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2023 IEEE Conference on Antenna Measurements and Applications, CAMA 2023

作者： Kanno, Atsushi Weng, Zu-Kai Kawanishi, Tetsuya Nagoya Institute of Technology Graduate School of Engineering Aichi Japan National Institute of Information and Communications Technology Tokyo Japan Waseda University Faculty of Science and Engineering Japan

Millimeter-wave fixed wireless systems and optical fiber converged network is proposed with their link design and control strategy. The environmental sensors attached to the FWSs are utilized for the link performance ... 详细信息

ISBN: (纸本)9798350323047

关键词： Millimeter waves

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Retroreflection Using Bloch Surface Wave Resonance for External Laser Mirror 12

Retroreflection Using Bloch Surface Wave Resonance for Exter...

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12th IEEE CPMT Symposium Japan, ICSJ 2023

作者： Ozawa, Keisuke Taniguchi, Aika Yamanishi, Yuya Inoue, Junichi Ura, Shogo Graduate School of Science and Technology Kyoto Institute of Technology Kyoto Japan Kyoto Institute of Technology Faculty of Electrical Engineering and Electronics Kyoto Japan

A narrowband retroreflector consisting of a dielectric multilayer is designed for both retroreflecting a diverging incident wave from a semiconductor optical amplifier and supporting a Bloch surface wave. The retroref... 详细信息

ISBN: (纸本)9798350325157

关键词： Surface waves

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Fault and Load Current Interruption in Low-Voltage System Using Fuse-Semiconductor Current-Limiting Circuit Breaker

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IEEJ Transactions on Industry Applications 2024年第6期144卷 502-508页

作者： Inada, Yuki Zen, Shungo Ohnishi, Wataru Kodama, Naoto Nakano, Yusuke Takada, Yasuhiro Sasaki, Reon Miyaoka, Yuta Tsukamoto, Kosuke Yamada, Keiya Yamano, Yasushi Graduate School of Science and Engineering Saitama University 255 Shimo-Okubo Sakura-ku Saitama Saitama338-8570 Japan School of Engineering Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8550 Japan Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Graduate School of Engineering Nagoya University Furo-cho Chikusa-ku Aichi Nagoya464-8603 Japan Institute of Science and Engineering Kanazawa University Kakuma-cho Ishikawa Kanazawa920-1192 Japan Faculty of Pure and Applied Sciences University of Tsukuba 1-1-1 Tenodai Ibaraki Tsukuba305-8573 Japan

For the realization of carbon neutrality and an advanced information society, we have previously developed a novel current-limiting circuit breaker composed of a fuse, a power semiconductor and a fuse exchanger. However, its feasibility has been confirmed only for fault current interruption in a low voltage range of 100–500 V. In this paper, the current-limiting circuit breaker was successfully used for fault and load current interruption at DC 1.5 kV, thus demonstrating the high versatility of the circuit breaker. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Electric circuit breakers

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Generation Method of Error-Specific Adversarial Examples Using Gradient Information for the Target Class 11

Generation Method of Error-Specific Adversarial Examples Usi...

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11th International Conference on Information and Education technology, ICIET 2023

作者： Kumagai, Ryo Takemoto, Shu Nozaki, Yusuke Yoshikawa, Masaya Meijo University Graduate School of Science and Technology Nagoya Japan Meijo University Faculty of Information Engineering Nagoya Japan

ISBN: (纸本)9781665465489

With the advancement of AI technology, vulnerabilities of AI systems have been pointed out. Adversarial Examples (AEs), in which makes AI wrong decisions, are one of the dreaded attacks for AI. Therefore, a thorough investigation of AEs is essential for the safe use of AI. In this paper, we propose a method for generating adversarial examples using gradient information for the target class of input images. We experimentally prove that the proposed method can generate target AEs that misclassify to an arbitrary class with high probability. © 2023 IEEE.

