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Formation of Laser-Induced Periodic Surface Structures on Reaction-Bonded Silicon Carbide by Femtosecond Pulsed Laser Irradiation

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Nanomanufacturing and Metrology 2023年第1期6卷 36-48页

作者： Tushar Meshram Jiwang Yan School of Integrated Design Engineering Graduate School of Science and TechnologyKeio UniversityHiyoshi 3-14-1Kohoku-kuYokohama 223-8522Japan Department of Mechanical Engineering Faculty of Science and TechnologyKeio UniversityHiyoshi 3-14-1Kohoku-kuYokohama 223-8522Japan

Reaction-bonded silicon carbide(RB-SiC)is an excellent engineering material with high hardness,stiffness,and resistance to chemical ***,its widespread use is hindered due to the properties mentioned above,making it difficult to machine functional surface structures through mechanical and chemical *** study investigated the fundamental characteristics of laser-induced periodic surface structures(LIPSSs)on RB-SiC via femtosecond pulsed laser irradiation at a wavelength of 1028 ***-spatial-frequency LIPSS(LSFL)and high-spatial-frequency LIPSS(HSFL)formed on the surface along directions perpendicular to the laser *** grains surrounded by a large amount of Si show a reduced threshold for LIPSS *** varying laser fluence and scanning speed,HSFL-LSFL hybrid structures were generated on the SiC *** electron microscopy observations and Raman spectroscopy were carried out to understand the formation mechanism of the hybrid LIPSS.A possible mechanism based on the generation of multiple surface electromagnetic waves due to the nonlinear response of SiC was proposed to explain the hybrid structure ***,the direction of laser scanning with respect to laser polarization affects the uniformity of the generated LIPSS.

关键词： Reaction-bonded silicon carbide Surface texturing Laser-induced periodic surface structure Composite material Hybrid nanostructure

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Fabrication of Miniature Surface Plasmon Resonance Sensor Chip Using Polymeric Prism

Fabrication of Miniature Surface Plasmon Resonance Sensor Ch...

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2023 International Symposium on Electrical Insulating Materials, ISEIM 2023

作者： Jaikeandee, Wisansaya Nootchanat, Supeera Lertvachirapaiboon, Chutiparn Ekgasit, Sanong Shinbo, Kazunari Kato, Keizo Baba, Akira Graduate School of Science and Technology Faculty of Engineering Niigata University Niigata Japan Department of Chemistry Faculty of Science Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9784886864376

In this work, we present the development of a miniature surface plasmon resonance (SPR) sensor chip using the Kretschmann configuration. The SPR sensor chip incorporates a polymeric prism made from Norland Optical Adhesive 61 (NOA 61). By utilizing NOA 61 instead of a conventional prism, we overcome certain limitations associated with conventional SPR spectroscopy. We employed the confined sessile drop technique to fabricate the NOA 61 polymeric prism, which offers several advantages, including simplicity, low-cost fabrication, and precise control over lens parameters. A liquid NOA 61 was dropped directly onto a flat circular disk with a 6-mm diameter made of poly(dimethyl siloxane) (PDMS). The sharp edge of the PDMS circular disk facilitated controlled formation and the desired amount of the liquid NOA 61, resulting in the formation of a hemispherical prism. Subsequently, UV curing was employed to solidify the NOA 61, then obtaining the NOA 61 polymeric prism. To complete the miniature SPR sensor chip, 3 nm-thick chromium layer, and 47 nm-thick gold layer were evaporated onto the planar side of the NOA 61 polymeric prism and then mounted on a microfluidic cell fabricated using a 3D printer. The resulting SPR excitation curves were observed in the visible region and exhibited a refractive index independence sensitivity of 885.4 nm/RIU. Furthermore, we demonstrated the capability of the miniature SPR sensor chip to detect nanomaterials. © 2023 The Institute of Electrical Engineers of Japan.

