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Mathematical analysis of the effect of process parameters on angular distortion of MIG welded stainless steel 202 plates by using the technique of response surface Methodology

Mathematical analysis of the effect of process parameters on...

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2019 Advances in Minerals, Metals, Materials, Manufacturing and Modelling, ICAM5 2019

作者： Pandit, Mayank Sood, Shruti Mishra, Prithu Khanna, Pradeep Department of Manufacturing Processes and Automation Engineering Netaji Subhas Institute of Technology New Delhi 110078 India

Gas Metal Arc Welding (GMAW) is a widely used semi-automated joining process used in metal fabrication and for producing good quality welds with high deposition rate. The process is versatile because of its ability to weld in all positions and the suitability of wide range of metals and alloys with compatible filler wire to get welded. The process further can be fully automated by using programmable robots thus making it suitable for mass production. Like other fusion welding processes, because of rapid heating and cooling cycles, various types of distortions are encountered, which are detrimental to the performance of the weld. Out of various kinds of distortions, the angular one is found to be prominent. This distortion once occurred require considerate amount of post-welding rectifications and creates design related issues because of the mismatch in the assembly. Therefore, the endeavour should be to keep this distortion minimum by selecting the weld parameters optimally. The present investigative work aims to study the effect of different individually controllable input parameters like wire feed rate, welding speed, voltage, standoff distance and torch angle on the resulting angular distortion of Stainless Steel 202 plates. SS 202 is manganese alloyed austenitic stainless steel, which is designed as a cost-effective alternative to 304 grades with similar corrosion and mechanical properties at lower temperatures and less harsh corrosive environment. By the use of statistical approach, an attempt has been made to develop a mathematical model that relates these input parameters to the response parameter which is angular distortion. This model would prove to be helpful in predicting the resulting angular distortion at different combinations of input parameters. Statistical technique of central composite face centred design has been used to develop the model and ANOVA is used to check the adequacy of the same. Response Surface Methodology (RSM) has been used to analy

关键词： Gas metal arc welding

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Recommending researchers in machine learning based on author-topic model

arXiv

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arXiv 2021年

作者： Sharma, Deepak Kumar, Bijendra Chand, Satish Department of Computer Engineering Netaji Subash Institute of Technology New Delhi India School of Computer & Systems Sciences Jawaharlal Nehru University New Delhi India

The aim of this paper is to uncover the researchers in machine learning using author-topic model (ATM). We collect 16,855 scientific papers from six top journals in the field of machine learning published from 1997 to 2016 and analyze them using ATM. The dataset is broken down into 4 intervals to identify the top researchers and find similar researchers using their similarity score. The similarity score is calculated using Hellinger distance. The researchers are plotted using t-SNE, which reduces the dimensionality of the data while keeping the same distance between the points. The analysis of our study helps the upcoming researchers to find the top researchers in their area of *** Codes H.4, I.7 Copyright © 2021, The Authors. All rights reserved.

关键词： Statistics

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Preface

Lecture Notes in Mechanical Engineering

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Lecture Notes in Mechanical engineering 2024年 v-vi页

作者： Singh, D.K. Hegde, Shriram Mishra, Ashutosh Department of Mechanical Engineering Netaji Subhas University of Technology Delhi New Delhi India Department of Applied Mechanics Indian Institute of Technology Delhi Delhi New Delhi India Department of Applied Mechanics Motilal Nehru National Institute of Technology Allahabad Uttar Pradesh Prayagraj India

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Designing a Project Leader Recommender System using Twitter Feed Analysis

Designing a Project Leader Recommender System using Twitter ...

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2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COMITCon 2019

作者： Rani, Poonam Shokeen, Jyoti Department of Computer Engineering Netaji Subhas University of Technology Delhi India Department of Computer Science and Engineering UIET Maharshi Dayanand University Rohtak India

ISBN: (纸本)9781728102115

People are increasingly using social media to share both their personal and professional interests. Though most social networks cater to no specific age group, in recent years, platforms such as Twitter have taken center stage for students to discuss and discover similar passions and areas of interest. In this paper, we first explore students' Twitter activity to determine the core interests of students and then propose a recommender system that assigns group leaders to projects. We use a clustering algorithm to group the students with similar interests in the projects. © 2019 IEEE.

