14,237 research outputs found

    Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

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    Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

    Data literacy in the smart university approach

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    Equipping classrooms with inexpensive sensors for data collection can provide students and teachers with the opportunity to interact with the classroom in a smart way. In this paper two approaches to acquiring contextual data from a classroom environment are presented. We further present our approach to analysing the collected room usage data on site, using low cost single board computer, such as a Raspberry Pi and Arduino units, performing a significant part of the data analysis on-site. We demonstrate how the usage data was used to model specifcic room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was then integrated in a room recommender system, reasoning on the formalised usage data, allowing for a convenient and intuitive end user experience based on the collected raw sensor data. Having implemented and tested our approaches we are currently investigating the possibility of using (XML)Schema-informed compression to enhance the security and efficiency of the transmission of a large number of sensor reports generated by interpreting the raw data on-site, to our central data sink. We are investigating this new approach to usage data transmission as we are aiming to integrate our on-going work into our vision of the Smart University to ensure and enhance the Smart University's data literacy

    Approaches to the use of sensor data to improve classroom experience

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    quipping classrooms with inexpensive sensors can enable students and teachers with the opportunity to interact with the classroom in a smart way. In this paper an approach to acquiring contextual data from a classroom environment, using inexpensive sensors, is presented. We present our approach to formalising the usage data. Further we demonstrate how the data was used to model specific room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was than integrated in a room recommendations system, reasoning on the formalised usage data. We also detail on our on-going work to integrating the systems presented in this paper into our Smart University vision

    Participatory Monitoring of Community-Based Rehabilitation and other Disability- Inclusive Development Programmes: the Development of a Manual and Menu

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    Purpose: This paper describes a three-year research project leading to the development of the CBR Monitoring Manual and Menu (MM&M). The MM&M is a practical toolkit that meets the needs of CBR managers and stakeholders, and is consistent with the philosophy of CBR and community-based disability-inclusive development. It is designed to produce meaningful and locally useful information and data, based on international data standards where possible, to enable aggregation at regional, national and international levels. Methods: Five complementary workstreams of research were carried out from 2011 to 2014: 1) literature review and analysis; 2) participatory action research with CBR stakeholders; 3) analysis and refinement of validity of concepts and structures; 4) consultation and review; and 5) synthesis of results. This article documents the method and key results of each of the five workstreams, and the lessons learned along the way. Results: The MM&M is now freely available on-line at http://sydney.edu.au/health-sciences/cdrp/projects/cbr-monitoring.shtml. Collaboration among members of the development team continues, chiefly via an on-line group to which new members have been welcomed. Conclusion and Implications: At the time of writing, the MM&M is the only international monitoring product, known to the authors, that consciously sets out to reflect both a ‘bottom- up’ and ‘top-down’ perspective of monitoring information and data. To achieve this for a complex programme such as CBR, and to align with its principles, it was essential to use a multi-component and multi-stage strategy for tool development, involving a diverse multidisciplinary team includingcollaboration with CBR stakeholders

    Heterogeneous V2V Communications in Multi-Link and Multi-RAT Vehicular Networks

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    Connected and automated vehicles will enable advanced traffic safety and efficiency applications thanks to the dynamic exchange of information between vehicles, and between vehicles and infrastructure nodes. Connected vehicles can utilize IEEE 802.11p for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. However, a widespread deployment of connected vehicles and the introduction of connected automated driving applications will notably increase the bandwidth and scalability requirements of vehicular networks. This paper proposes to address these challenges through the adoption of heterogeneous V2V communications in multi-link and multi-RAT vehicular networks. In particular, the paper proposes the first distributed (and decentralized) context-aware heterogeneous V2V communications algorithm that is technology and application agnostic, and that allows each vehicle to autonomously and dynamically select its communications technology taking into account its application requirements and the communication context conditions. This study demonstrates the potential of heterogeneous V2V communications, and the capability of the proposed algorithm to satisfy the vehicles' application requirements while approaching the estimated upper bound network capacity

    CAES: A Model of an RBR-CBR Course Advisory Expert System

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    Academic student advising is a gargantuan task that places heavy demand on the time, emotions and mental resources of the academic advisor. It is also a mission critical and very delicate task that must be handled with impeccable expertise and precision else the future of the intended student beneficiary may be jeopardized due to poor advising. One integral aspect of student academic advising is course registration, where students make decisions on the choice of courses to take in specific semesters based on their current academic standing. In this paper, we give the description of the design, implementation and trial evaluation of the Course Advisory Expert System (CAES) which is a hybrid of a rule based reasoning (RBR) and case based reasoning (CBR). The RBR component was implemented using JESS. The result of the trial experiment revealed that the system has high performance/user satisfaction rating from the sample expert population conducted

    Web-based CBR (case-based reasoning) as a tool with the application to tooling selection

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    Over the past few years, manufacturing companies have had to deal with an increasing demand for feature-rich products at low costs. The pressures exerted on their existing manufacturing processes have lead manufacturers to investigate internet-based solutions, in order to cope with growing competition. The decentralisation phenomenon also came up as a reason to implement networked-application, which has been the starting point for internet/intranet–based systems. Today, the availability of powerful and low cost 3D tools, database backend systems, along with web-based technologies, provides interesting opportunities to the manufacturing community, with solutions directly implementable at the core of their businesses and organisations. In this paper a web-based engineering approach is presented to developing a design support system using case-based reasoning (CBR) technology for helping in the decision-making process when choosing cutting tools. The system aims to provide on-line intelligent support for determining the most suitable configuration for turning operations, based on initial parameters and requirements for the cutting operation. The system also features a user-driven 3D turning simulator which allows testing the chosen insert for several turning operations. The system aims to be a useful e-manufacturing tool being able to quickly and responsively provide tooling data in a highly interactive way
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