Journal of Theoretical and Applied Information Technology

Cloud era brought revolution of computerization world. People could access their data from anywhere and anytime with different devices. One of the cloud's model is Software as a Service, which capable to provide applications that run on a cloud infrastructure.An IDE (Integrated Development Environment) is the most popular tool to develop application in the network or single computer development. By installing IDE in each computer of the network could causes the lot of time and budget spending. The objective of the research is developing an efficient cloud based IDE. The IDE could compile the code which sent from client browser through SaaS IDE to the server and send it back to the client. The method that used in the research is the System Development Life-Cycle: Waterfall and Unified Model Language as system designing tool. The research successfully produced the cloud-based SaaS IDE with excellent result from several testing in local network and internet.

For the realization of the vision and mission of Healthy Indonesia 2015, we need a health service with a broad and comprehensive scope.To provide health services, it can be realized by creating an integrated information system applications such as creating an electronic medical record that has the ability to process and store patient medical data. The specifications used medical record is an open specification contained in OpenEHR that includes information and service model for electronic medical records, demographics, and the archetype which allows software developers taking the logical structure as a universal functional interface, so it can facilitate the process of information by the recipient. It is because of using the interface with appropriate-purposed data presentation and data on computer screen of the same users. The purpose of this paper is to create an electronic website for the medical record by using OpenEHR specifications for easy accessing, processing and storing the medical records by the actors that play a role in the data processing of medical records. With this application it is expected to be useful for data processing and health information gathering, thus to improve the quality of services that will impact the improved performance of the hospital management. The improved performance of the hospital management will become a supporter of the vision and mission Healthy Indonesia 2015.

This paper investigates the effect of convergence of the documents in the same cluster which degrades the performance of the SA and Proposed knapsack. For this purpose, we have introduced a dynamic cluster selection mechanism of ACCS which enhances the performance.

Computing technology with its increased access has much interest in the mobile ad hoc networktechnology. However, the transactions strongly depend on the availability of security provisions, among otherfactors. In the open network environment practically any node can maliciously or selfishly disrupt and denycommunication of other nodes. This paper, propose a dynamic multicast group management protocols that aims atsolving problems that are specific to ad hoc networks such as mobility, unreliable links, and cost of multihopcommunication. The main idea is to have group members actively participate to the security of the multicast group,therefore reducing the communication and computation load on the source

Robust and reliable group communication plays a major role in developing distributed mobile application in which unannounced disconnections will occur frequently due to the mobility of the nodes which take part in mobile applications. The main objective is to achieve robust and reliable group communication in mobile ad hoc network based on a guarantee protocol that always considers the transmitting range, location, speed and direction of mobile nodes to ensure successful delivery of the message between the group members by calculating accurate delivery time. The consistent view of application state within the group of mobile nodes participating in application execution is necessary to achieve reliable message delivery. To solve any inconsistency during the group split or merge operation, when mobile hosts go out of the transmitting range, message delivery is assured and decided by guarantee protocol whether to deliver the message or not to avoid any inconsistent state. The guarantee protocol has been analyzed extensively to ensure the efficient communication among the participating hosts despite the high mobility environment and the mobility induced link failure cause inconsistent data and unrecoverability.

The Bresenham line algorithm is a promising computer graphics process whose basic justificationseems to have been its lack of reliance on floating-point operations and high dependence on Integers andoperations based on integers. In more recent time it has sometimes been passed by for other algorithms thatcan support scan conversion of regions with non-linear boundaries. However, the Bresenham algorithm can beconsidered as original algorithm for lines and to draw circles. Also this can be considered for simplearithmetic operations; quadratic or trigonometric expressions can be avoided or recursively dissolved intosimpler steps In this paper, we reviewed several of such operations [5] and showed how Brsenham Algorithmplays an important role.

A systematic controller design and implementation for a matrix-converter-based induction motor drive system is proposed. A nonlinear adaptive backstepping controller is proposed to improve the speed and position responses of the induction motor system. By using the proposed adaptive backstepping controller, the system can track a time-varying speed command and a time-varying position command well. Moreover, the system has a good load disturbance rejection capability. The realization of the controller is very simple. All of the control loops, including the current loop, speed loop and position loop, are implemented by a digital signal processor. Several experimental results are given to validate the theoretical analysis.

In this paper we discuss our research in mounting a distributed architecture for intruder detection. The key inspiration is touse data mining techniques to ascertain patterns of system features that can describe the program and user behavior and touse machine learning algorithm to analyze audit data and to extract features that can distinguish anomalies from legitimateactivities. Auditing agents are used in this research to assemble concise and accurate classifiers to detect anomalies. Toincreases computability we used a Web Service based distributed architecture which will provide high accuracy and lowcomputational cost. WinMine toolkit is used to build the statistical model and to facilitate model construction andincremental updates.