关键词： Students

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Application of Monte Carlo simulation and artificial neural network model to probabilistic health risk assessment in fluoride-endemic areas

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Heliyon 2024年第24期10卷 e40887页

作者： Islam, Raisul Sinha, Alok Hussain, Athar Usama, Mohammad Ali, Shahjad Ahmed, Salman Gani, Abdul Hassan, Najmaldin Ezaldin Mohammadi, Ali Akbar Deshmukh, Kamlesh Department of Civil Engineering GLA University Mathura India Department of Environmental Science and Engineering IIT (ISM) Jharkhand Dhanbad India Department of Civil Engineering Netaji Subhas University of Technology New Delhi India Department of Environmental Science Integral University Lucknow India Department of Environmental Science Sharda School of Smart Agriculture Sharda University Agra Keetham Agra 282007 India Interdisciplinary Department of Remote Sensing and GIS Applications Aligarh Muslim University Aligarh India Department of Civil and Environment Engineering University of Zakho Kurdistan Region Iraq Department of Environmental Health Engineering Neyshabur University of Medical Sciences Neyshabur Iran Department of Computer Science and Engineering Anand Engineering College Agra India Workplace health research center Neyshabur University of Medical Sciences Neyshabur Iran

Groundwater contamination with fluoride is a considerable public health concern that affects millions of people worldwide. The rapid growth of urbanization has led to increase in groundwater contamination. The health risk assessment focuses on both acute and chronic health consequences as it investigates the extent and effects of fluoride exposure through contaminated groundwater. Fluoride exposure, especially in endemic locations, has serious health consequences, including dental and skeletal fluorosis. An accurate assessment of these hazards is essential for public health planning and mitigation actions. The present study uses Monte Carlo Simulation (MCS) and an Artificial Neural Network (ANN) model to perform a Probabilistic Health Risk Assessment on populations in fluoride-endemic areas. Analysis of the results of the study reveals that the concentration of fluoride ranged from 0.58 to 3.80 mg/L with an average of 2.30 mg/L across the Kasganj district, which was higher than permissible limits given by BIS and WHO. The highest value of hazard quotient of 3.29 for Children is found to be in the Durga Colony area, while the lowest value of the hazard quotient of 0.31 for adults is found to be in the Nadrai Gate area. The assessment of health risks revealed a high probability of non-carcinogenic disease from the consumption of groundwater containing fluoride. The ANN model has the R² value of 0.9989 in training and 0.9870 in testing while RMSE value in training and testing was 0.02230 and 0.0267. The findings suggest that before being used, the groundwater in Kasganj, Uttar Pradesh, India, needs to be treated and made drinkable. The results emphasize the critical need for ongoing monitoring, public education initiatives, and implementing feasible mitigating techniques to lower fluoride exposure. The findings show that this hybrid model is excellent at addressing the numerous uncertainties associated with fluoride use, hence improving the reliability of he

关键词： Artificial neuro network Fluorosis Kasganj area Monte Carlo simulation Probabilistic health risk assessment

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An Intelligent Prediction Model of COVID-19 in India using Hybrid Epidemic Model

An Intelligent Prediction Model of COVID-19 in India using H...

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Smart Electronics and Communication (ICOSEC), International Conference on

作者： Manoj Kumar Jatin Bareja Manjot Singh Rupanshu Sharma Department of Computer Science & Engineering Delhi Technological University Delhi India Manufacturing process and automation engineering Netaji Subhas Institute of Technology Delhi India

ISBN: (数字)9781728154619

ISBN: (纸本)9781728154626

This article presents the current situation of COVID 19 spread in India and how it is impacted by various measures taken by the administration. Data source is taken (till 15th June 2020) from World Health organization (WHO) to study various trends and pattern. Hybrid epidemic susceptible-infected recovered model is used to make predictions at every stage of coronavirus. The basic reproduction number R 0 , is constructed using a logistic function. An improved or hybrid epidemic model is build based on various other factors to build a logistic infection rate to analyse the patterns and trend in the data. Secondly, ICU beds and ventilators available per 100,000 inhabitants is also taken in account for critical. Also, the timeline for changing the stage of coronavirus is used from various reliable resources. Moreover, in comparison with the traditional SIR models, accuracy in the predictions has significantly increased with the R 2 value of 96.8 percent for the future days in India.

