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eLight 2024年第1期4卷 251-261页

作者： Ze‑Yu Wang Zhou Zhou Han Zhang Yang Wei Hong‑Guan Yu Wei Hu Wei Chen Hai‑Tao Dai Ling‑Ling Ma Cheng‑Wei Qiu Yan‑Qing Lu National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and ManipulationCollaborative Innovation Center of Advanced MicrostructuresCollege of Engineering and Applied SciencesNanjing UniversityNanjing 210023China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology School of ScienceTianjin UniversityTianjin 300072China

Vectorial optics with fine inhomogeneous polarization control are highly *** have been captivated a promising candidate,but their static post-fabrication geometry largely limits the dynamic *** crystal(LC)is usually employed as an additional index-changing layer together with ***,most of the reported LCs only impart a varying but uniform phase on top of that from the metasurface,which we term“scalar”LC ***,we pixelate a single-layer LC to display versatile and tunable vectorial holography,in which the polarization and amplitude could be arbitrarily and independently controlled at varying spatial ***,the subtle and vectorial LC-holography highlights the broadband and electrically-switchable *** vectorial LC holography reveals significant opportunities for advanced cryptography,super-resolution imaging,and many other applications.

关键词： Liquid crystals Vectorial optics Holography

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Multimode amplitude squeezing through cascaded nonlinear processes

Multimode amplitude squeezing through cascaded nonlinear pro...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Pontula, Sahil Salamin, Yannick Soljacic, Marin Department of Physics MIT CambridgeMA02139 United States Department of Electrical Engineering and Computer Science MIT 02139 CambridgeMA United States Research Laboratory of Electronics MIT CambridgeMA02139 United States

We show how engineering a multimode nonlinear cavity with cascaded three wave mixing processes creates significant intracavity and output amplitude noise squeezing over 10 dB below the shot noise limit for multiple fr... 详细信息

ISBN: (纸本)9781957171395

关键词： Nonlinear optics

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Analyzing Fitts' Law using Offline and Online Optimal Control with Motor Noise

arXiv

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arXiv 2024年

作者： Bridges, Riley Parham, Ethan Li, Jing Shuang The Department of Electrical Engineering and Computer Science Department of Mechanical Engineering The University of Michigan United States The Department of Electrical Engineering and Computer Science The University of Michigan United States

The cause of the speed-accuracy tradeoff (typically quantified via Fitts' Law) is a debated topic of interest in motor neuroscience, and is commonly studied using tools from control theory. Two prominent theories involve the presence of signal dependent motor noise and planning variability - these factors are generally incorporated separately. In this work, we study how well the simultaneous presence of both factors explains the speed-accuracy tradeoff. A human arm reaching model is developed with bio-realistic signal dependent motor noise, and a Gaussian noise model is used to deterministically approximate the motor noise. Both offline trajectory optimization and online model predictive control are used to simulate the planning and execution of several different reaching tasks with varying target sizes and movement durations. These reaching trajectories are then compared to experimental human reaching data, revealing that both models produce behavior consistent with humans, and the speed-accuracy tradeoff is present in both online and offline control. These results suggest the speed-accuracy tradeoff is likely caused by a combination of these two factors, and also that it plays a role in both offline and online computation. Copyright © 2024, The Authors. All rights reserved.

关键词： Predictive control systems

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CHALLENGES AND CONCEPT FOR AN INTEROPERABLE DIGITAL TWIN ARCHITECTURE FOR PV-INTEGRATED HEATING NETWORKS

CHALLENGES AND CONCEPT FOR AN INTEROPERABLE DIGITAL TWIN ARC...

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2023 ISES Solar World Congress, SWC 2023

作者： Paredes, Theo Papadimitriou, Melachroinos Timoudas, Thomas Ohlson Peng, Zeng Wang, Qian KTH Royal Institute of Technology Department of Civil and Architectural Engineering Stockholm Sweden RISE Research Institutes of Sweden Department of Computer Science Stockholm Sweden University of Toulouse IMT Mines Albi Albi France University of Thessally Department of Electrical and Computer Engineering Volos Greece

ISBN: (纸本)9783982040899

Existing data-driven approaches are not always supported, or only partly implemented, by existing tools, platforms, and services. The study focuses on proposing a novel, theoretical and general model to describe the heating network of buildings. This study will consolidate and abstract access to standardized interfaces, using a transparent interoperability mechanism, the "meta" interface, supporting translation modules to translate from different components or hardware that are commonly used in current heating networks of buildings in Europe. The ICT architecture will be based on state-of-the-art digital twin technologies and methodologies, offering a unified ecosystem for orchestrated deployment of different input/output configurations, and data flow and energy exchanges. This study will further validate the reference ICT architecture using data-driven approaches, applied in a use case that could be considered a typical low-temperature district heating network. © 2023. The Authors.