A channel allocation algorithm includes a channel acquisition and a channel selection scheme. Most of the previous work concentrates on the channel selection algorithm since early channel acquisition algorithms are centralized and rely on a MSS to accomplish channel acquisition. The centralized schemes are neither scalable nor reliable. Recently, distributed dynamic channel allocation algorithms have received considerable attention due to their high reliability and scalability. The most of the distributed algorithm is based on non-resource planning model in which a borrower needs to consult with every interference neighbors in order to borrow a channel. The proposed distributed dynamic channel allocation algorithm is based on resource-planning model, a borrower need not to receive replies from every interfering neighbors, it can borrow a channel from that neighbor whose all group members replies with common free channels within the predefined time period. The proposed algorithm makes efficient reuse of channels and evaluates the performance in terms of message complexity, blocking rate.

The continuous growth in the demand for electric power necessitates the flexibility of operation in power system. Of different power electronics-based Flexible AC Transmission System (FACTS) devices, which enhance the power transmission capabilities, Unified Power Flow Controller (UPFC) provides an emerging and promising solution for the power flow problems in the system, as it simultaneously and/or selectively controls the transmission parameters. In this context, the paper proposes the power flow control in a simple system by injecting the series compensating voltage, which is an important function of UPFC. For this purpose, ANN controller based UPFC is used. Control patterns are generated for obtaining the adjustable series voltage from the second converter that, in turn, controls the power flow in the system. With the proposed model, by varying control coefficient the series injected voltage can be adjusted. MATLAB Simulation is used to test the proposed model. The control horizon is identified and presented for various values of existing active and reactive powers.

The stock market is one of the most popular investing places because of its expected high profit. Traditionally, technical analysis approach, that predicts stock prices based on historical prices and volume, basic concepts of trends, price patterns and oscillators, is commonly used by stock investors to aid investment decisions. Advanced intelligent techniques, ranging from pure mathematical models and expert systems to fuzzy logic networks, have also been used by many financial trading systems for investing and predicting stock prices. In recent years, most of the researchers have been concentrating their research work on the future prediction of share market prices by using Neural Networks. But, in this paper we newly propose a methodology inwhich the neural network is applied to the investor’s financial decision making to invest all type of shares irrespective of the high / low index value of the scripts, in a continuous time frame work and further it is further extended to obtain the expected return on investment through the Neural Networks and finally it is compared with the actual value. The proposed network has been tested with stock data obtained from the Indian Share Market BSE Index. Finally, the design, implementation and performance of the proposed neural network are described.

Indirect field orientation (IFO) induction machine drives are increasingly employed in industrial drive systems, but the drive performance is often degrades. Motor works on best performance at certain voltage and frequency for certain loads. In this paper artificial neural network is used to predict the operating voltage and frequency when the load torque and speed going changed so motor efficiency is increased. Simulation and experimental results are shown to validate the scheme.

The problem of distributed diagnosis in arbitrary network failures and repairs is considered in this paper. The basic idea behind incorporating a fault tolerance capability to a distributed system is to provide the system with extra (redundant) resources. A number of investigations have been attempted to extend traditional notions of “fault-tolerant computing”, to deal with the problem of failures, which affect the facilities of distributed systems and computer networks. as distinguish of diagnostic responsibility requires the flow of diagnostic information through the network, and the faulty facilities themselves may participate in this flow and may alter, destroy, or generate erroneous diagnostic information in the process, the whole diagnostic procedure itself becomes quite complex. The purpose of this study is to simulate a distributed system and carry out fault diagnosis under Arbitrary Network topologies. The distributed system level diagnosis algorithms discussed in this paper give a comprehensive idea about various issues one must keep track of while going to develop such fault tolerance algorithms. Since “system level diagnosis” is one of the steps in the process of building “distributed fault-tolerant systems”, reliability of such a system depends heavily on proper functioning of the diagnosis algorithm. The distributed system has been simulated in JAVA using the Console. Java program to create multiple windows, each one representing a different system node. Afterwards, distributed diagnosis algorithms have been simulated using this environment.

The communication sector is flourishing in many ways, leading to a growing number of users and system attached to the Internet which drives the need for efficient multicast communication architecture over the Internet. Multicasting has been at the center of Internet in the area of Internet activities and has already contributed to some major successes. As multicast communication runs closer towards widespread deployment, security issues have become a central concern and are increasingly important. The features that make multicast particularly significant also make security in multicast difficult. This paper looks at the impressive changes that have been needed in multicast key management architecture and also attempts to avoid the unauthorized duplication of data. It uses tree based subgroups approach which helps to minimize re-keying overhead and also to protect unconstitutional distribution of multicast data without intended users concern.

