http://hdl.handle.net/123456789/345 Sat, 13 Jun 2026 17:07:38 GMT 2026-06-13T17:07:38Z http://hdl.handle.net/123456789/391 Title: STUDY MATERIAL ON RESEARCH PUBLICATION ETHICS (20RPE000) Authors: ANEES, MOHAMED Wed, 01 Jan 2020 00:00:00 GMT http://hdl.handle.net/123456789/391 2020-01-01T00:00:00Z http://hdl.handle.net/123456789/374 Title: A STUDY OF ORGANIZATIONAL CLIMATE AND ITS IMPACT ON OCCUPATIONAL ROLE STRESS AMONGST FACULTY IN HIGHER EDUCATION Authors: Shintri, Shreedevi Abstract: The world is evolving at a fast pace. The industrial revolution, economic reforms, technological advancement, constant need to strive for excellence, cut-throat competition is restructuring social, economic, technological and legal setup across the globe. Change has become an inevitable part of every domain. With the invasion of technology and inter-disciplinary teaching and learning, changes are noticed in education sector too. India ranks the third in terms of number of universities in the world. Karnataka ranks third in terms if number of universities as per All India Survey on Higher Education 2018-19, Ministry of HRD, India. To meet to the demands employees, spend 50% of their time in the organizations and hence the climate (environment) in the organisation, the relationship between subordinates, peers, superiors and the management play a vital role. Constant interaction with number of stakeholders and the need to be at pace with the competition makes them feel stressed too. An employee will be able to give his/her best when there is conducive environment at the workplace. Though there are nearly 1000 universities in India, little emphasis is given to understand the impact of organisational climate on occupational role stress among faculty. The study aims to assess the relationship between demographic variables, Organization climate and occupational role stress among faculty in higher education; Also, to measure the association between organizational climate and Occupational Role Stress and evaluate the impact of specific organizational climate dimensions on specific occupational role stress dimensions chosen for the study. The results are derived assessing three hypotheses. The testing of the hypotheses is done by using statistical techniques like correlation, Regression analysis, Post Hoc test and Factor analysis. ‘Marital Status’ and ‘Hierarchy’ were among the demographic variables which showed an influence on Organisational Climate & Occupational Role Stress. A 6.4% impact of organisational climate on occupational role stress was recorded through the analysis. The factor analysis helped reduce the Organisational Climate dimensions to three factors and Occupational Role Stress dimensions were reduced to five factors. The research stated that as organizational climate improves occupational role stress among its faculty lessens and vice versa. To have a better organizational Climate, it is suggested that higher education institutes must focus on - personal and professional development; creating good team dynamics and supportive superiors attitude; management support; open communication; effective and efficient HR mechanism; employee welfare and transparency; scope for personal growth; meeting personal expectations; reducing ambiguity in their roles; catering to resource inadequacy; work overload; emphasizing social wellbeing and employee engagement. Higher education is witnessing technological advancements in pedagogy. Avoiding or escaping from technological adaption is impossible. The present research helped derive a model suggesting three dimensions to assess Organisational Climate and five dimensions to evaluate Occupational Role Stress among faculty in higher education. With a perceived increase of technostress and technophobia among teachers, the present research can also act as a groundwork for the studies on technostress in the education sector in future. Thu, 01 Apr 2021 00:00:00 GMT http://hdl.handle.net/123456789/374 2021-04-01T00:00:00Z http://hdl.handle.net/123456789/373 Title: Analysis of Retinopathy Images to Detect the effect of Diabetes on Eye Authors: Jadhav, Ambaji S. Abstract: Diabetic Retinopathy (DR) is one of the most occurred diabetic eye diseases that cause serious complication to the eye even to vision loss. The risk of this problem can be completely prevented by means of two fundamental public health interventions such as early diagnosis and treatment. However, the effective screening and diagnosing the DR from the retinal fundus images is a major challenge. In this scenario, the experts and other professional diagnosis teams depend on analyzing the retinal fundus images using the Computer-Aided Diagnosis (CAD) system. The general processing stages of CAD system involves pre-processing, segmentation and classification pertaining to retinal blood vessels or other abnormalities. Various machine learning methods have been developed. Further the recent contribution of deep learning models and its successful performance over the conventional techniques under medical applications have been motivated the researchers for adopting the deep learning models to diagnose the DR. This research work focuses to analyze the retinal fundus images for the effective diagnosis of DR using intelligent techniques. It performs the DR detection in different phases. In the first phase the blood vessel analysis is performed by, image enhancement, filtering and morphological operation. In the filtering, Peak Signal-to-Noise Ratio (PSNR) and Mean Squared Error (MSE) computation is performed on for DRIVE database. Blood vessels are segmented using morphology operation. Feature extraction by DWT and Gray-Level Co-Occurrence Matrix (GLCM) is done and classification by Support Vector Machine (SVM) and distance