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Dynamic control and manipulation of near-fields using direct feedback

Light(Science & Applications) 2024年第12期13卷 3151-3157页

作者： Jacob Kher-Aldeen Kobi Cohen Stav Lotan Kobi Frischwasser Bergin Gjonaj Shai Tsesses Guy Bartal The Andrew&Erna Viterbi Faculty of Electrical&Computer Engineering Technion—Israel Institute of TechnologyHaifa 3200003Israel Department of Physical Engineering Polytechnic University of Tirana—Faculty of Physical&Math EngineeringTirana 1000Albania Faculty of Medical Sciences Albanian UniversityDurrës StreetTirana 1000Albania Department of Physics MIT—Harvard Center for Ultracold Atoms and Research Laboratory of ElectronicsMassachusetts Institute of TechnologyCambridgeMAUSA

Shaping and controlling electromagnetic fields at the nanoscale is vital for advancing efficient and compact devices used in optical communications,sensing and metrology,as well as for the exploration of fundamental properties of light-matter interaction and optical ***-time feedback for active control over light can provide a significant advantage in these endeavors,compensating for ever-changing experimental conditions and inherent or accumulated device *** nearfield microscopy,being slow in essence,cannot provide such a real-time feedback that was thus far possible only by scattering-based ***,we present active control over nanophotonic near-fields with direct feedback facilitated by real-time near-field *** use far-field wavefront shaping to control nanophotonic patterns in surface waves,demonstrating translation and splitting of near-field focal spots at nanometer-scale precision,active toggling of different near-field angular momenta and correction of patterns damaged by structural defects using feedback enabled by the real-time *** ability to simultaneously shape and observe nanophotonic fields can significantly impact various applications such as nanoscale optical manipulation,optical addressing of integrated quantum emitters and near-field adaptive optics.

关键词： scattering metrology feedback

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Shadow Extraction and Elimination of Moving Vehicles for Tracking Vehicles

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computers, Materials & Continua 2023年第11期77卷 2009-2030页

作者： Kalpesh Jadav Vishal Sorathiya Walid El-Shafai Torki Altameem Moustafa HAly Vipul Vekariya Kawsar Ahmed Francis MBui Department of Electronics&Communication Engineering Faculty of Engineering and TechnologyParul Institute of Engineering and TechnologyParul UniversityVadodaraGujarat391760India Department Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Community CollegeKing Saud UniversityRiyadh11362Saudi Arabia Electronics and Communications Engineering Department College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt Department of Computer Engineering Faculty of Engineering and TechnologyParul Institute of Engineering and TechnologyParul UniversityVadodaraGujarat391760India Department of Electrical and Computer Engineering University of Saskatchewan57 Campus DriveSaskatoonSK S7N5A9Canada

Shadow extraction and elimination is essential for intelligent transportation systems(ITS)in vehicle tracking *** shadow is the source of error for vehicle detection,which causes misclassification of vehicles and a high false alarm rate in the research of vehicle counting,vehicle detection,vehicle tracking,and *** of the existing research is on shadow extraction of moving vehicles in high intensity and on standard datasets,but the process of extracting shadows from moving vehicles in low light of real scenes is *** real scenes of vehicles dataset are generated by self on the Vadodara–Mumbai highway during periods of poor illumination for shadow extraction of moving vehicles to address the above *** paper offers a robust shadow extraction of moving vehicles and its elimination for vehicle *** method is distributed into two phases:In the first phase,we extract foreground regions using a mixture of Gaussian model,and then in the second phase,with the help of the Gamma correction,intensity ratio,negative transformation,and a combination of Gaussian filters,we locate and remove the shadow region from the foreground *** to the outcomes proposed method with outcomes of an existing method,the suggested method achieves an average true negative rate of above 90%,a shadow detection rate SDR(η%),and a shadow discrimination rate SDR(ξ%)of 80%.Hence,the suggested method is more appropriate for moving shadow detection in real scenes.

关键词： Change illuminations ImageJ software intelligent traffic systems mixture of Gaussian model National institute of Health vehicle tracking

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The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures

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Journal of Machine Learning Research 2022年第1期23卷 1-79页

作者： Weinberger, Nir Bresler, Guy The Viterbi Faculty of Electrical and Computer Engineering Technion|Israel Institute of Technology Haifa3200004 Israel Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States

This paper studies the problem of estimating the means ± θ2 Rd of a symmetric twocomponent Gaussian mixture δN(θ;I) + (1 - δ) N(-θ;I), where the weights δand 1 - δare unequal. Assuming that δis known, we show that the population version of the EM algorithm globally converges if the initial estimate has non-negative inner product with the mean of the larger weight component. This can be achieved by the trivial initialization θ0 = 0. For the empirical iteration based on n samples, we show that when initialized at θ0 = 0, the EM algorithm adaptively achieves the minimax error rate O ( min n 1 (1-2δ) q d n;1 kθk q d n;- d n )1/4 }) in no more than O ( 1 θ (1-2δ) ) iterations (with high probability). We also consider the EM iteration for estimating the weight δ, assuming a fixed mean θ (which is possibly mismatched to θ). For the empirical iteration of n samples, we show that the minimax error rate ∼O ( 1 θ q d n ) is achieved in no more than O ( 1 θ2 ) iterations. These results robustify and complement recent results of Wu and Zhou (2019) obtained for the equal weights case δ= 1/2. © 2021 Nir Weinberger and Guy Bresler.

