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

Science.gov (United States)

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.

Interactive classification and content-based retrieval of tissue images

Science.gov (United States)

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.

Experimental evaluation of ontology-based HIV/AIDS frequently asked question retrieval system.

Science.gov (United States)

Ayalew, Yirsaw; Moeng, Barbara; Mosweunyane, Gontlafetse

2018-05-01

This study presents the results of experimental evaluations of an ontology-based frequently asked question retrieval system in the domain of HIV and AIDS. The main purpose of the system is to provide answers to questions on HIV/AIDS using ontology. To evaluate the effectiveness of the frequently asked question retrieval system, we conducted two experiments. The first experiment focused on the evaluation of the quality of the ontology we developed using the OQuaRE evaluation framework which is based on software quality metrics and metrics designed for ontology quality evaluation. The second experiment focused on evaluating the effectiveness of the ontology in retrieving relevant answers. For this we used an open-source information retrieval platform, Terrier, with retrieval models BM25 and PL2. For the measurement of performance, we used the measures mean average precision, mean reciprocal rank, and precision at 5. The results suggest that frequently asked question retrieval with ontology is more effective than frequently asked question retrieval without ontology in the domain of HIV/AIDS.

Relevance of useful visual words in object retrieval

Science.gov (United States)

Qi, Siyuan; Luo, Yupin

2013-07-01

The most popular methods in object retrieval are almost based on bag-of-words(BOW) which is both effective and efficient. In this paper we present a method use the relations between words of the vocabulary to improve the retrieval performance based on the BOW framework. In basic BOW retrieval framework, only a few words of the vocabulary is useful for retrieval, which are spatial consistent in images. We introduce a method to useful select useful words and build a relevance between these words. We combine useful relevance with basic BOW framework and query expansion as well. The useful relevance is able to discover latent related words which is not exist in the query image, so that we can get a more accurate vector model for retrieval. Combined with query expansion method, the retrieval performance are better and fewer time cost.

Design and development of semantic web-based system for computer science domain-specific information retrieval

Directory of Open Access Journals (Sweden)

Ritika Bansal

2016-09-01

Full Text Available In semantic web-based system, the concept of ontology is used to search results by contextual meaning of input query instead of keyword matching. From the research literature, there seems to be a need for a tool which can provide an easy interface for complex queries in natural language that can retrieve the domain-specific information from the ontology. This research paper proposes an IRSCSD system (Information retrieval system for computer science domain as a solution. This system offers advanced querying and browsing of structured data with search results automatically aggregated and rendered directly in a consistent user-interface, thus reducing the manual effort of users. So, the main objective of this research is design and development of semantic web-based system for integrating ontology towards domain-specific retrieval support. Methodology followed is a piecemeal research which involves the following stages. First Stage involves the designing of framework for semantic web-based system. Second stage builds the prototype for the framework using Protégé tool. Third Stage deals with the natural language query conversion into SPARQL query language using Python-based QUEPY framework. Fourth Stage involves firing of converted SPARQL queries to the ontology through Apache's Jena API to fetch the results. Lastly, evaluation of the prototype has been done in order to ensure its efficiency and usability. Thus, this research paper throws light on framework development for semantic web-based system that assists in efficient retrieval of domain-specific information, natural language query interpretation into semantic web language, creation of domain-specific ontology and its mapping with related ontology. This research paper also provides approaches and metrics for ontology evaluation on prototype ontology developed to study the performance based on accessibility of required domain-related information.

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

Science.gov (United States)

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

2017-12-01

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

Towards a Cloud Based Smart Traffic Management Framework

Science.gov (United States)

Rahimi, M. M.; Hakimpour, F.

2017-09-01

Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM) real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

Agricultural Library Information Retrieval Based on Improved Semantic Algorithm

OpenAIRE

Meiling , Xie

2014-01-01

International audience; To support users to quickly access information they need from the agricultural library’s vast information and to improve the low intelligence query service, a model for intelligent library information retrieval was constructed. The semantic web mode was introduced and the information retrieval framework was designed. The model structure consisted of three parts: Information data integration, user interface and information retrieval match. The key method supporting retr...

TOWARDS A CLOUD BASED SMART TRAFFIC MANAGEMENT FRAMEWORK

Directory of Open Access Journals (Sweden)

M. M. Rahimi

2017-09-01

Full Text Available Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

Tropospheric nitrogen dioxide column retrieval based on ground-based zenith-sky DOAS observations

Science.gov (United States)

Tack, F. M.; Hendrick, F.; Pinardi, G.; Fayt, C.; Van Roozendael, M.

2013-12-01

A retrieval approach has been developed to derive tropospheric NO2 vertical column amounts from ground-based zenith-sky measurements of scattered sunlight. Zenith radiance spectra are observed in the visible range by the BIRA-IASB Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument and analyzed by the DOAS technique, based on a least-squares spectral fitting. In recent years, this technique has shown to be a well-suited remote sensing tool for monitoring atmospheric trace gases. The retrieval algorithm is developed and validated based on a two month dataset acquired from June to July 2009 in the framework of the Cabauw (51.97° N, 4.93° E) Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). Once fully operational, the retrieval approach can be applied to observations from stations of the Network for the Detection of Atmospheric Composition Change (NDACC). The obtained tropospheric vertical column amounts are compared with the multi-axis retrieval from the BIRA-IASB MAX-DOAS instrument and the retrieval from a zenith-viewing only SAOZ instrument (Système d'Analyse par Observations Zénithales), owned by Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS). First results show a good agreement for the whole time series with the multi-axis retrieval (R = 0.82; y = 0.88x + 0.30) as well as with the SAOZ retrieval (R = 0.85; y = 0.76x + 0.28 ). Main error sources arise from the uncertainties in the determination of tropospheric and stratospheric air mass factors, the stratospheric NO2 abundances and the residual amount in the reference spectrum. However zenith-sky measurements have been commonly used over the last decades for stratospheric monitoring, this study also illustrates the suitability for retrieval of tropospheric column amounts. As there are long time series of zenith-sky acquisitions available, the developed approach offers new perspectives with regard to the use of observations from the NDACC

Supporting Polyrepresentation in a Quantum-inspired geometrical Retrieval Framework

DEFF Research Database (Denmark)

Frommholz, Ingo; Larsen, Birger; Piwowarski, Benjamin

2010-01-01

The relevance of a document has many facets, going beyond the usual topical one, which have to be considered to satisfy a user's information need. Multiple representations of documents, like user-given reviews or the actual document content, can give evidence towards certain facets of relevance....... In this respect polyrepresentation of documents, where such evidence is combined, is a crucial concept to estimate the relevance of a document. In this paper, we discuss how a geometrical retrieval framework inspired by quantum mechanics can be extended to support polyrepresentation. We show by example how...... of documents are not independent from a user point of view. Besides giving a principled framework for polyrepresentation, the potential of this approach is to capture and formalise the complex interdependent relationships that the different representations can have between each other....

Content-based histopathology image retrieval using CometCloud.

Science.gov (United States)

Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

2014-08-26

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two

A Survey: Framework of an Information Retrieval for Malay Translated Hadith Document

Directory of Open Access Journals (Sweden)

Zulkefli Nurul Syeilla Syazhween

2017-01-01

Full Text Available This paper reviews and analyses the limitation of the existing method used in the IR process in retrieving Malay Translated Hadith documents related to the search request. Traditional Malay Translated Hadith retrieval system has not focused on semantic extraction from text. The bag-of-words representation ignores the conceptual similarity of information in the query text and documents, which produce unsatisfactory retrieval results. Therefore, a more efficient IR framework is needed. This paper claims that the significant information extraction and subject-related information are actually important because the clues from this information can be used to search and find the relevance document to a query. Also, unimportant information can be discarded to represent the document content. So, semantic understanding of query and document is necessary to improve the effectiveness and accuracy of retrieval results for this domain study. Therefore, advance research is needed and it will be experimented in the future work. It is hoped that it will help users to search and find information regarding to the Malay Translated Hadith document.

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

Science.gov (United States)

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

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

A framework for evaluating automatic indexing or classification in the context of retrieval

DEFF Research Database (Denmark)

Golub, Korajlka; Soergel, Dagobert; Buchanan, George

2016-01-01

subject indexing, hard scientific evidence of their performance in operating information environments is scarce. A major reason for this is that research is usually conducted in laboratory conditions, excluding the complexities of real-life systems and situations. The paper reviews and discusses issues...... with existing evaluation approaches such as problems of aboutness and relevance assessments, implying the need to use more than a single “gold standard” method when evaluating indexing and retrieval and proposes a comprehensive evaluation framework. The framework is informed by a systematic review...

A contribution to semantic indexing and retrieval based on FCA - An application to song datasets

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Napoli , Amedeo

2012-01-01

International audience; Semantic indexing and retrieval is an important research area, as the available amount of information on the Web is growing more and more. In this paper, we introduce an original approach to semantic indexing and retrieval based on Formal Concept Analysis. The concept lattice is used as a semantic index and we propose an original algorithm for traversing the lattice and answering user queries. This framework has been used and evaluated on a song dataset.

View-based 3-D object retrieval

CERN Document Server

Gao, Yue

2014-01-01

Content-based 3-D object retrieval has attracted extensive attention recently and has applications in a variety of fields, such as, computer-aided design, tele-medicine,mobile multimedia, virtual reality, and entertainment. The development of efficient and effective content-based 3-D object retrieval techniques has enabled the use of fast 3-D reconstruction and model design. Recent technical progress, such as the development of camera technologies, has made it possible to capture the views of 3-D objects. As a result, view-based 3-D object retrieval has become an essential but challenging res

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

Science.gov (United States)

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

Efficient storage, retrieval and analysis of poker hands: An adaptive data framework

Directory of Open Access Journals (Sweden)

Gorawski Marcin

2017-12-01

Full Text Available In online gambling, poker hands are one of the most popular and fundamental units of the game state and can be considered objects comprising all the events that pertain to the single hand played. In a situation where tens of millions of poker hands are produced daily and need to be stored and analysed quickly, the use of relational databases no longer provides high scalability and performance stability. The purpose of this paper is to present an efficient way of storing and retrieving poker hands in a big data environment. We propose a new, read-optimised storage model that offers significant data access improvements over traditional database systems as well as the existing Hadoop file formats such as ORC, RCFile or SequenceFile. Through index-oriented partition elimination, our file format allows reducing the number of file splits that needs to be accessed, and improves query response time up to three orders of magnitude in comparison with other approaches. In addition, our file format supports a range of new indexing structures to facilitate fast row retrieval at a split level. Both index types operate independently of the Hive execution context and allow other big data computational frameworks such as MapReduce or Spark to benefit from the optimized data access path to the hand information. Moreover, we present a detailed analysis of our storage model and its supporting index structures, and how they are organised in the overall data framework. We also describe in detail how predicate based expression trees are used to build effective file-level execution plans. Our experimental tests conducted on a production cluster, holding nearly 40 billion hands which span over 4000 partitions, show that multi-way partition pruning outperforms other existing file formats, resulting in faster query execution times and better cluster utilisation.

Improve Biomedical Information Retrieval using Modified Learning to Rank Methods.

Science.gov (United States)

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

2016-06-14

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

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

Science.gov (United States)

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.

A Database Approach to Content-based XML retrieval

NARCIS (Netherlands)

Hiemstra, Djoerd

2003-01-01

This paper describes a rst prototype system for content-based retrieval from XML data. The system's design supports both XPath queries and complex information retrieval queries based on a language modelling approach to information retrieval. Evaluation using the INEX benchmark shows that it is

A content-based news video retrieval system: NVRS

Science.gov (United States)

Liu, Huayong; He, Tingting

2009-10-01

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

Content-Based Image Retrieval Based on Electromagnetism-Like Mechanism

Directory of Open Access Journals (Sweden)

Hamid A. Jalab

2013-01-01

Full Text Available Recently, many researchers in the field of automatic content-based image retrieval have devoted a remarkable amount of research looking for methods to retrieve the best relevant images to the query image. This paper presents a novel algorithm for increasing the precision in content-based image retrieval based on electromagnetism optimization technique. The electromagnetism optimization is a nature-inspired technique that follows the collective attraction-repulsion mechanism by considering each image as an electrical charge. The algorithm is composed of two phases: fitness function measurement and electromagnetism optimization technique. It is implemented on a database with 8,000 images spread across 80 classes with 100 images in each class. Eight thousand queries are fired on the database, and the overall average precision is computed. Experimental results of the proposed approach have shown significant improvement in the retrieval performance in regard to precision.

Web information retrieval based on ontology

Science.gov (United States)

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.

Retrieval Attempts Enhance Learning, but Retrieval Success (versus Failure) Does Not Matter

Science.gov (United States)

Kornell, Nate; Klein, Patricia Jacobs; Rawson, Katherine A.

2015-01-01

Retrieving information from memory enhances learning. We propose a 2-stage framework to explain the benefits of retrieval. Stage 1 takes place as one attempts to retrieve an answer, which activates knowledge related to the retrieval cue. Stage 2 begins when the answer becomes available, at which point appropriate connections are strengthened and…

IMAGE DESCRIPTIONS FOR SKETCH BASED IMAGE RETRIEVAL

OpenAIRE

SAAVEDRA RONDO, JOSE MANUEL; SAAVEDRA RONDO, JOSE MANUEL

2008-01-01

Due to the massive use of Internet together with the proliferation of media devices, content based image retrieval has become an active discipline in computer science. A common content based image retrieval approach requires that the user gives a regular image (e.g, a photo) as a query. However, having a regular image as query may be a serious problem. Indeed, people commonly use an image retrieval system because they do not count on the desired image. An easy alternative way t...

Cobra: A content-based video retrieval system

NARCIS (Netherlands)

Petkovic, M.; Jonker, W.; Jensen, C.S.; Jeffery, K.G.; Pokorny, J.; Saltenis, S.; Bertino, E.; Böhm, K.; Jarke, M.

2002-01-01

An increasing number of large publicly available video libraries results in a demand for techniques that can manipulate the video data based on content. In this paper, we present a content-based video retrieval system called Cobra. The system supports automatic extraction and retrieval of high-level

Active learning methods for interactive image retrieval.

Science.gov (United States)

Gosselin, Philippe Henri; Cord, Matthieu

2008-07-01

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

Harnessing the Power of Education Research Databases with the Pearl-Harvesting Methodological Framework for Information Retrieval

Science.gov (United States)

Sandieson, Robert W.; Kirkpatrick, Lori C.; Sandieson, Rachel M.; Zimmerman, Walter

2010-01-01

Digital technologies enable the storage of vast amounts of information, accessible with remarkable ease. However, along with this facility comes the challenge to find pertinent information from the volumes of nonrelevant information. The present article describes the pearl-harvesting methodological framework for information retrieval. Pearl…

Information retrieval for children based on the aggregated search paradigm

NARCIS (Netherlands)

Duarte Torres, Sergio

This report presents research to develop information services for children by expanding and adapting current Information retrieval technologies according to the search characteristics and needs of children. Concretely, we will employ the aggregated search paradigm as theoretical framework. The

Dialog-based Interactive Image Retrieval

OpenAIRE

Guo, Xiaoxiao; Wu, Hui; Cheng, Yu; Rennie, Steven; Feris, Rogerio Schmidt

2018-01-01

Existing methods for interactive image retrieval have demonstrated the merit of integrating user feedback, improving retrieval results. However, most current systems rely on restricted forms of user feedback, such as binary relevance responses, or feedback based on a fixed set of relative attributes, which limits their impact. In this paper, we introduce a new approach to interactive image search that enables users to provide feedback via natural language, allowing for more natural and effect...

Large-Scale Query-by-Image Video Retrieval Using Bloom Filters

OpenAIRE

Araujo, Andre; Chaves, Jason; Lakshman, Haricharan; Angst, Roland; Girod, Bernd

2016-01-01

We consider the problem of using image queries to retrieve videos from a database. Our focus is on large-scale applications, where it is infeasible to index each database video frame independently. Our main contribution is a framework based on Bloom filters, which can be used to index long video segments, enabling efficient image-to-video comparisons. Using this framework, we investigate several retrieval architectures, by considering different types of aggregation and different functions to ...

Wave Optics Based LEO-LEO Radio Occultation Retrieval

DEFF Research Database (Denmark)

von Benzon, Hans-Henrik; Høeg, Per

2016-01-01

of the atmospheric products such as the correct water vapor content in the atmosphere. These limitations can be overcome when a proper selected range of high frequency waves are used to probe the atmosphere. Probing frequencies close to the absorption line of water vapor have been included, thus allowing...... the retrieval of the water vapor content. Selecting the correct probing frequencies would make it possible to retrieve other information such as the content of ozone. The retrieval is performed through a number of processing steps which are based on the Full Spectrum Inversion (FSI) technique. The retrieval...... optics based retrieval chain is used on a number of examples and the retrieved atmospheric parameters are compared to the parameters from a global ECMWF analysis model. This model is used in a forward propagator that simulates the electromagnetic field amplitudes and phases at the receiver on board...

Fractional Fourier domain optical image hiding using phase retrieval algorithm based on iterative nonlinear double random phase encoding.

Science.gov (United States)

Wang, Xiaogang; Chen, Wen; Chen, Xudong

2014-09-22

We present a novel image hiding method based on phase retrieval algorithm under the framework of nonlinear double random phase encoding in fractional Fourier domain. Two phase-only masks (POMs) are efficiently determined by using the phase retrieval algorithm, in which two cascaded phase-truncated fractional Fourier transforms (FrFTs) are involved. No undesired information disclosure, post-processing of the POMs or digital inverse computation appears in our proposed method. In order to achieve the reduction in key transmission, a modified image hiding method based on the modified phase retrieval algorithm and logistic map is further proposed in this paper, in which the fractional orders and the parameters with respect to the logistic map are regarded as encryption keys. Numerical results have demonstrated the feasibility and effectiveness of the proposed algorithms.

Content-based multimedia retrieval: indexing and diversification

NARCIS (Netherlands)

van Leuken, R.H.

2009-01-01

The demand for efficient systems that facilitate searching in multimedia databases and collections is vastly increasing. Application domains include criminology, musicology, trademark registration, medicine and image or video retrieval on the web. This thesis discusses content-based retrieval

Content Based Medical Image Retrieval for Histopathological, CT and MRI Images

Directory of Open Access Journals (Sweden)

Swarnambiga AYYACHAMY

2013-09-01

Full Text Available A content based approach is followed for medical images. The purpose of this study is to access the stability of these methods for medical image retrieval. The methods used in color based retrieval for histopathological images are color co-occurrence matrix (CCM and histogram with meta features. For texture based retrieval GLCM (gray level co-occurrence matrix and local binary pattern (LBP were used. For shape based retrieval canny edge detection and otsu‘s method with multivariable threshold were used. Texture and shape based retrieval were implemented using MRI (magnetic resonance images. The most remarkable characteristics of the article are its content based approach for each medical imaging modality. Our efforts were focused on the initial visual search. From our experiment, histogram with meta features in color based retrieval for histopathological images shows a precision of 60 % and recall of 30 %. Whereas GLCM in texture based retrieval for MRI images shows a precision of 70 % and recall of 20 %. Shape based retrieval for MRI images shows a precision of 50% and recall of 25 %. The retrieval results shows that this simple approach is successful.

A Novel Optimization-Based Approach for Content-Based Image Retrieval

Directory of Open Access Journals (Sweden)

Manyu Xiao

2013-01-01

Full Text Available Content-based image retrieval is nowadays one of the possible and promising solutions to manage image databases effectively. However, with the large number of images, there still exists a great discrepancy between the users’ expectations (accuracy and efficiency and the real performance in image retrieval. In this work, new optimization strategies are proposed on vocabulary tree building, retrieval, and matching methods. More precisely, a new clustering strategy combining classification and conventional K-Means method is firstly redefined. Then a new matching technique is built to eliminate the error caused by large-scaled scale-invariant feature transform (SIFT. Additionally, a new unit mechanism is proposed to reduce the cost of indexing time. Finally, the numerical results show that excellent performances are obtained in both accuracy and efficiency based on the proposed improvements for image retrieval.

A Multisensor Approach to Global Retrievals of Land Surface Albedo

Directory of Open Access Journals (Sweden)

Aku Riihelä

2018-05-01

Full Text Available Satellite-based retrievals offer the most cost-effective way to comprehensively map the surface albedo of the Earth, a key variable for understanding the dynamics of radiative energy interactions in the atmosphere-surface system. Surface albedo retrievals have commonly been designed separately for each different spaceborne optical imager. Here, we introduce a novel type of processing framework that combines the data from two polar-orbiting optical imager families, the Advanced Very High-Resolution Radiometer (AVHRR and Moderate Resolution Imaging Spectroradiometer (MODIS. The goal of the paper is to demonstrate that multisensor albedo retrievals can provide a significant reduction in the sampling time required for a robust and comprehensive surface albedo retrieval, without a major degradation in retrieval accuracy, as compared to state-of-the-art single-sensor retrievals. We evaluated the multisensor retrievals against reference in situ albedo measurements and compare them with existing datasets. The results show that global land surface albedo retrievals with a sampling period of 10 days can offer near-complete spatial coverage, with a retrieval bias mostly comparable to existing single sensor datasets, except for bright surfaces (deserts and snow where the retrieval framework shows degraded performance because of atmospheric correction design compromises. A level difference is found between the single sensor datasets and the demonstrator developed here, pointing towards a need for further work in the atmospheric correction, particularly over bright surfaces, and inter-sensor radiance homogenization. The introduced framework is expandable to include other sensors in the future.

Content Based Retrieval System for Magnetic Resonance Images

International Nuclear Information System (INIS)

Trojachanets, Katarina

2010-01-01

The amount of medical images is continuously increasing as a consequence of the constant growth and development of techniques for digital image acquisition. Manual annotation and description of each image is impractical, expensive and time consuming approach. Moreover, it is an imprecise and insufficient way for describing all information stored in medical images. This induces the necessity for developing efficient image storage, annotation and retrieval systems. Content based image retrieval (CBIR) emerges as an efficient approach for digital image retrieval from large databases. It includes two phases. In the first phase, the visual content of the image is analyzed and the feature extraction process is performed. An appropriate descriptor, namely, feature vector is then associated with each image. These descriptors are used in the second phase, i.e. the retrieval process. With the aim to improve the efficiency and precision of the content based image retrieval systems, feature extraction and automatic image annotation techniques are subject of continuous researches and development. Including the classification techniques in the retrieval process enables automatic image annotation in an existing CBIR system. It contributes to more efficient and easier image organization in the system.Applying content based retrieval in the field of magnetic resonance is a big challenge. Magnetic resonance imaging is an image based diagnostic technique which is widely used in medical environment. According to this, the number of magnetic resonance images is enormously growing. Magnetic resonance images provide plentiful medical information, high resolution and specific nature. Thus, the capability of CBIR systems for image retrieval from large database is of great importance for efficient analysis of this kind of images. The aim of this thesis is to propose content based retrieval system architecture for magnetic resonance images. To provide the system efficiency, feature

Context based multimedia information retrieval

DEFF Research Database (Denmark)

Mølgaard, Lasse Lohilahti

The large amounts of digital media becoming available require that new approaches are developed for retrieving, navigating and recommending the data to users in a way that refl ects how we semantically perceive the content. The thesis investigates ways to retrieve and present content for users...... topics from a large collection of the transcribed speech to improve retrieval of spoken documents. The context modelling is done using a variant of probabilistic latent semantic analysis (PLSA), to extract properties of the textual sources that refl ect how humans perceive context. We perform PLSA...... of Wikipedia , as well as text-based semantic similarity. The final aspect investigated is how to include some of the structured data available in Wikipedia to include temporal information. We show that a multiway extension of PLSA makes it possible to extract temporally meaningful topics, better than using...

Content-based analysis improves audiovisual archive retrieval

NARCIS (Netherlands)

Huurnink, B.; Snoek, C.G.M.; de Rijke, M.; Smeulders, A.W.M.

2012-01-01

Content-based video retrieval is maturing to the point where it can be used in real-world retrieval practices. One such practice is the audiovisual archive, whose users increasingly require fine-grained access to broadcast television content. In this paper, we take into account the information needs

Improved image retrieval based on fuzzy colour feature vector

Science.gov (United States)

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

2013-03-01

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

Information retrieval system based on INIS tapes

International Nuclear Information System (INIS)

Pultorak, G.

1976-01-01

An information retrieval system based on the INIS computer tapes is described. It includes the three main elements of a computerized information system: a data base on a machine -readable medium, a collection of queries which represent the information needs from the data - base, and a set of programs by which the actual retrieval is done, according to the user's queries. The system is built for the center's computer, a CDC 3600, and its special features characterize, to a certain degree, the structure of the programs. (author)

Content-Based Multimedia Retrieval in the Presence of Unknown User Preferences

DEFF Research Database (Denmark)

Beecks, Christian; Assent, Ira; Seidl, Thomas

2011-01-01

Content-based multimedia retrieval requires an appropriate similarity model which reflects user preferences. When these preferences are unknown or when the structure of the data collection is unclear, retrieving the most preferable objects the user has in mind is challenging, as the notion...... address the problem of content-based multimedia retrieval in the presence of unknown user preferences. Our idea consists in performing content-based retrieval by considering all possibilities in a family of similarity models simultaneously. To this end, we propose a novel content-based retrieval approach...

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

Science.gov (United States)

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Retrieving handwriting by combining word spotting and manifold ranking

Science.gov (United States)

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%.

Design and Realization of Music Retrieval System Based on Feature Content

Directory of Open Access Journals (Sweden)

Li Lei

2015-01-01

Full Text Available As computer technology develops rapidly, retrieval systems have also undergone great changes. People are no longer contented with singular retrieval means, but are trying many other ways to retrieve feature content. When it comes to music, however, the complexity of sound is still preventing its retrieval from moving further forward. To solve this problem, systematic analysis and study is carried out on music retrieval system based on feature content. A music retrieval system model based on feature content consisting of technical approaches for processing and retrieving of extraction symbols of music feature content is built and realized. An SML model is proposed and tested on two different types of song sets. The result shows good performance of the system. Besides, the shortfalls of the model are also noted and the future prospects of the music retrieval system based on feature content are outlined.

Metadata and network API aspects of a framework for storing and retrieving civil infrastructure monitoring data

Science.gov (United States)

Wong, John-Michael; Stojadinovic, Bozidar

2005-05-01

A framework has been defined for storing and retrieving civil infrastructure monitoring data over a network. The framework consists of two primary components: metadata and network communications. The metadata component provides the descriptions and data definitions necessary for cataloging and searching monitoring data. The communications component provides Java classes for remotely accessing the data. Packages of Enterprise JavaBeans and data handling utility classes are written to use the underlying metadata information to build real-time monitoring applications. The utility of the framework was evaluated using wireless accelerometers on a shaking table earthquake simulation test of a reinforced concrete bridge column. The NEESgrid data and metadata repository services were used as a backend storage implementation. A web interface was created to demonstrate the utility of the data model and provides an example health monitoring application.

a Simulation-As Framework Facilitating Webgis Based Installation Planning

Science.gov (United States)

Zheng, Z.; Chang, Z. Y.; Fei, Y. F.

2017-09-01

Installation Planning is constrained by both natural and social conditions, especially for spatially sparse but functionally connected facilities. Simulation is important for proper deploy in space and configuration in function of facilities to make them a cohesive and supportive system to meet users' operation needs. Based on requirement analysis, we propose a framework to combine GIS and Agent simulation to overcome the shortness in temporal analysis and task simulation of traditional GIS. In this framework, Agent based simulation runs as a service on the server, exposes basic simulation functions, such as scenario configuration, simulation control, and simulation data retrieval to installation planners. At the same time, the simulation service is able to utilize various kinds of geoprocessing services in Agents' process logic to make sophisticated spatial inferences and analysis. This simulation-as-a-service framework has many potential benefits, such as easy-to-use, on-demand, shared understanding, and boosted performances. At the end, we present a preliminary implement of this concept using ArcGIS javascript api 4.0 and ArcGIS for server, showing how trip planning and driving can be carried out by agents.

Mobile object retrieval in server-based image databases

Science.gov (United States)

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.

Color-Based Image Retrieval from High-Similarity Image Databases

DEFF Research Database (Denmark)

Hansen, Michael Adsetts Edberg; Carstensen, Jens Michael

2003-01-01

Many image classification problems can fruitfully be thought of as image retrieval in a "high similarity image database" (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce...... a method for HSID retrieval using a similarity measure based on a linear combination of Jeffreys-Matusita (JM) distances between distributions of color (and color derivatives) estimated from a set of automatically extracted image regions. The weight coefficients are estimated based on optimal retrieval...... performance. Experimental results on the difficult task of visually identifying clones of fungal colonies grown in a petri dish and categorization of pelts show a high retrieval accuracy of the method when combined with standardized sample preparation and image acquisition....

A rapid place name locating algorithm based on ontology qualitative retrieval, ranking and recommendation

Science.gov (United States)

Fan, Hong; Zhu, Anfeng; Zhang, Weixia

2015-12-01

In order to meet the rapid positioning of 12315 complaints, aiming at the natural language expression of telephone complaints, a semantic retrieval framework is proposed which is based on natural language parsing and geographical names ontology reasoning. Among them, a search result ranking and recommended algorithms is proposed which is regarding both geo-name conceptual similarity and spatial geometry relation similarity. The experiments show that this method can assist the operator to quickly find location of 12,315 complaints, increased industry and commerce customer satisfaction.

Language-based multimedia information retrieval

NARCIS (Netherlands)

de Jong, Franciska M.G.; Gauvain, J.L.; Hiemstra, Djoerd; Netter, K.

2000-01-01

This paper describes various methods and approaches for language-based multimedia information retrieval, which have been developed in the projects POP-EYE and OLIVE and which will be developed further in the MUMIS project. All of these project aim at supporting automated indexing of video material

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Global polar geospatial information service retrieval based on search engine and ontology reasoning

Science.gov (United States)

Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Science.gov (United States)

El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

2015-11-01

Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

Working memory retrieval as a decision process.

Science.gov (United States)

Pearson, Benjamin; Raskevicius, Julius; Bays, Paul M; Pertzov, Yoni; Husain, Masud

2014-02-03

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation.

Exploiting database technology for object based event storage and retrieval

International Nuclear Information System (INIS)

Rawat, Anil; Rajan, Alpana; Tomar, Shailendra Singh; Bansal, Anurag

2005-01-01

This paper discusses the storage and retrieval of experimental data on relational databases. Physics experiments carried out using reactors and particle accelerators, generate huge amount of data. Also, most of the data analysis and simulation programs are developed using object oriented programming concepts. Hence, one of the most important design features of an experiment related software framework is the way object persistency is handled. We intend to discuss these issues in the light of the module developed by us for storing C++ objects in relational databases like Oracle. This module was developed under the POOL persistency framework being developed for LHC, CERN grid. (author)

Natural texture retrieval based on perceptual similarity measurement

Science.gov (United States)

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.

Learning Object Retrieval and Aggregation Based on Learning Styles

Science.gov (United States)

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…

A retrieval-based approach to eliminating hindsight bias.

Science.gov (United States)

Van Boekel, Martin; Varma, Keisha; Varma, Sashank

2017-03-01

Individuals exhibit hindsight bias when they are unable to recall their original responses to novel questions after correct answers are provided to them. Prior studies have eliminated hindsight bias by modifying the conditions under which original judgments or correct answers are encoded. Here, we explored whether hindsight bias can be eliminated by manipulating the conditions that hold at retrieval. Our retrieval-based approach predicts that if the conditions at retrieval enable sufficient discrimination of memory representations of original judgments from memory representations of correct answers, then hindsight bias will be reduced or eliminated. Experiment 1 used the standard memory design to replicate the hindsight bias effect in middle-school students. Experiments 2 and 3 modified the retrieval phase of this design, instructing participants beforehand that they would be recalling both their original judgments and the correct answers. As predicted, this enabled participants to form compound retrieval cues that discriminated original judgment traces from correct answer traces, and eliminated hindsight bias. Experiment 4 found that when participants were not instructed beforehand that they would be making both recalls, they did not form discriminating retrieval cues, and hindsight bias returned. These experiments delineate the retrieval conditions that produce-and fail to produce-hindsight bias.

Toward a Theoretical Framework for Information Science

Directory of Open Access Journals (Sweden)

Amanda Spink

2000-01-01

Full Text Available Information Science is beginning to develop a theoretical framework for the modeling of users’ interactions with information retrieval (IR technologies within the more holistic context of human information behavior (Spink, 1998b. This paper addresses the following questions: (1 What is the nature of Information Science? and (2 What theoretical framework and model is most appropriate for Information Science? This paper proposes a theoretical framework for Information Science based on an explication of the processes of human information coordinating behavior and information feedback that facilitate the relationship between human information behavior and human interaction with information retrieval (IR technologies (Web, digital libraries, etc..

Ontology-based Information Retrieval

DEFF Research Database (Denmark)

Styltsvig, Henrik Bulskov

In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information...... retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use......, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun...

