Information Technology

This paper presents three algorithms and one proposed algorithm to find relevant pages for a given Web page (URL). The first algorithm comes from the Pagerank analysis of the Web pages. It is intuitive and easy to implement. The second one takes advantage of HITS to identify relevant pages more precisely and effectively. The third one shows the advantages and limitations of Weighted Pagerank algorithm and the final proposed algorithm based on Topic Sensitive Pagerank algorithm. These algorithms could be used for various Web applications, such as enhancing Web search. The ideas and techniques in this work would be helpful to other Web-related researches.

Recognizing faces is something that people usually do effortlessly and without much conscious thought, yet it has remained a difficult problem in the area of computer vision, where some 20 years of research is just beginning to yield useful technological solutions. As a biometric technology, automated face recognition has a number of desirable properties that are driving research into practical techniques. The problem of face recognition can be stated as ‘identifying an individual from images of the face’ and encompasses a number of variations other than the most familiar Application of mug shot identification. One notable aspect of face recognition is the broad interdisciplinary nature of the interest in it: within computer recognition and pattern recognition; biometrics and security; multimedia processing; psychology and neuroscience. It is a field of research notable for the necessity and the richness of interaction between computer scientists and psychologists. The automatic recognition of human faces spans a variety of different technologies. At a highest level, the technologies are best distinguished by the input medium that is used, whether visible light, infra-red or 3-dimensional data from stereo or other range-finding technologies. Thus far, the field has concentrated on still, visible-light, photographic images, often black and white, though much interest is now beginning to be shown in the recognition of faces in colour video. Each input medium that is used for face recognition brings robustness to certain conditions, e.g. infra-red face imaging is practically invariant to lighting conditions while 3-dimensional data in theory is invariant to head pose. Imaging in the visible light spectrum, however, will remain the preeminent domain for research and application of face recognition because of the vast quantity of legacy data and the ubiquity and cheapness of photographic capture equipment.

Intrusion Detection System (IDS) has been used as a vital instrument in defending the network from this malicious activity. With the ability to analyze network traffic and recognize incoming and on- going network attack, majority of network administrator has turn to IDS to help them in detecting anomalies in network traffic. The gathering of information and analysis on the anomalies activity can be classified into fast and slow attack. Since fast attack activity make a connection in few second and uses a large amount of packet, detecting this early connection provide the administrator one step ahead in deflecting further damages towards the network infrastructure. This paper describes IDS that detects fast attack intrusion using time based detection method. The time based detection method calculates the statistic of the frequency event which occurs between one second time intervals for each connection made to a host thus providing the crucial information in detecting fast attack.

The computer revolution is now well advanced, but although we see a starting preparation of computer machines in many forms of work people do, the domain of computers is still significantly small because of the specialized training needed to use them and the lack of intelligence in computer systems. In the history of computer science five generations have passed by, each adding a new innovative technology that brought computers nearer and nearer to the people. Now it is sixth generation, whose prime objective is to make computers more intelligent i.e., to make computer systems that can think as humans. The fifth generation was aimed at using conventional symbolic Artificial Intelligence techniques to achieve machine intelligence. But it failed. Statistical modeling and Neural Networks falls in really sixth generation. The goal of work in Artificial Intelligence is to build the machines that perform tasks normally requiring human intelligence. Its true, but speech recognition, seeing and walking doesn’t require “intelligence”, but human perceptual ability and motor control.

Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. A cognitive radio is an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. Spectrum shortage was born the idea for cognitive radios. These devices utilize advanced radio and signal processing technology along with novel spectrum allocation policies to support new wireless users operating in the existing crowded spectrum, without degrading the performance of entrenched users. In this paper we present a Cognitive Radio approach for usage of Virtual Unlicensed Spectrum , a vision of a Cognitive Radio (CR) based approach that uses allocated spectrum in a opportunistic manner to create “virtual unlicensed bands” i.e. bands that are shared with the primary (often licensed) users on a non-interfering basis. Dynamic spectrum management techniques are used to adapt immediate local spectrum availability. One of the most important components of the cognitive radio concept is the ability to measure, sense, learn, and be aware of the parameters related to the radio channel characteristics, availability of spectrum and power, radio’s operating environment, user requirements and applications, available networks (infrastructures) and nodes, local policies and other operating restrictions. In cognitive radio terminology, primary users can be defined as the users who have higher priority or legacy rights on the usage of a specific part of the spectrum.

This paper organized as such: In the first section authors mention about all aspects of cloud computing – basic definitions, benefits, important features, workability and application, and so on. In the second section of this paper, authors mention Microsoft decisions about applying of cloud computing onto their newest products, such as Azure OS. In the third section of this paper, authors reveal new innovative algorithm for overcoming malfunctions and spyware actions from cloud platforms and resources. In this section, they purpose a new adaptively reduced-order extended Kalman filter for using as an estimator and predictor in cloud platforms. Authors claim that, if this algorithm were implemented on cloud gateways and resources, cloud service providers were able to track and trace lots of spyware and Trojans and also predict and estimate amount of power consumptions.

Rough Set Theory provides a formal framework for data mining. Feature Selection or Attribute Reduction is a preprocessing step in data mining, and it is very effective in reducing dimensionality, reducing irrelevant data, increasing learning accuracy and improving comprehensibility. The fuzzy-rough feature selection algorithm was used to handle the continuous real-valued data as well as to handle noisy data. It was implemented by standard fuzzification techniques enabling linguistic labels to be associated with attribute values. It also provides uncertainty modeling by allowing the possibility of the membership value to more than one fuzzy label. In this paper, we use an Improved Quickreduct algorithm by redefining the lower and upper approximations based on fuzzy set theory. The membership degrees of feature values to fuzzy sets are exploited in the process of dimensionality reduction. The experiments are carried out on public domain datasets available in UCI machine learning repository and real Tuberculosis data set.

The estimation accuracy has been focused in various formal estimation models in recent research initiatives. The formal estimation models were developed to measure lines of code and function points in the software projects but most of them failed to improve accuracy in estimation. The concept of reusability in software development in estimating effort using artificial neural network is focused in this paper. Incorporation of reusability metrics in COCOMO II may yield better results. In COCOMO II it is very difficult to find the values of size parameters. A new model called COREAN has been proposed in this paper for better effort estimation accuracy and reliability. The proposed model has focused on two components of COCOMO II. First, instead of using RUSE cost driver, three new reuse cost drivers are introduced. Second, In order to reduce the project cost, three cost drivers such as PEXE, AEXE, LTEX are combined into single cost driver Personnel Experience (PLEX). Finally, this proposed model accuracy is more improved with the help of Enhanced RPROP algorithm and simulated annealing optimization technique.

As the modernization of government is growing, E-Government is a grand new domain in recent years. More and more data is sent to databases system and large amounts of data are accumulated. Abundant knowledge exists in those Historical data. Meaning is to analyze those historical data and find useful knowledge and rules from the mass of data to provide better decision support and better adjustment guidance. The concept and steps of data mining is introduced in particular. When we use the E-Government system to process data, we need to choose what data is useful and what kind of new information we can get from the log file or from the database. Because of the special characters of knowledge, this paper presents an algorithm of the fuzzy data mining, and put great importance on the steps of the Fuzzy data mining.

At the of 20th Century and as well as in this present time ,discussion about technology and information technology has special in many scientific and research assemblies . In recent years in our country this issue has received special attention. One of the helpful application of IT is in educational areas. This present article investing acted this issue specially and it has investigated IT in all dimensions .This article expressed the history of information technology usage in training and investigated the application of information technology in training and educational areas as well as analyzed this technology besides students and teachers and examined the relationship between education and information technology and expressed aids of this technology in students training as well as examined children training by parents.