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arXiv 2021年

作者： Wu, Haiwen Jayawardhana, Bayu de Marina, Hector Garcia Xu, Dabo Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Department of Computer Architecture and Automatic Control Faculty of Physics Universidad Complutense de Madrid Madrid28040 Spain The School of Automation Nanjing University of Science and Technology Nanjing210094 China

This paper addresses the problem of end-effector formation control for manipulators that are subjected to external disturbances: input disturbance torques and disturbance forces at each end-effector. The disturbances are assumed to be non-vanishing and are superposition of finite number of sinusoidal and step signals. The formation control objective is achieved by assigning virtual springs between end-effectors, by adding damping terms at joints, and by incorporating internal model-based dynamic compensators to counteract the effect of the disturbances;all of which presents a clear physical interpretation of the proposed approach. Simulation results are presented to illustrate the effectiveness of the proposed approach. © 2021, CC BY.

关键词： End effectors

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AI-Based CSI Feedback With Digital Twins: Real-World Validation and Insights

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IEEE Wireless Communications Letters 2025年

作者： Huang, Tzu-Hao Wen, Chao-Kai Tsai, Shang-Ho Duong, Trung Q. National Yang Ming Chiao Tung University Institute of Electrical Control Engineering Hsinchu300 Taiwan National Sun Yat-sen University Institute of Communications Engineering Kaohsiung804 Taiwan National Yang Ming Chiao Tung University Department of Electrical Engineering Hsinchu300 Taiwan Memorial University Faculty of Engineering and Applied Science St. John’sNLA1C 5S7 Canada Queen’s University Belfast School of Electronics Electrical Engineering and Computer Science Belfast United Kingdom

Deep learning (DL) has shown great potential for enhancing channel state information (CSI) feedback in multiple-input multiple-output (MIMO) communication systems, a subject currently under study by the 3GPP standards body. Digital twins (DTs) have emerged as an effective means to generate site-specific datasets for training DL-based CSI feedback models. However, most existing studies rely solely on simulations, leaving the effectiveness of DTs in reducing DL training costs yet to be validated through realistic experimental setups. This paper addresses this gap by establishing a real-world (RW) environment and corresponding virtual channels using ray tracing with replicated 3D models and accurate antenna properties. We evaluate whether models trained in DT environments can effectively operate in RW scenarios and quantify the benefits of online learning (OL) for performance enhancement. Results show that a dedicated DT remains essential even with OL to achieve satisfactory performance in RW scenarios. © 2012 IEEE.

关键词： Digital elevation model

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Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging

Research Square

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Research Square 2021年

作者： Suwalska, Aleksandra Siuda, Joanna Kocot, Szymon Zmuda, Weronika Rudzinska-Bar, Monika Polanska, Joanna Department of Data Science and Engineering Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Neurology School of Medicine Medical University of Silesia Katowice Poland Department of Neurology Faculty of Medicine and Health Sciences Andrzej Frycz Modrzewski Krakow University Krakow Poland

Identification of Parkinson’s Disease (PD) patients at risk for development of dementia is crucial for early intervention. However, diagnosing dementia in PD patients requires advanced, time-consuming and expensive imaging techniques (such as DaT-SCAN-SPECT). The study aims to prove the usefulness of convolutional neural networks (CNN) for the identification of brain areas related to the progress of cognitive impairment by using standard Magnetic Resonance Imaging (MRI) sequences. T1&T2 sequences of 18 patients were used in the pilot study. Activation maps were generated, and the brain regions most involved in the classification process were identified, showing areas potentially significant in the diagnosis of cognitive impairment severity. The cerebellum was proven significant for distinguishing the above-mentioned classes in relative cerebellum volume (ANOVA p-value=0.0038 with large effect size η2=0.5254) and folding (p-value=0.0031, η2=0.5357), which is consistent with reports by other authors. Our analysis demonstrates that convolutional neural networks combined with a proper image preprocessing pipeline could be used for feature extraction in MRI sequences and can successfully support the identification of disease-specific abnormalities of the brain image. © 2021, CC BY.

