WorldWideScience

Sample records for video text extraction

  1. AViTExt: Automatic Video Text Extraction, A new Approach for video content indexing Application

    OpenAIRE

    Bouaziz, Baseem; Zlitni, Tarek; Walid MAHDI

    2013-01-01

    In this paper, we propose a spatial temporal video-text detection technique which proceed in two principal steps:potential text region detection and a filtering process. In the first step we divide dynamically each pair of consecutive video frames into sub block in order to detect change. A significant difference between homologous blocks implies the appearance of an important object which may be a text region. The temporal redundancy is then used to filter these regions and forms an effectiv...

  2. ViTexOCR; a script to extract text overlays from digital video

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The ViTexOCR script presents a new method for extracting navigation data from videos with text overlays using optical character recognition (OCR) software. Over the...

  3. Key Frame Extraction for Text Based Video Retrieval Using Maximally Stable Extremal Regions

    Directory of Open Access Journals (Sweden)

    Werachard Wattanarachothai

    2015-04-01

    Full Text Available This paper presents a new approach for text-based video content retrieval system. The proposed scheme consists of three main processes that are key frame extraction, text localization and keyword matching. For the key-frame extraction, we proposed a Maximally Stable Extremal Region (MSER based feature which is oriented to segment shots of the video with different text contents. In text localization process, in order to form the text lines, the MSERs in each key frame are clustered based on their similarity in position, size, color, and stroke width. Then, Tesseract OCR engine is used for recognizing the text regions. In this work, to improve the recognition results, we input four images obtained from different pre-processing methods to Tesseract engine. Finally, the target keyword for querying is matched with OCR results based on an approximate string search scheme. The experiment shows that, by using the MSER feature, the videos can be segmented by using efficient number of shots and provide the better precision and recall in comparison with a sum of absolute difference and edge based method.

  4. Fuzzy-Based Segmentation for Variable Font-Sized Text Extraction from Images/Videos

    Directory of Open Access Journals (Sweden)

    Samabia Tehsin

    2014-01-01

    Full Text Available Textual information embedded in multimedia can provide a vital tool for indexing and retrieval. A lot of work is done in the field of text localization and detection because of its very fundamental importance. One of the biggest challenges of text detection is to deal with variation in font sizes and image resolution. This problem gets elevated due to the undersegmentation or oversegmentation of the regions in an image. The paper addresses this problem by proposing a solution using novel fuzzy-based method. This paper advocates postprocessing segmentation method that can solve the problem of variation in text sizes and image resolution. The methodology is tested on ICDAR 2011 Robust Reading Challenge dataset which amply proves the strength of the recommended method.

  5. Automatic inpainting scheme for video text detection and removal.

    Science.gov (United States)

    Mosleh, Ali; Bouguila, Nizar; Ben Hamza, Abdessamad

    2013-11-01

    We present a two stage framework for automatic video text removal to detect and remove embedded video texts and fill-in their remaining regions by appropriate data. In the video text detection stage, text locations in each frame are found via an unsupervised clustering performed on the connected components produced by the stroke width transform (SWT). Since SWT needs an accurate edge map, we develop a novel edge detector which benefits from the geometric features revealed by the bandlet transform. Next, the motion patterns of the text objects of each frame are analyzed to localize video texts. The detected video text regions are removed, then the video is restored by an inpainting scheme. The proposed video inpainting approach applies spatio-temporal geometric flows extracted by bandlets to reconstruct the missing data. A 3D volume regularization algorithm, which takes advantage of bandlet bases in exploiting the anisotropic regularities, is introduced to carry out the inpainting task. The method does not need extra processes to satisfy visual consistency. The experimental results demonstrate the effectiveness of both our proposed video text detection approach and the video completion technique, and consequently the entire automatic video text removal and restoration process.

  6. Sign Language Video Processing for Text Detection in Hindi Language

    Directory of Open Access Journals (Sweden)

    Rashmi B Hiremath

    2016-10-01

    Full Text Available Sign language is a way of expressing yourself with your body language, where every bit of ones expressions, goals, or sentiments are conveyed by physical practices, for example, outward appearances, body stance, motions, eye movements, touch and the utilization of space. Non-verbal communication exists in both creatures and people, yet this article concentrates on elucidations of human non-verbal or sign language interpretation into Hindi textual expression. The proposed method of implementation utilizes the image processing methods and synthetic intelligence strategies to get the goal of sign video recognition. To carry out the proposed task implementation it uses image processing methods such as frame analysing based tracking, edge detection, wavelet transform, erosion, dilation, blur elimination, noise elimination, on training videos. It also uses elliptical Fourier descriptors called SIFT for shape feature extraction and most important part analysis for feature set optimization and reduction. For result analysis, this paper uses different category videos such as sign of weeks, months, relations etc. Database of extracted outcomes are compared with the video fed to the system as a input of the signer by a trained unclear inference system.

  7. Metadata extraction using text mining.

    Science.gov (United States)

    Seth, Shivani; Rüping, Stefan; Wrobel, Stefan

    2009-01-01

    Grid technologies have proven to be very successful in the area of eScience, and healthcare in particular, because they allow to easily combine proven solutions for data querying, integration, and analysis into a secure, scalable framework. In order to integrate the services that implement these solutions into a given Grid architecture, some metadata is required, for example information about the low-level access to these services, security information, and some documentation for the user. In this paper, we investigate how relevant metadata can be extracted from a semi-structured textual documentation of the algorithm that is underlying the service, by the use of text mining methods. In particular, we investigate the semi-automatic conversion of functions of the statistical environment R into Grid services as implemented by the GridR tool by the generation of appropriate metadata.

  8. An Algorithm of Extracting I-Frame in Compressed Video

    Directory of Open Access Journals (Sweden)

    Zhu Yaling

    2015-01-01

    Full Text Available The MPEG video data includes three types of frames, that is: I-frame, P-frame and B-frame. However, the I-frame records the main information of video data, the P-frame and the B-frame are just regarded as motion compensations of the I-frame. This paper presents the approach which analyzes the MPEG video stream in the compressed domain, and find out the key frame of MPEG video stream by extracting the I-frame. Experiments indicated that this method can be automatically realized in the compressed MPEG video and it will lay the foundation for the video processing in the future.

  9. Figure text extraction in biomedical literature.

    Directory of Open Access Journals (Sweden)

    Daehyun Kim

    Full Text Available BACKGROUND: Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. METHODOLOGY: We first evaluated an off-the-shelf Optical Character Recognition (OCR tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons. RESULTS/CONCLUSIONS: The evaluation on 382 figures (9,643 figure texts in total randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36

  10. User-oriented summary extraction for soccer video based on multimodal analysis

    Science.gov (United States)

    Liu, Huayong; Jiang, Shanshan; He, Tingting

    2011-11-01

    An advanced user-oriented summary extraction method for soccer video is proposed in this work. Firstly, an algorithm of user-oriented summary extraction for soccer video is introduced. A novel approach that integrates multimodal analysis, such as extraction and analysis of the stadium features, moving object features, audio features and text features is introduced. By these features the semantic of the soccer video and the highlight mode are obtained. Then we can find the highlight position and put them together by highlight degrees to obtain the video summary. The experimental results for sports video of world cup soccer games indicate that multimodal analysis is effective for soccer video browsing and retrieval.

  11. Ontology Assisted Formal Specification Extraction from Text

    Directory of Open Access Journals (Sweden)

    Andreea Mihis

    2010-12-01

    Full Text Available In the field of knowledge processing, the ontologies are the most important mean. They make possible for the computer to understand better the natural language and to make judgments. In this paper, a method which use ontologies in the semi-automatic extraction of formal specifications from a natural language text is proposed.

  12. A Unified Framework for Tracking Based Text Detection and Recognition from Web Videos.

    Science.gov (United States)

    Tian, Shu; Yin, Xu-Cheng; Su, Ya; Hao, Hong-Wei

    2017-04-12

    Video text extraction plays an important role for multimedia understanding and retrieval. Most previous research efforts are conducted within individual frames. A few of recent methods, which pay attention to text tracking using multiple frames, however, do not effectively mine the relations among text detection, tracking and recognition. In this paper, we propose a generic Bayesian-based framework of Tracking based Text Detection And Recognition (T2DAR) from web videos for embedded captions, which is composed of three major components, i.e., text tracking, tracking based text detection, and tracking based text recognition. In this unified framework, text tracking is first conducted by tracking-by-detection. Tracking trajectories are then revised and refined with detection or recognition results. Text detection or recognition is finally improved with multi-frame integration. Moreover, a challenging video text (embedded caption text) database (USTB-VidTEXT) is constructed and publicly available. A variety of experiments on this dataset verify that our proposed approach largely improves the performance of text detection and recognition from web videos.

  13. Unsupervised information extraction by text segmentation

    CERN Document Server

    Cortez, Eli

    2013-01-01

    A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors' approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a

  14. Advanced text and video analytics for proactive decision making

    Science.gov (United States)

    Bowman, Elizabeth K.; Turek, Matt; Tunison, Paul; Porter, Reed; Thomas, Steve; Gintautas, Vadas; Shargo, Peter; Lin, Jessica; Li, Qingzhe; Gao, Yifeng; Li, Xiaosheng; Mittu, Ranjeev; Rosé, Carolyn Penstein; Maki, Keith; Bogart, Chris; Choudhari, Samrihdi Shree

    2017-05-01

    Today's warfighters operate in a highly dynamic and uncertain world, and face many competing demands. Asymmetric warfare and the new focus on small, agile forces has altered the framework by which time critical information is digested and acted upon by decision makers. Finding and integrating decision-relevant information is increasingly difficult in data-dense environments. In this new information environment, agile data algorithms, machine learning software, and threat alert mechanisms must be developed to automatically create alerts and drive quick response. Yet these advanced technologies must be balanced with awareness of the underlying context to accurately interpret machine-processed indicators and warnings and recommendations. One promising approach to this challenge brings together information retrieval strategies from text, video, and imagery. In this paper, we describe a technology demonstration that represents two years of tri-service research seeking to meld text and video for enhanced content awareness. The demonstration used multisource data to find an intelligence solution to a problem using a common dataset. Three technology highlights from this effort include 1) Incorporation of external sources of context into imagery normalcy modeling and anomaly detection capabilities, 2) Automated discovery and monitoring of targeted users from social media text, regardless of language, and 3) The concurrent use of text and imagery to characterize behaviour using the concept of kinematic and text motifs to detect novel and anomalous patterns. Our demonstration provided a technology baseline for exploiting heterogeneous data sources to deliver timely and accurate synopses of data that contribute to a dynamic and comprehensive worldview.

  15. Extraction of information from unstructured text

    Energy Technology Data Exchange (ETDEWEB)

    Irwin, N.H.; DeLand, S.M.; Crowder, S.V.

    1995-11-01

    Extracting information from unstructured text has become an emphasis in recent years due to the large amount of text now electronically available. This status report describes the findings and work done by the end of the first year of a two-year LDRD. Requirements of the approach included that it model the information in a domain independent way. This means that it would differ from current systems by not relying on previously built domain knowledge and that it would do more than keyword identification. Three areas that are discussed and expected to contribute to a solution include (1) identifying key entities through document level profiling and preprocessing, (2) identifying relationships between entities through sentence level syntax, and (3) combining the first two with semantic knowledge about the terms.

  16. Terminology extraction from medical texts in Polish.

    Science.gov (United States)

    Marciniak, Małgorzata; Mykowiecka, Agnieszka

    2014-01-01

    Hospital documents contain free text describing the most important facts relating to patients and their illnesses. These documents are written in specific language containing medical terminology related to hospital treatment. Their automatic processing can help in verifying the consistency of hospital documentation and obtaining statistical data. To perform this task we need information on the phrases we are looking for. At the moment, clinical Polish resources are sparse. The existing terminologies, such as Polish Medical Subject Headings (MeSH), do not provide sufficient coverage for clinical tasks. It would be helpful therefore if it were possible to automatically prepare, on the basis of a data sample, an initial set of terms which, after manual verification, could be used for the purpose of information extraction. Using a combination of linguistic and statistical methods for processing over 1200 children hospital discharge records, we obtained a list of single and multiword terms used in hospital discharge documents written in Polish. The phrases are ordered according to their presumed importance in domain texts measured by the frequency of use of a phrase and the variety of its contexts. The evaluation showed that the automatically identified phrases cover about 84% of terms in domain texts. At the top of the ranked list, only 4% out of 400 terms were incorrect while out of the final 200, 20% of expressions were either not domain related or syntactically incorrect. We also observed that 70% of the obtained terms are not included in the Polish MeSH. Automatic terminology extraction can give results which are of a quality high enough to be taken as a starting point for building domain related terminological dictionaries or ontologies. This approach can be useful for preparing terminological resources for very specific subdomains for which no relevant terminologies already exist. The evaluation performed showed that none of the tested ranking procedures were

  17. The efficiency and economy of two learning modes: text with illustration and video with narration.

    Science.gov (United States)

    Gordon, Stuart

    2015-01-01

    The aim of this study was to determine whether video or text was more effective at knowledge transfer and retention. In this study, knowledge transfer with video and text was similar, and text consumed fewer resources to create.

  18. Euclidean Distance Based Classifier for Recognition and Generating Kannada Text Description from Live Sign Language Video

    Directory of Open Access Journals (Sweden)

    Ramesh Mahadev Kagalkar

    2017-10-01

    Full Text Available Sign language recognition has emerged in concert of the vital space of analysis in computer Vision. The problem long-faced by the researchers is that the instances of signs vary with each motion and look. Thus, during this paper a completely unique approach for recognizing varied alphabets of Kannada linguistic communication is projected wherever continuous video sequences of the signs are thought of. The system includes of three stages: Preprocessing stage, Feature Extraction and Classification. Preprocessing stage includes skin filtering, bar histogram matching. Eigen values and Eigen Vectors were thought of for feature extraction stage and at last Eigen value weighted Euclidean distance is employed to acknowledge the sign. It deals with vacant hands, so permitting the user to act with the system in natural manner. We have got thought of completely different alphabets within the video sequences and earned a hit rate of 95.25%.

  19. Text2Video: text-driven facial animation using MPEG-4

    Science.gov (United States)

    Rurainsky, J.; Eisert, P.

    2005-07-01

    We present a complete system for the automatic creation of talking head video sequences from text messages. Our system converts the text into MPEG-4 Facial Animation Parameters and synthetic voice. A user selected 3D character will perform lip movements synchronized to the speech data. The 3D models created from a single image vary from realistic people to cartoon characters. A voice selection for different languages and gender as well as a pitch shift component enables a personalization of the animation. The animation can be shown on different displays and devices ranging from 3GPP players on mobile phones to real-time 3D render engines. Therefore, our system can be used in mobile communication for the conversion of regular SMS messages to MMS animations.

  20. Extracting Conceptual Feature Structures from Text

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik; Lassen, Tine

    2011-01-01

    This paper describes an approach to indexing texts by their conceptual content using ontologies along with lexico-syntactic information and semantic role assignment provided by lexical resources. The conceptual content of meaningful chunks of text is transformed into conceptual feature structures...... and mapped into concepts in a generative ontology. Synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well...

  1. Automatic extraction of angiogenesis bioprocess from text

    Science.gov (United States)

    Wang, Xinglong; McKendrick, Iain; Barrett, Ian; Dix, Ian; French, Tim; Tsujii, Jun'ichi; Ananiadou, Sophia

    2011-01-01

    Motivation: Understanding key biological processes (bioprocesses) and their relationships with constituent biological entities and pharmaceutical agents is crucial for drug design and discovery. One way to harvest such information is searching the literature. However, bioprocesses are difficult to capture because they may occur in text in a variety of textual expressions. Moreover, a bioprocess is often composed of a series of bioevents, where a bioevent denotes changes to one or a group of cells involved in the bioprocess. Such bioevents are often used to refer to bioprocesses in text, which current techniques, relying solely on specialized lexicons, struggle to find. Results: This article presents a range of methods for finding bioprocess terms and events. To facilitate the study, we built a gold standard corpus in which terms and events related to angiogenesis, a key biological process of the growth of new blood vessels, were annotated. Statistics of the annotated corpus revealed that over 36% of the text expressions that referred to angiogenesis appeared as events. The proposed methods respectively employed domain-specific vocabularies, a manually annotated corpus and unstructured domain-specific documents. Evaluation results showed that, while a supervised machine-learning model yielded the best precision, recall and F1 scores, the other methods achieved reasonable performance and less cost to develop. Availability: The angiogenesis vocabularies, gold standard corpus, annotation guidelines and software described in this article are available at http://text0.mib.man.ac.uk/~mbassxw2/angiogenesis/ Contact: xinglong.wang@gmail.com PMID:21821664

  2. A Novel Key-Frame Extraction Approach for Both Video Summary and Video Index

    Science.gov (United States)

    Lei, Shaoshuai; Xie, Gang; Yan, Gaowei

    2014-01-01

    Existing key-frame extraction methods are basically video summary oriented; yet the index task of key-frames is ignored. This paper presents a novel key-frame extraction approach which can be available for both video summary and video index. First a dynamic distance separability algorithm is advanced to divide a shot into subshots based on semantic structure, and then appropriate key-frames are extracted in each subshot by SVD decomposition. Finally, three evaluation indicators are proposed to evaluate the performance of the new approach. Experimental results show that the proposed approach achieves good semantic structure for semantics-based video index and meanwhile produces video summary consistent with human perception. PMID:24757431

  3. Transition logo detection for sports videos highlight extraction

    Science.gov (United States)

    Su, Po-Chyi; Wang, Yu-Wei; Chen, Chien-Chang

    2006-10-01

    This paper presents a highlight extraction scheme for sports videos. The approach makes use of the transition logos inserted preceding and following the slow motion replays by the broadcaster, which demonstrate highlights of the game. First, the features of a MPEG compressed video are retrieved for subsequent processing. After the shot boundary detection procedure, the processing units are formed and the units with fast moving scenes are then selected. Finally, the detection of overlaying objects is performed to signal the appearance of a transition logo. Experimental results show the feasibility of this promising method for sports videos highlight extraction.

  4. Scorebox extraction from mobile sports videos using Support Vector Machines

    Science.gov (United States)

    Kim, Wonjun; Park, Jimin; Kim, Changick

    2008-08-01

    Scorebox plays an important role in understanding contents of sports videos. However, the tiny scorebox may give the small-display-viewers uncomfortable experience in grasping the game situation. In this paper, we propose a novel framework to extract the scorebox from sports video frames. We first extract candidates by using accumulated intensity and edge information after short learning period. Since there are various types of scoreboxes inserted in sports videos, multiple attributes need to be used for efficient extraction. Based on those attributes, the optimal information gain is computed and top three ranked attributes in terms of information gain are selected as a three-dimensional feature vector for Support Vector Machines (SVM) to distinguish the scorebox from other candidates, such as logos and advertisement boards. The proposed method is tested on various videos of sports games and experimental results show the efficiency and robustness of our proposed method.

  5. Text Character Extraction Implementation from Captured Handwritten Image to Text Conversionusing Template Matching Technique

    Directory of Open Access Journals (Sweden)

    Barate Seema

    2016-01-01

    Full Text Available Images contain various types of useful information that should be extracted whenever required. A various algorithms and methods are proposed to extract text from the given image, and by using that user will be able to access the text from any image. Variations in text may occur because of differences in size, style,orientation, alignment of text, and low image contrast, composite backgrounds make the problem during extraction of text. If we develop an application that extracts and recognizes those texts accurately in real time, then it can be applied to many important applications like document analysis, vehicle license plate extraction, text- based image indexing, etc and many applications have become realities in recent years. To overcome the above problems we develop such application that will convert the image into text by using algorithms, such as bounding box, HSV model, blob analysis,template matching, template generation.

  6. Methods for Evaluating Text Extraction Toolkits: An Exploratory Investigation

    Science.gov (United States)

    2015-01-22

    SNAPSHOT extracted “a b c d f”. Borrowing technical terms from the field of corpus linguistics , we would say that the text extracted by Tika 1.5 had 8...Although this effort focuses on the popular open source Apache Tika toolkit and the govdocs1 corpus , the method generally applies to other text...a text extraction toolkit. Although this effort focuses on the popular open source Apache Tika toolkit and the govdocs1 corpus , the method generally

  7. Parallel Key Frame Extraction for Surveillance Video Service in a Smart City.

    Directory of Open Access Journals (Sweden)

    Ran Zheng

    Full Text Available Surveillance video service (SVS is one of the most important services provided in a smart city. It is very important for the utilization of SVS to provide design efficient surveillance video analysis techniques. Key frame extraction is a simple yet effective technique to achieve this goal. In surveillance video applications, key frames are typically used to summarize important video content. It is very important and essential to extract key frames accurately and efficiently. A novel approach is proposed to extract key frames from traffic surveillance videos based on GPU (graphics processing units to ensure high efficiency and accuracy. For the determination of key frames, motion is a more salient feature in presenting actions or events, especially in surveillance videos. The motion feature is extracted in GPU to reduce running time. It is also smoothed to reduce noise, and the frames with local maxima of motion information are selected as the final key frames. The experimental results show that this approach can extract key frames more accurately and efficiently compared with several other methods.

  8. The Relative Efficacy of Video and Text Tutorials in Online Computing Education

    Science.gov (United States)

    Lang, Guido

    2016-01-01

    This study tests the effects of tutorial format (i.e. video vs. text) on student attitudes and performance in online computing education. A one-factor within-subjects experiment was conducted in an undergraduate Computer Information Systems course. Subjects were randomly assigned to complete two Excel exercises online: one with a video tutorial…

  9. Video as Text of Teaching: Toward More Deliberate Literacy Field Experience Supervision

    Science.gov (United States)

    Gelfuso, Andrea; Dennis, Danielle V.

    2017-01-01

    In this article, we theoretically explore how the deliberate use of video during literacy field experiences creates a text that can be read by triad members and can ameliorate the problem of relying on memory to engage in reflective conversations about literacy teaching and learning. The use of video, tools, and interactions with knowledgeable…

  10. Text feature extraction based on deep learning: a review.

    Science.gov (United States)

    Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

    2017-01-01

    Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

  11. Layout-aware text extraction from full-text PDF of scientific articles.

    Science.gov (United States)

    Ramakrishnan, Cartic; Patnia, Abhishek; Hovy, Eduard; Burns, Gully Apc

    2012-05-28

    The Portable Document Format (PDF) is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the 'Layout-Aware PDF Text Extraction' (LA-PDFText) system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1) Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2) Classifying text blocks into rhetorical categories using a rule-based method and (3) Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF. Finally, we discuss preliminary error analysis for

  12. Automatic Statistics Extraction for Amateur Soccer Videos

    NARCIS (Netherlands)

    van Gemert, J.C.; Schavemaker, J.G.M.; Bonenkamp, K.; Spink, A.J.; Loijens, L.W.S.; Woloszynowska-Fraser, M.; Noldus, L.P.J.J.

    2014-01-01

    Amateur soccer statistics have interesting applications such as providing insights to improve team performance, individual coaching, monitoring team progress and personal or team entertainment. Professional soccer statistics are extracted with labor intensive expensive manual effort which is not

  13. Layout-aware text extraction from full-text PDF of scientific articles

    Directory of Open Access Journals (Sweden)

    Ramakrishnan Cartic

    2012-05-01

    Full Text Available Abstract Background The Portable Document Format (PDF is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the ‘Layout-Aware PDF Text Extraction’ (LA-PDFText system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Results Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1 Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2 Classifying text blocks into rhetorical categories using a rule-based method and (3 Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF

  14. Automatic Definition Extraction and Crossword Generation From Spanish News Text

    Directory of Open Access Journals (Sweden)

    Jennifer Esteche

    2017-08-01

    Full Text Available This paper describes the design and implementation of a system that takes Spanish texts and generates crosswords (board and definitions in a fully automatic way using definitions extracted from those texts. Our solution divides the problem in two parts: a definition extraction module that applies pattern matching implemented in Python, and a crossword generation module that uses a greedy strategy implemented in Prolog. The system achieves 73% precision and builds crosswords similar to those built by humans.

  15. PDF text classification to leverage information extraction from publication reports.

    Science.gov (United States)

    Bui, Duy Duc An; Del Fiol, Guilherme; Jonnalagadda, Siddhartha

    2016-06-01

    Data extraction from original study reports is a time-consuming, error-prone process in systematic review development. Information extraction (IE) systems have the potential to assist humans in the extraction task, however majority of IE systems were not designed to work on Portable Document Format (PDF) document, an important and common extraction source for systematic review. In a PDF document, narrative content is often mixed with publication metadata or semi-structured text, which add challenges to the underlining natural language processing algorithm. Our goal is to categorize PDF texts for strategic use by IE systems. We used an open-source tool to extract raw texts from a PDF document and developed a text classification algorithm that follows a multi-pass sieve framework to automatically classify PDF text snippets (for brevity, texts) into TITLE, ABSTRACT, BODYTEXT, SEMISTRUCTURE, and METADATA categories. To validate the algorithm, we developed a gold standard of PDF reports that were included in the development of previous systematic reviews by the Cochrane Collaboration. In a two-step procedure, we evaluated (1) classification performance, and compared it with machine learning classifier, and (2) the effects of the algorithm on an IE system that extracts clinical outcome mentions. The multi-pass sieve algorithm achieved an accuracy of 92.6%, which was 9.7% (pPDF documents. Text classification is an important prerequisite step to leverage information extraction from PDF documents. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Rational kernels for Arabic Root Extraction and Text Classification

    Directory of Open Access Journals (Sweden)

    Attia Nehar

    2016-04-01

    Full Text Available In this paper, we address the problems of Arabic Text Classification and root extraction using transducers and rational kernels. We introduce a new root extraction approach on the basis of the use of Arabic patterns (Pattern Based Stemmer. Transducers are used to model these patterns and root extraction is done without relying on any dictionary. Using transducers for extracting roots, documents are transformed into finite state transducers. This document representation allows us to use and explore rational kernels as a framework for Arabic Text Classification. Root extraction experiments are conducted on three word collections and yield 75.6% of accuracy. Classification experiments are done on the Saudi Press Agency dataset and N-gram kernels are tested with different values of N. Accuracy and F1 report 90.79% and 62.93% respectively. These results show that our approach, when compared with other approaches, is promising specially in terms of accuracy and F1.

  17. Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

    Directory of Open Access Journals (Sweden)

    Gil-beom Lee

    2017-03-01

    Full Text Available Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos.

  18. Information Extraction from Unstructured Text for the Biodefense Knowledge Center

    Energy Technology Data Exchange (ETDEWEB)

    Samatova, N F; Park, B; Krishnamurthy, R; Munavalli, R; Symons, C; Buttler, D J; Cottom, T; Critchlow, T J; Slezak, T

    2005-04-29

    The Bio-Encyclopedia at the Biodefense Knowledge Center (BKC) is being constructed to allow an early detection of emerging biological threats to homeland security. It requires highly structured information extracted from variety of data sources. However, the quantity of new and vital information available from every day sources cannot be assimilated by hand, and therefore reliable high-throughput information extraction techniques are much anticipated. In support of the BKC, Lawrence Livermore National Laboratory and Oak Ridge National Laboratory, together with the University of Utah, are developing an information extraction system built around the bioterrorism domain. This paper reports two important pieces of our effort integrated in the system: key phrase extraction and semantic tagging. Whereas two key phrase extraction technologies developed during the course of project help identify relevant texts, our state-of-the-art semantic tagging system can pinpoint phrases related to emerging biological threats. Also we are enhancing and tailoring the Bio-Encyclopedia by augmenting semantic dictionaries and extracting details of important events, such as suspected disease outbreaks. Some of these technologies have already been applied to large corpora of free text sources vital to the BKC mission, including ProMED-mail, PubMed abstracts, and the DHS's Information Analysis and Infrastructure Protection (IAIP) news clippings. In order to address the challenges involved in incorporating such large amounts of unstructured text, the overall system is focused on precise extraction of the most relevant information for inclusion in the BKC.

  19. Enhancing biomedical text summarization using semantic relation extraction.

    Directory of Open Access Journals (Sweden)

    Yue Shang

    Full Text Available Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1 We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2 We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3 For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

  20. The Impact of Video-Based Materials on Chinese-Speaking Learners' English Text Comprehension

    Science.gov (United States)

    Lin, Lu-Fang

    2016-01-01

    This study investigated whether video-based materials can facilitate second language learners' text comprehension at the levels of macrostructure and microstructure. Three classes inclusive of 98 Chinese-speaking university students joined this study. The three classes were randomly assigned to three treatment groups: on-screen text (T Group),…

  1. Making sense with multimedia. A text theoretical study of a digital format integrating writing and video

    Directory of Open Access Journals (Sweden)

    Martin Engebretsen

    2006-03-01

    Full Text Available Digital text formats that allow a close interaction between writing and video represent new possibilities and challenges for the communication of educational content. What are the premises for functional and appropriate communication through web-based, multimedial text formats?This article explores the digital writing-video format from a structural, theoretical perspective. To begin with, the two media’s respective characteristics are discussed and compared as carriers of complex signs. Thereafter, the focus is upon how writing and video elements can be accommodated to web media. Finally, the article discusses the conditions for optimal co-ordination and interaction between the two media types within the framework of an integrated design. A design example is presented.

  2. Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text

    Science.gov (United States)

    Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.

    2015-12-01

    We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction

  3. Extracting biomedical events from pairs of text entities.

    Science.gov (United States)

    Liu, Xiao; Bordes, Antoine; Grandvalet, Yves

    2015-01-01

    Huge amounts of electronic biomedical documents, such as molecular biology reports or genomic papers are generated daily. Nowadays, these documents are mainly available in the form of unstructured free texts, which require heavy processing for their registration into organized databases. This organization is instrumental for information retrieval, enabling to answer the advanced queries of researchers and practitioners in biology, medicine, and related fields. Hence, the massive data flow calls for efficient automatic methods of text-mining that extract high-level information, such as biomedical events, from biomedical text. The usual computational tools of Natural Language Processing cannot be readily applied to extract these biomedical events, due to the peculiarities of the domain. Indeed, biomedical documents contain highly domain-specific jargon and syntax. These documents also describe distinctive dependencies, making text-mining in molecular biology a specific discipline. We address biomedical event extraction as the classification of pairs of text entities into the classes corresponding to event types. The candidate pairs of text entities are recursively provided to a multiclass classifier relying on Support Vector Machines. This recursive process extracts events involving other events as arguments. Compared to joint models based on Markov Random Fields, our model simplifies inference and hence requires shorter training and prediction times along with lower memory capacity. Compared to usual pipeline approaches, our model passes over a complex intermediate problem, while making a more extensive usage of sophisticated joint features between text entities. Our method focuses on the core event extraction of the Genia task of BioNLP challenges yielding the best result reported so far on the 2013 edition.

  4. Multimodal Semantics Extraction from User-Generated Videos

    Directory of Open Access Journals (Sweden)

    Francesco Cricri

    2012-01-01

    Full Text Available User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order to obtain semantic information about public happenings (e.g., sport and live music events being recorded in these videos. One of the key contributions of this work is a joint utilization of different data modalities, including such captured by auxiliary sensors during the video recording performed by each user. In particular, we analyze GPS data, magnetometer data, accelerometer data, video- and audio-content data. We use these data modalities to infer information about the event being recorded, in terms of layout (e.g., stadium, genre, indoor versus outdoor scene, and the main area of interest of the event. Furthermore we propose a method that automatically identifies the optimal set of cameras to be used in a multicamera video production. Finally, we detect the camera users which fall within the field of view of other cameras recording at the same public happening. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real sport events and live music performances.

  5. Mining knowledge from text repositories using information extraction ...

    Indian Academy of Sciences (India)

    Computational Linguistics, Stroudsburg, PA, USA, pp 66–73. Rose S, Engel D, Cramer N and Cowley W 2010 Automatic keyword extraction from individual document,. Text mining: Application and theory, M W Berry and J Kogan (eds) John Willey & Sons Ltd 2010, pp 3–20. Sánchez D, Martín-Bautista M J and Blanco I 2008 ...

  6. Enhanced root extraction and document classification algorithm for Arabic text

    OpenAIRE

    Alsaad, Amal

    2016-01-01

    This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London Many text extraction and classification systems have been developed for English and other international languages; most of the languages are based on Roman letters. However, Arabic language is one of the difficult languages which have special rules and morphology. Not many systems have been developed for Arabic text categorization. Arabic language is one of the Semitic languages with...

  7. METHOD OF RARE TERM CONTRASTIVE EXTRACTION FROM NATURAL LANGUAGE TEXTS

    Directory of Open Access Journals (Sweden)

    I. A. Bessmertny

    2017-01-01

    Full Text Available The paper considers a problem of automatic domain term extraction from documents corpus by means of a contrast collection. Existing contrastive methods successfully extract often used terms but mishandle rare terms. This could yield poorness of the resulting thesaurus. Assessment of point-wise mutual information is one of the known statistical methods of term extraction and it finds rare terms successfully. Although, it extracts many false terms at that. The proposed approach consists of point-wise mutual information application for rare terms extraction and filtering of candidates by criterion of joint occurrence with the other candidates. We build “documents-by-terms” matrix that is subjected to singular value decomposition to eliminate noise and reveal strong interconnections. Then we pass on to the resulting matrix “terms-by-terms” that reproduces strength of interconnections between words. This approach was approved on a documents collection from “Geology” domain with the use of contrast documents from such topics as “Politics”, “Culture”, “Economics” and “Accidents” on some Internet resources. The experimental results demonstrate operability of this method for rare terms extraction.

  8. Semantic-driven Generation of Hyperlapse from 360[Formula: see text] Video.

    Science.gov (United States)

    Lai, Wei-Sheng; Huang, Yujia; Joshi, Neel; Buehler, Christopher; Yang, Ming-Hsuan; Kang, Sing Bing

    2017-09-11

    We present a system for converting a fully panoramic (360[Formula: see text]) video into a normal field-of-view (NFOV) hyperlapse for an optimal viewing experience. Our system exploits visual saliency and semantics to non-uniformly sample in space and time for generating hyperlapses. In addition, users can optionally choose objects of interest for customizing the hyperlapses. We first stabilize an input 360[Formula: see text] video by smoothing the rotation between adjacent frames and then compute regions of interest and saliency scores. An initial hyperlapse is generated by optimizing the saliency and motion smoothness followed by the saliency-aware frame selection. We further smooth the result using an efficient 2D video stabilization approach that adaptively selects the motion model to generate the final hyperlapse. We validate the design of our system by showing results for a variety of scenes and comparing against the state-of-the-art method through a large-scale user study.

  9. The Impact of Text versus Video Communication on Instructor Feedback in Blended Courses

    Science.gov (United States)

    Borup, Jered; West, Richard E.; Thomas, Rebecca

    2015-01-01

    In this study we examined student and instructor perceptions of text and video feedback in technology integration courses that combined face-to-face with online instruction for teacher candidates. Items from the Feedback Environment Scale (Steelman et al. 2004) were used to measure student perceptions of feedback quality and delivery. Independent…

  10. Using Text Mining to Uncover Students' Technology-Related Problems in Live Video Streaming

    Science.gov (United States)

    Abdous, M'hammed; He, Wu

    2011-01-01

    Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streaming (LVS) students' technology related-problems and to…

  11. Web text corpus extraction system for linguistic tasks

    Directory of Open Access Journals (Sweden)

    Héctor Fabio Cadavid Rengifo

    2010-05-01

    Full Text Available Internet content, used as text corpus for natural language learning, offers important characteristics for such task, like its huge vo- lume, being permanently up-to-date with linguistic variants and having low time and resource costs regarding the traditional way that text is built for natural language machine learning tasks. This paper describes a system for the automatic extraction of large bodies of text from the Internet as a valuable tool for such learning tasks. A concurrent programming-based, hardware-use opti- misation strategy significantly improving extraction performance is also presented. The strategies incorporated into the system for maximising hardware resource exploitation, thereby reducing extraction time are presented, as are extendibility (supporting digi- tal-content formats and adaptability (regarding how the system cleanses content for obtaining pure natural language samples. The experimental results obtained after processing one of the biggest Spanish domains on the internet, are presented (i.e. es.wikipedia.org. Such results are used for presenting initial conclusions about the validity and applicability of corpus directly ex- tracted from Internet as morphological or syntactical learning input.

  12. Students' Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video

    DEFF Research Database (Denmark)

    Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte

    2017-01-01

    OBJECTIVES: The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students....... Students taught with video-based patient cases, in contrast, often referred to the patient cases when highlighting new insights, including the importance of patient perspectives when communicating with patients. CONCLUSION: The format of patient cases included in teaching may have a substantial impact...

  13. NAMED ENTITY RECOGNITION FROM BIOMEDICAL TEXT -AN INFORMATION EXTRACTION TASK

    Directory of Open Access Journals (Sweden)

    N. Kanya

    2016-07-01

    Full Text Available Biomedical Text Mining targets the Extraction of significant information from biomedical archives. Bio TM encompasses Information Retrieval (IR and Information Extraction (IE. The Information Retrieval will retrieve the relevant Biomedical Literature documents from the various Repositories like PubMed, MedLine etc., based on a search query. The IR Process ends up with the generation of corpus with the relevant document retrieved from the Publication databases based on the query. The IE task includes the process of Preprocessing of the document, Named Entity Recognition (NER from the documents and Relationship Extraction. This process includes Natural Language Processing, Data Mining techniques and machine Language algorithm. The preprocessing task includes tokenization, stop word Removal, shallow parsing, and Parts-Of-Speech tagging. NER phase involves recognition of well-defined objects such as genes, proteins or cell-lines etc. This process leads to the next phase that is extraction of relationships (IE. The work was based on machine learning algorithm Conditional Random Field (CRF.

  14. Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction

    Directory of Open Access Journals (Sweden)

    Darko Brodić

    2010-05-01

    Full Text Available Text line segmentation is an essential stage in off-line optical character recognition (OCR systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms.

  15. Using Text Mining for Unsupervised Knowledge Extraction and Organization

    Directory of Open Access Journals (Sweden)

    REZENDE, S. O.

