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Investigation of a 7-Axis Suspended Robotic Arm for Automated Spraying System 3

Investigation of a 7-Axis Suspended Robotic Arm for Automate...

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3rd International Conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Liu, Chao-Chung Liu, Jun-Chi Liu, Chao-Shu Dep. of Computer Science ZhaoQing University ZhaoQing526061 China Dep. of Industrial Design National United University Miaoli360301 Taiwan Dep. of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan

ISBN: (纸本)9781643685649

This study successfully develops a 7-axis suspended robotic arm for an automated spraying system, considering factors such as flexible operation modes, spray area dimensions, workpiece geometry, and the degrees of freedom required for effective operation. By using SolidWorks software for verification, the endpoints of the robotic arm can reach all positions within the workspace. The design and fabrication of the arm are completed according to specifications for structural strength, load capacity, rated torque output, and rotational speed. Kinematic analyses, both forward and inverse, are applied to determine the posture and position of the 7-axis robotic arm, facilitating the planning and design of the spraying trajectory. The control system architecture utilizes a multi-axis servo control board, integrated with a manifold deformation control method for trajectory tracking. Simulations and experiments are conducted to use a car shell workpiece provided by the manufacturer. The results from the simulations of MATLAB analyses show that the maximum tracking error is less than 0.4 mm. In experiments with the robotic arm, the maximum error is less than 0.7 mm. The results of the simulation and experiment are quite close, indicating that the deformation control method effectively operates the posture and movement of the 7-axis suspended robotic arm. Therefore, the 7-axis suspended robotic arm developed in this study will be effectively utilized in the production line of the automated spraying system. © 2024 The Authors.

关键词： MATLAB

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Enhanced Honey Badger Algorithm for Resource Allocation and Task Scheduling in Cloud Environment 4

Enhanced Honey Badger Algorithm for Resource Allocation and ...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Rajagopal, R. Arunarani, A.R. Arivarasi, A. Ingle, Anup Ravichandran, T. Prakash, R. Vijaya Alliance College of Engineering and Design Alliance University Department of Computer Science and Engineering Karnataka Bengaluru India School of Computing College of Engineering and Technology Srm Instutite of Science and Technology Department of Compuational Intelligence Tamilnadu Chennai India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Karnataka Bengaluru India Vishwakarma Institute of Information Technology Department of Electronics and Telecommunications Maharashtra Pune India Karpagam College of Engineering Department of Computer Science and Engineering Tamilnadu Coimbatore India School of Computer Science and Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798350300888

Cloud computing is a technology that offers dynamic resources to the users with enhanced scalability and flexibility. The major concerns in cloud environment that has direct impact on the throughput of cloud system and contentment of cloud users is the problem of task scheduling and resource allocation. The time taken to execute the tasks and cost incurred for the computation are the significant objectives that affect the performance of the cloud system. This work proposes a multi-objective task scheduling and resource allocation technique using meta-heuristic optimization algorithm. Enhanced Honey Badger algorithm (EHBA) is employed to schedule the tasks and allocate computing resources effectively while minimizing the time and cost objectives. The performance of the proposed technique is assessed in a simulation environment, CloudSim, which mimics the settings of real cloud computing system. Various measures such as Time-to-Execute, Cost-to-Compute, Task-to-Resource utilization and Time-to-Respond are used to assess the performance of the suggested EHBA method for efficient task scheduling and resource allocation. The experimental results produced by the proposed method is also compared against the state-of-the-art studies that employ meta-heuristic optimization algorithms. The outcomes revealed that EHBA outperformed other methods by executing the tasks in a minimum time with reduced cost and maximum utilization of the computing resources. © 2023 IEEE.

关键词： Resource allocation

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Study on the Robotic Arm Trajectory Compensation System with Deviation Sensing 3

Study on the Robotic Arm Trajectory Compensation System with...

