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Examination of Slit Defect Inspection Method for Steel Bars Using Only DC Magnetic Field with the Velocity Effect

Sensors and Materials 2024年第9期36卷 3691-3700页

作者： Kuromizu, Masafumi Gotoh, Yuji Graduate School of Engineering Oita University 700 Dannoharu Oita870-1192 Japan Faculty of Science and Technology Oita University 700 Dannoharu Oita870-1192 Japan

C45, a ferromagnetic material, can be strengthened by heat treatment such as quenching and is widely used as a material for general mechanical parts such as springs in automobiles. However, the presence of defects or flaws can cause cracking during the quenching stage, and a high-speed inspection method for detecting defects is required. In this study, we proposed and examined an inspection method for detecting defects using only a DC magnetic field by moving a round steel bar material at a high speed of 1 m/s inside a ring-shaped permanent magnet and generating eddy currents due to the velocity effect. © MYU K.K.

关键词： Ferromagnetic materials

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Tsunami Visualization Tool Using Numerical Simulation Utilizing 3D City Model 13

Tsunami Visualization Tool Using Numerical Simulation Utiliz...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Oshida, Ryutaro Sasaki, Kano Ota, Takao Emoto, Hisao Fukui, Nobuki Graduate School of Sustainability Science Tottori University Tottori Japan Tottori University Faculty of Engineering Department of Social Systems and Civil Engineering Tottori Japan

ISBN: (纸本)9798350373332

After the Noto Peninsula earthquake on January 1, 2024, the importance for residents on the Sea of Japan coast to have a correct understanding of the tsunami hazard is growing. One of the training tools for enhancing tsunami awareness is a tsunami visualization using Virtual Reality (VR). In this study, we create a VR space around Asahi-machi, Sakai-minato City using 3D City Model of PLATEAU, and develop a tsunami evacuation training tool by creating inundation scenarios in the VR space using the results of tsunami inundation simulations with the JAGURS tsunami model. © 2024 IEEE.

关键词： Digital elevation model

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Real-Time Calculation of Strain Energy Density in a Fingertip for Haptic Distribution Rendering

Real-Time Calculation of Strain Energy Density in a Fingerti...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Sase, Kazuya Kato, Haruki Nagano, Hikaru Konyo, Masashi Tohoku Gakuin University Faculty of Engineering Sendai Japan Tohoku Gakuin University Graduate School of Engineering Sendai Japan Kyoto Institute of Technology Graduate School of Science and Technology Kyoto Japan Tohoku University Graduate School of Information Sciences Sendai Japan

ISBN: (纸本)9798331531614

Considering the neural signals generated by mechanoreceptors in response to haptic stimuli when contacting virtual objects is essential to display spatial haptic distributions on the skin in virtual reality applications. This study focuses on reproducing the neural activities of Merkel cells, which are known as slowly adapting type-1 mechanoreceptors. The firing activity of these receptors is known to respond to strain energy density (SED). We developed a real-time SED calculation method using a specially designed finite element (FE) model of a fingertip, which features a simplified layer structure of skin and nail. We validated the model by comparing its calculation results with those of a detailed model and a homogeneous model, using reliable FE analysis software. We demonstrated that modeling the layered structure of the skin is effective in improving the reproducibility of the SED distribution at the locations of Merkel cells. © 2025 IEEE.

关键词： Strain energy

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Evaluation on Damage Behavior under Bending and Lateral Compressive Load of CF/PEEK Round Rod Manufactured by Prepreg Tape Thermal Pultrusion Process

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Zairyo/Journal of the Society of Materials science, Japan 2024年第5期73卷 402-409页

作者： Eguchi, Takeshi Tanabe, Daiki Nishiyabu, Kazuaki Graduate School of Science and Engineering Kindai University Higashiosaka577-8502 Japan Kobe City College of Technology Gakuen-Higashimachi Nishi-ku Kobe651-2194 Japan Faculty of Science and Engineering Kindai University Higashiosaka577-8502 Japan

This study focuses on the pultrusion process and mechanical properties of unidirectional carbon fiber reinforced poly-ether-ether-ketone (CF/PEEK) round rods. A laboratory-scale thermal pultrusion machine with a compressive insert mold was developed to manufacture thermoplastic CFRP round rods. The round rods manufactured using CF/PEEK prepreg tape exhibited high density without visible voids or fiber bundle layers. To investigate the effects of fiber orientation on the mechanical properties of CF/PEEK round rods, the prepreg tapes were pultruded in a twisted state. The mechanical properties of the CF/PEEK round rods were evaluated by a three-point bending test and a lateral compression test, and the damage behavior was investigated by cross-sectional observations after the test. CF/PEEK round rods with twisted fiber orientation exhibited lower elastic modulus and reduced maximum load in the three-point bending tests, but fiber twisting has a significant effect on resistance to lateral compressive loads and stress redistribution. It was confirmed that the complex fiber orientation obtained by twisting the prepreg tape suppresses the straight propagation of transverse cracks in the longitudinal direction of CF/PEEK round rod. The thermal pultrusion process developed in this study was realized as an effective reinforcing method against lateral compressive loads by adding tape twisting. © 2024 The Society of Materials science, Japan.

