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SSRN 2023年

作者： Liu, Xiaodong Guo, Haipeng Liu, Huanyu Li, Junbao Department of Automatic Test and Control School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin150080 China

Recently, magnetic resonance imaging has been widely used in clinical treatment to assist doctors in diagnosis because of its high resolution of soft tissue and no radiation. However, limited by imaging equipment and imaging time, the resolution of MR imaging is low. The previous super-resolution algorithms used for MR images use paired datasets to generate down-sampled images by artificially assuming the image degradation process, and forming a sample pair to monitor and train the super-resolution network. However, the super-resolution network obtained by this way will cause serious degradation of the network performance in practical application. In this paper, we propose a blind super-resolution framework DMN based on domain migration, which decouples the blind super-resolution network with the idea of domain migration, and avoids the false detail generation problem of the blind super-resolution network in the MR images super-resolution task through independent training. At the same time, we propose a multi-level parallel transformer feature enhancement module MPTB, which takes noise as the original input and embeds noise features step by step to enhance the fitting ability of the network while reducing the complexity of the network structure design. Besides, we also use the k-space loss function to form a constraint function, so that the domain migration network can fully consider the k-space characteristics of MR images. The experimental results on the MR images of the knee joint and brain in the fastMRI dataset show that the super-resolution performance of our proposed DMN network is better than the previous super-resolution networks. © 2023, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Discrete-Time Stress Matrix-Based Formation control of General Linear Multi-Agent Systems

arXiv

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arXiv 2024年

作者： Onuoha, Okechi Kurawa, Suleiman Tang, Zezhi Dong, Yi School of Computing Engineering and Intelligent Systems Ulster University United Kingdom School of Electrical and Electronic Engineering The University of Manchester United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom School of Electronics & Computer Science University of Southampton United Kingdom

This paper considers the distributed leader-follower stress-matrix-based affine formation control problem of discrete-time linear multi-agent systems with static and dynamic leaders. In leader-follower multi-agent formation control, the aim is to drive a set of agents comprising leaders and followers to form any desired geometric pattern and simultaneously execute any required manoeuvre by controlling only a few agents denoted as leaders. Existing works in literature are mostly limited to the cases where the agents’ inter-agent communications are either in the continuous-time settings or the sampled-data cases where the leaders are constrained to constant (or zero) velocities or accelerations. Here, we relax these constraints and study the discrete-time cases where the leaders can have stationary or time-varying velocities. We propose control laws in the study of different situations and provide some sufficient conditions to guarantee the overall system stability. Simulation study is used to demonstrate the efficacy of our proposed control laws. © 2024, CC BY.

关键词： Linear systems

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Spleen-preserving distal pancreatectomy from multi-port to reducedport surgery approach

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World Journal of Gastrointestinal Surgery 2023年第7期15卷 1501-1511页

作者： Ching-Lung Hsieh Tung-Sheng Tsai Cheng-Ming Peng Teng-Chieh Cheng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724TaiwanChina Department of Surgery Chung Shan Medical University HospitalTaichung 40201TaiwanChina PhD Program of Electrical and Communications Engineering Feng Chia UniversityTaichung 40724Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Da Vinci Minimally Invasive Surgery Center Chung Shan Medical University HospitalTaichung 40201Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

