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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Paweł Pawłowski Rafał Długosz Marek Radkowski Mateusz Wątły Adam Dąbrowski Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Signal Processing and Electronic Systems Poznań University of Technology Poznań Poland Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz University of Science and Technology Bydgoszcz Poland

The paper presents project and its verification of a prototype integrated circuit containing an analog, programmable finite impulse response (FIR) filter, implemented in CMOS 350 nm technology. The structure of the filter is based on the switched capacitor technique. In circuits of this type, one of main challenges is an efficient implementation of filter coefficients, which result from several factors described in this work. When implementing such filters as programmable circuits, the values of their coefficients have to be limited to a selected range, i.e. a given resolution in bits. In the implemented prototype filter, the filter coefficients are represented by 6 bits in sign-magnitude notation, so they can take 63 different values only. In such filters, it is not possible to directly implement any frequency response of the filter. Each time, it is necessary to properly round the theoretical values of the coefficients so that they fit into the available range of discrete values resulting from the implementation. The authors of the work designed an algorithm that allows such matching. The paper also presents results of measurements of the prototype chip.

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Knowledge-Driven Drug-Use NamedEntity Recognition with Distant Supervision 18

Knowledge-Driven Drug-Use NamedEntity Recognition with Dista...

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18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021

作者： Bajaj, Goonmeet Kursuncu, Ugur Gaur, Manas Lokala, Usha Hyder, Ayaz Parthasarathy, Srinivasan Sheth, Amit Department of Computer Science and Engineering The Ohio State University ColumbusOH United States Division of Environmental Health Sciences College of Public Health The Ohio State University ColumbusOH United States Ai Institute University of South Carolina ColumbiaSC United States

ISBN: (纸本)9781643682648

As Named Entity Recognition (NER) has been essential in identifying critical elements of unstructured content, generic NER tools remain limited in recognizing entities specific to a domain, such as drug use and public health. For such high-impact areas, accurately capturing relevant entities at a more granular level is critical, as this information influences real-world processes. On the other hand, training NER models for a specific domain without handcrafted features requires an extensive amount of labeled data, which is expensive in human effort and time. In this study, we employ distant supervision utilizing a domain-specific ontology to reduce the need for human labor and train models incorporating domain-specific (e.g., drug use) external knowledge to recognize domain specific entities. We capture entities related the drug use and their trends in government epidemiology reports, with an improvement of 8% in F1-score. © 2022 International Medical Informatics Association (IMIA) and IOS Press.

关键词： Digital storage

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Estimating the Sensitivity of Microoptoelectromechanical Micro-g Accelerometer 23

Estimating the Sensitivity of Microoptoelectromechanical Mic...

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23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

作者： Barbin, Evgenij S. Nesterenko, Tamara G. Koleda, Aleksej N. Shesterikov, Evgeniy V. Kulinich, Ivan V. Sheyerman, Fedor I. The Tomsk State University of Control Systems and Radioelectronics Laboratory of Radiophotonics Tomsk Russia Institute of Optics and Atmosphere Siberian Branch of the Russian Academy of Sciences Laboratory of Intelligent Computer Systems Tomsk Russia National Research Tomsk Polytechnic University Division for Electronic Engineering Tomsk Russia

ISBN: (纸本)9781665498043

The article studies a MOEMS-accelerometer with an optical measuring element based on an optical tunneling effect intended for measuring micro-g accelerations. The work estimates the sensitivity threshold of the accelerometer based on the Noise Equivalent Acceleration, which is stipulated by thermal Brownian motion of molecules, noises of a laser and photodiode. Shot noise has the largest effect on the MOEMS-accelerometer noise threshold and depends on its mechanical properties. The general sensitivity of the MOEMS-accelerometer equals 0.938, 3, or 6.255 A/g, depending on a chosen operational point. The sensitivity threshold in terms of photodiode dark current equals 107 × 10-9 g, 33.3 × 10-9 g, 16 × 10-9 g. The dynamic range for the photodiode equals ± 3.2 × 10-3 g, while for the measuring transducer it is ±0.32g, ±0.1, or ±0.05g. To decrease the noise down to 0.1 µ g, the inertial mass should amount at least to 65 × 10-7 kg, and the average laser noise power should be below 1 %. © 2022 IEEE.

