Faculty Publications
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Item Efficient fuzzy clustering based approach to brain tumor segmentation on MR images(2011) Arakeri, M.P.; Guddeti, G.Image segmentation is one of the most vital and significant step in medical applications. The conventional fuzzy c-means (FCM) clustering is the most widely used unsupervised clustering method for brain tumor segmentation on magnetic resonance (MR) images. However, the major limitation of the conventional FCM is its huge computational time and it is sensitive to initial cluster centers. In this paper, we present a novel efficient FCM algorithm to eliminate the drawback of conventional FCM. The proposed algorithm is formulated by incorporating distribution of the gray level information in the image and a new objective function which ensures better stability and compactness of clusters. Experiments are conducted on brain MR images to investigate the effectiveness of the proposed method in segmenting brain tumor. The conventional FCM and the proposed method are compared to explore the efficiency and accuracy of the proposed method. © 2011 Springer-Verlag.Item Performance Evaluation of Premium Services in Bangalore Metropolitan Transport Corporation (BMTC)(Elsevier B.V., 2016) Hanumappa, D.; Ramachandran, P.; Sitharam, T.G.; Lakshamana, S.; Mulangi, R.H.In this paper we are measuring the performance of Bangalore Metropolitan Transport Corporation (BMTC) specifically aiming at premium bus services of BMTC operating in Bangalore city. The performance measurement of premium bus services is done using two different approaches. Ratios were computed considering different operational and financial indicators and these ratios are benchmarked by considering the best performing units as the target to compare the bus depots performance. Further we studied the performance of bus depots using data envelopment analysis (DEA). Our analysis indicated that most of the depots are efficient where as depot 13 have significant opportunities for improvements. © 2016 The Authors.Item An improved user authentication scheme for telecare medical information systems(Institute of Electrical and Electronics Engineers Inc., 2018) Madhusudhan, R.; Nayak, C.S.Medical field is one of the many important fields that keeps growing day by day. Since health care is essential for every human being, development of medical systems play a vital role in the overall development of society. With the help of the Internet, medical services are provided through TMIS (Telecare Medicine Information System). During the process, information related to patient is transmitted over open channels and ensuring safety to this information is an essential task. For this, a number of remote user authentication schemes have been proposed and evolved over the time. Chen et al. proposed an authentication scheme for TMIS in 2018. Through analysis of their scheme, it has been shown that their scheme cannot withstand user impersonation attack, server masquerading attack, password guessing attack and cannot preserve user anonymity. These weaknesses have been presented in this paper. In addition to this, an improved scheme has been proposed which overcomes the aforementioned security defects. Also, this paper discusses the security analysis of the proposed scheme, which proves that it is more secure and can be practically implemented. © 2018 ACM.Item Exploring the Application of Data Envelopment Analysis in the Evaluation of Public Transport Organizations(Springer Science and Business Media Deutschland GmbH, 2022) Praveen Kumar, P.P.; George, V.; Mulangi, R.H.The work provides details on a study on performing a comparative analysis of productivity and efficiency of selected public transport organizations in India. The data envelopment analysis (DEA) method was used in this study using sub-routines specially developed in the open-source R programming environment used in statistical analyses. The DEA approach is a commonly adopted non-parametric method of analysis for the measurement of efficiency-related characteristics. Based on the availability and consistency of information, selected input and output data on 27 State Road Transport Undertakings (SRTUs) were used in this study. The scores of efficiencies were then computed using an input-oriented DEA model with constant return to scale. Finally, the analysis was used to distinguish between efficient and inefficient SRTUs based on weights assigned to peer units. The results of this study indicate that only 10 out of the 27 SRTUs performed well. It was also found that the performance parameters could be improved by reducing the quantity of input-related parameters in order to maintain the same level of output. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Efficiency improvement on the multicrystalline silicon wafer through six sigma methodology(2012) Saravanan, S.; Mahadevan, M.; Suratkar, P.; Gijo, E.V.Crystalline silicon solar cell technology continues to be dominant in the photovoltaic (PV) technology due to its novel process flow and the clear understanding of the material. Being a mature material-based technology; on the one hand, it has quite a few opportunities for improvement, on the other hand, the expansion of solar energy should depend on this technology. Due to increase in the global energy consumption and high competition level in the market, it has become necessary to show significant improvement in the performance of the present process/product. The demand for high efficiency solar cells at low costs with shorter cycle times forced the manufacturing industries to improve their processes by applying systematic methodologies such as Six Sigma. This paper illustrates the importance of anti-reflective coatings (ARCs) on the silicon solar cell processes and the successful implementation of Six Sigma to improve the efficiency of the silicon solar cells. The different phases of the Six Sigma DMAIC approach applied to the process and the results are interpreted. © 2012 Copyright Taylor and Francis Group, LLC.Item Removal of ammonia and particulate matter using a modified turbulent wet scrubbing system(2012) Byeon, S.-H.; Lee, B.