BACKGROUND Minimally invasive pancreatic surgery via the multi-port approach has become a primary surgical method for distal pancreatectomy(DP)due to its advantages of lower wound pain and superior cosmetic *** studies have applied reduced-port techniques for DP in an attempt to enhance cosmetic outcomes due to the minimally invasive *** recent review studies have compared multi-port laparoscopic DP(LDP)and multi-port robotic DP(RDP);most of these studies concluded multi-port RDP is more beneficial than multi-port LDP for spleen ***,there have been no comprehensive reviews of the value of reduced-port LDP and reduced-port *** To search for and review the studies on spleen preservation and the clinical outcomes of minimally invasive DP that compared reduced-port DP surgery with multi-port DP *** The PubMed medical database was searched for articles published between 2013 and *** search terms were implemented using the following Boolean search algorithm:(“distal pancreatectomy”OR“left pancreatectomy”OR“peripheral pancreatic resection”)AND(“reduced-port”OR“single-site”OR“single-port”OR“dual-incision”OR“single-incision”)AND(“spleen-preserving”OR“spleen preservation”OR“splenic preservation”).A literature review was conducted to identify studies that compared the perioperative outcomes of reduced-port LDP and reduced-port *** Fifteen articles published in the period from 2013 to 2022 were retrieved using three groups of search *** studies were added after manually searching the related ***,10 papers were selected after removing case reports(n=3),non-English language papers(n=1),technique papers(n=1),reviews(n=1),and animal studies(n=1).The common items were defined as items reported in more than five papers,and data on these common items were extracted from all *** ten studies included a total of 337 patients(females/males:231/106)who underwent *** total,166 patients(females/male

关键词： Minimally invasive surgery Robotic distal pancreatectomy Laparoscopic distal pancreatectomy Spleen preservation Reduced-port Multi-port

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Improving fNIRS Signal Quality Using Smoothing Filtering

Improving fNIRS Signal Quality Using Smoothing Filtering

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Progress in Applied Electrical Engineering (PAEE)

作者： Aleksandra Kawala-Sterniuk Dariusz Mikołajewski Luis A. Leiva Tuukka Ruotsalo Adam Lysiak Barbara Grochowicz Edward Jacek Gorzeńariczyk Adrian Luckiewicz Anna Wieczorek Mariusz Pelc Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg University of Helsinki Denmark University of Copenhagen Finland Institute of Philosophy Kazimiez Wielki University Bydgoszcz Poland

Biomedical signals are extremely difficult to analyze, mainly due to the non-stationary nature of these signals. Filtering does not always bring the desired results, because often the desired information is filtered out. In the case of EEG signals, smoothing filters gave very good results. In this paper, various types of smoothing filters for the analysis of infrared spectroscopy signals were compared.

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Graph Spiking Neural Network for Advanced Urban Flood Risk Assessment

SSRN

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SSRN 2024年

作者： Liang, Zhantu Fang, Xuhong Liang, Zhanhao Xiong, Jian Deng, Fang Nyamasvisva, Tadiwa Elisha Department of Artificial Intelligence and Data Science Guangzhou Xinhua University Guangdong Dongguan523133 China School of Computer Science and Technology Dongguan University of Technology Guangdong Dongguan523808 China Department of Automatic Control Kyrgyz State Technical University after named I.Razzakov Bishkek Kyrgyzstan Kajang Malaysia

Addressing urban floods is a critical challenge in engineering. It deeply affects urban planning, and it's vital for protecting residents and their assets. A high-performance and reliable tool for urban flood risk assessment is, therefore, indispensable. Current urban flood risk assessment tools are bifurcated into physical-mechanism and data-driven categories. Models based on physical mechanisms, such as hydrodynamic models, can deliver precise flood forecasts but require a substantial amount of data and computational time. Likewise, AI models driven by data also face challenges with data volume and are typically confined to certain cities or regions. In an innovative approach to resolve these issues, we have fused Graph Convolutional Networks with Spiking Neural Networks. To tackle the scarcity of data, we harnessed urban flooding information shared by social media users, combined with weather and geographical data, to construct a mixed urban flood risk dataset encompassing multiple cities across China. Our model, when applied to this dataset, demonstrates remarkable adaptability across diverse urban environments. Additionally, it surpasses the performance of both Graph Neural Networks and Long Short-Term Memory networks, attaining an impressive accuracy of 85.3% and also emerging as the most energy-efficient model. © 2024, The Authors. All rights reserved.

关键词： Floods

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Development of an Executive Design of a Station for Measuring the Curvature of Metallurgical Charge for Rolling 21st

Development of an Executive Design of a Station for Measurin...

