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Stability Analysis of Milling on Parallel Machine Tools 2

Stability Analysis of Milling on Parallel Machine Tools

引用

2nd international conference on automation, Robotics and computer engineering, ICARCE 2023

作者： Wang, Pengjia Zhu, Yushuo Wu, Wei Peng, Baoying School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing China School of Mechanical Engineering Ningxia Institute of Science and Technology Ningxia Shizuishan China

ISBN: (纸本)9798350308341

From the analysis of static and dynamic characteristics of parallel machine tools, it can be found that the stiffness and vibration response of machine tools in different positions are obvious, which will inevitably cause the phenomenon of instability in the milling process, so it is especially necessary to study the milling stability of parallel machine tools. First of all, this paper takes 6SPS parallel machine tool as the actual operation object, establishes the milling vibration model of its tool, and determines the key elements affecting the milling vibration model. The vibration signal of the parallel machine tool is collected through experiments, and the milling stability of the parallel machine tool is reflected by the method of expressing the vibration intensity through the root mean square of the vibration signal. The influence of milling parameters on milling stability under different positions is analyzed, and the spectral analysis method is adopted to identify the chattering phenomenon in the milling process. Finally, the weights of each milling parameter on vibration were determined by gray correlation analysis. © 2023 IEEE.

关键词： Milling (machining)

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Play Store App Analysis & Rating Prediction Using Classical ML Models & Artificial Neural Network 7

Play Store App Analysis & Rating Prediction Using Classical ...

引用

2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Moharana, Bhimasen Biswal, Bhramara Bar Dey, Snehasis Rath, Manas Kumar Banerjee, Shobhan Lovely Professional University Department of Computer Science and Engineering Punjab India College of Engineering P.G. Department of Computer Science & Applications Bhubaneswar India College of Engineering Electronics & Telecommunication Engineering Bhubaneswar India Maharaja Sriram Chandra Bhanja Deo University Department of Computer Application Baripada India Birla Institute of Technology and Science Department of Engineering Technology Pilani India

ISBN: (纸本)9798350304268

Each app available in the App Store or Play Store has various aspects linked to it such as its version, category, number of installations, genre, etc. which makes it unique, robust & popular. The reviews and ratings given by end users play an important role for both the developers and other users for the performance and survival of the app in the marketplace. Reviews are just a description for justification of the rating given by a user & the rating plays an important role in the first look. In this paper, we have used the Play Store Analysis Dataset to descriptively analyze the various attributes present in it and create models that predict the rating of an app, given its specifications. The models have been compared based on a common accuracy metric based on which their reliability can be judged and used in real-time rating predictions for a new application in the store for which a certain amount of data is available over some period. © 2023 IEEE.

关键词： Descriptive Statistics ML Classification Models Model Comparison Play Store App Analysis Rating Prediction

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Intelligent Systems for Data Driven Agriculture: Enhancing Farmer Productivity Through automation and Artificial Intelligence

Intelligent Systems for Data Driven Agriculture: Enhancing F...

引用

2024 international conference on Smart Systems for Electrical, Electronics, Communication and computer engineering, ICSSEEC 2024

作者： Lokesh, S. Madhavan, Arvind Ramanathan, R.M. Prakash Anand, Krteen PSG Institute of Technology and Applied Research Department of Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798350378177

Numerous obstacles endanger the livelihoods of smallholder farmers and global food security. Crop output losses due to plant diseases alone are estimated to be between 15% to 25% every year. However, farmers' capacity to recognize and treat illnesses in a timely manner is hampered by things like a lack of agronomic expertise, limited access to actionable insights, and information gaps. The work proposes a comprehensive end-to-end web application that uses machine learning models to help farmers with configurable expert advice, smart farm management, and automatic disease detection. Thus, enabling farmers to identify the infection using their smart phones and obtain crop - fertilizer recommendations for the crops to be treated in the farmer's area based on historical data analysis of yield-influencing elements such as geography, weather, and soil. The proposed system will employ Generative Artificial Intelligence, such as ChatGPT's natural language processing and generation capabilities, to engage in conversational interactions with farmers. The work achieves close to 95% accuracy after utilizing 30 epochs in the area of disease detection and 97% accurate models are achieved for fertilizer outputs. These features along with it's high accuracy can assist farmers in making informed decisions, utilising the data obtained to reduce crop output losses. © 2024 IEEE.