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3rd International Conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Liu, Chao-Chung Liu, Jun-Chi Liu, Chao-Shu Dep. of Computer Science Zhaoqing University Zhaoqing526061 China Dep. of Industrial Design National United University Miaoli360301 Taiwan Dep. of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan

ISBN: (纸本)9781643685649

Robotic arms play an important role in the automation industry. Robotic arms plan processing paths based on the shape of the workpiece. However, the processing path often deviates due to inaccurate placement of the workpiece. To solve the issue of deviations, this paper develops a trajectory compensation system for a robotic arm with offset perception. This system uses the concept of workpiece boundary projection and designs an offset calculation algorithm by comparing the dimensions of the workpiece drawings, correcting errors caused by missing corners of the workpiece. In terms of operation, the system uses photoelectric sensors to quickly scan the workpiece boundary and immediately calculate the displacement and rotational offset of the workpiece. Subsequently, when deviations occur due to different placement positions of the workpiece, the robotic arm's motion path and action must be corrected and compensated to maintain precision. Tests on selected workpieces show that the corrected rotational angle error is less than 0.4 degrees, and the translational error is less than 0.7 millimeters. Since these correction error values are lower than the 1.0 mm error threshold for the robotic arm's trajectory tracking control. The offset-sensing robotic arm trajectory compensation system developed in this study can satisfy the requirements of smart automation production lines and arrive at the manufacturer's application standards. © 2024 The Authors.

关键词： Robotic arms

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Age-of-Information and Energy Optimization in Digital Twin Edge Networks

Age-of-Information and Energy Optimization in Digital Twin E...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Guo, Yongna Fu, Yaru Zhang, Yan Quek, Tony Q. S. Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Hong Kong Metropolitan University School of Science and Technology Hong Kong University of Oslo Department of Informatics Oslo Norway Singapore University of Technology and Design Singapore

ISBN: (纸本)9798350351255

In this paper, we study the intricate realm of digital twin synchronization and deployment in multi-access edge computing (MEC) networks, with the aim of optimizing and balancing the two performance metrics Age of Information (AoI) and energy efficiency. We jointly consider the problems of edge association, power allocation, and digital twin deployment. However, the inherent randomness of the problem presents a significant challenge in identifying an optimal solution. To address this, we first analyze the feasibility conditions of the optimization problem. We then examine a specific scenario involving a static channel and propose a cyclic scheduling scheme. This enables us to derive the sum AoI in closed form. As a result, the joint optimization problem of edge association and power control is solved optimally by finding a minimum weight perfect matching. Moreover, we examine the one-shot optimization problem in the contexts of both frequent digital twin migrations and fixed digital twin deployments, and propose an efficient online algorithm to address the general optimization problem. This algorithm effectively reduces system costs by balancing frequent migrations and fixed deployments. Numerical results demonstrate the effectiveness of our proposed scheme in terms of low cost and high efficiency. © 2024 IEEE.

关键词： Costs

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Prediction Of Heat Transfer Performance Using Polynomial Regression 2

Prediction Of Heat Transfer Performance Using Polynomial Reg...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Bal, Sasmita Radha, R. Alliance University Alliance College of Engineering and Design Department of Mechanical Engineering Anekal Karnataka Bangalore India Alliance University Alliance College of Engineering and Design Department of Computer Science Engineering Anekal Karnataka Bangalore India

ISBN: (纸本)9781665400527

This paper is concentrated on the application of polynomial regression which is used to find the relation between two or more variables. In the present work polynomial regression model was used to find the contribution of the input parameters during spray impingement cooling on microchannel. The model was designed and trained using a total 120 experimental data points collected from the experiment. Experiment was carried out to find heat transfer coefficient and mass flux density during spray on microchannel which is used to cool electronic chips. The mass flux density calculated from the experiment, air and water pressures and nozzle tip to microchannel surface distance were used as input variables for the regression model, while the corresponding heat transfer coefficient was selected as its output variable. By comparing polynomial regression model with linear, ridge regression and ANN, it was evident that heat transfer coefficient with high accuracy was achieved for polynomial regression. Various degrees of model were also compared upon which it was found that regression model with degree three outperforms the others. Among four independent variables, Water Pressure, Nozzle height and Mass flux density turns out to be most significant variable in calculating the regression model for Heat Transfer Coefficient. © 2022 IEEE.

