knowledge of the angular distribution of the reflected and the incident radiation. However, prior to the study at hand, no operational goniometer system was able to fulfill this requirement. This study presents the first dual-view field goniometer system, which is able to simultaneously collect both the reflected and the incident radiation at high angular and spectral resolution and, thus, providing the necessary spectrodirectional datasets to accurately retrieve the surface specific BRF. Furthermore, the angular distribution of the incoming diffuse radiation is characterized for various atmospheric conditions and the BRF retrieval is performed for an artificial target and compared to laboratory spectrodirectional measurement results obtained with the same goniometer system. Suggestions for further improving goniometer systems are given and the need for intercalibration of various goniometers as well as for standardizing spectrodirectional measurements is expressed. PMID:27873805

The Improved Dual-view Field Goniometer System FIGOS.

PubMed

Schopfer, Jürg; Dangel, Stefan; Kneubühler, Mathias; Itten, Klaus I

2008-08-28

In spectrodirectional Remote Sensing (RS) the Earth's surface reflectance characteristics are studied by means of their angular dimensions. Almost all natural surfaces exhibit an individual anisotropic reflectance behaviour due to the contrast between the optical properties of surface elements and background and the geometric surface properties of the observed scene. The underlying concept, which describes the reflectance characteristic of a specific surface area, is called the bidirectional reflectance distribution function (BRDF). BRDF knowledge is essential for both correction of directional effects in RS data and quantitative retrieval of surface parameters. Ground-based spectrodirectional measurements are usually performed with goniometer systems. An accurate retrieval of the bidirectional reflectance factors (BRF) from field goniometer measurements requires hyperspectral knowledge of the angular distribution of the reflected and the incident radiation. However, prior to the study at hand, no operational goniometer system was able to fulfill this requirement. This study presents the first dual-view field goniometer system, which is able to simultaneously collect both the reflected and the incident radiation at high angular and spectral resolution and, thus, providing the necessary spectrodirectional datasets to accurately retrieve the surface specific BRF. Furthermore, the angular distribution of the incoming diffuse radiation is characterized for various atmospheric conditions and the BRF retrieval is performed for an artificial target and compared to laboratory spectrodirectional measurement results obtained with the same goniometer system. Suggestions for further improving goniometer systems are given and the need for intercalibration of various goniometers as well as for standardizing spectrodirectional measurements is expressed.

Passive Microwave Soil Moisture Retrieval through Combined Radar/Radiometer Ground Based Simulator with Special Reference to Dielectric Schemes

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K., ,, Dr.; O'Neill, Peggy, ,, Dr.

2014-05-01

Soil moisture is an important element for weather and climate prediction, hydrological sciences, and applications. Hence, measurements of this hydrologic variable are required to improve our understanding of hydrological processes, ecosystem functions, and the linkages between the Earth's water, energy, and carbon cycles (Srivastava et al. 2013). The retrieval of soil moisture depends not only on parameterizations in the retrieval algorithm but also on the soil dielectric mixing models used (Behari 2005). Although a number of soil dielectric mixing models have been developed, testing these models for soil moisture retrieval has still not been fully explored, especially with SMAP-like simulators. The main objective of this work focuses on testing different dielectric models for soil moisture retrieval using the Combined Radar/Radiometer (ComRAD) ground-based L-band simulator developed jointly by NASA/GSFC and George Washington University (O'Neill et al., 2006). The ComRAD system was deployed during a field experiment in 2012 in order to provide long active/passive measurements of two crops under controlled conditions during an entire growing season. L-band passive data were acquired at a look angle of 40 degree from nadir at both horizontal & vertical polarization. Currently, there are many dielectric models available for soil moisture retrieval; however, four dielectric models (Mironov, Dobson, Wang & Schmugge and Hallikainen) were tested here and found to be promising for soil moisture retrieval (some with higher performances). All the above-mentioned dielectric models were integrated with Single Channel Algorithms using H (SCA-H) and V (SCA-V) polarizations for the soil moisture retrievals. All the ground-based observations were collected from test site-United States Department of Agriculture (USDA) OPE3, located a few miles away from NASA GSFC. Ground truth data were collected using a theta probe and in situ sensors which were then used for validation. Analysis indicated a higher performance in terms of soil moisture retrieval accuracy for the Mironov dielectric model (RMSE of 0.035 m3/m3), followed by Dobson, Wang & Schmugge, and Hallikainen. This analysis indicates that Mironov dielectric model is promising for passive-only microwave soil moisture retrieval and could be a useful choice for SMAP satellite soil moisture retrieval. Keywords: Dielectric models; Single Channel Algorithm, Combined Radar/Radiometer, Soil moisture; L band References: Behari, J. (2005). Dielectric Behavior of Soil (pp. 22-40). Springer Netherlands O'Neill, P. E., Lang, R. H., Kurum, M., Utku, C., & Carver, K. R. (2006), Multi-Sensor Microwave Soil Moisture Remote Sensing: NASA's Combined Radar/Radiometer (ComRAD) System. In IEEE MicroRad, 2006 (pp. 50-54). IEEE. Srivastava, P. K., Han, D., Rico Ramirez, M. A., & Islam, T. (2013), Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology, 498, 292-304. USDA OPE3 web site at http://www.ars.usda.gov/Research/.

