One of the ways of test data generation is using the path-oriented (path-wise) test data generator. This generator takes the program code and test adequacy criteria as input and generates the test data in order to satisfy the adequacy criteria. One of the problems of this generator in test data generation is the lack of attention to generating the diagnostic test data. In this paper a new approach has been proposed for path-oriented test data generation and by utilizing it, test data is generated automatically realizing the goal of discovering more important errors in the least amount of time. Since that some of the instructions of any programming language are more error-prone, so the paths that contain these instructions are selected for perform test data generation process. Then, the input domains of these paths variables are divided by a divide-and-conquer algorithm to the subdomains. A set of different subdomains is called hypercuboids, and test data will be generated by these hypercuboids. We apply our method in some programs, and compare it with some previous methods. Experimental results show proposed approach outperforms same previous approaches.

Neutrosophic set is a power general formal framework, which generalizes the concept of the classic set, fuzzy set, interval valued fuzzy set, intuitionistic fuzzy set, and interval intuitionistic fuzzy set from philosophical point of view. In Geographical Information Systems (GIS) there is a need to model spatial regions with indeterminate boundary and under indeterminacy. In this paper, we first gives fundamental concepts and properties of a neutrosophic spatial region.

Wireless sensor networks (WSN) are widely developed to monitor different phenomena in a variety of areas including nature, medical centers, home automation, industrial and military applications. Such development in many different fields, raises important security issues related to the reliability of the WSNs. Due to the resource constrained nature of the WSNs, these networks are the target of many different types of attacks and prone to failure. In this paper, we consider the collision attack. An attempt has been made to measure the impact of the collision attack on the performance of WSNs under variety scenarios performed by the attackers. The main contribution of this paper is to present that although the attack does not consume much energy of the attacker, it can highly disrupt the normal operation of the target sensor networks. The implementation of the proposed attack model has been done by using NS2 network simulator.

Websites are very important means of communication in this current era of information technology. Different institutions / organizations put lots of efforts to portray complete information on beautifully designed websites. Organizations these days concerned more in providing users with all facilities online through websites, which act as an interface through which a user can get his work done without physically visiting the organization. With this the responsibility of the designer and the concerned institutions / organizations increases manifold so that the websites behavior should remain interactive and quick enough for the user to avail all facilities through websites comfortably. Speed and size of a Website are directly related with each other. Size is very important when targeting users that don't have optimal Internet connections. Author in this paper developed an online tool using .NET Framework using C# to study webpage size as Design issue in various categories of the websites like Government, Commercial, Educational, Social networking and Job portals. The automated tool developed by author function on the basis of the different standards prescribed in W3C and prescribed in analysis performed in [2]. The tool act like a parser and renders the complete code of the website and then produces result by examining the memory requirements of the component files that contribute to the total size of the website. The results produced shows that out of the five different categories of websites, it can be concluded that none of the website categories undertaken follows the recommended standards of the World Wide Web consortium showing huge violation as far as recommended page size for different websites is concerned.

Mobile learning (M-learning) becomes revolutionary way to educate the world with the mass advancement in information and communications technology (ICT). It is difficult to deal with m-learning due to increasing number of users, services, education contents and resources and modes to deploy. Cloud computing, with its dynamic scalability and virtualized resources usage, is widely deployed for several applications in many organizations. It has a significant impact in the educational and learning environment. This paper presents a new model for mobile learning system in cloud computing environment that is enriched with high performance computing (HPC) and graphical processing unit (GPU) cluster infrastructure. This model aggregates the power with new technologies to implement M-leaning process more effective with high performance and quick response.

This paper presents the integration of color histogram and DBC co-occurrence matrix for content based image retrieval. The exit DBC collect the directional edges which are calculated by applying the first-order derivatives in 0º, 45º, 90º and 135º directions. The feature vector length of DBC for a particular direction is 512 which are more for image retrieval. To avoid this problem, we collect the directional edges by excluding the center pixel and further applied the rotation invariant property. Further, we calculated the co-occurrence matrix to form the feature vector. Finally, the HSV color histogram and the DBC co-occurrence matrix are integrated to form the feature database. The retrieval results of the proposed method have been tested by conducting three experiments on Brodatz, MIT VisTex texture databases and Corel-1000 natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP, DBC and other transform domain features.

Cancer is a class of diseases characterized by out-of-control cell growth. There are over 200 different types of cancer, and each is classified by the type of cell that is initially affected. This paper discusses the technical aspects of some of the ontology-based medical systems for cancer diseases. It also proposes an ontology based system for cancer diseases knowledge management. The system can be used to help patients, students and physicians to decide what cancer type the patient has, what is the stage of the cancer and how it can be treated. The system performance and accuracy are acceptable, with a cancer diseases classification accuracy of 92%.

With the rapid advancement in technology, smart homes have become applicable and so the need arise to solve the security challenges that are accompanied with its operation. Passwords and identity cards have been used as traditional authentication mechanisms in home environments, however, the rise of misuse of these mechanisms are proving them to be less reliable. For instance, ID cards can be misplaced, copied or counterfeited and being misused. Conversely, studies have shown that biometrics authentication systems particularly Iris Recognition Technology (IRT) and Fingerprint Recognition Technology (FRT) have the most reliable mechanisms to date providing tremendous accuracy and speed. As the technology becomes less expensive, application of IRT& FRT in smart-homes becomes more reliable and appropriate solution for security challenges. In this paper, we present our approach to design an authentication system for smart homes based on IRT, FRT and ARM7TDMI-S.The system employs two biometrics mechanisms for high reliability whereby initially, system users must enroll their fingerprints and eyes into the camera. Iris and fingerprint biometrics are scanned and the images are stored in the database. In the stage of authentication, FRT and IRT fingerprint scan and analyze points of the user's current input iris and fingerprint and match with the database contents. If one or more captured images do not match with the one in the database, then the system will not give authorization.