Browsing by Author "Abhishek Kumar"

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3D Lighting Courseware development for 3D Motion Picture Science
(Institute of Electrical and Electronics Engineers Inc., 2018) Abhishek Kumar; K. Vengatesan; Achintya Singhal; Deepak Kumar Verma
This Paper examine the process of lighting and its effects. As many peoples don't have idea about 3d or CG (computer generated) lighting. So with the help of this course and study material they will have good idea about cg lighting and its usage among 3d world. © 2018 IEEE.
3D stereoscopy video production: Z-depth extraction and optimized rendering using foundry nuke
(Blue Eyes Intelligence Engineering and Sciences Publication, 2019) Abhishek Kumar; Achintya Singhal; Jitendra Sheetlani
This paper proposed an effective and efficient 3D stereo Video production methodology for Stereo conversion of any image or video using the 3D compositing tool Foundry Nuke. For efficient S3D conversion, there are several pipelines uses by video production engineer into the industry. There are several technical issues during the 3D stereo production like spilling, reflection, translucency, occlusion, flickering and noise problems as well due to imperfect calibration. This paper presents a theoretical explanation of the principles of stereo vision systems, followed by a quick review of the state of the art. The research paper concludes with validating the assumption of 3D stereoscopy video conversion with film case studies to execute high-end 3d stereo video production quality with roto-based depth map extraction with optimized render conversion methodology. © BEIESP.
A cognitive model for adopting ITIL framework to improve IT services in Indian IT industries
(IOS Press BV, 2020) Rasbihari Dayal; V. Vijayakumar; Rahul Chandra Kushwaha; Abhishek Kumar; V.D. Ambeth Kumar; Ankit Kumar
This research paper presents a cognitive model which manages to minimize the issues of the Information Technology Infrastructure by incorporation of service management practices. The importance of this research is that this model can be replicated in other companies for the distribution of products that wish to implement improvements in their management process technological services. This work introduces the use of Information Technology Infrastructure Library or ITIL as best practice, essential methodologies for IT Management, historical evolution, methodology, service life cycle, and ITIL certifications. Service automation is widely regarded as the usefulness and improves service guarantee. One of the most useful features of automation services is that the process will run the same way every time. Such precision in the execution of repetitive executions is virtually impossible when it comes to human labor. Therefore, the automation is the best way to improve the efficiency of the service provider and the next steps of the process. © 2020 - IOS Press and the authors. All rights reserved.
A modified current injection load flow method under different load model of EV for distribution system
(John Wiley and Sons Ltd, 2020) Bablesh K. Jha; Abhishek Kumar; Dharmendra K. Dheer; Devender Singh; Rakesh K. Misra
In this article, a modified single-phase current injection based load flow method for the distribution network with different load models of electric vehicle (EV) is proposed. The equations related to injected currents are non-linear and are represented in rectangular co-ordinates. The PQ and PV bus representations in load flow formulation are modified for the three different load models of EV including polynomial or ZIP load model (EV LM-I), voltage dependent load model (EV LM-II) and constant current load model (EV LM-III). In addition, a stochastic modelling of EV load and selection of candidate locations for DGs integration are also presented. The effect of the proposed EV load models in terms of real power loss index (ILP), reactive power loss index (ILQ), voltage profile index (IV D) and the MVA capacity index (IC) has been studied on IEEE 38-bus distribution system. Based on the values of ILP, ILQ, IV D and IC, best load model for EVs from among the load models EV LM-I, EV LM-II and EV LM-III is finally obtained. © 2019 John Wiley & Sons Ltd
A Nested-Iterative Newton-Raphson based Power Flow Formulation for Droop-based Islanded Microgrids
(Elsevier Ltd, 2020) Abhishek Kumar; Bablesh Kumar Jha; Dharmendra Kumar Dheer; Rakesh Kumar Misra; Devender Singh
In this paper, an iterative novel power flow technique is proposed to obtain the operating point of Droop Based Islanded Microgrid (DBIMG). The proposed technique considers system frequency as an additional variable to obtain the steady-state operating point of the system. To generalize the proposed technique, four operating modes of Distributed Generations (DGs) including droop control, isochronous, PV and PQ mode are considered. In this study, the formulated power flow problem consists of a set of non linear and linear power flow equations. To solve these set of equations, a Nested-Iterative Newton-Raphson algorithm is proposed. The proposed algorithm is implemented on several test systems including 6-bus, 22-bus, 38-bus, 69-bus, and 160-bus. To examine the robustness and effectiveness of the proposed algorithm, the power flow solutions obtained by implementing the proposed algorithm are compared with the power flow solutions obtained by implementing the existing Newton-Raphson algorithms including Modified Newton-Raphson (MNR), Newton Trust-Region (NTR) and time-domain simulator: PSCAD/EMTDC. The results show better efficiency and superior convergence of the proposed algorithm in comparison to the existing algorithms. © 2019 Elsevier B.V.
