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13th International Field Exploration and Development Conference, IFEDC 2023

作者： Feng, Hai-Xin Li, You-Ming Si, Jie-Ge Li, Zheng-Bin Cao, Yu The 3rd Research Institute of CETC Beijing China Key Laboratory of Petroleum Resources Research Institute of Geology and Geophysics Chinese Academy of Sciences Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Institute of Acoustics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819704828

This paper is based on elastic wave propagation and six component seismic detection methods to detect underwater targets, which makes up for the shortcomings of traditional underwater acoustic passive detection methods that cannot effectively detect targets in near shallow water. The implementation of this article requires four steps: firstly, using a self-developed six component seismometer to collect seismic signals excited by the target;Secondly, screen out abnormal six component seismic signals;Step 3: Data preprocessing such as denoising and azimuth correction;Finally, the target direction finding is achieved by comprehensively utilizing rotational and translational seismic signals. Through multiple experiments, it can be concluded that: (1) using a six component seismic sensor can detect the six component seismic signal excited by the target, and the lower the detection frequency band, the easier it is to detect the low-frequency signal excited by the target;(2) It can be clearly observed in the time-frequency domain that moving targets have a close far passing characteristic;(3) The energy of the six component seismic signal has a certain proportional relationship with the target distance. The closer the target distance is, the greater the energy of the excited six component seismic signal;(4) Six component seismic signals can be used to achieve target detection and positioning. Compared to traditional seismic detection, six component seismic detection has a higher ability and is an important supplement to traditional underwater acoustic detection methods. This article first discovered that underwater moving targets not only generate seismic translational signals, but also contain low-frequency rotational seismic signals. The accurate direction finding of the target was achieved using the six component seismic direction finding method proposed for the first time in this article. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 20

关键词： Underwater acoustics

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Intelligent New Energy Vehicle Battery Swap Scheme based on Blockchain Technology 23

Intelligent New Energy Vehicle Battery Swap Scheme based on ...

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Proceedings of the 2023 5th International Conference on Blockchain Technology

作者： Ya Han Jianbo Gao Zhi Guan Zhong Chen Lifeng Ren School of Computer Science Peking University China and Peking University Chongqing Research Institute of Big Data China National Engineering Research Center for Software Engineering Peking University China Peking University Chongqing Research Institute of Big Data China

ISBN: (纸本)9798400708930

With the development of electric vehicle technology, electric vehicles surpass fuel vehicles in terms of power performance and intelligence, and the cruising range has also increased to more than 400km with the increase of battery energy density and power consumption. However, the overall is still facing the problem of energy refueling anxiety, and the fuel vehicle refueling time is 5 minutes, and the current fast charge takes at least 60 minutes. The waiting time for charging during peak hours has also been further lengthened. Increasing the speed of energy replenishment has become an urgent need for new energy vehicle owners. The way electric vehicles are supplied with energy is fundamentally different from that of traditional cars. The battery swap mode naturally separates the vehicle and electricity, providing the possibility for novel business models (vehicle electricity separation, battery sharing). Let the battery return to its "energy carrier" use attribute, realize the sharing of batteries, create conditions for battery financialization, carry out full life cycle value management of batteries, implement battery gradient utilization, and provide a feasible path for future energy storage business. However, in battery swap mode, there are many divisions of responsibilities. For example, if the battery burns the car, should I find the main engine factory or the power exchange company/high-voltage electrical failure after the power exchange, especially when the responsibility is not clear, who will check and repair. This paper proposes a new energy vehicle monitoring platform based on blockchain technology, which can manage the whole process life cycle of new energy batteries through blockchain traceability technology. At the same time, according to the current responsibility division system, the transparent division of responsibilities is realized in combination with blockchain smart contracts.

关键词： Battery swap mode Blockchain New energy Responsibility division

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Application of AI to formal methods — an analysis of current trends

arXiv

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arXiv 2024年

作者： Stock, Sebastian Dunkelau, Jannik Mashkoor, Atif Johannes Kepler University Linz Institute of Software System Engineering Linz4040 Austria Heinrich Heine University Düsseldorf Faculty of Mathematics and Natural Sciences Institute of Computer Science Düsseldorf40225 Germany

With artificial intelligence (AI) being well established within the daily lives of research communities, we turn our gaze toward an application area that appears intuitively unsuited for probabilistic decision-making: the area of formal methods (FM). FM aim to provide sound and understandable reasoning about problems in computer science, which seemingly collides with the black-box nature that inhibits many AI approaches. However, many researchers have crossed this gap and applied AI techniques to enhance FM approaches. As this dichotomy of FM and AI sparked our interest, we conducted a systematic mapping study to map the current landscape of research publications. In this study, we investigate the previous five years of applied AI to FM (2019–2023), as these correspond to periods of high activity. This investigation results in 189 entries, which we explore in more detail to find current trends, highlight research gaps, and give suggestions for future research. Copyright © 2024, The Authors. All rights reserved.

