Bangkok, Thailand
Bangkok, Thailand

Siam University is a university located on Petkasem Road in Phasicharoen district of Bangkok. Siam University was founded by the late Narong Mongkhonvanit as a three-year private engineering school in 1965.In 1973, Siam University, then known as Siam Technical College, was formally established as a higher education institution with authorization to grant degrees. Later in 1986, Siam Technical College became Siam Technical University, a full-fledged private, non-profit university. Three years later, the name was changed again to Siam University to reflect the diversity in the fields of study offered.In 1995, the international college was established. Currently, over 400 international students from more than 15 countries are enrolled in the international college of Siam University.The governing body of Siam University is the university council led by Kasem Wattanachai, councilor of the Privy Council of Thailand. Wikipedia.

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Banchuin R.,Siam University
Cogent Engineering | Year: 2017

In this research, many novel expressions for time domain responses of fractance device to various often cited inputs have been proposed. Unlike the previous ones, our expressions have been derived based on the Caputo fractional derivative by also concerning the dimensional consistency with the integer order device based responses and the different between two types of fractance device i.e. fractional order inductor and fractional order capacitor. These previous expressions have been derived based on the Riemann-Liouvielle fractional derivative which has certain features that leads to contradictions and additional modeling difficulties unlike the Caputo fractional derivative. Our new expressions are applicable to both fractional order inductor and capacitor with arbitrary order. They are also applicable to any subject which its electrical characteristic can be modeled based on the fractance device. With our expressions and numerical simulations, the time domain behavioral analysis of both fractance device and such subject can be directly performed without requiring any time to frequency domain conversion and its inverse as already presented in this work. Therefore our work has been found to be beneficial to various fractance device related disciplines e.g. biomedical engineering, control system, electronic circuit and electrical engineering etc. © 2017 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Kuendee P.,Siam University
2017 4th International Conference on Industrial Engineering and Applications, ICIEA 2017 | Year: 2017

The purpose of the study was to apply some of the seven quality control tools (7 QC tools) for reducing delay the delivery problem. The Cause and Effect Diagram was found out the root causes of this problem and the Pareto Chart was used to help ordering the important of delay the delivery problem, it was found that coordination problem was the major cause. Finally, the Matrix Diagram was used to solve the problem for assigning responsibilities by improving the cause of three reasons: 1. work system equipment and 3.employees. The results showed that the percentage of operations with reduced error from between 5-10% to 2-3%. The paper is dedicated to present concepts to show how the quality tools can be used to solve problems and improve quality. © 2017 IEEE.

Romsaiyud W.,Siam University
International Conference on ICT and Knowledge Engineering | Year: 2015

Model-View-Controller (MVC) pattern is very useful and popular design pattern that separates the modeling of the domain, the presentation, and the actions based on user input into three separate classes. The model acts as the domain that software is built around, the view as the visual representation of a model. It is usually the resulting markup that the framework renders to the browser and the controller responsible for processing input, acting upon the model, and deciding on what action should be performed, such as rendering a view or redirecting to another page for supporting a business models. Hadoop MapReduce paradigm applied for collected the several datasets for generating the large volume of data in batch processing. In this paper enhanced the Hadoop MapReduce for processing large scale and different data set across platform with MVC pattern. In general, the system consists of five mainly methods: 1.) Collected data sources from different platforms such as the registrar system, web mail, web blogs, news and the English Wikipedia that are included in the data file system at local system, 2.) Generate the data into a map slot from input format, 3.) calculate the jobs from the business logic, 4.) Create a data model based on data entity framework, and 5.) Display an user interface for supporting the business interfaces. © 2014 IEEE.