关键词： Compression testing

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Recognition of American sign language using modified deep residual CNN with modified canny edge segmentation

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Multimedia Tools and Applications 2025年 1-28页

作者： Hariharan, U. Devarajan, Devikanniga Kumar, P. Santhosh Rajkumar, K. Meena, M. Akilan, T. Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab Mohali140413 India Department of Computer Science and Engineering GITAM University Karnataka Bengaluru561203 India Department of Information Technology Faculty of Engineering and technology SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai600089 India Department of Data Science and Business Systems School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India Department of Computer Science and Engineering Sri Sairam Engineering College Tamil Nadu Tambaram602109 India Research Coordinator Dept. of IQAC Amity University Kolkata West Bengal 700135 India

American Sign Language (ASL) recognition aims to recognize hand gestures, and it is a crucial solution to communicating between the deaf community and hearing people. However, existing sign language recognition algorithms still have some drawbacks, such as difficulty recognizing hand movements and low recognition accuracy for most sign language recognition. A Modified Convolutional Neural Network (MCNN) deep residual 101 classifier-based American Sign Language identification system has been developed to address this problem. There are three main parts presents in the method. The first part is pre-processing the images to remove the noise, enhance the contrast of the picture, adjust the contrast level and smoothen the picture using various filters. The second part is the segmentation, and it’s used to partition the image using a modified canny edge detection method by removing all weak edges present in the image. Finally, classification will be done using the Modified CNN deep residual 101 classifiers. By classifying the image, the American Sign Language is accurately identified. This process is conducted through images. The outcome shows that the suggested approach has a 0.97% accuracy and a 0.05% False Positive Rate. Other CNN architectures such as resNet 50 and resNet 18 reached 0.90% and 0.80% accuracy, respectively, which is lower than our proposed method. In addition, the resNet 101 classifier effectively recognizes the difficult hand gestures through the image data. It obtains high recognition accuracy for 36 signs is 0 to 9 numbers and a to z alphabets from American Sign Language. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Hue and Saturation oriented Imperceptible Adversarial Examples and their Evaluation 24

Hue and Saturation oriented Imperceptible Adversarial Exampl...

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6th International Conference on Information technology and Computer Communications, ITCC 2024

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

ISBN: (纸本)9798400717789

With the advancement of machine learning technology, AI can be applied to various systems such as autonomous driving and medical diagnosis. On the other hand, the vulnerability of AI system is pointed out. The adversarial examples (AEs), which causes incorrect decisions by AI, is one of the threats for AI. For using AI safely, AEs has to be investigated thoroughly. In order to evaluate threat of AEs, this paper proposes the generating method for AEs which is based on hue and saturation property of the image. The proposed method which is based on the conventional gradient-based method, introduces constraints for projection in the HSV color space. The proposed method utilizes properties of human vision which is insensitive to changes in color and sensitive to changes in brightness. These properties contribute imperceptibility of AEs. Experiments revealed the vulnerability of DNNs against imperceptible AEs and clarified the importance of countermeasures. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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An Analytical Approach for Nonlinear Buckling Analysis of Torsionally Loaded Sandwich Carbon Nanotube Reinforced Cylindrical Shells with Auxetic Core

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Advances in Applied Mathematics and Mechanics 2023年第2期15卷 468-484页

作者： Dang Thuy Dong Nguyen Thi Phuong Vu Hoai Nam Le Ngoc Ly Nguyen Van Tien Vu Minh Duc Tran Quang Minh Vu Tho Hung Nguyen Thi Huong Giang Faculty of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam Graduate School of Advanced Science and Engineering Hiroshima University1-4-1 KagamiyamaHigashi-HiroshimaHiroshima 739-8527Japan Faculty of Fundamental Science for Engineering University of Transport TechnologyHanoi 100000Vietnam

The main aim of this paper is to present an analytical approach on the postbuckling for torsionally loaded sandwich carbon nanotube(CNT)reinforced cylindrical shells with the auxetic *** considered shells consist of three layers,external and internal CNT reinforced layers,and the auxetic lattice core made by isotropic *** homogenization model for honeycomb auxetic lattice core is utilized,and the equilibrium equations are formulated based on the nonlinear Donnell’s thin shell theory with von Karman geometrical *** three terms of deflection are considered,the Airy’s stress function and Galerkin’s method are utilized,the explicit expression of critical buckling of torsionally loaded shells and load-deflection expression of postbuckling states are *** effects of two carbon nanotube reinforced layers,the auxetic core layer,the volume fraction of carbon nanotube on the torsional buckling behavior are examined and remarked.

