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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mohammadhossein Zahedi Bidgoli Mohammad Hatami Pouya Hossein Nejat Pishkenari Alireza Taheri Department of Mechanical Engineering Nano Robotics Laboratory Sharif University of Technology Tehran Iran Department of Mechanical Engineering Robotics Laboratory Sharif University of Technology Tehran Iran

Magnetic catheters have gained popularity as a safer and more precise alternative to manually guided catheters, reducing X-ray exposure for medical professionals. However, achieving precise control of the catheter’s tip remains a topic of debate. In this paper, we introduce a fuzzy controller designed to control the position of the magnetic catheter’s tip with high accuracy in a controlled environment with a uniform magnetic field and a feeder mechanism, providing a 3DOF setup. We implemented the fuzzy controller using a dynamic Cosserat model of the magnetic catheter and conducted simulations to assess its performance. To evaluate the closed-loop system, two trajectory paths, one following a cubic pattern and the other a helical pattern, were provided as desired inputs to the closed-loop system using the proposed controller. Additionally, Gaussian-distributed noise was added to the feedback loop of the system. The Root Mean Square Error (RMSE) values for a catheter with a variable free length ranging from 3 to 5 cm for these two input trajectories were 0.96 mm and 0.86 mm, respectively. The simulation results indicated that the presented control system has the capability to accurately track various trajectories with high precision.

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Exploring Neural Networks for Forward Kinematics of the Robotic Arm with Different Length Configurations: A Comparative Analysis 2

Exploring Neural Networks for Forward Kinematics of the Robo...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Bouzid, Rania Narayan, Jyotindra Gritli, Hassène Higher Institute of Information and Communication Technologies Tunis Borj Cedria1164 Tunisia Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Assam Guwahati781039 India National Engineering School of Tunis Le Belvédère Tunis1002 Tunisia

ISBN: (纸本)9798350360523

Our work investigates the utilization of Artificial Neural Networks (ANNs) to address the complexities associated with Forward Kinematics (FK) problems within the field of robotics. We undertake an extensive comparative analysis to assess how ANNs perform under different circumstances with robotic arms of varying lengths and impact the overall system's functionality. The training, testing, and validation of ANNs are carried out using MATLAB for a simulated 2-DoF serial robotic arm involving three distinct datasets: fixed step size, random step size, and sinusoidal step size. Three training optimizers, namely Levenberg Marquardt (LM), Bayesian Regularization (BR), and Stochastic Conjugate Gradient (SCG), are considered within the ANN architecture. Based on Mean Square Error (MSE) values, the numerical findings reveal the potential of ANN in estimating forward kinematic solutions of complex robotic manipulators with different arm lengths and reducing computational complexity. © 2024 IEEE.

关键词： Robotic arms

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Development of Wireless Integrated Early Warning System (EWS) for Hospital Patient 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Steady Oey, Endra Astuti, Winda Andriatin, Yuli Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Nursery Department Cilacap Regional General Hospital Gatot Subroto No. 28 Central Java Cilacap53223 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

The implementation of the Early Warning System (EWS) in hospitalized patients aims to identify worsening of the patient’s condition based on the assessment of vital signs. Currently, the EWS is still applied manually by nurses by filling out observation sheets to assess the risk of patient deterioration, so that it can be used. There was an error filling in by the human error factor. In addition, the lack of nurses in Indonesia makes the implementation of EWS not optimal. Therefore, a system for measuring vital signs and risk assessment of patient deterioration was created automatically which nurses can monitor through the website. The results of this study are a system design prototype consisting of five data retrieval devices and a Raspberry Pi as a web server. Each device sends data to the server wireless using the MQ Telemetry Transport (MQTT) protocol. The test results show that the system can retrieve vital signs data automatically every hour and displays a risk that is one level lower than manual EWS implementation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Deterioration

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Study on Optimal Machine Learning Approaches for Kidney Failure Detection System Based on Ammonia Level in the Mount 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Phandinata, Nicholas Puji, Muhammad Nurul Astuti, Winda Andriatin, Yuli Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Nursery Department Cilacap Regional General Hospital Gatot Subroto No.28 Central Jawa Cilacap53223 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Patients with kidney failure can emit bad breath with a certain level of ammonia content. The interpretation of ammonia levels in patients with renal failure was identified in this work. This research used the Chronic Kidney Disease dataset from UCI Machine Learning Repository. The dataset was processed first to get the value of eGFR (estimated Glomerular Filtration Rate) and ppb (parts per billion) of ammonia. Based on the eGFR value, the severity of kidney failure was divided into 5 categories, namely normal (Stage 1), mild (stage 2), moderate (stage 3), severe (stage 4) and failure (stage 5). The values of eGFR features are used as input for the machine learning technique in order to predict the level of kidney failure. Four different types of machine learning techniques, namely Support Vector Machine (SVM), Naïve Bayes (NB), Artificial Neural Network (ANN) and K-nearest neighbors (KNN), are applied and compared. The last process was to identify kidney failure using the K-Nearest Neighbors (KNN) method based on eGFR and ppb of ammonia dataset. AI-based kidney failure severity identification system with KNN algorithm had an average accuracy of 89.9% and 95.65% for training and testing accuracy, respectfully. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Support vector machines

