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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Nikolaos I. Deligiannis Riccardo Cantoro Matteo Sonza Reorda S. E. D. Habib Department of Control and Computer Engineering (DAUIN) Politecnico di Torino Turin Italy Department of Electronics and Electrical Communications Engineering Cairo University Giza Egypt

Arithmetic circuits form the foundation of modern digital computation, enabling us to conduct precise mathematical operations and drive the digital age. They are integral components in nearly every digital circuit, such as processors' arithmetic and logic units. Especially in safety-critical domains like automotive and aviation, the flawless operation of these circuits is of paramount importance. This paper presents a case study involving two variants of Dadda multipliers and assesses their intrinsic reliability when affected by permanent hardware faults. We conducted extensive fault injection campaigns on the circuit models under various datasets, presenting the aggregated statistical errors in the form of the mean absolute error (MAE) for each case. Specifically, we performed fault injection campaigns in which the operands are sourced from trained quantized weights of a convolutional neural network, as well as randomly generated sets of integers. The results not only reveal differences between the two circuits but also show significant variations when different datasets are used in the fault injection campaigns.

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Remotely controllable Data Self-Destruction for Privacy-Preserving Sensitive Data Services 25

Remotely Controllable Data Self-Destruction for Privacy-Pres...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zhou, Chengxin Xue, Xianbin Riad, Khaled Zhu, Yan Chu, William Cheng-Chung School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China North Navigation Control Technology Co. Ltd. Beijing China College of Computer Science and Information Technology King Faisal University Saudi Arabia Tunghai University Department of Computer Science Taichung Taiwan

ISBN: (纸本)9798350330014

This paper address a comprehensive solution to address data privacy and security challenges in data science, providing secure self-destruction of sensitive data, confidentiality through encryption, and flexible control over message destruction. Based on outsourcing cloud data services, we introduce a cloud retrograde storage (CRS) system for privacy-preserving self-destruction of sensitive data. The CRS is based on a frequently colliding hash table and recycle pool, and supports remote time, count, and range control. Hereby, we provide a remotely controllable mechanism for the prompt destruction of inactive messages against digital forensics without reducing the availability of services. The method used in the CRS involves storing messages in a recycle pool, where they are automatically erased at the end of their validity period or after being viewed by all recipients. The system also incorporates encryption and decryption processes to ensure confidentiality. The result of performance evaluation shows that the CRS effectively handles the destruction of messages and provides secure data removal from storage pools. The experiments demonstrate the efficiency and practicality of the CRS for large-scale data services. © 2023 IEEE.

关键词： Sensitive data

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Assessing the Dependence of Li-Ion Batteries Capacity on Load Current Frequency

Assessing the Dependence of Li-Ion Batteries Capacity on Loa...

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2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2022

作者： Chen, Yukai Wang, Wenlong Pagliari, Daniele Jahier MacIi, Enrico Poncino, Massimo Politecnico di Torino Department of Control and Computer Engineering Turin Italy Politecnico di Torino Interuniversity Department of Regional and Urban Studies and Planning Turin Italy

ISBN: (数字)9781665484596

ISBN: (纸本)9781665484596

Lithium-ion batteries are the most common chemistry thanks to their many desirable properties, such as high energy density and long lifetimes;however, they still exhibit several non-ideal properties common to other battery chemistries, such as rated capacity effect, capacity dependence on load variation, and recovery effects. In the last two decades, many works in the EDA community have focused on methods to characterize and model these non-idealities. In particular, for the rated capacity effect and the recovery effect, accurate models have been derived that allow tracking battery behaviour with a reasonable degree of fidelity. However, one effect that has not been thoroughly explored is how battery capacity is affected by the spectral properties of the load current and its frequency distribution. Some preliminary works analyzed this relation based only on the information provided by datasheets and lacked an experimental validation of the resulting models. We conduct experimental measurements to analyze this dependence between usable battery capacity and the frequency spectrum of load current in this work. Our measurements illustrate that this relation is much more sophisticated than the one extracted from datasheets information: it is not monotonic and exhibits a local maximum point that changes over time as the battery ages. © 2022 IEEE.