measures like city block, Spearman, and Minkowski are employed for CHASE_DBI and DRIVE databases. In the second phase, the examination of optic disc, exudates and blood vessels is done. Here, wavelet transform is used for detecting the optic disc using DIARETDB1 dataset, whereas morphological operation, grey level thresholding and Discrete Wavelet Transform (DWT) is used for detecting the exudates and classify the image into normal and abnormal. The third phase of the research work segments and analyses the blood vessels for detecting DR. Initially, the combination of Contrast Limited Adaptive Histogram Equalization (CLAHE) and average filter performs the pre-processing. Further, the optimized Gray level thresholding is used for the blood vessel segmentation and feature extraction techniques like Texture energy Measurement (TEM), Local Binary Pattern (LBP), Shanon’s entropy and Kapur’s entropy are utilized. The classification of the image is performed by the optimal trained Neural Network (NN). The developmed new algorithm termed as Modified Levy Updated-Dragonfly Algorithm (MLU-DA) enhances the performance of both segmentation and classification to classify the image as normal and abnormal using the High Resolution Fundus (HRF) images. The fourth phase of this research work diagnoses the DR from the retinal fundus images by segmenting and analyzing the retinal abnormalities like haemorrhages, Microaneurysm, soft exudates and hard exudates. After enhancing the contrast of the image by CLAHE, open-close watershed transformation helps to remove the optic disc and Grey Level thresholding helps to remove the blood vessels. Further, the utilization of Top hat transformation followed by Gabor filtering segments the retinal abnormalities. From the segmented abnormalities, LBP, TEM, Shanon’s, and Kapur’s entropy are extracted as features and carried out the optimal feature selection by proposed Modified Gear and Steering-based Rider Optimization Algorithm (MGS-ROA). Further, the optimized Deep Belief Network (DBN) classifies the image into normal, severe, moderate, and earlier stages of DR, in which MGS-ROA updates the DBN weight. The experiment is carried out for DIARETDB1image datasets. The final contribution of this research work focuses on analyzing the optic disc, blood vessels and retinal abnormalities for diagnosing DR using DIARETDB1 image datasets The open-close watershed transform segments the optic disc, Grey level thresholding segments the blood vessels and top hat transform followed by Gabor filtering segments the abnormalities like haemorrhages, Microaneurysm, soft exudates and hard exudates. Here also, features like LBP, TEM, Shanon’s, and Kapur’s entropy are extracted from the segmented optic disc, blood vessels, and abnormalities and the proposed Trial-based Bypass Improved Dragonfly Algorithm (TB-DA) is used to carry out the optimal feature selection process The classification of images is done by the hybridization of DBN and NN, in which the TB-DA optimizes weight function of both classifies. Thu, 01 Jul 2021 00:00:00 GMT http://hdl.handle.net/123456789/373 2021-07-01T00:00:00Z http://hdl.handle.net/123456789/372 Title: EXPERIMENTAL INVESTIGATION OF LOCAL DISTRIBUTION OF HEAT TRANSFER AND FLUID FLOW CHARACTERISTICS OF IMPINGING SLOT AIR JET Authors: M, ADIMURTHY Abstract: Jet impingement cooling has received considerable attention due to its inherent characteristics of high heat transfer rate. Impinging flow devices allow for short flow paths and relatively high rate of cooling from comparatively small surface area. Few industrial processes that employ impinging jets are drying of food products, textiles, films and papers, processing of some metals and glass, cooling of gas turbine blades and outer wall of the combustion chamber, cooling of electronic equipment, etc.” Air will continue to be used as the working fluid due to its low cost, easy availability and reliability. “The requirement for increased gas turbine engine performance has led to the use of much higher turbine entry temperature. The higher gas temperatures require active cooling of the turbine blade using compressor bleed air. Heat transfer enhancement by jet impingement has significant potential to increase the local heat transfer coefficient. Arrays of impinging jets are one of the methodscurrently used to reduce the blade temperature on the mid-chord and leading-edge regions. The present study focuses on one of the thermal issues of uniformity of distribution of heat transfer.” The influence of various geometric and flow parameters of the impingement system on the local distribution of heat transfer coefficients are investigated. The local heat transfer characteristics are studied experimentally using a thin foil heater and an infrared thermal imaging technique. “The local heat transfer and fluid flow distribution on smooth flat surface impinged by a single slot air jet is studied for different jet-to-plate distances (0.5Dh-10 Dh) and Reynolds numbers (2500-20000).” Semi-empirical correlations for local heat transfer coefficients in the stagnation region are obtained. Further, local heat transfer enhancements on rough flat surface (detached ribs) impinged by a single slot air jet is examined for different geometric parameters of ribs at various jet-to-plate distances. The influence of confinement and inclination angle of the jet with reference to impingement plate on the fluid and thermal characteristics of the single slot air jet are studied experimentally. Finally, the combined effect of confinement and surface roughness is evaluated for the local distribution of the heat transfer and the pressure on the impingement plate. Thu, 01 Jul 2021 00:00:00 GMT http://hdl.handle.net/123456789/372 2021-07-01T00:00:00Z