关键词： Surface plasmon resonance

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Effectiveness of generative adversarial networks in denoising medical imaging (CT/MRI images)

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Multimedia Tools and Applications 2024年 1-25页

作者： Ramadass, Sudhir Narayanan, Sreekumar Kumar, Rajiv K, Thilagavathi Data Analytics Sterck Systems Private Limited Chennai Nungambakkam India Network and Infrastructure Management Faculty of Engineering and Technology Botho University Gaborone Botswana School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India Department of Electronics and Communication Engineering Kumaraguru College of Technology Coimbatore India

For clinical analysis or medical intrusion, imaging technology is a potent tool for producing visual images of a body's inside. However, several existing methods include restricted access to high-quality and diverse datasets, overfitting, a lack of interpretability, high computational costs, varying medical imaging data, and ethical issues concerning patient privacy, consent, and bias. To overcome these issues, the effectiveness of generative adversarial networks in denoising medical imaging (CT/MRI images) is proposed. The input CT images are first gathered and preprocessed to reduce undesired noise using Altered Phase Preserving Dynamic Range Compression (APPDRC). The General Adversarial Network (GAN) is then given these preprocessed images to cope with the noisy areas of CT/MRI while also complying with maintaining image structures such as boundary details while preventing over-smoothing, and the weight parameters for the GAN are optimized using the Golden Eagle Optimization (GEO) technique. General Adversarial Network (GAN) has piqued the interest of academics studying medical image-denoising mechanisms and developing sophisticated medical image-denoising algorithms based on deep learning. In light of reducing the difficulty in feature learning and improving final diagnosis accuracy, data preprocessing is necessary and crucial in gan-based medical image denoising methods. This work focuses on GAN-based effective denoising approaches in CT/MRI. The potential challenges and research objectives are in the context of data preprocessing in medical image denoising. Because of how CT/MRI images are acquired, it was observed that noise in CT/MRI data follows the distribution. Generative Adversarial Networks (GANs) for denoising medical imaging, mainly CT and MRI images, have yielded promising results of 99% accuracy. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Generative adversarial networks

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Universality class of machine learning for critical phenomena

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science China(Physics,Mechanics & Astronomy) 2023年第12期66卷 63-70页

作者： Gaoke Hu Yu Sun Teng Liu Yongwen Zhang Maoxin Liu Jingfang Fan Wei Chen Xiaosong Chen School of Systems Science and Institute of Nonequilibrium Systems Beijing Normal UniversityBeijing 100875China Data Science Research Center Faculty of ScienceKunming University of Science and TechnologyKunming 650500China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning *** reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks(NNs),whereas phase transitions of different universality classes require different *** on this finding,we proposed the universality class of machine learning for critical ***,we investigated and discussed the NNs of different universality *** research contributes to machine learning by relating the NNs with the universality class.

关键词： universality class machine learning percolation

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Experimental Evaluation of WLAN-based Object Detection Using CSI in Outdoor and Large-scale Indoor Environments 100

Experimental Evaluation of WLAN-based Object Detection Using...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Shimizu, Shunsuke Muta, Osamu Murakami, Tomoki Otsuki, Shinya Otani, Ranae Kyushu University Graduate School of Information Science and Electrical Engineering Fukuoka Japan Kyushu University Faculty of Information Science and Electrical Engineering Fukuoka Japan Nit Corporation Access Network Service Systems Laboratories Japan

ISBN: (纸本)9798331517786

Recent studies have explored various object detection methods that use channel state information (CSI) in wireless local area networks (WLANs) such as IEEE 802.11ac. However, evaluations used with WLAN-based approaches by experimentation mainly target indoor object detection scenarios. Therefore, the effects of antenna placement of access points (AP) and stations (STA) on detection performance in outdoor environments have not been clarified. As described herein, by experimentation, we evaluate the performance of our developed WLAN-based object detection system with distributed antennas in outdoor and large-scale indoor scenarios. Then we clarify the effects of AP and STA placements on the achieved detection performance, where an off-the-shelf WLAN device is used to capture feedback CSI, including beamforming weight information. We leverage these data as feature information for machine learning (ML)-based object detection. Findings indicate that the object detection method can increase the detection probability effectively in specific locations by appropriate location of AP and STA, while reducing the necessary complexity for ML model training and detecting the target in outdoor and large-scale indoor scenarios. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

