Search results for: Amit Kr. Jain

Authors: Sarbjit Singh, Amit Kumar Lal

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In India there is no governing body to control advertisement apart from ASCI due to which most of the companies are targeting children in their advertisements that have a negative impact on their behaviour. The main purpose of this research paper is to find out the impact of the television advertisement on the behaviour of the children as observed and reported by parents. The exploratory research design is adopted by using in-depth interviews with 20 parents in various cities of Punjab on the basis semi-structured interviews a self-administered structured Questionnaire was developed for data collection. Exploratory factor analysis using varimax rotation is used to analyse the data from 100 parents from the conjoint cities of Punjab. (Jalandhar, Amritsar and Ludhiana) The finding suggests that children demand those products which are more advertised. Parents believe that television advertisements are affecting the study of their children. Moreover, the children are becoming more violent, stubborn and rebellious. They try to start copying from the advertisements and indulge in bad habits. Children demand, nag and pester their parents to purchase the advertised product. This research paper would help advertisers to understand children behaviour towards advertisements and more over what should be done to control the negative impact of advertisement on children. Advertisers can also understand the parental perception towards advertisement.

Keywords: advertisement, consumer behaviour, children perception, teen marketing

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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

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Authors: Rajiv Kumar, Amit Sachan, Arindam Mukherjee

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Despite the transparency and benefits of e-government, and its potential to serve citizens better, there is low diffusion and adoption of e-government services in India. Limited access to computer and internet, lack of computer and internet skills, low trust in technology, and risk associated in using e-government services are major hindrances in e-government adoption in India. Despite a large number of citizens belonging to the non-adopter category, the government has made some services mandatory to be accessed online where citizens have no other choice. Also despite the digital divide, a large number of citizens prefer online access to government services. In such cases intermediaries like common service centers, internet café and services agents’ roles are significant for accessing e-government services. Hence research is needed to explore this. The study aims to investigate the role of intermediaries in online access to public services by citizens. Qualitative research methodology using semi-structured interview was used. The results show that intermediaries play an important role in bridging the digital divide. The study also highlights on what circumstances citizens are taking help of these intermediaries. The study then highlights its limitations and discusses scope for future study.

Keywords: adoption, digital divide, e-government, India, intermediaries

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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

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Authors: Samereh Abdoli, Amit Vora, Anusha Vora

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Background: Diabetes burnout is one of the most common contributors to decreased quality of life, poor psychosocial well-being, and increased morbidity, mortality and diabetes cost. While the term diabetes burnout is widely accepted particularly in type 1 diabetes (T1D), the state of the science on diabetes burnout is lacking a systematic approach to overcome diabetes burnout. Objective: The study aimed to explore the strategies to overcome burnout by integrating the voices of individuals with T1D. Methods: In this study, we applied a descriptive qualitative design using YouTube videos produced by individuals with T1D. Seven YouTube videos (Austria= 1, U.S=6) with the highest rate of views which met the inclusion criteria were analyzed using a qualitative content analysis approach. Results: Participants verbalized overcoming diabetes burnout as a 'difficult hole to climb out of' which make them empowered. Themes that describes their strategies to overcome burnout in T1D, in general, include; 'make plan and take action', 'start with small steps', 'ask for help', 'get engage in diabetes community' and 'do not be perfect'. Future Work: These findings can begin the examination of different strategies to overcome diabetes burnout, which may change the course of action for diabetes care and management to improve quality of diabetes care and quality of life.

Keywords: diabetes burnout, type 1 diabetes, qualitative research, YouTube videos

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Authors: Hossein Lotfizadeh, André McDonald, Amit Kumar

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Renewable energy resources, which can supplement space and water heating for residential buildings, can have a noticeable impact on natural gas consumption and air pollution. This study considers a technical analysis of a combined solar water heating system with evacuated tube solar collectors for different solar coverage, ranging from 20% to 100% of the total roof area of a typical residential building located in Edmonton, Alberta, Canada. The alternative heating systems were conventional (non-condensing) and condensing tankless water heaters and condensing boilers that were coupled to solar water heating systems. The performance of the alternative heating systems was compared to a traditional heating system, consisting of a conventional boiler, applied to houses of various gross floor areas. A comparison among the annual natural gas consumption, carbon dioxide (CO₂) mitigation, and emissions for the various house sizes indicated that the combined solar heating system can reduce the natural gas consumption and CO₂ emissions, and increase CO₂ mitigation for all the systems that were studied. The results suggest that solar water heating systems are potentially beneficial for residential heating system applications in terms of energy savings and CO₂ mitigation.

