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Euromicro Symposium on Digital System Design

作者： Xabier Arauzo Irune Yarza Leonidas Kosmidis Alejandro J. Calderón Marcos Rodriguez Reliable Embedded Systems Ikerlan Technology Research Centre Computer Architecture Universitat Politècnica de Catalunya Mondragón Spain Reliable Embedded Systems Ikerlan Technology Research Centre Mondragón Spain Computer Architecture Universitat Politècnica de Catalunya Barcelona Super Computing Centre (BSC) Barcelona Spain

In the domain of safety-critical systems there is an increasing need for more compute-capable and higher performance devices. This comes from the dramatic increase on the software complexity caused by the newest intelligent and autonomous systems. Graphics Processing Units (GPUs), as multi-processing accelerators, are an ideal choice in this aspect due to their ability to handle big amount of data and computations. In order to ease the challenging task of programming such devices, vendors are continuously adding features, such as Unified Memory (UM), which allow the programmers to reduce their developing time on GPU applications. However, the use of GPU poses several challenges on safety-critical systems due to its close source nature and proprietary implementation. Therefore, this paper shows a deeper insight on how this feature works and present a way of exploiting this knowledge to reduce the execution time of applications using NVIDIA's UM feature. We demonstrate that these optimizations can make the data migrations predictable and reduce the required time.

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Anomaly Localization at High-Density Crowd Using Motion Shape Image (MSI) 1st

Anomaly Localization at High-Density Crowd Using Motion Shap...

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1st International Conference on Artificial Intelligence for Smart Community, AISC 2020

作者： Farooq, M.U. Mohamad Saad, M.N. Daud Khan, S. Saleh, Y. Universiti Teknologi PETRONAS Tronoh Malaysia Department of Computer Science National University of Technology Islamabad Pakistan Electrical Engineering Department Faculty of Engineering and Islamic Architecture Umm Al-Qura University Makkah Saudi Arabia

ISBN: (纸本)9789811621826

Anomaly localization plays a critical role if a disaster occurs in a high-density crowd to efficiently rescue the crowd from the right location. This paper enriches anomaly localization by introducing new localization features, in addition to the ‘only’ localization feature of source/start point detection existing literature offers. New features introduced include crowd density estimation in localized regions and direction/angle of a localized region. A motion shape image (MSI) based approach is introduced for localization and features detection and experimentation is performed on benchmark and our proposed high-density crowd datasets. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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Boosting the Restoring Performance of Deduplication Data by Classifying Backup Metadata

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ACM/IMS Transactions on Data Science 2021年第2期2卷 1–16页

作者： Yang, Ru Deng, Yuhui Zhou, Yi Huang, Ping Department of Computer Science Jinan University Guangzhou510632 China Department of Computer Science Jinan University China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China TSYS School of Computer Science Columbus State University Doimukh Georgia College of Engineering Temple University United States

Restoring data is the main purpose of data backup in storage systems. The fragmentation issue, caused by physically scattering logically continuous data across a variety of disk locations, poses a negative impact on the restoring performance of a deduplication system. Rewriting algorithms are used to alleviate the fragmentation problem by improving the restoring speed of a deduplication system. However, rewriting methods give birth to a big sacrifice in terms of deduplication ratio, leading to a huge storage space waste. Furthermore, traditional backup approaches treat file metadata and chunk metadata as the same, which causes frequent on-disk metadata accesses. In this article, we start by analyzing storage characteristics of backup metadata. An intriguing finding shows that with 10 million files, the file metadata merely takes up approximately 340 MB. Motivated by this finding, we propose a Classified-Metadata based Restoring method (CMR) that classifies backup metadata into file metadata and chunk metadata. Because the file metadata merely takes up a meager amount of space, CMR maintains all file metadata in memory, whereas chunk metadata are aggressively prefetched to memory in a greedy manner. A deduplication system with CMR in place exhibits three salient features: (i) It avoids rewriting algorithms' additional overhead by reducing the number of disk reads in a restoring process, (ii) it increases the restoring throughput without sacrificing the deduplication ratio, and (iii) it thoroughly leverages the hardware resources to boost the restoring performance. To quantitatively evaluate the performance of CMR, we compare our CMR against two state-of-the-art approaches, namely, a history-aware rewriting method (HAR) and a context-based rewriting scheme (CAP). The experimental results show that compared to HAR and CAP, CMR reduces the restoring time by 27.2% and 29.3%, respectively. Moreover, the deduplication ratio is improved by 1.91% and 4.36%, respectively. © 2

关键词： Metadata

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Improving social media use for disaster resilience: challenges and strategies

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International Journal of Digital Earth 2023年第1期16卷 3023-3044页

作者： Nina S.N.Lam Michelle Meyer Margaret Reams Seungwon Yang Kisung Lee Lei Zou Volodymyr Mihunov Kejin Wang Ryan Kirby Heng Cai Department of Environmental Sciences Louisiana State UniversityBaton RougeUSA Landscape Architecture and Urban Planning Texas A&M UniversityCollege StationUSA School of Information Studies Center for Computation and TechnologyLouisiana State UniversityBaton RougeUSA Division of Computer Science and Engineering Louisiana State UniversityBaton RougeUSA Department of Geography Texas A&M UniversityCollege StationUSA Escambia County Natural Resources Management PensacolaFloridaUSA

