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Understanding transitions in animated bar charts

Visual Intelligence 2023年第1期1卷 1-15页

作者： Wei, Datong Liu, Can Zhang, Xiaolong Yuan, Xiaoru Key Laboratory of Machine Perception (Ministry of Education) and the School of Intelligence Science and Technology Peking University Beijing China College of Information Sciences and Technology Pennsylvania State University University Park United States National Engineering Laboratory for Big Data Analysis and Application Peking University Beijing China

Animated bar charts have gained popularity on the Internet for their ability to display historical rankings through smooth animated transitions that clearly show the rankings over time. To investigate the usage scenarios of these charts, we analyzed the pop-up comments to understand viewers’ focus. Our findings suggest that animated transitions play a key role in viewers’ perception of ranking changes. We summarized various transition methods and evaluated their impact on user perception and memory through user experiments. We also conducted a detailed analysis of each transition method’s implementation. Our research sheds light on the effectiveness of different transition strategies for animated bar charts. © The Author(s) 2023.

关键词： Animation Quantitative evaluation Transition Visualization for the masses

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Test-Driven Feature Extraction of Web Components

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Journal of Computer Science & technology 2022年第2期37卷 389-404页

作者： Yong-Hao Long Yan-Cheng Chen Xiang-Ping Chen Xiao-Hong Shi Fan Zhou School of Computer Science and Engineering National Engineering Research Center of Digital Life Sun Yat-sen UniversityGuangzhou 510006China School of Design The Hong Kong Polytechnic UniversityHong KongChina Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion The School of Communication and DesignSun Yat-sen UniversityGuangzhou 510006China School of Information Technology and Engineering Guangzhou College of CommerceGuangzhou 511363China

With the growing requirements of web applications,web components are developed to package the implementation of commonly-used features for *** some cases,the developer may want to reuse some features which cannot be customized by the component’s ***/she has to extract the implementation by *** is labor-intensive and *** the widely-used test cases which can be useful to specify the software features,a test-driven approach is proposed to extract the implementation of the desired features in web *** satisfaction of the user^requirements is transformed into the passing rate of user-specified test *** this way,the quality of the extraction result can be evaluated ***,a record/replay-based GUI test generation method is proposed to ensure that the extraction result has the correct GUI *** extract the feature implementation,a hierarchical genetic algorithm is proposed to find the code snippet that can pass all the tests and has the approximate smallest *** compare our method with two existing feature extraction *** result shows that our method can extract the correct implementation with the minimum size.A human-subject study is conducted to show the effectiveness and weaknesses of our method in helping users extract the features.

关键词： feature extraction genetic algorithm graphical user interface software reuse

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Time series forecast of sales volume based on XGBoost 2

Time series forecast of sales volume based on XGBoost

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2021 2nd International Workshop on Electronic communication and Artificial Intelligence, IWECAI 2021

作者： Zhang, Lingyu Bian, Wenjie Qu, Wenyi Tuo, Liheng Wang, Yunhai School of Computer Science and Technology Shandong University Qingdao China Didi AI Labs Didi Chuxing Beijing China Smart Transportation Center National Engineering Laboratory for Big Data Analysis and Applications Beijing China

Some problems such as the decline of new labor force, the increase of retired labor force emerge because of the complex and changeable market environment, consequently exacerbating the staffing problem in the retail industry. Also, the unreasonable distribution of personnel, there are few people in busy hours and too many people in idle hours, which causes waste of labor. To address this issue, we analyzed the time series of sales volume in the retail industry in detail, and processed the data with feature engineering for predicting the in-store sales volume in the future. At the same time, other features such as weather and temperature are added to improve the accuracy of the model. Considering the characteristics of the data, we choose XGBoost as the prediction model. The experiments on real-world datasets verified better performance of proposed model compared with other state-of-art models. © Published under licence by IOP Publishing Ltd.

关键词： Time series

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Example-based web page recoloring method

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Frontiers of Computer Science 2020年第5期14卷 229-231页

作者： Yonghao Long Zhihao Zang Xiangping Chen Fan Zhou Xiaonan Luo School of Data and Computer Science National Engineering Research Center of Digital LifeSun Yat-sen UniversityGuangzhou510006China Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion The School of Communication and DesignSun Yat-sen UniversityGuangzhou510006China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China

1 Introduction The user interface(UI)is very important for a software product,and a well-designed UI will attract users and make a good *** has been shown that color plays an important role in invoking emotional reactions[1],influencing usability[2],forming first impressions[3],and affecting the energy cost of the UI[4].Generating satisfying color schemes has high requirements for experience,aesthetic,and creative inspiration of designers[5].

