Notice Board :

Call for Paper
Vol. 10 Issue 8

Submission Start Date:
Aug 01, 2018

Acceptence Notification Start:
Aug 10, 2018

Submission End:
Aug 15, 2018

Final MenuScript Due:
Aug 25, 2018

Publication Date:
Aug 30, 2018
                         Notice Board: Call for PaperVol. 10 Issue 8      Submission Start Date: Aug 01, 2018      Acceptence Notification Start: Aug 10, 2018      Submission End: Aug 15, 2018      Final MenuScript Due: Aug 25, 2018      Publication Date: Aug 30, 2018




Volume II Issue IV

Author Name
M Aflatooni
Year Of Publication
2010
Volume and Issue
Volume 2 Issue 4
Abstract
Application, resource and Network supervi sion and trust management is a significant issue due to today’s speedily development of computer and communication environment specially in Local Area Network (LAN).Client-server bas ed network management approach suffer from problems such as insufficient scalability, interoperability, reliabili ty , and flexibility, as networks become more geographically distributed [1]. Another big issue is trust management. RSA, DES and Kerberos is another good methods to achieve authentication but require but high computation is a big deal for LAN, another issue is availability. In this paper, we have proposed a new (novel) light weight approach for resource and trust management using the concept of Multi agent system. Proposed method used the concept of certificate authority (AS of Kerberos) for authenticating the users in LAN or peer to peer network. Availability and minimum delay are the key factor of any authentication scheme, in this paper we proposed a fresh new concept for authenticity and supervision of resources. Our Mobile agent based solution will work same as Kerberos with better throughput and with high availability due to distributed and roaming features of MAS system. Proposed method provides good solution for trust management as well as supervision for network resource and application. We have used SPADE for development of MAS.
PaperID
2010/EUSRM/02/04/1002

Author Name
S Chantara
Year Of Publication
2010
Volume and Issue
Volume 2 Issue 4
Abstract
This paper describes a Approach for Prediction of driver-fatigue monitor. It uses remotely located charge-coupled-device came-ras equipped with active infrared illuminators to acquire video images of the driver. Various visual cues that typically characterize the level of alertness of a person are extracted in real time and systematically combined to infer the fatigue level of the driver. The visual cues employed characterize eyelid movement, gaze movement, head movement, and facial expression. The eyes are one of the most salient features of the human face, playing a critical role in understanding a person’s desires, needs and emotional states. Robust eye detection and tracking is therefore essential not only for human-computer interaction, but also for Attentive user interfaces (like driver assistance systems), since the eyes contain a lot of information about the driver’s condition: gaze, attention level, fatigue. Furthermore, due to their unique physical properties (shape, size, reflectivity), the eyes represent very useful cues in more complex tasks, such as face detection and face recognition. A probabilistic model is developed to model human fatigue and to predict fatigue based on the visual cues obtained. The simultaneous use of multiple visual cues and their systematic combination yields a much more robust and accurate fatigue characterization than using a single visual cue. This system was validated under real-life fatigue conditions with human subjects of different ethnic backgrounds, genders, and ages; with/without glasses; and under different illumination conditions. It was found to be reasonably robust, reliable, and accurate in fatigue characterization.
PaperID
2010/EUSRM/02/04/1017

Author Name
D A K Chalabi1, H S Arif
Year Of Publication
2010
Volume and Issue
Volume 2 Issue 4
Abstract
A new dynamic clustering approach (DCPSO ), based on particle swarm optimization, is proposed. The proposed approach automatically determines the ‘‘op timum’’ number of clusters and simultaneously clusters the data set with minimal user interference. The algorithm starts by partitioning the data set into a relatively large number of clusters to reduce the effects of initial conditions. O ptimization in dynamic optimization problems (DO Ps) requires the optimization algorithms not only to locate, but also to continuously track the moving optima. Particle swarm optimization (PSO ) is a population-based optimization algorithm, originally developed for static problems. Recently, several researchers have proposed variants of PSO for optimization in DO Ps. This paper presents a multi-swarm PSO algorithm, namely competitive clustering PSO (CCPSO), designed especially for DO Ps. Employing a multistage clustering procedure, CCPSO splits the particles of the main swarm over a number of sub-swarms based on the particles positions and on their objective function values.
PaperID
2010/EUSRM/02/04/1023

Author Name
M A Hajabbasi
Year Of Publication
2010
Volume and Issue
Volume 2 Issue 4
Abstract
In recent years one cheap and reliable communication medium Email is gro wing and use o f it reached beyond the limit, but it has created one huge problem that is of spam(junk) Email. Solution of this spam is construction of automatic filtering system which eliminates unwanted mails. Bayesian approach is common and efficient for doing this task. Bayesian approach is nothing but casting the problem of removal of Junk Email into decision theoretic framework. At first glance it seem s to be simple text classification problem, but right now many researches are going on the same because cost of misclassification of the legitimate to Junk is very high. Here we have considered A Bayesian Approach for filtering Junk Email.
PaperID
2010/EUSRM/02/04/1030