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Effect of Cu addition on electrochemical activity of ribbons of Mg-Al-Ca anode materials for magnesium rechargeable batteries manufactured by rapid solidification method

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第1期74卷 14-17页

作者： Fukui, Shunsaku Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Program of Materials Science and Engineering Studies in Science and Engineering Graduate School of Science and Engineering University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama Japan CHUETSU METAL WORKS CO. LTD. Nakaniikawa-gun Toyama Japan Saitama Industrial Technology Center Kawaguchi Kawaguchi-shi Saitama Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan

The potential for magnesium storage batteries to become the next generation of rechargeable batteries is high. This is largely due to the abundance of magnesium metal resources and their high safety and electric capacity per volume. Our research team has been studying magnesium alloys as anode materials for these batteries. Specifically, we have been investigating the electrochemical activity and mechanism of adding copper to Mg-9mass%Al and Mg-9mass%Al-3mass%Ca. Our findings indicate that the electrochemical activity increased with the addition of 1mass%Cu, but decreased with the addition of 3mass%Cu. In addition, changes in lattice constant and basal orientation were also observed. These changes decreased with 1mass%Cu and increased with 3mass%Cu. SEM observations showed that the cell delimitation was indistinct for the 1%Cu addition. © 2024 The Japan Institute of Light Metals.

关键词： Secondary batteries

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Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification

Traffic Signs Detection System Using YOLO (You Only Look Onc...

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Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Yosua Setiawan Muhammad Nurul Puji Winda Astuti Computer Engineering Department Automotive & Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

Road accidents have become a problem for many road users in many countries. It may affect human daily activity and tasks, potentially influencing productivity and safety. Therefore, reducing road accidents as swiftly and effectively as possible is critical. For this reason, a Traffic signs detection system has been developed in this work to improve road safety. The detection system can detect traffic signs on the road such as traffic lights, speed limits, and no U-turn signs, and then it will provide users with the corresponding text on an LCD and vibration feedback using a motor. Throughout this work, the You Only Look Once (YOLO) algorithm is proposed for detecting traffic signs on the road. Moreover, a camera is used to extract live videos which serve as an input for the Raspberry Pi 4 model B containing custom YOLOv5 and YOLOv8 models. The system then sends the output to an LCD, a vibration motor, and a radio frequency (RF) module as notifications for users. In the end, the performance of the proposed method has been collected and it is found to produce good accuracy within an inconsiderable amount of 1.677 images and 2.263 annotations. Therefore, the accuracy of 0.69 for YOLOv5 and 0.7 for YOLOv8 were obtained from the training and validation process. Furthermore, the system accurately detects the traffic signs on the road.

关键词： YOLO Vibrations Training Road accidents Accuracy Motors Liquid crystal displays Road safety Safety Videos

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Investigation of the cap layer for improved GeSn multiple quantum well laser performance

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Optics Letters 2023年第7期48卷 1626-1629页

作者： Abernathy, Grey Ojo, Solomon Stanchu, Hryhorii Zhou, Yiyin Olorunsola, Oluwatobi Grant, Joshua Du, Wei Jheng, Yue-Tong Chang, Guo-En Li, Baohua Yu, Shui-Qing Department of Electrical Engineering University of Arkansas FayettevilleAR72701 United States Materials Science & Engineering Program University of Arkansas FayettevilleAR72701 United States Institute for Nanoscience and Engineering University of Arkansas FayettevilleAR72701 United States Department of Mechanical Engineering National Chung Cheng University Chiayi County62102 Taiwan Arktonics LLC 1339 South Pinnacle Drive FayettevilleAR72701 United States

The study of all-group-IV SiGeSn lasers has opened a new avenue to Si-based light sources. SiGeSn heterostructure and quantum well lasers have been successfully demonstrated in the past few years. It has been reported that, for multiple quantum well lasers, the optical confinement factor plays an important role in the net modal gain. In previous studies, adding a cap layer was proposed to increase the optical mode overlap with the active region and thereby improve the optical confinement factor of Fabry–Perot cavity lasers. In this work, SiGeSn/GeSn multiple quantum well (4-well) devices with various cap layer thicknesses, i.e., 0 (no cap), 190, 250, and 290 nm, are grown using a chemical vapor deposition reactor and characterized via optical pumping. While no-cap and thinner-cap devices only show spontaneous emission, the two thicker-cap devices exhibit lasing up to 77 K, with an emission peak at 2440 nm and a threshold of 214 kW/cm2 (250 nm cap device). The clear trend in device performance disclosed in this work provides guidance in device design for electrically injected SiGeSn quantum well lasers. © 2023 Optica Publishing Group.

关键词： Semiconductor quantum wells

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Design Of A ‘ Drive Wave ‘ System based on Communications System Remote Real-time Running Text and Speech to Text Converter using Light Emitting Diode (LED) Display

Design Of A ‘ Drive Wave ‘ System based on Communications ...