关键词： Accelerometers

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Lazy Probabilistic Roadmaps Revisited

arXiv

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arXiv 2022年

作者： Ramirez, Miquel Selvaratnam, Daniel Manzie, Chris School of Electric and Electronic Engineering University of Melbourne Australia Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

This paper describes a revision of the classic Lazy Probabilistic Roadmaps algorithm (Lazy PRM), that results from pairing PRM and a novel Branch-and-Cut (BC) algorithm. Cuts are dynamically generated constraints that are imposed on minimum cost paths over the geometric graphs selected by PRM. Cuts eliminate paths that cannot be mapped into smooth plans that satisfy suitably defined kinematic constraints. We generate candidate smooth plans by fitting splines to vertices in minimum-cost path. Plans are validated with a recently proposed algorithm that maps them into finite traces, without need to choose a fixed discretization step. Trace elements exactly describe when plans cross constraint boundaries modulo arithmetic precision. We evaluate several planners using our methods over the recently proposed BARN benchmark, and we report evidence of the scalability of our approach. Copyright © 2022, The Authors. All rights reserved.

关键词： Combinatorial optimization

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Constrained Optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic Control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Analysis of LO phonon properties in III-nitrides: Interaction with carriers and microscopic analysis 16

Analysis of LO phonon properties in III-nitrides: Interactio...

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Gallium Nitride Materials and Devices XVI 2021

作者： Ishitani, Y. Oki, K. Chizaki, M. Okamoto, S. Nakayama, T. Lin, B. Ma, B. Morita, K. Miyake, H. Iida, D. Ohkawa, K. Graduate School of Electric and Electronic Engineering 1-33 Yayoicho Inage-ku Chiba263-8522 Japan Graduate School of Electrical and Electronic Engineering Mie University 1577 Kurimamachiya Tsu514-8507 Japan Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

ISBN: (数字)9781510642089

ISBN: (纸本)9781510642072

Longitudinal optical (LO) phonon has strong electric interaction with particles and fields. Particularly, the interaction in III-nitrides is more significant than that in conventional III-V materials. We show phonon-exciton interaction properties in experimental PL spectrum analysis and theoretical calculation of population transfers of excitonic levels. Thermally nonequilibrium occupations of LO phonons and other modes generated by the LO-phonon decomposition are thought to shift the population distribution in principal quantum number states and kinetic energy to the higher energy side. The radiative exciton recombination lifetime is determined by the population distribution in the excitonic states, which is determined by the balance of the electronic and phononic elementary processes. The interaction of excitons and phonons releases the excess energy to the thermal bath of the lattice system, which sometimes yields negligible lattice temperature increase in the excited region or the nonequilibrium state between electron and phonon systems. A Raman scattering imaging measure is introduced to exhibit spatial transport of phonons generated by the energy relaxation and nonradiative recombination of the excited electrons and holes, where pump-probe measurements are enabled by the simultaneous irradiation of two laser beams. It is found that the phonon transport is blocked by the misfit dislocations located on a Ga0.84In0.16N/GaN heterointerface. © 2021 SPIE.

关键词： Phonons

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Efficient Lane Detection based on Feature Aggregation for Advanced Driver Assistance Systems

Efficient Lane Detection based on Feature Aggregation for Ad...

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International Conference on Advanced Robotics and Intelligent Systems (ARIS)

作者： Sin-Ye Jhong Ching-Hsiang Ko Yi-Feng Su Kai-Lung Hua Yung-Yao Chen Dept. of Engineering Science National Cheng Kung University Tainan Taiwan Dept. of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan Research and Development Division Automotive Research and Testing Center Changhua Taiwan Dept. of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan

As we enter the era of smart cars and electric vehicles, the significance of autonomous driving systems, especially crucial components like lane detection technology, increases dramatically. However, advanced solutions often face daunting challenges, especially under adverse environmental and lighting conditions, yielding varying detection results. This variability prompts automakers to enforce numerous restrictions on auxiliary functions, often deterring potential customers from upgrading relevant services. This study addresses these limitations and introduces a sophisticated deep learning-based lane detection model to supersede existing technologies. The model fuses an efficient feature extraction network with a Recurrent Feature-Shift Aggregator (RESA) and a Bilateral Up-Sampling Decoder (BUSD). These elements work harmoniously, enabling enhanced global information extraction and fortifying detection capability under challenging conditions. The methodology of this study is segregated into three parts: Efficient Backbone and Neck for feature extraction, Global Feature Enhancement Decoder for maximizing feature map details, and the actual implementation of a Lane Assist System. These modules collectively help us calculate high-accuracy lane coordinates, thereby overcoming the limitations of previous lane detection methods. Following the successful creation and validation of the model, the study extends the implementation to the Hexagon vehicle control platform, where the Lane Departure and Lane Keeping assistance systems are deployed. The proposed technology is validated through rigorous experiments and analyses, utilizing the highly recognized TuSimple dataset, custom-collected Taiwanese scene data, and actual road tests. Results illustrate high and consistent detection performance under diverse environmental conditions, validating the technology’s effectiveness and feasibility.

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Ultrasonic Index Modulation With Spread Spectrum for Intra-Body Communications

Ultrasonic Index Modulation With Spread Spectrum for Intra-B...

