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arXiv 2024年

作者： Yang, Zebo Alfauri, Haneen Farkiani, Behrooz Jain, Raj Di Pietro, Roberto Erbad, Aiman The Department of Computer Science and Engineering Washington University St. LouisMO63130 United States The Department of Electrical and Systems Engineering Washington University St. LouisMO63130 United States The Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia The College of Science and Engineering Hamad Bin Khalifa University Doha5825 Qatar

Blockchains have gained substantial attention from academia and industry for their ability to facilitate decentralized trust and communications. However, the rapid progress of quantum computing poses a significant threat to the security of existing blockchain technologies. Notably, the emergence of Shor’s and Grover’s algorithms raises concerns regarding the compromise of the cryptographic systems underlying blockchains. Consequently, it is essential to develop methods that reinforce blockchain technology against quantum attacks. In response to this challenge, two distinct approaches have been proposed. The first approach involves post-quantum blockchains, which aim to utilize classical cryptographic algorithms resilient to quantum attacks. The second approach explores quantum blockchains, which leverage the power of quantum computers and networks to rebuild the foundations of blockchains. This paper aims to provide a comprehensive overview and comparison of post-quantum and quantum blockchains while exploring open questions and remaining challenges in these domains. It offers an in-depth introduction, examines differences in blockchain structure, security, privacy, and other key factors, and concludes by discussing current research trends. © 2024, CC BY.

关键词： Quantum computers

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Advanced Multimodal Prediction of Components of Livestock Feed Materials Using Knowledge Distillation

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 272-285页

作者： Oluwabukunmi, Owoeye Babatunde Joseph, Akomolafe Ayobami Udurume, Miraculous Njoku, Judith Nkechinyere Nwakanma, Cosmas Ifeanyi Asem-Hiablie, Senorpe Mallipeddi, Rammohan Park, Tusan Uyeh, Daniel Dooyum Michigan State University Department of Biosystems and Agricultural Engineering East LansingMI48824 United States West Virginia University Department of Computer Science and Electrical Engineering MorgantownWV26505 United States Shell International Exploration and Production Inc. Shell Technology Center Biotechnology Department HoustonTX77082 United States Kyungpook National University Department of Artificial Intelligence Daegu41566 Korea Republic of Kyungpook National University Smart Agricultural Innovation Center Daegu41566 Korea Republic of Kyungpook National University Department of Applied Biosciences Daegu41566 Korea Republic of Kyungpook National University Department of Smart Bio-Industrial Mechanical Engineering Daegu41566 Korea Republic of

Accurate analysis of livestock feed quality is critical for enhancing productivity and supporting sustainable farming practices. This study explores the integration of red, green, and blue (RGB) and near-infrared (NIR) imaging modalities, leveraging their complementary strengths, RGB for physical properties and NIR for chemical compositions, to predict key nutritional metrics. A novel knowledge distillation model was developed to transfer insights from a complex teacher model to a simpler student model. The approach involved training three types of models: single-channel (RGB or NIR), double-channel (RGB and NIR), and knowledge distillation models. Key evaluation metrics, including mean squared error (MSE), mean absolute error, and root MSE, validated the model's predictive accuracy. Experimental results demonstrated that the knowledge distillation model significantly outperformed both single- and double-channel models, achieving a 91.86% reduction in the MSE compared to RGB single-channel models, an 89.68% reduction compared to NIR single-channel models, and a 63.43% improvement over double-channel models. This study provides a robust, efficient, and cost-effective solution for feed quality assessment, highlighting the transformative potential of multimodal imaging and machine learning in precision agriculture. © 2023 IEEE.