关键词： Magnetic resonance imaging

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Initial Study on Implementation of Smoothing Filters for the Purpose of Bioimpedance Spectroscopy Parameters Classification

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IFAC-PapersOnLine 2022年第4期55卷 393-398页

作者： Aleksandra Kawala-Sterniuk Amir F. Al-Bakri Mariusz Pelc Katarzyna Cichoń Wojciech Chlewicki Stepan Ozana Radek Martinek Jakub Możaryn Volodymyr Khoma Halyna Kenyo Edward Jacek Gorzelańczyk Michał Podpora Jarosław Zygarlicki Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics 45-758 Opole Poland Department of Biomedical Engineering College of Engineering University of Babylon 51001 Babylon Iraq University of Greenwich School of Computing and Mathematical Sciences SE10 9LS London UK West Pomeranian University of Technology in Szczecin Faculty of Electrical Engineering 70-313 Szczecin Poland Faculty of Mechatronics Warsaw University of Technology 02-525 Warsaw Poland Lviv Polytechnic National University Institute of Computer Technologies Automation and Metrology Lviv Ukraine Institute of Philosophy Kazimierz Wielki University 85-092 Bydgoszcz Poland Faculty of Mathematics and Computer Science Adam Mickiewicz University in Poznań 61-614 Poznań Poland

Bioimpedance is a commonly used method for various conditions monitoring. In this paper, the authors carried out some research where they implemented various smoothing filters to enable identification of the bioimpedance spectroscopy parameters. The proposed filtering methods may also be used for application on embedded systems, which have smaller computing power but have become recently very popular. The obtained results with the implementation of smoothing filters were promising, however, some of the obtained results were unsatisfactory. This work also contains a brief introduction to bioimpedance spectroscopy and smoothing filters.

关键词： Bioimpedance Spectroscopy smoothing-filtering Savitzky-Golay Filter Median Filtering Moving-Average Filters

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Fast projection onto convex smooth constraints

arXiv

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arXiv 2021年

作者： Usmanova, Ilnura Kamgarpour, Maryam Krause, Andreas Levy, Kfir Yehuda Automatic Control Laboratory D-ITET ETH Zürich Switzerland Department of Electrical and Computer Engineering University of British Columbia Canada Department of Computer Science ETH Zürich Switzerland Viterby Department of Electrical & Computer Engineering Technion - Israel Institute of Technology

The Euclidean projection onto a convex set is an important problem that arises in numerous constrained optimization tasks. Unfortunately, in many cases, computing projections is computationally demanding. In this work, we focus on projection problems where the constraints are smooth and the number of constraints is significantly smaller than the dimension. The runtime of existing approaches to solving such problems is either cubic in the dimension or polynomial in the inverse of the target accuracy. Conversely, we propose a simple and efficient primal-dual approach, with a runtime that scales only linearly with the dimension, and only logarithmically in the inverse of the target accuracy. We empirically demonstrate its performance, and compare it with standard baselines. © 2021, CC BY.

关键词： Constrained optimization

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The forgotten document-oriented database management systems: An overview and benchmark of native XML DODBMSes in comparison with JSON DODBMSes

arXiv

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arXiv 2021年

作者： Truică, Ciprian-Octavian Apostol, Elena-Simona Darmont, Jérôme Pedersen, Torben Bach Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania Department of Computer Science Aarhus University Aarhus Denmark Université de Lyon ERIC UR 3083 Lyon 2 France Center for Data Intensive Systems Aalborg University Aalborg Denmark

In the current context of Big Data, a multitude of new NoSQL solutions for storing, managing, and extracting information and patterns from semi-structured data have been proposed and implemented. These solutions were developed to relieve the issue of rigid data structures present in relational databases, by introducing semi-structured and flexible schema design. As current data generated by different sources and devices, especially from IoT sensors and actuators, use either XML or JSON format, depending on the application, database technologies that store and query semi-structured data in XML format are needed. Thus, Native XML Databases, which were initially designed to manipulate XML data using standardized querying languages, i.e., XQuery and XPath, were rebranded as NoSQL Document-Oriented Databases Systems. Currently, the majority of these solutions have been replaced with the more modern JSON based Database Management Systems. However, we believe that XML-based solutions can still deliver performance in executing complex queries on heterogeneous collections. Unfortunately nowadays, research lacks a clear comparison of the scalability and performance for database technologies that store and query documents in XML versus the more modern JSON format. Moreover, to the best of our knowledge, there are no Big Data-compliant benchmarks for such database technologies. In this paper, we present a comparison for selected Document-Oriented Database Systems that either use the XML format to encode documents, i.e., BaseX, eXist-db, and Sedna, or the JSON format, i.e., MongoDB, CouchDB, and Couchbase. To underline the performance differences we also propose a benchmark that uses a heterogeneous complex schema on a large DBLP corpus. © 2021, CC BY.

