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oceanS

作者： Anja Babić Martin Oreč Nikola Mišković Roee Diamant Laboratory for Underwater Systems and Technologies (LABUST) Faculty of Electrical Engineering and Computing University of Zagreb Croatia Department of Marine Technologies University of Haifa Israel

ISBN: (数字)9798350362077

ISBN: (纸本)9798350362084

The SOUND project focuses on developing a swarm of low-cost Lagrangian floaters capable of providing non-invasive aquaculture and fishing support, especially in remote areas and developing countries. The floaters drift with the current and use their buoyancy control mechanism to achieve profiling and depth-keeping behaviours, performing active acoustic fish detection and biomass assessment. This paper details the mechanical and algorithmic design of the SOUND floater prototype, as well as results achieved in laboratory experiments and during sea trials.

关键词： oceans Prototypes Buoyancy Developing countries Fish Acoustics Biomass

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Older and Wiser: The Marriage of Device Aging and Intellectual Property Protection of DNNs 24

Older and Wiser: The Marriage of Device Aging and Intellectu...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Lin, Ning Wang, Shaocong Zhang, Yue He, Yangu Wong, Kwunhang Basu, Arindam Shang, Dashan Chen, Xiaoming Wang, Zhongrui Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Access - Ai Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Laboratory of Microelectronics Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing China Department of Electrical Engineering City University of HongKong Hong Kong

ISBN: (纸本)9798400706011

Deep neural networks (DNNs), such as the widely-used GPT-3 with billions of parameters, are often kept secret due to high training costs and privacy concerns surrounding the data used to train them. Previous approaches to securing DNNs typically require expensive circuit redesign, resulting in additional overheads such as increased area, energy consumption, and latency. To address these issues, we propose a novel hardware-software co-design approach for DNN intellectual property (IP) protection that capitalizes on the inherent aging characteristics of circuits and a novel differential orientation fine-tuning (DOFT) to ensure effective ***-wise, we employ random aging to produce authorized chips. This process circumvents the need for chip redesign, thereby eliminating any additional hardware overhead during the inference procedure of DNNs. Moreover, the authorized chips demonstrate a considerable disparity in DNN inference performance when compared to unauthorized chips. Software-wise, we propose a novel DOFT, which allows pre-trained DNNs to maintain their original accuracy on authorized chips with minimal fine-tuning, while the model's performance on unauthorized chips is reduced to random guessing. Extensive experiments on various models, including MLP, VGG, ResNet, Mixer, and SwinTransformer, with lightweight binary and practical multi-bit weights demonstrate that the proposed method achieves effective IP protection, with only 10% accuracy on unauthorized chips, while preserving nearly the original accuracy on authorized ones. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Deep neural networks

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Improving Multiple Sclerosis Disease Prediction Using Hybrid Deep Learning Model

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Computers, Materials & Continua 2024年第10期81卷 643-661页

作者： Stephen Ojo Moez Krichen Meznah A.Alamro Alaeddine Mihoub Gabriel Avelino Sampedro Jaroslava Kniezova Department of Electrical and Computer Engineering College of EngineeringAnderson UniversityAndersonSC 29621USA Faculty of Computing and Information Al-Baha UniversityAl-Baha65528Saudi Arabia ReDCAD Laboratory University of SfaxSfax3038Tunisia Department of Information Technology College of Computer&Information SciencePrincess Nourah Bint Abdul Rahman UniversityRiyadh11564Saudi Arabia Department of Management Information Systems College of Business and EconomicsQassim UniversityP.O.Box 6640Buraidah51452Saudi Arabia School of Management and Information Technology De La Salle-College of Saint BenildeManila1004Philippines Department of Information Management and Business Systems Faculty of ManagementComenius University BratislavaBratislava 2582005Slovakia

Myelin damage and a wide range of symptoms are caused by the immune system targeting the central nervous system in Multiple Sclerosis(MS),a chronic autoimmune neurological *** disrupts signals between the brain and body,causing symptoms including tiredness,muscle weakness,and difficulty with memory and *** methods for detecting MS are less precise and time-consuming,which is a major gap in addressing this *** gap has motivated the investigation of new methods to improve MS detection consistency and *** paper proposed a novel approach named FAD consisting of Deep Neural Network(DNN)fused with an Artificial Neural Network(ANN)to detect MS with more efficiency and accuracy,utilizing regularization and combat *** use gene expression data for MS research in the GEO GSE17048 *** dataset is preprocessed by performing encoding,standardization using min-max-scaler,and feature selection using Recursive Feature Elimination with Cross-Validation(RFECV)to optimize and refine the ***,for experimenting with the dataset,another deep-learning hybrid model is integrated with different ML models,including Random Forest(RF),Gradient Boosting(GB),XGBoost(XGB),K-Nearest Neighbors(KNN)and Decision Tree(DT).Results reveal that FAD performed exceptionally well on the dataset,which was evident with an accuracy of 96.55%and an F1-score of 96.71%.The use of the proposed FAD approach helps in achieving remarkable results with better accuracy than previous studies.

