Ganga Institute of Technology and Management

Jhajjar, India

Ganga Institute of Technology and Management

Jhajjar, India

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Bhatia R.,Ganga Institute of Technology and Management
Proceedings - 2012 2nd International Conference on Advanced Computing and Communication Technologies, ACCT 2012 | Year: 2011

The advances in data collection have generated an urgent need for techniques that can intelligently and automatically analyze and mine knowledge from huge amounts of data. The Knowledge Discovery in Databases (KDD) is the process of extracting the knowledge from huge data collection. Data mining is a step of KDD in which patterns or models are extracted from data by using some automated techniques. Discovering knowledge in the form of classification rules is one of the most important tasks of data mining. Discovery of comprehensible, concise and interesting rules helps us to make right decisions. Therefore, several Machine Learning techniques such as Neural Network, Decision Tree Induction, K nearest neighbour and Bayesian approach have been applied for automated discovery of classification rules. Recently there have been several applications of genetic algorithms for successful discovery of concise and comprehensible rules with high predictive accuracy. © 2012 IEEE.


Korachagaon I.,Annasaheb Dange College of Engineering and Technology | Bapat V.N.,Ganga Institute of Technology and Management
Journal of Renewable and Sustainable Energy | Year: 2012

Solar energy is one of the most promising renewable energy sources. The availability of the solar energy potential data is very scarce and often not readily accessible. The main objective of this study was to estimate the monthly average global solar radiation at various locations for South America, by the generalized Iranna-Bapat's model. Iranna-Bapat's model is developed to estimate the value of global solar radiation at any location on earth surface. This model uses the most commonly measurable meteorological parameters such as ambient temperature, humidity, wind-speed, moisture for a given location. A total of 35 locations spread across the continent are used to validate this model. The computed values from Iranna-Bapat's model are compared with the measured values. Iranna-Bapat's model demonstrated acceptable results, and statistically displayed lower values of RMSEs. Therefore this model could be a good estimator for predicting the global solar radiation at other locations for South America, where such data is not available. © 2012 American Institute of Physics.


Korachagaon I.,Annasaheb Dange College of Engineering and Technology | Bapat V.N.,Ganga Institute of Technology and Management
Renewable Energy | Year: 2012

The data such as global solar radiation, air temperature, relative humidity, wind and moisture, was collected from 875 stations around the globe. Of which data from 210 stations fairly spread on the earth surface was used to develop the formula for estimating the monthly average daily global radiation on a horizontal surface. In this study, using air temperature, relative humidity, wind, moisture and few derived parameters as independent variables, the most accurate equations have been obtained. The results show that the general formula developed could be used for the estimation of solar radiation with the local site parameters. Thus developed models have been validated with remaining 665 data sites. Finally two candidate models have been proposed. These models are capable of covering 50% of the land area on earth surface between latitude ±30°, enabling estimation accuracy to 93% of sites, with an estimation error (RMSE) limiting to 15%. Thus it is envisaged that, the proposed equations (models) can be used to estimate the monthly average daily global solar radiation in area where the radiation data is missing or not available. This helps in assessing the solar energy potential over necessitated area. © 2011 Elsevier Ltd.


Korachagaon I.,Annasaheb Dange College of Engineering and Technology | Bapat V.N.,Ganga Institute of Technology and Management
IEEE-International Conference on Advances in Engineering, Science and Management, ICAESM-2012 | Year: 2012

Estimation of solar radiation is considered as the most important parameter for the design and development of various solar energy systems. But, the availability of the required data is very scarce and often not readily accessible. The foremost objective of the present study was to estimate the monthly average global solar radiation (GSR) at various locations for China province, by the generalized Iranna-Bapat's model. Iranna-Bapat's model is developed to estimate the value of global solar radiation at any location on earth surface. This model uses the most commonly measurable meteorological parameters such as ambient temperature, humidity, wind-speed, moisture for a given location. A total of 28 locations spread across China are used to validate this model. The computed values from Iranna-Bapat's model are compared with the measured values. Iranna-Bapat's model demonstrated acceptable results, and statistically displayed lower RMSE (<10%). Therefore this model could be a good estimator for predicting the global solar radiation at other locations for Chinese province, where such data is not available. © 2012 Pillay Engineering College.


Korachagaon I.,Annasaheb Dange College of Engineering and Technology | Bapat V.N.,Ganga Institute of Technology and Management
2012 International Conference on Computing, Electronics and Electrical Technologies, ICCEET 2012 | Year: 2012

Estimation of solar radiation is considered as the most important parameter for the design and development of various solar energy systems. But, the availability of the required data is very scarce and often not readily accessible. The foremost objective of the present study was to estimate the monthly average global solar radiation (GSR) at various locations for India, by the generalized Iranna-Bapat's model. Iranna-Bapat's model is developed to estimate the value of global solar radiation at any location on earth surface. This model uses the most commonly measurable meteorological parameters such as ambient temperature, humidity, wind-speed, moisture for a given location. A total of 57 locations spread across India are used to validate this model. The computed values from Iranna-Bapat's model are compared with the measured values. Iranna-Bapat's model demonstrated acceptable results, and statistically displayed lower RMSE (<10%) for many locations. Therefore this model could be a good estimator for predicting the global solar radiation at other locations for India, where such data is not available. © 2012 IEEE.