关键词： Sociology Statistics Predictive models Diseases Mathematical model Viruses (medical) Market research

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A Study on Discrete Mathematics: Sum Distance in Neutrosophic Graphs with Application

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Neutrosophic Sets and Systems 2020年 35卷 220-231页

作者： Das, Kousik Samanta, Sovan Khan, Shah Khalid Naseem, Usman De, Kajal Department of Mathematics D. J. H. School West Bengal Dantan721451 India Department of Mathematics Tamralipta Mahavidyalaya West Bengal 721636 India School of Engineering RMIT University CarltonVIC3053 Australia School of Computer Science University of Technology Sydney Ultimo Australia School of Sciences Netaji Subhas Open University West Bengal Kolkata700091 India

Distance is an important parameter in any networks/ graphs. The idea of strong sum distance in the fuzzy graph was introduced by Tom and Sunitha (2015). A generalization of fuzzy graph called neutrosophic graph is more realistic to handle imprecise data. In this study, the weight of an edge of a neutrosophic graph is defined and hence defined sum distance in a neutrosophic graph based on the idea of strong sum distance. This distance is also metric and based on this metric, the concepts of degree, eccentricity, radius, diameter etc. are studied with some properties. At last, a real-life application on the travelling salesman problem is illustrated. © 2020. Neutrosophic Sets and Systems. All Rights Reserved.

关键词： Graphic methods

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Preface

Lecture Notes in Mechanical Engineering

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Lecture Notes in Mechanical engineering 2023年 v-vi页

作者： Hegde, Shriram Singh, D.K. Mishra, Abhishek Department of Applied Mechanics Indian Institute of Technology Delhi Delhi New Delhi India Department of Mechanical Engineering Netaji Subhas University of Technology Delhi New Delhi India Department of Mechanical Engineering National Institute of Technology Delhi Delhi New Delhi India

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Figure of Merit Enhancement of Surface Plasmon Resonance Biosensor Using Ga-Doped Zinc Oxide in Near Infrared Range

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Photonic Sensors 2020年第4期10卷 340-352页

作者： Sarika PAL Alka VERMA Y.K.PRAJAPATI J.P.SAINI Department of ECE National Institute of Technology UttarakhandSrinagarGarhwal 246174India Department of ECE Institute of Engineering and Rural TechnologyAllahabadPrayagrajUttar Pradesh 211002India Department of ECE Motilal Nehru National Institute of Technology AllahabadPrayagrajUttar Pradesh 211004India Department of ECE Netaji Subhas University of Technology(NSUT)New Delhi 110078India

This work presents a surface plasmon resonance biosensor for the figure of merit enhancement by using Ga-doped zinc oxide(GZO),i.e.,nanostructured transparent conducting oxide as plasmonic material in place of metal at the telecommunication ***-dimentional graphene is used here as a biorecognition element(BRE)layer for stable and robust adsorption of *** is possible due to stronger van der Waals forces between graphene’s hexagonal cells and carbon-like ring arrangement present in *** proposed sensor shows improved biosensing due to fascinating electronic,optical,physical,and chemical properties of *** work analyses the sensitivity,detection accuracy,and figure of merit for the GZO/graphene SPR sensor on using the dielectric layer in between the prism and *** highest figure of merit of 366.7 RIU^(−1) is achieved for the proposed SPR biosensor on using the nanostructured GZO at the 3000 nm dielectric *** proposed SPR biosensor can be used practically for sensing of larger size biomolecules with due availability of advanced techniques for the fabrication of the nanostructured GZO and graphene.

关键词： SPR transparent conducting oxide Ga-doped zinc oxide sensitivity(S) detection accuracy figure of merit

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Predictive Maintenance of Air Conditioning Systems Using Supervised Machine Learning 20

Predictive Maintenance of Air Conditioning Systems Using Sup...

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20th International Conference on Intelligent System Application to Power Systems, ISAP 2019

作者： Trivedi, Shrishti Bhola, Sahil Talegaonkar, Archit Gaur, Prerna Sharma, Shreya Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India Computer Science Engineering Indraprastha Institute of Information Technology New Delhi India

ISBN: (纸本)9781728131924

Various types of faults can occur in an air conditioner resulting in a decrease in efficiency, a rise in energy consumption, and increasing maintenance costs. Hence predictive maintenance becomes important. In this paper, the two most common types of faults - gas leakage and capacitor malfunction have been detected using the decision tree machine learning algorithm. The data for faulty and operating air conditioners have been collected using distributed sensors, microcontroller, and dedicated circuitry and analyzed using MATLAB Classification App Learner Toolbox. The results obtained by the decision tree for fault detection and diagnosis and load monitoring were then compared with results obtained by support vector machine and the prediction accuracy for the decision tree was found to be higher. The presented research work can identify the air conditioner which is faulty as well as predicts the type of fault at an early stage to do maintenance beforehand. © 2019 IEEE.

关键词： Air conditioning

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