Browsing by Author "Kumar, K.P."

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    Mechanical and magnetic analysis of magnetostrictive disc brake system
    (2010) Kumar, K.P.; Kadoli, R.; Kumar, M.V.A.
    The present work is related to an electrically driven magnetostrictive brake for use in brake system of the vehicles, more particularly design of magnetostrictive actuator for moving friction pads in disc brake back and forth thus, capable of readily accomplishing intelligent braking functions similar to that achieved using antilock braking system. The detail of the mechanical and magnetic circuit design of magnetostrictive disc brake is elaborated here. �2010 IEEE.
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    Mechanical and magnetic analysis of magnetostrictive disc brake system
    (2010) Kumar, K.P.; Kadoli, R.; Kumar, M.V.A.
    The present work is related to an electrically driven magnetostrictive brake for use in brake system of the vehicles, more particularly design of magnetostrictive actuator for moving friction pads in disc brake back and forth thus, capable of readily accomplishing intelligent braking functions similar to that achieved using antilock braking system. The detail of the mechanical and magnetic circuit design of magnetostrictive disc brake is elaborated here. ©2010 IEEE.
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    Prediction of rock properties using grinding characteristics of ball mill
    (Inderscience Publishers, 2020) Ram Chandar, R.C.; Umamahesh, A.; Kumar, K.P.; Avinash, D.
    Knowledge of physico-mechanical properties of rocks is essential starting from the preliminary exploration to processing in mining projects. The strength properties of rocks considered necessary for mine planning and design, selection of equipment, use of suitable processing technique, etc. Sophisticated laboratory facilities are required to determine various properties of rocks using some international standards like ISRM, ASTM, etc., which is time consuming and costly affair. In this study, an attempt is to predict some of the rock properties like density, tensile strength using grinding characteristics of ball mill. Laboratory experiments conducted on samples of granite, limestone, slate and BHQ varying different parameters like quantity of feed, charge ratio, size of balls, grinding time, etc., at constant RPM of ball mill. Grinding characteristic curves used to obtain 25%, 50%, 80% cumulative passing sieve sizes. In addition, laboratory experiments carried out to find physico-mechanical properties like density, tensile strength, Protodyakonav's strength index, rebound hardness number. Regression analysis carried out with the data obtained from experiments. © © 2020 Inderscience Enterprises Ltd.
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    Privacy preserving data clustering using a heterogeneous data distortion
    (2019) Preethi, P.; Kumar, K.P.; Ullhaq, M.R.; Naveen, A.; Janapana, H.
    Modern age computation leads to huge amount of data. The whole data is analysed using data mining. In return, it made its path to disruption of the privacy of data owners. In order to achieve privacy on data we use Privacy Preserving Data Mining (PPDM). But when the privacy is maintained the data utility is decreased and vice versa. So, in order to maintain a balance in both privacy and data utility, Privacy Preserving Data Clustering (PPDC) using a Heterogeneous data distortion is introduced. In this article both original and perturbed data are analysed using K-means and density based clustering techniques and the results are compared to show the balance between privacy and utility of the data. � Springer Nature Singapore Pte Ltd. 2019.
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    Privacy preserving data clustering using a heterogeneous data distortion
    (Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2019) Preethi, P.; Kumar, K.P.; Ullhaq, M.R.; Naveen, A.; Hyma, H.
    Modern age computation leads to huge amount of data. The whole data is analysed using data mining. In return, it made its path to disruption of the privacy of data owners. In order to achieve privacy on data we use Privacy Preserving Data Mining (PPDM). But when the privacy is maintained the data utility is decreased and vice versa. So, in order to maintain a balance in both privacy and data utility, Privacy Preserving Data Clustering (PPDC) using a Heterogeneous data distortion is introduced. In this article both original and perturbed data are analysed using K-means and density based clustering techniques and the results are compared to show the balance between privacy and utility of the data. © Springer Nature Singapore Pte Ltd. 2019.