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Test Circuit Design for Accurately Characterizing Cells' Output Currents in a Read-Decoupled 8T SRAM Array for Computing-in-Memory Applications 35

Test Circuit Design for Accurately Characterizing Cells' Out...

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35th International Conference on Microelectronic Test Structure, ICMTS 2023

作者： Hong, Hao-Chiao Lin, Long-Yi Chen, Bo-Chang Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu30010 Taiwan Novatek MicroElectronics Corp. Hsinchu Taiwan

ISBN: (纸本)9798350346534

Computing-in-memory (CIM) is a promising technique for energy-efficiently conducting the massive amount of required multiply-And-Accumulate (MAC) calculations in neural networks (NNs). The read-decoupled 8T (RD8T) SRAM cell is popular in the CIM designs because of being read disturbance free. However, local process variations may lead significant errors to the CIM results. This work proposes an accurate on-chip test circuit design for characterizing the output current of every RD8T SRAM cell in a 8-kb RD8T SRAM array fabricated in 90nm CMOS. The experimental results show the detailed and accurate spatial distribution of the RD8T cells which helps optimize the CIM circuit design. © 2023 IEEE.

关键词： Static random access storage

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Image Enhancement for Facial Landmark Detection 21

Image Enhancement for Facial Landmark Detection

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21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Ciuntu, Victor Chiornita, Traian Boiangiu, Costin-Anton Tarba, Nicolae Voncila, Mihai-Lucian Rosner, Daniel Politehnica University Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

Facial landmark detection (FLD) is a field of study in computer vision that specializes in detecting and tracking key points from human faces. There are many applications, such as detecting a human's head pose (position and rotation), tracking whether drivers are paying attention or not, applying augmented reality, etc. This paper proposes to evaluate and decide what are the optimal techniques of image enhancement that can be used to improve different algorithms of FLD. After proposing different pipelines of contrast enhancement and grayscale conversion to enhance the image before applying the FLD algorithm, the results show that the performance will not increase drastically if an image enhancement pipeline is used, but for the reason that this step will not consume a lot of time in the process of detection, it is a step worth considering. © 2022 IEEE.

关键词： Face recognition

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PATH OPTIMIZATION FOR DYNAMIC OBSTACLE AVOIDANCE OF PIONEER ROBOT BASED ON DDPG SMART AGENT

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UPB Scientific Bulletin, Series D: Mechanical engineering 2023年第2期85卷 29-42页

作者： Zheng, Qingchun Peng, Zhi Zhu, Peihao Zhao, Yangyang Ma, Wenpeng Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China China School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

To improve the path efficiency for dynamic obstacle avoidance algorithms of Pioneer robots, this paper proposes an approach to create deep deterministic policy gradient (DDPG) smart agents with recurrent neural networks (RNN) to optimize the path strategy. This approach is realized by training RNN with the backpropagation (BP) algorithm to train the agent. First, the SolidWorks model and obstacle avoidance model of the Pioneer robot is established. The LIDAR sensor is used to obtain environmental information. Further, deep reinforcement learning obstacle avoidance algorithm based on RNN is presented. The dynamic obstacle avoidance path of the Pioneer robot is further simulated in two different virtual robot experiment platform (V-REP) scenarios. The simulation results show that the proposed algorithm shortens the training time by 26.3% compared with the DDPG algorithm. Our proposed scheme can improve the path efficiency for dynamic obstacle avoidance of the Pioneer robot. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Reinforcement learning

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Characterization and Trading of Energy Level and Energy Shift Considering Virtual Power Plant

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1784-1789页

作者： Shuai Fan Jucheng Xiao Zuyi Li Guangyu He Key Laboratory of Control of Power Transmission and Conversion Ministry of EducationShanghai Jiao Tong UniversityShanghai200240China Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIL 60616USA

The capability of shifting the electricity generation or consumption to proper time of the day,also defined as energy shift(ES),is the key factor to ensure the power balance,especially under high penetration of variable renewable energy(VRE).However,the ES is not characterized and traded as an independent product in current market *** this letter,the marginal utility of an ES is assessed and leveraged to characterize the effective ES,while a novel market scheme is proposed considering the trading of both ES and energy level(EL).The proposed scheme can well integrate ES producers such as virtual power plants that cannot be rewarded sufficiently to actively participate in the current market because they are principally labeled as EL ***,the novel concept and mechanism are illustrated by a numerical study and verified to outperform the existing price schemes on integrating the ES resources and VRE.

关键词： Energy level energy shift variable renewable energy virtual power plant marginal utility

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High fault-tolerant DNA image storage system based on VAE

IEEE Transactions on Nanobioscience

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IEEE Transactions on Nanobioscience 2025年 PP卷 PP页

作者： Lu, Yuyang Zhang, Zhihao Yang, Jing Zhang, Cheng The School of control and computer engineering North China Electric Power University Beijing102206 China The School of Electronics Engineering and Computer Science Peking University Beijing100871 China

DNA-based storage has emerged as a promising storage paradigm due to its immense storage potential. However, the error-prone nature of DNA sequencing and synthesis processes limits this potential. Image data is typically compressed before storage, and even a single mismatch can lead to catastrophic error propagation during decompression, rendering the image unrecoverable. To reduce the error rate of DNA storage-based image compression, we have designed a high fault-tolerant DNA image storage system and applied it to image compression for DNA storage. This system achieves significant improvements in both image data compression ratio and resilience through three key innovations: 1) Using a Variational Autoencoder (VAE) to compress the image into uniformly sized latent variable blocks, followed by further compression via Singular Value Decomposition (SVD);2) Quantizing the floating-point numbers in the latent variable blocks and applying rotational coding to the resulting ternary sequences, effectively ensuring positive constraints on homopolymer run lengths and GC content;3) Optimizing the error-correction scheme to best recover each type of error by quantizing it back to its original value. Through image scaling, we adjust the compression ratio, and the comparative results of image compression simulations demonstrate the performance of the proposed model, highlighting its superiority in fault tolerance and storage density. © 2002-2011 IEEE.