关键词： Nonlinear postbuckling carbon nanotube reinforced composite cylindrical shell torsion auxetic core

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Luminance Correction based Countermeasure against Adversarial Examples 24

Luminance Correction based Countermeasure against Adversaria...

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6th International Conference on Information technology and Computer Communications, ITCC 2024

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

ISBN: (纸本)9798400717789

Recently, many kinds of deep learning-based image classification are introduced in various fields, such as face recognition for security authentication and autonomous driving, in order to improve their accuracy. However, previous studies have pointed out the vulnerability of them against Adversarial Examples (AE) which are able to cause misclassification intentionally. The AE utilize micro-perturbations which cannot be detected by the naked eye for causing misclassification. For practical use of the deep learning-based image classification, countermeasure against AE is a mandatory requirement. Therefore, this paper proposes countermeasures of the deep learning-based image classification against AE. The proposed method introduces luminance correction to eliminate the effect of perturbations on AE. After the proposed luminance correction, the deep learning-based image classification classifies images which are contained perturbations. Experiments prove the validity of the proposed method. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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Cross-city insights on sustainable consumption:consistency and disparities in willingness to buy and pay for green air conditioners

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Frontiers of Environmental science & engineering 2025年第4期19卷 169-185页

作者： Jiachao Ke Shujie Zhao Yaozhong Guo Qingbin Song Ni Sheng Jinhui Li National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research Institute Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao SAR 999078China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao SAR 999078China 3.School of EnvironmentTsinghua UniversityBeijing 100084China The Institute for Sustainable Development Macao University of Science and TechnologyMacao SAR 999078China School of Business Macao University of Science and TechnologyMacao SAR 999078China

The intensification of climate change action has made air conditioners a key target for emission *** study examines the factors influencing residents’willingness to buy(WTB)and willingness to pay(WTP)for green air conditioners across six cities in the Pearl River Delta(PRD)region,aiming to understand consumer behavior and inform targeted market *** a novel Contingent Valuation Method(CVM),this study surveyed 1732 residents through online and face-to-face *** logistic and ordered logistic regression analyses identified key factors affecting WTB and WTP,including gender,income,education,knowledge of green air conditioners,and confidence in their emission reduction ***,the study reveals significant regional disparities in WTP and payment amounts through the Kruskal-Wallis H and Mann-Whitney U *** results also highlight Shenzhen has significant difference and highest payment value than other *** findings provide valuable insights into regional disparities and common factors in green consumption,offering guidance for market strategies and policy development aimed at promoting green air conditioners.

关键词： Contingent valuation method Green air conditioners WTB and WTP Influence factors Consistency and difference

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Efficient Parameter Determination for BPDN in Underwater Acoustic MIMO-OSDM Communications Using Stein's Unbiased Risk Estimate

Efficient Parameter Determination for BPDN in Underwater Aco...

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2025 IEEE Underwater technology, UT 2025

作者： Ishijima, Ryoichi Ebihara, Tadashi Wakatsuki, Naoto Maeda, Yuka Mizutani, Koichi Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798331534189

Underwater acoustic (UWA) communication schemes including multiple-input-multiple-output orthogonal signal division multiplexing (MIMO-OSDM) are crucial for the wireless operation of autonomous unmanned vehicles and remotely operated vehicles. This paper presents an efficient regularization parameter determination for MIMO-OSDM to design a reliable communication system. Recent studies have revealed that utilizing sparsity, a physical nature of the UWA channel can improve communication quality. While the combination of MIMO-OSDM and basis pursuit denoising (BPDN) enables the UWA communication that accounts for channel sparsity, this approach requires the prior simulation to obtain a database to fine-tune linear coefficients which decide the regularization parameter of BPDN. To reduce computational cost without sacrificing communication quality, we propose the statistical solution: an application of Stein's unbiased risk estimate (SURE) for MIMO-OSDM using BPDN aiming for parameter determination through a minimization of the channel estimation error. Our simulation results demonstrated that the proposed parameter determinator serves as an estimator of channel estimation error. Our experimental results demonstrated that the proposed channel estimator using SURE achieved almost the same communication quality and demodulation performance as the existing method without prior database creation. © 2025 IEEE.

关键词： Risk perception

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