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Numerical simulations on self-referential holographic data storage with built-in denoising function by self-referential holographic deep neural network

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Optical Review 2025年 1-12页

作者： Eto, Yuta Tomioka, Rio Takatsu, Taichi Takabayashi, Masanori Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology Wakamatsu Japan

Self-referential holography (SRH), a holographic technique that enables the recording, reading, and control of two-dimensional (2D) patterns using a one-beam geometry, can be applied to holographic data storage (HDS) and optoelectronic deep neural network (OE-DNN). Since both applications are implemented using the same optical system, they can be integrated into a single system. We propose a self-referential HDS (SR-HDS) with a built-in denoising function using a self-referential holographic deep neural network (SR-HDNN), where the quality of reconstructed datapages in HDS can be enhanced using deep neural networks (DNNs) without requiring costly electronic computers for implementation. Numerical simulations are performed to demonstrate the feasibility of the proposed method.

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Zero-Change CMOS Nanophotonics: Converting Foundry Semiconductor Chips to Plasmonic Electro-optic Modulators

Zero-Change CMOS Nanophotonics: Converting Foundry Semicondu...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： ElKabbash, Mohamed Harris, Isaac Trajtenberg-Mills, Sivan Bandyopadhyay, Saumil Chen, Xibi Ibrahim, Mohamed I. Han, Ruonan Englund, Dirk Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

We create nanophotonic devices using CMOS foundry processes where the top metal layers exhibit a plasmonic resonance. By integrating liquid crystals and applying a bias, we measure a 20 nm resonance shift at -700 nm. ... 详细信息

ISBN: (纸本)9781957171258

关键词： Liquid crystals

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A Survey of Cyber Attacks on Cyber Physical Systems:Recent Advances and Challenges

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 784-800页

作者： Wenli Duo MengChu Zhou Abdullah Abusorrah Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China IEEE Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center and Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz University

A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over *** plays a key role in modern industry since it connects physical and cyber *** order to meet ever-changing industrial requirements,its structures and functions are constantly ***,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and *** paper presents a survey of state-of-the-art results of cyber attacks on cyber physical ***,as typical system models are employed to study these systems,time-driven and event-driven systems are ***,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are *** particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and ***,both attack and defense strategies are discussed based on different system *** challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area.

关键词： Attack detection attack strategy cyber attack cyber physical system(CPS) secure control

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Evaluating the Usefulness of Data Mining for Business Process Automation 15

Evaluating the Usefulness of Data Mining for Business Proces...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Zaidi, Taskeen Khurana, Shivam Sharma, Kunal Jayasree, S. Mahajan, Rupali A. Pandey, Megha Karnataka Bangalore India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Department of Mechanical Engineering Vivekananda Global University Jaipur India Department of Science and Humanities Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9798350370249

Information mining can be used for up-to-date operational efficiency and decreased charges for business procedures up to detonation. It allows specific analysis of present datasets, which can be utilized to identify patterns, dependencies, and trends within the data. By uncovering these insights, groups can make knowledgeable selections about optimizing their approaches. Moreover, data mining can leverage artificial intelligence (AI) methods to identify specific behaviors that could require additional motion. The usefulness of statistics mining for process update demotion depends on the available updated statistics and the algorithms' pleasantness. The updated statistics need to be complete and correct. Otherwise, the results can be imprecise. The algorithms used to date must also be better crafted, as the wrong ones may produce misguided or beside-the-point predictions. Up to date, the effectiveness of information mining for procedure au up to detonation, its miles vital updated degree the accuracy of the consequences, up-to-date the cost, time, and labor up to date imposing the hints. Moreover, the impact date is monies-to-deterred up to date, making sure that any adjustments are up-to-date and a natural development in performance. Finally, up-to-date remarks are collected from users to date to ensure the adjustments are proper and beneficial for all stakeholders. ©2024 IEEE.

关键词： Detonation

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Spatiotemporal Control of Nonlinear Effects in Multimode Fibers for Two-Octave High-Peak-Power Femtosecond Tunable Source

Spatiotemporal Control of Nonlinear Effects in Multimode Fib...