关键词： Agricultural robots

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Twenty-one days of bed rest alter motor unit properties and neuromuscular junction transmission in young adults

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Journal of Applied Physiology 2025年第6期138卷 1411-1424页

作者： Sarto, Fabio Kalc, Miloš Motanova, Evgeniia S. Franchi, Martino V. Stashuk, Daniel Murks, Nina Valli, Giacomo Negro, Samuele Prašnikar, Tomaž Gasparini, Mladen Martino, Giovanni De Vito, Giuseppe Holobar, Aleš Simunič, Boštjan Pišot, Rado Narici, Marco V. Department of Biomedical Sciences University of Padova Padova Italy Centre of Studies and Activities for Space "Giuseppe Colombo Padova Italy Science and Research Center Koper Institute for Kinesiology Research Koper Slovenia CIR-MYO Myology Center University of Padova Padova Italy Department of Systems Design Engineering University of Waterloo Waterloo ON Canada Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Department of Clinical and Experimental Sciences University of Brescia Brescia Italy Izola General Hospital Izola Slovenia

Previous studies showed that properties of higher-threshold motor units (MUs) and neuromuscular junction (NMJ) function are preserved during short-term disuse. This study aimed to test how a longer disuse period affects MU properties, NMJ transmission, and NMJ morphology remodeling. Nine young healthy males (age: 18-29 yr) underwent 21 days of horizontal bed rest. Pre- (BR0) and postbed rest (BR21), quadriceps maximal voluntary contraction (MVC), and size were assessed. We combined intramuscular electromyography (iEMG) and high-density surface electromyography (HDsEMG) recordings on the vastus lateralis to assess MU properties at 25% and 50% of MVC. Muscle biopsies and blood samples were also collected. Quadriceps MVC and size decreased at BR21. We found alterations in MU properties at both contraction intensities, including reduced discharge rate, MU potential area changes, and increased complexity. NMJ transmission was found to be reduced at BR21 at 25% MVC. This functional NMJ impairment was biochemically corroborated by an increase in serum C-terminal agrin fragment concentration, a biomarker of NMJ instability. In addition, a direct assessment of NMJ morphology revealed the presence of some denervated NMJs exclusively at BR21. In conclusion, 21-day bed rest altered MU properties across different contraction intensities and impaired NMJ transmission with initial signs of remodeling/denervation. Disuse duration appears to be a critical factor, as previous shorter studies failed to detect some of these changes. We believe these findings are clinically relevant for disuse after trauma, surgery, or illness and may support the development of effective *** & NOTEWORTHY Leveraging both intramuscular and high-density surface EMG recordings in the vastus lateralis, we identified alterations in motor unit (MU) properties in young adults after 21 days of bed rest. These included reduced discharge rates and changes in MU potential size and complexity, observ

关键词： disuse electromyography electrophysiology physical inactivity unloading

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Characterization of GNRFET Devices for Applications towards 5G Communication 3

Characterization of GNRFET Devices for Applications towards ...

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3rd IEEE International Conference on Design and Test of Integrated Micro and Nano-systems, DTS 2021

作者： Rahmani, Maryam Patnala, Mounica Ytterdal, Trond Rizkalla, Maher Indiana University Purdue University Indianapolis Electrical and Computer Engineering IN United States Department of Electronics Systems Norway

ISBN: (纸本)9780738132631

The fifth generation (5G) wireless technology will provide the nation's future telecommunications network, featuring higher bandwidth and data rates with lower delay and power consumption. This shift facilitates the ultra-level of integration, for systems loaded with embedded sensors that are enabled by this technology. A few challenges remain regarding the standards to proper interfacing, security for cellular based services, and ability of portable devices to be employed in this technology. These challenges include high-speed amplifiers and signal processors. Millimeter wave communications with frequencies above 10 GHz for mobile networks may be required to meet the propagation quality demands of this technology. This paper proposes the Graphene Nano Ribbon Field Effect Transistor (GNRFET) device as a potential candidate that fits well in this technology, featuring high frequency amplifiers and high switching speed in digital circuits with ultra-low power consumption. These advantages may be attributed to the high mobility and mean free path of the device, leading to major ballistic carrier transport. The simulation was conducted at a switching speed in the order of 10GHz and 0.7V supply. The device was also employed for high frequency amplifiers, achieving as much as 5.1 THz gain bandwidth product (70GHz at a gain of 75), with very clean output signals. Near 115 dBs attenuation losses for harmonics was determined within the operating bandwidth. This paper details the device model, circuit design, and power consumption, suitable for the 5-G communication system. The nanoscale size of the device provides the ultra-level of integration, incorporating the embedded and IoT devices supporting this technology. © 2021 IEEE.

