86,852 research outputs found

    Integration of sensorimotor mappings by making use of redundancies

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    Hemion N, Joublin F, Rohlfing K. Integration of sensorimotor mappings by making use of redundancies. In: IEEE Computational Intelligence Society, Institute of Electrical and Electronics Engineers, eds. The 2012 International Joint Conference on Neural Networks (IJCNN). Brisbane, Australia: IEEE; 2012

    Student Professional Awareness Conference - Additional Details | Electrical and Computer Engineering

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    LOGAN, Utah – March 16, 2015 – The USU local chapter of IEEE, institute of electrical and electronics engineers, will have the privilege of hosting the annual StudentProfessional Awareness conference, SPAC 2015, on March 28, 2015.https://digitalcommons.usu.edu/engineering_news/1043/thumbnail.jp

    Capacities of classical compound quantum wiretap and classical quantum compound wiretap channels

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    We determine the capacity of the classical compound quantum wiretapper channel with channel state information at the transmitter. Moreover we derive a lower bound on the capacity of this channel without channel state information and determine the capacity of the classical quantum compound wiretap channel with channel state information at the transmitter

    Impacts of buffering voice calls in integrated voice and data services

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    In this study, we aim to analyse the relationship between various characteristics of a communication system with data and voice call requests. Queuing theory and Markov chain analysis are effectively used for this purpose. Such a study is useful for understanding how the proposed mathematical models behave which represents a system with integrated voice and data calls in homogenous wireless networks. We also propose to optimise the system characteristics in an attempt to provide better Quality of Service (QoS) for systems with integrated voice and data calls. The proposed models have two dimensions; one for voice calls and one for data calls. A channel is assigned for two input traffic call, namely, voice and data calls. The incoming voice and data calls are queued when the channel is busy. Since voice calls are delay-sensitive, priority is given to voice calls. Also, since there is only one channel, data calls are only serviced if there are no voice calls in the system. For such systems, it is important to analyse the impact of buffering the voice calls as well as data calls for various mean rates of call requests, and mean service times. The analytical models presented are generic which is applicable for various systems with similar characteristics. Numerical results are also provided. The results show that the proposed models can be used for optimisation of the performance of a given network

    Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals

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    From 2000, mobile Learning (m-Learning) and ubiquitous Learning (u-Learning) has been the hottest research topic in e-learning, and now, integrating ubiquitous learning into mainstream of education and train has been the direction in the area, which demand new generational e-learning system. The paper introduces our research efforts in this direction. Based on the key concepts, such as ubiquitous learning object, mini-courseware, a new generational ubiquitous e-learning system is designed, which can be used for new requirements in m-Learning and u-Learning environments. In the system, learning resource related to a course is encapsulated into different ubiquitous learning objects, and mini-courseware can be assembled dynamically with learning resource extracted from these ubiquitous learning objects, accordingly, a mini-courseware player is designed for the situation. Based on these work, a resource based ubiquitous e-Learning system is designed considering pedagogical requirements under m-Learning and u-Learning environment

    Anggota IEEE

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    Menjadi anggota organisasi profesi Kode: E.3.a.3. Tingkat Internasional: Anggota The Institute of Electrical and Electronics Engineers (IEEE

    EFFICIENT FINE-GRAINED 802.11AX BSR-BASED OFDMA RU ALLOCATION

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    Proposed herein are techniques that provide a simple Institute of Electrical and Electronics Engineers (IEEE) 802.11ax (WiFi6®) uplink (UL) orthogonal frequency-division multiple access (OFDMA) throughput improvement by exploiting existing standards and enterprise traffic patterns

    Education and Workforce Development

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    The University of Maine Artificial Intelligence Initiative (UMaine AI) is a unique Maine-based venture that brings together university, industry, government, and community collaborators from Maine and beyond to advance the field of artificial intelligence, and through development of innovative technologies and applications find transformative solutions to enhance human life and societal well-being in Maine and beyond
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