关键词： Deep neural networks

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A Detection Method of Garbage Collection Status from Sound of Garbage Trucks

A Detection Method of Garbage Collection Status from Sound o...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Kunieda, Yuki Suzuki, Hidekazu Meijo University Graduate School of Science and Technology Aichi468-8502 Japan Meijo University Faculty of Information Engineering Aichi468-8502 Japan

ISBN: (纸本)9798350324136

As part of services for citizens in smart cities and the Sustainable Development Goals, there is a service that visualizes the status of garbage collection and allows citizens and government officials to check the status. In Japan, household garbage is put into designated garbage bags and dropped off at designated collection points or in front of homes, and garbage trucks collect them. Therefore, it is not possible to introduce the well-known method of detecting the presence or absence of garbage by attaching sensors to garbage containers. This paper proposes a method to determine the garbage collection status from the sound emitted by garbage trucks utilizing edge computing. A spectrogram of the garbage truck sound is generated and a Convolutional Neural Network is used to identify the characteristic sounds generated during garbage collection. The proposed method was applied to 14 days of garbage collection, and it was confirmed that the proposed method could determine the garbage collection with 90 % accuracy. © 2024 IEEE.

关键词： CNN Garbage collection Loading Sound

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Effect of Takeover Guidance and Surrounding Traffic Information Affect Takeover Performance in Conditional Driving Automation

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International Journal of Automotive engineering 2024年第1期15卷 47-57页

作者： An, Suyang Itoh, Makoto University of Tsukuba Graduate School of Science and Technology 1-1-1 Tennodai Ibaraki Tsukuba305-8573 Japan University of Tsukuba Institute of Systems and Information Engineering 1-1-1 Tennodai Ibaraki Tsukuba305-8573 Japan

With the increasing number of vehicles equipped with conditional driving automation entering the market, it has become important to address the topic of improving driver takeover performance. This study focuses on designing the request to intervene (RtI) under conditional driving automation. We investigated takeover guidance and surrounding traffic information in the RtI influent takeover performance by conducting a driving simulator experiment. 32 participants were divided into four different groups based on the RtI design. The results show that adding surrounding traffic information to the RtI improves the safety of takeover performance. However, the combination of surrounding traffic information and takeover guidance impairs the takeover performance quality. Although all types of additional content (takeover guidance, surrounding traffic information, combination of takeover guidance, and surrounding traffic information) did not increase the participants’ workload during takeover, the participants gave a higher rating to the usability of the surrounding traffic information than the combination. This study demonstrates the importance of providing surrounding traffic information in RtI and the effectiveness of the system usability scale (SUS) in evaluating RtI designs. © 2024 Society of Automotive Engineers of Japan, Inc. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

关键词： Autonomous vehicles

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Development of Machine Learning-Based Assessment System for Laparoscopic Surgical Skills Using Motion-Capture

Development of Machine Learning-Based Assessment System for ...

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

作者： Ebina, Koki Abe, Takashige Yan, Lingbo Hotta, Kiyohiko Highuchi, Madoka Iwahara, Naoya Furumido, Jun Kon, Masafumi Murai, Sachiyo Kurashima, Yo Komizunai, Shunsuke Tsujita, Teppei Sase, Kazuya Chen, Xiaoshuai Senoo, Taku Shinohara, Nobuo Konno, Atsushi Graduate School of Information Science and Technology Hokkaido University Sapporo Japan Hokkaido University Faculty of Medicine Department of Renal and Genitourinary Surgery Sapporo Japan Hokkaido University Clinical Simulation Center Faculty of Medicine Sapporo Japan Kagawa University Faculty of Engineering and Design Takamatsu Japan National Defense Academy of Japan Department of Mechanical Engineering Yokosuka Japan Tohoku Gakuin University Department of Mechanical Engineering and Intelligent Systems Sendai Japan Graduate School of Science and Technology Hirosaki University Hirosaki Japan