关键词： Lithium-ion batteries

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Development of a Converter-based Supercapacitor System Emulator for PV Applications

Development of a Converter-based Supercapacitor System Emula...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Kritprajun, Paychuda Sutton, Elizabeth Tolbert, Leon M. Liu, Yunting Wang, Jingxin Praisuwanna, Nattapat Ferrari, Maximiliano The University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN United States The Pennsylvania State University Department of Electrical Engineering University ParkPA United States Grid Components and Control Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350316445

As the utilization of supercapacitors in power system applications continues to increase, it is important to observe their behavior under transient and long-term operations in order to understand their impact on power grids. A real-time reconfigurable hardware testbed (HTB) is a power network emulator that provides flexibility to study various power system scenarios. This paper presents an emulation of a supercapacitor for a photovoltaic (PV) system on the HTB platform such that its dynamic behavior during power system scenarios can be observed. The developed emulator on the HTB is verified by comparing the emulation results with the model developed in MATLAB/Simulink. The experimental results of the emulator are consistent with the simulation results under the grid support scenarios. This supercapacitor emulator can be potentially used for various power system scenarios in addition to the PV applications presented in this paper. © 2023 IEEE.

关键词： grid ancillary services grid-connected photovoltaic system hardware testbed supercapacitor

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Fault-tolerant formation control of a team of quadrotors with a suspended payload

Fault-tolerant formation control of a team of quadrotors wit...

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2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Saiella, Lorenzo Cristofaro, Andrea Ferro, Marco Vendittelli, Marilena Sapienza University of Rome Department of Computer Control and Management Engineering Italy

ISBN: (纸本)9780738131153

This paper proposes a fault-tolerant architecture for formation control and cooperative trajectory tracking for a team of autonomous quadrotors carrying a suspended load. Formation control is provided by the combination of passivity-based techniques and backstepping, while a supervisory fault-tolerant control policy is responsible to reconfigure the network topology and the control objectives upon detection of faults among the vehicles. © 2021 IEEE.

关键词： Fault tolerance

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A note on a ode model of micro rna-dependent regulation of messenger rna levels

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2021年第4期83卷 171-176页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

We study the qualitative behavior (invariance, boundedness and equilibria) of the solutions of a mathematical model describing the dynamics of microRNA AGO complexes and mRNA targets interaction. © 2021, Politech... 详细信息

关键词： Ordinary differential equations

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Robust Face Tracking using Improved Mean Shift Algorithm 1

Robust Face Tracking using Improved Mean Shift Algorithm

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1st International Conference on Industrial Automation, Smart Grid and its Application, ICIASGA 2020

作者： Setyawan, S.B. Arrosida, H. Sudaryanto, A. Yudha, R.G.P. Department of Computer Control Engineering Politeknik Negeri Madiun Madiun Indonesia

Face tracking is important system for robotic. The problem is that it is less resistant to occlusion and noise. Robust face tracking algorithm in this paper using improved mean shift algorithm is proposed. This algorithm consist of face detection and tracking. The face identification is done by the Viola-Jones algorithm. Then, Mean Shift algorithm is done to track face as a target and improve robustness from occlusion. CBWH is added in face as target to reduce noise. The experimental results prove that it is robust from noise background and occlusion.. © Published under licence by IOP Publishing Ltd.

关键词： Face recognition

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Research and Mathematical Modeling of The Dependence of The Frequency of Transverse Vibrations of a Variable-Length String on The Amplitude 8

Research and Mathematical Modeling of The Dependence of The ...

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8th International Conference on Information, control, and Communication Technologies, ICCT 2024

作者： Litvinov, Vladislav Litvinova, Kristina Tarakanov, Alexey Uyutov, Anatoly Almeev, Ruslan Samara State Technical University Department of General Theoretical Disciplines Samara Russia Moscow State University Department of Oil and Gas Development Moscow Russia Samara State Technical University Department of Computer Science and Control Systems Samara Russia Samara State Technical University Department of Mechanical Engineering Technology Samara Russia

ISBN: (纸本)9798331517564

When studying string vibrations, the linear wave equation is most often used. This does not take into account the dependence of the string tension force on the amplitude. For metals, even with a slight elongation, the tension force will increase significantly, which will affect the speed of propagation of transverse waves and the frequency of vibrations. The speed of transverse vibrations is limited by the tensile strength of the material. Thus, for high-strength silicon-chromium-manganese steel, the ratio of the speed of longitudinal waves to the maximum speed of transverse waves is approximately equal to 10. For other materials, this ratio is much larger, so we will assume that longitudinal deformations at each moment of time have time to be evenly distributed along the length of the string, because during one transverse vibration a large number of longitudinal vibrations occur. © 2024 IEEE.

