International Journal of Computer Networks and Communications Security

Volume 2, Issue 1, November 2014

 

 

 

School of Fish in Creating Swarm Groups

Pages: 30-33 (4) | [Full Text] PDF (REMOVED)
Ali Ghermezian
University of Hertfordshire, Hatfield, UK

Abstract -
The aggregate motion of a school of fish or a flock of birds is really wonderful to watch but this kind of complicated motion becomes a wealthy resource for scientists to investigate. The interaction of agents based on aggregate motion is defined as swarm intelligence. These swarm behaviors have utilized in different areas such as robotic, animations, army and also in NASA investigation in universal. This thesis explore on school of fish based on swarm intelligence to follow their behaviors. In order to search on how these behaviors come up from school and how this algorithm can be used to create our intelligence group we have investigated on schooling behaviors under the attacks of predator in different situations. Furthermore, we have studied some inventions which are based on schooling and swarm behaviors and we present an approach to a group of swarm agents according to one of recent researches which is done by Nissan Company named as EPORO robot. We test our applications to reach problems which affect on swarm intelligence in our life.
 
Index Terms - Artificial Inteligence, School of Fish, swarm intelligence, EPORO.
 

Optimal offloading in Clouds by NSGA II

Pages: 34-41 (8) | [Full Text] PDF (475 KB)
Dadmehr Rahbari
University of Applied Science and Technology, Iran

Abstract -
Mobile systems have limited resources such as battery life, network bandwidth, storage capacity, and CPU performance. These restrictions may be reduced by the extra-time computing: a heavy calculations and get results from server to server. Barry out a way to strengthen the capabilities of the transmission system, mobile computing is rich in computers. The main issue in this paper to obtain an optimal percent no load to achieve optimal energy consumption. In this paper, NSGA II optimization algorithm to optimize the parameters simultaneously, without time and energy is spent. The parameters of the proposed algorithms are designed in a way that would have been converging to the optimal. According to NSGA II algorithm in Matlab software simulation output results of the ranking member on several fronts, the optimal percentage of idle energy consumption at the client side, bandwidth and the average duration of a cycle, the different generations compared with each other and with other papers that show the performance improvement of the proposed method in this project.
 
Index Terms - Cloud Computing, Offload, Genetic Algorithm, NSGA II
 

A Framework to Evaluate the Quality in Use of a System from Socio-technical Questions

Pages: 42-49 (8) | [Full Text] PDF (413 KB)
Elizabeth S. Furtado and Danielly Barboza Guimarães
Universidade de Fortaleza, Washington Soares, 1321- Edson Queiroz, Brazil

Abstract -
The definition of quality objectives for business processes of a proposed system and the specification of responsibilities among the stakeholders (professionals, users and organizations) are basic requirements for the success of such system. A framework is being proposed to guide stakeholders to evaluate the defined quality by applying ISO standards. User Experience ISO standards suggested in this framework were obtained from a socio-technical analysis of scenarios related to Digital TV systems. The Framework can be used in any process of socio-technical evaluation of an interactive system. Specifically, evaluators should apply the technical inspection of products or processes using the ISO standards suggested.
 
Index Terms - Usability Standards, Quality in Use, User Experience, Socio-Technical Evaluation
 

Bayesian Network-Based Causal Analysis of Injury Risk in Elite Rhythmic Gymnastics

Pages: 50-61 (12) | [Full Text] PDF (1.39 MB)
Lyudmila Dimitrova and Kristina Petkova
Department of Computer and Information Technology, University Prof. As. Zlatarov, 8008 Burgas, Bulgaria
Faculty of Industrial technology, Technical University of Sofia, 1756 Sofia, Bulgaria

Abstract -
Bayesian networks (BN) are a key information technology for dealing with probabilities in artificial intelligence. In the present work we introduce an application of BN as a tool for estimating injury risk in high level rhythmic gymnastics. At this stage we propose the base structure of the model consisting of five subnets, contributing to overall injury risk. Most of the model conditional probability tables are estimated with T Normal functions – a feature included in Agena Risk tool. Sensitivity analysis characterizes the degree of influence of the different input factors, which is consistent with expert knowledge. The model results are satisfactory for the test set of gymnasts in the current competitive season. Quantitative predictions show a significant opportunity for reducing injury rate, but further data collection and research are necessary to improve the precision of the model.
 
Index Terms - Bayesian Network, Risk Analysis, Gymnastics Injury