Keywords: CO2 emissions, CO2 mitigation, natural gas consumption, solar water heating system

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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

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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

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Authors: Vikas Chawla, Buta Singh Sidhu, Amita Rani, Amit Handa

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The main objective of the present work is microstructural and mechanical characterization of the conventional and nanostructured TiAlN and AlCrN coatings deposited on T-11 boiler steel. In case of conventional coatings, Al-Cr and Ti-Al metallic powders were deposited using plasma spray process followed by gas nitriding of the surface which was done in the lab with optimized parameters after conducting several trials on plasma-sprayed coated specimens. The physical vapor deposition process (PAPVD) was employed for depositing nanostructured TiAlN and AlCrN coatings. The field emission scanning electron microscopy (FE-SEM) with energy dispersive X-ray analysis (EDAX) attachment, X-ray diffraction (XRD) analysis, atomic force microscopy (AFM) analysis and the X-Ray mapping analysis techniques have been used to study surface and cross-sectional morphology of the coatings. The surface roughness and micro-hardness were also measured. A good adhesion of the conventional thick TiAlN and AlCrN coatings was found. The coatings under study are recommended for the applications to super-heater and re-heater tubes of the boilers based upon the outcomes of the research work.

Keywords: nanostructure, physical vapour deposition, oxides, thin films, electron microscopy

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Authors: Subodh Kumar, Amit Varde

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Typical on-premises high-performance computing (HPC) environments consist of a fixed number and a fixed set of computing hardware. During the design of the HPC environment, the hardware components, including but not limited to CPU, Memory, GPU, and networking, are carefully chosen from select vendors for optimal performance. High capital cost for building the environment is a prime factor influencing the design environment. A class of software called “Job Schedulers” are critical to maximizing these resources and running multiple workloads to extract the maximum value for the high capital cost. In principle, schedulers work by preventing workloads and users from monopolizing the finite hardware resources by queuing jobs in a workload. A cloud-based HPC environment does not have the limitations of fixed (type of and quantity of) hardware resources. In theory, users and workloads could spin up any number and type of hardware resource. This paper discusses the limitations of using traditional scheduling algorithms for cloud-based HPC workloads. It proposes a new set of features, called “HPC optimizers,” for maximizing the benefits of the elasticity and scalability of the cloud with the goal of cost-performance optimization of the workload.

Keywords: high performance computing, HPC, cloud computing, optimization, schedulers

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Authors: Amit Saraswat, Ruchi Tewari

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Purpose: The research paper aims at understanding the alignment of business and IT in the Indian context and the business value attached to such an alignment. Methodology: The study is conducted in two stages. Stage one: Bibliographic research was conducted to evolve the parameters for defining alignment. Stage two: Evolving a model for strategic alignment to conduct an empirical study. The model is defined in terms of four fundamental domains of strategic management choice – business strategy, information strategy, organizational structure, and information technology structure. A survey through a questionnaire was conducted across organizations from 4 different industries and Structure Equation Modelling (SEM) technique is used for validating the model. Findings: In the Indian scenario all the subscales of alignment could not be validated. It could be validated that organizational strategy impacts information strategy and information technology structure. Research Limitations: The study is limited to the Indian context. Business IT alignment may be culture dependent so further research is required to validate the model in other cultures. Originality/Value: In the western world several models of alignment of business strategy and information systems is available but they do not measure the extent of alignment which the current study in the Indian context. Findings of the study can be used by managers in strategizing and understanding their business and information systems needs holistically and cohesively leading to efficient use of resources and output.

Keywords: business strategy, information technology (IT), business IT alignment, SEM

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Authors: Gupta Amit, Kumar Ramesh, P. C. Tewari

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Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model-based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies Economic Order Quantity (EOQ), Just in Time (JIT), Vendor Managed Inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.

Keywords: inventory policy, ranking, DBA, selection criteria

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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

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

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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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Authors: Ashish Kumar Jain, Deepak Mishra

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

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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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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

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Authors: Amit Verma, Pardeep Kaur

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In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there.

