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2024 International Conference on Advanced Robotics, Automation engineering and Machine Learning, ARAEML 2024

作者： Du, Yao Xie, Pan Peng, Taiying Hu, Xiaohui School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400717116

Sign language translation aims to transform continuous sign language videos into text, thereby mapping sign language actions onto natural language. Current research primarily focuses on the Transformer's encoder-decoder architecture, employing an autoregressive (AR) approach for SLT. This one-by-one token generation method has a slow speed to translate. We design a Non-Autoregressive Sign Language Translation (NA-SLT) model based on Transformer Encoder. The proposed model consists of three components: The text-encoder, sign-encoder, and sign-Text-encoder. Both the text-encoder and sign-encoder utilize the Encoder to model single-modality data. The sign-Text-encoder effectively engages with multi-modal data, producing high-quality corresponding text after minimal refinement iterations. Moreover, during model training, we devise a double-mask strategy. In addition to traditional random masking, the schedule allocates mask probabilities based on each word's frequency, ensuring long-Tail tokens have an increased chance of being masked and receiving extensive training. We evaluate the model on PHOENIX-2014T, and the results indicate that NA-SLT approaches the performance of AR models on BLEU (21.06) and ROUGE(49.59) metrics while significantly improving translation speed (5.4x-7.9x). © 2024 ACM.

关键词： Metadata

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Accuracy Enhancement in Sweep-Free BOTDA Enabled by Simultaneous Full-Field Brillouin Spectrums Measurement

Accuracy Enhancement in Sweep-Free BOTDA Enabled by Simultan...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： He, Huan Zhao, Zhiyong Tang, Ming National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China

Utilizing frequency-agility double-sideband digital optical frequency comb, a fast BOTDA based on full-field Brillouin spectrums is demonstrated with a record 4-m spatial resolution and less than 1.4-MHz frequency unc... 详细信息

ISBN: (纸本)9781957171395

关键词： Optical depth

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Implementation and uniformity calibration of LED array for photodynamic therapy

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Journal of Innovative Optical Health sciences 2022年第4期15卷 61-69页

作者： Xu Wang Jiyuan Xiong Xiaoming Hu Qin Li Key Laboratory of Convergence Medical Engineering System and Healthcare Technology Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing 100081 P.R.China

Irradiance uniformity is an important parameter for a Photodynamic Therapy(PDT)*** calibration and verification of a LED array light source based on computer vision technology were implemented and carried ***,the correlation coe±cients between the pulse width modulate value and the irradiance were ***,the correction of the actual light center and divergence angle were solved by image processing to reduce errors from each LED ***,uniformity was optimized according to the irradiance formula of the Lambertian *** lowest coe±cients of variation of irradiance were 4.87%in a 5 cm×12 cm area and 3.55%in a 3 cm×10 cm area within the depth range of 8–12 cm when the expected irradiance was 100 mW/cm^(2).This finding indicated that the light source can achieve a more uniform illumination and provide a better therapeutic effect for the PDT of port-wine stains.

关键词： Photodynamic therapy computer vision light source calibration

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Cooperative Optimization Method of UAV Swarm for Multi-objective High-Precision Location 5th

Cooperative Optimization Method of UAV Swarm for Multi-objec...

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

作者： Li, Bowen Ji, Xiaoting Huang, Yuanling School of Information System Engineering Information Engineering University Zhengzhou450001 China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu610041 China

ISBN: (纸本)9789811939976

In the field of electromagnetic radiation source location, using UAVs to locate the radiation source target has become a new location method. At present, the UAV swarm cooperative optimization method for high-precision location has some challenges, such as insufficient ability of multi-objective high-precision location, poor timeliness and so on. To solve these problems, this paper proposes a cooperative optimization method of UAV swarm for multi-objective location. Firstly, the multi-objective joint location accuracy is derived, which is taken as the objective function of swarm cooperative optimization. Secondly, in order to allocate multiple UAVs to multiple targets efficiently, the initialization strategy based on target isolation and the random allocation method of UAV based on probability are proposed. Finally, by combining the above improved strategies, an optimization method of UAV swarm cooperative location is proposed. Through the analysis of experimental results, the cooperative optimization method in this paper has obvious advantages in global optimization and convergence ability, which can improve the joint location accuracy and optimization speed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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RETIA: Relation-Entity Twin-Interact Aggregation for Temporal Knowledge Graph Extrapolation 39

RETIA: Relation-Entity Twin-Interact Aggregation for Tempora...

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Liu, Kangzheng Zhao, Feng Xu, Guandong Wang, Xianzhi Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan China University of Technology Sydney Data Science and Machine Intelligence Lab Sydney Australia

ISBN: (纸本)9798350322279

Temporal knowledge graph (TKG) extrapolation aims to predict future unknown events (facts) based on historical information, and has attracted considerable attention due to its great practical significance. Accurate representations (embeddings) of entities and relations form the basis of TKG extrapolation. Recent work has been devoted to improving the rationality of entity representations. However, on the one hand, ignoring relation modeling results in incomplete relation representations;therefore, some approaches aggregate only immediately adjacent entities of relations, but this can lead to the "message islands"problem of relation modeling. On the other hand, ignoring the association constraints between relations and entities can make the embeddings of both relations and entities prone to overfitting. To address the abovementioned challenges, we propose an advanced method, namely, RETIA. For the former issue, we generate twin hyperrelation subgraphs for each historical subgraph and then aggregate both the adjacent entities and relations in the hyperrelation subgraphs through a graph convolutional network (GCN). About the latter concern, we propose a twin-interact module (TIM), which provides communication channels for relation aggregation and entity aggregation during the evolution of the historical sequence. Experiments conducted on five public datasets show that RETIA has made great improvements across several evaluation metrics. Our released code is available at https://***/CGCL-codes/RETIA. © 2023 IEEE.

