Institution
National Institute of Technology, Meghalaya
Education•Shillong, India•
About: National Institute of Technology, Meghalaya is a education organization based out in Shillong, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 503 authors who have published 1062 publications receiving 6818 citations. The organization is also known as: NIT Meghalaya & NITM.
Papers
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01 Jan 2020TL;DR: In this paper, the authors presented a layout of work in progress of proposed m-way balanced tree data aggregation approach for clustered wireless sensor networks that aggregates the data at each level of balanced tree instead of performed by the cluster head solely and also reduces the wake-up time period of cluster head.
Abstract: Energy efficiency has been the prime design issue for wireless sensor networks as sensor nodes are embedded with limited energy. Clustering algorithms are considered as energy-efficient approach for wireless sensor network. Cluster head nodes have been overburdened in most of clustering algorithms that result in load unbalanced network. Work of this paper presents a layout of work in progress of proposed m-way balanced tree data aggregation approach for clustered wireless sensor networks that aggregates the data at each level of m-way balanced tree instead of performed by the cluster head solely and also reduces the wake-up time period of cluster head.
1 citations
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TL;DR: In this article, the authors applied various machine learning algorithms such as logistic regression, a decision tree classifier, a random forest classifier and a naive Bayes classifier on a relevant dataset and verified their results with the cross-validation method.
Abstract: We attempt to predict the accidental fall of human beings due to sudden abnormal changes in their health parameters such as blood pressure, heart rate, and sugar level. In medical terminology, this problem is known as Syncope. The primary motivation is to prevent such falls by predicting abnormal changes in these health parameters that might trigger a sudden fall. We apply various machine learning algorithms such as logistic regression, a decision tree classifier, a random forest classifier, K-Nearest Neighbours (KNN), a support vector machine, and a naive Bayes classifier on a relevant dataset and verify our results with the cross-validation method. We observe that the KNN algorithm provides the best accuracy in predicting such a fall. However, the accuracy results of some other algorithms are also very close. Thus, we move one step further and propose an ensemble model, Majority Voting, which aggregates the prediction results of multiple machine learning algorithms and finally indicates the probability of a fall that corresponds to a particular human being. The proposed ensemble algorithm yields 87.42% accuracy, which is greater than the accuracy provided by the KNN algorithm.
1 citations
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01 Jan 2018TL;DR: This paper provides a detailed performance study of an IGBT-based modified full-bridge inverter topology from the aspect of single-phase transformerless grid-connected PV system application to validate suitability in the transformerlessgrid-connected application.
Abstract: Solar photovoltaic (PV) systems are getting more and more widespread due to the recent price reduction in modules and technological developments of power electronics devices to be used in designing power conditioning unit. Generally, a strong affinity in grid-connected PV inverter topology is to use transformer in the grid interface. However, due to transformer, systems become bulky and involve additional losses. The elimination of the transformer abolishes galvanic isolation between the PV system and the utility grid, thus treating from the danger of direct current (dc) injection into the grid. Therefore, the choice of a proper topology for transformerless grid-connected application is crucial to avoid undesirable operational effects. This paper provides a detailed performance study of an IGBT-based modified full-bridge inverter topology from the aspect of single-phase transformerless grid-connected PV system application. Detailed simulation results under different environmental conditions are presented to validate suitability in the transformerless grid-connected application.
1 citations
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01 Oct 2016TL;DR: The presented model is an attempt to enable the analytical model to take into account the non-linear nature of ferromagnetic material and results for radial and tangential components of air-gap magnetic field along with relative permeability variation in stator core for no load and on load have been presented.
Abstract: Permanent Magnet (PM) motors, among various type of motors have high energy density. This features makes PM motors favorable choice for application involving high torque and volume constraints such as electric vehicles. While running the vehicle at high speed PM motors are made to operate in a large speed range. During the operation many a times motor core gets saturated. In this paper, an analytical model for surface mounted PM motor considering the non-linear behavior of motor core has been presented. The presented model is an attempt to enable the analytical model to take into account the non-linear nature of ferromagnetic material. Material property has been included in the analytical model in a novel way while defining boundary conditions between different regions of the motor. Results for radial and tangential components of air-gap magnetic field along with relative permeability variation in stator core for no load and on load have been presented in comparison to the results obtained from finite element analysis.
1 citations
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TL;DR: A model for evaluating non-damaging flow for a set of sub basins in a river system is presented in this paper, where linear programming technique incorporating multiple inflows routing scheme is employed to evaluate upstream flow conditions necessary for satisfying specified downstream flood flow conditions.
Abstract: A model for evaluating non damaging flow for a set of sub basins in a river system is presented. Linear Programming technique incorporating multiple inflows routing scheme is employed to evaluate upstream flow conditions necessary for satisfying specified downstream flood flow conditions. Non damaging flow for the sub basins are determined by using river system properties. The model is applied to a river system in India having flows from gauged and ungauged sub basins; flow contributions from the ungauged basins are estimated by using unit hydrograph technique. Peak flow studies involving major and minor sub basins indicate relative importance of the basins in the study area. Results obtained in the study depict variations in the non-damaging flow with the flow in the main channel. Model applications show that for flood with peaks exceeding 7566 m 3 /s regulating intervening basins only may not lead to safe flow at the downstream section(s). The model allows evaluating effectiveness of controlling the intervening basins in a river system; model applications to a real life river system yield results that are useful in adopting flood control measures for the study area.
1 citations
Authors
Showing all 517 results
Name | H-index | Papers | Citations |
---|---|---|---|
Sudip Misra | 48 | 535 | 9846 |
Robert Wille | 43 | 457 | 6881 |
Paul C. van Oorschot | 41 | 150 | 21478 |
Sourav Das | 30 | 174 | 4026 |
Mukul Pradhan | 23 | 53 | 1990 |
Bibhuti Bhusan Biswal | 20 | 155 | 1413 |
Naba K. Nath | 20 | 39 | 1813 |
Atanu Singha Roy | 19 | 48 | 1071 |
Akhilendra Pratap Singh | 19 | 99 | 1775 |
Abhishek Singh | 19 | 107 | 1354 |
Vinay Kumar | 19 | 130 | 1442 |
Dipankar Das | 19 | 67 | 1904 |
Gayadhar Panda | 18 | 123 | 1093 |
Gitish K. Dutta | 16 | 26 | 1168 |
Kamalika Datta | 15 | 69 | 676 |