Typical real time computer vision tasks require huge amount of processing power and time for handling real time computer vision applications. The nature of processing in a typical computer vision algorithm usually ranges from many small arithmetic operations (Fine Grain Parallelism) to symbolic operations (Coarse grain parallelism). The task become more complicate while considering image processing application due to large data sets and there processing. The existing processing system responds efficiently under sequential working and result in efficient output, but results in a slow operating system which results in a inefficient processing system under high speed image processing systems. Parallel processing founds to be the only solution to obtain the require processing speed for handling high-speed image processing applications. The existing image processing systems support usually only one suit of operations at once and fail to respond under multiple tasks. System taking single instruction or multiple instruction process operates using low level and high-level operations. Generally SIMD architecture is suitable under low level processing while MIMD architecture is suitable for high-level processing. This paper explores on modeling and simulation of parallel Image Processing architecture for Image Processing applications using Parallel Virtual Machine(PVM) , MATLAB external interface API and C language on the Linux operating system platform.

The gain of SVC depends upon the type of reactive power load for optimum performance. As the load and input wind power conditions are variable, the gain setting of SVC needs to be adjusted or tuned. In this paper, an ANN based approach has been used to tune the gain parameters of the SVC controller over a wide range of load characteristics. The multi-layer feed-forward ANN tool with the error back-propagation training method is employed. Loads have been taken as the function of voltage. Analytical techniques have mostly been based on impedance load reduced network models, which suffer from several disadvantages, including inadequate load representation and lack of structural integrity. The ability of ANNs to spontaneously learn from examples, reason over inexact and fuzzy data and provide adequate and quick responses to new information not previously stored in memory has generated high performance dynamical system with unprecedented robustness. ANNs models have been developed for different hybrid power system configurations for tuning the proportional-integral controller for SVC. Transient responses of different autonomous configurations show that SVC controller with its gained tuned by the ANNs provide optimum system performance for a variety of loads.

The advent of e-commerce has brought about a radical change in the process of auctions that can be achieved by using agents. One of the important capabilities of agent is learning from the environment. In this paper, the authors are proposing case based learning for agents in online e-auctions. Case-based reasoning (CBR) is a problem solving paradigm based on the principle that similar problems have similar solutions has inherent learning capability. In auctions, CBR has been proposed to store past histories of similar auctions with their solutions which helps agent to learn from past experience. Proposed bidding agent that uses CBR (CBR-agent) participates in the auction and performs better than those bidders who have no past knowledge about similar auctions. Empirical evaluation is done and the performance of CBR-agent is calculated by comparing its success percentage and average winning price with that of other agents participating in auctions.

An electronic voting scheme is a set of protocols that allow a collection of voters to cost their votes, while enabling a collection of authorities to collect votes, compute the final tally, and communicate the final tally that is checked by talliers. This scheme is based on the RSA and factoring assumptions. We apply the protocols of [CDS – 88] to Guillon – Quisqnater’s identification protocol [GQ –88] to constant proofs of validity for ballots.

This study is dedicated to proposing a two-stage method, which first uses Self-Organizing Feature Maps (SOM) neural network to determine the number of clusters and cluster centroids, then uses honey bee mating optimization algorithm based on K-means algorithm to find the final solution. The results of simulated data via a Monte Carlo study show that the proposed method outperforms two other methods, SOM followed by K-means (Kuo, Ho & Hu, 2002a) and SOM followed by GAK (Kuo, An, Wang & Chung, 2006), based on both within-cluster variations (SSW) and the number of misclassification. In order to further demonstrate the proposed approach’s capability, a real-world problem of an internet bookstore market segmentation based on customer loyalty is employed. The RFM model is used for comparison of customers' loyalty. Then the proposed method is used to cluster the customers. The results also indicate that the proposed method is better than the other two methods.

Within the context of health education through information and communication technologies (ICT), software on different aspects and subspecialties of health has been developed by senior students and lecturers at the Department of Computer Education and Instructional Technologies at Anadolu University. The study briefly abstracts the evolution of health education, articulates its relationship with ICT, provides pedagogical implications, and introduces readers to a computer program, which helps learners develop an understanding of cells, organelles and bacteria along with their structures and functions.