This paper develops a social media-disaster resilience analysis framework by categorizing types of social media use and their challenges to better understand and assess its role in disaster resilience research and *** framework is derived primarily from several case studies of Twitter use in three hurricane events in the United States-Hurricanes Isaac,Sandy,and *** paper first outlines four major contributions of social media data for disaster resilience research and management,which include serving as an effective communication platform,providing ground truth information for emergency response and rescue operations,providing information on people's sentiments,and allowing predictive ***,there are four_key challenges to its uses,which include,easy spreading of false information,social and geographical disparities of Twitter use,technical issues on processing and analyzing big and noisy data,especially on improving the locational accuracy of the tweets,and algorithm bias in Al and other types of ***,the paper proposes twenty strategies that the four sectors of the social media community-organizations,individuals,social media companies,and researchers-could take to improve social media use to increase disaster resilience.

关键词： Twitter use challenges and strategies disaster resilience social and geographical disparities emergency rescue Hurricane Isaac Hurricane Sandy Hurricane Harvey

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Statistical static timing analysis for circuit aging prediction

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The Journal of China Universities of Posts and Telecommunications 2021年第2期28卷 14-23页

作者： Duan Shengyu Zhai Dongyao Lu Yue Shanghai Engineering Research Center of Intelligent Computing System Shanghai UniversityShanghai 200444China State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China School of Electronics and Computer Science University of SouthamptonSouthamptonUK

Complementary metal oxide semiconductor(CMOS)aging mechanisms including bias temperature instability(BTI)pose growing concerns about circuit *** results in threshold voltage increases on CMOS transistors,causing delay shifts and timing violations on logic *** amount of degradation is dependent on the circuit workload,which increases the challenge for accurate BTI aging prediction at the design *** this paper,a BTI prediction method for logic circuits based on statistical static timing analysis(SSTA)is proposed,especially considering the correlation between circuit workload and BTI *** consists of a training phase,to discover the relationship between circuit scale and the required workload samples,and a prediction phase,to present the degradations under different workloads in Gaussian probability *** method can predict the distribution of degradations with negligible errors,and identify 50%more BTI-critical paths in an affordable time,compared with conventional methods.

关键词： bias temperature instability(BTI) reliability prediction statistical static timing analysis(SSTA)

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Purification control system of balanced charge lubricating oil based on PLC 5

Purification control system of balanced charge lubricating o...

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5th International Conference on Mechanical, Electric, and Industrial Engineering, MEIE 2022

作者： Xu, Fangyang Yang, Bikai Zhao, Xinrui Zhang, Jieshuo Jiang, Pan School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuchang Wuhan China School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuchang Wuhan China School of Navigation Wuhan University of Technology Wuchang Wuhan China School of Transportation and Logistics Engineering Wuhan University of Technology Wuchang Wuhan China

Marine diesel engine lubricating oil after long-term use, due to pollution and chemical activity, internal impurities increased, lubrication effect gradually deteriorated. The lubricating oil purification device based on balanced charge agglomeration (BCA) can realize the on-line purification of lubricating oil. In order to further improve the purification efficiency, a purification control system based on PLC is designed in this paper. The system consists of a complex electromechanical integration equipment composed of oil purification equipment, PLC control equipment and touch screen. The precise control of control parameters is realized by PLC, which ensures the strict logical relationship between various steps of oil purification, and realizes the visualization and convenience of operation process. On this basis, the safety of the device is also guaranteed. Purification device in the actual operation, smooth operation, stable performance, high reliability. © Published under licence by IOP Publishing Ltd.

关键词： Purification

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Spline Global MPPT with PID Controller Based on Levy Invasive Weed Technique for Renewable Energy Resources of Smart Homes

Spline Global MPPT with PID Controller Based on Levy Invasiv...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Aziza I. Hussein Mady Mohammad Passent Elkafrawy Rabab Hamed M. Aly College of Engineering Energy and Technology Research Center Effat University Jeddah Saudi Arabia College of Architecture Effat University Jeddah Saudi Arabia The Higher Institute for Management and Information Technology Minya Egypt Computer Science Department Faculty of Computer Science Nahda University Beni Suef Egypt

