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Chinese Intelligent Automation Conference, CIAC 2023

作者： Chen, Maojian Luo, Xiong Peng, Qiaojuan Shen, Hailun Huang, Ziyang School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Shunde Innovation School University of Science and Technology Beijing Foshan528399 China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083 China Ouyeel Co. Ltd. Shanghai201999 China

ISBN: (纸本)9789819961863

Quality objection texts provided by customers are crucial for steel e-commerce platforms. How to classify these texts and quickly provide corresponding solutions is very important. This article presents an approach based on deep learning for classifying steel quality objection text. With the help of deep learning, the proposed model can automatically extract semantic features from unstructured text without manual intervention. Different from traditional methods, to further improve the model’s performance, this article employs contrastive learning to learn more robust representations. The evaluation of this approach on a large dataset of steel quality objection text demonstrates that it outperforms traditional methods and achieves excellent results. The proposed approach enables the identification of quality issues quickly, which is of utmost importance for the steel industrial practical implications. By reducing the time and resources required to identify quality objections, the proposed approach can help to improve the efficiency of the steel industry. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Large dataset

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Bandwidth Enhancement of Silicon Thermo-Optic Phase Shifter with Electronic-Photonic Co-Design

Bandwidth Enhancement of Silicon Thermo-Optic Phase Shifter ...

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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： Han, keyi Lu, Liangjun Li, Xin Liu, Chuxin Xu, Weihan Guo, Yuyao Chen, Jianping Zhou, Linjie State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China

Based on a resistance-capacitance equalizer, we demonstrated a silicon thermo-optic phase shifter with a rise time of 2.3 µs and a modulation bandwidth of 250 kHz, offering 10 times enhancement over the original ... 详细信息

ISBN: (纸本)9781957171395

关键词： Silicon photonics

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Embedding VLAD in Transformer for Video Question Answering

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Jisuanji Xuebao/Chinese Journal of Computers 2023年第4期46卷 671-689页

作者： Guo, Dan Yao, Shen-Tao Wang, Hui Wang, Meng School of Computer and Information Engineering Hefei University of Technology Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230094 China Key Laboratory of Knowledge Engineering with Big Data（Hefei University of Technology） Ministry of Education Hefei230601 China Intelligent Interconnected Systems Laboratory of Anhui Province（Hefei University of Technology） Hefei230601 China

Video question answering（VideoQA）is a typical cross-modal understanding task. Its challenge lies in how to learn appropriate multimodal representation and cross-modal correlation for answer inference. Most existing video question answering methods focus on the latter，e. g.，relationship learning between each video frame or clip and word. In this work， we devote to advanced feature embedding of both video and query. We develop a clustering-based VLAD technique for VideoQA. The novelty of our work is the joint exploitation of temporal aggregation and correlation in multimodality. We propose an end-to-end trainable Transformed VLAD embedding network， named TVLAD-Net. TVLAD-Net constructs a differentiable aggregation network module（i. e.， convolutional Residual-less VLAD Block）to generate compact VLAD descriptors（transforming N frames，clips or words to compact K descriptors while K © 2023 Science Press. All rights reserved.

关键词： Semantics

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Are LLMs Aware that Some Questions are not Open-ended?

arXiv

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arXiv 2024年

作者： Yang, Dongjie Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

Large Language Models (LLMs) have shown the impressive capability of answering questions in a wide range of scenarios. However, when LLMs face different types of questions, it is worth exploring whether LLMs are aware that some questions have limited answers and need to respond more deterministically but some do not. We refer to this as question awareness of LLMs. The lack of question awareness in LLMs leads to two phenomena that LLMs are: (1) too casual to answer non-open-ended questions or (2) too boring to answer open-ended questions. In this paper, we first evaluate the question awareness in LLMs. The experimental results show that LLMs have the issues of lacking awareness of questions in certain domains, e.g. factual knowledge, resulting in hallucinations during the generation. To mitigate these, we propose a method called Question Awareness Temperature Sampling (QuATS). This method enhances the question awareness of LLMs by adaptively adjusting the output distributions based on question features. The automatic adjustment in QuATS eliminates the need for manual temperature tuning in text generation and consistently improves model performance in various benchmarks. Copyright © 2024, The Authors. All rights reserved.