关键词： Mapping

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Generalized Gumbel-Softmax gradient estimator for generic discrete random variables

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Pattern Recognition Letters 2025年 196卷 148-155页

作者： Weonyoung Joo Dongjun Kim Seungjae Shin Il-Chul Moon Department of Statistics EWHA Womans University Seoul Republic of Korea Department of Computer Science Stanford University CA United States Qualcomm AI Research Seoul Republic of Korea Department of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon Republic of Korea

Estimating the gradients of stochastic nodes in stochastic computational graphs is one of the crucial research questions in the deep generative modeling community, which enables gradient descent optimization on neural network parameters. Stochastic gradient estimators of discrete random variables, such as the Gumbel-Softmax reparameterization trick for Bernoulli and categorical distributions, are widely explored. Meanwhile, other discrete distribution cases, such as the Poisson, geometric, binomial, multinomial, negative binomial, etc., have not been explored. This paper proposes a generalized version of the Gumbel-Softmax stochastic gradient estimator. The proposed method is able to reparameterize generic discrete distributions, not restricted to the Bernoulli and the categorical, and it enables learning on large-scale stochastic computational graphs with discrete random nodes. Our experiments consist of (1) synthetic examples and applications on variational autoencoders, which show the efficacy of our methods; and (2) topic models, which demonstrate the value of the proposed estimation in practice.

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Customers' sentiment on food delivery services: An Arabic text mining approach

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International Journal of Information Management Data Insights 2024年第2期4卷

作者： Mustafa, Dheya Khabour, Safaa M. Shatnawi, Ahmed S. Department of Computer Engineering Faculty of Engineering The Hashemite University Zarqa 13133 Jordan Department of Information Systems Faculty of Information Technology and Computer Sciences Yarmouk University Irbid 21163 Jordan Department of Software Engineering Jordan University of Science & Technology Irbid 21110 Jordan

The Covid-19 pandemic has accelerated the shift in organizations' strategies toward innovative online services. Customer reviews on platforms for online ordering and delivery are a vital source of information about how well a business is performing. Businesses that provide food delivery services (FDS) seek to leverage consumer input to locate areas where customer satisfaction could be raised. Sentiment analysis (SA) has been the subject of an enormous amount of English-language research. Despite Arabic's increasing popularity as a writing language on the Internet, not much study has been conducted on sentiment analysis of Arabic up to this point, with a limited number of publicly available resources for Arabic SA such as datasets and lexicons. The present study collects FDS-related reviews in Arabic to conduct extensive emotion mining, taking advantage of Natural Language Processing, feature selection, and Machine Learning techniques to elicit personal judgments, identify polarity, and recognize customers’ feelings in the FDS domain. To demonstrate that the proposed approach is suitable for analyzing human perceptions of FDS, we designed and carried out excessive experiments that assess the utility of each phase. Our highest categorization accuracy was 90 % using Mutual Information with the SVM classifier. The study's findings provide various managerial insights for improving their plans and service delivery, as well as revealing the main reasons for consumer complaints. It also demonstrates how future academics might harness the power of online business reviews in Arabic using a variety of text-mining approaches. © 2024 The Author(s)

关键词： Arabic dialects Arabic sentiments resources Consumer sentiment Features selection Food delivery services Machine learning

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Frequency Domain Auto-tuning of Structured LPV Controllers for High-Precision Motion Control

arXiv

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arXiv 2024年

作者： Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands The Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Hungary

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator *** Codes 37M15 © 2024, CC BY.

关键词： Continuous time systems

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Electrochemical Sensor for Ingestible Capsule-Based In-Vivo Detection of Hydrogen Sulfide 22

Electrochemical Sensor for Ingestible Capsule-Based In-Vivo ...

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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Stine, Justin M. Ruland, Katie L. Levy, Joshua A. Beardslee, Luke A. Ghodssi, Reza University Of Maryland Department Of Electrical And Computer Engineering College ParkMD United States University Of Maryland Institute For Systems Research College ParkMD United States University Of Maryland Robert E. Fischell Institute For Biomedical Devices College ParkMD United States University Of Maryland Department Of Materials Science And Engineering College ParkMD United States

ISBN: (纸本)9784886864352

We present the fabrication and validation of a thin, flexible electrochemical sensor module for real-time capsule-based detection of hydrogen sulfide (H2S) in the gastrointestinal (GI) tract. This work advances ingestible gas sensor design using a nafion solid-state electrolyte and Au electrode to selectively monitor trace physiological H2S concentrations within a linear range of 0.9-9 ppm. Pretreatment parameters to optimize nafion conductivity and hydration retention were investigated. Selectivity from known interference gases and operation in humid conditions was compared to a commercial SPEC-H2S sensor. The sensor was integrated with a previously reported ingestible capsule to perform amperometric measurements, providing the framework for non-invasive, in-vivo monitoring of gaseous biomarkers in the GI tract. © 2023 IEEJ.

