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2023 IEEE National Aerospace and Electronics Conference, NAECON 2023

作者： Gopinath, Anoop Ytterdal, Trond Lee, John Rizkalla, Maher Kumar, Mukesh Norwegian University of Science and Technology Department of Electronic Systems Trondheim Norway Indiana University-Purdue University Indianapolis Department of Electrical and Computer Engineering Indianapolis United States Indian Institute of Technology Indore Department of Electrical Engineering Indore India

ISBN: (纸本)9798350338782

In this paper, a RAZOR-based in-situ monitoring scheme is described for process variation characterization and silicon debug in SRAM arrays. The scheme can identify whether the datapath being monitored has slowed-down due to process variation or hard errors. This information can be used to estimate the impact of process variation or hard errors on memory access time setting critical path in SRAM arrays. Pre-silicon characterized datapath delay via selectable data delay lines referred to as data TRIMs are obtained via SPICE simulations. These pre-silicon data TRIMs, along with post-silicon error output can be used to estimate the datapath slow-down with a margin of error. The margin of error can be reduced by using finer granularity in data TRIMs but comes at the cost of area and power overheads. The scheme can be shared across multiple SRAM arrays, and can also be used in a column-by-column manner to test memory access time with respect to individual bitcells in an array. This provides a deep level of visibility into SRAM macros post-silicon for debug purposes too. The scheme can estimate the slow-down on memory access time setting critical path in global TT corner with up to 99.2 % accuracy. © 2023 IEEE.

关键词： Static random access storage

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Multi-Class Skin Cancer Detection Using Fusion of Textural Features Based CAD Tool

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computers, Materials & Continua 2024年第12期81卷 4217-4263页

作者： Khushmeen Kaur Brar Bhawna Goyal Ayush Dogra Sampangi Rama Reddy Ahmed Alkhayyat Rajesh Singh Manob Jyoti Saikia Department of Electronics and Communication Engineering Chandigarh UniversityMohali140413India Chitkara University Institute of Engineering and Technology Chitkara UniversityChandigarh140401India Department of Physics&Electronics School of SciencesJAIN(Deemed to be University)Bangalore560001India College of Technical Engineering The Islamic UniversityNajaf54001Iraq Department of Electronics and Communication Engineering Uttaranchal Institute of TechnologyUttaranchal UniversityDehradun248007India Electrical and Computer Engineering Department University of MemphisMemphisTN 38152USA Biomedical Sensors&Systems Lab University of MemphisMemphisTN 38152USA

Skin cancer has been recognized as one of the most lethal and complex types of cancer for over a *** diagnosis of skin cancer is of paramount importance,yet the process is intricate and *** analysis and modeling of human skin pose significant difficulties due to its asymmetrical nature,the visibility of dense hair,and the presence of various substitute *** texture of the epidermis is notably different from that of normal skin,and these differences are often evident in cases of unhealthy *** a consequence,the development of an effective method for monitoring skin cancer has seen little ***,the task of diagnosing skin cancer from dermoscopic images is particularly *** is crucial to diagnose skin cancer at an early stage,despite the high cost associated with the procedure,as it is an expensive ***,the advancement of diagnostic techniques for skin cancer has been *** address this issue,there is a need for a more accurate and efficient method for identifying and categorizing skin cancer *** involves the evaluation of specific characteristics to distinguish between benign and malignant skin cancer *** present and evaluate several techniques for segmentation,categorized into three main types:thresholding,edge-based,and *** techniques are applied to a dataset of 200 benign and melanoma lesions from the Hospital Pedro Hispano(PH2)*** evaluation is based on twelve distinct metrics,which are designed to measure various types of errors with particular clinical ***,we assess the effectiveness of these techniques independently for three different types of lesions:melanocytic nevi,atypical nevi,and *** first technique is capable of classifying lesions into two categories:atypical nevi and melanoma,achieving the highest accuracy score of 90.00%with the Otsu(3-level)*** second technique also classifies lesions int

关键词： Melanoma computer-aided diagnosis segmentation PH2 ISIC(International Skin Imaging Collaboration) dermoscopy non-melanoma

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement 63

Distributed Optimization with Finite Bit Adaptive Quantizati...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Artificial Intelligence Thrust of the Information Hub Guangzhou China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Clear Water Bay Hong Kong Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia1678 Cyprus Kth Royal Institute of Technology Division of Decision and Control Systems StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3 -bits). Our proposed algorithm respects the network's bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm's operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm's unique characteristics. © 2024 IEEE.

