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Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2024

作者： Dostalova, Tatjana Nocar, Adam Eliasova, Hana Macek, Milan Hliňáková, Petra Procházka, Aleš Department of Stomatology Charles University 2nd Faculty of Medicine Motol University Hospital Prague V Uvalu 84 Prague150 06 Czech Republic Department of Biology and Medical Genetics Charles University 2nd Faculty of Medicine Motol University Hospital Prague V Uvalu 84 Prague150 06 Czech Republic Department of Computing and Control Engineering University of Chemistry and Technology in Prague Prague166 28 Czech Republic

ISBN: (纸本)9781510668959

In prosthodontics, 3D printing primarily relies on intraoral scanners equipped with a handheld camera, computer, and software. These scanners capture and reconstruct the three-dimensional geometry of the dental arch. Traditional plaster models of teeth are typically obtained through an impression process, where the choice of appropriate impression material is determined by the desired model type. Subsequently, the dental impression is covered with plaster in the laboratory. Three-dimensional (3D) printing, formerly an industrial technology with a development history spanning over forty years, is based on creating a 3D model of any shape from a digitally prepared scan, employing an addition of selected material. The thickness of the layers in the printing process depends on the technology of the used printer and the quality of the print. The layers are systematically applied, and cured, and, after this process, a complete model is generated. 3D printing can be utilized to prepare models for various applications, including prosthodontics, orthodontics, surgery, and more. Our study aimed to assess stereolithography-printed models in vitro and in vivo over the last three years. © 2024 SPIE.

关键词： Dentistry

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CPT-based Active Power Filter with Repetitive controller and Capacitor Voltage Feedforward under Non-Ideal Grid

CPT-based Active Power Filter with Repetitive Controller and...

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IEEE ANDESCON

作者： José de Arimatéia O. Filho Paulo Fernando Silva Luis De Oro Arenas Tiago Davi Curi Busarello Helmo Kelis Morales Paredes Institute of Science and Technology of Sorocaba São Paulo State University (Unesp) Sorocaba Brazil Department of Control Automation and Computing Engineering Federal University of Santa Catarina (UFSC) Blumenau Brazil

ISBN: (数字)9798350355284

ISBN: (纸本)9798350355291

This paper proposes the design of a repetitive controller along with capacitor voltage feedforward applied to an LCL filter active power filter (APF). The repetitive controller can operate in systems with disturbances exhibiting high harmonic content and the feedforward action can reshape the output impedance of the APF. The conservative power theory (CPT) is proposed to obtain reference signals for the purpose of total mitigation of unwanted currents. The proposed technique ensures that only the active current flows through the electrical grid, while maintaining the stability of the APF-grid system through passivity theory. Finally, the proposed control strategy is validated using the Matlab/Simulink® software under several conditions of grid imbalances and harmonic distortions.

关键词： Power filters Stability criteria Capacitors Power system stability Active filters Filtering theory Impedance Voltage control Feedforward systems Power harmonic filters

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Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

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Computers, Materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),Multi-Layer Perceptron(MLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： Metamaterial antenna dipper throated optimization feature selection parameters prediction

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Survey on Foundation Models for Prognostics and Health Management in Industrial Cyber-Physical Systems

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2024年 2卷 264-280页

作者： Liu, Ruonan Zhang, Quanhu Han, Te Yang, Boyuan Zhang, Weidong Yin, Shen Zhou, Donghua Shanghai Jiao Tong University Department of Automation Shanghai200240 China Tianjin University College of Intelligence and Computing Tianjin300350 China Beijing Institute of Technology Center for Energy and Environmental Policy Research Beijing100081 China Beijing Institute of Technology School of Management Beijing100081 China Beijing Laboratory for System Engineering of Carbon Neutrality Beijing100081 China Nanjing University Center for Advanced Control and Smart Operations Suzhou215163 China Hainan University School of Information and Communication Engineering Haikou570228 China Shanghai Jiaotong University Department of Automation Shanghai200240 China Norwegian University of Science and Technology Trondheim7491 Norway

