Flexible Data Streaming In Stream Cloud

Abstract: Most of the applications in some special domains such as Telecommunication systems, Share market, Fraud detection and network security which required online processing of incoming data. They produce very high incoming load which needs to process by multiple nodes. The current system is on single node bottleneck and with the static configuration and hence it is not able to scale with the input load. So in this paper we present stream cloud a high flexible data stream processing engine for processing bulky data stream. This is particularly suitable for applications in online transactions, monitoring financial data processing and fraud detection systems that require timely processing of continuous data. Stream cloud using novel parallelization technique which splits one query into sub queries which are independently allocates to individual nodes for execution. It is having some elastic protocols which is used to dynamic resource management and load balancing of incoming load. Keywords: Data stream, Load balancing, Elasticity, Scalability, Flexibility I. INTRODUCTION Number of applications where large amount of data need to be processed in quasi-real-time process which is having the limitations of store then process paradig

Design of optimal search engine using text summarization through artificial intelligence techniques

Natural language processing is the trending topic in the latest research areas, which allows the developers to create the human-computer interactions to come into existence. The natural language processing is an integration of artificial intelligence, computer science and computer linguistics. The research towards natural Language Processing is focused on creating innovations towards creating the devices or machines which operates basing on the single command of a human. It allows various Bot creations to innovate the instructions from the mobile devices to control the physical devices by allowing the speech-tagging. In our paper, we design a search engine which not only displays the data according to user query but also performs the detailed display of the content or topic user is interested for using the summarization concept. We find the designed search engine is having optimal response time for the user queries by analyzing with number of transactions as inputs. Also, the result findings in the performance analysis show that the text summarization method has been an efficient way for improving the response time in the search engine optimizations

An effective identification of crop diseases using faster region based convolutional neural network and expert systems

The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop