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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Jeong, Ongee Martin, Antoinette Deborah Ahamadzadeh, Ezat Moon, Inkyu Department of Robotics and Mechatronics Engineering Daegu Korea Republic of Keimyung University Dongsan Hospital Daegu Korea Republic of

ISBN: (纸本)9798350360721

In the Ciphertext Only Attack (COA), an attacker can access and use only ciphertexts, identifying the type of cryptosystem is critical for further attack. The attacker can analyze patterns in the ciphertexts that have different forms according to the cryptosystem and recognize the type of cryptosystem. We propose deep learning-based cryptosystem identification by investigating eight cryptosystems, DES, S-DES, AES, S-AES, Blowfish, RC2, SPECK, and RSA. The Recurrent Neural Network (RNN)-based deep learning model with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) is utilized to identify cryptosystems. The proposed method is used to classify ciphertext in each operation mode such as CBC, CFB, OFB, and CTR, into the corresponding cipher system. The performance of the proposed method was evaluated with recall, precision, classification accuracy, and F1 score. To verify effectiveness and superiority, we compared the proposed method with different machine learning-based and deep learning-based classifiers such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and BERT, a Large Language Model (LLM). Moreover, the previous methods in cryptosystem identification were also compared with the proposed method, and the results showed that eight cryptosystems were successfully recognized under various operation modes. The proposed method outperformed the other machine learning-based, and its deep learning-based classifiers were superior in cryptosystem identification. Furthermore, the proposed method showed a classification accuracy of 97.3 and 96.2 % in CBC and CFB, respectively, while the highest accuracy in the previous methods was 20% in CBC and 85.5% in CFB. © 2024 IEEE.

关键词： Cryptography

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Behavior of cracked Euler–Bernoulli beam and inverse problem for assessing crack severity

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Noise and Vibration Worldwide 2022年第3期53卷 104-119页

作者： Samir Mohamed Mohamed Soliman, Ehab Mechatronics and Robotics Department Faculty of Engineering Egyptian Russian University Cairo Badr City Egypt

In this present study, natural frequencies of the first two modes of bending vibration for the cracked simply supported Euler–Bernoulli beam is determined using finite element analysis (FEA). FEA natural frequencies for the cracked beam are used to investigate the behavior of the cracked beam and also used in the inverse problem of crack depth detection. Dynamic behavior of the cracked simply supported beam is observed, and it is found that normalized mode shape at crack location has great effect on amount of decreasing of natural frequencies. When normalized mode shape at crack location is increased, then natural frequencies decrease. In this study, pattern of mode shape played a vital role in decreasing or increasing natural frequencies. At the midpoint of the beam, there is largest bending moment in first bending mode and there is nodal point in second bending mode. Harmonic analysis for the cracked simply supported beam is carried out to find von Mises stress responses and appearance of peaks at frequency of first bending mode is noticed in graphs of von Mises stress response, expressing high values of von Mises stress at crack tip. Inverse problem of assessing the crack depth is performed using results of FEA first mode frequency ratio and published experimental results and the method showed good results in case of high crack depth ratios. © The Author(s) 2021.

关键词： Natural frequencies

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Exploring Classification, Size, and Quality of Mangifera Indica L. Through Image Processing and AI Techniques 2

Exploring Classification, Size, and Quality of Mangifera Ind...

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2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Wanthong, Irin Sri-On, Theeraphat Seangsri, Soontaree Khaengkarn, Sorada Srisertpol, Jiraphon Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology Nakhon Ratchasima Thailand Department of Mechatronics and Robotics Engineering School of Engineering and Innovation Rajamangala University of Technology Tawan-ok Chonburi Thailand

ISBN: (纸本)9781643685403

This paper introduces methods for efficiently classifying mangoes intended for export, a market valued at approximately 4,500 million baht annually. The classification process is divided into two primary components: size categorization and quality assessment. The first phase involves categorizing mango sizes into four distinct categories (M, 1L, 2L, 3L), while the second phase focuses on assessing mango quality, particularly detecting anthracnoseâ€"a prevalent disease affecting mangoes. This detection is achieved through image processing techniques, where images are converted into binary representations and analyzed using both Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs). Comparative analysis reveals that CNN outperforms ANN in size classification, achieving a remarkable train accuracy of 99.16% and a test accuracy of 88.0%. Furthermore, in quality classification, CNN demonstrates a train accuracy of 91.0% and a test accuracy of 88.0%. These findings underscore the effectiveness of CNN techniques in accurately classifying mangoes for export, thereby facilitating improved quality control and market competitiveness. Â© 2024 The Authors.

关键词： Convolutional neural networks

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Effect of Pneumatic Based Hybrid Robotic Gripper for Safer Handling of Complex Geometries 11

Effect of Pneumatic Based Hybrid Robotic Gripper for Safer H...