关键词： Heat transfer coefficients

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E-Authentication System using Eye-Blinking and Deep Learning

E-Authentication System using Eye-Blinking and Deep Learning

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Network, Multimedia and Information Technology (NMITCON) International Conference on

作者： Rathnakar Achary Chetan J Shelke Department of Computer Science Alliance College of Engineering and Design Alliance University Bangalore India

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

The Personal Identification Number (PIN) are commonly employed as a security measure for authentication purposes. When utilizing a PIN for verification of authentication, the users are required to input a physical PIN. However, this method may be susceptive to security vulnerabilities through methods such as observing someone’s shoulder or tracking thermal signatures. In this research, we adopted Eye-Blinking for authentication of the system, with the advantage that it leaves no bodily footprints in the system and provides a more robust alternative for advanced security. The eye-blinking pattern is a highly secured and unique biometric identifier that cannot be easy replicates, making it difficult to hack or bypass. An E-Authentication System using Eye-Blinking and its analysis using deep learning explains an individual’s eye-blinking patterns as a unique identifier to verify their identities. The systems capture their eye-blinking patterns and compare them to the stored patterns in its databases. If the patterns match, the systems grant access to the user. The systems aim at achieving high accuracy, reliability, and integration with existing security infrastructure and authentication protocols.

关键词： Deep learning Biometrics Protocols System performance Authentication Passwords Pins Security Reliability Pattern matching

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Segmentation of Maya Hieroglyphs through Fine-Tuned Foundation Models 23

Segmentation of Maya Hieroglyphs through Fine-Tuned Foundati...

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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Shivam, F.N.U. Leight, Megan Kelly, Mary Kate Davis, Claire Clodfelter, Kelsey Thrasher, Jacob Rahman, Chowdhury Mohammad Abid Reddy, Yenumula Gyawali, Prashnna West Virginia University Lane Department of Computer Science and Electrical Engineering United States School of Art and Design West Virginia University Department of Art History United States Mount Royal University Canada

ISBN: (纸本)9798350374889

The study of Maya hieroglyphic writing unlocks the rich history of cultural and societal knowledge embedded within this ancient civilization's visual narrative. Machine learning (ML) offers a novel lens through which we can translate these inscriptions, with the potential to allow non-specialists access to reading these texts and to aid in the decipherment of those hieroglyphs which continue to elude comprehensive interpretation. Toward this, we leverage a large foundation model to segment Maya hieroglyphs from an open-source digital library dedicated to Maya artifacts. Despite the initial promise of publicly available foundation segmentation models, their effectiveness in accurately segmenting Maya hieroglyphs was initially limited. Addressing this challenge, our study involved the meticulous curation of image and label pairs with the assistance of experts in Maya art and history, enabling the fine-tuning of these foundation models. This process significantly enhanced model performance, illustrating the potential of fine-tuning approaches and the value of our expanding dataset. We plan to open-source this dataset for encouraging future research, and eventually to help make the hieroglyphic texts legible to a broader community, particularly for Maya heritage community members. © 2024 IEEE.

关键词： Image segmentation

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AI based Security in computer vision and machine learning algorithms for hand sign recognition

AI based Security in computer vision and machine learning al...

