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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Peihao Chen Dongyu Ji Kunyang Lin Runhao Zeng Thomas H. Li Mingkui Tan Chuang Gan South China University of Technology and Information Technology R&D Innovation Center of Peking University South China University of Technology South China University of Technology and Pazhou Laboratory Shenzhen University Information Technology R&D Innovation Center of Peking University South China University of Technology and Key Laboratory of Big Data and Intelligent Robot Ministry of Education MIT-IBM Watson AI Lab and UMass Amherst

ISBN: (纸本)9781713871088

We address a practical yet challenging problem of training robot agents to navigate in an environment following a path described by some language instructions. The instructions often contain descriptions of objects in the environment. To achieve accurate and efficient navigation, it is critical to build a map that accurately represents both spatial location and the semantic information of the environment objects. However, enabling a robot to build a map that well represents the environment is extremely challenging as the environment often involves diverse objects with various attributes. In this paper, we propose a multi-granularity map, which contains both object fine-grained details (e.g., color, texture) and semantic classes, to represent objects more comprehensively. Moreover, we propose a weakly-supervised auxiliary task, which requires the agent to localize instruction-relevant objects on the map. Through this task, the agent not only learns to localize the instruction-relevant objects for navigation but also is encouraged to learn a better map representation that reveals object information. We then feed the learned map and instruction to a waypoint predictor to determine the next navigation goal. Experimental results show our method outperforms the state-of-the-art by 4.0% and 4.6% w.r.t. success rate both in seen and unseen environments, respectively on VLN-CE dataset.

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Long term results in children underwent nuss procedure preschool with pectus excavatum: Real-world study with propensity matching

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Heliyon 2024年第20期10卷 e39477页

作者： Wang, Quan Kong, Xiangpan Ren, Chunian Pan, Zhengxia Wu, Chun Li, Hongbo Li, Yonggang Wang, Gang Dai, Jiangtao Department of Cardiothoracic Surgery Children's Hospital of Chongqing Medical University Ministry of Education Key Laboratory of Child Development and Disorders International Science and Technology Cooperation Base of Child Development and Critical Disorders National Clinical Research Center for Child Health and Disorders Chongqing Key Laboratory of Pediatrics Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering Chongqing Higher Institution Engineering Research Center of Children's Medical Big Data Intelligent Application Chongqing China Department of Urology Children's Hospital of Chongqing Medical University China

Background: It is controversial when surgery should be performed for pectus excavatum (PE). The study retrospectively compared the long-term prognosis in PE children undergoing the Nuss procedure at the age of 4–6 versus those performing surgery at the age of 12–14. Methods: 178 patients were included in the retrospective real-world research. Clinical Characteristics were collected at baseline. The endpoint of the study was set as the last follow-up at the age of 18 in outpatient services. Satisfaction and complication rate were set as the primary outcome and were collected at the endpoint. Hospital stay post-surgery and analgesia dosage were regard as the secondary outcome. To reduce potential bias between two different age groups, propensity score matching (PSM) analysis was analysized. Results: The oral analgesic dosage of children in the 4–6 years old age group is significantly lower than that of the 12–14 years old group (0.70/kg, 0.30–1.50/kg versus 1.50/kg, 0.90–2.30/kg, P < 0.001), and children in the younger age group are discharged earlier. There was no difference in overall satisfaction (89.1 %, versus 88.20 %, P = 0.99) and recurrence rate (7.2 %, versus 6.8 %, P = 0.99) between the two groups of when they reach the age of 18. Conclusions: Performing Nuss procedure at the age of 4–6 does not affect the overall long-term satisfaction of the child or increase the long-term recurrence rate. Surgical intervention in children with pectus excavatum preschool can provide a better postoperative experience in hospital compared with intervention in adolescent. © 2024 The Authors

关键词： Long-term results Nuss procedure Pectus excavatum Preschool

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Flow Characteristic of Scroll Compressor with Combined Profile Scroll 7th

Flow Characteristic of Scroll Compressor with Combined Profi...

