The idea of establishing a private university to support private sector development in Thailand and the region was initiated in 1996 by Dr. Thaksin Shinawatra and his colleagues. This was followed by the design and development of an environmentally friendly campus by Dr. Soontorn Boonyatikarn in 1997. A year later, the innovative plans were presented to Her Royal Highness Princess Mahachakri Sirindhorn, and then to the Ministry of Universities which granted the license for operation towards the end of 1999. The first Shinawatra University Council Meeting was held on May 19th, 2000, marking the initial milestone of the long road to becoming an accomplished private university. In September 2002, the first batch of students was admitted, and the venture of creating and nurturing a prospective university had begun. Wikipedia.
Walsh J.,Shinawatra University
International Journal of Agricultural Resources, Governance and Ecology | Year: 2015
Although agricultural households operate on the basis of the gendered division of labour, it is not clear whether a similar division of labour occurs with respect to decision-making when it comes to agricultural activities. This paper reports on three empirical studies conducted in Cambodia and Thailand with a total sample size of 520 respondents. The sample consists entirely of women, many of whom were heads of households. The surveys discovered information about gender and decision-making in terms of new inputs into production (e.g. insecticides and fertilisers) and in livestock management. It was observed that different decision-making processes were followed when a woman was head of the household rather than a man and factors contributing to this result are explained. Implications and recommendations are discussed, along with the necessary limitations to the research in terms of time and space. Copyright © 2015 Inderscience Enterprises Ltd.
Maleewong K.,Shinawatra University
Advances in Intelligent Systems and Computing | Year: 2016
Although several community-based question answering or CQA systems have been successful at encouraging vast numbers of users to ask and answer questions, and leading to unanticipated explosion of community knowledge, the user-generated contents are confronted with poor quality and untrustworthy problems, while the CQA community deals with conflicts occurred during the question answering process. To tackle such problems, this paper presents a novel approach to predict the best answer as quality-assured consensual answer by simultaneously concerning the content quality and group preference. A set of important features of the answer and its interrelated components as well as social interaction are identified and used to model the predicting function by applying binary logistic regression method. In contrast to the voting-based CQA systems, the proposed model evaluates group preference based on the content quality and community agreement. By training the proposed model using the defined features, the results show that the proposed approach is efficient and outperforms the voting method. © Springer International Publishing Switzerland 2016.
Yuenyong S.,Shinawatra University
7th International Conference on Information Communication Technology for Embedded Systems 2016, IC-ICTES 2016 | Year: 2016
Echo State Network (ESN) is a type of neural network with convex training used as nonlinear adaptive filters. It requires relative large network size and O(N2) training algorithm in order to realize its full potential. We present a subspace training scheme for ESN that reduces the training cost from O(N2) to O(NL) where L < N is the dimension of the subspace. Experiments show that L = 20 is sufficient for networks of size N = 100 and that the performance of subspace training algorithm is actually better than current standard training algorithm while having only 20% computational cost and preserving convex training. © 2016 IEEE.
Mingotti N.,University of Cambridge |
Chenvidyakarn T.,Shinawatra University |
Woods A.W.,University of Cambridge
Energy and Buildings | Year: 2013
We explore the impacts of climate and wall insulation on the energy demand of a room connected to single or double glazing exposed to solar radiation. We show that in cold climates with weak solar radiation double glazing reduces the requirement for mechanical heating of buildings with poor wall insulation and/or small occupancy, particularly when its inner layer is tinted. In these climates the energy benefit of multi-layered glazing connected to well-insulated buildings with large internal heat gain is smaller. However, in warmer climates with stronger solar flux, double glazing reduces the requirement for mechanical cooling of buildings with good wall insulation and relatively small ventilation, particularly when its outer layer is tinted or highly reflective. For buildings with poor wall insulation located in warm climates with strong solar radiation, the energy saving provided by the extra layer of glazing in the facade is small. © 2012 Elsevier B.V. All rights reserved.
Yuenyong S.,Shinawatra University
ICSEC 2015 - 19th International Computer Science and Engineering Conference: Hybrid Cloud Computing: A New Approach for Big Data Era | Year: 2015
Echo State Network (ESN) is a special type of neural network with a randomly generated structure called the reservoir. The performance of ESN is sensitive to the reservoir parameters, which have to be tuned for best performance. Tuning of the reservoir parameters using evolutionary algorithms can be slow and produce inconsistent results. In this paper, we present a simple method for generating reservoirs based on templates that makes the reservoir matrices deterministic with respect to the parameters. Compared with the traditional method where the reservoir matrices are random, tuning of the reservoir parameters with an evolutionary algorithm needs less time, less number of cost function evaluations, and produces more reliable results using the proposed method. © 2015 IEEE.