Retrieval-Based Learning: Positive Effects of Retrieval Practice in Elementary School Children

Directory of Open Access Journals (Sweden)

Jeffrey D. Karpicke

2016-03-01

Full Text Available A wealth of research has demonstrated that practicing retrieval is a powerful way to enhance learning. However, nearly all prior research has examined retrieval practice with college students. Little is known about retrieval practice in children, and even less is known about possible individual differences in retrieval practice. In three experiments, 88 children (mean age 10 years studied a list of words and either restudied the items or practiced retrieving them. They then took a final free recall test (Experiments 1 and 2 or recognition test (Experiment 3. In all experiments, children showed robust retrieval practice effects. Although a range of individual differences in reading comprehension and processing speed were observed among these children, the benefits of retrieval practice were independent of these factors. The results contribute to the growing body of research supporting the mnemonic benefits of retrieval practice and provide preliminary evidence that practicing retrieval may be an effective learning strategy for children with varying levels of reading comprehension and processing speed.

Annotation and retrieval system of CAD models based on functional semantics

Science.gov (United States)

Wang, Zhansong; Tian, Ling; Duan, Wenrui

2014-11-01

CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.

Signature detection and matching for document image retrieval.

Science.gov (United States)

Zhu, Guangyu; Zheng, Yefeng; Doermann, David; Jaeger, Stefan

2009-11-01

As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document analysis problem. In this paper, we focus on two fundamental problems in signature-based document image retrieval. First, we propose a novel multiscale approach to jointly detecting and segmenting signatures from document images. Rather than focusing on local features that typically have large variations, our approach captures the structural saliency using a signature production model and computes the dynamic curvature of 2D contour fragments over multiple scales. This detection framework is general and computationally tractable. Second, we treat the problem of signature retrieval in the unconstrained setting of translation, scale, and rotation invariant nonrigid shape matching. We propose two novel measures of shape dissimilarity based on anisotropic scaling and registration residual error and present a supervised learning framework for combining complementary shape information from different dissimilarity metrics using LDA. We quantitatively study state-of-the-art shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple instances as query in document image retrieval. We further demonstrate our matching techniques in offline signature verification. Extensive experiments using large real-world collections of English and Arabic machine-printed and handwritten documents demonstrate the excellent performance of our approaches.

Retrieving top-k prestige-based relevant spatial web objects

DEFF Research Database (Denmark)

Cao, Xin; Cong, Gao; Jensen, Christian S.

2010-01-01

The location-aware keyword query returns ranked objects that are near a query location and that have textual descriptions that match query keywords. This query occurs inherently in many types of mobile and traditional web services and applications, e.g., Yellow Pages and Maps services. Previous...... of prestige-based relevance to capture both the textual relevance of an object to a query and the effects of nearby objects. Based on this, a new type of query, the Location-aware top-k Prestige-based Text retrieval (LkPT) query, is proposed that retrieves the top-k spatial web objects ranked according...... to both prestige-based relevance and location proximity. We propose two algorithms that compute LkPT queries. Empirical studies with real-world spatial data demonstrate that LkPT queries are more effective in retrieving web objects than a previous approach that does not consider the effects of nearby...

Functional alarming and information retrieval

International Nuclear Information System (INIS)

Goodstein, L.P.

1985-08-01

This paper deals with two facets of the design and efficient utilisation by operating personnel of computer-based interfaces for monitoring and the supervisory control of complex industrial systems - e.g., power stations, chemical plants, etc. These are alarming and information retrieval both of which are extremely sensitive to computerisation. For example, the advent of computers for display requires that some means of assuring easy and rapid access to large amounts of relevant stored information be found. In this paper, alarming and information retrieval are linked together through a multilevel functional description of the target plant. This representation serves as a framework for structuring the access to information as well as defining associated ''alarms'' at the various descriptive levels. Particular attention is paid to the level where mass and energy flows and balances are relevant. It is shown that the number of alarms here is reduced considerably while information about content and interrelationships is enhanced - which at the same time eases the retrieval problem. (author)

GRAMMAR RULE BASED INFORMATION RETRIEVAL MODEL FOR BIG DATA

Directory of Open Access Journals (Sweden)

T. Nadana Ravishankar

2015-07-01

Full Text Available Though Information Retrieval (IR in big data has been an active field of research for past few years; the popularity of the native languages presents a unique challenge in big data information retrieval systems. There is a need to retrieve information which is present in English and display it in the native language for users. This aim of cross language information retrieval is complicated by unique features of the native languages such as: morphology, compound word formations, word spelling variations, ambiguity, word synonym, other language influence and etc. To overcome some of these issues, the native language is modeled using a grammar rule based approach in this work. The advantage of this approach is that the native language is modeled and its unique features are encoded using a set of inference rules. This rule base coupled with the customized ontological system shows considerable potential and is found to show better precision and recall.

The Use of QBIC Content-Based Image Retrieval System

Directory of Open Access Journals (Sweden)

Ching-Yi Wu

2004-03-01

Full Text Available The fast increase in digital images has caught increasing attention on the development of image retrieval technologies. Content-based image retrieval (CBIR has become an important approach in retrieving image data from a large collection. This article reports our results on the use and users study of a CBIR system. Thirty-eight students majored in art and design were invited to use the IBM’s OBIC (Query by Image Content system through the Internet. Data from their information needs, behaviors, and retrieval strategies were collected through an in-depth interview, observation, and self-described think-aloud process. Important conclusions are:（1）There are four types of information needs for image data: implicit, inspirational, ever-changing, and purposive. The types of needs may change during the retrieval process. （2）CBIR is suitable for the example-type query, text retrieval is suitable for the scenario-type query, and image browsing is suitable for the symbolic query. （3）Different from text retrieval, detailed description of the query condition may lead to retrieval failure more easily. （4）CBIR is suitable for the domain-specific image collection, not for the images on the Word-Wide Web.[Article content in Chinese

Content-based TV sports video retrieval using multimodal analysis

Science.gov (United States)

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.

Content-based image retrieval: Color-selection exploited

NARCIS (Netherlands)

Broek, E.L. van den; Vuurpijl, L.G.; Kisters, P. M. F.; Schmid, J.C.M. von; Moens, M.F.; Busser, R. de; Hiemstra, D.; Kraaij, W.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

Content-Based Image Retrieval: Color-selection exploited

NARCIS (Netherlands)

Moens, Marie-Francine; van den Broek, Egon; Vuurpijl, L.G.; de Brusser, Rik; Kisters, P.M.F.; Hiemstra, Djoerd; Kraaij, Wessel; von Schmid, J.C.M.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

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

Science.gov (United States)

Kemp, Z. D. C.

2018-04-01

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

Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection

Directory of Open Access Journals (Sweden)

Zhimin Lin

2017-01-01

Full Text Available Target image detection based on a rapid serial visual presentation (RSVP paradigm is a typical brain-computer interface system with various applications, such as image retrieval. In an RSVP paradigm, a P300 component is detected to determine target images. This strategy requires high-precision single-trial P300 detection methods. However, the performance of single-trial detection methods is relatively lower than that of multitrial P300 detection methods. Image retrieval based on multitrial P300 is a new research direction. In this paper, we propose a triple-RSVP paradigm with three images being presented simultaneously and a target image appearing three times. Thus, multitrial P300 classification methods can be used to improve detection accuracy. In this study, these mechanisms were extended and validated, and the characteristics of the multi-RSVP framework were further explored. Two different P300 detection algorithms were also utilized in multi-RSVP to demonstrate that the scheme is universally applicable. Results revealed that the detection accuracy of the multi-RSVP paradigm was higher than that of the standard RSVP paradigm. The results validate the effectiveness of the proposed method, and this method can provide a whole new idea in the field of EEG-based target detection.

A humming retrieval system based on music fingerprint

Science.gov (United States)

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

A SIMULATION-AS-A-SERVICE FRAMEWORK FACILITATING WEBGIS BASED INSTALLATION PLANNING

Directory of Open Access Journals (Sweden)

Z. Zheng

2017-09-01

Full Text Available Installation Planning is constrained by both natural and social conditions, especially for spatially sparse but functionally connected facilities. Simulation is important for proper deploy in space and configuration in function of facilities to make them a cohesive and supportive system to meet users’ operation needs. Based on requirement analysis, we propose a framework to combine GIS and Agent simulation to overcome the shortness in temporal analysis and task simulation of traditional GIS. In this framework, Agent based simulation runs as a service on the server, exposes basic simulation functions, such as scenario configuration, simulation control, and simulation data retrieval to installation planners. At the same time, the simulation service is able to utilize various kinds of geoprocessing services in Agents’ process logic to make sophisticated spatial inferences and analysis. This simulation-as-a-service framework has many potential benefits, such as easy-to-use, on-demand, shared understanding, and boosted performances. At the end, we present a preliminary implement of this concept using ArcGIS javascript api 4.0 and ArcGIS for server, showing how trip planning and driving can be carried out by agents.

A visual retrieval environment for hypermedia information system

Energy Technology Data Exchange (ETDEWEB)

Lucarella, D; Zanzi, A [ENEL s.p.a., Centro Ricerca di Automatica, Cologno Monzese, Milan (Italy)

1995-03-01

The authors a graph-based object model that may be used as a uniform framework for direct manipulation of multimedia information. After an introduction motivating the need for abstraction and structuring mechanisms in hypermedia systems, the authors introduce the data model and the notion of perspective, a form of data abstraction that acts as a user interface to the system, providing control over the visibility of the objects and their properties. A perspective is defined to include an intention and an extension. The authors present a visual retrieval environment that effectively combines filtering, browsing, and navigation to provide an integrated view of the retrieval problem. Design and implementation issues are outlined for MORE (Multimedia Object Retrieval Environment), a prototype system relying on the proposed model. The focus is on the main user interface functionalities, and actual interaction sessions are presented including schema creation, information loading, and information retrieval

Exploring Database Improvements for GPM Constellation Precipitation Retrievals

Science.gov (United States)

Ringerud, S.; Kidd, C.; Skofronick Jackson, G.

2017-12-01

The Global Precipitation Measurement Mission (GPM) offers an unprecedented opportunity for understanding and mapping of liquid and frozen precipitation on a global scale. GPM mission development of physically based retrieval algorithms, for application consistently across the constellation radiometers, relies on combined active-passive retrievals from the GPM core satellite as a transfer standard. Radiative transfer modeling is then utilized to compute a priori databases at the frequency and footprint geometry of each individual radiometer. The Goddard Profiling Algorithm (GPROF) performs constellation retrievals across the GPM databases in a Bayesian framework, constraining searches using model data on a pixel-by-pixel basis. This work explores how the retrieval might be enhanced with additional information available within the brightness temperature observations themselves. In order to better exploit available information content, model water vapor is replaced with retrieved water vapor. Rather than treating each footprint as a 1D profile alone in space, information regarding Tb variability in the horizontal is added as well as variability in the time dimension. This additional information is tested and evaluated for retrieval improvement in the context of the Bayesian retrieval scheme. Retrieval differences are presented as a function of precipitation and surface type for evaluation of where the added information proves most effective.

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

Science.gov (United States)

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

2016-10-10

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

Intelligent image retrieval based on radiology reports

Energy Technology Data Exchange (ETDEWEB)

Gerstmair, Axel; Langer, Mathias; Kotter, Elmar [University Medical Center Freiburg, Department of Diagnostic Radiology, Freiburg (Germany); Daumke, Philipp; Simon, Kai [Averbis GmbH, Freiburg (Germany)

2012-12-15

To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

Intelligent image retrieval based on radiology reports

International Nuclear Information System (INIS)

Gerstmair, Axel; Langer, Mathias; Kotter, Elmar; Daumke, Philipp; Simon, Kai

2012-01-01

To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

Distinguishing Reconfiguration and Compound-cue Retrieval in Task Switching

Directory of Open Access Journals (Sweden)

Gordon D Logan

2010-10-01

Full Text Available Many researchers claim that task switching requires reconfiguration of the cognitive system. Others claim that task switching involves cue-based memory retrieval processes and not reconfiguration. We evaluate these competing claims by developing both reconfiguration and cue-based memory models in a common theoretical framework and by fitting the models to' target functions', which show how performance on individual target stimuli varies depending on the task subjects perform on the targets. Our analyses show that the process of compound-cue retrieval – using the task cue and the target as joint retrieval cues to select a response from memory – is sufficient to explain target functions for parity and magnitude judgments of digits and that reconfiguration does not seem to add anything to the explanation. We address the generality of this conclusion and speculate about the conditions under which reconfiguration may be necessary for task switching.

Multi-instance learning based on instance consistency for image retrieval

Science.gov (United States)

Zhang, Miao; Wu, Zhize; Wan, Shouhong; Yue, Lihua; Yin, Bangjie

2017-07-01

Multiple-instance learning (MIL) has been successfully utilized in image retrieval. Existing approaches cannot select positive instances correctly from positive bags which may result in a low accuracy. In this paper, we propose a new image retrieval approach called multiple instance learning based on instance-consistency (MILIC) to mitigate such issue. First, we select potential positive instances effectively in each positive bag by ranking instance-consistency (IC) values of instances. Then, we design a feature representation scheme, which can represent the relationship among bags and instances, based on potential positive instances to convert a bag into a single instance. Finally, we can use a standard single-instance learning strategy, such as the support vector machine, for performing object-based image retrieval. Experimental results on two challenging data sets show the effectiveness of our proposal in terms of accuracy and run time.

Low-dose multiple-information retrieval algorithm for X-ray grating-based imaging

International Nuclear Information System (INIS)

Wang Zhentian; Huang Zhifeng; Chen Zhiqiang; Zhang Li; Jiang Xiaolei; Kang Kejun; Yin Hongxia; Wang Zhenchang; Stampanoni, Marco

2011-01-01

The present work proposes a low dose information retrieval algorithm for X-ray grating-based multiple-information imaging (GB-MII) method, which can retrieve the attenuation, refraction and scattering information of samples by only three images. This algorithm aims at reducing the exposure time and the doses delivered to the sample. The multiple-information retrieval problem in GB-MII is solved by transforming a nonlinear equations set to a linear equations and adopting the nature of the trigonometric functions. The proposed algorithm is validated by experiments both on conventional X-ray source and synchrotron X-ray source, and compared with the traditional multiple-image-based retrieval algorithm. The experimental results show that our algorithm is comparable with the traditional retrieval algorithm and especially suitable for high Signal-to-Noise system.

Pulse retrieval algorithm for interferometric frequency-resolved optical gating based on differential evolution.

Science.gov (United States)

Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

2017-10-01

A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely, differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove the robustness of the algorithm against experimental artifacts and noise. These tests show that the integrated error-correction mechanisms of the iFROG method can be successfully used to remove the effect from timing errors and spectrally varying efficiency in the detection. Moreover, the accuracy and noise resilience of the new algorithm are shown to outperform retrieval based on the generalized projections algorithm, which is widely used as the standard method in FROG retrieval. The differential evolution algorithm is further validated with experimental data, measured with unamplified three-cycle pulses from a mode-locked Ti:sapphire laser. Additionally introducing group delay dispersion in the beam path, the retrieval results show excellent agreement with independent measurements with a commercial pulse measurement device based on spectral phase interferometry for direct electric-field retrieval. Further experimental tests with strongly attenuated pulses indicate resilience of differential-evolution-based retrieval against massive measurement noise.

Ontology of gaps in content-based image retrieval.

Science.gov (United States)

Deserno, Thomas M; Antani, Sameer; Long, Rodney

2009-04-01

Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potential for making a strong impact in diagnostics, research, and education. Research as reported in the scientific literature, however, has not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed (without supporting analysis) to the inability of these applications in overcoming the "semantic gap." The semantic gap divides the high-level scene understanding and interpretation available with human cognitive capabilities from the low-level pixel analysis of computers, based on mathematical processing and artificial intelligence methods. In this paper, we suggest a more systematic and comprehensive view of the concept of "gaps" in medical CBIR research. In particular, we define an ontology of 14 gaps that addresses the image content and features, as well as system performance and usability. In addition to these gaps, we identify seven 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, as the systematic analysis of gaps provides detailed insight in system comparison and helps to direct future research.

CIRQuL: Complex Information Retrieval Query Language

NARCIS (Netherlands)

Mihajlovic, V.; Hiemstra, Djoerd; Apers, Peter M.G.

In this paper we will present a new framework for the retrieval of XML documents. We will describe the extension for existing query languages (XPath and XQuery) geared toward ranked information retrieval and full-text search in XML documents. Furthermore we will present language models for ranked

An Effective Combined Feature For Web Based Image Retrieval

Directory of Open Access Journals (Sweden)

H.M.R.B Herath

2015-08-01

Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

Compounds in dictionary-based Cross-language information retrieval_revised

Directory of Open Access Journals (Sweden)

2002-01-01

Full Text Available Compound words form an important part of natural language. From the cross-lingual information retrieval (CLIR point of view it is important that many natural languages are highly productive with compounds, and translation resources cannot include entries for all compounds. Also, compounds are often content bearing words in a sentence. In Swedish, German and Finnish roughly one tenth of the words in a text prepared for information retrieval purposes are compounds. Important research questions concerning compound handling in dictionary-based cross-language information retrieval are 1 compound splitting into components, 2 normalisation of components, 3 translation of components and 4 query structuring for compounds and their components in the target language. The impact of compound processing on the performance of the cross-language information retrieval process is evaluated in this study and the results indicate that the effect is clearly positive.

COLDEX New Data Acquisition Framework

CERN Document Server

Grech, Christian

2015-01-01

COLDEX (COLD bore EXperiment) is an experiment of the TE-VSC group installed in the Super Proton Synchrotron (SPS) which mimics a LHC type cryogenic vacuum system. In the framework of the High Luminosity upgrade of the LHC (HL-LHC project), COLDEX has been recommissioned in 2014 in order to validate carbon coatings performances at cryogenic temperature with LHC type beams. To achieve this mission, a data acquisition system is needed to retrieve and store information from the different experiment’s systems (vacuum, cryogenics, controls, safety) and perform specific calculations. This work aimed to completely redesign, implement, test and operate a brand new data acquisition framework based on communication with the experiment’s PLCs for the devices potentially available over network. The communication protocol to the PLCs is based on data retrieval both from CERN middleware infrastructures (CMW, JAPC) and on a novel open source Simatic S7 data exchange package over TCP/IP (libnodave).

Multi-clues image retrieval based on improved color invariants

Science.gov (United States)

Liu, Liu; Li, Jian-Xun

2012-05-01

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

Collaborative Video Search Combining Video Retrieval with Human-Based Visual Inspection

NARCIS (Netherlands)

Hudelist, M.A.; Cobârzan, C.; Beecks, C.; van de Werken, Rob; Kletz, S.; Hürst, W.O.; Schoeffmann, K.

2016-01-01

We propose a novel video browsing approach that aims at optimally integrating traditional, machine-based retrieval methods with an interface design optimized for human browsing performance. Advanced video retrieval and filtering (e.g., via color and motion signatures, and visual concepts) on a

A Framework for Video Modeling

NARCIS (Netherlands)

Petkovic, M.; Jonker, Willem

In recent years, research in video databases has increased greatly, but relatively little work has been done in the area of semantic content-based retrieval. In this paper, we present a framework for video modelling with emphasis on semantic content of video data. The video data model presented

A Novel Technique for Shape Feature Extraction Using Content Based Image Retrieval

Directory of Open Access Journals (Sweden)

Dhanoa Jaspreet Singh

2016-01-01

Full Text Available With the advent of technology and multimedia information, digital images are increasing very quickly. Various techniques are being developed to retrieve/search digital information or data contained in the image. Traditional Text Based Image Retrieval System is not plentiful. Since it is time consuming as it require manual image annotation. Also, the image annotation differs with different peoples. An alternate to this is Content Based Image Retrieval (CBIR system. It retrieves/search for image using its contents rather the text, keywords etc. A lot of exploration has been compassed in the range of Content Based Image Retrieval (CBIR with various feature extraction techniques. Shape is a significant image feature as it reflects the human perception. Moreover, Shape is quite simple to use by the user to define object in an image as compared to other features such as Color, texture etc. Over and above, if applied alone, no descriptor will give fruitful results. Further, by combining it with an improved classifier, one can use the positive features of both the descriptor and classifier. So, a tryout will be made to establish an algorithm for accurate feature (Shape extraction in Content Based Image Retrieval (CBIR. The main objectives of this project are: (a To propose an algorithm for shape feature extraction using CBIR, (b To evaluate the performance of proposed algorithm and (c To compare the proposed algorithm with state of art techniques.

Learning effective color features for content based image retrieval in dermatology

NARCIS (Netherlands)

Bunte, Kerstin; Biehl, Michael; Jonkman, Marcel F.; Petkov, Nicolai

We investigate the extraction of effective color features for a content-based image retrieval (CBIR) application in dermatology. Effectiveness is measured by the rate of correct retrieval of images from four color classes of skin lesions. We employ and compare two different methods to learn

Retrieval and analysis of atmospheric XCO2 using ground-based spectral observation.

Science.gov (United States)

Qin, Xiu-Chun; Lei, Li-Ping; Kawasaki, Masahiro; Masafumi, Ohashi; Takahiro, Kuroki; Zeng, Zhao-Cheng; Zhang, Bing

2014-07-01

Atmospheric CO2 column concentration (column-averaged dry air mole fractions of atmospheric carbon dioxide) data obtained by ground-based hyperspectral observation is an important source of data for the verification and improvement of the results of CO2 retrieval based on satellite hyperspectral observation. However, few studies have been conducted on atmospheric CO2 column concentration retrieval based on ground-based spectral hyperspectral observation in China. In the present study, we carried out the ground-based hyperspectral observation in Xilingol Grassland, Inner Mongolia of China by using an observation system which is consisted of an optical spectral analyzer, a sun tracker, and some other elements. The atmospheric CO2 column concentration was retrieved using the observed hyperspectral data. The effect of a wavelength shift of the observation spectra and the meteorological parameters on the retrieval precision of the atmospheric CO2 concentration was evaluated and analyzed. The results show that the mean value of atmospheric CO2 concentration was 390.9 microg x mL(-1) in the study area during the observing period from July to September. The shift of wavelength in the range between -0.012 and 0.042 nm will generally lead to 1 microg x mL(-1) deviation in the CO2 retrievals. This study also revealed that the spectral transmittance was sensitive to meteorological parameters in the wavelength range of 6 357-6 358, 6 360-6 361, and 6 363-6 364 cm(-1). By comparing the CO2 retrievals derived from the meteorological parameters observed in synchronous and non-synchronous time, respectively, with the spectral observation, it was showed that the concentration deviation caused by using the non-synchronously observed meteorological parameters is ranged from 0.11 to 4 microg x mL(-1). These results can be used as references for the further improvement of retrieving CO2 column concentration based on spectral observation.

Design Guidelines for a Content-Based Image Retrieval Color-Selection Interface

NARCIS (Netherlands)

Eggen, Berry; van den Broek, Egon; van der Veer, Gerrit C.; Kisters, Peter M.F.; Willems, Rob; Vuurpijl, Louis G.

2004-01-01

In Content-Based Image Retrieval (CBIR) two query-methods exist: query-by-example and query-by-memory. The user either selects an example image or selects image features retrieved from memory (such as color, texture, spatial attributes, and shape) to define his query. Hitherto, research on CBIR

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

Science.gov (United States)

Wang, James Z.; Du, Yanping

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

A 3D model retrieval approach based on Bayesian networks lightfield descriptor

Science.gov (United States)

Xiao, Qinhan; Li, Yanjun

2009-12-01

A new 3D model retrieval methodology is proposed by exploiting a novel Bayesian networks lightfield descriptor (BNLD). There are two key novelties in our approach: (1) a BN-based method for building lightfield descriptor; and (2) a 3D model retrieval scheme based on the proposed BNLD. To overcome the disadvantages of the existing 3D model retrieval methods, we explore BN for building a new lightfield descriptor. Firstly, 3D model is put into lightfield, about 300 binary-views can be obtained along a sphere, then Fourier descriptors and Zernike moments descriptors can be calculated out from binaryviews. Then shape feature sequence would be learned into a BN model based on BN learning algorithm; Secondly, we propose a new 3D model retrieval method by calculating Kullback-Leibler Divergence (KLD) between BNLDs. Beneficial from the statistical learning, our BNLD is noise robustness as compared to the existing methods. The comparison between our method and the lightfield descriptor-based approach is conducted to demonstrate the effectiveness of our proposed methodology.

Content Based Radiographic Images Indexing and Retrieval Using Pattern Orientation Histogram

Directory of Open Access Journals (Sweden)

Abolfazl Lakdashti

2008-06-01

Full Text Available Introduction: Content Based Image Retrieval (CBIR is a method of image searching and retrieval in a  database. In medical applications, CBIR is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. As the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retrieval is increasingly  becoming a necessity.  Materials and Methods: This paper presents a new content based radiographic image retrieval approach  based on histogram of pattern orientations, namely pattern orientation histogram (POH. POH represents  the  spatial  distribution  of  five  different  pattern  orientations:  vertical,  horizontal,  diagonal  down/left,  diagonal down/right and non-orientation. In this method, a given image is first divided into image-blocks  and  the  frequency  of  each  type  of  pattern  is  determined  in  each  image-block.  Then,  local  pattern  histograms for each of these image-blocks are computed.   Results: The method was compared to two well known texture-based image retrieval methods: Tamura  and  Edge  Histogram  Descriptors  (EHD  in  MPEG-7  standard.  Experimental  results  based  on  10000  IRMA  radiography  image  dataset,  demonstrate  that  POH  provides  better  precision  and  recall  rates  compared to Tamura and EHD. For some images, the recall and precision rates obtained by POH are,  respectively, 48% and 18% better than the best of the two above mentioned methods.    Discussion and Conclusion: Since we exploit the absolute location of the pattern in the image as well as  its global composition, the proposed matching method can retrieve semantically similar medical images.

Mutual information based feature selection for medical image retrieval

Science.gov (United States)

Zhi, Lijia; Zhang, Shaomin; Li, Yan

2018-04-01

In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

Qualification of a Null Lens Using Image-Based Phase Retrieval

Science.gov (United States)

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.

Evolutionary Computing Methods for Spectral Retrieval

Science.gov (United States)

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

2009-01-01

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

STUDY COMPARISON OF SVM-, K-NN- AND BACKPROPAGATION-BASED CLASSIFIER FOR IMAGE RETRIEVAL

Directory of Open Access Journals (Sweden)

Muhammad Athoillah

2015-03-01

Full Text Available Classification is a method for compiling data systematically according to the rules that have been set previously. In recent years classification method has been proven to help many people’s work, such as image classification, medical biology, traffic light, text classification etc. There are many methods to solve classification problem. This variation method makes the researchers find it difficult to determine which method is best for a problem. This framework is aimed to compare the ability of classification methods, such as Support Vector Machine (SVM, K-Nearest Neighbor (K-NN, and Backpropagation, especially in study cases of image retrieval with five category of image dataset. The result shows that K-NN has the best average result in accuracy with 82%. It is also the fastest in average computation time with 17,99 second during retrieve session for all categories class. The Backpropagation, however, is the slowest among three of them. In average it needed 883 second for training session and 41,7 second for retrieve session.

Progress in Understanding the Impacts of 3-D Cloud Structure on MODIS Cloud Property Retrievals for Marine Boundary Layer Clouds

Science.gov (United States)

Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu

2016-01-01

Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).

Region-Based Color Image Indexing and Retrieval

DEFF Research Database (Denmark)

Kompatsiaris, Ioannis; Triantafyllou, Evangelia; Strintzis, Michael G.

2001-01-01

In this paper a region-based color image indexing and retrieval algorithm is presented. As a basis for the indexing, a novel K-Means segmentation algorithm is used, modified so as to take into account the coherence of the regions. A new color distance is also defined for this algorithm. Based on ....... Experimental results demonstrate the performance of the algorithm. The development of an intelligent image content-based search engine for the World Wide Web is also presented, as a direct application of the presented algorithm....

Representation and alignment of sung queries for music information retrieval

Science.gov (United States)

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.

AFFECT: Altered-Fidelity Framework for Enhancing Cognition and Training

Directory of Open Access Journals (Sweden)

Ryan Patrick McMahan

2016-11-01

Full Text Available In this paper, we present a new framework for analyzing and designing virtual reality (VR techniques. This framework is based on two concepts—system fidelity (i.e., the degree with which real-world experiences are reproduced by a system and memory (i.e., the formation and activation of perceptual, cognitive, and motor networks of neurons. The premise of the framework is to manipulate an aspect of system fidelity in order to assist a stage of memory. We call it the Altered-Fidelity Framework for Enhancing Cognition and Training (AFFECT. AFFECT provides nine categories of approaches to altering system fidelity to positively affect learning or training. These categories are based on the intersections of three aspects of system fidelity (interaction fidelity, scenario fidelity, and display fidelity and three stages of memory (encoding, implicit retrieval, and explicit retrieval. In addition to discussing the details of our new framework, we show how AFFECT can be used as a tool for analyzing and categorizing VR techniques designed to facilitate learning or training. We also demonstrate how AFFECT can be used as a design space for creating new VR techniques intended for educational and training systems.

Ground-based FTIR retrievals of SF6 on Reunion Island

Directory of Open Access Journals (Sweden)

M. Zhou

2018-02-01

Full Text Available SF6 total columns were successfully retrieved from FTIR (Fourier transform infrared measurements (Saint Denis and Maïdo on Reunion Island (21° S, 55° E between 2004 and 2016 using the SFIT4 algorithm: the retrieval strategy and the error budget were presented. The FTIR SF6 retrieval has independent information in only one individual layer, covering the whole of the troposphere and the lower stratosphere. The trend in SF6 was analysed based on the FTIR-retrieved dry-air column-averaged mole fractions (XSF6 on Reunion Island, the in situ measurements at America Samoa (SMO and the collocated satellite measurements (Michelson Interferometer for Passive Atmospheric Sounding, MIPAS, and Atmospheric Chemistry Experiment Fourier Transform Spectrometer, ACE-FTS in the southern tropics. The SF6 annual growth rate from FTIR retrievals is 0.265 ± 0.013 pptv year−1 for 2004–2016, which is slightly weaker than that from the SMO in situ measurements (0.285 ± 0.002 pptv year−1 for the same time period. The SF6 trend in the troposphere from MIPAS and ACE-FTS observations is also close to the ones from the FTIR retrievals and the SMO in situ measurements.

Ground-based FTIR retrievals of SF6 on Reunion Island

Science.gov (United States)

Zhou, Minqiang; Langerock, Bavo; Vigouroux, Corinne; Wang, Pucai; Hermans, Christian; Stiller, Gabriele; Walker, Kaley A.; Dutton, Geoff; Mahieu, Emmanuel; De Mazière, Martine

2018-02-01

SF6 total columns were successfully retrieved from FTIR (Fourier transform infrared) measurements (Saint Denis and Maïdo) on Reunion Island (21° S, 55° E) between 2004 and 2016 using the SFIT4 algorithm: the retrieval strategy and the error budget were presented. The FTIR SF6 retrieval has independent information in only one individual layer, covering the whole of the troposphere and the lower stratosphere. The trend in SF6 was analysed based on the FTIR-retrieved dry-air column-averaged mole fractions (XSF6) on Reunion Island, the in situ measurements at America Samoa (SMO) and the collocated satellite measurements (Michelson Interferometer for Passive Atmospheric Sounding, MIPAS, and Atmospheric Chemistry Experiment Fourier Transform Spectrometer, ACE-FTS) in the southern tropics. The SF6 annual growth rate from FTIR retrievals is 0.265 ± 0.013 pptv year-1 for 2004-2016, which is slightly weaker than that from the SMO in situ measurements (0.285 ± 0.002 pptv year-1) for the same time period. The SF6 trend in the troposphere from MIPAS and ACE-FTS observations is also close to the ones from the FTIR retrievals and the SMO in situ measurements.

Cross document ontology based information for multimedia retrieval

NARCIS (Netherlands)

Reidsma, Dennis; Kuper, Jan; Declerck, T.; Saggion, H.; Cunningham, H.; Ganter, B.; de Moor, A.

2003-01-01

This paper describes the MUMIS project, which applies ontology based Information Extraction to improve the results of Information Retrieval in multimedia archives. It makes use of a domain specific ontology, multilingual lexicons and reasoning algorithms to automatically create a semantic annotation

Phase retrieval for X-ray in-line phase contrast imaging

International Nuclear Information System (INIS)

Scattarella, F.; Bellotti, R.; Tangaro, S.; Gargano, G.; Giannini, C.

2011-01-01

A review article about phase retrieval problem in X-ray phase contrast imaging is presented. A simple theoretical framework of Fresnel diffraction imaging by X-rays is introduced. A review of the most important methods for phase retrieval in free-propagation-based X-ray imaging and a new method developed by our collaboration are shown. The proposed algorithm, Combined Mixed Approach (CMA) is based on a mixed transfer function and transport of intensity approach, and it requires at most an initial approximate estimate of the average phase shift introduced by the object as prior knowledge. The accuracy with which this initial estimate is known determines the convenience speed of algorithm. The new proposed algorithm is based on the retrieval of both the object phase and its complex conjugate. The results obtained by the algorithm on simulated data have shown that the obtained reconstructed phase maps are characterized by particularly low normalized mean square errors. The algorithm was also tested on noisy experimental phase contrast data, showing a good efficiency in recovering phase information and enhancing the visibility of details inside soft tissues.

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

Science.gov (United States)

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.

