This paper is written using an intelligent vehicle movement monitoring system which is based on GPS and GPRS. In this system GPS information is transmitted by means of GPRS wireless network to the monitoring centre. The Monitoring Centre displays the above information on Google Map by means of Internet and sends commands to all the subsystems. This Paper would primarily concentrate on the design and development of specific class of wearable computing systems that could prevent loss of human lives due to common road-accidents and devising a mechanism for avoidance of accidents by providing an efficient recovery-support system. This application can be reused in various other monitoring situations. The real time availability of all  exact locations and speeds of the vehicles enables the system to encompass very clear traffic information. This paper introduces GPRS module that receives data sent by GPS module and the software part includes the flow chart  of station reporting and network access. It also introduces the software design of the Monitoring Centre for Driver Safety Rating. This system has features such as high speed data transfer, high precision in real time and reliability.

In this paper, we propose to label a Self-Organizing Map (SOM) to measure image similarity. To manage this goal, we feed Facial images associated to the regions of interest into the neural network. At the end of the learning step, each neural unit is tuned to a particular Facial image prototype. Facial recognition is then performed by a probabilistic decision rule. This scheme offers very promising results for face identification dealing with illumination variation and facial poses and expressions. This paper presents a novel Self-Organizing Map (SOM) for face recognition. The SOM method is trained on images from one database. The novelty of this work comes from the integration of Images from input database, Training and Mapping. Face Recognition using unsupervised mode in neural network by SOM. Among the architectures and algorithms suggested for artificial neural network, the Self-Organizing Map has special property of effectively creating spatially organized “internal representation’ of various features of input signals and their abstractions. After supervised fine tuning of its weight vectors, the Self-Organizing Map has been particularly successful in various pattern recognition tasks involving very noisy signal. One develops realistic cortical structures when given approximations of visual environment as input, and is effective way to model the development of face recognition capability.
Here, we have developed and illustrated a recognition system for human faces using a novel Kohonen self-organizing map (SOM) based retrieval system. SOM has good feature extracting property due to its topological ordering. The Facial Analytics results for the 400 images of AT&T database reflects that the face recognition rate using one of the neural network algorithm SOM is 92.40% for 40 persons.

Data mining refers to extracting knowledge from large amount of data. Real life data mining approaches are interesting because they often present a different set of problems for data miners. The process of designing a model helps to identify the different blood groups with available stock in Indian Red Cross Society (IRCS) Blood Bank Hospital Classification techniques for analysis of Blood bank data sets. The availability of blood groups in blood banks is a critical and important aspect in a Blood bank. Blood banks are typically based on a healthy person voluntarily donating blood and used for transfusions or made into medications. The ability to identify regular blood donors will enable blood bank and voluntary organizations to plan systematically for organizing blood donation camps in an efficient manner. The analysis had been carried out using a standard blood group donor’s dataset and using the J48 decision tree algorithm implemented in Weka. The research work is used to classify the blood donors based on the sex, blood group, weight and age. This may be achieved through collecting the data utilizing the data mining technique and choosing the most suitable implementation tool for the domain

The educational systems currently face number of issues such as high dropout rates, identifying students in need, personalization of training, predicting the quality of student interactions and placement of students. Data mining provides a set of techniques, which can help the educational system to overcome these issues. One of the biggest challenges that higher education faces today is predicting the academic paths of student. To better manage and serve the student population, the institutions need better assessment, analysis, and prediction tools to analyze and predict student related issues. These tools can be very helpful in managing and assisting students in higher education that serve thousands of students for job placement and higher studies. In this paper, we proposes data mining tool that can help to improve an education system by enabling better understanding of the students

This paper discusses cyberinformation studies of the amino acid composition of insulin, amino acid Gln, in particular the identification of scientific terminology that could describe this phenomenon, ie, the study of genetic information, as well as the relationship between the genetic language of proteins and theoretical aspects of this system and ybernetics. The results of this research show that there is a matrix code for insulin. It also shows that the coding system within the amino acid language gives detailed information, not only on the amino acid “record”, but also on its structure, configuration, and various shapes. The issue of the existence of an insulin code and coding of the individual structural elements of this protein are discussed. Answers to the following questions are sought. Does the matrix mechanism for biosynthesis of this protein function within the law of the general theory of information systems, and what is the significance of this for understanding the genetic language of insulin?  What is the essence of existence and functioning of this language? Is the genetic information characterized only by biochemical principles or it is also characterized by cyberinformation principles? The potential effects of physical and chemical, as well as cybernetic and information principles, on the biochemical basis of insulin are also investigated. This paper discusses new methods for developing genetic technologies, in particular more advanced digital technology based on programming, cybernetics, and informational laws and systems, and how this new technology could be useful in medicine, bioinformatics, genetics, biochemistry, and other natural sciences.

Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction data in real-world applications, however, usually consist of quantitative values. This paper, thus, proposes a fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions. A genetic algorithm (GA)-based framework for finding membership functions suitable for mining problems is proposed. The fitness of each set of membership functions is evaluated by the fuzzy-supports of the linguistic terms in the large 1-itemsets and by the suitability of the derived membership functions. Experiments are conducted to analyze different fitness functions and setting different supports and confidences. Experiments are also conducted to compare the proposed algorithm, the one with uniform fuzzy partition, and the existing one without divide-and-conquer, with results validating the performance of the proposed algorithm.

This Paper presents a coherent survey on to detect the misbehaving node in Mobile Ad hoc Network (MANET) with the intent of serving as a quick reference to the current research issues in MANET. A mobile ad-hoc network is an infrastructure  less network,  that is self-configuring mobile nodes connected by wireless links. The open medium and the decentralized property of these nodes relay on each other to store and forward packets. Most of the proposed MANET protocols do not address security issues. Furthermore, MANETs are highly vulnerable for passive and active attacks because of their open medium, rapidly changing topology, lack of centralized monitoring. The encryption and authentication solution, which are considered as the first line of defence, are no longer sufficient to protect MANETs. Therefore, Intrusion Detection System (IDSs) is needed to be the second line of defence to protect the network from Security problems. In recent years, the security issues on MANET have become one of the primary concerns and several existing security problem on MANET can be probed quickly for future researches.

Open networks are often insecure and provide an opportunity for viruses and DDOS activities to spread. To make such networks more resilient against these kind of threats, we propose the use of a peer-to-peer architecture whereby each peer is responsible for: (a) detecting whether a virus or worm is uncontrollably propagating through the network resulting in an epidemic; (b) automatically dispatching warnings and information to other peers of a security-focused group; and (c) taking specific precautions for protecting their host by automatically hardening their security measures during the epidemic. This can lead to auto-adaptive secure operating systems that automatically change the trust level of the services they provide. We demonstrate our approach through a prototype application based on the JXTA peer-to-peer infrastructure.

In today’s “E-World” computing is taking up an essential part of business. Computing is coming up as the fifth utility after water, gas, electricity and telephony. This has led to the development of various computing paradigms like grid computing and Cluster computing. This article deals with cloud computing as the upcoming and most efficient source of computing. It aims at explaining the importance of cloud computing as an appropriate method for computation in the near future. It also tries to explain how I-Cluster clouds can work as a framework of tools that takes advantage of unused network resources and federates them into a huge virtual cluster. The virtual cluster is created by crystallizing the unused network resources into specific virtual functions using resource management strategies. I-Cluster Cloud enables automatic real time analysis of work load and allocates the set of machines into a virtual cluster and proceeds with the execution of the function. So basically this paper gives an idea of cloud computing

In this paper Very large scale integration architecture for inversion is presented. This architecture is scalable with respect to the throughput rate. The scalability is achieved by applying time sharing technique. Time sharing systems are designed to allow several operations to execute simultaneously. This approach leads to a small silicon area in comparison with several inversion implementations published in the past.

Three decades ago Gordon Moore predicted that number of transistors per integrated circuit (IC) would double every two years. Today the high performance ICs are counting upto two billion of transistors and working at 10 GHz clock frequencies. The on chip interconnects are going to be a major bottleneck to the performance of such ICs. The use of copper interconnects & low K dielectrics has provided one time improvement of resistivity and electromigration, but with this the global interconnect performance required for future generations of ICs cannot be achieved. In this paper, optical interconnects which is the most promising approach to interconnect problem has been discussed. Also the performance of opical interconnects and copper interconnects for intrachip global signaling is compared. 

Key establishment in sensor networks is a challenging problem because existing security schemes are unsuitable for use in resource constrained sensor nodes, and also because the nodes could be physically compromised by an adversary. In this paper two key establishment scheme are presented using the framework of pre-distributing a random set of keys to each node. One is the random-pairwise key scheme, which perfectly preserves the secrecy of the rest of the network when any node is captured, and also enables node-to-node authentication(EG SCHEME) and  other is EG SCHEME with deployment knowledge) and going to compare the basic scheme(EG SCHEME) with the deployment model(EG SCHEME with deployment knowledge).