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Computer Sciences, engineering, and Technology Innovation (ICoCSETI), International Conference on

作者： Juan Felix Christopher Sandy Setiawan Elioenai Sitepu Winda Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

Drive Wave is a device that can help drivers communicate with other road users by displaying familiar words and icons as well as a speech to text feature that can make it easier for drivers to communicate with other road users. in this work, a system design prototype consisting of two devices, namely Remote and LED message board. The most spoken words used and icons displayed on the LED message board are controlled wireless using a Remote using the ESP-NOW protocol and Bluetooth Low Energy (Bluetooth LE). The two ways of he LED message board controlled by the remote are manual and automatic speech to text converter system controlled the LED message board displayed. the manual way, the user pressed the button to choice the word to be displayed. in the automatic voiced control, the LED displayed the word uttered by the user. the automatic voiced controlled applied Mel-frequency cepstral coefficients (MFCC) as feature extraction techniques and Long Short-Term Memory (LSTM) method for word identification methods. The results showed that the automatic voice controlled 99.78% and 100% for training and validating accuracy, respectively. the real testing result showed that 24 times testing which have 100% accuracy.

关键词： Meters Pediatrics Roads Drives Light emitting diodes Mel frequency cepstral coefficient Long short term memory Speech to text Vehicles Testing

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Vision-Based Object Sorting in Dynamic Environments using YOLO for RoboCup ARM Challenge 2023 7

Vision-Based Object Sorting in Dynamic Environments using YO...

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7th IEEE Conference on Information and Communication Technology, CICT 2023

作者： Sahu, Yash Kumar Mittal, Radhika Patel, Deep Maiti, Chayan Sreekumar, M. Indian Institute of Information Technology Design and Manufacturing Centre for AI IoT and Robotics Department of Mechanical Engineering Kancheepuram Chennai India Indian Institute of Information Technology Design and Manufacturing Centre for AI IoT and Robotics Department of Computer Science Kancheepuram Chennai India

ISBN: (纸本)9798350305173

In the intersection of Artificial Intelligence (AI) and robotics, autonomous object manipulation has emerged as a pivotal research domain, finding applications in sectors as diverse as manufacturing and healthcare. While significant strides have been made in object identification, trajectory planning, and manipulation tasks, these advancements often fall short in real-world, dynamic settings, revealing a critical research gap in algorithmic adaptability and computational efficiency. This paper addresses the gap by applying YOLOv4, a state-of-the-art object detection AI algorithm, within the context of the RoboCup Autonomous Robot Manipulation (ARM) Challenge - a competitive platform designed to simulate real-world complexities in autonomous systems. The research objectives are twofold: firstly, the performance of YOLOv4 in object detection and classification under dynamically changing conditions is rigorously evaluated, employing varied training strategies in both simulated and real-world scenarios. Secondly, the robustness and adaptability of the algorithm in object manipulation tasks are scrutinized and facilitated by the real-world dynamics inherent to the competition. Empirical results demonstrate the algorithm's high accuracy, efficiency, and robustness in dynamic environments, substantiating its broader applicability in the development of autonomous systems. © 2023 IEEE.

关键词： Object detection

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A Comparative Analysis of Electric Vehicles Charging-Discharging Topologies for Sustainable Energy

A Comparative Analysis of Electric Vehicles Charging-Dischar...

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Communication, Control and Intelligent Systems (CCIS)

作者： Ashish Kumar Sinha Mukesh Pushkarna Prashant Kumar Department of Electrical Engineering Institute of Engineering and Technology GLA University Mathura India Department of Mechanical Robotics and Energy Engineering Dongguk University Seoul Republic of Korea

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

Electric vehicles (EVs) have gained immense popularity in recent times owing to the decrease in conventional energy resource reserves and the concurrent threat to the environment caused from the harmful discharge of IC engine vehicles. EVs are mainly divided into the following three categories: pure electrical vehicles or battery electric vehicles, hybrid electrical vehicles, and fuel cell electrical vehicles. All these classifications have certain advantages and drawbacks associated with them. Based on the associated advantages and disadvantages, various aspects of EV performance have been scrutinized namely, design optimization, transmission performance optimization, battery management system (BMS) and charging technology to name a few. While all the abovementioned aspects affect the EV performance critically, BMS and charging technology have been the main area of concern for design engineers and researchers. Herein, two major charging topologies are prevalent, i.e. vehicle-to-grid (V2G) and grid-to-vehicle (G2V). Moreover, a third and fourth scheme of operation, namely, vehicle-to-home (V2H) and vehicle-to-vehicle (V2V) topology respectively, is also gaining importance off-late. With this view, the present manuscript aims to categorize, engulf and encapsulate the different EVs along with the existing charging technologies in EVs and BMS. This shall make the topic at hand easier to comprehend for the prospective future researchers.

关键词： Hands Vehicle-to-grid Pollution Battery management systems Vehicular ad hoc networks LoRa Power grids Topology Intelligent systems Optimization

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