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Traffic congestion is one of the major challenges in smart cities due to rapid urbanization. In this paper, we study the problem of traffic congestion prediction in smart city transportation systems. While there are various methods to tackle this problem, most of them suffer from improper label generation. Therefore, motivated by such shortcomings, we propose an intuitive and logical solution where we consider several road-related factors for the effective prediction of traffic congestion. For the same, we consider two datasets from the CityPulse EU FP7 project and employed two well-known binary classifiers. Our results indicate that labels generated based on the hybridization of the average speed of vehicles and the number of vehicles plying on the road prove to be effective in properly discriminating congestion and non-congestion scenarios. Moreover, number of vehicles alone can produce significant discrimination as well. Furthermore, the cumulative distribution function (CDF) applied to the above-mentioned factors with respect to the labels generated also validates the effectiveness of our approach.

The technique of finding the optimal processing method to answer a query is called Query optimization, whereas a collection of various sites, distributed over a computer network is called Distributed Database. In Distributed Database, the site communicates with each other through networks. There are various issues arise during evaluation of query cost, among which the processing cost and a transmission cost are important. There are several algorithms developed to find the best possible solution for a particular query, but they all have their certain limitations. The optimizer is mainly concern on search space, search strategy, and the cost model. It primarily focuses on these three factors. The mining cost of a query depends on the order of evaluation of the operators, for the same query we can have different cost if the order is changed. Hence, to find the optimal cost for a particular query is emerging as an open challenge for many researchers. Therefore, the cost-based query optimization technique has emerged as an important concept for dealing with the query optimization. This paper explores the issues and challenges of query optimization in mining of distributed data.

This paper explores the various code smells or the so called bad code symptoms present in procedural C software. The code smells are analyzed in the light of aspect oriented programming. The intention is to handle the code smells with aspect oriented constructs as it offers more versatile decomposition techniques than the traditional modularization techniques, for software evolution and understandability. The code smells are described at the function and program level. The code smells are followed by the aspect oriented transformations that may be required in order to improve the code quality.

The emergence of semantic web will result in an enormous amount of knowledge base resources on the web. The efficient use of knowledge resource totally depends on internet search engines which do not only help organization who are involved in the development of web browsers but also international economy as a whole buy facilitating efficient transition, managing and sending appropriate results to the web browser user. It is observed that data flowing from internet is often vague and therefore there is need to develop technology which has to get relevant and focused information. The Knowledge base grid in semantic web is an important instrument to enhance the application domain of semantic web. using the semantic web technologies for the solution of the problems of the students in the knowledge based grid distributed environment is major challenging task where they can collect coordinate publish and share knowledge to get the the admission in the course according to their ability. they can get knowledge about different universities, colleges and institutions in the distributed environment within these they select different courses according to their ability for decision making for their career and also find jobs available in the different colleges, universities and institutions in the distributed environment.

Refactoring has become a well-known technique for improving the code in a way that preserves behavior. The application of refactorings during development process of an object oriented or procedure oriented software improves the design and therefore the quality of software. During the evolution of software it is a requirement to refactor them in order to make it more compatible and flexible with the new environment. Much work is being done in refactoring object oriented code with aspect oriented programming. But this paper describes the various types of refactoring being done on procedural codes for eg: C language and the utility of refactoring the procedural codes with the help of aspect oriented programming. The paper also proposes certain refactorings that could be achieved in a better way using AOP.

Multimedia database can be define as a collection of storage and retrieval systems, in which large amount of media objects are created, modified, searched and retrieved, where as Multimedia is the combination of text, image, graphics, animations, audio and video. The extension of database application to handle multimedia objects requires synchronization of multiple media data streams. Multimedia data mining refers to the extraction of implicit knowledge, data relationships, or other patterns which are not stored in multimedia files explicitly. The system's overall performance in retrieval can be increase by indexing and classification of multimedia data with efficient information fusion of the different modalities is mandatory. Apart from text retrieval, the current waves in web searching and multimedia data retrieval are the search for and delivery of 3D scenes, images, music and video. The content-based multimedia information retrieval provides new techniques and methods for searching various multimedia databases over the world.

Digital audio watermarking technique is a process of embedding perceptually transparent digital information into an original audio signal. Watermarking can be fragile or non fragile depends upon the user's requirements. The main concern of digital watermarking is to prove ownership as well as protection of the embedded information. This paper gives brief overview of existing audio watermarking techniques, their applications and future prospects of digital watermarking.

Today, Internet is a huge database which comprises of a large number of Web sites, search engines and other information. Due to the unstructured and semi structured data in the web pages, it is a challenging task for researchers to make a relevant and efficient search in warehouse of such type of database. Ontology may be a good mechanism for achieving this goal and Web Mining technique may be used to discover and extract meaningful or relevant information from the Web documents. In this paper, analysis of web usage mining has been made with the help of an example of sample data for which WebLog analyzer tool, “Web Log Expert” has been used and it has been appended with the development of an Ontology for an intelligent or efficient web and it’s relation with web usage mining. Finally, it also summarizes some other research challenges towards an intelligent machine and web environment.

The development of real life problem is not the key issue. Various information technologies available now a days. But the major issue is that to get more advantages of these technologies for academic purpose in distributed environment where faculty and students communicate with software technology rather then with individual. Knowledge Based Grid was introduced for publishing, managing, sharing and utilizing different amount of knowledge base resources on Semantic Web in distributed environment. Knowledge discovery from heterogeneous information sources available on knowledge Grid environment is a major challenging research and development issue. This paper mainly concerns all aspects of the knowledge discovery, sharing process and integrates grid data resource by ontology server for educational institutes and university in distributed environment.

Digital Right Management and copy-protection static techniques have been used to prevent unauthorized copying and illegal distribution of software products by the software publishers. Rigid licensing structure for software distribution used with most legacy systems, is becoming less popular and less useful due to increase in businesses which dependent on flexible software applications and change according to market environment. According to Business Software Alliance, software publishers lost several hundred billions USD in previous years due to copying of their products. Many defense mechanisms have been devised till date but the hobbyists or the black market leaders so called software pirates have always found a way out of it. This paper identifies the flaws in the existing defense mechanisms and examines social and technical challenges associated with handling software piracy prevention. The paper also characterized the currently used static licensing structure in software distribution along with its drawback and proposes a dynamic software licensing scheme which comprises software serial keys integrated with hardware token to provide an ethical optimal utilization of software to customer organization and initiates to stop software piracy.

The information retrieving from millions of data available on the computational resource is not a major challenge. But how to get relevant knowledge from the information through various information technologies available is the key issue and to utilize relevant knowledge outcomes from information for academic purpose in distributed environment where faculty and students communicate with software technology rather then with individual. Knowledge learning from heterogeneous information sources available on knowledge Grid environment is a challenging research and development issue. This paper mainly concerns all aspects of the knowledge discovery, learning, sharing process and integrates grid data resource by agents for educational institutes and university in distributed environment.