Learning Psychological Research and Statistical Concepts using Retrieval-based Practice

OpenAIRE

Stephen Wee Hun eLim; Gavin Jun Peng eNg; Gabriel Qi Hao eWong

2015-01-01

Research methods and statistics are an indispensable subject in the undergraduate psychology curriculum, but there are challenges associated with engaging students in it, such as making learning durable. Here we hypothesized that retrieval-based learning promotes long-term retention of statistical knowledge in psychology. Participants either studied the educational material in four consecutive periods, or studied it just once and practiced retrieving the information in the subsequent three pe...

Graph-Based Interactive Bibliographic Information Retrieval Systems

Science.gov (United States)

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…

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

Science.gov (United States)

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.

2007-2017: 10 years of IASI CO retrievals

Science.gov (United States)

George, M.; Clerbaux, C.; Hadji-Lazaro, J.; Pierre-Francois, C.; Hurtmans, D.; Edwards, D. P.; Worden, H. M.; Deeter, M. N.; Mao, D.; August, T.; Crapeau, M.

2017-12-01

Carbon monoxide (CO) is an important trace gas for understanding air quality and atmospheric composition. It is a good tracer of pollution plumes and atmospheric dynamics. IASI CO concentrations are retrieved from the radiance data using the Fast Operational Retrievals on Layers for IASI (FORLI) algorithm, based on the Optimal Estimation theory. The operational production is performed at EUMETSAT and the products are distributed in NRT via EUMETCast under the AC SAF auspices. We present here an analysis of 10 years of global distributions of CO. Improvements of the last FORLI-CO version (v20151001) will be shown. Updates in the auxiliary parameters (temperature, cloud information) have an impact on the retrieved product. Comparison with MOPITT CO data (v7T, record starting in 2000) was performed, both for partial and total columns. Harmonizing IASI and MOPITT CO products is challenging: a method using corrective factors (developed in the framework of the QA4ECV project) will be presented.

Framework for near-field-communication-based geo-localization and personalization for Android-based smartphones--application in hospital environments.

Science.gov (United States)

Meng, Philipp; Fehre, Karsten; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

2014-01-01

Various applications using near field communication (NFC) have been developed for the medical sector. As a method of short-range wireless contact-driven data transfer, NFC is a useful tool in medicine. It can be used to transfer data such as blood pressure, control adherence to medication, or transmit in vivo data. The first proposed general framework uses NFC as a mechanism for indoor geo-localization in hospitals. NFC geo-localization is economical compared to classical concepts using indoor GPS or WLAN triangulation, and the granularity of location retrieval can be defined at a tag level. Using this framework, we facilitate the development of medical applications that require exact indoor geo-localization. Multi-user Android systems are addressed in the second framework. Using private NFC tags, users are able to carry on their personal settings for enabled applications. This eliminates the need for multiple user accounts on common Android devices, improves usability, and eases technical administration. Based on the prototypes presented here, we show a novel concept of using NFC-enabled Android devices in hospital environments.

Rocchio-based relevance feedback in video event retrieval

NARCIS (Netherlands)

Pingen, G.L.J.; de Boer, M.H.T.; Aly, Robin; Amsaleg, Laurent; Guðmundsson, Gylfi Þór; Gurrin, Cathal; Jónsson, Björn Þór; Satoh, Shin’ichi

This paper investigates methods for user and pseudo relevance feedback in video event retrieval. Existing feedback methods achieve strong performance but adjust the ranking based on few individual examples. We propose a relevance feedback algorithm (ARF) derived from the Rocchio method, which is a

Optical multiple-image encryption based on multiplane phase retrieval and interference

International Nuclear Information System (INIS)

Chen, Wen; Chen, Xudong

2011-01-01

In this paper, we propose a new method for optical multiple-image encryption based on multiplane phase retrieval and interference. An optical encoding system is developed in the Fresnel domain. A phase-only map is iteratively extracted based on a multiplane phase retrieval algorithm, and multiple plaintexts are simultaneously encrypted. Subsequently, the extracted phase-only map is further encrypted into two phase-only masks based on a non-iterative interference algorithm. During image decryption, the advantages and security of the proposed optical cryptosystem are analyzed. Numerical results are presented to demonstrate the validity of the proposed optical multiple-image encryption method

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

Science.gov (United States)

Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

2017-08-25

We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

Sy Mohameth-François

2012-01-01

Full Text Available Abstract 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

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

Science.gov (United States)

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

2016-01-01

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

Retrieval of Landuse and Hydrology-based Parameters from ...

African Journals Online (AJOL)

Landuse and hydrology-based information on the Volta Lake Basin have been retrieved from Satellite remote sensing data. The results obtained could be applied in Hydro-Geographical Information System models, such as the TOPMODEL, for water balance studies. Eight Synthetic Aperture Radar Precision Images of the ...

Design and development of a content-based medical image retrieval system for spine vertebrae irregularity.

Science.gov (United States)

Mustapha, Aouache; Hussain, Aini; Samad, Salina Abdul; Zulkifley, Mohd Asyraf; Diyana Wan Zaki, Wan Mimi; Hamid, Hamzaini Abdul

2015-01-16

Content-based medical image retrieval (CBMIR) system enables medical practitioners to perform fast diagnosis through quantitative assessment of the visual information of various modalities. In this paper, a more robust CBMIR system that deals with both cervical and lumbar vertebrae irregularity is afforded. It comprises three main phases, namely modelling, indexing and retrieval of the vertebrae image. The main tasks in the modelling phase are to improve and enhance the visibility of the x-ray image for better segmentation results using active shape model (ASM). The segmented vertebral fractures are then characterized in the indexing phase using region-based fracture characterization (RB-FC) and contour-based fracture characterization (CB-FC). Upon a query, the characterized features are compared to the query image. Effectiveness of the retrieval phase is determined by its retrieval, thus, we propose an integration of the predictor model based cross validation neural network (PMCVNN) and similarity matching (SM) in this stage. The PMCVNN task is to identify the correct vertebral irregularity class through classification allowing the SM process to be more efficient. Retrieval performance between the proposed and the standard retrieval architectures are then compared using retrieval precision (Pr@M) and average group score (AGS) measures. Experimental results show that the new integrated retrieval architecture performs better than those of the standard CBMIR architecture with retrieval results of cervical (AGS > 87%) and lumbar (AGS > 82%) datasets. The proposed CBMIR architecture shows encouraging results with high Pr@M accuracy. As a result, images from the same visualization class are returned for further used by the medical personnel.

Implementation and evaluation of a medical image management system with content-based retrieval support

International Nuclear Information System (INIS)

Carita, Edilson Carlos; Seraphim, Enzo; Honda, Marcelo Ossamu; Azevedo-Marques, Paulo Mazzoncini de

2008-01-01

Objective: the present paper describes the implementation and evaluation of a medical images management system with content-based retrieval support (PACS-CBIR) integrating modules focused on images acquisition, storage and distribution, and text retrieval by keyword and images retrieval by similarity. Materials and methods: internet-compatible technologies were utilized for the system implementation with free ware, and C ++ , PHP and Java languages on a Linux platform. There is a DICOM-compatible image management module and two query modules, one of them based on text and the other on similarity of image texture attributes. Results: results demonstrate an appropriate images management and storage, and that the images retrieval time, always < 15 sec, was found to be good by users. The evaluation of retrieval by similarity has demonstrated that the selected images extractor allowed the sorting of images according to anatomical areas. Conclusion: based on these results, one can conclude that the PACS-CBIR implementation is feasible. The system has demonstrated to be DICOM-compatible, and that it can be integrated with the local information system. The similar images retrieval functionality can be enhanced by the introduction of further descriptors. (author)

Medical Content Searching, Retrieving, and Sharing Over the Internet: Lessons Learned From the mEducator Through a Scenario-Based Evaluation

Science.gov (United States)

Spachos, Dimitris; Mylläri, Jarkko; Giordano, Daniela; Dafli, Eleni; Mitsopoulou, Evangelia; Schizas, Christos N; Pattichis, Constantinos; Nikolaidou, Maria

2015-01-01

Background The mEducator Best Practice Network (BPN) implemented and extended standards and reference models in e-learning to develop innovative frameworks as well as solutions that enable specialized state-of-the-art medical educational content to be discovered, retrieved, shared, and re-purposed across European Institutions, targeting medical students, doctors, educators and health care professionals. Scenario-based evaluation for usability testing, complemented with data from online questionnaires and field notes of users’ performance, was designed and utilized for the evaluation of these solutions. Objective The objective of this work is twofold: (1) to describe one instantiation of the mEducator BPN solutions (mEducator3.0 - “MEdical Education LINnked Arena” MELINA+) with a focus on the metadata schema used, as well as on other aspects of the system that pertain to usability and acceptance, and (2) to present evaluation results on the suitability of the proposed metadata schema for searching, retrieving, and sharing of medical content and with respect to the overall usability and acceptance of the system from the target users. Methods A comprehensive evaluation methodology framework was developed and applied to four case studies, which were conducted in four different countries (ie, Greece, Cyprus, Bulgaria and Romania), with a total of 126 participants. In these case studies, scenarios referring to creating, sharing, and retrieving medical educational content using mEducator3.0 were used. The data were collected through two online questionnaires, consisting of 36 closed-ended questions and two open-ended questions that referred to mEducator 3.0 and through the use of field notes during scenario-based evaluations. Results The main findings of the study showed that even though the informational needs of the mEducator target groups were addressed to a satisfactory extent and the metadata schema supported content creation, sharing, and retrieval from an end

Multi-stage phase retrieval algorithm based upon the gyrator transform.

Science.gov (United States)

Rodrigo, José A; Duadi, Hamootal; Alieva, Tatiana; Zalevsky, Zeev

2010-01-18

The gyrator transform is a useful tool for optical information processing applications. In this work we propose a multi-stage phase retrieval approach based on this operation as well as on the well-known Gerchberg-Saxton algorithm. It results in an iterative algorithm able to retrieve the phase information using several measurements of the gyrator transform power spectrum. The viability and performance of the proposed algorithm is demonstrated by means of several numerical simulations and experimental results.

Multi-stage phase retrieval algorithm based upon the gyrator transform

OpenAIRE

Rodrigo Martín-Romo, José Augusto; Duadi, Hamootal; Alieva, Tatiana Krasheninnikova; Zalevsky, Zeev

2010-01-01

The gyrator transform is a useful tool for optical information processing applications. In this work we propose a multi-stage phase retrieval approach based on this operation as well as on the well-known Gerchberg-Saxton algorithm. It results in an iterative algorithm able to retrieve the phase information using several measurements of the gyrator transform power spectrum. The viability and performance of the proposed algorithm is demonstrated by means of several numerical simulations and exp...

Retrieval of Brain Tumors by Adaptive Spatial Pooling and Fisher Vector Representation.

Science.gov (United States)

Cheng, Jun; Yang, Wei; Huang, Meiyan; Huang, Wei; Jiang, Jun; Zhou, Yujia; Yang, Ru; Zhao, Jie; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

2016-01-01

Content-based image retrieval (CBIR) techniques have currently gained increasing popularity in the medical field because they can use numerous and valuable archived images to support clinical decisions. In this paper, we concentrate on developing a CBIR system for retrieving brain tumors in T1-weighted contrast-enhanced MRI images. Specifically, when the user roughly outlines the tumor region of a query image, brain tumor images in the database of the same pathological type are expected to be returned. We propose a novel feature extraction framework to improve the retrieval performance. The proposed framework consists of three steps. First, we augment the tumor region and use the augmented tumor region as the region of interest to incorporate informative contextual information. Second, the augmented tumor region is split into subregions by an adaptive spatial division method based on intensity orders; within each subregion, we extract raw image patches as local features. Third, we apply the Fisher kernel framework to aggregate the local features of each subregion into a respective single vector representation and concatenate these per-subregion vector representations to obtain an image-level signature. After feature extraction, a closed-form metric learning algorithm is applied to measure the similarity between the query image and database images. Extensive experiments are conducted on a large dataset of 3604 images with three types of brain tumors, namely, meningiomas, gliomas, and pituitary tumors. The mean average precision can reach 94.68%. Experimental results demonstrate the power of the proposed algorithm against some related state-of-the-art methods on the same dataset.

Research of image retrieval technology based on color feature

Science.gov (United States)

Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

2009-10-01

Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram

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

Science.gov (United States)

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

2016-04-27

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

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

Science.gov (United States)

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

2018-01-01

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

Music Retrieval Based on the Relation between Color Association and Lyrics

Science.gov (United States)

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.

RETRIEVAL EVENTS EVALUATION

International Nuclear Information System (INIS)

Wilson, T.

1999-01-01

The purpose of this analysis is to evaluate impacts to the retrieval concept presented in the Design Analysis ''Retrieval Equipment and Strategy'' (Reference 6), from abnormal events based on Design Basis Events (DBE) and Beyond Design Basis Events (BDBE) as defined in two recent analyses: (1) DBE/Scenario Analysis for Preclosure Repository Subsurface Facilities (Reference 4); and (2) Preliminary Preclosure Design Basis Event Calculations for the Monitored Geologic Repository (Reference 5) The objective of this task is to determine what impacts the DBEs and BDBEs have on the equipment developed for retrieval. The analysis lists potential impacts and recommends changes to be analyzed in subsequent design analyses for developed equipment, or recommend where additional equipment may be needed, to allow retrieval to be performed in all DBE or BDBE situations. This analysis supports License Application design and therefore complies with the requirements of Systems Description Document input criteria comparison as presented in Section 7, Conclusions. In addition, the analysis discusses the impacts associated with not using concrete inverts in the emplacement drifts. The ''Retrieval Equipment and Strategy'' analysis was based on a concrete invert configuration in the emplacement drift. The scope of the analysis, as presented in ''Development Plan for Retrieval Events Evaluation'' (Reference 3) includes evaluation and criteria of the following: Impacts to retrieval from the emplacement drift based on DBE/BDBEs, and changes to the invert configuration for the preclosure period. Impacts to retrieval from the main drifts based on DBE/BDBEs for the preclosure period

EARS: An Online Bibliographic Search and Retrieval System Based on Ordered Explosion.

Science.gov (United States)

Ramesh, R.; Drury, Colin G.

1987-01-01

Provides overview of Ergonomics Abstracts Retrieval System (EARS), an online bibliographic search and retrieval system in the area of human factors engineering. Other online systems are described, the design of EARS based on inverted file organization is explained, and system expansions including a thesaurus are discussed. (Author/LRW)

Lightweight Active Object Retrieval with Weak Classifiers.

Science.gov (United States)

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.

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

Science.gov (United States)

Olson, William S.

1990-01-01

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

Ask Alice: an Artificial Retrieval of Information Agent

NARCIS (Netherlands)

Valstar, M.; Baur, T.; Cafaro, A.; Ghitulescu, A.; Potard, B.; Wagner, J.; Andre, E.; Durieu, L.; Aylett, M.; Dermouche, P.; Pelachaud, C.; Coutinho, E.; Schuller, B.; Zhang, Yue; Heylen, Dirk K.J.; Theune, Mariet; van Waterschoot, Jelte Barachia

2016-01-01

We present a demonstration of the ARIA framework, a modular approach for rapid development of virtual humans for information retrieval that have linguistic, emotional, and social skills and a strong personality. We demonstrate the capabilities of our framework in a scenario where a popular book from

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

Science.gov (United States)

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

2013-05-01

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

Learning Psychological Research and Statistical Concepts using Retrieval-based Practice

Directory of Open Access Journals (Sweden)

Stephen Wee Hun eLim

2015-10-01

Full Text Available Research methods and statistics are an indispensable subject in the undergraduate psychology curriculum, but there are challenges associated with teaching it, such as making learning durable. Here we hypothesized that retrieval-based learning promotes long-term retention of statistical knowledge in psychology. Participants either studied the educational material in four consecutive periods, or studied it just once and practised retrieving the information in the subsequent three periods, and then took a final test through which their learning was assessed. Whereas repeated studying yielded better test performance when the final test was immediately administered, repeated practice yielded better performance when the test was administered a week after. The data suggest that retrieval practice enhanced the learning – produced better long-term retention – of statistical knowledge in psychology than did repeated studying.

Beyond information retrieval: information discovery and multimedia information retrieval

OpenAIRE

Roberto Raieli

2017-01-01

The paper compares the current methodologies for search and discovery of information and information resources: terminological search and term-based language, own of information retrieval (IR); semantic search and information discovery, being developed mainly through the language of linked data; semiotic search and content-based language, experienced by multimedia information retrieval (MIR).MIR semiotic methodology is, then, detailed.

Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

Science.gov (United States)

Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

2018-06-15

Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

Content-Based Image Retrial Based on Hadoop

Directory of Open Access Journals (Sweden)

DongSheng Yin

2013-01-01

Full Text Available Generally, time complexity of algorithms for content-based image retrial is extremely high. In order to retrieve images on large-scale databases efficiently, a new way for retrieving based on Hadoop distributed framework is proposed. Firstly, a database of images features is built by using Speeded Up Robust Features algorithm and Locality-Sensitive Hashing and then perform the search on Hadoop platform in a parallel way specially designed. Considerable experimental results show that it is able to retrieve images based on content on large-scale cluster and image sets effectively.

Context-based adaptive filtering of interest points in image retrieval

DEFF Research Database (Denmark)

Nguyen, Phuong Giang; Andersen, Hans Jørgen

2009-01-01

Interest points have been used as local features with success in many computer vision applications such as image/video retrieval and object recognition. However, a major issue when using this approach is a large number of interest points detected from each image and created a dense feature space...... a subset of features. Our approach differs from others in a fact that selected feature is based on the context of the given image. Our experimental results show a significant reduction rate of features while preserving the retrieval performance....

Application of discriminative models for interactive query refinement in video retrieval

Science.gov (United States)

Srivastava, Amit; Khanwalkar, Saurabh; Kumar, Anoop

2013-12-01

The ability to quickly search for large volumes of videos for specific actions or events can provide a dramatic new capability to intelligence agencies. Example-based queries from video are a form of content-based information retrieval (CBIR) where the objective is to retrieve clips from a video corpus, or stream, using a representative query sample to find more like this. Often, the accuracy of video retrieval is largely limited by the gap between the available video descriptors and the underlying query concept, and such exemplar queries return many irrelevant results with relevant ones. In this paper, we present an Interactive Query Refinement (IQR) system which acts as a powerful tool to leverage human feedback and allow intelligence analyst to iteratively refine search queries for improved precision in the retrieved results. In our approach to IQR, we leverage discriminative models that operate on high dimensional features derived from low-level video descriptors in an iterative framework. Our IQR model solicits relevance feedback on examples selected from the region of uncertainty and updates the discriminating boundary to produce a relevance ranked results list. We achieved 358% relative improvement in Mean Average Precision (MAP) over initial retrieval list at a rank cutoff of 100 over 4 iterations. We compare our discriminative IQR model approach to a naïve IQR and show our model-based approach yields 49% relative improvement over the no model naïve system.

Castsearch - Context Based Spoken Document Retrieval

DEFF Research Database (Denmark)

Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther; Hansen, Lars Kai

2007-01-01

The paper describes our work on the development of a system for retrieval of relevant stories from broadcast news. The system utilizes a combination of audio processing and text mining. The audio processing consists of a segmentation step that partitions the audio into speech and music. The speech...... is further segmented into speaker segments and then transcribed using an automatic speech recognition system, to yield text input for clustering using non-negative matrix factorization (NMF). We find semantic topics that are used to evaluate the performance for topic detection. Based on these topics we show...

Algorithm for image retrieval based on edge gradient orientation statistical code.

Science.gov (United States)

Zeng, Jiexian; Zhao, Yonggang; Li, Weiye; Fu, Xiang

2014-01-01

Image edge gradient direction not only contains important information of the shape, but also has a simple, lower complexity characteristic. Considering that the edge gradient direction histograms and edge direction autocorrelogram do not have the rotation invariance, we put forward the image retrieval algorithm which is based on edge gradient orientation statistical code (hereinafter referred to as EGOSC) by sharing the application of the statistics method in the edge direction of the chain code in eight neighborhoods to the statistics of the edge gradient direction. Firstly, we construct the n-direction vector and make maximal summation restriction on EGOSC to make sure this algorithm is invariable for rotation effectively. Then, we use Euclidean distance of edge gradient direction entropy to measure shape similarity, so that this method is not sensitive to scaling, color, and illumination change. The experimental results and the algorithm analysis demonstrate that the algorithm can be used for content-based image retrieval and has good retrieval results.

Strategic retrieval, confabulations, and delusions: theory and data.

Science.gov (United States)

Gilboa, Asaf

2010-01-01

Based on Moscovitch and Winocur's "working with memory" framework, confabulation is described as a deficit in strategic retrieval processes. The present paper suggests that only a confluence of deficits on multiple memory-related processes leads to confabulation. These are divided into three categories. Core processes that are unique to confabulation and required for its evolution include: (1) an intuitive, rapid, preconscious "feeling of rightness" monitoring, (2) an elaborate conscious "editor" monitoring, and (3) control processes that mediate the decision whether to act upon a retrieved memory. The second category is deficits on constitutional processes which are required for confabulation to occur but are not unique to it. These include the formation of erroneous memory representation, (temporal) context confusion, and deficits in retrieval cue generation. Finally, associated Features of confabulations determine the content "flavour" and frequency of confabulation but are not required for their evolution. Some associated features are magnification of normal reconstructive memory processes such as reliance on generic/schematic representations, and positivity biases in memory, whereas others are abnormal such as perseveration or source memory deficits. Data on deficits in core processes in confabulation are presented. Next, the apparent correspondences between confabulation and delusion are discussed. Considering confabulation within a strategic memory framework may help elucidate both the commonalities and differences between the two symptoms. Delusions are affected by a convergence of abnormal perception and encoding of information, associated with aberrant cognitive schema structure and disordered belief monitoring. Whereas confabulation is primarily a disorder of retrieval, mnemonic aspects of delusions can be described as primarily a disorder of input and integration of information. It is suggested that delusions might share some of the associated features

The impact of retrievability on disposal of radioactive waste

International Nuclear Information System (INIS)

Gera, F.; Hill, M.

2000-01-01

There are discussions in various countries about whether and to what degree the ability to retrieve wastes might be built into geological repositories for long lived radioactive waste. It is generally accepted that repositories should be designed so that retrieval will never be necessary on safety grounds. Nevertheless, reasons for retrieval have been put forward. The ways in which retrievability might be built into geological repositories and various expected impacts of such actions are briefly discussed in this paper. A preliminary comparison of some notional geological disposal strategies with varying degrees of retrievability is proposed. The comparison is qualitative because at present there are few detailed designs for geological repositories with retrievability and few assessments of the safety and other aspects of such repositories. The comparison has the aims of highlighting those factors that differ most from one strategy to another and identifying which of these factors require further assessment in order to make more complete and quantitative comparisons. The framework used for the preliminary comparison is that of a multi-attribute analysis, such as might be employed in an environmental impact assessment (EIA). This type of framework is chosen because it would be used in many countries to aid decisions between disposal options or strategies. The framework encompasses radiological and nuclear safety factors but goes well beyond these and includes a number of factors that are not quantifiable in the technical sense. However, consideration of such factors is considered important because they can have a significant impact on decision-making. The groups of factors are: radiological, nuclear safety and financial (quantifiable factors); non-radiological environmental impacts (partially quantifiable factors); non-quantifiable attributes (such as ethical and societal factors). (author)

Retrieval options study

International Nuclear Information System (INIS)

1980-03-01

This Retrieval Options Study is part of the systems analysis activities of the Office of Nuclear Waste Isolation to develop the scientific and technological bases for radioactive waste repositories in various geologic media. The study considers two waste forms, high level waste and spent fuel, and defines various classes of waste retrieval and recovery. A methodology and data base are developed which allow the relative evaluation of retrieval and recovery costs and the following technical criteria: safety; technical feasibility; ease of retrieval; probable intact retrieval time; safeguards; monitoring; criticality; and licensability. A total of 505 repository options are defined and the cost and technical criteria evaluated utilizing a combination of facts and engineering judgments. The repositories evaluated are selected combinations of the following parameters: Geologic Media (salt, granite, basalt, shale); Retrieval Time after Emplacement (5 and 25 years); Emplacement Design (nominal hole, large hole, carbon steel canister, corrosion resistant canister, backfill in hole, nominal sleeves, thick wall sleeves); Emplacement Configuration (single vertical, multiple vertical, single horizontal, multiple horizontal, vaults; Thermal Considerations; (normal design, reduced density, once-through ventilation, recirculated ventilation); Room Backfill; (none, run-of-mine, early, 5 year delay, 25 year delay, decommissioned); and Rate of Retrieval;

A 1DVAR-based snowfall rate retrieval algorithm for passive microwave radiometers

Science.gov (United States)

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

2017-06-01

Snowfall rate retrieval from spaceborne passive microwave (PMW) radiometers has gained momentum in recent years. PMW can be so utilized because of its ability to sense in-cloud precipitation. A physically based, overland snowfall rate (SFR) algorithm has been developed using measurements from the Advanced Microwave Sounding Unit-A/Microwave Humidity Sounder sensor pair and the Advanced Technology Microwave Sounder. Currently, these instruments are aboard five polar-orbiting satellites, namely, NOAA-18, NOAA-19, Metop-A, Metop-B, and Suomi-NPP. The SFR algorithm relies on a separate snowfall detection algorithm that is composed of a satellite-based statistical model and a set of numerical weather prediction model-based filters. There are four components in the SFR algorithm itself: cloud properties retrieval, computation of ice particle terminal velocity, ice water content adjustment, and the determination of snowfall rate. The retrieval of cloud properties is the foundation of the algorithm and is accomplished using a one-dimensional variational (1DVAR) model. An existing model is adopted to derive ice particle terminal velocity. Since no measurement of cloud ice distribution is available when SFR is retrieved in near real time, such distribution is implicitly assumed by deriving an empirical function that adjusts retrieved SFR toward radar snowfall estimates. Finally, SFR is determined numerically from a complex integral. The algorithm has been validated against both radar and ground observations of snowfall events from the contiguous United States with satisfactory results. Currently, the SFR product is operationally generated at the National Oceanic and Atmospheric Administration and can be obtained from that organization.

BR-Explorer: A sound and complete FCA-based retrieval algorithm (Poster)

OpenAIRE

Messai , Nizar; Devignes , Marie-Dominique; Napoli , Amedeo; Smaïl-Tabbone , Malika

2006-01-01

In this paper we present BR-Explorer, a sound and complete biological data sources retrieval algorithm based on Formal Concept Analysis and domain ontologies. BR-Explorer addresses the problem of retrieving the relevant data sources for a given query. Initially, a formal context representing the relation between biological data sources and their metadata is provided and its corresponding concept lattice is built. Then BR-Explorer starts by generating the formal concept for the considered quer...

Lightweight Active Object Retrieval with Weak Classifiers

Directory of Open Access Journals (Sweden)

László Czúni

2018-03-01

Full Text Available 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.

Definition of an automatic information retrieval system independent from the data base used

International Nuclear Information System (INIS)

Cunha, E.R.

1983-04-01

A bibliographic information retrieval system using data stored at the standardized interchange format ISO 2709 or ANSI Z39.2, is specified. A set of comands for interchange format manipulation wich allows the data access at the logical level, achieving the data independence, are used. A data base description language, a storage structure and data base manipulation comands are specified, using retrieval techniques which consider the applications needs. (Author) [pt

On the integrated cognitive theory for information retrieval

DEFF Research Database (Denmark)

Ingwersen, Peter; Järvelin, Kalervo

2008-01-01

The paper demonstrates how the Laboratory Research Framework fits into the holistic Cognitive Framework for IR. It first discusses the Laboratory Framework with emphasis on its underlying assumptions and known limitations. This is followed by a view of interaction and relevance phenomena associat...... drawn from a collection, matching principles in a retrieval system, and the searcher's situation and task context. The paper ends with concluding points of summarization of issues encountered....

On the Holistic Cognitive Theory for Information Retrieval

DEFF Research Database (Denmark)

Ingwersen, Peter; Järvelin, Kalervo

2007-01-01

The paper demonstrates how the Laboratory Research Framework fits into the holistic Cognitive Framework for IR. It first discusses the Laboratory Framework with emphasis on its underlying assumptions and known limitations. This is followed by a view of interaction and relevance phenomena associat...... drawn from a collection, matching principles in a retrieval system, and the searcher's situation and task context. The paper ends with concluding points of summarization of issues encountered....

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-01-01

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. (paper)

An SOA-based architecture framework

NARCIS (Netherlands)

Aalst, van der W.M.P.; Beisiegel, M.; Hee, van K.M.; König, D.; Stahl, C.

2007-01-01

We present an Service-Oriented Architecture (SOA)– based architecture framework. The architecture framework is designed to be close to industry standards, especially to the Service Component Architecture (SCA). The framework is language independent and the building blocks of each system, activities

An Abstraction-Based Data Model for Information Retrieval

Science.gov (United States)

McAllister, Richard A.; Angryk, Rafal A.

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

Image Retrieval Algorithm Based on Discrete Fractional Transforms

Science.gov (United States)

Jindal, Neeru; Singh, Kulbir

2013-06-01

The discrete fractional transforms is a signal processing tool which suggests computational algorithms and solutions to various sophisticated applications. In this paper, a new technique to retrieve the encrypted and scrambled image based on discrete fractional transforms has been proposed. Two-dimensional image was encrypted using discrete fractional transforms with three fractional orders and two random phase masks placed in the two intermediate planes. The significant feature of discrete fractional transforms benefits from its extra degree of freedom that is provided by its fractional orders. Security strength was enhanced (1024!)4 times by scrambling the encrypted image. In decryption process, image retrieval is sensitive for both correct fractional order keys and scrambling algorithm. The proposed approach make the brute force attack infeasible. Mean square error and relative error are the recital parameters to verify validity of proposed method.

[Design and implementation of medical instrument standard information retrieval system based on APS.NET].

Science.gov (United States)

Yu, Kaijun

2010-07-01

This paper Analys the design goals of Medical Instrumentation standard information retrieval system. Based on the B /S structure,we established a medical instrumentation standard retrieval system with ASP.NET C # programming language, IIS f Web server, SQL Server 2000 database, in the. NET environment. The paper also Introduces the system structure, retrieval system modules, system development environment and detailed design of the system.

Dual-force ISOMAP: a new relevance feedback method for medical image retrieval.

Science.gov (United States)

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

With great potential for assisting radiological image interpretation and decision making, content-based image retrieval in the medical domain has become a hot topic in recent years. Many methods to enhance the performance of content-based medical image retrieval have been proposed, among which the relevance feedback (RF) scheme is one of the most promising. Given user feedback information, RF algorithms interactively learn a user's preferences to bridge the "semantic gap" between low-level computerized visual features and high-level human semantic perception and thus improve retrieval performance. However, most existing RF algorithms perform in the original high-dimensional feature space and ignore the manifold structure of the low-level visual features of images. In this paper, we propose a new method, termed dual-force ISOMAP (DFISOMAP), for content-based medical image retrieval. Under the assumption that medical images lie on a low-dimensional manifold embedded in a high-dimensional ambient space, DFISOMAP operates in the following three stages. First, the geometric structure of positive examples in the learned low-dimensional embedding is preserved according to the isometric feature mapping (ISOMAP) criterion. To precisely model the geometric structure, a reconstruction error constraint is also added. Second, the average distance between positive and negative examples is maximized to separate them; this margin maximization acts as a force that pushes negative examples far away from positive examples. Finally, the similarity propagation technique is utilized to provide negative examples with another force that will pull them back into the negative sample set. We evaluate the proposed method on a subset of the IRMA medical image dataset with a RF-based medical image retrieval framework. Experimental results show that DFISOMAP outperforms popular approaches for content-based medical image retrieval in terms of accuracy and stability.

The Ecosystem of Information Retrieval

Science.gov (United States)

Rodriguez-Munoz, Jose-Vicente; Martinez-Mendez, Francisco-Javier; Pastor-Sanchez, Juan-Antonio

2012-01-01

Introduction: This paper presents an initial proposal for a formal framework that, by studying the metric variables involved in information retrieval, can establish the sequence of events involved and how to perform it. Method: A systematic approach from the equations of Shannon and Weaver to establish the decidability of information retrieval…

Content-based video retrieval by example video clip

Science.gov (United States)

Dimitrova, Nevenka; Abdel-Mottaleb, Mohamed

1997-01-01

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

Simultenious binary hash and features learning for image retrieval

Science.gov (United States)

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.

Retrieval options study

Energy Technology Data Exchange (ETDEWEB)

1980-03-01

This Retrieval Options Study is part of the systems analysis activities of the Office of Nuclear Waste Isolation to develop the scientific and technological bases for radioactive waste repositories in various geologic media. The study considers two waste forms, high level waste and spent fuel, and defines various classes of waste retrieval and recovery. A methodology and data base are developed which allow the relative evaluation of retrieval and recovery costs and the following technical criteria: safety; technical feasibility; ease of retrieval; probable intact retrieval time; safeguards; monitoring; criticality; and licensability. A total of 505 repository options are defined and the cost and technical criteria evaluated utilizing a combination of facts and engineering judgments. The repositories evaluated are selected combinations of the following parameters: Geologic Media (salt, granite, basalt, shale); Retrieval Time after Emplacement (5 and 25 years); Emplacement Design (nominal hole, large hole, carbon steel canister, corrosion resistant canister, backfill in hole, nominal sleeves, thick wall sleeves); Emplacement Configuration (single vertical, multiple vertical, single horizontal, multiple horizontal, vaults; Thermal Considerations; (normal design, reduced density, once-through ventilation, recirculated ventilation); Room Backfill; (none, run-of-mine, early, 5 year delay, 25 year delay, decommissioned); and Rate of Retrieval; (same as emplacement, variably slower depending on repository/canister condition).