关键词： Bandwidth

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A Taxonomy of Defenses against Memory Corruption Attacks 44

A Taxonomy of Defenses against Memory Corruption Attacks

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44th International Convention on Information, Communication and Electronic Technology, MIPRO 2021

作者： Novkovic, Bojan University of Zagreb Faculty of Electrical Engineering and Computing Department of Electronics Microelectronics Computer and Intelligent Systems Zagreb Croatia

ISBN: (纸本)9789532331011

Vulnerabilities caused by memory corruption related bugs are a pervasive threat, continually undermining the security of the whole computing environment. The lack of memory safety mechanisms in indispensable systems programming languages like C or C++ leaves plenty of room for programmer-induced errors which often result in catastrophic security breaches. We analyze the root causes of these vulnerabilities, providing a concise overview of memory corruption bugs and related attacks. Although present in a number of programming languages, we use the C/C++ programming language as a basis for our analyses. We categorize existing defensive mechanisms based on the attack techniques they focused on preventing and give a brief insight into state-of-the-art defenses introduced throughout the years, with a special focus on operating system defenses. © 2021 Croatian Society MIPRO.

关键词： C++ (programming language)

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Technologies Applied to Solve Facility Layout Problems with Resilience – A Systematic Review 1

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3rd International Conference on Applied Technologies, ICAT 2021

作者： Vázquez, Jorge Llivisaca, Juan Carlos Ortiz, Daisy Naranjo, Israel Siguenza-Guzman, Lorena Department of Computer Sciences Faculty of Engineering University of Cuenca Cuenca Ecuador Department of Applied Chemistry and Production Systems Faculty of Chemical Sciences University of Cuenca Cuenca Ecuador Faculty of Systems Electronics and Industrial Engineering Technical University of Ambato Ambato Ecuador Research Centre Accountancy Faculty of Economics and Business KU Leuven Leuven Belgium

ISBN: (数字)9783031038846

ISBN: (纸本)9783031038839

In the industry, the need to optimize daily tasks became mainly a requirement to stay competitive. The Facility Layout Problem (FLP) arises from this need and is the most used technique to improved manufacturing processes. Over the years, the distribution of the different facilities became more complex and more susceptible to interventions in their usual workflow. Hence, FLPs emerged to solve these interventions. This capacity to solve various problems is known as resilience. By searching the literature for information on technologies used to solve FLP, many software solutions can be obtained. Still, none of them manage resilience as a factor in the solution. They have also not been compiled in an analysis to determine the most modern options for existing solutions. The current study reviews the most widely used software tools that solve FLP and how these studies view resilience. A systematic literature review was applied to select relevant studies from 2015–2021. This work allowed analyzing a final sample of 133 articles obtained in two different search strings. As a result, this study identified two manners to solve FLP with software tools: using already developed tools and developing an own tool. In the former, three proprietary software were identified: MATLAB, CPLEX, and LINGO. When developing their software tool, the technology used varies significantly between studies. They use very different language programming, depending on the researcher’s domain. Furthermore, the results do not find any case in which some resilience factor was part of the solution obtained. © 2022, Springer Nature Switzerland AG.