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When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system

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Green Energy and Intelligent Transportation 2024年第3期3卷 24-41页

作者： Malak Abid Ali Khan Hongbin Ma Arshad Farhad Asad Mujeeb Imran Khan Mirani Muhammad Hamza National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Computer Science Namal UniversityPakistan Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

LoRa technology contributes to green energy by enabling efficient,long-range communication for the Internet of Things(IoT).This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa,where the network performance is affected by the density of gateways(GWs)and end devices(EDs),as well as environmental *** mitigate interference,data throughput losses,and high-power consumption,the proposed spreading factor(SF)and hybrid(data rate|SF)models dynamically adjust the transmission *** orchestration of concurrent data modifications within the network server(NS)is crucial for uninterrupted communication between GWs and EDs,especially in monitoring electric vehicle(EV)stations to reduce traffic congestion and *** K-means and density-based spatial clustering of applications with noise(DBSCAN)algorithms optimizes ED allocation,averts data congestion,and improves the signal-tointerference noise ratio(SINR).These methods ensure seamless information reception by meticulously allocated EDs across various GW *** estimate the free-space losses(FSL),a log-distance path loss model(log-PL)is *** various bandwidths(BWs),bidirectional communications,and duty cycles(DCs)helps to prevent saturation,thus prolonging the operational lifespan of *** findings reveal a notable packet rejection rate(PRR)of 0%for the DBSCAN(hybrid model).In contrast,the K-means exhibits a PRR ranging from 5%(hybrid model)to 35.29%(SF model)for the ten GWs ***,the network saturation is reduced to 10.185%and 9.503%,respectively,highlighting an improvement in the average efficiency of slotted ALOHA(91.1%)and pure ALOHA(90.7%).These enhancements increase the lifespan of EDs to 15,465.27 days.

关键词： DBSCAN Green transportation Hybrid model Intelligent transportation K-means

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Whole Slide Image Annotation Support for Estimating Lesion Proportions 23

Whole Slide Image Annotation Support for Estimating Lesion P...

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23rd International Conference on Cyberworlds, CW 2024

作者： Takano, Nana Nishiguchi, Satoshi Toyoura, Masahiro Osaka Institute of Technology Graduate School of Information Science and Technology Osaka Japan Osaka Institute of Technology Faculty of Information Science and Technology Osaka Japan University of Yamanashi Department of Computer Science and Engineering Yamanashi Japan

ISBN: (纸本)9798331527174

The annotation of medical images for the purpose of segmentation demands a high level of expertise and experience, and the generation of suitable datasets represents a significant challenge. In this study, we propose a method that facilitates annotation on a whole slide image (WSI) without requiring detailed specification of the lesion area. The objective is to enable annotation without the need for specialised knowledge. In particular, the WSI is divided into smaller regions for annotation purposes, with the proportion of lesions in each region being compared with reference images of similar regions, for which the proportion of lesions is known. The proportion of lesions in the reference small region image deemed to be most analogous is then designated as the annotation. The outcomes of an annotation experiment on multiple subjects based on this approach indicated that as the level of experience of the annotator increased, the variability in the accuracy rate diminished. This suggests that the annotators had acquired knowledge and skills through the process of annotation. © 2024 IEEE.

关键词： Medical imaging

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Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning

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Big Data Mining and Analytics 2024年第2期7卷 294-314页

作者： Shahriar Kaisar Md Mamunur Rashid Abdullahi Chowdhury Sakib Shahriar Shafin Joarder Kamruzzaman Abebe Diro Department of Information Systems and Business Analytics RMIT UniversityMelbourne 3000Australia School of Engineering and Technology Central Queensland UniversityRockhampton 4700Australia Faculty of Engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide 5005Australia Centre for Smart Analytics Federation University AustraliaBallarat 3350Australia School of Accounting Information Systems and Supply ChainRMIT UniversityMelbourne 3000Australia