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

Science.gov (United States)

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

2016-12-01

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

Extending a DBMS to Support Content-Based Video Retrieval : A Formula 1 Case Study

NARCIS (Netherlands)

Petkovic, M.; Jonker, Willem; Mihajlovic, V.

Content-based retrieval has been identified as one of the most challenging problems, requiring a multidisciplinary research among computer vision, information retrieval, artificial intelligence, database, and other fields. In this paper, we address the specific aspect of inferring semantics

From Medieval Philosophy to the Virtual Library: a descriptive framework for scientific knowledge and documentation as basis for document retrieval

Directory of Open Access Journals (Sweden)

Frances Morrissey

2001-11-01

Full Text Available This paper examines the conceptual basis of document retrieval systems for the Virtual Library in science and technology. It does so through analysing some cognitive models for scientific knowledge, drawing on philosophy, sociology and linguistics. It is important to consider improvements in search/ retrieval functionalities for scientific documents because knowledge creation and transfer are integral to the functioning of scientific communities, and on a larger scale, science and technology are central to the knowledge economy. This paper proposes four new and innovative understandings. Firstly, it is proposed that formal scientific communication constitutes the documentation and dissemination of concepts, and that conceptualism is a useful philosophical basis for study. Second, it is proposed that the scientific document is a dyadic con-struct, being both the physical manifestation as an encoded medium, and also being the associated knowledge, or intangible ideation, that is carried within the document. Third, it is shown that major philosophers of science divide science into three main activities, dealing with data, derived or inferred laws, and the axioms or the paradigm. Fourth, it is demonstrated that the data, information and conceptual frameworks carried by a scientific document, as different levels of signification or semiotic systems, can each be characterised in ways assisting in search and retrieval functionalities for the Virtual Library.

Eight-component retrievals from ground-based MAX-DOAS observations

Directory of Open Access Journals (Sweden)

H. Irie

2011-06-01

Full Text Available We attempt for the first time to retrieve lower-tropospheric vertical profile information for 8 quantities from ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS observations. The components retrieved are the aerosol extinction coefficients at two wavelengths, 357 and 476 nm, and NO₂, HCHO, CHOCHO, H₂O, SO₂, and O₃ volume mixing ratios. A Japanese MAX-DOAS profile retrieval algorithm, version 1 (JM1, is applied to observations performed at Cabauw, the Netherlands (51.97° N, 4.93° E, in June–July 2009 during the Cabauw Intercomparison campaign of Nitrogen Dioxide measuring Instruments (CINDI. Of the retrieved profiles, we focus here on the lowest-layer data (mean values at altitudes 0–1 km, where the sensitivity is usually highest owing to the longest light path. In support of the capability of the multi-component retrievals, we find reasonable overall agreement with independent data sets, including a regional chemical transport model (CHIMERE and in situ observations performed near the surface (2–3 m and at the 200-m height level of the tall tower in Cabauw. Plumes of enhanced HCHO and SO₂ were likely affected by biogenic and ship emissions, respectively, and an improvement in their emission strengths is suggested for better agreement between CHIMERE simulations and MAX-DOAS observations. Analysis of air mass factors indicates that the horizontal spatial representativeness of MAX-DOAS observations is about 3–15 km (depending mainly on aerosol extinction, comparable to or better than the spatial resolution of current UV-visible satellite observations and model calculations. These demonstrate that MAX-DOAS provides multi-component data useful for the evaluation of satellite observations and model calculations and can play an important role in bridging different data sets having different spatial resolutions.

Parallel content-based sub-image retrieval using hierarchical searching.

Science.gov (United States)

Yang, Lin; Qi, Xin; Xing, Fuyong; Kurc, Tahsin; Saltz, Joel; Foran, David J

2014-04-01

The capacity to systematically search through large image collections and ensembles and detect regions exhibiting similar morphological characteristics is central to pathology diagnosis. Unfortunately, the primary methods used to search digitized, whole-slide histopathology specimens are slow and prone to inter- and intra-observer variability. The central objective of this research was to design, develop, and evaluate a content-based image retrieval system to assist doctors for quick and reliable content-based comparative search of similar prostate image patches. Given a representative image patch (sub-image), the algorithm will return a ranked ensemble of image patches throughout the entire whole-slide histology section which exhibits the most similar morphologic characteristics. This is accomplished by first performing hierarchical searching based on a newly developed hierarchical annular histogram (HAH). The set of candidates is then further refined in the second stage of processing by computing a color histogram from eight equally divided segments within each square annular bin defined in the original HAH. A demand-driven master-worker parallelization approach is employed to speed up the searching procedure. Using this strategy, the query patch is broadcasted to all worker processes. Each worker process is dynamically assigned an image by the master process to search for and return a ranked list of similar patches in the image. The algorithm was tested using digitized hematoxylin and eosin (H&E) stained prostate cancer specimens. We have achieved an excellent image retrieval performance. The recall rate within the first 40 rank retrieved image patches is ∼90%. Both the testing data and source code can be downloaded from http://pleiad.umdnj.edu/CBII/Bioinformatics/.

An Intelligent Information Retrieval Approach Based on Two Degrees of Uncertainty Fuzzy Ontology

Directory of Open Access Journals (Sweden)

Maryam Hourali

2011-01-01

Full Text Available In spite of the voluminous studies in the field of intelligent retrieval systems, effective retrieving of information has been remained an important unsolved problem. Implementations of different conceptual knowledge in the information retrieval process such as ontology have been considered as a solution to enhance the quality of results. Furthermore, the conceptual formalism supported by typical ontology may not be sufficient to represent uncertainty information due to the lack of clear-cut boundaries between concepts of the domains. To tackle this type of problems, one possible solution is to insert fuzzy logic into ontology construction process. In this article, a novel approach for fuzzy ontology generation with two uncertainty degrees is proposed. Hence, by implementing linguistic variables, uncertainty level in domain's concepts (Software Maintenance Engineering (SME domain has been modeled, and ontology relations have been modeled by fuzzy theory consequently. Then, we combined these uncertain models and proposed a new ontology with two degrees of uncertainty both in concept expression and relation expression. The generated fuzzy ontology was implemented for expansion of initial user's queries in SME domain. Experimental results showed that the proposed model has better overall retrieval performance comparing to keyword-based or crisp ontology-based retrieval systems.

Connectionist Interaction Information Retrieval.

Science.gov (United States)

Dominich, Sandor

2003-01-01

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

INIS information retrieval based on IBM's IRMS

International Nuclear Information System (INIS)

Gadjokov, V.; Schmid, H.; Del Bigio, G.

1975-01-01

An information retrieval system for the INIS data base is described. It allows for batch processing on an IBM/360 or /370 computer operated under OS or VS. The program package consists basically of IBM's IRMS system which was converted from DOS to OS and adapted for INIS requirements. Sections 1-9 present the system from the user's point of view, deliberately omitting all the programming details. Program descriptions with data set definitions and file formats are given in sections 10-12. (author)

Component-based framework for subsurface simulations

International Nuclear Information System (INIS)

Palmer, B J; Fang, Yilin; Hammond, Glenn; Gurumoorthi, Vidhya

2007-01-01

Simulations in the subsurface environment represent a broad range of phenomena covering an equally broad range of scales. Developing modelling capabilities that can integrate models representing different phenomena acting at different scales present formidable challenges both from the algorithmic and computer science perspective. This paper will describe the development of an integrated framework that will be used to combine different models into a single simulation. Initial work has focused on creating two frameworks, one for performing smooth particle hydrodynamics (SPH) simulations of fluid systems, the other for performing grid-based continuum simulations of reactive subsurface flow. The SPH framework is based on a parallel code developed for doing pore scale simulations, the continuum grid-based framework is based on the STOMP (Subsurface Transport Over Multiple Phases) code developed at PNNL Future work will focus on combining the frameworks together to perform multiscale, multiphysics simulations of reactive subsurface flow

Ontology of Gaps in Content-Based Image Retrieval

OpenAIRE

Deserno, Thomas M.; Antani, Sameer; Long, Rodney

2008-01-01

Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potential for making a strong impact in diagnostics, research, and education. Research as reported in the scientific literature, however, has not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed (without supporting analysis) to the ina...

Information retrieval models foundations and relationships

CERN Document Server

Roelleke, Thomas

2013-01-01

Information Retrieval (IR) models are a core component of IR research and IR systems. The past decade brought a consolidation of the family of IR models, which by 2000 consisted of relatively isolated views on TF-IDF (Term-Frequency times Inverse-Document-Frequency) as the weighting scheme in the vector-space model (VSM), the probabilistic relevance framework (PRF), the binary independence retrieval (BIR) model, BM25 (Best-Match Version 25, the main instantiation of the PRF/BIR), and language modelling (LM). Also, the early 2000s saw the arrival of divergence from randomness (DFR).Regarding in

The role of retrieval mode and retrieval orientation in retrieval practice: insights from comparing recognition memory testing formats and restudying.

Science.gov (United States)

Gao, Chuanji; Rosburg, Timm; Hou, Mingzhu; Li, Bingbing; Xiao, Xin; Guo, Chunyan

2016-12-01

The effectiveness of retrieval practice for aiding long-term memory, referred to as the testing effect, has been widely demonstrated. However, the specific neurocognitive mechanisms underlying this phenomenon remain unclear. In the present study, we sought to explore the role of pre-retrieval processes at initial testing on later recognition performance by using event-related potentials (ERPs). Subjects studied two lists of words (Chinese characters) and then performed a recognition task or a source memory task, or restudied the word lists. At the end of the experiment, subjects received a final recognition test based on the remember-know paradigm. Behaviorally, initial testing (active retrieval) enhanced memory retention relative to restudying (passive retrieval). The retrieval mode at initial testing was indexed by more positive-going ERPs for unstudied items in the active-retrieval tasks than in passive retrieval from 300 to 900 ms. Follow-up analyses showed that the magnitude of the early ERP retrieval mode effect (300-500 ms) was predictive of the behavioral testing effect later on. In addition, the ERPs for correctly rejected new items during initial testing differed between the two active-retrieval tasks from 500 to 900 ms, and this ERP retrieval orientation effect predicted differential behavioral testing gains between the two active-retrieval conditions. Our findings confirm that initial testing promotes later retrieval relative to restudying, and they further suggest that adopting pre-retrieval processing in the forms of retrieval mode and retrieval orientation might contribute to these memory enhancements.

Retrieval techniques and graphics displays using a computerized stellar data base

Science.gov (United States)

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.

Private information retrieval

CERN Document Server

Yi, Xun; Bertino, Elisa

2013-01-01

This book deals with Private Information Retrieval (PIR), a technique allowing a user to retrieve an element from a server in possession of a database without revealing to the server which element is retrieved. PIR has been widely applied to protect the privacy of the user in querying a service provider on the Internet. For example, by PIR, one can query a location-based service provider about the nearest car park without revealing his location to the server.The first PIR approach was introduced by Chor, Goldreich, Kushilevitz and Sudan in 1995 in a multi-server setting, where the user retriev

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

Science.gov (United States)

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.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring.

Science.gov (United States)

Alirezaie, Marjan; Kiselev, Andrey; Längkvist, Martin; Klügl, Franziska; Loutfi, Amy

2017-11-05

This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment-central Stockholm-in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as "find all regions close to schools and far from the flooded area". The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring

Directory of Open Access Journals (Sweden)

Marjan Alirezaie

2017-11-01

Full Text Available This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

Personal health records: retrieving contextual information with Google Custom Search.

Science.gov (United States)

Ahsan, Mahmud; Seldon, H Lee; Sayeed, Shohel

2012-01-01

Ubiquitous personal health records, which can accompany a person everywhere, are a necessary requirement for ubiquitous healthcare. Contextual information related to health events is important for the diagnosis and treatment of disease and for the maintenance of good health, yet it is seldom recorded in a health record. We describe a dual cellphone-and-Web-based personal health record system which can include 'external' contextual information. Much contextual information is available on the Internet and we can use ontologies to help identify relevant sites and information. But a search engine is required to retrieve information from the Web and developing a customized search engine is beyond our scope, so we can use Google Custom Search API Web service to get contextual data. In this paper we describe a framework which combines a health-and-environment 'knowledge base' or ontology with the Google Custom Search API to retrieve relevant contextual information related to entries in a ubiquitous personal health record.

An evaluation of canonical forms for non-rigid 3D shape retrieval

OpenAIRE

Pickup, David; Liu, Juncheng; Sun, Xianfang; Rosin, Paul L.; Martin, Ralph R.; Cheng, Zhiquan; Lian, Zhouhui; Nie, Sipin; Jin, Longcun; Shamai, Gil; Sahillioğlu, Yusuf; Kavan, Ladislav

2018-01-01

Canonical forms attempt to factor out a non-rigid shape’s pose, giving a pose-neutral shape. This opens up the\\ud possibility of using methods originally designed for rigid shape retrieval for the task of non-rigid shape retrieval.\\ud We extend our recent benchmark for testing canonical form algorithms. Our new benchmark is used to evaluate a\\ud greater number of state-of-the-art canonical forms, on five recent non-rigid retrieval datasets, within two different\\ud retrieval frameworks. A tota...

Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

Science.gov (United States)

Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

2018-01-01

An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

A LDA-based approach to promoting ranking diversity for genomics information retrieval.

Science.gov (United States)

Chen, Yan; Yin, Xiaoshi; Li, Zhoujun; Hu, Xiaohua; Huang, Jimmy Xiangji

2012-06-11

In the biomedical domain, there are immense data and tremendous increase of genomics and biomedical relevant publications. The wealth of information has led to an increasing amount of interest in and need for applying information retrieval techniques to access the scientific literature in genomics and related biomedical disciplines. In many cases, the desired information of a query asked by biologists is a list of a certain type of entities covering different aspects that are related to the question, such as cells, genes, diseases, proteins, mutations, etc. Hence, it is important of a biomedical IR system to be able to provide relevant and diverse answers to fulfill biologists' information needs. However traditional IR model only concerns with the relevance between retrieved documents and user query, but does not take redundancy between retrieved documents into account. This will lead to high redundancy and low diversity in the retrieval ranked lists. In this paper, we propose an approach which employs a topic generative model called Latent Dirichlet Allocation (LDA) to promoting ranking diversity for biomedical information retrieval. Different from other approaches or models which consider aspects on word level, our approach assumes that aspects should be identified by the topics of retrieved documents. We present LDA model to discover topic distribution of retrieval passages and word distribution of each topic dimension, and then re-rank retrieval results with topic distribution similarity between passages based on N-size slide window. We perform our approach on TREC 2007 Genomics collection and two distinctive IR baseline runs, which can achieve 8% improvement over the highest Aspect MAP reported in TREC 2007 Genomics track. The proposed method is the first study of adopting topic model to genomics information retrieval, and demonstrates its effectiveness in promoting ranking diversity as well as in improving relevance of ranked lists of genomics search

Regional frameworks applied to hydrology: can landscape-based frameworks capture the hydrologic variability?

Science.gov (United States)

R. McManamay; D. Orth; C. Dolloff; E. Frimpong

2011-01-01

Regional frameworks have been used extensively in recent years to aid in broad-scale management. Widely used landscape-based regional frameworks, such as hydrologic landscape regions (HLRs) and physiographic provinces, may provide predictive tools of hydrologic variability. However, hydrologic-based regional frameworks, created using only streamflow data, are also...

Comparison of the effectiveness of alternative feature sets in shape retrieval of multicomponent images

Science.gov (United States)

Eakins, John P.; Edwards, Jonathan D.; Riley, K. Jonathan; Rosin, Paul L.

2001-01-01

Many different kinds of features have been used as the basis for shape retrieval from image databases. This paper investigates the relative effectiveness of several types of global shape feature, both singly and in combination. The features compared include well-established descriptors such as Fourier coefficients and moment invariants, as well as recently-proposed measures of triangularity and ellipticity. Experiments were conducted within the framework of the ARTISAN shape retrieval system, and retrieval effectiveness assessed on a database of over 10,000 images, using 24 queries and associated ground truth supplied by the UK Patent Office . Our experiments revealed only minor differences in retrieval effectiveness between different measures, suggesting that a wide variety of shape feature combinations can provide adequate discriminating power for effective shape retrieval in multi-component image collections such as trademark registries. Marked differences between measures were observed for some individual queries, suggesting that there could be considerable scope for improving retrieval effectiveness by providing users with an improved framework for searching multi-dimensional feature space.

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

Science.gov (United States)

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.

Optical image encryption using password key based on phase retrieval algorithm

Science.gov (United States)

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

2016-04-01

A novel optical image encryption system is proposed using password key based on phase retrieval algorithm (PRA). In the encryption process, a shared image is taken as a symmetric key and the plaintext is encoded into the phase-only mask based on the iterative PRA. The linear relationship between the plaintext and ciphertext is broken using the password key, which can resist the known plaintext attack. The symmetric key and the retrieved phase are imported into the input plane and Fourier plane of 4f system during the decryption, respectively, so as to obtain the plaintext on the CCD. Finally, we analyse the key space of the password key, and the results show that the proposed scheme can resist a brute force attack due to the flexibility of the password key.

Some aspects of the file organization and retrieval strategy in large data-bases

International Nuclear Information System (INIS)

Arnaudov, D.D.; Govorun, N.N.

1977-01-01

Methods of organizing a big information retrieval system are discribed. A special attention is paid to the file organization. An adapting file structure is described in more detail. The discussed method gives one the opportunity to organize large files in such a way that the response time of the system can be minimized, when the file is increasing. In connection with the retrieval strategy a method is proposed, which uses the frequencies of the descr/iptors and the couples of the descriptors to forecast the expected number of the relevant documents. Programmes are made, on the base of these methods, which are used in the information retrieval systems of JINR

Multimedia information retrieval theory and techniques

CERN Document Server

Raieli, Roberto

2013-01-01

Novel processing and searching tools for the management of new multimedia documents have developed. Multimedia Information Retrieval (MMIR) is an organic system made up of Text Retrieval (TR); Visual Retrieval (VR); Video Retrieval (VDR); and Audio Retrieval (AR) systems. So that each type of digital document may be analysed and searched by the elements of language appropriate to its nature, search criteria must be extended. Such an approach is known as the Content Based Information Retrieval (CBIR), and is the core of MMIR. This novel content-based concept of information handling needs to be integrated with more traditional semantics. Multimedia Information Retrieval focuses on the tools of processing and searching applicable to the content-based management of new multimedia documents. Translated from Italian by Giles Smith, the book is divided in to two parts. Part one discusses MMIR and related theories, and puts forward new methodologies; part two reviews various experimental and operating MMIR systems, a...

Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

Science.gov (United States)

Wang, Y.; Hioki, S.; Yang, P.; Di Girolamo, L.; Fu, D.

2017-12-01

The precise estimation of two important cloud optical and microphysical properties, cloud particle optical thickness and cloud particle effective radius, is fundamental in the study of radiative energy budget and hydrological cycle. In retrieving these two properties, an appropriate selection of ice particle surface roughness is important because it substantially affects the single-scattering properties. At present, using a predetermined ice particle shape without spatial and temporal variations is a common practice in satellite-based retrieval. This approach leads to substantial uncertainties in retrievals. The cloud radiances measured by each of the cameras of the Multi-angle Imaging SpectroRadiometer (MISR) instrument are used to estimate spherical albedo values at different scattering angles. By analyzing the directional distribution of estimated spherical albedo values, the degree of ice particle surface roughness is estimated. With an optimal degree of ice particle roughness, cloud optical thickness and effective radius are retrieved based on a bi-spectral shortwave technique in conjunction with two Moderate Resolution Imaging Spectroradiometer (MODIS) bands centered at 0.86 and 2.13 μm. The seasonal biases of retrieved cloud optical and microphysical properties, caused by the uncertainties in ice particle roughness, are investigated by using one year of MISR-MODIS fused data.

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

Science.gov (United States)

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

2013-12-01

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

A flexible framework for secure and efficient program obfuscation.

Energy Technology Data Exchange (ETDEWEB)

Solis, John Hector

2013-03-01

In this paper, we present a modular framework for constructing a secure and efficient program obfuscation scheme. Our approach, inspired by the obfuscation with respect to oracle machines model of [4], retains an interactive online protocol with an oracle, but relaxes the original computational and storage restrictions. We argue this is reasonable given the computational resources of modern personal devices. Furthermore, we relax the information-theoretic security requirement for computational security to utilize established cryptographic primitives. With this additional flexibility we are free to explore different cryptographic buildingblocks. Our approach combines authenticated encryption with private information retrieval to construct a secure program obfuscation framework. We give a formal specification of our framework, based on desired functionality and security properties, and provide an example instantiation. In particular, we implement AES in Galois/Counter Mode for authenticated encryption and the Gentry-Ramzan [13]constant communication-rate private information retrieval scheme. We present our implementation results and show that non-trivial sized programs can be realized, but scalability is quickly limited by computational overhead. Finally, we include a discussion on security considerations when instantiating specific modules.

A machine learning-based framework to identify type 2 diabetes through electronic health records.

Science.gov (United States)

Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You

2017-01-01

To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature

MAC/FAC: A Model of Similarity-Based Retrieval

Science.gov (United States)

1994-10-01

Grapes (0.28) 327 Sour Grapes, analog The Taming of the Shrew (0.22), Merry Wives 251 (0.18), S[11 stories], Sour Grapes (-0.19) Sour Grapes, literal... The Institute for the 0 1 Learning Sciences Northwestern University CD• 00 MAC/FAC: A MODEL OF SIMILARITY-BASED RETRIEVAL Kenneth D. Forbus Dedre...Gentner Keith Law Technical Report #59 • October 1994 94-35188 wit Establisthed in 1989 with the support of Andersen Consulting Form Approved REPORT

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

Science.gov (United States)

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.

Implementation of Texture Based Image Retrieval Using M-band Wavelet Transform

Institute of Scientific and Technical Information of China (English)

LiaoYa-li; Yangyan; CaoYang

2003-01-01

Wavelet transform has attracted attention because it is a very useful tool for signal analyzing. As a fundamental characteristic of an image, texture traits play an important role in the human vision system for recognition and interpretation of images. The paper presents an approach to implement texture-based image retrieval using M-band wavelet transform. Firstly the traditional 2-band wavelet is extended to M-band wavelet transform. Then the wavelet moments are computed by M-band wavelet coefficients in the wavelet domain. The set of wavelet moments forms the feature vector related to the texture distribution of each wavelet images. The distances between the feature vectors describe the similarities of different images. The experimental result shows that the M-band wavelet moment features of the images are effective for image indexing.The retrieval method has lower computational complexity, yet it is capable of giving better retrieval performance for a given medical image database.

Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

Directory of Open Access Journals (Sweden)

Lijuan Duan

2017-01-01

Full Text Available Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency. Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks. Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image. In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI, to generate a more compact hash code which has stronger expression ability and distinction capability. In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images. Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.

Hospital nurses' information retrieval behaviours in relation to evidence based nursing: a literature review.

Science.gov (United States)

Alving, Berit Elisabeth; Christensen, Janne Buck; Thrysøe, Lars

2018-03-01

The purpose of this literature review is to provide an overview of the information retrieval behaviour of clinical nurses, in terms of the use of databases and other information resources and their frequency of use. Systematic searches carried out in five databases and handsearching were used to identify the studies from 2010 to 2016, with a populations, exposures and outcomes (PEO) search strategy, focusing on the question: In which databases or other information resources do hospital nurses search for evidence based information, and how often? Of 5272 titles retrieved based on the search strategy, only nine studies fulfilled the criteria for inclusion. The studies are from the United States, Canada, Taiwan and Nigeria. The results show that hospital nurses' primary choice of source for evidence based information is Google and peers, while bibliographic databases such as PubMed are secondary choices. Data on frequency are only included in four of the studies, and data are heterogenous. The reasons for choosing Google and peers are primarily lack of time; lack of information; lack of retrieval skills; or lack of training in database searching. Only a few studies are published on clinical nurses' retrieval behaviours, and more studies are needed from Europe and Australia. © 2018 Health Libraries Group.

A new method for information retrieval in two-dimensional grating-based X-ray phase contrast imaging

International Nuclear Information System (INIS)

Wang Zhi-Li; Gao Kun; Chen Jian; Ge Xin; Tian Yang-Chao; Wu Zi-Yu; Zhu Pei-Ping

2012-01-01

Grating-based X-ray phase contrast imaging has been demonstrated to be an extremely powerful phase-sensitive imaging technique. By using two-dimensional (2D) gratings, the observable contrast is extended to two refraction directions. Recently, we have developed a novel reverse-projection (RP) method, which is capable of retrieving the object information efficiently with one-dimensional (1D) grating-based phase contrast imaging. In this contribution, we present its extension to the 2D grating-based X-ray phase contrast imaging, named the two-dimensional reverse-projection (2D-RP) method, for information retrieval. The method takes into account the nonlinear contributions of two refraction directions and allows the retrieval of the absorption, the horizontal and the vertical refraction images. The obtained information can be used for the reconstruction of the three-dimensional phase gradient field, and for an improved phase map retrieval and reconstruction. Numerical experiments are carried out, and the results confirm the validity of the 2D-RP method

Performance benefits of telerobotics and teleoperation - enhancements for an arm-based tank waste retrieval system

International Nuclear Information System (INIS)

Horschel, D.S.; Gibbons, P.W.; Draper, J.V.

1995-06-01

This report evaluates telerobotic and teleoperational arm-based retrieval systems that require advanced robotic controls. These systems will be deployed in waste retrieval activities in Hanford's Single Shell Tanks (SSTs). The report assumes that arm-based, retrieval systems will combine a teleoperational arm and control system enhanced by a number of advanced and telerobotic controls. The report describes many possible enhancements, spanning the full range of the control spectrum with the potential for technical maturation. The enhancements considered present a variety of choices and factors including: the enhancements to be included in the actual control system, safety, detailed task analyses, human factors, cost-benefit ratios, and availability and maturity of technology. Because the actual system will be designed by an offsite vendor, the procurement specifications must have the flexibility to allow bidders to propose a broad range of ideas, yet build in enough restrictions to filter out infeasible and undesirable approaches. At the same time they must allow selection of a technically promising proposal. Based on a preliminary analysis of the waste retrieval task, and considering factors such as operator limitations and the current state of robotics technology, the authors recommend a set of enhancements that will (1) allow the system to complete its waste retrieval mission, and (2) enable future upgrades in response to changing mission needs and technological advances

Performance benefits of telerobotics and teleoperation - enhancements for an arm-based tank waste retrieval system

Energy Technology Data Exchange (ETDEWEB)

Horschel, D.S. [Sandia National Labs., Albuquerque, NM (United States); Gibbons, P.W. [Westinghouse Hanford Co., Richland, WA (United States); Draper, J.V. [Oak Ridge National Lab., TN (United States)] [and others

1995-06-01

This report evaluates telerobotic and teleoperational arm-based retrieval systems that require advanced robotic controls. These systems will be deployed in waste retrieval activities in Hanford`s Single Shell Tanks (SSTs). The report assumes that arm-based, retrieval systems will combine a teleoperational arm and control system enhanced by a number of advanced and telerobotic controls. The report describes many possible enhancements, spanning the full range of the control spectrum with the potential for technical maturation. The enhancements considered present a variety of choices and factors including: the enhancements to be included in the actual control system, safety, detailed task analyses, human factors, cost-benefit ratios, and availability and maturity of technology. Because the actual system will be designed by an offsite vendor, the procurement specifications must have the flexibility to allow bidders to propose a broad range of ideas, yet build in enough restrictions to filter out infeasible and undesirable approaches. At the same time they must allow selection of a technically promising proposal. Based on a preliminary analysis of the waste retrieval task, and considering factors such as operator limitations and the current state of robotics technology, the authors recommend a set of enhancements that will (1) allow the system to complete its waste retrieval mission, and (2) enable future upgrades in response to changing mission needs and technological advances.

DORS: DDC Online Retrieval System.

Science.gov (United States)

Liu, Songqiao; Svenonius, Elaine

1991-01-01

Describes the Dewey Online Retrieval System (DORS), which was developed at the University of California, Los Angeles (UCLA), to experiment with classification-based search strategies in online catalogs. Classification structures in automated information retrieval are discussed; and specifications for a classification retrieval interface are…

AGRIS: Categorization and information retrieval based on IBM's IRMS

International Nuclear Information System (INIS)

Schmid, H.; Leatherdale, D.

1976-01-01

The subject breakdown of the AGRIS data base by categories interlinked with object and geographical codes is described. The use of these categories and codes in a mechanized information retrieval system is then considered. The system is a modification of IBM's Information Retrieval and Management System (IRMS); it allows for batch processing on an IBM/360 or /370 computer operated under OS or VS. As IRMS was developed for use with a controlled vocabulary, the search possibilities on the AGRIS files are necessarily limited. An artificial vocabulary is presented, derived from the AGRIS subject categories, object codes, geographic codes, language codes, and bibliographic data: type of record, literary indicator, volume/issue number, and the country code of the submitting centre. The use of the IRMS system for AGRIS is described, with details of programming deliberately omitted. Program descriptions with data set definitions and file formats are presented separately

Image Retrieval Berdasarkan Fitur Warna, Bentuk, dan Tekstur

Directory of Open Access Journals (Sweden)

Rita Layona

2014-12-01

Full Text Available Along with the times, information retrieval is no longer just on textual data, but also the visual data. The technique was originally used is Text-Based Image Retrieval (TBIR, but the technique still has some shortcomings such as the relevance of the picture successfully retrieved, and the specific space required to store meta-data in the image. Seeing the shortage of Text-Based Image Retrieval techniques, then other techniques were developed, namely Image Retrieval based on content or commonly called Content Based Image Retrieval (CBIR. In this research, CBIR will be discussed based on color, shape and texture using a color histogram, Gabor and SIFT. This study aimed to compare the results of image retrieval with some of these techniques. The results obtained are by combining color, shape and texture features, the performance of the system can be improved.

Automating the construction of scene classifiers for content-based video retrieval

NARCIS (Netherlands)

Khan, L.; Israël, Menno; Petrushin, V.A.; van den Broek, Egon; van der Putten, Peter

2004-01-01

This paper introduces a real time automatic scene classifier within content-based video retrieval. In our envisioned approach end users like documentalists, not image processing experts, build classifiers interactively, by simply indicating positive examples of a scene. Classification consists of a

Ontology driven framework for multimedia information retrieval in P2P network

CERN Document Server

Sokhn, Maria

During the last decade we have witnessed an exponential growth of digital documents and multimedia resources, including a vast amount of video resources. Videos are becoming one of the most popular media thanks to the rich audio, visual and textual content they may convey. The recent technological advances have made this large amount of multimedia resources available to users in a variety of areas, including the academic and scientific realms. However, without adequate techniques for effective content based multimedia retrieval, this large and valuable body of data is barely accessible and remains in effect unusable. This thesis explores semantic approaches to content based management browsing and visualization of the multimedia resources generated for and during scientific conferences. Indeed, a so-called semantic gap exists between the explicit knowledge representation required by users who search the multimedia resources and the implicit knowledge conveyed within a conference life cycle. The aim of this wo...

Less we forget: retrieval cues and release from retrieval-induced forgetting.

Science.gov (United States)

Jonker, Tanya R; Seli, Paul; Macleod, Colin M

2012-11-01

Retrieving some items from memory can impair the subsequent recall of other related but not retrieved items, a phenomenon called retrieval-induced forgetting (RIF). The dominant explanation of RIF-the inhibition account-asserts that forgetting occurs because related items are suppressed during retrieval practice to reduce retrieval competition. This item inhibition persists, making it more difficult to recall the related items on a later test. In our set of experiments, each category was designed such that each exemplar belonged to one of two subcategories (e.g., each BIRD exemplar was either a bird of prey or a pet bird), but this subcategory information was not made explicit during study or retrieval practice. Practicing retrieval of items from only one subcategory led to RIF for items from the other subcategory when cued only with the overall category label (BIRD) at test. However, adapting the technique of Gardiner, Craik, and Birtwistle (Journal of Learning and Verbal Behavior 11:778-783, 1972), providing subcategory cues during the final test eliminated RIF. The results challenge the inhibition account's fundamental assumption of cue independence but are consistent with a cue-based interference account.

Enhancing Image Retrieval System Using Content Based Search ...

African Journals Online (AJOL)

The output shows more efficiency in retrieval because instead of performing the search on the entire image database, the image category option directs the retrieval engine to the specified category. Also, there is provision to update or modify the different image categories in the image database as need arise. Keywords: ...

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

Science.gov (United States)

Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

2006-01-01

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

Towards Intelligible Query Processing in Relevance Feedback-Based Image Retrieval Systems

OpenAIRE

Mohammed, Belkhatir

2008-01-01

We have specified within the scope of this paper a framework combining semantics and relational (spatial) characterizations within a coupled architecture in order to address the semantic gap. This framework is instantiated by an operational model based on a sound logic-based formalism, allowing to define a representation for image documents and a matching function to compare index and query structures. We have specified a query framework coupling keyword-based querying with a relevance feedba...

