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Task Planning and Collaboration of Jellyfish-inspired Multiple Spherical Underwater Robots

Journal of Bionic engineering 2022年第3期19卷 643-656页

作者： Ruochen An Shuxiang Guo Yuanhua Yu Chunying Li Tendeng Awa Graduate School of Engineering Kagawa UniversityTakamatsuKagawa761-0396Japan Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information TechnologySchool of Life Science and TechnologyBeijing Institute of TechnologyBeijing100081China School of Life Science and Technology Changchun University of Science and TechnologyChangchun130022China

Task planning and collaboration of multiple robots have broad application prospects and value in the field of *** improve the performance and working efficiency of our Spherical Underwater Robot(SUR),we propose a multi-robot control strategy that can realize the task planning and collaboration of multiple *** complete real-time information sharing of multiple robots,we first build an acoustic communication system with excellent communication performance under low noise ratio ***,the task planning and collaboration control strategy adjust the SURs so that they maintain their positions in the desired formation when the formation *** SURs can move along desired trajectories in the expected *** control strategy of each SUR uses only its information and limited information of its neighboring ***,based on theoretical analysis and experiments,we evaluate the validity and reliability of the proposed *** comparison to the traditional leader–follower method,it is not necessary to designate a leader and its followers explicitly in our system;thus,important advantages,such as fault tolerance,are achieved.

关键词： Task planning Collaboration control Multiple spherical underwater robots(SUR) Shape keeping

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Tooth Localization using YOLOv3 for Dental Diagnosis on Panoramic Radiographs

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2022年第5期142卷 557-562页

作者： Bui, Toan Huy Hamamoto, Kazuhiko Paing, May Phu Course of Science and Technology Graduate School of Science and Technology Tokai University Tokyo108-8619 Japan School of Information and Telecommunication Engineering Tokai University Tokyo108-8619 Japan School of Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok10520 Thailand

Oral health is one of most major concerns that affect the life quality of billions of people around the world. Diagnosis treatment usually takes time due to the lack of doctors compared to a huge number of patients. Many researchers proposed methods to make an early disease detection for patients to assist doctors using computer aid diagnosis (CAD). However, most previous methods are not end-to-end methods and still require human involvement. The biggest challenge is that most researchers do not provide a good tooth detection technique before diagnosis. Therefore, the main objective, that builds a system to assist doctors, remains unaccomplished or just fairly successful. This paper proposed a detection method to localize the tooth using the Yolov3 model as a base network in the dental panoramic radiograph. The method consists of two main parts: image preprocessing and tooth localization. Firstly, because deep learning requires a big dataset, the original image is applied augmentation technique to improve the size of the dataset as well as diversity. Then, each image is resized to fit the input layer of the network;however, to prevent the information loss and boost the performance, we keep the original ratio of the images and change the ratio of the input layer in the model that can fit the image ratio. Next, we feed images into Yolov3, which is specially modified to fit the problem, for training. We add more detection heads into the backbone and concatenate the previous head detection’s result with a proper layer to produce a more preeminent result. The final assessment shows an impressive result that the method reaches 95.58% and 94.90% for precision and recall, respectively. As a result, our proposed method is more reliable and practical in the tooth localization field, as well as helpful to reduce the doctor's effort. © 2022 The Institute of Electrical Engineers of Japan.

关键词： Object detection

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices 3

Random Number Generator for Securing Data Exchange in Smart ...

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3rd International Conference on Computer Technologies, ICCTech 2024

作者： Sama, Andi Meyliana Heryadi, Yaya Sahroni, Taufik Roni Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information System Information System Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Jakarta Computer Science Department Jakarta11530 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350395419

IT/OT convergence in the form of a Cyber-Physical system (CPS) presents an opportunity to apply recent information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption. © 2024 IEEE.

关键词： Data transfer

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Proposal of a novel peeling of nano-particle (PNP) process for localized material removal on a hard material surface by controllable magnetic fields 22

Proposal of a novel peeling of nano-particle (PNP) process f...

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22nd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2022

作者： Permpatdechakul, Thitipat Khajornrungruang, Panart Suzuki, Keisuke Kutomi, Shotaro Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Avanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

This article proposes a novel Peeling of Nano-Particle (PNP) process to locally remove material on a hard material surface using controllable magnetic fields. Fe3O4 particles in the size range of 50-100 nm in aqueous solution (pH value 11 adjusted by KOH) were magnetically controlled to adhere and remove from a 4H-SiC surface by two electromagnetic coils, which were sandwiched between the substrate. The particle controlling phenomenon on the surface was experimentally observed and verified by our developed apparatus applying an evanescent field. According to the results, particles could be controlled to approach and remove from the substrate surface with 12mT of magnetic field at the selective area on the substrate surface to realise the proposed PNP process. © European Society for Precision engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Magnetic fields

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A Teaching Materials Recommendation system Considering Individual Characteristics 16

A Teaching Materials Recommendation System Considering Indiv...

