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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Xiao, Zian Ren, Zhihao Zhuge, Yangyang Zhang, Zixuan Zhou, Jingkai Xu, Siyu Xu, Cheng Dong, Bowei Lee, Chengkuo Agency for Science Technology and Research Singapore National University of Singapore Department of Electrical & Computer Engineering Singapore Singapore National Centre for Advanced Integrated Photonics S2-B3-01 50 Nanyang Avenue Singapore

ISBN: (纸本)9798331508890

Photonic integrated circuits provide compact and efficient solutions for multimodal spectroscopic sensors. However, the resulting sensory data is highly complex and contains significant redundancy. To circumvent high communication cost for redundancy, the photonic sensor and processor are brought into intimacy and propose a photonic multimodal edge computing system. A microring resonator crossbar is used as photonic processor with 5-bit accuracy. The in-situ processing of sensory data is demonstrated in this system, achieving a classification accuracy of 94.27% across 45 different classes. The multimodal edge computing system demonstrates the feasibility of integrating photonic processors and photonic sensors to enhance the photonic data processing capability. © 2025 IEEE.

关键词： In situ processing

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SLSNet: Weakly-Supervised Skin Lesion Segmentation Network with Self-attentions 20th

SLSNet: Weakly-Supervised Skin Lesion Segmentation Network w...

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20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Pei, Songwen Huang, Junjie School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education East China Normal University Shanghai200062 China

ISBN: (纸本)9789819970247

computer-aided skin lesion segmentation with high precision is crucial to diagnose skin cancers in the early stage. However, the lack of pixel-level labels makes the skin lesion segmentation tasks challenging. To tackle this problem, a new weakly-supervised skin lesion segmentation network with self-attentions named SLSNet is proposed. SLSNet contains two modules and uses image-level labels as supervision information. One module named Intra-image Self-attention Seed Expansion (ISE) digs intra-image self-attentions with an expansion loss and a confidence loss to expand seed areas. The other module named Inter-image Affinity-based Noise Suppression (IAS) suppresses the noise pixels in attention maps via inter-image correlations. Extensive experiments conducted on ISIC-2017 dataset show that SLSNet achieves relatively high performance while reducing human labeling efforts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Expansion

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Cybertwin-Assisted Mode Selection in Ultra-Dense LEO Integrated Satellite-Terrestrial Network

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Journal of Communications and Information Networks 2022年第4期7卷 360-374页

作者： Xin Zhang Bo Qian Xiaohan Qin Ting Ma Jiachen Chen Haibo Zhou Xuemin(Sherman)Shen School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China Laboratory Shenzhen 518000China Department of Electrical and Computer Engineering University of WaterlooWaterlooON N2L 3G1Canada

Ultra-dense low earth orbit(LEO)integrated satellite-terrestrial network(ULISTN)has become an emerging paradigm to support massive access of Internet of things(IoT)in beyond fifth generation mobile networks(B5G).In ULISTN,there are two communication modes:cellular mode and satellite mode,where IoT users assessing terrestrial small base stations(TSBSs)and terrestrial-satellite terminals(TSTs)***,how to optimize the network performance and guarantee self-interests of the operator and IoT users in ULISTN is a challenging *** this paper,we propose a cybertwin-assisted joint mode selection and dynamic pricing(JMSDP)scheme for effective network management in ULISTN,where cybertwin serves as the intelligent *** JMSDP,the operator determines optimal access prices of TSBSs and TSTs,while each user selects the access mode according to access ***,the operator conducts the Stackelberg game aiming at maximizing average throughput depending on the mode selection results of IoT ***,IoT users as followers adopt the evolutionary game to choose an access mode based on the access prices provided by the *** results show that the proposed JMSDP can improve the average throughput and reduce the delay effectively,comparing with random access(RA)and maximum rate access.