In recent years, wireless communication is increasingly used in voice and messaging due to the mobility it offers. There is a growing demand for high data rate wireless communication because of the possibility of using this for internet and multimedia applications in the near future. To achieve high data rate communication, the system has to overcome problems such as multipath fading and cochannel interference. The channel statistic is significantly often Rayleigh which makes it difficult for the receiver to reliably determine the transmitted signal unless some less attenuated replica of the signal is provided to the receiver. This technique is called diversity, which can be provided using temporal, frequency, polarization and spatial resources. However, in many situations, the wireless channel is neither significantly time variant nor highly frequency selective. This forces the communication engineers to consider the possibility of deploying multiple antennas at both the transmitter and receiver to achieve spatial diversity and also provide high performance. The space-Time Block code is a technique that can provide diversity and coding gain. In this paper we propose coding gain analysis of the orthogonal polynomials based on Space-Time Block Code.

CADWORK has been employed for the design of a keyboard layout and compared with QWERTY keyboard layout evaluated by CADWORK heuristics. The time simulated by CADWORK to type a document supplied as data using the QWERTY layout was 647.79 TMU while that obtained when using the layout designed by CADWORK was 604.69 TMU. From the standpoint of ergonomic considerations, a keyboard layout which permits the operator to type more efficiently is to be preferred in order to reduce the medical problem of cumulative trauma disorders. A test set up to determine the acceptability of the CADWORK layout using participants drawn from experienced keyboard layout users indicated a bias towards the QWERTY layout. After a third trial, some participants were found to type faster with the CADWORK layout than others using the QWERTY layout.

This paper proposes a new control algorithm for a matrix converter (MC) induction motor drive system. First, a new switching strategy, which applies a back-propagation neural network to adjust a pseudo dc bus voltage, is proposed to reduce the current harmonics of the induction motor. Next, a two-degree-of-freedom controller is proposed to improve the system performance. The controller design algorithm can be applied in an adjustable speed control system and a position control system to obtain good transient responses and good load disturbance rejection abilities. The implementation of this kind of controller is only possible by using a high-speed digital signal processor. In this paper, all the control loops, including current-loop, speed-loop, and position-loop, are implemented by TMS320C6711 digital signal processor. Several experimental results are shown to validate the theoretical analysis.

Software development time depends on various attributes of the software product. In this paper, attempt has been made to define an empirical relation between software development time with respect to its dependence on lines of code, variables and methods. We have attempted to analyze the various dependencies of development time of a program upon its member functions, instance variables and the number of non-blank, non-comment lines of code. Statistical techniques have been used to assign weights to the independent variables to arrive at the results.

The basic phases in text categorization include preprocessing features, extracting relevant features against the features in a database, and finally categorizing a set of documents into predefined categories. Most of the researches in text categorization are focusing more on the development of algorithms and computer techniques. An algorithm for pre-processing features is seem to be like a "black-box" and ignored by them. Thus, it is significant and worthwhile to develop an algorithm for preprocessing features and finally can be used by other beginners before going in depth in the field of text categorization. This research proposes an algorithm for preprocessing features with capability of Microsoft .NET framework technology. The actual implementation shows that, this algorithm can extract interested features from the standard corpus of collection and upload into a relational database.

In this paper an adaptable algorithm for simulating CNN arrays is implemented using various RK-fourth order means such as Arithmetic Mean [AM], Centroidal Mean [CM], Harmonic Mean [HM], Contra Harmonic Mean [CoM], Heronian Mean [HeM], Geometric Mean [GM] and Root Mean Square [RMS] also, it is compared with RK-fourth order embedded means such as the RK-Embedded Heronian Mean, RK-Embedded Centroidal Mean, Harmonic Mean and Contra-Harmonic Mean. The role of the simulator is that it is capable of performing Raster Simulation for any kind as well as any size of input image. It is a powerful tool for researchers to investigate the potential applications of CNN. This article proposes an efficient pseudo code exploiting the latency properties of Cellular Neural Networks along with well known RK-Fourth Order numerical integration algorithms. Simulation results and comparison have also been presented to show the efficiency of the various means in Numerical integration Algorithms. It is observed that the RK-fourth order embedded means outperforms well in comparison with RK-fourth order means. In particular it is found that the RK-Embedded Heronian Mean outperforms well in comparison with the RK-Embedded Centroidal Mean, Harmonic Mean and Contra-Harmonic Mean.