关键词： Amperometry Hydrogen Sulfide Ingestible Capsule

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Active Learning for Level Set Estimation Using Randomized Straddle Algorithms

arXiv

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arXiv 2024年

作者： Inatsu, Yu Takeno, Shion Kutsukake, Kentaro Takeuchi, Ichiro Department of Computer Science Nagoya Institute of Technology Japan Department of Mechanical Systems Engineering Graduate School of Engineering Nagoya University Japan RIKEN Center for Advanced Intelligence Project Japan Institute of Materials and Systems for Sustainability Nagoya University Japan Department of Materials Process Engineering Graduate School of Engineering Nagoya University Japan

Level set estimation (LSE), the problem of identifying the set of input points where a function takes value above (or below) a given threshold, is important in practical applications. When the function is expensive-to-evaluate and black-box, the straddle algorithm, which is a representative heuristic for LSE based on Gaussian process models, and its extensions having theoretical guarantees have been developed. However, many of existing methods include a confidence parameter βt1/2 that must be specified by the user, and methods that choose βt1/2 heuristically do not provide theoretical guarantees. In contrast, theoretically guaranteed values of βt1/2 need to be increased depending on the number of iterations and candidate points, and are conservative and not good for practical performance. In this study, we propose a novel method, the randomized straddle algorithm, in which βt in the straddle algorithm is replaced by a random sample from the chi-squared distribution with two degrees of freedom. The confidence parameter in the proposed method has the advantages of not needing adjustment, not depending on the number of iterations and candidate points, and not being conservative. Furthermore, we show that the proposed method has theoretical guarantees that depend on the sample complexity and the number of iterations. Finally, we confirm the usefulness of the proposed method through numerical experiments using synthetic and real data. Copyright © 2024, The Authors. All rights reserved.

关键词： Active learning

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Analyzing α-divergence in Gaussian Rate-Distortion-Perception Theory

Analyzing α-divergence in Gaussian Rate-Distortion-Percepti...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Martha V. Sourla Giuseppe Serra Photios A. Stavrou Marios Kountouris School of Electrical & Computer Engineering Technical University of Crete Chania Greece Communication Systems Department EURECOM France Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Spain

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

The problem of the estimation of the information rate-distortion-perception function (RDPF), which is a relevant information-theoretic quantity in goal-oriented lossy compression and semantic information reconstruction, is investigated here. Specifically, we study the RDPF tradeoff for Gaussian sources subject to a mean-squared error (MSE) distortion and a perception measure that belongs to the family of α-divergences. Assuming a jointly Gaussian RDPF, which forms a convex optimization problem, we characterize an upper bound for which we find a parametric solution. We show that evaluating the optimal parameters of this parametric solution is equivalent to finding the roots of a reduced exponential polynomial of degree α. Additionally, we determine which disjoint sets contain each root, which enables us to evaluate them numerically using the well-known bisection method. Finally, we validate our analytical findings with numerical results and establish connections with existing results.

关键词： Wireless communication Upper bound Semantics Measurement uncertainty Estimation Distortion Polynomials Convex functions Distortion measurement Information theory

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Deep Unfolding 3D Non-Local Transformer Network for Hyperspectral Snapshot Compressive Imaging

Deep Unfolding 3D Non-Local Transformer Network for Hyperspe...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zheng Zhou Zongxin Liu Yongyong Chen Bingzhi Chen Biqing Zeng Yicong Zhou School of Electronics and Communication Engineering Guangzhou University Guangzhou China School of Software South China Normal University Foshan China School of Computer Science and Technology Harbin Institute of Technology Shenzhen China Department of Computer and Information Science University of Macau Macau China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Hyperspectral compressive imaging has shown remarkable advancements through the adoption of deep unfolding frameworks, which integrate the proximal mapping prior into the data fidelity term to formulate the reconstruction problem. However, existing technologies still face challenges in effectively capturing spatial-spectral features during the iterative deep prior learning stage, leading to unsatisfactory performance degradation. To address this issue, we propose a deep unfolding 3D non-local transformer (3DNLT) network for hyperspectral compressive imaging. A learnable half-quadratic splitting (HQS) algorithm is utilized to iteratively update the linear projection. Furthermore, a 3D non-local attention ushaped transformer is presented as the deep proximal mapping prior module to obtain the spatial-spectral long-range dependency features, leading to enhance the network’s ability to capture fine-grained hyperspectral and spatial details. Experimental results on both synthetic and real hyperspectral image reconstruction have demonstrated the superior performance of the 3DNLT network compared to state-of-the-art methods.

关键词： Degradation Three-dimensional displays Image coding Imaging Transformers Robustness Iterative methods

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