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7th International Conference on Life System Modeling and Simulation, LSMS 2021, and the 7th International Conference on intelligent Computing for Sustainable Energy and Environment, ICSEE 2021

作者： Liu, Zhenghui Chen, Zhongli Qian, Lijuan Lin, Jian Liu, Yongqing College of Mechanical and Electrical Engineering China Jiliang University Zhejiang Hangzhou310018 China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang University Zhejiang Hangzhou310018 China Zhejiang Santian Automotive Air Conditioning Compressor Co. Ltd. Zhejiang Lishui323000 China

ISBN: (纸本)9789811672125

Scroll compressor is widely used in machines for gases compression, and scroll profile is the basic of a scroll compressor. The combined profile of scroll has advantages of several single scroll profiles. For improving the performance of a scroll compressor, it is necessary to investigate characteristics of the internal flow of combined profile of scroll compressors. In this paper, the combined profile is composed of the base circle involute-variable radius and base circle involute. A two-dimensional transient flow model of the combined profile of scroll refrigeration compressor operating with ammonia is established. The pressure, temperature, and velocity distribution of the working chamber are collected using the computational fluid dynamic method. Based on comparison between the combined profile and the circular involute profile, it is found that the combined profile is more favorable to bear the pressure, decrease the leakage, and decrease the fluctuation of mass flow rate than the circular involute profile. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Computational fluid dynamics

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Text-guided Reconstruction Network for Sentiment Analysis with Uncertain Missing Modalities

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IEEE Transactions on Affective Computing 2025年

作者： Shi, Piao Hu, Min Nakagawa, Satoshi Zheng, Xiangming Shi, Xuefeng Ren, Fuji Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine National Smart Eldercare International Science and Technology Cooperation Base School of Computer Science and Information Engineering Anhui Hefei230601 China Bozhou University School of Electronic and Information Engineering Bozhou236800 China University of Tokyo Graduate School of Information Science and Technology Tokyo113-8656 Japan University of Electronic Science and Technology of China College of Computer Science and Engineering Chengdu611731 China University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study Shenzhen518110 China

Multimodal Sentiment Analysis (MSA) is an attractive research that aims to integrate sentiment expressed in textual, visual, and acoustic signals. There are two main problems in the existing methods: 1) the dominant role of the text is underutilization in unaligned multimodal data, and 2) the modality under uncertain missing feature is not sufficiently explored. This paper proposes a Text-guided Reconstruction Network (TgRN) for MSA with uncertain missing modalities in non-aligned sequences. The TgRN network includes three primary modules: Text-guided Extraction Module (TEM), Reconstruction Module (RM) and Text-guided Fusion Module (TFM). First, the TEM consists of the text-guided cross attention units and self-attention units to capture inter-modal features and intra-modal features, respectively. Second, leveraging enhanced attention units and a three-way squeeze-and-excitation block, the RM is designed to learn semantic information from incomplete data and reconstruct missing modality features. Third, the TFM utilizes a progressive modality-mixing adaptation gate to explore the dynamic correlations between nonverbal and verbal modalities, effectively addressing the modality gap issue. Finally, under the supervision of sentiment prediction loss and reconstruction loss, the TgRN effectively processes both uncertain missing-modality conditions and ideal complete modality conditions. Extensive experiments on CMU-MOSI and CH-SIMS demonstrate that our proposed method outperforms state-of-the-art approaches. © 2010-2012 IEEE.

关键词： Semantics

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Study on Frost Layer Growth Characteristics of Finned Tube Evaporator Under Fast Flow Conditions

SSRN

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SSRN 2024年

作者： Chen, Qinghua Zhou, Yingying Lu, Yu Ji, Jiadong Liu, Ping Anhui Key Laboratory of Mine Intelligent Equipment and Technology Anhui University of Science and Technology Anhui Huainan232001 China Institute of Environment-friendly Materials and Occupational Health Anhui University of Science and Technology Anhui Wuhu241003 China College of Mathematics and Big Data Anhui University of Science and Technology Anhui Huainan232001 China Guangdong Lijia Industrial Co. Ltd. Guangdong Dongguan523000 China