A novel approach for agile software development methodology selection using fuzzy inference system
(Institute of Electrical and Electronics Engineers Inc., 2018) Anand Kumar Rai; Shalini Agarwal; Abhishek Kumar
An Agile Methodology of software development has been more popular in the software industry in terms of fast software delivery, less documentation, more satisfaction and more interactions between developers and users. In this paper Fuzzy Inference System based model is proposed to select an appropriate agile method for successful software development. A number of agile methods such as Extreme Programming (XP), Scrum, Feature Driven Development (FDD) and Dynamic System Development Method (DSDM) have been proposed in the literature. Selection of an appropriate method for a given project is a pivotal and a challenging issue. As a solution to this problem, the projects are categorized into four classes namely, Small scale, Medium scale, large scale and safety critical projects, where project size is estimated based on programmer months (PM) and the proposed model is applied to select the most appropriate agile method for each of the project category. MATLAB Simulation results reveal that the proposed model is efficient in predicting the suitability of one of the agile methods. © 2018 IEEE.
A novel arp approach for cloud resource management
(Blue Eyes Intelligence Engineering and Sciences Publication, 2019) Abhishek Kumar; K. Vengatesan; Rajiv Vincent; M. Rajesh; Achintya Singhal
Cloud computing proposes on-request arrange admittance to the calculating resources over virtualization. This changes in perspective the PC resources to the cloud giving price adequacy and it additionally gives versatile users openness to working resources. This proposal is execution prototypes of these frameworks with acceptance of entry of jobs to the framework and a work may comprise of numerous no.of jobs with every job needs a virtual machine for its implementation. This Paper consider both steady and variable task sizes in no.of jobs amid their administration times. On account of steady job estimate, this paperpermit distinctive classes of jobs, which are resolved over their entry and administration rates and no.of works in a job. In the multiple kind a job creates arbitrarily novel tasks amid its administration time. The last requires dynamic task of virtual machines to a work, which will be required in the versatile cloud. In the two cases, framework is displayed utilizing birth-demise forms. On account of consistent job measure, here decided joint likelihood dispersion of the quantity of works from every class in the framework, work delaying likelihoods and appropriation of the usage of resources for together heterogeneous and homogeneous kinds of virtual machines. Paper displayed mathematical results and any estimates are confirmed by usage result. © BEIESP.
A Survey on the Usage of Pattern Recognition and Image Analysis Methods for the Lifestyle Improvement on Low Vision and Visually Impaired People
(Pleiades journals, 2021) M. Anitha; V. D. Ambeth Kumar; S. Malathi; V. D. Ashok Kumar; M. Ramakrishnan; Abhishek Kumar; Rashid Ali
Abstract: According to World Health Organization in 2017 nearly 253 million people are visually impaired of whom 36 million are blind. Braille books involve the tactile format that helps the visually impaired people to gain knowledge but only a limited resource is available. Enormous papers and studies describe the method for obtaining machine readable document from textual image. In upcoming days character recognition might serve a key role to create a paperless environment that helps the visually impaired people to gain enormous amount of educational material. Handwritten script recognition is gaining vital importance in today’s electronically interconnected society. In the field of machine learning and pattern matching handwritten has gained lot of attention. This paper first summarizes the pros and cons of technologies developed for the visually impaired people in terms of education material obtained from text image and handwritten image. Along with that it presents a performance comparison of different methods. Finally, it describes the future research work in this domain. © 2021, Pleiades Publishing, Ltd.
