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arXiv 2024年

作者： He, Botao Wang, Ze Zhou, Yuan Chen, Jingxi Singh, Chahat Deep Li, Haojia Gao, Yuman Shen, Shaojie Wang, Kaiwei Cao, Yanjun Xu, Chao Aloimonos, Yiannis Gao, Fei Fermüller, Cornelia Department of Computer Science University of Maryland College ParkMD20742 United States College of Control Science and Engineering Zhejiang University Hangzhou China Huzhou Institute of Zhejiang University Huzhou China College of Optical Science and Engineering Zhejiang University Hangzhou China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Institute for Advance Computer Studies University of Maryland College ParkMD20742 United States Institute for Systems Research University of Maryland College ParkMD20742 United States

Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and texture. However, the event camera fails to capture object edges that are parallel to the camera motion. This is a problem intrinsic to the sensor and therefore challenging to solve algorithmically. Human vision deals with perceptual fading using the active mechanism of small involuntary eye movements - the most prominent ones called microsaccades. By moving the eyes constantly and slightly during fixation, microsaccades can substantially maintain texture stability and persistence. Inspired by microsaccades, we designed an event-based perception system capable of simultaneously maintaining low reaction time and stable texture. In this design, a rotating wedge prism was mounted in front of the aperture of an event camera to redirect light and trigger events. The geometrical optics of the rotating wedge prism allows for algorithmic compensation of the additional rotational motion, resulting in a stable texture appearance and high informational output independent of external motion. The hardware device and software solution are integrated into a system, which we call Artificial MIcrosaccade-enhanced EVent camera (AMI-EV). Benchmark comparisons validate the superior data quality of AMI-EV recordings in scenarios where both standard cameras and event cameras fail to deliver. Various real-world experiments demonstrate the potential of the system to facilitate robotics perception both for low-level and high-level vision tasks. © 2024, CC BY.

关键词： Cameras

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The Impact of the Digital Transformation of Education on Literacy

The Impact of the Digital Transformation of Education on Lit...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Imre Farkas Attila Kovari Mónika Rajcsanyi-Molnar Department of Computer Systems and Control Technology Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Economics and Management Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills.

关键词： Power engineering Epidemics Navigation Knowledge acquisition Digital transformation Education Information age Digital intelligence Cultural differences Problem-solving

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A Rolling Horizon Game Considering Network Effect in Cluster Forming for Dynamic Resilient Multiagent Systems

arXiv

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arXiv 2023年

作者： Nugraha, Yurid Cetinkaya, Ahmet Hayakawa, Tomohisa Ishii, Hideaki Zhu, Quanyan Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan Department of Functional Control Systems Shibaura Institute of Technology Tokyo135-8548 Japan Department of Computer Science Tokyo Insitute of Technology Yokohama226-8502 Japan Department of Electrical and Computer Engineering New York University BrooklynNY11201 United States

A two-player game-theoretic problem on resilient graphs in a multiagent consensus setting is formulated. An attacker is capable to disable some of the edges of the network with the objective to divide the agents into clusters by emitting jamming signals while, in response, the defender recovers some of the edges by increasing the transmission power for the communication signals. Specifically, we consider repeated games between the attacker and the defender where the optimal strategies for the two players are derived in a rolling horizon fashion based on utility functions that take both the agents’ states and the sizes of clusters (known as network effect) into account. The players’ actions at each discrete-time step are constrained by their energy for transmissions of the signals, with a less strict constraint for the attacker. Necessary conditions and sufficient conditions of agent consensus are derived, which are influenced by the energy constraints. The number of clusters of agents at infinite time in the face of attacks and recoveries are also characterized. Simulation results are provided to demonstrate the effects of players’ actions on the cluster forming and to illustrate the players’ performance for different horizon parameters. © 2023, CC BY.

关键词： Game theory

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Study on Degradation of Benzo[a]pyrene in Marine Environment by Chlorella vulgaris LH-1 with Heterotrophic Ability 44

Study on Degradation of Benzo[a]pyrene in Marine Environment...

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44th AMOP Technical Seminar on Environmental Contamination and Response 2022

作者： Chen, Qingguo Song, Zhao Chen, Yu Zhu, Baikang Liu, Mei Li, Yijing Chen, Zhi Zhejiang Provincial Key Laboratory of Petrochemical Pollution Control Zhejiang Ocean University Zhoushan China School of Marine Science and Technology Zhejiang Ocean University Zhoushan China Department of Building Civil and Environmental Engineering Faculty of Engineering and Computer Sciences Concordia University MontrealQC Canada