Telemarketing is a well-established marketing approach to offering products and services to prospective *** effectiveness of such an approach,however,is highly dependent on the selection of the appropriate consumer base,as reaching uninterested customers will induce annoyance and consume costly enterprise resources in vain while missing interested *** introduction of business intelligence and machine learning models can positively influence the decision-making process by predicting the potential customer base,and the existing literature in this direction shows promising ***,the selection of influential features and the construction of effective learning models for improved performance remain a ***,from the modelling perspective,the class imbalance nature of the training data,where samples with unsuccessful outcomes highly outnumber successful ones,further compounds the problem by creating biased and inaccurate ***,customer preferences are likely to change over time due to various reasons,and/or a fresh group of customers may be targeted for a new product or service,necessitating model retraining which is not addressed at all in existing works.A major challenge in model retraining is maintaining a balance between stability(retaining older knowledge)and plasticity(being receptive to new information).To address the above issues,this paper proposes an ensemble machine learning model with feature selection and oversampling techniques to identify potential customers more accurately.A novel online learning method is proposed for model retraining when new samples are available over *** newly introduced method equips the proposed approach to deal with dynamic data,leading to improved readiness of the proposed model for practical adoption,and is a highly useful addition to the *** experiments with real-world data show that the proposed approach achieves excellent results in all cases(e.g.,98.6

关键词： machine learning online learning oversampling telemarketing imbalanced dataset ensemble model

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A Doughnut Shaped Soft Gripper Based on 4D Printed Hydrogels

A Doughnut Shaped Soft Gripper Based on 4D Printed Hydrogels

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Qiu, Zhe Liu, Zaiyang Xue, Yitong Xie, Qinshang Chihara, Takuto Sakurai, Yuma Kobayashi, Tatsuya Honma, Tsubasa Furukawa, Hidemitsu Wang, Zhongkui Ritsumeikan University Research Organization of Science and Technology Japan Ritsumeikan University Graduate School of Science and Engineering Japan Yamagata University Department of Mechanical Systems Engineering Japan Ritsumeikan University Department of Robotics Japan

ISBN: (纸本)9798350372601

Soft grippers have recently been implemented to various applications due to their flexibility and compliance. They are conventionally actuated by electric and pneumatic systems. However, it is difficult to apply electric- and pneumatic-driven grippers to underwater applications thanks to the lack of waterproof ability. In this paper, we propose a doughnut shaped soft gripper based on four dimensional (4D) printing of hydrogels. The 4D printed hydrogels is capable of deforming when exposing to water stimuli. According to the property analysis of 4D printed hydrogels, such as deformation and force calibration, design parameters of the doughnut shaped gripper was determined. Underwater handling experiments were successfully conducted using the proposed soft gripper for grasping various objects with different shapes. © 2024 IEEE.

关键词： Pneumatics

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Additional verification of strength reduction factor related to opening height of RC shear walls and assurance DESIGN for predominant flexural yielding

Journal of Structural and Construction Engineering

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Journal of Structural and Construction engineering 2021年第780期86卷 267-277页

作者： Liu, Hong Sanada, Yasushi Yoon, Rokhyun Ichinose, Toshikatsu Izaki, Shu Kato, Koichi Kusuhara, Fumio Suzuki, Suguru Takahashi, Susumu Graduate School of Engineering Osaka University Faculty of Science and Technology Meijo University Graduate School of Engineering Nagoya Institute of Technology Faculty of Engineering Kochi University of Technology

Focusing on a strength reduction factor related to door openings provided in AIJ standards in 2010, a series of experimental studies was performed with multi-story shear wall specimens with different configurations of door openings. In this study, besides the former specimen with eccentricallyaligned door openings, two specimens were designed to fail between the door openings. The observed strengths of all specimens agreed well with the values predicted using the index proposed by the authors' previous study. Furthermore, a specimen with shear margin of 1.2 obtained using the proposed index was tested, and its effectiveness for the assurance design was verified. © 2021 Architectural Institute of Japan. All rights reserved.

关键词： Shear walls

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