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arXiv 2023年

作者： Kang, Mincheul Ha, Junhyoung Mechatronics Research and Development Center Samsung Electronics Hwaseong-si18448 Korea Republic of The Center for Healthcare Robotics Artificial Intelligence and Robotics Institute Korea Institute of Science and Technology Seoul02792 Korea Republic of

A vision system attached to a manipulator excels at tracing a moving target object while effectively handling obstacles, overcoming limitations arising from the camera's confined field of view and occluded line of sight. Meanwhile, the manipulator may encounter certain challenges, including restricted motion due to kinematic constraints and the risk of colliding with external obstacles. These challenges are typically addressed by assigning multiple task objectives to the manipulator. However, doing so can cause an increased risk of driving the manipulator to its kinematic limits, leading to failures in object tracking or obstacle avoidance. To address this issue, we propose a novel visual tracking control method for a redundant manipulator that takes the kinematic constraints into account via a reachability measure. Our method employs an optimization-based controller that considers object tracking, occlusion avoidance, collision avoidance, and the kinematic constraints represented by the reachability measure. Subsequently, it determines a suitable joint configuration through real-time inverse kinematics, accounting for dynamic obstacle avoidance and the continuity of joint configurations. To validate our approach, we conducted simulations and hardware experiments involving a moving target and dynamic obstacles. The results of our evaluations highlight the significance of incorporating the reachability measure. © 2023, CC BY.

关键词： Redundant manipulators

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AI - Driven Drug Discovery and Therapeutic Target Identification for Rare Genetic Diseases

AI - Driven Drug Discovery and Therapeutic Target Identifica...

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Advancements in Smart, Secure and Intelligent Computing (ASSIC), International Conference on

作者： Suresh T S. Kaliappan H. Mohammed Ali Bura Vijay Kumar Department of Mechatronics Engineering Kumaraguru College of Technology Coimbatore Tamil Nadu India Division of Research and Development Lovely Professional University Phagwara Punjab India Department Mechanical Engineering SRM Institute of Science and Technology- Ramapuram Campus Chennai School of Computer Science and Artificial Intelligence SR University Warangal Telangana

This method for AI-driven drug discovery and therapeutic target selection for rare genetic diseases is a cutting-edge and comprehensive strategy for addressing the challenges posed by such diseases. As a prerequisite, it is necessary to collect and combine genomic, transcriptomic, proteomic, and clinical data from numerous sources in a systematic manner. By integrating genetic and clinical data, it is possible to construct a more complete picture of the disorders. Feature selection procedures are utilized to further simplify the research by focusing on the most essential characteristics for target identification and reducing the dimensionality of the data. Based on the integrated data set, machine learning models such as Neural Networks, Support Vector Machines, and Random Forests are utilized to recommend prospective therapeutic targets. Validation and cross-validation techniques are used to assure the validity and generalizability of these models. The strategy emphasizes adherence to applicable ethical principles and legal frameworks while encouraging collaboration across specialties. The patient is the focal point throughout, and new data is continuously collected to improve results and develop more individualized therapies based on everyone's unique genetic profile. The iterative nature of the methodology allows for continual refinement as new data and clinical insights emerge. AI-predicted targets undergo biological validation through in vitro and in vivo experiments, bridging the gap between computational predictions and clinical applications. Knowledge and insights are shared with the scientific community through open-access databases and collaborative platforms.

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Efficiency and fatigue in marksmanship training 5

Efficiency and fatigue in marksmanship training

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5th Scientific School on Dynamics of Complex Networks and their Applications, DCNA 2021

作者： Grubov, Vadim Badarin, Artem Savosenkov, Andrey Grigoriev, Nikita Lukojanov, Maxim Ydoratina, Anna Maximenko, Vladimir Kazantsev, Viktor B. Hramov, Alexander E. Neuroscience and Cognitive Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Brain-Machine Interface Development Lab Institute for Neurosciences Lobachevskiy University Nijnij Novgorod Russia

In the present study we developed experimental paradigm and setup for marksmanship training in untrained subjects. We aimed to demonstrate correlation between subject’s fatigue and efficiency during training. © ... 详细信息

ISBN: (纸本)9781665442824

关键词： Efficiency

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Assessment of Carbon Fibre Composites for Product development in Aerospace and Transportation Industries

Assessment of Carbon Fibre Composites for Product Developmen...

