International Journal of Control and Automation 

About: International Journal of Control and Automation is an academic journal. The journal publishes majorly in the area(s): Control theory & Fuzzy logic. It has an ISSN identifier of 2005-4297. Over the lifetime, 1606 publications have been published receiving 4488 citations.

Intelligent Mobile Health Monitoring System (IMHMS)

Abstract: Health monitoring is repeatedly mentioned as one of the main application areas for Pervasive computing. Mobile Health Care is the integration of mobile computing and health monitoring. It is the application of mobile computing technologies for improving communication among patients, physicians, and other health care workers. As mobile devices have become an inseparable part of our life it can integrate health care more seamlessly to our everyday life. It enables the delivery of accurate medical information anytime anywhere by means of mobile devices. Recent technological advances in sensors, low-power integrated circuits, and wireless communications have enabled the design of low-cost, miniature, lightweight and intelligent bio-sensor nodes. These nodes, capable of sensing, processing, and communicating one or more vital signs, can be seamlessly integrated into wireless personal or body area networks for mobile health monitoring. In this paper we present Intelligent Mobile Health Monitoring System (IMHMS), which can provide medical feedback to the patients through mobile devices based on the biomedical and environmental data collected by deployed sensors.

An Improved Biogeography-based Optimization Algorithm for Optimal Reactive Power Flow

Abstract: Optimal reactive power flow (OPRF) reduces power system losses and provides better system voltage control by adjusting the reactive power control variables. It has significant influence on economic and secure operation of power systems. In this article, an improved biogeography-based optimization algorithm based on local search strategy (ILSBBO) is presented for solving optimal reactive power flow. The proposed method integrates local search strategy and selection operation of differential evolution (DE) with migration operator in original BBO to improve the efficiency of migration and overcome the premature convergence in BBO algorithm. It has been applied to standard IEEE 30-bus and IEEE 118-bus test systems, and the comparison results show that the proposed approach is feasible and efficient.

Effects of Flipped Classroom based on Smart Learning on Self-directed and Collaborative Learning

Abstract: This study seeks to explore the effects of smart-based flipped learning activities on learners’ study achievement, self-directed learning, collaborative learning and information use ability. To achieve this study purpose, 112 6th-grade students in the elementary school P in Gympo-si, Gyeonggi-do South Korea were selected as this research experiment group (Flipped classroom based on smart-learning, and normal flipped learning) as well as the control group (traditional ICT-based class learning). They were examined for 11 weeks from the 2nd week of March to 2nd week of May, 2014. In the Flipped classroom based on smart-learning, the participants studied at home in advance with materials made by their teachers. Then, in class, they searched data instantly by using smart pads, used applications for learning or as a tool, and conducted online evaluation, etc. The normal flipped learning-based education group studied at home in advance with videos made by their teachers and, in class, they were instructed to focus on knowledge sharing among themselves and discussions. As a result, an effect on study achievement was found between the flipped learning and traditional ICT-based learning methods. And the smart-based flipped learning was found to have improved self-directed learning ability more than the general flipped learning and traditional ICT-based method. Collaborative learning ability and information use ability were found to be more improved with statistical significance in the smart-based flipped learning group than the other groups.

Classifying Driving Fatigue Based on Combined Entropy Measure Using EEG Signals

Abstract: Driving fatigue is a common occupational hazard for any long distance or professional driver, and fatigue detecting has major implications for transportation safety. Monitoring physiological signal while driving can provide the possibility to detect the fatigue and give the necessary warning. In this paper, fifty subjects participated in driving simulations experiment with their recorded EEG signals to induce two kinds of fatigue states: Alert and drowsy. Two nonlinear methods, approximate Entropy (AE) and Sample Entropy (SE), were used to characterize irregularity and complexity of EEG data. Subsequently Support Vector Machine (SVM) was applied to classify these two fatigue states. The experimental result shows that two complexity parameters are significantly decreased as the fatigue level increases. The result indicates that both of two nonlinear indicators can be used to characterize driver fatigue level. Furthermore, the combined measure feature results in higher classification accuracy, indicating the proposed classification method is more robust and effective, compared with single complexity measure.

Estimation of State of Charge of Batteries for Electric Vehicles

Abstract: State of charge (SOC) can be applied in various fields characterized as an important parameter for estimating residual capacity state of battery. It is obtained from current or collected data, such as voltage, current and temperature as well. The accuracy of estimation of SOC of power battery can be essential and premise in designing the battery management system. Researchers in the fields shall take it an important and challenging task, requiring lots of work and energy, in order to improve the accuracy in estimation of SOC for eletric vehicles (EV). The SOC estimation tasks have made it great headway from classical and typical methods. This paper has proposed the shortcomings over various existed estimation methods and discussed the definition of SOC in details in the application. Study on the principle and application of the SOC estimation algorithm against many existing technical difficulties of SOC estimation algorithm for power batteries is very necessary. This paper analyzes the influence of charge and discharge rate, temperature, self-discharge and aging on SOC. It has important meaning for the further development of power battery SOC estimation.