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11th IEEE International Conference on Advances in Computing and Communications, ICACC 2024

作者： Sivaraj, Santhosh Ravi, Ajay Jose, Bibin Joe Kaliyannan, Gobinath Velu Sivakumar, Rajkamal Amalraj, Riya Catherine Easwari Engineering College Department of Robotics and Automation TamilNadu Chennai600089 India Kongu Engineering College Department of Mechatronics Engineering TamilNadu Perundurai638060 India

ISBN: (纸本)9798350379136

The present research work mainly concentrates on development of hybrid grippers with the integration of hard and soft components for achieving object manipulation. By combining pneumatic actuation with mechanical fingers, complex geometries can be handled effectively. Pneumatic hybrid gripper fabricated with PLA and silicone rubber offers adaptability and versatility. Resistive sensors over silicone surface of gripper lead to cost-effective force detection and tactile sensing. The proposed gripper was designed and analyzed using Fusion 360 and ANSYS. Inflatable silicone rubber and gripper body were fabricated using liquid casting and Fused Deposited Modelling 3D printing techniques. Real-time feedback sensors were employed with fabricated gripper to get better performance. Testing proves its capability to handle loads up to 500g with a force of 3.3N. Finally, the assembled hybrid gripper offers a versatile solution for robotic manipulation, ensuring stability and minimizing damage across various industries. © 2024 IEEE.

关键词： Silicones

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Vision Based Leader-Follower Control of Wheeled Mobile Robots using Reinforcement Learning and Deep Learning 9

Vision Based Leader-Follower Control of Wheeled Mobile Robot...

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9th International Symposium on System Security, Safety, and Reliability, ISSSR 2023

作者： Garmon, Kayleb Wang, Ying Kennesaw State University Department of Robotics and Mechatronics Engineering MariettaGA United States

ISBN: (纸本)9798350302479

Vision-based control of mobile robots often involves complex calculations to derive a control law. The reinforcement learning algorithm (Q-learning) offers a machine learning method to extrapolate a control law from an environment given discretized actions, without the need of complex calculations. In this paper, a vision-based controller is created using Q-Learning to enable tracking in a leader-follower configuration of two nonholonomic autonomous mobile robots. The follower robot gathers its desired trajectory values by using a deep learning SSD model to identify a distinguishing visual feature on the leader robot and uses a lidar to determine the distance between two robots. These parameters are utilized to select an optimal action of the follower robot through reinforcement learning. The emulated results in a ROS Gazebo environment show this method to be effective in enabling a wheeled mobile robot to follow another, while simultaneously avoiding obstacles. © 2023 IEEE.

关键词： Mobile robots

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EZ3micro - A Novel Miniaturized Pick & Place Prototype for Improved Industrial Applications 20

EZ3micro - A Novel Miniaturized Pick & Place Prototype for I...

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20th IEEE International Conference on Smart Communities: Improving Quality of Life using AI, robotics and IoT, HONET 2023

作者： Sangree, Haden Kofiah, Mahmoud Voicu, Razvan Cristian Tanveer, M. Hassan Kennesaw State University Department of Robotics & Mechatronics Engineering MariettaGA United States

ISBN: (纸本)9798350331110

This research paper focuses on the development of a miniaturized pick-and-place robotic prototype, which utilizes a magnetically levitated ACOPOS 6D shuttle developed by BandR Industrial Automation Corp. The aim is to meet the technological demands of various industries, including manufacturing, logistical, biomedical, and agricultural. The prototype boasts several cutting-edge features, such as wireless communication, battery-operated design, low weight, high stability, precision control, visual recognition, and advanced end effector control. The end effector can perform pick-and-place and orientation change functions, and the modular design allows for endless applications, including rapid sorting for manufacturing, agriculture, and logistics. Furthermore, the prototype offers advancements in biomedical applications by automating sample selection, transportation, and testing. Overall, this research paper presents a new technological advancement to help maintain the current growth rate of various industries. © 2023 IEEE.

关键词： Medical applications

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INTEGRATION OF DIGITAL TWINS INTO VIRTUAL COMMISSIONING PRACTICES

INTEGRATION OF DIGITAL TWINS INTO VIRTUAL COMMISSIONING PRAC...

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ASME 2024 International Mechanical engineering Congress and Exposition, IMECE 2024

作者： Guerra-Zubiaga, David A. Richards, Gershom Forsberg, Paul Nwachukwu, Kingsley Burroughs, Andrew Sabula, Eric Kuts, Vladimir Kennesaw State University Department of Robotics and Mechatronics Engineering MariettaGA United States Tallinn University of Technology Department of Mechanical and Industrial Engineering Estonia

ISBN: (纸本)9780791888605

The demands of manufacturing equipment often led to operating the equipment most effectively to maximize productivity or *** need for maximized operating time for the equipment has made the maintenance aspect resort to more creative means to address the risk of equipment *** failure of equipment can range in effect from producing poor quality products, hindering the manufacturing process, or endangering the workers around ***, the damage done to equipment that has malfunctioned often causes a greater loss in profit as the equipment would need to be fixed or *** knowledge gap is in how a manufacturing plant can balance good quality maintenance without hindering the operation of the equipment *** historical maintenance practice is to run scheduled maintenance breaks on the equipment, check for system variables that have been shown to correlate to a decaying system or wait for the equipment to *** Commissioning (VC), which is the practice of using a simulated model of a system to explore the potential of a system without impeding the operation of the physical system, seems to be a sound *** paper explores the potential of integrating Digital Twins, a real-time simulation of a system, into the practice of VC to gather real-time data from the manufacturing *** the ability to collect and store complex data, the algorithms used to diagnose the system would enlighten the industry to various observations of the current practice of maintaining and operating certain *** the effectiveness and potential of this new data have yet to be defined, the ability to obtain the data would prove to be a great step forward in optimizing the maintenance and operation practices within the manufacturing industry. Copyright © 2024 by ASME.