This paper introduces different construction techniques of parity-check matrix H for irregular Low-Density Parity-Check (LDPC) codes. The first one is the proposed Accurate Random Construction Technique (ARCT) which is an improvement of the Random Construction Technique (RCT) to satisfy an accurate profile. The second technique, Speed Up Technique (SUT), improves the performance of irregular LDPC codes by growing H from proposed initial construction but not from empty matrix as usual. The third and fourth techniques are further improvements of the SUT that insure simpler decoding. In Double Speed Up Technique (DSUT), the decoder size of SUT matrix is fixed and the size of H is doubled. In Partitioned Speed Up Technique (PSUT), the H size is fixed and the decoder size decreases by using small size of SUT matrices to grow H. Simulations show that the performance of LDPC codes formed using SUT outperforms ARCT at block length N = 1000 with 0.342dB at BER = 10-5 and LDPC codes created by DSUT outperforms SUT with 0.194dB at BER = 10-5. Simulations illustrate that the partitioning of H to small SUT submatrices not only simplifies the decoding process, it also simplifies the implementation and improves the performance. The improvement, in case of half, is 0.139dB at BER=10-5 however as partitioning increases the performance degrades. It is about 0.322dB at BER=10-5 in case of one-fourth.

Image colour classification and Image segmentation using comprehensive learning particle swarm optimization (CLPSO) technique was developed by Parag Puranik, Dr. P.R. Baja, Prof. P.M. Palsodkar [1], the aim was to produce a fuzzy system for colour classification and image segmentation with least number of rules and minimum error rate. In this paper we propose exponential particle swarm optimization (EPSO). EPSO has a great impact on global and local exploration it is supposed to bring out the search behaviour quickly and intelligently as it avoid the particles from stagnation of local optima by varying inertia weight exponentially, so that the movement of the particles will be faster and distant from each other. The EPSO is used to find optimal fuzzy rules and membership functions. The best fuzzy rule is selected for image segmentation.EPSO give best rule set than standard PSO.

Application of Support Vector Machine (SVM) for QRS detection in single lead and 12-lead Electrocardiogram (ECG) using entropy and combined entropy criterion is presented in this paper. The ECG signal is filtered using digital filtering techniques to remove power line interference and base line wander. SVM is used as a classifier for detection of QRS complexes in ECG. Using the standard CSE ECG database, both the algorithms performed highly effectively. The performance of the algorithm with sensitivity (Se) of 99.70% and positive prediction (+P) of 97.75% is achieved when tested using single lead ECG with entropy criteria. It improves to 99.79% and 99.15% respectively for combined entropy criteria. Similarly for simultaneously recorded 12-lead ECG signal, sensitivity of 99.93% and positive prediction of 99.13% is achieved when tested using entropy criteria and sensitivity of 99.93% and positive prediction of 99.46% respectively is achieved for combined entropy criteria. The percentage of false positive and false negative are reduced substantially when simultaneously recorded 12-lead ECG signal is used. The proposed algorithms perform better as compared with published results of other QRS detectors tested on the same database.

One of the recent developments in telecommunication industry is the introduction of communications through Internet. Some of the applications of internet are easy communications, vast library of information at one place, electronic business through internet, e learning modules and so on. E- learning is an important application of communication through Internet. E Learning is an integrated and continues approach to build knowledge skills and competencies through web enabled technologies. Effective e learning is having advantage in delivering the right content to the right person at the right time.E learning uses the new or existing network connections connected to internet. The wide area network maintains a high speed connection to an internet service provider that local centers can use to connect to the central LAN from a geographical distance away. Though they offer great accessibility, every one using the internet can see the traffic that passes between a local center and central office over these insecure internet LAN connections.Considering the fact that different encryption approaches target different types of computational complexity, it may be interesting to see if any further improvement can be achieved when different data encryptions are arranged with compression into a pipeline operation. In this work some effort has been put to calculate computational complexities and computational overhead of some encryption algorithms in e- learning environment.

The idea of our work is on one of the basic problems, namely the fast calculation of the distance between two objects. We haveimplemented an enhanced version of the shortest distance routine on the basis of mathematical equations, which allows thetracking of the distance between a pair of conics and quadrics in time that to be bounded by a constant is expected. Experimentalresults confirm this result, at least for moderate shortest distance calculation, and suggest that the enhanced algorithm might alsocome in handy. Computing the distance between two objects is a common problem, using the mathematical model of twoobjects, we find the point on each object such that the distance between the objects is minimized. To do this we took care ofefficient computing, which is possible with simplifying the polynomials and their relative coefficients. Effectiveness ofcomputing algorithms and executing time are also analyzed. We tested the calculation on various natural quadrics. The graphicspart is implemented in openGL and QT library is used for user interface. The execution time is calculated by running thedistance calculation routines 10,000,000 times.

