Search results for: Gaurav Jain
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 257

Search results for: Gaurav Jain

167 A Study of the Performance Parameter for Recommendation Algorithm Evaluation

Authors: C. Rana, S. K. Jain

Abstract:

The enormous amount of Web data has challenged its usage in efficient manner in the past few years. As such, a range of techniques are applied to tackle this problem; prominent among them is personalization and recommender system. In fact, these are the tools that assist user in finding relevant information of web. Most of the e-commerce websites are applying such tools in one way or the other. In the past decade, a large number of recommendation algorithms have been proposed to tackle such problems. However, there have not been much research in the evaluation criteria for these algorithms. As such, the traditional accuracy and classification metrics are still used for the evaluation purpose that provides a static view. This paper studies how the evolution of user preference over a period of time can be mapped in a recommender system using a new evaluation methodology that explicitly using time dimension. We have also presented different types of experimental set up that are generally used for recommender system evaluation. Furthermore, an overview of major accuracy metrics and metrics that go beyond the scope of accuracy as researched in the past few years is also discussed in detail.

Keywords: collaborative filtering, data mining, evolutionary, clustering, algorithm, recommender systems

Procedia PDF Downloads 393
166 Computer Aided Classification of Architectural Distortion in Mammograms Using Texture Features

Authors: Birmohan Singh, V.K.Jain

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Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Masses and microcalcifications, architectural distortions are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support Vector Machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and accuracy of 96% for the detection of abnormalities with mammogram images collected from Digital Database for Screening Mammography (DDSM) database.

Keywords: architecture distortion, mammograms, GLCM texture features, GLRLM texture features, support vector machine classifier

Procedia PDF Downloads 472
165 Coloured Petri Nets Model for Web Architectures of Web and Database Servers

Authors: Nidhi Gaur, Padmaja Joshi, Vijay Jain, Rajeev Srivastava

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Web application architecture is important to achieve the desired performance for the application. Performance analysis studies are conducted to evaluate existing or planned systems. Web applications are used by hundreds of thousands of users simultaneously, which sometimes increases the risk of server failure in real time operations. We use Coloured Petri Net (CPN), a very powerful tool for modelling dynamic behaviour of a web application system. CPNs extend the vocabulary of ordinary Petri nets and add features that make them suitable for modelling large systems. The major focus of this work is on server side of web applications. The presented work focuses on modelling restructuring aspects, with major focus on concurrency and architecture, using CPN. It also focuses on bringing out the appropriate architecture for web and database servers given the number of concurrent users.

Keywords: coloured Petri Nets (CPNs), concurrent users, per- formance modelling, web application architecture

Procedia PDF Downloads 586
164 Automated Pothole Detection Using Convolution Neural Networks and 3D Reconstruction Using Stereovision

Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

Abstract:

Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

Procedia PDF Downloads 118
163 Graphene/h-BN Heterostructure Interconnects

Authors: Nikhil Jain, Yang Xu, Bin Yu

Abstract:

The material behavior of graphene, a single layer of carbon lattice, is extremely sensitive to its dielectric environment. We demonstrate improvement in electronic performance of graphene nanowire interconnects with full encapsulation by lattice-matching, chemically inert, 2D layered insulator hexagonal boron nitride (h- BN). A novel layer-based transfer technique is developed to construct the h-BN/MLG/h-BN heterostructures. The encapsulated graphene wires are characterized and compared with that on SiO2 or h-BN substrate without passivating h-BN layer. Significant improvements in maximum current-carrying density, breakdown threshold, and power density in encapsulated graphene wires are observed. These critical improvements are achieved without compromising the carrier transport characteristics in graphene. Furthermore, graphene wires exhibit electrical behavior less insensitive to ambient conditions, as compared with the non-passivated ones. Overall, h-BN/graphene/h- BN heterostructure presents a robust material platform towards the implementation of high-speed carbon-based interconnects.