关键词： District heating

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Understanding Cybercrime: A Study of Malware Analysis, Phishing Attacks, and Sentiment Trends 3

Understanding Cybercrime: A Study of Malware Analysis, Phish...

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3rd International Conference on Intelligent and Innovative Technologies in Computing, electrical and Electronics, IITCEE 2025

作者： Kumaran, U. Sreeraag, G. Narendran, Advik Meena, V.P. Gupta, Sushil Kumar Appaji, Abhishek Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bangalore India National Institute of Technology Department of Electrical Engineering Jharkhand Jamshedpur831014 India Bms College of Engineering Department of Medical Electronics Engineering Bangalore India

ISBN: (纸本)9798331515911

With the rapid evolution of computer systems and technologies, individuals face an increasing threat of cybercrime. This research explores the changing landscape of cybercrime by focusing on three key areas: malware analysis, phishing attack analysis, and sentiment analysis. The study aims to identify malware strategies for evading detection and analyze the prevalence of spyware by examining diverse malware samples. Additionally, trend analysis highlights the rising complexity and frequency of phishing attacks, with a notable shift toward targeting reputable platforms. Sentiment analysis of media headlines surrounding data breaches uncovers a paradox: while concerns about cybersecurity remain, there is a growing confidence in the ability to manage cybersecurity crises. These findings provide insights into emerging threats and evolving public perceptions, offering a comprehensive understanding of the current cyber- crime landscape. © 2025 IEEE.

关键词： Phishing

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Practical aberration correction using deep transfer learning with limited experimental data

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Optics Express 2025年第6期33卷 14431-14444页

作者： Kok, Yong En Bentley, Alexander Parkes, Andrew J. Somekh, Michael G. Wright, Amanda J. Pound, Michael P. University of Nottingham School of Computer Science NottinghamNG8 1BB United Kingdom Optics and Photonics Group Department of Electrical and Electronic Engineering University of Nottingham NottinghamNG7 2RD United Kingdom Research Center for Humanoid Sensing Zhejiang Laboratory Hangzhou3111100 China

Adaptive optics is a technique for correcting aberrations and improving image quality. When adaptive optics was first used in microscopy, it was common to rely on iterative approaches to determine the aberrations present. It is advantageous to avoid iteration, and therefore there has been a shift to deep learning for aberration prediction. However, issues remain regarding the practicalities of machine learning for adaptive optics, an important one being the requirement for a large training dataset. Here, we explore transfer learning to overcome this need for data by pre-training a network on a large simulated dataset and fine-tuning it with reduced experimental data for application in an experimental setting. We demonstrate that the pre-trained network can make noticeable improvements with fine-tuning on just 24 experimental samples. To further enhance practicality, we significantly extend the range of aberrations present, predicting up to 25 Zernike modes with each coefficient ranging from −1 to 1, and perform a thorough analysis of the type and magnitude of phase-diversity required in the input data for a successful network. Our approach demonstrates substantial aberration reduction on experimental data for 10 Zernike modes, with an average 73% decrease in RMS wavefront error from 1.81 to 0.48 rad when correction is applied. This method achieves complete experimental image capture and aberration inference at rates comparable to the image acquisition time of a typical laser scanning microscope. Additionally, we consider the benefits of further improvements via an iterative step. As such, this work addresses some of the key practical hurdles that remain in the use of deep learning for aberration prediction and correction. © 2025 Optica Publishing Group (formerly OSA). All rights reserved.

关键词： Adaptive optics

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Recognition of Fire Situation Using Graph Convolutional Network Model 15th

Recognition of Fire Situation Using Graph Convolutional Netw...

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15th International Conference on computer science and its Applications, CSA 2023 and 17th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2023

作者： Kim, Si Jin Park, Ji Su Kang, Jungho Shon, Jin Gon Advanced Convergence Technology Laboratory Korea National Open University Seoul Korea Republic of Department of Computer Science and Engineering Jeonju University Jeonju-Si Korea Republic of Department of Software Engineering Baewha Woman University Seoul Korea Republic of Department of Computer Science Korea National Open University Seoul Korea Republic of

ISBN: (纸本)9789819724468

Fires cause a lot of casualties and economic losses. In order to prevent fire accidents in advance, it is necessary to find out the cause of the fire. Existing fire alarm systems detected fires with temperature, smoke, and flame sensors, but could not distinguish the cause of the fire. In this paper, to solve this problem, the recognition of fire situation was tested using the GCN model. The fire dataset used in the experiment is a fire dataset composed of causes such as boxes, clothing, and electricity. The accuracy of 93.44% was confirmed as a result of the learning experiment with the GCN model, a graph-based deep learning model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Premixed flames