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Science, Engineering and Business for Sustainable development Goals (SEB-SDG), International Conference on

作者： Korede J. Ogundare Felix Ale Olatunbosun T. Yusuf Seyi F. Olatoyinbo Ilesanmi A. Daniyan Department of Systems Engineering Institute of Space Science & Engineering African University of Science & Technology Abuja FCT Nigeria National Space Research and Development Agency Abuja FCT Nigeria Department of Mechanical & Mechatronics Engineering Achievers University Owo Ondo State Nigeria

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

The need to develop high-performing materials coupled with effective component recovery into service at the end-of-life (EOL) is essential to reduce waste generation and achieve a circular economy. Less-performing materials may promote indiscriminate disposal of components made from them at the end of their life, thereby increasing the cost of manufacturing. It can also make the environment less friendly. This study assesses the applicability of carbon fibre composites for product development in the aerospace and transportation sectors. A literature review on carbon fibre applications in the transportation and aerospace sectors was conducted. The study also presents a process design for processing carbon fibre with a potential for energy saving. The findings indicate that carbon fibre boasts of a high strength-to-weight ratio and thus suitable for transportation and aviation applications. However, its processing is energy-intensive and has no effective recycling options. This study also provides theoretical and empirical findings drawn from the literature on the feasibility of fibre composites for component development in the aerospace and transportation industries. The results and findings of this study can promote manufacturing sustainability and the concept of circular economy with improvement in the performance and useful life of components developed from carbon fibre. It can also assist the manufacturing industries in making effective decisions relating to component recovery.

关键词： Process design Transportation industry Energy conservation Transportation Product development Manufacturing Recycling

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Commercial and Technological Feasibility of Solar Powered e-Rickshaw: A Case Study in the Capital of Chhattisgarh

Commercial and Technological Feasibility of Solar Powered e-...

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Sustainable Energy Technologies and Computational Intelligence (SETCOM), International Conference on

作者： Shravan Kumar Singh Nihar Ranjan Sahu Mohammad Arif Khan Jagat Narayan Baiga Rajesh Singh Rana Nikhil Chander Department of Electrical Engineering Indian Institute of Technology Bhilai Tadoba Solutions Pvt. Ltd. Sejbahar Raipur Durg India Chhattisgarh State Renewable Energy Development Agency (CREDA) Raipur India Department of Mechatronics Engineering Indian Institute of Technology Bhilai Durg India Department of Electrical Engineering and Electronics and Communication Engineering Indian Institute of Technology Bhilai Durg India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

India accounts for around $18 \%$ of global CO 2 emissions from transportation. Transportation with conventional energy sources such as coal, oil, and natural gas is costly and poses environmental challenges. The Government of India promotes and subsidizes electric vehicles for fast adoption. The e-Rickshaw is an ideal option for short-distance travel in urban areas due to its low cost. However, one major challenge of e-Rickshaws is battery charging for long-distance travel. In this research article, a survey of e-Rickshaws is conducted in the capital of Chhattisgarh, with an e-Rickshaw powered by a flexible solar photovoltaic (PV) module ($\mathbf{4 2 5} \mathbf{~ W p}$) with a maximum power point tracking (MPPT) charge controller, properly designed, installed, and commissioned on the roof of the vehicle. A comparative analysis of a conventional e-Rickshaw and an e-Rickshaw integrated with a solar PV module is presented. The conventional e-Rickshaw consumes around 7-9 units of electricity per day to fully charge the batteries, resulting in an annual utility bill of approximately Rs. $15,330-19,710$ at a rate of Rs. 6.0 per unit. After integrating the PV module, the e-Rickshaw operator can save up to Rs. 5,475 per year. Additionally, the operator’s travel range and income increase by up to Rs. 7,200 per month. Solar PV integration on the e-Rickshaw mitigates about 0.56 tonnes of CO 2 emissions per year per e-Rickshaw.

关键词： Maximum power point trackers Surveys Oils Urban areas Transportation Batteries Solar panels Sun Carbon emissions Natural gas

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The Classification of Skateboarding Tricks by Means of the Integration of Transfer Learning Models and K-Nearest Neighbors

The Classification of Skateboarding Tricks by Means of the I...