Active volume control in smart phones based on user activity and ambient noise
(MDPI AG, 2020) V.D. Ambeth Kumar; S. Malathi; Abhishek Kumar; M. Prakash; Kalyana C. Veluvolu
To communicate efficiently with a prospective user, auditory interfaces are employed in mobile communication devices. Diverse sounds in different volumes are used to alert the user in various devices such as mobile phones, modern laptops and domestic appliances. These alert noises behave erroneously in dynamic noise environments, leading to major annoyances to the user. In noisy environments, as sounds can be played quietly, this leads to the improper masked rendering of the necessary information. To overcome these issues, a multi-model sensing technique is developed as a smartphone application to achieve automatic volume control in a smart phone. Based on the ambient environment, the volume is automatically controlled such that it is maintained at an appropriate level for the user. By identifying the average noise level of the ambient environment from dynamic microphone and together with the activity recognition data obtained from the inertial sensors, the automatic volume control is achieved. Experiments are conducted with five different mobile devices at various noise-level environments and different user activity states. Results demonstrate the effectiveness of the proposed application for active volume control in dynamic environments. © 2020 by the authors Licensee MDPI, Basel, Switzerland.
An approach for remove missing values in numerical and categorical values using two way table marginal joint probability
(Science and Engineering Research Support Society, 2020) K. Vengatesan; E. Saravana Kumar; S. Yuvaraj; Punjabi Shivkumar Tanesh; Abhishek Kumar
Data analytics is a wide area which helps to extract the essential information from a huge volume of data. Data gathered from different sources are not in the same format, hence it is very difficult for pre-processing such data. Each and every data set has different categories of data types such as numerical or categorical data types. In this proposed work, we will discuss about identifying the missing values from the dataset using statistical techniques such as two-way table joint probability, two-way table marginal probabilities and two-way table conditional probability. The work also focuses on how to extract the essential features from the data set. Different visualization methods are used to easily understand the data set and feature prediction. © 2020 SERSC.
An effective method for predicting postpartum haemorrhage using deep learning techniques
(Springer, 2022) V. D. Ambeth Kumar; S.V. Ruphitha; Abhishek Kumar; Ankit kumar; Linesh Raja; Achintya Singhal
Postpartum haemorrhage is a type of blood loss that occurs after the birth of a baby. When you lose more than 500 ml of blood, your blood pressure drops, and you may suffer and die as a result. Deep learning techniques can predict postpartum hemorrhage earlier. As a result, we would be able to save the human. This paper discusses various types of deep learning techniques. This paper focuses on the concept of Convolutional neural networks and divides it into two sections: ZFnet and VGG-16net. By comparing the results of two nets, we can determine which of the techniques is best for predicting postpartum hemorrhage at an earlier stage. This study will be more beneficial to pregnant women in the future. The paper focuses on two nets that are said to be more useful and to be a standardized technique that also helps to give relevant medicine to patients at the appropriate time. In this paper, the algorithm is used for the VGG-16net, and the Confusion matrix is used for both nets to improve performance. Many metrics are used in this research to improve accuracy and results. Finally, the convolutional neural network concept of VGG-16net produced better results than ZF-net. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
An investigation on adaptive HTTP media streaming Quality-of-Experience (QoE) and agility using cloud media services
(Taylor and Francis Ltd., 2021) Selvaraj Kesavan; E. Saravana Kumar; Abhishek Kumar; K. Vengatesan
Web services is software entity allows machine to machine communication, operates as standalone unit and interoperability over network using standard web technologies such as Hypertext transfer protocol (HTTP) and eXtensible markup language (XML). With the rapid growth of cloud platform, infrastructure and emergence of multiple Digital transformation technologies, more and more conventional applications are transformed into web-based services. Service-based approach creates tremendous impact on multimedia content storage, retrieval, delivery and communication. With cloud infrastructure and service, get economically viable, real time, high resolution multimedia content on-the-go anywhere and everywhere using adaptive http streaming approach. This paper presents convergence of adaptive http streaming from conventional infrastructure to cloud enabled model and presents the advancement and architecture of adaptive http streaming delivery as a web-based service delivery approach. The detailed performance evaluation of conventional and cloud enabled service-based approaches were presented, and the metrics were compared from real-time experiment. By analyzing performance indices and characteristics, cloud enabled multimedia service delivery approach poses advantages, gives promising result and better user experience compare to the conventional adaptive HTTP streaming approach. © 2019 Informa UK Limited, trading as Taylor & Francis Group.