关键词： Data compression ratio

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Complete OCR Solution for Image Analysis of World War 2 Documents 21

Complete OCR Solution for Image Analysis of World War 2 Docu...

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21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Gradinaru, Mihai Negru, Andrei Boiangiu, Costin-Anton Tarba, Nicolae Voncila, Mihai-Lucian Deaconescu, Razvan Adrian Politehnica University Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

The field of Optical Character Recognition (OCR) consists of techniques that are mainly focused on document image analysis. Aside from generating significant speedups of everyday procedures, OCR has a considerable role in the preservation of historical sources of information. Most of the World War 2 (WW2) documents are of great importance, especially with applications in virtual archives, museums, and research. The situation asks for an efficient, yet not aggressive, transcribing method using OCR tools. This paper describes an approach in the context of the given problem. The focus is oriented towards extracting the information from documents affected by their age, but with simpler structures, mainly split into paragraphs, such as letters and military reports. The approach is based on combining the results of multiple OCR engines, with the final objective of achieving better performance compared to the individual performance of each engine. © 2022 IEEE.

关键词： Engines

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LLCoach: Generating Robot Soccer Plans Using Multi-role Large Language Models

LLCoach: Generating Robot Soccer Plans Using Multi-role Larg...

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27th RoboCup International Symposium, 2024

作者： Brienza, M. Musumeci, E. Suriani, V. Affinita, D. Pennisi, A. Nardi, D. Bloisi, D.D. Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy School of Engineering University of Basilicata Potenza Italy Department of International Humanities and Social Sciences International University of Rome Rome Italy

ISBN: (纸本)9783031858581

The deployment of robots into human scenarios necessitates advanced planning strategies, particularly when we ask robots to operate in dynamic, unstructured environments. RoboCup offers the chance to deploy robots in one of those scenarios, a human-shaped game represented by a soccer match. In such scenarios, robots must operate using predefined behaviors that can fail in unpredictable conditions. This paper introduces a novel application of Large Language Models (LLMs) to address the challenge of generating actionable plans in such settings, specifically within the context of the RoboCup Standard Platform League (SPL) competitions where robots are required to autonomously execute soccer strategies that emerge from the interactions of individual agents. In particular, we propose a multi-role approach leveraging the capabilities of LLMs to generate and refine plans for a robotic soccer team. The potential of the proposed method is demonstrated through an experimental evaluation, carried out simulating multiple matches where robots with AI-generated plans play against robots running human-built code. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Anthropomorphic robots

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Dipper Throated Optimization for Detecting Black-Hole Attacks inMANETs

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computers, Materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

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Increasing the security of web applications by using smartphones 21

Increasing the security of web applications by using smartph...

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21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Contasel, Cristian Tranca, Dumitru-Cristian Palacean, Alexandru-Viorel University Politehnica of Bucharest Bucharest Faculty of Automatic Control and Computers Department of Computer Engineering Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

The web applications security systems often use the authentication strategy and credentials to assess the identity of the user. Based on the credentials, the system is able to claim the identity of the user. Also, the authenticity of identity is claimed based on authentication strategy. This paper analyzes and compares different strategies used to enforce the web applications security systems by using location and biometric features of the smartphones to provide two-way authentications. © 2022 IEEE.

关键词： Smartphones

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Task Offloading and Resource Allocation in IoT Based Mobile Edge Computing Using Deep Learning

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computers, Materials & Continua 2023年第8期76卷 1463-1477页

作者： Ily s Abdullaev Natalia Prodanova KAruna Bhaskar ELaxmi Lydia Seifedine Kadry Jungeun Kim Dean of the Faculty of Economics Department of Management and MarketingFaculty of EconomicsUrgench State UniversityUrganch220100Uzbekistan Basic Department Financial Control Analysis and Audit of Moscow Main Control DepartmentPlekhanov Russian University of EconomicsMoscow117997Russia Department of Computer Science and Engineering KL Deemed to UniversityVaddeswaramGunturAndhra PradeshIndia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajamIndia Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-based data *** city benefitted from offloading to edge *** a mobile edge computing(MEC)network in multiple *** comprise N MDs and many access points,in which everyMDhasM independent real-time *** study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization(TORA-DLSGO)*** proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,which enables an optimum offloading decision to minimize the system *** addition,an objective function is derived based on minimizing energy consumption subject to the latency requirements and restricted *** TORA-DLSGO technique uses the deep belief network(DBN)model for optimum offloading ***,the SGO algorithm is used for the parameter tuning of the DBN *** simulation results exemplify that the TORA-DLSGO technique outperformed the existing model in reducing client overhead in the MEC systems with a maximum reward of 0.8967.

关键词： Mobile edge computing seagull optimization deep belief network resource management parameter tuning

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