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Blockchain and Distributed Systems Security (ICBDS), IEEE International Conference on

作者： Nilesh N. Thorat Nilesh M. Kulal Khedekar Vilas Baburao Sumit Arun Hirve Sachin Kolekar Rohidas Sangore Department of Computer Science and Engineering MIT Art Design and Technology University Pune India

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

In order to facilitate intuitive control and communication across a variety of areas, hand gesture recognition is an essential component of human-computer interaction systems. In this paper, a real-time hand gesture recognition system developed with the MediaPipe library, and convolutional neural networks (CNNs) is presented. The system utilizes a CNN model provided by MediaPipe for accurate detection of hand landmarks in camera feed images. Through extensive preprocessing and feature extraction, hand gestures, including finger gestures and palm orientations, are classified in real-time. The system offers dynamic selection between two modes: logging key points and logging point history, facilitating data collection for training or analysis *** features of the system include bounding rectangle calculation, landmark visualization, and gesture classification, providing users with immediate feedback on detected hand gestures. The modular design and parameter configurability make the system versatile for a wide range of applications, from interactive interfaces to sign language interpretation. The outcomes of the experiments showcase the practicality and efficacy of the suggested method, indicating that it has the potential to improve the experiences of people interacting with computers. Incorporating AI security measures, the system can significantly enhance security protocols in various applications. For instance, it can be used for gesture-based authentication, where specific hand gestures act as passwords to grant access to secure systems. This method can be further secured by combining it with traditional authentication techniques, creating a robust multi-factor authentication framework. Additionally, the real-time detection capability allows for immediate response to unauthorized access attempts, triggering alerts or lockdown procedures when unfamiliar gestures are detected.

关键词： Hands Solid modeling Sign language Accuracy Transfer learning Virtual reality Feature extraction Real-time systems Security Convolutional neural networks

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Tutorial: How to Use Model Checking to Analyze Circuits at the Transistor Level

Tutorial: How to Use Model Checking to Analyze Circuits at t...

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Proceedings of the 2023 International Conference on Hardware/Software Codesign and System Synthesis

作者： Michael Raitza Steffen Märcker Faculty of Computer Science Department of Computer Engineering Chair of Processor Design TU Dresden Dresden Saxony Germany

ISBN: (纸本)9798400702891

Model checking can be a valuable addition to industry-standard approaches to perform quantitative and qualitative analysis of circuits at the transistor level. The device models are simple yet powerful enough to capture essential electrical characteristics. With its unique approach to formally specify the experimental setup and query quantitative measures, model checking provides you definitive answers to questions about energy consumption, power dissipation and delay properties. With the advent of reconfigurable transistors, systematic investigation and comparison becomes even more important, as reconfigurable logic gates come in different implementations with varying trade-offs. This tutorial will give you a hands-on introduction into the possibilities of investigating logic circuits that use reconfigurable transistors. You will both, design a single circuit graphically, and synthesize a whole family of reconfigurable circuits automatically from a Boolean function.

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Effect of Pesticides on Crop Health Monitoring Based on NDVI Using Machine Learning

Effect of Pesticides on Crop Health Monitoring Based on NDVI...

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Delhi Section Conference (DELCON), IEEE

作者： Suvarna Pawar Aman Badure Adikrishna Bade Sai Kolhe Prasad Takwane Department of Computer Science and Engineering MIT Art Design and Technology University Pune India

ISBN: (数字)9798331518592

ISBN: (纸本)9798331518608

The aim of this research paper is to evaluate the crucial impact of pesticides. This control measure is an important agricultural input for improving crop health. However, due to the nature of agriculture, we need developments in machine learning which are urgently required to analyze it. The utilization of pesticides is important in preventing severe damage from pest and disease outbreaks. This work suggests the application of remote sensing finding devices like drones with multispectral imaging, which can be used to obtain Normalized Difference Vegetation Index (NDVI), with the aim of measuring the status of the crops' health as a function of the chlorophyll content of the plants. The model being presented is based on the use of IoT sensors, drone images, and machine learning algorithms to supervise the energy status of the plants in the field. Preliminary imaging data based on NDVI will highlight the images of drones conditions. However, in this research offers solutions to the problem of diverse resolution images that need to be registered in order to create a mosaic. In the end, the results will illustrate how pesticides impact the efficiency of crops, which will help in developing sustainable agriculture solutions that are environmentally friendly.

关键词： Precision agriculture Normalized difference vegetation index Crops Pesticides Machine learning Robustness Sensors Indexes Remote sensing Drones

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