Nonmaterialized Relations and the Support of Information Retrieval Applications by Relational Database Systems.

ERIC Educational Resources Information Center

Lynch, Clifford A.

1991-01-01

Describes several aspects of the problem of supporting information retrieval system query requirements in the relational database management system (RDBMS) environment and proposes an extension to query processing called nonmaterialized relations. User interactions with information retrieval systems are discussed, and nonmaterialized relations are…

SPIRES (Stanford Public Information REtrieval System). Annual Report (2d, 1968).

ERIC Educational Resources Information Center

Parker, Edwin B.; And Others

During 1968 the name of the project was changed from Stanford Physics Information Retrieval System" to "Stanford Public Information Retrieval System" to reflect the broadening of perspective and goals due to formal collaboration with Project BALLOTS (Bibliographic Automation of Large Library Operations using a Time-Sharing System).…

A Prototype of an Intelligent System for Information Retrieval: IOTA.

ERIC Educational Resources Information Center

Chiaramella, Y.; Defude, B.

1987-01-01

Discusses expert systems and their value as components of information retrieval systems related to semantic inference, and describes IOTA, a model of an intelligent information retrieval system which emphasizes natural language query processing. Experimental results are discussed and current and future developments are highlighted. (Author/LRW)

Content-based image retrieval by matching hierarchical attributed region adjacency graphs

NASA Astrophysics Data System (ADS)

Fischer, Benedikt; Thies, Christian J.; Guld, Mark O.; Lehmann, Thomas M.

2004-05-01

Content-based image retrieval requires a formal description of visual information. In medical applications, all relevant biological objects have to be represented by this description. Although color as the primary feature has proven successful in publicly available retrieval systems of general purpose, this description is not applicable to most medical images. Additionally, it has been shown that global features characterizing the whole image do not lead to acceptable results in the medical context or that they are only suitable for specific applications. For a general purpose content-based comparison of medical images, local, i.e. regional features that are collected on multiple scales must be used. A hierarchical attributed region adjacency graph (HARAG) provides such a representation and transfers image comparison to graph matching. However, building a HARAG from an image requires a restriction in size to be computationally feasible while at the same time all visually plausible information must be preserved. For this purpose, mechanisms for the reduction of the graph size are presented. Even with a reduced graph, the problem of graph matching remains NP-complete. In this paper, the Similarity Flooding approach and Hopfield-style neural networks are adapted from the graph matching community to the needs of HARAG comparison. Based on synthetic image material build from simple geometric objects, all visually similar regions were matched accordingly showing the framework's general applicability to content-based image retrieval of medical images.

Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

PubMed

Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

2014-01-01

Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

Study of systems and techniques for data base management

NASA Technical Reports Server (NTRS)

1976-01-01

Data management areas were studied to identify pertinent problems and issues that will affect future NASA data users in terms of performance and cost. Specific topics discussed include the identifications of potential NASA data users other than those normally discussed, consideration affecting the clustering of minicomputers, low cost computer system for information retrieval and analysis, the testing of minicomputer based data base management systems, ongoing work related to the use of dedicated systems for data base management, and the problems of data interchange among a community of NASA data users.

The Observed Behavior of the Bias in MODIS-retrieved Cloud Droplet Effective Radius through MISR-MODIS Data Fusion

NASA Astrophysics Data System (ADS)

Fu, D.; Di Girolamo, L.; Liang, L.; Zhao, G.