关键词： Natural language processing systems

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Research on Pedestrian Gender Detection Based on A Lightweight Model

Research on Pedestrian Gender Detection Based on A Lightweig...

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Chinese Control and Decision Conference, CCDC

作者： Hu Yuling Wang Xinyi Zou Weiguang Institute of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture Beijing China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In recent years, a variety of emergency events have been occurring in buildings in countries. For there are some differences between male and female in movement ability and evacuation behavior, gender has a non-negligible impact on evacuation and decision-making of emergency events. Thus, it is of great practical significance to detect the gender of pedestrians at entrances or exits of buildings in real time to grasp the proportion of different gender people in buildings and to formulate emergency warning or evacuation strategies scientifically. In response to the requirement of rapid emergency response, this paper proposes a pedestrian gender detection method based on a lightweight object detection model YOLOX-Tiny. In addition, considering the inaccurate pedestrian gender detection caused by the change of pedestrian posture and camera angle, the attention mechanism CBAM is introduced to enhance the ability of filtering a large amount of redundant information, obtaining key information and acquiring pedestrian gender characteristic information. Through the experiments of self-made pedestrian gender datasets, the results show that the detection accuracy of the improved model is increased by 1.8%, and the detection speed reaches 251FPS, which can meet both speed and accuracy of pedestrian gender detection in emergencies.

关键词： Pedestrians Accuracy Attention mechanisms Filtering Buildings Urban areas Object detection

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RGB-D SLAM Method Based on Feature Association in Dynamic Environment

RGB-D SLAM Method Based on Feature Association in Dynamic En...

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Artificial Intelligence Technology (ACAIT), Asian Conference on

作者： Baofu Fang Hao Wang School of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Hefei China

Simultaneous localization and mapping (SLAM) is one of the current research hotspots. However, in visual SLAM for dynamic environments, inaccurate detection of object motion states and incomplete dynamic region culling will lead to large localization errors. To address these issues, this paper proposes an RGB-D SLAM method based on feature association. The method has strongly correlated features in time and space according to the input image sequence. Using the moving probability of the feature points in the previous frame, the movement of the feature points in the current frame is calculated in combination with the dynamic corner points screened in the current frame. Then, the motion state of the object is determined according to the proportion of different feature points. Then combined with semantic information and object depth information, the fast search method is used to obtain accurate dynamic regions. Finally, the selected effective feature points are used to estimate the camera pose and establish a static map of the environment. This paper evaluates the robustness and accuracy of our method on the TUM dataset and real environment, and the results show that our method can significantly improve the system tracking effect and reduce the system tracking error compared with other SLAM methods in dynamic environments.

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A review on global spatial distribution,sources and toxicity of perfluoroalkyl acid and prospect in the cryosphere

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Journal of Mountain Science 2025年第1期22卷 167-183页

作者： LI Bowen Du Wentao KANG Shichang CHEN Jizu JIANG Youyan YIN Lichen LU Changsheng LIU Hongyi State Key Laboratory of Cryospheric Science and frozen soil engineering Northwest Institute of Eco-Environment and ResourcesChinese Academy of Sciences(CAS)Lanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China Gansu Provincial Industry Technology Center of Intelligent Equipment and Big Data for Disaster Prevention Northwest Institute of Eco-Environment and ResourcesChinese Academy of Sciences(CAS)Lanzhou 730000China Lanzhou Regional Climate Center Lanzhou 730000China School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Energy and Power Engineering Lanzhou University of TechnologyLanzhou 730000China Zhangye Meteorological Service Zhangye 734000China