    2011-06-01

    Full Text Available The progress in digitally generated data aquisition and storage has allowed for a huge growth in information generated in organizations. Around 80% ofthose data are created in non structured format and a significant part of those are texts. Intelligent organization of those textual collection is a matter of interest for most organizations, for it speed up information search and retrieval. In this context, Text Mining can transform this great amount non structure text data un useful knowledge, that can even be innovative for those organizations. Using unsupervised methods for knowledge extraction and organization has received great attention in literature, because it does not require previous knowledge on the textual collections that are going to be explored. In this article we describe the main techniques and algorithms used for unsupervised knowledege extraction and organization from textual data. The most relevant works in literature are presented and discussed in each phase of the Text Mining process and some existing computational tools are suggested for each task at hand. At last, some examples and applications are present to show the use of Text Mining on real problems.

  16. Extracting BI-RADS Features from Portuguese Clinical Texts

    Science.gov (United States)

    Nassif, Houssam; Cunha, Filipe; Moreira, Inês C.; Cruz-Correia, Ricardo; Sousa, Eliana; Page, David; Burnside, Elizabeth; Dutra, Inês

    2013-01-01

    In this work we build the first BI-RADS parser for Portuguese free texts, modeled after existing approaches to extract BI-RADS features from English medical records. Our concept finder uses a semantic grammar based on the BIRADS lexicon and on iterative transferred expert knowledge. We compare the performance of our algorithm to manual annotation by a specialist in mammography. Our results show that our parser’s performance is comparable to the manual method. PMID:23797461

  17. Basic test framework for the evaluation of text line segmentation and text parameter extraction.

    Science.gov (United States)

    Brodić, Darko; Milivojević, Dragan R; Milivojević, Zoran

    2010-01-01

    Text line segmentation is an essential stage in off-line optical character recognition (OCR) systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms.

  18. Automatic extraction of ontological relations from Arabic text

    Directory of Open Access Journals (Sweden)

    Mohammed G.H. Al Zamil

    2014-12-01

    The proposed methodology has been designed to analyze Arabic text using lexical semantic patterns of the Arabic language according to a set of features. Next, the features have been abstracted and enriched with formal descriptions for the purpose of generalizing the resulted rules. The rules, then, have formulated a classifier that accepts Arabic text, analyzes it, and then displays related concepts labeled with its designated relationship. Moreover, to resolve the ambiguity of homonyms, a set of machine translation, text mining, and part of speech tagging algorithms have been reused. We performed extensive experiments to measure the effectiveness of our proposed tools. The results indicate that our proposed methodology is promising for automating the process of extracting ontological relations.

  19. Detecting and extracting identifiable information from vehicles in videos

    Science.gov (United States)

    Roheda, Siddharth; Kalva, Hari; Naik, Mehul

    2015-03-01

    This paper presents a system to detect and extract identifiable information such as license plates, make, model, color, and bumper stickers present on vehicles. The goal of this work is to develop a system that automatically describes a vehicle just as a person would. This information can be used to improve traffic surveillance systems. The presented solution relies on efficient segmentation and structure of license plates to identify and extract information from vehicles. The system was evaluated on videos captures on Florida highways and is expected to work in other regions with little or no modifications. Results show that license plate was successfully segmented 92% of the cases, the make and the model of the car were segmented out and in 93% of the cases and bumper stickers were segmented in 92.5% of the cases. Over all recognition accuracy was 87%.

  20. Automatic extraction of relations between medical concepts in clinical texts.

    Science.gov (United States)

    Rink, Bryan; Harabagiu, Sanda; Roberts, Kirk

    2011-01-01

    A supervised machine learning approach to discover relations between medical problems, treatments, and tests mentioned in electronic medical records. A single support vector machine classifier was used to identify relations between concepts and to assign their semantic type. Several resources such as Wikipedia, WordNet, General Inquirer, and a relation similarity metric inform the classifier. The techniques reported in this paper were evaluated in the 2010 i2b2 Challenge and obtained the highest F1 score for the relation extraction task. When gold standard data for concepts and assertions were available, F1 was 73.7, precision was 72.0, and recall was 75.3. F1 is defined as 2*Precision*Recall/(Precision+Recall). Alternatively, when concepts and assertions were discovered automatically, F1 was 48.4, precision was 57.6, and recall was 41.7. Although a rich set of features was developed for the classifiers presented in this paper, little knowledge mining was performed from medical ontologies such as those found in UMLS. Future studies should incorporate features extracted from such knowledge sources, which we expect to further improve the results. Moreover, each relation discovery was treated independently. Joint classification of relations may further improve the quality of results. Also, joint learning of the discovery of concepts, assertions, and relations may also improve the results of automatic relation extraction. Lexical and contextual features proved to be very important in relation extraction from medical texts. When they are not available to the classifier, the F1 score decreases by 3.7%. In addition, features based on similarity contribute to a decrease of 1.1% when they are not available.

  1. Domain-independent information extraction in unstructured text

    Energy Technology Data Exchange (ETDEWEB)

    Irwin, N.H. [Sandia National Labs., Albuquerque, NM (United States). Software Surety Dept.

    1996-09-01

    Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.

  2. Unsupervised Learning of mDTD Extraction Patterns for Web Text Mining.

    Science.gov (United States)

    Kim, Dongseok; Jung, Hanmin; Lee, Gary Geunbae

    2003-01-01

    Presents a new extraction pattern, modified Document Type Definition (mDTD), which relies on analytical interpretation to identify extraction target from the contents of Web documents. Experiments with 330 Korean and 220 English Web documents on audio and video shopping sites yielded an average extraction precision of 91.3% for Korean and 81.9%…

  3. Automated Extraction of Substance Use Information from Clinical Texts.

    Science.gov (United States)

    Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

    2015-01-01

    Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

  4. Text Mining approaches for automated literature knowledge extraction and representation.

    Science.gov (United States)

    Nuzzo, Angelo; Mulas, Francesca; Gabetta, Matteo; Arbustini, Eloisa; Zupan, Blaz; Larizza, Cristiana; Bellazzi, Riccardo

    2010-01-01

    Due to the overwhelming volume of published scientific papers, information tools for automated literature analysis are essential to support current biomedical research. We have developed a knowledge extraction tool to help researcher in discovering useful information which can support their reasoning process. The tool is composed of a search engine based on Text Mining and Natural Language Processing techniques, and an analysis module which process the search results in order to build annotation similarity networks. We tested our approach on the available knowledge about the genetic mechanism of cardiac diseases, where the target is to find both known and possible hypothetical relations between specific candidate genes and the trait of interest. We show that the system i) is able to effectively retrieve medical concepts and genes and ii) plays a relevant role assisting researchers in the formulation and evaluation of novel literature-based hypotheses.

  5. Feature Extraction in IR Images Via Synchronous Video Detection

    Science.gov (United States)

    Shepard, Steven M.; Sass, David T.

    1989-03-01

    IR video images acquired by scanning imaging radiometers are subject to several problems which make measurement of small temperature differences difficult. Among these problems are 1) aliasing, which occurs When events at frequencies higher than the video frame rate are observed, 2) limited temperature resolution imposed by the 3-bit digitization available in existing commercial systems, and 3) susceptibility to noise and background clutter. Bandwidth narrowing devices (e.g. lock-in amplifiers or boxcar averagers) are routinely used to achieve a high degree of signal to noise improvement for time-varying 1-dimensional signals. We will describe techniques which allow similar S/N improvement for 2-dimensional imagery acquired with an off the shelf scanning imaging radiometer system. These techniques are iplemented in near-real-time, utilizing a microcomputer and specially developed hardware and software . We will also discuss the application of the system to feature extraction in cluttered images, and to acquisition of events which vary faster than the frame rate.

  6. Using Semantic Linking to Understand Persons’ Networks Extracted from Text

    Directory of Open Access Journals (Sweden)

    Alessio Palmero Aprosio

    2017-11-01

    Full Text Available In this work, we describe a methodology to interpret large persons’ networks extracted from text by classifying cliques using the DBpedia ontology. The approach relies on a combination of NLP, Semantic web technologies, and network analysis. The classification methodology that first starts from single nodes and then generalizes to cliques is effective in terms of performance and is able to deal also with nodes that are not linked to Wikipedia. The gold standard manually developed for evaluation shows that groups of co-occurring entities share in most of the cases a category that can be automatically assigned. This holds for both languages considered in this study. The outcome of this work may be of interest to enhance the readability of large networks and to provide an additional semantic layer on top of cliques. This would greatly help humanities scholars when dealing with large amounts of textual data that need to be interpreted or categorized. Furthermore, it represents an unsupervised approach to automatically extend DBpedia starting from a corpus.

  7. Unsupervised Extraction of Diagnosis Codes from EMRs Using Knowledge-Based and Extractive Text Summarization Techniques.

    Science.gov (United States)

    Kavuluru, Ramakanth; Han, Sifei; Harris, Daniel

    2013-05-01

    Diagnosis codes are extracted from medical records for billing and reimbursement and for secondary uses such as quality control and cohort identification. In the US, these codes come from the standard terminology ICD-9-CM derived from the international classification of diseases (ICD). ICD-9 codes are generally extracted by trained human coders by reading all artifacts available in a patient's medical record following specific coding guidelines. To assist coders in this manual process, this paper proposes an unsupervised ensemble approach to automatically extract ICD-9 diagnosis codes from textual narratives included in electronic medical records (EMRs). Earlier attempts on automatic extraction focused on individual documents such as radiology reports and discharge summaries. Here we use a more realistic dataset and extract ICD-9 codes from EMRs of 1000 inpatient visits at the University of Kentucky Medical Center. Using named entity recognition (NER), graph-based concept-mapping of medical concepts, and extractive text summarization techniques, we achieve an example based average recall of 0.42 with average precision 0.47; compared with a baseline of using only NER, we notice a 12% improvement in recall with the graph-based approach and a 7% improvement in precision using the extractive text summarization approach. Although diagnosis codes are complex concepts often expressed in text with significant long range non-local dependencies, our present work shows the potential of unsupervised methods in extracting a portion of codes. As such, our findings are especially relevant for code extraction tasks where obtaining large amounts of training data is difficult.

  8. Extracting Useful Semantic Information from Large Scale Corpora of Text

    Science.gov (United States)

    Mendoza, Ray Padilla, Jr.

    2012-01-01

    Extracting and representing semantic information from large scale corpora is at the crux of computer-assisted knowledge generation. Semantic information depends on collocation extraction methods, mathematical models used to represent distributional information, and weighting functions which transform the space. This dissertation provides a…

  9. Preserving color fidelity for display devices using scalable memory compression architecture for text, graphics, and video

    Science.gov (United States)

    Lebowsky, Fritz; Nicolas, Marina

    2014-01-01

    High-end monitors and TVs based on LCD technology continue to increase their native display resolution to 4k by 2k and beyond. Subsequently, uncompressed pixel amplitude processing becomes costly not only when transmitting over cable or wireless communication channels, but also when processing with array processor architectures. For motion video content, spatial preprocessing from YCbCr 444 to YCbCr 420 is widely accepted. However, due to spatial low pass filtering in horizontal and vertical direction, quality and readability of small text and graphics content is heavily compromised when color contrast is high in chrominance channels. On the other hand, straight forward YCbCr 444 compression based on mathematical error coding schemes quite often lacks optimal adaptation to visually significant image content. We present a block-based memory compression architecture for text, graphics, and video enabling multidimensional error minimization with context sensitive control of visually noticeable artifacts. As a result of analyzing image context locally, the number of operations per pixel can be significantly reduced, especially when implemented on array processor architectures. A comparative analysis based on some competitive solutions highlights the effectiveness of our approach, identifies its current limitations with regard to high quality color rendering, and illustrates remaining visual artifacts.

  10. Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video.

    Science.gov (United States)

    Lee, Gil-Beom; Lee, Myeong-Jin; Lee, Woo-Kyung; Park, Joo-Heon; Kim, Tae-Hwan

    2017-03-22

    Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object's vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos.

  11. Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction

    OpenAIRE

    Darko Brodić; Milivojević, Dragan R.; Zoran Milivojević

    2010-01-01

    Text line segmentation is an essential stage in off-line optical character recognition (OCR) systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, som...

  12. Extracting Temporal Information from Open Domain Text: A Comparative Exploration

    NARCIS (Netherlands)

    Ahn, D.D.; Fissaha Adafre, S.; de Rijke, M.

    2005-01-01

    The utility of data-driven techniques in the end-to-end problem of temporal information extraction is unclear. Recognition of temporal expressions yields readily to machine learning, but normalization seems to call for a rule-based approach. We explore two aspects of the (potential) utility of

  13. Extraction of Relations between Entities from Texts by Learning Methods

    Science.gov (United States)

    2006-12-01

    Tasks, in Proceedings of the Eleventh National Conference on Artificial Intelligence, 811-816. AAAI Press / The MIT Press . Rohmer J. (2002...pour une extraction d’informations sur le web dédiées à la veille . Réalisation du système informatique JavaVeille. PhD Thesis, Université Paris 4

  14. Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

    Science.gov (United States)

    Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

    2012-04-01

    In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

  15. Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

    Directory of Open Access Journals (Sweden)

    Ebrahimi Touradj

    2004-01-01

    Full Text Available The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into low-level and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one “sees” in a scene depends on the scene itself (region segmentation as well as on the cognitive task (semantic segmentation at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an -dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to cope with multiple

  16. Temporal and spatial information extraction from videos based on the change in length of the shadow

    Science.gov (United States)

    Wang, Jiayun; Zu, Jian; Wang, Likang

    2017-03-01

    In this paper, considering the atmospheric refractive index, we present an approach to extract the recording date and geo-location from videos, based on the alteration of the shadow length. The paper carefully takes different information (photographed date, the length of the selected object) of the given video into consideration and forms a comprehensive approach to extract the temporal and spatial information of the given video. On the basis of this approach, we analyze the shadow length data of a chosen object from a real video and extract the temporal and spatial information of the video. Compared with the actual information, the error is less than 1%, which proves the validity of our approach.

  17. Texting

    Science.gov (United States)

    Tilley, Carol L.

    2009-01-01

    With the increasing ranks of cell phone ownership is an increase in text messaging, or texting. During 2008, more than 2.5 trillion text messages were sent worldwide--that's an average of more than 400 messages for every person on the planet. Although many of the messages teenagers text each day are perhaps nothing more than "how r u?" or "c u…

  18. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

    Directory of Open Access Journals (Sweden)

    Florian Eyben

    Full Text Available Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

  19. A COMPREHENSIVE STUDY ON TEXT INFORMATION EXTRACTION FROM NATURAL SCENE IMAGES

    Directory of Open Access Journals (Sweden)

    Anit V. Manjaly

    2016-08-01

    Full Text Available In Text Information Extraction (TIE process, the text regions are localized and extracted from the images. It is an active research problem in computer vision applications. Diversity in text is due to the differences in size, style, orientation, alignment of text, low image contrast and complex backgrounds. The semantic information provided by an image can be used in different applications such as content based image retrieval, sign board identification etc. Text information extraction comprises of text image classification, text detection, localization, segmentation, enhancement and recognition. This paper contains a quick review on various text localization methods for localizing texts from natural scene images.

  20. Effects of Explicit Instruction and Self-Directed Video Prompting on Text Comprehension of Students with Autism Spectrum Disorder

    Science.gov (United States)

    Sartini, Emily Claire

    2016-01-01

    The purpose of this study was to investigate the effects of explicit instruction combined with video prompting to teach text comprehension skills to students with autism spectrum disorder. Participants included 4 elementary school students with autism. A multiple probe across participants design was used to evaluate the intervention's…

  1. A Comparison of Video Modeling, Text-Based Instruction, and No Instruction for Creating Multiple Baseline Graphs in Microsoft Excel

    Science.gov (United States)

    Tyner, Bryan C.; Fienup, Daniel M.

    2015-01-01

    Graphing is socially significant for behavior analysts; however, graphing can be difficult to learn. Video modeling (VM) may be a useful instructional method but lacks evidence for effective teaching of computer skills. A between-groups design compared the effects of VM, text-based instruction, and no instruction on graphing performance.…

  2. Text extraction method for historical Tibetan document images based on block projections

    Science.gov (United States)

    Duan, Li-juan; Zhang, Xi-qun; Ma, Long-long; Wu, Jian

    2017-11-01

    Text extraction is an important initial step in digitizing the historical documents. In this paper, we present a text extraction method for historical Tibetan document images based on block projections. The task of text extraction is considered as text area detection and location problem. The images are divided equally into blocks and the blocks are filtered by the information of the categories of connected components and corner point density. By analyzing the filtered blocks' projections, the approximate text areas can be located, and the text regions are extracted. Experiments on the dataset of historical Tibetan documents demonstrate the effectiveness of the proposed method.

  3. Supporting Reporting: On the Positive Effects of Text- and Video-Based Awareness Material on Responsible Journalistic Suicide News Writing.

    Science.gov (United States)

    Scherr, Sebastian; Arendt, Florian; Schäfer, Markus

    2017-01-01

    Suicide is a global public health problem. Media impact on suicide is well confirmed and there are several recommendations on how media should and should not report on suicide to minimize the risk of copycat behavior. Those media guidelines have been developed to improve responsible reporting on suicide (RRS). Although such guidelines are used in several countries, we lack empirical evidence on their causal effect on actual journalistic news writing. We conducted an experiment with journalism students (N = 78) in Germany in which we tested whether exposure to awareness material promoting RRS influences news writing. As a supplement to the widely used text-based material, we tested the impact of a video in which a suicide expert presents the guidelines. A video was used as a supplement to text partly due to its potential benefit for prevention efforts over the Internet. We chose a low-budget production process allowing easy reproduction in different countries by local suicide experts. In the experiment, participants were either exposed to written, audio-visual, or no awareness material. Afterwards, participants read numerous facts of an ostensible suicide event and were asked to write a factual suicide news story based on these facts. Analyses indicate that awareness material exposure helped to improve RRS with the awareness video showing the strongest effects. We recommend that suicide prevention should use instructive awareness videos about RRS complementary to text-based awareness material.

  4. Extracting foreground ensemble features to detect abnormal crowd behavior in intelligent video-surveillance systems

    Science.gov (United States)

    Chan, Yi-Tung; Wang, Shuenn-Jyi; Tsai, Chung-Hsien

    2017-09-01

    Public safety is a matter of national security and people's livelihoods. In recent years, intelligent video-surveillance systems have become important active-protection systems. A surveillance system that provides early detection and threat assessment could protect people from crowd-related disasters and ensure public safety. Image processing is commonly used to extract features, e.g., people, from a surveillance video. However, little research has been conducted on the relationship between foreground detection and feature extraction. Most current video-surveillance research has been developed for restricted environments, in which the extracted features are limited by having information from a single foreground; they do not effectively represent the diversity of crowd behavior. This paper presents a general framework based on extracting ensemble features from the foreground of a surveillance video to analyze a crowd. The proposed method can flexibly integrate different foreground-detection technologies to adapt to various monitored environments. Furthermore, the extractable representative features depend on the heterogeneous foreground data. Finally, a classification algorithm is applied to these features to automatically model crowd behavior and distinguish an abnormal event from normal patterns. The experimental results demonstrate that the proposed method's performance is both comparable to that of state-of-the-art methods and satisfies the requirements of real-time applications.

  5. Impact of Interactive Video Communication Versus Text-Based Feedback on Teaching, Social, and Cognitive Presence in Online Learning Communities.

    Science.gov (United States)

    Seckman, Charlotte

    A key element to online learning is the ability to create a sense of presence to improve learning outcomes. This quasi-experimental study evaluated the impact of interactive video communication versus text-based feedback and found a significant difference between the 2 groups related to teaching, social, and cognitive presence. Recommendations to enhance presence should focus on providing timely feedback, interactive learning experiences, and opportunities for students to establish relationships with peers and faculty.

  6. Tagline: Information Extraction for Semi-Structured Text Elements in Medical Progress Notes

    Science.gov (United States)

    Finch, Dezon Kile

    2012-01-01

    Text analysis has become an important research activity in the Department of Veterans Affairs (VA). Statistical text mining and natural language processing have been shown to be very effective for extracting useful information from medical documents. However, neither of these techniques is effective at extracting the information stored in…

  7. CHARACTER RECOGNITION OF VIDEO SUBTITLES\\

    Directory of Open Access Journals (Sweden)

    Satish S Hiremath

    2016-11-01

    Full Text Available An important task in content based video indexing is to extract text information from videos. The challenges involved in text extraction and recognition are variation of illumination on each video frame with text, the text present on the complex background and different font size of the text. Using various image processing algorithms like morphological operations, blob detection and histogram of oriented gradients the character recognition of video subtitles is implemented. Segmentation, feature extraction and classification are the major steps of character recognition. Several experimental results are shown to demonstrate the performance of the proposed algorithm

  8. Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries (Open Access)

    Science.gov (United States)

    2014-09-05

    boundary. We 6 RAZA ET AL.: DEPTH EXTRACTION FROM VIDEOS assume a pinhole camera with no lens distortion. A 3D point in world coordinate is pro- jected...blue) to 80m (red). and glass buildings can have error in ground truth depth due to velodyne limitation. More- over, occlusion boundary prediction

  9. Students’ Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video: A Qualitative Study

    DEFF Research Database (Denmark)

    Pedersen, Kamilla; Holdgaard, Martin Møller; Paltved, Charlotte

    2017-01-01

    on students' patient-centeredness. Video-based patient cases are probably more effective than text-based patient cases in fostering patient-centered perspectives in medical students. Teachers sharing stories from their own clinical experiences stimulates both engagement and excitement, but may also provoke......' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. METHODS: The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed....... Students taught with video-based patient cases, in contrast, often referred to the patient cases when highlighting new insights, including the importance of patient perspectives when communicating with patients. CONCLUSION: The format of patient cases included in teaching may have a substantial impact...

  10. BioFoV - An open platform for forensic video analysis and biometric data extraction

    DEFF Research Database (Denmark)

    Almeida, Miguel; Correia, Paulo Lobato; Larsen, Peter Kastmand

    2016-01-01

    to tailor-made software, based on state of art knowledge in fields such as soft biometrics, gait recognition, photogrammetry, etc. This paper proposes an open and extensible platform, BioFoV (Biometric Forensic Video tool), for forensic video analysis and biometric data extraction, aiming to host some...... of the developments that researchers come up with for solving specific problems, but that are often not shared with the community. BioFoV includes a simple to use Graphical User Interface (GUI), is implemented with open software that can run in multiple software platforms, and its implementation is publicly available....

  11. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

    Directory of Open Access Journals (Sweden)

    Abdul Wahab Muzaffar

    2015-01-01

    Full Text Available The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

  12. A survey of event extraction methods from text for decision support systems

    NARCIS (Netherlands)

    Hoogenboom, F.P.; Frasincar, Flavius; Kaymak, Uzay; de Jong, Franciska; Caron, E.A.M.

    2016-01-01

    Event extraction, a specialized stream of information extraction rooted back into the 1980s, has greatly gained in popularity due to the advent of big data and the developments in the related fields of text mining and natural language processing. However, up to this date, an overview of this

  13. Video to Text (V2T) in Wide Area Motion Imagery

    Science.gov (United States)

    2015-09-01

    microtext) or a document (e.g., using Sphinx or Apache NLP ) as an automated approach [102]. Previous work in natural language full-text searching...language processing ( NLP ) based module. The heart of the structured text processing module includes the following seven key word banks...Features Tracker MHT Multiple Hypothesis Tracking MIL Multiple Instance Learning NLP Natural Language Processing OAB Online AdaBoost OF Optic Flow

  14. INTER-LINE DISTANCE ESTIMATION AND TEXT LINE EXTRACTION FOR UNCONSTRAINED ONLINE HANDWRITING

    NARCIS (Netherlands)

    Ratzlaff, E.

    2004-01-01

    Methods for detecting and extracting whole text lines from unconstrained online handwritten text are described. The general approach is a ``bottom-up'' clustering of discrete strokes into small groups that are then merged into isolated lines of text. Initial clustering of strokes into groups is

  15. Big data extraction with adaptive wavelet analysis (Presentation Video)

    Science.gov (United States)

    Qu, Hongya; Chen, Genda; Ni, Yiqing

    2015-04-01

    Nondestructive evaluation and sensing technology have been increasingly applied to characterize material properties and detect local damage in structures. More often than not, they generate images or data strings that are difficult to see any physical features without novel data extraction techniques. In the literature, popular data analysis techniques include Short-time Fourier Transform, Wavelet Transform, and Hilbert Transform for time efficiency and adaptive recognition. In this study, a new data analysis technique is proposed and developed by introducing an adaptive central frequency of the continuous Morlet wavelet transform so that both high frequency and time resolution can be maintained in a time-frequency window of interest. The new analysis technique is referred to as Adaptive Wavelet Analysis (AWA). This paper will be organized in several sections. In the first section, finite time-frequency resolution limitations in the traditional wavelet transform are introduced. Such limitations would greatly distort the transformed signals with a significant frequency variation with time. In the second section, Short Time Wavelet Transform (STWT), similar to Short Time Fourier Transform (STFT), is defined and developed to overcome such shortcoming of the traditional wavelet transform. In the third section, by utilizing the STWT and a time-variant central frequency of the Morlet wavelet, AWA can adapt the time-frequency resolution requirement to the signal variation over time. Finally, the advantage of the proposed AWA is demonstrated in Section 4 with a ground penetrating radar (GPR) image from a bridge deck, an analytical chirp signal with a large range sinusoidal frequency change over time, the train-induced acceleration responses of the Tsing-Ma Suspension Bridge in Hong Kong, China. The performance of the proposed AWA will be compared with the STFT and traditional wavelet transform.

  16. Extracting Concepts Related to Homelessness from the Free Text of VA Electronic Medical Records.

    Science.gov (United States)

    Gundlapalli, Adi V; Carter, Marjorie E; Divita, Guy; Shen, Shuying; Palmer, Miland; South, Brett; Durgahee, B S Begum; Redd, Andrew; Samore, Matthew

    2014-01-01

    Mining the free text of electronic medical records (EMR) using natural language processing (NLP) is an effective method of extracting information not always captured in administrative data. We sought to determine if concepts related to homelessness, a non-medical condition, were amenable to extraction from the EMR of Veterans Affairs (VA) medical records. As there were no off-the-shelf products, a lexicon of terms related to homelessness was created. A corpus of free text documents from outpatient encounters was reviewed to create the reference standard for NLP training and testing. V3NLP Framework was used to detect instances of lexical terms and was compared to the reference standard. With a positive predictive value of 77% for extracting relevant concepts, this study demonstrates the feasibility of extracting positively asserted concepts related to homelessness from the free text of medical records.

  17. Automatic Extraction of Drug Adverse Effects from Product Characteristics (SPCs): A Text Versus Table Comparison.

    Science.gov (United States)

    Lamy, Jean-Baptiste; Ugon, Adrien; Berthelot, Hélène

    2016-01-01

    Potential adverse effects (AEs) of drugs are described in their summary of product characteristics (SPCs), a textual document. Automatic extraction of AEs from SPCs is useful for detecting AEs and for building drug databases. However, this task is difficult because each AE is associated with a frequency that must be extracted and the presentation of AEs in SPCs is heterogeneous, consisting of plain text and tables in many different formats. We propose a taxonomy for the presentation of AEs in SPCs. We set up natural language processing (NLP) and table parsing methods for extracting AEs from texts and tables of any format, and evaluate them on 10 SPCs. Automatic extraction performed better on tables than on texts. Tables should be recommended for the presentation of the AEs section of the SPCs.

  18. Mode extraction on wind turbine blades via phase-based video motion estimation

    Science.gov (United States)

    Sarrafi, Aral; Poozesh, Peyman; Niezrecki, Christopher; Mao, Zhu

    2017-04-01

    In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

  19. Extracting of implicit information in English advertising texts with phonetic and lexical-morphological means

    Directory of Open Access Journals (Sweden)

    Traikovskaya Natalya Petrovna

    2015-12-01

    Full Text Available The article deals with phonetic and lexical-morphological language means participating in the process of extracting implicit information in English-speaking advertising texts for men and women. The functioning of phonetic means of the English language is not the basis for implication of information in advertising texts. Lexical and morphological means play the role of markers of relevant information, playing the role of the activator ofimplicit information in the texts of advertising.

  20. Knowledge Extraction and Semantic Annotation of Text from the Encyclopedia of Life

    OpenAIRE

    Anne E Thessen; Cynthia Sims Parr

    2014-01-01

    Numerous digitization and ontological initiatives have focused on translating biological knowledge from narrative text to machine-readable formats. In this paper, we describe two workflows for knowledge extraction and semantic annotation of text data objects featured in an online biodiversity aggregator, the Encyclopedia of Life. One workflow tags text with DBpedia URIs based on keywords. Another workflow finds taxon names in text using GNRD for the purpose of building a species association n...

  1. Extracting Hierarchical Structure of Web Video Groups Based on Sentiment-Aware Signed Network Analysis

    OpenAIRE

    Harakawa, Ryosuke; Ogawa, Takahiro; Haseyama, Miki

    2017-01-01

    Sentiment in multimedia contents has an influence on their topics, since multimedia contents are tools for social media users to convey their sentiment. Performance of applications such as retrieval and recommendation will be improved if sentiment in multimedia contents can be estimated; however, there have been few works in which such applications were realized by utilizing sentiment analysis. In this paper, a novel method for extracting the hierarchical structure of Web video groups based o...

  2. A Survey of Neural Network Techniques for Feature Extraction from Text

    OpenAIRE

    John, Vineet

    2017-01-01

    This paper aims to catalyze the discussions about text feature extraction techniques using neural network architectures. The research questions discussed in the paper focus on the state-of-the-art neural network techniques that have proven to be useful tools for language processing, language generation, text classification and other computational linguistics tasks.

  3. An automatic system to detect and extract texts in medical images for de-identification

    Science.gov (United States)

    Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

    2010-03-01

    Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

  4. A concept-driven biomedical knowledge extraction and visualization framework for conceptualization of text corpora.

    Science.gov (United States)

    Jahiruddin; Abulaish, Muhammad; Dey, Lipika

    2010-12-01

    A number of techniques such as information extraction, document classification, document clustering and information visualization have been developed to ease extraction and understanding of information embedded within text documents. However, knowledge that is embedded in natural language texts is difficult to extract using simple pattern matching techniques and most of these methods do not help users directly understand key concepts and their semantic relationships in document corpora, which are critical for capturing their conceptual structures. The problem arises due to the fact that most of the information is embedded within unstructured or semi-structured texts that computers can not interpret very easily. In this paper, we have presented a novel Biomedical Knowledge Extraction and Visualization framework, BioKEVis to identify key information components from biomedical text documents. The information components are centered on key concepts. BioKEVis applies linguistic analysis and Latent Semantic Analysis (LSA) to identify key concepts. The information component extraction principle is based on natural language processing techniques and semantic-based analysis. The system is also integrated with a biomedical named entity recognizer, ABNER, to tag genes, proteins and other entity names in the text. We have also presented a method for collating information extracted from multiple sources to generate semantic network. The network provides distinct user perspectives and allows navigation over documents with similar information components and is also used to provide a comprehensive view of the collection. The system stores the extracted information components in a structured repository which is integrated with a query-processing module to handle biomedical queries over text documents. We have also proposed a document ranking mechanism to present retrieved documents in order of their relevance to the user query. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. A neural joint model for entity and relation extraction from biomedical text.

    Science.gov (United States)

    Li, Fei; Zhang, Meishan; Fu, Guohong; Ji, Donghong

    2017-03-31

    Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

  6. An unsupervised text mining method for relation extraction from biomedical literature.

    Directory of Open Access Journals (Sweden)

    Changqin Quan

    Full Text Available The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1 Protein-protein interactions extraction, and (2 Gene-suicide association extraction. The evaluation of task (1 on the benchmark dataset (AImed corpus showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on gene-suicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method.

  7. Using Gazetteers to Extract Sets of Keywords from Free-Flowing Texts

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    Adam Crymble

    2015-12-01

    Full Text Available If you have a copy of a text in electronic format stored on your computer, it is relatively easy to keyword search for a single term. Often you can do this by using the built-in search features in your favourite text editor. However, scholars are increasingly needing to find instances of many terms within a text or texts. For example, a scholar may want to use a gazetteer to extract all mentions of English placenames within a collection of texts so that those places can later be plotted on a map. Alternatively, they may want to extract all male given names, all pronouns, stop words, or any other set of words. Using those same built-in search features to achieve this more complex goal is time consuming and clunky. This lesson will teach you how to use Python to extract a set of keywords very quickly and systematically from a set of texts. It is expected that once you have completed this lesson, you will be able to generalise the skills to extract custom sets of keywords from any set of locally saved files.

  8. Text mining facilitates database curation - extraction of mutation-disease associations from Bio-medical literature.

    Science.gov (United States)

    Ravikumar, Komandur Elayavilli; Wagholikar, Kavishwar B; Li, Dingcheng; Kocher, Jean-Pierre; Liu, Hongfang

    2015-06-06

    Advances in the next generation sequencing technology has accelerated the pace of individualized medicine (IM), which aims to incorporate genetic/genomic information into medicine. One immediate need in interpreting sequencing data is the assembly of information about genetic variants and their corresponding associations with other entities (e.g., diseases or medications). Even with dedicated effort to capture such information in biological databases, much of this information remains 'locked' in the unstructured text of biomedical publications. There is a substantial lag between the publication and the subsequent abstraction of such information into databases. Multiple text mining systems have been developed, but most of them focus on the sentence level association extraction with performance evaluation based on gold standard text annotations specifically prepared for text mining systems. We developed and evaluated a text mining system, MutD, which extracts protein mutation-disease associations from MEDLINE abstracts by incorporating discourse level analysis, using a benchmark data set extracted from curated database records. MutD achieves an F-measure of 64.3% for reconstructing protein mutation disease associations in curated database records. Discourse level analysis component of MutD contributed to a gain of more than 10% in F-measure when compared against the sentence level association extraction. Our error analysis indicates that 23 of the 64 precision errors are true associations that were not captured by database curators and 68 of the 113 recall errors are caused by the absence of associated disease entities in the abstract. After adjusting for the defects in the curated database, the revised F-measure of MutD in association detection reaches 81.5%. Our quantitative analysis reveals that MutD can effectively extract protein mutation disease associations when benchmarking based on curated database records. The analysis also demonstrates that incorporating

  9. Structured learning for spatial information extraction from biomedical text: bacteria biotopes.

    Science.gov (United States)

    Kordjamshidi, Parisa; Roth, Dan; Moens, Marie-Francine

    2015-04-25

    We aim to automatically extract species names of bacteria and their locations from webpages. This task is important for exploiting the vast amount of biological knowledge which is expressed in diverse natural language texts and putting this knowledge in databases for easy access by biologists. The task is challenging and the previous results are far below an acceptable level of performance, particularly for extraction of localization relationships. Therefore, we aim to design a new system for such extractions, using the framework of structured machine learning techniques. We design a new model for joint extraction of biomedical entities and the localization relationship. Our model is based on a spatial role labeling (SpRL) model designed for spatial understanding of unrestricted text. We extend SpRL to extract discourse level spatial relations in the biomedical domain and apply it on the BioNLP-ST 2013, BB-shared task. We highlight the main differences between general spatial language understanding and spatial information extraction from the scientific text which is the focus of this work. We exploit the text's structure and discourse level global features. Our model and the designed features substantially improve on the previous systems, achieving an absolute improvement of approximately 57 percent over F1 measure of the best previous system for this task. Our experimental results indicate that a joint learning model over all entities and relationships in a document outperforms a model which extracts entities and relationships independently. Our global learning model significantly improves the state-of-the-art results on this task and has a high potential to be adopted in other natural language processing (NLP) tasks in the biomedical domain.

  10. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus

    Science.gov (United States)

    2015-01-01

    Background Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. Methods To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Results Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. Conclusions PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our

  11. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus.

    Science.gov (United States)

    Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

    2015-01-01

    Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our annotation is currently limited to a single

  12. The Giles Ecosystem – Storage, Text Extraction, and OCR of Documents

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    Julia Damerow

    2017-09-01

    Full Text Available In the digital humanities, there is a constant need to turn images and PDF files into plain text to apply analyses such as topic modelling, named entity recognition, and other techniques. However, although there exist different solutions to extract text embedded in PDF files or run OCR on images, they typically require additional training (for example, scholars have to learn how to use the command line or are difficult to automate without programming skills. The Giles Ecosystem is a distributed system based on Apache Kafka that allows users to upload documents for text and image extraction. The system components are implemented using Java and the Spring Framework and are available under an Open Source license on GitHub (https://github.com/diging/. Funding statement: Funding was provided by grants from NSF SES 1656284, ASU Presidential Strategic Initiative Fund and the Smart Family Foundation.

  13. Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) final report

    Energy Technology Data Exchange (ETDEWEB)

    Kegelmeyer, Philip W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shead, Timothy M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dunlavy, Daniel M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2013-09-01

    This SAND report summarizes the activities and outcomes of the Network and Ensemble Enabled Entity Extraction in Information Text (NEEEEIT) LDRD project, which addressed improving the accuracy of conditional random fields for named entity recognition through the use of ensemble methods.

  14. A Comparison of Multiple Approaches for the Extractive Summarization of Portuguese Texts

    OpenAIRE

    Miguel Ângelo Abrantes Costa; Bruno Martins

    2015-01-01

    Automatic document summarization is the task of automatically generating condensed versions of source texts, presenting itself as one of the fundamental problems in the areas of Information Retrieval and Natural Language Processing. In this paper, different extractive approaches are compared in the task of summarizing individual documents corresponding to journalistic texts written in Portuguese. Through the use of the ROUGE package for measuring the quality of the produced summaries, we repo...