Korachagaon I.,Annasaheb Dange College of Engineering and Technology | Bapat V.N.,Ganga Institute of Technology and Management
International Journal of Applied Engineering Research | Year: 2011

Solar radiation is a primary driver for many physical, chemical and biological processes on the earth's surface. Complete and accurate solar radiation data at a specific region are quite indispensable to the solar energy related research. For locations where measured values are not available, a number of formulas and models have been developed to estimate solar radiation. This study aimed to develop new model(s) for estimating global solar radiation data using meteorological parameters. Measured solar radiation, air temperature, relative humidity, wind and moisture data from 210 sites around the earth was used for model development for estimating the monthly average daily global radiation on a horizontal surface. Several models and correlations that embrace such variables as the fraction of air temperature, relative humidity, wind and moisture, latitude, longitude and altitude have been selected. In this study, using air temperature, relative humidity, wind and moisture and derived parameters as independent variables, the most accurate equations have been obtained. The results show that the general formula developed could be used for the estimation of solar radiation with the local site parameters. After validation with 665 data sites on these models, finally two candidate models have been proposed. These models are capable of covering 50% of the land area on earth surface between latitude ± 30 o, enabling estimation accuracy to 93% of sites, with an estimation error (RMSE) limiting to 15%. Thus it is envisaged that, the proposed equations can be used to estimate the monthly average daily global solar in area where the radiation data is missing or not available. This helps in assessing the solar energy potential over large area. © Research India Publications.


Kumar P.,National Institute of Technology Hamirpur | Chauhan S.R.,National Institute of Technology Hamirpur | Aggarwal A.,Ganga Institute of Technology and Management
International Journal of Manufacturing Technology and Management | Year: 2015

Hard turning is a precise machining operation that imposes strict requirements on both the cutting and machine tools. During the last few decades, the application of hard turning has been increasing in various automotive industrial areas. With the development of new cutting tool, the precision and rigidity of machine tools have been improved to allow hard turning to become a viable process. The objective of this paper is to report a survey of the recent research progress in hard turning with cubic boron nitride tools in regard of machine tool, cutting tool, tool wear, tool geometry and surface issues. This paper report a survey of all the factors that affect the performance of hard turning process, in an attempt to achieve better understanding of hard turning process. A summary of the hard turning techniques is outlined and further a comparison of hard turning and grinding is discussed in brief. © 2015 Inderscience Enterprises Ltd.


Naik U.,k-Technology | Bapat V.N.,Ganga Institute of Technology and Management
Wireless Personal Communications | Year: 2013

Location estimation in a wireless local area network (WLAN) using received signal strength indication (RSSI) has gained considerable attention in recent years. In a conventional RSSI based indoor WLAN localization, mobile node position is estimated through access point (AP) placed at ceiling height. Researchers have proposed solutions for location estimation in line of sight (LOS) scenarios, by installing the AP at a fixed position. This paper demonstrates the improved location accuracy in LOS and obstructed line of sight (OLOS) scenarios by placing the AP at lower heights. The RSSI variations caused by shadow fading for changing AP heights are used to estimate the location accuracy. The localization performance is computed in terms of Cramer-Rao lower bound (CRLB) of range estimate under dynamic environments which is relatively less complex computation technique and is calibration free. Simulation results reveal that the proposed method has better performance than the multilateration with linearization for access point localization algorithm. The minimum mean localization errors are obtained by deploying the access point at 2 m height. The results also demonstrate that the indoor localization accuracy improves for higher order path loss exponent. © 2012 Springer Science+Business Media New York.


Naik U.,k-Technology | Bapat V.N.,Ganga Institute of Technology and Management
IET Conference Publications | Year: 2013

The location estimation techniques based on 802.11 b/g wireless local area network (WLAN) have received significant attention in recent years. In this paper we report Cramer-Rao Lower bounds (CRLB) for WLAN user location estimation in a computer laboratory. The CRLBs are computed by using real time radio signal strength measurements performed by user's mobile terminal. This distance error lower bound provides the reference for the accuracy of node localization. The numerical results shows that the mean location error is 1.30 meters and is better as compared to the localization technique using linear least square estimate. The experimental results also demonstrate that the location accuracy improves for higher values of path loss exponent.


Naik U.,k-Technology | Bapat V.N.,Ganga Institute of Technology and Management
Wireless Personal Communications | Year: 2014

This paper presents robust empirical path loss models to characterize indoor propagation for access point (AP) deployed at different heights. The proposed models are developed with wireless local area network infrastructure at 2.4 GHz. The models are backed by extensive received signal strength (RSS) measurements acquired in line of sight and obstructed line of sight regions. The models are developed for two conditions, viz; quasi realistic and realistic RSS measurements. The quasi realistic measurements are taken after suppressing human intervention and electrical interferences to minimum. While the realistic RSS measurements are made in presence of all the human interventions and electrical interferences. The shadow fading component for both quasi realistic and realistic conditions is statistically modeled with the dependency on AP height. The proposed technique can be applied with higher confidence level to the buildings with similar construction features where RSS measurements are made upon. The results reveal that the performance of the proposed propagation models is significantly higher than the existing International Telecommunication Union-path loss model. The results also demonstrate that the realistic path loss model is more robust than the quasi realistic model. © 2014, Springer Science+Business Media New York.

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