10 research outputs found
A Geospatial approach to determine Lake Depth and Configuration of Reingkhyongkine (Pukur Para) Lake, Rangamati Hill District, Bangladesh with Multi-Temporal Satellite data
No full textReingkhyongkine (Pukur Para) Lake is the largest hilly natural lake under Belaichhari Upazila in the Hill district of Rangamati, Bangladesh. Due to remoteness and rugged terrain this lake is never being investigated and not documented in the literature. This research is done following standard method and state-of-art-technology. As natural resource management foster sustainable development the present research is of immense importance. Global Positioning System (GPS) is used for water depth point positioning along with sounding techniques was used for water depth measurement. The highest and lowest depths are observed 145 m and 0.50 m respectively. The worldwide available Landsat 8 OLI/TIRS imagery of 13 May 2015 was considered as the base imagery to know the lake area at present context compare with other different years. The Lake depth and 3D configuration maps are developed based on field depth and derived contour data. In addition to this, surface elevation profile in different direction of lake and bathymetric mapping based on longitudinal and horizontal transect bottom topographic profile, lake surface area and water volume are also calculated to understand the real scenario of this largest lake. All these studies are integrated with local as well as the regional geological structures. The study using geo-integrated technology on Reingkhyongkine lake reveals that the changes of lake area which is 35.02 hectare (May 2015 Landsat 8 OLI Imagery), 40.65 hectare and 34.91 hectare (2010 and 1989 Landsat TM imagery) respectively which indicate an decreasing-increasing-decreasing trend scenario and changing at the rate of 0.11 percent per year and this changing phenomenon is related with the active tectonism of the area as the study area has suffered extensive thrusting, faulting and folding. Besides this the surface elevation of lake is not similar and it varies from 353 meter to 409 meters. Results shows that changes in the configuration and reduction of water volume of Reingkhyongkine Lake establish fragile conditions which indicate of its future drying status and needs continuous monitoring of water depth by considering environmental factors which are involved for the lake changes and finally researcher seeks urgent attention to international scientific community for protection and conservation of this hilly natural lake
Finite Difference Time Domain Simulation of Active Cancellation of Radar Echoes
No full textAbstractRadar evasion or Stealth is a technology most desirable among all the military research areas currently pursued. Research organisations have focused their attention on electronic stealth technology or cancellation of waves since it is feasible now due to the improvement of high end processing and fast electronic systems. In an attempt to increase our understanding of this field, we have analysed the phenomenon through computer aided simulation. In this paper, we have created an electromagnetic wave simulation platform and using finite difference time domain method, analysed a method of active cancellation. We have found results showing complete effectiveness of this method assured by the accuracy of FDTD method
CHALLENGES IN E -LEARNING IN INDIA
No full text<p>In a fastly growing world e- learning has very important role to play. But inherent nature of<br>this dynamic learning process, is itself creating a lot of challenges. Unless these challenges are met, it is<br>considerably impossible to promote e-learning in India. We need stringent statutory provisions to prevent<br>threats related to e learning. But above all our approach should be conducive enough, so that we can see<br>improvements in realistic level in society by imparting education through e learning</p>
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Simulation of Low Power Heater for Gas Sensing Application
No full textAbstractThis paper presents design, simulation and analysis of a platinum (Pt) based micro-heater for gas sensing applications. Finite element method (FEM) analysis is employed for the purpose of performing the tasks mentioned above thereby investigates the various properties of the high resistive material platinum (Pt) using COMSOL Multiphysics. The Micro-heater is principally designed to ensure minimum power consumption, low thermal mass and better temperature uniformity. Furthermore, the effect of variation of thickness of heating element with created temperature and power consumption of the MEMS micro-heater is observed and evaluated
A novel deep unsupervised learning method for sum-rate optimization in device-to-device networks with a quality-of-service constraint