  15. Discovery of Predicate-Oriented Relations among Named Entities Extracted from Thai Texts

    Science.gov (United States)

    Tongtep, Nattapong; Theeramunkong, Thanaruk

    Extracting named entities (NEs) and their relations is more difficult in Thai than in other languages due to several Thai specific characteristics, including no explicit boundaries for words, phrases and sentences; few case markers and modifier clues; high ambiguity in compound words and serial verbs; and flexible word orders. Unlike most previous works which focused on NE relations of specific actions, such as work_for, live_in, located_in, and kill, this paper proposes more general types of NE relations, called predicate-oriented relation (PoR), where an extracted action part (verb) is used as a core component to associate related named entities extracted from Thai Texts. Lacking a practical parser for the Thai language, we present three types of surface features, i.e. punctuation marks (such as token spaces), entity types and the number of entities and then apply five alternative commonly used learning schemes to investigate their performance on predicate-oriented relation extraction. The experimental results show that our approach achieves the F-measure of 97.76%, 99.19%, 95.00% and 93.50% on four different types of predicate-oriented relation (action-location, location-action, action-person and person-action) in crime-related news documents using a data set of 1,736 entity pairs. The effects of NE extraction techniques, feature sets and class unbalance on the performance of relation extraction are explored.

  16. Extracting Various Classes of Data From Biological Text Using the Concept of Existence Dependency.

    Science.gov (United States)

    Taha, Kamal

    2015-11-01

    One of the key goals of biological natural language processing (NLP) is the automatic information extraction from biomedical publications. Most current constituency and dependency parsers overlook the semantic relationships between the constituents comprising a sentence and may not be well suited for capturing complex long-distance dependences. We propose in this paper a hybrid constituency-dependency parser for biological NLP information extraction called EDCC. EDCC aims at enhancing the state of the art of biological text mining by applying novel linguistic computational techniques that overcome the limitations of current constituency and dependency parsers outlined earlier, as follows: 1) it determines the semantic relationship between each pair of constituents in a sentence using novel semantic rules; and 2) it applies a semantic relationship extraction model that extracts information from different structural forms of constituents in sentences. EDCC can be used to extract different types of data from biological texts for purposes such as protein function prediction, genetic network construction, and protein-protein interaction detection. We evaluated the quality of EDCC by comparing it experimentally with six systems. Results showed marked improvement.

  17. Vaccine adverse event text mining system for extracting features from vaccine safety reports.

    Science.gov (United States)

    Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

    2012-01-01

    To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

  18. A language independent acronym extraction from biomedical texts with hidden Markov models.

    Science.gov (United States)

    Osiek, Bruno Adam; Xexeo, Gexéo; Vidal de Carvalho, Luis Alfredo

    2010-11-01

    This paper proposes to model the extraction of acronyms and their meaning from unstructured text as a stochastic process using Hidden Markov Models (HMM). The underlying, or hidden, chain is derived from the acronym where the states in the chain are made by the acronyms characters. The transition between two states happens when the origin state emits a signal. Signals recognizable by the HMM are tokens extracted from text. Observations are sequence of tokens also extracted from text. Given a set of observations, the acronym definition will be the observation with the highest probability to emerge from the HMM. Modelling this extraction probabilistically allows us to deal with two difficult aspects of this process: ambiguity and noise. We characterize ambiguity when there is no unique alignment between a character in the acronym with a token in the expansion while the feature characterizing noise is the absence of such alignment. Our experiments have proven that this approach has high precision (93.50%) and recall (85.50%) rates in an environment where acronym coinage is ambiguous and noisy such as the biomedical domain. Processing and comparing the HMM approach with different ones, showed ours to reach the highest F1 score (89.40%) on the same corpus.

  19. Automatic extraction of gene/protein biological functions from biomedical text.

    Science.gov (United States)

    Koike, Asako; Niwa, Yoshiki; Takagi, Toshihisa

    2005-04-01

    With the rapid advancement of biomedical science and the development of high-throughput analysis methods, the extraction of various types of information from biomedical text has become critical. Since automatic functional annotations of genes are quite useful for interpreting large amounts of high-throughput data efficiently, the demand for automatic extraction of information related to gene functions from text has been increasing. We have developed a method for automatically extracting the biological process functions of genes/protein/families based on Gene Ontology (GO) from text using a shallow parser and sentence structure analysis techniques. When the gene/protein/family names and their functions are described in ACTOR (doer of action) and OBJECT (receiver of action) relationships, the corresponding GO-IDs are assigned to the genes/proteins/families. The gene/protein/family names are recognized using the gene/protein/family name dictionaries developed by our group. To achieve wide recognition of the gene/protein/family functions, we semi-automatically gather functional terms based on GO using co-occurrence, collocation similarities and rule-based techniques. A preliminary experiment demonstrated that our method has an estimated recall of 54-64% with a precision of 91-94% for actually described functions in abstracts. When applied to the PUBMED, it extracted over 190 000 gene-GO relationships and 150 000 family-GO relationships for major eukaryotes.

  20. Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

    Science.gov (United States)

    Liang, Yu-Li

    Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

  1. Information extraction from full text scientific articles: Where are the keywords?

    Directory of Open Access Journals (Sweden)

    Perez-Iratxeta Carolina

    2003-05-01

    Full Text Available Abstract Background To date, many of the methods for information extraction of biological information from scientific articles are restricted to the abstract of the article. However, full text articles in electronic version, which offer larger sources of data, are currently available. Several questions arise as to whether the effort of scanning full text articles is worthy, or whether the information that can be extracted from the different sections of an article can be relevant. Results In this work we addressed those questions showing that the keyword content of the different sections of a standard scientific article (abstract, introduction, methods, results, and discussion is very heterogeneous. Conclusions Although the abstract contains the best ratio of keywords per total of words, other sections of the article may be a better source of biologically relevant data.

  2. Medical Student and Tutor Perceptions of Video Versus Text in an Interactive Online Virtual Patient for Problem-Based Learning: A Pilot Study.

    Science.gov (United States)

    Woodham, Luke A; Ellaway, Rachel H; Round, Jonathan; Vaughan, Sophie; Poulton, Terry; Zary, Nabil

    2015-06-18

    The impact of the use of video resources in primarily paper-based problem-based learning (PBL) settings has been widely explored. Although it can provide many benefits, the use of video can also hamper the critical thinking of learners in contexts where learners are developing clinical reasoning. However, the use of video has not been explored in the context of interactive virtual patients for PBL. A pilot study was conducted to explore how undergraduate medical students interpreted and evaluated information from video- and text-based materials presented in the context of a branched interactive online virtual patient designed for PBL. The goal was to inform the development and use of virtual patients for PBL and to inform future research in this area. An existing virtual patient for PBL was adapted for use in video and provided as an intervention to students in the transition year of the undergraduate medicine course at St George's, University of London. Survey instruments were used to capture student and PBL tutor experiences and perceptions of the intervention, and a formative review meeting was run with PBL tutors. Descriptive statistics were generated for the structured responses and a thematic analysis was used to identify emergent themes in the unstructured responses. Analysis of student responses (n=119) and tutor comments (n=18) yielded 8 distinct themes relating to the perceived educational efficacy of information presented in video and text formats in a PBL context. Although some students found some characteristics of the videos beneficial, when asked to express a preference for video or text the majority of those that responded to the question (65%, 65/100) expressed a preference for text. Student responses indicated that the use of video slowed the pace of PBL and impeded students' ability to review and critically appraise the presented information. Our findings suggest that text was perceived to be a better source of information than video in virtual

  3. Medical Student and Tutor Perceptions of Video Versus Text in an Interactive Online Virtual Patient for Problem-Based Learning: A Pilot Study

    Science.gov (United States)

    Ellaway, Rachel H; Round, Jonathan; Vaughan, Sophie; Poulton, Terry; Zary, Nabil

    2015-01-01

    Background The impact of the use of video resources in primarily paper-based problem-based learning (PBL) settings has been widely explored. Although it can provide many benefits, the use of video can also hamper the critical thinking of learners in contexts where learners are developing clinical reasoning. However, the use of video has not been explored in the context of interactive virtual patients for PBL. Objective A pilot study was conducted to explore how undergraduate medical students interpreted and evaluated information from video- and text-based materials presented in the context of a branched interactive online virtual patient designed for PBL. The goal was to inform the development and use of virtual patients for PBL and to inform future research in this area. Methods An existing virtual patient for PBL was adapted for use in video and provided as an intervention to students in the transition year of the undergraduate medicine course at St George’s, University of London. Survey instruments were used to capture student and PBL tutor experiences and perceptions of the intervention, and a formative review meeting was run with PBL tutors. Descriptive statistics were generated for the structured responses and a thematic analysis was used to identify emergent themes in the unstructured responses. Results Analysis of student responses (n=119) and tutor comments (n=18) yielded 8 distinct themes relating to the perceived educational efficacy of information presented in video and text formats in a PBL context. Although some students found some characteristics of the videos beneficial, when asked to express a preference for video or text the majority of those that responded to the question (65%, 65/100) expressed a preference for text. Student responses indicated that the use of video slowed the pace of PBL and impeded students’ ability to review and critically appraise the presented information. Conclusions Our findings suggest that text was perceived to be a

  4. COMPOSITIONAL AND CONTENT-RELATED PARTICULARITIES OF POLITICAL MEDIA TEXTS (THROUGH THE EXAMPLE OF THE TEXTS OF POLITICAL VIDEO CLIPS ISSUED BY THE CANDIDATES FOR PRESIDENCY IN FRANCE IN 2017

    Directory of Open Access Journals (Sweden)

    Dmitrieva, A.V.

    2017-09-01

    Full Text Available The article examines the texts of political advertising video clips issued by the candidates for presidency in France during the campaign before the first round of elections in 2017. The mentioned examples of media texts are analysed from the compositional point of view as well as from that of the content particularities which are directly connected to the text structure. In general, the majority of the studied clips have a similar structure and consist of three parts: introduction, main part and conclusion. However, as a result of the research, a range of advantages marking well-structured videos was revealed. These include: addressing the voters and stating the speech topic clearly at the beginning of the clip, a relevant attention-grabbing opening phrase, consistency and clarity of the information presentation, appropriate use of additional video plots, conclusion at the end of the clip.

  5. Verbal methods of realisation of addresser-addressee relations in French political media texts (through the example of the texts of political videos issued by the candidates for the French 2017 presidential election

    Directory of Open Access Journals (Sweden)

    Dmitrieva Anastasia Valerievna

    2017-10-01

    Full Text Available The article deals with the addresser-addressee relations in the texts of French political advertising video clips from the verbal, textual point of view. The texts of video clips issued by the candidates for the French 2017 presidential election during the first round of the campaign serve as the material for this article. The aim of the article is to determine how the candidates (i.e. the addressers effectuate their relations with the voters (i.e. the addressees in the texts of their videos. As a result, a range of rhetorical methods were used by the candidates allowing them to attract maximum attention of the target audience. It makes the addressees trust the addresser and provide the desired perlocutionary effect.

  6. Effectiveness of a Video-Versus Text-Based Computer-Tailored Intervention for Obesity Prevention after One Year: A Randomized Controlled Trial

    Directory of Open Access Journals (Sweden)

    Kei Long Cheung

    2017-10-01

    Full Text Available Computer-tailored programs may help to prevent overweight and obesity, which are worldwide public health problems. This study investigated (1 the 12-month effectiveness of a video- and text-based computer-tailored intervention on energy intake, physical activity, and body mass index (BMI, and (2 the role of educational level in intervention effects. A randomized controlled trial in The Netherlands was conducted, in which adults were allocated to a video-based condition, text-based condition, or control condition, with baseline, 6 months, and 12 months follow-up. Outcome variables were self-reported BMI, physical activity, and energy intake. Mixed-effects modelling was used to investigate intervention effects and potential interaction effects. Compared to the control group, the video intervention group was effective regarding energy intake after 6 months (least squares means (LSM difference = −205.40, p = 0.00 and 12 months (LSM difference = −128.14, p = 0.03. Only video intervention resulted in lower average daily energy intake after one year (d = 0.12. Educational role and BMI did not seem to interact with this effect. No intervention effects on BMI and physical activity were found. The video computer-tailored intervention was effective on energy intake after one year. This effect was not dependent on educational levels or BMI categories, suggesting that video tailoring can be effective for a broad range of risk groups and may be preferred over text tailoring.

  7. The Fractal Patterns of Words in a Text: A Method for Automatic Keyword Extraction.

    Science.gov (United States)

    Najafi, Elham; Darooneh, Amir H

    2015-01-01

    A text can be considered as a one dimensional array of words. The locations of each word type in this array form a fractal pattern with certain fractal dimension. We observe that important words responsible for conveying the meaning of a text have dimensions considerably different from one, while the fractal dimensions of unimportant words are close to one. We introduce an index quantifying the importance of the words in a given text using their fractal dimensions and then ranking them according to their importance. This index measures the difference between the fractal pattern of a word in the original text relative to a shuffled version. Because the shuffled text is meaningless (i.e., words have no importance), the difference between the original and shuffled text can be used to ascertain degree of fractality. The degree of fractality may be used for automatic keyword detection. Words with the degree of fractality higher than a threshold value are assumed to be the retrieved keywords of the text. We measure the efficiency of our method for keywords extraction, making a comparison between our proposed method and two other well-known methods of automatic keyword extraction.

  8. Extracting salient sublexical units from written texts: "Emophon," a corpus-based approach to phonological iconicity.

    Science.gov (United States)

    Aryani, Arash; Jacobs, Arthur M; Conrad, Markus

    2013-01-01

    A GROWING BODY OF LITERATURE IN PSYCHOLOGY, LINGUISTICS, AND THE NEUROSCIENCES HAS PAID INCREASING ATTENTION TO THE UNDERSTANDING OF THE RELATIONSHIPS BETWEEN PHONOLOGICAL REPRESENTATIONS OF WORDS AND THEIR MEANING: a phenomenon also known as phonological iconicity. In this article, we investigate how a text's intended emotional meaning, particularly in literature and poetry, may be reflected at the level of sublexical phonological salience and the use of foregrounded elements. To extract such elements from a given text, we developed a probabilistic model to predict the exceeding of a confidence interval for specific sublexical units concerning their frequency of occurrence within a given text contrasted with a reference linguistic corpus for the German language. Implementing this model in a computational application, we provide a text analysis tool which automatically delivers information about sublexical phonological salience allowing researchers, inter alia, to investigate effects of the sublexical emotional tone of texts based on current findings on phonological iconicity.

  9. Knowledge extraction and semantic annotation of text from the encyclopedia of life.

    Science.gov (United States)

    Thessen, Anne E; Parr, Cynthia Sims

    2014-01-01

    Numerous digitization and ontological initiatives have focused on translating biological knowledge from narrative text to machine-readable formats. In this paper, we describe two workflows for knowledge extraction and semantic annotation of text data objects featured in an online biodiversity aggregator, the Encyclopedia of Life. One workflow tags text with DBpedia URIs based on keywords. Another workflow finds taxon names in text using GNRD for the purpose of building a species association network. Both workflows work well: the annotation workflow has an F1 Score of 0.941 and the association algorithm has an F1 Score of 0.885. Existing text annotators such as Terminizer and DBpedia Spotlight performed well, but require some optimization to be useful in the ecology and evolution domain. Important future work includes scaling up and improving accuracy through the use of distributional semantics.

  10. DiMeX: A Text Mining System for Mutation-Disease Association Extraction.

    Science.gov (United States)

    Mahmood, A S M Ashique; Wu, Tsung-Jung; Mazumder, Raja; Vijay-Shanker, K

    2016-01-01

    The number of published articles describing associations between mutations and diseases is increasing at a fast pace. There is a pressing need to gather such mutation-disease associations into public knowledge bases, but manual curation slows down the growth of such databases. We have addressed this problem by developing a text-mining system (DiMeX) to extract mutation to disease associations from publication abstracts. DiMeX consists of a series of natural language processing modules that preprocess input text and apply syntactic and semantic patterns to extract mutation-disease associations. DiMeX achieves high precision and recall with F-scores of 0.88, 0.91 and 0.89 when evaluated on three different datasets for mutation-disease associations. DiMeX includes a separate component that extracts mutation mentions in text and associates them with genes. This component has been also evaluated on different datasets and shown to achieve state-of-the-art performance. The results indicate that our system outperforms the existing mutation-disease association tools, addressing the low precision problems suffered by most approaches. DiMeX was applied on a large set of abstracts from Medline to extract mutation-disease associations, as well as other relevant information including patient/cohort size and population data. The results are stored in a database that can be queried and downloaded at http://biotm.cis.udel.edu/dimex/. We conclude that this high-throughput text-mining approach has the potential to significantly assist researchers and curators to enrich mutation databases.

  11. Improving the extraction of complex regulatory events from scientific text by using ontology-based inference

    Directory of Open Access Journals (Sweden)

    Kim Jung-jae

    2011-10-01

    Full Text Available Abstract Background The extraction of complex events from biomedical text is a challenging task and requires in-depth semantic analysis. Previous approaches associate lexical and syntactic resources with ontologies for the semantic analysis, but fall short in testing the benefits from the use of domain knowledge. Results We developed a system that deduces implicit events from explicitly expressed events by using inference rules that encode domain knowledge. We evaluated the system with the inference module on three tasks: First, when tested against a corpus with manually annotated events, the inference module of our system contributes 53.2% of correct extractions, but does not cause any incorrect results. Second, the system overall reproduces 33.1% of the transcription regulatory events contained in RegulonDB (up to 85.0% precision and the inference module is required for 93.8% of the reproduced events. Third, we applied the system with minimum adaptations to the identification of cell activity regulation events, confirming that the inference improves the performance of the system also on this task. Conclusions Our research shows that the inference based on domain knowledge plays a significant role in extracting complex events from text. This approach has great potential in recognizing the complex concepts of such biomedical ontologies as Gene Ontology in the literature.

  12. Extracting and connecting chemical structures from text sources using chemicalize.org.

    Science.gov (United States)

    Southan, Christopher; Stracz, Andras

    2013-04-23

    Exploring bioactive chemistry requires navigating between structures and data from a variety of text-based sources. While PubChem currently includes approximately 16 million document-extracted structures (15 million from patents) the extent of public inter-document and document-to-database links is still well below any estimated total, especially for journal articles. A major expansion in access to text-entombed chemistry is enabled by chemicalize.org. This on-line resource can process IUPAC names, SMILES, InChI strings, CAS numbers and drug names from pasted text, PDFs or URLs to generate structures, calculate properties and launch searches. Here, we explore its utility for answering questions related to chemical structures in documents and where these overlap with database records. These aspects are illustrated using a common theme of Dipeptidyl Peptidase 4 (DPPIV) inhibitors. Full-text open URL sources facilitated the download of over 1400 structures from a DPPIV patent and the alignment of specific examples with IC50 data. Uploading the SMILES to PubChem revealed extensive linking to patents and papers, including prior submissions from chemicalize.org as submitting source. A DPPIV medicinal chemistry paper was completely extracted and structures were aligned to the activity results table, as well as linked to other documents via PubChem. In both cases, key structures with data were partitioned from common chemistry by dividing them into individual new PDFs for conversion. Over 500 structures were also extracted from a batch of PubMed abstracts related to DPPIV inhibition. The drug structures could be stepped through each text occurrence and included some converted MeSH-only IUPAC names not linked in PubChem. Performing set intersections proved effective for detecting compounds-in-common between documents and merged extractions. This work demonstrates the utility of chemicalize.org for the exploration of chemical structure connectivity between documents and

  13. Knowledge-based extraction of adverse drug events from biomedical text.

    Science.gov (United States)

    Kang, Ning; Singh, Bharat; Bui, Chinh; Afzal, Zubair; van Mulligen, Erik M; Kors, Jan A

    2014-03-04

    Many biomedical relation extraction systems are machine-learning based and have to be trained on large annotated corpora that are expensive and cumbersome to construct. We developed a knowledge-based relation extraction system that requires minimal training data, and applied the system for the extraction of adverse drug events from biomedical text. The system consists of a concept recognition module that identifies drugs and adverse effects in sentences, and a knowledge-base module that establishes whether a relation exists between the recognized concepts. The knowledge base was filled with information from the Unified Medical Language System. The performance of the system was evaluated on the ADE corpus, consisting of 1644 abstracts with manually annotated adverse drug events. Fifty abstracts were used for training, the remaining abstracts were used for testing. The knowledge-based system obtained an F-score of 50.5%, which was 34.4 percentage points better than the co-occurrence baseline. Increasing the training set to 400 abstracts improved the F-score to 54.3%. When the system was compared with a machine-learning system, jSRE, on a subset of the sentences in the ADE corpus, our knowledge-based system achieved an F-score that is 7 percentage points higher than the F-score of jSRE trained on 50 abstracts, and still 2 percentage points higher than jSRE trained on 90% of the corpus. A knowledge-based approach can be successfully used to extract adverse drug events from biomedical text without need for a large training set. Whether use of a knowledge base is equally advantageous for other biomedical relation-extraction tasks remains to be investigated.

  14. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

    Science.gov (United States)

    Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

    2013-01-01

    Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

  15. Extraction of V-N-Collocations from Text Corpora A Feasibility Study for German

    CERN Document Server

    Breidt, E

    1996-01-01

    The usefulness of a statistical approach suggested by Church et al. (1991) is evaluated for the extraction of verb-noun (V-N) collocations from German text corpora. Some problematic issues of that method arising from properties of the German language are discussed and various modifications of the method are considered that might improve extraction results for German. The precision and recall of all variant methods is evaluated for V-N collocations containing support verbs, and the consequences for further work on the extraction of collocations from German corpora are discussed. With a sufficiently large corpus (>= 6 mio. word-tokens), the average error rate of wrong extractions can be reduced to 2.2% (97.8% precision) with the most restrictive method, however with a loss in data of almost 50% compared to a less restrictive method with still 87.6% precision. Depending on the goal to be achieved, emphasis can be put on a high recall for lexicographic purposes or on high precision for automatic lexical acquisiti...

  16. The Boy Who Learned To Read Through Sustained Video Game Play: Considering Systemic Resistance To The Use Of New Texts In The Classroom

    Directory of Open Access Journals (Sweden)

    Rochelle SKOGEN

    2012-12-01

    Full Text Available Various studies have discussed the pedagogical potential of video game play in the classroom but resistance to such texts remains high. The study presented here discusses the case study of one young boy who, having failed to learn to read in the public school system was able to learn in a private Sudbury model school where video games were not only allowed but considered important learning tools. Findings suggest that the incorporation of such new texts in today’s public schools have the potential to motivate and enhance the learning of children.

  17. Linking genes to literature: text mining, information extraction, and retrieval applications for biology.

    Science.gov (United States)

    Krallinger, Martin; Valencia, Alfonso; Hirschman, Lynette

    2008-01-01

    Efficient access to information contained in online scientific literature collections is essential for life science research, playing a crucial role from the initial stage of experiment planning to the final interpretation and communication of the results. The biological literature also constitutes the main information source for manual literature curation used by expert-curated databases. Following the increasing popularity of web-based applications for analyzing biological data, new text-mining and information extraction strategies are being implemented. These systems exploit existing regularities in natural language to extract biologically relevant information from electronic texts automatically. The aim of the BioCreative challenge is to promote the development of such tools and to provide insight into their performance. This review presents a general introduction to the main characteristics and applications of currently available text-mining systems for life sciences in terms of the following: the type of biological information demands being addressed; the level of information granularity of both user queries and results; and the features and methods commonly exploited by these applications. The current trend in biomedical text mining points toward an increasing diversification in terms of application types and techniques, together with integration of domain-specific resources such as ontologies. Additional descriptions of some of the systems discussed here are available on the internet http://zope.bioinfo.cnio.es/bionlp_tools/.

  18. Complex Biological Event Extraction from Full Text using Signatures of Linguistic and Semantic Features

    Energy Technology Data Exchange (ETDEWEB)

    McGrath, Liam R.; Domico, Kelly O.; Corley, Courtney D.; Webb-Robertson, Bobbie-Jo M.

    2011-06-24

    Building on technical advances from the BioNLP 2009 Shared Task Challenge, the 2011 challenge sets forth to generalize techniques to other complex biological event extraction tasks. In this paper, we present the implementation and evaluation of a signature-based machine-learning technique to predict events from full texts of infectious disease documents. Specifically, our approach uses novel signatures composed of traditional linguistic features and semantic knowledge to predict event triggers and their candidate arguments. Using a leave-one out analysis, we report the contribution of linguistic and shallow semantic features in the trigger prediction and candidate argument extraction. Lastly, we examine evaluations and posit causes for errors of infectious disease track subtasks.

  19. tmVar: a text mining approach for extracting sequence variants in biomedical literature.

    Science.gov (United States)

    Wei, Chih-Hsuan; Harris, Bethany R; Kao, Hung-Yu; Lu, Zhiyong

    2013-06-01

    Text-mining mutation information from the literature becomes a critical part of the bioinformatics approach for the analysis and interpretation of sequence variations in complex diseases in the post-genomic era. It has also been used for assisting the creation of disease-related mutation databases. Most of existing approaches are rule-based and focus on limited types of sequence variations, such as protein point mutations. Thus, extending their extraction scope requires significant manual efforts in examining new instances and developing corresponding rules. As such, new automatic approaches are greatly needed for extracting different kinds of mutations with high accuracy. Here, we report tmVar, a text-mining approach based on conditional random field (CRF) for extracting a wide range of sequence variants described at protein, DNA and RNA levels according to a standard nomenclature developed by the Human Genome Variation Society. By doing so, we cover several important types of mutations that were not considered in past studies. Using a novel CRF label model and feature set, our method achieves higher performance than a state-of-the-art method on both our corpus (91.4 versus 78.1% in F-measure) and their own gold standard (93.9 versus 89.4% in F-measure). These results suggest that tmVar is a high-performance method for mutation extraction from biomedical literature. tmVar software and its corpus of 500 manually curated abstracts are available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/pub/tmVar

  20. Interdisciplinary Approach to the Mental Lexicon: Neural Network and Text Extraction From Long-term Memory

    Directory of Open Access Journals (Sweden)

    Vardan G. Arutyunyan

    2013-01-01

    Full Text Available The paper touches upon the principles of mental lexicon organization in the light of recent research in psycho- and neurolinguistics. As a focal point of discussion two main approaches to mental lexicon functioning are considered: modular or dual-system approach, developed within generativism and opposite single-system approach, representatives of which are the connectionists and supporters of network models. The paper is an endeavor towards advocating the viewpoint that mental lexicon is complex psychological organization based upon specific composition of neural network. In this regard, the paper further elaborates on the matter of storing text in human mental space and introduces a model of text extraction from long-term memory. Based upon data available, the author develops a methodology of modeling structures of knowledge representation in the systems of artificial intelligence.

  1. A Comparison of Multiple Approaches for the Extractive Summarization of Portuguese Texts

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    Miguel Ângelo Abrantes Costa

    2015-07-01

    Full Text Available Automatic document summarization is the task of automatically generating condensed versions of source texts, presenting itself as one of the fundamental problems in the areas of Information Retrieval and Natural Language Processing. In this paper, different extractive approaches are compared in the task of summarizing individual documents corresponding to journalistic texts written in Portuguese. Through the use of the ROUGE package for measuring the quality of the produced summaries, we report on results for two different experimental domains, involving (i the generation of headlines for news articles written in European Portuguese, and (ii the generation of summaries for news articles written in Brazilian Portuguese. The results demonstrate that methods based on the selection of the first sentences have the best results  when building extractive news headlines in terms of several ROUGE metrics. Regarding the generation of summaries with more than one sentence, the method that achieved the best results was the LSA Squared algorithm, for the various ROUGE metrics.

  2. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications.

    Science.gov (United States)

    Savova, Guergana K; Masanz, James J; Ogren, Philip V; Zheng, Jiaping; Sohn, Sunghwan; Kipper-Schuler, Karin C; Chute, Christopher G

    2010-01-01

    We aim to build and evaluate an open-source natural language processing system for information extraction from electronic medical record clinical free-text. We describe and evaluate our system, the clinical Text Analysis and Knowledge Extraction System (cTAKES), released open-source at http://www.ohnlp.org. The cTAKES builds on existing open-source technologies-the Unstructured Information Management Architecture framework and OpenNLP natural language processing toolkit. Its components, specifically trained for the clinical domain, create rich linguistic and semantic annotations. Performance of individual components: sentence boundary detector accuracy=0.949; tokenizer accuracy=0.949; part-of-speech tagger accuracy=0.936; shallow parser F-score=0.924; named entity recognizer and system-level evaluation F-score=0.715 for exact and 0.824 for overlapping spans, and accuracy for concept mapping, negation, and status attributes for exact and overlapping spans of 0.957, 0.943, 0.859, and 0.580, 0.939, and 0.839, respectively. Overall performance is discussed against five applications. The cTAKES annotations are the foundation for methods and modules for higher-level semantic processing of clinical free-text.

  3. EnvMine: A text-mining system for the automatic extraction of contextual information

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    de Lorenzo Victor

    2010-06-01

    Full Text Available Abstract Background For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles. So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations from textual sources of any kind. Results EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings. Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude, thus allowing the calculation of distance between the individual locations. Conclusion EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical

  4. v3NLP Framework: Tools to Build Applications for Extracting Concepts from Clinical Text.

    Science.gov (United States)

    Divita, Guy; Carter, Marjorie E; Tran, Le-Thuy; Redd, Doug; Zeng, Qing T; Duvall, Scott; Samore, Matthew H; Gundlapalli, Adi V

    2016-01-01

    Substantial amounts of clinically significant information are contained only within the narrative of the clinical notes in electronic medical records. The v3NLP Framework is a set of "best-of-breed" functionalities developed to transform this information into structured data for use in quality improvement, research, population health surveillance, and decision support. MetaMap, cTAKES and similar well-known natural language processing (NLP) tools do not have sufficient scalability out of the box. The v3NLP Framework evolved out of the necessity to scale-up these tools up and provide a framework to customize and tune techniques that fit a variety of tasks, including document classification, tuned concept extraction for specific conditions, patient classification, and information retrieval. Beyond scalability, several v3NLP Framework-developed projects have been efficacy tested and benchmarked. While v3NLP Framework includes annotators, pipelines and applications, its functionalities enable developers to create novel annotators and to place annotators into pipelines and scaled applications. The v3NLP Framework has been successfully utilized in many projects including general concept extraction, risk factors for homelessness among veterans, and identification of mentions of the presence of an indwelling urinary catheter. Projects as diverse as predicting colonization with methicillin-resistant Staphylococcus aureus and extracting references to military sexual trauma are being built using v3NLP Framework components. The v3NLP Framework is a set of functionalities and components that provide Java developers with the ability to create novel annotators and to place those annotators into pipelines and applications to extract concepts from clinical text. There are scale-up and scale-out functionalities to process large numbers of records.

  5. EnvMine: a text-mining system for the automatic extraction of contextual information.

    Science.gov (United States)

    Tamames, Javier; de Lorenzo, Victor

    2010-06-01

    For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles). So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations) from textual sources of any kind. EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved) of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings.Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude), thus allowing the calculation of distance between the individual locations. EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical variables of sampling sites, thus facilitating the performance

  6. Extracting Road Features from Aerial Videos of Small Unmanned Aerial Vehicles

    Science.gov (United States)

    Rajamohan, D.; Rajan, K. S.

    2013-09-01

    With major aerospace companies showing interest in certifying UAV systems for civilian airspace, their use in commercial remote sensing applications like traffic monitoring, map refinement, agricultural data collection, etc., are on the rise. But ambitious requirements like real-time geo-referencing of data, support for multiple sensor angle-of-views, smaller UAV size and cheaper investment cost have lead to challenges in platform stability, sensor noise reduction and increased onboard processing. Especially in small UAVs the geo-referencing of data collected is only as good as the quality of their localization sensors. This drives a need for developing methods that pickup spatial features from the captured video/image and aid in geo-referencing. This paper presents one such method to identify road segments and intersections based on traffic flow and compares well with the accuracy of manual observation. Two test video datasets, one each from moving and stationary platforms were used. The results obtained show a promising average percentage difference of 7.01 % and 2.48 % for the road segment extraction process using moving and stationary platform respectively. For the intersection identification process, the moving platform shows an accuracy of 75 % where as the stationary platform data reaches an accuracy of 100 %.

  7. Supported eText in Captioned Videos: A Comparison of Expanded versus Standard Captions on Student Comprehension of Educational Content

    Science.gov (United States)

    Anderson-Inman, Lynne; Terrazas-Arellanes, Fatima E.

    2009-01-01

    Expanded captions are designed to enhance the educational value by linking unfamiliar words to one of three types of information: vocabulary definitions, labeled illustrations, or concept maps. This study investigated the effects of expanded captions versus standard captions on the comprehension of educational video materials on DVD by secondary…

  8. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2017-03-01

    Full Text Available Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT, speed-up robust feature (SURF, local binary patterns (LBP, histogram of oriented gradients (HOG, and weighted HOG. Recently, the convolutional neural network (CNN method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  9. A crowdsourcing workflow for extracting chemical-induced disease relations from free text.

    Science.gov (United States)

    Li, Tong Shu; Bravo, Àlex; Furlong, Laura I; Good, Benjamin M; Su, Andrew I

    2016-01-01

    Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available athttps://github.com/SuLab/crowd_cid_relexDatabase URL:https://github.com/SuLab/crowd_cid_relex. © The Author(s) 2016. Published by Oxford University Press.

  10. Learners' Use of Communication Strategies in Text-Based and Video-Based Synchronous Computer-Mediated Communication Environments: Opportunities for Language Learning

    Science.gov (United States)

    Hung, Yu-Wan; Higgins, Steve

    2016-01-01

    This study investigates the different learning opportunities enabled by text-based and video-based synchronous computer-mediated communication (SCMC) from an interactionist perspective. Six Chinese-speaking learners of English and six English-speaking learners of Chinese were paired up as tandem (reciprocal) learning dyads. Each dyad participated…

  11. Pregnancy Prevention at Her Fingertips: A Text- and Mobile Video-Based Pilot Intervention to Promote Contraceptive Methods among College Women

    Science.gov (United States)

    Walsh-Buhi, Eric R.; Helmy, Hannah; Harsch, Kristin; Rella, Natalie; Godcharles, Cheryl; Ogunrunde, Adejoke; Lopez Castillo, Humberto

    2016-01-01

    Objective: This paper reports on a pilot study evaluating the feasibility and acceptability of a text- and mobile video-based intervention to educate women and men attending college about non-daily contraception, with a particular focus on long-acting reversible contraception (LARC). A secondary objective is to describe the process of intervention…

  12. The enhancement of TextRank algorithm by using word2vec and its application on topic extraction

    Science.gov (United States)

    Zuo, Xiaolei; Zhang, Silan; Xia, Jingbo

    2017-08-01

    TextRank is a traditional method for keyword matching and topic extraction, while its drawback stems from the ignoring of the semantic similarity among texts. By using word embedding technique, Word2Vec was incorporated into traditional TextRank and four simulation tests were carried on for model comparison. The results showed that the hybrid combination of Word2Vec and TextRank algorithms achieved better keyword/topic extraction towards our testing text dataset.

  13. Protein function prediction using text-based features extracted from the biomedical literature: the CAFA challenge.

    Science.gov (United States)

    Wong, Andrew; Shatkay, Hagit

    2013-01-01

    Advances in sequencing technology over the past decade have resulted in an abundance of sequenced proteins whose function is yet unknown. As such, computational systems that can automatically predict and annotate protein function are in demand. Most computational systems use features derived from protein sequence or protein structure to predict function. In an earlier work, we demonstrated the utility of biomedical literature as a source of text features for predicting protein subcellular location. We have also shown that the combination of text-based and sequence-based prediction improves the performance of location predictors. Following up on this work, for the Critical Assessment of Function Annotations (CAFA) Challenge, we developed a text-based system that aims to predict molecular function and biological process (using Gene Ontology terms) for unannotated proteins. In this paper, we present the preliminary work and evaluation that we performed for our system, as part of the CAFA challenge. We have developed a preliminary system that represents proteins using text-based features and predicts protein function using a k-nearest neighbour classifier (Text-KNN). We selected text features for our classifier by extracting key terms from biomedical abstracts based on their statistical properties. The system was trained and tested using 5-fold cross-validation over a dataset of 36,536 proteins. System performance was measured using the standard measures of precision, recall, F-measure and overall accuracy. The performance of our system was compared to two baseline classifiers: one that assigns function based solely on the prior distribution of protein function (Base-Prior) and one that assigns function based on sequence similarity (Base-Seq). The overall prediction accuracy of Text-KNN, Base-Prior, and Base-Seq for molecular function classes are 62%, 43%, and 58% while the overall accuracy for biological process classes are 17%, 11%, and 28% respectively. Results

  14. Protein Function Prediction using Text-based Features extracted from the Biomedical Literature: The CAFA Challenge

    Science.gov (United States)

    2013-01-01

    Background Advances in sequencing technology over the past decade have resulted in an abundance of sequenced proteins whose function is yet unknown. As such, computational systems that can automatically predict and annotate protein function are in demand. Most computational systems use features derived from protein sequence or protein structure to predict function. In an earlier work, we demonstrated the utility of biomedical literature as a source of text features for predicting protein subcellular location. We have also shown that the combination of text-based and sequence-based prediction improves the performance of location predictors. Following up on this work, for the Critical Assessment of Function Annotations (CAFA) Challenge, we developed a text-based system that aims to predict molecular function and biological process (using Gene Ontology terms) for unannotated proteins. In this paper, we present the preliminary work and evaluation that we performed for our system, as part of the CAFA challenge. Results We have developed a preliminary system that represents proteins using text-based features and predicts protein function using a k-nearest neighbour classifier (Text-KNN). We selected text features for our classifier by extracting key terms from biomedical abstracts based on their statistical properties. The system was trained and tested using 5-fold cross-validation over a dataset of 36,536 proteins. System performance was measured using the standard measures of precision, recall, F-measure and overall accuracy. The performance of our system was compared to two baseline classifiers: one that assigns function based solely on the prior distribution of protein function (Base-Prior) and one that assigns function based on sequence similarity (Base-Seq). The overall prediction accuracy of Text-KNN, Base-Prior, and Base-Seq for molecular function classes are 62%, 43%, and 58% while the overall accuracy for biological process classes are 17%, 11%, and 28

  15. Automatic extraction of reference gene from literature in plants based on texting mining.

    Science.gov (United States)

    He, Lin; Shen, Gengyu; Li, Fei; Huang, Shuiqing

    2015-01-01

    Real-Time Quantitative Polymerase Chain Reaction (qRT-PCR) is widely used in biological research. It is a key to the availability of qRT-PCR experiment to select a stable reference gene. However, selecting an appropriate reference gene usually requires strict biological experiment for verification with high cost in the process of selection. Scientific literatures have accumulated a lot of achievements on the selection of reference gene. Therefore, mining reference genes under specific experiment environments from literatures can provide quite reliable reference genes for similar qRT-PCR experiments with the advantages of reliability, economic and efficiency. An auxiliary reference gene discovery method from literature is proposed in this paper which integrated machine learning, natural language processing and text mining approaches. The validity tests showed that this new method has a better precision and recall on the extraction of reference genes and their environments.

