This paper deals with design of the agile method RISVICO. The method is for more effective collaboration between software engineer and database analyst by using an effective visualization tool in 3D environment, database analyst and software engineer belong to the software engineering. The method is for more effective collaboration between software and database development by using an effective visualization tool in 3D environment, database analyst and software engineer belongs to the software engineering. The visualization tool will provide important information for a database analyst and for a software engineer. Main idea is make use of nature of data which the program uses, for development and maintenance in software life cycle. Data which software will use determine procedure in development and maintenance, in this way we can provide better quality of software product.

In this article we present our approach developed concerning the generation of usable User Interfaces (UI), then we show its results, starting as a basis with UML models. Indeed, we based the approach on the Model Driven Engineering and the development of specific meta models for UI from the perspective of a UML model-based design on one hand and a set of transformations on the other hand. Indeed, we defined a new meta model that is neither a use case nor an activity diagram, but our way to describe the UI in terms of the user's interactions. Thus we used the good practices of Designs Patterns when developing the meta models. The approach includes first creating a platform independent model (PIM) and transforming this PIM into platform specific model (PSM) thought transformation rules. The PIM is created first based on the UML use case and activities diagrams to extract the main functionalities offered by the system to be developed. Then we established the PSM meta model, being the target model of our transformation engine, taking into account the design patterns composite and MVC. With this methodology, the UI can easily be analyzed, designed, and generated to increase system development

The World Wide Web is the biggest source of data that the general public has access to. Students and researchers working on data-related problems need a well-maintained source to get their data from. Most online services provide APIs to use their service. However, this may not provide all the data that they actually need even though it exists on the website. In this paper, Scrapple – a framework for creating semi-automatic web scrapers, which extract required data from the Web, is introduced. Users do not need to write the entire scraping programs - they only need to define a configuration file which is used to build the required scraper. The configuration provides support for CSS selectors and XPath expressions

In this paper, we presented a Wavelet based video compression method. The wavelet transform is performed by lifting scheme methodology which allows temporal and special scalability as well as lossless reconstruction. The spatial decorrelation was elaborated with the standard JPEG2000. We exploited the inter-frames correlation thanks to a temporal wavelet transformation. A Simulink based implementation is then experimented in order to accelerate the process thanks to a co-simulation step

Cloud computing is the fastest growing, popular and most widely used technology in the current web. Interoperability is one of the major issues found in cloud environments where it is not an easy go for the cloud consumers to have a direct interaction with the cloud providers in order to request for a service. The semantic web technology is the most powerful growing technology to the current web which allows adding semantic metadata to the cloud services. Addition of Semantic web technologies to the cloud platforms provides scalable and efficient results to the consumers. This paper presents a semantic interoperability model which provides an improved interaction between the cloud Platform as a service provider and the cloud consumers. The semantic interoperability layer that sits between the cloud provider and the user does the semantic description generation of the service which helps in discovering the service and invoking the service with respect to the user’s request. This proposed method is done with the cloud service called Google app engine which is Platform as a service provided by Google and the semantic web technology tool used is JRDF, a framework for RDF and SPARQL Query language.

The monitoring of the earth by meteorological satellites became an indispensable process. The main mission of these satellites consists to improve daily weather forecasts and anticipate severe weather. But they also follow a few activities such as: the monitoring of urban spaces, the evolution of the vegetation cover, and the detection of forest fires etc. The Meteosat Second Generation satellite is equipped with a radiometric sensor SEVIRI (Spinning Enhanced Visible & Infrared Imager), allows the acquisition of 12 image files that correspond to the 12 channels of visible and mid-infrared, thermal infrared every 15 minutes. The accumulation of these images confront us with problems of storage and transmission. There are many interesting techniques of image compression that allow an efficient minimization of the size of the images with a good rate-distortion compromise. This paper presents a novel Meteosat Second Generation image compression method based on Radon transform and two novel techniques, which are Linear Predictive Coding (LPC) with filtering and the Sorted Run Length Coding (SRLC). The Radon transform is applied to MSG images to retrieve the Radon points. The residual predictions are extracted first from the filtered Radon points and then encoded by the arithmetic encoding to recover a single codeword using the LPC coding with filtering. Finally, the SRLC coding is performed to achieve a high and fixe compression ratio by the generation of a sorted sequence of the codeword and a sorted occurrence table. This method ensures an excellent rate-distortion compromise: high and fixed compression ratio of 99.90 % while preserving the integrity and the quality of the MSG images after decompression.

Multimodal medical image fusion gives the complementary information present in each imaging sensor combined into a single image. This is done to reduce the data, better visualization and clinical diagnosis. In this paper, an efficient fusion approach based on redundant transforms, which, in particular, restores and shift-invariant the image as fused image contains artifacts when reconstructed. Different wavelets like Daubechies, orthogonal, Biorthogonal, Symlets and Curvelets are compared with the proposed technique. Medical image fusion results are determined using subjective and objective analysis with the existing state of the art techniques which include wavelets and curvelets. The comparative analysis of the obtained fusion results are performed with RMS error, Entropy, Correlation coefficient, PSNR, Standard deviation, Spatial Frequency and Median frequency. The combined subjective and objective evaluation of the proposed fusion method shows the accuracy and increased robustness.

Vehicular ad-hoc networking can provide efficient traffic information, emergency warning, alert messages and infotainment dissemination. It takes a vital role in safety fields such as defense system, traffic system, etc. Even though, some advanced Public Key Infrastructure and digital signature method was used for security, intrusion detection is an inevitable challenge in networks. Prevention and detection of malicious vehicle from jeopardizing the safety of the other vehicle is focused in this paper by using region-based FBB (Flooding-Bilinear-Bloom Filter) authentication protocol. Authentication is performed in any PKI (Public Key Infrastructure) system by checking if the certificate of the sender is included in the CRL (Certificate Revocation List) and verifying the authenticity and checking the sign of the sender. Bilinear pairing method is used to create an anonymous Id for each vehicle. The CRL checking process has been done using Bloom Filter method which avoids false negative. CRL can be passed between vehicles by bi-directional flooding method which avoids network congestion. This paper focuses mainly the CRL dissemination using the bi-directional flooding method. It replaces the time-consuming CRL Checking process. It reduces message loss ratio by using fast revocation checking and CRL updating method as well as it needs very less memory space compared to other methods.

Web service is an emerging technology in this decade for its openness and loosely coupled interaction among systems. Due to the proliferation of web services, more number of web services is available for similar functionality. QoS deals about the non-functional information of a Web services. Furthermore, QoS plays a vital role for differentiating web services which has similar functionality. Predicting the QoS value of a web service is an important process for web service discovery and selection. Due to the different network environment includes bandwidth, capacity and delay, the QoS value of a web service is differs from user to user. Therefore, QoS prediction is imperative for a recommendation system to provide best services based on QoS values. To achieve this, an enhanced collaborative filtering approach is introduced. In this approach, the PCC (Pearson Correlation Coefficient) is calculated for identifying the similar user and items. To increase the prediction accuracy, the user’s personalized degree of similarity is calculated and the Top-k users and items are identified. The confidence value computation helps to predict the missing values in the user-item matrix. By systematic integration of user-based and item-based methods, the final QoS values of a web services is predicted. The system has been tested with the invocation of real world web services, and the efficiency of the proposed approach is compared with the existing approaches. The MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) between the proposed and existing approaches shows the accurate prediction of the proposed approach.