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16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Yin, Chengjiu Shiroki, Ryoya Lin, Lin Li, Huiyong Research Institute for Information Technology Kyushu University Fukuoka Japan Graduate School of System Informatics Kobe University Kobe Japan School of Software Technology and DUT-RU International School of Information Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350377903

In this study, we proposed and implemented a combined recommendation system by utilizing both learning log data, which contributes to improving learning performance, and learning style questionnaire, which contributes to increasing learning motivation. We also conducted an empirical experiment to evaluate the effect of the proposed recommendation system on learning performance, read efficiency, and perception of the proposed system. Students learned the same teaching material from the Commercial Law course. They were divided into three groups and received a page recommendation of the teaching material: recommended by only VARK data, recommended by only learning log, and recommended by both of V ARK data and learning log data. The findings show that the students who received the combined recommendation increased their mean values of learning performance and reading efficiency in the experiment and reported the highest improvement in usefulness and satisfaction on the system. On the other hand, the students who received the log data-only recommendation didn't increase their mean values of learning performance and reading efficiency and reported the lowest improvement of usefulness and satisfaction on the system. The students' post-questionnaires on their learning motivation and suggestions for learning recommendation system are also discussed. © 2024 IEEE.

关键词： Federated learning

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A Sensorless Parallel Gripper Capable of Generating Sub-Newton Level Grasping Force

A Sensorless Parallel Gripper Capable of Generating Sub-Newt...

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2024 IEEE/SICE International Symposium on system Integration, SII 2024

作者： Sato, Mutsuhito Arita, Hikaru Mori, Yoshiki Kawamura, Sadao Wang, Zhongkui Robotics Course of the Graduate School of Science and Engineering Ritsumeikan University Kusatsu Japan Kyushu University Department of Mechanical Engineering Fukuoka Japan Ritsumeikan University Department of Information Science and Engineering Kusatsu Japan Ritsumeikan Global Innovation Research Organization Ritsumeikan University Japan Ritsumeikan University Department of Robotics Kusatsu Japan

ISBN: (纸本)9798350312072

Upon grasping a fragile object, small grasping force and gripper compliance are required to avoid large deformation or damage to the object. In this study, linear servomotor based mechanism is used to construct a parallel gripper which is able to achieve small gripping force and compliance without using external force sensors. The linear motor mechanism has low friction and no reduction gear. Therefore, it can produce small thrust force with high back-drivability. The proposed parallel gripper consists of two linear motor mechanisms, a guide rail, a frame, and two fingers. The thrust force of the linear motor can be controlled through a driver. The components of the gripper were manufactured using metal machining and 3D printing, and they were carefully assembled to ensure good axial alignments. Force calibration was conducted and the minimum grasping force was confirmed as a value of 0.076 N. The friction force of the guide rail was also experimentally measured and it was confirmed to be 0.090 N. Finally, grasping experiments were conducted on potato chips and tofu. Results suggested that the proposed parallel gripper is able to handle fragile objects with sub-Newton level force. © 2024 IEEE.

关键词： Grippers

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Evaluation of User Interface, User Experience, and Usability in Software Through Electroencephalography (EEG) Signal Detection: A Mapping Review

Evaluation of User Interface, User Experience, and Usability...

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2023 International Workshop on Artificial Intelligence and Image Processing, IWAIIP 2023

作者： Syahidi, Aulia Akhrian Kiyokawa, Kiyoshi Politeknik Negeri Banjarmasin Smart City Information System Department of Electrical Engineering Banjarmasin Indonesia Nara Institute of Science and Technology Division of Information Science Graduate School of Science and Technology Nara Ikoma Japan

