Journal Articles
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Item Air pollution by inland waterways transportation in India(IJSRST, 2023-06) Mehrotra, Parag.; Veera SethilKumar G.Economy of any country depends on the existence of an efficient transport sector. There exists different modes of transportation such as railways, roadways, inland waterways, coastal shipping and airways. Sea freight is the best choice for international freight shipping because ships are used for transporting 80% of the world’s goods by volume. But at the same time, it becomes a great threat to human and ecosystem in the form of carbon emissions. Now-a-days, inland waterways are preferred over roadways and railways for domestic shipping in all the countries. India invests more in the development of inland waterways to have a cost effective cargo shipping. As the number of inland vessels increases, it may lead to the severe impact on environment due to more carbon emissions. Unless steps to reduce carbon emissions from vessels are adopted, it could increase by as much as 20% to 120% by 2050. This study reviews the inland waterways transportation of India and investigates the air pollution from inland vessels. Keywords: inland vessel; air pollution; carbon emission; transportation; environmentItem Analysis of band Selection algorithms for endmember extraction in hyperspectral Images(IOSR-JECE, 2016-12) Rashini, M; Veera SenthilKumar, G.This paper presents a novel approach of band selection for dimensionality reduction in Hyperspectral images (HSI). There are several methods of dimensionality reduction which can be further categorized into two groups; feature extraction and feature or band selection. Due to transformation in feature extraction, the critical information may have been distorted. Hence feature selection is preferable for dimensionality reduction because it preserves the relevant original information. Despite many algorithms exist for dimensionality reduction; it is even now a challenging task of selecting informative bands from the large volume data. The number of bands is estimated with the concept of Virtual Dimensionality (VD), because it provides reliable estimate. Bands are selected from hyperspectral images using Exemplar Based Band Selection (EBBS). End members are extracted from the selected bands using Simplex Growing Algorithm(SGA). The performance of EBBS is compared with the existing band selection techniques such as Constrained Band Selection (CBS) and Similarity Based Band Selection (SBBS) using the spectral angle distance as a measure. Keywords: Hyperspectral images, Virtual Dimensionality, Simplex Growing Algorithm, Exemplar based band selection, Spectral angle distance.Item Clustering based band selection for endmember extraction using simplex growing algorithm in hyperspectral images(Springer, 2017-03) Veera SenthilKumar, G.; Vasuki, S.With the advancement in technology, hyperspectral images have potential applications in the field of remote sensing due to their high spectral resolution. Despite the hyperspectral image providing abundant information, its analysis suffers from the problem of high dimensionality. Hence, Dimensionality Reduction (DR) is an essential task in all hyperspectral image analysis. Band Selection, which is one of the DR techniques, is still a challenging issue even though many algorithms have been developed. To provide remedy for this issue, this paper explores a novel approach for band selection using K-means clustering on statistical feature in hyperspectral images. The proposed method of clustering based band selection for DR is simple and accurate. A reliable estimate of number of bands to be selected is provided by Virtual Dimensionality (VD). Informative bands preserving maximum information are selected based on the statistical feature, the variance using K-means Clustering technique. Further, our proposed work involves the utilization of the effectiveness of Simplex Growing Algorithm (SGA) on endmember extraction in association with clustering based band selection. Using Fully Constrained Least Squares (FCLS) method, abundance fraction is estimated based on endmember signatures, which are derived using Endmember Extraction Algorithm (EEA). The proposed work is investigated and compared with that of N-FINDR and Vertex Component Analysis (VCA) algorithms. The performance of the proposed algorithm is evaluated using Root Mean Square Error (RMSE), Spectral Angle Distance (SAD) and computation time. Experimental results show that the proposed clustering based band selection with SGA endmember extraction algorithm reduces the average SAD by 8 to 10 % and the average RMSE by nearly 1 %, compared to that of N-FINDR and VCA algorithms. In terms of computation time, the proposed band selection based DR with SGA algorithm is seven times faster than conventional transform based DR with SGA algorithmItem Determination of absorption coefficients of different material(IJRAR.ORG, 2023-05) Puranik, Sanjay M.; Erande, Aparna.Linear and mass absorption coefficients and its related data for various soils have been determined using simple G.M. tube experiment. Strontium 90 continuous beta source is used for measurement of counts. Values are measured for aluminum absorber and then for soil samples. Among all soils, it is observed that Red soil absorbed maximum beta radiation.Item Hybrid noise removal in color images using wavelet shrinkage approaches of PURE-LET and Neighshrink SURE(2013-04) Karthikeyan, P.; Vasuki, S; Veera SenthilKumar, G.Image denoising is an indispensable task where the complication of noise is prevalent and the contrast of low cost surveillance camera is more over low due to various image acquisitions. For the past two decades, denoising is performed by the Wavelet transform. The proposed work presents a novel approach of denoising by Poisson Unbiased Risk Estimate- Linear Expansion of Threshold (PURE-LET) and Neighshrink-Stein’s Unbiased Risk Estimate (SURE) for mixed Poisson and Gaussian noise. Finally the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities are demonstrated. Neigh Shrink is an efficient image denoising algorithm based on the Discrete Wavelet Transform (DWT).The observed results reported here are in encouraging agreement.Item Library services in higher education institutions: issues and challenges during and after covid-19 period(Indian Journals, 2021-12-17) Rajanikanta, S.T.; Devendrappa, T.M.The purpose of writing this article is to create the awareness among the library professionals regarding the functionality of higher educational institutional libraries who preferred to serve their users during the period of covid-19 pandemic and to discuss the issues and challenges they have faced while confronting the tough situation and new techniques they used to beat the pandemic situation and at the same time the role played by library staff of higher educational institutions while providing information for needy users, to avoid the transformation of coronavirus during the transaction of library physical information resources/materials, library services to their users and also the precautionary measures to be taken to provide the service to reader or users.Item Maximin distance based band selection for endmember extraction in hyperspectral images using simplex growing algorithm(Springer, 2017-03) Veera SenthilKumar, G.; Vasuki, S.With the fast growing technologies in the field of remote sensing, hyperspectral image analysis has made a great breakthrough. It provides accurate and detailed information of objects in the image when compared to any other remotely sensed data. It is possible because of its high redundancy in nature. But this redundancy in hyperspectral images leads to high computational complexity in their analysis. Hence Dimensionality Reduction (DR) is a significant task in all hyperspectral image processing. DR can be achieved either by feature extraction or feature selection. Feature selection or Band selection is adopted in this paper because of no compromise in original data. Despite many algorithms that exist for band selection, this paper proposes a new concept of Maximin distance algorithm using Spectral Angle Distance (SAD) as distance measure for band selection. Virtual Dimensionality (VD) is used to provide the number of bands to be selected because it has been proved to be reliable estimate. Simplex Growing Algorithm (SGA) is deployed for endmember extraction in the experiment work. In order to evaluate the performance of the proposed band selection algorithm, the Spectral Angle Distance (SAD) and Spectral Similarity Value (SSV) are used as measures. The efficacy of our proposed algorithm has been proved from experimental results in comparison with Constrained Band Selection (CBS), Similarity Based Band Selection (SBBS), Clustering Based Band Selection (CBBS), Uniform Band Selection (UBS), Minimum Variance Principal Component Analysis (MVPCA) and Exemplar Component Analysis (ECA) and Firefly Algorithm Based Band Selection (FABBS).Item Quarantine of library materials and library services during covid-19 period(Indian Journals, 2021-09-18) Devendrappa, T.M.; Rajanikanta, S.T.The purpose of writing this article is to create awareness among the library professionals during the period of covid-19 spread across the world. The need of information is very essential and this information played a major role in identifying the vaccine for Coronavirus also. Similarly, providing information for needy people in society is also necessary to avoid the transmission of Coronavirus during the transaction of library physical information resources/materials, library services to their users. What are the precautionary measures to be taken and how to quarantine the library materials which may be infected by reader or user. The process and procedure of quarantine of library materials and services, these issues have been discussed in this article.Item Segmentation of color images using EM Cost with spatial refinement algorithm on MBWT Features(IJCSET, 2011-03) Vasuki, S.; Veera SenthilKumar, G.; Ganesan, L.This paper proposes a novel technique to segment the color images combining M-Band Wavelet transform(MBWT) and Expectation Maximization (EM) with cost spatial refinement algorithm. One of the drawbacks of standard wavelets is that they are not suitable for the analysis of high frequency signals with relatively narrow bandwidth. This drawback has been overcome using MBWT. Also M-band wavelet decomposition yields a large number of sub bands which is required for improving the performance accuracy. The proposed algorithm first decomposes the input image into sixteen subimages by applying MBWT. Then, median feature is computed for each subimage and maximum energy subimage is chosen as the appropriate feature space on which EM with cost spatial refinement algorithm is applied. This new combined algorithm produces very good segmentation results by taking advantage of M-Band Wavelet feature extraction and EM with cost spatial refinement algorithm. The segmentation result is more homogeneous and quite consistent with the visualized color distribution in the objects of the original images compared to Fuzzy C means and K means spatial refinement algorithms. Also EM with cost spatial refinement algorithm needs less computational time compared to other clustering algorithms.Item Selection of reference management tools for creation and managing the references for academic purposes: A Comparative study(SSARSC, 2016-07) Devendrappa, T.M.; Dhingra, Shweta.; Rigzin, Sonam.With changing times the publishing industry has adopted various standards of reference, bibliographic standards in publishing the electronic content such as books, articles, theses and dissertation, websites, data, e-publications, videos, white papers and more. Managing of such references is becoming challenging day by day for users. To overcome this problem, many references management tools are available in IT environment to collate and manage citations and references to help the users, research scholars and faculty. However with the advent of reference management tool. It has been possible to correct format for citing references in research papers. It is also important to remember that scholars don't have to wed their self to any one tool as each has its pros and cons, and one can use different tools for different purpose. One can usually exchange references/citations between different tools quite easily, so if a researcher start using one tool and decide to move to a different tool, researcher can transfer all their references/citations and not have to go out and find them again. Following are the major reference management tools which discussed in this paper 1) Mendeley 2) Ref works 3) Bibliotext 4) Zotero and 5) Endnote. A comparative study has been done for available reference management tools which may help the users to decide which one is the appropriate and more user friendly for their research work. The paper studies the problem which occur while using the reference management tools and how to overcome those problem using alternative tools and converter etc.Item Use and impact of E-Resources at Jawaharlal Nehru University: A case study(Pearl, 2016-03) Awashthi, Shipra.; Devendrappa, T.M.; Rigzin, Sonam.The Present paper explores the impact of e-resources among the students of Jawaharlal Nehru University (JNU), India. It also highlights the use of different online resources and software subscribed by central library