Welcome to Journal of Theoretical and Applied Information Technology

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 In this paper a simple noise (Salt and Pepper) detection technique is proposed by using 3 x 3 sub-windows in which the test pixel appears. A weight is assigned to the test pixel based on its position after sorting in each sub-window. Two thresholds are used to decide whether the test pixel is corrupted or not. If corrupted then only the standard median of the 3 x 3 vicinity is used to eliminate noise, other –wise no filtering is applied. The proposed scheme is simulated using standard images under different noisy conditions. The performance study shows the superiority of the proposed scheme over the existing standard median filters using 3 x 3 and 5 x 5 windows.

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VoIP technology in general refers to the set of software, hardware and industry standards that enable “voice” to be transported using the Internet Protocol (IP). The technology is compelling to a wide audience for several reasons:
• VoIP phone bills are typically cheaper than traditional phone bills to the consumer.
• VoIP networks offers providers easier IT management and reduction in operating cost for a combined network for voice and data.
• VoIP technology is feature rich to support next generation multimedia applications
With private phone conversations being conducted on insecure public networks, security of VoIP communications is increasingly important. VoIP has a very different architecture than traditional circuit based telephony, and these differences result in significant security issues. Encryption is one of the essential security technologies for computer data, and it will go a long way toward securing VOIP[1,2,3]. In our discussion we proposed a Biometric-Crypto system which generates a cryptographic key from the fingerprints for Encrypting and Decrypting the voice data packets for VoIP Security. if your VoIP packets traverse the Internet to reach a destination, a number of attackers have a shot at your voice data. The calls are also vulnerable to hijacking or a man in the middle attack . In such a scenario, an attacker would intercept a connection and modify call parameters. This is an especially scary attack, since the participants likely wouldn't notice a change. The ramifications include spoofing or identity theft and call redirection, making data integrity a major risk. One way to help protect your privacy is to encrypt these conversations so that they aren't simply floating around out there for potential hackers to latch onto. In our approach we have proposed a system which will encrypt the VoIP data packets using Advanced Encryption Standard (AES)[7] with the novel method of Biometrics based Key Generation technique.

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 Microarray technology has provided the means to monitor the expression levels of a large number of genes simultaneously. Constructing a classifier based on microarray data has emerged as an important problem for diseases such as cancer. Difficulty arises from the fact that the number of samples are usually less than the number of genes which may interact with one another. Selection of a small number of significant genes is fundamental to correctly analyze the samples. Gene selection is usually based on univariate or multivariate methods. Univariate methods for gene selection cannot address interactions among multiple genes, a situation which demands the multivariate methods [1], [2]. In this paper, we considered new parameters which come up from singular value decomposition and present a combination algorithm for gene selection to integrate the univariate and multivariate approaches and compare it with gene selection based on correlation coefficient with binary output classes to analyze the effect of new parameters. Repeatability of selected genes is evaluated by external 10-fold cross validation whereas SVM and PLR classifiers are used to classify two well known datasets for cancers. We calculated the misclassification error in training samples and independent samples of two datasets (breast cancer and Leukemia). The results show that the mean of misclassification error of training samples in 100 iteration are almost equal in two algorithms but our algorithm have the better ability to classify independent samples.

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 Traffics from real-time and interactive applications are bursty and are known to associate with self-similar property. It has a direct impact on network performance. Link characteristics may also contribute to the network performance, particularly when routing decisions are to be made at a router node. Therefore, if the source traffic and the link quality can be precisely characterized for resource allocation and reservation at the time of routing, a better level of QoS guarantees could then be granted to user applications. However, the problem lies in the formulation of a mathematical model that can incorporate least possible parameters but well describing the application requirements, such that an efficient and reliable QoS routing is achieved. Thus, this work aims to develop a parsimonious traffic-descriptor, which will be used intermediately for resource reservation and ultimately for QoS routing decisions at a router node. The performance of the traffic-descriptor is recorded through a Matlab simulation. It was found that the traffic-descriptor could describe the source traffic and the link quality with fairly good precision.