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Innovative Manufacturing, mechatronics and Materials Forum, iM3F 2020

作者： Shapiee, Muhammad Nur Aiman Ibrahim, Muhammad Ar Rahim Mohd Razman, Mohd Azraai Abdullah, Muhammad Amirul Musa, Rabiu Muazu Abu Osman, Noor Azuan P. P. Abdul Majeed, Anwar Innovative Manufacturing Mechatronics and Sports Laboratory Faculty of Manufacturing and Mechatronic Engineering Technology Universiti Malaysia Pahang Pekan Pahang Darul Makmur26600 Malaysia Universiti Malaysia Terengganu Terengganu Malaysia Centre for Software Development & Integrated Computing Universiti Malaysia Pahang Pekan Pahang Darul Makmur26600 Malaysia

ISBN: (纸本)9789813345966

The skateboarding scene has reached new heights, especially with its first appearance at the now postponed Tokyo Summer Olympic Games. Therefore, owing to the scale of the sport in such competitive games, advanced innovative assessment approaches have increasingly gained due attention by relevant stakeholders, especially with the interest of a more objective-based evaluation. We employed pre-trained Transfer Learning coupled with a fine-tuned k-Nearest Neighbor (k-NN) classifier to form several pipelines to investigate its efficacy in classifying skateboarding tricks, namely Kickflip, Pop Shove-it, Frontside 180, Ollie and Nollie Front Shove-it. From the five skateboarding tricks, a skateboarder would repeatedly perform it for five successful landed tricks captured by YI action camera. From that, the images would be feature engineered and extracted through five Transfer Learning models, namely VGG-16, VGG-19, DenseNet-121, DenseNet-201 and InceptionV3, then classified by employing the k-Nearest Neighbor (k-NN) classifier. It is demonstrated from the preliminary results, that the VGG-19 and DenseNet-201 pipeline, both attained a classification accuracy (CA) of 97% on the test dataset, followed by the DenseNet-121 and InceptionV3, in which both obtained a test CA of 96%. The least performing pipeline is the VGG-16, where a test CA of 94% is recorded. The result from the current study validated it could providing an objective judgment for judges in classifying skateboard tricks for the competition. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Pipelines

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Heart Rate-Based Prediction of Daily Activity Levels Using Wearable Devices for Home Rehabilitation Process of Cardiac Patients

Heart Rate-Based Prediction of Daily Activity Levels Using W...

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International Conf on Electrical and Electronic Engineering (ICEEE)

作者： Sahika Betul Yayli Yasemin Yetimova Isil Ozkan Ibrahim Cem Balci Irem Sayin Serkan Salturk Ipek Aydin Abdullah Omer Ebeoglu Hasan Ali Barman Huseyin Uvet Artificial Intelligence & Digital Analytic Solutions Turkcell Technology Istanbul Turkey RD Strategy and Business Development Turkcell Technology Istanbul Turkey Department of Mechatronics Engineering Yildiz Technical University Istanbul Turkey Department of Informatics Yildiz Technical University Istanbul Turkey Faculty of Medicine Istanbul University - Cerrahpasa Istanbul Turkey

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

This study aims to contribute to the literature by developing an advanced Long Short-Term Memory (LSTM) model that classifies and predicts the duration of patients' daily physical activities (resting, light, moderate, intense) using heart rate data. This approach is an innovative step towards personalizing cardiac rehabilitation programs and accurately monitoring patients' daily activity levels. The application of this model aims to allow healthcare professionals to objectively track patients' activity levels. Data collection was conducted at the Istanbul University - Cerrahpaşa, Cardiology Institute exercise test laboratory during the years 2023–2024. Heart rate (bpm) of the patients was recorded through a Garmin watch worn on the wrist during exercise tests conducted using the Modified Bruce Protocol. The study included patients aged between 18 and 85 with medium-risk pre-test probability for coronary artery disease. The collected data underwent preprocessing, including synchronization of heart rate data with exercise test records and removal of inconsistent or illogical data points. LSTM model was chosen for analyzing sequential data related to heart rate over time. The model consisted of two LSTM layers and one output layer, achieving a prediction accuracy of 59.1% on the test dataset. Further efforts are underway to enhance the model's performance within the project scope. This research underscores the importance of objective activity tracking and highlights the potential to fill existing gaps in this field. The developed model, based on heart rate data collected via wearables, is expected to serve as an objective tool for monitoring cardiac rehabilitation processes and daily activity levels. By evaluating data collected through wearables, the model facilitates the calculation of individuals' durations of rest, light, moderate, and high-intensity activities throughout the day, contributing to personalized health care practices.

