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14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023

作者： Tanaka, Toru Fukazawa, Takaki Kameya, Yoshitaka Yamada, Keiichi Hotta, Kazuhiro Takahashi, Tomoichi Sassa, Naoto Matsukawa, Yoshihisa Iwano, Shingo Yamamoto, Tokunori Meijo University Graduate School of Science and Technology Japan Meijo University Faculty of Science and Technology Japan Meijo University Faculty of Information Engineering Japan Meis Technology Inc. Japan Aichi Medical University School of Medicine Japan Nagoya University Graduate School of Medicine Japan

ISBN: (纸本)9798350324228

Convolutional neural networks (CNNs) have been used as standard deep neural networks in medical image analysis owing to their ability to automatically extract high-level features from training images. However, detecting kidney cancer from a wide variety of abdominal computed tomography (CT) images remains challenging. Recently, Transformer-based models have demonstrated higher predictive performance in computer vision tasks. Thus, in this study, we applied two Transformer-based models named the Vision Transformer (ViT) and the Swin Transformer to detection of kidney cancer from various types of abdominal CT images. Our experimental results show that our transformer-based models generally performed better than conventional CNNs, such as VGG-16 and ResNet-50, in term of detection accuracy across various types of CT images. © 2023 IEEE.

关键词： Convolutional neural networks

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SEASONAL PATTERNS OF PHYSICAL ACTIVITY AND SEDENTARY BEHAVIOR AND INDOOR THERMAL ENVIRONMENT AMONG ADULTS LIVING IN SUBURBAN RESIDENTIAL AREA

Journal of Environmental Engineering (Japan)

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Journal of Environmental engineering (Japan) 2024年第820期89卷 340-350页

作者： Ito, Maki Ando, Shintaro Umishio, Wataru Oguma, Yuko Saito, Yoshinobu Ikaga, Toshiharu Sekisui House Ltd. Japan Faculty of Environmental Engineering The Univ. of Kitakyushu Japan School of Environment and Society Tokyo Institute of Technology Japan Graduate School of Health Management Sports Medicine Research Center Keio Univ Japan Faculty of Sport Management Nippon Sport Science Univ. Japan Sports Medicine Research Center Keio Univ. Japan Faculty of Science and Technology Keio Univ. Japan

This study examined the seasonal patterns of physical activity (PA) and sedentary behavior (SB) and the relationship between PA and SB and the indoor thermal environment in each season. 98 of 131 the participants were analyzed. 1) Daily moderate-to-vigorous PA was significantly greater in fall than in winter. 2) Adjusting the accelerometer wearing time, outdoor PA and SB were not significantly related to season, but indoor moderate-to-vigorous PA were significantly greater in fall and summer than in winter. 3) Using a kotatsu in winter was associated with longer SB and less light-intensity PA than using an air conditioner. © 2024 Architectural Institute of Japan. All rights reserved.

关键词： Air conditioning

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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif Zohaib Mushtaq Muhammad Irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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Data-Driven State Feedback Gain Update Based on Model Matching in Frequency Domain

Data-Driven State Feedback Gain Update Based on Model Matchi...

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2024 International Conference on Advanced Mechatronic systems, ICAMechS 2024

作者： Matsui, Yoshihiro Ayano, Hideki Masuda, Shiro Nakano, Kazushi Fukuoka Institute of Technology Faculty of Engineering Fukuoka Fukuoka Japan Tokyo College National Institute of Technology Department of Electrical Engineering Hachioji Tokyo Japan Tokyo Metropolitan University Graduate School of Systems Design Engineering Hino Tokyo Japan The University of Electro-Communications Chofu Tokyo Japan

ISBN: (纸本)9798350366204

This paper presents a method for updating the state feedback gain of an LTI single-input nth-order system using data-driven techniques. The goal is to match the closed-loop system to a desired reference model, which is represented by a complementary sensitivity function. To achieve this, a new model matching error is introduced. The appropriate gain can be determined using the least squares method in the frequency domain, based on closed-loop data obtained from an improperly tuned system due to model errors. Although the proposed method is specialized for updating the state feedback gain, it can perform gain updates that take into account the effects of noise at an extremely low computational cost. The method's effectiveness is demonstrated through numerical experiments. © 2024 IEEE.

