IT industry in the present market situation faces high demand for performance and burgeoning user expectations; with the pressure manifesting itself in three forms – Development Cost, Time-to-market and Product Quality. Researchers have proposed several techniques to effectively deal with these conflicting scenarios and draw optimized output. One of the relevant techniques in this context is Component Based Software Development (CBSD) with a targeted and discriminative approach influencing all phases of development. Although, CBSD proposes a multi-faceted approach in complex scenarios, its prime focus lies in “write once and reuse multiple times” methodology with either no or minor modifications. The model has been markedly successful in large enterprise applications with companies deriving benefits from shorter development time, increased productivity and better quality product. This research paper focuses and discusses Empirical Study of an Improved Component Based Software Development (ICBD) Model using Expert Opinion Technique which covers both component based software development as well as Component development phases. ICBD Model tries to overcome some of the issues in the contemporary CBD Models. A case study was conducted to investigate and evaluate our model by experienced professionals working in the IT industry. Results have shown that our improved model registers significant improvement over previous models suggested by other researchers.

This article serves two purposes: firstly, it presents an innovative methodology that increases the accuracy of fault prediction measurements. This method is based on the novel concept of "fault persistency", which enables to correct prediction metrics with a weighted value related to the module’s history. Secondly, it aims to develop operational processes from the aforesaid prediction metrics that may contribute to software construction and validation. It presents an example of an allocation methodology for resources used for testing purposes. The theoretical part is followed by an extensive experimental phase.

The process of fuzzy modeling or fuzzy model identification is an arduous task. This paper presents the application of Memetic algorithms (MAs) for the identification of complete fuzzy model that includes membership function design for input and output variables and rulebase generation from the numerical data set. We have applied the algorithms on four bench mark data: A rapid Ni-Cd battery charger, the Box & Jenkins’s gas-furnace data, the Iris data classification problem and the wine data classification problem. The comparison of obtained results from MAs with Genetic algorithms (GAs) brings out the remarkable efficiency of MAs. The result suggests that for these problems the proposed approach is better than those suggested in the literature.

Low power design of VLSI circuits has been identified as vital technology in battery powered portable electronic devices and signal processing applications such as Digital Signal Processors (DSP). Multiplier has an important role in the DSPs. Without degrading the performance of the processor, low power parallel multipliers are needed to be design. Bypassing is the widely used technique in the DSPs when the input operand of the multiplier is zero. A Row based Bypassing Multiplier with compressor at the final addition of the ripple carry adder (RCA) is designed to focus on low power and high speed. The proposed bypassing multiplier with compressor shows high performance and energy efficiency than Kuo multiplier with Carry Save Adder (CSA) at the final RCA.

Different characteristics can be considered in a suspension system design like: ride comfort, body travel, road handling and suspension travel. No suspension system can optimize all these parameters together but a better tradeoff among these parameters can be achieved in active suspension system.
Objective of this paper is to establish a robust control technique of the active suspension system for a quarter-car model. The paper describes also the model and controller used in the study and discusses the vehicle response results obtained from a range of road input simulations. A comparison of robust suspension sliding fuzzy control and passive control is shown using MATLAB simulations.

Different types and techniques of DDoS attacks & defense are studied in this paper with some recent information on attacks dominated in year 2012 (1st Quarter). We further provide simulation based analysis of an FTP server’s performance in a typical enterprise network under distributed denial of service attack. Simulations in OPNET show noticeable variations in connection capacity, task processing and delay parameters of the attacked server as compared to the performance without attack. DDoS detection and mitigation mechanisms discussed in this paper mainly focus on some recently investigated techniques. Finally, conclusions are drawn on the basis of survey based study as well as simulation results.

IEEE 802.16 standard supports five different service classes in order to support different needs of the mobile users with different QoS criteria. But, this standard doesn’t specify admission control and scheduling mechanisms and so far many solutions are proposed in the science world. In this paper we propose priority based uplink scheduling scheme for IEEE 802.16 standard that improves the QoS performances of the five WiMAX service classes, especially of the ertPS service class. Simulation experiments and analysis are done choosing the most adequate WiMAX simulator and the ns-2 simulation tool. Traffic load of the ertPS connections is changed from low to high in order to perform detailed performance analysis of the results. Results given in average delay, average jitter and average throughput are evaluated and compared with so far known uplink scheduling mechanism. The results show that our proposed uplink scheduling scheme based on the priority of the service classes improves the QoS performances especially in high loaded scenarios.

