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Optimization of process Capability Index for Ultrasonic Machining of WC-Co Composite 2

Optimization of Process Capability Index for Ultrasonic Mach...

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2nd international conference on Computational modelling, simulation and Optimization, ICCMSO 2023

作者： Kataria, Ravinder Kumar, Jatinder National Institute of Fashion Technology Department of Fashion Design Srinagar India National Institute of Technology Department of Mechanical Engineering Kurukshetra India

ISBN: (纸本)9798350326666

In manufacturing industries, the demand of WC-Co composite is flourishing because of the distinctive characteristics it offers, such as;toughness (with hardness), good dimensional stability, higher mechanical strength etc. WC-Co composite materials are machined using conventional and non-conventional techniques. However, these techniques have their own limitations, in the perspective of deteriorated surface quality (cracks, heat affected zone, recast layer), high cutting forces and alteration of mechanical properties. The present investigation is aimed at studying the impact of different experimental conditions (by varying cobalt content, thickness of work piece, tool profile, tool material, abrasive grit size and power rating) on process capability of ultrasonic machining process for WC-CO composite material. The process capability index has been evaluated for the different experiments planned as per Taguchi L36 OA and further optimized as per DOE methodology. Significant factors for the index have been identified through Analysis of variance and the optimized process setting has been realized. it is concluded that evaluation of process capability index is of utmost importance for a mechanical energy based process like USM, where the dimensional inaccuracy such as hole oversize is significant and the machining databases are lacking any kind of information on it. © 2023 IEEE.

关键词： Taguchi methods

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Modeling Hot Rolling process Forces Using Bio-Inspired Metaheuristic Search Algorithm 2

Modeling Hot Rolling Process Forces Using Bio-Inspired Metah...

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2nd international conference of Intelligent Methods, Systems and Applications, IMSA 2024

作者： Sheta, Alaa Braik, Malik Oznergiz, Ertan Elashmawi, Walaa H. Rausch, Peter Othman, Emad S. Southern Connecticut State University Department of Computer Science New HavenCT United States Al-Balqa Applied University Computer Science Department Salt Jordan Istanbul Technical University Mechanical Engineering Faculty Istanbul Turkey Misr International University Dept of Computer Science Cairo Egypt George Simon Ohm Univ. of Applied Sciences Computer Science Department Nuremberg Germany AL-Shorouk Academy Management Information System Dept. Cairo Egypt

ISBN: (纸本)9798350362633

This research introduces the application of an innovative bio-inspired metaheuristic technique, termed the Crow Search Algorithm (CSA), to model a crucial industrial process - hot rolling manufacturing. Inspired by the foraging patterns of crows, the CSA algorithm has demonstrated its prowess in solving diverse optimization challenges. In the context of this study, the CSA algorithm is harnessed to fine-tune the parameters of a simulation model focused on predicting the force exerted during a hot rolling procedure. The proposed model takes into consideration a range of influential factors, including the initial temperature (Ti), width (Ws), carbon equivalent (Ce), gauge (hi), draft (i), and roll diameter (R). The findings underscore the CSA's capability to deliver an exceptional modeling performance characterized by swift convergence and high solution quality. By getting along very well with the proposed model with the CSA algorithm, a robust and efficient avenue to optimize the hot rolling process emerges, with the potential for expansion into other manufacturing domains. The computational and simulation results demonstrated that the proposed approach-based CSA outperformed different meta-heuristic search algorithms, such as the Salp Swarm Algorithm (SSA), Dandelion Optimizer (DO), Particle Swarm Optimization (PSO), Gray Wolf Optimizer (GWO), and Moth-Flame Optimization (MFO), in all test cases. The CSA has achieved the highest coefficient of determination (R2), equal to 0.97244, and the lowest mean squared error (MSE), equal to 1904.97, compared to its opponent algorithms. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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MEMS Design process Based simulation and Analysis of a Hypothetical Sensor Design with Electromechanics Interface 2nd

MEMS Design Process Based Simulation and Analysis of a Hypot...

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2nd international conference on Data Security and Privacy Protection, DSPP 2024

作者： Sathish, K. Ravikumar, C.V. Su, Chunhua Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Deemed University Chennai602105 India School of Electronics Engineering Vellore Institute of Technology Vellore632014 India Division of Computer Science University of Aizu Aizuwakamatsu City Fukushima965-8580 Japan

ISBN: (纸本)9789819785452

This study simulates and examinesthe MEMS design process for a hypothetical sensor with an electromechanical interface. Conceptualizing the sensor entails establishing its purpose, operational environment, and capacitive sensing mechanism for sensitivity and precision. Geometric and physical models are developed using advanced COMSOL Multiphysics software to create a moveable proof mass supported by micro-fabricated beams. Static and dynamic finite element analysis (FEA) simulations can be used to evaluate the sensor’s mechanical reaction to input signals and electrode electrostatic forces. This guarantees that mechanical signals are properly transformed into electrical signals. These data are evaluated to determine the best performance criteria such as sensitivity, linearity, and thermal stability, resulting in iterative design improvements. Robustness analysis, including tolerance and FMEA, ensures dependability. Additionally, typical MEMS manufacturing technologies are being examined for fabrication. This simulation-driven strategy prioritises electro-mechanical interface issues throughout the design process, resulting in high-performance, and dependable MEMS sensors for a wide range of applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Microchannels

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2nd international conference on Modeling and simulation of Social-Behavioral Phenomena in Creative Societies, MSBC 2022

2nd International Conference on Modeling and Simulation of S...

