Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

Domain experts' knowledge-based intelligent decision support system in occupational shoulder and neck pain therapy

Abstract: This research develops a fuzzy knowledge-based decision support system (FKBDSS) that measures and predicts the degree of severity of the work-related risk associated with shoulder and neck pain (SNP) that is a prevalent pain complaint in an occupational environment. Assessing the harshness of SNP is a dreary chore, since the risk factors are featured with imprecision, uncertainty and vagueness. Predicting SNP subjective risk level provides key decision support information to medical practitioners in diagnosis. The objective involves knowledge acquisition performed through literature analysis, traditional and concept mapping interviews with domain experts comprising neurologist, orthopaedist, psychologist and physiotherapist to identify risk factors that include mechanical, physical and psychosocial categories. The determination of ranking the relative factor importance has accomplished using analytic hierarchy processing (AHP) analysis. The linguistic variables that qualify risk levels are quantified using fuzzy set theory (FST) that provides linguistic and numeric value outputs to predict the hazard level of SNP.

Measurement of relative operational efficiency of SOEUs in India using data envelopment analysis

Abstract: A nonparametric approach to frontier analysis, data envelopment analysis (DEA) is applied in this work to evaluate the relative operational efficiency of state owned electric utilities (SOEU) in India. Two different models viz CCR model and BCC model are applied to evaluate the overall efficiency and technical efficiency. Twenty nine SOEUs in India are considered for the analysis and the relative operational efficiency scores are calculated. The results indicate that the performance of several SOEUs are sub-optimal, suggesting a potential for significant improvements in the operation so as to improve the overall efficiency. Also sensitivity analysis is carried out to investigate the effect of changes in the solutions of the model.

Application of Integrated IoT Framework to Water Pipeline Transportation System in Smart Cities

Abstract: The era of water pipelines is enduring an informational renovation to enhance performance, minimalize ruptures and spills, and rise safety and is fetching to resemble as an example of the data-enabled substructure. Pipelines come to the vision of public cognizance only when a leak occurs, prominent to a toxic spill, or result in an explosion that outlays live. The Internet of things is integrating sensing knowledge to monitor pressure, flow rate, pumping station parameters, temperature, viscosity, and other external parameters. In industrial enactments, the Internet of things progresses on top of the previously prevailing system, permitting for a transfer from “monitor and respond” to a prognostic and pre-emptive approach assisting upgraded decision making. Remote monitoring and intellectual control using IoT are vital criteria for exploiting production rate and process feasibility. Hence, in this paper, integrated IoT architecture for water pipeline system is developed, and implementing computing techniques is suggested to analyze abnormality at initial stage using fabricated smart IoT module with enhanced data communication.

Investigation and validation of solar photovoltaic-fed modular multilevel inverter for marine water-pumping applications

Abstract: This article discussed the development of a solar photovoltaic-fed modular multilevel inverter (MMI) with reduced switch count to operate an asynchronous motor drive for maritime applications. The proposed marine water-pumping system consist of a PV panel, an asynchronous motor drive, and modular inverter. The suggested topology can produce 11 levels of output using asymmetric DC sources. The proposed MMI consists of five DC sources, and they are powered by the PV panels. The primary advantage of the proposed topology is that it does not need any auxiliary circuit to produce the negative levels. Moreover, the active sources (PV panels) in the proposed system are reduced by implementing a modified single-input and multiple-output SEPIC converter. The power consumption by on-board pumping systems in maritime is estimated to be almost 50% of the total power. Taking this into account, this article investigates an adaptive fuzzy logic-based closed-loop control design for reducing the losses in the induction machine and thereby improving the efficiency of the system. Further, the performance of the proposed system is compared with the conventional PI controller, and from the results, it is proved that the proposed control system works effectively in reducing the losses as well as improving the efficiency of the system. The simulations are carried out in MATLAB/Simulink, and the experimental investigations are carried out in the laboratory. The obtained experimental results are similar to the simulation results.