Volume 6, Issue 6, June 2015

A Semi-Automatic Method for Self-Configuration in Distributed Systems Using Hidden Markov Model

Reza Mohamadi Bahram Abadi and Mohsen Jahanshahi

Dep. of Computer Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Dep. of Computer Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract - The fast, continuous changes in systems require the re-configurations be programmed in such a way that the system can respond to changes efficiently. Self-configuration is the capability of automatic re-configuration of a system in response to such changes. In distributed systems, because of the inconsistent nodes, dynamism of resources and heterogeny of communicative networks, the changes are dramatic. Therefore, the system needs to be monitored consistently and/or periodically to be reconfigured, if required. Upon entry of any user and/or an applied application considering the status quo, the system needs to be re-configured. Also in case of system failure, the configuration has to be done automatically in line with the predetermined objectives. This paper presents a semi-automatic method using the hidden Markov model for self-configuration of the system considering infrastructural resources and requests by users.

Index Terms - Self-Configuration, Hidden Markov Model and Distributed System

Comparative Study of PAPR Reduction Techniques

Pages: 8-12 (5) | [Full Text] PDF (550K)

Divya Singh and Ashish Vats

MRIU, Faridabad, India

Abstract - Orthogonal Frequency Division Multiplexing (OFDM) is a widely used modulation and multiplexing technology which gives the basic supports of many telecommunication standards. Orthogonal Frequency Division Multiplexing (OFDM), which is one of multi-carrier modulation (MCM) techniques, offers a considerable high spectral efficiency, multipath delay spread tolerance, immunity to the frequency selective fading channels and power efficiency. However, still some challenging issues remain unresolved in the design of the OFDM systems. One of the major problems is high Peak-to-Average Power Ratio (PAPR) of transmitted OFDM signals. Here in this paper, we had done the comparative analysis of different PAPR reduction techniques such as Enhanced Iterative Flipping Partial Transmit Sequence (EIFPTS), Partial Transmit Sequence (PTS), Iterative Flipping Partial Transmit Sequence (IFPTS) and Selective Mapping Technique (SLM) that are several transmitting techniques used while working with Orthogonal Frequency Division Multiplexing (OFDM).

Index Terms - Selective Mapping Technique (SLM), Partial Transmit Sequence (PTS), IFPTS, EIFPTS, OFDM and Peak-to-Average Power Ratio (PAPR)

A New Wireless Indoor Localization Algorithm

Pages: 13-17 (5) | [Full Text] PDF (299K)

Ha. Nguyen Thi and Khanh. Ngo Tan Vu

Computer Networking Faculty, Hoa Sen University, Ho Chi Minh City, Vietnam
Computer Science Department, Tien Giang University, Tien Giang, Vietnam

Abstract - In the recent years, the advances in localization based technologies and the increasing importance of ubiquitous computing and context-dependent information have led to a growing business interest in location-based applications and services. There are many applications like security, healthcare, location based services, and social networking use wireless indoor localization to locate or track of physical belongings inside buildings. In the art of wireless indoor localization, a lot of research works have been done, mostly classified into two categories, namely, fingerprinting-based and model-based. To take advantage of their strengths and overcome their limitations, we propose a new algorithm which can not only determine position of a device without training stage but also in-depend on hardware configurations. By using mathematical formulation analysis, we demonstrate its advantages than the other techniques.

Index Terms - Wireless Indoor Localization, Fingerprinting, Radio Propagation and Received Signal Strength

Face Recognition Using Neural Network

Pages: 18-20 (3) | [Full Text] PDF (571K)

Deepshikha Arora and Darshna Kundu

MRIU, Faridabad

Abstract - In this article, we are going to do the face recognition, using the neural network concept. In this whole process of face recognition, canny edge detection operator as well as improved canny edge detection has been used to detect a wide range of edges in image. Gaussian filter is also used to smooth the image in order to remove the noise. At last neural network toolbox software uses the network object to store all the information that defines a neural network.

Index Terms - Neural Network, Improved Canny Edge Detection Technique and Gaussian Filters

A Partial Iris Pattern Recognition Using Neural Network Based FFDTD and HD Approach

Pages: 21-27 (7) | [Full Text] PDF (664K)

P. Vishnu Priya and M. Gopikrishnan

Department of Computer Science and Engineering, Prathyusha Institute of Technology and Management, Chennai, India

Abstract - Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on images of one or both of the irises of an individual's eyes, whose complex random patterns are unique, stable, and can be seen from some distance. An iris recognition system is a highly secure and confidence biometric identification system. In this paper, the partial iris pattern recognition system of template size 10 X 480 is considered by using hamming distance (HD) and neural network based Feed forward distributed time delay (FFDTD). Hough transform is the standard algorithm used for segmenting the iris patterns. Daugman’s rubber sheet model is used for normalization and unwrapping. Gabor filter is used for feature extraction. The experimental results shows that the Gabor filter of template size 10 x 480 provides slightly better results when compared to Gabor filter of template size 20 x480 based on HD and FFDTDNN. There are few public and freely available databases. For the purpose of research and development the system is tested on a CASIA database which contains nearly 4500 iris images.

Index Terms - Iris Recognition System, Daugman’s Rubber Sheet Model, Feed Forward Distributed Time Delay (FFDTDNN), Hamming Distance (HD)

Volume 6, Issue 6, June 2015

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