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2nd international conference on Modeling and simulation of Social-Behavioral Phenomena in Creative Societies, MSBC 2022

ISBN: (纸本)9783031337277

The proceedings contain 15 papers. The special focus in this conference is on Modeling and simulation of Social-Behavioral Phenomena in Creative Societies. The topics include: Behavioral Model of Interaction Between Economic Agents and the Institutional Environment;attitudes to Vaccination: How the Opinion Dynamics Affects the Influenza Epidemic process;free-Rider Problem: Simulating of System Convergence to Stable Equilibrium State by Means of Finite Markov Chain Models;econometric Modeling of Adaptation of the Russian Economy to Western Countries’ Sanctions;improved Free Disposal Hull Methodology for China Provinces Effective Social-Economic Development Modeling;dynamics of the Long-Term Orientation in Russian Society Over the Past 100 years: Results of the Analysis of the Russian Subcorpus of Google Books Ngram;editorial;studying Simulated Mobs Using Monte Carlo Method and the Theory of Collective Action;sustainable Development Issues of the Belt and Road Initiative in Educational Modeling Cases;carbon Dioxide Emissions modelling Along the Route Using Various Transportation Modes;Research on the Prediction of Highly Cited Papers Based on PCA-BPNN;logical Dimension in Modeling;quantification of Textual Responses To Open-Ended Questions In Big Data.

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The Acceptance of Machine module in the Hospitality Industry with Prospects and Challenges: A Review 2

The Acceptance of Machine module in the Hospitality Industry...

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2nd international conference on Computational modelling, simulation and Optimization, ICCMSO 2023

作者： Rohit Sethi, Kapil Sharma, Milan Gusain, Amit Ct University School of Hotel Management Airline and Tourism Ludhiana India Bahra University Computer Science and Engineering Himachal Pradesh Solan India Sgt University Faculty of Hotel and Tourism Management Gurgaon India

ISBN: (纸本)9798350326666

In the growth of technology there have been some discussions recently regarding the use of such technology and how they affect hotels function as technology has advanced, the hotel sector has begun using state-of-the-art technologies such as Machine Learning (ML) and robots. Several recent discussions have been held on the use of these technologies and how they affect the cost of running hotels. With these new technologies becoming increasingly important, this paper examines the trend of the hotel industry's adoption of machine learning and robotics. To determine the fundamental elements that influence ML adoption, we used the TOE framework across three domains: technology, organization, and environment. The finding expose the hotels are using ML and robotics due to the numerous factors that influence their adoption. The study illustrates how machine learning could be implemented in the hospitality sector and is one of the initial efforts to explore the full scope of how it may be applied. © 2023 IEEE.

关键词： Robotics

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Predictive modelling of Anaemia Using Clinical And Laboratory Data 2

Predictive Modelling of Anaemia Using Clinical And Laborator...

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2nd international conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Yaswanth, M. Prasad, R. Ganga Siva Mahesh, P. Mudgal, Himanshu Chawla, Pronika Dept of Computer Science SET MRIIRS Faridabad India Dept of Biotechnology SET MRIIRS Faridabad India

ISBN: (纸本)9798331541217

Anaemia is a widespread medical condition which is characterized by a deficiency of red blood cells or hemoglobin that leads to various health issues. Early diagnosis and the efficient monitoring of anaemia are essential for treatment and prevention of health risks from anaemia. Generally, diagnosis of anaemia involves collection of clinical data from patient and laboratory tests, which are expensive and time-consuming process. With the advancements of machine learning techniques, there are different ways to automate the diagnosis process, which enables faster and accurate anaemia detection based on hematological data. This paper proposes a machine learning system for anaemia detection using Logistic Regression. The objective of this work is creating a web- based platform which predicts anaemia in individuals based on key medical data like gender, hemoglobin levels, MCV (Mean Corpuscular Volume), MCH (Mean Corpuscular hemoglobin), MCHC (Mean Corpuscular Hemoglobin Concentration), aiding for healthcare professionals with better accurate diagnostics. It also addresses the need for accessible and cost-effective tools for settings of resource limited. Even the system offers an automated, faster and non-invasive diagnostic approach. © 2024 IEEE.

关键词： Logistic regression

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Enhancing Medical Image Analysis and Disease Surveillance in Healthcare: A Study on PSO- ACO Optimization using Swarm Intelligence 2

Enhancing Medical Image Analysis and Disease Surveillance in...

