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Industrial Chemistry & Materials 2024年第3期2卷 378-392页

作者： Zachary Applebee Caitlin Howell Department of Chemical and Biomedical Engineering Maine College of Engineering and ComputingUniversity of MaineME 04469USA Graduate School of Biomedical Science and Engineering University of MaineME 04469USA

Antifouling liquid-infused surfaces have generated interest in multiple fields due to their diverse applications in industry and *** nearly all reports to date,the liquid component consists of only one chemical ***,unlike traditional solid surfaces,the unique nature of liquid surfaces holds the potential for synergistic and even adaptive functionality simply by including additional elements in the liquid *** this work,we explore the concept of multi-component liquid-infused systems,in which the coating liquid consists of a primary liquid and a secondary component or components that provide additional *** ease of understanding,we categorize recently reported multi-component liquid-infused surfaces according to the size of the secondary components:molecular scale,in which the secondary components are molecules;nanoscale,in which they are nanoparticles or their equivalent;and microscale,in which the additional components are micrometer size or *** present examples at each scale,showing how introducing a secondary element into the liquid can result in synergistic effects,such as maintaining a pristine surface while actively modifying the surrounding environment,which are difficult to achieve in other surface *** review highlights the diversity of fabrication methods and provides perspectives on future research *** secondary components into the liquid matrix of liquid-infused surfaces is a promising strategy with significant potential to create a new class of multifunctional materials.

关键词： Active surfaces Antimicrobial Antifouling Interfaces Sensing surfaces

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253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 Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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Delay-CJ:A novel cryptojacking covert attack method based on delayed strategy and its detection

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Digital Communications and Networks 2023年第5期9卷 1169-1179页

作者： Guangquan Xu Wenyu Dong Jun Xing Wenqing Lei Jian Liu Lixiao Gong Meiqi Feng Xi Zheng Shaoying Liu Big Data School Qingdao Huanghai UniversityQingdao266427China College of Intelligence and Computing Tianjin UniversityTianjin300350China School of Computing Macquarie UniversityNSW2109Australia Graduate School of Advanced Science and Engineering Hiroshima UniversityJapan

Cryptojacking is a type of resource embezzlement attack,wherein an attacker secretly executes the cryptocurrency mining program in the target host to gain *** has been common since 2017,and in fact,it once became the greatest threat to network *** better prove the attack ability the harm caused by cryptojacking,this paper proposes a new covert browser-based mining attack model named Delay-CJ,this model was deployed in a simulation environment for *** on the general framework of cryptojacking,Delay-CJ adds hybrid evasion detection techniques and applies the delayed execution strategy specifically for video websites in the prototype *** results show that the existing detection methods used for testing may become invalid as result of this *** view of this situation,to achieve a more general and robust detection scheme,we built a cryptojacking detection system named CJDetector,which is based on cryptojacking process ***,it identifies malicious mining by monitoring CPU usage and analyzing the function call *** system not only effectively detects the attack in our example but also has universal *** recognition accuracy of CJDetector reaches 99.33%.Finally,we tested the web pages in Alexa 50K websites to investigate cryptojacking activity in the real *** found that although cryptojacking is indeed on the decline,it remains a part of network security threats that cannot be ignored.

关键词： Cryptojacking Evasion techniques Delayed strategy Cryptocurrency mining Behavior-based detection

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Dynamic Sampling-Based Meta-Learning Using Multilingual Acoustic Data for Under-Resourced Speech Recognition

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IEEE Access 2024年 12卷 106070-106083页

作者： Hsieh, I-Ting Wu, Chung-Hsien Zhao, Zhe-Hong National Cheng Kung University Graduate Program of Multimedia Systems and Intelligent Computing Tainan70101 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan

Under-resourced automatic speech recognition (ASR) has become an active field of research and has experienced significant progress during the past decade. However, the performance of under-resourced ASR trained by existing methods is still far inferior to high-resourced ASR for practical applications. In this paper, speech data from languages that share the most phonemes with the under-resourced language are selected as supplementary resources for meta-training based on the Model-Agnostic Meta-Learning (MAML) strategy. Besides supplementary language selection, this paper proposes a dynamic sampling method instead of the original random sampling method to select support and query sets for each task in MAML to improve meta-training performance. In this study, Taiwanese is selected as the under-resourced language, and the speech corpus of five languages, including Mandarin, English, Japanese, Cantonese, and Thai, are chosen as supplementary training data for acoustic model training. The proposed dynamic sampling approach uses phonemes, pronunciation, and speech recognition models as the basis to determine the proportion of each supplementary language to select helpful utterances for MAML. For evaluation, with the selected utterances from each supplementary language for meta-training, we obtained a Word Error Rate of 20.24% and a Syllable Error Rate of 8.35% for Taiwanese ASR, which were better than the baseline model (26.18% and 13.99%) using only the Taiwanese corpus and other methods. © 2013 IEEE.