After long-term weathering, the most toxic components of residual spilled oil in seawater are polycyclic aromatic hydrocarbons. Benzo[a]pyrene (BaP) is a typical polycyclic aromatic hydrocarbon with high molecular weight, wide distribution, stable properties, and strong carcinogenicity in marine environment. Marine microalgae play an important role in the removal of BaP. Previous studies have mainly focused on the photodegradation of BaP by microalga. However, there are few research on microalgae with heterotrophic ability to degrade BaP. In this study, a microalga, Chlorella vulgaris (C. vulgaris) LH-1, with heterotrophic ability to degrade BaP was studied, the effect of BaP concentration on microalgae growth was explored, and the possible degradation mechanism of BaP by this kind of microalgae was proposed. The results showed that low concentration BaP (-1) had less obvious influence on the growth of C. vulgaris under the mixotrophic condition (with illumination), but a higher concentration BaP (＞ 5 mg L-1) had a significant inhibitory effect on the growth of this microalgae. Under heterotrophic cultivation (without illumination), low concentration BaP (-1) promoted the growth of C. vulgaris LH-1, while high concentration BaP (＞20 mg L-1) led to inhibit the growth of this microalga significantly. The degradation rates of mixotrophic and heterotrophic C. vulgaris LH-1 were 62.56~74.13%, and 52.07~71.67%, respectively, when BaP concentration range from 0.5 to 2 mg/L. Microalgae RNA transcriptome sequencing analysis showed that the gene expression of functional enzyme of C. Vulgaris LH-1 such as phenol 2-monooxygenase activity, protocatechuate 3,4-dioxygenase activity, catechol 1,2-dioxygenase activity, styrene degradation, and benzoate degradation were up-regulated in the process of BaP degradation. Based on the results of metabolites detected by high performance liquid chromatography/ quadruple time-of-flight mass spectrometry (HPLC/ Q-TOF), C. Vulgaris LH-1 may de

关键词： Degradation

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The Emergence of Artificial Intelligence in Education and its Impact on Individual Literacy in Higher Education

The Emergence of Artificial Intelligence in Education and it...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Imre Farkas Attila Kovari Mónika Rajcsanyi-Molnar Department of Computer Systems and Control Technology Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Institute of Electronics and Communication Systems Kandó Kalmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Economics and Management Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

In the last three years, a new partner has emerged for teachers and educators in the field of education. The mushrooming of applications based on large language models has greatly shaped the educational development fields of the present era. The use of various AI applications has become commonplace among students and teachers alike. Many questions are being raised by researchers in this field. What does the rapid development of AI applications bring to the field of pedagogy? Should the products of such applications be compared with human performance? The form presented in this thesis seeks to answer similar questions. What is the impact of frequent use of these applications on the literacy level of individuals? In which areas do students tend to use these applications? The results indicate that half of the students believe their literacy levels will decrease with the mass emergence of AI applications, while 36% feel it will not change. However, 88 % of students have already dealt with AI-based applications, with 64 % using them several times or more, suggesting a high level of integration into their educational processes.

关键词： Ethics Power engineering Large language models Education Collaboration Learning (artificial intelligence) Reliability Artificial intelligence Monitoring Guidelines

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H∞ Delayed Filtering of Markov Jump Fuzzy Systems in Consumer Electronics: Input–Output Analysis

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IEEE Transactions on Consumer Electronics 2025年

作者： Aslam, Muhammad Shamrooz Bilal, Hazrat Chang, Wen-Jer Kumar, Neeraj Khan, Izaz Ahmad Vasilakos, Athanasios V. China University of Mining and Technology Artificial Intelligence Research Institute Xuzhou221110 China College of Mechatronics and Control Engineering College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Marine Engineering Keelung202 Taiwan Thapar University Patiala India Bacha Khan University Charsadda Department of Computer Science Pakistan Grimstad Norway

This article investigates the design of robust H∞ filters for Takagi–Sugeno (T–S) fuzzy systems with time-varying delays, with a critical challenge in many consumer electronics applications. We extend existing research by incorporating Markovian jump parameters to model system uncertainties and considering internal–like time–varying delays, which are prevalent in real-world scenarios such as wireless communication and networked control systems in consumer devices. To address the complexities introduced by time-varying delays, we employ a three-term approximation model that more accurately captures the system dynamics compared to traditional approaches. Furthermore, we incorporate the time derivative of the membership functions (MFs) into the filter design, and its impact on system stability and performance. To ensure filter stability, we derive novel stability conditions based on the mode–dependent Lyapunov-Krasovskii functional approach, incorporating constraints on the higher bounds of the MF time derivatives. Leveraging the small–gain theorem with scaling techniques, we propose the design of both full-order and reduced-order H∞ filters, expressed in terms of linear matrix inequalities (LMIs). These LMI–based solutions provide a systematic and computationally efficient approach for filter synthesis. Finally, we validate the effectiveness of our proposed filtering strategies through illustrative examples drawn from relevant consumer electronics applications, such as noise cancellation in audio devices, image stabilization in cameras, and vibration suppression in wearable devices. The results demonstrate the enhanced robustness and performance of the proposed filters in the presence of time-varying delays and uncertainties. © 1975-2011 IEEE.

关键词： Membership functions

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Individually-guided Evolutionary Algorithm for Solving Multi-task Optimization Problems

Individually-guided Evolutionary Algorithm for Solving Multi...