  16. Improving Students� Ability in Writing Hortatory Exposition Texts by Using Process-Genre Based Approach with YouTube Videos as the Media

    Directory of Open Access Journals (Sweden)

    fifin naili rizkiyah

    2017-06-01

    Full Text Available Abstract: This research is aimed at finding out how Process-Genre Based Approach strategy with YouTube Videos as the media are employed to improve the students� ability in writing hortatory exposition texts. This study uses collaborative classroom action research design following the procedures namely planning, implementing, observing, and reflecting. The procedures of carrying out the strategy are: (1 relating several issues/ cases to the students� background knowledge and introducing the generic structures and linguistic features of hortatory exposition text as the BKoF stage, (2 analyzing the generic structure and the language features used in the text and getting model on how to write a hortatory exposition text by using the YouTube Video as the MoT stage, (3 writing a hortatory exposition text collaboratively in a small group and in pairs through process writing as the JCoT stage, and (4 writing a hortatory exposition text individually as the ICoT stage. The result shows that the use of Process-Genre Based Approach and YouTube Videos can improve the students� ability in writing hortatory exposition texts. The percentage of the students achieving the score above the minimum passing grade (70 had improved from only 15.8% (3 out of 19 students in the preliminary study to 100% (22 students in the Cycle 1. Besides, the score of each aspect; content, organization, vocabulary, grammar, and mechanics also improved. � Key Words: writing ability, hortatory exposition text, process-genre based approach, youtube video

  17. Extraction of events and rules of land use/cover change from the policy text

    Science.gov (United States)

    Lin, Guangfa; Xia, Beicheng; Huang, Wangli; Jiang, Huixian; Chen, Youfei

    2007-06-01

    The database of recording the snapshots of land parcels history is the foundation for the most of the models on simulating land use/cover change (LUCC) process. But the sequences of temporal snapshots are not sufficient to deduce and describe the mechanism of LUCC process. The temporal relationship between scenarios of LUCC we recorded could not be transfer into causal relationship categorically, which was regarded as a key factor in spatial-temporal reasoning. The proprietor of land parcels adapted themselves to the policies from governments and the change of production market, and then made decisions in this or that way. The occurrence of each change of a land parcel in an urban area was often related with one or more decision texts when it was investigated on the local scale with high resolution of the background scene. These decision texts may come from different sections of a hierarchical government system on different levels, such as villages or communities, towns or counties, cities, provinces or even the paramount. All these texts were balance results between advantages and disadvantages of different interest groups. They are the essential forces of LUCC in human dimension. Up to now, a methodology is still wanted for on how to express these forces in a simulation system using GIS as a language. The presented paper was part of our initial research on this topic. The term "Event" is a very important concept in the frame of "Object-Oriented" theory in computer science. While in the domain of temporal GIS, the concept of event was developed in another category. The definitions of the event and their transformation relationship were discussed in this paper on three modeling levels as real world level, conceptual level and programming level. In this context, with a case study of LUCC in recent 30 years in Xiamen city of Fujian province, P. R. China, the paper focused on how to extract information of events and rules from the policy files collected and integrate

  18. Clinical records anonymisation and text extraction (CRATE): an open-source software system.

    Science.gov (United States)

    Cardinal, Rudolf N

    2017-04-26

    Electronic medical records contain information of value for research, but contain identifiable and often highly sensitive confidential information. Patient-identifiable information cannot in general be shared outside clinical care teams without explicit consent, but anonymisation/de-identification allows research uses of clinical data without explicit consent. This article presents CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system with separable functions: (1) it anonymises or de-identifies arbitrary relational databases, with sensitivity and precision similar to previous comparable systems; (2) it uses public secure cryptographic methods to map patient identifiers to research identifiers (pseudonyms); (3) it connects relational databases to external tools for natural language processing; (4) it provides a web front end for research and administrative functions; and (5) it supports a specific model through which patients may consent to be contacted about research. Creation and management of a research database from sensitive clinical records with secure pseudonym generation, full-text indexing, and a consent-to-contact process is possible and practical using entirely free and open-source software.

  19. Image Segmentation and Feature Extraction for Recognizing Strokes in Tennis Game Videos

    NARCIS (Netherlands)

    Zivkovic, Z.; van der Heijden, Ferdinand; Petkovic, M.; Jonker, Willem; Langendijk, R.L.; Heijnsdijk, J.W.J.; Pimentel, A.D.; Wilkinson, M.H.F.

    This paper addresses the problem of recognizing human actions from video. Particularly, the case of recognizing events in tennis game videos is analyzed. Driven by our domain knowledge, a robust player segmentation algorithm is developed for real video data. Further, we introduce a number of novel

  20. The use of telehealth (text messaging and video communications) in patients with cystic fibrosis: A pilot study.

    Science.gov (United States)

    Gur, Michal; Nir, Vered; Teleshov, Anna; Bar-Yoseph, Ronen; Manor, Eynav; Diab, Gizelle; Bentur, Lea

    2017-05-01

    Background Poor communications between cystic fibrosis (CF) patients and health-care providers may result in gaps in knowledge and misconceptions about medication usage, and can lead to poor adherence. We aimed to assess the feasibility of using WhatsApp and Skype to improve communications. Methods This single-centre pilot study included CF patients who were older than eight years of age assigned to two groups: one without intervention (control group), and one with intervention. Each patient from the intervention group received Skype-based online video chats and WhatsApp messages from members of the multidisciplinary CF team. CF questionnaires, revised (CFQ-R) scores, knowledge and adherence based on CF My Way and patients satisfaction were evaluated before and after three months. Feasibility was assessed by session attendance, acceptability and satisfaction survey. Descriptive analysis and paired and non-paired t-tests were used as applicable. Results Eighteen patients were recruited to this feasibility study (nine in each group). Each intervention group participant had between four and six Skype video chats and received 22-45 WhatsApp messages. In this small study, CFQ-R scores, knowledge, adherence and patient satisfaction were similar in both groups before and after the three-month intervention. Conclusions A telehealth-based approach, using Skype video chats and WhatsApp messages, was feasible and acceptable in this pilot study. A larger and longer multi-centre study is warranted to examine the efficacy of these interventions to improve knowledge, adherence and communication.

  1. Efficient extraction of protein-protein interactions from full-text articles.

    Science.gov (United States)

    Hakenberg, Jörg; Leaman, Robert; Vo, Nguyen Ha; Jonnalagadda, Siddhartha; Sullivan, Ryan; Miller, Christopher; Tari, Luis; Baral, Chitta; Gonzalez, Graciela

    2010-01-01

    Proteins and their interactions govern virtually all cellular processes, such as regulation, signaling, metabolism, and structure. Most experimental findings pertaining to such interactions are discussed in research papers, which, in turn, get curated by protein interaction databases. Authors, editors, and publishers benefit from efforts to alleviate the tasks of searching for relevant papers, evidence for physical interactions, and proper identifiers for each protein involved. The BioCreative II.5 community challenge addressed these tasks in a competition-style assessment to evaluate and compare different methodologies, to make aware of the increasing accuracy of automated methods, and to guide future implementations. In this paper, we present our approaches for protein-named entity recognition, including normalization, and for extraction of protein-protein interactions from full text. Our overall goal is to identify efficient individual components, and we compare various compositions to handle a single full-text article in between 10 seconds and 2 minutes. We propose strategies to transfer document-level annotations to the sentence-level, which allows for the creation of a more fine-grained training corpus; we use this corpus to automatically derive around 5,000 patterns. We rank sentences by relevance to the task of finding novel interactions with physical evidence, using a sentence classifier built from this training corpus. Heuristics for paraphrasing sentences help to further remove unnecessary information that might interfere with patterns, such as additional adjectives, clauses, or bracketed expressions. In BioCreative II.5, we achieved an f-score of 22 percent for finding protein interactions, and 43 percent for mapping proteins to UniProt IDs; disregarding species, f-scores are 30 percent and 55 percent, respectively. On average, our best-performing setup required around 2 minutes per full text. All data and pattern sets as well as Java classes that

  2. Text data extraction for a prospective, research-focused data mart: implementation and validation

    Directory of Open Access Journals (Sweden)

    Hinchcliff Monique

    2012-09-01

    Full Text Available Abstract Background Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of ‘machine generated’ sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Methods Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. Results There was a near perfect (99.5% agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Conclusions Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor to parse, abstract and assemble

  3. Text data extraction for a prospective, research-focused data mart: implementation and validation.

    Science.gov (United States)

    Hinchcliff, Monique; Just, Eric; Podlusky, Sofia; Varga, John; Chang, Rowland W; Kibbe, Warren A

    2012-09-13

    Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of 'machine generated' sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. There was a near perfect (99.5%) agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor) to parse, abstract and assemble structured data from text data contained in the electronic health

  4. THE COMPARISON OF DESCRIPTIVE TEXT WRITING ABILITY USING YOU TUBE DOWNLOADED VIDEO AND SERIAL PICTURES AT THE STUDENTS’OF SMPN 2 METROACADEMIC YEAR 2012/2013

    Directory of Open Access Journals (Sweden)

    Eka Bayu Pramanca

    2013-10-01

    Full Text Available This research discusses about how two different techniques affect the students’ ability in descriptive text at SMP N 2 Metro. The objectives of this research are (1 to know the difference result of using YouTube Downloaded Video and Serial Pictures media toward students’ writing ability in descriptive text and (2 to know which one is more effective of students’ writing ability in descriptive text instruction between learning by using YouTube Downloaded Video and Serial Pictures media. The implemented method is quantitative research design in that both researchers use true experimental research design. In this research , experimental and control class pre-test and post test are conducted. It is carried out at the first grade of SMP N 2 Metro in academic year 2012/2013. The population in this research is 7 different classes with total number of 224 students. 2 classes of the total population are taken as the samples; VII.1 students in experimental class and VII.2 students  in control class by using cluster random sampling technique.  The instruments of the research are tests, treatment and post-test. The data analyzing procedure uses t-test  and results the following output. The result of ttest is 3,96 and ttable  is 2,06. It means that tcount > ttable with the criterion of ttest is Ha is accepted if tcount  > ttable. So, there is any difference result of students’ writing ability using YouTube Downloaded Video and Serial Pictures Media. However; Youtube Downloaded Video media is more effective media than Serial Pictures media toward students’ writing ability. This research is consistent with the previous result of the studies and thus this technique is  recommended to use in writing instruction especially in descriptive text in order that students may feel fun and enjoy during the  learning process.

  5. Knowledge-based extraction of adverse drug events from biomedical text

    NARCIS (Netherlands)

    N. Kang (Ning); B. Singh (Bharat); C. Bui (Chinh); Z. Afzal (Zubair); E.M. van Mulligen (Erik); J.A. Kors (Jan)

    2014-01-01

    textabstractBackground: Many biomedical relation extraction systems are machine-learning based and have to be trained on large annotated corpora that are expensive and cumbersome to construct. We developed a knowledge-based relation extraction system that requires minimal training data, and applied

  6. RST-Resilient Video Watermarking Using Scene-Based Feature Extraction

    OpenAIRE

    Jung Han-Seung; Lee Young-Yoon; Lee Sang Uk

    2004-01-01

    Watermarking for video sequences should consider additional attacks, such as frame averaging, frame-rate change, frame shuffling or collusion attacks, as well as those of still images. Also, since video is a sequence of analogous images, video watermarking is subject to interframe collusion. In order to cope with these attacks, we propose a scene-based temporal watermarking algorithm. In each scene, segmented by scene-change detection schemes, a watermark is embedded temporally to one-dimens...

  7. Validation of the Total Visual Acuity Extraction Algorithm (TOVA) for Automated Extraction of Visual Acuity Data From Free Text, Unstructured Clinical Records.

    Science.gov (United States)

    Baughman, Douglas M; Su, Grace L; Tsui, Irena; Lee, Cecilia S; Lee, Aaron Y

    2017-03-01

    With increasing volumes of electronic health record data, algorithm-driven extraction may aid manual extraction. Visual acuity often is extracted manually in vision research. The total visual acuity extraction algorithm (TOVA) is presented and validated for automated extraction of visual acuity from free text, unstructured clinical notes. Consecutive inpatient ophthalmology notes over an 8-year period from the University of Washington healthcare system in Seattle, WA were used for validation of TOVA. The total visual acuity extraction algorithm applied natural language processing to recognize Snellen visual acuity in free text notes and assign laterality. The best corrected measurement was determined for each eye and converted to logMAR. The algorithm was validated against manual extraction of a subset of notes. A total of 6266 clinical records were obtained giving 12,452 data points. In a subset of 644 validated notes, comparison of manually extracted data versus TOVA output showed 95% concordance. Interrater reliability testing gave κ statistics of 0.94 (95% confidence interval [CI], 0.89-0.99), 0.96 (95% CI, 0.94-0.98), 0.95 (95% CI, 0.92-0.98), and 0.94 (95% CI, 0.90-0.98) for acuity numerators, denominators, adjustments, and signs, respectively. Pearson correlation coefficient was 0.983. Linear regression showed an R2 of 0.966 (P unstructured clinical notes and provides an open source method of data extraction. Automated visual acuity extraction through natural language processing can be a valuable tool for data extraction from free text ophthalmology notes.

  8. Apache Clinical Text and Knowledge Extraction System (cTAKES) | Informatics Technology for Cancer Research (ITCR)

    Science.gov (United States)

    The tool extracts deep phenotypic information from the clinical narrative at the document-, episode-, and patient-level. The final output is FHIR compliant patient-level phenotypic summary which can be consumed by research warehouses or the DeepPhe native visualization tool.

  9. MedXN: an open source medication extraction and normalization tool for clinical text

    Science.gov (United States)

    Sohn, Sunghwan; Clark, Cheryl; Halgrim, Scott R; Murphy, Sean P; Chute, Christopher G; Liu, Hongfang

    2014-01-01

    Objective We developed the Medication Extraction and Normalization (MedXN) system to extract comprehensive medication information and normalize it to the most appropriate RxNorm concept unique identifier (RxCUI) as specifically as possible. Methods Medication descriptions in clinical notes were decomposed into medication name and attributes, which were separately extracted using RxNorm dictionary lookup and regular expression. Then, each medication name and its attributes were combined together according to RxNorm convention to find the most appropriate RxNorm representation. To do this, we employed serialized hierarchical steps implemented in Apache's Unstructured Information Management Architecture. We also performed synonym expansion, removed false medications, and employed inference rules to improve the medication extraction and normalization performance. Results An evaluation on test data of 397 medication mentions showed F-measures of 0.975 for medication name and over 0.90 for most attributes. The RxCUI assignment produced F-measures of 0.932 for medication name and 0.864 for full medication information. Most false negative RxCUI assignments in full medication information are due to human assumption of missing attributes and medication names in the gold standard. Conclusions The MedXN system (http://sourceforge.net/projects/ohnlp/files/MedXN/) was able to extract comprehensive medication information with high accuracy and demonstrated good normalization capability to RxCUI as long as explicit evidence existed. More sophisticated inference rules might result in further improvements to specific RxCUI assignments for incomplete medication descriptions. PMID:24637954

  10. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction

    National Research Council Canada - National Science Library

    Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

    2013-01-01

    .... Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer...

  11. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos was designed ... Activity Role of Body Weight in Osteoarthritis Educational Videos for Patients Rheumatoid Arthritis Educational Video Series Psoriatic ...

  12. Impact of Machine-Translated Text on Entity and Relationship Extraction

    Science.gov (United States)

    2014-12-01

    onto an existing ontology of frames at the sentence level, using FrameNet, a structured language model, and through Semantic Role Labeling (SRL...Arabic language news articles collected from the web using Contour, a social network analysis tool acquired via a Small Business Innovation Research... semantic modeling software to automatically build detailed network models from unstructured text. Contour imports unstructured text and then maps the text

  13. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... NEI YouTube Videos > NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration ... Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: ...

  14. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... YouTube Videos > NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia ... of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia ...

  15. Comparison of Grouping Methods for Template Extraction from VA Medical Record Text.

    Science.gov (United States)

    Redd, Andrew M; Gundlapalli, Adi V; Divita, Guy; Tran, Le-Thuy; Pettey, Warren B P; Samore, Matthew H

    2017-01-01

    We investigate options for grouping templates for the purpose of template identification and extraction from electronic medical records. We sampled a corpus of 1000 documents originating from Veterans Health Administration (VA) electronic medical record. We grouped documents through hashing and binning tokens (Hashed) as well as by the top 5% of tokens identified as important through the term frequency inverse document frequency metric (TF-IDF). We then compared the approaches on the number of groups with 3 or more and the resulting longest common subsequences (LCSs) common to all documents in the group. We found that the Hashed method had a higher success rate for finding LCSs, and longer LCSs than the TF-IDF method, however the TF-IDF approach found more groups than the Hashed and subsequently more long sequences, however the average length of LCSs were lower. In conclusion, each algorithm appears to have areas where it appears to be superior.

  16. Conversation Thread Extraction and Topic Detection in Text-Based Chat

    National Research Council Canada - National Science Library

    Adams, Paige H

    2008-01-01

    Text-based chat systems are widely used within the Department of Defense, but the standard systems available do not provide robust capabilities for search, information retrieval, or information assurance...

  17. Text mining tools for extracting information about microbial biodiversity in food

    OpenAIRE

    Deleger, Louise; Bossy, Robert; Nédellec, Claire

    2017-01-01

    Introduction Information on food microbial biodiversity is scattered across millions of scientific papers (2 million references in the PubMed bibliographic database in 2017). It is impossible to manually achieve an exhaustive analysis of these documents. Text-mining and knowledge engineering methods can assist the researcher in finding relevant information. Material & Methods We propose to study bacterial biodiversity using text-mining tools from the Alvis platform. First, w...

  18. Face Recognition and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Swapnil Vitthal Tathe

    2017-07-01

    Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

  19. Parts-of-Speech Tagger Errors Do Not Necessarily Degrade Accuracy in Extracting Information from Biomedical Text

    Directory of Open Access Journals (Sweden)

    2008-06-01

    Full Text Available Background: An ongoing assessment of the literature is difficult with the rapidly increasing volume of research publications and limited effective information extraction tools which identify entity relationships from text. A recent study reported development of Muscorian, a generic text processing tool for extracting protein-protein interactions from text that achieved comparable performance to biomedical-specific text processing tools. This result was unexpected since potential errors from a series of text analysis processes is likely to adversely affect the outcome of the entire process. Most biomedical entity relationship extraction tools have used biomedical-specific parts-of-speech (POS tagger as errors in POS tagging and are likely to affect subsequent semantic analysis of the text, such as shallow parsing. This study aims to evaluate the parts-of-speech (POS tagging accuracy and attempts to explore whether a comparable performance is obtained when a generic POS tagger, MontyTagger, was used in place of MedPost, a tagger trained in biomedical text. Results: Our results demonstrated that MontyTagger, Muscorian's POS tagger, has a POS tagging accuracy of 83.1% when tested on biomedical text. Replacing MontyTagger with MedPost did not result in a significant improvement in entity relationship extraction from text; precision of 55.6% from MontyTagger versus 56.8% from MedPost on directional relationships and 86.1% from MontyTagger compared to 81.8% from MedPost on nondirectional relationships. This is unexpected as the potential for poor POS tagging by MontyTagger is likely to affect the outcome of the information extraction. An analysis of POS tagging errors demonstrated that 78.5% of tagging errors are being compensated by shallow parsing. Thus, despite 83.1% tagging accuracy, MontyTagger has a functional tagging accuracy of 94.6%. Conclusions: The POS tagging error does not adversely affect the information extraction task if the

  20. Computerized extraction of information on the quality of diabetes care from free text in electronic patient records of general practitioners

    NARCIS (Netherlands)

    Voorham, Jaco; Denig, Petra

    2007-01-01

    Objective: This study evaluated a computerized method for extracting numeric clinical measurements related to diabetes care from free text in electronic patient records (EPR) of general practitioners. Design and Measurements: Accuracy of this number-oriented approach was compared to manual chart

  1. An e-Learning System for Extracting Text Comprehension and Learning Style Characteristics

    Science.gov (United States)

    Samarakou, Maria; Tsaganou, Grammatiki; Papadakis, Andreas

    2018-01-01

    Technology-mediated learning is very actively and widely researched, with numerous e-learning environments designed for different educational purposes developed during the past few decades. Still, their organization and texts are not structured according to any theory of educational comprehension. Modern education is even more flexible and, thus,…

  2. Adding a Capability to Extract Sentiment from Text Using HanDles

    Science.gov (United States)

    2012-05-01

    effectuer la transition d’HanDles vers un environnement opérationnel, les intervenants de RDDC et des FC doivent décider quels sont les documents les plus...choisi une catégorie de texte, nous pourrons procéder à la formation et à la mise à l’essai du système au sein d’un environnement plus réaliste que ceux

  3. A Text Mining Approach for Extracting Lessons Learned from Project Documentation: An Illustrative Case Study

    Directory of Open Access Journals (Sweden)

    Benjamin Matthies

    2017-12-01

    Full Text Available Lessons learned are important building blocks for continuous learning in project-based organisations. Nonetheless, the practical reality is that lessons learned are often not consistently reused for organisational learning. Two problems are commonly described in this context: the information overload and the lack of procedures and methods for the assessment and implementation of lessons learned. This paper addresses these problems, and appropriate solutions are combined in a systematic lesson learned process. Latent Dirichlet Allocation is presented to solve the first problem. Regarding the second problem, established risk management methods are adapted. The entire lessons learned process will be demonstrated in a practical case study

  4. Surveillance Video Synopsis in GIS

    Directory of Open Access Journals (Sweden)

    Yujia Xie

    2017-10-01

    Full Text Available Surveillance videos contain a considerable amount of data, wherein interesting information to the user is sparsely distributed. Researchers construct video synopsis that contain key information extracted from a surveillance video for efficient browsing and analysis. Geospatial–temporal information of a surveillance video plays an important role in the efficient description of video content. Meanwhile, current approaches of video synopsis lack the introduction and analysis of geospatial-temporal information. Owing to the preceding problems mentioned, this paper proposes an approach called “surveillance video synopsis in GIS”. Based on an integration model of video moving objects and GIS, the virtual visual field and the expression model of the moving object are constructed by spatially locating and clustering the trajectory of the moving object. The subgraphs of the moving object are reconstructed frame by frame in a virtual scene. Results show that the approach described in this paper comprehensively analyzed and created fusion expression patterns between video dynamic information and geospatial–temporal information in GIS and reduced the playback time of video content.

  5. C-C1-02: Data Extraction From Text, Step 1: Preparing Test for Machine Processing

    Science.gov (United States)

    Carrell, David

    2010-01-01

    Background: Natural language processing (NLP) uses software to assist in the extraction of information from clinical text, a process usually performed entirely by chart abstractors. Before NLP can be applied the text in question must be prepared for machine processing. In research settings this pre- processing work often involves several successive and related tasks, requiring substantial amounts of time and attention from people representing various types of clinical, scientific and technical expertise. Appreciating the tasks and participants involved in pre-processing clinical text can make the work more manageable, efficient, and effective. Methods: The information presented here comes from case study analyses of three small-scale projects involving preparation of clinical text (pathology reports, radiology reports, and progress notes) for processing by the Cancer Text Information Extraction System. Supplementing these experiences is information from anecdotal conversations with natural language processing experts. Results: Ten separate pre-processing tasks were identified: obtaining source feeds, assessing completeness, de-duplication, universe description, cleaning and formatting, de-identification, database loading, sampling, preparation of the NLP system input feed, and quality assurance. Nine types of expertise or task participants required for preprocessing were identified: IRB representative, source-system manager, network/dbase administrator, programmer, statistician, investigator, informaticist, clinical domain expert, and manual chart abstractor. Conclusions: Pre-processing clinical text is an important phase and potentially challenging aspect of extracting information from clinical text using NLP. Because researchers require accurate information about the larger universe of documents or patients represented by the sampled and processed text, pre-processing can present numerous challenges, the solutions to which draw on many areas of expertise in a

  6. Extracting salient sublexical units from written texts: “Emophon,” a corpus-based approach to phonological iconicity

    Science.gov (United States)

    Aryani, Arash; Jacobs, Arthur M.; Conrad, Markus

    2013-01-01

    A growing body of literature in psychology, linguistics, and the neurosciences has paid increasing attention to the understanding of the relationships between phonological representations of words and their meaning: a phenomenon also known as phonological iconicity. In this article, we investigate how a text's intended emotional meaning, particularly in literature and poetry, may be reflected at the level of sublexical phonological salience and the use of foregrounded elements. To extract such elements from a given text, we developed a probabilistic model to predict the exceeding of a confidence interval for specific sublexical units concerning their frequency of occurrence within a given text contrasted with a reference linguistic corpus for the German language. Implementing this model in a computational application, we provide a text analysis tool which automatically delivers information about sublexical phonological salience allowing researchers, inter alia, to investigate effects of the sublexical emotional tone of texts based on current findings on phonological iconicity. PMID:24101907

  7. Extracting salient sublexical units from written texts:‘Emophon’, a corpus-based approach to phonological iconicity

    Directory of Open Access Journals (Sweden)

    Arash eAryani

    2013-10-01

    Full Text Available A growing body of literature in psychology, linguistics, and the neurosciences has paid increasing attention to the understanding of the relationships between phonological representations of words and their meaning: a phenomenon also known as phonological iconicity. In this article, we investigate how a text’s intended emotional meaning, particularly in literature and poetry, may be reflected at the level of sublexical phonological salience and the use of foregrounded elements. To extract such elements from a given text, we developed a probabilistic model to predict the exceeding of a confidence interval for specific sublexical units concerning their frequency of occurrence within a given text contrasted with a reference linguistic corpus for the German language. Implementing this model in a computational application, we provide a text analysis tool which automatically delivers information about sublexical phonological salience allowing researchers, inter alia, to investigate effects of the sublexical emotional tone of texts based on current findings on phonological iconicity.

  8. Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles.

    Science.gov (United States)

    Xu, Rong; Wang, QuanQiu

    2015-06-01

    Targeted anticancer drugs such as imatinib, trastuzumab and erlotinib dramatically improved treatment outcomes in cancer patients, however, these innovative agents are often associated with unexpected side effects. The pathophysiological mechanisms underlying these side effects are not well understood. The availability of a comprehensive knowledge base of side effects associated with targeted anticancer drugs has the potential to illuminate complex pathways underlying toxicities induced by these innovative drugs. While side effect association knowledge for targeted drugs exists in multiple heterogeneous data sources, published full-text oncological articles represent an important source of pivotal, investigational, and even failed trials in a variety of patient populations. In this study, we present an automatic process to extract targeted anticancer drug-associated side effects (drug-SE pairs) from a large number of high profile full-text oncological articles. We downloaded 13,855 full-text articles from the Journal of Oncology (JCO) published between 1983 and 2013. We developed text classification, relationship extraction, signaling filtering, and signal prioritization algorithms to extract drug-SE pairs from downloaded articles. We extracted a total of 26,264 drug-SE pairs with an average precision of 0.405, a recall of 0.899, and an F1 score of 0.465. We show that side effect knowledge from JCO articles is largely complementary to that from the US Food and Drug Administration (FDA) drug labels. Through integrative correlation analysis, we show that targeted drug-associated side effects positively correlate with their gene targets and disease indications. In conclusion, this unique database that we built from a large number of high-profile oncological articles could facilitate the development of computational models to understand toxic effects associated with targeted anticancer drugs. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions (Open Access)

    Science.gov (United States)

    2013-10-03

    1 are the average per-frame pix- el error rate compared to the ground-truth. The definition is [20]: error = XOR (f,GT ) F , (11) where f is the...object cutout using localized classifiers. ACM Transactions on Graphics , 28(3):70, 2009. [3] W. Brendel and S. Todorovic. Video object segmentation by...anisotropic kernel mean shift. In ECCV, 2004. [12] J. Kleinberg and E. Tardos. Algorithm design . Pearson Edu- cation and Addison Wesley, 2006. [13] Y

  10. Indexed Captioned Searchable Videos: A Learning Companion for STEM Coursework

    Science.gov (United States)

    Tuna, Tayfun; Subhlok, Jaspal; Barker, Lecia; Shah, Shishir; Johnson, Olin; Hovey, Christopher

    2017-02-01

    Videos of classroom lectures have proven to be a popular and versatile learning resource. A key shortcoming of the lecture video format is accessing the content of interest hidden in a video. This work meets this challenge with an advanced video framework featuring topical indexing, search, and captioning (ICS videos). Standard optical character recognition (OCR) technology was enhanced with image transformations for extraction of text from video frames to support indexing and search. The images and text on video frames is analyzed to divide lecture videos into topical segments. The ICS video player integrates indexing, search, and captioning in video playback providing instant access to the content of interest. This video framework has been used by more than 70 courses in a variety of STEM disciplines and assessed by more than 4000 students. Results presented from the surveys demonstrate the value of the videos as a learning resource and the role played by videos in a students learning process. Survey results also establish the value of indexing and search features in a video platform for education. This paper reports on the development and evaluation of ICS videos framework and over 5 years of usage experience in several STEM courses.

  11. 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.

  12. Using Medical Text Extraction, Reasoning and Mapping System (MTERMS) to process medication information in outpatient clinical notes.

    Science.gov (United States)

    Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Karipineni, Neelima; Chang, Frank; Yan, Xuemin; Chang, Fenny; Dimaggio, Dana; Goldman, Debora S; Rocha, Roberto A

    2011-01-01

    Clinical information is often coded using different terminologies, and therefore is not interoperable. Our goal is to develop a general natural language processing (NLP) system, called Medical Text Extraction, Reasoning and Mapping System (MTERMS), which encodes clinical text using different terminologies and simultaneously establishes dynamic mappings between them. MTERMS applies a modular, pipeline approach flowing from a preprocessor, semantic tagger, terminology mapper, context analyzer, and parser to structure inputted clinical notes. Evaluators manually reviewed 30 free-text and 10 structured outpatient clinical notes compared to MTERMS output. MTERMS achieved an overall F-measure of 90.6 and 94.0 for free-text and structured notes respectively for medication and temporal information. The local medication terminology had 83.0% coverage compared to RxNorm's 98.0% coverage for free-text notes. 61.6% of mappings between the terminologies are exact match. Capture of duration was significantly improved (91.7% vs. 52.5%) from systems in the third i2b2 challenge.

  13. Temporal Segmentation of MPEG Video Streams

    Directory of Open Access Journals (Sweden)

    Janko Calic

    2002-06-01

    Full Text Available Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.

  14. Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

    Directory of Open Access Journals (Sweden)

    André SANTOS

    2012-07-01

    Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

  15. Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

    Directory of Open Access Journals (Sweden)

    Anália LOURENÇO

    2013-07-01

    Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

  16. Do participants' preferences for mode of delivery (text, video, or both) influence the effectiveness of a Web-based physical activity intervention?

    Science.gov (United States)

    Vandelanotte, Corneel; Duncan, Mitch J; Plotnikoff, Ronald C; Mummery, W Kerry

    2012-02-29

    In randomized controlled trials, participants cannot choose their preferred intervention delivery mode and thus might refuse to participate or not engage fully if assigned to a nonpreferred group. This might underestimate the true effectiveness of behavior-change interventions. To examine whether receiving interventions either matched or mismatched with participants' preferred delivery mode would influence effectiveness of a Web-based physical activity intervention. Adults (n = 863), recruited via email, were randomly assigned to one of three intervention delivery modes (text based, video based, or combined) and received fully automated, Internet-delivered personal advice about physical activity. Personalized intervention content, based on the theory of planned behavior and stages of change concept, was identical across groups. Online, self-assessed questionnaires measuring physical activity were completed at baseline, 1 week, and 1 month. Physical activity advice acceptability and website usability were assessed at 1 week. Before randomization, participants were asked which delivery mode they preferred, to categorize them as matched or mismatched. Time spent on the website was measured throughout the intervention. We applied intention-to-treat, repeated-measures analyses of covariance to assess group differences. Attrition was high (575/863, 66.6%), though equal between groups (t(86) (3) =1.31, P =.19). At 1-month follow-up, 93 participants were categorized as matched and 195 as mismatched. They preferred text mode (493/803, 61.4%) over combined (216/803, 26.9%) and video modes (94/803, 11.7%). After the intervention, 20% (26/132) of matched-group participants and 34% (96/282) in the mismatched group changed their delivery mode preference. Time effects were significant for all physical activity outcomes (total physical activity: F(2,801) = 5.07, P = .009; number of activity sessions: F(2,801) = 7.52, P < .001; walking: F(2,801) = 8.32, P < .001; moderate physical

  17. stil113_0401r -- Point coverage of locations of still frames extracted from video imagery which depict sediment types

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  18. Ventilator Data Extraction with a Video Display Image Capture and Processing System.

    Science.gov (United States)

    Wax, David B; Hill, Bryan; Levin, Matthew A

    2017-06-01

    Medical hardware and software device interoperability standards are not uniform. The result of this lack of standardization is that information available on clinical devices may not be readily or freely available for import into other systems for research, decision support, or other purposes. We developed a novel system to import discrete data from an anesthesia machine ventilator by capturing images of the graphical display screen and using image processing to extract the data with off-the-shelf hardware and open-source software. We were able to successfully capture and verify live ventilator data from anesthesia machines in multiple operating rooms and store the discrete data in a relational database at a substantially lower cost than vendor-sourced solutions.

  19. Assessment of blind source separation techniques for video-based cardiac pulse extraction

    Science.gov (United States)

    Wedekind, Daniel; Trumpp, Alexander; Gaetjen, Frederik; Rasche, Stefan; Matschke, Klaus; Malberg, Hagen; Zaunseder, Sebastian

    2017-03-01

    Blind source separation (BSS) aims at separating useful signal content from distortions. In the contactless acquisition of vital signs by means of the camera-based photoplethysmogram (cbPPG), BSS has evolved the most widely used approach to extract the cardiac pulse. Despite its frequent application, there is no consensus about the optimal usage of BSS and its general benefit. This contribution investigates the performance of BSS to enhance the cardiac pulse from cbPPGs in dependency to varying input data characteristics. The BSS input conditions are controlled by an automated spatial preselection routine of regions of interest. Input data of different characteristics (wavelength, dominant frequency, and signal quality) from 18 postoperative cardiovascular patients are processed with standard BSS techniques, namely principal component analysis (PCA) and independent component analysis (ICA). The effect of BSS is assessed by the spectral signal-to-noise ratio (SNR) of the cardiac pulse. The preselection of cbPPGs, appears beneficial providing higher SNR compared to standard cbPPGs. Both, PCA and ICA yielded better outcomes by using monochrome inputs (green wavelength) instead of inputs of different wavelengths. PCA outperforms ICA for more homogeneous input signals. Moreover, for high input SNR, the application of ICA using standard contrast is likely to decrease the SNR.

  20. PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries

    Directory of Open Access Journals (Sweden)

    Barbosa-Silva Adriano

    2011-11-01

    Full Text Available Abstract Background Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation. Results To help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer. Conclusions PESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador/

  1. Coding Local and Global Binary Visual Features Extracted From Video Sequences.

    Science.gov (United States)

    Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

    2015-11-01

    Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

  2. Application of text information extraction system for real-time cancer case identification in an integrated healthcare organization

    Directory of Open Access Journals (Sweden)

    Fagen Xie

    2017-01-01

    Full Text Available Background: Surgical pathology reports (SPR contain rich clinical diagnosis information. The text information extraction system (TIES is an end-to-end application leveraging natural language processing technologies and focused on the processing of pathology and/or radiology reports. Methods: We deployed the TIES system and integrated SPRs into the TIES system on a daily basis at Kaiser Permanente Southern California. The breast cancer cases diagnosed in December 2013 from the Cancer Registry (CANREG were used to validate the performance of the TIES system. The National Cancer Institute Metathesaurus (NCIM concept terms and codes to describe breast cancer were identified through the Unified Medical Language System Terminology Service (UTS application. The identified NCIM codes were used to search for the coded SPRs in the back-end datastore directly. The identified cases were then compared with the breast cancer patients pulled from CANREG. Results: A total of 437 breast cancer concept terms and 14 combinations of “breast” and “cancer” terms were identified from the UTS application. A total of 249 breast cancer cases diagnosed in December 2013 was pulled from CANREG. Out of these 249 cases, 241 were successfully identified by the TIES system from a total of 457 reports. The TIES system also identified an additional 277 cases that were not part of the validation sample. Out of the 277 cases, 11% were determined as highly likely to be cases after manual examinations, and 86% were in CANREG but were diagnosed in months other than December of 2013. Conclusions: The study demonstrated that the TIES system can effectively identify potential breast cancer cases in our care setting. Identified potential cases can be easily confirmed by reviewing the corresponding annotated reports through the front-end visualization interface. The TIES system is a great tool for identifying potential various cancer cases in a timely manner and on a regular basis

  3. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-01-01

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images. PMID:28335510

  4. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction.