关键词： Multi Sclerosis(MS) machine learning deep learning artificial neural network healthcare

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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Engineered common environmental effects on multitransistor systems

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Physical Review B 2023年第7期107卷 075440-075440页

作者： Uthpala N. Ekanayake Sarath D. Gunapala Malin Premaratne Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia Jet Propulsion Laboratory California Institute of Technology Pasadena California 91109 USA

In this paper, we analyze the impact of physically large baths used in terminals of thermal multitransistor systems formed using two-level systems (TLSs). In particular, we simulate the effects of a two-transistor system introduced as a thermal Darlington pair (DP). The size and proximity of the baths can cause multiple interactions with the transistor terminals represented by the TLS, not just the TLS directly connected to them. Such interactions can ultimately suppress the heat flows or impair the transistor action. However, we demonstrate that the DP model can achieve more than a 50% increase in heat flows. Using the engineered interactions leading to the correlated TLS-thermal bath interactions, we establish an incoherent (no quantum coherence in the density matrix at the steady state) yet correlated (joint excitation of two TLSs due to bath interaction) heat transfer model to a two-transistor arrangement in a substrate. This model helps us to interpret the environmental effects on the device by treating the common environment as separate thermal baths and all the transitions in the system as independent. We also show that this model can be mapped to contain dark-states. These dark-states can provide an external channel for transistor switching. We use this knowledge to design thermal counterparts of electronic AND and OR gates, and to study their switching time and operation, paving the way to realizing thermal logic gates.

关键词： Open quantum systems Quantum gates Thermal properties Nanotechnology Transistors

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Performance Optimization for Vehicular Cooperative Sensing: A Graph Attention Based Reinforcement Learning Approach

Performance Optimization for Vehicular Cooperative Sensing: ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Li, Xuefei Chen, Mingzhe Liu, Danpu Zhang, Zhilong Quek, Tony Q. S. Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL33146 United States Information Systems Technology and Design Pillar Singapore University of Technology and Design 487372 Singapore

ISBN: (纸本)9798350351255

In this paper, the problem of collaborative vehicle sensing is investigated. In the considered model, a set of cooperative vehicles provide sensing information to sensing request vehicles with limited sensing and communication resources. A base station (BS) determines the subset of sensing request vehicles that each cooperative vehicle will serve and the sub-regions that each cooperative vehicle will detect. We formulate an optimization problem aiming to maximize the number of successfully detected sub-regions of sensing request vehicles while satisfying the cooperative sensing energy requirement by jointly determining the cooperative vehicle association and the sensing sub-region selection. To solve this problem, we propose a graph attention based reinforcement learning (RL) algorithm that can generate the graph information vectors based on the correlation between each cooperative vehicle and each sensing request vehicle. Using the learned graph information, the joint cooperative vehicle association and sensing sub-region selection strategy will be determined. Simulation results show that the proposed scheme can improve the number of successfully detected sub-regions of sensing request vehicles by up to 12.5% compared to the conventional RL algorithm without using graph attention networks (GANs). © 2024 IEEE.

关键词： Reinforcement learning

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Generalized model for the charge transport properties of dressed quantum Hall systems

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Physical Review B 2022年第3期105卷 035430-035430页

作者： Kosala Herath Malin Premaratne Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton 3800 VIC Australia

We present a generalized mathematical model for predicting the transport properties of a quantum system exposed to a stationary magnetic field and a high-intensity electromagnetic field. The new formulation, which applies to two-dimensional (2D) dressed quantum Hall systems, is based on Landau quantization theory and the Floquet-Drude conductivity approach. We model our system as a two-dimensional electron gas (2DEG) that interacts with two external fields. To analyze the strong light coupling with the 2DEG, we employ the Floquet theory as a nonperturbative procedure. Moreover, the Floquet-Fermi golden rule is adopted to explore the impurity scattering effects on charge transport in disordered quantum Hall systems. We derive fully analytical expressions to describe longitudinal components in the conductivity tensor in dressed quantum Hall systems. Subsequently, we demonstrate that the conductivity characteristics of quantum Hall systems can be manipulated using strong external light. Our results align with well-established and experimentally verified theoretical descriptions for undressed systems while providing a more generalized analysis of the conductivity characteristics in quantum Hall systems. Thus our model can be applied to accurately interpret the usage of strong external radiation as a tool in nanoscale quantum devices.