Industrial Cyber-Physical Systems (ICPS) integrating disciplines such as computer science, communication technology, and engineering, have become a crucial component of modern manufacturing and industry. However, ICPS faces numerous challenges during long-term operation, including equipment faults, performance degradation, and security threats, etc. To achieve efficient maintenance and management, prognostics and health management (PHM) has been widely applied in the critical tasks of ICPS such as fault prediction, health monitoring, and maintenance decision-making. The emergence of large-scale foundation models (LFMs) like BERT and GPT marks a significant advancement in artificial intelligence (AI) technology, demonstrating substantial application potential in multiple fields. The accumulation of AI technology, rapid development of LFMs, and the abundance of industrial data and industrial process knowledge provide the foundational conditions for the construction and advancement of industrial LFMs. However, there is currently a lack of consensus on applying LFMs of PHM in ICPS, necessitating a systematic review and roadmap to clarify future development directions. To bridge this gap, this survey provides a comprehensive survey and understanding of the recent advances in LFMs of PHM in ICPS. It provides valuable references for decision makers and researchers in the industry, and helps to further improve the reliability, availability and safety of ICPS. © 2023 IEEE.

关键词： Cyber Physical System

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Research on Fault Diagnosis Method and Application of Gas Turbine Based on Acoustic Imaging Technology

Research on Fault Diagnosis Method and Application of Gas Tu...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Yan, Wen Hu, Mingliang Wen, Fei Guo, Peipei Guo, Ziang AVIC Shanghai Aviation Measurement & Control Technology Research Institute Shanghai201601 China Xi'an Aeronautics Computing Technique Research Institute AVIC Xi'an710068 China Department of Electronics College of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Aviation Technology for Fault Diagnosis and Health Management Technology Shanghai201601 China

Gas turbine health management is of great significant for enhancing flight safety and reducing maintenance costs. Based on the architecture of gas turbine fault identification system, a multi-arm spiral microphone array with high positioning accuracy, high beam resolution, and strong anti-interference capability is designed in this paper with simulation and experiment. On this basis, by utilizing multi-channel acoustic digital acquisition and analysis equipment, high-precision, wide dynamic range, and high-real-time acquisition of audio data from the combustion chamber of gas turbines are achieved. An audio data analysis strategy based on feature extraction and an autoencoder network construction strategy are proposed, fulfilling the imaging of audio data from the combustion chamber of gas turbines, which can effectively identify gas turbine faults. Experiments conducted on the platform of the multi-arm spiral microphone array indecates that the proposed fault detection strategy has an accuracy rate of over 98%. This is of great theoretical significance and practical value for enhancing the level of gas turbine fault detection, and improving the performance, reliability, and lifespan of gas turbine systems. © The Institution of engineering & Technology 2024.

关键词： Combustion chambers

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Development of the Predictive control System for Ethylbenzene Dehydration 3

Development of the Predictive Control System for Ethylbenzen...

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3rd International Conference on control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Popov, Alexey Tikhomirov, Sergey Neizvestny, Oleg Podvalny, Semyon Voronezh State University of Engineering Technologies Department of Information and Control Systems Voronezh Russia Voronezh State Technical University Department of Automated and Computing Systems Voronezh Russia

ISBN: (纸本)9781665439817

the article describes the application of the predictive functional control method in the synthesis of an automated control system for the ethylbenzene dehydrogenation. Based on the results of the control object system analysis, the choice of the control method has been justified, a review and assessment of the possibility of using various types of control devices have been carried out. Within the framework of the model-based design concept, a control system has been synthesized that implements predictive functional control (PFC) of the styrene concentration at the output from the first stage of the reactor block. Structural synthesis has been performed and an algorithm for the functioning of the control system has been developed. A complex of dynamic models describing heat exchange processes and physicochemical transformations occurring during the dehydrogenation of ethylbenzene has been used as a structural element for constructing a predicted trajectory of changes in the control and controlled parameters. The calculation of the control action has been carried out taking into account the inertia of the process equipment, the state parameters of the reactor's catalytic layer, the values of energy flows and concentrations of the components. A comparative analysis of the results of calculating transient processes for the main channel of the control system, obtained using a PID structure controller and a control device that implements the PFC control method, has been presented. It was found that the use of the proposed algorithm and control system allows for the on-line computation of control actions and timely compensation for the decrease in the activity of the reactor's catalytic layer, which, in turn, prevents the decrease in the yield of the target product below the preset value, and also increases the energy efficiency and productivity of the reactor plant. © 2021 IEEE.