关键词： Heart rate Wrist Accuracy Medical services Predictive models Data models Synchronization Wearable devices Long short term memory Monitoring

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Technologies for e-Mobility

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IEEJ Transactions on Industry Applications 2024年第7期144卷 513-522页

作者： Kato, Takashi Kuroda, Hisashi Matsumoto, Kaori Onaya, Jun Hosono, Kenji Kaneo, Hidetsugu Yamaguchi, Koji Morimoto, Masayuki Yoshimoto, Kantaro Yamamoto, Masayoshi Ota, Yutaka Nissan Motor Co. Ltd. 1 Natsushima-cho Kanagawa Yokosuka237-8523 Japan New Energy and Industrial Technology Development Organization 15F Muza Kawasaki Central Tower 1310 Omiya-cho Saiwai-ku Kanagawa Kawasaki212-8554 Japan IHI Corporation 3-1-1 Toyosu Koto-ku Tokyo135-8710 Japan MorimotoR Labs. Higashi-cho Kanagawa Atsugi243-0001 Japan Department of Robotics and Mechatronics School of Science and Technology for Future Life Tokyo Denki University 5 Senju Asahi-cho Adachi-ku Tokyo120-8551 Japan Nagoya University Furo-cho Chikusa-ku Nagoya464-8603 Japan Graduate School of Engineering Osaka University 2-1 Yamadaoka Suita Osaka565-9871 Japan

To reduce carbon dioxide emissions from mobility, electrified vehicles and mobility have been rapidly increasing in recent years. In this regard, this paper presents the latest trend of technologies supporting mobility electrification, such as electric motors, inverters, and related technologies including vehicle-to-everything, as social systems. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Carbon dioxide

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Advanced Cybersecurity: A Comprehensive Overview of an Enhanced Cybersecurity Assisted Cryptography Strategy for Protected Image Communication

Advanced Cybersecurity: A Comprehensive Overview of an Enhan...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Ramesh, S. Rajalakshmi, A. Balan, A Siva Vijaya Vardan Reddy, S.P. Jayant, Giri Al-Safarini, M.Y. Rajalakshmi Engineering College Department of Mechatronics Engineering Chennai India Vel tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Information Technology Chennai India Easwari Engineering College Department of Ece Chennai India R.M.K. Engineering College Department of Ece Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Zarqa University Computer Science Department Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

Some problems exist with the classic Elliptic Curve Cryptography (ECC) algorithm, which uses logistic maps as its foundation. We employ an upgraded ECC system to make things more secure. It relies on a location transform and a random sequence to change the pixel values. The Cybersecurity based Cryptography Strategy (CCS) is a new model that improves upon the previous approach in terms of security. It was introduced in this publication. By modifying the values of each pixel, the suggested algorithm shuffles the picture according to the protected sequence. The key uses a secret look-up matrix to generate 32 security key sequences from a given sequence. The encryption key works by operating on n sub-parts of the picture, which increases efficiency. An image encryption technique can be practically tested in Matlab. Histogram comparison, correlation coefficient, and secret key sensitivity are some of the ways the algorithm's security is examined. The suggested algorithm can withstand statistical, brute-force, and plain-text attacks with ease. This innovation provides a safer method of guaranteeing the safety of image data, which may be stored anywhere, even on the cloud. We have presented the final product after testing it on many types of photographs. Lastly, the results of the experiments demonstrate that the encryption is well-built and has protection capabilities;moreover, it is able to resist intense, statistical, and differential attacks. © 2024 IEEE.

关键词： CCS Cryptography Cybersecurity ECC Elliptic Curve Cryptography Enhanced Security Protected Image Secured Communication

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Research on Fuzzy PI Control Method of GDI Engine Common Rail Pressure

Research on Fuzzy PI Control Method of GDI Engine Common Rai...

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2021 China Automation Congress, CAC 2021

作者： Zhang, Liying Li, Hongbo Xi, Zhiyuan Xu, Ting Department of Mechatronics and Information Engineering Changchun College of Humanities Changchun China Research and Development Department Changchun Zhongke Keyi Technology Limited Company Changchun China Electronic Information Engineering ChangChun University ChangChun China

ISBN: (纸本)9781665426473

The rail pressure of engine common rail system fluctuates with different driving conditions. The constant value control of rail pressure is one of the key technologies to improve the emission and dynamic characteristics. Fuzzy algorithm is used to adaptively adjust the parameters of PI controller under all working conditions. According to the information of the reference rail pressure, the change rate of the reference rail pressure and the rail pressure error, the parameters of the PI controller under each working condition are adjusted by fuzzy reasoning, The rail pressure of the common rail system is adaptively controlled under idle speed, acceleration, high-speed driving, moving condition and sudden change condition. The simulation results show that the fuzzy PI method is superior to the traditional control method in tracking accuracy and response speed, and meets the requirements of the actual common rail system rail pressure control. © 2021 IEEE

关键词： Controllers

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