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3D Image Acquisition and Display: technology, Perception and Applications, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 - Part of Imaging and Applied Optics Congress 2023

作者： Qiu, Tong Cao, Honghao Liu, Kunzan You, Sixian Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

We developed a two-octave high-peak-power femtosecond tunable source by spatiotemporal control of nonlinear effects in a step-index MMF through a customer-designed fiber shaper. Its application to improve label-free i... 详细信息

ISBN: (纸本)9781957171289

关键词： High power fiber lasers Image quality Multimode fibers Nonlinear effects Optical computing Tissue imaging

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Predicting the Unseen: A Novel Dataset for Hidden Intention Localization in Pre-abnormal Analysis 24

Predicting the Unseen: A Novel Dataset for Hidden Intention ...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Qi, Zehao Zhang, Ruixu Hu, Xinyi Liu, Wenxuan Wang, Zheng National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence Wuhan University Hubei Key Laboratory of Multimedia and Network Communication Engineering School of Computer Science Wuhan China School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China

ISBN: (纸本)9798400706868

Our paper introduces a novel video dataset specifically for Temporal Intention Localization (TIL), aimed at identifying hidden abnormal intention in densely populated and complex environments. Traditional Temporal Action Localization (TAL) frameworks, focusing on overt actions within constrained temporal intervals, often miss subtle pre-abnormal actions that unfold over extended periods. Our dataset comprises 228 videos with 5790 clips, each annotated to capture fine-grained actions within ambiguous temporal boundaries using the Joint-Linear-Assignment methodology. This approach enables detailed analysis of the evolution of abnormal intention over time. To detect subtle, hidden intention, we developed the Intention-Action Fusion module, an creative approach integrating dynamic feature fusion across 11 behavioral subcategories, significantly enhancing the model's ability to discern nuanced intention. This enhancement has led to performance improvements of up to 139% in specific scenarios, dramatically boosting the model's sensitivity and interpretability, crucial for advancing proactive surveillance systems. By pushing the boundaries of technology, our dataset and methodologies foster proactive surveillance systems capable of preemptively identifying potential threats from nuanced behavioral patterns, encouraging further exploration into the complexities of intention beyond observable actions. The dataset is available at https://***/Zzz99999/Hidden-Abnormal-Intention. © 2024 ACM.

关键词： Security systems

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Large Language Models as Evolutionary Optimizers 13

Large Language Models as Evolutionary Optimizers

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Liu, Shengcai Chen, Caishun Qu, Xinghua Tang, Ke Ong, Yew-Soon Southern University of Science and Technology Centre for Frontier Ai Research A∗star Department of Computer Science and Engineering China Centre for Frontier Ai Research A∗star Singapore Tianqiao & Chrissy Chen Institute China Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering China Nanyang Technological University Centre for Frontier Ai Research A∗star College of Computing and Data Science Singapore

ISBN: (纸本)9798350308365

Evolutionary algorithms (EAs) have achieved remarkable success in tackling complex combinatorial optimization problems. However, EAs often demand carefully-designed operators with the aid of domain expertise to achieve satisfactory performance. In this work, we present the first study on large language models (LLMs) as evolutionary combinatorial optimizers. The main advantage is that it requires minimal domain knowledge and human efforts, as well as no additional training of the model. This approach is referred to as LLM-driven EA (LMEA). Specifically, in each generation of the evolutionary search, LMEA instructs the LLM to select parent solutions from current population, and perform crossover and mutation to generate offspring solutions. Then, LMEA evaluates these new solutions and include them into the population for the next generation. LMEA is equipped with a self-adaptation mechanism that controls the temperature of the LLM. This enables it to balance between exploration and exploitation and prevents the search from getting stuck in local optima. We investigate the power of LMEA on the classical traveling salesman problems (TSPs) widely used in combinatorial optimization research. Notably, the results show that LMEA performs competitively to traditional heuristics in finding high-quality solutions on TSP instances with up to 20 nodes. Additionally, we also study the effectiveness of LLM-driven crossover/mutation and the self- adaptation mechanism in evolutionary search. In summary, our results reveal the great potentials of LLMs as evolutionary optimizers for solving combinatorial problems. We hope our research shall inspire future explorations on LLM-driven EAs for complex optimization challenges. © 2024 IEEE.

