Sirindhorn International Institute of Technology

About: Sirindhorn International Institute of Technology is a based out in . It is known for research contribution in the topics: Supply chain & Combustion. The organization has 1048 authors who have published 1678 publications receiving 30067 citations.

Effect of the number of parents on the performance of multi-parent genetic algorithm

Abstract: Multi-parent genetic algorithm (MPGA) has become more interestingly algorithm, instead of using the number of parents more than the original genetic algorithm (GA) in reproduction process; the diversity of gene transformation from the parents literally affects the performance of genetic algorithms (GAs). In this paper, we compare binary coded multi-parent genetic algorithm with traditional genetic algorithm and analyze when one is better than the other as well as the effect of the number of parents by performing experiments on ten multimodal benchmark functions of up to 90 dimensions. The results show that using high number of parents yields better convergence without significantly increase in running time.

Quantification of csf velocity through the narrowest point in aqueduct of sylvia for normal and normal pressure hydrocephalus patient by cfd analysis

Abstract: The aim of this comprehensive study is to quantify the velocity variation of cerebrospinal fluid (CSF) for narrowest point in aqueduct of Sylvia (AqSylv) of normal patients and normal pressure hydrocephalus (NPH) patient by corresponds to its concave shapes of anteriorly and inferiorly. T1-weighted 3-T magnetic resonance images (MRI) of the head in DICOM (Digital Imaging and Communications in Medicine) format were taken from three controlled patients whose were admitted to Thammasat Hospital, Thailand. Patients were 29 to 52 y of age with two normal patients and one (NPH) patient. DICOM files were three-dimensionally reconstructed by using 3D slicer software, and geometric information of an aqueduct for all three cases was noted. Solid models of the aqueduct for both normal patient and NPH condition were developed based on the geometric information. Computational fluid dynamics (CFD) were analyzed to quantify the CSF velocity variation throughout the narrowest point of the aqueduct for both cases, i.e. normal and NPH condition. Retrospective results of “mathematical model for dynamics of CSF through the aqueduct of Sylvia based on an analogy of arterial dilation and contraction” were used as initial data for ANSYS CFX analysis. The results showed the CSF flow through the aqueduct in a pulsatile pattern in both cases. At the narrowest point of the aqueduct, amplitude of peak CSF velocity for NPH patients was significantly higher than that of normal patient. CSF velocity variation throughout the aqueduct co-relates with the pressure gradient inside the aqueduct and increased in the third ventricle direction.

Speed Compensation for Improving Thai Spelling Recognition with a Continuous Speech Corpus

Abstract: Spelling recognition is an approach to enhance a speech recognizer to cope with incorrectly recognized words and out-of-vocabulary words. This paper presents a general framework for Thai speech recognition, enhanced with spelling recognition. To implement Thai spelling recognition, Thai alphabets and their spelling methods are analyzed. Based on hidden Markov models, we propose a method to construct a Thai spelling recognition system using an existing continuous speech corpus. To compensate for speed differences between spelling utterances and continuous speech utterances, the adjustment of utterance speed is taken into account. Our system achieves up to 87.37% correctness and 87.18% accuracy with the mix-type language model.

Enhanced vector flow of significant directions for five-axis machining of STL surfaces

Abstract: Matching a five-axis toolpath and a vector field (VF) of preferred directions (VFPD) is increasingly popular in the five-axis machining industry. However, surfaces represented by industrial formats...

Meta-prediction model for introducing lateral transshipment policies in a retail supply chain network through regression analysis

Abstract: This study finds a way to alleviate and predict the effects of uncertainty in a retail supply chain network through lateral transshipment policies. The study develops a simulation-based optimisation model using the ARENA and OptQuest optimisation tool, and proposes an improved application of the lateral transshipment policy, in addition to four existing policies, to solve such uncertainty. A series of experiments is performed, varying significant cost parameters to study their effects on the profit of the whole chain. In order to determine the best transshipment policy and predict its financial performance, a proposed meta-prediction model based on regression analysis is used to assist in making decisions on the implementation of different types of transshipment policies under various cost scenarios. The proposed methodology assists in decision making on the selection and management of a lateral transshipment policy for a retail supply chain network in a certain situation under an uncertain environment. [Received 20 March 2016; Revised 8 September 2016; Revised 7 December 2017; Accepted 13 December 2017]