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Using Artificial Intelligence Techniques in Law Enforcement: A Survey 25

Using Artificial Intelligence Techniques in Law Enforcement:...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Al-Shaikh, Ala'a Alalfi, Ashraf Hasan Al-Nsour, Esam Y. A. Afaneh, Suha Samara, Ghassan Alqawasmi, Khaled Al-Milli, Nabeel Khouj, Mohammed Salem, Amer Abu Zarqa University Department of Cybersecurity Zarqa Jordan Zarqa University Department of Computer Science Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

Integration of Artificial Intelligence (AI) with law enforcement has improved humane safety and crime prevention. It offers numerous applications, including predictive policing, facial recognition systems, natural language processing, and algorithmic decision-making tools, which can improve crime prevention and resolution. However, the employment of AI creates ethical problems concerning privacy, bias, and accountability. Addressing these challenges is vital to guarantee AI applications conform with legal and ethical standards, encouraging public trust. This survey paper reviews some of the tools and techniques of AI used in law enforcement (Criminal Identification, Virtual Crime Scene Reconstruction, Automated License Plate Recognition (ALPR), Natural Language Processing (NLP), Gunshot Detection Systems, Data-driven Policing Strategies), and explains the challenges, and mentions some opinions regarding this use. © 2024 IEEE.

关键词： c Artificial Intelligence law enforcement

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Transfer Learning-Assisted DementiaNet: A Four Layer Deep CNN for Accurate Alzheimer’s Disease Detection from MRI Images 16th

Transfer Learning-Assisted DementiaNet: A Four Layer Deep CN...

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16th International Conference on Brain Informatics, BI 2023

作者： Umme Habiba, Sultana Debnath, Tanoy Islam, Md. Khairul Nahar, Lutfun Shahadat Hossain, Mohammad Basnin, Nanziba Andersson, Karl Khulna University of Engineering & Technology Khulna Bangladesh Department of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Computer Science and Engineering University of Chittagong Chittagong Bangladesh Leeds Beckett University Leeds United Kingdom Pervasive and Mobile Computing Laboratory Luleå University of Technology Luleå Sweden

ISBN: (纸本)9783031430749

Alzheimer’s disease is the most common type of dementia and the sixth highest cause of mortality among people over 65. Also, according to statistics, the number of deaths from Alzheimer’s disease has increased dramatically. As a result, early detection of Alzheimer’s disease can improve patient survival chances. Machine learning methods using magnetic resonance imaging have been utilized in the diagnosis of Alzheimer’s disease to help clinicians and speed up the procedure. This research mainly focuses on Alzheimer’s disease detection to overcome previous limitations. We use a publicly available dataset which contains 6400 MRI images. In order to train our dataset, we employ our suggested model, "DementiaNet", using "EfficientNet" as a feature extractor and a Deep CNN as a classifier. In order to capture all the features, this framework uses a small number of convolutional layers, which improves the effectiveness of feature learning and results in a more accurate and reliable output. In addition, to address the issue of data imbalance, we apply data augmentation to enhance the size of the minority class by considering four stages of dementia. Also, in this study, we take advantage of the transfer learning approach with the attachment of "EfficientNet", which allows our model to easily solve the overfitting problem and also extract all the features in a effective way. Finally, we compare our proposed models with those reported in the literature. Our experimental results indicate that our "DementiaNet" model achieve an overall classification accuracy of 97% to detect Alzheimer from brain MRI images, exceeding all other state-of-the-art models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Magnetic resonance imaging

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Virtuous, multi-level integration of research and education within the project "european Digital Dynamic Mapping" (EDDY) Excellent applied research as an enabler for excellent education in the context of Project-Based Learning in Higher Education Institutions

Virtuous, multi-level integration of research and education ...

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2023 Designing Futures: Zukunfte gestalten, INFORMATIK 2023 - 2023 Designing Futures: Shaping the Future, INFORMATIK 2023

作者： Rettig, Rasmus Weltz, Maximilian Hamburg University of Applied Sciences Faculty of Engineering and Computer Science Department of Information and Electrical Engineering Berliner Tor 7 Hamburg20099 Germany

ISBN: (纸本)9783885797319

Project-and Problem-Based Learning has been subject to research and implementation in engineering and computer science curricula for about the last 20 years. However, the projects and problems focused on in education have hardly been questioned for their relevance and effect. Considering current global and financial challenges, the authors propose to revise project-and problem-based approaches in education in the context of relevance and excellence in applied research. Besides coping with current cost-cutting, existing control mechanisms could ensure both relevance and excellence. Example projects based on more than 10 years of hands-on experience in Project-Based Learning in the context of externally funded research, for various classroom situations are included. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Autonomous vehicles

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