Keywords: two-dimensional nanosheet, graphene, hexagonal boron nitride, heterostructure, interconnects

Procedia PDF Downloads 301
162 Cybersecurity Strategies for Protecting Oil and Gas Industrial Control Systems

Authors: Gaurav Kumar Sinha

Abstract:

The oil and gas industry is a critical component of the global economy, relying heavily on industrial control systems (ICS) to manage and monitor operations. However, these systems are increasingly becoming targets for cyber-attacks, posing significant risks to operational continuity, safety, and environmental integrity. This paper explores comprehensive cybersecurity strategies for protecting oil and gas industrial control systems. It delves into the unique vulnerabilities of ICS in this sector, including outdated legacy systems, integration with IT networks, and the increased connectivity brought by the Industrial Internet of Things (IIoT). We propose a multi-layered defense approach that includes the implementation of robust network security protocols, regular system updates and patch management, advanced threat detection and response mechanisms, and stringent access control measures. We illustrate the effectiveness of these strategies in mitigating cyber risks and ensuring the resilient and secure operation of oil and gas industrial control systems. The findings underscore the necessity for a proactive and adaptive cybersecurity framework to safeguard critical infrastructure in the face of evolving cyber threats.

Keywords: cybersecurity, industrial control systems, oil and gas, cyber-attacks, network security, IoT, threat detection, system updates, patch management, access control, cybersecurity awareness, critical infrastructure, resilience, cyber threats, legacy systems, IT integration, multi-layered defense, operational continuity, safety, environmental integrity

Procedia PDF Downloads 17
161 Ion-Acoustic Double Layers in a Non-Thermal Electronegative Magnetized Plasma

Authors: J. K. Chawla, S. K. Jain, M. K. Mishra

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Ion-acoustic double layers have been studied in magnetized plasma. The modified Korteweg-de Vries (m-KdV) equation using reductive perturbation method is derived. It is found that for the selected set of parameters, the system supports rarefactive double layers depending upon the value of nonthermal parameters. It is also found that the magnetization affects only the width of the double layer. For a given set of parameter values, increases in the magnetization and the obliqueness angle (θ) between wave vector and magnetic field, affect the width of the double layers, however the amplitude of the double layers have no effect. An increase in the values of nonthermal parameter decreases the amplitude of the rarefactive double layer. The effect of the ion temperature ratio on the amplitude and width of the double layers are also discussed in detail.

Keywords: ion-acoustic double layers, magnetized electronegative plasma, reductive perturbation method, the modified Korteweg-de Vries (KdV) equation

Procedia PDF Downloads 592
160 Energy Efficiency and Sustainability Analytics for Reducing Carbon Emissions in Oil Refineries

Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

Procedia PDF Downloads 13
159 Two-Dimensional Nanostack Based On Chip Wiring

Authors: Nikhil Jain, Bin Yu

Abstract:

The material behavior of graphene, a single layer of carbon lattice, is extremely sensitive to its dielectric environment. We demonstrate improvement in electronic performance of graphene nanowire interconnects with full encapsulation by lattice-matching, chemically inert, 2D layered insulator hexagonal boron nitride (h-BN). A novel layer-based transfer technique is developed to construct the h-BN/MLG/h-BN heterostructures. The encapsulated graphene wires are characterized and compared with that on SiO2 or h-BN substrate without passivating h-BN layer. Significant improvements in maximum current-carrying density, breakdown threshold, and power density in encapsulated graphene wires are observed. These critical improvements are achieved without compromising the carrier transport characteristics in graphene. Furthermore, graphene wires exhibit electrical behavior less insensitive to ambient conditions, as compared with the non-passivated ones. Overall, h-BN/graphene/h-BN heterostructure presents a robust material platform towards the implementation of high-speed carbon-based interconnects.

Keywords: two-dimensional nanosheet, graphene, hexagonal boron nitride, heterostructure, interconnects

Procedia PDF Downloads 430
158 Learning Dynamic Representations of Nodes in Temporally Variant Graphs

Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

Procedia PDF Downloads 300
157 Transport Related Air Pollution Modeling Using Artificial Neural Network

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

Procedia PDF Downloads 504
156 Improved Throttled Load Balancing Approach for Cloud Environment

Authors: Sushant Singh, Anurag Jain, Seema Sabharwal

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Cloud computing is advancing with a rapid speed. Already, it has been adopted by a huge set of users. Easy to use and anywhere access like potential of cloud computing has made it more attractive relative to other technologies. This has resulted in reduction of deployment cost on user side. It has also allowed the big companies to sell their infrastructure to recover the installation cost for the organization. Roots of cloud computing have extended from Grid computing. Along with the inherited characteristics of its predecessor technologies it has also adopted the loopholes present in those technologies. Some of the loopholes are identified and corrected recently, but still some are yet to be rectified. Two major areas where still scope of improvement exists are security and performance. The proposed work is devoted to performance enhancement for the user of the existing cloud system by improving the basic throttled mapping approach between task and resources. The improved procedure has been tested using the cloud analyst simulator. The results are compared with the original and it has been found that proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, load balancing, throttled