The paper presents a conceptual framework in the context of Knowledge Management (KM) in Business Schools (B-schools) in India. We believe that if the framework is adopted in business schools, it will yield more benefits to increase the quality of knowledge sharing. There has been indeed a paradigm shift in management education in India. The new breed of management professionals need to be efficient to tackle problems from cross functional, cultural and ethical perspectives and equipped with skills to bench mark for global leadership positions. There has been a crying need to usher in a quality movement and to benchmark the same with world standards. We have made an attempt to support our framework by analyzing one of the Knowledge Management tools that was implemented in India’s Test Institute of Management (TIM), (a pseudonym is given to mask the institution’s name). This paper studies the knowledge management tool and features that are implemented in TIM and some problems that hindered knowledge management practices at TIM.

Object Oriented Programming Structure (OOPS) has proved its importance in software development in terms of advantages like Abstraction, Encapsulation, Polymorphism, Concurrency, Modularity and Reusability. Also the Object Oriented codes are found to be more verifiable & maintainable. Hence they allow reduction in efforts for development, testing & maintenance of the software. In current scenario, digital-VLSI design life cycle begins with modeling using some Hardware Description Language (HDL) followed by functional verification of the HDL-model by its simulation. Often, VLSI-developers show interest in getting software that simulates the functional behavior of the hardware for its analysis from different points of concern. For the sack of effort minimization in co-designing of Digital VLSI chips and their simulating software, it is of interest to introduce automation in code conversion from HDL to OOPS and vise versa. Author’s efforts in this direction are summarized in this document. The outcome of this paper may be developed as a code converter from C++ to VHDL and vise versa.

This paper presents a hybrid system controller, incorporating fuzzy controller with vector-control method for induction motors. The vector-control method has been optimized by using fuzzy controller instead of a simple P-I controller. The presented hybrid controller combines the benefits of fuzzy logic controller and vector-control in a single system controller. High quality of the regulation process is achieved through utilization of the fuzzy logic controller, while stability of the system during transient processes and a wide range of operation are assured through application of the vector-control. The hybrid controller has been validated by applying it to a simulation model.

This paper presents a novel method for optimal location of FACTS controllers in a multi machine power system using Genetic Algorithm(GA). Using the proposed method, the location of FACTS controller, their type and rated values are optimized simultaneously. Among the various FACTS controllers, Thyristor Controlled Series Compensator (TCSC) and Unified power Flow Controller (UPFC) are considered. The proposed algorithm is an effective method for finding the optimal choice and location of FACTS controller and also in minimizing the overall system cost, which comprises of generation cost and investment cost of FACTS controller using GA and conventional Newton Raphson’s power flow method. A VC++ coding is developed for Genetic Algorithm. In order to verify the effectiveness of the proposed method, IEEE 9 bus system is used. Different operating conditions of the power system are considered for finding the optimal choice and location of FACTS controllers. The proposed algorithm is an effective and practical method for the optimal allocation of FACTS controllers.

The paper describes a variable speed wind generation system where fuzzy logic principles are used for light load efficiency improvement and optimization. A squirrel cage induction generator feeds the power to an improved topology of matrix converter which pumps power to a utility grid or can supply to an autonomous system. The power factor at the interface with the grid is controlled by the matrix converter to ensure purely active power injection into the grid for optimal utilization of the installed wind turbine capacity. Furthermore, the reactive power requirements of the induction generator are satisfied by the matrix converter to avoid self-excitation capacitors. The generation system has fuzzy logic control with vector control in the inner loops. Fuzzy controller tracks the angular frequency with the wind velocity to extract the maximum power and programs the machine flux for light load efficiency improvement. The complete control system has been developed, analyzed, and validated by simulation study. Performances have then been evaluated in detail.

Signal interference, route disruption, congestion and fluctuations cause several consecutive bits arriving at the receiver in error. The error handling method in tradition communication protocols is error detection and retransmission. This method is inappropriate for distributed multimedia systems for two reasons: It introduces variable delay unacceptable for isochronous streams, and it is very inefficient and difficult to use in the multicast environment typical for many multimedia applications. We propose Enhanced MAC Node Cooperation with Two-Stage Forward Error Correction Scheme to be used on WLANs. The proposed scheme enables the joint optimization of protection strategies across the protocol stack. Node cooperation technique improves networks’ overall system throughput and reliability, reduces the cost of retransmission and energy consumption. In stage 1 of FEC, packet-level FEC is added across packets at the application layer to correct packet losses due to congestion and route disruption. In stage 2, bit-level FEC is processed within both application packets and stage 1 FEC packets to recover from bit errors in the MAC/PHY layer. Thus, we add FEC at the application layer to correct both application layer packet errors and MAC/PHY layer bit errors. MAC is enhanced to support node cooperation and header CRC.