关键词： Styrene

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Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

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Computers, Materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed M.El-kenawy Nagwan Abdel Samee Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Ahmad Taher Azar Nima Khodadadi Reham A.Ghanem Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical *** all the cancers unveiled,breast cancer is considered the second most severe ***,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical *** recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death *** this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated *** proposed algorithm is evaluated using four publicly available breast cancer *** evaluation results show the effectiveness of the proposed approach from the accuracy and speed *** prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted *** addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed *** best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： Medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics

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Decentralized Goal Function-Based control of DGSs in Microgrid Applications

Decentralized Goal Function-Based Control of DGSs in Microgr...

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Power Tech Conference

作者： Ivana Isakov Milan Rapaić Marko Vekić Ivan Todorović Department of Power Electronic and Telecommunication Engineering Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

control structures governing distributed generation sources (DGSs), utilized in microgrids, have to provide several important functionalities and generally secure stable network operation. The large majority of these control structures are based either on droop (or droop-derived) or other, more advanced, control paradigms. The former are overly simplistic and necessitate control layerization and many extensions for the overall control structure to be applicable in the general case. The latter are either too complex or application-specific, rendering them unfit to be adopted as a general tool for controlling DGSs in microgrids. The control scheme derived in this paper is based on a goal function that simultaneously secures safe and stable operation, respecting voltage amplitude and frequency limits, and precise active power exchange. As such, the proposed control scheme integrates what is traditionally called primary and secondary control of microgrids and enables reliable peer-to-peer power exchange. The control scheme was tested using simulation tools and together with the simulation results, a performance analysis is provided.

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DexRepNet: Learning Dexterous Robotic Grasping Network with Geometric and Spatial Hand-Object Representations

arXiv

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arXiv 2023年

作者： Liu, Qingtao Cui, Yu Ye, Qi Sun, Zhengnan Li, Haoming Li, Gaofeng Shao, Lin Chen, Jiming College of Control Science and Engineering Zhejiang University Hangzhou310027 China Department of Computer Science National University of Singapore 15 Computing Dr 117418 Singapore

Robotic dexterous grasping is a challenging problem due to the high degree of freedom (DoF) and complex contacts of multi-fingered robotic hands. Existing deep reinforcement learning (DRL) based methods leverage human demonstrations to reduce sample complexity due to the high dimensional action space with dexterous grasping. However, less attention has been paid to hand-object interaction representations for high-level generalization. In this paper, we propose a novel geometric and spatial hand-object interaction representation, named DexRep, to capture object surface features and the spatial relations between hands and objects during grasping. DexRep comprises Occupancy Feature for rough shapes within sensing range by moving hands, Surface Feature for changing hand-object surface distances, and Local-Geo Feature for local geometric surface features most related to potential contacts. Based on the new representation, we propose a dexterous deep reinforcement learning method DexRepNet to learn a generalizable grasping policy. Experimental results show that our method outperforms baselines using existing representations for robotic grasping dramatically both in grasp success rate and convergence speed. It achieves a 93% grasping success rate on seen objects and higher than 80% grasping success rates on diverse objects of unseen categories in both simulation and real-world ex eriments © 2023, CC BY-NC-ND.

关键词： Reinforcement learning

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Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

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Computers, Materials & Continua 2023年第4期75卷 1827-1845页

作者： Abdul Sattar Palli Jafreezal Jaafar Manzoor Ahmed Hashmani Heitor Murilo Gomes Aeshah Alsughayyir Abdul Rehman Gilal Department of Computer and Information Sciences Universiti Teknologi PETRONAS(UTP)Seri Iskandar32610Malaysia Centre for Research in Data Science UTPPerak32610Malaysia High Performance Cloud Computing Centre(HPC3) UTPPerak32610Malaysia School of Engineering and Computer Science Victoria University of WellingtonWellington6012New Zealand AI Institute University of Waikato WellingtonHamilton3240New Zealand Anti-Narcotics Force Ministry of Narcotics ControlIslamabad46000Pakistan College of Computer Science and Engineering Taibah UniversityMadinah42353Saudi Arabia

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more *** existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s *** analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream ***, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority *** study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

关键词： Classification data streams class imbalance concept drift class imbalance ratio

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