Procedia PDF Downloads 228
155 Pawn or Potentates: Corporate Governance Structure in Indian Central Public Sector Enterprises

Authors: Ritika Jain, Rajnish Kumar

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The Department of Public Enterprises had made submissions of Self Evaluation Reports, for the purpose of corporate governance, mandatory for all central government owned enterprises. Despite this, an alarming 40% of the enterprises did not do so. This study examines the impact of external policy tools and internal firm-specific factors on corporate governance of central public sector enterprises (CPSEs). We use a dataset of all manufacturing and non-financial services owned by the central government of India for the year 2010-11. Using probit, ordered logit and Heckman’s sample selection models, the study finds that the probability and quality of corporate governance is positively influenced by the CPSE getting into a Memorandum of Understanding (MoU) with the central government of India, and hence, enjoying more autonomy in terms of day to day operations. Besides these, internal factors, including bigger size and lower debt size contribute significantly to better corporate governance.

Keywords: corporate governance, central public sector enterprises (CPSEs), sample selection, Memorandum of Understanding (MoU), ordered logit, disinvestment

Procedia PDF Downloads 239
154 Effect of Various Tillage Systems on Soil Compaction

Authors: Sushil Kumar, Mukesh Jain, Vijaya Rani, Vinod Kumar

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The prime importance of tillage is that it prepares the land where the seed easily germinate and later the plant can well establish. Using different types of equipments driven manually or by powered, machines make the soil suitable to place the seeds into the desirable depth. Moreover, tillage loosens the compacted layers. Heavy equipment and tillage implements can cause damage to the soil structure. Effect of various tillage methods on soil compaction was studied in Rabi season of 2013-14 at village Ladwa, Hisar, Haryana (India). The experiments studied the effect of six tillage treatments i.e. no tillage or zero tillage (T1), tillage with rotavator (T2), disc harrow (T3), rotavator + sub soiler (T4), disc harrow + sub soiler (T5) and power harrow (T6) on soil compaction. Soil compaction was measured before tillage and after sowing at 0, 30, 60 and 90 days after sowing. No change in soil resistance was recorded before and after no tillage treatment. Maximum soil resistance was found in zero tillage followed by disc harrow up to 150 mm soil depth. Minimum soil resistance was found in rotavator immediately after the tillage treatment. However, the soil resistance approached the same level as it had been before the tillage after the soil strata where the implement cannot reach.

Keywords: tillage, no tillage, rotavator, subsoiler, compaction

Procedia PDF Downloads 295
153 Optimization of Multiplier Extraction Digital Filter On FPGA

Authors: Shiksha Jain, Ramesh Mishra

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One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.

Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table

Procedia PDF Downloads 374
152 Graphene Transistor Employing Multilayer Hexagonal Boron Nitride as Substrate and Gate Insulator

Authors: Nikhil Jain, Bin Yu

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We explore the potential of using ultra-thin hexagonal boron nitride (h-BN) as both supporting substrate and gate dielectric for graphene-channel field effect transistors (GFETs). Different from commonly used oxide-based dielectric materials which are typically amorphous, very rough in surface, and rich with surface traps, h-BN is layered insulator free of dangling bonds and surface states, featuring atomically smooth surface. In a graphene-channel-last device structure with local buried metal gate electrode (TiN), thin h-BN multilayer is employed as both supporting “substrate” and gate dielectric for graphene active channel. We observed superior carrier mobility and electrical conduction, significantly improved from that in GFETs with SiO2 as substrate/gate insulator. In addition, we report excellent dielectric behavior of layered h-BN, including ultra-low leakage current and high critical electric field for breakdown.

Keywords: graphene, field-effect transistors, hexagonal boron nitride, dielectric strength, tunneling

Procedia PDF Downloads 409
151 Enhancing Neural Connections through Music and tDCS: Insights from an fNIRS Study

Authors: Dileep G., Akash Singh, Dalchand Ahirwar, Arkadeep Ghosh, Ashutosh Purohit, Gaurav Guleria, Kshatriya Om Prashant, Pushkar Patel, Saksham Kumar, Vanshaj Nathani, Vikas Dangi, Shubhajit Roy Chowdhury, Varun Dutt

Abstract:

Transcranial direct current stimulation (tDCS) has shown promise as a novel approach to enhance cognitive performance and provide therapeutic benefits for various brain disorders. However, the exact underlying brain mechanisms are not fully understood. We conducted a study to examine the brain's functional changes when subjected to simultaneous tDCS and music (Indian classical raga). During the study, participants in the experimental group underwent a 20-minute session of tDCS at two mA while listening to music (raga) for a duration of seven days. In contrast, the control group received a sham stimulation for two minutes at two mA over the same seven-day period. The objective was to examine whether repetitive tDCS could lead to the formation of additional functional connections between the medial prefrontal cortex (the stimulated area) and the auditory cortex in comparison to a sham stimulation group. In this study, 26 participants (5 female) underwent pre- and post-intervention scans, where changes were compared after one week of either tDCS or sham stimulation in conjunction with music. The study revealed significant effects of tDCS on functional connectivity between the stimulated area and the auditory cortex. The combination of tDCS applied over the mPFC and music resulted in newly formed connections. Based on our findings, it can be inferred that applying anodal tDCS over the mPFC enhances functional connectivity between the stimulated area and the auditory cortex when compared to the effects observed with sham stimulation.

Keywords: fNIRS, tDCS, neuroplasticity, music

Procedia PDF Downloads 53
150 Life Cycle Assessment: Drinking Glass Systems

Authors: Devina Jain

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The choice between single-use drinking glasses and reusable glasses is of major concern to our lifestyles, and hence, the environment. This study is aimed at comparing three systems - a disposable paper cup, a disposable cup and a reusable stainless steel cup or glass - with respect to their effect on the environment to find out which one is more advantageous for reducing the impact on the environment. Life Cycle Assessment was conducted using modeling software, Umberto NXT Universal (Version 7.1). For the purpose of this study, the cradle to grave approach was considered. Results showed that cleaning is of a very strong influence on the environmental burden by these drinking systems, with a contribution of up to 90 to 100%. Thus, the burden is determined by the way in which the utensils are washed, and how much water is consumed. It maybe seems like a small, insignificant daily practice. In the short term, it would seem that paper and plastic cups are a better idea, since they are easy to acquire and do not need to be stored, but in the long run, we can say that steel cups will have less of an environmental impact. However, if the frequency of use and the number of glasses employed per use are of significance to decide the appropriateness of the usage, it is better to use disposable cups and glasses.

Keywords: disposable glass, life cycle assessment, paper, plastic, reusable glass, stainless steel

Procedia PDF Downloads 320
149 Effect of Traffic Composition on Delay and Saturation Flow at Signal Controlled Intersections

Authors: Arpita Saha, Apoorv Jain, Satish Chandra, Indrajit Ghosh

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Level of service at a signal controlled intersection is directly measured from the delay. Similarly, saturation flow rate is a fundamental parameter to measure the intersection capacity. The present study calculates vehicle arrival rate, departure rate, and queue length for every five seconds interval in each cycle. Based on the queue lengths, the total delay of the cycle has been calculated using Simpson’s 1/3rd rule. Saturation flow has been estimated in terms of veh/hr of green/lane for every five seconds interval of the green period until at least three vehicles are left to cross the stop line. Vehicle composition shows an immense effect on total delay and saturation flow rate. The increase in two-wheeler proportion increases the saturation flow rate and reduces the total delay per vehicle significantly. Additionally, an increase in the heavy vehicle proportion reduces the saturation flow rate and increases the total delay for each vehicle.

Keywords: delay, saturation flow, signalised intersection, vehicle composition

Procedia PDF Downloads 444
148 Quantum Entangled States and Image Processing

Authors: Sanjay Singh, Sushil Kumar, Rashmi Jain

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Quantum registering is another pattern in computational hypothesis and a quantum mechanical framework has a few helpful properties like Entanglement. We plan to store data concerning the structure and substance of a basic picture in a quantum framework. Consider a variety of n qubits which we propose to use as our memory stockpiling. In recent years classical processing is switched to quantum image processing. Quantum image processing is an elegant approach to overcome the problems of its classical counter parts. Image storage, retrieval and its processing on quantum machines is an emerging area. Although quantum machines do not exist in physical reality but theoretical algorithms developed based on quantum entangled states gives new insights to process the classical images in quantum domain. Here in the present work, we give the brief overview, such that how entangled states can be useful for quantum image storage and retrieval. We discuss the properties of tripartite Greenberger-Horne-Zeilinger and W states and their usefulness to store the shapes which may consist three vertices. We also propose the techniques to store shapes having more than three vertices.