关键词： MATLAB

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Precision Oral Medicine: A DPR Segmentation and Transfer Learning Approach for Detecting Third Molar Compress Inferior Alveolar Nerve

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IEEE Journal of Translational engineering in Health and Medicine 2025年 13卷 286-298页

作者： Lin, Yuan-Jin Chen, Shih-Lun Mao, Yi-Cheng Chen, Tsung-Yi Peng, Cheng-Hao Tsai, Tzu-Hsiang Li, Kuo-Chen Chen, Chiung-An Tu, Wei-Chen Abu, Patricia Angela R. National Cheng Kung University Department of Program on Semiconductor Manufacturing Technology Academy of Innovative Semiconductor and Sustainable Manufacturing Tainan City701401 Taiwan Chung Yuan Christian University Department of Electronic Engineering Taoyuan City32023 Taiwan Taoyuan Chang Gang Memorial Hospital Department of Operative Dentistry Taoyuan City33305 Taiwan Feng Chia University Department of Electronic Engineering Taichung city40724 Taiwan Chung Yuan Christian University Taoyuan City32023 Taiwan Chung Yuan Christian University Department of Information Management Taoyuan City32023 Taiwan Ming Chi University of Technology Department of Electronic Engineering New Taipei City243303 Taiwan National Cheng Kung University Department of Electrical Engineering Tainan city701401 Taiwan Ateneo de Manila University Department of Information Systems and Computer Science Quezon City Philippines

Objective: Extraction of the third molar of the mandible is one of the most common oral surgical procedures. Preoperative monitoring and assessment are crucial to mitigate neurological risks. Identifying whether the third molar in the mandible compresses the inferior alveolar nerve still relies on dental professionals, a task that is repetitive and time-consuming. Thus, the primary objective is to utilize dental panoramic radiography for image processing and classify whether the third molar compresses the inferior alveolar nerve, aiming to reduce the demand for CT images in symptom diagnosis and mitigate the risks associated with high-dose radiation. Technology or Method: This study proposes an innovative dental panoramic radiography segmentation technique to locate the third molar position. Subsequently, an innovative edge masking enhancement method is used to extract features of the inferior alveolar nerve and the third molar. Moreover, a transformer-based image detection model to consider whether the third molar compresses the inferior alveolar nerve. Results: The third molar position localization method achieved an accuracy rate of 97.92%, compared to recent research at least improved by 3.6% accuracy. Subsequently, innovative edge masking and image enhancement methods improve classification accuracy by 4.3%, when supplemented with computed tomography scan images for further evaluation, the maximum accuracy reached 98.45%, representing a 4.5% improvement compared to previous studies. Conclusions: The third molar position detection results will impact the identification of the inferior alveolar nerve compressed by the third molar. Through the innovative edge region segmentation algorithm can effectively distinguish this object, and the overall evaluation accuracy can be improved by approximately 3.8%. © 2013 IEEE.

关键词： Neurophysiology

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Convergence of energy-based learning in linear resistive networks

arXiv

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arXiv 2025年

作者： Huijzer, Anne-Men Chaffey, Thomas Besselink, Bart van Waarde, Henk J. Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands CogniGron - Groningen Cognitive Systems and Materials Center Netherlands Control Group Department of Engineering University of Cambridge United Kingdom School of Electrical and Computer Engineering University of Sydney Australia

Energy-based learning algorithms are alternatives to backpropagation and are well-suited to distributed implementations in analog electronic devices. However, a rigorous theory of convergence is lacking. We make a first step in this direction by analysing a particular energy-based learning algorithm, Contrastive Learning, applied to a network of linear adjustable resistors. It is shown that, in this setup, Contrastive Learning is equivalent to projected gradient descent on a convex function, for any step size, giving a guarantee of convergence for the *** Codes 65K10, 68T05, 93B30, 93D99 © 2025, CC BY-SA.