2017-12-01

Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude (Liang et al., 2015). Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud-top height and the spatial variability of the radiance field, sun-view geometry, and the driving meteorology had from reanalysis data. Our results show interesting relationships in Re bias behavior with these observed properties, revealing that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in MODIS-retrieved Re bias.

Intrinsic retrieval efficiency for quantum memories: A three-dimensional theory of light interaction with an atomic ensemble

NASA Astrophysics Data System (ADS)

Gujarati, Tanvi P.; Wu, Yukai; Duan, Luming

2018-03-01

Duan-Lukin-Cirac-Zoller quantum repeater protocol, which was proposed to realize long distance quantum communication, requires usage of quantum memories. Atomic ensembles interacting with optical beams based on off-resonant Raman scattering serve as convenient on-demand quantum memories. Here, a complete free space, three-dimensional theory of the associated read and write process for this quantum memory is worked out with the aim of understanding intrinsic retrieval efficiency. We develop a formalism to calculate the transverse mode structure for the signal and the idler photons and use the formalism to study the intrinsic retrieval efficiency under various configurations. The effects of atomic density fluctuations and atomic motion are incorporated by numerically simulating this system for a range of realistic experimental parameters. We obtain results that describe the variation in the intrinsic retrieval efficiency as a function of the memory storage time for skewed beam configuration at a finite temperature, which provides valuable information for optimization of the retrieval efficiency in experiments.

Retrievals with the Infrared Atmospheric Sounding Interferometer

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schlussel, Peter; Strow, L. Larrabee; Calbet, Xavier; Mango, Stephen A.

2007-01-01

The Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite was launched on October 19, 2006. The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations during the JAIVEx are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated.

Fast, axis-agnostic, dynamically summarized storage and retrieval for mass spectrometry data.

PubMed

Handy, Kyle; Rosen, Jebediah; Gillan, André; Smith, Rob

2017-01-01

Mass spectrometry, a popular technique for elucidating the molecular contents of experimental samples, creates data sets comprised of millions of three-dimensional (m/z, retention time, intensity) data points that correspond to the types and quantities of analyzed molecules. Open and commercial MS data formats are arranged by retention time, creating latency when accessing data across multiple m/z. Existing MS storage and retrieval methods have been developed to overcome the limitations of retention time-based data formats, but do not provide certain features such as dynamic summarization and storage and retrieval of point meta-data (such as signal cluster membership), precluding efficient viewing applications and certain data-processing approaches. This manuscript describes MzTree, a spatial database designed to provide real-time storage and retrieval of dynamically summarized standard and augmented MS data with fast performance in both m/z and RT directions. Performance is reported on real data with comparisons against related published retrieval systems.

Compliance program data management system for The Idaho National Engineering Laboratory/Environmental Protection Agency

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

Hertzler, C.L.; Poloski, J.P.; Bates, R.A.

1988-01-01

The Compliance Program Data Management System (DMS) developed at the Idaho National Engineering Laboratory (INEL) validates and maintains the integrity of data collected to support the Consent Order and Compliance Agreement (COCA) between the INEL and the Environmental Protection Agency (EPA). The system uses dBase III Plus programs and dBase III Plus in an interactive mode to enter, store, validate, manage, and retrieve analytical information provided on EPA Contract Laboratory Program (CLP) forms and CLP forms modified to accommodate 40 CFR 264 Appendix IX constituent analyses. Data analysis and presentation is performed utilizing SAS, a statistical analysis software program. Archivingmore » of data and results is performed at appropriate stages of data management. The DMS is useful for sampling and analysis programs where adherence to EPA CLP protocol, along with maintenance and retrieval of waste site investigation sampling results is desired or requested. 3 refs.« less

Sensitivity Analysis for Atmospheric Infrared Sounder (AIRS) CO2 Retrieval

NASA Technical Reports Server (NTRS)