Keywords: component based development, clustering, back propagation algorithm, keyword based retrieval

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Authors: Radha Tomar, Satish K. Jain, Manish Panchal, P. S. Rathore

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In the presented work, inset fed microstrip patch antenna (IFMPA) based two port MIMO Antenna system has been proposed, which is suitable for wireless local area network (WLAN) applications. IFMPA has been designed, optimized for 2.4 GHz and applied for MIMO formation. The optimized parameters of the proposed IFMPA have been used for fabrication of antenna and two port MIMO in a laboratory. Fabrication of the designed MIMO antenna has been done and tested experimentally for performance parameters like Envelope Correlation Coefficient (ECC), Mean Effective Gain (MEG), Directive Gain (DG), Channel Capacity Loss (CCL), Multiplexing Efficiency (ME) etc and results are compared with simulated parameters extracted with simulated S parameters to validate the results. The simulated and experimentally measured plots and numerical values of these MIMO performance parameters resembles very much with each other. This shows the success of MIMO antenna design methodology.

Keywords: multiple-input and multiple-output, wireless local area network, vector network analyzer, envelope correlation coefficient

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Authors: Min Yu, Olivier T. Picot, Theo Graves Saunders, Ivo Dlouhy, Amit Mahajan, Michael J. Reece

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Graphene was successfully introduced into a polymer-derived silicon oxycarbide (SiOC) matrix by phase transfer of graphene oxide (GO) from an aqueous (GO dispersed in water) to an organic phase (copolymer as SiOC precursor in diethyl ether). With GO concentrations increasing up to 2 vol%, graphene-containing flakes self-assembled into a lamellar structure in the matrix leading to composite with the anisotropic property. Spark plasma sintering (SPS) was applied to densify the composites with four different GO concentrations (0, 0.5, 1 and 2 vol%) up to ~2.3 g/cm3. The fracture toughness of SiOC-2 vol% GO composites was significantly increased by ~91% (from 0.70 to 1.34 MPa·m¹/²), at the expense of a decrease in the flexural strength (from 85MPa to 55MPa), compared to SiOC-0 vol% GO composites. Moreover, the electrical conductivity in the perpendicular direction (σ┴=3×10⁻¹ S/cm) in SiOC-2 vol% GO composite was two orders of magnitude higher than the parallel direction (σ║=4.7×10⁻³ S/cm) owing to the self-assembled lamellar structure of graphene in the SiOC matrix. The composites exhibited increased electrical conductivity (σ┴) from 8.4×10⁻³ to 3×10⁻¹ S/cm, with the increasing GO content from 0.5 to 2 vol%. The SiOC-2 vol% GO composites further showed the better electrochemical performance of oxygen reduction reaction (ORR) than pure graphene, exhibiting a similar onset potential (~0.75V vs. RHE) and more positive half-wave potential (~0.6V vs. RHE).

Keywords: composite, fracture toughness, flexural strength, electrical conductivity, electrochemical performance

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Ekta Jain, Kalpana Dahiya, Vanita Verma

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This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory.

Keywords: assignment, imbalanced, priority, time minimization

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Authors: Abhijit Pattnayak, Abhijith N.V, Deepak Kumar, Jayant Jain, Vijay Chaudhry

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Hard and dense ceramic coatings deposited on the surface provide the ideal solution to the poor tribological properties exhibited by some popular stainless steels like EN-36, 17-4PH, etc. These steels are widely used in nuclear, fertilizer, food processing, and marine industries under extreme environmental conditions. The present study focuses on the development of Al₂O₃-CeO₂-rGO-based coatings on the surface of 17-4PH steel using High-Velocity Oxygen Flame (HVOF) thermal spray process. The coating is developed using an oxyacetylene flame. Further, we report the physical (Density, Surface roughness, Surface energetics), Metallurgical (Scanning electron microscopy, X-ray diffraction, Raman), Mechanical (Hardness(Vickers and Nano Hard-ness)), Tribological (Wear, Scratch hardness) and Chemical (corrosion) characterization of both As-sprayed coating and the Substrate (17-4 PH steel). The comparison of the properties will help us to understand the microstructure-property relationship of the coating and reveal the necessity and challenges of such coatings.

