No abstract

No abstract

<p>Agriculture is important for human survival because it serves the basic need. A well-known fact that the majority of population (≥55%) in India is into agriculture. Due to variations in climatic conditions, there exist bottlenecks for increasing the crop production in India. It has become challenging task to achieve desired targets in Agri based crop yield. Factors like climate, geographical conditions, economic and political conditions are to be considered which have direct impact on the production, productivity of the crops. Crop yield prediction is one of the important factors in agriculture practices. Farmers need information regarding crop yield before sowing seeds in their fields to achieve enhanced crop yield. The use of technology in agriculture has increased in recent year and data analytics is one such trend that has penetrated into the agriculture field being used for management of crop yield and monitoring crop health. The recent trends in the domain of agriculture have made the people to understand the significance of          Big data. The main challenge using big data in agriculture is identification of impact and effectiveness of big data analytics.  Efforts are going on to understand how big data analytics can be used to improve the productivity in agricultural practices. The analysis of data related to agriculture helps in crop yield prediction, crop health monitoring and other such related activities. In literature, there exist several studies related to the use of data analytics in the agriculture domain. The present study gives insights on various data analytics methods applied to crop yield prediction. The work also signifies the important lacunae points’ in the proposed area of research.</p>

Abstract-This paper presents a routing algorithm for computer network using mobile agents (Ant algorithm) and genetic algorithm. Ant algorithm is a class of Swarm Intelligence (SI) algorithms. SI is the local interaction of many simple agents to achieve a global goal. SI is based on social insect metaphor for solving different types of problems. Ant algorithm uses mobile agents called ants to explore network. Ants help in finding paths between two nodes in the network. Paths generated by ants act as input to Genetic Algorithm (GA). GA finds the set of suboptimal paths between nodes with the objective of minimum cost. This hybrid algorithm exhibits better performance when compared to basic ant algorithm.

A Brain Computer Interface (BCI) provides a communication path between human brain and the computer system. The major goal of BCI research is to develop a system that allows disabled people to communicate with other people, to control artificial limbs, or to control their environment. BCI is a challenging topic of computer vision research. It is extensively used by disabled people to communicate with other persons and helps to interact with the external environments. This paper provides an insight into object recognition by analyzing EEG signals in real-time. Three machine learning algorithms are implemented which are used for classification by supervised learning, namely Decision Trees, K-Nearest Neighbors and Support Vector Machine (SVM), multiple training sets and users are taken into account during the experiment and the efficiency of each algorithm is compared to suggest the best suited algorithm for this purpose.