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 ZigBee is an IEEE 802.15.4 standard for data communications with business and consumer devices. It is designed around low-power consumption allowing batteries to essentially last forever. The ZigBee standard provides network, security, and application support services operating on top of the IEEE 802.15.4 Medium Access Control (MAC) and Physical Layer (PHY) wireless standard. It employs a suite of technologies to enable scalable, self-organizing, self-healing networks that can manage various data traffic patterns. ZigBee is a low-cost, low-power, wireless mesh networking standard. The low cost allows the technology to be widely deployed in wireless control and monitoring applications, the low power-usage allows longer life with smaller batteries, and the mesh networking provides high reliability and larger range.ZigBee has been developed to meet the growing demand for capable wireless networking between numerous low-power devices. In industry ZigBee is being used for next generation automated manufacturing, with small transmitters in every device on the floor, allowing for communication between devices to a central computer. This new level of communication permits finely-tuned remote monitoring and manipulation.

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 SS7 or Signaling System Number 7 is a set of protocols that describes a means of communication between telephone switches in public telephone networks.SS7 is a highly sophisticated and powerful form of Common Channel Signaling (CCS). The use of out-of-band signaling procedures offers considerable benefits over and above other signaling methodologies. The primary function of SS7 is to provide call control, remote network management, and maintenance capabilities for the inter- office telephone network. SS7 performs these functions by exchanging control messages between SS7 telephone exchanges (signaling points or SPs) and SS7 signaling transfer points (STPs). The switching offices (SPs) handle the SS7 control network as well as the user circuit switched network. Basically, the SS7 control network tells the switching office which paths to establish over the circuit-switched network. The STPs route SS7 control packets across the signaling network. A switching office may or may not be an STP.

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 Background: The objective of this study is to examine the relationship between the protein variates and to infer the variation across the 3 species namely man (Homo sapiens), house mouse (Mus Musculus) and Norway rat (Rattus Norvegicus).
Results For this purpose, a dataset of size 639 proteins has been taken representing 213 type 2 diabetes related proteins each belonging to Man, Mouse and Rat. Principal Component Analysis technique is used to reduce the dimensionality of the variables. The results show that the protein variates variation in man differs from those of two species.
Conclusion Principal Component analysis of type 2 diabetes related genes showed that those of house mouse and Norway rat were closer to each other than that of human being.

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With the increase in the number of studies on supply chain management practices and their application, many studies have proposed methodologies that can be used by manufacturers to evaluate vendors. These methodologies allow a buyer to choose several specific indicators or multiple criteria to evaluate vendors and distinguish them from one another based on their performance. Manufacturers can then make decisions on further cooperation with vendors who have high performance scores. Nevertheless, few studies have proposed methodologies that can be used to evaluate a supply cluster network, which consists of interlaced supply chains, as a whole. In this paper, we first apply a max-min approach and attempt to determine alternative supply chain permutations in a supply cluster network, in an effort to ascertain the preferred choice from among the supply chains in the network. We use the proposed methodology to maximize the buyer’s profits under several conditions set by the buyer, and list the performance sequence of each supply chain in the supply cluster network as a whole. The results of this process can be used as criteria for future reference. Finally, we put forward suggested solutions and analytical information, and make further suggestions in relation to each individual supply chain.

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 We review work on image-based 3D modelling. 3D modelling entails the availability of complete 3D coordinates, and yet obtaining the coordinates is one of the most difficult tasks. Resorting to using 2D images appears a promising means to achieve this task and has been much reported. Prevalent methods are the shape from shading, photometry, stereopsis, photogrammetry and the video approach. Shape from shading takes minimal input (one image) but requires huge mathematical complexity. Photometry takes in at least twice as much input but produces more accurate results. Stereopsis takes in input of similar order but offers even better accuracy with less mathematical complexity. Photogrammetry uses even more input and produces good results in some types of applications. Video approach does away with assumptions in the previous methods and produces good results. However, stereopsis, photogrammetry and video approaches suffer from the correspondence problem.