Keywords: Greenberger-Horne-Zeilinger, image storage and retrieval, quantum entanglement, W states

Procedia PDF Downloads 286
147 TiO2 Adsorbed on Cement Balls for Effective Photomineralization of Organic Pollutants under UV Light Irradiation

Authors: Tarun Jain, Lovnish Gupta, Soumen Basu

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Organic pollutants like phenols and organic dyes present in industrial waste water are posing a hazardous threat to aquatic ecosystem. Several measures have been adopted for the neutralization and photodecomposition of these harmful organic moieties, among these semiconductor photocatalysis has been provided a major thrust after the discovery of Honda-Fujishema effect. Present study demonstrates the adsorption of TiO2- P25 in nano size (~36 nm) on cement balls for effective photodegradation of Alizarin and penta chlorophenol (PCP) under UV light illumination. Triton-X was used as a stabilizer for effective adsorption of TiO2 on cement balls (TCB) followed by calcination at ~300oC for 4 h. The TCB’s were dispersed randomly in a self designed reactor for phototcatalytic performance as shown in scheme 1. The change in concentration of alizarin and PCP was observed under UV-Vis spectroscopy, PCP was detoxified within 40 min while alizarin photodecomposed within 15 min of UV light irradiation. Taking into consideration the go green slogan and future prospective this technique can be also utilized under visible light and on mass scale because this is an effective tool for environmental remediation and waste water treatment.

Keywords: organic pollutants, TiO2 cement balls, photodegradation, UV light irradiation

Procedia PDF Downloads 247
146 The Evolution of Online Hate: How Decades of Tactical and Technological Innovation Created a Hate Epidemic

Authors: Kashvi Jain, Adam Burston

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Right-wing social movements are a dominant force in American politics, as evidenced by the January 6th Insurrection, the prevalence of extremist conspiracy theories, and a nationwide surge in hate crime. Despite an abundance of scholarship on contemporary right-wing extremism, there is little scholarship that explains their rise. This paper examines how the white power movement developed through tactical innovation and strategic use of increasingly powerful digital technologies. Using qualitative content analysis of archived digital bulletin boards and websites, we examine right-wing extremists’ digital communication during three consequential time periods of tactical and technological innovation: pre-internet (1980s), web 1.0 (1990s), and web 2.0 (2000s). Our analysis suggests that right-wing activists innovatively exploited the features and affordances of digital technologies and their knowledge of free speech rights to spread supremacist collective identity and ideology. Beyond our empirical contribution, we offer policy advice that school administrators can employ to limit hate.

Keywords: leaderless resistance, technological affordances, anti-defamation league, white power movement, tactical

Procedia PDF Downloads 49
145 A Two Level Load Balancing Approach for Cloud Environment

Authors: Anurag Jain, Rajneesh Kumar

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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling

Procedia PDF Downloads 413
144 Studies on the Characterization and Machinability of Duplex Stainless Steel 2205 during Dry Turning

Authors: Gaurav D. Sonawane, Vikas G. Sargade

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The present investigation is a study of the effect of advanced Physical Vapor Deposition (PVD) coatings on cutting temperature residual stresses and surface roughness during Duplex Stainless Steel (DSS) 2205 turning. Austenite stabilizers like nickel, manganese, and molybdenum reduced the cost of DSS. Surface Integrity (SI) plays an important role in determining corrosion resistance and fatigue life. Resistance to various types of corrosion makes DSS suitable for applications with critical environments like Heat exchangers, Desalination plants, Seawater pipes and Marine components. However, lower thermal conductivity, poor chip control and non-uniform tool wear make DSS very difficult to machine. Cemented carbide tools (M grade) were used to turn DSS in a dry environment. AlTiN and AlTiCrN coatings were deposited using advanced PVD High Pulse Impulse Magnetron Sputtering (HiPIMS) technique. Experiments were conducted with cutting speed of 100 m/min, 140 m/min and 180 m/min. A constant feed and depth of cut of 0.18 mm/rev and 0.8 mm were used, respectively. AlTiCrN coated tools followed by AlTiN coated tools outperformed uncoated tools due to properties like lower thermal conductivity, higher adhesion strength and hardness. Residual stresses were found to be compressive for all the tools used for dry turning, increasing the fatigue life of the machined component. Higher cutting temperatures were observed for coated tools due to its lower thermal conductivity, which results in very less tool wear than uncoated tools. Surface roughness with uncoated tools was found to be three times higher than coated tools due to lower coefficient of friction of coating used.

