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arXiv 2022年

作者： Wang, Ran Zhao, Yifei Wang, Shipan Du, Kehan Tang, Mojie Li, Yiyao Chen, Qianhe Tao, Hongxi Wang, Yong School of Journalism and Information Communication Huazhong University of Science and Technology China School of Artificial Intelligence and Automation Huazhong University of Science and Technology China School of Computer Science United Kingdom University of Bristol United Kingdom School of Architecture and Urban Planning Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China Computer Science Department University College London United Kingdom School of Computing and Information Systems Singapore Management University Singapore

With the development of social media, various rumors can be easily spread on the Internet and such rumors can have serious negative effects on society. Thus, it has become a critical task for social media platforms to deal with suspected rumors. However, due to the lack of effective tools, it is often difficult for platform administrators to analyze and validate rumors from a large volume of information on a social media platform efficiently. We have worked closely with social media platform administrators for four months to summarize their requirements of identifying and analyzing rumors, and further proposed an interactive visual analytics system, RumorLens, to help them deal with the rumor efficiently and gain an in-depth understanding of the patterns of rumor spreading. RumorLens integrates natural language processing (NLP) and other data processing techniques with visualization techniques to facilitate interactive analysis and validation of suspected rumors. We propose well-coordinated visualizations to provide users with three levels of details of suspected rumors: an overview displays both spatial distribution and temporal evolution of suspected rumors;a projection view leverages a metaphor-based glyph to represent each suspected rumor and further enable users to gain a quick understanding of their overall characteristics and similarity with each other;a propagation view visualizes the dynamic spreading details of a suspected rumor with a novel circular visualization design, and facilitates interactive analysis and validation of rumors in a compact manner. By using a real-world dataset collected from Sina Weibo, one case study with a domain expert is conducted to evaluate RumorLens. The results demonstrated the usefulness and effectiveness of our approach. Copyright © 2022, The Authors. All rights reserved.

关键词： Social networking (online)

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Lock-Free Simulation Algorithm to Enhance the Performance of Sequential and Parallel Devs Simulators in Shared-Memory architectures

SSRN

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SSRN 2024年

作者： Cárdenas, Román Arroba García, Patricia Risco-Martín, José Luis Department of Electronics Engineering Universidad Politécnica de Madrid Avenida Complutense 30 Madrid Madrid28040 Spain Center for Computational Simulation Universidad Politécnica de Madrid Campus de Montegancedo Boadilla del Monte Madrid28660 Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Calle Profesor José García Santesmases 9 Madrid Madrid28040 Spain

This paper presents a new algorithm for the Discrete EVent System Specification (DEVS) formalism that improves the performance of simulating complex systems by reducing the number of iterations through the model components in each simulation step. It also minimizes unnecessary visits to model components by propagating simulation routines only when necessary. Additionally, we provide two parallel versions of this new simulation algorithm that use work-stealing scheduling and avoid locking mechanisms without compromising the validity of the execution in shared-memory architectures. We implemented the proposed algorithms in the xDEVS simulator and evaluated their performance using the DEVStone synthetic benchmark. The results show that the proposed algorithms outperform state-of-the-art alternatives. For computationally intensive models, parallel implementations achieve high parallelism efficiency. Furthermore, they are more resilient to model complexity than the sequential algorithm, showing better performance for complex models even without computational overhead in state transition functions. © 2024, The Authors. All rights reserved.

关键词： Discrete event simulation

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Ultracolor Multiplexing in QR Codes for Data Encryption and Transmission

Ultracolor Multiplexing in QR Codes for Data Encryption and ...

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2024 Frontiers in Optics, FiO 2024

作者： Ignacio-Cerrato, Sara Pacios, David Rodríguez, José Miguel Ezquerro Vázquez-Poletti, José Luis Mariño, María Estefanía Avilés Stravakakis, Konstantinos Di Iorio, Alessio Cesarano, Clemente Schetakis, Nikolaos Optics Department Faculty of Optics and Optometry Universidad Complutense de Madrid Calle Arcos de Jalón 118 Madrid28037 Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain Alma Sistemi Srl Guidonia Rome00012 Italy Section of Mathematics International Telematic University Uninettuno Corso Vittorio Emanuele II 39 Rome Italy Departamento de Lingüística Aplicada a la Ciencia y a la Tecnología Universidad Politécnica de Madrid Calle de José Gutiérrez Abascal 2 Madrid28006 Spain Computational Mechanics and Optimization Laboratory School of Production Engineering and Management Technical University of Crete Chania73100 Greece Quantum Innovation Pc Chania73100 Greece

This paper introduces an innovative encryption method using ultracolor codification via the Prism Algorithm, which effectively encodes large data volumes into images with base64 encoding, demonstrating practical reliability and potential for secure data transmission. © Optica Publishing Group 2024, © 2024 The Author(s)

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States-Based Energy Management System for an EV Hybrid Charging Station with Z-Source Converters

States-Based Energy Management System for an EV Hybrid Charg...

