213 research outputs found

    An educational ontology-based M-learning system

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    Smart devices applications can assist young children in improving their learning capabilities and comprehension skills. However most of learning applications are built without taking into consideration the effective needs and background of Arab users. They are somehow incompatible with their local environment and culture. We propose in this paper a mobile-based educational system that displays illustrations automatically to characterize the content of children' stories on animal domain, and we use some intelligent technique to answer users' questions using an educational ontology. The generation of illustrations passes through different phases which include text processing, extraction of word-to-word relationships, building and accessing an ontology, and using Internet search engines for retrieval of complimentary information. The system can be used also by instructors to teach the children in a nonconventional manner. They can customize semantically the structure of the questions and determine how the answers will be displayed. In order to customize questions and answers, we have defined a semantic infrastructure to define the logic of terms, and the workflow of answers. The aim of our system is to improve the children educational skills to grasp vocabulary and grammar using multimedia with a portable smart device which includes observation, comprehension, realization, and deduction. Children will then be able to continue learning outside the limited time of their schools and from any location.Scopu

    Expanding the Usage of Web Archives by Recommending Archived Webpages Using Only the URI

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    Web archives are a window to view past versions of webpages. When a user requests a webpage on the live Web, such as http://tripadvisor.com/where_to_t ravel/, the webpage may not be found, which results in an HyperText Transfer Protocol (HTTP) 404 response. The user then may search for the webpage in a Web archive, such as the Internet Archive. Unfortunately, if this page had never been archived, the user will not be able to view the page, nor will the user gain any information on other webpages that have similar content in the archive, such as the archived webpage http://classy-travel.net. Similarly, if the user requests the webpage http://hokiesports.com/football/ from the Internet Archive, the user will only find the requested webpage, and the user will not gain any information on other webpages that have similar content in the archive, such as the archived webpage http://techsideline.com. In this research, we will build a model for selecting and ranking possible recommended webpages at a Web archive. This is to enhance both HTTP 404 responses and HTTP 200 responses by surfacing webpages in the archive that the user may not know existed. First, we detect semantics in the requested Uniform Resource Identifier (URI). Next, we classify the URI using an ontology, such as DMOZ or any website directory. Finally, we filter and rank candidates based on several features, such as archival quality, webpage popularity, temporal similarity, and content similarity. We measure the performance of each step using different techniques, including calculating the F1 to measure of different tokenization methods and the classification. We tested the model using human evaluation to determine if we could classify and find recommendations for a sample of requests from the Internet Archive’s Wayback Machine access log. Overall, when selecting the full categorization, reviewers agreed with 80.3% of the recommendations, which is much higher than “do not agree” and “I do not know”. This indicates the reviewer is more likely to agree on the recommendations when selecting the full categorization. But when selecting the first level only, reviewers only agreed with 25.5% of the recommendations. This indicates that having deep level categorization improves the performance of finding relevant recommendations

    Information Outlook, February 2001

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    Volume 5, Issue 2https://scholarworks.sjsu.edu/sla_io_2001/1001/thumbnail.jp

    Embodied science and mixed reality: How gesture and motion capture affect physics education

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    abstract: A mixed design was created using text and game-like multimedia to instruct in the content of physics. The study assessed which variables predicted learning gains after a 1-h lesson on the electric field. The three manipulated variables were: (1) level of embodiment; (2) level of active generativity; and (3) presence of story narrative. Two types of tests were administered: (1) a traditional text-based physics test answered with a keyboard; and (2) a more embodied, transfer test using the Wacom large tablet where learners could use gestures (long swipes) to create vectors and answers. The 166 participants were randomly assigned to four conditions: (1) symbols and text; (2) low embodied; (3) high embodied/active; or (4) high embodied/active with narrative. The last two conditions were active because the on-screen content could be manipulated with gross body gestures gathered via the Kinect sensor. Results demonstrated that the three groups that included embodiment learned significantly more than the symbols and text group on the traditional keyboard post-test. When knowledge was assessed with the Wacom tablet format that facilitated gestures, the two active gesture-based groups scored significantly higher. In addition, engagement scores were significantly higher for the two active embodied groups. The Wacom results suggest test sensitivity issues; the more embodied test revealed greater gains in learning for the more embodied conditions. We recommend that as more embodied learning comes to the fore, more sensitive tests that incorporate gesture be used to accurately assess learning. The predicted differences in engagement and learning for the condition with the graphically rich story narrative were not supported. We hypothesize that a narrative effect for motivation and learning may be difficult to uncover in a lab experiment where participants are primarily motivated by course credit. Several design principles for mediated and embodied science education are proposed.The electronic version of this article is the complete one and can be found online at: http://cognitiveresearchjournal.springeropen.com/articles/10.1186/s41235-017-0060-

    Web Archive Services Framework for Tighter Integration Between the Past and Present Web

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    Web archives have contained the cultural history of the web for many years, but they still have a limited capability for access. Most of the web archiving research has focused on crawling and preservation activities, with little focus on the delivery methods. The current access methods are tightly coupled with web archive infrastructure, hard to replicate or integrate with other web archives, and do not cover all the users\u27 needs. In this dissertation, we focus on the access methods for archived web data to enable users, third-party developers, researchers, and others to gain knowledge from the web archives. We build ArcSys, a new service framework that extracts, preserves, and exposes APIs for the web archive corpus. The dissertation introduces a novel categorization technique to divide the archived corpus into four levels. For each level, we will propose suitable services and APIs that enable both users and third-party developers to build new interfaces. The first level is the content level that extracts the content from the archived web data. We develop ArcContent to expose the web archive content processed through various filters. The second level is the metadata level; we extract the metadata from the archived web data and make it available to users. We implement two services, ArcLink for temporal web graph and ArcThumb for optimizing the thumbnail creation in the web archives. The third level is the URI level that focuses on using the URI HTTP redirection status to enhance the user query. Finally, the highest level in the web archiving service framework pyramid is the archive level. In this level, we define the web archive by the characteristics of its corpus and building Web Archive Profiles. The profiles are used by the Memento Aggregator for query optimization

    Motion capture data processing, retrieval and recognition.