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

Renewable energy systems, particularly photovoltaic (PV) systems, have been played important role in the reducing carbon emissions. A primary concern in the field of photovoltaics (PV) based on the design of the maximum power point tracking (MPPT) is the capacity to accurately monitor power across many parameters in addition to ascertain the power production of solar cells or wind turbines and adjust the load to maximise power efficiency under varying weather conditions. On another hands, the hybrid smart system uses a wind catcher to reduce the amount of energy consumed by buildings from the grid, which is a historically significant architectural component for cross ventilation and passive cooling. This paper presents an updating of model that proposes improvements to the regulation of Spline MPPT with tuning PID controller by using Levy Invasive Weed optimization (LIWO)technique. A rapid, accurate, and straightforward approach for determining the (MPPT) of PV systems under consistent irradiation and partial shade, as well as wind turbines, is presented using the Spline- MPPT technique. The model of this paper employs LIWO in conjunction with a PID controller to improve the selection of PID gains. Moreover, is applied to generate the optimal values of duty cycle of the model. The comprehensive system design depicted has been simulated using MATLAB Simulink to verify the functionality of the system. The model has attained an accuracy of 93%. The outcomes of this model contribute greatly to our understanding of the suitability and efficacy of both AI and traditional MPPT controllers. This modeling will be beneficial to the renewable energy industry.

关键词： Maximum power point trackers Photovoltaic systems Renewable energy sources Accuracy Software packages Mathematical models Wind turbines Splines (mathematics) Optimization Tuning

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The zero-tax data center: a use case through quantum resilient communications

The zero-tax data center: a use case through quantum resilie...

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International Conference on Transparent Optical Networks

作者： Daniel Lawo Michal Podleś Raphael Frantz Abraham Cano Aguilera Dismothenis Iliadis-Apostolidis Jeronimo Sanchez Sokol Kosta Idelfonso Tafur Monroy José Luis Imaña J.J. Vegas Olmos Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands Department of Electronic Systems Aalborg University Copenhagen Denmark Department of Computer Architecture and Automation Complutense University of Madrid Spain Software Architecture NVIDIA Corporation Ofer Industrial Park Yokneam Israel

ISBN: (数字)9798350377323

ISBN: (纸本)9798350377330

Data centers, cloud and edge computing platforms are absorbing heavy AI-based workloads. This raises two concerns: how to reduce the networking overhead by host processors in order to focus only on AI-processing, and how to provide quantum resilient level protection for any connection running such workloads. In this paper, we will show case the concept of zero-tax data center, which is achieved through offloading of networking functions from the host to the network. In particular, the implementation of postquantum cryptography algorithms providing quantum resilient links and how the processing its complex processing is moved from host to network through the utilization of data-processing units.

关键词： Data centers Cloud computing Quantum computing Program processors Optical fiber networks Cryptography Network interfaces

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Deep Learning Approach for Divergence Behavior Detection at High Density Crowd 1st

Deep Learning Approach for Divergence Behavior Detection at ...

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1st International Conference on Artificial Intelligence for Smart Community, AISC 2020

作者： Farooq, M.U. Mohamad Saad, M.N. Saleh, Y. Daud Khan, S. Universiti Teknologi PETRONAS Tronoh Malaysia Electrical Engineering Department Faculty of Engineering and Islamic Architecture Umm Al-Qura University Makkah Saudi Arabia Department of Computer Science National University of Technology Islamabad Pakistan

ISBN: (纸本)9789811621826

At high-density crowd gatherings, people naturally escape from the region where any unexpected event happens. Escape in high-density crowds appears as a divergence pattern in the scene and timely detecting divergence patterns can save many human lives. In this paper, we propose to physically capture crowd normal and divergence motion patterns (or motion shapes) in form of images and train a shallow convolution neural network (CNN) on motion shape images for divergence behavior detection. Crowd motion pattern shape is obtained by extracting ridges of Lagrangian Coherent Structure (LCS) from the Finite-Time Lyapunov Exponent (FTLE) field and convert ridges into the grey-scale image. We also propose a divergence localization algorithm to pinpoint anomaly location(s). Experimentation is carried out on synthetic crowd datasets simulating normal and divergence behaviors at the high-density crowd. Comparison with state-of-the-art methods shows our method can obtain better accuracy for both divergence behavior detection and localization problems. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion estimation

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Radio spectrum awareness using deep learning: Identification of fading channels, signal distortions, medium access control protocols, and cellular systems

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Intelligent and Converged Networks 2021年第1期2卷 16-29页

作者： Yu Zhou Hatim Alhazmi Mohsen H.Alhazmi Alhussain Almarhabi Mofadal Alymani Mingju He Shengliang Peng Abdullah Samarkandi Zikang Sheng Huaxia Wang Yu-Dong Yao Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA the College of Information Science and Engineering Huaqiao UniversityXiamen 361021China the College of Engineering Architecture and TechnologyOklahoma State UniversityStillwaterOK 74078-1010USA

Radio spectrum awareness,including understanding radio signal activities,is crucial for improving spectrum utilization,detecting security vulnerabilities,and supporting adaptive *** tasks include spectrum sensing,identifying systems and terminals,and understanding various protocol *** this paper,we investigate various identification and classification tasks related to fading channel parameters,signal distortions,Medium Access Control(MAC)protocols,radio signal types,and cellular ***,we utilize deep learning methods in those identification and classification *** evaluations demonstrate the effectiveness of deep learning in those radio spectrum awareness tasks.

关键词： cellular system deep learning signal classification spectrum awareness Convolutional Neural Network(CNN)

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