Aims: Netizens share their personal experiences, opinions at the review sites, discussion groups, blogs, forums and etc. With the rapid growth of technology, now-a-days almost everyone uses internet. Opinions are important because whenever a person needs to take a decision, helikes to hear others’ opinions. Quotes of the attitude may be generally positive or negative. We propose a system for classifying text sentiment based on Neural Networks classifier. In this paper, we focus on classifying product reviews according to the opinion and the value judgment they posses, into two polarities, positive and negative, using the multilayer neural network. We also address opinion prediction application for the products that are being launched in future. The product features, given as input to recursive neural network are used to predict the opinions, which are expected from customers. The opinion prediction is done using recurrent neural network with the help of back propagation with time (BPTT) algorithm. Place and Duration of Study: Department of Computer Science and Engineering, Sri Sairam College of Engineering, Anekal, Bangalore between July 2014 and December 2014. Methodology: We experimented on 500 opinions, among them 400 were used as training set, and 100 were taken to be testing set, for each type of mobile (Nokia Lumia 720, LG G3). Results: For each mobile type we achieved up to 85% of correct classification of opinion reviews. Conclusion: We presented a system for determining text sentiment of product reviews by classifying them using Neural Network. The method uses feed-forward Neural Network with ten hidden layers. From the presented results, it can be seen that, a new approach is developed categorizing product reviews in 2 classes in the context of opinion mining. Experiments conducted on training sets show that with our approach we are able to extract relevant feedback from a specific domain of products. We compared our proposed opinion classification algorithm to standard algorithm BPNSO which showed the results are good between 60% to 80%.
In the literature of information measure, there exist many well known parametric generalized information measures with their merits and limitations. In the present paper a ‘useful’ R-norm information measure of type and degree is introduce and characterized axiomatically. This new measure is parametric generalization of ‘useful’ R-norm information measures introduced and characterized by the authors earlier refer to Hooda et al. . Properties of the new generalized ‘useful’ R-norm information measure of type and degree have also been studied. The new measure has been applied in studying the lower and upper bounds of a generalized ‘useful’ R-norm mean codeword length.
In this article, we study the conformal mean curvature equation in Thurston’s geometries of Sol space. The classification of revolution surfaces with mean curvature was obtained by studying the corresponding profile curves in Sol space. According to the characteristics of the conformal metric, the revolution surfaces in Sol manifold were obtained through a profile curve revolving respectively. Assumes that the mean curvatures of these revolution surfaces were certain functions, the corresponding differential equations about the profile curves can be obtained. By solving these differential equations, the classification of the revolution surfaces with conformal mean curvature was achieved.
Mobile Ad Hoc Networks (MANETs) is a growing technology which magnetizes many useful applications because nodes can communicate with each other and join and leave network without any predetermined network infrastructure. This behavior of MANETs makes it vulnerable to various different types of attack, so security solutions must be implemented for such environment. Developing adequate countermeasures requires understanding and classification of these attacks. In this paper a comprehensive survey of MANET attacks is performed, and a new classification scheme that is based on the security service targeted by the attack, namely, confidentiality, integrity and availability is proposed. This new classification will provide a better understanding to MANETs attacks that can aid in developing a security service oriented detection and prevention techniques.
The impact of globalization coupled with the pressure by recent economic downturn have stirred increased customer outlook on availability, scalability and efficiency to enterprise information technology (IT) solutions. The increasing interest of a broad based business leaders and organisations centre on how best cloud computing can contain these requirements to reduce or eliminate the huge capital outlay for infrastructure ownership, increase efficiency, ensure higher returns on investment (ROI), dynamic provisioning and utility – such as pay-as-use services. However, the slow adoption of cloud computing by many organizations such as those with high business economic drives and those with very sensitive security concerns raises huge concerns. A number of these enterprises along with some information security professionals have expressed fear of the cloud, stating their unflinching consciousness on security and privacy issues associated with this new computing platform for the next generation of the Internet. Thus, this research paper analyses the level and nature of cloud service adoption and deployment among IT practitioners and organizations in Nigeria. It further identified the various barriers (security, privacy and forensic issues) generating fear and inhibiting the full adoption and deployment of this new IT paradigm. The methodology takes a quantitative approach and the results of which analysis were discussed and interpreted in relation to the key issues of cloud service adoption and deployment to achieve the research aim of the paper. The results of the research survey conducted provisions the research outcomes which attempts to demystify cloud computing and most associated risks in the virtualized cloud environment by pining the issues of outsourcing data and its control via external data storage as top ranking among others. Further, Proper implementation of security, privacy and forensic measures were advocated to be seen not just as the cloud providers’ sole concern, but the responsibilities of all consumers of the services. Finally, arguments to back-up the need for progression in this new paradigm shift were elucidated.
Motivated by the results of J. Kou, et al. 2007  which is a family of iterative methods having third order of convergence in general and optimal fourth order of convergence for a particlue case, in this paper, a new class of optimal fourth-order iterative methods is obtained based on that and by using the weight function approach. The convergence analysis of our new class of iterative methods is presented in this paper. Moreover, several numerical examples are considered and compared with the available methods in the literature to confirm our theoretical results.
In this paper, we study the conditions satisfying (ξ, X)P = 0, P(ξ, X)S = 0, P(ξ, X) = 0, and P(ξ, X)P = 0 on a Lorentzian concircular structure manifold. According to these cases, (LCS)-manifolds are categorized and an example is used to demonstrate that the method presented in this paper is effective.