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21st Polish control Conference, PCC 2023

作者： Placzek, Marek Krauze, Piotr Ryfa, Arkadiusz Jablonka, Tomasz Balys, Karol Helmich, Magdalena Badora, Dawid Florkiewicz, Bartosz Polak, Kamil Slonka, Piotr Trybulowski, Mateusz Faculty of Mechanical Engineering Silesian University of Technology Konarskiego 18A Gliwice44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Faculty of Energy and Environmental Engineering Silesian University of Technology Konarskiego 18 Gliwice44-100 Poland MOSTOSTAL ZABRZE Biprohut S.A Dubois 16 Gliwice44-100 Poland

ISBN: (纸本)9783031351723

The work is a report on the implementation of interdisciplinary group project classes conducted in accordance with the Project Based Learning approach. The aim of the project was to develop an automated station for measuring the curvature of metallurgical charge and to create its technical documentation. The station is intended to work in cooperation with devices of an automated line for spreading and transporting metallurgical charges, which is a part of the technological line for hot rolling. The task of the station is to identify the curvature value, so that a charge with exceeded parameters does not proceed to the next stage of the process (the goal is significant in terms of eliminating defects). The final outcome of the project was to be a complete technical documentation of the designed station along with the measurement algorithm. Additionally, a laboratory test station and a system design for use in real industrial conditions were developed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Hot rolling

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One-Dimensional EEG Artifact Removal Network Based on Convolutional Neural Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第1期9卷 142-159页

作者： Xiong, Jun Meng, Xiang-Long Chen, Zhao-Qi Wang, Chuan-Sheng Zhang, Fu-Quan Grau, Antoni Chen, Yang Huang, Jing-Wei School of Computer and Data Science Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China College of Electronic Engineering Shandong University of Science and Technology No. 579 Qianwangang Road Huangdao District Qingdao China College of Computer and Big Data Fuzhou University Fuzhou University Town No. 2 Wulongjiang North Road Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China Fujian Province University No. 1 Campus New Village Longjiang Street Fuqing China School of Mechanical and Automotive Engineering Fujian University of Technology No. 33 Xuefu South Road University New District Fuzhou China

The electroencephalogram (EEG) serves as a significant tool in the realms of clinical medicine, cerebral investigation, and neurological disorders research. However, the EEG records we obtain are often easily contaminated by various artifacts, which can blur or distort the underlying EEG signals and make data interpretation difficult. Generally speaking, removing EEG artifacts is considered an essential step in brain signal analysis. Therefore, removing artifacts is crucial for obtaining accurate and reliable EEG signals for subsequent analysis. Recently, deep learning techniques have found widespread application across various domains for denoising tasks, including image denoising and EEG denoising. Many advanced algorithms have been developed in image denoising, which has achieved good results in enhancing low-quality images. Moreover, it has shown superior performance in EEG denoising. In contrast, few people have devoted themselves to studying EEG denoising, and existing convolutional neural network EEG denoising methods still have problems of overfitting and poor denoising effect in Electromyograph(EMG) and ElectroOculoGram(EOG) artifact removal. Therefore, this paper proposes a method called DWINet (De-artifacting with Image-based Network for EEG Signals) based on an image dehazing network DRHNet for removing artifacts from EEG signals. Specifically, our approach DWINet, addresses the de-artifacting issue in EEG signals by converting it as an image dehazing problem and utilizes the image dehazing capability of DRHNet to enhance the denoising performance of EEG signals. Experimental results demonstrate that the proposed method outperforms the compared algorithms in removing the ocular artifact in EEG signals and exhibits higher accuracy and robustness. © 2024, J. Network Intell. All rights reserved.

关键词： Image enhancement

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New On-line Algorithms for Modelling, Identification and Simulation of Dynamic Systems Using Modulating Functions and Non-asymptotic State Estimators: Case Study for a Chosen Physical Process 21st

New On-line Algorithms for Modelling, Identification and Sim...