    Science.gov (United States)

    Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

    2017-03-20

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

  5. Fast Aerial Video Stitching

    Directory of Open Access Journals (Sweden)

    Jing Li

    2014-10-01

    Full Text Available The highly efficient and robust stitching of aerial video captured by unmanned aerial vehicles (UAVs is a challenging problem in the field of robot vision. Existing commercial image stitching systems have seen success with offline stitching tasks, but they cannot guarantee high-speed performance when dealing with online aerial video sequences. In this paper, we present a novel system which has an unique ability to stitch high-frame rate aerial video at a speed of 150 frames per second (FPS. In addition, rather than using a high-speed vision platform such as FPGA or CUDA, our system is running on a normal personal computer. To achieve this, after the careful comparison of the existing invariant features, we choose the FAST corner and binary descriptor for efficient feature extraction and representation, and present a spatial and temporal coherent filter to fuse the UAV motion information into the feature matching. The proposed filter can remove the majority of feature correspondence outliers and significantly increase the speed of robust feature matching by up to 20 times. To achieve a balance between robustness and efficiency, a dynamic key frame-based stitching framework is used to reduce the accumulation errors. Extensive experiments on challenging UAV datasets demonstrate that our approach can break through the speed limitation and generate an accurate stitching image for aerial video stitching tasks.

  6. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... member of our patient care team. Managing Your Arthritis Managing Your Arthritis Managing Chronic Pain and Depression ...

  7. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos was designed to help you learn more about Rheumatoid Arthritis (RA). You will learn how the diagnosis of ...

  8. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... questions Clinical Studies Publications Catalog Photos and Images Spanish Language Information Grants and Funding Extramural Research Division ... Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video ...

  9. stil119_0601a -- Point coverage of locations of still frames extracted from video imagery which depict sediment types

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Canadian ROPOS remotely operated vehicle (ROV) outfitted with video equipment (and other devices) was deployed from the NOAA Ship McAurthurII during May-June...

  10. Multimedia Information Extraction

    CERN Document Server

    Maybury, Mark T

    2012-01-01

    The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance.  While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and vid

  11. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... support group for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ... group for me? Find a group Back Upcoming events Video Library Photo Gallery One-on-One Support ...

  12. Videos, Podcasts and Livechats

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    Full Text Available ... Doctor Find a Provider Meet the Team Blog Articles News Resources Links Videos Podcasts Webinars For the ... Doctor Find a Provider Meet the Team Blog Articles News Provider Directory Donate Resources Links Videos Podcasts ...

  13. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Doctor Find a Provider Meet the Team Blog Articles & Stories News Resources Links Videos Podcasts Webinars For ... Doctor Find a Provider Meet the Team Blog Articles & Stories News Provider Directory Donate Resources Links Videos ...

  14. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Back Support Groups Is a support group for me? Find a Group Upcoming Events Video Library Photo ... Support Groups Back Is a support group for me? Find a group Back Upcoming events Video Library ...

  15. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... group for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork ... for me? Find a group Back Upcoming events Video Library Photo Gallery One-on-One Support Back ...

  16. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... the Team Blog Articles & Stories News Resources Links Videos Podcasts Webinars For the Media For Clinicians For ... Family Caregivers Glossary Menu In this section Links Videos Podcasts Webinars For the Media For Clinicians For ...

  17. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... a Provider Meet the Team Blog Articles & Stories News Resources Links Videos Podcasts Webinars For the Media ... a Provider Meet the Team Blog Articles & Stories News Provider Directory Donate Resources Links Videos Podcasts Webinars ...

  18. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork Peer ... me? Find a group Back Upcoming events Video Library Photo Gallery One-on-One Support Back ANetwork ...

  19. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... News Resources Links Videos Podcasts Webinars For the Media For Clinicians For Policymakers For Family Caregivers Glossary ... this section Links Videos Podcasts Webinars For the Media For Clinicians For Policymakers For Family Caregivers Glossary ...

  20. EXTRACT

    DEFF Research Database (Denmark)

    Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra

    2016-01-01

    The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have the...... and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/......., organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual...

  1. Combining position weight matrices and document-term matrix for efficient extraction of associations of methylated genes and diseases from free text.

    Directory of Open Access Journals (Sweden)

    Arwa Bin Raies

    Full Text Available BACKGROUND: In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually. METHODOLOGY: We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text. CONCLUSION: The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download.

  2. Accelerating video carving from unallocated space

    Science.gov (United States)

    Kalva, Hari; Parikh, Anish; Srinivasan, Avinash

    2013-03-01

    Video carving has become an essential tool in digital forensics. Video carving enables recovery of deleted video files from hard disks. Processing data to extract videos is a computationally intensive task. In this paper we present two methods to accelerate video carving: a method to accelerate fragment extraction, and a method to accelerate combining of these fragments into video segments. Simulation results show that complexity of video fragment extraction can be reduced by as much as 75% with minimal impact on the videos recovered.

  3. Design and Implementation of Video Shot Detection on Field Programmable Gate Arrays

    Directory of Open Access Journals (Sweden)

    Jharna Majumdar

    2012-09-01

    Full Text Available Video has become an interactive medium of communication in everyday life. The sheer volume of video makes it extremely difficult to browse through and find the required data. Hence extraction of key frames from the video which represents the abstract of the entire video becomes necessary. The aim of the video shot detection is to find the position of the shot boundaries, so that key frames can be selected from each shot for subsequent processing such as video summarization, indexing etc. For most of the surveillance applications like video summery, face recognition etc., the hardware (real time implementation of these algorithms becomes necessary. Here in this paper we present the architecture for simultaneous accessing of consecutive frames, which are then used for the implementation of various Video Shot Detection algorithms. We also present the real time implementation of three video shot detection algorithms using the above mentioned architecture on FPGA (Field Programmable Gate Arrays.

  4. Combining position weight matrices and document-term matrix for efficient extraction of associations of methylated genes and diseases from free text.

    Science.gov (United States)

    Bin Raies, Arwa; Mansour, Hicham; Incitti, Roberto; Bajic, Vladimir B

    2013-01-01

    In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually. We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs) for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text. The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download.

  5. Combining Position Weight Matrices and Document-Term Matrix for Efficient Extraction of Associations of Methylated Genes and Diseases from Free Text

    KAUST Repository

    Bin Raies, Arwa

    2013-10-16

    Background:In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually.Methodology:We developed a novel text mining methodology based on a new concept of position weight matrices (PWMs) for text representation and feature generation. We applied PWMs in conjunction with the document-term matrix to extract with high accuracy associations between methylated genes and diseases from free text. The performance results are based on large manually-classified data. Additionally, we developed a web-tool, DEMGD, which automates extraction of these associations from free text. DEMGD presents the extracted associations in summary tables and full reports in addition to evidence tagging of text with respect to genes, diseases and methylation words. The methodology we developed in this study can be applied to similar association extraction problems from free text.Conclusion:The new methodology developed in this study allows for efficient identification of associations between concepts. Our method applied to methylated genes in different diseases is implemented as a Web-tool, DEMGD, which is freely available at http://www.cbrc.kaust.edu.sa/demgd/. The data is available for online browsing and download. © 2013 Bin Raies et al.

  6. Digital Video in Research

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2012-01-01

    questions of our media literacy pertaining to authoring multimodal texts (visual, verbal, audial, etc.) in research practice and the status of multimodal texts in academia. The implications of academic video extend to wider issues of how researchers harness opportunities to author different types of texts......Is video becoming “the new black” in academia, if so, what are the challenges? The integration of video in research methodology (for collection, analysis) is well-known, but the use of “academic video” for dissemination is relatively new (Eriksson and Sørensen). The focus of this paper is academic...... video, or short video essays produced for the explicit purpose of communicating research processes, topics, and research-based knowledge (see the journal of academic videos: www.audiovisualthinking.org). Video is increasingly used in popular showcases for video online, such as YouTube and Vimeo, as well...

  7. Interactive video algorithms and technologies

    CERN Document Server

    Hammoud, Riad

    2006-01-01

    This book covers both algorithms and technologies of interactive videos, so that businesses in IT and data managements, scientists and software engineers in video processing and computer vision, coaches and instructors that use video technology in teaching, and finally end-users will greatly benefit from it. This book contains excellent scientific contributions made by a number of pioneering scientists and experts from around the globe. It consists of five parts. The first part introduces the reader to interactive video and video summarization and presents effective methodologies for automatic abstraction of a single video sequence, a set of video sequences, and a combined audio-video sequence. In the second part, a list of advanced algorithms and methodologies for automatic and semi-automatic analysis and editing of audio-video documents are presented. The third part tackles a more challenging level of automatic video re-structuring, filtering of video stream by extracting of highlights, events, and meaningf...

  8. MPEG-2 Compressed-Domain Algorithms for Video Analysis

    Directory of Open Access Journals (Sweden)

    Hesseler Wolfgang

    2006-01-01

    Full Text Available This paper presents new algorithms for extracting metadata from video sequences in the MPEG-2 compressed domain. Three algorithms for efficient low-level metadata extraction in preprocessing stages are described. The first algorithm detects camera motion using the motion vector field of an MPEG-2 video. The second method extends the idea of motion detection to a limited region of interest, yielding an efficient algorithm to track objects inside video sequences. The third algorithm performs a cut detection using macroblock types and motion vectors.

  9. An Enhanced Text-Mining Framework for Extracting Disaster Relevant Data through Social Media and Remote Sensing Data Fusion

    Science.gov (United States)

    Scheele, C. J.; Huang, Q.

    2016-12-01

    In the past decade, the rise in social media has led to the development of a vast number of social media services and applications. Disaster management represents one of such applications leveraging massive data generated for event detection, response, and recovery. In order to find disaster relevant social media data, current approaches utilize natural language processing (NLP) methods based on keywords, or machine learning algorithms relying on text only. However, these approaches cannot be perfectly accurate due to the variability and uncertainty in language used on social media. To improve current methods, the enhanced text-mining framework is proposed to incorporate location information from social media and authoritative remote sensing datasets for detecting disaster relevant social media posts, which are determined by assessing the textual content using common text mining methods and how the post relates spatiotemporally to the disaster event. To assess the framework, geo-tagged Tweets were collected for three different spatial and temporal disaster events: hurricane, flood, and tornado. Remote sensing data and products for each event were then collected using RealEarthTM. Both Naive Bayes and Logistic Regression classifiers were used to compare the accuracy within the enhanced text-mining framework. Finally, the accuracies from the enhanced text-mining framework were compared to the current text-only methods for each of the case study disaster events. The results from this study address the need for more authoritative data when using social media in disaster management applications.

  10. Improving text recognition by distinguishing scene and overlay text

    Science.gov (United States)

    Quehl, Bernhard; Yang, Haojin; Sack, Harald

    2015-02-01

    Video texts are closely related to the content of a video. They provide a valuable source for indexing and interpretation of video data. Text detection and recognition task in images or videos typically distinguished between overlay and scene text. Overlay text is artificially superimposed on the image at the time of editing and scene text is text captured by the recording system. Typically, OCR systems are specialized on one kind of text type. However, in video images both types of text can be found. In this paper, we propose a method to automatically distinguish between overlay and scene text to dynamically control and optimize post processing steps following text detection. Based on a feature combination a Support Vector Machine (SVM) is trained to classify scene and overlay text. We show how this distinction in overlay and scene text improves the word recognition rate. Accuracy of the proposed methods has been evaluated by using publicly available test data sets.

  11. Extraction of Pluvial Flood Relevant Volunteered Geographic Information (VGI by Deep Learning from User Generated Texts and Photos

    Directory of Open Access Journals (Sweden)

    Yu Feng

    2018-01-01

    Full Text Available In recent years, pluvial floods caused by extreme rainfall events have occurred frequently. Especially in urban areas, they lead to serious damages and endanger the citizens’ safety. Therefore, real-time information about such events is desirable. With the increasing popularity of social media platforms, such as Twitter or Instagram, information provided by voluntary users becomes a valuable source for emergency response. Many applications have been built for disaster detection and flood mapping using crowdsourcing. Most of the applications so far have merely used keyword filtering or classical language processing methods to identify disaster relevant documents based on user generated texts. As the reliability of social media information is often under criticism, the precision of information retrieval plays a significant role for further analyses. Thus, in this paper, high quality eyewitnesses of rainfall and flooding events are retrieved from social media by applying deep learning approaches on user generated texts and photos. Subsequently, events are detected through spatiotemporal clustering and visualized together with these high quality eyewitnesses in a web map application. Analyses and case studies are conducted during flooding events in Paris, London and Berlin.

  12. An economic evaluation of a video- and text-based computer-tailored intervention for smoking cessation: a cost-effectiveness and cost-utility analysis of a randomized controlled trial.

    Science.gov (United States)

    Stanczyk, Nicola E; Smit, Eline S; Schulz, Daniela N; de Vries, Hein; Bolman, Catherine; Muris, Jean W M; Evers, Silvia M A A

    2014-01-01

    Although evidence exists for the effectiveness of web-based smoking cessation interventions, information about the cost-effectiveness of these interventions is limited. The study investigated the cost-effectiveness and cost-utility of two web-based computer-tailored (CT) smoking cessation interventions (video- vs. text-based CT) compared to a control condition that received general text-based advice. In a randomized controlled trial, respondents were allocated to the video-based condition (N = 670), the text-based condition (N = 708) or the control condition (N = 721). Societal costs, smoking status, and quality-adjusted life years (QALYs; EQ-5D-3L) were assessed at baseline, six-and twelve-month follow-up. The incremental costs per abstinent respondent and per QALYs gained were calculated. To account for uncertainty, bootstrapping techniques and sensitivity analyses were carried out. No significant differences were found in the three conditions regarding demographics, baseline values of outcomes and societal costs over the three months prior to baseline. Analyses using prolonged abstinence as outcome measure indicated that from a willingness to pay of €1,500, the video-based intervention was likely to be the most cost-effective treatment, whereas from a willingness to pay of €50,400, the text-based intervention was likely to be the most cost-effective. With regard to cost-utilities, when quality of life was used as outcome measure, the control condition had the highest probability of being the most preferable treatment. Sensitivity analyses yielded comparable results. The video-based CT smoking cessation intervention was the most cost-effective treatment for smoking abstinence after twelve months, varying the willingness to pay per abstinent respondent from €0 up to €80,000. With regard to cost-utility, the control condition seemed to be the most preferable treatment. Probably, more time will be required to assess changes in quality of life

  13. An Economic Evaluation of a Video- and Text-Based Computer-Tailored Intervention for Smoking Cessation: A Cost-Effectiveness and Cost-Utility Analysis of a Randomized Controlled Trial

    Science.gov (United States)

    Stanczyk, Nicola E.; Smit, Eline S.; Schulz, Daniela N.; de Vries, Hein; Bolman, Catherine; Muris, Jean W. M.; Evers, Silvia M. A. A.

    2014-01-01

    Background Although evidence exists for the effectiveness of web-based smoking cessation interventions, information about the cost-effectiveness of these interventions is limited. Objective The study investigated the cost-effectiveness and cost-utility of two web-based computer-tailored (CT) smoking cessation interventions (video- vs. text-based CT) compared to a control condition that received general text-based advice. Methods In a randomized controlled trial, respondents were allocated to the video-based condition (N = 670), the text-based condition (N = 708) or the control condition (N = 721). Societal costs, smoking status, and quality-adjusted life years (QALYs; EQ-5D-3L) were assessed at baseline, six-and twelve-month follow-up. The incremental costs per abstinent respondent and per QALYs gained were calculated. To account for uncertainty, bootstrapping techniques and sensitivity analyses were carried out. Results No significant differences were found in the three conditions regarding demographics, baseline values of outcomes and societal costs over the three months prior to baseline. Analyses using prolonged abstinence as outcome measure indicated that from a willingness to pay of €1,500, the video-based intervention was likely to be the most cost-effective treatment, whereas from a willingness to pay of €50,400, the text-based intervention was likely to be the most cost-effective. With regard to cost-utilities, when quality of life was used as outcome measure, the control condition had the highest probability of being the most preferable treatment. Sensitivity analyses yielded comparable results. Conclusion The video-based CT smoking cessation intervention was the most cost-effective treatment for smoking abstinence after twelve months, varying the willingness to pay per abstinent respondent from €0 up to €80,000. With regard to cost-utility, the control condition seemed to be the most preferable treatment. Probably, more time will be

  14. Automated Identification and Reconstruction of YouTube Video Access

    Directory of Open Access Journals (Sweden)

    Jonathan Patterson

    2012-06-01

    Full Text Available YouTube is one of the most popular video-sharing websites on the Internet, allowing users to upload, view and share videos with other users all over the world. YouTube contains many different types of videos, from homemade sketches to instructional and educational tutorials, and therefore attracts a wide variety of users with different interests. The majority of YouTube visits are perfectly innocent, but there may be circumstances where YouTube video access is related to a digital investigation, e.g. viewing instructional videos on how to perform potentially unlawful actions or how to make unlawful articles.When a user accesses a YouTube video through their browser, certain digital artefacts relating to that video access may be left on their system in a number of different locations. However, there has been very little research published in the area of YouTube video artefacts.The paper discusses the identification of some of the artefacts that are left by the Internet Explorer web browser on a Windows system after accessing a YouTube video. The information that can be recovered from these artefacts can include the video ID, the video name and possibly a cached copy of the video itself. In addition to identifying the artefacts that are left, the paper also investigates how these artefacts can be brought together and analysed to infer specifics about the user’s interaction with the YouTube website, for example whether the video was searched for or visited as a result of a suggestion after viewing a previous video.The result of this research is a Python based prototype that will analyse a mounted disk image, automatically extract the artefacts related to YouTube visits and produce a report summarising the YouTube video accesses on a system.

  15. ADEPt, a semantically-enriched pipeline for extracting adverse drug events from free-text electronic health records.

    Directory of Open Access Journals (Sweden)

    Ehtesham Iqbal

    Full Text Available Adverse drug events (ADEs are unintended responses to medical treatment. They can greatly affect a patient's quality of life and present a substantial burden on healthcare. Although Electronic health records (EHRs document a wealth of information relating to ADEs, they are frequently stored in the unstructured or semi-structured free-text narrative requiring Natural Language Processing (NLP techniques to mine the relevant information. Here we present a rule-based ADE detection and classification pipeline built and tested on a large Psychiatric corpus comprising 264k patients using the de-identified EHRs of four UK-based psychiatric hospitals. The pipeline uses characteristics specific to Psychiatric EHRs to guide the annotation process, and distinguishes: a the temporal value associated with the ADE mention (whether it is historical or present, b the categorical value of the ADE (whether it is assertive, hypothetical, retrospective or a general discussion and c the implicit contextual value where the status of the ADE is deduced from surrounding indicators, rather than explicitly stated. We manually created the rulebase in collaboration with clinicians and pharmacists by studying ADE mentions in various types of clinical notes. We evaluated the open-source Adverse Drug Event annotation Pipeline (ADEPt using 19 ADEs specific to antipsychotics and antidepressants medication. The ADEs chosen vary in severity, regularity and persistence. The average F-measure and accuracy achieved by our tool across all tested ADEs were 0.83 and 0.83 respectively. In addition to annotation power, the ADEPT pipeline presents an improvement to the state of the art context-discerning algorithm, ConText.

  16. Application of Text Mining to Extract Hotel Attributes and Construct Perceptual Map of Five Star Hotels from Online Review: Study of Jakarta and Singapore Five-Star Hotels

    Directory of Open Access Journals (Sweden)

    Arga Hananto

    2015-12-01

    Full Text Available The use of post-purchase online consumer review in hotel attributes study was still scarce in the literature. Arguably, post purchase online review data would gain more accurate attributes thatconsumers actually consider in their purchase decision. This study aims to extract attributes from two samples of five-star hotel reviews (Jakarta and Singapore with text mining methodology. In addition,this study also aims to describe positioning of five-star hotels in Jakarta and Singapore based on the extracted attributes using Correspondence Analysis. This study finds that reviewers of five star hotels in both cities mentioned similar attributes such as service, staff, club, location, pool and food. Attributes derived from text mining seem to be viable input to build fairly accurate positioning map of hotels. This study has demonstrated the viability of online review as a source of data for hotel attribute and positioning studies.

  17. Random Numbers Generated from Audio and Video Sources

    Directory of Open Access Journals (Sweden)

    I-Te Chen

    2013-01-01

    Full Text Available Random numbers are very useful in simulation, chaos theory, game theory, information theory, pattern recognition, probability theory, quantum mechanics, statistics, and statistical mechanics. The random numbers are especially helpful in cryptography. In this work, the proposed random number generators come from white noise of audio and video (A/V sources which are extracted from high-resolution IPCAM, WEBCAM, and MPEG-1 video files. The proposed generator applied on video sources from IPCAM and WEBCAM with microphone would be the true random number generator and the pseudorandom number generator when applied on video sources from MPEG-1 video file. In addition, when applying NIST SP 800-22 Rev.1a 15 statistics tests on the random numbers generated from the proposed generator, around 98% random numbers can pass 15 statistical tests. Furthermore, the audio and video sources can be found easily; hence, the proposed generator is a qualified, convenient, and efficient random number generator.

  18. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... search for current job openings visit HHS USAJobs Home > NEI YouTube Videos > NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract ...

  19. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... Amaurosis Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia NEI Home Contact Us A-Z Site Map NEI on Social Media Information in Spanish (Información en español) Website, ...

  20. Advanced video coding systems

    CERN Document Server

    Gao, Wen

    2015-01-01

    This comprehensive and accessible text/reference presents an overview of the state of the art in video coding technology. Specifically, the book introduces the tools of the AVS2 standard, describing how AVS2 can help to achieve a significant improvement in coding efficiency for future video networks and applications by incorporating smarter coding tools such as scene video coding. Topics and features: introduces the basic concepts in video coding, and presents a short history of video coding technology and standards; reviews the coding framework, main coding tools, and syntax structure of AV

  1. The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records.

    Science.gov (United States)

    Shah, Anoop D; Martinez, Carlos; Hemingway, Harry

    2012-08-07

    Electronic health records are invaluable for medical research, but much information is stored as free text rather than in a coded form. For example, in the UK General Practice Research Database (GPRD), causes of death and test results are sometimes recorded only in free text. Free text can be difficult to use for research if it requires time-consuming manual review. Our aim was to develop an automated method for extracting coded information from free text in electronic patient records. We reviewed the electronic patient records in GPRD of a random sample of 3310 patients who died in 2001, to identify the cause of death. We developed a computer program called the Freetext Matching Algorithm (FMA) to map diagnoses in text to the Read Clinical Terminology. The program uses lookup tables of synonyms and phrase patterns to identify diagnoses, dates and selected test results. We tested it on two random samples of free text from GPRD (1000 texts associated with death in 2001, and 1000 general texts from cases and controls in a coronary artery disease study), comparing the output to the U.S. National Library of Medicine's MetaMap program and the gold standard of manual review. Among 3310 patients registered in the GPRD who died in 2001, the cause of death was recorded in coded form in 38.1% of patients, and in the free text alone in 19.4%. On the 1000 texts associated with death, FMA coded 683 of the 735 positive diagnoses, with precision (positive predictive value) 98.4% (95% confidence interval (CI) 97.2, 99.2) and recall (sensitivity) 92.9% (95% CI 90.8, 94.7). On the general sample, FMA detected 346 of the 447 positive diagnoses, with precision 91.5% (95% CI 88.3, 94.1) and recall 77.4% (95% CI 73.2, 81.2), which was similar to MetaMap. We have developed an algorithm to extract coded information from free text in GP records with good precision. It may facilitate research using free text in electronic patient records, particularly for extracting the cause of death.

  2. Anthropocentric Video Segmentation for Lecture Webcasts

    Directory of Open Access Journals (Sweden)

    Raul Rojas

    2008-03-01

    Full Text Available Many lecture recording and presentation systems transmit slides or chalkboard content along with a small video of the instructor. As a result, two areas of the screen are competing for the viewer's attention, causing the widely known split-attention effect. Face and body gestures, such as pointing, do not appear in the context of the slides or the board. To eliminate this problem, this article proposes to extract the lecturer from the video stream and paste his or her image onto the board or slide image. As a result, the lecturer acting in front of the board or slides becomes the center of attention. The entire lecture presentation becomes more human-centered. This article presents both an analysis of the underlying psychological problems and an explanation of signal processing techniques that are applied in a concrete system. The presented algorithm is able to extract and overlay the lecturer online and in real time at full video resolution.

  3. Classifying smoke in laparoscopic videos using SVM

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    Alshirbaji Tamer Abdulbaki

    2017-09-01

    Full Text Available Smoke in laparoscopic videos usually appears due to the use of electrocautery when cutting or coagulating tissues. Therefore, detecting smoke can be used for event-based annotation in laparoscopic surgeries by retrieving the events associated with the electrocauterization. Furthermore, smoke detection can also be used for automatic smoke removal. However, detecting smoke in laparoscopic video is a challenge because of the changeability of smoke patterns, the moving camera and the different lighting conditions. In this paper, we present a video-based smoke detection algorithm to detect smoke of different densities such as fog, low and high density in laparoscopic videos. The proposed method depends on extracting various visual features from the laparoscopic images and providing them to support vector machine (SVM classifier. Features are based on motion, colour and texture patterns of the smoke. We validated our algorithm using experimental evaluation on four laparoscopic cholecystectomy videos. These four videos were manually annotated by defining every frame as smoke or non-smoke frame. The algorithm was applied to the videos by using different feature combinations for classification. Experimental results show that the combination of all proposed features gives the best classification performance. The overall accuracy (i.e. correctly classified frames is around 84%, with the sensitivity (i.e. correctly detected smoke frames and the specificity (i.e. correctly detected non-smoke frames are 89% and 80%, respectively.

  4. ZK DrugResist 2.0: A TextMiner to extract semantic relations of drug resistance from PubMed.

    Science.gov (United States)

    Khalid, Zoya; Sezerman, Osman Ugur

    2017-05-01

    Extracting useful knowledge from an unstructured textual data is a challenging task for biologists, since biomedical literature is growing exponentially on a daily basis. Building an automated method for such tasks is gaining much attention of researchers. ZK DrugResist is an online tool that automatically extracts mutations and expression changes associated with drug resistance from PubMed. In this study we have extended our tool to include semantic relations extracted from biomedical text covering drug resistance and established a server including both of these features. Our system was tested for three relations, Resistance (R), Intermediate (I) and Susceptible (S) by applying hybrid feature set. From the last few decades the focus has changed to hybrid approaches as it provides better results. In our case this approach combines rule-based methods with machine learning techniques. The results showed 97.67% accuracy with 96% precision, recall and F-measure. The results have outperformed the previously existing relation extraction systems thus can facilitate computational analysis of drug resistance against complex diseases and further can be implemented on other areas of biomedicine. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Modelling and extraction of variability in free-text medication prescriptions from an anonymised primary care electronic medical record research database.

    Science.gov (United States)

    Karystianis, George; Sheppard, Therese; Dixon, William G; Nenadic, Goran

    2016-02-09

    Free-text medication prescriptions contain detailed instruction information that is key when preparing drug data for analysis. The objective of this study was to develop a novel model and automated text-mining method to extract detailed structured medication information from free-text prescriptions and explore their variability (e.g. optional dosages) in primary care research databases. We introduce a prescription model that provides minimum and maximum values for dose number, frequency and interval, allowing modelling variability and flexibility within a drug prescription. We developed a text mining system that relies on rules to extract such structured information from prescription free-text dosage instructions. The system was applied to medication prescriptions from an anonymised primary care electronic record database (Clinical Practice Research Datalink, CPRD). We have evaluated our approach on a test set of 220 CPRD prescription free-text directions. The system achieved an overall accuracy of 91 % at the prescription level, with 97 % accuracy across the attribute levels. We then further analysed over 56,000 most common free text prescriptions from CPRD records and found that 1 in 4 has inherent variability, i.e. a choice in taking medication specified by different minimum and maximum doses, duration or frequency. Our approach provides an accurate, automated way of coding prescription free text information, including information about flexibility and variability within a prescription. The method allows the researcher to decide how best to prepare the prescription data for drug efficacy and safety analyses in any given setting, and test various scenarios and their impact.

  6. Combining Recurrence Analysis and Automatic Movement Extraction from Video Recordings to Study Behavioral Coupling in Face-to-Face Parent-Child Interactions.

    Science.gov (United States)

    López Pérez, David; Leonardi, Giuseppe; Niedźwiecka, Alicja; Radkowska, Alicja; Rączaszek-Leonardi, Joanna; Tomalski, Przemysław

    2017-01-01

    The analysis of parent-child interactions is crucial for the understanding of early human development. Manual coding of interactions is a time-consuming task, which is a limitation in many projects. This becomes especially demanding if a frame-by-frame categorization of movement needs to be achieved. To overcome this, we present a computational approach for studying movement coupling in natural settings, which is a combination of a state-of-the-art automatic tracker, Tracking-Learning-Detection (TLD), and nonlinear time-series analysis, Cross-Recurrence Quantification Analysis (CRQA). We investigated the use of TLD to extract and automatically classify movement of each partner from 21 video recordings of interactions, where 5.5-month-old infants and mothers engaged in free play in laboratory settings. As a proof of concept, we focused on those face-to-face episodes, where the mother animated an object in front of the infant, in order to measure the coordination between the infants' head movement and the mothers' hand movement. We also tested the feasibility of using such movement data to study behavioral coupling between partners with CRQA. We demonstrate that movement can be extracted automatically from standard definition video recordings and used in subsequent CRQA to quantify the coupling between movement of the parent and the infant. Finally, we assess the quality of this coupling using an extension of CRQA called anisotropic CRQA and show asymmetric dynamics between the movement of the parent and the infant. When combined these methods allow automatic coding and classification of behaviors, which results in a more efficient manner of analyzing movements than manual coding.

  7. SECRETS OF SONG VIDEO

    Directory of Open Access Journals (Sweden)

    Chernyshov Alexander V.

    2014-04-01

    Full Text Available The article focuses on the origins of the song videos as TV and Internet-genre. In addition, it considers problems of screen images creation depending on the musical form and the text of a songs in connection with relevant principles of accent and phraseological video editing and filming techniques as well as with additional frames and sound elements.

  8. Segmentation Based Video Steganalysis to Detect Motion Vector Modification

    Directory of Open Access Journals (Sweden)

    Peipei Wang

    2017-01-01

    Full Text Available This paper presents a steganalytic approach against video steganography which modifies motion vector (MV in content adaptive manner. Current video steganalytic schemes extract features from fixed-length frames of the whole video and do not take advantage of the content diversity. Consequently, the effectiveness of the steganalytic feature is influenced by video content and the problem of cover source mismatch also affects the steganalytic performance. The goal of this paper is to propose a steganalytic method which can suppress the differences of statistical characteristics caused by video content. The given video is segmented to subsequences according to block’s motion in every frame. The steganalytic features extracted from each category of subsequences with close motion intensity are used to build one classifier. The final steganalytic result can be obtained by fusing the results of weighted classifiers. The experimental results have demonstrated that our method can effectively improve the performance of video steganalysis, especially for videos of low bitrate and low embedding ratio.

  9. Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER)system.

    Science.gov (United States)

    Pandey, Abhishek; Kreimeyer, Kory; Foster, Matthew; Botsis, Taxiarchis; Dang, Oanh; Ly, Thomas; Wang, Wei; Forshee, Richard

    2018-01-01

    Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

  10. A Standard-Compliant Virtual Meeting System with Active Video Object Tracking

    Directory of Open Access Journals (Sweden)

    Chang Yao-Jen

    2002-01-01

    Full Text Available This paper presents an H.323 standard compliant virtual video conferencing system. The proposed system not only serves as a multipoint control unit (MCU for multipoint connection but also provides a gateway function between the H.323 LAN (local-area network and the H.324 WAN (wide-area network users. The proposed virtual video conferencing system provides user-friendly object compositing and manipulation features including 2D video object scaling, repositioning, rotation, and dynamic bit-allocation in a 3D virtual environment. A reliable, and accurate scheme based on background image mosaics is proposed for real-time extracting and tracking foreground video objects from the video captured with an active camera. Chroma-key insertion is used to facilitate video objects extraction and manipulation. We have implemented a prototype of the virtual conference system with an integrated graphical user interface to demonstrate the feasibility of the proposed methods.

  11. Seafloor video footage and still-frame grabs from U.S. Geological Survey cruises in Hawaiian nearshore waters

    Science.gov (United States)

    Gibbs, Ann E.; Cochran, Susan A.; Tierney, Peter W.

    2013-01-01

    Underwater video footage was collected in nearshore waters (video footage collected during four USGS cruises and more than 10,200 still images extracted from the videos, including still frames from every 10 seconds along transect lines, and still frames showing both an overview and a near-bottom view from fixed stations. Environmental Systems Research Institute (ESRI) shapefiles of individual video and still-image locations, and Google Earth kml files with explanatory text and links to the video and still images, are included. This report documents the various camera systems and methods used to collect the videos, and the techniques and software used to convert the analog video tapes into digital data in order to process the images for optimum viewing and to extract the still images, along with a brief summary of each survey cruise.

  12. Reflections on academic video

    Directory of Open Access Journals (Sweden)

    Thommy Eriksson

    2012-11-01

    Full Text Available As academics we study, research and teach audiovisual media, yet rarely disseminate and mediate through it. Today, developments in production technologies have enabled academic researchers to create videos and mediate audiovisually. In academia it is taken for granted that everyone can write a text. Is it now time to assume that everyone can make a video essay? Using the online journal of academic videos Audiovisual Thinking and the videos published in it as a case study, this article seeks to reflect on the emergence and legacy of academic audiovisual dissemination. Anchoring academic video and audiovisual dissemination of knowledge in two critical traditions, documentary theory and semiotics, we will argue that academic video is in fact already present in a variety of academic disciplines, and that academic audiovisual essays are bringing trends and developments that have long been part of academic discourse to their logical conclusion.

  13. Video Inter-frame Forgery Identification Based on Optical Flow Consistency

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    Qi Wang

    2014-03-01

    Full Text Available Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the optical flows are consistent in an original video, while in forgeries the consistency will be destroyed. We first extract optical flow from frames of videos and then calculate the optical flow consistency after normalization and quantization as distinguishing feature to identify inter-frame forgeries. We train the Support Vector Machine to classify original videos and video forgeries with optical flow consistency feature of some sample videos and test the classification accuracy in a large database. Experimental results show that the proposed method is efficient in classifying original videos and forgeries. Furthermore, the proposed method performs also pretty well in classifying frame insertion and frame deletion forgeries.

  14. Video Shot Boundary Recognition Based on Adaptive Locality Preserving Projections

    Directory of Open Access Journals (Sweden)

    Yongliang Xiao

    2013-01-01

    Full Text Available A novel video shot boundary recognition method is proposed, which includes two stages of video feature extraction and shot boundary recognition. Firstly, we use adaptive locality preserving projections (ALPP to extract video feature. Unlike locality preserving projections, we define the discriminating similarity with mode prior probabilities and adaptive neighborhood selection strategy which make ALPP more suitable to preserve the local structure and label information of the original data. Secondly, we use an optimized multiple kernel support vector machine to classify video frames into boundary and nonboundary frames, in which the weights of different types of kernels are optimized with an ant colony optimization method. Experimental results show the effectiveness of our method.

  15. Automatic Person Identification in Camera Video by Motion Correlation

    Directory of Open Access Journals (Sweden)

    Dingbo Duan

    2014-01-01

    Full Text Available Person identification plays an important role in semantic analysis of video content. This paper presents a novel method to automatically label persons in video sequence captured from fixed camera. Instead of leveraging traditional face recognition approaches, we deal with the task of person identification by fusing information from motion sensor platforms, like smart phones, carried on human bodies and extracted from camera video. More specifically, a sequence of motion features extracted from camera video are compared with each of those collected from accelerometers of smart phones. When strong correlation is detected, identity information transmitted from the corresponding smart phone is used to identify the phone wearer. To test the feasibility and efficiency of the proposed method, extensive experiments are conducted which achieved impressive performance.

  16. H.264/AVC Video Compressed Traces: Multifractal and Fractal Analysis

    Directory of Open Access Journals (Sweden)

    Samčović Andreja

    2006-01-01

    Full Text Available Publicly available long video traces encoded according to H.264/AVC were analyzed from the fractal and multifractal points of view. It was shown that such video traces, as compressed videos (H.261, H.263, and MPEG-4 Version 2 exhibit inherent long-range dependency, that is, fractal, property. Moreover they have high bit rate variability, particularly at higher compression ratios. Such signals may be better characterized by multifractal (MF analysis, since this approach describes both local and global features of the process. From multifractal spectra of the frame size video traces it was shown that higher compression ratio produces broader and less regular MF spectra, indicating to higher MF nature and the existence of additive components in video traces. Considering individual frames (I, P, and B and their MF spectra one can approve additive nature of compressed video and the particular influence of these frames to a whole MF spectrum. Since compressed video occupies a main part of transmission bandwidth, results obtained from MF analysis of compressed video may contribute to more accurate modeling of modern teletraffic. Moreover, by appropriate choice of the method for estimating MF quantities, an inverse MF analysis is possible, that means, from a once derived MF spectrum of observed signal it is possible to recognize and extract parts of the signal which are characterized by particular values of multifractal parameters. Intensive simulations and results obtained confirm the applicability and efficiency of MF analysis of compressed video.

  17. Video microblogging

    DEFF Research Database (Denmark)

    Bornoe, Nis; Barkhuus, Louise

    2010-01-01

    Microblogging is a recently popular phenomenon and with the increasing trend for video cameras to be built into mobile phones, a new type of microblogging has entered the arena of electronic communication: video microblogging. In this study we examine video microblogging, which is the broadcasting...... of short videos. A series of semi-structured interviews offers an understanding of why and how video microblogging is used and what the users post and broadcast....

  18. Olympic Coast National Marine Sanctuary - stil120_0602a - Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during September 2006. Video data...

  19. still116_0501n-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vesselTatoosh during August 2005. Video data from...

  20. still116_0501d-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  1. still116_0501c-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  2. still116_0501s-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  3. still114_0402c-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  4. still115_0403-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  5. still114_0402b-- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfitted with video equipment (and other devices) was deployed from the NOAA research vessel Tatoosh during August 2005. Video data from...