Interactive Exploration for Image Retrieval

Directory of Open Access Journals (Sweden)

Jérôme Fournier

2005-08-01

Full Text Available We present a new version of our content-based image retrieval system RETIN. It is based on adaptive quantization of the color space, together with new features aiming at representing the spatial relationship between colors. Color analysis is also extended to texture. Using these powerful indexes, an original interactive retrieval strategy is introduced. The process is based on two steps for handling the retrieval of very large image categories. First, a controlled exploration method of the database is presented. Second, a relevance feedback method based on statistical learning is proposed. All the steps are evaluated by experiments on a generalist database.

Cloud based automated framework for semantic rich ontology construction and similarity computation for E-health applications

Directory of Open Access Journals (Sweden)

T. MuthamilSelvan

Full Text Available Ontology structure, a core of semantic web is an excellent tool for knowledge representation and semantic visualization. Moreover, knowledge reuse is made possible through similarity measure estimation between two ontologies, threshold estimation and use of simple if-then rules for checking relevancy and irrelevancy measures. Reduced semantic representations of the ontology provide reduced knowledge visualization which is critical especially for e-health data processing and analysis. This usually occurs due to the presence of implicit knowledge and polymorphic objects and can be made semantically rich through the construction by resolving this implicit knowledge occurring in the form of non-dominant words and conditional dependence actions. This paper presents the working of the automated framework for the construction of semantic rich ontology structures and store in the repository. This construction uses dyadic deontic logic based Graph Derivation Representation in order to construct semantically rich ontologies. Moreover, in order to retrieve a set of relevant documents in response to the cloud user document, the degree of similarity between two ontologies is estimated using the traditional cosine similarity measure and simple if-then rules are used to determine the number of relevant documents and obtain such document's metadata for further processing. These working modules will be extremely beneficial to the authenticated cloud users for document retrieval, information extraction and domain dictionary construction which are especially used for e-health applications. The proposed framework is implemented using diabetes dataset and the effectiveness of the experimental results is high when compared to other Graph Derivation Representation methods. The graphical results shown in the paper is an added visualization for viewing the performance of the proposed framework. Keywords: Ontology, Implicit knowledge, Conditional dependence, Graph

Multiscale Distance Coherence Vector Algorithm for Content-Based Image Retrieval

Science.gov (United States)

Jiexian, Zeng; Xiupeng, Liu

2014-01-01

Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise. PMID:24883416

Indexing, learning and content-based retrieval for special purpose image databases

NARCIS (Netherlands)

M.J. Huiskes (Mark); E.J. Pauwels (Eric)

2005-01-01

textabstractThis chapter deals with content-based image retrieval in special purpose image databases. As image data is amassed ever more effortlessly, building efficient systems for searching and browsing of image databases becomes increasingly urgent. We provide an overview of the current

The utilization of human color categorization for content-based image retrieval

NARCIS (Netherlands)

van den Broek, Egon; Rogowitz, Bernice E.; Kisters, Peter M.F.; Pappas, Thrasyvoulos N.; Vuurpijl, Louis G.

2004-01-01

We present the concept of intelligent Content-Based Image Retrieval (iCBIR), which incorporates knowledge concerning human cognition in system development. The present research focuses on the utilization of color categories (or focal colors) for CBIR purposes, in particularly considered to be useful

Pulse Retrieval Algorithm for Interferometric Frequency-Resolved Optical Gating Based on Differential Evolution

OpenAIRE

Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

2017-01-01

A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove robustness of the algorithm against experimental artifacts and noise. These tests show that the i...

ImageGrouper: a group-oriented user interface for content-based image retrieval and digital image arrangement

NARCIS (Netherlands)

Nakazato, Munehiro; Manola, L.; Huang, Thomas S.

In content-based image retrieval (CBIR), experimental (trial-and-error) query with relevance feedback is essential for successful retrieval. Unfortunately, the traditional user interfaces are not suitable for trying different combinations of query examples. This is because first, these systems

A Framework-Based Environment for Object-Oriented Scientific Codes

Directory of Open Access Journals (Sweden)

Robert A. Ballance

1993-01-01

Full Text Available Frameworks are reusable object-oriented designs for domain-specific programs. In our estimation, frameworks are the key to productivity and reuse. However, frameworks require increased support from the programming environment. A framework-based environment must include design aides and project browsers that can mediate between the user and the framework. A framework-based approach also places new requirements on conventional tools such as compilers. This article explores the impact of object-oriented frameworks upon a programming environment, in the context of object-oriented finite element and finite difference codes. The role of tools such as design aides and project browsers is discussed, and the impact of a framework-based approach upon compilers is examined. Examples are drawn from our prototype C++ based environment.

Image Information Retrieval: An Overview of Current Research

OpenAIRE

Abby A. Goodrum

2000-01-01

This paper provides an overview of current research in image information retrieval and provides an outline of areas for future research. The approach is broad and interdisciplinary and focuses on three aspects of image research (IR): text-based retrieval, content-based retrieval, and user interactions with image information retrieval systems. The review concludes with a call for image retrieval evaluation studies similar to TREC.

Dress like a Star: Retrieving Fashion Products from Videos

OpenAIRE

Garcia, Noa; Vogiatzis, George

2017-01-01

This work proposes a system for retrieving clothing and fashion products from video content. Although films and television are the perfect showcase for fashion brands to promote their products, spectators are not always aware of where to buy the latest trends they see on screen. Here, a framework for breaking the gap between fashion products shown on videos and users is presented. By relating clothing items and video frames in an indexed database and performing frame retrieval with temporal a...

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

Science.gov (United States)

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.

Content-Based Image Retrieval Benchmarking: Utilizing color categories and color distributions

NARCIS (Netherlands)

van den Broek, Egon; Kisters, Peter M.F.; Vuurpijl, Louis G.

From a human centered perspective three ingredients for Content-Based Image Retrieval (CBIR) were developed. First, with their existence confirmed by experimental data, 11 color categories were utilized for CBIR and used as input for a new color space segmentation technique. The complete HSI color

Distributed open environment for data retrieval based on pattern recognition techniques

International Nuclear Information System (INIS)

Pereira, A.; Vega, J.; Castro, R.; Portas, A.

2010-01-01

Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, interoperability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE (Java 2 Enterprise Edition), which provides a mature standard framework and a modular architecture. It can handle transactions and concurrency of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows hiding of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests.

Distributed Open Environment for Data Retrieval based on Pattern Recognition Techniques

Energy Technology Data Exchange (ETDEWEB)

Pereira, A.; Vega, J.; Castro, R.; Portas, A. [Association EuratomCIEMAT para Fusion, Madrid (Spain)

2009-07-01

Full text of publication follows: Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, inter-operability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE, which provides a mature standard framework and a modular architecture. It can handle transactions and competition of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows concealment of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests. (authors)

Distributed open environment for data retrieval based on pattern recognition techniques

Energy Technology Data Exchange (ETDEWEB)

Pereira, A., E-mail: augusto.pereira@ciemat.e [Asociacion EURATOM/CIEMAT para Fusion, CIEMAT, Edificio 66, Avda. Complutense, 22, 28040 Madrid (Spain); Vega, J.; Castro, R.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, CIEMAT, Edificio 66, Avda. Complutense, 22, 28040 Madrid (Spain)

2010-07-15

Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, interoperability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE (Java 2 Enterprise Edition), which provides a mature standard framework and a modular architecture. It can handle transactions and concurrency of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows hiding of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests.

Model-based magnetization retrieval from holographic phase images

Energy Technology Data Exchange (ETDEWEB)

Röder, Falk, E-mail: f.roeder@hzdr.de [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Vogel, Karin [Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Wolf, Daniel [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Hellwig, Olav [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); AG Magnetische Funktionsmaterialien, Institut für Physik, Technische Universität Chemnitz, D-09126 Chemnitz (Germany); HGST, A Western Digital Company, 3403 Yerba Buena Rd., San Jose, CA 95135 (United States); Wee, Sung Hun [HGST, A Western Digital Company, 3403 Yerba Buena Rd., San Jose, CA 95135 (United States); Wicht, Sebastian; Rellinghaus, Bernd [IFW Dresden, Institute for Metallic Materials, P.O. Box 270116, D-01171 Dresden (Germany)

2017-05-15

The phase shift of the electron wave is a useful measure for the projected magnetic flux density of magnetic objects at the nanometer scale. More important for materials science, however, is the knowledge about the magnetization in a magnetic nano-structure. As demonstrated here, a dominating presence of stray fields prohibits a direct interpretation of the phase in terms of magnetization modulus and direction. We therefore present a model-based approach for retrieving the magnetization by considering the projected shape of the nano-structure and assuming a homogeneous magnetization therein. We apply this method to FePt nano-islands epitaxially grown on a SrTiO{sub 3} substrate, which indicates an inclination of their magnetization direction relative to the structural easy magnetic [001] axis. By means of this real-world example, we discuss prospects and limits of this approach. - Highlights: • Retrieval of the magnetization from holographic phase images. • Magnetostatic model constructed for a magnetic nano-structure. • Decomposition into homogeneously magnetized components. • Discretization of a each component by elementary cuboids. • Analytic solution for the phase of a magnetized cuboid considered. • Fitting a set of magnetization vectors to experimental phase images.

A Secured Cognitive Agent based Multi-strategic Intelligent Search System

Directory of Open Access Journals (Sweden)

Neha Gulati

2018-04-01

Full Text Available Search Engine (SE is the most preferred information retrieval tool ubiquitously used. In spite of vast scale involvement of users in SE’s, their limited capabilities to understand the user/searcher context and emotions places high cognitive, perceptual and learning load on the user to maintain the search momentum. In this regard, the present work discusses a Cognitive Agent (CA based approach to support the user in Web-based search process. The work suggests a framework called Secured Cognitive Agent based Multi-strategic Intelligent Search System (CAbMsISS to assist the user in search process. It helps to reduce the contextual and emotional mismatch between the SE’s and user. After implementation of the proposed framework, performance analysis shows that CAbMsISS framework improves Query Retrieval Time (QRT and effectiveness for retrieving relevant results as compared to Present Search Engine (PSE. Supplementary to this, it also provides search suggestions when user accesses a resource previously tagged with negative emotions. Overall, the goal of the system is to enhance the search experience for keeping the user motivated. The framework provides suggestions through the search log that tracks the queries searched, resources accessed and emotions experienced during the search. The implemented framework also considers user security. Keywords: BDI model, Cognitive Agent, Emotion, Information retrieval, Intelligent search, Search Engine

FRESCO+: an improved O2 A-band cloud retrieval algorithm for tropospheric trace gas retrievals

Directory of Open Access Journals (Sweden)

M. van Roozendael

2008-11-01

Full Text Available The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds show that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger. The effect of FRESCO+ cloud parameters on O3 and NO2 vertical column density (VCD retrievals is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO2 retrievals but a minor effect on total O3 retrievals. The retrieved SCIAMACHY tropospheric NO2 VCDs using FRESCO+ cloud parameters (v1.1 are lower than the tropospheric NO2VCDs which used FRESCO cloud parameters (v1.04, in particular over heavily polluted areas with low clouds. The difference between SCIAMACHY tropospheric NO2 VCDs v1.1 and ground-based MAXDOAS measurements performed in Cabauw, The Netherlands, during the DANDELIONS campaign is about −2.12×1014molec cm−2.

Top-down NOx and SO2 emissions simultaneously estimated from different OMI retrievals and inversion frameworks

Science.gov (United States)

Qu, Z.; Henze, D. K.; Wang, J.; Xu, X.; Wang, Y.

2017-12-01

Quantifying emissions trends of nitrogen oxides (NOx) and sulfur dioxide (SO2) is important for improving understanding of air pollution and the effectiveness of emission control strategies. We estimate long-term (2005-2016) global (2° x 2.5° resolution) and regional (North America and East Asia at 0.5° x 0.667° resolution) NOx emissions using a recently developed hybrid (mass-balance / 4D-Var) method with GEOS-Chem. NASA standard product and DOMINO retrievals of NO2 column are both used to constrain emissions; comparison of these results provides insight into regions where trends are most robust with respect to retrieval uncertainties, and highlights regions where seemingly significant trends are retrieval-specific. To incorporate chemical interactions among species, we extend our hybrid method to assimilate NO2 and SO2 observations and optimize NOx and SO2 emissions simultaneously. Due to chemical interactions, inclusion of SO2 observations leads to 30% grid-scale differences in posterior NOx emissions compared to those constrained only by NO2 observations. When assimilating and optimizing both species in pseudo observation tests, the sum of the normalized mean squared error (compared to the true emissions) of NOx and SO2 posterior emissions are 54-63% smaller than when observing/constraining a single species. NOx and SO2 emissions are also correlated through the amount of fuel combustion. To incorporate this correlation into the inversion, we optimize seven sector-specific emission scaling factors, including industry, energy, residential, aviation, transportation, shipping and agriculture. We compare posterior emissions from inversions optimizing only species' emissions, only sector-based emissions, and both species' and sector-based emissions. In situ measurements of NOx and SO2 are applied to evaluate the performance of these inversions. The impacts of the inversion on PM2.5 and O3 concentrations and premature deaths are also evaluated.

A Framework for IT-based Design Tools

DEFF Research Database (Denmark)

Hartvig, Susanne C

The thesis presents a new apprach to develop design tools that can be integrated, bypresenting a framework consisting of a set of guidelines for design tools, an integration andcommunication scheme, and a set of design tool schemes.This framework has been based onanalysis of requirements to integ...... to integrated design enviornments, and analysis of engineeringdesign and design problem solving methods. And the developed framework has been testedby applying it to development of prototype design tools for realistic design scenarios.......The thesis presents a new apprach to develop design tools that can be integrated, bypresenting a framework consisting of a set of guidelines for design tools, an integration andcommunication scheme, and a set of design tool schemes.This framework has been based onanalysis of requirements...

Robust histogram-based image retrieval

Czech Academy of Sciences Publication Activity Database

Höschl, Cyril; Flusser, Jan

2016-01-01

Roč. 69, č. 1 (2016), s. 72-81 ISSN 0167-8655 R&D Projects: GA ČR GA15-16928S Institutional support: RVO:67985556 Keywords : Image retrieval * Noisy image * Histogram * Convolution * Moments * Invariants Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.995, year: 2016 http://library.utia.cas.cz/separaty/2015/ZOI/hoschl-0452147.pdf

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

Science.gov (United States)

Taylor, Jaime R.

2003-01-01

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

An efficient similarity measure for content based image retrieval using memetic algorithm

Directory of Open Access Journals (Sweden)

Mutasem K. Alsmadi

2017-06-01

Full Text Available Content based image retrieval (CBIR systems work by retrieving images which are related to the query image (QI from huge databases. The available CBIR systems extract limited feature sets which confine the retrieval efficacy. In this work, extensive robust and important features were extracted from the images database and then stored in the feature repository. This feature set is composed of color signature with the shape and color texture features. Where, features are extracted from the given QI in the similar fashion. Consequently, a novel similarity evaluation using a meta-heuristic algorithm called a memetic algorithm (genetic algorithm with great deluge is achieved between the features of the QI and the features of the database images. Our proposed CBIR system is assessed by inquiring number of images (from the test dataset and the efficiency of the system is evaluated by calculating precision-recall value for the results. The results were superior to other state-of-the-art CBIR systems in regard to precision.

Scientometric Indicators and Webometrics - and the Polyrepresentation Principle in Information Retrieval

DEFF Research Database (Denmark)

Ingwersen, Peter

and new ones based on scientific dataset usage and comparisons of link and download/reading patterns for newspapers. The third lecture on poly-representation provides an integrated and explicitly cognitive framework for understanding the process involved in information retrieval. The lecture outlined......This book contains the text of three lectures from the 28th Sarada Ranganathan Endowment Lectures, held in Bangalore in December 2010. The lectures were delivered by Dr. Peter Ingwersen, Professor at the Danish School of Library and Information Science, Copenhagen. The first lecture...

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

Directory of Open Access Journals (Sweden)

Perez-Rey David

2012-04-01

Full Text Available Abstract Background Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs. In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA, (ii identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH, automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard

towards a theory-based multi-dimensional framework for assessment in mathematics: The "SEA" framework

Science.gov (United States)

Anku, Sitsofe E.

1997-09-01

Using the reform documents of the National Council of Teachers of Mathematics (NCTM) (NCTM, 1989, 1991, 1995), a theory-based multi-dimensional assessment framework (the "SEA" framework) which should help expand the scope of assessment in mathematics is proposed. This framework uses a context based on mathematical reasoning and has components that comprise mathematical concepts, mathematical procedures, mathematical communication, mathematical problem solving, and mathematical disposition.

Using the CARDAMOM framework to retrieve global terrestrial ecosystem functioning properties

Science.gov (United States)

Exbrayat, Jean-François; Bloom, A. Anthony; Smallman, T. Luke; van der Velde, Ivar R.; Feng, Liang; Williams, Mathew

2016-04-01

Terrestrial ecosystems act as a sink for anthropogenic emissions of fossil-fuel and thereby partially offset the ongoing global warming. However, recent model benchmarking and intercomparison studies have highlighted the non-trivial uncertainties that exist in our understanding of key ecosystem properties like plant carbon allocation and residence times. It leads to worrisome differences in terrestrial carbon stocks simulated by Earth system models, and their evolution in a warming future. In this presentation we attempt to provide global insights on these properties by merging an ecosystem model with remotely-sensed global observations of leaf area and biomass through a data-assimilation system: the CARbon Data MOdel fraMework (CARDAMOM). CARDAMOM relies on a Markov Chain Monte Carlo algorithm to retrieve confidence intervals of model parameters that regulate ecosystem properties independently of any prior land-cover information. The MCMC method thereby enables an explicit representation of the uncertainty in land-atmosphere fluxes and the evolution of terrestrial carbon stocks through time. Global experiments are performed for the first decade of the 21st century using a 1°×1° spatial resolution. Relationships emerge globally between key ecosystem properties. For example, our analyses indicate that leaf lifespan and leaf mass per area are highly correlated. Furthermore, there exists a latitudinal gradient in allocation patterns: high latitude ecosystems allocate more carbon to photosynthetic carbon (leaves) while plants invest more carbon in their structural parts (wood and root) in the wet tropics. Overall, the spatial distribution of these ecosystem properties does not correspond to usual land-cover maps and are also partially correlated with disturbance regimes. For example, fire-prone ecosystems present statistically significant higher values of carbon use efficiency than less disturbed ecosystems experiencing similar climatic conditions. These results

Interactive information seeking, behaviour and retrieval

CERN Document Server

Ruthven, Ian

2011-01-01

Information retrieval (IR) is a complex human activity supported by sophisticated systems. This book covers the whole spectrum of information retrieval, including: history and background information; behaviour and seeking task-based information; searching and retrieval approaches to investigating information; and, evaluation interfaces for IR.

Pleasant/Unpleasant Filtering for Affective Image Retrieval Based on Cross-Correlation of EEG Features

Directory of Open Access Journals (Sweden)

Keranmu Xielifuguli

2014-01-01

Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

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

Science.gov (United States)

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

2013-04-01

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

An automated and integrated framework for dust storm detection based on ogc web processing services

Science.gov (United States)

Xiao, F.; Shea, G. Y. K.; Wong, M. S.; Campbell, J.

2014-11-01

Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data

Retrieval of liquid water cloud properties from ground-based remote sensing observations

NARCIS (Netherlands)

Knist, C.L.

2014-01-01

Accurate ground-based remotely sensed microphysical and optical properties of liquid water clouds are essential references to validate satellite-observed cloud properties and to improve cloud parameterizations in weather and climate models. This requires the evaluation of algorithms for retrieval of

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

Science.gov (United States)

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote

Content-based image retrieval using a signature graph and a self-organizing map

Directory of Open Access Journals (Sweden)

Van Thanh The

2016-06-01

Full Text Available In order to effectively retrieve a large database of images, a method of creating an image retrieval system CBIR (contentbased image retrieval is applied based on a binary index which aims to describe features of an image object of interest. This index is called the binary signature and builds input data for the problem of matching similar images. To extract the object of interest, we propose an image segmentation method on the basis of low-level visual features including the color and texture of the image. These features are extracted at each block of the image by the discrete wavelet frame transform and the appropriate color space. On the basis of a segmented image, we create a binary signature to describe the location, color and shape of the objects of interest. In order to match similar images, we provide a similarity measure between the images based on binary signatures. Then, we present a CBIR model which combines a signature graph and a self-organizing map to cluster and store similar images. To illustrate the proposed method, experiments on image databases are reported, including COREL,Wang and MSRDI.

Elaborative Retrieval: Do Semantic Mediators Improve Memory?

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Lehman, Melissa; Karpicke, Jeffrey D.

2016-01-01

The elaborative retrieval account of retrieval-based learning proposes that retrieval enhances retention because the retrieval process produces the generation of semantic mediators that link cues to target information. We tested 2 assumptions that form the basis of this account: that semantic mediators are more likely to be generated during…

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

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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.

A Matlab based framework for the real-time environment at FTU

International Nuclear Information System (INIS)

Vitale, V.; Iannone, F.; Centioli, C.; Pangione, L.; Zaccarian, L.

2006-01-01

The Feedback Control System running at FTU has been recently ported from a commercial platform (O.S. LynxOS) to an open-source GNU/Linux-RTAI platform, obtaining significant performance and cost improvements. Thanks to the new platform, more user friendly tools can be developed in order to help the designer with new control laws. A relevant goal within this new framework is to provide a high level environment where new control algorithms can be created then simulated and finally released without minding the code implementation issues. The ideal situation would be to have a dedicated framework which provides all the necessary phases from the design to the commissioning of the new software. This framework should simulate the real-time context and make transparent to the user on the one hand all the issues related to the simulation (e.g. experimental data retrieving) and on the other hand all the aspects (platform, operating system, programming language, network, hardware...) related to the actual environment where the new algorithm will be run. In this paper we report on recent developments, based on The MathWorks' Simulink and Real Time Workshop (RTW) packages, aimed at obtaining the above mentioned environment where a new control law can be easily modelled, simulated with the real time constraints and then translated in the appropriate executable format. Using this tool, the control designer only needs to specify the control law in the Simulink graphical environment. The arising model is then automatically translated in C code, integrated with control system code and simulated in real-time using the data from the FTU data base archive. All the necessary steps to adapt the RTW scripts and the control system code to the new simulation/validation environment will be illustrated in this paper. Moreover we will report on some experimental tests where the actual experiment is compared with the simulations provided by the proposed environment. (author)

Transaction-Based Building Controls Framework, Volume 1: Reference Guide

Energy Technology Data Exchange (ETDEWEB)

Somasundaram, Sriram [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pratt, Robert G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Akyol, Bora A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fernandez, Nicholas [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Foster, Nikolas AF [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Katipamula, Srinivas [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Mayhorn, Ebony T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Somani, Abhishek [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Steckley, Andrew C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Taylor, Zachary T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2014-12-01

This document proposes a framework concept to achieve the objectives of raising buildings’ efficiency and energy savings potential benefitting building owners and operators. We call it a transaction-based framework, wherein mutually-beneficial and cost-effective market-based transactions can be enabled between multiple players across different domains. Transaction-based building controls are one part of the transactional energy framework. While these controls realize benefits by enabling automatic, market-based intra-building efficiency optimizations, the transactional energy framework provides similar benefits using the same market -based structure, yet on a larger scale and beyond just buildings, to the society at large.

Improving data retrieval quality: Evidence based medicine perspective.

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Kamalov, M; Dobrynin, V; Balykina, J; Kolbin, A; Verbitskaya, E; Kasimova, M

2015-01-01

The actively developing approach in modern medicine is the approach focused on principles of evidence-based medicine. The assessment of quality and reliability of studies is needed. However, in some cases studies corresponding to the first level of evidence may contain errors in randomized control trials (RCTs). Solution of the problem is the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Studies both in the fields of medicine and information retrieval are conducted for developing search engines for the MEDLINE database [1]; combined techniques for summarization and information retrieval targeted to solving problems of finding the best medication based on the levels of evidence are being developed [2]. Based on the relevance and demand for studies both in the field of medicine and information retrieval, it was decided to start the development of a search engine for the MEDLINE database search on the basis of the Saint-Petersburg State University with the support of Pavlov First Saint-Petersburg State Medical University and Tashkent Institute of Postgraduate Medical Education. Novelty and value of the proposed system are characterized by the use of ranking method of relevant abstracts. It is suggested that the system will be able to perform ranking based on studies level of evidence and to apply GRADE criteria for system evaluation. The assigned task falls within the domain of information retrieval and machine learning. Based on the results of implementation from previous work [3], in which the main goal was to cluster abstracts from MEDLINE database by subtypes of medical interventions, a set of algorithms for clustering in this study was selected: K-means, K-means ++, EM from the sklearn (http://scikit-learn.org) and WEKA (http://www.cs.waikato.ac.nz/~ml/weka/) libraries, together with the methods of Latent Semantic Analysis (LSA) [4] choosing the first 210 facts and the model "bag of words" [5] to represent clustered documents

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

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Oh, Heung-Seon; Jung, Yuchul

2015-12-01

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

Understanding human quality judgment in assessing online forum contents for thread retrieval purpose

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Ismail, Zuriati; Salim, Naomie; Huspi, Sharin Hazlin

2017-10-01

Compared to traditional materials or journals, user-generated contents are not peer-reviewed. Lack of quality control and the explosive growth of web contents make the task of finding quality information on the web especially critical. The existence of new facilities for producing web contents such as forum makes this issue more significant. This study focuses on online forums threads or discussion, where the forums contain valuable human-generated information in a form of discussions. Due to the unique structure of the online forum pages, special techniques are required to organize and search for information in these forums. Quality biased retrieval is a retrieval approach that search for relevant document and prioritized higher quality documents. Despite major concern of quality content and recent development of quality biased retrieval, there is an urgent need to understand how quality content is being judged, for retrieval and performance evaluation purposes. Furthermore, even though there are various studies on the quality of information, there is no standard framework that has been established. The primary aim of this paper is to contribute to the understanding of human quality judgment in assessing online forum contents. The foundation of this study is to compare and evaluate different frameworks (for quality biased retrieval and information quality). This led to the finding that many quality dimensions are redundant and some dimensions are understood differently between different studies. We conducted a survey on crowdsourcing community to measure the importance of each quality dimensions found in various frameworks. Accuracy and ease of understanding are among top important dimensions while threads popularity and contents manipulability are among least important dimensions. This finding is beneficial in evaluating contents of online forum.

Considering polarization in MODIS-based cloud property retrievals by using a vector radiative transfer code

International Nuclear Information System (INIS)

Yi, Bingqi; Huang, Xin; Yang, Ping; Baum, Bryan A.; Kattawar, George W.

2014-01-01

In this study, a full-vector, adding–doubling radiative transfer model is used to investigate the influence of the polarization state on cloud property retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. Two sets of lookup tables (LUTs) are developed for the retrieval purposes, both of which provide water cloud and ice cloud reflectivity functions at two wavelengths in various sun-satellite viewing geometries. However, only one of the LUTs considers polarization. The MODIS reflectivity observations at 0.65 μm (band 1) and 2.13 μm (band 7) are used to infer the cloud optical thickness and particle effective diameter, respectively. Results indicate that the retrievals for both water cloud and ice cloud show considerable sensitivity to polarization. The retrieved water and ice cloud effective diameter and optical thickness differences can vary by as much as ±15% due to polarization state considerations. In particular, the polarization state has more influence on completely smooth ice particles than on severely roughened ice particles. - Highlights: • Impact of polarization on satellite-based retrieval of water/ice cloud properties is studied. • Inclusion of polarization can change water/ice optical thickness and effective diameter values by up to ±15%. • Influence of polarization on cloud property retrievals depends on sun-satellite viewing geometries

Empirical wind retrieval model based on SAR spectrum measurements

Science.gov (United States)

Panfilova, Maria; Karaev, Vladimir; Balandina, Galina; Kanevsky, Mikhail; Portabella, Marcos; Stoffelen, Ad

ambiguity from polarimetric SAR. A criterion based on the complex correlation coefficient between the VV and VH signals sign is applied to select the wind direction. An additional quality control on the wind speed value retrieved with the spectral method is applied. Here, we use the direction obtained with the spectral method and the backscattered signal for CMOD wind speed estimate. The algorithm described above may be refined by the use of numerous SAR data and wind measurements. In the present preliminary work the first results of SAR images combined with in situ data processing are presented. Our results are compared to the results obtained using previously developed models CMOD, C-2PO for VH polarization and statistical wind retrieval approaches [1]. Acknowledgments. This work is supported by the Russian Foundation of Basic Research (grants 13-05-00852-a). [1] M. Portabella, A. Stoffelen, J. A. Johannessen, Toward an optimal inversion method for synthetic aperture radar wind retrieval, Journal of geophysical research, V. 107, N C8, 2002

Seven years of global retrieval of cloud properties using space-borne data of GOME

Directory of Open Access Journals (Sweden)

L. Lelli

2012-07-01

Full Text Available We present a global and regional multi-annual (June 1996–May 2003 analysis of cloud properties (spherical cloud albedo – CA, cloud optical thickness – COT and cloud top height – CTH of optically thick (COT > 5 clouds, derived using measurements from the GOME instrument on board the ESA ERS-2 space platform. We focus on cloud top height, which is obtained from top-of-atmosphere backscattered solar light measurements in the O₂ A-band using the Semi-Analytical CloUd Retrieval Algorithm SACURA. The physical framework relies on the asymptotic equations of radiative transfer. The dataset has been validated against independent ground- and satellite-based retrievals and is aimed to support trace-gases retrievals as well as to create a robust long-term climatology together with SCIAMACHY and GOME-2 ensuing retrievals. We observed the El Niño-Southern Oscillation anomaly in the 1997–1998 record through CTH values over the Pacific Ocean. The global average CTH as derived from GOME is 5.6 ± 3.2 km, for a corresponding average COT of 19.1 ± 13.9.

Passive Microwave Precipitation Retrieval Uncertainty Characterized based on Field Campaign Data over Complex Terrain

Science.gov (United States)

Derin, Y.; Anagnostou, E. N.; Anagnostou, M.; Kalogiros, J. A.; Casella, D.; Marra, A. C.; Panegrossi, G.; Sanò, P.

2017-12-01

Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements. Such measurements can be obtained from field campaigns facilitated by research quality sensors such as locally deployed weather radar and in situ weather stations. This study uses such high quality and resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations from three field experiments in Mid-Atlantic US East Coast (NASA IPHEX experiment), the Olympic Peninsula of Washington State (NASA OLYMPEX experiment), and the Mediterranean to characterize the error characteristics of multiple passive microwave (PMW) sensor retrievals. The study first conducts an independent error analysis of the XPOL radar reference rainfall fields against in situ rain gauges and disdrometer observations available by the field experiments. Then the study evaluates different PMW precipitation products using the XPOL datasets (GR) over the three aforementioned complex terrain study areas. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW field-of-view sampling volumes, and scaled GR parameters to the satellite products' nominal spatial resolution. The following PMW precipitation retrieval algorithms are evaluated: the NASA Goddard PROFiling algorithm (GPROF), standard and climatology-based products (V 3, 4 and 5) from four PMW sensors (SSMIS, MHS, GMI, and AMSR2), and the precipitation products based on the algorithms Cloud Dynamics and Radiation Database (CDRD) for SSMIS and Passive microwave Neural network

Utah Text Retrieval Project

Energy Technology Data Exchange (ETDEWEB)

Hollaar, L A

1983-10-01

The Utah Text Retrieval project seeks well-engineered solutions to the implementation of large, inexpensive, rapid text information retrieval systems. The project has three major components. Perhaps the best known is the work on the specialized processors, particularly search engines, necessary to achieve the desired performance and cost. The other two concern the user interface to the system and the system's internal structure. The work on user interface development is not only concentrating on the syntax and semantics of the query language, but also on the overall environment the system presents to the user. Environmental enhancements include convenient ways to browse through retrieved documents, access to other information retrieval systems through gateways supporting a common command interface, and interfaces to word processing systems. The system's internal structure is based on a high-level data communications protocol linking the user interface, index processor, search processor, and other system modules. This allows them to be easily distributed in a multi- or specialized-processor configuration. It also allows new modules, such as a knowledge-based query reformulator, to be added. 15 references.

Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

Science.gov (United States)

Ebrahimi-Khusfi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-05-01

This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (HR) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m3/m3 to 0.06 m3/m3. Second, using the algorithm selected in a first step and defined above, the ω and HR parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and HR were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and HR were found for the different land cover classes. The obtained results indicated that the

Hybrid iterative phase retrieval algorithm based on fusion of intensity information in three defocused planes.