关键词： Hall effect Quantum transport 2-dimensional systems Floquet systems Drude model

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Floquet engineering of dressed surface plasmon polariton modes in plasmonic waveguides

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Physical Review B 2022年第23期106卷 235422-235422页

作者： Kosala Herath Malin Premaratne Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton 3800 VIC Australia

We present a comprehensive study surface plasmon polariton (SPP) propagation on planar metallic waveguides under a dressing field. We perform a set of analytical calculations of the periodic time-dependent Schrödinger equation to study the interaction of an intense electromagnetic field with a metallic system. We model the strong light coupling to the metallic system using a nonperturbative procedure. In this paper, we show that, by introducing Floquet theory into the dressed metal, the behavior of the Floquet states are similar to the phase-modulated signals in the communication system. This will reveal a new perspective on the underlying science in an intricate, dressed quantum system. Furthermore, we examine the impurity scattering effects on charge transport in disordered plasmonic metals using the generalized Floquet-Fermi golden rule and provide a novel approach to diminish the losses in plasmonic materials using the dressing field. To gauge the effectiveness of our results, we introduce a figure of merit to compare the performance of plasmonic metals, subjective to a dressing field. The calculated dressed SPP characteristics suggest that high-efficiency SPP propagation can be achieved in practice. Our findings open up new directions for state-of-the-art nanoplasmonic devices.

关键词： Surface plasmons Waveguides Nanotechnology

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Comparison of Discrete Bipolar Transistors and MOSFETs for High-Speed Switching Application 44

Comparison of Discrete Bipolar Transistors and MOSFETs for H...

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

作者： Bogdanovic, F. Osrecki, Z. Zilak, J. Koricic, M. Suligoj, T. University of Zagreb Micro and Nano Electronics Laboratory Faculty of Electrical Engineering and Computing Department of Electronics Microelectronics Computing and Intelligent Systems Zagreb Croatia

ISBN: (纸本)9789532331011

Switching performance analysis in this paper presents how Horizontal Current Bipolar Transistor (HCBT) performs under switching mode of operation compared to other commercially available bipolar and MOS transistors, focusing mainly on power efficiency. Rudimentary measurement setup is devised, with target frequency spectrum for this analysis up to 100 MHz. Measurements were performed at frequencies of 1 MHz, 10 MHz and 100 MHz. Signal waveforms were measured at the input and output of analysed device. Dissipated power at each component of test circuit was calculated from the measurements to determine efficiency. The results show similar performance among RF bipolar junction transistors analysed in this paper. All bipolar transistors exhibit efficiency around 80% at 100 MHz, whereas the best performing MOSFET has n = 54.31%. The analysed MOSFETs show somewhat better performance comparing to bipolar transistors at lower frequencies, but with larger performance degradation with the frequency increase. This analysis shows potential of HCBT to be used in switching part of Envelope Tracking (ET), hybrid power supply modulation, pulse width modulation (PWM) or multilevel power supply switching to obtain higher efficiencies. Most of the efficiency reduction is caused by nonideal input signal. © 2021 Croatian Society MIPRO.

关键词： Efficiency

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Deep Learning Control for Autonomous Robot

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Computers, Materials & Continua 2022年第8期72卷 2811-2824页

作者： Rihem Farkh Saad Alhuwaimel Sultan Alzahrani Khaled Al Jaloud Mohammad Tabrez Quasim College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Laboratory for Analysis Conception and Control of SystemsLR-11-ES20Department of Electrical Engineering National Engineering School of TunisTunis El Manar University1002Tunisia King Abdulaziz City for Science and Technology Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

Several applications of machine learning and artificial intelligence,have acquired importance and come to the fore as a result of recent advances and improvements in these *** cars are one such *** is expected to have a significant and revolutionary influence on *** with smart cities,new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving *** autonomous automobile,often known as selfdriving systems or driverless vehicles,is a vehicle that can perceive its surroundings and navigate predetermined routes without human *** are on the verge of evolving into autonomous robots,thanks to significant breakthroughs in artificial intelligence and related technologies,and this will have a wide range of socio-economic ***,in order for these automobiles to become a reality,they must be endowed with the perception and cognition necessary to deal with high-pressure real-life events and make proper judgments and take appropriate *** majority of self-driving car technologies are based on computer systems that automate vehicle control *** forward-collision warning and antilock brakes to lane-keeping and adaptive drive control,to fully automated driving,these technological components have a wide range of capabilities.A self-driving car combines a wide range of sensors,actuators,and *** researches on computer vision and deep learning are used to control autonomous driving *** self-driving automobiles,lane-keeping is *** study presents a deep learning approach to obtain the proper steering angle to maintain the robot in the *** propose an advanced control for a selfdriving robot by using two controllers *** neural networks(CNNs)are employed,to predict the car’and a proportionalintegral-derivative(PID)controller is designed for speed and steering *** stu

关键词： Autonomous car cascade PID control deep learning convolutional neural network differential drive system raspberry PI road lane detector

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