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    Character animation plays an essential role in the area of featured film and computer games. Manually creating character animation by animators is both tedious and inefficient, where motion capture techniques (MoCap) have been developed and become the most popular method for creating realistic character animation products. Commercial MoCap systems are expensive and the capturing process itself usually requires an indoor studio environment. Procedural animation creation is often lacking extensive user control during the generation progress. Therefore, efficiently and effectively reusing MoCap data can brings significant benefits, which has motivated wider research in terms of machine learning based MoCap data processing. A typical work flow of MoCap data reusing can be divided into 3 stages: data capture, data management and data reusing. There are still many challenges at each stage. For instance, the data capture and management often suffer from data quality problems. The efficient and effective retrieval method is also demanding due to the large amount of data being used. In addition, classification and understanding of actions are the fundamental basis of data reusing. This thesis proposes to use machine learning on MoCap data for reusing purposes, where a frame work of motion capture data processing is designed. The modular design of this framework enables motion data refinement, retrieval and recognition. The first part of this thesis introduces various methods used in existing motion capture processing approaches in literature and a brief introduction of relevant machine learning methods used in this framework. In general, the frameworks related to refinement, retrieval, recognition are discussed. A motion refinement algorithm based on dictionary learning will then be presented, where kinematical structural and temporal information are exploited. The designed optimization method and data preprocessing technique can ensure a smooth property for the recovered result. After that, a motion refinement algorithm based on matrix completion is presented, where the low-rank property and spatio-temporal information is exploited. Such model does not require preparing data for training. The designed optimization method outperforms existing approaches in regard to both effectiveness and efficiency. A motion retrieval method based on multi-view feature selection is also proposed, where the intrinsic relations between visual words in each motion feature subspace are discovered as a means of improving the retrieval performance. A provisional trace-ratio objective function and an iterative optimization method are also included. A non-negative matrix factorization based motion data clustering method is proposed for recognition purposes, which aims to deal with large scale unsupervised/semi-supervised problems. In addition, deep learning models are used for motion data recognition, e.g. 2D gait recognition and 3D MoCap recognition. To sum up, the research on motion data refinement, retrieval and recognition are presented in this thesis with an aim to tackle the major challenges in motion reusing. The proposed motion refinement methods aim to provide high quality clean motion data for downstream applications. The designed multi-view feature selection algorithm aims to improve the motion retrieval performance. The proposed motion recognition methods are equally essential for motion understanding. A collection of publications by the author of this thesis are noted in publications section

    Spartan Daily, September 25, 1995

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    Volume 105, Issue 17https://scholarworks.sjsu.edu/spartandaily/8732/thumbnail.jp

    Integrating Wireless Sensor Networks and Mobile Ad-hoc NETworks for enhanced value-added services

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    In some situations where the standard telecommunication infrastructure is not available, Mobile Ad hoc NETworks (MANETs) can be deployed to provide the required communication. These networks are established "on the fly" without a need for prior communication organization and are composed of autonomous mobile devices, such as cell phones, PDAs or laptops. In similar conditions, such as in emergency response operations, integrating MANETs and Wireless Sensor Networks (WSNs) can notably enhance the MANET participant's end-user experience. WSNs sense and aggregate ambient information, such as physiological, environmental or physical data related to a nearby phenomenon. The integration, which provides end-user availability to WSN required information, is feasible via gateways. However, when the ambient information collected by WSNs is intended for applications residing in MANETs, centralized and fixed gateways are not practicably feasible. This is mainly due to ad-hoc nature, lack of centralized control and constraints on the end-user devices that are used in MANETs. These devices are usually limited in power and capacity and cannot host centralized gateways. In this thesis we exploit the integration of WSN and MANET in order to provide novel value-added services which enhance the end-user experience of MANET participants. Motivating scenarios are introduced, background information is presented, requirements are derived and the state of the art regarding the integration of WSN with existing networks, including MANETs, is evaluated. Based on the evaluation, none of the existing solutions satisfies all of our derived requirements. Therefore, we propose an overall two-level overlay architecture to integrate WSNs (with mobile sinks) and MANETs. This architecture is based on the distributed gateway and applications which form the P2P overlays. Overlays are application-layer networks which are created on top of the exiting MANET. To interconnect gateway and application overlays we derive corresponding requirements and evaluate the existing approaches. Since none of these approaches fulfills all of our requirements, we propose protocols, mechanisms and design corresponding modules for the interconnection of overlays. Finally we refine our overall architecture based on the interconnection aspects. As a proof of concept, we implement a prototype for the inter-overlay information exchange. This implementation is based on SIP extensions and uses two existing P2P middlewares. We also simulate our prototype using Oversim simulation tool and collect experimental results. Based on these results, we can see that our architecture is a valid and promising approach for interconnecting different P2P overlays and can be deployed to provide the overall solution for WSN and MANET integrated system
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