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Zeng, Fa; Tan, Qiaofeng; Yan, Yingbai; Jin, Guofan

2007-10-01

Study of phase retrieval technology is quite meaningful, for its wide applications related to many domains, such as adaptive optics, detection of laser quality, precise measurement of optical surface, and so on. Here a hybrid iterative phase retrieval algorithm is proposed, based on fusion of the intensity information in three defocused planes. First the conjugate gradient algorithm is adapted to achieve a coarse solution of phase distribution in the input plane; then the iterative angular spectrum method is applied in succession for better retrieval result. This algorithm is still applicable even when the exact shape and size of the aperture in the input plane are unknown. Moreover, this algorithm always exhibits good convergence, i.e., the retrieved results are insensitive to the chosen positions of the three defocused planes and the initial guess of complex amplitude in the input plane, which has been proved by both simulations and further experiments.

Agent-Based Data Integration Framework

Directory of Open Access Journals (Sweden)

Łukasz Faber

2014-01-01

Full Text Available Combining data from diverse, heterogeneous sources while facilitating a unified access to it is an important (albeit difficult task. There are various possibilities of performing it. In this publication, we propose and describe an agent-based framework dedicated to acquiring and processing distributed, heterogeneous data collected from diverse sources (e.g., the Internet, external software, relational, and document databases. Using this multi-agent-based approach in the aspects of the general architecture (the organization and management of the framework, we create a proof-of-concept implementation. The approach is presented using a sample scenario in which the system is used to search for personal and professional profiles of scientists.

A Framework for the Flexible Content Packaging of Learning Objects and Learning Designs

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Lukasiak, Jason; Agostinho, Shirley; Burnett, Ian; Drury, Gerrard; Goodes, Jason; Bennett, Sue; Lockyer, Lori; Harper, Barry

2004-01-01

This paper presents a platform-independent method for packaging learning objects and learning designs. The method, entitled a Smart Learning Design Framework, is based on the MPEG-21 standard, and uses IEEE Learning Object Metadata (LOM) to provide bibliographic, technical, and pedagogical descriptors for the retrieval and description of learning…

Encoding specificity manipulations do affect retrieval from memory.

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Zeelenberg, René

2005-05-01

In a recent article, P.A. Higham (2002) [Strong cues are not necessarily weak: Thomson and Tulving (1970) and the encoding specificity principle revisited. Memory &Cognition, 30, 67-80] proposed a new way to analyze cued recall performance in terms of three separable aspects of memory (retrieval, monitoring, and report bias) by comparing performance under both free-report and forced-report instructions. He used this method to derive estimates of these aspects of memory in an encoding specificity experiment similar to that reported by D.M. Thomson and E. Tulving (1970) [Associative encoding and retrieval: weak and strong cues. Journal of Experimental Psychology, 86, 255-262]. Under forced-report instructions, the encoding specificity manipulation did not affect performance. Higham concluded that the manipulation affected monitoring and report bias, but not retrieval. I argue that this interpretation of the results is problematic because the Thomson and Tulving paradigm is confounded, and show in three experiments using a more appropriate design that encoding specificity manipulations do affect performance in forced-report cued recall. Because in Higham's framework forced-report performance provides a measure of retrieval that is uncontaminated by monitoring and report bias it is concluded that encoding specificity manipulations do affect retrieval from memory.

Flexible patient information search and retrieval framework: pilot implementation

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Erdal, Selnur; Catalyurek, Umit V.; Saltz, Joel; Kamal, Jyoti; Gurcan, Metin N.

2007-03-01

Medical centers collect and store significant amount of valuable data pertaining to patients' visit in the form of medical free-text. In addition, standardized diagnosis codes (International Classification of Diseases, Ninth Revision, Clinical Modification: ICD9-CM) related to those dictated reports are usually available. In this work, we have created a framework where image searches could be initiated through a combination of free-text reports as well as ICD9 codes. This framework enables more comprehensive search on existing large sets of patient data in a systematic way. The free text search is enriched by computer-aided inclusion of additional search terms enhanced by a thesaurus. This combination of enriched search allows users to access to a larger set of relevant results from a patient-centric PACS in a simpler way. Therefore, such framework is of particular use in tasks such as gathering images for desired patient populations, building disease models, and so on. As the motivating application of our framework, we implemented a search engine. This search engine processed two years of patient data from the OSU Medical Center's Information Warehouse and identified lung nodule location information using a combination of UMLS Meta-Thesaurus enhanced text report searches along with ICD9 code searches on patients that have been discharged. Five different queries with various ICD9 codes involving lung cancer were carried out on 172552 cases. Each search was completed under a minute on average per ICD9 code and the inclusion of UMLS thesaurus increased the number of relevant cases by 45% on average.

Applying GA for Optimizing the User Query in Image and Video Retrieval

OpenAIRE

Ehsan Lotfi

2014-01-01

In an information retrieval system, the query can be made by user sketch. The new method presented here, optimizes the user sketch and applies the optimized query to retrieval the information. This optimization may be used in Content-Based Image Retrieval (CBIR) and Content-Based Video Retrieval (CBVR) which is based on trajectory extraction. To optimize the retrieval process, one stage of retrieval is performed by the user sketch. The retrieval criterion is based on the proposed distance met...

Tau-REx: A new look at the retrieval of exoplanetary atmospheres

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Waldmann, Ingo

2014-11-01

The field of exoplanetary spectroscopy is as fast moving as it is new. With an increasing amount of space and ground based instruments obtaining data on a large set of extrasolar planets we are indeed entering the era of exoplanetary characterisation. Permanently at the edge of instrument feasibility, it is as important as it is difficult to find the most optimal and objective methodologies to analysing and interpreting current data. This is particularly true for smaller and fainter Earth and Super-Earth type planets.For low to mid signal to noise (SNR) observations, we are prone to two sources of biases: 1) Prior selection in the data reduction and analysis; 2) Prior constraints on the spectral retrieval. In Waldmann et al. (2013), Morello et al. (2014) and Waldmann (2012, 2014) we have shown a prior-free approach to data analysis based on non-parametric machine learning techniques. Following these approaches we will present a new take on the spectral retrieval of extrasolar planets. Tau-REx (tau-retrieval of exoplanets) is a new line-by-line, atmospheric retrieval framework. In the past the decision on what opacity sources go into an atmospheric model were usually user defined. Manual input can lead to model biases and poor convergence of the atmospheric model to the data. In Tau-REx we have set out to solve this. Through custom built pattern recognition software, Tau-REx is able to rapidly identify the most likely atmospheric opacities from a large number of possible absorbers/emitters (ExoMol or HiTran data bases) and non-parametrically constrain the prior space for the Bayesian retrieval. Unlike other (MCMC based) techniques, Tau-REx is able to fully integrate high-dimensional log-likelihood spaces and to calculate the full Bayesian Evidence of the atmospheric models. We achieve this through a combination of Nested Sampling and a high degree of code parallelisation. This allows for an exact and unbiased Bayesian model selection and a fully mapping of potential

PEOPLE RETRIEVAL BY MEANS OF COMPOSITE PICTURES: METHODS, SYSTEMS AND PRACTICAL DECISIONS

Directory of Open Access Journals (Sweden)

G. A. Kukharev

2015-07-01

Full Text Available We discuss the problem of people retrieval by means of composite pictures and methods of its practical realization. Earlier on, the problem was posed in the previous paper by the authors, and this paper deals with its further development. The starting premise here is that for the successful search of people by their sketches it is necessary to transform these sketches into sets of populations of sketches imitating evidence of «group of witnesses» and evidence with incomplete information in verbal portraits. Variants of structures for benchmark «photo-sketch» databases are presented, intended for modeling and practical realization of original photos retrieval by sketches, which new component is a population of sketches. Problems of preprocessing for initial sketches and original photos and its influence on the result of their comparison are discussed. Simple sketch recognition systems (Simple FaRetSys and a problem of original photos retrieval by the sketches are considered. Shortcomings of such systems are shown and new decisions on extending and development of simple systems (Extended FaRetSys are presented. Experiments on searching of original photos by sketches in the CUFS database of sketches and similar experiments on widely known FERET and CUFSF facial databases are presented. Three frameworks are offered for retrieval performance improvement. In the first one, original sketches are transformed into populations, and then in these populations the sketch similar to the given sketch (Forensic Sketch is already defined. The class of the sketch found in a population «by definition» unambiguously corresponds to a class of the original photo. In the second framework, the Forensic Sketch is transformed to a population of sketches, and all original sketches in a benchmarking database are compared to sketches from populations of the Forensic Sketch. The class of matches is determined in the same manner as in the first framework. The third

A Novel Image Retrieval Based on Visual Words Integration of SIFT and SURF.

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Nouman Ali

Full Text Available With the recent evolution of technology, the number of image archives has increased exponentially. In Content-Based Image Retrieval (CBIR, high-level visual information is represented in the form of low-level features. The semantic gap between the low-level features and the high-level image concepts is an open research problem. In this paper, we present a novel visual words integration of Scale Invariant Feature Transform (SIFT and Speeded-Up Robust Features (SURF. The two local features representations are selected for image retrieval because SIFT is more robust to the change in scale and rotation, while SURF is robust to changes in illumination. The visual words integration of SIFT and SURF adds the robustness of both features to image retrieval. The qualitative and quantitative comparisons conducted on Corel-1000, Corel-1500, Corel-2000, Oliva and Torralba and Ground Truth image benchmarks demonstrate the effectiveness of the proposed visual words integration.

A model-based risk management framework

Energy Technology Data Exchange (ETDEWEB)

Gran, Bjoern Axel; Fredriksen, Rune

2002-08-15

The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

Relevance Feedback in Content Based Image Retrieval: A Review

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Manesh B. Kokare

2011-01-01

Full Text Available This paper provides an overview of the technical achievements in the research area of relevance feedback (RF in content-based image retrieval (CBIR. Relevance feedback is a powerful technique in CBIR systems, in order to improve the performance of CBIR effectively. It is an open research area to the researcher to reduce the semantic gap between low-level features and high level concepts. The paper covers the current state of art of the research in relevance feedback in CBIR, various relevance feedback techniques and issues in relevance feedback are discussed in detail.

Modeling multiple visual words assignment for bag-of-features based medical image retrieval

KAUST Repository

Wang, Jim Jing-Yan

2012-01-01

In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments\\' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

Modeling multiple visual words assignment for bag-of-features based medical image retrieval

KAUST Repository

Wang, Jim Jing-Yan; Almasri, Islam

2012-01-01

In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

A Resource Based Framework for Planning and Replanning

NARCIS (Netherlands)

Van der Krogt, R.P.J.; De Weerdt, M.M.; Witteveen, C.

2003-01-01

We discuss a rigorous unifying framework for both planning and replanning, extending an existing logic-based approach to resource-based planning. The primitive concepts in this Action Resource Framework (ARF) are actions and resources. Actions consume and produce resources. Plans are structures

A framework for automatic information quality ranking of diabetes websites.

Science.gov (United States)

Belen Sağlam, Rahime; Taskaya Temizel, Tugba

2015-01-01

Objective: When searching for particular medical information on the internet the challenge lies in distinguishing the websites that are relevant to the topic, and contain accurate information. In this article, we propose a framework that automatically identifies and ranks diabetes websites according to their relevance and information quality based on the website content. Design: The proposed framework ranks diabetes websites according to their content quality, relevance and evidence based medicine. The framework combines information retrieval techniques with a lexical resource based on Sentiwordnet making it possible to work with biased and untrusted websites while, at the same time, ensuring the content relevance. Measurement: The evaluation measurements used were Pearson-correlation, true positives, false positives and accuracy. We tested the framework with a benchmark data set consisting of 55 websites with varying degrees of information quality problems. Results: The proposed framework gives good results that are comparable with the non-automated information quality measuring approaches in the literature. The correlation between the results of the proposed automated framework and ground-truth is 0.68 on an average with p < 0.001 which is greater than the other proposed automated methods in the literature (r score in average is 0.33).

Memory networks supporting retrieval effort and retrieval success under conditions of full and divided attention.

Science.gov (United States)

Skinner, Erin I; Fernandes, Myra A; Grady, Cheryl L

2009-01-01

We used a multivariate analysis technique, partial least squares (PLS), to identify distributed patterns of brain activity associated with retrieval effort and retrieval success. Participants performed a recognition memory task under full attention (FA) or two different divided attention (DA) conditions during retrieval. Behaviorally, recognition was disrupted when a word, but not digit-based distracting task, was performed concurrently with retrieval. PLS was used to identify patterns of brain activation that together covaried with the three memory conditions and which were functionally connected with activity in the right hippocampus to produce successful memory performance. Results indicate that activity in the right dorsolateral frontal cortex increases during conditions of DA at retrieval, and that successful memory performance in the DA-digit condition is associated with activation of the same network of brain regions functionally connected to the right hippocampus, as under FA, which increases with increasing memory performance. Finally, DA conditions that disrupt successful memory performance (DA-word) interfere with recruitment of both retrieval-effort and retrieval-success networks.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2004-12-01

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

A framework for designing hand hygiene educational interventions in schools.

Science.gov (United States)

Appiah-Brempong, Emmanuel; Harris, Muriel J; Newton, Samuel; Gulis, Gabriel

2018-03-01

Hygiene education appears to be the commonest school-based intervention for preventing infectious diseases, especially in the developing world. Nevertheless, there remains a gap in literature regarding a school-specific theory-based framework for designing a hand hygiene educational intervention in schools. We sought to suggest a framework underpinned by psychosocial theories towards bridging this knowledge gap. Furthermore, we sought to propound a more comprehensive definition of hand hygiene which could guide the conceptualisation of hand hygiene interventions in varied settings. Literature search was guided by a standardized tool and literature was retrieved on the basis of a predetermined inclusion criteria. Databases consulted include PubMed, ERIC, and EBSCO host (Medline, CINAHL, PsycINFO, etc.). Evidence bordering on a theoretical framework to aid the design of school-based hand hygiene educational interventions is summarized narratively. School-based hand hygiene educational interventions seeking to positively influence behavioural outcomes could consider enhancing psychosocial variables including behavioural capacity, attitudes and subjective norms (normative beliefs and motivation to comply). A framework underpinned by formalized psychosocial theories has relevance and could enhance the design of hand hygiene educational interventions, especially in schools.

From 2D Silhouettes to 3D Object Retrieval: Contributions and Benchmarking

Directory of Open Access Journals (Sweden)

Napoléon Thibault

2010-01-01

Full Text Available 3D retrieval has recently emerged as an important boost for 2D search techniques. This is mainly due to its several complementary aspects, for instance, enriching views in 2D image datasets, overcoming occlusion and serving in many real-world applications such as photography, art, archeology, and geolocalization. In this paper, we introduce a complete "2D photography to 3D object" retrieval framework. Given a (collection of picture(s or sketch(es of the same scene or object, the method allows us to retrieve the underlying similar objects in a database of 3D models. The contribution of our method includes (i a generative approach for alignment able to find canonical views consistently through scenes/objects and (ii the application of an efficient but effective matching method used for ranking. The results are reported through the Princeton Shape Benchmark and the Shrec benchmarking consortium evaluated/compared by a third party. In the two gallery sets, our framework achieves very encouraging performance and outperforms the other runs.

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

Science.gov (United States)

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…

Pareto-depth for multiple-query image retrieval.

Science.gov (United States)

Hsiao, Ko-Jen; Calder, Jeff; Hero, Alfred O

2015-02-01

Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts.

Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

Directory of Open Access Journals (Sweden)

Kompatsiaris Ioannis

2004-01-01

Full Text Available An image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions and endow the indexing and retrieval system with content-based functionalities. Low-level descriptors for the color, position, size, and shape of each region are subsequently extracted. These arithmetic descriptors are automatically associated with appropriate qualitative intermediate-level descriptors, which form a simple vocabulary termed object ontology. The object ontology is used to allow the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword and their relations in a human-centered fashion. When querying for a specific semantic object (or objects, the intermediate-level descriptor values associated with both the semantic object and all image regions in the collection are initially compared, resulting in the rejection of most image regions as irrelevant. Following that, a relevance feedback mechanism, based on support vector machines and using the low-level descriptors, is invoked to rank the remaining potentially relevant image regions and produce the final query results. Experimental results and comparisons demonstrate, in practice, the effectiveness of our approach.

On effectiveness of network sensor-based defense framework

Science.gov (United States)

Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh

2012-06-01

Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

Stochastic Optimized Relevance Feedback Particle Swarm Optimization for Content Based Image Retrieval

Directory of Open Access Journals (Sweden)

Muhammad Imran

2014-01-01

Full Text Available One of the major challenges for the CBIR is to bridge the gap between low level features and high level semantics according to the need of the user. To overcome this gap, relevance feedback (RF coupled with support vector machine (SVM has been applied successfully. However, when the feedback sample is small, the performance of the SVM based RF is often poor. To improve the performance of RF, this paper has proposed a new technique, namely, PSO-SVM-RF, which combines SVM based RF with particle swarm optimization (PSO. The aims of this proposed technique are to enhance the performance of SVM based RF and also to minimize the user interaction with the system by minimizing the RF number. The PSO-SVM-RF was tested on the coral photo gallery containing 10908 images. The results obtained from the experiments showed that the proposed PSO-SVM-RF achieved 100% accuracy in 8 feedback iterations for top 10 retrievals and 80% accuracy in 6 iterations for 100 top retrievals. This implies that with PSO-SVM-RF technique high accuracy rate is achieved at a small number of iterations.

OpenTox predictive toxicology framework: toxicological ontology and semantic media wiki-based OpenToxipedia.

Science.gov (United States)

Tcheremenskaia, Olga; Benigni, Romualdo; Nikolova, Ivelina; Jeliazkova, Nina; Escher, Sylvia E; Batke, Monika; Baier, Thomas; Poroikov, Vladimir; Lagunin, Alexey; Rautenberg, Micha; Hardy, Barry

2012-04-24

The OpenTox Framework, developed by the partners in the OpenTox project (http://www.opentox.org), aims at providing a unified access to toxicity data, predictive models and validation procedures. Interoperability of resources is achieved using a common information model, based on the OpenTox ontologies, describing predictive algorithms, models and toxicity data. As toxicological data may come from different, heterogeneous sources, a deployed ontology, unifying the terminology and the resources, is critical for the rational and reliable organization of the data, and its automatic processing. The following related ontologies have been developed for OpenTox: a) Toxicological ontology - listing the toxicological endpoints; b) Organs system and Effects ontology - addressing organs, targets/examinations and effects observed in in vivo studies; c) ToxML ontology - representing semi-automatic conversion of the ToxML schema; d) OpenTox ontology- representation of OpenTox framework components: chemical compounds, datasets, types of algorithms, models and validation web services; e) ToxLink-ToxCast assays ontology and f) OpenToxipedia community knowledge resource on toxicology terminology.OpenTox components are made available through standardized REST web services, where every compound, data set, and predictive method has a unique resolvable address (URI), used to retrieve its Resource Description Framework (RDF) representation, or to initiate the associated calculations and generate new RDF-based resources.The services support the integration of toxicity and chemical data from various sources, the generation and validation of computer models for toxic effects, seamless integration of new algorithms and scientifically sound validation routines and provide a flexible framework, which allows building arbitrary number of applications, tailored to solving different problems by end users (e.g. toxicologists). The OpenTox toxicological ontology projects may be accessed via the Open

Lure(d) into listening: The potential of cognition-based music information retrieval.

NARCIS (Netherlands)

Honing, H.

2010-01-01

This paper argues for the potential of cognition-based music retrieval by introducing the notion of a musical ‘hook’ as a key memorization, recall, and search mechanism. A hook is considered the most salient, memorable, and easy to recall moment of a musical phrase or song. Next to its role in

TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu

2016-06-25

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu; Qin, Lu; Cheng, Hong; Zhang, Xiangliang; Zhou, Xiaofang

2016-01-01

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

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

Science.gov (United States)

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.

Retrieval of spent fuel from the Lepse floating base in Russia

International Nuclear Information System (INIS)

Clement, G.; De la Bassetiere, H.; Watson, C.J.H.; Ruksha, V.V.

1998-01-01

The LEPSE is a service vessel in the fleet operated by the Murmansk Shipping Company located in the Murmansk harbour in the north west of Russia. The ship is currently used to store spent nuclear fuel from icebreakers. In 1967, fuel elements which had been damaged during an accident, were transferred and stored into the LEPSE vessel. The condition of the ship, the damaged spent fuel and other radioactive waste it contains is a matter of significant concern for both Russia and international community. The Murmansk Shipping Company could rot remove the damaged fuel with their existing equipment and technology. Consequently the European Commission, under Tacis program, funded a preliminary study for the benefit of the Murmansk Shipping Company to address the feasibility of safely retrieving the spent fuel from the LEPSE. The study demonstrates the feasibility of the safe retrieval of the damaged fuel. The approach is based upon retrieval of the fuel together with the storage channel inside which it is presently stored, and its enclosure in a tight and clean canister for subsequent transfer and transportation. Following this study an international committee was established to find ways and means to actually implement the project. The organisation of the project has been further detailed and agreements prepared in the frame of a complementary contract funded by EC and Norway. (author)

Spline based iterative phase retrieval algorithm for X-ray differential phase contrast radiography.

Science.gov (United States)

Nilchian, Masih; Wang, Zhentian; Thuering, Thomas; Unser, Michael; Stampanoni, Marco

2015-04-20

Differential phase contrast imaging using grating interferometer is a promising alternative to conventional X-ray radiographic methods. It provides the absorption, differential phase and scattering information of the underlying sample simultaneously. Phase retrieval from the differential phase signal is an essential problem for quantitative analysis in medical imaging. In this paper, we formalize the phase retrieval as a regularized inverse problem, and propose a novel discretization scheme for the derivative operator based on B-spline calculus. The inverse problem is then solved by a constrained regularized weighted-norm algorithm (CRWN) which adopts the properties of B-spline and ensures a fast implementation. The method is evaluated with a tomographic dataset and differential phase contrast mammography data. We demonstrate that the proposed method is able to produce phase image with enhanced and higher soft tissue contrast compared to conventional absorption-based approach, which can potentially provide useful information to mammographic investigations.

Generating Concise Rules for Human Motion Retrieval

Science.gov (United States)

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

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

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

Science.gov (United States)

Miernecki, Maciej; Wigneron, Jean-Pierre; Lopez-Baeza, Ernesto; Kerr, Yann; DeJeu, Richard; DeLannoy, Gabielle J. M.; Jackson, Tom J.; O'Neill, Peggy E.; Shwank, Mike; Moran, Roberto Fernandez;

Fit of screw-retained fixed implant frameworks fabricated by different methods: a systematic review.

Science.gov (United States)

Abduo, Jaafar; Lyons, Karl; Bennani, Vincent; Waddell, Neil; Swain, Michael

2011-01-01

The aim of this study was to review the published literature investigating the accuracy of fit of fixed implant frameworks fabricated using different materials and methods. A comprehensive electronic search was performed through PubMed (MEDLINE) using Boolean operators to combine key words. The search was limited to articles written in English and published through May 2010. In addition, a manual search through articles and reference lists retrieved from the electronic search and peer-reviewed journals was also conducted. A total of 248 articles were retrieved, and 26 met the specified inclusion criteria for the review. The selected articles assessed the fit of fixed implant frameworks fabricated by different techniques. The investigated fabrication approaches were one-piece casting, sectioning and reconnection, spark erosion with an electric discharge machine, computer-aided design/computer-assisted manufacturing (CAD/CAM), and framework bonding to prefabricated abutment cylinders. Cast noble metal frameworks have a predictable fit, and additional fit refinement treatment is not indicated in well-controlled conditions. Base metal castings do not provide a satisfactory level of fit unless additional refinement treatment is performed, such as sectioning and laser welding or spark erosion. Spark erosion, framework bonding to prefabricated abutment cylinders, and CAD/CAM have the potential to provide implant frameworks with an excellent fit; CAD/CAM is the most consistent and least technique-sensitive of these methods.

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

Science.gov (United States)

Zarifi, Davoud; Soleimani, Mohammad; Abdolali, Ali

2013-08-01

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

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

Science.gov (United States)

Dai, Guoxian; Xie, Jin; Fang, Yi

2018-07-01

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

Content-based retrieval in videos from laparoscopic surgery

Science.gov (United States)

Schoeffmann, Klaus; Beecks, Christian; Lux, Mathias; Uysal, Merih Seran; Seidl, Thomas

2016-03-01

In the field of medical endoscopy more and more surgeons are changing over to record and store videos of their endoscopic procedures for long-term archival. These endoscopic videos are a good source of information for explanations to patients and follow-up operations. As the endoscope is the "eye of the surgeon", the video shows the same information the surgeon has seen during the operation, and can describe the situation inside the patient much more precisely than an operation report would do. Recorded endoscopic videos can also be used for training young surgeons and in some countries the long-term archival of video recordings from endoscopic procedures is even enforced by law. A major challenge, however, is to efficiently access these very large video archives for later purposes. One problem, for example, is to locate specific images in the videos that show important situations, which are additionally captured as static images during the procedure. This work addresses this problem and focuses on contentbased video retrieval in data from laparoscopic surgery. We propose to use feature signatures, which can appropriately and concisely describe the content of laparoscopic images, and show that by using this content descriptor with an appropriate metric, we are able to efficiently perform content-based retrieval in laparoscopic videos. In a dataset with 600 captured static images from 33 hours recordings, we are able to find the correct video segment for more than 88% of these images.

Soil Moisture Retrieval Based on GPS Signal Strength Attenuation

Directory of Open Access Journals (Sweden)

Franziska Koch

2016-07-01

Full Text Available Soil moisture (SM is a highly relevant variable for agriculture, the emergence of floods and a key variable in the global energy and water cycle. In the last years, several satellite missions have been launched especially to derive large-scale products of the SM dynamics on the Earth. However, in situ validation data are often scarce. We developed a new method to retrieve SM of bare soil from measurements of low-cost GPS (Global Positioning System sensors that receive the freely available GPS L1-band signals. The experimental setup of three GPS sensors was installed at a bare soil field at the German Weather Service (DWD in Munich for almost 1.5 years. Two GPS antennas were installed within the soil column at a depth of 10 cm and one above the soil. SM was successfully retrieved based on GPS signal strength losses through the integral soil volume. The results show high agreement with measured and modelled SM validation data. Due to its non-destructive, cheap and low power setup, GPS sensor networks could also be used for potential applications in remote areas, aiming to serve as satellite validation data and to support the fields of agriculture, water supply, flood forecasting and climate change.

Robustness of phase retrieval methods in x-ray phase contrast imaging: A comparison

International Nuclear Information System (INIS)

Yan, Aimin; Wu, Xizeng; Liu, Hong

2011-01-01

Purpose: The robustness of the phase retrieval methods is of critical importance for limiting and reducing radiation doses involved in x-ray phase contrast imaging. This work is to compare the robustness of two phase retrieval methods by analyzing the phase maps retrieved from the experimental images of a phantom. Methods: Two phase retrieval methods were compared. One method is based on the transport of intensity equation (TIE) for phase contrast projections, and the TIE-based method is the most commonly used method for phase retrieval in the literature. The other is the recently developed attenuation-partition based (AP-based) phase retrieval method. The authors applied these two methods to experimental projection images of an air-bubble wrap phantom for retrieving the phase map of the bubble wrap. The retrieved phase maps obtained by using the two methods are compared. Results: In the wrap's phase map retrieved by using the TIE-based method, no bubble is recognizable, hence, this method failed completely for phase retrieval from these bubble wrap images. Even with the help of the Tikhonov regularization, the bubbles are still hardly visible and buried in the cluttered background in the retrieved phase map. The retrieved phase values with this method are grossly erroneous. In contrast, in the wrap's phase map retrieved by using the AP-based method, the bubbles are clearly recovered. The retrieved phase values with the AP-based method are reasonably close to the estimate based on the thickness-based measurement. The authors traced these stark performance differences of the two methods to their different techniques employed to deal with the singularity problem involved in the phase retrievals. Conclusions: This comparison shows that the conventional TIE-based phase retrieval method, regardless if Tikhonov regularization is used or not, is unstable against the noise in the wrap's projection images, while the AP-based phase retrieval method is shown in these

New framework of NGN web-based management system

Science.gov (United States)

Nian, Zhou; Jie, Yin; Qian, Mao

2007-11-01

This paper introduces the basic conceptions and key technology of the Ajax and some popular frameworks in the J2EE architecture, try to integrate all the frameworks into a new framework. The developers can develop web applications much more convenient by using this framework and the web application can provide a more friendly and interactive platform to the end users. At last an example is given to explain how to use the new framework to build a web-based management system of the softswitch network.

Guenter Tulip Filter Retrieval Experience: Predictors of Successful Retrieval

International Nuclear Information System (INIS)

Turba, Ulku Cenk; Arslan, Bulent; Meuse, Michael; Sabri, Saher; Macik, Barbara Gail; Hagspiel, Klaus D.; Matsumoto, Alan H.; Angle, John F.

2010-01-01

We report our experience with Guenter Tulip filter placement indications, retrievals, and procedural problems, with emphasis on alternative retrieval techniques. We have identified 92 consecutive patients in whom a Guenter Tulip filter was placed and filter removal attempted. We recorded patient demographic information, filter placement and retrieval indications, procedures, standard and nonstandard filter retrieval techniques, complications, and clinical outcomes. The mean time to retrieval for those who experienced filter strut penetration was statistically significant [F(1,90) = 8.55, p = 0.004]. Filter strut(s) IVC penetration and successful retrieval were found to be statistically significant (p = 0.043). The filter hook-IVC relationship correlated with successful retrieval. A modified guidewire loop technique was applied in 8 of 10 cases where the hook appeared to penetrate the IVC wall and could not be engaged with a loop snare catheter, providing additional technical success in 6 of 8 (75%). Therefore, the total filter retrieval success increased from 88 to 95%. In conclusion, the Guenter Tulip filter has high successful retrieval rates with low rates of complication. Additional maneuvers such as a guidewire loop method can be used to improve retrieval success rates when the filter hook is endothelialized.

Recent advances in intelligent image search and video retrieval

CERN Document Server

2017-01-01

This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring. Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant conte...

A DSM-based framework for integrated function modelling

DEFF Research Database (Denmark)

Eisenbart, Boris; Gericke, Kilian; Blessing, Lucienne T. M.

2017-01-01

an integrated function modelling framework, which specifically aims at relating between the different function modelling perspectives prominently addressed in different disciplines. It uses interlinked matrices based on the concept of DSM and MDM in order to facilitate cross-disciplinary modelling and analysis...... of the functionality of a system. The article further presents the application of the framework based on a product example. Finally, an empirical study in industry is presented. Therein, feedback on the potential of the proposed framework to support interdisciplinary design practice as well as on areas of further...

Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code

Science.gov (United States)

Román, R.; Benavent-Oltra, J. A.; Casquero-Vera, J. A.; Lopatin, A.; Cazorla, A.; Lyamani, H.; Denjean, C.; Fuertes, D.; Pérez-Ramírez, D.; Torres, B.; Toledano, C.; Dubovik, O.; Cachorro, V. E.; de Frutos, A. M.; Olmo, F. J.; Alados-Arboledas, L.

2018-05-01

In this paper we present an approach for the profiling of aerosol microphysical and optical properties combining ceilometer and sun/sky photometer measurements in the GRASP code (General Retrieval of Aerosol and Surface Properties). For this objective, GRASP is used with sun/sky photometer measurements of aerosol optical depth (AOD) and sky radiances, both at four wavelengths and obtained from AErosol RObotic NETwork (AERONET), and ceilometer measurements of range corrected signal (RCS) at 1064 nm. A sensitivity study with synthetic data evidences the capability of the method to retrieve aerosol properties such as size distribution and profiles of volume concentration (VC), especially for coarse particles. Aerosol properties obtained by the mentioned method are compared with airborne in-situ measurements acquired during two flights over Granada (Spain) within the framework of ChArMEx/ADRIMED (Chemistry-Aerosol Mediterranean Experiment/Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) 2013 campaign. The retrieved aerosol VC profiles agree well with the airborne measurements, showing a mean bias error (MBE) and a mean absolute bias error (MABE) of 0.3 μm3/cm3 (12%) and 5.8 μm3/cm3 (25%), respectively. The differences between retrieved VC and airborne in-situ measurements are within the uncertainty of GRASP retrievals. In addition, the retrieved VC at 2500 m a.s.l. is shown and compared with in-situ measurements obtained during summer 2016 at a high-atitude mountain station in the framework of the SLOPE I campaign (Sierra Nevada Lidar AerOsol Profiling Experiment). VC from GRASP presents high correlation (r = 0.91) with the in-situ measurements, but overestimates them, MBE and MABE being equal to 23% and 43%.

Photopolarimetric Retrievals of Snow Properties

Science.gov (United States)

Ottaviani, M.; van Diedenhoven, B.; Cairns, B.

2015-01-01

Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

EM-21 Retrieval Knowledge Center: Waste Retrieval Challenges

Energy Technology Data Exchange (ETDEWEB)

Fellinger, Andrew P.; Rinker, Michael W.; Berglin, Eric J.; Minichan, Richard L.; Poirier, Micheal R.; Gauglitz, Phillip A.; Martin, Bruce A.; Hatchell, Brian K.; Saldivar, Eloy; Mullen, O Dennis; Chapman, Noel F.; Wells, Beric E.; Gibbons, Peter W.