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 After appearance of semantic web, the framework which is machine-readable and machine-understandable, by Berners Lee, current web should be annotated by W3C standards in order to define semantic domain of each word by its ontology to alleviate the posed problems in the realm of search and information retrieval. However annotation is one major problem in the semantic web domain, which is presently performed by a human agent. But, considering low human precision for this time-consuming and expensive task and the advent of data mining in recent years, in this article, a system is proposed for automatic semantic web annotation that is based on machine learning techniques for mining association rules between words in already annotated texts.  In the present article, ASWAACC annotation system will be introduced. In this system, annotation rules are produced by analysis of words co-occurrence in a paragraph to eliminate sense ambiguity of words. This system has two phases: 1-learning by mining association rules in text data which has been already annotated by human. 2-utilizing mined rules to automatically annotate the new unseen text data in order to define domain ontology of each word.

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 Face recognition(FR) has become a specialized application area within the field of computer, among which the appearance-based approaches are popular. The appearance-based FR can be induced into the subspace projection step and a nearest neighbor classifier. Because face image data have the property of high dimension, the subspace projection methods should be employed for dimensionality reduction. They include Principal component analysis (PCA), Linear discriminant analysis (LDA), Independent component analysis (ICA) and Non-negative matrix factorization (NMF). In this paper, all the subspace projection algorithms are explored and face recognition system based on the four techniques presented. The simulation experiments are implemented with ORL face dataset, the results presented and analyzed. Also the four techniques are compared in recognition performance for FR.

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 Extracting high level features is an important field in video indexing and retrieving. Identifying the presence of human in video is one of these high level features, which facilitate the understanding of other aspects concerning people or the interactions between people. Our work proposes a method for identifying the presence of human in videos. The proposed algorithm detects the human face based on the colour and motion information extracted from frames over wide range of variations in lightning conditions, skin colour races, backgrounds and faces' sizes and orientations. Experimental results demonstrate the successfulness of the algorithm used and its capability in detecting faces under different challenges. The proposed work is crucial in lots of applications whose concern is mainly human activities and can be a basic step in such activities.

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This paper presents a development of an Emulation Network Analyzer for heterogeneous services in campus environment. We propose a framework and implementation named ENA that models the network behavior of heterogeneous environment. The purpose of this paper is to inform potential tool of analyzing the network in campus environment by providing an overview of the capabilities of ENA tool. For this purpose, we demonstrate our Emulation Network Analyzer (ENA) development is differ from others system such as application and hardware network analyzer (e.g. Fluke Optiview). This study focuses on the characteristics and functionality of two different systems (ENA and hardware network analyzer) and the study conclude that each system has their strength and functionality. With unique knowledge of this emulation available and a solid background in modeling and simulation, it is possible to utilize some of the campus problems dramatically shorten the time span involved in providing useful network architectural solutions, cost reduction and optimization of network resources during preparation, proposal and planning phases. Finally, ENA tool is a good emulation analyzer that can be used in small to medium size networks for campus environment purposes with minimum cost.

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A difficult pattern recognition problem is to recognize objects despite distortions in position, orientation and scale in cluttered backgrounds. A system capable of detecting target objects despite any kind of geometrical distortion has many potential applications since it will be able to detect target objects when the orientation and position of the target or camera is unknown. In this work we report the use of fully invariant correlation filters for object detection in still images despite any kind of geometrical distortion of the target object. A mapping technique is combined with a bandpass difference of gaussian composite correlation filter, capable of creating invariance to various types of distortion of the target object.

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 In this paper a new robust load frequency controller for a two area interconnected power system is presented to quench the deviations in frequency and tie line power due to different load disturbances. The dynamic model of the interconnected power system is developed without the integral control. The area control error is also not included. The frequency and derivatives are zero under normal operation and after the disturbance effects are died. Then the problem is restructured as the problem of state transfer from the initial steady state to final steady state without oscillations in less time. The fuzzy controller designed here consists of two crisp inputs namely deviation of frequency and the other is
derivative of frequency deviation. The output of the fuzzy controller is the control input to each area. The studies power system is subjected to a wide range of load disturbances to validate the effectiveness of the proposed fuzzy controller. The simulated results are obtained for different configurations of the fuzzy controller like placing in area 1 only and placing area 1 and area 2 for different options of load variations. The digital results prove the present fuzzy controller over the other control studies presented in earlier work in terms of fast response (dead beat response for certain configuration of fuzzy controller) with very less undershoots and negligible overshoot with having small state transfer time to reach the
final steady state with zero frequency.