关键词： Smart agriculture

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Smart Vehicle Health Monitoring System Based On ARIMA and Ordinal Logistic Regression for Analysis of Vehicle Parameters

Smart Vehicle Health Monitoring System Based On ARIMA and Or...

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2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Mahaalakshmi, B. Padmapriya, R. Ellora Jeya Suji, J. Cloudin, S. Kcg College of Technology Department of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350315127

Existing Vehicle Monitoring Systems use an OBD-II device to retrieve problem codes and live data from the vehicle, which is then displayed to the user as raw data. A user-friendly system is required so that the user can grasp the vehicle's status on their own, preventing serious accidents. The purpose of this study is to produce a user-friendly and intelligible web application that allows the user to monitor the vehicle's health. The concept of the Internet of Vehicles (IoV) is discussed in this study, in which several vehicles form a network and communicate with one another. Machine learning models (Autoregressive Integrated Moving Average and Ordinal Logistic Regression) are used to estimate future vehicle conditions from available data and categorize the condition as 'Good ', 'Moderate,' or 'Bad'. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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7th international Russian automation conference, RusAutoCon 2024

7th International Russian Automation Conference, RusAutoCon ...

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7th international Russian automation conference, RusAutoCon 2024

ISBN: (纸本)9783031824937

The proceedings contain 37 papers. The special focus in this conference is on Russian automation. The topics include: Mapping and Path Planning Methods for Highly Automated Vehicles in Agriculture;morphological Analysis and Synthesis Features of Technological Processes;a Modern Method of Wireless Control of Unguarded Railway Crossings;duties and Obligations of the Railway Staff Concerned When the Microprocessorized Contactless Controlling Gauge Device Signal Is Triggered;integration of Automated Management Systems for Enterprises’ Transport and Technical Services;development of an automation Module for Planning Trajectories for Painting Aircraft Fuselage Elements;identification of Metal Sheets in the Flow, Based on the Marking Imprint, Using Neural Networks;study of the Performance of Adaptive Sensor Networks for Collecting and Processing Thermoelectric Data;development and Research of a Cartographic Model for Municipal Planning as the Basis of an Intelligent Geoinformation System;BIM Visual Programming of Bionic Architecture Construction Using Dynamo and Revit;development of a Model and Algorithms for Trigger Control of Technological Processes of Resource Provision;system for Statistical Assessment of Means of Controlling Engineers’ Qualification for Information Support to Manage the Recruiting Process in Industry;smart Enumeration Technology;comparative Analysis of C-Band Conical Horn Antenna Sparse Structures Characteristics at Different Frequencies;software Implementation of Heuristic Methods of Optimization and Integration into a Cloud Service;computer System for Modeling Fluid Flow Around Bodies and Its Potential in Industry;the Effect of Regular and Irregular Segmentations on Characteristics and Charge Distribution Densities of Microstrip Lines;reinforcement Learning with External Teacher for Building Energy Management.

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An Integration of Machine Learning and Big Data in for the Purpose of Healthcare and Its Impact 2

An Integration of Machine Learning and Big Data in for the P...