关键词： Speech recognition

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Multimodal attention-driven visual question answering for Malayalam

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Neural computing and Applications 2024年第24期36卷 14691-14708页

作者： Kovath, Abhishek Gopinath Nayyar, Anand Sikha, O.K. Department of Computer Science and Engineering Amrita School of Computing Coimbatore Amrita Vishwa Vidyapeetham Coimbatore India Graduate School Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

Visual question answering is a challenging task that necessitates for sophisticated reasoning over the visual elements to provide an accurate answer to a question. Majority of the state-of-the-art VQA models are only applicable to English questions. However, applications such as visual assistance and tourism necessitate the incorporation of multilingual VQA systems. This paper presents an effective deep learning framework for Malayalam visual question answering (MVQA), which can answer a specific natural language question about an image in Malayalam. As there is no available dataset in English–Malayalam VQA, a MVQA dataset was created by translating English question–answer pairs from the visual genome dataset. The paper proposes an attention-driven MVQA model on the developed dataset. The proposed MVQA model uses a deep learning-based co-attention mechanism to jointly learn the attention for images and Malayalam questions. A second-order multimodal factorized high-order pooling is used for multi modal feature fusion. Different VQA models using combinations of classical CNNs and RNNs were experimented on the developed MVQA dataset, and the performance was compared against the proposed attention-driven model. Experimental results show that the proposed attention-driven MVQA model achieves state-of-the-art results as compared to other models for MVQA on the custom Malayalam VQA dataset. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Deep learning

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A Quantum Q-Learning Model for the Capacitated Vehicle Routing Problem 17

A Quantum Q-Learning Model for the Capacitated Vehicle Routi...

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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Xu, Jiahua Xie, Ningyi Lee, Xinwei Saito, Yoshiyuki Asai, Nobuyoshi Cai, Dongsheng University of Tsukuba Graduate School of Science and Technology Japan Singapore Management University School of Computing and Information Systems Singapore University of Aizu Graduate School of Computer Science and Engineering Japan University of Aizu School of Computer Science and Engineering Japan University of Tsukuba Faculty of Engineering Information and Systems Japan

ISBN: (纸本)9798331530471

The research on Variational Quantum Algorithms (VQAs) has gained significant momentum because of their promising practicality in the noisy intermediate-scale quantum (NISQ) era. Recent studies highlight the potential of VQAs in reinforcement learning (RL) by replacing classical components with parameterized quantum circuits (PQCs). Building on this, we propose a quantum Q-learning model for the Capacitated Vehicle Routing Problem (CVRP), combining a PQC with an RL training process. We present a PQC for embedding both static and dynamic states in RL environments. The proposed PQC approximates the Q-value function by using the expectation values of different observables. Experimental results demonstrate that the proposed PQC outperforms the existing PQC for the CVRP with fewer quantum resources. Furthermore, our method shows competitive performance compared to the classical counterpart. © 2024 IEEE.

关键词： Vehicle routing

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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

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IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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Spatial Calibration of Airborne Ultrasonic Phased Arrays with Two-Dimensional Visualization of Ultrasound Emissions

Spatial Calibration of Airborne Ultrasonic Phased Arrays wit...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Nakagawa, Masato Hasegawa, Keisuke The University of Tokyo Graduate School of Information Science and Technology Department of Information Physics and Computing Tokyo Japan Saitama University Graduate School of Science and Engineering Department of Mechanical Science Saitama Japan

ISBN: (纸本)9798350346459

In order to expand the applications of electronically controllable intense mid-air ultrasonic fields generated with airborne ultrasonic phased arrays (AUPA), a precise spatial calibration method between multiple AUPAs is in great demand. However, the conventional methods, such as manual fine-tuning and acoustic beam scanning, take a long time to complete. Here, we propose a quicker calibration method using thermal imaging. By placing an acoustically translucent screen in the AUPAs' sound field containing narrow and straight sound beams, acoustic energy in the field is converted into a two-dimensional heat map. By shooting several images with a thermal camera changing the beam position, information about the relative spatial information between the screen and the AUPAs is promptly visualized. We developed the algorithm to estimate the postures of AUPAs from the obtained image. We conducted a preliminary experiment about thermal imaging and a numerical simulation of the AUPA posture estimation algorithm and verified the effectiveness of our proposed method. © 2023 IEEE.

关键词： Calibration

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Numerical Verification of Generation of Ultrasound-Driven Bent Flow by Centripetal and Tangential Body Force Field

Numerical Verification of Generation of Ultrasound-Driven Be...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Matsuuchi, Kenta Hasegawa, Keisuke The University of Tokyo Graduate School of Information Science and Technology Department of Information Physics and Computing Tokyo Japan Saitama University Graduate School of Science and Engineering Department of Mechanical Science Saitama Japan

ISBN: (纸本)9798350346459

We propose a method of generating midair acoustic streaming traveling along a curve by combining a central acceleration field with a tangential one by ultrasound emissions from multiple phased arrays of ultrasound transducers. Via numerical experiments, we confirmed, using a hypothetical acceleration field, that a centripetal force contributed to the steady formation of a narrow curved flow. We also demonstrated that a curved flow (0.4 m radius semicircle) could be generated by the phased arrays emitting both centripetal and tangential acceleration field in their possible arrangements, both numerically and experimentally. Half of the arrays generated tangential force field parallel to the given beam trajectory and the others generated centripetal force field that penetrated the center of the array. Although currently generated flows being short in spatial range, such curved flows can potentially increase the spatial flexibility of applications, by circumventing obstacles in the environment, for example. © 2023 IEEE.

关键词： Ultrasonic transducers

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Predefined-Time Sliding Mode Control with Prescribed Convergent Region

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 934-936页

作者： Ke Shao Jinchuan Zheng Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVIC 3122Australia IEEE

Dear editor,K1 In recent years,the finite-time and fixed-time control techniques have drawn much *** letter will present a new method for designing a predefined-time adaptive sliding mode controller with prescribed convergent *** specifically,class function is used to construct the sliding function,and to achieve a real sliding mode,the function is also adopted in designing the adaptive gain without knowing the disturbance’s upper bound(DUB).Compared to the existing finite-time and fixed-time controllers,the key superiority of the proposed method is that the system can converge to a prescribed arbitrarily small region in predefined time irrespective of the initial *** addition,the control signal is bounded along the settling period,where the settling time instance can be estimated without conservation.

关键词： prescribed designing letter

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