关键词： State feedback

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Quality Improvement of Children's Speech by Speaker Vector in General Purpose Vocoder 11

Quality Improvement of Children's Speech by Speaker Vector i...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Yoshida, Satoshi Furuya, Ken'Ichi Mizuno, Hideyuki Oita University Graduate School of Engineering Japan Oita University Faculty of Science and Technology Japan Suwa University of Science Faculty of Engineering Japan

ISBN: (纸本)9781665492324

A neural vocoder is a vocoder that converts acoustic features into speech signals by applying deep learning and is capable of synthesizing high-quality speech so that it is indistinguishable from human speech. The objective of this research is to create a general-purpose vocoder that can synthesize high-quality speech for children and adults. We propose a speaker vector to improve the quality of synthesized speech of children. The quality of the synthesized speech is evaluated by comparing each model with the speaker vector and the amount of training data, and the effectiveness of the proposed method is confirmed. © 2022 IEEE.

关键词： Speech synthesis

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Size-fractionated carbonaceous particles and climate effects in the eastern region of Myanmar

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Particuology 2024年第7期90卷 31-40页

作者： Mai Kai Suan Tial Nwe Nwe Kyi Muhammad Amin Mitsuhiko Hata Masami Furuuchi Rahmi Mulia Putri Phakphum Paluang Phuchiwan Suriyawong Worradorn Phairuang Department of Electrical Power Engineering Yangon Technological UniversityYangon11011Myanmar Faculty of Geosciences and Civil Engineering Institute of Science and EngineeringKanazawa UniversityKanazawaIshikawa920-1192Japan Faculty of Engineering Maritim University of Raja Ali HajiTanjung PinangKepulauan Riau 29115Indonesia Graduate School of Natural Science and Technology Kanazawa UniversityKanazawaIshikawa920-1192Japan Department of Geography Faculty of Social SciencesChiang Mai UniversityMuangChiang Mai50200Thailand Research Unit for Energy Economics and Ecological Management Multidisciplinary Research InstituteChiang Mai UniversityMuangChiang Mai50200Thailand

This study reports on an investigation of fine and coarse carbonaceous particulate matters(PM)in Tachileik,eastern Myanmar,during the dry and wet seasons of *** carbon compositions,including organic carbon(OC)and elemental carbon(EC),in each size(PM10-2.5,PM2.5-1.0,and PM1.0-0.5)were determined by a carbon *** average total mass concentration of the three fractions of particle samples during the dry season was higher(51.23±23.86μg/m3)than that of the wet season(14.00±5.26μg/m3).The results indicate that OC and EC levels were highest for PM1.0-0.5 during the dry season and the sizes were similar for both *** OC/EC ratios varied in different seasons,from 1.93 to 4.40 and 4.13 to 5.25 in the dry and wet seasons,*** was sub-divided into char-EC and soot-EC;the char-EC/soot-EC in the dry season was higher than in the wet season,signifying that biomass burning is the main particle source during the dry ***,vehicle emissions dominated during the wet *** effective carbon ratio(ECR)suggested that finer particles contributed more to global *** information is important in terms of air quality control and mitigation in Myanmar and elsewhere.

关键词： Air quality Biomass burning Carbon Coarse particles Fine particles Myanmar

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KDRM: Kernel Data Relocation Mechanism to Mitigate Privilege Escalation Attack 17th

KDRM: Kernel Data Relocation Mechanism to Mitigate Privileg...

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Network and System Security - 17th International Conference, NSS 2023, Proceedings

作者： Kuzuno, Hiroki Yamauchi, Toshihiro Graduate School of Engineering Kobe University Kobe Japan Faculty of Environmental Life Natural Science and Technology Okayama University Okayama Japan

ISBN: (纸本)9783031398278

A privilege escalation attack by memory corruption based on kernel vulnerability has been reported as a security threat to operating systems. Kernel address layout randomization (KASLR) randomizes kernel code and data placement on the kernel memory section for attack mitigation. However, a privilege escalation attack will succeed because the kernel data of privilege information is identified during a user process execution in a running kernel. In this paper, we propose a kernel data relocation mechanism (KDRM) that dynamically relocates privilege information in the running kernel to mitigate privilege escalation attacks using memory corruption. The KDRM provides multiple relocation-only pages in the kernel. The KDRM selects one of the relocation-only pages and moves the privilege information to the relocation-only pages when the system call is invoked. This allows the virtual address of the privilege information to change by dynamically relocating for a user process. The evaluation results confirmed that privilege escalation attacks by user processes on Linux could be prevented with KDRM. As a performance evaluation, we showed that the overhead of issuing a system call was up to 149.67%, and the impact on the kernel performance score was 2.50%, indicating that the impact on the running kernel can be negligible. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Virtual addresses

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Adaptive FRIT-Based Recursive Robust Controller Design Using Forgetting Factors 32

Adaptive FRIT-Based Recursive Robust Controller Design Using...