In the era of information and communication technology, Security is an important issue. A lot of effort and finance are being invested in this sector. Intrusion detection is one of the most prominent fields in this area. Data mining in network intrusion detection can automate the network intrusion detection field with a greater efficiency. This paper presents a literature survey on intrusion detection system. The research papers taken in this literature survey are published from 2000 to 2012. We can see that almost 67 % of the research papers are focused on anomaly detection, 23 % on both anomaly and misuse detection and 10 % on misuse detection. In this literature survey statistics shows that 42 % KDD cup dataset, 20 % DARPA dataset and 38 % other datasets are used by the different researchers for testing the effectiveness of their proposed method for misuse detection, anomaly detection or both.

Web interface design patterns provide solutions to recurring design problems. Many design patterns use various techniques, which have been proven to be significantly different, to solve the same design problem. Normally, web designers do not know whether users would be satisfied with their chosen choice until near or at the end of the web development process. To obtain user feedback, users are usually asked to interact with a web prototype or the finished web and give their opinion through standardized questionnaires. Net Promoter Score is one of such questionnaires. This scale categorizes users’ responses into promoters and detractors, which makes it easier for companies to understand user satisfaction towards their web. To enable the designers to obtain user feedback early in the design stage, Net Easy Score, a new metric based on Net Promoter Score, was proposed. With Net Easy Score (NES), ease-of-use scores on different design patterns will be divided into a positive and a negative group. The NES is a difference between percentages of positive responses and negative ones. This study examined ease-of-use scores on design patterns for five common tasks in commercial web applications. Results showed that NES and mean ease-of-use score were significantly correlated with an r of 0.965 (p < .000). Also, ranking the average ease-of-use scores and NES revealed the same design patterns identified as the best and the worst ones, which was consistent with the easiest-to-use design patterns voted by participants.

Focus of this paper is on energy heterogeneity and distributed algorithms for scheduling and adjustable range. The problem of lifetime enhancement of wireless sensor networks is dealt with the adjustment of transmission or sensing range of the sensor nodes and implementation of heterogeneous energy model. In this work, we deploy the sensor nodes in 2-D using triangular, square, and hexagonal tiles. The initial energies of the sensors and their positions along with the positions of targets are known. For this environment, we investigate the maximum achievable lifetime using heterogeneous deterministic energy efficient protocol with adjustable sensing range (HADEEPS) and heterogeneous load balancing protocol with adjustable sensing range (HALBPS). We observe that deploying the sensors in triangular tiles gives better lifetime.

Component-based technology can increase reuse and productivity, but high-quality component-based systems are often difficult to implement. Component developers do not know the systems where the components will be used, while software engineers must develop new systems with limited knowledge on available components. We propose a new testing technique that generates, at the time of component development, integration test cases from the specification of the behavior expected from other components of the system. The technique presented in this paper supports both the component developer, who can early test the integration of the components with the system, and the software engineers, who can test concrete components at deployment time, simply re-using existing test cases.
The technique presented in this paper supports both the component developer, who can early test the integration of the components with the system, and the software engineers, who can test components at deployment time. We used questionnaires to validate the proposed solution.

This paper describes the design and implementation of robust nonlinear sliding mode control strategies for robot manipulators whose dynamic or kinematic models are uncertain. Therefore a fuzzy sliding mode tracking controller for robot manipulators with uncertainty in the kinematic and dynamic models is design and analyzes. The controller is developed based on the unit quaternion representation so that singularities associated with the otherwise commonly used three parameter representations are avoided. Simulation results for a planar application of the continuum or hyper-redundant robot manipulator (CRM) are provided to illustrate the performance of the developed adaptive controller. These manipulators do not have rigid joints, hence, they are difficult to model and this leads to significant challenges in developing high-performance control algorithms. In this research, a joint level controller for continuum robots is described which utilizes a fuzzy methodology component to compensate for dynamic uncertainties.