Keywords: cutting temperature, DSS2205, dry turning, HiPIMS, surface integrity

Procedia PDF Downloads 115
143 Non-Contact Characterization of Standard Liquids Using Waveguide at 12.4 to18 Ghz Frequency Span

Authors: Kasra Khorsand-Kazemi, Bianca Vizcaino, Mandeep Chhajer Jain, Maryam Moradpour

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This work presents an approach to characterize a non- contact microwave sensor using waveguides for different standard liquids such as ethanol, methanol and 2-propanol (Isopropyl Alcohol). Wideband waveguides operating between 12.4GHz to 18 GHz form the core of the sensing structure. Waveguides are sensitive to changes in conductivity of the sample under test (SUT), making them an ideal tool to characterize different polar liquids. As conductivity of the sample under test increase, the loss tangent of the material increase, thereby decreasing the S21 (dB) response of the waveguide. Among all the standard liquids measured, methanol exhibits the highest conductivity and 2-Propanol exhibits the lowest. The cutoff frequency measured for ethanol, 2-propanol, and methanol are 10.28 GHz, 10.32 GHz, and 10.38 GHz respectively. The measured results can be correlated with the loss tangent results of the standard liquid measured using the dielectric probe. This conclusively enables us to characterize different liquids using waveguides expanding the potential future applications in domains ranging from water quality management to bio-medical, chemistry and agriculture.

Keywords: Waveguides, , Microwave sensors, , Standard liquids characterization, Non-contact sensing

Procedia PDF Downloads 120
142 Nanomaterial Based Electrochemical Sensors for Endocrine Disrupting Compounds

Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

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Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: electrochemical, endocrine disruptors, microscopy, nanoparticles, sensors

Procedia PDF Downloads 260
141 Comparative Study of Accuracy of Land Cover/Land Use Mapping Using Medium Resolution Satellite Imagery: A Case Study

Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar

Abstract:

Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.

Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices

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140 Development and Characterization of Double Liposomes Based Dual Drug Delivery System for H. Pylori Targeting

Authors: Ashish Kumar Jain, Deepak Mishra

Abstract:

The objective of the present investigation was to prepare and evaluate a vesicular dual drug delivery system for effective management of mucosal ulcer. Inner encapsulating and Double liposomes were prepared by glass bead and reverse phase evaporation method respectively. The formulation consisted of inner liposomes bearing Ranitidine Bismuth Citrate (RBC) and outer liposomes encapsulating Amoxicillin trihydrate (AMOX). The optimized inner liposomes and double liposomes were extensively characterized for vesicle size, morphology, zeta potential, vesicles count, entrapment efficiency and in vitro drug release. In vitro, the double liposomes demonstrated a sustained release of AMOX and RBC viz 91.4±1.8% and 77.2±2.1% respectively at the end of 72 hr. Furthermore binding specificity and targeting propensity toward H. pylori (SKP-56) was confirmed by agglutination and in situ adherence assay. Reduction of the absolute alcohol induced ulcerogenic index from 3.01 ± 0.25 to 0.31 ± 0.09 and 100% H. pylori clearance rate was observed. These results suggested that double liposomes are potential vector for the development of dual drug delivery for effective treatment of H. pylori-associated peptic ulcer.

Keywords: double liposomes, H. pylori targeting, PE liposomes, glass-beads method, peptic ulcers

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139 Searchable Encryption in Cloud Storage

Authors: Ren Junn Hwang, Chung-Chien Lu, Jain-Shing Wu

Abstract:

Cloud outsource storage is one of important services in cloud computing. Cloud users upload data to cloud servers to reduce the cost of managing data and maintaining hardware and software. To ensure data confidentiality, users can encrypt their files before uploading them to a cloud system. However, retrieving the target file from the encrypted files exactly is difficult for cloud server. This study proposes a protocol for performing multikeyword searches for encrypted cloud data by applying k-nearest neighbor technology. The protocol ranks the relevance scores of encrypted files and keywords, and prevents cloud servers from learning search keywords submitted by a cloud user. To reduce the costs of file transfer communication, the cloud server returns encrypted files in order of relevance. Moreover, when a cloud user inputs an incorrect keyword and the number of wrong alphabet does not exceed a given threshold; the user still can retrieve the target files from cloud server. In addition, the proposed scheme satisfies security requirements for outsourced data storage.

Keywords: fault-tolerance search, multi-keywords search, outsource storage, ranked search, searchable encryption

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138 Optimizing Energy Efficiency: Leveraging Big Data Analytics and AWS Services for Buildings and Industries

Authors: Gaurav Kumar Sinha

Abstract:

In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

Procedia PDF Downloads 47