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32nd Mediterranean Conference on Control and Automation, MED 2024

作者： Tsuruhara, Satoshi Ito, Kazuhisa Graduate School of Engineering and Science Functional Control Systems Shibaura Institute of Technology Minuma Saitama3378570 Japan Japan Society for the Promotion of Science Tokyo1020083 Japan Shibaura Institute of Technology Department of Machinery and Control Systems Minuma Saitama3378570 Japan

ISBN: (纸本)9798350395440

Adaptive FRIT (A-FRIT) with exponential for-getting (EF) has been proposed for time-varying systems to improve the data dependence of FRIT, which is a direct data-driven tuning method. However, the EF -based method is not a reliable controller because it can cause significant degradation of the control performance and instability unless the persistent excitation (PE) condition is satisfied. To solve this problem, we propose a new A-FRIT method based on directional forgetting (DF) and exponential resetting that can forget old data without instability regardless of the PE condition. To confirm the effectiveness of the proposed method, we applied it to artificial muscle control with strong asymmetric hysteresis characteristics and evaluated its robust performance against load changes during the experiment. The experimental results show that the proposed method based on DF achieves high control performance and is robust against changes in the characteristics and/or target trajectory. The proposed method is also practical because it does not require system identification, model structure, or prior experimentation. © 2024 IEEE.

关键词： Time varying systems

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Recent Progress in MXene‑Based Materials for Metal‑Sulfur and Metal‑Air Batteries:Potential High‑Performance Electrodes

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Electrochemical Energy Reviews 2022年第1期5卷 112-144页

作者： Anmin Liu Xingyou Liang Xuefeng Ren Weixin Guan Tingli Ma State Key Laboratory of Fine Chemicals School of Chemical EngineeringDalian University of TechnologyDalian 116024LiaoningChina School of Ocean Science and Technology Dalian University of TechnologyPanjin 124221LiaoningChina Department of Materials Science and Engineering ChinaJiliang UniversityHangzhou 310018ZhejiangChina Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology2‑4 HibikinoWakamatsuKitakyushuFukuoka 808‑0196Japan

Rechargeable batteries,which are used for renewable energy storage,have paved the way for reducing the enormous pressure of the energy crisis and environmental ***,promising electrode materials with high energy and power density and favorable electrochemical performance for energy conversion and storage have been developed to meet the ever-growing demand for renewable power for electric vehicles or grid ***,which constitute an impressive two-dimensional transition metal carbide/carbonitride family,exhibit great energy storage potential based on their ideal specific surface area,excellent electrical conductivity,and superior chemical durability in *** recent advances in MXenes and their composites for metal-sulfur batteries(specifically lithium-sulfur and sodium-sulfur batteries)and metal-air batteries(specifically lithium-air and zinc-air batteries)are comprehensively and systematically summarized in this ***,the performance management strategies,next-stage research prospects,and remaining practical challenges for MXene-based materials in battery applications are discussed in *** review may provide some guidance for the development and application of MXene-based electrode materials in renewable electrochemical energy storage.

关键词： MXene Metal-sulfur batteries Metal-air batteries Electrode

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Sleep Visualization through Indirect Biofeedback for Patients’ Behavioral Changes and Sleep Quality

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2022年第6期142卷 637-642页

作者： Takahara, Madoka Suto, Hidetsugu Tanev, Ivan Shimohara, Katsunori College of Information and Systems Design and Manufacturing Technology Graduate School of Engineering Muroran Institute of Technology 27-1 Muzumotocho Hokkaido Muroran050-8585 Japan Graduate School of Science and Engineering Doshisha University 1-3 Tatara Miyakodani Kyoto Kyotanabe610-0394 Japan

This paper proposes a sleep visualization system through indirect biofeedback for patients’ behavioral changes and improves sleep quality. In a super-aging society that has been developing in the world, efficient and high-quality cares for elderly people are needed. Especially in nursing care, a lot of patients have sleep problems due to reduced stamina and activity, and it eventually results in the increase of caregivers’ strain and burden. For solving this problem, a sleep visualization system using indirect biofeedback is developed for patients aiming to behavioral changes and improving the sleep quality. To validate the proposed system, an experiment was conducted with five elderly persons. As a result, it is verified that some patients were interested in their sleep quality through the proposed system and the sleep score could be improved. © 2022 The Institute of Electrical Engineers of Japan.

关键词： Visualization

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