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IEEE International Conference on Communications (ICC)

作者： Qianqian Wang Quansheng Guan Julian Cheng Xiangdong Jia Mangang Xie Yuankun Tang College of Computer Science and Engineering Northwest Normal University Lanzhou China School of Electronic and Information Engineering South China University of Technology Guangzhou China Key Laboratory of Marine Environmental Survey Technology and Application Ministry of Natural Resources Guangzhou China School of Engineering The University of British Columbia Kelowna BC Canada

Ultrasonic intra-body communication (IBC) is an emerging technique to enable revolutionary healthcare applications. This paper proposes an ultrasonic index modulation with spread spectrum (UsIM-SS) scheme for IBCs. The information bits consist of modulation bits and index bits. The core idea of UsIM-SS is that the modulation bits are spread by spreading codes and the index bits are leveraged to select the time-hoping sequence to transmit the spreading bits. We also find that the existing ultrasonic wideband (UsWB) and UsIM can be regarded as special cases of the proposed UsIM-SS. Furthermore, the soft decision-based maximum likelihood (S-ML) receiver and hard decision-based ML (H-ML) receiver are proposed for UsIM-SS, providing a trade-off between bit-error rate (BER) and complexity. Theoretical spectrum efficiency (SE) and BER expressions for UsIM-SS using S-ML and H-ML are also derived and verified by extensive Monte Carlo simulations. Both theoretical and simulation results show that UsIM-SS can achieve lower BER and higher SE than existing UsWB and Us 1M techniques.

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GNSS Interference Classification Using Federated Reservoir Computing

GNSS Interference Classification Using Federated Reservoir C...

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International Conference on Communication Technology (ICCT)

作者： Ziqiang Ye Yulan Gao Xinyue Liu Yue Xiao Ming Xiao Saviour Zammit National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu China Division of Information Science and Engineering KTH Royal Institute of Technology Stockholm Sweden SWJTU-Leeds Joint School Southwest Jiaotong University Chengdu China Department of Communications and Computer Engineering University of Malta Malta

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

The expanding use of Unmanned Aerial Vehicles (UAVs) in vital areas like traffic management, surveillance, and environmental monitoring highlights the need for robust communication and navigation systems. Particularly vulnerable are Global Navigation Satellite Systems (GNSS), which face a spectrum of interference and jamming threats that can significantly undermine their performance. While traditional deep learning approaches are adept at mitigating these issues, they often fall short for UAV applications due to significant computational demands and the complexities of managing large, centralized datasets. In response, this paper introduces Federated Reservoir Computing (FedRC) as a potent and efficient solution tailored to enhance interference classification in GNSS systems used by UAVs. Our experimental results demonstrate that FedRC not only achieves faster convergence but also sustains lower loss levels than traditional models, highlighting its exceptional adaptability and operational efficiency.

关键词： Deep learning Global navigation satellite system Adaptation models Computational modeling Reservoir computing Interference Traffic control Autonomous aerial vehicles Jamming Convergence

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Write Summary Step-by-Step: A Pilot Study of Stepwise Summarization

arXiv

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arXiv 2024年

作者： Chen, Xiuying Gao, Shen Li, Mingzhe Zhu, Qingqing Gao, Xin Zhang, Xiangliang The Computer Electrical and Mathematical Sciences and Engineering division KAUST Saudi Arabia The University of Electronic Science and Technology of China China Ant Group China Peking university China University of Notre Dame American Samoa KAUST Saudi Arabia

Nowadays, neural text generation has made tremendous progress in abstractive summarization tasks. However, most of the existing summarization models take in the whole document all at once, which sometimes cannot meet the needs in practice. Practically, social text streams such as news events and tweets keep growing from time to time, and can only be fed to the summarization system step by step. Hence, in this paper, we propose the task of Stepwise Summarization, which aims to generate a new appended summary each time a new document is proposed. The appended summary should not only summarizes the newly added content but is also coherent with the previous summary, to form an up-to-date complete summary. To tackle this challenge, we design an adversarial learning model, named Stepwise Summary Generator (SSG). First, SSG selectively processes the new document under the guidance of the previous summary, obtaining polished document representation. Next, SSG generates the summary considering both the previous summary and the document. Finally, a convolutional-based discriminator is employed to determine whether the newly generated summary is coherent with the previous summary. For the experiment, we extend the traditional two-step update summarization setting to multi-step stepwise setting, and re-propose a large-scale stepwise summarization dataset based on a public story generation dataset. Extensive experiments on this dataset show that SSG achieves state-of-the-art performance in terms of both automatic metrics and human evaluations. Ablation studies demonstrate the effectiveness of each module in our framework. We also discuss the benefits and limitations of recent large language models on this task. © 2024, CC BY.

关键词： Large datasets

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