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Power Tech Conference

作者： Enrique González-Rivera Pablo García-Triviño Luis M. Fernández-Ramirez Raúl Sarrias-Mena Juan P. Torreglosa Francisco Jurado Department of Electrical Engineering Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP-023) University of Cadiz Algeciras Spain Department of Engineering in Automation Research Group in Sustainable and Renewable Electrical Technologies (PAIDI-TEP-023) Electronics and Computer Architecture & Networks University of Cadiz Algeciras Spain Electrical Engineering Department University of Huelva Palos de la Frontera Spain Department of Electrical Engineering Research Group in Research and Electrical Technology (PAIDI- TEP-152) University of Jaen Linares Spain

ISBN: (数字)9781665435970

ISBN: (纸本)9781665411738

This work presents a new energy management system (EMS) based on states for a hybrid charging station of electric vehicles (EV). The hybrid charging station is composed of a photovoltaic (PV) system, a complete hydrogen system based on fuel cell (FC), electrolyzer (EZ) and tank as energy storage system (ESS), a battery energy storage system (BES), a grid connection, and six fast charging units, all of them connected to a common MVDC bus through Z-sources converters (ZSC). The states-based EMS is designed to control the power flow among the energy sources of the hybrid charging station. The viability of the EMS is proved under a long-term simulation of 25 years in Simulink by using an EV load profile taken from the Strategy Technology Energy Plan of the EU and real data for the sun irradiance.

关键词： Photovoltaic systems Renewable energy sources Costs Software packages Hydrogen Charging stations Hybrid power systems

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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High energy storage efficiency and large electrocaloric effect in lead-free BaTi0.89Sn0.11O3 ceramic

arXiv

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arXiv 2020年

作者： Merselmiz, Soukaina Hanani, Zouhair Mezzane, Daoud Spreitzer, Matjaz Bradeško, Andraž Fabijan, David Vengust, Damjan Hajji, Lahoucine Abkhar, Zahra Razumnaya, Anna Rožič, Brigita Luk'yanchuk, Igor A. Kutnjak, Zdravko IMED-Lab Cadi Ayyad University Marrakesh40000 Morocco ICMCB University of Bordeaux Pessac33600 France Jozef Stefan Institute Ljubljana1000 Slovenia LPMC University of Picardy Jules Verne Amiens80039 France Physics Faculty Southern Federal University Rostov-on-Don344090 Russia Department of Cybersecurity and Computer Engineering Faculty of Automation and Information Technologies Kyiv National University of Construction and Architecture Kyiv Ukraine

Lead-free BaTi0.89Sn0.11O3 (BTSn) ceramic was elaborated via a solid-state reaction method and its dielectric, ferroelectric, energy storage, electromechanical as well as electrocaloric properties were investigated at 25 kV/cm. Pure perovskite structure was confirmed by X-ray diffraction analysis. The maximum of the dielectric constant was found to be 17390 at 41 °C. The enhanced total energy density, the recovered energy density, and the energy storage efficiency of 92.7 mJ/cm3, 84.4 mJ/cm3, and 91.04%, respectively, were observed at 60 °C, whereas the highest storage efficiency of 95.87 % was obtained at 100 °C. At room temperature, the electromechanical strain and the large-signal piezoelectric coefficient reached a maximum of 0.07 % and 280 pm/V. The large electrocaloric effect of 0.71 K and the electrocaloric responsivity of 0.28 × 10-6 ***/kV at 49 °C under 25 kV/cm were indirectly calculated via Maxwell relation from the ferroelectric polarization P (T, E) that was determined from the P-E hysteresis loops. By exploiting the Landau-Ginzburg-Devonshire (LGD) phenomenological theory, the electrocaloric response was estimated to be of 0.61 K at 50 °C under 25 kV/cm. We conclude that BTSn lead-free ceramic is a promising candidate for potential applications in high-efficiency energy storage devices and solid-state refrigeration technology. © 2020, CC-BY.