Gat, Ilana

2012-01-01

The Atmospheric Infrared Sounder (AIRS) is a thermal infrared sensor able to retrieve the daily atmospheric state globally for clear as well as partially cloudy field-of-views. The AIRS spectrometer has 2378 channels sensing from 15.4 micrometers to 3.7 micrometers, of which a small subset in the 15 micrometers region has been selected, to date, for CO2 retrieval. To improve upon the current retrieval method, we extended the retrieval calculations to include a prior estimate component and developed a channel ranking system to optimize the channels and number of channels used. The channel ranking system uses a mathematical formalism to rapidly process and assess the retrieval potential of large numbers of channels. Implementing this system, we identifed a larger optimized subset of AIRS channels that can decrease retrieval errors and minimize the overall sensitivity to other iridescent contributors, such as water vapor, ozone, and atmospheric temperature. This methodology selects channels globally by accounting for the latitudinal, longitudinal, and seasonal dependencies of the subset. The new methodology increases accuracy in AIRS CO2 as well as other retrievals and enables the extension of retrieved CO2 vertical profiles to altitudes ranging from the lower troposphere to upper stratosphere. The extended retrieval method for CO2 vertical profile estimation using a maximum-likelihood estimation method. We use model data to demonstrate the beneficial impact of the extended retrieval method using the new channel ranking system on CO2 retrieval.

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

Nurses' information retrieval skills in psychiatric hospitals - are the requirements for evidence-based practice fulfilled?

PubMed

Koivunen, Marita; Välimäki, Maritta; Hätönen, Heli

2010-01-01

Nursing professionals have long recognized the importance to practice of research and the value of research evidence. Nurses still do not use research findings in practice. The purpose of this paper was to describe nurses' skills in using literature databases and the Internet in psychiatric hospitals and associations of nurses' gender, age, and job position with their information retrieval skills. The study was carried out in 2004 among nursing staff (N=183) on nine acute psychiatric wards in two psychiatric hospitals in Finland (n=180, response rate 98%). The Finnish version of the European Computer Driving Licence test (ECDL) was used as a data collection instrument. The study showed that there were clear deficits in information retrieval skills among nurses working in psychiatric hospitals. Thus, nurses' competence does not support the realization of evidence-based practice in the hospitals. Therefore, it is important to increase nurses' information retrieval skills by tailoring continuing education modules. It would be also advisable to develop centralized systems for the internal dissemination of research findings for the use of nursing staff.

USL NASA/RECON project presentations at the 1985 ACM Computer Science Conference: Abstracts and visuals

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Chum, Frank Y.; Gallagher, Suzy; Granier, Martin; Hall, Philip P.; Moreau, Dennis R.; Triantafyllopoulos, Spiros

1985-01-01

This Working Paper Series entry represents the abstracts and visuals associated with presentations delivered by six USL NASA/RECON research team members at the above named conference. The presentations highlight various aspects of NASA contract activities pursued by the participants as they relate to individual research projects. The titles of the six presentations are as follows: (1) The Specification and Design of a Distributed Workstation; (2) An Innovative, Multidisciplinary Educational Program in Interactive Information Storage and Retrieval; (3) Critical Comparative Analysis of the Major Commercial IS and R Systems; (4) Design Criteria for a PC-Based Common User Interface to Remote Information Systems; (5) The Design of an Object-Oriented Graphics Interface; and (6) Knowledge-Based Information Retrieval: Techniques and Applications.

Automated Text Markup for Information Retrieval from an Electronic Textbook of Infectious Disease

PubMed Central

Berrios, Daniel C.; Kehler, Andrew; Kim, David K.; Yu, Victor L.; Fagan, Lawrence M.

1998-01-01

The information needs of practicing clinicians frequently require textbook or journal searches. Making these sources available in electronic form improves the speed of these searches, but precision (i.e., the fraction of relevant to total documents retrieved) remains low. Improving the traditional keyword search by transforming search terms into canonical concepts does not improve search precision greatly. Kim et al. have designed and built a prototype system (MYCIN II) for computer-based information retrieval from a forthcoming electronic textbook of infectious disease. The system requires manual indexing by experts in the form of complex text markup. However, this mark-up process is time consuming (about 3 person-hours to generate, review, and transcribe the index for each of 218 chapters). We have designed and implemented a system to semiautomate the markup process. The system, information extraction for semiautomated indexing of documents (ISAID), uses query models and existing information-extraction tools to provide support for any user, including the author of the source material, to mark up tertiary information sources quickly and accurately.

Selected Mechanized Scientific and Technical Information Systems.

ERIC Educational Resources Information Center

Ackerman, Lynn, Ed.; And Others

The publication describes the following thirteen computer-based, operational systems designed primarily for the announcement, storage, retrieval and secondary distribution of scientific and technical reports: Defense Documentation Center; Highway Research Board; National Aeronautics and Space Administration; National Library of Medicine; U.S.…