ISBN: (纸本)9798350312072

Laparoscopic surgery is a widely used surgical technique, on the other hand, its high degree of difficulty makes it difficult for beginners to learn the technique efficiently. In addition, recent working hour restrictions and shortages of surgeons have resulted in insufficient training time, and establishing the efficiently training methods is becoming urgent needs. Therefore, to promote the skill proficiency of novice surgeons, machine learning-based assessment system for laparo-scopic surgical skills was developed. A measurement system with a simple configuration was introduced so that trainees can easily use it alone. Alternatively, the indices related to the opening ratio and the rotation angle of surgical instruments, which were measured in the authors' previous study were no longer available. Therefore, comparative experiments were conducted to verify the effect of the lack of indices related to these data on the accuracy of skill evaluation. Based on the measurement data of 104 wet lab trainings measured in the previous study, a machine learning model that evaluates surgeon's skill at 3 levels based on the number of surgical experiences, and global operative assessment of laparoscopic skills (GOALS) which is a type of surgical skill evaluation index were established. By using the explainable AI method, this system can present the skill evaluation result including its basis to the trainee. Since the developed system can be easily operated by a GUI-based program, trainees can confirm the quantitative evaluation result on-site immediately after the training. © 2024 IEEE.

关键词： Laparoscopy

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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Computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Waveform Design and Performance Analysis of DFT-Spread WR-OCDM System for PAPR and OOBE Reduction 5

Waveform Design and Performance Analysis of DFT-Spread WR-OC...

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5th IEEE International Conference on Telecommunications and Photonics, ICTP 2023

作者： Hossain, Md. Najmul Nayeem, Md. Aheteshamul Haque Paul, Liton Chandra Shimamura, Tetsuya Pabna University of Science and Technology Faculty of Engineering and Technology Department of Electrical Electronic and Communication Engineering Pabna6600 Bangladesh Graduate School of Science and Engineering Saitama University Sakura-ku Saitama338-8570 Japan

ISBN: (纸本)9798350393477

Recently, orthogonal chirp division multiplexing (OCDM) system has been proposed as an alternative waveform contender for next-generation wireless communication systems. OCDM is a spread spectrum (SS) technique that uses a set of orthogonal chirps as carriers for maximizing the spectral efficiency (SE). However, like OFDM, the OCDM system suffers due to its high out-of-band emissions (OOBE) and high peak-to-average power ratio (PAPR). These lead to adjacent channel interference (ACI) and signal degradation in transmissions. To solve these serious issues, we proposed an advanced OCDM system for reducing OOBE and PAPR without degrading communication quality. The proposed scheme combines discrete Fourier transform (DFT) precoding and time-domain windowing techniques along with the OCDM system. By DFT operation, the energy of each chirp of the OCDM system spreads over all the chirps. Hence, PAPR of the OCDM system is reduced. On the other hand, to reduce the OOBE of OCDM system, time-domain windowing is applied at the transmitter side. Simulation results verify that the proposed scheme reduces PAPR at the CCDF level of 1 × 10-3by 2.43 dB compared to the conventional OFDM, OCDM, and windowing and restructuring (WR)-OCDM systems. In addition, the proposed scheme reduces OOBE by a maximum of 67 dB compared to the OFDM and OCDM systems. Moreover, the bit error rate (BER) performance is evaluated for different modulation formats, such as 4-QAM, 16-QAM, and 64-QAM over the AWGN channel. Our proposed system shows similar BER performance to the conventional multicarrier systems. © 2023 IEEE.

关键词： Peak to average power ratio

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Design of Protocol Converter to Interconnect Matter and ECHONET Lite 12

Design of Protocol Converter to Interconnect Matter and ECHO...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Nagashige, Shunya Suzuki, Hidekazu Meijo University Graduate School of Science and Technology Nagoya Japan Meijo University Faculty of Information Engineering Nagoya Japan

ISBN: (纸本)9798350340181

The iHAC Hub is proposed to interconnect heterogeneous standards of IoT systems. The authors have proposed an interconnection method between Matter, the latest common global smart home standard, and ECHONET Lite, which is certified as a home energy management system standard protocol in Japan, via the iHAC Hub. This paper describes the design of a protocol converter that performs message conversion between Matter and ECHONET Lite. © 2023 IEEE.

关键词： Automation

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