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2022 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2022

作者： Liu, Dong Wang, Shaoping Shi, Jian Qiao, Shichang Liu, Guiling School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big-Data Based Precision Medicine Beihang University Beijing China

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

With the development of aircraft towards multi-electricity and all-electricity, the application of electromechanical actuators has received more and more extensive attention. Compared with the traditional electro-hydraulic actuator, the transmission components of the electromechanical actuator have mechanical lockout, gradually increasing transmission clearance and other failure modes, which directly affect the safety of the whole aircraft. Therefore, the accurate status identification method of electromechanical actuator transmission components is a key technology to ensure the safety of multi-electric aircraft maneuvering. Since the actual electromechanical actuators are usually not installed with vibration sensors, it is difficult to obtain signals to characterize the wear and jamming status of transmission components. In this thesis, with the help of digital twin, a virtual dynamics model for ball screw-nut pair is established, which is the core component of the electromechanical actuator, and the vibration mode of the ball screw is captured by mapping the collected command information and load information of the electromechanical actuator into the multi-field operation conditions of the digital twin model, so as to realize the health status assessment of the ball screw. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Electromechanical actuators

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Low-cost surface modification of a biomedical Zr-2.5Nb alloy fabricated by electron beam melting

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Journal of Materials science & Technology 2023年第12期143卷 178-188页

作者： Caixu Wang Xiaoli Zhao Shujun Li Lu Liu Deliang Zhang Mitsuo Niinomi School of Materials Science and Engineering Northeastern UniversityShenyang 110819China Shi-changxu Innovation Center for Advanced Materials Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern UniversityShenyang 110819China Tianjin Key Laboratory of Bone Implants Interface Functionalization and Personalization Tianjin 300190China Institute for Materials Research Tohoku UniversitySendaiMiyagi 9808577Japan Division of Materials and Manufacturing Science Graduate School of EngineeringOsaka UniversityOsaka 565-0871Japan Department of Materials Science and Engineering Graduate School of Science and TechnologyMeijo UniversityNagoya 468-8502Japan Faculty of Chemistry Materials and BioengineeringKansai UniversityOsaka 564-860Japan

The Zr-2.5Nb alloy with a fine microstructure consisting ofαlaths was successfully prepared by electron beam melting(EBM).The thermal oxidation behaviors and kinetics of the as-built,and the EBM-built and hot isostatically pressed(HIPed)Zr-2.5Nb materials in a temperature range of 450-600°C were in-vestigated and compared with those of the alloy prepared by conventional casting and *** was found that the oxidation kinetics of the as-built and the forged materials followed the parabolic rate law during isothermal oxidation at 550°C,but the HIPed materials exhibited a parabolic-to-linear kinetic transition,suggesting that the larger grain sizes enhanced the *** oxide layers of all materials were composed of a large fraction of monoclinic zirconia phase(m-ZrO_(2))and a small fraction of tetrago-nal zirconia phase(t-ZrO_(2)),and transformed from t-ZrO_(2)to m-ZrO_(2)with increasing oxidation *** surface hardness of the as-built,the forged and the HIPed materials increased from 215,204,and 188 HV before oxidation to 902,1070,and 1137 HV after oxidation,*** cross-sections of the materi-als showed the presence of micropores and microcracks inside the oxide layers with thicknesses ranging from 4 to 8μ*** the oxidation temperature of 600°C and oxidation time duration of 3 h,a dense black m-ZrO_(2)oxide layer with smooth surface and 902 HV hardness was obtained on the EBM as-built Zr-2.5Nb materials.

关键词： Zr-2.5Nb alloy Electron beam melting Thermal oxidation Oxidation behaviors and kinetics Grain size

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Indonesian Sign Language (BISINDO) Alphabet Detection Using the You Only Look Once (YOLO) Algorithm Version 8

Indonesian Sign Language (BISINDO) Alphabet Detection Using ...

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International Conference on Computer, Control, Informatics and Its Applications (IC3INA)

作者： Foni Agus Setiawan Zakiah Aulia Rohmah Gibtha Fitri Laxmi Research Center for Data and Information Science National Research and Innovation Agency Bandung Indonesia Informatics Engineering Universitas Ibn Khaldun Bogor Indonesia

ISBN: (数字)9798331542313

ISBN: (纸本)9798331542320

People with disabilities have increased over the past few years in Indonesia. data from the Central Bureau of Statistics, Republic of Indonesia shows that the number of people with disabilities reached 212,240 in 2022 and specifically deaf people reached 19,392. This shows the need for attention to people with disabilities, especially the deaf and hard of hearing. This research aims to develop an Indonesian Sign Language (BISINDO) alphabet detection model using the You Only Look Once (YOLO) v8 algorithm. The resulting model is expected to help people in understanding sign language, thus expanding accessibility for people with disabilities. The model was trained using 2.759 images and 30 videos. The results show that the model can identify 26 letters in BISINDO alphabet including letters with motion (G, J and R) with an accuracy rate of 99%, a precision value of 99.4%, recall 98.4% and F1-score reached 98.9%. These values indicated that the model works well in predicting the BISINDO alphabet. The model built using this YOLOv8 produces sign language gesture conversion output into text, which can then be assembled into words, thus facilitating communication with deaf and hard of hearing people.