关键词： Chromium steel

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Depth Image Restoration for High-Level Vision Tasks 2

Depth Image Restoration for High-Level Vision Tasks

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2nd International Conference on Artificial Intelligence, Human-computer Interaction and Robotics, AIHCIR 2023

作者： Gao, Ying Song, Shaojing Ding, Xie Wang, Yu Sun, Xiang Zheng, Shaoqiu School of Computer and Information Engineering Shanghai Polytechnic University Shanghai China Wonders Information Co. Ltd Data Intelligence Product Department Shanghai China School of Intelligent Manufacturing and Control Engineering Shanghai Polytechnic University Shanghai China

ISBN: (纸本)9798350360363

High-level computer vision tasks often necessitate large-scale, high-quality depth images. However, real-world depth images are unsuitable for direct application in experimental studies due to their inherent noise and presence of holes. Consequently, image restoration becomes imperative. Large-scale hole repair often proves ineffective in the face of realistic and complex degraded scenes. To address this issue, our research introduces the fast Fourier convolution and a Multi-Scale Attention mechanism into an unsupervised learning network. This integration expands the network's sensory field and enhances perception of spatial feature details within the depth image. Its objective is to improve the restoration performance of depth images that possess substantial regions of missing depth values. Our experimental results demonstrate significant enhancements achieved by our restoration algorithm. Specifically, relative to the original depth images, the algorithm improves PSNR and SSIM by 25% and 60%. On average, improvements exceed the baseline by 9% and 15%, respectively. Moreover, our algorithm outperforms the original depth images in target detection, with the average precision values for human pose recognition tasks increasing by 24% and 25%, respectively. Compared to the baseline, these AP values experience additional enhancements of 11% and 18%, respectively. The restoration algorithm presented in this paper not only achieves visually pleasing results in terms of image quality but also significantly enhances the performance of downstream advanced vision tasks. © 2023 IEEE.

关键词： Image reconstruction

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Climate Data Forecasting Using ARIMA and Holt Winter Methods

Climate Data Forecasting Using ARIMA and Holt Winter Methods

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Remote Sensing Symposium (InGARSS), 2020 IEEE India Geoscience and

作者： Surendra Singh Choudhary Rashmi Saini Rahul Raj Choudhary Laxman Singh Khangarot Department: Computer Science & Engineering Govt. Engineering College Bikaner Computer Science & Engineering G. B. Pant Institute of Engineering and Technology Uttarakhand Department: Electronics and Instrument & Control Engineering Govt. Engineering College Bikaner Computer Science & Engineering Indian Institute of Technology Roorkee Uttarakhand

ISBN: (数字)9798350390346

ISBN: (纸本)9798350390353

The Artificial Neural Networks (ANNs) models have provided mixed results to solve linear problems, so it is not widely used for any data types. The autoregressive integrated moving average (ARIMA) model is a massive, very popular, and connivance linear model for long time series forecasting. Mainly used to construct different hybrid models for forecasting other time series data in the last decade. The study analyzes ARIMA and Holt-Winters (HW) forecasting procedure analysis. The machine learning and deep learning model have good frameworks that can apply to multiple forecasting processes with good precision and accuracy. Autoregressive Integrated moving average (ARIMA) and Holt-Winters (HW) approaches have been used to forecasting time series climatic variables. The two different forecasting methods are generated, and the output of both methods is compared by the climate variables rainfall and temperature for monthly data of 2001-2021.

关键词： Temperature sensors Temperature distribution Rain Time series analysis Stochastic processes Predictive models Data models Autocorrelation Forecasting Meteorology

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