Perfluoroalkyl acid analogs(PFAAs)are a class of chemically stable environmentally persistent organic pollutants(POPs)that are difficult to degrade and have a strong capacity to accumulate in the human *** have been found to be biotoxic to humans and have been detected in various environmental media,especially in the cryosphere at trace *** cryosphere,sensitively responds to climate change,plays a crucial role in the global water,carbon and energy ***,researches on cryosphere PFAAs especially in Tibetan Plateau(TP)is ***,we summarize the physicochemical properties,physiological toxicity,spatiotemporal distribution,sources,diffusion and migration pathways,as well as analysis and removal methods of PFAAs in the cryosphere *** results show that PFAAs pollutants are mainly produced and distributed in the more economically developed countries in Europe and the United States,as well as in East Asia,and PFAAs can be transported by atmospheric circulation and water cycle to remote regions including cryosphere *** current detection methods for PFAAs in cryosphere need to be further refined for increased accuracy and *** is also a need to develop more effective removal methods that will reduce the environmental and human threats posed by these ***,we propose key scientific questions for future research in cryosphere including PFAAs redistribution influenced by cryosphere changes,human activities,and the interaction of other spheres.

关键词： Perfluoroalkyl acid Cryosphere Physiological toxicity Analytical method Removal method

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Single-Stage Grasping Algorithm for the Manipulator Based on Rotational Gaussian Encoding 13

Single-Stage Grasping Algorithm for the Manipulator Based on...

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13th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2023

作者： Liu, Zhenghao Liu, Yizhe Yang, Guowei Chen, Dongyue Jia, Tong College of Information Science and Engineering Northeastern University Shenyang China Foshan Graduate School of Innovation Northeastern University China Northeastern University Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education China

ISBN: (纸本)9798350315196

As we all know, there is an unsolved problem for robots to accurately and quickly grasp unknown objects in an unstructured environment. In order to describe the pose information of objects more accurately, a rotational Gaussian encoding method is proposed in this paper. Different from the traditional 2-D Gaussian encoding to represent ground-truth, this method introduces rotation information based on 2-D Gaussian. Grasping is made more accurate and robust by treating the grasp pose as a rotating bounding box in the image plane. In addition, a balanced loss function is introduced in this paper. This loss function not only solves the problem of positive and negative sample imbalance in the traditional cross-entropy loss but also reduces the penalty of points around the Gaussian center location. In this paper, a pixel-level single-stage grasping algorithm is designed in an end-to-end manner without the intermediate process of using anchor points, which saves time and improves the accuracy of grasping simultaneously. Then, the proposed model in this paper is evaluated on two standard datasets, Cornell dataset and Jacquard dataset, achieving 96.8% and 94.7% accuracy, respectively. Finally, we use a 6 DoF UR5e robotic arm for real-world grasping experiments. The success rate of single-object grasping is 94.7% and the time to generate the grasp frame is 8 ms. Experiments demonstrat that the algorithm is equally effective in real-world environments and has a faster detection time. © 2023 IEEE.

关键词： Signal encoding

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Global and Adaptive Local Label Correlation for Multi-label Learning with Missing Labels

Global and Adaptive Local Label Correlation for Multi-label ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Qingxia Jiang Peipei Li Yuhong Zhang Xuegang Hu Key Laboratory of Knowledge Engineering with Big Data (the ministry of Education) Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei Anhui Province China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei Anhui Province China

Label missing is a major challenge in multi-label learning. Many existing methods try to use label correlation to recover ground-truth labels, but they only focus on the label correlation within the original label space, however, the label correlation learned in this way is incomplete. Thus, inspired $b$ y the matrix adaptive column correlation, we propose a method to continuously adjust the label correlation matrix while the labels are filled in by adaptive column correlation learning method. Specifically, to reduce the impact of the missing label s on label correlation, the label space is firstly completed through manifold regularization while learning the local label information by adaptive column correlation learning in the complemented label space. Secondly, the global label correlation is utilized by adding a low-rank constraint to the entire label space. Finally, by jointly taking advantage of the global and adaptive local label correlation, our proposed approach achieves superior performance on both synthetic and real-world data sets from diverse domains compared to state-of-the art baselines.

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An Isomerism Learning Model to Solve Time-Varying Problems Through Intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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