  6. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... Grants and Funding Extramural Research Division of Extramural Science Programs Division of Extramural Activities Extramural Contacts NEI ... Amaurosis Low Vision Refractive Errors Retinopathy of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded ...

  7. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five ... was designed to help you learn more about Rheumatoid Arthritis (RA). You will learn how the diagnosis ...

  8. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... Our Staff Rheumatology Specialty Centers You are here: Home / Patient Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video ... to take a more active role in your care. The information in these videos should not take ...

  9. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... will allow you to take a more active role in your care. The information in these videos ... Stategies to Increase your Level of Physical Activity Role of Body Weight in Osteoarthritis Educational Videos for ...

  10. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... here. Will You Support the Education of Arthritis Patients? Each year, over 1 million people visit this ... of Body Weight in Osteoarthritis Educational Videos for Patients Rheumatoid Arthritis Educational Video Series Psoriatic Arthritis 101 ...

  11. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... listen? see more videos from Veterans Health Administration 1 Act see more videos from Veterans Health Administration ... videos from Veterans Health Administration The Power of 1 PSA see more videos from Veterans Health Administration ...

  12. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... videos about getting help. Be There: Help Save a Life see more videos from Veterans Health Administration ... listen? see more videos from Veterans Health Administration 1 Act see more videos from Veterans Health Administration ...

  13. Video demystified

    CERN Document Server

    Jack, Keith

    2004-01-01

    This international bestseller and essential reference is the "bible" for digital video engineers and programmers worldwide. This is by far the most informative analog and digital video reference available, includes the hottest new trends and cutting-edge developments in the field. Video Demystified, Fourth Edition is a "one stop" reference guide for the various digital video technologies. The fourth edition is completely updated with all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video (Video over DSL, Ethernet, etc.), as well as discussions of the latest standards throughout. The accompanying CD-ROM is updated to include a unique set of video test files in the newest formats. *This essential reference is the "bible" for digital video engineers and programmers worldwide *Contains all new chapters on MPEG-4, H.264, SDTV/HDTV, ATSC/DVB, and Streaming Video *Completely revised with all the latest and most up-to-date industry standards.

  14. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork Peer Support Program Community Connections Overview ... group Back Upcoming events Video Library Photo Gallery One-on-One Support Back ANetwork Peer Support Program ...

  15. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... support group for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork Peer ... group for me? Find a group Back Upcoming events Video Library Photo Gallery One-on-One Support Back ANetwork ...

  16. E-text

    DEFF Research Database (Denmark)

    Finnemann, Niels Ole

    2018-01-01

    the print medium, rather than written text or speech. In late 20th century, the notion of text was subject to increasing criticism as in the question raised within literary text theory: is there a text in this class? At the same time, the notion was expanded by including extra linguistic sign modalities...... (images, videos). Thus, a basic question is this: should electronic text be included in the expanded notion of text as a new digital sign modality added to the repertoire of modalities, or should it be included as a sign modality, which is both an independent modality and a container in which other...

  17. Video Shot Boundary Detection based on Multifractal Analisys

    Directory of Open Access Journals (Sweden)

    B. D. Reljin

    2011-11-01

    Full Text Available Extracting video shots is an essential preprocessing step to almost all video analysis, indexing, and other content-based operations. This process is equivalent to detecting the shot boundaries in a video. In this paper we presents video Shot Boundary Detection (SBD based on Multifractal Analysis (MA. Low-level features (color and texture features are extracted from each frame in video sequence. Features are concatenated in feature vectors (FVs and stored in feature matrix. Matrix rows correspond to FVs of frames from video sequence, while columns are time series of particular FV component. Multifractal analysis is applied to FV component time series, and shot boundaries are detected as high singularities of time series above pre defined treshold. Proposed SBD method is tested on real video sequence with 64 shots, with manually labeled shot boundaries. Detection accuracy depends on number FV components used. For only one FV component detection accuracy lies in the range 76-92% (depending on selected threshold, while by combining two FV components all shots are detected completely (accuracy of 100%.

  18. Representing videos in tangible products

    Science.gov (United States)

    Fageth, Reiner; Weiting, Ralf

    2014-03-01

    Videos can be taken with nearly every camera, digital point and shoot cameras, DSLRs as well as smartphones and more and more with so-called action cameras mounted on sports devices. The implementation of videos while generating QR codes and relevant pictures out of the video stream via a software implementation was contents in last years' paper. This year we present first data about what contents is displayed and how the users represent their videos in printed products, e.g. CEWE PHOTOBOOKS and greeting cards. We report the share of the different video formats used, the number of images extracted out of the video in order to represent the video, the positions in the book and different design strategies compared to regular books.

  19. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia Animations Blindness Cataract Convergence Insufficiency Diabetic Eye Disease Dilated Eye Exam Dry Eye For Kids Glaucoma ...

  20. SPECIAL REPORT: Creating Conference Video

    Directory of Open Access Journals (Sweden)

    Noel F. Peden

    2008-12-01

    Full Text Available Capturing video at a conference is easy. Doing it so the product is useful is another matter. Many subtle problems come into play so that video and audio obtained can be used to create a final product. This article discusses what the author learned in the two years of shooting and editing video for Code4Lib conference.

  1. Video Games and Digital Literacies

    Science.gov (United States)

    Steinkuehler, Constance

    2010-01-01

    Today's youth are situated in a complex information ecology that includes video games and print texts. At the basic level, video game play itself is a form of digital literacy practice. If we widen our focus from the "individual player + technology" to the online communities that play them, we find that video games also lie at the nexus of a…

  2. Rheumatoid Arthritis Educational Video Series

    Medline Plus

    Full Text Available ... Corner / Patient Webcasts / Rheumatoid Arthritis Educational Video Series Rheumatoid Arthritis Educational Video Series This series of five videos ... Your Arthritis Managing Chronic Pain and Depression in Arthritis Nutrition & Rheumatoid Arthritis Arthritis and Health-related Quality of Life ...

  3. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Care Disease Types FAQ Handout for Patients and Families Is It Right for You How to Get ... For the Media For Clinicians For Policymakers For Family Caregivers Glossary Menu In this section Links Videos ...

  4. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Donate Search Search What Is It Definition Pediatric Palliative Care Disease Types FAQ Handout for Patients and Families ... Policymakers For Family Caregivers Glossary Resources Browse our palliative care resources below: Links Videos Podcasts Webinars For the ...

  5. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Click to learn more... LOGIN CALENDAR DONATE NEWS Home Learn Back Learn about acoustic neuroma AN Facts ... Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video Ronson and Kerri Albany Support ...

  6. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Donate Search Search What Is It Definition Pediatric Palliative Care Disease Types FAQ Handout for Patients and ... Policymakers For Family Caregivers Glossary Resources Browse our palliative care resources below: Links Videos Podcasts Webinars For ...

  7. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Click to learn more... LOGIN CALENDAR DONATE NEWS Home Learn Back Learn about acoustic neuroma AN Facts ... Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video Howard of NJ Gloria hiking ...

  8. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Mission, Vision & Values Shop ANA Leadership & Staff Annual Reports Acoustic Neuroma Association 600 Peachtree Parkway Suite 108 ... About ANA Mission, Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video English English ...

  9. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Disease Types Stories FAQ Handout for Patients and Families Is It Right for You How to Get ... For the Media For Clinicians For Policymakers For Family Caregivers Glossary Menu In this section Links Videos ...

  10. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Search Search What Is It Definition Pediatric Palliative Care Disease Types FAQ Handout for Patients and Families ... For Family Caregivers Glossary Resources Browse our palliative care resources below: Links Videos Podcasts Webinars For the ...

  11. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Educational Video Scott at the Grand Canyon Proton Center load more hold SHIFT key to load all load all Stay Connected with ANA Newly Diagnosed Living with AN Healthcare Providers Acoustic Neuroma Association Donate Now Newly Diagnosed ...

  12. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... a patient kit Keywords Join/Renew Programs Back Support Groups Is a support group for me? Find ... Events Video Library Photo Gallery One-on-One Support ANetwork Peer Support Program Community Connections Overview Find ...

  13. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Click to learn more... LOGIN CALENDAR DONATE NEWS Home Learn Back Learn about acoustic neuroma AN Facts ... Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video English English Arabic Catalan Chinese ( ...

  14. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... to your Doctor Find a Provider Meet the Team Blog Articles & Stories News Resources Links Videos Podcasts ... to your Doctor Find a Provider Meet the Team Blog Articles & Stories News Provider Directory Donate Resources ...

  15. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Click to learn more... LOGIN CALENDAR DONATE NEWS Home Learn Back Learn about acoustic neuroma AN Facts ... Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video Keck Medicine of USC ANWarriors ...

  16. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... illness: Toby’s palliative care story Access the Provider Directory Handout for Patients and Families Is it Right ... Provider Meet the Team Blog Articles News Provider Directory Donate Resources Links Videos Podcasts Webinars For the ...

  17. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Click to learn more... LOGIN EVENTS DONATE NEWS Home Learn Back Learn about acoustic neuroma AN Facts ... Vision & Values Leadership & Staff Annual Reports Shop ANA Home Learn Educational Video Scott at the Grand Canyon ...

  18. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Is a support group for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork Peer Support Program Community Connections Overview Find a Meeting ...

  19. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... All rights reserved. GetPalliativeCare.org does not provide medical advice, diagnosis or treatment. ... the Team Blog Articles & Stories News Provider Directory Donate Resources Links Videos ...

  20. Digital video.

    Science.gov (United States)

    Johnson, Don; Johnson, Mike

    2004-04-01

    The process of digital capture, editing, and archiving video has become an important aspect of documenting arthroscopic surgery. Recording the arthroscopic findings before and after surgery is an essential part of the patient's medical record. The hardware and software has become more reasonable to purchase, but the learning curve to master the software is steep. Digital video is captured at the time of arthroscopy to a hard disk, and written to a CD at the end of the operative procedure. The process of obtaining video of open procedures is more complex. Outside video of the procedure is recorded on digital tape with a digital video camera. The camera must be plugged into a computer to capture the video on the hard disk. Adobe Premiere software is used to edit the video and render the finished video to the hard drive. This finished video is burned onto a CD. We outline the choice of computer hardware and software for the manipulation of digital video. The techniques of backup and archiving the completed projects and files also are outlined. The uses of digital video for education and the formats that can be used in PowerPoint presentations are discussed.

  1. Automated analysis and annotation of basketball video

    Science.gov (United States)

    Saur, Drew D.; Tan, Yap-Peng; Kulkarni, Sanjeev R.; Ramadge, Peter J.

    1997-01-01

    Automated analysis and annotation of video sequences are important for digital video libraries, content-based video browsing and data mining projects. A successful video annotation system should provide users with useful video content summary in a reasonable processing time. Given the wide variety of video genres available today, automatically extracting meaningful video content for annotation still remains hard by using current available techniques. However, a wide range video has inherent structure such that some prior knowledge about the video content can be exploited to improve our understanding of the high-level video semantic content. In this paper, we develop tools and techniques for analyzing structured video by using the low-level information available directly from MPEG compressed video. Being able to work directly in the video compressed domain can greatly reduce the processing time and enhance storage efficiency. As a testbed, we have developed a basketball annotation system which combines the low-level information extracted from MPEG stream with the prior knowledge of basketball video structure to provide high level content analysis, annotation and browsing for events such as wide- angle and close-up views, fast breaks, steals, potential shots, number of possessions and possession times. We expect our approach can also be extended to structured video in other domains.

  2. Video quality assessment for web content mirroring

    Science.gov (United States)

    He, Ye; Fei, Kevin; Fernandez, Gustavo A.; Delp, Edward J.

    2014-03-01

    Due to the increasing user expectation on watching experience, moving web high quality video streaming content from the small screen in mobile devices to the larger TV screen has become popular. It is crucial to develop video quality metrics to measure the quality change for various devices or network conditions. In this paper, we propose an automated scoring system to quantify user satisfaction. We compare the quality of local videos with the videos transmitted to a TV. Four video quality metrics, namely Image Quality, Rendering Quality, Freeze Time Ratio and Rate of Freeze Events are used to measure video quality change during web content mirroring. To measure image quality and rendering quality, we compare the matched frames between the source video and the destination video using barcode tools. Freeze time ratio and rate of freeze events are measured after extracting video timestamps. Several user studies are conducted to evaluate the impact of each objective video quality metric on the subjective user watching experience.

  3. Immersive video

    Science.gov (United States)

    Moezzi, Saied; Katkere, Arun L.; Jain, Ramesh C.

    1996-03-01

    Interactive video and television viewers should have the power to control their viewing position. To make this a reality, we introduce the concept of Immersive Video, which employs computer vision and computer graphics technologies to provide remote users a sense of complete immersion when viewing an event. Immersive Video uses multiple videos of an event, captured from different perspectives, to generate a full 3D digital video of that event. That is accomplished by assimilating important information from each video stream into a comprehensive, dynamic, 3D model of the environment. Using this 3D digital video, interactive viewers can then move around the remote environment and observe the events taking place from any desired perspective. Our Immersive Video System currently provides interactive viewing and `walkthrus' of staged karate demonstrations, basketball games, dance performances, and typical campus scenes. In its full realization, Immersive Video will be a paradigm shift in visual communication which will revolutionize television and video media, and become an integral part of future telepresence and virtual reality systems.

  4. Obscene Video Recognition Using Fuzzy SVM and New Sets of Features

    Directory of Open Access Journals (Sweden)

    Alireza Behrad

    2013-02-01

    Full Text Available In this paper, a novel approach for identifying normal and obscene videos is proposed. In order to classify different episodes of a video independently and discard the need to process all frames, first, key frames are extracted and skin regions are detected for groups of video frames starting with key frames. In the second step, three different features including 1- structural features based on single frame information, 2- features based on spatiotemporal volume and 3-motion-based features, are extracted for each episode of video. The PCA-LDA method is then applied to reduce the size of structural features and select more distinctive features. For the final step, we use fuzzy or a Weighted Support Vector Machine (WSVM classifier to identify video episodes. We also employ a multilayer Kohonen network as an initial clustering algorithm to increase the ability to discriminate between the extracted features into two classes of videos. Features based on motion and periodicity characteristics increase the efficiency of the proposed algorithm in videos with bad illumination and skin colour variation. The proposed method is evaluated using 1100 videos in different environmental and illumination conditions. The experimental results show a correct recognition rate of 94.2% for the proposed algorithm.

  5. Diversity-Aware Multi-Video Summarization

    Science.gov (United States)

    Panda, Rameswar; Mithun, Niluthpol Chowdhury; Roy-Chowdhury, Amit K.

    2017-10-01

    Most video summarization approaches have focused on extracting a summary from a single video; we propose an unsupervised framework for summarizing a collection of videos. We observe that each video in the collection may contain some information that other videos do not have, and thus exploring the underlying complementarity could be beneficial in creating a diverse informative summary. We develop a novel diversity-aware sparse optimization method for multi-video summarization by exploring the complementarity within the videos. Our approach extracts a multi-video summary which is both interesting and representative in describing the whole video collection. To efficiently solve our optimization problem, we develop an alternating minimization algorithm that minimizes the overall objective function with respect to one video at a time while fixing the other videos. Moreover, we introduce a new benchmark dataset, Tour20, that contains 140 videos with multiple human created summaries, which were acquired in a controlled experiment. Finally, by extensive experiments on the new Tour20 dataset and several other multi-view datasets, we show that the proposed approach clearly outperforms the state-of-the-art methods on the two problems-topic-oriented video summarization and multi-view video summarization in a camera network.

  6. Video games

    OpenAIRE

    Kolář, Vojtěch

    2012-01-01

    This thesis is based on a detailed analysis of various topics related to the question of whether video games can be art. In the first place it analyzes the current academic discussion on this subject and confronts different opinions of both supporters and objectors of the idea, that video games can be a full-fledged art form. The second point of this paper is to analyze the properties, that are inherent to video games, in order to find the reason, why cultural elite considers video games as i...

  7. Robust video object cosegmentation.

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing; Li, Xuelong; Porikli, Fatih

    2015-10-01

    With ever-increasing volumes of video data, automatic extraction of salient object regions became even more significant for visual analytic solutions. This surge has also opened up opportunities for taking advantage of collective cues encapsulated in multiple videos in a cooperative manner. However, it also brings up major challenges, such as handling of drastic appearance, motion pattern, and pose variations, of foreground objects as well as indiscriminate backgrounds. Here, we present a cosegmentation framework to discover and segment out common object regions across multiple frames and multiple videos in a joint fashion. We incorporate three types of cues, i.e., intraframe saliency, interframe consistency, and across-video similarity into an energy optimization framework that does not make restrictive assumptions on foreground appearance and motion model, and does not require objects to be visible in all frames. We also introduce a spatio-temporal scale-invariant feature transform (SIFT) flow descriptor to integrate across-video correspondence from the conventional SIFT-flow into interframe motion flow from optical flow. This novel spatio-temporal SIFT flow generates reliable estimations of common foregrounds over the entire video data set. Experimental results show that our method outperforms the state-of-the-art on a new extensive data set (ViCoSeg).

  8. Text Mining.

    Science.gov (United States)

    Trybula, Walter J.

    1999-01-01

    Reviews the state of research in text mining, focusing on newer developments. The intent is to describe the disparate investigations currently included under the term text mining and provide a cohesive structure for these efforts. A summary of research identifies key organizations responsible for pushing the development of text mining. A section…

  9. Twofold Video Hashing with Automatic Synchronization

    OpenAIRE

    Li, Mu; Monga, Vishal

    2014-01-01

    Video hashing finds a wide array of applications in content authentication, robust retrieval and anti-piracy search. While much of the existing research has focused on extracting robust and secure content descriptors, a significant open challenge still remains: Most existing video hashing methods are fallible to temporal desynchronization. That is, when the query video results by deleting or inserting some frames from the reference video, most existing methods assume the positions of the dele...

  10. Contextual analysis of videos

    CERN Document Server

    Thida, Myo; Monekosso, Dorothy

    2013-01-01

    Video context analysis is an active and vibrant research area, which provides means for extracting, analyzing and understanding behavior of a single target and multiple targets. Over the last few decades, computer vision researchers have been working to improve the accuracy and robustness of algorithms to analyse the context of a video automatically. In general, the research work in this area can be categorized into three major topics: 1) counting number of people in the scene 2) tracking individuals in a crowd and 3) understanding behavior of a single target or multiple targets in the scene.

  11. Olympic Coast National Marine Sanctuary - stil110_0204c - Still frame shots of sediment extracted from video for survey area 110_0204c

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfit with video equipment, lasers and lights was deployed from the NOAA research vessel Tatoosh during the month of September 2006 and...

  12. Olympic Coast National Marine Sanctuary - stil110_0204a - Still frame shots of sediment extracted from video for survey area 110_0204a.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A custom built camera sled outfit with video equipment, lasers and lights was deployed from the NOAA research vessel Tatoosh during the month of September 2006 and...

  13. stil113_0401p -- Still frame locations of sediment extracted from video imagery collected by Delta submersible in September 2001.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Delta submersible vehicle, outfitted with video equipment (and other devices), was deployed from the R/V Auriga during September 2001 to monitor seafloor...

  14. Object classification methods for application in FPGA based vehicle video detector

    Directory of Open Access Journals (Sweden)

    Wiesław PAMUŁA

    2009-01-01

    Full Text Available The paper presents a discussion of properties of object classification methods utilized in processing video streams from a camera. Methods based on feature extraction, model fitting and invariant determination are evaluated. Petri nets are used for modelling the processing flow. Data objects and transitions are defined which are suitable for efficient implementation in FPGA circuits. Processing characteristics and problems of the implementations are shown. An invariant based method is assessed as most suitable for application in a vehicle video detector.

  15. Analisis dan Simulasi Video Watermarking Menggunakan Metode Dual Tree Complex Wavelet Transform (DT-CWT dan Singular Value Decomposition (SVD

    Directory of Open Access Journals (Sweden)

    Arina Fadhilah

    2016-08-01

    Full Text Available Video piracy is the act of obtaining, copying, and selling or distributing videos that already had the copyright without the consent of the copyright owner. Watermarking is a process which embeds an additional information in the host video signal so that the embedded watermark cannot be seen and difficult to be erased or altered. Video watermarking in this journal used a mp4 format video and two different watermark images. Host video frames are divided into two equal lots, some of the frames are embedded by watermark image 1, and the others are embedded by watermark images 2. The methods used are Dual-Tree Complex Wavelet Transform (DTCWT and Singular Value Decomposition (SVD. The two watermarks are embedded and extracted in each subband at a depth level 1 to level 4 DTCWT - SVD with the aim of seeking the best subband and the best level for embedding and extracting. In the extraction testing, watermarked video is given several attacks before extraction process. Based on the MOS and PSNR value the DTCWT-SVD level for embedding process is level 4, and based on the MOS and MSE value, the best extraction images are produced from the level 3. The best subband for embedding watermark are the subbands with three parts such as {1,5}{1,1}{1,2} and {1,5}{1,2}{1,2}.

  16. Video Podcasts

    DEFF Research Database (Denmark)

    Nortvig, Anne Mette; Sørensen, Birgitte Holm

    2016-01-01

    This project’s aim was to support and facilitate master’s students’ preparation and collaboration by making video podcasts of short lectures available on YouTube prior to students’ first face-to-face seminar. The empirical material stems from group interviews, from statistical data created through...... YouTube analytics and from surveys answered by students after the seminar. The project sought to explore how video podcasts support learning and reflection online and how students use and reflect on the integration of online activities in the videos. Findings showed that students engaged actively...

  17. A Neuromorphic System for Video Object Recognition

    Directory of Open Access Journals (Sweden)

    Deepak eKhosla

    2014-11-01

    Full Text Available Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS, is inspired by recent findings in computational neuroscience on feed-forward object detection and classification pipelines for processing and extracting relevant information from visual data. The NEOVUS architecture is inspired by the ventral (what and dorsal (where streams of the mammalian visual pathway and combines retinal processing, form-based and motion-based object detection, and convolutional neural nets based object classification. Our system was evaluated by the Defense Advanced Research Projects Agency (DARPA under the NEOVISION2 program on a variety of urban area video datasets collected from both stationary and moving platforms. The datasets are challenging as they include a large number of targets in cluttered scenes with varying illumination and occlusion conditions. The NEOVUS system was also mapped to commercially available off-the-shelf hardware. The dynamic power requirement for the system that includes a 5.6Mpixel retinal camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W, for an effective energy consumption of 5.4 nanoJoules (nJ per bit of incoming video. In a systematic evaluation of five different teams by DARPA on three aerial datasets, the NEOVUS demonstrated the best performance with the highest recognition accuracy and at least three orders of magnitude lower energy consumption than two independent state of the art computer vision systems. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition towards enabling practical low-power and mobile video processing applications.

  18. 61214++++','DOAJ-ART-EN'); return false;" href="+++++https://jual.nipissingu.ca/wp-content/uploads/sites/25/2014/06/v61214.m4v">61214++++">Jailed - Video

    Directory of Open Access Journals (Sweden)

    Cameron CULBERT

    2012-07-01

    Full Text Available As the public education system in Northern Ontario continues to take a downward spiral, a plethora of secondary school students are being placed in an alternative educational environment. Juxtaposing the two educational settings reveals very similar methods and characteristics of educating our youth as opposed to using a truly alternative approach to education. This video reviews the relationship between public education and alternative education in a remote Northern Ontario setting. It is my belief that the traditional methods of teaching are not appropriate in educating at risk students in alternative schools. Paper and pencil worksheets do not motivate these students to learn and succeed. Alternative education should emphasize experiential learning, a just in time curriculum based on every unique individual and the students true passion for everyday life. Cameron Culbert was born on February 3rd, 1977 in North Bay, Ontario. His teenage years were split between attending public school and his willed curriculum on the ski hill. Culbert spent 10 years (1996-2002 & 2006-2010 competing for Canada as an alpine ski racer. His passion for teaching and coaching began as an athlete and has now transferred into the classroom and the community. As a graduate of Nipissing University (BA, BEd, MEd. Camerons research interests are alternative education, physical education and technology in the classroom. Currently Cameron is an active educator and coach in Northern Ontario.

  19. Visual instance mining of news videos using a graph-based approach

    OpenAIRE

    Almendros Gutiérrez, David

    2014-01-01

    [ANGLÈS] The aim of this thesis is to design a tool that performs visual instance search mining for news video summarization. This means to extract the relevant content of the video in order to be able to recognize the storyline of the news. Initially, a sampling of the video is required to get the frames with a desired rate. Then, different relevant contents are detected from each frame, focusing on faces, text and several objects that the user can select. Next, we use a graph-based clusteri...

  20. Know Stroke: Know the Signs, Act in Time Video

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    Full Text Available ... treatment immediately. View the Video » View the Transcript » Download the Video » Ataque Cerebral Video Loading the player... ... Jose Merino. View the Video » View the Transcript » Download the Video (75,830K) » Home | About the Campaign | ...

  1. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... out for help. Bittersweet More Videos from Veterans Health Administration Watch additional videos about getting help. Behind the Scenes see more videos from Veterans Health Administration Be There: Help Save a Life see ...

  3. Veterans Crisis Line: Videos About Reaching out for Help

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  8. Veterans Crisis Line: Videos About Reaching out for Help

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  10. Veterans Crisis Line: Videos About Reaching out for Help

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  11. Veterans Crisis Line: Videos About Reaching out for Help

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  12. Veterans Crisis Line: Videos About Reaching out for Help

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  13. Veterans Crisis Line: Videos About Reaching out for Help

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  14. Low-Complexity Saliency Detection Algorithm for Fast Perceptual Video Coding

    Directory of Open Access Journals (Sweden)

    Pengyu Liu

    2013-01-01

    Full Text Available A low-complexity saliency detection algorithm for perceptual video coding is proposed; low-level encoding information is adopted as the characteristics of visual perception analysis. Firstly, this algorithm employs motion vector (MV to extract temporal saliency region through fast MV noise filtering and translational MV checking procedure. Secondly, spatial saliency region is detected based on optimal prediction mode distributions in I-frame and P-frame. Then, it combines the spatiotemporal saliency detection results to define the video region of interest (VROI. The simulation results validate that the proposed algorithm can avoid a large amount of computation work in the visual perception characteristics analysis processing compared with other existing algorithms; it also has better performance in saliency detection for videos and can realize fast saliency detection. It can be used as a part of the video standard codec at medium-to-low bit-rates or combined with other algorithms in fast video coding.

  15. Video Pulses: User-Based Modeling of Interesting Video Segments

    Directory of Open Access Journals (Sweden)

    Markos Avlonitis

    2014-01-01

    Full Text Available We present a user-based method that detects regions of interest within a video in order to provide video skims and video summaries. Previous research in video retrieval has focused on content-based techniques, such as pattern recognition algorithms that attempt to understand the low-level features of a video. We are proposing a pulse modeling method, which makes sense of a web video by analyzing users' Replay interactions with the video player. In particular, we have modeled the user information seeking behavior as a time series and the semantic regions as a discrete pulse of fixed width. Then, we have calculated the correlation coefficient between the dynamically detected pulses at the local maximums of the user activity signal and the pulse of reference. We have found that users' Replay activity significantly matches the important segments in information-rich and visually complex videos, such as lecture, how-to, and documentary. The proposed signal processing of user activity is complementary to previous work in content-based video retrieval and provides an additional user-based dimension for modeling the semantics of a social video on the web.

  16. Video Tracking dalam Digital Compositing untuk Paska Produksi Video

    Directory of Open Access Journals (Sweden)

    Ardiyan Ardiyan

    2012-04-01

    Full Text Available Video Tracking is one of the processes in video postproduction and motion picture digitally. The ability of video tracking method in the production is helpful to realize the concept of the visual. It is considered in the process of visual effects making. This paper presents how the tracking process and its benefits in visual needs, especially for video and motion picture production. Some of the things involved in the process of tracking such as failure to do so are made clear in this discussion. 

  17. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Special Needs: Planning for Adulthood (Video) KidsHealth > For Parents > Special Needs: Planning for Adulthood (Video) Print A A A Young adults with special needs have many programs, services, and ...

  18. Celiac Family Health Education Video Series

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    Full Text Available ... Program Growth and Nutrition Program Celiac Disease Program | Videos Contact the Celiac Disease Program 1-617-355- ... live happy and productive lives. Each of our video segments provides practical information about celiac disease from ...

  19. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Search English Español Special Needs: Planning for Adulthood (Video) KidsHealth / For Parents / Special Needs: Planning for Adulthood (Video) Print Young adults with special needs have many ...

  20. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Healthy Drinks for Kids Special Needs: Planning for Adulthood (Video) KidsHealth > For Parents > Special Needs: Planning for Adulthood (Video) Print A A A Young adults with ...

  1. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Health Food & Fitness Diseases & Conditions Infections Drugs & Alcohol School & Jobs Sports Expert Answers (Q&A) Staying Safe Videos for Educators Search English Español Special Needs: Planning for Adulthood (Video) KidsHealth / ...

  2. Video Analysis: Lessons from Professional Video Editing Practice

    Directory of Open Access Journals (Sweden)

    Eric Laurier

    2008-09-01

    Full Text Available In this paper we join a growing body of studies that learn from vernacular video analysts quite what video analysis as an intelligible course of action might be. Rather than pursuing epistemic questions regarding video as a number of other studies of video analysis have done, our concern here is with the crafts of producing the filmic. As such we examine how audio and video clips are indexed and brought to hand during the logging process, how a first assembly of the film is built at the editing bench and how logics of shot sequencing relate to wider concerns of plotting, genre and so on. In its conclusion we make a number of suggestions about the future directions of studying video and film editors at work. URN: urn:nbn:de:0114-fqs0803378

  3. A la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge.

    Science.gov (United States)

    Cherry, Colin; Zhu, Xiaodan; Martin, Joel; de Bruijn, Berry

    2013-01-01

    An analysis of the timing of events is critical for a deeper understanding of the course of events within a patient record. The 2012 i2b2 NLP challenge focused on the extraction of temporal relationships between concepts within textual hospital discharge summaries. The team from the National Research Council Canada (NRC) submitted three system runs to the second track of the challenge: typifying the time-relationship between pre-annotated entities. The NRC system was designed around four specialist modules containing statistical machine learning classifiers. Each specialist targeted distinct sets of relationships: local relationships, 'sectime'-type relationships, non-local overlap-type relationships, and non-local causal relationships. The best NRC submission achieved a precision of 0.7499, a recall of 0.6431, and an F1 score of 0.6924, resulting in a statistical tie for first place. Post hoc improvements led to a precision of 0.7537, a recall of 0.6455, and an F1 score of 0.6954, giving the highest scores reported on this task to date. Methods for general relation extraction extended well to temporal relations, and gave top-ranked state-of-the-art results. Careful ordering of predictions within result sets proved critical to this success.

  4. still108_0201 -- Point coverage of locations of still frames extracted from video imagery which depict sediment types at various locations.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Phantom DH2+2 remotely operated vehicle (ROV) outfitted with video equipment (and other devices) was deployed from the NOAA Ship McAurthurII (AR04-04) in an...

  5. ABOUT SOUNDS IN VIDEO GAMES

    Directory of Open Access Journals (Sweden)

    Denikin Anton A.

    2012-12-01

    Full Text Available The article considers the aesthetical and practical possibilities for sounds (sound design in video games and interactive applications. Outlines the key features of the game sound, such as simulation, representativeness, interactivity, immersion, randomization, and audio-visuality. The author defines the basic terminology in study of game audio, as well as identifies significant aesthetic differences between film sounds and sounds in video game projects. It is an attempt to determine the techniques of art analysis for the approaches in study of video games including aesthetics of their sounds. The article offers a range of research methods, considering the video game scoring as a contemporary creative practice.

  6. Robust Watermarking of Video Streams

    Directory of Open Access Journals (Sweden)

    T. Polyák

    2006-01-01

    Full Text Available In the past few years there has been an explosion in the use of digital video data. Many people have personal computers at home, and with the help of the Internet users can easily share video files on their computer. This makes possible the unauthorized use of digital media, and without adequate protection systems the authors and distributors have no means to prevent it.Digital watermarking techniques can help these systems to be more effective by embedding secret data right into the video stream. This makes minor changes in the frames of the video, but these changes are almost imperceptible to the human visual system. The embedded information can involve copyright data, access control etc. A robust watermark is resistant to various distortions of the video, so it cannot be removed without affecting the quality of the host medium. In this paper I propose a video watermarking scheme that fulfills the requirements of a robust watermark. 

  7. Compact Visualisation of Video Summaries

    Directory of Open Access Journals (Sweden)

    Janko Ćalić

    2007-01-01

    Full Text Available This paper presents a system for compact and intuitive video summarisation aimed at both high-end professional production environments and small-screen portable devices. To represent large amounts of information in the form of a video key-frame summary, this paper studies the narrative grammar of comics, and using its universal and intuitive rules, lays out visual summaries in an efficient and user-centered way. In addition, the system exploits visual attention modelling and rapid serial visual presentation to generate highly compact summaries on mobile devices. A robust real-time algorithm for key-frame extraction is presented. The system ranks importance of key-frame sizes in the final layout by balancing the dominant visual representability and discovery of unanticipated content utilising a specific cost function and an unsupervised robust spectral clustering technique. A final layout is created using an optimisation algorithm based on dynamic programming. Algorithm efficiency and robustness are demonstrated by comparing the results with a manually labelled ground truth and with optimal panelling solutions.

  8. GPS-Aided Video Tracking

    Directory of Open Access Journals (Sweden)

    Udo Feuerhake

    2015-08-01

    Full Text Available Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS- and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.

  9. Instructional Effectiveness of Video Media.

    Science.gov (United States)

    Wetzel, C. Douglas; And Others

    This volume is a blend of media research, cognitive science research, and tradecraft knowledge regarding video production techniques. The research covers: visual learning; verbal-auditory information; news broadcasts; the value of motion and animation in film and video; simulation (including realism and fidelity); the relationship of text and…

  10. NEI You Tube Videos: Amblyopia

    Medline Plus

    Full Text Available ... National Eye Institute’s mission is to “conduct and support research, training, health information dissemination, and other programs ... search for current job openings visit HHS USAJobs Home > NEI YouTube Videos > NEI YouTube Videos: Amblyopia NEI ...

  11. AN EFFICIENT HILBERT AND INTEGER WAVELET TRANSFORM BASED VIDEO WATERMARKING

    Directory of Open Access Journals (Sweden)

    AGILANDEESWARI L.

    2016-03-01

    Full Text Available In this paper, an efficient, highly imperceptible, robust, and secure digital video watermarking technique for content authentication based on Hilbert transform in the Integer Wavelet Transform (IWT domain has been introduced. The Hilbert coefficients of gray watermark image are embedded into the cover video frames Hilbert coefficients on the 2-level IWT decomposed selected block on sub-bands using Principal Component Analysis (PCA technique. The authentication is achieved by using the digital signature mechanism. This mechanism is used to generate and embed a digital signature after embedding the watermarks. Since, the embedding process is done in Hilbert transform domain, the imperceptibility and the robustness of the watermark is greatly improved. At the receiver end, prior to the extraction of watermark, the originality of the content is verified through the authentication test. If the generated and received signature matches, it proves that the received content is original and performs the extraction process, otherwise deny the extraction process due to unauthenticated received content. The proposed method avoids typical degradations in the imperceptibility level of watermarked video in terms of Average Peak Signal – to – Noise Ratio (PSNR value of about 48db, while it is still providing better robustness against common video distortions such as frame dropping, averaging, and various image processing attacks such as noise addition, median filtering, contrast adjustment, and geometrical attacks such as, rotation and cropping in terms of Normalized Correlation Coefficient (NCC value of about nearly 1.

  12. Akademisk video

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2017-01-01

    Dette kapitel har fokus på metodiske problemstillinger, der opstår i forhold til at bruge (digital) video i forbindelse med forskningskommunikation, ikke mindst online. Video har længe været benyttet i forskningen til dataindsamling og forskningskommunikation. Med digitaliseringen og internettet er...... der dog opstået nye muligheder og udfordringer i forhold til at formidle og distribuere forskningsresultater til forskellige målgrupper via video. Samtidig er klassiske metodologiske problematikker som forskerens positionering i forhold til det undersøgte stadig aktuelle. Både klassiske og nye...... problemstillinger diskuteres i kapitlet, som rammesætter diskussionen ud fra forskellige positioneringsmuligheder: formidler, historiefortæller, eller dialogist. Disse positioner relaterer sig til genrer inden for ’akademisk video’. Afslutningsvis præsenteres en metodisk værktøjskasse med redskaber til planlægning...

  13. Towards a Video Passive Content Fingerprinting Method for Partial-Copy Detection Robust against Non-Simulated Attacks.

    Directory of Open Access Journals (Sweden)

    Zobeida Jezabel Guzman-Zavaleta

    Full Text Available Passive content fingerprinting is widely used for video content identification and monitoring. However, many challenges remain unsolved especially for partial-copies detection. The main challenge is to find the right balance between the computational cost of fingerprint extraction and fingerprint dimension, without compromising detection performance against various attacks (robustness. Fast video detection performance is desirable in several modern applications, for instance, in those where video detection involves the use of large video databases or in applications requiring real-time video detection of partial copies, a process whose difficulty increases when videos suffer severe transformations. In this context, conventional fingerprinting methods are not fully suitable to cope with the attacks and transformations mentioned before, either because the robustness of these methods is not enough or because their execution time is very high, where the time bottleneck is commonly found in the fingerprint extraction and matching operations. Motivated by these issues, in this work we propose a content fingerprinting method based on the extraction of a set of independent binary global and local fingerprints. Although these features are robust against common video transformations, their combination is more discriminant against severe video transformations such as signal processing attacks, geometric transformations and temporal and spatial desynchronization. Additionally, we use an efficient multilevel filtering system accelerating the processes of fingerprint extraction and matching. This multilevel filtering system helps to rapidly identify potential similar video copies upon which the fingerprint process is carried out only, thus saving computational time. We tested with datasets of real copied videos, and the results show how our method outperforms state-of-the-art methods regarding detection scores. Furthermore, the granularity of our method makes

  14. Video Analytics

    DEFF Research Database (Denmark)

    This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real...... World Videos. The workshops were run on December 4, 2016, in Cancun in Mexico. The two workshops together received 13 papers. Each paper was then reviewed by at least two expert reviewers in the field. In all, 11 papers were accepted to be presented at the workshops. The topics covered in the papers...

