Earticle

Component-Based System (CBS) is a promised approach to build applications from deployed components. It provides efficiency, reliability, maintainability. Interpreting the results of performance analysis and generating an alternative design to build system from component (Hardware/Software) is a great challenge in the software performance domain. There are so many options to compose the system. Span of design space hinders the selection of the appropriate design alternative. Currently, Meta-heuristics such as Genetic Algorithm (GA) methods are used to solve the problem. In recent investigations Particle Swarm Optimization (PSO), an alternative search technique, often outperforms GA when applied to various problems. In this paper, we describe performance prediction approach based on PSO for component-Based system development. PSO technique can be used to effectively generate alternatives design options in spanned design space and facilitate the design decision during the development process. The proposed approach aids developers to effectively trades-off between architectural designs alternatives, because it covers and generates all possible options and provides the best solution. To the best of our knowledge, we are the first who use PSO in software performance prediction, particularly in the context of CBS. To this end, outlines and an example are presented in the paper to describe the approach.

A triple metal double gate (TM-DG) MOSFET with high-k dielectrics has been proposed to overcome the short channel effects. We are using top and bottom metal gates with different work functions to screen the effect of drain (DIBL effect). It has been found that this is effective in reducing the short channel effects. The metal gates have been used to remove the poly silicon depletion of conventional double gate (DG) MOSFET due to aggressive scaling to sub 100 nm regimes. It has been observed that use of metal gate with different workfunctions along with high-k dielectric improves the carrier transport in the channel.

Classification is a data mining technique widely used in critical domains like financial risk analysis, biology, communication network management, etc. Classification accuracy and learning from distributed datasets are the most challenging topics in the field of supervised learning. In this paper, we first briefly review the background of parallel and distributed classification algorithms and then propose a novel approach for classification in distributed large datasets. This approach is based on code migration instead of data migration. Extensive experimental results using a popular benchmark test suite show the effectiveness of this approach in term of accuracy. These results show also that the proposed method improved slightly classification accuracy over standard methods.

Preview Control is a field well suited for application to systems that have reference signals known a priori. The use of advance knowledge of reference signal can improve the tracking quality of the concerned control system. The classical solution to the Preview Control problem is obtained using the Algebraic Riccati Equation. The solution obtained is good but it is not optimal and has a scope of improvement, as the Preview Control problem has many parameters to be defined and optimized. The Evolutionary Algorithms, inspired by real-time natural systems, are a solution to this multi-dimensional problem. This paper studies the performance of Preview Control optimized by three Evolutionary Algorithms (Genetic Algorithm, Particle Swarm Optimization and Marriage in Honey Bees Optimization) for two bench-mark control systems: Industrial Servo and Inverted Pendulum System in terms of processing time, convergence characteristics and the quality of solution obtained. The results of this paper illustrate the benefits and weaknesses of the Evolutionary Algorithms for solving the Preview Control problem. The PSO algorithm proves to be the best for Preview Control based problems. It performs well in both small and large search spaces. The study reveals that the MBO algorithm requires more computation time while the performance of GA degrades with the increase in number of parameters to be tuned.

Developing dependable distributed multi-agent programs is not an easy task. Even with extensive testing and debugging, faults cannot be completely removed. However, many distributed multi-agent programs, especially those employed in safety critical environments, should be able to function properly even in the presence of software faults. Monitoring the execution of a distributed multi-agent program, detecting failures, and reacting to these failures at runtime is the appropriate way to tolerate these failures. In this paper, we have designed and implemented a framework for monitoring the execution of distributed multi-agent programs. The proposed framework extends the Java Agent DEvelopment framework (JADE) allowing agent programmers to monitor global states, to detect the occurrence of certain events and to react to these events at runtime. An example of monitoring a distributed multi-agent program has been presented to demonstrate the effectiveness of the proposed framework.

The main objective of medical image segmentation is to extract and characterize anatomical structures with respect to some input features or expert knowledge. The Otsu method is a popular non-parametric method in medical image segmentation. Traditional Otsu method for medical image segmentation is time–consuming computation and became an obstacle in real time application systems. In the same way TSMO method also compared. This paper describes a way of medical image segmentation using optimized Otsu method based on improved thresholding algorithm. In proposed algorithm, the experimental results show that the new optimized method dramatically reduces the operating time and increases the separability factor in medical image segmentation while ensures the final image segmentation quality. However, the computation time grows exponentially with the number of thresholds when this method extended to multi-level thresholding.

Korea has made a plan to transfer from analog television to Digital Television (DTV). Therefore, TV White Spaces (TVWS）are the unused TV broadcast channels which can be available for wireless communication systems. This paper assumes that DTV operates on Channel 34 and Long Term Evolution (LTE) is assumed that it uses Frequency Division Duplexing (FDD), and then upper 4 MHz of Channel 32 and channel 33 are assumed to allocate to LTE Uplink, and channel 35 and lower 4 MHz of channel 36 are assumed to allocate to Downlink. However, the interference effect of LTE on DTV has to be taken into account. Therefore, according to the interference probability of 5% required by DTV receiver and the allowable transmit power of LTE Base Station (BS) and Mobile Station (MS), the protection distance from the reference LTE BS and MS to DTV receiver and the guard band will be analyzed by using Spectrum Engineering Advanced Monte-Carlo Analysis Tool (SEAMCAT). As a result, in the case that 8 MHz guard band is required and the assumed emission mask of LTE BS is used, the required protection distance between the LTE BS and DTV receiver is about 2 km. In the case of interference between LTE MS and DTV receiver considering the assumed emission mask of LTE MS, the protection distance is negligible above 8 MHz of guard band. The results can be as a guideline and reference in making plan for the coexistence of LTE and DTV.

e-shopping has grown in popularity over the years, mainly because people find it convenient and easy to buy various items comfortably from their office or home. This paper has proposed a personalized e-shopping system, which makes use of agent technology to enhance the automation and efficiency of shopping process in Internet commerce. The agent technology is used to enhance the customer’s needs which include availability, speedy response time, and efficiency. Agent for e-Shopping creates connectivity on an anytime-anywhere-any-device-basis to provide the specific goods required by the consumers. But Internet being heterogeneous and non secure medium; privacy, authenticity, integrity, and non-repudiation are the key requirements to be addressed by such systems where face to face interaction is not possible. Most of the systems do not provide the required level of security service so that many problems exist in the systems like denying, losing, misusing, stealing double-spending etc. This paper address all the above said security service problems to an e-shopping system using Elliptic Curve Cryptosystem (ECC).