Mahattanatawee K.,Siam University | Rouseff R.L.,University of Florida
Food Chemistry | Year: 2014

Aroma volatiles from three cooked fragrant rice types (Jasmine, Basmati and Jasmati) were characterised and identified using SPME GC-O, GC-PFPD and confirmed using GC-MS. A total of 26, 23, and 22 aroma active volatiles were observed in Jasmine, Basmati and Jasmati cooked rice samples. 2-Acetyl-1-pyrroline was aroma active in all three rice types, but the sulphur-based, cooked rice character impact volatile, 2-acetyl-2-thiazoline was aroma active only in Jasmine rice. Five additional sulphur volatiles were found to have aroma activity: dimethyl sulphide, 3-methyl-2-butene-1-thiol, 2-methyl-3-furanthiol, dimethyl trisulphide, and methional. Other newly-reported aroma active rice volatiles were geranyl acetate, β-damascone, β-damascenone, and É-ionone, contributing nutty, sweet floral attributes to the aroma of cooked aromatic rice. The first two principal components from the principal component analysis of sulphur volatiles explained 60% of the variance. PC1 separated Basmati from the other two cultivars and PC2 completely separated Jasmine from Jasmati cultivars. © 2014 Elsevier Ltd. All rights reserved.

Banchuin R.,Siam University
Journal of Electrical and Computer Engineering | Year: 2013

The novel probabilistic models of the random variations in nanoscale MOSFET's high frequency performance defined in terms of gate capacitance and transition frequency have been proposed. As the transition frequency variation has also been considered, the proposed models are considered as complete unlike the previous one which take only the gate capacitance variation into account. The proposed models have been found to be both analytic and physical level oriented as they are the precise mathematical expressions in terms of physical parameters. Since the up-to-date model of variation in MOSFET's characteristic induced by physical level fluctuation has been used, part of the proposed models for gate capacitance is more accurate and physical level oriented than its predecessor. The proposed models have been verified based on the 65 nm CMOS technology by using the Monte-Carlo SPICE simulations of benchmark circuits and Kolmogorov-Smirnov tests as highly accurate since they fit the Monte-Carlo-based analysis results with 99% confidence. Hence, these novel models have been found to be versatile for the statistical/variability aware analysis/design of nanoscale MOSFET-based analog/mixed signal circuits and systems. © 2013 Rawid Banchuin.

Romsaiyud W.,Siam University
2014 International Computer Science and Engineering Conference, ICSEC 2014 | Year: 2014

Extracting words, data patterns and topic models from streaming big data by way of real-time processing is a challenging job. Currently, many of applied machine learning techniques in data mining aim to utilize online feedbacks by making model updates faster and quicker. However, Mahout and Massive Online Analysis (MOA) existing solutions are not supported for streaming machine learning, and consequently, not suitable for scalable multiple machines. In this paper enhanced the machine learning algorithms for extracting the words and generating topic models based on the continuing data which was initially proposed. One of the great advantages of the proposed algorithm was the capability to be scaled into multiple machines, in which made it very suitable for real-time processing of streaming data. In general, the algorithm includes two main methods: (a) the first method introduces a principle approach to pre-process documents in an associated time sequence. It implements a class to detect identical files from input files so as to reduce computation time. (b) The second method suits real time monitoring and control of the process from multiple asynchronous text streams. In the experiment, these two methods were alternatively executed, and subsequently after iterations a monotonic convergence was guaranteed. The study conducts the experiments based on a real-world dataset collected from TREC KBA Stream Corpus in 2012. Finally, the accuracy of the proposed method resulted in greater robustness towards the ability to deal with noise and reduce the computation. © 2014 IEEE.

Ploysuwan T.,Siam University
IEEE Region 10 Annual International Conference, Proceedings/TENCON | Year: 2015

In this paper, the author presents the joint of spectral mixture Gaussian and a single squared exponential kernel function which used in predictive solution of Gaussian process (QfP) to find new pattern discovery and forecasting of electricity peak load demand of Thailand in next five years. Several analytical results have been evaluated in simulations such as pattern discovery performance, property of each kernel function, and mean absolute percentage error (MAPE) of the method. © 2014 IEEE.