2009-04-10

EM-21 is the Waste Processing Division of the Office of Engineering and Technology, within the U.S. Department of Energy’s (DOE) Office of Environmental Management (EM). In August of 2008, EM-21 began an initiative to develop a Retrieval Knowledge Center (RKC) to provide the DOE, high level waste retrieval operators, and technology developers with centralized and focused location to share knowledge and expertise that will be used to address retrieval challenges across the DOE complex. The RKC is also designed to facilitate information sharing across the DOE Waste Site Complex through workshops, and a searchable database of waste retrieval technology information. The database may be used to research effective technology approaches for specific retrieval tasks and to take advantage of the lessons learned from previous operations. It is also expected to be effective for remaining current with state-of-the-art of retrieval technologies and ongoing development within the DOE Complex. To encourage collaboration of DOE sites with waste retrieval issues, the RKC team is co-led by the Savannah River National Laboratory (SRNL) and the Pacific Northwest National Laboratory (PNNL). Two RKC workshops were held in the Fall of 2008. The purpose of these workshops was to define top level waste retrieval functional areas, exchange lessons learned, and develop a path forward to support a strategic business plan focused on technology needs for retrieval. The primary participants involved in these workshops included retrieval personnel and laboratory staff that are associated with Hanford and Savannah River Sites since the majority of remaining DOE waste tanks are located at these sites. This report summarizes and documents the results of the initial RKC workshops. Technology challenges identified from these workshops and presented here are expected to be a key component to defining future RKC-directed tasks designed to facilitate tank waste retrieval solutions.

EM-21 Retrieval Knowledge Center: Waste Retrieval Challenges

International Nuclear Information System (INIS)

Fellinger, Andrew P.; Rinker, Michael W.; Berglin, Eric J.; Minichan, Richard L.; Poirier, Micheal R.; Gauglitz, Phillip A.; Martin, Bruce A.; Hatchell, Brian K.; Saldivar, Eloy; Mullen, O Dennis; Chapman, Noel F.; Wells, Beric E.; Gibbons, Peter W.

2009-01-01

EM-21 is the Waste Processing Division of the Office of Engineering and Technology, within the U.S. Department of Energy's (DOE) Office of Environmental Management (EM). In August of 2008, EM-21 began an initiative to develop a Retrieval Knowledge Center (RKC) to provide the DOE, high level waste retrieval operators, and technology developers with centralized and focused location to share knowledge and expertise that will be used to address retrieval challenges across the DOE complex. The RKC is also designed to facilitate information sharing across the DOE Waste Site Complex through workshops, and a searchable database of waste retrieval technology information. The database may be used to research effective technology approaches for specific retrieval tasks and to take advantage of the lessons learned from previous operations. It is also expected to be effective for remaining current with state-of-the-art of retrieval technologies and ongoing development within the DOE Complex. To encourage collaboration of DOE sites with waste retrieval issues, the RKC team is co-led by the Savannah River National Laboratory (SRNL) and the Pacific Northwest National Laboratory (PNNL). Two RKC workshops were held in the Fall of 2008. The purpose of these workshops was to define top level waste retrieval functional areas, exchange lessons learned, and develop a path forward to support a strategic business plan focused on technology needs for retrieval. The primary participants involved in these workshops included retrieval personnel and laboratory staff that are associated with Hanford and Savannah River Sites since the majority of remaining DOE waste tanks are located at these sites. This report summarizes and documents the results of the initial RKC workshops. Technology challenges identified from these workshops and presented here are expected to be a key component to defining future RKC-directed tasks designed to facilitate tank waste retrieval solutions

SIFT Meets CNN: A Decade Survey of Instance Retrieval.

Science.gov (United States)

Zheng, Liang; Yang, Yi; Tian, Qi

2018-05-01

In the early days, content-based image retrieval (CBIR) was studied with global features. Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively studied for over a decade due to the advantage of SIFT in dealing with image transformations. Recently, image representations based on the convolutional neural network (CNN) have attracted increasing interest in the community and demonstrated impressive performance. Given this time of rapid evolution, this article provides a comprehensive survey of instance retrieval over the last decade. Two broad categories, SIFT-based and CNN-based methods, are presented. For the former, according to the codebook size, we organize the literature into using large/medium-sized/small codebooks. For the latter, we discuss three lines of methods, i.e., using pre-trained or fine-tuned CNN models, and hybrid methods. The first two perform a single-pass of an image to the network, while the last category employs a patch-based feature extraction scheme. This survey presents milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods. After analyzing and comparing retrieval performance of different categories on several datasets, we discuss promising directions towards generic and specialized instance retrieval.

Structure retrieval in HREM

International Nuclear Information System (INIS)

Gribelyuk, M.A.

1991-01-01

A new iteration method for direct structure retrieval starting from the exit plane-wave function Ψ e (r) is proposed and tested on models. The imaginary part of the potential cannot be retrieved. The effects of the limited resolution of Ψ e (r) as well as neglect of high-order Laue-zone effects and the choice of the starting potential on the result are discussed. The procedure is found to be preferable to that based on the subsequent approximation method with respect to a higher convergence rate. It is shown that an error as low as 10% may be obtained for the real part of the retrieved potential up to vertical strokeσV(r)tvertical stroke<5. (orig.)

Framework for Railway Phase-based Planning

DEFF Research Database (Denmark)

Li, Rui; Landex, Alex; Nielsen, Otto Anker

spending) to evaluate the project alternatives. The comparison result can identify the most cost-efficient solution in a long run and therefore reduce the overall costs. This article defines a phase-based framework to guide the railway maintenance and renewal project planning at strategic level....... The framework evaluates the project options from a larger LCC scope: The costs from train operation companies and passengers, together with the maintenance and renewal costs from Infrastructure Managers are included in the calculation. The framework simplifies the planning processes and the LCC calculation...... and compared. A case study is introduced in the article to demonstrate how the framework works to compare timber sleepers and concrete sleepers from strategic planning level. Two Life Cycle Cost oriented policies are discussed to illustrate: high quality track is necessity to improve the cost efficiency...

A stochastic cloud model for cloud and ozone retrievals from UV measurements

International Nuclear Information System (INIS)

Efremenko, Dmitry S.; Schüssler, Olena; Doicu, Adrian; Loyola, Diego

2016-01-01

The new generation of satellite instruments provides measurements in and around the Oxygen A-band on a global basis and with a relatively high spatial resolution. These data are commonly used for the determination of cloud properties. A stochastic model and radiative transfer model, previously developed by the authors, is used as the forward model component in retrievals of cloud parameters and ozone total and partial columns. The cloud retrieval algorithm combines local and global optimization routines, and yields a retrieval accuracy of about 1% and a fast computational time. Retrieved parameters are the cloud optical thickness and the cloud-top height. It was found that the use of the independent pixel approximation instead of the stochastic cloud model leads to large errors in the retrieved cloud parameters, as well as, in the retrieved ozone height resolved partial columns. The latter can be reduced by using the stochastic cloud model to compute the optimal value of the regularization parameter in the framework of Tikhonov regularization. - Highlights: • A stochastic radiative transfer model for retrieving clouds/ozone is designed. • Errors of independent pixel approximation (IPA) for O3 total column are small. • The error of IPA for ozone profile retrieval may become large. • The use of stochastic model reduces the error of ozone profile retrieval.

Encoding and Retrieval Interference in Sentence Comprehension: Evidence from Agreement

Directory of Open Access Journals (Sweden)

Sandra Villata

2018-01-01

Full Text Available Long-distance verb-argument dependencies generally require the integration of a fronted argument when the verb is encountered for sentence interpretation. Under a parsing model that handles long-distance dependencies through a cue-based retrieval mechanism, retrieval is hampered when retrieval cues also resonate with non-target elements (retrieval interference. However, similarity-based interference may also stem from interference arising during the encoding of elements in memory (encoding interference, an effect that is not directly accountable for by a cue-based retrieval mechanism. Although encoding and retrieval interference are clearly distinct at the theoretical level, it is difficult to disentangle the two on empirical grounds, since encoding interference may also manifest at the retrieval region. We report two self-paced reading experiments aimed at teasing apart the role of each component in gender and number subject-verb agreement in Italian and English object relative clauses. In Italian, the verb does not agree in gender with the subject, thus providing no cue for retrieval. In English, although present tense verbs agree in number with the subject, past tense verbs do not, allowing us to test the role of number as a retrieval cue within the same language. Results from both experiments converge, showing similarity-based interference at encoding, and some evidence for an effect at retrieval. After having pointed out the non-negligible role of encoding in sentence comprehension, and noting that Lewis and Vasishth’s (2005 ACT-R model of sentence processing, the most fully developed cue-based retrieval approach to sentence processing does not predict encoding effects, we propose an augmentation of this model that predicts these effects. We then also propose a self-organizing sentence processing model (SOSP, which has the advantage of accounting for retrieval and encoding interference with a single mechanism.

Encoding and Retrieval Interference in Sentence Comprehension: Evidence from Agreement

Science.gov (United States)

Villata, Sandra; Tabor, Whitney; Franck, Julie

2018-01-01

Long-distance verb-argument dependencies generally require the integration of a fronted argument when the verb is encountered for sentence interpretation. Under a parsing model that handles long-distance dependencies through a cue-based retrieval mechanism, retrieval is hampered when retrieval cues also resonate with non-target elements (retrieval interference). However, similarity-based interference may also stem from interference arising during the encoding of elements in memory (encoding interference), an effect that is not directly accountable for by a cue-based retrieval mechanism. Although encoding and retrieval interference are clearly distinct at the theoretical level, it is difficult to disentangle the two on empirical grounds, since encoding interference may also manifest at the retrieval region. We report two self-paced reading experiments aimed at teasing apart the role of each component in gender and number subject-verb agreement in Italian and English object relative clauses. In Italian, the verb does not agree in gender with the subject, thus providing no cue for retrieval. In English, although present tense verbs agree in number with the subject, past tense verbs do not, allowing us to test the role of number as a retrieval cue within the same language. Results from both experiments converge, showing similarity-based interference at encoding, and some evidence for an effect at retrieval. After having pointed out the non-negligible role of encoding in sentence comprehension, and noting that Lewis and Vasishth’s (2005) ACT-R model of sentence processing, the most fully developed cue-based retrieval approach to sentence processing does not predict encoding effects, we propose an augmentation of this model that predicts these effects. We then also propose a self-organizing sentence processing model (SOSP), which has the advantage of accounting for retrieval and encoding interference with a single mechanism. PMID:29403414

A novel architecture for information retrieval system based on semantic web

Science.gov (United States)

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.

Exploiting CReP for Knowledge Retrieval and Use in Complex Domains

Science.gov (United States)

Manenti, Lorenza; Sartori, Fabio

Case Based Reasoning (CBR) is a Knowledge Management approach that consists in the development of decision support systems where problem are solved by analogy with similar problem solved in the past. In this way, the system supports users in finding solutions without starting from scratch. CBR has become a very important research topic in Artificial Intelligence, with the definition of methodologies and architectural patterns for supporting developers in the design and implementation of case-based systems. The paper presents one of this frameworks, namely CReP, an on-going research project of the Artificial Intelligence Laboratory (L.Int.Ar.) of University of Milan-Bicocca, focusing on the integration between CBR paradigm and metadata approach to obtain domain-independent case structure and retrieval algorithm definition.

Ethics issues in retrievability

International Nuclear Information System (INIS)

Jensen, M.; Larsson, C.M.; Norden, M.

2000-01-01

We can isolate some issues, which should not be unresolved for a longer period of time. Disputes over well-defined waste management options fall in this category. The concept of retrievability has a possibility to invoke a series of questions in the minds of both specialists and non-specialists. It is intrinsically vague, in that it may refer to different phases in the repository's life, and to both open and closed repositories in the long time frame. Requirements for retrievability opens a series of issues, including open-ended philosophical question, which may give the impressions that things are not properly taken care of, since the experts differ in opinion. If such disputes cannot be resolved by consulting the existing legal framework, efforts should be made to put them to trial in the proper forum, i.e. parliament and national or local government or authorities, depending on the problem. In contrast, the value of institutional controls can easily be seen as an ethical value, whether included in the regulation of not. It has the potential to deter human intrusion and to allow remedial action by carrying information about a repository. (author)

A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

Directory of Open Access Journals (Sweden)

Hossien Pourghassem

2011-04-01

Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

Constraining lidar stand-alone retrievals with lunar photometry measurements

Science.gov (United States)

Ortiz-Amezcua, Pablo; Luis Guerrero-Rascado, Juan; Antonio Benavent-Oltra, Jose; Román, Roberto; Böckmann, Christine; Alados-Arboledas, Lucas

2018-04-01

This study combines atmospheric optical information measured with lidar and nocturnal photometers in order to find configurations that allow for the retrieval of particle microphysical properties without "3+2" lidar setups. It has been carried out using data measured at the EARLINET Granada station during the experimental campaign SLOPE in the framework of ACTRIS-2 project.

Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

Science.gov (United States)

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-10-23

A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

Self-Referential Information Alleviates Retrieval Inhibition of Directed Forgetting Effects—An ERP Evidence of Source Memory

Directory of Open Access Journals (Sweden)

Xinrui Mao

2017-10-01

Full Text Available Directed forgetting (DF assists in preventing outdated information from interfering with cognitive processing. Previous studies pointed that self-referential items alleviated DF effects due to the elaboration of encoding processes. However, the retrieval mechanism of this phenomenon remains unknown. Based on the dual-process framework of recognition, the retrieval of self-referential information was involved in familiarity and recollection. Using source memory tasks combined with event-related potential (ERP recording, our research investigated the retrieval processes of alleviative DF effects elicited by self-referential information. The FN400 (frontal negativity at 400 ms is a frontal potential at 300–500 ms related to familiarity and the late positive complex (LPC is a later parietal potential at 500–800 ms related to recollection. The FN400 effects of source memory suggested that familiarity processes were promoted by self-referential effects without the modulation of to-be-forgotten (TBF instruction. The ERP results of DF effects were involved with LPCs of source memory, which indexed retrieval processing of recollection. The other-referential source memory of TBF instruction caused the absence of LPC effects, while the self-referential source memory of TBF instruction still elicited the significant LPC effects. Therefore, our neural findings suggested that self-referential processing improved both familiarity and recollection. Furthermore, the self-referential processing advantage which was caused by the autobiographical retrieval alleviated retrieval inhibition of DF, supporting that the self-referential source memory alleviated DF effects.

Associative conceptual space-based information retrieval systems

NARCIS (Netherlands)

M.J. Schuemie (Martijn); J.H. van den Berg (Jan)

1998-01-01

textabstractIn this `Information Era' with the availability of large collections of books, articles, journals, CD-ROMs, video films and so on, there exists an increasing need for intelligent information retrieval systems that enable users to find the information desired easily. Many attempts have

Rotation Invariant Color Retrieval

OpenAIRE

Swapna Borde; Udhav Bhosle

2013-01-01

The new technique for image retrieval using the color features extracted from images based on LogHistogram is proposed. The proposed technique is compared with Global color histogram and histogram ofcorners .It has been observed that number of histogram bins used for retrieval comparison of proposedtechnique (Log Histogram)is less as compared to Global Color Histogram and Histogram of corners. Theexperimental results on a database of 792 images with 11 classes indicate that proposed method (L...

Intelligent Information Retrieval: Diagnosing Information Need. Part I. The Theoretical Framework for Developing an Intelligent IR Tool.

Science.gov (United States)

Cole, Charles

1998-01-01

Suggests that the principles underlying the procedure used by doctors to diagnose a patient's disease are useful in the design of intelligent information-retrieval systems because the task of the doctor is conceptually similar to the computer or human intermediary's task in information retrieval: to draw out the user's query/information need.…

Using Framework Analysis in nursing research: a worked example.

Science.gov (United States)

Ward, Deborah J; Furber, Christine; Tierney, Stephanie; Swallow, Veronica

2013-11-01

To demonstrate Framework Analysis using a worked example and to illustrate how criticisms of qualitative data analysis including issues of clarity and transparency can be addressed. Critics of the analysis of qualitative data sometimes cite lack of clarity and transparency about analytical procedures; this can deter nurse researchers from undertaking qualitative studies. Framework Analysis is flexible, systematic, and rigorous, offering clarity, transparency, an audit trail, an option for theme-based and case-based analysis and for readily retrievable data. This paper offers further explanation of the process undertaken which is illustrated with a worked example. Data were collected from 31 nursing students in 2009 using semi-structured interviews. The data collected are not reported directly here but used as a worked example for the five steps of Framework Analysis. Suggestions are provided to guide researchers through essential steps in undertaking Framework Analysis. The benefits and limitations of Framework Analysis are discussed. Nurses increasingly use qualitative research methods and need to use an analysis approach that offers transparency and rigour which Framework Analysis can provide. Nurse researchers may find the detailed critique of Framework Analysis presented in this paper a useful resource when designing and conducting qualitative studies. Qualitative data analysis presents challenges in relation to the volume and complexity of data obtained and the need to present an 'audit trail' for those using the research findings. Framework Analysis is an appropriate, rigorous and systematic method for undertaking qualitative analysis. © 2013 Blackwell Publishing Ltd.

Retrievable Inferior Vena Cava Filters: Factors that Affect Retrieval Success

Energy Technology Data Exchange (ETDEWEB)

Geisbuesch, Philipp, E-mail: philippgeisbuesch@gmx.de; Benenati, James F.; Pena, Constantino S.; Couvillon, Joseph; Powell, Alex; Gandhi, Ripal; Samuels, Shaun; Uthoff, Heiko [Baptist Cardiac and Vascular Institute, Division of Vascular and Interventional Radiology (United States)

2012-10-15

Purpose: To report and analyze the indications, procedural success, and complications of retrievable inferior vena cava filters (rIVCF) placement and to identify parameters that influence retrieval attempt and failure. Methods: Between January 2005 and December 2010, a total of 200 patients (80 men, median age 67 years, range 11-95 years) received a rIVCF with the clinical possibility that it could be removed. All patients with rIVCF were prospectively entered into a database and followed until retrieval or a decision not to retrieve the filter was made. A retrospective analysis of this database was performed. Results: Sixty-one percent of patients had an accepted indication for filter placement; 39% of patients had a relative indication. There was a tendency toward a higher retrieval rate in patients with relative indications (40% vs. 55%, P = 0.076). Filter placement was technically successful in all patients, with no procedure-related mortality. The retrieval rate was 53%. Patient age of >80 years (odds ratio [OR] 0.056, P > 0.0001) and presence of malignancy (OR 0.303, P = 0.003) was associated with a significantly reduced probability for attempted retrieval. Retrieval failure occurred in 7% (6 of 91) of all retrieval attempts. A time interval of > 90 days between implantation and attempted retrieval was associated with retrieval failure (OR 19.8, P = 0.009). Conclusions: Patient age >80 years and a history of malignancy are predictors of a reduced probability for retrieval attempt. The rate of retrieval failure is low and seems to be associated with a time interval of >90 days between filter placement and retrieval.

Retrievable Inferior Vena Cava Filters: Factors that Affect Retrieval Success

International Nuclear Information System (INIS)

Geisbüsch, Philipp; Benenati, James F.; Peña, Constantino S.; Couvillon, Joseph; Powell, Alex; Gandhi, Ripal; Samuels, Shaun; Uthoff, Heiko

2012-01-01

Purpose: To report and analyze the indications, procedural success, and complications of retrievable inferior vena cava filters (rIVCF) placement and to identify parameters that influence retrieval attempt and failure. Methods: Between January 2005 and December 2010, a total of 200 patients (80 men, median age 67 years, range 11–95 years) received a rIVCF with the clinical possibility that it could be removed. All patients with rIVCF were prospectively entered into a database and followed until retrieval or a decision not to retrieve the filter was made. A retrospective analysis of this database was performed. Results: Sixty-one percent of patients had an accepted indication for filter placement; 39% of patients had a relative indication. There was a tendency toward a higher retrieval rate in patients with relative indications (40% vs. 55%, P = 0.076). Filter placement was technically successful in all patients, with no procedure-related mortality. The retrieval rate was 53%. Patient age of >80 years (odds ratio [OR] 0.056, P > 0.0001) and presence of malignancy (OR 0.303, P = 0.003) was associated with a significantly reduced probability for attempted retrieval. Retrieval failure occurred in 7% (6 of 91) of all retrieval attempts. A time interval of > 90 days between implantation and attempted retrieval was associated with retrieval failure (OR 19.8, P = 0.009). Conclusions: Patient age >80 years and a history of malignancy are predictors of a reduced probability for retrieval attempt. The rate of retrieval failure is low and seems to be associated with a time interval of >90 days between filter placement and retrieval.

A review of content-based image retrieval systems in medical applications-clinical benefits and future directions.

Science.gov (United States)

Müller, Henning; Michoux, Nicolas; Bandon, David; Geissbuhler, Antoine

2004-02-01

Content-based visual information retrieval (CBVIR) or content-based image retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. The availability of large and steadily growing amounts of visual and multimedia data, and the development of the Internet underline the need to create thematic access methods that offer more than simple text-based queries or requests based on matching exact database fields. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of differing sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever-increasing quantities and used for diagnostics and therapy. The Radiology Department of the University Hospital of Geneva alone produced more than 12,000 images a day in 2002. The cardiology is currently the second largest producer of digital images, especially with videos of cardiac catheterization ( approximately 1800 exams per year containing almost 2000 images each). The total amount of cardiologic image data produced in the Geneva University Hospital was around 1 TB in 2002. Endoscopic videos can equally produce enormous amounts of data. With digital imaging and communications in medicine (DICOM), a standard for image communication has been set and patient information can be stored with the actual image(s), although still a few problems prevail with respect to the standardization. In several articles, content-based access to medical images for supporting clinical decision-making has been proposed that would ease the management of clinical data and scenarios for the integration of

A Bayesian Retrieval of Greenland Ice Sheet Internal Temperature from Ultra-wideband Software-defined Microwave Radiometer (UWBRAD) Measurements

Science.gov (United States)

Duan, Y.; Durand, M. T.; Jezek, K. C.; Yardim, C.; Bringer, A.; Aksoy, M.; Johnson, J. T.

2017-12-01

The ultra-wideband software-defined microwave radiometer (UWBRAD) is designed to provide ice sheet internal temperature product via measuring low frequency microwave emission. Twelve channels ranging from 0.5 to 2.0 GHz are covered by the instrument. A Greenland air-borne demonstration was demonstrated in September 2016, provided first demonstration of Ultra-wideband radiometer observations of geophysical scenes, including ice sheets. Another flight is planned for September 2017 for acquiring measurements in central ice sheet. A Bayesian framework is designed to retrieve the ice sheet internal temperature from simulated UWBRAD brightness temperature (Tb) measurements over Greenland flight path with limited prior information of the ground. A 1-D heat-flow model, the Robin Model, was used to model the ice sheet internal temperature profile with ground information. Synthetic UWBRAD Tb observations was generated via the partially coherent radiation transfer model, which utilizes the Robin model temperature profile and an exponential fit of ice density from Borehole measurement as input, and corrupted with noise. The effective surface temperature, geothermal heat flux, the variance of upper layer ice density, and the variance of fine scale density variation at deeper ice sheet were treated as unknown variables within the retrieval framework. Each parameter is defined with its possible range and set to be uniformly distributed. The Markov Chain Monte Carlo (MCMC) approach is applied to make the unknown parameters randomly walk in the parameter space. We investigate whether the variables can be improved over priors using the MCMC approach and contribute to the temperature retrieval theoretically. UWBRAD measurements near camp century from 2016 was also treated with the MCMC to examine the framework with scattering effect. The fine scale density fluctuation is an important parameter. It is the most sensitive yet highly unknown parameter in the estimation framework

System engineering approach to GPM retrieval algorithms

Energy Technology Data Exchange (ETDEWEB)

Rose, C. R. (Chris 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. Ground 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

Functional-anatomic study of episodic retrieval using fMRI. I. Retrieval effort versus retrieval success.

Science.gov (United States)

Buckner, R L; Koutstaal, W; Schacter, D L; Wagner, A D; Rosen, B R

1998-04-01

A number of recent functional imaging studies have identified brain areas activated during tasks involving episodic memory retrieval. The identification of such areas provides a foundation for targeted hypotheses regarding the more specific contributions that these areas make to episodic retrieval. As a beginning effort toward such an endeavor, whole-brain functional magnetic resonance imaging (fMRI) was used to examine 14 subjects during episodic word recognition in a block-designed fMRI experiment. Study conditions were manipulated by presenting either shallow or deep encoding tasks. This manipulation yielded two recognition conditions that differed with regard to retrieval effort and retrieval success: shallow encoding yielded low levels of recognition success with high levels of retrieval effort, and deep encoding yielded high levels of recognition success with low levels of effort. Many brain areas were activated in common by these two recognition conditions compared to a low-level fixation condition, including left and right prefrontal regions often detected during PET episodic retrieval paradigms (e.g., R. L. Buckner et al., 1996, J. Neurosci. 16, 6219-6235) thereby generalizing these findings to fMRI. Characterization of the activated regions in relation to the separate recognition conditions showed (1) bilateral anterior insular regions and a left dorsal prefrontal region were more active after shallow encoding, when retrieval demanded greatest effort, and (2) right anterior prefrontal cortex, which has been implicated in episodic retrieval, was most active during successful retrieval after deep encoding. We discuss these findings in relation to component processes involved in episodic retrieval and in the context of a companion study using event-related fMRI.

Enhancements to knowledge discovery framework of SOPHIA textual case-based reasoning

Directory of Open Access Journals (Sweden)

Islam Elhalwany

2014-11-01

This paper contributes to propose enhancements to SOPHIA approach that aims to enhance the retrieval efficiency and increase the precision degree. It also aimed to grantee that all results will have the same subject of the user query. The enhancements include performing an automatic classification to the case-base before the clustering step in the indexing stage, and include performing an automatic classification to the user query before the retrieval stage. Moreover, proofing that SOPHIA approach is a domain and language independent by applying it in the domain of Islamic jurisprudence in Arabic language.

A Framework for Enterprise Operating Systems Based on Zachman Framework

Science.gov (United States)

Ostadzadeh, S. Shervin; Rahmani, Amir Masoud

Nowadays, the Operating System (OS) isn't only the software that runs your computer. In the typical information-driven organization, the operating system is part of a much larger platform for applications and data that extends across the LAN, WAN and Internet. An OS cannot be an island unto itself; it must work with the rest of the enterprise. Enterprise wide applications require an Enterprise Operating System (EOS). Enterprise operating systems used in an enterprise have brought about an inevitable tendency to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of enterprise operating systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman Framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have prominent roles in enterprise-wide system development. In this paper, we propose a framework based on ZF for enterprise operating systems. The presented framework helps developers to design and justify completely integrated business, IT systems, and operating systems which results in improved project success rate.

Emergent web intelligence advanced information retrieval

CERN Document Server

Badr, Youakim; Abraham, Ajith; Hassanien, Aboul-Ella

2010-01-01

Web Intelligence explores the impact of artificial intelligence and advanced information technologies representing the next generation of Web-based systems, services, and environments, and designing hybrid web systems that serve wired and wireless users more efficiently. Multimedia and XML-based data are produced regularly and in increasing way in our daily digital activities, and their retrieval must be explored and studied in this emergent web-based era. 'Emergent Web Intelligence: Advanced information retrieval, provides reviews of the related cutting-edge technologies and insights. It is v

Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

Science.gov (United States)

Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

2017-08-01

The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest

The development of soliton physics: an analysis based on information retrieval

International Nuclear Information System (INIS)

Ichikawa, Y.H.; Ohe, Takeru; Kanada, Yasumasa.

1978-01-01

This paper uses information retrieval from available data bases such as INSPEC tapes in an attempt to quantify and demonstrate trends in the recent development of Soliton physics research. The date shows that Soliton physics research may be classified into three stages according to the annual numbers of published scientific papers (N): Stage 1: N - 10 0 Gestation (up to 1965) Stage 2: N - 10 1 Introduction (1966 - 1971) Stage 3: N - 10 2 Growth (1971 - present) (author)

A framework for AI-based nuclear design support system

International Nuclear Information System (INIS)

Furuta, Kazuo; Kondo, Shunsuke

1991-01-01

Nowadays many computer programs are being developed and used for the analytic tasks in nuclear reactor design, but experienced designers are still responsible for most of the synthetic tasks which are not amenable to algorithmic computer processes. Artificial intelligence (AI) is a promising technology to deal with these intractable tasks in design. In development of AI-based design support systems, it is desirable to choose a comprehensive framework based on the scientific theory of design. In this work a framework for AI-based design support systems for nuclear reactor design will be proposed based on an exploration model of design. The fundamental architectures of this framework will be described especially on knowledge representation, context management and design planning. (author)

Hull Surface Information Retrieval and Optimization of High Speed Planing Craft

International Nuclear Information System (INIS)

Ayob, A F; Wan Nik, W B; Ray, T; Smith, W F

2012-01-01

Traditional approach on ship design involve the use of a method which takes a form that was earlier called the 'general design diagram' and is now known as the 'design spiral' – an iterative ship design process that allows for an increase in complexity and precision across the design cycle. Several advancements have been made towards the design spiral, however inefficient for handling complex simultaneous design changes, especially when later variable changes affect the ship's performance characteristics evaluated in earlier stages. Reviewed in this paper are several advancements in high speed planing craft design in preliminary design stage. An optimization framework for high speed planing craft is discussed which consist of surface information retrieval module, a suite of state-of-the-art optimization algorithms and standard naval architectural performance estimation tools. A summary of the implementation of the proposed hull surface information retrieval and several case studies are presented to demonstrate the capabilities of the framework.

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

International Nuclear Information System (INIS)

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

Cognitive Process as a Basis for Intelligent Retrieval Systems Design.

Science.gov (United States)

Chen, Hsinchun; Dhar, Vasant

1991-01-01

Two studies of the cognitive processes involved in online document-based information retrieval were conducted. These studies led to the development of five computational models of online document retrieval which were incorporated into the design of an "intelligent" document-based retrieval system. Both the system and the broader implications of…

Polarimetric SAR interferometry-based decomposition modelling for reliable scattering retrieval

Science.gov (United States)

Agrawal, Neeraj; Kumar, Shashi; Tolpekin, Valentyn

2016-05-01

Fully Polarimetric SAR (PolSAR) data is used for scattering information retrieval from single SAR resolution cell. Single SAR resolution cell may contain contribution from more than one scattering objects. Hence, single or dual polarized data does not provide all the possible scattering information. So, to overcome this problem fully Polarimetric data is used. It was observed in previous study that fully Polarimetric data of different dates provide different scattering values for same object and coefficient of determination obtained from linear regression between volume scattering and aboveground biomass (AGB) shows different values for the SAR dataset of different dates. Scattering values are important input elements for modelling of forest aboveground biomass. In this research work an approach is proposed to get reliable scattering from interferometric pair of fully Polarimetric RADARSAT-2 data. The field survey for data collection was carried out for Barkot forest during November 10th to December 5th, 2014. Stratified random sampling was used to collect field data for circumference at breast height (CBH) and tree height measurement. Field-measured AGB was compared with the volume scattering elements obtained from decomposition modelling of individual PolSAR images and PolInSAR coherency matrix. Yamaguchi 4-component decomposition was implemented to retrieve scattering elements from SAR data. PolInSAR based decomposition was the great challenge in this work and it was implemented with certain assumptions to create Hermitian coherency matrix with co-registered polarimetric interferometric pair of SAR data. Regression analysis between field-measured AGB and volume scattering element obtained from PolInSAR data showed highest (0.589) coefficient of determination. The same regression with volume scattering elements of individual SAR images showed 0.49 and 0.50 coefficients of determination for master and slave images respectively. This study recommends use of

An efficient and robutst method for shape-based image retrieval

International Nuclear Information System (INIS)

Salih, N.D.; Besar, R.; Abas, F.S.

2007-01-01

Shapes can be thought as being the words oft he visual language. Shape boundaries need to be simplified and estimated in a wide variety of image analysis applications. Representation and description of Shapes is one of the major problems in content-based image retrieval (CBIR). This paper present an a novel method for shape representation and description named block-based shape representation (BSR), which is capable of extracting reliable information of the object outline in a concise manner. Our technique is translation, scale, and rotation invariant. It works well on different types of shapes and fast enough for use in real-time. This technique has been implemented and evaluated in order to analyze its accuracy and Efficiency. Based on the experimental results, we urge that the proposed BSR is a compact and reliable shape representation method. (author)

A Framework-Based Approach for Fault-Tolerant Service Robots

Directory of Open Access Journals (Sweden)

Heejune Ahn

2012-11-01

Full Text Available Recently the component-based approach has become a major trend in intelligent service robot development due to its reusability and productivity. The framework in a component-based system should provide essential services for application components. However, to our knowledge the existing robot frameworks do not yet support fault tolerance service. Moreover, it is often believed that faults can be handled only at the application level. In this paper, by extending the robot framework with the fault tolerance function, we argue that the framework-based fault tolerance approach is feasible and even has many benefits, including that: 1 the system integrators can build fault tolerance applications from non-fault-aware components; 2 the constraints of the components and the operating environment can be considered at the time of integration, which – cannot be anticipated eaily at the time of component development; 3 consistency in system reliability can be obtained even in spite of diverse application component sources. In the proposed construction, we build XML rule files defining the rules for probing and determining the fault conditions of each component, contamination cases from a faulty component, and the possible recovery and safety methods. The rule files are established by a system integrator and the fault manager in the framework controls the fault tolerance process according to the rules. We demonstrate that the fault-tolerant framework can incorporate widely accepted fault tolerance techniques. The effectiveness and real-time performance of the framework-based approach and its techniques are examined by testing an autonomous mobile robot in typical fault scenarios.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Fast DCNN based on FWT, intelligent dropout and layer skipping for image retrieval.