关键词： Piezoelectricity

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Deep learning-based instance segmentation for the precise automated quantification of digital breast cancer immunohistochemistry images

arXiv

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arXiv 2023年

作者： Priego-Torres, Blanca Maria Lobato-Delgado, Barbara Atienza-Cuevas, Lidia Sanchez-Morillo, Daniel Biomedical Engineering and Telemedicine Research Group Department of Automation Engineering Electronics and Computer Architecture and Networks School of Engineering University of Cádiz Avda. Universidad de Cádiz 10 Cádiz Puerto Real11510 Spain Hospital Universitario Puerta del Mar Avda Ana de Viya 21 Cádiz11009 Spain Department of Pathology Hospital Universitario Puerta del Mar Avda. Ana de Viya 21 Cádiz11009 Spain

The quantification of biomarkers on immunohistochemistry breast cancer images is essential for defining appropriate therapy for breast cancer patients, as well as for extracting relevant information on disease prognosis. This is an arduous and time-consuming task that may introduce a bias in the results due to intra- and inter-observer variability which could be alleviated by making use of automatic quantification tools. However, this is not a simple processing task given the heterogeneity of breast tumors that results in non-uniformly distributed tumor cells exhibiting different staining colors and intensity, size, shape, and texture, of the nucleus, cytoplasm and membrane. In this research work we demonstrate the feasibility of using a deep learning-based instance segmentation architecture for the automatic quantification of both nuclear and membrane biomarkers applied to IHC-stained slides. We have solved the cumbersome task of training set generation with the design and implementation of a web platform, which has served as a hub for communication and feedback between researchers and pathologists as well as a system for the validation of the automatic image processing models. Through this tool, we have collected annotations over samples of HE, ER and Ki-67 (nuclear biomarkers) and HER2 (membrane biomarker) IHC-stained images. Using the same deep learning network architecture, we have trained two models, so-called nuclei- and membrane-aware segmentation models, which, once successfully validated, have revealed to be a promising method to segment nuclei instances in IHC-stained images. The quantification method proposed in this work has been integrated into the developed web platform and is currently being used as a decision support tool by pathologists. © 2023, CC BY-NC-ND.

关键词： Textures

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Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report

Power Efficient Video Super-Resolution on Mobile NPUs with...

引用

17th European Conference on computer Vision, ECCV 2022

作者： Ignatov, Andrey Timofte, Radu Chiang, Cheng-Ming Kuo, Hsien-Kai Xu, Yu-Syuan Lee, Man-Yu Lu, Allen Cheng, Chia-Ming Chen, Chih-Cheng Yong, Jia-Ying Shuai, Hong-Han Cheng, Wen-Huang Jia, Zhuang Xu, Tianyu Zhang, Yijian Bao, Long Sun, Heng Zhang, Diankai Gao, Si Liu, Shaoli Wu, Biao Zhang, Xiaofeng Zheng, Chengjian Lu, Kaidi Wang, Ning Sun, Xiao Wu, HaoDong Liu, Xuncheng Zhang, Weizhan Yan, Caixia Du, Haipeng Zheng, Qinghua Wang, Qi Chen, Wangdu Duan, Ran Sun, Mengdi Zhu, Dan Chen, Guannan Cho, Hojin Kim, Steve Yue, Shijie Li, Chenghua Zhuge, Zhengyang Chen, Wei Wang, Wenxu Zhou, Yufeng Cai, Xiaochen Cai, Hengxing Xu, Kele Liu, Li Cheng, Zehua Lian, Wenyi Lian, Wenjing Computer Vision Lab ETH Zurich Zürich Switzerland AI Witchlabs Zürich Switzerland University of Wuerzburg Würzburg Germany MediaTek Inc. Hsinchu Taiwan National Yang Ming Chiao Tung University Hsinchu Taiwan Video Algorithm Group Camera Department Xiaomi Inc. Beijing China Audio & Video Technology Platform Department ZTE Corporation Shenzhen China Beijing China School of Computer Science and Technology Xi’an Jiaotong University Xi’an China MIGU Video Co. Ltd. Beijing China BOE Technology Group Co. Ltd. Beijing China GenGenAI Seoul Korea Republic of North China University of Technology Beijing China Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Beijing China 4Paradigm Inc. Beijing China National University of Defense Technology Changsha China University of Oxford Oxford United Kingdom Uppsala University Uppsala Sweden Northeastern University Shenyang China