关键词： Maximum principle

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Secure Adaptive Group Testing

Secure Adaptive Group Testing

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作者： Cohen, Alejandro Cohen, Asaf Gurewitz, Omer The Faculty of Electrical and Computer Engineering Technion—Israel Institute of Technology Haifa3200003 Israel The School of Electrical and Computer Engineering Ben-Gurion University of the Negev Beer Sheva84105 Israel

Group Testing (GT) addresses the problem of identifying a small subset of defective items from a large population, by grouping items into as few test pools as possible. In Adaptive GT (AGT), outcomes of previous tests can influence the makeup of future tests. Using an information theoretic point of view, Aldridge 2012 showed that in the regime of a few defectives, adaptivity does not help much, as the number of tests required is essentially the same as for non-adaptive GT. Secure GT considers a scenario where there is an eavesdropper who may observe on average a fraction δ of the tests results, yet should not be able to infer the status of the items. In the non-adaptive scenario, the number of tests required is 1/(1 − δ) times the number of tests without the secrecy constraint. In this paper, we consider Secure Adaptive GT. Specifically, when during the makeup of the pools one has access to a private feedback link from the lab, of rate R f . We prove that the number of tests required for both correct reconstruction at the legitimate lab, with high probability, and negligible mutual information at the eavesdropper is 1/min{1, 1 − δ + R f } times the number of tests required with no secrecy constraint. Thus, unlike non-secure GT, where an adaptive algorithm has only a mild impact, under a security constraint it can significantly boost performance. A key insight is that not only the adaptive link should disregard the actual test results and simply send keys, these keys should be enhanced through a "secret sharing" scheme before usage. We derive sufficiency and necessity bounds that completely characterizes the Secure Adaptive GT capacity. Moreover, we consider additional models of Secure Adaptive GT, where we make a clear distinction between the lab performing the tests, and the doctor analyzing the results. Specifically, we consider curious but non-malicious, non-cooperating labs. Each lab gets a fraction δ of pool-tests to perform. Yet, we want to keep each lab ignor

关键词： Decoding

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Coverage Probability of EH-enabled LoRa networks - A Deep Learning Approach

EAI Endorsed Transactions on Industrial Networks and Intelli...

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EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 2025年第2期12卷 1-11页

作者： Nguyen, Thi-Tuyet-Hai Hung, Tran Cong Son, Nguyen Hong Hanh, Tan Duy, Tran Trung Tu, Lam-Thanh Faculty of Information Technology Posts and Telecommunications Institute of Technology Viet Nam School of Computer Science & Engineering Saigon International University Ho Chi Minh City Viet Nam Faculty of Telecommunications Posts and Telecommunications Institute of Technology Viet Nam Communication and Signal Processing Research Group Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam

The performance of energy harvesting (EH)-enabled long-range (LoRa) networks is analyzed in this work. Specifically, we employ deep learning (DL) to estimate the coverage probability (Pcov) of the considered networks. Our study incorporates a general fading distribution, specifically the Nakagami-m distribution, and utilizes tools from stochastic geometry (SG) to model the spatial distributions of all nodes and end-devices (EDs) with EH capability. The DL approach is employed to overcome the limitations of model-based methods that can only evaluate the Pcov under simplified network conditions. Therefore, we propose a deep neural network (DNN) that estimates the Pcov with high accuracy compared to the ground truth values. Additionally, we demonstrate that DL significantly outperforms the Monte Carlo simulation approach in terms of resource consumption, including time and memory. © (2025), (European Alliance for Innovation). All rights reserved.

关键词： Coverage probability deep learning energy harvesting long range power beacon

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A Note on the Local Observability of Uniform Hypergraphs

A Note on the Local Observability of Uniform Hypergraphs

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94th Annual Meeting of the International Association of Applied Mathematics and Mechanics, GAMM 2024

作者： Gerbet, Daniel Röbenack, Klaus Institute of Control Theory Faculty of Electrical and Computer Engineering TUD Dresden University of Technology Dresden Germany

Hypergraphs generalize graphs in such a way that edges may connect any number of nodes. If all edges are adjacent to the same number of nodes, the hypergraph is called uniform. Thus, a graph is a 2-uniform hypergraph. Each uniform hypergraph can be identified with an autonomous dynamical state-space system, whose vector field is composed of homogenous polynomials. We consider the observability of dynamical systems, which possess this special structure. In control theory, the observability of a dynamical system asks for the possibility to reconstruct the systems state from an output trajectory, where the output is a projective measurement of the systems state. In addition, one can ask for the observable subspace of the state. Nonlinear systems, although observable at almost all points in the state space, may possess not-locally observable ones. The existence and location of such states are important for observability analysis and observer design. Recently, the observability of these hypergraph systems has been studied for the general case. We apply an extended deterministic observability test to uniform hypergraphs and also compute the not-observable states for different linear output maps. We are able to confirm the results of the recent study, at least for graphs with a small number of nodes, due to the computational complexity of our method. In addition, the not-locally observable states are computed for different combinations of measured nodes. © 2025 The Author(s).