关键词： Computer aided logic design

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COVIDXception-Net: A Bayesian Optimization-Based Deep Learning Approach to Diagnose COVID-19 from X-Ray Images

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SN Computer Science 2022年第2期3卷 115页

作者： Arman, Shifat E. Rahman, Sejuti Deowan, Shamim Ahmed Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

COVID-19 is spreading around the world like wildfire. Chest X-rays are used as one of the primary tools for diagnosing COVID-19. However, about two-thirds of the world population do not have access to sufficient radiological services. In this work, we propose a deep learning-driven automated system, COVIDXception-Net, for diagnosing COVID-19 from chest X-rays. A primary challenge in any data-driven COVID-19 detection is the scarcity of COVID-19 data, which heavily deteriorates a deep learning model’s performance. To address this issue, we incorporate a weighted-loss function that ensures the COVID-19 cases are given more importance during the training process. We also propose using Bayesian Optimization to find the best architecture for detecting COVID-19. Extensive experimentation on four publicly available COVID-19 datasets shows that our proposed model achieves an accuracy of 0.94, precision 0.95, recall 0.94, specificity 0.997, F1-score 0.94, and Matthews correlation coefficient 0.992 outperforming three widely used architectures—VGG16, MobileNetV2, and InceptionV3. It also surpasses the performance of several state-of-the-art COVID-19 detection methods. We also performed two ablation studies that show our model’s accuracy degrades from 0.994 to 0.950 when a random search is used and to 0.983 when a regular loss function is employed instead of the Bayesian and weighted loss, respectively. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2021.

关键词： Bayesian optimization Chest X-ray COVID-19 Deep learning SARS-CoV-2

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Control Simulation of Proportional-Integral and Sliding Mode Control for Precision Seed Planters

Control Simulation of Proportional-Integral and Sliding Mode...

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2023 International Conference on robotics and Automation in Industry, ICRAI 2023

作者： Nawaz, Yasir Qadir, Muhammad Usman Khan, Muhammad Awais Haq, Izhar Ul Shah, Kamran Khan, Tahir Advanced Robotics & Automation Lab Department of Mechatronics University of Engineering and Technology Peshawar Pakistan

ISBN: (纸本)9781665464727

The desired development and design of an electric control system (ECS) for a precision planter is one of the most crucial elements in evaluating the efficacy of applicators for plant production. The seeds would be sown using this approach. Years have been invested in the continuous development of a range of application methods and metering systems, each of which offers specific advantages for applying the required system with a high degree of precision. Researchers worldwide have been trying to make electric-driven seed meters (EDSM) for planters, but they haven't succeeded. This study looks into the current state of installing seed metering systems for precision planters. Proportional-integral (PI) and sliding mode control (SMC) designs of the control system have been implemented to improve the planting quality of the planters. We want to highlight the electrically driven control system (EDCS) using these designs. An overview of the noteworthy features and limitations of past research is given. We also discuss several future directions for future research, concentrating on the knowledge gaps in this area. © 2023 IEEE.

关键词： Sliding mode control

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A Study on Improving the Performance of Dynamic Model Based Redundant Navigation System for Sensor Fault Scenarios

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Journal of Institute of Control, robotics and Systems 2025年第4期31卷 351-359页

作者： Ko, Bo Sung Choi, Hyeong Jun Jeon, Myung Jun Cho, Hyeon Jin Song, Jin Woo Department of Artificial Intelligence and Robotics and Convergence Engineering for Intelligent Drone AIRI Sejong University Korea Republic of Department of Intelligent Mechatronics Engineering and Convergence Engineering for Intelligent Drone AIRI Sejong University Korea Republic of Agency for Defense Development Maritime Technology Research Institute Korea Republic of

This study proposes a redundant navigation system for UUV (Unmanned Underwater Vehicle) utilizing a 6 DOF (Degree of Freedom) VDM (Vehicle Dynamic Model). The system is designed to enable safe UUV asset return when all navigation sensors become inoperable. Since it is impossible to perfectly determine VDM coefficients through water tank experiments, a method to improve VDM output accuracy in real time during UUV mission is necessary. Here in this study, we introduce real-time adaptive 6 DOF VDM output error compensation algorithm to enhance the performance of redundant navigation systems. This research aims to establish the foundation for backup navigation solutions in situations when critical UUV sensor failures occur. © ICROS 2025.

关键词： Water tanks

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