International Journal of Cognitive Performance Support (4 papers in press)
A Novel Discrete Particle Swarm Optimization for Scheduling Projects with Resource-Constrained
by Shih-Chieh Chen, Chiung-Fen Cheng, Ching-Chiuan Lin
Abstract: The objective of resource-constrained project scheduling problem (RCPSP) is to schedule the operating start time of each activity in a project subject to resource constraints and precedence constraints such that the makespan of this project is minimized. Being an NP-Hard problem, evolutionary algorithms are proposed to solve RCPSP. Particle swarm optimization (PSO) is a nature-inspired algorithm to solve optimization problems that is performed by the movements of particles, presented by real-valued vectors, along the trajectories in the solution space of an optimization problem to search the optimal solution. Such a mechanism and representation of particles are difficult to apply PSO to solve discrete combinatorial optimization problems. Therefore, in this paper, we propose a novel discrete particle swarm optimization (DPSO) algorithm to solve RCPSP. A new problem-based similarity measure of permutations, the position representation, the direction and velocity of movement representation of permutations in the solution space are also proposed in DPSO such that the particles can search the optimal solution in a discrete solution space. The computational results show that DPSO is compatible to other state-of-the-art algorithms in solving RCPSP.
Keywords: resourced-constrained project scheduling, particle swarm optimization, similarity measure, evolutionary algorithm
Augmented reality supported mobile self-guided system for enhancing authentic learning activities
by Kai Yi Chin
Abstract: Traditional teaching models can often only provide a one-way transmission of knowledge in real-world situations. These methods are rarely effective, as students require much more interaction with the instructor to gain and retain knowledge from the curriculum. In addition, to understand the information presented in the classroom, extra assistance is usually required since many learners are not equipped with the skills to pursue independent study. It is evident that students are easily distracted, particularly during outdoor teaching cases where external factors cannot be controlled. For these reasons, this study supports the use of an interactive Augmented Reality (AR) system that combines AR and QR code technologies for teaching purposes. The AR system includes two subsystems: the mobile AR system and the AR materials remote server. Users can easily build their own learning environments and include information and materials relevant to their needs. We hope that this study will promote the use of AR systems for educational purposes and provide students with virtual content linked to real-world objects to create an interactive method of learning new information. Our final goal is to encourage the widespread use of AR technology.
Keywords: Augmented Reality, Authentic Learning Activities, AR System
Botnet Detection and Feature Analysis Using Back-propagation Neural network with Bio-inspired Algorithms
by Jen-Li Liao, Kuan-Cheng Lin, Jyh-Yih Hsu
Abstract: Botnets has been the major type of cybercrime recently, the amount of infected computers gradually increasing each year. Many companies and schools are often troubled with problems, such as DDOS, phishing, spam, and stealing of personal data, because botnet is constantly changing its network structure, attack patterns and data transmission, making it more and more difficult to detect. In this paper, we proposed some new features to detect the botnet traffic, and we found the best solutions by using feature selection algorithm. These two methods are Particle Swarm Optimization and Genetic Algorithms, and by using Back-propagation network as the classifier, we evaluate our subset feature on botnet detection that shows high detection rate, and we validate that own manufactured feature packet transmission time of regularity can be adopted, and the accuracy will change with the t-value.
Keywords: Botnet, Genetic Algorithms, Particle Swarm Optimization, Back-propagation network
The Application of Remote Control Home Appliances Based on Bluetooth Phone App
by Yung-Hui Chen, Ching-Lien Huang, Chun-Hsiung Tseng, Lawrence Y. Deng, Deng-Qing Jian
Abstract: Entering the era of science and technology, there are many inventions and researches developed in the modern society. Technologies have been gradually integrated as parts of modern life, especially on the mobile phone and computer. They are closely related to our life and generate far-reaching influence among people communication and convenience. A smart phone contains all functions launched to the era of market and goes far beyond the traditional role of a phone: communication. However, how to achieve convenience and simple manipulation is still an emerging issue. Therefore, we design a multi-function menu in an App program that allows you to select your required electrical remote control function in cell phone. A user delivers an instruction to the Bluetooth receiver through Bluetooth technology. Receiving the command, the Bluetooth receiver will further control home appliances and then controls home appliances. After that, we use TV remote control as the subject and design the required fundamental functions. Finally, we then extend this method to design Bluetooth receiver module or Bluetooth receiver of USB interface and apply to other home appliances. That is so-called smart appliances.
Keywords: Bluetooth Phone; Phone App; Remote Control Home Appliances; Intelligent Appliance; Internet of Things.