关键词： ULISTN massive IoT cybertwin mode selection dynamic pricing game theory

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Fortifying Strong PUFs: A Modeling Attack-Resilient Approach Using Weak PUF for IoT Device Security

Fortifying Strong PUFs: A Modeling Attack-Resilient Approach...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Sara Alahmadi Kasem Khalil Haytham Idriss Magdy Bayoumi Center of Advanced Computer Studies University of Louisiana at Lafayette USA Department of Electrical and Computer Engineering University of Mississippi USA Computer Science Department Purdue University Fort Wayne USA Department of Electrical and Computer Engineering University of Louisiana at Lafayette USA

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Strong Physical Unclonable Functions (PUFs) have gained traction as lightweight authentication solutions for IoT devices. However, their vulnerability to machine learning attacks poses a security risk. Various strategies have been introduced in the literature to enhance its resilience against modeling attacks, introducing additional complexity and making them unsuitable for resource-constrained devices. In contrast, weak PUFs exhibit inherent resistance to modeling attacks, but they suffer from a restricted number of Challenge-Response Pairs (CRPs), thus unsuitable for authentication. This paper proposes a PUF design that incorporates weak PUFs to obscure the responses of Strong PUFs, effectively safeguarding them from modeling attacks. Our design shows resilience against a modeling attack, revealing a maximum accuracy of 57% despite using 10 7 CRPs. The proposed method is implemented on the Artix-7 FPGA with Verilog HDL. The results demonstrate that the proposed method has a small footprint in terms of resource utilization. This innovative approach offers a lightweight solution for IoT device authentication, combining the strengths of strong and weak PUFs while mitigating the vulnerabilities associated with modeling attacks.

关键词： Resistance Authentication Machine learning Physical unclonable function Security Internet of Things Hardware design languages

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computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Liang, Tailin Yuan, Zhaolin School of Computer Science and Engineering Beihang University State Key Laboratory of Software Development Environment Beijing China Research Institute of Advanced Manufacturing Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350378658

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications. © 2024 IEEE.

关键词： Radiation hazards

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Harnessing the power of functionalized biochar:progress,challenges,and future perspectives in energy,water treatment,and environmental sustainability

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Biochar 2024年第1期6卷 407-486页

作者： Muhammad Zubair Yameen Salman Raza Naqvi Dagmar Juchelková Muhammad Nouman Aslam Khan Laboratory of Alternative Fuels and Sustainability School of Chemical and Materials Engineering(SCME)National University of Sciences and Technology(NUST)Sector H-12Islamabad 44000Pakistan. Department of Electronics Faculty of Electrical Engineering and Computer ScienceVŠB-Technical University of Ostrava17.Listopadu 2172/1570800 OstravaPorubaCzech Republic. Department of Engineering and Chemical Sciences Karlstad UniversityKarlstadSweden.

The swift advancement of sustainable energy technologies,coupled with the urgent need to address environmental challenges,has generated considerable interest in the multifaceted applications of biochar materials to promote energy,water,and environmental *** comprehensive review examines recent advancements in the production and applications of functionalized biochar materials,emphasizing their pivotal roles in energy conversion and storage,wastewater treatment,CO_(2)reduction,soil amelioration,and the promotion of carbon neutrality within a circular economy *** functionalization of biochar materials involves surface chemistry and porosity modifications,achieved through techniques like templating,chemical activation,metal impregnation,or heteroatom *** modifications substantially enhance the catalytic activity,energy storage capacity,and cycling stability of biochar materials,making them particularly effective in diverse energy applications such as water splitting,fuel cells,and ***,functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment,proficiently removing pollutants like heavy metals,organic contaminants,and nutrients,thereby facilitating resource recovery from *** review also underscores the potential of functionalized biochar materials in CO_(2)capture and conversion,exploring innovative strategies to augment their CO_(2)adsorption capacity and state-of-the-art catalytic processes for transforming captured CO_(2)into valuable fuels and *** summary,this review offers valuable insights into the recent advancements in biochar research,underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.