The frosting phenomenon is one of the main adverse factors that hinder the application of finned tube evaporators in refrigeration systems. To accurately predict the growth characteristics of the frost layer, based on the coupled VOF multiphase flow and phase change mass transfer rate model method, the frost layer growth behavior on the surface of the three-dimensional finned tube under rapid convection conditions was numerically simulated. The maximum difference between the simulated frost layer thickness and the experimental results was controlled within 15%. The estimated value of frost layer density is within a confidence interval of up to 90%, which is in good agreement. By building a visual experimental platform for frosting on the surface of the finned tube of the evaporator, the influence of ambient temperature, relative humidity and headwind speed on the frost growth characteristics on the surface of the finned tube under single-factor changes was analyzed. The results show that the thickness of the frost layer gradually decreases from front to back with the direction of the inlet airflow. The lower the air temperature, the greater the head wind speed, and the higher the relative humidity, the greater the thickness of the frost layer, and the amount of frost, the greater the density of the frost layer and the thermal resistance of the frost layer. The thickness of the frost layer reached the highest at 85% relative humidity, which was 2.344 mm. According to the Morris sensitivity analysis method, the relative humidity has the greatest influence on the frost layer thermal resistance, and the sensitivity coefficient reaches 2.41, and the correlation of frost layer thermal resistance with different environmental parameters is obtained by using the least squares regression method. © 2024, The Authors. All rights reserved.

关键词： Evaporators

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Learning Gated Non-Local Residual for Single-Image Rain Streak Removal

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2021年第6期31卷 2147-2159页

作者： Zhu, Lei Deng, Zijun Hu, Xiaowei Xie, Haoran Xu, Xuemiao Qin, Jing Heng, Pheng-Ann Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Lingnan Univ Dept Comp & Decis Sci Hong Kong Peoples R China Minist Educ Key Lab Big Data & Intelligent Robot State Key Lab Subtrop Bldg Sci Guangzhou 510006 Peoples R China Guangdong Prov Key Lab Computat Intelligence & Cy Guangzhou 510006 Peoples R China Hong Kong Polytech Univ Ctr Smart Hlth Sch Nursing Hong Kong Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Guangdong Prov Key Lab Comp Vis & Virtual Real Te Shenzhen 518055 Peoples R China

This work presents a gated non-local deep residual learning framework for image deraining. It can avoid the over-deraining or under-deraining caused by the global residual learning in existing deraining networks, since the learned soft gate in our method adaptively adjusts the amount of global residual to be passed for generating the final derained result. To generate feature maps for global residual prediction, we develop a non-local guided attention module (NLAM), which first obtains non-local features by exploiting spatial inter-dependencies among all the feature positions of local features produced by convolutional neural network (CNN), and then leverages the attention mechanism to merge the local and non-local features based on their complementary relation. Moreover, we develop a channel-wise gated prediction module to learn a soft gate on the global residual by explicitly modelling channel inter-dependencies of the feature maps obtained from NLAM. Experiments on four deraining benchmark datasets and real-world rainy images show that our network has a quantitative and qualitative improvement over state-of-the-arts.

关键词： Rain Logic gates Computer science Convolutional neural networks Benchmark testing Computer vision Computer architecture Single-image rain streak removal non-local residual learning gated learning

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A Virtual Network Mapping Method Based on Compound Particle Swarm Optimization

A Virtual Network Mapping Method Based on Compound Particle ...

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Cyber Security and Information Engineering (ICCSIE), International Conference on

作者： Jianhua Huang Yunlong Tang Yongjun Wei Huan Wang Haifeng Zhang Bing Zhang Liuzhou Key Laboratory of Big Data Intelligent Processing and Security Guangxi Education System Network Security Monitoring Center School of Computer Science and Technology (School of Software) Guangxi University of Science and Technology Liuzhou China Liuzhou Railway Vocational Technical College Liuzhou China

ISBN: (纸本)9781665455756

Aiming at problems of low credibility of results and low accuracy of the scheme in the mapping process of virtual networks. It is suggested to use a composite particle swarm optimization approach for virtual network mapping. Firstly, to derive the maximum number of virtual cyberspaces, we construct the virtual network model and the physical network model; secondly, resource limitations are used to build the node mapping and link mapping models, and once more, the mapping scheme of the virtual network on the physical network is solved using the composite particle swarm algorithm to improve the acceptance rate of virtual network requests. In simulation experiments, we compare our established algorithm with two algorithms, D-ViNE-SP and VNE-R-PSO, in two dimensions, and the results show that our proposed VNE-MM-PSO mapping method improves the acceptance rate of network requests by 8% and also improves on the benefit-cost ratio.