ISBN: (纸本)9783031250651

Video super-resolution is one of the most popular tasks on mobile devices, being widely used for an automatic improvement of low-bitrate and low-resolution video streams. While numerous solutions have been proposed for this problem, they are usually quite computationally demanding, demonstrating low FPS rates and power efficiency on mobile devices. In this Mobile AI challenge, we address this problem and propose the participants to design an end-to-end real-time video super-resolution solution for mobile NPUs optimized for low energy consumption. The participants were provided with the REDS training dataset containing video sequences for a 4X video upscaling task. The runtime and power efficiency of all models was evaluated on the powerful MediaTek Dimensity 9000 platform with a dedicated AI processing unit capable of accelerating floating-point and quantized neural networks. All proposed solutions are fully compatible with the above NPU, demonstrating an up to 500 FPS rate and 0.2 [Watt/30 FPS] power consumption. A detailed description of all models developed in the challenge is provided in this paper. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Energy utilization

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The Colarado Multistatic FMCW Radar System

The Colarado Multistatic FMCW Radar System

引用

European Conference on Microwave

作者： P.J.F. Swart J. Schier A.J.C. van Gemund W.F. van der Zwan J.P. Karelse G.L. Reijns P. van Genderen L.P. Ligthart H.T. Steenstra Department of Information Technology and Systems International Research Centre for Telecommunications-Transmission and Radar Delft Netherlands Academy of Sciences of the Czech Republic Inst. of Information Theory and Automation Delft University of Technology Dept. of Information Technology and Systems Mekelweg 4 2628 CD Delft The Netherlands Tel.: +31 15 278 1023 Fax: +31 15 278 4046. E-mail: schier@utia.cas.cz Computer Architecture and Digital Techniques (CARDIT) Delft University of Technology Dept. of Information Technology and Systems Mekelweg 4 2628 CD Delft The Netherlands Tel.: +31 15 278 1023 Fax: +31 15 278 4046. E-mail: a.vgemund@et.tudelft.nl Department of Information Technology and Systems Computer Architecture and Digital Techniques (CARDIT) Delft University슠of슠Technology Delft Netherlands

A multstatic frequency-modulated continuous wave (FMCW) radar system is under development for use in the control system of autonomous vehicles. The aim of the system, named Colarado, is the 3D location of obstacles in the surrounding environment. In this paper a laboratory prototype system version, the demonstrator, is described and current results are presented.

关键词： Receiving antennas Transmitting antennas Radar signal processing Radar antennas Voltage-controlled oscillators Spatial resolution Radar theory Vehicles Containers Layout

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Wireless-Friendly Window Position Optimization for RIS-Aided Outdoor-to-Indoor Networks based on Multi-Modal Large Language Model

arXiv

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arXiv 2024年

作者： Hou, Jinbo Qiu, Kehai Zhang, Zitian Yu, Yong Wang, Kezhi Capolongo, Stefano Zhang, Jiliang Li, Zeyang Zhang, Jie The Department of Electronic and Electrical Engineering the University of Sheffield Sheffield United Kingdom The Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom Brunel University London United Kingdom The School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou China The Design & Health Lab Department of Architecture Built Environment and Construction Engineering Politecnico di Milano Italy The Department of Computer Science Brunel University London Middlesex UxbridgeUB8 3PH United Kingdom The State Key Laboratory of Synthetical Automation for Process Industries The College of Information Science and Engineering Northeastern University Shenyang China The Centre for Wireless Innovation Queen’s University of Belfast BelfastBT3 9DT United Kingdom

This paper aims to simultaneously optimize indoor wireless and daylight performance by adjusting the positions of windows and the beam directions of window-deployed reconfigurable intelligent surfaces (RISs) for RIS-aided outdoor-to-indoor (O2I) networks utilizing large language models (LLM) as optimizers. Firstly, we illustrate the wireless and daylight system models of RIS-aided O2I networks and formulate a joint optimization problem to enhance both wireless traffic sum rate and daylight illumination performance. Then, we present a multi-modal LLM-based window optimization (LMWO) framework, accompanied by a prompt construction template to optimize the overall performance in a zero-shot fashion, functioning as both an architect and a wireless network planner. Finally, we analyze the optimization performance of the LMWO framework and the impact of the number of windows, room size, number of RIS units, and daylight factor. Numerical results demonstrate that our proposed LMWO framework can achieve outstanding optimization performance in terms of initial performance, convergence speed, final outcomes, and time complexity, compared with classic optimization methods. The building’s wireless performance can be significantly enhanced while ensuring indoor daylight performance. Copyright © 2024, The Authors. All rights reserved.

关键词： Daylighting

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