关键词： Contrastive Learning

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Additive manufacturing of a Co-Cr-W alloy by selective laser melting:In-situ oxidation,precipitation and the corresponding strengthening effects

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Journal of Materials Science & Technology 2022年第30期125卷 171-181页

作者： Kefeng Li Zhi Wang Kaikai Song Khashayar Khanlari Xu-Sheng Yang Qi Shi Xin Liu Xinhua Mao Institute of New Materials Guangdong Academy of SciencesGuangzhou 510650China National Engineering Research Center of Powder Metallurgy of Titanium and Rare Metals Guangzhou 510650China Guangdong Key Laboratory for Advanced Metallic Materials Processing South China University of TechnologyGuangzhou 510641China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China Advanced Manufacturing Technology Research Center Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen 518000China

Additive manufacturing exhibits great potentials for the fabrication of novel materials due to its unique non-equilibrium solidification and heating *** this work,a novel nano-oxides dispersion strengthened Co28 Cr9 W1.5 Si(wt.%)alloy,fabricated by laser powder bed fusion(LPBF),was comprehensively *** the layer-by-layer featured process,in-situ formation of Si rich,amorphous,nano-oxide inclusions was observed,whose formation is ascribed to the high affinity of Si to ***,distinctive body-centered cubic(BCC)Co5 Cr3 Si2 nano-precipitates with an 8-fold symmetry were also confirmed to *** precipitates,rarely reported in previous studied Co-Cr alloys,were found to tightly bond with the in-situ ***,the morphologies,the size distributions as well as the microstructure of the interface between the matrix and the inclusions were investigated in detail and their influence on the tensile deformation was also *** existence of transition boundaries between these inclusions and the matrix strongly blocked the movement of dislocations,thereby increasing the strength of the *** was understood that when the plastic deformation proceeds,the fracture occurs in the vicinity of the oxide inclusions where dislocations accumulate.A quantitative analysis of the strengthening mechanism was also established,in which an additional important contribution to strength(~169 MPa)caused by the effects of in-situ formed oxide inclusions was calculated.

关键词： Co-Cr-W-Si alloy Selective laser melting Oxide inclusion Precipitation Strengthening mechanisms

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Sailfish: A Dependency-Aware and Resource Efficient Scheduling for Low Latency in Clouds

Sailfish: A Dependency-Aware and Resource Efficient Scheduli...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Liu, Jinwei Lao, Yingjie Mao, Ying Buyya, Rajkumar Florida A and M University Department of Computer and Information Sciences TallahasseeFL32307 United States Clemson University Department of Electrical and Computer Engineering ClemsonSC29634 United States Fordham University Department of Computer and Information Science BronxNY10458 United States The University of Melbourne School of Computing and Information Systems ParkvilleVIC3010 Australia

ISBN: (纸本)9798350324457

Efficiently scheduling jobs in clouds is critical for job performance, system throughput and resource utilization. The growing importance of parallel applications in clouds introduces challenges in scheduling data-parallel jobs. Production data-parallel jobs increasingly have complex dependency structure, i.e., complex task dependencies expressed as directed acyclic graphs (DAGs), and heterogeneous resource demands. NP-hard problems are introduced by relaxing either of these challenges (i.e., scheduling of homogeneous tasks with dependency constraints or independent and heterogeneous tasks) for scheduler design. It is challenging to design a scheduler for simultaneously achieving low latency and high resource utilization due to the complex dependency structure and job heterogeneity. In this paper, we propose Sailfish, a dependency-aware and resource efficient scheduling for low latency in clouds. Sailfish first uses the machine learning algorithm to classify jobs into two categories (high priority jobs and low priority jobs) based on the extracted features. Next, Sailfish splits the jobs into tasks and distributes the tasks to the master nodes based on the dependency of tasks and the load of master nodes. Then, Sailfish utilizes the dependency information of tasks to determine tasks' priority, and packs tasks by leveraging the complementary of tasks' requirements on different resource types and task dependency. Finally, the master nodes leverage the proposed mutual reinforcement algorithm to distribute tasks to workers in the system based on the resource demands of tasks, the available resources of workers and task dependency. Extensive experimental results based on a real cluster and experiments using real-world Amazon EC2 cloud service show that Sailfish can improve the average resource utilization (by up to 40%) and reduce the latency (the average job completion time) significantly (by up to 91%) compared to the existing schedulers. © 2023 IEEE.

关键词： heterogeneity latency resource utilization scheduling task dependency

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