  15. Video databases: automatic retrieval based on content.

    Science.gov (United States)

    Bolle, R. M.; Yeo, B.-L.; Yeung, M.

    Digital video databases are becoming more and more pervasive and finding video of interest in large databases is rapidly becoming a problem. Intelligent means of quick content-based video retrieval and content-based rapid video viewing is, therefore, an important topic of research. Video is a rich source of data, it contains visual and audio information, and in many cases, there is text associated with the video. Content-based video retrieval should use all this information in an efficient and effective way. From a human perspective, a video query can be viewed as an iterated sequence of navigating, searching, browsing, and viewing. This paper addresses video search in terms of these phases.

  16. Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

    OpenAIRE

    Dat Tien Nguyen; Ki Wan Kim; Hyung Gil Hong; Ja Hyung Koo; Min Cheol Kim; Kang Ryoung Park

    2017-01-01

    Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has ...

  17. Automatic Story Segmentation for TV News Video Using Multiple Modalities

    Directory of Open Access Journals (Sweden)

    Émilie Dumont

    2012-01-01

    Full Text Available While video content is often stored in rather large files or broadcasted in continuous streams, users are often interested in retrieving only a particular passage on a topic of interest to them. It is, therefore, necessary to split video documents or streams into shorter segments corresponding to appropriate retrieval units. We propose here a method for the automatic segmentation of TV news videos into stories. A-multiple-descriptor based segmentation approach is proposed. The selected multimodal features are complementary and give good insights about story boundaries. Once extracted, these features are expanded with a local temporal context and combined by an early fusion process. The story boundaries are then predicted using machine learning techniques. We investigate the system by experiments conducted using TRECVID 2003 data and protocol of the story boundary detection task, and we show that the proposed approach outperforms the state-of-the-art methods while requiring a very small amount of manual annotation.

  18. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available ... Donate Resources Links Videos Podcasts Webinars For the Media For Clinicians For Policymakers For Family Caregivers Glossary Sign Up for Our Blog Subscribe to Blog Enter your email address to subscribe to this blog and receive notifications of new posts by email. Email Address CLOSE Home About ...

  19. Video processing project

    CSIR Research Space (South Africa)

    Globisch, R

    2009-03-01

    Full Text Available Video processing source code for algorithms and tools used in software media pipelines (e.g. image scalers, colour converters, etc.) The currently available source code is written in C++ with their associated libraries and DirectShow- Filters....

  20. Videos, Podcasts and Livechats

    Medline Plus

    Full Text Available Home About Donate Search Search What Is It Definition Pediatric Palliative Care Disease Types FAQ Handout for Patients and Families Is It Right for You How to Get It Talk to your Doctor Find a Provider Meet the Team Blog Articles & Stories News Resources Links Videos Podcasts ...

  1. Acoustic Neuroma Educational Video

    Medline Plus

    Full Text Available ... Surgery What is acoustic neuroma Diagnosing Symptoms Side effects ... Groups Is a support group for me? Find a Group Upcoming Events Video Library Photo Gallery One-on-One Support ANetwork Peer Support Program Community Connections Overview Find a Meeting ...

  2. P2P Video Streaming Strategies based on Scalable Video Coding

    Directory of Open Access Journals (Sweden)

    F.A. López-Fuentes

    2015-02-01

    Full Text Available Video streaming over the Internet has gained significant popularity during the last years, and the academy and industry have realized a great research effort in this direction. In this scenario, scalable video coding (SVC has emerged as an important video standard to provide more functionality to video transmission and storage applications. This paper proposes and evaluates two strategies based on scalable video coding for P2P video streaming services. In the first strategy, SVC is used to offer differentiated quality video to peers with heterogeneous capacities. The second strategy uses SVC to reach a homogeneous video quality between different videos from different sources. The obtained results show that our proposed strategies enable a system to improve its performance and introduce benefits such as differentiated quality of video for clients with heterogeneous capacities and variable network conditions.

  3. Video Analytics

    DEFF Research Database (Denmark)

    This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real W...

  4. A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos.

    Science.gov (United States)

    Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

    2016-04-01

    Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today's keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users' information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively.ResultsThe authors produced a prototype implementation of the proposed system, which is publicly accessible athttps://patentq.njit.edu/oer To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable

  5. Video y desarrollo rural

    Directory of Open Access Journals (Sweden)

    Fraser Colin

    2015-01-01

    Full Text Available Las primeras experiencias de video rural fueron realizadas en Perú y México. El proyecto peruano es conocido como CESPAC (Centro de Servicios de Pedagogía Audiovisual para la Capacitación. Con financiamiento externo de la FAO fue iniciado en la década del 70. El proyecto mexicano fue bautizado con el nombre de PRODERITH (Programa de Desarrollo Rural Integrado del Trópico Húmedo. Su componente de video rural tuvo un éxito muy particular a nivel de base.La evaluación concluyó en que el video rural como sistema de comunicación social para el desarrollo es excelente y de bajo costo

  6. TRAFFIC SIGN RECOGNATION WITH VIDEO PROCESSING TECHNIQUE

    Directory of Open Access Journals (Sweden)

    Musa AYDIN

    2013-01-01

    Full Text Available In this study, traffic signs are aimed to be recognized and identified from a video image which is taken through a video camera. To accomplish our aim, a traffic sign recognition program has been developed in MATLAB/Simulink environment. The target traffic sign are recognized in the video image with the developed program.

  7. Veterans Crisis Line: Videos About Reaching out for Help

    Medline Plus

    Full Text Available ... see more videos from Blue Star Families These Hands PSA see more videos from Veterans Health Administration ... Line text-messaging service does not store mobile phone numbers of users who access information via text ...

  8. Online scene change detection of multicast (MBone) video

    Science.gov (United States)

    Zhou, Wensheng; Shen, Ye; Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    Many multimedia applications, such as multimedia data management systems and communication systems, require efficient representation of multimedia content. Thus semantic interpretation of video content has been a popular research area. Currently, most content-based video representation involves the segmentation of video based on key frames which are generated using scene change detection techniques as well as camera/object motion. Then, video features can be extracted from key frames. However most of such research performs off-line video processing in which the whole video scope is known as a priori which allows multiple scans of the stored video files during video processing. In comparison, relatively not much research has been done in the area of on-line video processing, which is crucial in video communication applications such as on-line collaboration, news broadcasts and so on. Our research investigates on-line real-time scene change detection of multicast video over the Internet. Our on-line processing system are designed to meet the requirements of real-time video multicasting over the Internet and to utilize the successful video parsing techniques available today. The proposed algorithms extract key frames from video bitstreams sent through the MBone network, and the extracted key frames are multicasted as annotations or metadata over a separate channel to assist in content filtering such as those anticipated to be in use by on-line filtering proxies in the Internet. The performance of the proposed algorithms are demonstrated and discussed in this paper.

  9. Rheumatoid Arthritis Educational Video Series

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  10. Rheumatoid Arthritis Educational Video Series

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  11. NEI You Tube Videos: Amblyopia

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  12. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... is Happening to the Joints? Rheumatoid Arthritis: Gaining Control – Working with your Rheumatologist Rheumatoid Arthritis: Additional Conditions ... Hopkins Stategies to Increase your Level of Physical Activity Role of Body Weight in Osteoarthritis Educational Videos ...

  14. Rheumatoid Arthritis Educational Video Series

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  15. NEI You Tube Videos: Amblyopia

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  17. Video Analytics

    DEFF Research Database (Denmark)

    This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real...... include: re-identification, consumer behavior analysis, utilizing pupillary response for task difficulty measurement, logo detection, saliency prediction, classification of facial expressions, face recognition, face verification, age estimation, super-resolution, pose estimation, and pain recognition...

  18. Video Analytics

    DEFF Research Database (Denmark)

    include: re-identification, consumer behavior analysis, utilizing pupillary response for task difficulty measurement, logo detection, saliency prediction, classification of facial expressions, face recognition, face verification, age estimation, super-resolution, pose estimation, and pain recognition......This book collects the papers presented at two workshops during the 23rd International Conference on Pattern Recognition (ICPR): the Third Workshop on Video Analytics for Audience Measurement (VAAM) and the Second International Workshop on Face and Facial Expression Recognition (FFER) from Real...

  19. Color image and video enhancement

    CERN Document Server

    Lecca, Michela; Smolka, Bogdan

    2015-01-01

    This text covers state-of-the-art color image and video enhancement techniques. The book examines the multivariate nature of color image/video data as it pertains to contrast enhancement, color correction (equalization, harmonization, normalization, balancing, constancy, etc.), noise removal and smoothing. This book also discusses color and contrast enhancement in vision sensors and applications of image and video enhancement.   ·         Focuses on enhancement of color images/video ·         Addresses algorithms for enhancing color images and video ·         Presents coverage on super resolution, restoration, in painting, and colorization.

  20. Performance Analysis of Video Transmission Using Sequential Distortion Minimization Method for Digital Video Broadcasting Terrestrial

    Directory of Open Access Journals (Sweden)

    Novita Astin

    2016-12-01

    Full Text Available This paper presents about the transmission of Digital Video Broadcasting system with streaming video resolution 640x480 on different IQ rate and modulation. In the video transmission, distortion often occurs, so the received video has bad quality. Key frames selection algorithm is flexibel on a change of video, but on these methods, the temporal information of a video sequence is omitted. To minimize distortion between the original video and received video, we aimed at adding methodology using sequential distortion minimization algorithm. Its aim was to create a new video, better than original video without significant loss of content between the original video and received video, fixed sequentially. The reliability of video transmission was observed based on a constellation diagram, with the best result on IQ rate 2 Mhz and modulation 8 QAM. The best video transmission was also investigated using SEDIM (Sequential Distortion Minimization Method and without SEDIM. The experimental result showed that the PSNR (Peak Signal to Noise Ratio average of video transmission using SEDIM was an increase from 19,855 dB to 48,386 dB and SSIM (Structural Similarity average increase 10,49%. The experimental results and comparison of proposed method obtained a good performance. USRP board was used as RF front-end on 2,2 GHz.

  1. A Framework for Advanced Video Traces: Evaluating Visual Quality for Video Transmission Over Lossy Networks

    Directory of Open Access Journals (Sweden)

    Reisslein Martin

    2006-01-01

    Full Text Available Conventional video traces (which characterize the video encoding frame sizes in bits and frame quality in PSNR are limited to evaluating loss-free video transmission. To evaluate robust video transmission schemes for lossy network transport, generally experiments with actual video are required. To circumvent the need for experiments with actual videos, we propose in this paper an advanced video trace framework. The two main components of this framework are (i advanced video traces which combine the conventional video traces with a parsimonious set of visual content descriptors, and (ii quality prediction schemes that based on the visual content descriptors provide an accurate prediction of the quality of the reconstructed video after lossy network transport. We conduct extensive evaluations using a perceptual video quality metric as well as the PSNR in which we compare the visual quality predicted based on the advanced video traces with the visual quality determined from experiments with actual video. We find that the advanced video trace methodology accurately predicts the quality of the reconstructed video after frame losses.

  2. Videography-Based Unconstrained Video Analysis.

    Science.gov (United States)

    Li, Kang; Li, Sheng; Oh, Sangmin; Fu, Yun

    2017-05-01

    Video analysis and understanding play a central role in visual intelligence. In this paper, we aim to analyze unconstrained videos, by designing features and approaches to represent and analyze videography styles in the videos. Videography denotes the process of making videos. The unconstrained videos are defined as the long duration consumer videos that usually have diverse editing artifacts and significant complexity of contents. We propose to construct a videography dictionary, which can be utilized to represent every video clip as a sequence of videography words. In addition to semantic features, such as foreground object motion and camera motion, we also incorporate two novel interpretable features to characterize videography, including the scale information and the motion correlations. We then demonstrate that, by using statistical analysis methods, the unique videography signatures extracted from different events can be automatically identified. For real-world applications, we explore the use of videography analysis for three types of applications, including content-based video retrieval, video summarization (both visual and textual), and videography-based feature pooling. In the experiments, we evaluate the performance of our approach and other methods on a large-scale unconstrained video dataset, and show that the proposed approach significantly benefits video analysis in various ways.

  3. Intelligent Model for Video Survillance Security System

    Directory of Open Access Journals (Sweden)

    J. Vidhya

    2013-12-01

    Full Text Available Video surveillance system senses and trails out all the threatening issues in the real time environment. It prevents from security threats with the help of visual devices which gather the information related to videos like CCTV’S and IP (Internet Protocol cameras. Video surveillance system has become a key for addressing problems in the public security. They are mostly deployed on the IP based network. So, all the possible security threats exist in the IP based application might also be the threats available for the reliable application which is available for video surveillance. In result, it may increase cybercrime, illegal video access, mishandling videos and so on. Hence, in this paper an intelligent model is used to propose security for video surveillance system which ensures safety and it provides secured access on video.

  4. Uncertainty-aware video visual analytics of tracked moving objects

    Directory of Open Access Journals (Sweden)

    Markus Höferlin

    2011-01-01

    Full Text Available Vast amounts of video data render manual video analysis useless while recent automatic video analytics techniques suffer from insufficient performance. To alleviate these issues, we present a scalable and reliable approach exploiting the visual analytics methodology. This involves the user in the iterative process of exploration, hypotheses generation, and their verification. Scalability is achieved by interactive filter definitions on trajectory features extracted by the automatic computer vision stage. We establish the interface between user and machine adopting the VideoPerpetuoGram (VPG for visualization and enable users to provide filter-based relevance feedback. Additionally, users are supported in deriving hypotheses by context-sensitive statistical graphics. To allow for reliable decision making, we gather uncertainties introduced by the computer vision step, communicate these information to users through uncertainty visualization, and grant fuzzy hypothesis formulation to interact with the machine. Finally, we demonstrate the effectiveness of our approach by the video analysis mini challenge which was part of the IEEE Symposium on Visual Analytics Science and Technology 2009.

  5. Uncertainty-aware video visual analytics of tracked moving objects

    Directory of Open Access Journals (Sweden)

    Markus Höferlin

    1969-12-01

    Full Text Available Vast amounts of video data render manual video analysis useless while recent automatic video analytics techniques suffer from insufficient performance. To alleviate these issues, we present a scalable and reliable approach exploiting the visual analytics methodology. This involves the user in the iterative process of exploration, hypotheses generation, and their verification. Scalability is achieved by interactive filter definitions on trajectory features extracted by the automatic computer vision stage. We establish the interface between user and machine adopting the VideoPerpetuoGram (VPG for visualization and enable users to provide filter-based relevance feedback. Additionally, users are supported in deriving hypotheses by context-sensitive statistical graphics. To allow for reliable decision making, we gather uncertainties introduced by the computer vision step, communicate these information to users through uncertainty visualization, and grant fuzzy hypothesis formulation to interact with the machine. Finally, we demonstrate the effectiveness of our approach by the video analysis mini challenge which was part of the IEEE Symposium on Visual Analytics Science and Technology 2009.

  6. A Secure and Robust Object-Based Video Authentication System

    Directory of Open Access Journals (Sweden)

    Dajun He

    2004-10-01

    Full Text Available An object-based video authentication system, which combines watermarking, error correction coding (ECC, and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI.

  7. Roadside video data analysis deep learning

    CERN Document Server

    Verma, Brijesh; Stockwell, David

    2017-01-01

    This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

  8. Cobra: A Content-Based Video Retrieval System

    NARCIS (Netherlands)

    Petkovic, M.; Jonker, Willem

    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

  9. Celiac Family Health Education Video Series

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  10. Celiac Family Health Education Video Series

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    Full Text Available ... so much more than a hospital—it’s a community of researchers, clinicians, administrators, support staff, ... Innovation Videos Contact Us Boston Children's Hospital 300 ...

  11. Video Quality Prediction Models Based on Video Content Dynamics for H.264 Video over UMTS Networks

    Directory of Open Access Journals (Sweden)

    Asiya Khan

    2010-01-01

    Full Text Available The aim of this paper is to present video quality prediction models for objective non-intrusive, prediction of H.264 encoded video for all content types combining parameters both in the physical and application layer over Universal Mobile Telecommunication Systems (UMTS networks. In order to characterize the Quality of Service (QoS level, a learning model based on Adaptive Neural Fuzzy Inference System (ANFIS and a second model based on non-linear regression analysis is proposed to predict the video quality in terms of the Mean Opinion Score (MOS. The objective of the paper is two-fold. First, to find the impact of QoS parameters on end-to-end video quality for H.264 encoded video. Second, to develop learning models based on ANFIS and non-linear regression analysis to predict video quality over UMTS networks by considering the impact of radio link loss models. The loss models considered are 2-state Markov models. Both the models are trained with a combination of physical and application layer parameters and validated with unseen dataset. Preliminary results show that good prediction accuracy was obtained from both the models. The work should help in the development of a reference-free video prediction model and QoS control methods for video over UMTS networks.

  12. Problem with multi-video format M-learning applications

    CSIR Research Space (South Africa)

    Adeyeye, MO

    2014-01-01

    Full Text Available in conjunction with the technical aspects of video display in browsers, when varying media formats are used. The <video> tag used in this work renders videos from two sources with different MIME types. Feeds from the video sources, namely YouTube and UCT...

  13. Know Stroke: Know the Signs, Act in Time Video

    Medline Plus

    Full Text Available ... Stroke Home » Stroke Materials » Loading the player... Video Transcript Weakness on one Side. Trouble Speaking. Trouble Seeing. ... medical treatment immediately. View the Video » View the Transcript » Download the Video » Ataque Cerebral Video Loading the ...

  14. Accidental chest penetration of glass foreign bodies in a 53 year old lady—The challenges with video assisted thoracoscopic extraction

    Directory of Open Access Journals (Sweden)

    Tomohisa Shoko

    2016-01-01

    Conclusion: The patients who injured the chest with the glass without awareness of the implant of the foreign body, we take an intrathoracic foreign body by the penetration of the glass piece into consideration, need the search by the imaging. The extraction of the glass foreign bodies by VATS is very useful.

  15. Using Video in the English Language Clasroom

    Directory of Open Access Journals (Sweden)

    Amado Vicente

    2002-08-01

    Full Text Available Video is a popular and a motivating potential medium in schools. Using video in the language classroom helps the language teachers in many different ways. Video, for instance, brings the outside world into the language classroom, providing the class with many different topics and reasons to talk about. It can provide comprehensible input to the learners through contextualised models of language use. It also offers good opportunities to introduce native English speech into the language classroom. Through this article I will try to show what the benefits of using video are and, at the end, I present an instrument to select and classify video materials.

  16. Video streaming in the Wild West

    Directory of Open Access Journals (Sweden)

    Helen Gail Prosser

    2006-11-01

    Full Text Available Northern Lakes College in north-central Alberta is the first post-secondary institution in Canada to use the Media on Demand digital video system to stream large video files between dispersed locations (Karlsen. Staff and students at distant locations of Northern Lakes College are now viewing more than 350 videos using video streaming technology. This has been made possible by SuperNet, a high capacity broadband network that connects schools, hospitals, libraries and government offices throughout the province of Alberta (Alberta SuperNet. This article describes the technical process of implementing video streaming at Northern Lakes College from March 2005 until March 2006.

  17. Video Primal Sketch: A Unified Middle-Level Representation for Video

    OpenAIRE

    Han, Zhi; Xu, Zongben; Zhu, Song-Chun

    2015-01-01

    This paper presents a middle-level video representation named Video Primal Sketch (VPS), which integrates two regimes of models: i) sparse coding model using static or moving primitives to explicitly represent moving corners, lines, feature points, etc., ii) FRAME /MRF model reproducing feature statistics extracted from input video to implicitly represent textured motion, such as water and fire. The feature statistics include histograms of spatio-temporal filters and velocity distributions. T...

  18. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... Help see more videos from Veterans Health Administration Suicide Prevention PSA for Military Families see more videos ... About About the Veterans Crisis Line FAQs Veteran Suicide The Veterans Crisis Line text-messaging service does ...

  19. Keeping the Game Alive: Evaluating Strategies for the Preservation of Console Video Games

    Directory of Open Access Journals (Sweden)

    Mark Guttenbrunner

    2010-07-01

    Full Text Available Interactive fiction and video games are part of our cultural heritage. As original systems cease to work because of hardware and media failures, methods to preserve obsolete video games for future generations have to be developed. The public interest in early video games is high, as exhibitions, regular magazines on the topic and newspaper articles demonstrate. Moreover, games considered to be classic are rereleased for new generations of gaming hardware. However, with the rapid development of new computer systems, the way games look and are played changes constantly. When trying to preserve console video games one faces problems of classified development documentation, legal aspects and extracting the contents from original media like cartridges with special hardware. Furthermore, special controllers and non-digital items are used to extend the gaming experience making it difficult to preserve the look and feel of console video games.This paper discusses strategies for the digital preservation of console video games. After a short overview of console video game systems, there follows an introduction to digital preservation and related work in common strategies for digital preservation and preserving interactive art. Then different preservation strategies are described with a specific focus on emulation. Finally a case study on console video game preservation is shown which uses the Planets preservation planning approach for evaluating preservation strategies in a documented decision-making process. Experiments are carried out to compare different emulators as well as other approaches, first for a single console video game system, then for different console systems of the same era and finally for systems of all eras. Comparison and discussion of results show that, while emulation works very well in principle for early console video games, various problems exist for the general use as a digital preservation alternative. We show what future work

  20. Six degrees of video game narrative: a classification for narrative in video games

    OpenAIRE

    Şengün, Sercan

    2013-01-01

    158 pages This study aims to construct a systematical approach to classification of narrative usage in video games. The most recent dominant approaches of reading a video game text – narratology and ludology - are discussed. By inquiring the place of interactivity and autonomy inside the discourse of video game narrative, a classification is proposed. Consequently six groups of video games are determined, depending on the levels of combination of narration and ludic context. These Six Degr...

  1. Developing an accessible video player

    Directory of Open Access Journals (Sweden)

    Juan José Rodríguez Soler

    2012-05-01

    Full Text Available Online Channels in financial institutions allows customers with disabilities to access services in a convenient way for them.However, one of the current challenges of this sector is to improve web accessibility and to incorporate technological resources to provide access to multimedia and video content, which has become a new form of internet communication.The present work shows in detail the strategy followed when designing and developing the new video player used by Bankinter for these purposes.

  2. A Blind Video Watermarking Scheme Robust To Frame Attacks Combined With MPEG2 Compression

    Directory of Open Access Journals (Sweden)

    C. Cruz-Ramos

    2010-12-01

    Full Text Available ABSTRACTIn this paper, we propose a robust digital video watermarking scheme with completely blind extraction process wherethe original video data, original watermark or any other information derivative of them are not required in order toretrieve the embedded watermark. The proposed algorithm embeds 2D binary visually recognizable patterns such ascompany trademarks and owner’s logotype, etc., in the DWT domain of the video frames for copyright protection.Before the embedding process, only two numerical keys are required to transform the watermark data into a noise-likepattern using the chaotic mixing method which helps to increase the security. The main advantages of the proposedscheme are its completely blind detection scheme, robustness against common video attacks, combined attacks andits low complexity implementation. The combined attacks consist of MPEG-2 compression and common video attackssuch as noise contamination, collusion attacks, frame dropping and swapping. Extensive simulation results also showthat the watermark imperceptibility and robustness outperform other previously reported methods. The extractedwatermark data from the watermarked video sequences is clear enough even after the watermarked video hadsuffered from several attacks.

  3. Creating and Editing Video to Accompany Manuscripts.

    Science.gov (United States)

    Gordon, Shayna L; Porto, Dennis A; Ozog, David M; Council, M Laurin

    2016-02-01

    The use of video can enhance the learning experience by demonstrating procedural techniques that are difficult to relay in writing. Several peer-reviewed journals allow publication of videos alongside articles to complement the written text. The purpose of this article is to instruct the dermatologic surgeon on how to create and edit a video using a smartphone, to accompany a article. The authors describe simple tips to optimize surgical videography. The video that accompanies this article further demonstrates the techniques described. Creating a surgical video requires little experience or equipment and can be completed in a modest amount of time. Making and editing a video to accompany a article can be accomplished by following the simple recommendations in this article. In addition, the increased use of video in dermatologic surgery education can enhance the learning opportunity.

  4. Video Game Accessibility: A Legal Approach

    Directory of Open Access Journals (Sweden)

    George Powers

    2015-02-01

    Full Text Available Video game accessibility may not seem of significance to some, and it may sound trivial to anyone who does not play video games. This assumption is false. With the digitalization of our culture, video games are an ever increasing part of our life. They contribute to peer to peer interactions, education, music and the arts. A video game can be created by hundreds of musicians and artists, and they can have production budgets that exceed modern blockbuster films. Inaccessible video games are analogous to movie theaters without closed captioning or accessible facilities. The movement to have accessible video games is small, unorganized and misdirected. Just like the other battles to make society accessible were accomplished through legislation and law, the battle for video game accessibility must be focused toward the law and not the market.

  5. CARACTERIZACION VOZ Y VIDEO

    Directory of Open Access Journals (Sweden)

    Octavio José Salcedo Parra

    2011-11-01

    Full Text Available La motivación para caracterizar el tráfico de voz y video está en la necesidad de las empresas proveedoras de servicio en mantener redes de transporte de información con capacidades acordes a los requerimientos de los usuarios.  Poder determinar en forma oportuna como los elementos técnicos que hacen parte de las redes afectan su desempeño, teniendo en cuenta que cada tipo de servicio es afectado en mayor o menor medida por dichos elementos dentro de los que tenemos el jitter, las demoras y las pérdidas de paquetes entre otros. El presente trabajo muestra varios casos de caracterización de tráfico tanto de voz como de video en las que se utilizan una diversidad de técnicas para diferentes tipos de servicio.

  6. Impairment-Factor-Based Audiovisual Quality Model for IPTV: Influence of Video Resolution, Degradation Type, and Content Type

    Directory of Open Access Journals (Sweden)

    Garcia MN

    2011-01-01

    Full Text Available This paper presents an audiovisual quality model for IPTV services. The model estimates the audiovisual quality of standard and high definition video as perceived by the user. The model is developed for applications such as network planning and packet-layer quality monitoring. It mainly covers audio and video compression artifacts and impairments due to packet loss. The quality tests conducted for model development demonstrate a mutual influence of the perceived audio and video quality, and the predominance of the video quality for the overall audiovisual quality. The balance between audio quality and video quality, however, depends on the content, the video format, and the audio degradation type. The proposed model is based on impairment factors which quantify the quality-impact of the different degradations. The impairment factors are computed from parameters extracted from the bitstream or packet headers. For high definition video, the model predictions show a correlation with unknown subjective ratings of 95%. For comparison, we have developed a more classical audiovisual quality model which is based on the audio and video qualities and their interaction. Both quality- and impairment-factor-based models are further refined by taking the content-type into account. At last, the different model variants are compared with modeling approaches described in the literature.

  7. Video in foreign language teaching

    Directory of Open Access Journals (Sweden)

    Joe Hambrook

    2013-02-01

    Full Text Available Much of the attention paid to video in foreign language teaching is focused upon a relatively small amount of commercially produced and distributed material. This paper briefly describes the development of this material in the EFLIESL field; looks at some current issues and concerns, and considers future possibilities with particular reference to computer assisted interactive video. Heelwat van die aandag wat video geniet as hulpmiddel by tweedetaalonderrig is toegespits op 'n relatief klein hoeveelheid kommersieel vervaardigde en verspreide materiaal. Hierdie artikel beskryf kortliks die ontwikkeling van bogenoemde materiaal waar dit Engels as tweede of vreemde taal betref. Verder word daar aandag gegee aan huidige tendense en toekomstige moontlikhede word oorweeg, met spesifieke verwysing na rekenaarondersteunde interaktiewe video.

  8. NEI You Tube Videos: Amblyopia

    Science.gov (United States)

    ... YouTube Videos > NEI YouTube Videos: Amblyopia NEI YouTube Videos YouTube Videos Home Age-Related Macular Degeneration Amblyopia ... of Prematurity Science Spanish Videos Webinars NEI YouTube Videos: Amblyopia Embedded video for NEI YouTube Videos: Amblyopia ...

  9. Weaving with text

    DEFF Research Database (Denmark)

    Hagedorn-Rasmussen, Peter

    This paper explores how a school principal by means of practical authorship creates reservoirs of language that provide a possible context for collective sensemaking. The paper draws upon a field study in which a school principal, and his managerial team, was shadowed in a period of intensive cha...... changes. The paper explores how the manager weaves with text, extracted from stakeholders, administration, politicians, employees, public discourse etc., as a means of creating a new fabric, a texture, of diverse perspectives that aims for collective sensemaking....

  10. Ethnic Drama: Video-Texts and Study Guides.

    Science.gov (United States)

    Valletta, Clement, Ed.; And Others

    The document contains scripts, study guides, and discussion questions for two ethnic dramas suitable for ethnic studies at the secondary school level. The first, "A Glass Rose," an adaptation of the novel by Richard Bankowsky, depicts the hopes, dreams, and problems of a Polish immigrant family who reside in an ethnic neighborhood in an…

  11. Video Malware - Behavioral Analysis

    Directory of Open Access Journals (Sweden)

    Rajdeepsinh Dodia

    2015-04-01

    Full Text Available Abstract The counts of malware attacks exploiting the internet increasing day by day and has become a serious threat. The latest malware spreading out through the media players embedded using the video clip of funny in nature to lure the end users. Once it is executed and installed then the behavior of the malware is in the malware authors hand. The spread of the malware emulates through Internet USB drives sharing of the files and folders can be anything which makes presence concealed. The funny video named as it connected to the film celebrity where the malware variant was collected from the laptop of the terror outfit organization .It runs in the backend which it contains malicious code which steals the user sensitive information like banking credentials username amp password and send it to the remote host user called command amp control. The stealed data is directed to the email encapsulated in the malicious code. The potential malware will spread through the USB and other devices .In summary the analysis reveals the presence of malicious code in executable video file and its behavior.

  12. Comparing a knowledge-driven approach to a supervised machine learning approach in large-scale extraction of drug-side effect relationships from free-text biomedical literature.

    Science.gov (United States)

    Xu, Rong; Wang, QuanQiu

    2015-01-01

    Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for both drug target discovery and drug repositioning. However, a comprehensive drug-SE association knowledge base does not exist. In this study, we present a novel knowledge-driven (KD) approach to effectively extract a large number of drug-SE pairs from published biomedical literature. For the text corpus, we used 21,354,075 MEDLINE records (119,085,682 sentences). First, we used known drug-SE associations derived from FDA drug labels as prior knowledge to automatically find SE-related sentences and abstracts. We then extracted a total of 49,575 drug-SE pairs from MEDLINE sentences and 180,454 pairs from abstracts. On average, the KD approach has achieved a precision of 0.335, a recall of 0.509, and an F1 of 0.392, which is significantly better than a SVM-based machine learning approach (precision: 0.135, recall: 0.900, F1: 0.233) with a 73.0% increase in F1 score. Through integrative analysis, we demonstrate that the higher-level phenotypic drug-SE relationships reflects lower-level genetic, genomic, and chemical drug mechanisms. In addition, we show that the extracted drug-SE pairs can be directly used in drug repositioning. In summary, we automatically constructed a large-scale higher-level drug phenotype relationship knowledge, which can have great potential in computational drug discovery.

  13. Video Design Games

    DEFF Research Database (Denmark)

    Smith, Rachel Charlotte; Christensen, Kasper Skov; Iversen, Ole Sejer

    We introduce Video Design Games to train educators in teaching design. The Video Design Game is a workshop format consisting of three rounds in which participants observe, reflect and generalize based on video snippets from their own practice. The paper reports on a Video Design Game workshop...

  14. Characterization of social video

    Science.gov (United States)

    Ostrowski, Jeffrey R.; Sarhan, Nabil J.

    2009-01-01

    The popularity of social media has grown dramatically over the World Wide Web. In this paper, we analyze the video popularity distribution of well-known social video websites (YouTube, Google Video, and the AOL Truveo Video Search engine) and characterize their workload. We identify trends in the categories, lengths, and formats of those videos, as well as characterize the evolution of those videos over time. We further provide an extensive analysis and comparison of video content amongst the main regions of the world.

  15. An Automatic Multimedia Content Summarization System for Video Recommendation

    Science.gov (United States)

    Yang, Jie Chi; Huang, Yi Ting; Tsai, Chi Cheng; Chung, Ching I.; Wu, Yu Chieh

    2009-01-01

    In recent years, using video as a learning resource has received a lot of attention and has been successfully applied to many learning activities. In comparison with text-based learning, video learning integrates more multimedia resources, which usually motivate learners more than texts. However, one of the major limitations of video learning is…

  16. Video visual analytics

    OpenAIRE

    Höferlin, Markus Johannes

    2013-01-01

    The amount of video data recorded world-wide is tremendously growing and has already reached hardly manageable dimensions. It originates from a wide range of application areas, such as surveillance, sports analysis, scientific video analysis, surgery documentation, and entertainment, and its analysis represents one of the challenges in computer science. The vast amount of video data renders manual analysis by watching the video data impractical. However, automatic evaluation of video material...

  17. A Novel Quantum Video Steganography Protocol with Large Payload Based on MCQI Quantum Video

    Science.gov (United States)

    Qu, Zhiguo; Chen, Siyi; Ji, Sai

    2017-11-01

    As one of important multimedia forms in quantum network, quantum video attracts more and more attention of experts and scholars in the world. A secure quantum video steganography protocol with large payload based on the video strip encoding method called as MCQI (Multi-Channel Quantum Images) is proposed in this paper. The new protocol randomly embeds the secret information with the form of quantum video into quantum carrier video on the basis of unique features of video frames. It exploits to embed quantum video as secret information for covert communication. As a result, its capacity are greatly expanded compared with the previous quantum steganography achievements. Meanwhile, the new protocol also achieves good security and imperceptibility by virtue of the randomization of embedding positions and efficient use of redundant frames. Furthermore, the receiver enables to extract secret information from stego video without retaining the original carrier video, and restore the original quantum video as a follow. The simulation and experiment results prove that the algorithm not only has good imperceptibility, high security, but also has large payload.

  18. Veterans Crisis Line: Videos About Reaching out for Help

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  19. Veterans Crisis Line: Videos About Reaching out for Help

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  20. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... in crisis, find a facility near you. Spread the Word Download logos, Web ads, and materials and ... Administration Watch additional videos about getting help. Be There: Help Save a Life see more videos from ...

  1. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... in crisis, find a facility near you. Spread the Word Download logos, Web ads, and materials and ... videos about getting help. Be There: Help Save a Life see more videos from Veterans Health Administration ...

  2. Veterans Crisis Line: Videos About Reaching out for Help

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  3. Know Stroke: Know the Signs, Act in Time Video

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    Full Text Available ... Stroke Materials  » Loading the player... Video Transcript Weakness on one Side. Trouble Speaking. Trouble ... Stroke: Know the Signs. Act in Time. Ambulance Video Loading the player... This PSA alerts audiences about ...

  4. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... from Veterans Health Administration Be There: Help Save a Life see more videos from Veterans Health Administration ... more videos from Veterans Health Administration I am A Veteran Family/Friend Active Duty/Reserve and Guard ...

  5. Veterans Crisis Line: Videos About Reaching out for Help

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  6. Veterans Crisis Line: Videos About Reaching out for Help

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    Full Text Available ... in crisis, find a facility near you. Spread the Word Download logos, Web ads, and materials and ... Administration Watch additional videos about getting help. Behind the Scenes see more videos from Veterans Health Administration ...

  7. Know Stroke: Know the Signs, Act in Time Video

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    Full Text Available ... Know Stroke Home » Stroke Materials » Loading the player... Video Transcript Weakness on one Side. Trouble Speaking. Trouble ... Stroke: Know the Signs. Act in Time. Ambulance Video Loading the player... This PSA alerts audiences about ...

  8. No-Reference Video Quality Assessment by HEVC Codec Analysis

    DEFF Research Database (Denmark)

    Huang, Xin; Søgaard, Jacob; Forchhammer, Søren

    2015-01-01

    the transform coefficients, estimates the distortion, and assesses the video quality. The proposed scheme generates VQA features based on Intra coded frames, and then maps features using an Elastic Net to predict subjective video quality. A set of HEVC coded 4K UHD sequences are tested. Results show......This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by High Efficiency Video Coding (HEVC). The proposed assessment can be performed either as a BitstreamBased (BB) method or as a Pixel-Based (PB). It extracts or estimates...

  9. No-Reference Video Quality Assessment using MPEG Analysis

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

    2013-01-01

    We present a method for No-Reference (NR) Video Quality Assessment (VQA) for decoded video without access to the bitstream. This is achieved by extracting and pooling features from a NR image quality assessment method used frame by frame. We also present methods to identify the video coding...... and estimate the video coding parameters for MPEG-2 and H.264/AVC which can be used to improve the VQA. The analysis differs from most other video coding analysis methods since it is without access to the bitstream. The results show that our proposed method is competitive with other recent NR VQA methods...

  10. Video Game Training and the Reward System

    Directory of Open Access Journals (Sweden)

    Robert C. Lorenz

    2015-02-01

    Full Text Available Video games contain elaborate reinforcement and reward schedules that have the potential to maximize motivation. Neuroimaging studies suggest that video games might have an influence on the reward system. However, it is not clear whether reward-related properties represent a precondition, which biases an individual towards playing video games, or if these changes are the result of playing video games. Therefore, we conducted a longitudinal study to explore reward-related functional predictors in relation to video gaming experience as well as functional changes in the brain in response to video game training.Fifty healthy participants were randomly assigned to a video game training (TG or control group (CG. Before and after training/control period, functional magnetic resonance imaging (fMRI was conducted using a non-video game related reward task.At pretest, both groups showed strongest activation in ventral striatum (VS during reward anticipation. At posttest, the TG showed very similar VS activity compared to pretest. In the CG, the VS activity was significantly attenuated.This longitudinal study revealed that video game training may preserve reward responsiveness in the ventral striatum in a retest situation over time. We suggest that video games are able to keep striatal responses to reward flexible, a mechanism which might be of critical value for applications such as therapeutic cognitive training.