关键词： Traveling salesman problem

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Intelligent GlucoSense: Innovations in Smart Devices for Personalized Health Monitoring 7

Intelligent GlucoSense: Innovations in Smart Devices for Per...

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7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Nagesh, H.B. Arvind, R. Harish, L. Chethan, L.S. Kumar S, Mohana Maranan, Ramya Acs College of Engineering Electronics and Communication Engineering Karnataka Bangalore560074 India Cmr Institute of Technology Information Science and Engineering Karnataka Bangalore560037 India Pes Institute of Technology and Management Computer Science and Engineering Karnataka Shivamogga577204 India Ramaiah Institute of Technology Computer Science and Engineering Karnataka Bengaluru560054 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350341485

The constant monitoring of glucose levels is crucial for the effective management of diabetes and related conditions. With the advent of advanced technologies, glucose level monitoring systems have evolved to provide accurate and convenient solutions for individuals living with diabetes. The paper presents a comprehensive review of the various technologies and applications employed in glucose level monitoring systems. The earlier method provides an overview of the conventional methods for glucose monitoring, such as fingerstick blood glucose meters. While widely used, these methods have limitations in terms of invasiveness, discomfort, and the inability to capture continuous glucose data. To address these limitations, the proposed method discusses the emergence of non-invasive and minimally invasive techniques. system. The paper explores the integration of glucose level monitoring systems with the Blynk app to monitor the data remotely using smartphone applications and wearable devices which may incorporate the glucose and Heart Rate (HR) sensors and an OLED display for user interface. The benefits of integrations, such as enhanced user experience, remote monitoring, and data accessibility, are highlighted. The proposed wearable devices have paved the way for more accurate, convenient, and personalized glucose monitoring solutions, ultimately empowering individuals with diabetes to manage their condition effectively and lead healthier lives. © 2023 IEEE.

关键词： Glucose

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Bamboo Forest Growth Optimization Algorithm for Night Image Enhancement 15th

Bamboo Forest Growth Optimization Algorithm for Night Image...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Shi, Hao-Jie Pan, Jeng-Shyang Chu, Shu-Chuan Kong, Lingping Snášel, Václav College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

ISBN: (纸本)9789819700677

The Bamboo Forest Growth Optimization(BFGO) algorithm is an algorithm proposed by the growth law of bamboo forest, which has the advantages of fast convergence and not easily falling into local optimum. In this paper we have experimented the BFGO with several other population intelligence optimization algorithms on 23 benchmark test functions and proved its superiority. Also we apply the bamboo forest optimization algorithm to nighttime image enhancement in this paper, and the algorithm achieves better results on this application. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Dynamic Multihead Attention for Enhancing Neural Machine Translation Performance 5th

Dynamic Multihead Attention for Enhancing Neural Machine Tra...

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5th International Conference on Trends in Computational and Cognitive engineering, TCCE 2023

作者： Pandey, Mrinal Pandey, Rashmikiran Nazarov, Alexey Department of Radio Engineering and Cybernetics Moscow Institute of Physics and Technology Moscow Russia Federal Research Center Computer Science and Control Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9789819719228

The research paper delves into the realm of "Attention-Based Neural Machine Translation for Multilingual Communication", focusing on the revolutionary impact of attention mechanisms in enhancing cross-language understanding. Through dynamic allocation of focus to pertinent segments of source sequences, attention mechanisms have significantly improved the precision and coherence of translations, playing a pivotal role in multilingual communication. The paper underscores the importance of this technology in addressing the complexities of aligning words across diverse languages and maintaining grammatical accuracy, crucial for effective cross-lingual interactions. The study also presents a visual flowchart outlining the core components of attention-based NMT, encompassing the encoder, decoder, and attention context. Moreover, the paper extrapolates the future trajectory of attention-based NMT, identifying areas for continued exploration and innovation. researchers are urged to refine attention models to cater to intricate linguistic structures, potentially unveiling novel mechanisms that strike a balance between capturing long-range dependencies and computational efficiency. Furthermore, the paper anticipates the integration of attention-based NMT with multimodal inputs, unlocking the potential for comprehensive communication by incorporating visual and auditory cues. These advancements hold the promise of revolutionising multilingual communication, shaping a future where language barriers are transcended in various domains, from global diplomacy to education and beyond. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Neural machine translation

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