Keywords: thermal spray process, HVOF, ceramic coating, hardness, wear, corrosion

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Authors: Jitin Rahul, Manish Kumar Jain

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Dust pollution refers to the various locations, activities, or factors which are responsible for the releasing of pollutants into the atmosphere. The sources of dust can be classified into two major categories anthropogenic sources (man-made sources) and natural sources. Dust kicked up by heavy vehicles (Bus, Truck, Loaders, Tankers, car etc.) travelling on highways may make up approximately 33-40% of air pollution. Plants naturally cleanse the atmosphere by absorbing gases and particulate matter plants (Leaves). Plants are very good pollution indicator and also very good for dust capturing (Dust controlling). Many types tree species like Azadirachta indica A. juss, Butea monosperma (Lam.) Kuntz., Ficus bengalensis (Linn)., Pterocarpus marspium (Roxb.), Terminalia arjuna (Roxb, exDC.), Dalbergia sissoo roxb., and Ficus religiosa (Linn.) generally occur in roadside. These selected tree spiciness can control the dust pollution or dust capturing. It is well known that plants absorb particulate pollutants and help in dust controlling. Some tree species like (Ficus bengalensis, Ficus religiosa and Azadirachta indica) are very effective and natural means for controlling air pollution.

Keywords: dust, pollution, road, tree species

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Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

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Authors: Siamak Epackachi, Andrew S. Whittaker, Amit H. Varma

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An experimental program on steel-plate concrete (SC) composite shear walls was executed in the NEES laboratory at the University at Buffalo. Four large-size specimens were tested under displacement-controlled cyclic loading. The design variables considered in the testing program included wall thickness, reinforcement ratio, and faceplate slenderness ratio. The aspect ratio (height-to-length) of the four walls was 1.0. Each SC wall was installed on top of a re-usable foundation block. A bolted baseplate to RC foundation connection was used for all four walls. The walls were identified to be flexure-critical. This paper presents the damage to SC walls at different drift ratios, the cyclic force-displacement relationships, energy dissipation and equivalent viscous damping ratios, the strain and stress fields in the steel faceplates and the contribution of the steel faceplates to the total shear load, the variation of vertical strain in the steel faceplates along the length of the wall, near the base, at different drift ratios, the contributions of shear, flexure, and base rotation to the total lateral displacement, the displacement ductility of the SC walls, and the cyclic secant stiffness of the four SC walls.

Keywords: steel-plate composite shear wall, safety-related nuclear structure, flexure-critical wall, cyclic loading

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Authors: Ashish Kumar Agrahari, Amit Kumar

Abstract:

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore the atomistic level impact of PIGA mutations on the structure and dynamics of the protein. In the current work, we are mainly interested to get insights into the molecular mechanism of PIGA mutations. In the initial step, we screened the most pathogenic mutations from the pool of publicly available mutations. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and subjected to 50ns molecular dynamics simulation. Our computational study suggests that four mutations are highly vulnerable to altering the structural conformation and stability of the PIGA protein, which illustrates its association with PNH and MCAHS2 phenotype.

Keywords: homology modeling, molecular dynamics simulation, missense mutations PNH, MCAHS2, PIGA

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

Abstract:

Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, lévy flight distribution, optimization, improved multi–objective firefly algorithms, Pareto optimal

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Authors: Rajinder Pal Kaur, Amit Sharma, Anuj Kumar Sharma, Govind Prasad Sahu

Abstract:

The existence of chaos in the marine ecosystems may cause planktonic blooms, disease outbreaks, extinction of some plankton species, or some complex dynamics in oceans, which can adversely affect the sustainable marine ecosystem. The control of the chaotic plankton-fish dynamics is one of the main motives of marine ecologists. In this paper, we have studied the impact of phytoplankton refuge, zooplankton refuge, and fear effect on the chaotic plankton-fish dynamics incorporating phytoplankton, zooplankton, and fish biomass. The fear of fish predation transfers the unpredictable(chaotic) behavior of the plankton system to a stable orbit. The defense mechanism developed by prey species due to fear of the predator population can also terminate chaos from the given dynamics. Moreover, the impact of external disturbances like seasonality, noise, periodic fluctuations, and time delay on the given chaotic plankton system has also been discussed. We have applied feedback mechanisms to control the complexity of the system through the parameter noise. The non-feedback schemes are implemented to observe the role of seasonal force, periodic fluctuations, and time delay in suppressing the given chaotic system. Analytical results are substantiated by numerical simulation.

Keywords: plankton, chaos, noise, seasonality, fluctuations, fear effect, prey refuge

Procedia PDF Downloads 55