Analysis of Mirai Botnet Malware Issues and Its Prediction Methods in Internet of Things
(Springer Science and Business Media Deutschland GmbH, 2020) K. Vengatesan; Abhishek Kumar; M. Parthibhan; Achintya Singhal; R. Rajesh
The Internet of Things is progressively turning into a pervasive figuring service, requiring immense volumes of information stockpiling and preparing. Lamentably, because of the one of a kind qualities of asset requirements, self-association, and short-run communication in IoT, it generally depends on the cloud for outsourced capacity and calculation, which has realized a progression of new difficult security and protection dangers. The IoT peripherals are utilized in houses, industry, and prescription. The Mirai-botnet is the biggest enrolled botnet that utilizing the IoTs. At the pinnacle of its movement, the botnet figured out how to arrange a hack wherever around thousand devices partook. This paper gives a point by point investigation of mirai malware attacking issues and its forecast systems, particularly in the territory of IoT. © Springer Nature Switzerland AG 2020.
Anomaly based novel intrusion detection system for network traffic reduction
(Institute of Electrical and Electronics Engineers Inc., 2018) K. Vengatesan; Abhishek Kumar; Radhakrishana Naik; Deepak Kumar Verma
With the coming of anomaly based intrusion detection systems, numerous methodologies and strategies have been produced to track novel assaults on the systems. High detection rate of 98% at a low caution rate of 1% can be accomplished by utilizing these procedures. In spite of the fact that anomaly-based methodologies are productive, signature-based detection is favored for standard usage of intrusion detection systems. As an assortment of anomaly detection procedures were recommended, it is hard to look at the qualities, shortcomings of these strategies. The motivation behind why ventures don't support the anomaly-based intrusion detection techniques can be surely knew by approving the efficiencies of the every one of the strategies. To explore this issue, the present condition of the examination hone in the field of anomaly-based intrusion detection is surveyed moreover. In this paper, we utilize Deep learning strategies to actualize an anomaly based Novel-IDS. These procedures demonstrate the touchy intensity of generative models with great arrangement, capacities to reason some portion of its knowledge from inadequate data and the versatility. © 2018 IEEE.
Artificial intelligence-based novel scheme for location area planning in cellular networks
(John Wiley and Sons Inc, 2021) Vrince Vimal; Teekam Singh; Shamimul Qamar; Bhaskar Nautiyal; Kamred Udham Singh; Abhishek Kumar
Planning of location area (LA) in cellular networks plays a vital role in utilizing the resources efficiently and economically. Location update and paging costs directly affect the cost to the service provider. When the size of the Mobile Switching Centre (MSC) is large, the paging cost becomes maximum. Though, no location update is required for this case. On the contrary, paging cost shoots high if each cell forms individual LA, but in this case, location update cost shoots to the maximum value. Therefore, deducing the network to the optimal amount of LA's is an intractable combinatorial optimization problem. In this paper, we intend to optimize the partitions of the MSC service area into an optimal number of LA, to curtail the total location management cost. We propose a novel scheme bearing in mind cell attributes of the network to deduce an optimum number of location areas, leading to minimum cost per call. It is revealed by the results of this work, attained after simulating the scenario on MATLAB 2018a that Cell Attributes Based Algorithm is a very promising scheme for cellular networks, and it outperforms the existing algorithms in a practical scenario. © 2020 Wiley Periodicals LLC.
Askin tumor: A rare neoplasm of thoracopulmonary region
(Medknow Publications, 2016) Ankur Singh; Abhishek Abhinay; Abhishek Kumar; Rajniti Prasad; Amrita Ghosh; Om Prakash Mishra
Askin tumor is a rare neoplasm of thoracopulmonary region. But it mimics other common pediatric disorders, such as empyema, lymphoma, and tuberculosis, posing a great diagnostic and therapeutic challenge to the treating clinicians. So it is of utmost importance to make an early diagnosis and proper referral/treatment in such cases. We highlighted diagnostic challenge, treatment, and favorable outcome of a case that presented to us. © 2016 Indian Chest Society.
