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.

Novel Compliant Control of Pneumatic Artificial Muscle Driven by Hydrogen Pressure under Varying Environment

Abstract: A pneumatic artificial muscle (PAM) based on a metal hydride (MH) is considered for a compact compliant actuator. It is suitable for board applications of human robot interaction (HRI). To address the problem of HRI representing by varying environment, a compliant control is introduced. In fact, the bottlenecks of improving the performance in the compliant control of the PAM actuator are: a) an inherent non-linear dynamics of a PAM, b) the parametric and non-linear uncertainties, influenced by varying environment, and c) an additional high dimension introduced by an MH employed as a driving force for the PAM. We propose a learning-based adaptive robust control (LARC) framework to tackle these challenges. A Bayesian learning technique deals with the parameter adaptation for the adaptive control. The effectiveness of the LARC has been examined in extensive experiments of tracking control.

Real-time sensor- and camera-based logging of sleep postures

Abstract: This paper presents a process of feature selection, and classification algorithm evaluation for a continuous sleep monitoring system, using a tri-axial accelerometer attached to the subject's chest. Two feature selection algorithms, i.e., Relief-F and support vector machine recursive feature elimination (SVM-RFE), and seven classification algorithms, i.e., Bayesian network, naive Bayesian network, support vector machine, pruned decision tree, instance-based learning with one neighbor, instance-based learning with three neighbors, and multi-layer perceptron, were investigated. By using four features according to the rank obtained from Relief-F, and a multi-layer perceptron classifier, an average accuracy of 85.68 percent has been achieved. Based on the selected model, a real-time logging system of sleeping images triggered by a sleep posture change detected using a wireless sensor node has been developed.

A safety assessment approach using safety enablers and results

Abstract: Industrial safety is an important issue in Thailand, and attempts have been made to improve safety performance and accident records. This paper examines key criteria influencing safety improvement. Exploratory factor analysis confirms 9 safety criteria, including 5 "enablers" and 4 "results", with a total of 47 associated attributes. A safety assessment approach is developed, using those 9 key criteria, to measure an organization's current safety maturity level. Organizations can use the assessment approach to plan its safety improvement, and progress through to higher maturity levels by focusing on the weakest criteria shown in the assessment results with the lowest scores.