关键词： XML

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Reduct-based ranking of attributes 24

Reduct-based ranking of attributes

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24th KES International Conference on Knowledge-Based and Intelligent Information and engineering Systems, KES 2020

作者： Zielosko, Beata Stanczyk, Urszula Institute of Computer Science University of Silesia in Katowice Bedzi nska 39 Sosnowiec41-200 Poland Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

The paper is dedicated to the area of feature selection, in particular a notion of attribute rankings that allow to estimate importance of variables. In the research presented for ranking construction a new weighting factor was defined, based on relative reducts. A reduct constitutes an embedded mechanism of feature selection, specific to rough set theory. The proposed factor takes into account the number of reducts in which a given attribute exists, as well as lengths of reducts. Two approaches for reduct generation were employed and compared, with search executed by a genetic algorithm. To validate the usefulness of the reduct-based rankings in the process of feature reduction, for gradually decreasing subsets of attributes, selected through rankings, sets of decision rules were induced in classical rough set approach. The performance of all rule classifiers was evaluated, and experimental results showed that the proposed rankings led to at least the same, or even increased classification accuracy for reduced sets of features than in the case of operating on the entire set of condition attributes. The experiments were performed on datasets from stylometry domain, with treating authorship attribution as a classification task, and stylometric descriptors as characteristic features defining writing styles. © 2020 The Authors. Published by Elsevier B.V.

关键词： Classification (of information)

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Radiomics model based on computed tomography images for prediction of radiation-induced optic neuropathy following radiotherapy of brain and head and neck tumors

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Heliyon 2025年第1期11卷 e41409页

作者： Nafchi, Elham Raiesi Fadavi, Pedram Amiri, Sepideh Cheraghi, Susan Garousi, Maryam Nabavi, Mansoureh Daneshi, Iman Gomar, Marzieh Molaie, Malihe Nouraeinejad, Ali Department of Radiation Sciences Faculty of Allied Medicine Iran University of Medical Sciences Tehran Iran Department of Radiation Oncology School of Medicine Iran University of Medical Science Tehran Iran Department of Information Technology Faculty of Electrical and Computer Engineering University of Tehran Tehran Iran Radiation Biology Research Center Iran University of Medical Sciences Tehran Iran Radiation Oncology Research Center (RORC) Cancer Institute Tehran University of Medical Sciences Tehran Iran Department of Clinical Oncology Haft-e-Tir Hospital Iran University of Medical Science Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Optometry and Vision Science School of Rehabilitation Tehran University of Medical Science Tehran Iran

Purpose: We aimed to build a machine learning-based model to predict radiation-induced optic neuropathy in patients who had treated head and neck cancers with radiotherapy. Materials and methods: To measure radiation-induced optic neuropathy, the visual evoked potential values were obtained in both case and control groups and compared. Radiomics features were extracted from the area segmented which included the right and left optic nerves and chiasm. We integrated CT image features with dosimetric and clinical data subsequently, ranked 5 supervised ML models Bernoulli Naive Bayes, Decision Tree, Gradient Boosting Decision Trees, K-Nearest Neighbor, and Random Forest on 4 input datasets to predict radiation-induced visual complications classifiers by implementing 5-fold cross-validation. The F1 score, accuracy, sensitivity, specificity, and area under the ROC curve were compared to access prediction capability. Results: radiation-induced optic neuropathy affected 31 % of the patients. 856 radiomic characteristics were extracted and selected from each segmented area. Decision Tree and Random Forest with the highest AUC (97 % and 95 % respectively) among the five classifiers were the most powerful algorithms to predict radiation-induced optic neuropathy. Chiasm with higher sensitivity and precision was able to predict radiation-induced optic neuropathy better than right or left optic nerve or combination of all radiomic features. Conclusion: We found that combination of radiomic, dosimetric, and clinical factors can predict radiation-induced optic neuropathy after radiation treatment with high accuracy. To acquire more reliable results, it is recommended to conduct visual evoked potential tests before and after radiation therapy, with multiple follow-up courses and more patients. © 2024 The Authors