The quality of voice in IP based networks is highly reliant on Packet loss and delay. Packet loss is the failure of packets toreach the destination [1,2]. The multi-path diversity is a phenomenon to send identical packets from diversified paths.Therefore, if certain packet is lost from one stream, still its identical packet has fair chance to arrive at the destination [3]. Wefirst discuss the modeling of packet loss and delay using Bernoulli and Extended Gilbert Model [4]. We then evaluate theresults of both models. We have developed a modified loss model for modeling of packet loss using multi-path diversity. Thepresent research aims to increase the efficiency of Forward Error Correction (FEC) by the modeling of packet loss and delayin the real time communication. The set of examined results from our research shows that multi-path diversity bestowspositive effect on the voice quality of VoIP network. The results also validate our model as comparison with actual dataresults in similar trend.

This paper proposes a new technique for Mobile IP (MIP) registration by WLAN host (WH) of the Internet through GPRS network. The home agent (HA) of WH resides in the Internet. The gateway GPRS Support Node (GGSN) provides foreign agent (FA) functionality for WH in GPRS. After successful attachment with GPRS network in roaming scenario, WH needs two mandatory passes for MIP registration with HA. In first pass, it establishes PDP context in GPRS network and in second pass, it sends MIP registration request to FA at GGSN. This two-pass registration causes substantial delay for handoff from WLAN to GPRS. To minimize this delay, we propose a one-pass MIP registration technique through GPRS network by modifying the activate-PDP-context request (APCR) message. In this scheme, the APCR message carries MIP-registration request in its information field to GGSN. Therefore, FA at GGSN can process MIP registration packet before completion of PDP context in GPRS network. Thus, both PDP context creation and MIP registration are accomplished in one pass of signaling. This technique reduces handoff delay from WLAN to GPRS minimizing the control signals. We observed from simulation results that the proposed one-pass technique reduces handoff delay by 18% compared to that of two-pass method proposed in [8]

This paper aims to present an electronic voting system (E-Voting), hopefully, to be applied to the Lebanese electoral system. This E-Voting system (E-VS) was designed for electorates through computers programmed with convivial Graphical User Interfaces. The complex treatments and features are achieved at the levels of applicative layer and database. Several security measures were integrated into the E-VS in order to achieve an enhanced, speedy and accurate performance. It is about time that conventional voting in Lebanon gives way to E-Voting and hence simplifies the task for Electorates, Deputy Returning Officer and Returning Officer.

Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach for obtaining simultaneous arrangement of part families and machine cells for cellular manufacturing systems. The main feature of the proposed method is, the relevant production data such as process sequences and setup times are taken in to account. It has the ability to select the best solution among the solutions of compactness, group technology efficiency and reducing setup time efficiency for each part before attempting to cluster the machines and parts. The formation of part family and machine cell has been treated as a maximization problem according to a defined performance measure ‘β’. A genetic algorithm has been developed for solving the cell formation problem considering the reduction in setup time. The validation has been done based on a real time manufacturing data. This algorithm is written in the ‘C’ language on Intel Pentium / PIII compatible system.

Language is a unique phenomenon that distinguishes man from other animals. It is our primary method of communication with each other, yet very little is understood about how language is acquired when we are infants. A greater understanding in this area would have the potential to improve man machine communication. The problem that is attempted to be solved in this paper is that of programming a computer to play the Shannon Game. To play the Shannon game, one must predict which words are most likely to follow a given segment of English Text. Word Prediction would be most useful for writers with physical disabilities and severe spelling problems. The aim of this paper is to improve on existing results by writing a program that is capable of automatically inferring a grammar from a Natural Language Corpus, and applying this to the Shannon Game. To play the Shannon Game, a stochastic Grammar for an approximation to the target language must be inferred from a text sample, and as the quality of this grammar improves so too does the quality of the predictor that uses the inferred grammar. The proposed algorithm in the paper uses Support Vector Machine to perform the part of speech tagging which produces 97.6% correct predictions.

The present study examines the growth performance of India’s IT industries, with particular attention paidto the role of policy in this process. The study recognizes that emergence of a strong Indian IT industryhappened due to concerted efforts on the part of the Government, particularly since 1980s, and host of otherfactors like Government-Diaspora relationships, private initiatives, emergence of software technologyparks, clustering and public private partnerships. In this study we further look at the major parameters ofthe Indian IT industry and give justification for including the main factors responsible for the IT boom inIndia. The study has looked into the past and present trends of the Indian IT industry and has consideredfurther needs of IT sector to act as a catalyst of growth and development. The study has examined whetherthe Indian IT growth does have enough lessons for other countries to model their IT policy which may helpthem to shape their IT industry as driver of growth and development.