关键词： Engineered biochar Sustainable energy technologies Wastewater treatment Carbon reduction Circular economy

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Cryptanalysis of DBST, a lightweight block cipher

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Frontiers of computer science 2024年第4期18卷 219-221页

作者： Sadegh SADEGHI Nasour BAGHERI Department of Mathematics Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Research Center for Basic Sciences and Modern Technologies(RBST) Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Electrical Engineering Department Shahid Rajaee Teacher Training UniversityTehran 16788-15811Iran School of Computer Science(SCS) Institute for Research in Fundamental Sciences(IPM)Tehran 19395-5531Iran

1 Introduction Conventional cryptographic primitives are not suitable for resource-constrained ***,numerous lightweight primitives have been proposed over the past decade,specifically tailored for such ***,such ciphers would not be used in a real-world application unless they were thoroughly tested for security against existing *** this direction,DBST[1]cipher has been recently proposed by Yan et *** balance security,cost,and efficiency,DBST has implemented a novel 4-branch generalized Feistel variant *** this structure,a 2-branch XOR operation has been incorporated in the middle section,establishing interconnections between all *** the other hand,by leveraging the bit-slice technique and subkeys,the algorithm introduces an innovative approach to constructing a dynamic S-box *** designers of DBST cipher have extensively investigated its resistance to known attacks such as linear and differential cryptanalysis,as well as impossible differential cryptanalysis,among *** them,the objective of differential cryptanalysis[2]is to identify high-probability characteristics in the plaintext that are transmitted to the ciphertext,known as distinguishers.

关键词： structure. primitive branch

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Recent Advances in Trustworthy Explainable Artificial Intelligence: Status, Challenges, and Perspectives

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第6期3卷 852-866页

作者： Rawal, Atul McCoy, James Rawat, Danda B. Sadler, Brian M. Amant, Robert St. Howard University Department of Electrical Engineering and Computer Science WashingtonDC20059 United States U.S. Army Research Laboratory AdelphiMD20783 United States

Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier days of conceptual theories, to being an integral part of today's technological society. Rapid growth of AI/ML and their penetration within a plethora of civilian and military applications, while successful, has also opened new challenges and obstacles. With almost no human involvement required for some of the new decision-making AI/ML systems, there is now a pressing need to gain better insights into how these decisions are made. This has given rise to a new field of AI research, explainable AI (XAI). In this article, we present a survey of XAI characteristics and properties. We provide an indepth review of XAI themes, and describe the different methods for designing and developing XAI systems, both during and post model-development. We include a detailed taxonomy of XAI goals, methods, and evaluation, and sketch the major milestones in XAI research. An overview of XAI for security and cybersecurity of XAI systems is also provided. Open challenges are delineated, and measures for evaluating XAI system robustness are described. © 2020 IEEE.

关键词： Machine learning

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Corrugated Silicon Nitride Masks with Enhanced Mechanical Strength for Patterning RGB-Stripe OLED Microdisplays

Corrugated Silicon Nitride Masks with Enhanced Mechanical St...

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International Symposium, Seminar, and Exhibition, Display Week 2024

作者： Dong, Shou-Cheng Yang, Jiye Ting Tam, Bryan Siu Tang, Ching W. State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Institute for Advanced Study The Hong Kong University of Science and Technology Hong Kong Co. Ltd Suzhou China Department of Chemical Engineering University of Rochester RochesterNY United States

Corrugated silicon nitride masks (SiNMs) with improved mechanical strength are developed for patterning OLED microdisplays. The corrugations in the nitride membrane significantly increase the rigidity of the mask and reduce sagging, enabling 3000-ppi slot apertures for patterning RGB-stripe pixel layouts that are normally not achievable by fine metal masks. © 2024, John Wiley and Sons Inc. All rights reserved.

关键词： Silicon nitride

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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