关键词： YOLO Sign language Java Accuracy Computational modeling Auditory system Predictive models People with disabilities Prediction algorithms Videos

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Personalized Federated Learning with Collaborative Aggregation Networks for Multi-Site Brain Disorder Diagnosis 4

Personalized Federated Learning with Collaborative Aggregati...

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4th International Conference on Industrial Automation, Robotics and Control engineering, IARCE 2024

作者： Si, Qian Li, Yang School of Cyber Science and Technology Beihang University Beijing China Department of Automation Science and Electrical Engineering The Beijing Advanced Innovation Center for Big Data and Brain Computing State Key Laboratory of Virtual Reality Technology and Systems Beijing China Advanced Institute of Information Technology Peking University Beijing China Beihang University Beijing China

ISBN: (纸本)9798350380323

In multi-site brain disease diagnosis studies, traditional centralized training methods necessitate sharing medical data, posing significant privacy risks. Federated learning (FL) offers a privacy-preserving solution by enabling global model training through aggregating locally trained models from multiple data centers without sharing raw data. However, current FL approaches rely on a server-based network topology, where central server failure disrupts training. Additionally, data heterogeneity across sites often slows convergence and reduces accuracy. To overcome these issues, we introduce a decentralized personalized federated learning collaborative aggregation network (pFedCAN). This framework has two core components: (1) separating local models into shared and personalized layers, and (2) forming a collaborative aggregation network via similarity detection in the shared layers. Specifically, each center trains its local model, then separates it into shared and personalized layers. The shared layer is exchanged with other centers, while the personalized layer remains local. data centers analyze similarities in received shared layers to build a collaborative network, where shared layers from similar centers are aggregated to refine the model. This approach flexibly adapts to varying levels of data heterogeneity, enhancing model training efficiency. Validation on public datasets, ABIDE I and ADHD, shows that the proposed method outperforms current leading techniques. © 2024 IEEE.

关键词： Federated learning

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MA2-FPN for Tiny Object Detection from Remote Sensing Images 15

MA2-FPN for Tiny Object Detection from Remote Sensing Images

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15th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2022

作者： Li, Saiwei Tong, Qiang Liu, Xuhong Cui, Zhanqi Liu, Xiulei College of Computer Beijing Information Science and Technology University Beijing China Beijing Information Science and Technology University Beijing Advanced Innovation Center for Materials Genome Engineering Laboratory of Data Science and Information Studies Beijing China

ISBN: (数字)9781665488877

ISBN: (纸本)9781665488877

Tiny object detection has been a challenging topic in computer vision recent years. Moreover, in remote sensing field, smaller and clustered tiny objects make its detection more difficult compared to ground-based images. This makes general detectors fail to achieve good performance when facing tiny objects in remote sensing images. In this paper, we propose a Mask Augmented Attention Feature Pyramid Network(MA2-FPN) to detect tiny objects in remote sensing images, which consists of two modules, Attention Enhancement Module(AEM) and Mask Supervision Module(MSM). Specifically, AEM aggregates tiny target context and spatial feature information by large kernel separable convolutional attention mechanism, and MSM supervises AEM through a segmentation attention loss to aggregate attention information more accurately while suppressing the influence of irrelevant background. Experiments based on the AI-TOD benchmark show that our MA2-FPN achieves state-of-the-art(SOTA) level. © 2022 IEEE.

关键词： Object detection

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Comparative Study of Word2Vec, FastText, and Glove Embeddings for Synonym Identification in Bugis Language

Comparative Study of Word2Vec, FastText, and Glove Embedding...

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2024 Beyond Technology Summit on Informatics International Conference, BTS-I2C 2024

作者： Arianto, Wahyu Ramadhan Yuyun Abrar, Ahmad Umar, Najirah Nasrullah Nurfaedah Gusnawaty Jarin, Asril Handayani University of Makassar Dept. of informatics engineering Makassar Indonesia National Research and Innovation Agency Research center for data and information science Bandung Indonesia Handayani University of Makassar Dept. of informatics management Makassar Indonesia Hasanuddin University Dept. of Regional Literature Makassar Indonesia

ISBN: (纸本)9798331508579

This research aims to analyze the performance of word vectors generated by three pre-trained word embedding models, namely Word2Vec, Fast'Text, and Glove, to detect synonyms at the word level in the Bugis language. The word vectors from each model were integrated with a Bugis language dataset containing 12,060 monolingual texts, and then trained using the Long Short-Term Memory (LSTM) model. The results show that Word2Vec has the highest accuracy of 0.9412, followed by Glove with 0.9353 and FastText with 0.9262. Additional experiments with cosine similarity revealed that Glove performed best for predicting synonyms across all word occurrence frequency categories, while FastText and Word2Vec had inferior results. These findings indicate that although high training accuracy is achieved, it does not always imply that the model will excel in predicting synonyms. © 2024 IEEE.