关键词： Dynamical systems

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Cultural Heritage Monitoring and Predictive Maintenance using Internet of Things: Assessment and Future Aspects

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Journal of Mobile Multimedia 2024年第6期20卷 1211-1250页

作者： Um-E-habiba Shaikh, Faisal Karim Chowdhry, Bhawani Shankar Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and Technology Hyderabad Pakistan Telecommunication Engineering Department Mehran University of Engineering and Technology Jamshoro Pakistan Faculty of Electrical Electronics and Computer Engineering Mehran University of Engineering and Technology Jamshoro Pakistan

This study presents a detailed survey on the use of the Internet of Things (IoT) for predictive maintenance and monitoring of cultural heritage, focusing on museums and exhibitions. The integration of IoT in these fields offers significant potential for optimizing maintenance and supervision of heritage resources while also enhancing maintenance strategies. This review examines the application of IoT devices, data analysis, and predictive algorithms in monitoring the state of heritage resources to improve tourist experiences and conserve cultural resources. Key enabling technologies can enable adaptive interactions and engagement with enhanced navigation. Visualization technologies are also common, offering hands-on displays. The study also emphasizes the value of accessibility and interactivity, providing personalization and content sharing features. Several initiatives prioritize the delivery of digital content through mobile applications, internet browsers, and downloadable *** study examines how IoT-enabled predictive maintenance systems can recognize potential hazards, like resource decay or environmental dangers, enabling immediate action. This survey also highlights trends, challenges, and future research in IoT and cultural heritage monitoring. © 2025 River Publishers.

关键词： heritage monitoring IoTs predictive maintenance trends

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Construction and Decoding of Codes over the Dual-Parameter Barrier Error Model

Construction and Decoding of Codes over the Dual-Parameter B...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Ben-Hur, Yuval Cassuto, Yuval Technion-Israel Institute of Technology The Viterbi Faculty of Electrical and Computer Engineering Haifa Israel

ISBN: (纸本)9781665475549

Barrier-error channels have been suggested as a model for non-binary channels that are milder than symmetric-error channels. Such channels are motivated by practical applications in data storage and communications. The barrier-error model allows errors only to (downward) and from (upward) a specific symbol within the alphabet. We study a generalization of prior barrier-error models that considers different numbers of downward and upward errors. The results of this paper include a sufficient condition for error correction, code-size upper and lower bounds, a code construction decomposing to just two constituent symmetric-error codes (prior ones used many), and a decoding algorithm that decodes the two codes jointly. The decoder is shown empirically to achieve better block error rates when compared to previous algorithms. © 2023 IEEE.

关键词： Digital storage

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Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

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Chinese Physics B 2024年第4期33卷 418-433页

作者：周新卫蒋东华 Jean De Dieu Nkapkop Musheer Ahmad Jules Tagne Fossi Nestor Tsafack 吴建华 Department of Information Engineering Gongqing CollegeNanchang UniversityJiujiang 332020China School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 511400China Department of Electrical Engineering and Industrial Computing University Institute of TechnologyDoualaCameroon Department of Computer Engineering Jamia Millia IslamiaNew Delhi 110025India Department of Physics Faculty of ScienceUniversity of YaoundeCameroon Electrical Engineering Department and Industrial Computing of ISTAMA University of DoualaDoualaCameroon

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

关键词： cellular neural network memristor hardware circuit compressive sensing privacy data protection

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A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries

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Frontiers of computer Science 2024年第5期18卷 1-10页

作者： Lingling ZHAO Shitao SONG Pengyan WANG Chunyu WANG Junjie WANG Maozu GUO Faculty of Computing Harbin Institute of TechnologyHarbin 150001China School of Electrical Engineering Liaoning University of TechnologyJinzhou 121004China School of Computer Science Northeast Electric Power UniversityJilin 132000China Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China

Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management *** learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacity time series ***,the representation learning of features such as long-distance sequence dependencies and mutations in capacity time series still needs to be *** address this challenge,this paper proposes a novel deep learning model,the MLP-Mixer and Mixture of Expert(MMMe)model,for RUL *** MMMe model leverages the Gated Recurrent Unit and Multi-Head Attention mechanism to encode the sequential data of battery capacity to capture the temporal features and a re-zero MLP-Mixer model to capture the high-level ***,we devise an ensemble predictor based on a Mixture-of-Experts(MoE)architecture to generate reliable RUL *** experimental results on public datasets demonstrate that our proposed model significantly outperforms other existing methods,providing more reliable and precise RUL predictions while also accurately tracking the capacity degradation *** code and dataset are available at the website of github.

关键词： lithium-ion battery remaining useful life deep learning MLP-Mixer mixture-of-experts

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