ISBN: (纸本)9798350382914

As the digital landscape continues to evolve through the widespread use of software, understanding how users interact with software becomes increasingly important. This article presents the findings of a literature review that explores the use of Electroencephalography (EEG) signals to assess user interfaces, user experience, and/or software usability. We used the mapping review method in this research with the main stages including: 1) Establishing research questions;2) Source selection;3) Identifying keywords;4) Carrying out a screening process;and 5) Extracting and synthesizing data. As a result, we determined 16 relevant papers as primary sources. We highlight the distribution of papers from various databases and their suitability for the period January 2013 to May 2023. In addition, we find that traditional EEG devices, standard five frequency bands, 32 electrodes, signal classification techniques such as Linear Discriminant Analysis (LDA), Frequency Fourier Transform (FFT), and Power Spectrum Density (PSD), gaming software as research subjects, and user experience evaluation questionnaires are most widely used in research practice. The results of this literature review provide comprehensive insight into the latest developments in the use of EEG signals to evaluate software in terms of the field of Human-Computer Interaction, to reduce the factors of subjectivity, bias, efficiency, and accuracy of evaluation results. These insights can serve as a basis for further research and the development of more effective methods and tools for improving software quality. © 2023 IEEE.

关键词： User interfaces

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Stock Monitoring and Localization systems for FIFO Method Using RFID Based Pressure Sensing Tag and AI

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2024年第9期144卷 894-900页

作者： Hadi, Danang Kumara Song, Zequn Rahmadya, Budi Sun, Ran Takeda, Shigeki Graduate School of Science and Engineering Ibaraki University 4-12-1 Nakanarusawa Ibaraki Hitachi316-8511 Japan Department of Agroindustrial Technology Universitas Muhammadiyah Jember Jember68124 Indonesia Computer System Department Faculty of Information Technology Andalas University Padang25175 Indonesia

This research introduces real-time monitoring and localizing product stock using the First-In-First-Out (FIFO) method with radio frequency identification (RFID) pressure sensing tags. The proposed FIFO system has RFID pressure sensing tags that detect pressure changes, generate sensor codes, and estimate a stock location. Integrating artificial intelligence (AI) improves location estimation accuracy of up-to-date stock visibility. The ability of RFID pressure sensing tags and AI to detect stock from sensor code data enables more effective asset management, optimizes stock management, reduces product waste, and contributes to better efficiency in product inventory management. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Inventory control

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Detection of Pre Shoplifting Suspicious Behavior Using Deep Learning 16

Detection of Pre Shoplifting Suspicious Behavior Using Deep ...

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16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Shrestha, Sujan Taniguchi, Yoji Tanaka, Tetsuo Graduate school of Engineering Kanagawa Institute of Tehnology Course of Information and computer sciences Atsugi Japan Daiichi Institute of Technology Artificial Intelligence and Data Science Department of Information Tokyo Japan Kanagawa Institute of Technology Faculty of Information Technology Dept. of Information and Computer Sciences Atsugi Japan

ISBN: (纸本)9798350377903

Shoplifting presents a significant challenge for retailers, leading to substantial financial losses and security concerns. Current surveillance systems effectively identify shoplifting incidents postoccurrence;however, the capability to detect and prevent such activities preemptively remains limited. This research focuses on identifying behaviors that likely precede shoplifting events. To this end, we introduce a novel benchmark dataset, specifically designed for the early detection of suspicious behavior that may lead to shoplifting. This dataset is curated by selecting and segmenting relevant sequences from the UCF101-Crime dataset, encompassing suspicious behavior, actual shoplifting incidents, and normal activities. Our approach addresses the limitations of existing datasets where the brief duration of shoplifting events may skew neural network performance. The dataset includes clips of only a few seconds each, for which we propose a robust neural network architecture combining the strengths of convolutional neural networks (CNN) for efficient feature extraction and Bidirectional long short-term memory (BiLSTM) networks for capturing temporal dependencies within action sequences. Our model achieves an impressive classification accuracy of 86.21 % on the newly created dataset. © 2024 IEEE.

关键词： Convolutional neural networks

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Human-Robot Interaction through an Object Grasped with Two Fingers Based on Plastic Deformation Control

Human-Robot Interaction through an Object Grasped with Two F...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Senoo, Taku Konno, Atsushi Kawahara, Hiromichi Ishii, Idaku Course of Systems Science and Informatic Graduate School of Information Science and Technology Hokkaido University Kita 14 Nishi 9 Kita-ku Sapporo Hokkaido060-0814 Japan Smart Innovation Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8527 Japan

ISBN: (纸本)9781665481090

In this study, two-finger grasping based on plastic deformation control for human-robot interaction is designed and implemented. This control strategy is derived based on the concept that balances both retention of grasping force on objects and plastic behavior in response to external forces. The control law consists of a set of constraints and offsets with respect to the springs that appear in the Maxwell model. In particular, the inner loop that is robust against parameter errors is implemented for actual machine experiments. Simulation and actual experiments with a robotic hand are executed to validate the proposed control law. © 2024 IEEE.

关键词： Human robot interaction

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