Most of the refinement approach is about functional property of systems. Non-functional properties are as important as functional one. Without an accurate approach for specifying and refining their behaviors, software models will be regarded as imperfect and imprecise, and as a result, software systems cannot be generated correctly. Therefore, how to model such behaviors and how to stepwise refine these behaviors automatically, have become two critical problems in Model Driven Development. In this paper we present an approach for Non-functional refinement in model driven development using high order transformation languages and traceability property of them. We extend the idea of model refinement to non-functional properties of software and propose a stepwise refinement framework with conformance checking between abstract and concrete descriptions of system model using model transformation. The approach is extendable to all quantitative and quantitative non-functional properties.

The process of finding the finest hotel in central location is time consuming, information overload and overwhelming and in some cases poses a security risk to the client. Over time with competition in the market among travel agents and hotels, the process of hotel search and booking has improved with the advances in technology. Various web sites allow a user to select a destination from a pull-down list along with several categories to suit one’s preference.. Some of the more advanced web sites allow for a search of the destination via a map for example hotelguidge.com and jamaica.hotels.hu. Recently good amount of work been carried in the use of Intelligent agents towards hotel search on J2ME based mobile handset which still has some weakness. The proposed system so developed uses smart software agents that overcomes the weakness in the previous system by collaborating among themselves and search Google map based on criteria selected by the user and return results to the client that is precise and best suit the user requirements. In addition, the agent possesses learning capability of searching the hotels too which is based on past search experience. The booking of hotel involving cryptography has not been incorporated in this research paper and been published elsewhere. This will be facilitated on Android 2.2-enabled mobile phone using JADE-LEAP Agent development kit.

This work is aimed at providing a neuro-fuzzy system for heart attack detection. Theneuro-fuzzy system was designed with eight input field and one output field. The input variables are heart rate, exercise, blood pressure, age, cholesterol, chest pain type, blood sugar and sex. The output detects the risk levels of patients which are classified into 4 different fields: very low, low, high and very high. The data set used was extracted from the database and modeled in order to make it appropriate for the training, then the initial FIS structure was generated, the network was trained with the set of training data after which it was tested and validated with the set of testing data. The output of the system was designed in a way that the patient can use it personally. The patient just need to supply some values which serve as input to the system and based on the values supplied the system will be able to predict the risk level of the patient.

Analyzing object – oriented systems in order to evaluate their quality gains its importance as the paradigm continues to increase in popularity. Consequently, several object- oriented metrics have been proposed to evaluate different aspects of these systems such as class coupling. This paper presents a new cognitive complexity metric namely cognitive weighted coupling between objects for measuring coupling in object- oriented systems. In this metric, five types of coupling that may exist between classes: control coupling, global data coupling, internal data coupling, data coupling and lexical content coupling are consider in computing CWCBO.

In this paper new methods Tri Non Linear Interpolation and nearest neighbor interpolation for image denoising in wavelet domain are proposed. Tri non linear interpolation methods better de-noising method which preserves the image feature like edges and background. Interpolation is way through which images are enlarged. The nearest neighbor interpolation used forward wavelet and enlarges the size of image which retains the image parameter. The nearest neighbor interpolation technique is fruit full for variety of noisy images. PSNR is key parameter for measurement of image quality throughout this text. The existing methods used the threshold technique for noise removal but our methods image quality is better as compared to the existing threshold technique.

Scrum model always welcome the new requirements from customer at any stage of software development. This situation creates problem for development team to meet estimated timelines. The Scrum development team is always under heavy workload and stress because of this situation. A high level of coordination among team members is required in order to overcome this work pressure and meet quality demands within estimated time and cost. Scrum model emphasis to coordinate through communication to cope with changing requirements. Scrum development is facing new challenges to meet high quality demands with critical timeline environment. The ability of a team to act intelligently in such situation is gaining key position for the survival and success of an organization. The goal of this paper is to highlight the role of implicit coordination helping the software development team members to act intelligently in time demand environment to achieve common goals. Implicit coordination among team members during sprint zero development can show significant improvement in team performance. This will help to achieve high quality product under heavy workload within estimated time period. A survey is conducted to validate the research i.e., implicit coordination has strong impact for successful implementation of Scrum methodology.

It is hard to believe a web form without a CAPTCHA. The web survival in this cut-throat competition is impossible without the mechanisms for blocking spam-boats. The spam-boats have now been made intelligent enough to break through machine printed CAPTCHAs. Handwritten CAPTCHA image can be one solution. In this paper handwritten CAPTCHA images have been used to enhance the web security. Introduction of randomness at various stages is proven to increase the recognition complexity for the spam boats, whereas the ease of recognition of handwritten words by human beings eventually increases the usefulness of such CAPTCHA. The technique used to produce colored image of handwritten letters also has randomness associated with it. The proposed CAPTCHA images contain alphanumeric content, one word with letters and a number with handwritten numerals. CAPTCHA images developed using proposed technique have been tested across various OCRs and online available resources as well.

Orthogonal Frequency Division Multiplexing (OFDM) is an attractive modulation technique for transmitting large amounts of digital data over radio waves. One major disadvantage of OFDM is that the time domain OFDM signal which is a sum of several sinusoids leads to high peak to average power ratio (PAPR) which leads to power inefficiency in RF section of the transmitter and increased complexity in the analog to digital and digital to analog Converter. Selected mapping (SLM) is a well-known method for reducing the PAPR in OFDM. In this paper, we have studied the performance of SLM for Different Number of Subcarriers. Simulation result shows that the PAPR is reduced significantly when the number of phase sequences is increased and PAPR is increased when the number of subcarriers is increased. It also shows that data speed increases when subcarriers increase where N-point IFFT/FFT circuit depends on N-subcarriers.

Many distributed applications require a group of destinations to be coordinated to a single source. Multicasting is a communication paradigm to implement these distributed applications. In multicasting, at least one of the member in the group cannot satisfy the service requirement of the application, the multicast request said to be blocked. On the contrary in manycasting, destinations can join or leave the group, depending upon whether it satisfies the service requirement or not. Manycasting is performed over optical burst-switched (OBS) networks based on multiple qualities of service (QoS) constraints. The multiple constraints can be in the form of physical layer impairments, transmission delay, and reliability of the link. Destinations qualify only if they satisfy the Qos constraints. We develop a simple yet efficient routing algorithm which is based on the classic shortest path algorithm. The proposed layer aware FEC (L-FEC) generates repair symbols so that protection of less important dependency layers can be used with protection of more important layers for combined error correction.

Correlation between gene expression profiles to disease or different developmental stages of a cell through microarray data and its analysis has been a great deal in molecular biology. As the microarray data have thousands of genes and very few sample, thus efficient feature extraction and computational method development is necessary for the analysis. In this paper we have proposed an effective feature extraction method based on factor analysis (FA) with discrete wavelet transform (DWT) to detect informative genes. Radial basis function neural network (RBFNN) classifier is used to efficiently predict the sample class which has a low complexity than other classifier. The potential of the proposed approach is evaluated through an exhaustive study by many benchmark datasets. The experimental results show that the proposed method can be a useful approach for cancer classification.