关键词： Extrapolation

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A novel U-net model for brain tumor segmentation from MRI images

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Alexandria engineering Journal 2025年 126卷 220-230页

作者： Obayya, Marwa Alshuhail, Asma Mahmood, Khalid Alanazi, Meshari H. Alqahtani, Mohammed Aljehane, Nojood O. Almansour, Hamad Al-Hagery, Mohammed Abdullah Department of Biomedical Engineering College of Engineering Princess Nourah bint Abdulrahman University PO Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems College of Computer Sciences & Information Technology King Faisal university Saudi Arabia Department of Information Systems Applied College at Mahayil King Khalid University Saudi Arabia Department of Computer Science College of Sciences Northern Border University Arar Saudi Arabia Department of Information System and Cyber Security College of Computing and Information Technology University of Bisha Bisha61922 Saudi Arabia Department of Computer Science Faculty of Computers and Information Technology University of Tabuk Tabuk Saudi Arabia Applied Collage Najran University Najran Saudi Arabia Department of Computer Science College of Computer Qassim University Saudi Arabia

Segmentation of brain tumors aids in diagnosing the disease early, planning treatment, and monitoring its progression in medical image analysis. Automation is necessary to eliminate the time and variability associated with traditional segmentation methods. Convolutional neural networks (CNNs) and U-Net architectures have demonstrated their efficiency and effectiveness in segmenting brain tumors from MRI images using deep learning techniques. The paper presents an improved U-Net-based segmentation algorithm that integrates nested skip paths to improve encoder-decoder feature fusion. The performance of segmentation was optimized by utilizing a variety of activation functions and loss functions, including Dice Loss and Intersection over Union (IoU). A high level of accuracy was demonstrated in the proposed model when it was evaluated using the LGG Segmentation Dataset. The proposed approach for segmenting medical images has been shown to be both robust and efficient in a comparative analysis. © 2025 The Authors

关键词： Convolutional neural networks

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Enhancing the Performance of BOCDA Sensor using Deconvolution Algorithm

Enhancing the Performance of BOCDA Sensor using Deconvolutio...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Chen, Shuyan Zhao, Zhiyong He, Huan Wei, Weilun Zou, Xuan Tang, Ming National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China

We have achieved a fourfold-improved spatial resolution and a much wider dynamic range without extra system hardware complexity by using deconvolution algorithm to post-process the data of traditional BOCDA sensor. &#... 详细信息

ISBN: (纸本)9781957171395

关键词： Deconvolution

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Vector Bending Sensor Based on Tapered Few-Mode Multi-Core Fiber Enabled by Power Monitoring

Vector Bending Sensor Based on Tapered Few-Mode Multi-Core F...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Liu, Zhuyixiao Jiang, Zijian Wu, Qixuan Zhang, Fengming Du, Haoze Yao, Yucheng Zhao, Luming Tang, Ming National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China

We proposed a vector bending sensor based on tapered few-mode multi-core fiber. The sensor could accomplish the recognition of direction and curvature through only power monitoring. The theoretical curvature sensitivity is higher than 0.14/m-1 within the interval of 2.5 m-1 to 10 m-1 © Optica Publishing Group 2024

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Micro-interfaces modulation by UV-ozone substrate treatment for MPEA vapor fluorescence detection

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Nano Research 2023年第3期16卷 4055-4060页

作者： Bin Li Keke Li Wei Xu Mingzhu Yan Jianhao Zhao Wukun Zhang Mingshuai Yuan Yanyan Fu Qingguo He Jiangong Cheng State Key Lab of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Physical Science and Technology ShanghaiTech UniversityShanghai 201210China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China

Drug abuse directly endangers human health and social security,hence its sensitive and rapid detection is vitally *** recent years,organic film-based fluorescent sensing technology has attracted more and more attention in the detection of drugs and explosives due to its advantages of simple operation and rapid *** film-based fluorescent sensors,in addition to sensitive materials,the surface morphology of the film is also an important factor affecting the *** previous studies,the regulation of surface morphology mainly depends on concentration changes or complex ***,a novel fluorescent polymer probe was designed and synthesized,and a simple and efficient ultraviolet(UV)-ozone substrate treatment method is used to adjust their surface *** results show that film has an excellent fluorescence enhancement effect upon exposure to methylphenethylamine(MPEA,a simulant of methamphetamine)*** sensing effect of the film is significantly improved after UV-ozone substrate treatment,and the limit of detection was decreased by 10.4 times from 2.59 to 0.25 *** experiments show that the sensing performance of other fluorescent probe can also be improved by the UV-ozone substrate *** convenient and general method may become a very effective approach to improve the performance of film-based fluorescent sensors.

关键词： fluorescence sensing ultraviolet(UV)-ozone substrate treatment organic sensing materials film-based gas sensors

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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