-K.; Raj Mohan, B.Conventional scrubbers are typically modified to serve the needs of modern industries that discharge effluents that cause synergetic, adverse effects on the environment. We designed and developed a modified turbulent wet scrubber (MTWS) to remove air pollutants as they emerge from a coal furnace. Experiments were conducted to estimate the pressure drop and the efficiencies of ammonia gas and particulate removal via the MTWS. The optimum water levels and gas flow rates for effective scrubbing of ammonia gas at different concentrations and particulate matter at different feed rates were estimated. For ammonia gas at a concentration of 45 ppm, a gas flow rate of 3.5 m 3/s and a water level of 58 cm in MTWS and position B (central position of the nozzle) in the water level of the nozzle yielded efficient ammonia gas removal for the given time. Similarly, for a fly ash feeding rate of 140 mg/min, the same gas flow rate and water level in the MTWS yielded high efficiencies even for particles at the submicron level. © 2012 Elsevier B.V. All rights reserved.Item Effect of oxygen enrichment of intake air on the performance and emission of single cylinder CI engine fueled with cardanol blends(Taylor and Francis Inc. 325 Chestnut St, Suite 800 Philadelphia PA 19106, 2015) Dinesha, P.; Mohanan, P.In this study, the effect of intake air enrichment on the performance and emission characteristics of a single-cylinder direct-injection diesel engine fueled with non edible oil namely Cardanol-diesel-methanol blend (B20M10) are investigated. With increase of intake air oxygen concentration, CO and HC decreased while brake thermal efficiency and NOx considerably increased. The maximum Brake Thermal Efficiency of 33.98% is obtained for B20M10 with 7% oxygen enrichment of intake air. Maximum NOx emission 20% is obtained for B20M10 with 7% oxygen enrichment for the full load condition. Decreases of 20% and 14.5% in CO emission are obtained for B20M10, over B20M10 with 7% oxygen enrichment, where as 76.8% and 74% decrease in hydrocarbon emission is obtained over B20M10 without oxygen enrichment.Item Effect of exhaust gas recirculation (EGR) on diesel engine using Simarouba glauca biodiesel blends(Regional Energy Resources Information Center (RERIC) enreric@ait.ac.th, 2015) Bedar, P.; Pandey, J.K.; Kumar, G.N.This article deals with the usage of non-edible Simarouba glauca (paradise) oil as a biodiesel for single cylinder diesel engine with application of exhaust gas recirculation (EGR) rates. Biodiesel blends B10, B20 with EGR rates of 10%, 15%, and 20% are used for different load conditions. Parameters like brake thermal efficiency (BTE), nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbons (HC) and smoke opacity were evaluated from the experimental study. The results show that Simarouba glauca biodiesel usage decreases HC, CO and smoke emissions with slight increase of NOx, also an improvement in the performance was observed for B10 blend. EGR rates 10% and 15% are beneficiated in terms of performance and emission but negative trend is observed for 20% EGR rate. On the whole it is concluded that a better trade-off between NOx and other emissions is attained with simultaneous application of EGR (15%) and biodiesel blend (B10) without compromising engine performance.Item Modeling and design of field programmable gate array based real time robust controller for active control of vibrating smart system(Academic Press, 2015) Parameswaran, A.P.; Ananthakrishnan, B.; Gangadharan, K.V.The current paper focuses on accurate mathematical modeling of a vibrating piezoelectric laminate cantilever beam theoretically as well as experimentally so as to obtain the best replication of the system dynamics on the software platform for simulation studies. The developed models were tested for accuracy in time as well as frequency domain by employing the sweep sine test. The focus of the study is on the flexural modes of vibrations of the cantilever beam. Here, modeling is focused on the first vibratory mode as it has been observed that the effects of felt vibrations would be maximum in terms of system stability and its operational efficiency when the excitation frequency matches with the first natural frequency of the system (fn1). This was validated by appropriate non-parametric modeling of the smart system by subjecting it to the Impact Hammer test. Development of accurate system models play an important role in designing and testing various control algorithms for reliable active vibration control (AVC). In the final stage, a real time active vibration robust controller was designed using a proportional derivative sliding mode control (PDSMC) technique and deployed on a Field Programmable Gate Array (FPGA) platform. The efficiency of the developed real time controller was proved in time as well as frequency domains by subjecting the closed loop system to harmonic excitations at first natural frequency as well as sweep sine test focussing on the first vibratory mode with the conclusion that the developed controller will function satisfactorily at higher modes of vibrations. © 2015 Elsevier Ltd.Item An extreme learning machine approach for modeling evapotranspiration using extrinsic inputs(Elsevier B.V., 2016) Patil, A.P.; Deka, P.C.Precise estimation of evapotranspiration is crucial for accurate crop-water estimation. Recently machine learning (ML) techniques like artificial neural network (ANN) are being widely used for modeling the process of evapotranspiration. However, ANN faces issues like trapping in local minima, slow learning and tuning of meta-parameters. In this study an improved extreme learning machine (ELM) algorithm was used to estimate weekly reference crop evapotranspiration (ETo). The study was carried out for Jodhpur and Pali meteorological weather stations located in the Thar Desert, India. The study evaluated the performance of three different input combinations. The first input combination used locally available maximum and minimum air temperature data while the second and third combination used ETo values from another station (extrinsic inputs) along with the locally available temperature data as inputs. The performance of ELM models was compared with the empirical Hargreaves equation, ANN and least-square support vector machine (LS-SVM) models. Root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE) and threshold statistics (TS) were used for comparing the performance of the models. The performance of ELM model was found to be better than the Hargreaves and ANN model. The LS-SVM and ELM displayed similar performance. ELM3 models, with 36 and 33 neurons in hidden layer were found to be the best models (RMSE of 0.43 for Jodhpur and 0.33 for Pali station) for estimating weekly ETo at Jodhpur and Pali stations respectively. The results showed that ELM is a simple yet efficient algorithm which exhibited good performance; hence, can be recommended for estimating weekly ETo. Furthermore, it was also found that use of ETo values from another station can help in improving the efficiency of ML models in limited data scenario. © 2016 Elsevier B.V.