In this paper, we propose two approach intelligent techniques of improvement of Direct Torque Control (DTC) of Induction motor such as fuzzy logic (FL) and artificial neural network (ANN), applied in switching select voltage vector .The comparison with conventional direct torque control (DTC), show that the use of the DTC_FL and DTC_ANN, reduced the torque, stator flux, and current ripples. The validity of the proposed methods is confirmed by the simulative results.

N-grams are consecutive overlapping N-character sequences formed from an input stream. N-grams are used as alternatives to word-based retrieval in a number of systems. In this paper we propose a model applicable to categorization of Telugu document. Telugu is an official language derived from ancient Brahmi script and also the official language of the state of Andhra Pradesh. Brahmi based script is noted for complex conjunct formations. The canonical structure is described as ((C) C) CV. The structure evolves any character from a set of basic syllables known as vowels and consonants where consonant, vowel (CV) core is the basic unit optionally preceded by one or two consonants. A huge set of characters that resemble the phonetic nature with an equivalent character shape are derived from the canonical structure. Words formed from this set evolved into a large corpus. Stringent grammar rules in word formation are part of this corpus. Certain word combinations result in the formation of single word is to be addressed where the last character of the first word and first character of the successive word are combined. Keeping in view of these complexities we propose a trigram based system that provides a reasonable alternative to a word based system in achieving document categorization for the language Telugu.

An active database system is a conventional database system extended with a facility for managing active rules (ortriggers). Active rules may interact in complex and sometimes unpredictable ways, thus possibly yielding infiniterule executions by triggering each other indefinitely. In this paper, we propose a method of termination analysis ofactive rules based on Petri nets (PN) and give an object oriented representation to implement it. This approach isbetter than the previous ones because it takes into a count composite events and the rule priority on the one hand, andboth rule representation and rule analysis are performed in the same PN on the other hand.

“Reduction in Runtime using trap analysis “ concentrates on finding the procedure for inserting traps at required places and optimizing runtime by moving the traps to low frequency regions. Using this, one can benefit in two ways: (i) being able to generate efficient code (ii) being able to produce more reliable programs by careful examination of errors in the programs. Traps are placed within a loop so as to avoid abrupt termination on bound violations. Since these traps are placed in high frequency regions, apply frequency reduction optimization technique to move this trap to low frequency regions. The results clearly indicates significant reduction in number of instructions, number of machine cycles and execution times for array bound checks applied on sorting techniques for inner loops as well as outer loops. In the present paper, the trap analysis is performed on all sorting techniques which have nested loops of depth two. However insertion of traps increases the run time, hence to overcome this disadvantage,an innovative method of optimization has been proposed in the present paper which move the checking code out of loops.

In this paper a "Low Voltage, Low Power, High Speed and High Linearity-CMOS Analog Multiplier for Modem ASK is proposed". The multiplier circuit is implemented in 180nm CMOS technology. It can be operated even at low Supply voltage VDD=0.9V. Band width of operation is about 4.10MHz, which is suitable for high frequency/high speed applications. This device modulates an analog carrier signal to encode digital information, and also demodulates such a carrier signal to decode the transmitted information. The goal is to produce a signal that can be transmitted easily and decoded to reproduce the original digital data.

Low noise and low Power transimpedance amplifiers (TIA) are essential modules for optical sensor based systems. But low power and low noise TIAs are still a challenge for the scientists despite of rapid advances in complementary metal oxide semiconductor (CMOS) technology. This paper proposes a three-stage nested miller compensated (NMC) based design of low noise low power transimpedance amplifier for stable wideband operation. The circuit is designed in the 0.18μm CMOS technology by using Mentor Graphics environment. The simulation results show that the proposed TIA can operate at frequency 20 KHz and produces an output of 1.4265V for ±1.2 V input voltages dissipating only 2.9206 mW power at 27°C temperature. The complete layout of the TIA is only 0.005 μm2.This shunt-feedback TIA can be a better choice for high-resolution, low-to mid frequency applications.

In this paper, the new structure of Artificial Magnetic Conductor is presented. The AMC is designed to overcome the failure of detecting the RFID tag when placed near to the metal based object. It is too complicated to design an AMC at low frequency due to limitation of size and bandwidth. In this paper, the 0.92 GHz AMC is designed with different sizes and shapes of slots inserted into the square PEC patch. The size of single unit cell of this AMC is 45.5 mm × 45.5 mm. The AMC is designed in stacked layer to increase the bandwidth of single unit cell. The optimized AMC at 0.92 GHz frequency, had increase the performance of dipole antenna by return loss = -21.8 dB, gain = 3.0 4dB and directivity = 5.149.