Assessment of Arsenic Removal Units in Arsenic-Prone Rural Area in Uttar Pradesh, India
(Springer, 2019) Abhishek Kumar; Malabika Biswas Roy; Pankaj Kumar Roy; John Mike Wallace
To mitigate arsenic contamination in Uttar Pradesh, India, the state government installed 365 arsenic removal units (ARUs) in arsenic-prone areas of the Ballia District for last 10 years. Each unit was capable of serving approximately 200–300 households. The local communities were to assume responsibility for the day-to-day operation and maintenance of the filters. A field survey was conducted to determine the outcome of the state government project based on a sample of 200 ARUs, very few of which are still functioning. It is shown that the project failed because the siting of the ARUs was less than optimal, many families living in villages with ARUs were denied access to or chose not to use the filtered water for socioeconomic reasons, and the ARUs were not properly maintained. Factors that contributed to the demise of the filters were the unavailability of filtration media and spare parts in local markets and a lack of participation of families in the communities responsible for maintaining the ARUs. The overall results conclude for operation and maintenance a constant monitoring is essential to sustain all installed ARUs at different locations. Also there is a training need assessment for the beneficiary group who run the individual unit through people’s participatory approach with optimum management related to hazardous sludge. © 2019, The Institution of Engineers (India).
Ayurvedic processed seeds of nux-vomica: Neuropharmacological and chemical evaluation
(2010) Chandrakant Katiyar; Abhishek Kumar; S.K. Bhattacharya; R.S. Singh
The effect of detoxification on Strychnos nux-vomica seeds by traditional processing with aloe and ginger juices (B), by frying in cow ghee (C), and by boiling in cow milk (D) was investigated. The ethanolic extracts of these samples were subjected to spontaneous motor activity (SMA), pentobarbitone-induced hypnosis, PTZ induced convulsions, diazepam-assisted protection, and morphine-induced catalepsy. All samples reduced SMA and inhibited catalepsy. The seeds processed in milk (D) showed the lowest strychnine content in the cotyledons, exhibited marked inhibition of PTZ induced convulsions and maximal potentiation of hypnosis, and were the safest (LD50). © 2009 Elsevier B.V. All rights reserved.
Black hole attack detection in vehicular ad-hoc network using secure AODV routing algorithm
(Elsevier B.V., 2021) Ankit Kumar; Vijayakumar Varadarajan; Abhishek Kumar; Pankaj Dadheech; Surendra Singh Choudhary; V.D. Ambeth Kumar; B.K. Panigrahi; Kalyana C. Veluvolu
Vehicular ad hoc networks (VANETs) has received significant attention in the research domain of intelligent transportation system (ITS) as they provide safety and security to drivers and passengers. As compared to mobile ad hoc networks (MANETs), VANETs are mainly different in terms of characteristics, and system architecture. Security in VANET has been an important issue as it effects the communication between both (V-2-V) vehicles-to-vehicle and (V-2-I) vehicle to infrastructure. In VANET, malicious attacks affect the security of the networks, and it is necessary to identify and prevent such security attacks. In VANET network, any node can function as a router for the others nodes, and a malicious node connected to the network may inject spoofed routing tables to the other nodes thereby affecting the operation of the network. To overcome this issue, a secure AODV routing protocol is developed for detection of black hole attack in this paper. The proposed method is a modified version of the original AODV routing protocol with improvements in the RREQ packet and RREP packet protocols. For added security, a cryptography function-based encryption and decryption is included to verify the source and destination nodes. The proposed approach is demonstrated on a NS-2.33 simulator using different network parameters like drop packets, end-to-end delay, and packet delivery ratio (PDR) and routing request overhead. Results demonstrate that the proposed method outperforms existing AODV routing protocol under black hole attack and improves the network performance. © 2020 Elsevier B.V.
Brain Inspired Visual Effects and Animation Psychological Computing Impact in Indian Television Advertisement Pre and Post 2000s
(IOS Press BV, 2021) Gondi Surender Dhanunjay; Pranjal Singh; Sayyad Samee; K. Vengatesan; Abhishek Kumar; Achintya Singhal
Technology in its immense boom in the last decade has made us aware of a lot of ways to increase consumer potential and engagement with different products in various spheres and aspects of production. Taking this idea forward, the main idea of this study is to identify the major visual effects facets being used and how they contributed towards consumer engagement. In this regard, a pilot study was done and then questionnaire has been prepared which was completed by 369 participants between the age group 18-60 years. Hence the main aim of this work is to use statistical data to understand how the last decade has proved beneficial for the Advertising industry through the use of visual effects Statistical analysis is used to interpret the data. © 2021 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).