关键词： Bandwidth

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Towards new realities: Implications of personalized online layers in our daily lives

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i-com 2024年第2期23卷 221-229页

作者： Herder, Eelco Stojko, Laura Strecker, Jannis Neumayr, Thomas Yigitbas, Enes Augstein, Mirjam Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Department of Computer Science University of the Bundeswehr Munich Neubiberg Germany Institute of Computer Science University of St. Gallen St. Gallen Switzerland Research Group Personalized Environments and Collaborative Systems University of Applied Sciences Upper Austria Hagenberg Austria Faculty of Electrical Engineering Computer Science and Mathematics Paderborn University Paderborn Germany

We are currently in a period of upheaval, as many new technologies are emerging that open up new possibilities to shape our everyday lives. Particularly, within the field of Personalized Human-computer Interaction we observe high potential, but also challenges. In this article, we explore how an increasing amount of online services and tools not only further facilitates our lives, but also shapes our lives and how we perceive our environments. For this purpose, we adopt the metaphor of personalized 'online layers' and show how these layers are and will be interwoven with the lives that we live in the 'human layer' of the real world. © 2024 the author(s), published by De Gruyter, Berlin/Boston.

关键词： Human computer interaction

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Toward a Low-Cost Perception System in Autonomous Vehicles: A Spectrum Learning Approach

arXiv

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arXiv 2025年

作者： Alsakabi, Mohammed Erickson, Aidan Dolan, John M. Tonguz, Ozan K. Department of Electrical and Computer Engineering College of Engineering The Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA United States

We present a cost-effective new approach for generating denser depth maps for Autonomous Driving (AD) and Autonomous Vehicles (AVs) by integrating the images obtained from deep neural network (DNN) 4D radar detectors with conventional camera RGB images. Our approach introduces a novel pixel positional encoding algorithm inspired by Bartlett’s spatial spectrum estimation technique. This algorithm transforms both radar depth maps and RGB images into a unified pixel image subspace called the Spatial Spectrum, facilitating effective learning based on their similarities and differences. Our method effectively leverages high-resolution camera images to train radar depth map generative models, addressing the limitations of conventional radar detectors in complex vehicular environments, thus sharpening the radar output. We develop spectrum estimation algorithms tailored for radar depth maps and RGB images, a comprehensive training framework for data-driven generative models, and a camera-radar deployment scheme for AV operation. Our results demonstrate that our approach also outperforms the state-of-the-art (SOTA) by 27.95% in terms of Unidirectional Chamfer Distance (UCD). © 2025, CC BY-NC-ND.

关键词： Radar imaging

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Decisioning-Based Approach for Optimising Control engineering Tools Using Digital Twin Capabilities and Other Cyber-Physical Metaverse Manufacturing System Components

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IEEE Transactions on Consumer Electronics 2024年第1期70卷 3212-3221页

作者： Mourad, Nahia Alsattar, Hassan A. Qahtan, Sarah Zaidan, Aws Alaa Deveci, Muhammet Sangaiah, Arun Kumar Pedrycz, Witold British University in Dubai Faculty of Engineering and IT Dubai United Arab Emirates University of Mashreq College of Administrative Science Department of Business Administration Baghdad10067 Iraq Middle Technical University College of Health and Medical Technology-Baghdad Department of Computer Center Baghdad10047 Iraq SP Jain School of Global Management SydneyNSW2141 Australia National Defence University Turkish Naval Academy Department of Industrial Engineering Istanbul34040 Turkey Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon International Graduate Institute of AI National Yunlin University of Science and Technology Yunlin64002 Taiwan University of Alberta Faculty of Engineering Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul34010 Turkey