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2nd international conference on Computational modelling, simulation and Optimization, ICCMSO 2023

作者： Kaur, Simran Singh, Jaspreet Chandigarh University Computer Science & Engineering Mohali India

ISBN: (纸本)9798350326666

Medical Image Analysis and Disease Surveillance plays a crucial role in the healthcare industry, allowing for early detection and diagnosis of diseases. However, the complexity and size of medical images and healthcare data make analysis and surveillance a challenging task. This research paper proposes a hybrid PSO-ACO algorithm that utilizes the strengths of both the algorithms to investigate the clustering of medical images and improve disease surveillance in a cloud computing and IoT environment. The data sources used for this study includes medical images and patient records from various hospitals. This study presents the implementation of the algorithm in the cloud computing and IoT environment, and evaluates its performance using various metrices such as accuracy, sensitivity, specificity and Fl score of medical image analysis and disease surveillance. The algorithm was able to select the most relevant features from medical images, reducing the computational time and improving the accuracy of the analysis. This study provides a foundation for further research in the area and highlights the potential benefits include diagnostic accuracy, faster diagnosis by using PSOACO technique in healthcare system. © 2023 IEEE.

关键词： Medical imaging

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Tata Steel Stock Forecasting Using Deep Learning 2

Tata Steel Stock Forecasting Using Deep Learning

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2nd international conference on Computational modelling, simulation and Optimization, ICCMSO 2023

作者： Kumar, Dinesh Gupta, Meenu Kumar, Rakesh Chandigarh University Computer Science Engineering Punjab India

ISBN: (纸本)9798350326666

Trend finding in Stock market is highly unpredictable due to the heavy buying and selling of the stocks. Tata Steel holds the highest capital of the steel industry and it holds the heavy volume of the particular stock. Tata Steel is a flagship company of the Tata Group. In this study, Tata Steel stock movement was predicted with the help of deep learning pre-trained SCNN and Inception V3 Model. The dataset uses from May 2018 to May 2023, and the dataset is classified into three different category Holding position, Bearish, and Bullish classes with the help of expert opinion. MACD (Trend following), BB indicator (Volatility), Candlestick (price action), and Volume technical indicator uses to train the model. The dataset is based om 1 day time frame from May 2018 to May 2023 followed by image form and the image is screen scrap by trading ***. The SCNN model reported 95.6% accuracy and the Inception V3 model reported 93.4% accuracy. This study does not include any sentimental approach. © 2023 IEEE.

关键词： Support vector machines

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2nd international conference on Renewable Power, ICRP 2023

2nd International Conference on Renewable Power, ICRP 2023

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2nd international conference on Renewable Power, ICRP 2023

ISBN: (纸本)9789819967483

The proceedings contain 68 papers. The special focus in this conference is on Renewable Power. The topics include: The Airfoil Design for Small-Scale Wind Turbines in Maximizing Renewable Wind Energy;Comparative Study on Solar PV Module Performance with Sun Irradiance Trapping Mechanism: Power Generation Forecasting Using Machine Learning;the Geometric modelling and Linearization of Small-Scale Wind Turbine Blades for Optimized Renewable Energy;performance Analysis of H-Type Vertical Axis Wind Turbine by Using Novelty Numerical Simulink Method;energy Production from Various Bio-wastes Under Different Electrode and Temperature Conditions: Experimental Study;simulation and Prototype Design of Hybrid Renewable Energy Harvesting System;design and Development of an Inexpensive Intelligent Device for Sag Measurement for Overhead Transmission Lines;Gradient Descent Back-Propagation Through Momentum (GDBPM) Endorsed icos Control Technique-Based DSTATCOM Intended for Shunt Indemnification;improvement in Voltage Stability of the System Due to Increased Penetration of Electric Vehicles Using Distributed Solar Photovoltaic Sources;an Efficient Algorithm for Energy Management in Smart Grid for Various Improvements;an Intelligent System for Furfural Estimation in the Power Transformers;Design of PID-Tuned Controller for Automatic Voltage Regulator for Frequency Stability in thermal Power Plant;optimization of Distributed Generators in a Virtual Power Plan Using Mixed Integer Linear Programming Method;solving Unit Commitment Problem Using Mixed Integer Linear Programming for Demand Side Management;deployment of Renewable Embedded Generation and Unified Power Quality Conditioner in Distribution System using Firefly Algorithm;application of Wind Power in Backwashing Filter Media;mixed Reality Accelerates the Designing process in Automotive Industry.

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Research on computer 3D simulation Construction System in Urban Landscape Design 2

Research on Computer 3D Simulation Construction System in Ur...

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2nd international conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2023

作者： Wei, Liu Chongqing College of Architecture and Technology Chongqing401331 China

ISBN: (纸本)9798350339765

In this paper, based on virtual reality, generation rules are used to represent the rules in landscape design. Secondly, formalized expression of the suitability rules and spatial layout rules of landscape greening is carried out, and corresponding knowledge base is constructed. Design the process of collecting landscape 3D image data. Three dimensional graphical simulation decision analysis method is used. Determine that the data is in conformity with the plan specification. Through the least number of objects, the motion vector, rotation matrix and scale coefficient are obtained, and the eigenvalues of the image are obtained. Finally, a new environmental impact simulation system is constructed. The test and simulation results show that the authenticity of the landscape design scheme is more than 95%. © 2023 IEEE.

关键词： Knowledge based systems

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