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2nd IEEE international conference on IoT, Communication and automation Technology, ICICAT 2024

作者： Raja, M.A. Kumhar, Bhupchand Femilin Jana, D Little Al-Farouni, Mohammed Kuppuraj, T. Jaiganesh, S. Nehru Institute of Technology T. M. Palayam Department of Electronics and Communication Engineering Tamil Nadu Coimbutore641105 India IES University M.P Bhopal462044 India Prince Shri Venkateshwara Padmavathy Engineering College Department of S&H Chennai India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Karpagam Academy of Higher Education Department of Computer Applications Coimbatore India Autonomous Department of Master of Computer Applications PSNA College of Engineering and Technology Tamil Nadu India

ISBN: (纸本)9798350368109

Due to its particular difficulties, multimorbidity - the living together of multiple chronic ailments in one person - requires expert care. Because they based themselves on single-disease models, present-day medical systems are frequently finding it difficult to meet the complicated needs of multimorbid patients. A basic amendment to how medical study and treatment are handled is important in order to enhanced how people make choices and care for people in this situation. An innovative method that deviates coming from conventional simplified techniques mixes intelligent machines (AI) with advanced big data metrics via live research. This approach uses widely gathered personal medical information to provide a full platform for study activities involving multimorbidity, including labeling, association, and predicting based on a number of interaction factors. The effective operation, standards, and particularly, for the merging of digital medical records into the same national while worldwide study infrastructure are necessary conditions for this evolution in method to occur. Above all else, it's critical that successful AI techniques - in specifically, deep learning - be effortlessly merged into medical their processes. This new method has the ability to totally change the topic of multimorbidity study, opening up the door to improve interactions between patients and better healthcare service. © 2024 IEEE.

关键词： Adversarial machine learning

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Adaptation for Case-based Reasoning Classifier: An Extended Framework With Introspection Learning Approach 2

Adaptation for Case-based Reasoning Classifier: An Extended ...

引用

2nd international conference on automation, Robotics and computer engineering, ICARCE 2023

作者： Zhao, Hui Gong, Zejun Innovation Lab of China Citic Bank Beijing China School of Civil and Transportation Engineering Beijing University of Civil Engineering and Architecture Beijing China

ISBN: (纸本)9798350308341

The learning ability has a great influence on further application development and generalization ability of Case based reasoning (CBR), the traditional CBR framework could not satisfy the strict performance requirement of certain complex scenarios, While the improvement of CBR classifier framework is also a challenging task. Therefore, in order to ensure the classification performance, improve the leaning ability, expand the range of fields of application. An adapted 5R framework for CBR classifier is proposed: A new case reconstitute process is added between case retrieve and case reuse, where a reconstitution strategy with risk factor based on introspective learning is proposed to evaluate the Credibility of suggested solutions, then divide the target cases into different groups, and conduct the revise on the cases that are evaluated as risky to guarantee the reliability of the results. What's more a weight optimization based on evolutionary computation is also proposed to improve the retrieval accuracy. The comparison experiment with other common models, indicates that the proposed 5R framework could provide a more accurate and reliable result, verifies the feasibility of the framework, proves that the proposed model has better learning ability, which could use the potential information from the risk factor, improve the classification accuracy, and guarantee the reliability at the same time. © 2023 IEEE.

关键词： Genetic algorithms

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Design and Implementation of Industrial Temperature Control System 2

Design and Implementation of Industrial Temperature Control ...

引用

2nd international conference on Advanced Manufacturing Technology and Manufacturing Systems, ICAMTMS 2023

作者： Tong, Yulong Wang, Chenyu Shen, Hai College of Communication Engineering Jilin University Changchun130022 China College of Physics Science and Technology Shenyang Normal University Shenyang110034 China

ISBN: (纸本)9781510667327

The technical realization of temperature control system plays a key role in the development of industrial automation. This paper designs a temperature control system with the heating furnace model as the controlled object, the heating furnace water temperature as the data acquisition object and controlled parameters, and the Siemens S7-1500 PLC as the lower computer controller. The PLC ladder diagram programming language in the software carries out the programming design of the lower computer, and combines the configuration and monitoring screen of the upper computer to design the configuration monitoring screen. At the same time, the function expansion and operation debugging are carried out to realize the monitoring and automatic control of the temperature data. © 2023 SPIE.