No full textThis study introduces a new Deep Unsupervised Learning (DUL) approach based on an optimization problem with box constraints coupled with polytope constraints for maximizing the sum rate in Device-to-Device (D2D) networks, a key factor in enhancing network capacity and efficiency. Current deep learning methods struggle with managing resource-intensive projection steps and need multiple iterations to optimize the sum rate in varying D2D environments. The proposed approach overcomes these challenges by minimizing the loss function and satisfying constraints when dealing with a monotone matrix. The novel approach controls transmit power through a fully connected, multi-layer Deep Neural Network (DNN), solving the complex, non-convex optimization problem associated with optimizing the sum rate in a symmetric interference channel model. The result shows that this method outperforms other power control methods regarding average sum rate, hit rate, and complexity when applied to a standard symmetric K-user Gaussian interference channel.D2D communicationsum-rate optimizationdeep learning (DL)unsupervised learning (UL)box constraintsmonotone matri
An efficient hybrid system for anomaly detection in social networks
No full textAnomaly detection has been an essential and dynamic research area in the data mining. A wide range of applications including different social medias have adopted different state-of-the-art methods to identify anomaly for ensuring user’s security and privacy. The social network refers to a forum used by different groups of people to express their thoughts, communicate with each other, and share the content needed. This social networks also facilitate abnormal activities, spread fake news, rumours, misinformation, unsolicited messages, and propaganda post malicious links. Therefore, detection of abnormalities is one of the important data analysis activities for the identification of normal or abnormal users on the social networks. In this paper, we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms including decision tree (C5.0), Support Vector Machine (SVM) and Naïve Bayesian classifier (NBC) for classifying normal and abnormal users in social networks. We have extracted a list of unique features derived from users’ profile and contents. Using two kinds of dataset with the selected features, the proposed machine learning model called DT-SVMNB is trained. Our model classifies users as depressed one or suicidal one in the social network. We have conducted an experiment of our model using synthetic and real datasets from social network. The performance analysis demonstrates around 98% accuracy which proves the effectiveness and efficiency of our proposed system. © 2021, The Author(s)
Assessment of Research output on Bamboo in India: A Bibliometric Study
No full textThis study assessed the research output on Bamboo for a period of 29 years (1989-2018). The web of science database has been used to retrieve worldwide publication records on bamboo research. The records were analysed using the descriptive statistics. Based on the retrieved data, various aspect of literature on bamboo research analysed and interpreted. The performance of the most productivity countries, authors, journals, Institution wise, and Growth rate and doubling time have assessed. The articles were classified as Research, review and others and grouped under 22 subjects to identify the subject coverage of bamboo research. The study found a positive growth in research and review article while very sharp decrement was observed. The growth rate and doubling period were estimated 8.5 and 8.34 respectively. Most of the articles written on Agriculture, Material Science, building technology and chemistry. M. Das (Presidency University, Department Life Science, Kolkata) is the most prolific primary author while R. Kumar (National Institute of Technology, Department of Mechanical Engineer, Silchar, India) mostly occurred as secondary author. Local and National collaboration mostly observed in the paper. India is the most productive country of world followed by china and Tamilnadu is most productive state of India. Indian Institute of Technology, India is a premier institute in bamboo research activity
NAD depletion mediates cytotoxicity in human neurons with autophagy deficiency
No full text\ua9 2023 The Author(s)Autophagy is a homeostatic process critical for cellular survival, and its malfunction is implicated in human diseases including neurodegeneration. Loss of autophagy contributes to cytotoxicity and tissue degeneration, but the mechanistic understanding of this phenomenon remains elusive. Here, we generated autophagy-deficient (ATG5−/−) human embryonic stem cells (hESCs), from which we established a human neuronal platform to investigate how loss of autophagy affects neuronal survival. ATG5−/− neurons exhibit basal cytotoxicity accompanied by metabolic defects. Depletion of nicotinamide adenine dinucleotide (NAD) due to hyperactivation of NAD-consuming enzymes is found to trigger cell death via mitochondrial depolarization in ATG5−/− neurons. Boosting intracellular NAD levels improves cell viability by restoring mitochondrial bioenergetics and proteostasis in ATG5−/− neurons. Our findings elucidate a mechanistic link between autophagy deficiency and neuronal cell death that can be targeted for therapeutic interventions in neurodegenerative and lysosomal storage diseases associated with autophagic defect
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Advancements in Urban Environmental Studies : Application of Geospatial Technology and Artificial Intelligence in Urban Studies
No full textAdvancements in Urban Environmental Studie
