Qi Wang
Northwest University

Published : 3 Documents
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THE RESEARCH ON INTELLIGENT SEATING POSITION TYPE LED TABLE LAMP Liu, Ling; Wang, Qi
Indonesian Journal of Electrical Engineering and Computer Science Vol 3, No 2: August 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v3.i2.pp331-335

Abstract

Taking STC89C52RC single-chip as control core, this research realizes intelligent control function, which can automatically detect whether there is someone in the room and turn on/off LED table lamp; brightness of LED lamp can be adjusted with manual mode. In addition to that, it also has other functions such as displaying time and date, and posture correction. In general, time, data and brightness can be regulated through key module. 8 high brightness white LED are used in illumination module, among which, light sensitive module is applied for testing luminous intensity of environment; ultrasonic distance measuring module is utilized for detecting the distance from men to table lamp through transmitting and receiving ultrasound. In the evening, light is on when the distance from men to table lamp is within certain range; and light is off when exceeding this range. However, if the distance is lower than the specified minimum distance, buzzer will alarm to warn user that the seating position needs to be corrected. C language programming is employed for the integrated software to achieve the overall control function.
A Community Detection Algorithm Based on NSGA-II Zhang, Lishuo; Wang, Qi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3A: 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.54 KB) | DOI: 10.12928/telkomnika.v14i3A.4411

Abstract

The community detection problem is modeled as multi-objective optimization problem, and a classic NSGA-II (nondominated sorting genetic algorithm) is adopted to optimize this problem, which overcomes the resolution problem in the process of modularity density optimization and the parameter adjustment in the process of general modularity density optimization. In this case, a set of Pareto solutions with different partitioning results can be obtained in one time, which can be chosen by the decision maker. Besides that, the crossover and mutation operators take the neighborhood information of the vertices of networks into consideration, which matches up with the property of real world complex networks. The graph based on coding scheme confirms the self-adjustment of the community numbers, rather than sets up in advance. All the experiment results indicate that NSGA-II based algorithm can detect the construction of community effectively.
A Community Detection Algorithm Based on NSGA-II Zhang, Lishuo; Wang, Qi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3A: 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.54 KB) | DOI: 10.12928/telkomnika.v14i3A.4411

Abstract

The community detection problem is modeled as multi-objective optimization problem, and a classic NSGA-II (nondominated sorting genetic algorithm) is adopted to optimize this problem, which overcomes the resolution problem in the process of modularity density optimization and the parameter adjustment in the process of general modularity density optimization. In this case, a set of Pareto solutions with different partitioning results can be obtained in one time, which can be chosen by the decision maker. Besides that, the crossover and mutation operators take the neighborhood information of the vertices of networks into consideration, which matches up with the property of real world complex networks. The graph based on coding scheme confirms the self-adjustment of the community numbers, rather than sets up in advance. All the experiment results indicate that NSGA-II based algorithm can detect the construction of community effectively.