关键词： Cyberspace Compounds Particle swarm optimization Computer crime

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Joint Visual and Semantic Optimization for zero-shot learning

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KNOWLEDGE-BASED SYSTEMS 2021年 215卷

作者： Wu, Hanrui Yan, Yuguang Chen, Sentao Huang, Xiangkang Wu, Qingyao Ng, Michael K. Univ Hong Kong Hong Kong Peoples R China Shantou Univ Shantou Peoples R China South China Univ Technol Guangzhou Peoples R China Minist Educ Pazhou Lab Key Lab Big Data & Intelligent Robot Guangzhou Peoples R China

Zero-shot learning (ZSL) aims to classify instances whose classes could be unseen during training. Most existing ZSL methods project visual or semantic features into the space of the other one, or into a common subspace. The main goal of projection is to find out the similar features in the latent subspace. However, existing methods barely consider common features that preserve knowledge, here we refer to these features as the shared concepts, which are essential to model the relationship between the visual and semantic spaces. In this paper, we exploit the underlying concepts shared by both visual and semantic features in a latent common subspace and propose to match their latent visual and semantic representations. To reduce domain shift and information loss, we introduce reconstruction losses for both visual and semantic features. As a result, the reconstruction regularizations are added to the similar features and thereby obtain knowledge preserving shared concepts via the proposed method. Mathematically, it is formulated as the minimization problem for mutual orthogonal projection to their latent common subspace. The problem involves two projection variables, thus we develop an algorithm based on the Gauss-Seidel iteration scheme and split the problem into two subproblems in the scheme. These two subproblems are further solved by searching algorithms based on the Barzilai-Borwein stepsize. Extensive experiments on six benchmark data sets are conducted to demonstrate that the accuracy of the proposed method is better than that of existing ZSL methods. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Zero-shot learning Generalized zero-shot learning Orthogonal projection

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On-line modification of T-S fuzzy models based on gradient descent algorithm

On-line modification of T-S fuzzy models based on gradient d...

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第33届中国控制与决策会议

作者： FENG Haodong WEI Dong JIAO Huanyan School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing Municipal Science and Technology Commission

The gradient descent algorithm is applied to the model parameter correction algorithm in view of the shortcoming that T-S fuzzy model cannot be used for real-time adaptive parameter *** this paper,an online model correction method combining T-S fuzzy model with gradient descent algorithm is proposed,and the operation data of a subway air-conditioning system in Wuhan is used for *** experimental results show that the T-S fuzzy model modified by gradient descent algorithm has better accuracy and higher operational efficiency.

关键词： T-S fuzzy model Gradient descent algorithm Air conditioning system model

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QoI-aware incentive for multimedia crowdsensing enabled learning system

QoI-aware incentive for multimedia crowdsensing enabled lear...

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作者： Gu, Yiren Shen, Hang Bai, Guangwei Wang, Tianjing Liu, Xuejun College of Computer Science and Technology Nanjing Tech University Nanjing211816 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing210023 China

While much research has been devoted to algorithm improvement of the machine learning model for multimedia applications, relatively little research has focused on the acquisition of massive multimedia datasets with strict data demands for model training. In this paper, we propose a Quality-of-Information (QoI) aware incentive mechanism in multimedia crowdsensing, with the objective of promoting the growth of an initial training model. We begin with a reverse auction incentive model to maximize social welfare while meeting the requirements in quality, timeliness, correlation, and coverage. Then, we discuss how to achieve the optimal social welfare in the presence of an NP-hard winner determination problem. Lastly, we design an effective incentive mechanism to solve the auction problem, which is shown to be truthful, individually rational and computationally efficient. Our evaluation study is carried out using a real multimedia dataset. Extensive simulation results demonstrate that the proposed incentive mechanism produces close-to-optimal social welfare noticeably, while accompanied by accelerating the growth of the machine learning model with a high-QoI dataset. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Machine learning

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