  11. Using video in teacher education

    Directory of Open Access Journals (Sweden)

    Jo Towers

    2007-06-01

    Full Text Available This paper draws on a research study of elementary- and secondary-route preservice teachers in a two-year, after-degree teacher preparation programme. The paper includes excerpts of classroom data, taken from the author’s own university classroom, demonstrating preservice teachers’ responses to carefully selected video extracts of children learning mathematics in a high-school class also taught by the author. The paper includes commentary on some of the advantages and limitations of video as a teaching tool, develops an argument for the increased use, in both preservice teacher education and inservice teacher professional development, of videotaped episodes that focus on the learners rather than on the classroom teacher, and explores the value of having the teacher whose classroom is featured on the videos present for the discussion of the episodes. The paper explores the potential offered by video material to foster the belief that teaching is a learning activity by (i refocusing attention on the learner rather than the teacher in the analysis of classroom practices, (ii raising awareness of the importance of reflective practice, and (iii providing a prompt for the imaginative rehearsal of action. Résumé : Le présent article se fonde sur une étude technique portant sur des stagiaires des niveaux primaire et secondaire dans un programme de préparation à l’enseignement de deux ans après l’obtention du diplôme. L’article comprend des extraits de données en salle de classe qui proviennent de la salle de classe de l’université de l’auteur même, illustrant les réponses des stagiaires à des extraits vidéo choisis avec soins, extraits portant su des enfants apprenant les mathématiques dans une classe du secondaire dont l’enseignant est l’auteur. L’article comporte des commentaires sur certains des avantages et limites du vidéo comme outil d’enseignement, il présente un argument pour l’augmentation accrue, à la

  12. Forest Fire Smoke Video Detection Using Spatiotemporal and Dynamic Texture Features

    Directory of Open Access Journals (Sweden)

    Yaqin Zhao

    2015-01-01

    Full Text Available Smoke detection is a very key part of fire recognition in a forest fire surveillance video since the smoke produced by forest fires is visible much before the flames. The performance of smoke video detection algorithm is often influenced by some smoke-like objects such as heavy fog. This paper presents a novel forest fire smoke video detection based on spatiotemporal features and dynamic texture features. At first, Kalman filtering is used to segment candidate smoke regions. Then, candidate smoke region is divided into small blocks. Spatiotemporal energy feature of each block is extracted by computing the energy features of its 8-neighboring blocks in the current frame and its two adjacent frames. Flutter direction angle is computed by analyzing the centroid motion of the segmented regions in one candidate smoke video clip. Local Binary Motion Pattern (LBMP is used to define dynamic texture features of smoke videos. Finally, smoke video is recognized by Adaboost algorithm. The experimental results show that the proposed method can effectively detect smoke image recorded from different scenes.

  13. Deep Learning for Detection of Object-Based Forgery in Advanced Video

    Directory of Open Access Journals (Sweden)

    Ye Yao

    2017-12-01

    Full Text Available Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based forgery in the advanced video. The presented deep learning approach utilizes a convolutional neural network (CNN to automatically extract high-dimension features from the input image patches. Different from the traditional CNN models used in computer vision domain, we let video frames go through three preprocessing layers before being fed into our CNN model. They include a frame absolute difference layer to cut down temporal redundancy between video frames, a max pooling layer to reduce computational complexity of image convolution, and a high-pass filter layer to enhance the residual signal left by video forgery. In addition, an asymmetric data augmentation strategy has been established to get a similar number of positive and negative image patches before the training. The experiments have demonstrated that the proposed CNN-based model with the preprocessing layers has achieved excellent results.

  14. Video Playback Modifications for a DSpace Repository

    Directory of Open Access Journals (Sweden)

    Keith Gilbertson

    2016-01-01

    Full Text Available This paper focuses on modifications to an institutional repository system using the open source DSpace software to support playback of digital videos embedded within item pages. The changes were made in response to the formation and quick startup of an event capture group within the library that was charged with creating and editing video recordings of library events and speakers. This paper specifically discusses the selection of video formats, changes to the visual theme of the repository to allow embedded playback and captioning support, and modifications and bug fixes to the file downloading subsystem to enable skip-ahead playback of videos via byte-range requests. This paper also describes workflows for transcoding videos in the required formats, creating captions, and depositing videos into the repository.

  15. Implementation of video surveillance in crime control

    Directory of Open Access Journals (Sweden)

    Kovačević-Lepojević Marina

    2012-01-01

    Full Text Available Modern trends in crime control include a variety of technological innovations, including video surveillance systems. The aim of this paper is to review the implementation of video surveillance in contemporary context, considering fundamental theoretical aspects, the legislation and the effectiveness in controlling crime. While considering the theoretical source of ideas on the implementation of video surveillance, priority was given to the concept of situational prevention that focuses on the contextual factors of crime. Capacities for the implementation of video surveillance in Serbia are discussed based on the analysis of the relevant international and domestic legislation, the shortcomings in regulation of this area and possible solutions. Special attention was paid to the effectiveness of video surveillance in public places, in schools and prisons. Starting from the results of studies of video surveillance effectiveness, strengths and weaknesses of these measures and recommendations for improving practice were discussed.

  16. A system for endobronchial video analysis

    Science.gov (United States)

    Byrnes, Patrick D.; Higgins, William E.

    2017-03-01

    Image-guided bronchoscopy is a critical component in the treatment of lung cancer and other pulmonary disorders. During bronchoscopy, a high-resolution endobronchial video stream facilitates guidance through the lungs and allows for visual inspection of a patient's airway mucosal surfaces. Despite the detailed information it contains, little effort has been made to incorporate recorded video into the clinical workflow. Follow-up procedures often required in cancer assessment or asthma treatment could significantly benefit from effectively parsed and summarized video. Tracking diagnostic regions of interest (ROIs) could potentially better equip physicians to detect early airway-wall cancer or improve asthma treatments, such as bronchial thermoplasty. To address this need, we have developed a system for the postoperative analysis of recorded endobronchial video. The system first parses an input video stream into endoscopic shots, derives motion information, and selects salient representative key frames. Next, a semi-automatic method for CT-video registration creates data linkages between a CT-derived airway-tree model and the input video. These data linkages then enable the construction of a CT-video chest model comprised of a bronchoscopy path history (BPH) - defining all airway locations visited during a procedure - and texture-mapping information for rendering registered video frames onto the airwaytree model. A suite of analysis tools is included to visualize and manipulate the extracted data. Video browsing and retrieval is facilitated through a video table of contents (TOC) and a search query interface. The system provides a variety of operational modes and additional functionality, including the ability to define regions of interest. We demonstrate the potential of our system using two human case study examples.

  17. Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

    Directory of Open Access Journals (Sweden)

    Irfan Mehmood

    2014-09-01

    Full Text Available Wireless capsule endoscopy (WCE has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

  18. Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC

    Directory of Open Access Journals (Sweden)

    Sima Ahmadpour

    2017-01-01

    Full Text Available Designing an effective and high performance network requires an accurate characterization and modeling of network traffic. The modeling of video frame sizes is normally applied in simulation studies and mathematical analysis and generating streams for testing and compliance purposes. Besides, video traffic assumed as a major source of multimedia traffic in future heterogeneous network. Therefore, the statistical distribution of video data can be used as the inputs for performance modeling of networks. The finding of this paper comprises the theoretical definition of distribution which seems to be relevant to the video trace in terms of its statistical properties and finds the best distribution using both the graphical method and the hypothesis test. The data set used in this article consists of layered video traces generating from Scalable Video Codec (SVC video compression technique of three different movies.

  19. Quality of Experience Assessment of Video Quality in Social Clouds

    Directory of Open Access Journals (Sweden)

    Asif Ali Laghari

    2017-01-01

    Full Text Available Video sharing on social clouds is popular among the users around the world. High-Definition (HD videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS. Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE level of end users. To assess the QoE of video compression, we conducted subjective (QoE experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

  20. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Program Growth and Nutrition Program Celiac Disease Program | Videos Contact the Celiac Disease Program 1-617-355-6058 Visit the Celiac ... live happy and productive lives. Each of our video segments provides practical information about celiac disease from real-life families, as well as health ...

  1. Special Needs: Planning for Adulthood (Videos)

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    Full Text Available ... Lessons? Visit KidsHealth in the Classroom What Other Parents Are Reading Folic Acid and Pregnancy Medical Care ... Special Needs: Planning for Adulthood (Video) KidsHealth > For Parents > Special Needs: Planning for Adulthood (Video) Print A ...

  2. Celiac Family Health Education Video Series

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    Full Text Available ... ease and allow children with celiac disease to live happy and productive lives. Each of our video segments provides practical information ... Hospital About Us Giving to Boston Children's Newsroom Quality and Patient Safety Research + Innovation Videos Contact Us ...

  3. A methodology for semiautomatic taxonomy of concepts extraction from nuclear scientific documents using text mining techniques; Metodologia para extracao semiautomatica de uma taxonomia de conceitos a partir da producao cientifica da area nuclear utilizando tecnicas de mineracao de textos

    Energy Technology Data Exchange (ETDEWEB)

    Braga, Fabiane dos Reis

    2013-07-01

    This thesis presents a text mining method for semi-automatic extraction of taxonomy of concepts, from a textual corpus composed of scientific papers related to nuclear area. The text classification is a natural human practice and a crucial task for work with large repositories. The document clustering technique provides a logical and understandable framework that facilitates the organization, browsing and searching. Most clustering algorithms using the bag of words model to represent the content of a document. This model generates a high dimensionality of the data, ignores the fact that different words can have the same meaning and does not consider the relationship between them, assuming that words are independent of each other. The methodology presents a combination of a model for document representation by concepts with a hierarchical document clustering method using frequency of co-occurrence concepts and a technique for clusters labeling more representatives, with the objective of producing a taxonomy of concepts which may reflect a structure of the knowledge domain. It is hoped that this work will contribute to the conceptual mapping of scientific production of nuclear area and thus support the management of research activities in this area. (author)

  4. Text Association Analysis and Ambiguity in Text Mining

    Science.gov (United States)

    Bhonde, S. B.; Paikrao, R. L.; Rahane, K. U.

    2010-11-01

    Text Mining is the process of analyzing a semantically rich document or set of documents to understand the content and meaning of the information they contain. The research in Text Mining will enhance human's ability to process massive quantities of information, and it has high commercial values. Firstly, the paper discusses the introduction of TM its definition and then gives an overview of the process of text mining and the applications. Up to now, not much research in text mining especially in concept/entity extraction has focused on the ambiguity problem. This paper addresses ambiguity issues in natural language texts, and presents a new technique for resolving ambiguity problem in extracting concept/entity from texts. In the end, it shows the importance of TM in knowledge discovery and highlights the up-coming challenges of document mining and the opportunities it offers.

  5. Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course

    Directory of Open Access Journals (Sweden)

    Michail N. Giannakos

    2015-02-01

    Full Text Available Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may provide insights into student learning performance and inform the improvement of video-assisted teaching tactics. Nevertheless, video analytics are not accessible to learning stakeholders, such as researchers and educators, mainly because online video platforms do not broadly share the interactions of the users with their systems. For this purpose, we have designed an open-access video analytics system for use in a video-assisted course. In this paper, we present a longitudinal study, which provides valuable insights through the lens of the collected video analytics. In particular, we found that there is a relationship between video navigation (repeated views and the level of cognition/thinking required for a specific video segment. Our results indicated that learning performance progress was slightly improved and stabilized after the third week of the video-assisted course. We also found that attitudes regarding easiness, usability, usefulness, and acceptance of this type of course remained at the same levels throughout the course. Finally, we triangulate analytics from diverse sources, discuss them, and provide the lessons learned for further development and refinement of video-assisted courses and practices.

  6. Mengolah Data Video Analog menjadi Video Digital Sederhana

    Directory of Open Access Journals (Sweden)

    Nick Soedarso

    2010-10-01

    Full Text Available Nowadays, editing technology has entered the digital age. Technology will demonstrate the evidence of processing analog to digital data has become simpler since editing technology has been integrated in the society in all aspects. Understanding the technique of processing analog to digital data is important in producing a video. To utilize this technology, the introduction of equipments is fundamental to understand the features. The next phase is the capturing process that supports the preparation in editing process from scene to scene; therefore, it will become a watchable video.   

  7. Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

    Directory of Open Access Journals (Sweden)

    Hong Yi

    2008-01-01

    Full Text Available Abstract Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

  8. Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

    Directory of Open Access Journals (Sweden)

    Yuchou Chang

    2008-02-01

    Full Text Available Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

  9. Robust Shot Boundary Detection from Video Using Dynamic Texture

    Directory of Open Access Journals (Sweden)

    Peng Taile

    2014-03-01

    Full Text Available Video boundary detection belongs to a basis subject in computer vision. It is more important to video analysis and video understanding. The existing video boundary detection methods always are effective to certain types of video data. These methods have relatively low generalization ability. We present a novel shot boundary detection algorithm based on video dynamic texture. Firstly, the two adjacent frames are read from a given video. We normalize the two frames to get the same size frame. Secondly, we divide these frames into some sub-domain on the same standard. The following thing is to calculate the average gradient direction of sub-domain and form dynamic texture. Finally, the dynamic texture of adjacent frames is compared. We have done some experiments in different types of video data. These experimental results show that our method has high generalization ability. To different type of videos, our algorithm can achieve higher average precision and average recall relative to some algorithms.

  10. Deteksi Keaslian Video Pada Handycam Dengan Metode Localization Tampering

    Directory of Open Access Journals (Sweden)

    Dewi Yunita Sari

    2017-07-01

    Full Text Available Video merupakan barang bukti digital yang salah satunya berasal dari handycam, dalam hal kejahatan video biasanya dimanipulasi untuk menghilangkan bukti-bukti yang ada di dalamnya, oleh sebab itu diperlukan analisis forensik untuk dapat mendeteksi keaslian video tersebut. Dalam penelitian ini di lakukan manipulasi video dengan attack cropping, zooming, rotation, dan grayscale, hal ini bertujuan untuk membandingkan antara rekaman video asli dan rekaman video tampering, dari rekaman video tersebut dianalisis dengan menggunakann metode localization tampering, yaitu metode deteksi yang menunjukkan bagian pada video yang telah dimanipulasi, dengan menganalisis frame, perhitungan histogram, dan grafik histogram. Dengan localization tampering tersebut maka dapat diketahui letak frame dan durasi pada video yang telah mengalami tampering.

  11. Video Classification and Adaptive QoP/QoS Control for Multiresolution Video Applications on IPTV

    Directory of Open Access Journals (Sweden)

    Huang Shyh-Fang

    2012-01-01

    Full Text Available With the development of heterogeneous networks and video coding standards, multiresolution video applications over networks become important. It is critical to ensure the service quality of the network for time-sensitive video services. Worldwide Interoperability for Microwave Access (WIMAX is a good candidate for delivering video signals because through WIMAX the delivery quality based on the quality-of-service (QoS setting can be guaranteed. The selection of suitable QoS parameters is, however, not trivial for service users. Instead, what a video service user really concerns with is the video quality of presentation (QoP which includes the video resolution, the fidelity, and the frame rate. In this paper, we present a quality control mechanism in multiresolution video coding structures over WIMAX networks and also investigate the relationship between QoP and QoS in end-to-end connections. Consequently, the video presentation quality can be simply mapped to the network requirements by a mapping table, and then the end-to-end QoS is achieved. We performed experiments with multiresolution MPEG coding over WIMAX networks. In addition to the QoP parameters, the video characteristics, such as, the picture activity and the video mobility, also affect the QoS significantly.

  12. A Study of Vehicle Detection and Counting System Based on Video

    Directory of Open Access Journals (Sweden)

    Shuang XU

    2014-10-01

    Full Text Available About the video image processing's vehicle detection and counting system research, which has video vehicle detection, vehicle targets' image processing, and vehicle counting function. Vehicle detection is the use of inter-frame difference method and vehicle shadow segmentation techniques for vehicle testing. Image processing functions is the use of color image gray processing, image segmentation, mathematical morphology analysis and image fills, etc. on target detection to be processed, and then the target vehicle extraction. Counting function is to count the detected vehicle. The system is the use of inter-frame video difference method to detect vehicle and the use of the method of adding frame to vehicle and boundary comparison method to complete the counting function, with high recognition rate, fast, and easy operation. The purpose of this paper is to enhance traffic management modernization and automation levels. According to this study, it can provide a reference for the future development of related applications.

  13. Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

    Directory of Open Access Journals (Sweden)

    Ji Ming

    2008-03-01

    Full Text Available We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

  14. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... of five videos was designed to help you learn more about Rheumatoid Arthritis (RA). You will learn how the diagnosis of RA is made, what ... and what other conditions are associated with RA. Learning more about your condition will allow you to ...

  15. Rheumatoid Arthritis Educational Video Series

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  16. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... will allow you to take a more active role in your care. The information in these videos should not take the place of any advice you receive from your rheumatologist. Click A Link Below To Play Rheumatoid Arthritis: Symptoms and Diagnosis Rheumatoid Arthritis: What ...

  17. Rheumatoid Arthritis Educational Video Series

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    Full Text Available ... are available, what is happening in the immune system and what other conditions are associated with RA. Learning more about your condition will allow you to take a more active role in your care. The information in these videos should not take the place ...

  18. Video nueva herramienta del campo

    Directory of Open Access Journals (Sweden)

    Manuel Calvelo Ríos

    2015-01-01

    Full Text Available El Video resulta ser una herramienta sumamente útil para el desarrollo rural. Entendemos por desarrollo rural el intento de regular las relaciones campo-ciudad en términos más equitativos para el hombre del campo. Es por tanto una decisión política.

  19. Video Games and Citizenship

    National Research Council Canada - National Science Library

    Bourgonjon, Jeroen; Soetaert, Ronald

    2013-01-01

    ... by exploring a particular aspect of digitization that affects young people, namely video games. They explore the new social spaces which emerge in video game culture and how these spaces relate to community building and citizenship...

  20. Videos, Podcasts and Livechats

    Science.gov (United States)

    ... the Team Blog Articles & Stories News Resources Links Videos Podcasts Webinars For the Media For Clinicians For ... Family Caregivers Glossary Menu In this section Links Videos Podcasts Webinars For the Media For Clinicians For ...

  1. Video Screen Capture Basics

    Science.gov (United States)

    Dunbar, Laura

    2014-01-01

    This article is an introduction to video screen capture. Basic information of two software programs, QuickTime for Mac and BlueBerry Flashback Express for PC, are also discussed. Practical applications for video screen capture are given.

  2. A Customizable Text Classifier for Text Mining

    Directory of Open Access Journals (Sweden)

    Yun-liang Zhang

    2007-12-01

    Full Text Available Text mining deals with complex and unstructured texts. Usually a particular collection of texts that is specified to one or more domains is necessary. We have developed a customizable text classifier for users to mine the collection automatically. It derives from the sentence category of the HNC theory and corresponding techniques. It can start with a few texts, and it can adjust automatically or be adjusted by user. The user can also control the number of domains chosen and decide the standard with which to choose the texts based on demand and abundance of materials. The performance of the classifier varies with the user's choice.

  3. Transmission of compressed video

    Science.gov (United States)

    Pasch, H. L.

    1990-09-01

    An overview of video coding is presented. The aim is not to give a technical summary of possible coding techniques, but to address subjects related to video compression in general and to the transmission of compressed video in more detail. Bit rate reduction is in general possible by removing redundant information; removing information the eye does not use anyway; and reducing the quality of the video. The codecs which are used for reducing the bit rate, can be divided into two groups: Constant Bit rate Codecs (CBC's), which keep the bit rate constant, but vary the video quality; and Variable Bit rate Codecs (VBC's), which keep the video quality constant by varying the bit rate. VBC's can be in general reach a higher video quality than CBC's using less bandwidth, but need a transmission system that allows the bandwidth of a connection to fluctuate in time. The current and the next generation of the PSTN does not allow this; ATM might. There are several factors which influence the quality of video: the bit error rate of the transmission channel, slip rate, packet loss rate/packet insertion rate, end-to-end delay, phase shift between voice and video, and bit rate. Based on the bit rate of the coded video, the following classification of coded video can be made: High Definition Television (HDTV); Broadcast Quality Television (BQTV); video conferencing; and video telephony. The properties of these classes are given. The video conferencing and video telephony equipment available now and in the next few years can be divided into three categories: conforming to 1984 CCITT standard for video conferencing; conforming to 1988 CCITT standard; and conforming to no standard.

  4. Making good physics videos

    Science.gov (United States)

    Lincoln, James

    2017-05-01

    Online videos are an increasingly important way technology is contributing to the improvement of physics teaching. Students and teachers have begun to rely on online videos to provide them with content knowledge and instructional strategies. Online audiences are expecting greater production value, and departments are sometimes requesting educators to post video pre-labs or to flip our classrooms. In this article, I share my advice on creating engaging physics videos.

  5. Desktop video conferencing

    OpenAIRE

    Potter, Ray; Roberts, Deborah

    2007-01-01

    This guide aims to provide an introduction to Desktop Video Conferencing. You may be familiar with video conferencing, where participants typically book a designated conference room and communicate with another group in a similar room on another site via a large screen display. Desktop video conferencing (DVC), as the name suggests, allows users to video conference from the comfort of their own office, workplace or home via a desktop/laptop Personal Computer. DVC provides live audio and visua...

  6. Summarization of human activity videos via low-rank approximation

    OpenAIRE

    Mademlis, Ioannis; Tefas, Anastasios; Nikolaidis, Nikos; Pitas, Ioannis

    2017-01-01

    Summarization of videos depicting human activities is a timely problem with important applications, e.g., in the domains of surveillance or film/TV production, that steadily becomes more relevant. Research on video summarization has mainly relied on global clustering or local (frame-by-frame) saliency methods to provide automated algorithmic solutions for key-frame extraction. This work presents a method based on selecting as key-frames video frames able to optimally reconstruct the entire vi...

  7. 47 CFR 79.3 - Video description of video programming.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 4 2010-10-01 2010-10-01 false Video description of video programming. 79.3... CLOSED CAPTIONING AND VIDEO DESCRIPTION OF VIDEO PROGRAMMING § 79.3 Video description of video programming. (a) Definitions. For purposes of this section the following definitions shall apply: (1...

  8. Tech Tips: Using Video Management/ Analysis Technology in Qualitative Research

    Directory of Open Access Journals (Sweden)

    J.A. Spiers

    2004-03-01

    Full Text Available This article presents tips on how to use video in qualitative research. The author states that, though there many complex and powerful computer programs for working with video, the work done in qualitative research does not require those programs. For this work, simple editing software is sufficient. Also presented is an easy and efficient method of transcribing video clips.

  9. Video Vortex reader II: moving images beyond YouTube

    NARCIS (Netherlands)

    Lovink, G.; Somers Miles, R.

    2011-01-01

    Video Vortex Reader II is the Institute of Network Cultures' second collection of texts that critically explore the rapidly changing landscape of online video and its use. With the success of YouTube ('2 billion views per day') and the rise of other online video sharing platforms, the moving image

  10. Video Self-Modeling

    Science.gov (United States)

    Buggey, Tom; Ogle, Lindsey

    2012-01-01

    Video self-modeling (VSM) first appeared on the psychology and education stage in the early 1970s. The practical applications of VSM were limited by lack of access to tools for editing video, which is necessary for almost all self-modeling videos. Thus, VSM remained in the research domain until the advent of camcorders and VCR/DVD players and,…

  11. Tracing Sequential Video Production

    DEFF Research Database (Denmark)

    Otrel-Cass, Kathrin; Khalid, Md. Saifuddin

    2015-01-01

    With an interest in learning that is set in collaborative situations, the data session presents excerpts from video data produced by two of fifteen students from a class of 5th semester techno-anthropology course. Students used video cameras to capture the time they spent working with a scientist...... video, nature of the interactional space, and material and spatial semiotics....

  12. Developing a Promotional Video

    Science.gov (United States)

    Epley, Hannah K.

    2014-01-01

    There is a need for Extension professionals to show clientele the benefits of their program. This article shares how promotional videos are one way of reaching audiences online. An example is given on how a promotional video has been used and developed using iMovie software. Tips are offered for how professionals can create a promotional video and…

  13. Obtaining video descriptors for a content-based video information system

    Science.gov (United States)

    Bescos, Jesus; Martinez, Jose M.; Cabrera, Julian M.; Cisneros, Guillermo

    1998-09-01

    This paper describes the first stages of a research project that is currently being developed in the Image Processing Group of the UPM. The aim of this effort is to add video capabilities to the Storage and Retrieval Information System already working at our premises. Here we will focus on the early design steps of a Video Information System. For this purpose, we present a review of most of the reported techniques for video temporal segmentation and semantic segmentation, previous steps to afford the content extraction task, and we discuss them to select the more suitable ones. We then outline a block design of a temporal segmentation module, and present guidelines to the design of the semantic segmentation one. All these operations trend to facilitate automation in the extraction of low level features and semantic features that will finally take part of the video descriptors.

  14. ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

    Directory of Open Access Journals (Sweden)

    I Made Oka Widyantara

    2015-12-01

    Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG-DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views

  15. Text mining for systems biology.

    Science.gov (United States)

    Fluck, Juliane; Hofmann-Apitius, Martin

    2014-02-01

    Scientific communication in biomedicine is, by and large, still text based. Text mining technologies for the automated extraction of useful biomedical information from unstructured text that can be directly used for systems biology modelling have been substantially improved over the past few years. In this review, we underline the importance of named entity recognition and relationship extraction as fundamental approaches that are relevant to systems biology. Furthermore, we emphasize the role of publicly organized scientific benchmarking challenges that reflect the current status of text-mining technology and are important in moving the entire field forward. Given further interdisciplinary development of systems biology-orientated ontologies and training corpora, we expect a steadily increasing impact of text-mining technology on systems biology in the future. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Detection of Double-Compressed H.264/AVC Video Incorporating the Features of the String of Data Bits and Skip Macroblocks

    Directory of Open Access Journals (Sweden)

    Heng Yao

    2017-12-01

    Full Text Available Today’s H.264/AVC coded videos have a high quality, high data-compression ratio. They also have a strong fault tolerance, better network adaptability, and have been widely applied on the Internet. With the popularity of powerful and easy-to-use video editing software, digital videos can be tampered with in various ways. Therefore, the double compression in the H.264/AVC video can be used as a first step in the study of video-tampering forensics. This paper proposes a simple, but effective, double-compression detection method that analyzes the periodic features of the string of data bits (SODBs and the skip macroblocks (S-MBs for all I-frames and P-frames in a double-compressed H.264/AVC video. For a given suspicious video, the SODBs and S-MBs are extracted for each frame. Both features are then incorporated to generate one enhanced feature to represent the periodic artifact of the double-compressed video. Finally, a time-domain analysis is conducted to detect the periodicity of the features. The primary Group of Pictures (GOP size is estimated based on an exhaustive strategy. The experimental results demonstrate the efficacy of the proposed method.

  17. Text-Attentional Convolutional Neural Network for Scene Text Detection.

    Science.gov (United States)

    He, Tong; Huang, Weilin; Qiao, Yu; Yao, Jian

    2016-06-01

    Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images. They extract a high-level feature globally computed from a whole image component (patch), where the cluttered background information may dominate true text features in the deep representation. This leads to less discriminative power and poorer robustness. In this paper, we present a new system for scene text detection by proposing a novel text-attentional convolutional neural network (Text-CNN) that particularly focuses on extracting text-related regions and features from the image components. We develop a new learning mechanism to train the Text-CNN with multi-level and rich supervised information, including text region mask, character label, and binary text/non-text information. The rich supervision information enables the Text-CNN with a strong capability for discriminating ambiguous texts, and also increases its robustness against complicated background components. The training process is formulated as a multi-task learning problem, where low-level supervised information greatly facilitates the main task of text/non-text classification. In addition, a powerful low-level detector called contrast-enhancement maximally stable extremal regions (MSERs) is developed, which extends the widely used MSERs by enhancing intensity contrast between text patterns and background. This allows it to detect highly challenging text patterns, resulting in a higher recall. Our approach achieved promising results on the ICDAR 2013 data set, with an F-measure of 0.82, substantially improving the state-of-the-art results.

  18. An Evaluation of Educational Neurological Eye Movement Disorder Videos Posted on Internet Video Sharing Sites.

    Science.gov (United States)

    Hickman, Simon J

    2016-03-01

    Internet video sharing sites allow the free dissemination of educational material. This study investigated the quality and educational content of videos of eye movement disorders posted on such sites. Educational neurological eye movement videos were identified by entering the titles of the eye movement abnormality into the search boxes of the video sharing sites. Also, suggested links were followed from each video. The number of views, likes, and dislikes for each video were recorded. The videos were then rated for their picture and sound quality. Their educational value was assessed according to whether the video included a description of the eye movement abnormality, the anatomical location of the lesion (if appropriate), and the underlying diagnosis. Three hundred fifty-four of these videos were found on YouTube and Vimeo. There was a mean of 6,443 views per video (range, 1-195,957). One hundred nineteen (33.6%) had no form of commentary about the eye movement disorder shown apart from the title. Forty-seven (13.3%) contained errors in the title or in the text. Eighty (22.6%) had excellent educational value by describing the eye movement abnormality, the anatomical location of the lesion, and the underlying diagnosis. Of these, 30 also had good picture and sound quality. The videos with excellent educational value had a mean of 9.84 "likes" per video compared with 2.37 for those videos without a commentary (P educational value with good picture and sound quality had a mean of 10.23 "likes" per video (P = 0.004 vs videos with no commentary). There was no significant difference in the mean number of "dislikes" between those videos that had no commentary or which contained errors and those with excellent educational value. There are a large number of eye movement videos freely available on these sites; however, due to the lack of peer review, a significant number have poor educational value due to having no commentary or containing errors. The number of "likes

  19. Refilming with depth-inferred videos.

    Science.gov (United States)

    Zhang, Guofeng; Dong, Zilong; Jia, Jiaya; Wan, Liang; Wong, Tien-Tsin; Bao, Hujun

    2009-01-01

    Compared to still image editing, content-based video editing faces the additional challenges of maintaining the spatiotemporal consistency with respect to geometry. This brings up difficulties of seamlessly modifying video content, for instance, inserting or removing an object. In this paper, we present a new video editing system for creating spatiotemporally consistent and visually appealing refilming effects. Unlike the typical filming practice, our system requires no labor-intensive construction of 3D models/surfaces mimicking the real scene. Instead, it is based on an unsupervised inference of view-dependent depth maps for all video frames. We provide interactive tools requiring only a small amount of user input to perform elementary video content editing, such as separating video layers, completing background scene, and extracting moving objects. These tools can be utilized to produce a variety of visual effects in our system, including but not limited to video composition, "predator" effect, bullet-time, depth-of-field, and fog synthesis. Some of the effects can be achieved in real time.

  20. Studenterproduceret video til eksamen

    Directory of Open Access Journals (Sweden)

    Kenneth Hansen

    2016-05-01

    Full Text Available Formålet med denne artikel er at vise, hvordan læringsdesign og stilladsering kan anvendes til at skabe en ramme for studenterproduceret video til eksamen på videregående uddannelser. Artiklen tager udgangspunkt i en problemstilling, hvor uddannelsesinstitutionerne skal håndtere og koordinere undervisning inden for både det faglige område og mediefagligt område og sikre en balance mellem en fagfaglighed og en mediefaglig tilgang. Ved at dele opgaven ud på flere faglige resurser, er der mere koordinering, men man kommer omkring problemet med krav til underviserne om dobbelt faglighed ved medieproduktioner. Med afsæt i Lanarca Declarationens perspektiver på læringsdesign og hovedsageligt Jerome Bruners principper for stilladsering, sammensættes en model for understøttelse af videoproduktion af studerende på videregående uddannelser. Ved at anvende denne model for undervisningssessioner og forløb får de fagfaglige og mediefaglige undervisere et redskab til at fokusere og koordinere indsatsen frem mod målet med, at de studerende producerer og anvender video til eksamen.

  1. Summarization of Surveillance Video Sequences Using Face Quality Assessment

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.; Rahmati, Mohammad

    2011-01-01

    Constant working surveillance cameras in public places, such as airports and banks, produce huge amount of video data. Faces in such videos can be extracted in real time. However, most of these detected faces are either redundant or useless. Redundant information adds computational costs to facial...

  2. Practicality in Virtuality: Finding Student Meaning in Video Game Education

    Science.gov (United States)

    Barko, Timothy; Sadler, Troy D.

    2013-01-01

    This paper looks at the conceptual differences between video game learning and traditional classroom and laboratory learning. It explores the notion of virtual experience by comparing a commonly used high school laboratory protocol on DNA extraction with a similar experience provided by a biotechnology themed video game. When considered…

  3. Intelligent video surveillance systems

    CERN Document Server

    Dufour, Jean-Yves

    2012-01-01

    Belonging to the wider academic field of computer vision, video analytics has aroused a phenomenal surge of interest since the current millennium. Video analytics is intended to solve the problem of the incapability of exploiting video streams in real time for the purpose of detection or anticipation. It involves analyzing the videos using algorithms that detect and track objects of interest over time and that indicate the presence of events or suspect behavior involving these objects.The aims of this book are to highlight the operational attempts of video analytics, to identify possi

  4. VBR video traffic models

    CERN Document Server

    Tanwir, Savera

    2014-01-01

    There has been a phenomenal growth in video applications over the past few years. An accurate traffic model of Variable Bit Rate (VBR) video is necessary for performance evaluation of a network design and for generating synthetic traffic that can be used for benchmarking a network. A large number of models for VBR video traffic have been proposed in the literature for different types of video in the past 20 years. Here, the authors have classified and surveyed these models and have also evaluated the models for H.264 AVC and MVC encoded video and discussed their findings.

  5. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... Search Parents Home General Health Growth & Development Infections Diseases & Conditions Pregnancy & Baby Nutrition & Fitness Emotions & Behavior School & ... Safety Too Late for the Flu Vaccine? Eating Disorders Arrhythmias Special Needs: Planning for Adulthood (Video) KidsHealth > ...

  6. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... page is best accessed via your desktop. Celiac Disease Program Home > Centers + Services > Programs and Services > Celiac ... Bone Health Program Growth and Nutrition Program Celiac Disease Program | Videos Contact the Celiac Disease Program 1- ...

  7. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Find a Doctor Find a Location Overview Meet our Team Conditions and Treatments Celiac Support Group Patient ... to live happy and productive lives. Each of our video segments provides practical information about celiac disease ...

  8. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... This page is best accessed via your desktop. Celiac Disease Program Home > Centers + Services > Programs and Services > Celiac ... Nutrition Bone Health Program Growth and Nutrition Program Celiac Disease Program | Videos Contact the Celiac Disease Program 1- ...

  9. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... get the care they need. Learn about giving This page is best accessed via your desktop. Celiac ... Disease Program | Videos Contact the Celiac Disease Program 1-617-355-6058 Visit the Celiac Support Group ...

  10. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... Cope With a Parent's Suicide? Special Needs: Planning for Adulthood (Video) KidsHealth > For Parents > Special Needs: Planning ... options. For Teens For Kids For Parents MORE ON THIS TOPIC Financial Planning for Kids With Special ...

  11. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Disease Program Overview > Videos Request an Appointment Second Opinion Find a Doctor Find a Location Overview Meet ... We Help You? International Visitors Get a Second Opinion Find a Doctor Centers and Services Conditions + Treatments ...

  12. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Overview Meet our Team Conditions and Treatments Celiac Support Group Patient Resources + Videos – Experiencing Celiac Disease What ... Program 1-617-355-6058 Visit the Celiac Support Group Facebook page CSG Facebook Page Boston Children's ...

  13. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Back to School Programs Healthful Living Injuries and Safety More Boston Children's Hospital #1 Ranked Children’s Hospital ... Giving to Boston Children's Newsroom Quality and Patient Safety Research + Innovation Videos Contact Us Boston Children's Hospital ...

  14. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... video series together to learn about everything from financial and health care benefits to employment and housing ... For Kids For Parents MORE ON THIS TOPIC Financial Planning for Kids With Special Needs Giving Teens ...

  15. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... for Adulthood (Video) Print A A A Young adults with special needs have many programs, services, and ... Care for Your Child With Special Needs Special Education: Getting Support for Your Child Words to Know ( ...

  16. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Us Giving to Boston Children's Newsroom Quality and Patient Safety Research + Innovation Videos Contact Us Boston Children's Hospital 300 Longwood Avenue, Boston, MA 02115 For Patients: 617-355-6000 For Referring Providers: 844-BCH- ...

  17. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... This page is best accessed via your desktop. Celiac Disease Program Home > Centers + Services > Programs and Services > ... Nutrition Bone Health Program Growth and Nutrition Program Celiac Disease Program | Videos Contact the Celiac Disease Program ...

  18. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... they need. Learn about giving This page is best accessed via your desktop. Celiac Disease Program Home ... Resources + Videos – Experiencing Celiac Disease What is Celiac ...

  19. Celiac Family Health Education Video Series

    Medline Plus

    Full Text Available ... Videos – Experiencing Celiac Disease What is Celiac Disease Diet Information At Home Shopping Cooking + School Eating Out ... What is Celiac Disease? : Diagnosis and treatment III. Diet Information : How to start and maintain a gluten- ...

  20. Special Needs: Planning for Adulthood (Videos)

    Medline Plus

    Full Text Available ... video series together to learn about everything from financial and health care benefits to employment and housing options. More on this topic for: Parents Financial Planning for Kids With Special Needs Giving Teens ...