关键词： computer control systems

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Design and Implementation of IoT Smart System for Sensing Toxic Gas Emissions and Security System of Chemical Laboratories or Stores of Universities 10

Design and Implementation of IoT Smart System for Sensing To...

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10th international conference on automation, Robotics, and Applications, ICARA 2024

作者： Majeed, Ammar S Majdi, Hasan Sh. Mohammed, Hayder A Raheem, Leith Ali Abdul Hassooni, Ali Shaban Almaamori, Mohammed Hamza University of Baghdad Development Education Center Baghdad Iraq AI-Mustaqbal University College Chemical Engineering and Petroleum Industries Department Hilla Iraq University of Babylon Hilla Iraq College of Engineering University of Babylon Department of Electrical Engineering Hilla Iraq College of Engineering University of Babylon Department of Biomedical Engineering Hilla Iraq AI-Mustaqbal University Hilla Iraq

ISBN: (纸本)9798350394245

It has been clearly observed in recent years that the rate of injuries caused by toxic gases for workers inside laboratories and chemical warehouses has increased. The need for intelligent and efficient sensor systems in university chemical laboratories and repositories is becoming increasingly important. To meet this need, the design and implementation of an intelligent system was developed to sense and detect gas emissions within these laboratories. The system was developed as it relies primarily on sensors to measure the percentage of toxic gases within the laboratory and consists of a wireless sensor network (WSN) with the Internet of Things (IoT) in laboratories and warehouses. Chemicals inside the university. The WSN device is used to collect toxic gas data in laboratories and distribute it from sensors that include the MQ4 sensor and the MQ135 sensor. The process of exploring toxic gases in laboratories and chemical stores at universities is considered by linking the wireless sensors with a micro controller using two XBEE (S2) MODULE nodes, one for transmission and the other for reception. The data is collected and processed on a computer, and then the processed data is transferred to the cloud using an application via MIT APP and an ESP8266 simple unit (NodeMCU) with a wireless sensor network to monitor gases inside the laboratory. The implementation of this system will greatly enhance the safety and security of the university's laboratories and chemical stores, providing a safer and healthier environment for students, staff and faculty. © 2024 IEEE.

关键词： Laboratories

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Real-Time Gesture-Based Control of a Quadruped Robot Using a Stacked Convolutional Bi-Long Short-Term Memory (Bi-LSTM) Neural Network 10

Real-Time Gesture-Based Control of a Quadruped Robot Using a...

引用

10th international conference on automation, Robotics, and Applications, ICARA 2024

作者： Zafar, Muhammad Hamza Langas, Even Falkenberg Sanfilippo, Filippo University of Agder Dept. of Engineering Sciences Grimstad Norway Kaunas University of Technology Dept. of Software Engineering Kaunas Lithuania

ISBN: (纸本)9798350394245

In recent years, advancements in robotics have driven a growing interest in enhancing human-robot interaction (HRI) for improved collaboration and effectiveness, particularly in critical scenarios like search and rescue (SAR) operations. This paper introduces an innovative approach for intuitive control of a quadruped robot, MiT Spot Robot, through hand gestures, using a Stacked Convolutional Bi-Long Short-Term Memory (Bi-LSTM) neural network model. To enable seamless and efficient human-robot interaction (HRI), this advanced model is integrated with the Robot Operating System (ROS) and the Gazebo simulation environment. We propose a robust hand gesture recognition system employing computer vision techniques that accurately interpret dynamic hand gestures in real time. The recognised gestures are mapped to specific locomotion and task commands, facilitating natural and intuitive control of the Quadruped Robot during search and rescue (SAR) operations. A comprehensive hyperparameter tuning approach using a grid search is implemented to optimise the model's performance. Our simulation-based experimentation in ROS/Gazebo validates the effectiveness and responsiveness of the proposed control scheme, showcasing its potential to enhance human-robot collaboration (HRC) in critical scenarios such as SAR missions. © 2024 IEEE.

关键词： Long short-term memory

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