Science.gov (United States)

ElAdel, Asma; Zaied, Mourad; Amar, Chokri Ben

2017-11-01

Deep Convolutional Neural Network (DCNN) can be marked as a powerful tool for object and image classification and retrieval. However, the training stage of such networks is highly consuming in terms of storage space and time. Also, the optimization is still a challenging subject. In this paper, we propose a fast DCNN based on Fast Wavelet Transform (FWT), intelligent dropout and layer skipping. The proposed approach led to improve the image retrieval accuracy as well as the searching time. This was possible thanks to three key advantages: First, the rapid way to compute the features using FWT. Second, the proposed intelligent dropout method is based on whether or not a unit is efficiently and not randomly selected. Third, it is possible to classify the image using efficient units of earlier layer(s) and skipping all the subsequent hidden layers directly to the output layer. Our experiments were performed on CIFAR-10 and MNIST datasets and the obtained results are very promising. Copyright © 2017 Elsevier Ltd. All rights reserved.

G-Bean: an ontology-graph based web tool for biomedical literature retrieval.

Science.gov (United States)

Wang, James Z; Zhang, Yuanyuan; Dong, Liang; Li, Lin; Srimani, Pradip K; Yu, Philip S

2014-01-01

Currently, most people use NCBI's PubMed to search the MEDLINE database, an important bibliographical information source for life science and biomedical information. However, PubMed has some drawbacks that make it difficult to find relevant publications pertaining to users' individual intentions, especially for non-expert users. To ameliorate the disadvantages of PubMed, we developed G-Bean, a graph based biomedical search engine, to search biomedical articles in MEDLINE database more efficiently. G-Bean addresses PubMed's limitations with three innovations: (1) Parallel document index creation: a multithreaded index creation strategy is employed to generate the document index for G-Bean in parallel; (2) Ontology-graph based query expansion: an ontology graph is constructed by merging four major UMLS (Version 2013AA) vocabularies, MeSH, SNOMEDCT, CSP and AOD, to cover all concepts in National Library of Medicine (NLM) database; a Personalized PageRank algorithm is used to compute concept relevance in this ontology graph and the Term Frequency - Inverse Document Frequency (TF-IDF) weighting scheme is used to re-rank the concepts. The top 500 ranked concepts are selected for expanding the initial query to retrieve more accurate and relevant information; (3) Retrieval and re-ranking of documents based on user's search intention: after the user selects any article from the existing search results, G-Bean analyzes user's selections to determine his/her true search intention and then uses more relevant and more specific terms to retrieve additional related articles. The new articles are presented to the user in the order of their relevance to the already selected articles. Performance evaluation with 106 OHSUMED benchmark queries shows that G-Bean returns more relevant results than PubMed does when using these queries to search the MEDLINE database. PubMed could not even return any search result for some OHSUMED queries because it failed to form the appropriate Boolean

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

Energy Technology Data Exchange (ETDEWEB)

Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili, E-mail: wangnsrl@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029 (China); Zhang, Kai [Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Zhu, Peiping; Wu, Ziyu, E-mail: wuzy@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029, China and Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)

2015-02-15

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

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

International Nuclear Information System (INIS)

Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili; Zhang, Kai; Zhu, Peiping; Wu, Ziyu

2015-01-01

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

Learning and Relevance in Information Retrieval: A Study in the Application of Exploration and User Knowledge to Enhance Performance

Science.gov (United States)

Hyman, Harvey

2012-01-01

This dissertation examines the impact of exploration and learning upon eDiscovery information retrieval; it is written in three parts. Part I contains foundational concepts and background on the topics of information retrieval and eDiscovery. This part informs the reader about the research frameworks, methodologies, data collection, and…

AX Tank Farm waste retrieval alternatives cost estimates

International Nuclear Information System (INIS)

Krieg, S.A.

1998-01-01

This report presents the estimated costs associated with retrieval of the wastes from the four tanks in AX Tank Farm. The engineering cost estimates developed for this report are based on previous cost data prepared for Project W-320 and the HTI 241-C-106 Heel Retrieval System. The costs presented in this report address only the retrieval of the wastes from the four AX Farm tanks. This includes costs for equipment procurement, fabrication, installation, and operation to retrieve the wastes. The costs to modify the existing plant equipment and systems to support the retrieval equipment are also included. The estimates do not include operational costs associated with pumping the waste out of the waste receiver tank (241-AY-102) between AX Farm retrieval campaigns or transportation, processing, and disposal of the retrieved waste

How ground-based observations can support satellite greenhouse gas retrievals

Science.gov (United States)

Butler, J. H.; Tans, P. P.; Sweeney, C.; Dlugokencky, E. J.

2012-04-01

Global society will eventually accelerate efforts to reduce greenhouse gas emissions in a variety of ways. These would likely involve international treaties, national policies, and regional strategies that will affect a number of economic, social, and environmental sectors. Some strategies will work better than others and some will not work at all. Because trillions of dollars will be involved in pursuing greenhouse gas emission reductions - through realignment of energy production, improvement of efficiencies, institution of taxes, implementation of carbon trading markets, and use of offsets - it is imperative that society be given all the tools at its disposal to ensure the ultimate success of these efforts. Providing independent, globally coherent information on the success of these efforts will give considerable strength to treaties, policies, and strategies. Doing this will require greenhouse gas observations greatly expanded from what we have today. Satellite measurements may ultimately be indispensable in achieving global coverage, but the requirements for accuracy and continuity of measurements over time are demanding if the data are to be relevant. Issues such as those associated with sensor drift, aging electronics, and retrieval artifacts present challenges that can be addressed in part by close coordination with ground-based and in situ systems. This presentation identifies the information that ground-based systems provide very well, but it also looks at what would be deficient even in a greatly expanded surface system, where satellites can fill these gaps, and how on-going, ground and in situ measurements can aid in addressing issues associated with accuracy, long-term continuity, and retrieval artifacts.

Framework for AI-based nuclear reactor design support system

International Nuclear Information System (INIS)

Furuta, Kazuo; Kondo, Shunsuke

1992-01-01

Nowadays many computer programs are being developed and used for the analytic tasks in nuclear reactor design, but experienced designers are still responsible for most of the synthetic tasks which are not amenable to algorithmic computer processes. Artificial intelligence (AI) is a promising technology to deal with these intractable tasks in design. In development of AI-based design support systems, it is desirable to choose a comprehensive framework based on the scientific theory of design. In this work a framework for AI-based design support systems for nuclear reactor design will be proposed based on an explorative abduction model of design. The fundamental architectures of this framework will be described especially on knowledge representation, context management and design planning. (author)

Selective memory retrieval can impair and improve retrieval of other memories.

Science.gov (United States)

Bäuml, Karl-Heinz T; Samenieh, Anuscheh

2012-03-01

Research from the past decades has shown that retrieval of a specific memory (e.g., retrieving part of a previous vacation) typically attenuates retrieval of other memories (e.g., memories for other details of the event), causing retrieval-induced forgetting. More recently, however, it has been shown that retrieval can both attenuate and aid recall of other memories (K.-H. T. Bäuml & A. Samenieh, 2010). To identify the circumstances under which retrieval aids recall, the authors examined retrieval dynamics in listwise directed forgetting, context-dependent forgetting, proactive interference, and in the absence of any induced memory impairment. They found beneficial effects of selective retrieval in listwise directed forgetting and context-dependent forgetting but detrimental effects in all the other conditions. Because context-dependent forgetting and listwise directed forgetting arguably reflect impaired context access, the results suggest that memory retrieval aids recall of memories that are subject to impaired context access but attenuates recall in the absence of such circumstances. The findings are consistent with a 2-factor account of memory retrieval and suggest the existence of 2 faces of memory retrieval. 2012 APA, all rights reserved

Evaluation of OMI operational standard NO2 column retrievals using in situ and surface-based NO2 observations

Directory of Open Access Journals (Sweden)

L. N. Lamsal

2014-11-01

Full Text Available We assess the standard operational nitrogen dioxide (NO2 data product (OMNO2, version 2.1 retrieved from the Ozone Monitoring Instrument (OMI onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8 with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI chemistry-transport model (CTM used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

High Resolution Trajectory-Based Smoke Forecasts Using VIIRS Aerosol Optical Depth and NUCAPS Carbon Monoxide Retrievals

Science.gov (United States)

Pierce, R. B.; Smith, N.; Barnet, C.; Barnet, C. D.; Kondragunta, S.; Davies, J. E.; Strabala, K.

2016-12-01

We use Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth (AOD) and combined Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) NOAA-Unique CrIS-ATMS Processing System (NUCAPS) carbon monoxide (CO) retrievals to initialize trajectory-based, high spatial resolution North American smoke dispersion forecasts during the May 2016 Fort McMurray wildfire in northern Alberta and the July 2016 Soberanes Fire in Northern California. These two case studies illustrate how long range transport of wild fire smoke can adversely impact surface air quality thousands of kilometers downwind and how local topographic flow can lead to complex transport patterns near the wildfire source region. The NUCAPS CO retrievals are shown to complement the high resolution VIIRS AOD retrievals by providing retrievals in partially cloudy scenes and also providing information on the vertical distribution of the wildfire smoke. This work addresses the need for low latency, web-based, high resolution forecasts of smoke dispersion for use by NWS Incident Meteorologists (IMET) to support on-site decision support services for fire incident management teams. The primary user community for the IDEA-I smoke forecasts is the Western regions of the NWS and US EPA due to the significant impacts of wildfires in these regions. Secondary users include Alaskan NWS offices and Western State and Local air quality management agencies such as the Western Regional Air Partnership (WRAP).

An XML-based framework for personalized health management.

Science.gov (United States)

Lee, Hiye-Ja; Park, Seung-Hun; Jeong, Byeong-Soo

2006-01-01

This paper proposes a framework for personalized health management. In this framework, XML technology is used for representing and managing the health information and knowledge. Major components of the framework are Health Management Prescription (HMP) Expert System and Health Information Repository. The HMP Expert System generates a HMP efficiently by using XML-based templates. Health Information Repository provides integrated health information and knowledge for personalized health management by using XML and relational database together.

Validation of the CrIS fast physical NH3 retrieval with ground-based FTIR

NARCIS (Netherlands)

Dammers, E.; Shephard, M.W.; Palm, M.; Cady-Pereira, K.; Capps, S.; Lutsch, E.; Strong, K.; Hannigan, J.W.; Ortega, I.; Toon, G.C.; Stremme, W.; Grutter, M.; Jones, N.; Smale, D.; Siemons, J.; Hrpcek, K.; Tremblay, D.; Schaap, M.; Notholt, J.; Willem Erisman, J.

2017-01-01

Presented here is the validation of the CrIS (Cross-track Infrared Sounder) fast physical NH3 retrieval (CFPR) column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. We use the total columns and profiles from seven FTIR sites in the Network for the

Retrieval interval mapping, a tool to optimize the spectral retrieval range in differential optical absorption spectroscopy

Science.gov (United States)

Vogel, L.; Sihler, H.; Lampel, J.; Wagner, T.; Platt, U.

2012-06-01

Remote sensing via differential optical absorption spectroscopy (DOAS) has become a standard technique to identify and quantify trace gases in the atmosphere. The technique is applied in a variety of configurations, commonly classified into active and passive instruments using artificial and natural light sources, respectively. Platforms range from ground based to satellite instruments and trace-gases are studied in all kinds of different environments. Due to the wide range of measurement conditions, atmospheric compositions and instruments used, a specific challenge of a DOAS retrieval is to optimize the parameters for each specific case and particular trace gas of interest. This becomes especially important when measuring close to the detection limit. A well chosen evaluation wavelength range is crucial to the DOAS technique. It should encompass strong absorption bands of the trace gas of interest in order to maximize the sensitivity of the retrieval, while at the same time minimizing absorption structures of other trace gases and thus potential interferences. Also, instrumental limitations and wavelength depending sources of errors (e.g. insufficient corrections for the Ring effect and cross correlations between trace gas cross sections) need to be taken into account. Most often, not all of these requirements can be fulfilled simultaneously and a compromise needs to be found depending on the conditions at hand. Although for many trace gases the overall dependence of common DOAS retrieval on the evaluation wavelength interval is known, a systematic approach to find the optimal retrieval wavelength range and qualitative assessment is missing. Here we present a novel tool to determine the optimal evaluation wavelength range. It is based on mapping retrieved values in the retrieval wavelength space and thus visualize the consequence of different choices of retrieval spectral ranges, e.g. caused by slightly erroneous absorption cross sections, cross correlations and

Foreign Body Retrieval

Medline Plus

Full Text Available ... Physician Resources Professions Site Index A-Z Foreign Body Retrieval Foreign body retrieval is the removal of ... foreign body detection and removal? What is Foreign Body Retrieval? Foreign body retrieval involves the removal of ...

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

Science.gov (United States)

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

2017-06-01

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

Ice particle mass-dimensional parameter retrieval and uncertainty analysis using an Optimal Estimation framework applied to in situ data

Science.gov (United States)

Xu, Zhuocan; Mace, Jay; Avalone, Linnea; Wang, Zhien

2015-04-01

The extreme variability of ice particle habits in precipitating clouds affects our understanding of these cloud systems in every aspect (i.e. radiation transfer, dynamics, precipitation rate, etc) and largely contributes to the uncertainties in the model representation of related processes. Ice particle mass-dimensional power law relationships, M=a*(D ^ b), are commonly assumed in models and retrieval algorithms, while very little knowledge exists regarding the uncertainties of these M-D parameters in real-world situations. In this study, we apply Optimal Estimation (OE) methodology to infer ice particle mass-dimensional relationship from ice particle size distributions and bulk water contents independently measured on board the University of Wyoming King Air during the Colorado Airborne Multi-Phase Cloud Study (CAMPS). We also utilize W-band radar reflectivity obtained on the same platform (King Air) offering a further constraint to this ill-posed problem (Heymsfield et al. 2010). In addition to the values of retrieved M-D parameters, the associated uncertainties are conveniently acquired in the OE framework, within the limitations of assumed Gaussian statistics. We find, given the constraints provided by the bulk water measurement and in situ radar reflectivity, that the relative uncertainty of mass-dimensional power law prefactor (a) is approximately 80% and the relative uncertainty of exponent (b) is 10-15%. With this level of uncertainty, the forward model uncertainty in radar reflectivity would be on the order of 4 dB or a factor of approximately 2.5 in ice water content. The implications of this finding are that inferences of bulk water from either remote or in situ measurements of particle spectra cannot be more certain than this when the mass-dimensional relationships are not known a priori which is almost never the case.

Large-Scale Partial-Duplicate Image Retrieval and Its Applications

Science.gov (United States)

2016-04-23

tree based image retrieval , a semantic-aware co-indexing algorithm is proposed to jointly embed two strong cues into the inverted indexes: 1) local...based image retrieval , a semantic-aware co-indexing algorithm is proposed to jointly embed two strong cues into the inverted indexes: 1) local...Distribution Unlimited UU UU UU UU 23-04-2016 23-Jan-2012 22-Jan-2016 Final Report: Large-Scale Partial-Duplicate Image Retrieval and Its Applications

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

Science.gov (United States)

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.

Texture Retrieval from VHR Optical Remote Sensed Images Using the Local Extrema Descriptor with Application to Vineyard Parcel Detection

Directory of Open Access Journals (Sweden)

Minh-Tan Pham

2016-04-01

Full Text Available In this article, we develop a novel method for the detection of vineyard parcels in agricultural landscapes based on very high resolution (VHR optical remote sensing images. Our objective is to perform texture-based image retrieval and supervised classification algorithms. To do that, the local textural and structural features inside each image are taken into account to measure its similarity to other images. In fact, VHR images usually involve a variety of local textures and structures that may verify a weak stationarity hypothesis. Hence, an approach only based on characteristic points, not on all pixels of the image, is supposed to be relevant. This work proposes to construct the local extrema-based descriptor (LED by using the local maximum and local minimum pixels extracted from the image. The LED descriptor is formed based on the radiometric, geometric and gradient features from these local extrema. We first exploit the proposed LED descriptor for the retrieval task to evaluate its performance on texture discrimination. Then, it is embedded into a supervised classification framework to detect vine parcels using VHR satellite images. Experiments performed on VHR panchromatic PLEIADES image data prove the effectiveness of the proposed strategy. Compared to state-of-the-art methods, an enhancement of about 7% in retrieval rate is achieved. For the detection task, about 90% of vineyards are correctly detected.

A model-based framework for design of intensified enzyme-based processes

DEFF Research Database (Denmark)

Román-Martinez, Alicia

This thesis presents a generic and systematic model-based framework to design intensified enzyme-based processes. The development of the presented methodology was motivated by the needs of the bio-based industry for a more systematic approach to achieve intensification in its production plants...... in enzyme-based processes which have found significant application in the pharmaceutical, food, and renewable fuels sector. The framework uses model-based strategies for (bio)-chemical process design and optimization, including the use of a superstructure to generate all potential reaction......(s)-separation(s) options according to a desired performance criteria and a generic mathematical model represented by the superstructure to derive the specific models corresponding to a specific process option. In principle, three methods of intensification of bioprocess are considered in this thesis: 1. enzymatic one...

Information retrieval in particle physics

International Nuclear Information System (INIS)

Oyanagi, Yoshio

1983-01-01

Various information retrieval systems for elementary particle physics are introduced. Scientific information has been distributed in the form of books, periodicals or preprints. Some periodicals include the abstracts of information only. Recently, computer systems, by which the information retrieval can be easily done, have been developed. The construction of networks connecting various computer systems is in progress. It is possible to call the data base of Rutherford Laboratory from a telephone terminal of Laurence Berkeley Laboratory. The access to the Network by British Science Research Council can be made from DESY or CERN. The examples of on-line information retrieval in Japan are presented. Some of the periodicals of secondary information and data books are also introduced. (Kato, T.)

ABrowse - a customizable next-generation genome browser framework

Directory of Open Access Journals (Sweden)

Kong Lei

2012-01-01

Full Text Available Abstract Background With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects. Results Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access. Conclusions ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at http://www.abrowse.org/. To demonstrate all the features of ABrowse, a live demo for

ABrowse--a customizable next-generation genome browser framework.

Science.gov (United States)

Kong, Lei; Wang, Jun; Zhao, Shuqi; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2012-01-05

With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects. Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access. ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at http://www.abrowse.org/. To demonstrate all the features of ABrowse, a live demo for Arabidopsis thaliana genome has been built at http://arabidopsis.cbi.edu.cn/.

ABrowse - a customizable next-generation genome browser framework

Science.gov (United States)

2012-01-01

Background With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects. Results Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access. Conclusions ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at http://www.abrowse.org/. To demonstrate all the features of ABrowse, a live demo for Arabidopsis thaliana genome

A Learning State-Space Model for Image Retrieval

Directory of Open Access Journals (Sweden)

Lee Greg C

2007-01-01

Full Text Available This paper proposes an approach based on a state-space model for learning the user concepts in image retrieval. We first design a scheme of region-based image representation based on concept units, which are integrated with different types of feature spaces and with different region scales of image segmentation. The design of the concept units aims at describing similar characteristics at a certain perspective among relevant images. We present the details of our proposed approach based on a state-space model for interactive image retrieval, including likelihood and transition models, and we also describe some experiments that show the efficacy of our proposed model. This work demonstrates the feasibility of using a state-space model to estimate the user intuition in image retrieval.

An Approach to Retrieval of OCR Degraded Text

Directory of Open Access Journals (Sweden)

Yuen-Hsien Tseng

1998-12-01

Full Text Available The major problem with retrieval of OCR text is the unpredictable distortion of characters due to recognition errors. Because users have no ideas of such distortion, the terms they query can hardly match the terms stored in the OCR text exactly. Thus retrieval effectiveness is significantly reduced , especially for low-quality input. To reduce the losses from retrieving such noisy OCR text, a fault-tolerant retrieval strategy based on automatic keyword extraction and fuzzy matching is proposed. In this strategy, terms, correct or not, and their term frequencies are extracted from the noisy text and presented for browsing and selection in response to users' initial queries , With theunderstanding of the real terms stored in the noisy text and of their estimated frequency distributions, users may then choose appropriate terms for a more effective searching, A text retrieval system based on this strategy has been built. Examples to show the effectiveness are demonstrated. Finally, some OCR issues for further enhancingretrieval effectiveness are discussed.

Explicit and Observation-based Aerosol Treatment in Tropospheric NO2 Retrieval over China from the Ozone Monitoring Instrument

Science.gov (United States)

Liu, M.; Lin, J.; Boersma, F.; Pinardi, G.; Wang, Y.; Chimot, J.; Wagner, T.; Xie, P.; Eskes, H.; Van Roozendael, M.; Hendrick, F.

2017-12-01

Satellite retrieval of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) is influenced by aerosols substantially. Aerosols affect the retrieval of "effective cloud fraction (CF)" and "effective cloud top pressure (CP)" that are used in the subsequent NO2 retrieval to account for the presentence of clouds. And aerosol properties and vertical distributions directly affect the NO2 air mass factor (AMF) calculations. Our published POMINO algorithm uses a parallelized LIDORT-driven AMFv6 code to derive CF, CP and NO2 VCD. Daily information on aerosol optical properties are taken from GEOS-Chem simulations, with aerosol optical depth (AOD) further constrained by monthly MODIS AOD. However, the published algorithm does not include an observation-based constraint of aerosol vertical distribution. Here we construct a monthly climatological observation dataset of aerosol extinction profiles, based on Level-2 CALIOP data over 2007-2015, to further constrain aerosol vertical distributions. GEOS-Chem captures the temporal variations of CALIOP aerosol layer heights (ALH) but has an overall underestimate by about 0.3 km. It tends to overestimate the aerosol extinction by 10% below 2 km but with an underestimate by 30% above 2 km, leading to a low bias by 10-30% in the retrieved tropospheric NO2 VCD. After adjusting GEOS-Chem aerosol extinction profiles by the CALIOP monthly ALH climatology, the retrieved NO2 VCDs increase by 4-16% over China on a monthly basis in 2012. The improved NO2 VCDs are better correlated to independent MAX-DOAS observations at three sites than POMINO and DOMINO are - especially for the polluted cases, R2 reaches 0.76 for the adjusted POMINO, much higher than that for the published POMINO (0.68) and DOMINO (0.38). The newly retrieved CP increases by 60 hPa on average, because of a stronger aerosol screening effect. Compared to the CF used in DOMINO, which implicitly includes aerosol information, our improved CF is much lower and can

Coupled binary embedding for large-scale image retrieval.

Science.gov (United States)

Zheng, Liang; Wang, Shengjin; Tian, Qi

2014-08-01

Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

Natural language retrieval in nuclear safety information system

International Nuclear Information System (INIS)

Komata, Masaoki; Oosawa, Yasuo; Ujita, Hiroshi

1983-01-01

A natural language retrieval program NATLANG is developed to assist in the retrieval of information from event-and-cause descriptions in Licensee Event Reports (LER). The characteristics of NATLANG are (1) the use of base forms of words to retrieve related forms altered by the addition of prefixes or suffixes or changes in inflection, (2) direct access and short time retrieval with an alphabet pointer, (3) effective determination of the items and entries for a Hitachi event classification in a two step retrieval scheme, and (4) Japanese character output with the PL-1 language. NATLANG output reduces the effort needed to re-classify licensee events in the Hitachi event classification. (author)

Extension of frequency-based dissimilarity for retrieving similar plasma waveforms

International Nuclear Information System (INIS)

Hochin, Teruhisa; Koyama, Katsumasa; Nakanishi, Hideya; Kojima, Mamoru

2008-01-01

Some computer-aided assistance in finding the waveforms similar to a waveform has become indispensable for accelerating data analysis in the plasma experiments. For the slowly-varying waveforms and those having time-sectional oscillation patterns, the methods using the Fourier series coefficients of waveforms in calculating the dissimilarity have successfully improved the performance in retrieving similar waveforms. This paper treats severely-varying waveforms, and proposes two extensions to the dissimilarity of waveforms. The first extension is to capture the difference of the importance of the Fourier series coefficients of waveforms against frequency. The second extension is to consider the outlines of waveforms. The correctness of the extended dissimilarity is experimentally evaluated by using the metrics used in evaluating that of the information retrieval, i.e. precision and recall. The experimental results show that the extended dissimilarity could improve the correctness of the similarity retrieval of plasma waveforms

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

Science.gov (United States)

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

2015-01-01

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

Modelling of chromatic contrast for retrieval of wallpaper images

OpenAIRE

Gao, Xiaohong W.; Wang, Yuanlei; Qian, Yu; Gao, Alice

2015-01-01

Colour remains one of the key factors in presenting an object and consequently has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour-based image retrieval. To comprehend this effect, in this paper, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing t...

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

Science.gov (United States)

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.

Nature-based supportive care opportunities: a conceptual framework.

Science.gov (United States)

Blaschke, Sarah; O'Callaghan, Clare C; Schofield, Penelope

2018-03-22

Given preliminary evidence for positive health outcomes related to contact with nature for cancer populations, research is warranted to ascertain possible strategies for incorporating nature-based care opportunities into oncology contexts as additional strategies for addressing multidimensional aspects of cancer patients' health and recovery needs. The objective of this study was to consolidate existing research related to nature-based supportive care opportunities and generate a conceptual framework for discerning relevant applications in the supportive care setting. Drawing on research investigating nature-based engagement in oncology contexts, a two-step analytic process was used to construct a conceptual framework for guiding nature-based supportive care design and future research. Concept analysis methodology generated new representations of understanding by extracting and synthesising salient concepts. Newly formulated concepts were transposed to findings from related research about patient-reported and healthcare expert-developed recommendations for nature-based supportive care in oncology. Five theoretical concepts (themes) were formulated describing patients' reasons for engaging with nature and the underlying needs these interactions address. These included: connecting with what is genuinely valued, distancing from the cancer experience, meaning-making and reframing the cancer experience, finding comfort and safety, and vital nurturance. Eight shared patient and expert recommendations were compiled, which address the identified needs through nature-based initiatives. Eleven additional patient-reported recommendations attend to beneficial and adverse experiential qualities of patients' nature-based engagement and complete the framework. The framework outlines salient findings about helpful nature-based supportive care opportunities for ready access by healthcare practitioners, designers, researchers and patients themselves. © Article author(s) (or their

Proof of concept: concept-based biomedical information retrieval

NARCIS (Netherlands)

Trieschnigg, Rudolf Berend

2010-01-01

In this thesis we investigate the possibility to integrate domain-specific knowledge into biomedical information retrieval (IR). Recent decades have shown a fast growing interest in biomedical research, reflected by an exponential growth in scientific literature. An important problem for biomedical

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

Science.gov (United States)

Stamnes, S; Hostetler, C; Ferrare, R; Burton, S; Liu, X; Hair, J; Hu, Y; Wasilewski, A; Martin, W; van Diedenhoven, B; Chowdhary, J; Cetinić, I; Berg, L K; Stamnes, K; Cairns, B

2018-04-01

We present an optimal-estimation-based retrieval framework, the microphysical aerosol properties from polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular total and polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High-Spectral-Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355 and 532 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ångstrøm exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio-Optical Research (SABOR) campaign. For the SABOR campaign, 73% RSP MAPP retrievals fall within ±0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.933 and root-mean-square deviation of 0.0372. For the TCAP campaign, 53% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.927 and root-mean-square deviation of 0.0673. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.959 and a root-mean-square deviation of 0.0694. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar + polarimeter retrieval using both HSRL and RSP measurements.

Data Discretization for Novel Relationship Discovery in Information Retrieval.

Science.gov (United States)

Benoit, G.

2002-01-01

Describes an information retrieval, visualization, and manipulation model which offers the user multiple ways to exploit the retrieval set, based on weighted query terms, via an interactive interface. Outlines the mathematical model and describes an information retrieval application built on the model to search structured and full-text files.…

Today's and tomorrow's retrieval practice in the audiovisual archive

NARCIS (Netherlands)

Huurnink, B.; Snoek, C.G.M.; de Rijke, M.; Smeulders, A.W.M.

2010-01-01

Content-based video retrieval is maturing to the point where it can be used in real-world retrieval practices. One such practice is the audiovisual archive, whose users increasingly require fine-grained access to broadcast television content. We investigate to what extent content-based video

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

Science.gov (United States)

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)

SOFTWARE FOR REGIONS OF INTEREST RETRIEVAL ON MEDICAL 3D IMAGES

Directory of Open Access Journals (Sweden)

G. G. Stromov

2014-01-01

Full Text Available Background. Implementation of software for areas of interest retrieval in 3D medical images is described in this article. It has been tested against large volume of model MRIs.Material and methods. We tested software against normal and pathological (severe multiple sclerosis model MRIs from tge BrainWeb resource. Technological stack is based on open-source cross-platform solutions. We implemented storage system on Maria DB (an open-sourced fork of MySQL with P/SQL extensions. Python 2.7 scripting was used for automatization of extract-transform-load operations. The computational core is written on Java 7 with Spring framework 3. MongoDB was used as a cache in the cluster of workstations. Maven 3 was chosen as a dependency manager and build system, the project is hosted at Github.Results. As testing on SSMU's LAN has showed, software has been developed is quite efficiently retrieves ROIs are matching for the morphological substratum on pathological MRIs.Conclusion. Automation of a diagnostic process using medical imaging allows to level down the subjective component in decision making and increase the availability of hi-tech medicine. Software has shown in the article is a complex solution for ROI retrieving and segmentation process on model medical images in full-automated mode.We would like to thank Robert Vincent for great help with consulting of usage the BrainWeb resource.

Validation of the CrIS fast physical NH3 retrieval with ground-based FTIR

Directory of Open Access Journals (Sweden)

E. Dammers

2017-07-01

Full Text Available Presented here is the validation of the CrIS (Cross-track Infrared Sounder fast physical NH3 retrieval (CFPR column and profile measurements using ground-based Fourier transform infrared (FTIR observations. We use the total columns and profiles from seven FTIR sites in the Network for the Detection of Atmospheric Composition Change (NDACC to validate the satellite data products. The overall FTIR and CrIS total columns have a positive correlation of r  =  0.77 (N  =  218 with very little bias (a slope of 1.02. Binning the comparisons by total column amounts, for concentrations larger than 1.0  ×  1016 molecules cm−2, i.e. ranging from moderate to polluted conditions, the relative difference is on average ∼ 0–5 % with a standard deviation of 25–50 %, which is comparable to the estimated retrieval uncertainties in both CrIS and the FTIR. For the smallest total column range (< 1.0  × 1016 molecules cm−2 where there are a large number of observations at or near the CrIS noise level (detection limit the absolute differences between CrIS and the FTIR total columns show a slight positive column bias. The CrIS and FTIR profile comparison differences are mostly within the range of the single-level retrieved profile values from estimated retrieval uncertainties, showing average differences in the range of  ∼ 20 to 40 %. The CrIS retrievals typically show good vertical sensitivity down into the boundary layer which typically peaks at  ∼ 850 hPa (∼ 1.5 km. At this level the median absolute difference is 0.87 (std  =  ±0.08 ppb, corresponding to a median relative difference of 39 % (std  =  ±2 %. Most of the absolute and relative profile comparison differences are in the range of the estimated retrieval uncertainties. At the surface, where CrIS typically has lower sensitivity, it tends to overestimate in low-concentration conditions and underestimate

A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data

International Nuclear Information System (INIS)

Wan, Z.; Li, Z.L.

1997-01-01

The authors have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NEΔT) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4--0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10--12.5 microm IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2--3 K

Content-based image retrieval using spatial layout information in brain tumor T1-weighted contrast-enhanced MR images.

Science.gov (United States)

Huang, Meiyan; Yang, Wei; Wu, Yao; Jiang, Jun; Gao, Yang; Chen, Yang; Feng, Qianjin; Chen, Wufan; Lu, Zhentai

2014-01-01

This study aims to develop content-based image retrieval (CBIR) system for the retrieval of T1-weighted contrast-enhanced MR (CE-MR) images of brain tumors. When a tumor region is fed to the CBIR system as a query, the system attempts to retrieve tumors of the same pathological category. The bag-of-visual-words (BoVW) model with partition learning is incorporated into the system to extract informative features for representing the image contents. Furthermore, a distance metric learning algorithm called the Rank Error-based Metric Learning (REML) is proposed to reduce the semantic gap between low-level visual features and high-level semantic concepts. The effectiveness of the proposed method is evaluated on a brain T1-weighted CE-MR dataset with three types of brain tumors (i.e., meningioma, glioma, and pituitary tumor). Using the BoVW model with partition learning, the mean average precision (mAP) of retrieval increases beyond 4.6% with the learned distance metrics compared with the spatial pyramid BoVW method. The distance metric learned by REML significantly outperforms three other existing distance metric learning methods in terms of mAP. The mAP of the CBIR system is as high as 91.8% using the proposed method, and the precision can reach 93.1% when the top 10 images are returned by the system. These preliminary results demonstrate that the proposed method is effective and feasible for the retrieval of brain tumors in T1-weighted CE-MR Images.