引用

21st International Conference on Computational science, ICCS 2021

作者： Byrski, Witold Drapala, Michal Byrski, Jędrzej Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Kraków30-059 Poland Department of Applied Computer Science AGH University of Science and Technology Al. Mickiewicza 30 Kraków30-059 Poland

ISBN: (纸本)9783030779696

The paper presents an advanced application of computation methodology with complicated algorithms and calculation methods dedicated to optimal identification and simulation of dynamic processes. These models may have an unknown structure (the order of a differential equation) and unknown parameters. The presented methodology uses non-standard algorithms for identification of such continuous-time models that can represent linear and non-linear physical processes. Typical approaches, presented in the literature, most often utilize discrete-time models. However, for the case of continuous-time differential equation models, in which both, the parameters and the derivatives of the output variable are unknown, the solution is not easy. In the paper, for the solution of the identification task, the convolution transformation of the differential equation with a special Modulating Function will be used. Also, to be able to properly simulate the behaviour of the process based on the obtained model, the exact state integral observers with minimal norm will be used for the reconstruction of the exact value of the initial conditions (not their estimate). For multidimensional process case, with multiple control signals (many inputs), additional problems arise that make continuous identification and observation of the vector state (and hence simulation) impossible by the use of the standard methods. Application of the above-mentioned methods for solving this problem will be also presented. Both algorithms, for the parameter identification and the state observation, will be implemented on-line in two independent but cooperating windows that will simultaneously move along the time axis. The presented algorithms will be tested using data collected during the heat exchange process in an industrial glass melting installation. © 2021, Springer Nature Switzerland AG.

关键词： Differential equations

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Consistent, highly throughput and space scalable distributed architecture for layered NoSQL data store

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Scientific Reports 2025年第1期15卷 1-20页

作者： Krechowicz, Adam Deniziak, Stanisław Łukawski, Grzegorz Faculty of Electrical Engineering Automatic Control and Computer Science Kielce University of Technology Kielce Poland

Maintaining strong consistency and throughput in distributed NoSQL systems is very important these days, but often impossible to achieve at the same time. Consistency problems in distributed systems result in serious consequences, e.g. data loss, while throughput problems lead to poor system performance. This paper goes beyond solving consistency issues in distributed NoSQL systems and addresses the important problem of ensuring high throughput in such systems at the same time. To this end, we proposed a novel architecture of the layered NoSQL system that enables greater throughput by using replication of data items in a dynamic way while still preserving strong consistency. It is characterized by high availability, enhanced throughput, strong consistency, and space scalability. This system was built on top of a very efficient NoSQL system, called Scalable Distributed Two-Layer Data Store (SD2DS). To develop our system, we identified and analyzed the inconsistencies in the case of SD2DS architecture with increased throughput in the case of concurrent operations execution, as well as in the case of unfinished operations. The theoretical correctness of the proposed solution was proved. Its performance was experimentally evaluated in comparison with common NoSQL systems such as MemCached and MongoDB. The results confirmed its superiority in terms of performance, so it can successfully compete with publicly available solutions. It makes it possible to use the SD2DS system in practical IT systems that require high performance and consistency. © The Author(s) 2025.

关键词： Big data Consistency Data replication NoSQL Scalability Throughput

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Energy, QoS and Security Aware Edge Services 1

引用

2nd International Symposium on Security in computer and Information sciences, EuroCybersec 2021

作者： Gelenbe, Erol Nowak, Mateusz P. Frohlich, Piotr Fiolka, Jerzy Checinski, Jacek Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland LabI3S Universite Cote d’Azur Grand Chateau Nice06103 France Faculty of Automatic Control Electronics and Computer Science The Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (数字)9783031093579

ISBN: (纸本)9783031093562

With the development of communication technologies and the increasing bandwidth of optical fibres and transmission speeds in current 5G and future 6G wireless networks, there is a growing demand for solutions organising traffic in such networks, taking into account both end-to-end transmissions and the possibility of data processing by edge services. The most pressing problems of today’s computer networks are not only bandwidth and transmission delays, but also security and energy consumption, which is becoming increasingly important in today’s climate. This paper presents a solution based on neural networks that organises network traffic taking into account the above criteria - quality of service (QoS), energy consumption and security. © 2022, The Author(s).

关键词： Quality of service

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