关键词： Computed tomography Machine learning Radiation-induced optic neuropathy Radiomics Visual evoked potential

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Optimization of DCM boost chopper performance controlled by optimal PIDF regulator for stand-alone PV system

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Solar Compass 2025年 14卷

作者： Nkouna Paul Lionnel, Ella Obono Biyobo, Arnaud Owoundi Etouke, Paul Dangwe Sounsoumou, Yves Paulin Jean Jacques Molu, Reagan Dzonde Naoussi, Serge Raoul Computer and Automatic Engineering Research Laboratory ENSET University of Douala Douala Cameroun PB: 1872 Douala Cameroon Faculty of Science Renewable Energies Department University of Garoua Garoua Cameroon PB 346 Garoua Cameroon Technologies and Applied Sciences Laboratory University Institute of Technology of Douala University of Douala P.O. Box: 8689 Douala Cameroon

This paper proposes a Maximum Power Point Tracking (MPPT) strategy for a photovoltaic (PV) panel, combining the Perturb and Observe (P&O) technique, Particle Swarm Optimization (PSO), and an optimal Duty Cycle Modulation (DCM) circuit. The Boost chopper, regulated by a Proportional-Integral-Derivative controller with a first-order low-pass filter (PIDF), serves as an interface between the photovoltaic source (PV) and the load, maximizing the extraction of energy produced by the solar panel. The results obtained in virtual simulation in the MATLAB/Simulink environment are satisfactory: we observe in standard conditions, namely temperature T = 25 °C and solar irradiation of 1000W/m², a response without overshoot, a zero static error, a system stability time of 0.32 s, 0.13 s and 0.15 s respectively for three respective load values (R₀ = 50 Ω, R₀₁ = 37.5 Ω and R₀₂ = 25 Ω) in steady state. In transient state, taking into account the variation in solar irradiation, it can be seen that despite the fluctuations, the system manages to remain stable, attesting to the robustness of the controller used. To control the DCM Boost chopper. The comparative study carried out with other MPPT techniques such as (VSS-P&O, MIC, FOCV, FSS-RBFA, VSS-RBFA, AFLC, PSO and CS) applied to conventional boost converters attests that the proposed new prototype offers quite satisfactory performances compared to the latter. © 2025 The Author(s)

关键词： DCM (duty cycle modulation) LQR (linear quadratic regulator) P&O (Perturb and Observe) PIDF (Proportional, Integral, Derivative with low-pass Filter) PSO (Particle Swarm Optimization)

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Frequency Measurement Research with Weight Averaging of Pulse Output Signal of Voltage-to-Frequency Converter

SSRN

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SSRN 2022年

作者： Dorozhovets, Mykhaylo Pawlowski, Eligiusz Świsulski, Dariusz Department of Metrology and Diagnostic Systems Faculty of Electrical and Computer Engineering Rzeszow University of Technology ul. Wincentego Pola 2A Rzeszów35-959 Poland Department of Information and Measuring Technology National University Lviv Polytechnic Lviv Ukraine Faculty of Electrical Engineering and Computer Science Lublin University of Technology Lublin Poland Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdańsk Poland

The paper presents investigation of the efficiency of weight averaging of a pulse frequency modulated signal. The sampling effects and the interference influence in the input signal of the voltage-to frequency converter on the result of output frequency weight averaging are analyzed. A general form of the averaging result dependence on the used weighting function, signal value, interference level and modulation parameters is derived. In the case of high interferences whose frequencies are unstable or may change over a wide range, the specified level of their suppression, together with the reduction of the sampling effect, can be achieved using weighting functions, such as trigonometric, with an appropriate level of side lobes. The interference suppression dependently on frequency ranges using selected weighing functions are tested using both the simulation and experimental methods. The obtained results show very good convergence with the values calculated from theoretical formulas. © 2022, The Authors. All rights reserved.

关键词： Weighing

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