2.05 Vincent Mary School of Science and Technology
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ItemThe 2002 AU academic awards(Assumption University, 2003) Narong Chomchalow ; Assumption University. Vincent Mary School of Science and Technology
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ItemThe 2003 AU awards for excellence(Assumption University, 2004) Narong Chomchalow ; Assumption University. Vincent Mary School of Science and Technology
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ItemThe 2006 AU Academic Award presentations(Assumption University, 2007) Staff, Editorial ; Assumption University. Vincent Mary School of Science and Technology
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ItemAcademic call center(Bangkok : Assumption University, 2001) Thitipong Srivatanakul ; Pichit Cheirsilpa, jt. auth. ; Pongthorn Wanitchinda, jt. auth.
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ItemAn Adaptive Learning Algorithm for Supervised Neural Network with Contour Preserving Classification( 2009-11) Piyabute Fuangkhon ; Thitipong TanprasertA study of noise tolerance characteristics of an adaptive learning algorithm for supervised neural network is presented in this paper. The algorithm allows the existing knowledge to age out in slow rate as a supervised neural network is gradually retrained with consecutive sets of new samples, resembling the change of application locality under a consistent environment. The algorithm utilizes the contour preserving classification algorithm to pre-process the training data to improve the classification and the noise tolerance. The experimental results convincingly confirm the effectiveness of the algorithm and the improvement of noise tolerance.
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ItemAdaptive Location Update Schemes for Continuous Cell Zooming Algorithm in Wireless Networks( 2015) Tun, Khin Cho ; Kunagorn KunavutContinuous cell zooming algorithm is a potential dynamic cell zooming algorithm for energy-efficient operation of mobile wireless networks. In this algorithm, location management strategy (location update process) is required to know the location of the farthest user in each cell to perform cell zooming. However, the application of conventional periodic update scheme in continuous cell zooming algorithm can lead to a high signaling cost. Therefore, in this paper, two adaptive location update schemes, namely, Time-Adaptive Periodic Update (TAPU) and Location-Adaptive Periodic Update (LAPU) are proposed aiming to reduce the number of update messages in continuous cell zooming operation. The performances of the proposed adaptive location update schemes are compared with that of Convention Periodic Update (CPU) scheme. Their performances are evaluated in terms of power saving capability, outage ratio and number of update messages raised in cell zooming operation in both omni-directional and sector-based cell networks. The TAPU and LAPU have no significant effect on power saving capability of continuous cell zooming algorithm and they give less number of update messages compared to CPU scheme. However, outage occurs in cell zooming operation with TAPU scheme because it has longer update intervals. Meanwhile the LAPU scheme can eliminate outage in cell zooming operation as CPU scheme does.
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ItemAdaptive Membership Functions for Handover Decision System in Wireless Mobile Network( 2016) Thanachai ThumthawatwornWireless mobile networks in the future are envisioned to demand more intelligent handover decision mechanisms to achieve seamless mobility and services. Fuzzy logic algorithms were proposed to enhance the handover decision process in recent years. However, most proposed algorithms deploy fixed fuzzy membership functions (FMFs). This approach gives an unsatisfactory network selection performance when different traffic types (service options) are required. In this work, we are proposing a new approach to handover decision system (HDS) design. The proposed design incorporates self-tuning of FMFs, which dynamically modifies the FMFs to match the requirements requested. The simulation results show improvements in network selection performance.
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