The optimisation of control engineering tools based on digital twin capabilities and other cyber-physical metaverse manufacturing system (CPMMS) components are crucial for the successful performance. This study proposes a model for optimising control engineering tools using digital twin capabilities and other CPMMS components to solve the open issues. The main contributions and novelty aspects of the methodological process are outlined as follows: Formulated and developed is a decision matrix based on a utility procedure for 10 control engineering tools with digital twin capabilities and other three CPMMS components (Programmable-Logic-Controller and Human-Machine-Interface, Internet of Things connectivity and cybersecurity features). This matrix accounts for the uncertainty associated with tool assessment and transformation evaluation issue;formulated and develop an integrating fuzzy weighted with zero-inconsistency-interval-valued spherical fuzzy rough sets (IvSFRS-FWZIC) and combined compromise solution (CoCoSo) methods. The IvSFRS-FWZIC method is utilised to assign importance degrees to the digital twin capabilities and other CPMMS components. The applicability and robustness of the proposed approach are validated and evaluated through conducting sensitivity, correlation, and comparative analyses. The proposed approach can assist managers in analysing and selecting the most suitable tool for developing CPMMS. © 1975-2011 IEEE.

关键词： Internet of things

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Modeling and Robust Control of Single Board Heater System with Arduino based Implementation 2

Modeling and Robust Control of Single Board Heater System wi...

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2nd IEEE International Conference on Intelligent Technologies, CONIT 2022

作者： Miyani, Piyush B. Thakar, Parth S. Markana, Anilkumar Gujarat Power Engineering and Research Institute Electrical Engineering Department Mehsana India Institute for Systems and Robotics Instituto Superior Técnico Lisbon Portugal Pandit Deendayal Energy University Electrical Engineering Department Gandhinagar India

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

In this paper, a new discrete-time implementation of sliding mode control is proposed through open-source Arduino-based hardware for a single board heater system (SBHS). The designed control input with discrete-time sliding mode control (DSMC) is realized by proposing a MOSFET-based current control circuit. This designed hardware will provide a plat-form for researchers and practitioners to validate their control algorithms with ease of use through Arduino-based control implementation. Besides, the proposed strategy also features the first of its kind practical application of DSMC for temperature control using Arduino which is not reported before. The designed control is validated in terms of setpoint tracking for temperature control through the simulation studies in MATLAB and also through hardware implementation with the Arduino controller. The obtained simulation and experimental results showcase the efficacy of the proposed methods. © 2022 IEEE.

关键词： Temperature control

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Automation 5.0: The Key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Improving Lidar Based Tracking of UAVs Using an Approach Based on Focusing

Improving Lidar Based Tracking of UAVs Using an Approach Bas...

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Iberian robotics Conference (ROBOT)

作者： Alberto Cerutti Sedat Dogru Lino Marques Department of Electronics and Telecommunications (DET) Polytechnic University of Turin Turin Italy Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

This paper presents a novel approach for detecting drones using a lidar sensor integrated on a robotic turret. The turret rotates allowing the sensor to scan the sky, and both hardware components communicate in real-time. When the lidar sensor detects a drone, the detection data is used to dynamically adjust the motion pattern of the turret, allowing the system to capture more data by orienting the lidar sensor towards the drone, eventually improving tracking accuracy thanks to the higher number of detections achieved in this manner. In this paper we also explore different motion patterns for the turret, comparing them on the field to track a drone using the built lidar-turret system.

关键词： Laser radar Accuracy Uncertainty Tracking Focusing Robot sensing systems Real-time systems Hardware Optimization Drones

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Numerical study on the flow field for deep-sea hydrothermal plume tracking simulation 17

Numerical study on the flow field for deep-sea hydrothermal ...

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17th Asian Congress of Fluid Mechanics, ACFM 2023

作者： Xu, Xue-Han Liu, Jing-Cheng Hou, Hui-Rang Meng, Qing-Hao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin300072 China Laboratory for High-speed Aerodynamics Department of Mechanics Tianjin University Tianjin300072 China

In this paper, the distribution of hydrothermal buoyancy plume in the deep-sea environment is studied numerically. Submarine hydrothermal vents are prominent manifestations of hydrothermal activities and are of great scientific and engineering importance. It is an important basis to obtain the temporal and spatial distribution information of different hydrothermal plumes for tracking and locating the source of hydrothermal plumes. Based on Reynolds-averaged Navier-Stokes equations and Realizable k-ϵ turbulence model, the plumes of hydrothermal vents at depths of 800 m, 1200 m, and 1400 m were calculated and studied to obtain the spatial distribution of variables such as velocity field, temperature field and turbulent kinetic energy. The research results of this paper provide an important basis for the simulation of deep-sea hydrothermal plume tracking based on autonomous underwater vehicles. © The Institution of engineering & Technology 2023.

关键词： Flow fields

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