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A large amount of data is accumulated by the health-care industry. This data contains effective patterns which enable efficient decision-making. These patterns often go unexplored. Various machine learning methods can be incorporated in such situation. This work uses various machine learning methods such as Decision Tree, MARS, Random Forest and TMGA to realize the data mining goals. Results show that the Decision Tree method predicts the diagnosis of heart disease most effectively from patient's data. The dataset used to carry on this research work is taken from the popular UCI repository and is known as the Cleveland Dataset. It is implemented on the R platform. [ABSTRACT FROM AUTHOR]

Trend of social networking sites is at peak, so ocean of data is being created and generated. Micro blogging sites are used by billions of individuals to express their opinions on different topics related to different fields. Micro blogging has become a dynamic platform of communication between Internet users. Twitter a micro blogging service, has become the main portal where users prompt their views, emotions and opinions. Twitter is the fundamental social networking website. Opinion mining and sentiment analysis is most trending hot topic with numerous multi applications ranging from simple to complex. With the speedy improvement and progress of social network websites, sentiment analyses have become the main central talk of every conversation. This paper presents a review of various research works done in this field. [ABSTRACT FROM AUTHOR]

As traffic and population is increasing, it's monitoring and automation is finding a scope for development and it is emerging as a lucrative field for research and development. Intelligent transportation systems (ITS) are advanced applications which aim to provide innovative services relating to different modes of transport and traffic management and enable various users to be better informed and make safer, more coordinated, and 'smarter' use of transport networks. Realizing its enormous potential in automation, this review work was built around ITS and its applications. As ITS majorly involves the Wireless Sensor Networks, it was also explored to some extent. Various architectures were explored and compared to deduce the strengths and weaknesses of proposed solution. [ABSTRACT FROM AUTHOR]

Groups of sensor nodes are called as sensor networks. They transmit sensed data to base station in cooperation with one another. An efficient use of power is important for increased network lifespan. Wireless sensor networks are tiny, light in weight, battery powered sensor nodes. Various parameters like clustering overhead, lifetime of network, energy hole, FND (first node dies) LND (last end dies) are optimized in WSN with the help of various proposed hybrid unequal clustering protocol. Another issue for data gathering in WSN is the hot spot or energy hole that are formed near sink node are also addressed. Various new emerging strategies laid stress on the best optimal usage of constrain resources like energy, memory and various other processing abilities. This paper addresses a review of different research works done in this area. [ABSTRACT FROM AUTHOR]

In VANET environment the data of consecutive vehicle position truly are discrete, so the key to the moving vehicle modeling is to efficiently reduces update frequency of the position data to progress the Major Attributes regarding Security like communication and database management load Privacy, authentication and confidentiality for all applications of VANET. Geograhically VANET might be of two types either Fully connected or sparsly connected. Its type depends on day time or saturation rate of market devices. Many solutions of security Problems in VANET exist but its implementation is very costly for both user and for Service Provider. [ABSTRACT FROM AUTHOR]