Faculty Publications
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Publications by NITK Faculty
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Item An improved web page recommendation system using partitioning and web usage mining(Association for Computing Machinery acmhelp@acm.org, 2015) Chanda, J.; Annappa, B.There are different types of hypertext documents available on the Internet. Accessing relevant information and serving useful information to the user from the Internet has become a complex and expensive task. To make this process simpler, one of the widely used recommendation systems is item based collaborative filtering recommendation system which predicts web pages based on the browsing activity of the user on the Internet and recommends web pages as per their interests. There are certain challenges in these systems like sparsity and scalability, the proposed approach overcomes these problems. The proposed approach uses weighted kmean clustering instead of simple k-mean clustering and the obtained clusters are partitioned on the basis of similarity which helps in reducing the processing time of recommendation generation. Clustering and partitioning enhances the existing item based collaborative filtering recommendation system. The MovieLens data set is used for demonstrating the proposed approach. The performance of the proposed approach is evaluated using various metrics. The result shows that the proposed approach is 30% efficient in terms of root mean square error and 21% effective in respect of mean absolute error analysis and the accuracy measures factors like precision, recall and F-measure are found to have higher values than the existing item based collaborative filtering recommendation systems. © 2015 ACM.Item Simulation of varada aquifer system for sustainable groundwater development(2008) Ramesh, H.; Mahesha, A.Groundwater flow modeling has been used extensively worldwide with varying degrees of success. The ability to predict the groundwater flow is critical in planning and implementing groundwater development projects under increasing demand for fresh water resources. This paper presents the simulation of the aquifer system for planning the groundwater development of Varada basin, Karnataka, India using the Galerkin finite-element method. The government of Karnataka State, India is implementing the World Bank assisted project, "Jal Nirmal" for a sustainable development of the region, thereby ensuring a safe supply of drinking water to the northern districts of the state. Varada basin is one of the beneficiaries of the project in Haveri district. Field tests carried out in the study area indicate that the region is predominantly a confined aquifer with transmissivity and storage coefficients ranging from 5.787×10-6m2/s (0.500 m2/day) to 4.213×10-3m2/s (3.640×102m2/day) and 0.011-0.001× 10-2, respectively. This study mainly emphasizes the spatial and temporal variability of groundwater potential under different developmental scenarios. The model predictions were reasonably good with correlation coefficients ranging from 0.78 to 0.91 with the root mean square error of about 0.46-0.78 during calibration and validation. The stated accuracies are based on comparisons between measured and calculated heads. The outcome of the study would be a useful input for the conjunctive use of surface water and groundwater planning for the sustainable development of the region. © 2008 ASCE.Item Waveform agile sensing approach for tracking benchmark in the presence of ECM using IMMPDAF(Czech Technical University, 2017) Satapathi, G.S.; Srihari, P.This paper presents an efficient approach based on waveform agile sensing, to enhance the performance of benchmark target tracking in the presence of strong interference. The waveform agile sensing library consists of different waveforms such as linear frequency modulation (LFM), Gaussian frequency modulation (GFM) and stepped frequency modulation (SFM) waveforms. Improved performance is accomplished through a waveform agile sensing technique. In this method, the selection of waveform to be transmitted at each scan is determined, by jointly computing ambiguity function of waveform and Cramer-Rao Lower Bound (CRLB) matrix of measurement errors. Electronic counter measures (ECM) comprises of stand-off jammer (SOJ) and self-screening jammer (SSJ). Interacting multiple model probability data association filter (IMMPDAF) is employed for tracking benchmark trajectories. Experimental results demonstrate that, waveform agile sensing approach require only 39:98 percent lower mean average power compared to earlier studies. Further, it is observed that the position and velocity root mean square error values are decreasing as the number of waveforms are increasing from 5 to 50.Item Improved cross sample entropy with error-metric based cardiac variability time series evaluation(Springer Science and Business Media B.V., 2024) Sharma, K.; Sunkaria, R.K.; Marwaha, P.The cardiac rate variability analysis is a tool used to diagnose pathological and physiological variations in subjects in the premature stages. The cross-sample entropy (CSE) measure is used to analyze cardiac variability to diagnose cardiovascular diseases. In the proposed work, CSE is evaluated to detect arrhythmia subjects. It has been observed that CSE is restricted by a fixed threshold and any distance measure for cardiac disorder detection. In the proposed work, a new measure, named the error-metric cross sample entropy (E-metricCSE), is introduced to detect various cardiac disorders by using dynamic threshold and an error metric, root mean square error (RMSE). It signifies that the use of the RMSE makes the proposed algorithm most convenient for noise free data when compared to a distance metric. Different sets of MIX (Q) processes are executed on both real and simulated data to test the effectiveness of the proposed method. It is further noticed that the proposed algorithm is more consistent and more effective to quantify pathological and physiological subjects than the original CSE. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.