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IEEE International Conference on Networking, Sensing and control

作者： XiaoLing Wang Qi Kang MengChu Zhou Department of Control Science and Engineering Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark USA

ISBN: (纸本)9781665472449

Multi-task optimization (MTO) is a novel emerging evolutionary computation paradigm that is used for solving multiple optimization tasks concurrently. Most MTO algorithms limit each individual to one task, and thus weaken the performance of information exchange. To address this issue and improve the efficiency of knowledge transfer, this work proposes an efficient MTO framework named individually-guided multi-task optimization (IMTO). It divides evolutions into vertical and horizontal ones. To further improve the efficiency of knowledge transfer, a partial individuals' learning scheme is used to choose suitable individuals to learn from other tasks. Experimental results show its superior advantages over the multifactorial evolutionary algorithm and its variants.

关键词： Focusing Evolutionary computation Multitasking Sensors Task analysis Optimization Knowledge transfer

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NLP4: An Architecture for Intent-Driven Data Plane Programmability

NLP4: An Architecture for Intent-Driven Data Plane Programma...

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IEEE Conference on Network Softwarization (NetSoft)

作者： Antonino Angi Alessio Sacco Flavio Esposito Guido Marchetto Alexander Clemm Department of Control and Computer Engineering Politecnico di Torino Italy Computer Science Department Saint Louis University USA Futurewei Inc. USA

ISBN: (数字)9781665406949

ISBN: (纸本)9781665406956

Translating high-level policies to lower-level network rules is one of the main goals of control or data plane network programmability. To further abstract requirements and propel automation in networking, several industries have proposed the paradigm of “network intent”. However, the translation from intents to low-level policies is considered critical to program data planes and other network elements, especially when dealing with P4-enabled switches. In this paper, we present NLP4, an architecture that helps translate intents, in the form of human language, into data-plane programs, in the form of P4 rules. In particular, NLP4 uses Natural Language Processing (NLP) techniques to translate high-level human-language intents, a MultiLayer Perceptron (MLP) model for processing the NLP output and converting it into mid-level policy. An API then uses this information, which separates the intent from the network to generate commands readable by P4-enabled switches. Our initial prototype on a network emulator validates our architecture for a specific case: load profiling, demonstrating how even users with limited P4 expertise may customize their networks by merely specifying intents.

关键词： Industries Automation Conferences Prototypes Multilayer perceptrons Propulsion Natural language processing

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On the Impact of Noisy Labels on Supervised Classification Models 23rd

On the Impact of Noisy Labels on Supervised Classificatio...

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23rd International Conference on Computational science, ICCS 2023

作者： Dubel, Rafal Wijata, Agata M. Nalepa, Jakub Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Faculty of Biomedical Engineering Silesian University of Technology Roosevelta 40 Zabrze41-800 Poland KP Labs Konarskiego 18C Gliwice44-100 Poland

ISBN: (纸本)9783031360206

The amount of data generated daily grows tremendously in virtually all domains of science and industry, and its efficient storage, processing and analysis pose significant practical challenges nowadays. To automate the process of extracting useful insights from raw data, numerous supervised machine learning algorithms have been researched so far. They benefit from annotated training sets which are fed to the training routine which elaborates a model that is further deployed for a specific task. The process of capturing real-world data may lead to acquring noisy observations, ultimately affecting the models trained from such data. The impact of the label noise is, however, under-researched, and the robustness of classic learners against such noise remains unclear. We tackle this research gap and not only thoroughly investigate the classification capabilities of an array of widely-adopted machine learning models over a variety of contamination scenarios, but also suggest new metrics that could be utilized to quantify such models’ robustness. Our extensive computational experiments shed more light on the impact of training set contamination on the operational behavior of supervised learners. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Digital storage

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Deciphering Modern Customer Loyalty: A Machine Learning Approach

Deciphering Modern Customer Loyalty: A Machine Learning Appr...

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International Conference on Internet of Things and Machine Learning, IoTML 2023

作者： Li, Kechen Xu, Chang Zhao, Zheyuan Zhu, Mengyu Cui, Xiangxuan Xu, Shurui Zou, Jichen Nantong Normal College Nantong China Ulink College of Suzhou industrial Park Suzhou China Jiangsu Lincheng Technology Co. Ltd. Nantong China School of computer science and technology China University of Mining and Technology Xuzhou China Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9781510671805

In the contemporary retail sector, deciphering customer behavior is crucial for businesses vying for a competitive advantage. While customer loyalty has conventionally been gauged through parameters such as repeat purchases and promotional response, the merging of technology, media, and commerce has necessitated a reevaluation of these benchmarks. This study recognizes the inadequacy of solely relying on traditional transactional data to evaluate loyalty. Utilizing Machine Learning (ML), we crafted a novel model to predict customer loyalty, taking into account a plethora of modern factors, including online behavior and social media interactions. This research leveraged a diverse dataset and sophisticated ML algorithms to identify subtle patterns and relationships. Key findings include the significance of online behavior in loyalty prediction, the emerging role of social media interactions, and the nuanced influence of device preferences on brand loyalty. Notably, this manuscript offers a pioneering ML model that accurately reflects the complexities of the modern retail landscape, providing a valuable tool for businesses seeking to foster enduring customer relationships. © 2023 SPIE.

关键词： Forecasting

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