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.
Chirawichitchai N.,Sripatum University
2014 11th Int. Joint Conf. on Computer Science and Software Engineering: "Human Factors in Computer Science and Software Engineering" - e-Science and High Performance Computing: eHPC, JCSSE 2014 | Year: 2014
In this research, I proposed Emotion Classification of Thai Text based Using Term weighting and Machine Learning Techniques focusing on the comparison of various common term weighting schemes. I found Boolean weighting with Support Vector Machine is most effective in our experiments. I also discovered that the Boolean weighting is suitable for combination with the Information gain feature selection method. The Boolean weighting with Support Vector Machine algorithm yielded the best performance with the accuracy over all algorithms. Based on our experiments, the Support Vector Machine algorithm with the Information gain feature selection yielded the best performance with the accuracy of 77.86%. Our experimental results also reveal that feature weighting methods have a positive effect on the Thai Emotion Classification Framework. © 2014 IEEE.
Phollawan S.,Sripatum University
Journal of Applied Security Research | Year: 2017
This article aims at analyzing the legal situation and restriction of laws concerning protection of the wife murdering their husband as a result of having battered wife syndrome so as to develop a guideline on the appropriate legal proceedings against the wife having battered wife syndrome, who murders her own husband, in summary leading to the revision of laws and regulations on performing duties of concerned government agencies for an efficient solution. © 2017 Taylor & Francis Group, LLC.
Vanichchinchai A.,Sripatum University |
Igel B.,Asian Institute of Technology
International Journal of Production Research | Year: 2011
This research investigates the relationships among total quality management practices (TQMP), supply chain management practices (SCMP) and firm's supply performance (FSP) in the automotive industry in Thailand. The measurement instruments for SCMP, TQMP and FSP were developed based on an extensive literature review and verified by experts, pilot test and various statistical techniques to ensure reliability and validity in structural equation modeling constructs. The hypothesized model was tested through a path analysis. Qualitative case studies of two large first-tier automotive suppliers were conducted to obtain more in-depth information. We found that the set of SCMP, TQMP and FSP measures are reliable and valid for Thailand's automotive industry. TQMP not only has a significant direct positive impact on SCMP and on FSP but also a significant indirect positive impact on FSP through SCMP. © 2011 Taylor & Francis.
Juanuwattanakul P.,Sripatum University |
Masoum M.A.S.,Curtin University Australia
IET Generation, Transmission and Distribution | Year: 2012
This study proposes a new iterative algorithm to improve the performance of multiphase distribution networks by proper placement and sizing of distributed generation (DG) units and single-phase capacitors. The approach consists of utilising the positive-sequence voltage ratio Vcollapse/Vno-load to identify the weakest three-phase and single-phase buses for the installation of DG units and shunt capacitors, respectively. DG penetration levels are increased by evaluating their impacts on voltage profile, grid losses and voltage stability margin while considering the voltage limits at all buses. Detailed simulations are performed for the placement and sizing of a doubly fed induction generator (DFIG) and single-phase capacitors in the IEEE multiphase 34 node test feeder using the DIgSILENT PowerFactory software. The impacts of DFIG on voltage profile, active power loss, maximum loading factor and voltage unbalance factor are highlighted. © The Institution of Engineering and Technology 2012.
Rungratri S.,Sripatum University |
Usanavasin S.,Sripatum University
Journal of Convergence Information Technology | Year: 2012
In this research, we propose a semantic based approach and a framework for performing Capability Maturity Model Integration (CMMI) gap analysis process, which is intended to support software houses for their software process improvement. In our approach, we use the Semantic Web technology to support the gap analysis process based on CMMI standard. Two ontologies and a set of Semantic Web Rule Language (SWRL) rules are designed and developed to support the CMMI gap analysis process in the proposed framework. The framework consists of a set of components that is designed for extracting data from a project asset, annotating the extracted data and generating a profile description to represent the asset. All generated profiles are evaluated based on semantic context and rules in order to discover gaps between organization's existing processes and the CMMI recommendations. We evaluated our proposed approach by performing experiments on a set of 90 project assets, which resulted in 81.09% for precision and 79.83% for recall and 80.45% for F-Measure.
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.
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.
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.
Boonpirom N.,Sripatum University
2015 18th International Conference on Electrical Machines and Systems, ICEMS 2015 | Year: 2015
This paper presents the electromagnetic interference (EMI) improvement on active filter using common-mode noise circuits balanced method. The main objective is to reduce the electromagnetic interference (EMI) by reducing the common-mode noise current being generated from the effect of PWM signal of active filter. For this reason, this common-mode noise current flows through the reference ground and generates the conducted noise emission flowing around the circuit. Thus, this paper suggests the common-mode circuit balanced method by modifying the impedance of common-mode circuit impedance. The result shows that the common-mode currents is cancelled themselves. From the experimental results, both the spectrum of conductive noise before and after improving is compared. © 2015 IEEE.
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.