关键词： Embeddings

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Spatial-temporal evolution analysis of Dongting Lake using multi-source remote sensing data 6

Spatial-temporal evolution analysis of Dongting Lake using m...

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6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Zheng, Yuanmao Fu, Mingzhe He, Qiuhua He, Yuanrong Huang, Jianwei Liang, Xueyu Liu, Xinyue School of Environmental Science and Engineering Xiamen University of Technology Xiamen361024 China Technology Innovation Center for Ecological Conservation and Restoration in Dongting Lake Basin Ministry of Natural Resources Changsha410007 China Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781510688018

This study analyzes the Dongting Lake's spatiotemporal changes using long-term remote sensing data. The key findings include: (1) From 2005 to 2015, the lake's water area decreased by 61.12% during the wet season and increased by 50.38% in the arid season. (2) The centroid migration was most significant from 2005 to 2010 (8565.82 meters) due to water area fluctuations but decreased to 0.95 meters from 2010 to 2015. (3) Climate factors, particularly precipitation, had a moderate correlation with area changes (0.20 in the wet season, 0.31 in the dry season). The study also explores the impact of human activities on water area changes, providing valuable insights for sustainable development strategies. © 2025 SPIE.

关键词： Lakes

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data-Driven Intersection Safety Evaluation Methodology and Analysis 23

Data-Driven Intersection Safety Evaluation Methodology and A...

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23rd COTA International Conference of Transportation Professionals: Emerging data-Driven Sustainable Technological innovation in Transportation, CICTP 2023

作者： Wu, Pingping Lu, Guangquan Liu, Miaomiao Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang Univ. Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang Univ. Beijing China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Southeast Univ. Nanjing China

ISBN: (数字)9780784485040

ISBN: (纸本)9780784485040

With the development of information and sensing technologies, a wide variety of intersection traffic data is available. The purpose of this paper is to make full use of video and commercial vehicle trajectory data to deeply explore the intersection safety status. In this paper, based on different sample sizes, different sampling frequencies, and different accuracies of data, the safety analysis of intersections is carried out from micro and macro aspects based on post-encroachment time (PET) and vehicle deceleration behavior, respectively. On the one hand, we use the full-sample and high-precision trajectory data extracted from video to analyze the safety of each region of intersection based on PET. On the other hand, using the trajectory data with low penetration rate and low sampling frequency extracted from the positioning data of the online car-hailing, a distribution fit, and non-parametric test are conducted for the vehicle deceleration behavior, and then the overall safety state of the intersection is evaluated. The results can provide ideas for the identification of intersection risk points and the application of different kinds of data on intersection safety evaluation. © ASCE.

关键词： Commercial vehicles

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Dynamic Formation Tracking of Multi-agent Systems with Bounded Unknown Leader Input 5th

Dynamic Formation Tracking of Multi-agent Systems with Bou...

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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Su, Piaoyi Dong, Xiwang Zhao, Qin Li, Qingdong Ren, Zhang School of Automation Science and Electronic Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Beijing Institute of Control and Electronics Technology Beijing100038 China

ISBN: (纸本)9789811939976

This literature investigate the dynamic formation tracking problem of multiple Lagrange systems with linear nonautonomous leader over directed topology. In order to estimate the leader system, a distributed control scheme is proposed firstly by constructing adaptive distributed observer. Secondly, this paper design a nonlinear function to decrease the influence from the leader’s bounded unknown input. Then, the dynamic formation tracking problem of multiple Euler-Lagrange systems with nonlinear uncertainties and disturbances is solved by distributed tracking algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Detection of the Anaerobic Threshold from Cardiopulmonary Exercise Test data with EO-Attention-LSTM 42

Detection of the Anaerobic Threshold from Cardiopulmonary Ex...

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42nd Chinese Control Conference, CCC 2023

作者： Guo, Xin Lun, Zhaoxin Chu, Qitong School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin300130 China Qinhuangdao Research Institute National Research Center for Rehabilitation Technical Aids Qinhuangdao066004 China Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology Tianjin300401 China

ISBN: (纸本)9789887581543

The physiological indicators at the anaerobic threshold play an essential role in guiding scientific exercise. The gold standard methodology for detecting the anaerobic threshold is expert visual inspection, but its efficiency is low. Given the above problems, we propose an anaerobic threshold detection method combining the equilibrium optimizer (EO) algorithm and Attention-LSTM, which was verified on the data of 334 cardiopulmonary exercise tests. Through comparative experiments, the coefficient of determination (R2) of the Attention-LSTM anaerobic threshold detection model is 0.797, the R2 of the Attention-LSTM model after hyperparameter optimization by EO is 0.834. The results show that the detection error of the anaerobic threshold detection model proposed in this paper is consistent with that of experts, which can provide a certain reference value. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Long short-term memory

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