International Journal of Intelligent Engineering and Systems

6

Authors: Pawan Whig, Syed Naseem Ahmad

: The Spice Model for photo catalytic sensor (PCS) proposed by Whig and Ahmad overcome several drawbacks like complex designing, non-linearity and long computation time generally found in Flow Injection Analysis (FIA) technique by Yoon-Chang Kim et al for the determination of Chemical Oxygen Demand (COD). FIA technique involves the complete analysis including sampling and washing. Flow Injection Analysis is analytical method for the measurement of chemical oxygen demand using photochemical column. This method uses a bulky setup and takes 10-15 minutes to get the output result which is a tedious and time consuming job. If conventional method is continuously used for a long time than it is stable only for 15 days. The purpose of this paper is to propose a new Quasi Floating Gate Photo Catalytic Sensor (QFGPCS) approach which has low power consumption and compared the results with the conventional models. The proposed model operates under sub threshold conditions which are appreciated in large integrated system design. The results of simulation were found to be fairly in agreement with the theoretical predictions. The results are exhibited near linear variations of parameters of interest with appreciably reduced response time.

7

Authors: Chintan Bhatt, C. K. Bhensdadia

Data Mining techniques are broadly utilized crosswise over numerous orders to recognize hidden patents, rules or relationships among gigantic volumes of information. Induction Tree, for example, C4.5 is the most favored technique since it functions well under any dataset set being utilized. Exponential ascent in the utilization of the internet because of informal organizations began to get enormous volume of information crosswise over various areas in brief timeframe. These attributes by which the colossal measures of informal organization information are produced make them to order as Big Data. When adapting to huge information (Big Data), the greater part of the current discretization methodologies won't be very productive with respect to implementation. The most effective method to separate significant data from huge information has been a famous open issue. In this paper, we are proposing new algorithm of decision tree in big data. At last, we have shown some result using weka.