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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 106773-106773页

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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Comparative Analysis Between New Combined Profile Scroll and Circular Involute Profile Scroll 7th

Comparative Analysis Between New Combined Profile Scroll and...

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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 Qian, Lijuan Shao, Xianyue 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 Ruifeng Wufu Pneumatic Tools Co. Ltd. Zhejiang Taizhou317500 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. To further study the combined profile of scroll compressor, a new type of combined profile scroll composed of base circle involutes, variable radius and base circle involutes is introduced. Firstly, it is modeled according to the parametric equation of the vortex disk generatrix and the isometric method. Then, compression ratio is analyzed, deformation of the scroll and pressure distribution in internal scroll are simulated using ANSYS software. The results are compared with circular involute profile scroll. The results show that, under the condition of a certain number of scrolls, the new profile scroll compressor has larger compression ratio, less deformation, and better pressure condition than the circular involute profile scroll. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Deformation

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The design of a mechanical force feedback VR data glove

The design of a mechanical force feedback VR data glove

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IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Jiliang Lin Bin Hu Jiahao Pang Jingjie Liao School of international education Xiamen University of technology Xiamen China School of Arts Soochow University Suzhou China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China school of big data and software engineering Wuzhou University Wuzhou China

With the development of virtual reality technology, data gloves began to widely popularize various fields. Some of the force feedback data gloves at this stage still have problems such as high cost and complex structure. The mechanical force feedback data glove proposed in this paper uses the principle of mechanical rotation, using a potentiometer as the rotating shaft and a nylon rope to drive the potentiometer to rotate, so that it records the relevant data instead of sensors, and uses a servo to bring force feedback experience. Experiments indicate that the force feedback glove in this paper has both the force feedback effect of the existing force feedback data gloves and is lower in cost than the existing data gloves and has good generalizability.

关键词： Shafts Mechanical sensors Costs Force feedback Virtual reality data gloves Potentiometers

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A Service Composition Evolution Method that Combines Deep Clustering and a Service Requirement Context Model

SSRN

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SSRN 2022年

作者： Xiao, Gang Lu, Jiawei Zheng, Jiahong Chen, Zhenbo Wang, Qibing Li, Duanni School of Computer Science and Technology Zhejiang University of Technology Hangzhou China College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang University Hangzhou China

Service composition can quickly build new value-added composite services by combining existing Web services. However, with the complex and changeable Internet environment, composite services need to effectively understand and manage requirements in a flexible and adaptive manner, and also be able to quickly and proactively provide high-quality services through a series of dynamic evolution models. In response to these challenges, in this study, we propose a service composition evolution method that can adaptively select the appropriate service to improve user satisfaction and service quality. First, we introduce a deep clustering method based on the topic model and auto-encoder, which considers the function description documents and parameter information of the services to reduce the search space of the candidate services. Furthermore, we describe a requirement-oriented context-sensitive task model to integrate functional and non-functional user requirements by connecting the context of Web subtasks. Then, we present a dynamic service matching method with QoS threshold judgement to filter and rank the services. We applied the proposed evolution method to the datasets of real-world Web services and measured the performance using standard measurement metrics. The prototype implementation and results of simulation experiments verified the effectiveness of each part of our method. © 2022, The Authors. All rights reserved.

关键词： Web services

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Few-shot learning for deformable image registration in 4DCT images

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BRITISH JOURNAL OF RADIOLOGY 2022年第1129期95卷 20210819页

作者： Chi, Weicheng Xiang, Zhiming Guo, Fen South China Univ Technol Sch Software Engn Guangzhou Guangdong Peoples R China Pazhou Lab Guangzhou Guangdong Peoples R China South China Univ Technol Key Lab Big Data & Intelligent Robot Minist Educ Guangzhou Guangdong Peoples R China Guangzhou Panyu Ctr Hosp Dept Radiol Guangzhou Guangdong Peoples R China

Objectives: To develop a rapid and accurate 4D deform able image registration (DIR) approach for online adaptive radiotherapy. Methods: We propose a deep learning (DL) based few shot registration network (FR Net) to generate deformation vector fields from each respiratory phase to an implicit reference image, thereby mitigating the bias introduced by the selection of reference images. The proposed FR Net is pretrained with limited unlabeled 4D data and further optimized by maximizing the intensity similarity of one specific four-dimensional computed tomography (4DCT) scan. Because of the learning ability of DL models, the few shot learning strategy facilitates the generalization of the model to other 4D data sets and the acceleration of the optimization process. Results: The proposed FR Net is evaluated for 4D group wise and 3D pairwise registration on thoracic 4DCT data sets DIR- Lab and POPI. FR Net displays an averaged target registration error of 1.48 mm and 1.16 mm between the maximum inhalation and exhalation phases in the 4DCT of DIR- Lab and POPI, respectively, with approximately 2 min required to optimize one 4DCT. Overall, FR Net outperforms state-of-the art methods in terms of registration accuracy and exhibits a low computational time. Conclusion: We develop a few shot groupwise DIR algorithm for 4DCT images. The promising registration performance and computational efficiency demonstrate the prospective applications of this approach in registration tasks for online adaptive radiotherapy. Advances in knowledge: This work exploits DL models to solve the optimization problem in registering 4DCT scans while combining groupwise registration and few shot learning strategy to solve the problem of consuming computational time and inferior registration accuracy.

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