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Bangkok, Thailand

Sripatum University or SPU is one of the oldest and most prestigious private universities in Bangkok, Thailand. Dr. Sook Pookayaporn established the university in 1970 under the name of "Thai Suriya College" in order to create opportunities for Thai youths to develop their potential. In 1987, the college was promoted to university status by the Ministry of University Affairs, and has since been known as Sripatum University."Sripatum" means the "Source of Knowledge Blooming Like a Lotus" and was graciously conferred on the college by Her Royal Highness, the late Princess Mother Srinagarindra . She presided over the official opening ceremony of SPU and awarded vocational certificates to the first three graduating classes. Sripatum University is therefore one of the first five private universities of Thailand. The university’s main goal is to create well-rounded students who can develop themselves to their chosen fields of study and to instill students with correct attitudes towards education so that they are enthusiastic in their pursuit of knowledge and self-development. This will provide students with a firm foundation for the future after graduation. The university's philosophy is "Education develops human resources who enrich the nation" which focuses on characteristics of Wisdom, Skills, Cheerfulness and Morality.In March 2002, Sripatum University has reached another key milestone for being accredited by the International Standards Organization for both undergraduate and graduate programs. Wikipedia.

Masdisornchote M.,Sripatum University
IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society | Year: 2015

Sentiment analysis has been adopted in several areas to gain insight into user feedbacks. Most existing approaches focus on explicit opinions whereas none contributes in implicit opinions expressed in Thai language. This paper presents a sentiment analysis framework in implicit opinions for Thai language. Evaluation results in representative domain of mobile device products show that the framework is relatively effective. © 2015 IEEE. Source

Panyakapo P.,Sripatum University
Engineering Structures | Year: 2014

Conventional Pushover Analysis relies on the use of monotonic lateral load distribution. The seismic displacement demands based on this procedure are considered an approximate solution that has not taken into account the cyclic loading effects. Under earthquake loading, structural components experience stiffness degradation and strength deterioration, which are the important characteristics of reinforced concrete members under cyclic loading, causing a reduction of deformation capacity. The Cyclic Pushover Procedure is proposed to estimate seismic demands of buildings that take into account the cumulative damage under cyclic loading. The cyclic lateral force distribution is developed based on the mode shapes and the prescribed displacement history. The cyclic pushover curve is converted to the equivalent SDOF pseudo-acceleration and displacement relationship based on the first mode response of the structure. The seismic demands of a 9-story reinforced concrete building are evaluated by Cyclic Pushover Procedure. Four types of loading protocol, i.e., Laboratory, ATC-24, International Organization for Standardization (ISO), and Sequential Phased Displacement (SPD) protocols are employed to investigate the effects of displacement histories on seismic demands. The seismic demands include the peak roof displacement, the peak floor displacement and the peak inter-story drift ratio. The results are compared with the exact demands resulting from nonlinear time history analyses of MDOF structure subjected to 20 ground motions, as well as the demands estimated from the Modal Pushover Analysis. The results demonstrate that the Cyclic Pushover Analysis provides a reasonable and accurate estimate of seismic displacement demands. © 2014 Elsevier Ltd. Source

Chirawichitchai N.,Sripatum University
Lecture Notes in Electrical Engineering | Year: 2015

Term weighting is an important task for sentiment classification. Inverse document frequency (IDF) is one of the most popular methods for this task; however, in some situations, such as supervised learning for sentiment classification, it doesn’t weight terms properly, because it neglects the category information and assumes that a term that occurs in smaller set of documents should get a higher weight. In this paper, I purpose sentiment classification framework focusing on the comparison of various term weighting schemes, including Boolean, TF, TFIDF and a novel term weighting (TOW). I have evaluated these methods on Internet Movie Database corpus with four supervised learning classifiers. I found TOW weighting most effective in our experiments with SVM NB and NN algorithms. Based on our experiments, using TOW weighting with SVM algorithm yielded the best performance with the accuracy equaling 93.45%. © Springer-Verlag Berlin Heidelberg 2015. Source

Chayakulkheeree K.,Sripatum University
Electric Power Components and Systems | Year: 2013

This article proposes a probabilistic optimal power flow for hour-ahead scheduling in a power system considering the statistical distribution function of system loading using the Weibull probability distribution function. In the proposed probabilistic optimal power flow, the deterministic optimal power flow problem is solved as the sub-problem in probabilistic optimal power flow and decomposed into a total operating cost minimization sub-objective, which is solved by successive quadratic programming and the real power loss minimization sub-objective, which is solved by successive linear programming. In the proposed method, the Weibull probability distribution function parameters of the optimal power flow variables are estimated from percentile values and evaluated by Akaike information criteria. The proposed probabilistic optimal power flow algorithm is tested on the IEEE 30-bus and IEEE 300-bus systems and compared to Monte Carlo simulation. The investigations show that the proposed probabilistic optimal power flow can successfully estimate the probability distribution function parameters of optimal power flow output variables considering the Weibull probability distribution function of system load with simple and minimal computational procedure. With the proposed estimation of the Weibull parameters method, the number of optimal power flow runs can be reduced substantially in the probabilistic optimal power flow process. © 2013 Copyright Taylor and Francis Group, LLC. Source

Darawong C.,Sripatum University
Journal of High Technology Management Research | Year: 2015

Absorptive capacity (ACAP) is an essential component for new product development (NPD) teams to effectively manage knowledge received from external sources. This paper extends the existing theory of ACAP by examining the impact of cross-functional communication on the ACAP of NPD teams at high technology firms in Thailand. The results indicate that all characteristics of cross-functional communication, including frequency, quality, and informality have direct impacts on ACAP. However, only quality and informality have a significantly direct effect on all activities of ACAP, which includes knowledge acquisition, assimilation, transformation, and application. © 2015 Elsevier Inc. All rights reserved. Source

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