Chaiyapinunt S.,Chulalongkorn University | Khamporn N.,Siam University
Solar Energy | Year: 2013

This paper presents a study of thermal performance for a glass window with a curved venetian blind installed on the indoor side in terms of heat gain in the shortwave part of radiation. The curved venetian blind, whose optical properties are considered nonspecular, is modeled as an effective layer. The mathematical model of the combined glass window and venetian blind is developed by combining the mathematical model of glass window and the mathematical model of a curved venetian blind using the matrix layer calculation method. The experiment is performed in a test room to measure the heat gain due to solar radiation passing through the glass window with a curved venetian blind installed in the shortwave part of radiation. The predicted results from the developed model are compared with the experimental results. The agreement between the predicted results and the experimental results is good. From the study it is found that installing a curved venetian blind to the glass window causes a significant reduction in heat gain compared to the plain glass window. The heat gain through the glass window with blind in the shortwave part of radiation (solar heat gain coefficient in the shortwave part of radiation (ShW SHGC)) is analyzed. It is found that the ShW SHGC is mainly affected by the slat properties, slat angle and solar profile angle. The glass window using blind with a lower value of slat reflectance, will have a smaller value of ShW SHGC. The slat distance also affects the ShW SHGC. The glass window using blind with a lower value of slat distance has a lower value of ShW SHGC. The effect of the slat curvature on the ShW SHGC is small when compared to the effect of other parameters. The effects of the investigated parameters on the ShW SHGC for diffuse radiation are similar to the effects on the ShW SHGC for direct radiation. When installing blind to different kinds of glass window other than clear glass window, it is found that the thermal performance is similar to the case of clear glass window. The magnitude of the ShW SHGC for the glass window with blind is also dependent on the optical properties of the glass window used. The glass window with blind using a lower value of the glass transmittance has a lower value of the ShW SHGC. The absorptance of the glass window has direct effect on the solar heat gain coefficient in the longwave part of radiation (LoW SHGC). © 2013 Elsevier Ltd.

Premchaiswadi W.,Siam University | Romsaiyud W.,Siam University
International Journal of Intelligent Systems | Year: 2013

Data-intensive applications process large volumes of data using a parallel processing method. MapReduce is a programming model designed for data-intensive applications for massive data sets and an execution framework for large-scale data processing on clusters of commodity servers. While fault tolerance, easy programming structure, and high scalability are considered strong points of MapReduce; however its configuration parameters must be fine-tuned to the specific deployment, which makes it more complex in configuration and performance. This paper explains tuning of the Hadoop configuration parameters, which directly affect MapReduce's job workflow performance under various conditions to achieve maximum performance. On the basis of the empirical data we collected, it became apparent that three main methodologies can affect the execution time of MapReduce running on cluster systems. Therefore, in this paper, we present a model that consists of three main modules: (1) Extending a data redistribution technique in order to find the high-performance nodes, (2) Utilizing the number of map/reduce slots in order to make it more efficient in terms of execution time, and (3) Developing a new hybrid routing schedule shuffle phase in order to define the scheduler task while memory management level is reduced. © 2012 Wiley Periodicals, Inc.

The comprehensive analytical probabilistic model of the random variation in subthreshold MOSFET's high frequency performance defined in term of variation in its gate capacitance, has been proposed. Both random dopant fluctuation and process variation effects have been taken into account. The proposed model has been found to be both analytic and comprehensive as it is the analytical expression in terms of various MOSFET's physical parameters. As a result, the behavior of such random variation in gate capacitance can be analytically explained and the physical level parameters which affect this variation can be precisely seen. The model has been verified at the nanometer level by using the 65 nm CMOS technology based Monte-Carlo simulations with the BSIM4. It can be seen that the model has very high accuracy. Hence, this model been found to be the potential analytical tool for the statistical/variabilityaware analysis/design of the subthreshold MOSFET based Monte-Carlo simulations with the BSIM4. It can be seen that the model has very high accuracy. Hence, this model been found to be the potential analytical tool for the statistical/variabilityaware analysis/design of the subthreshold MOSFET based lowpower/high frequency applications. © 2013 American Scientific Publishers All rights reserved.

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