关键词： web coloring satisfying

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Neural multi-atlas label fusion: Application to cardiac MR images

arXiv

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arXiv 2017年

作者： Yang, Heran Sun, Jian Li, Huibin Wang, Lisheng Xu, Zongben School of Mathematics and Statistics Xi’an Jiaotong University China National Engineering Laboratory for Big Data Algorithm and Analysis Technology China Department of Automation Shanghai Jiaotong University China

Multi-atlas segmentation approach is one of the most widely-used image segmentation techniques in biomedical applications. There are two major challenges in this category of methods, i.e., atlas selection and label fusion. In this paper, we propose a novel multi-atlas segmentation method that formulates multi-atlas segmentation in a deep learning framework for better solving these challenges. The proposed method, dubbed deep fusion net (DFN), is a deep architecture that integrates a feature extraction subnet and a non-local patch-based label fusion (NL-PLF) subnet in a single network. The network parameters are learned by end-to-end training for automatically learning deep features that enable optimal performance in a NL-PLF framework. The learned deep features are further utilized in defining a similarity measure for atlas selection. By evaluating on two public cardiac MR datasets of SATA-13 and LV-09 for left ventricle segmentation, our approach achieved 0.833 in averaged Dice metric (ADM) on SATA-13 dataset and 0.95 in ADM for epicardium segmentation on LV-09 dataset, comparing favorably with the other automatic left ventricle segmentation methods. We also tested our approach on Cardiac Atlas Project (CAP) testing set of MICCAI 2013 SATA Segmentation Challenge, and our method achieved 0.815 in ADM, ranking highest at the time of writing. Copyright © 2017, The Authors. All rights reserved.

关键词： Image segmentation

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A Novel Control algorithm for Interaction Between Surface Waves and A Permeable Floating Structure

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China Ocean engineering 2016年第2期30卷 161-176页

作者： Pei-Wei TSAI A.ALSAEDI T.HAYAT Cheng-Wu CHEN College of information Science and Engineering Fujian University of TechnologyFuzhou 350118China Fujian Provincial Key Laboratory of Big Data Mining and Applications(Fujian University of Technology) Fuzhou 350118China Nonlinear Analysis and Applied Mathematics(NAAM)Research Group King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics Quaid-I-Azam UniversityIslamabad 44000Pakistan Department of Maritime Information and Technology National Kaohsiung Marine UniversityKaohsiung 80543China Faculty of Engineering King Abdulaziz UniversityJeddah 21589Saudi Arabia

An analytical solution is undertaken to describe the wave-induced flow field and the surge motion of a permeable platform structure with fuzzy controllers in an oceanic *** the design procedure of the controller,a parallel distributed compensation（PDC） scheme is utilized to construct a global fuzzy logic controller by blending all local state feedback controllers.A stability analysis is carried out for a real structure system by using Lyapunov *** corresponding boundary value problems are then incorporated into scattering and radiation *** are analytically solved,based on separation of variables,to obtain series solutions in terms of the harmonic incident wave motion and surge *** dependence of the wave-induced flow field and its resonant frequency on wave characteristics and structure properties including platform width,thickness and mass has been thus drawn with a parametric *** which mathematical models are applied for the wave-induced displacement of the surge motion.A nonlinearly inverted pendulum system is employed to demonstrate that the controller tuned by swarm intelligence method can not only stabilize the nonlinear system,but has the robustness against external disturbance.

关键词： fuzzy Lyapunov function Takagi?Sugeno form swarm intelligence algorithm

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Advancing biological fluorescence microscopy with deep learning:a bibliometric perspective

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Medical data Mining 2022年第4期5卷 42-55页

作者： Li Fu Cheng-Liang Yin Jia-Lei Wang Xiao-Zhu Liu College of Materials and Environmental Engineering Hangzhou Dianzi UniversityHangzhou 310018China Medical Big Data Research Center Medical Innovation Research Division of PLA General HospitalBeijing 100853China National Engineering Laboratory for Medical Big Data Application Technology Chinese PLA General HospitalBeijing 100853China Department of Algorithm Shining3D Technology Company LimitidHangzhou 311258China Department of Cardiology The Second Affiliated Hospital of Chongqing Medical UniversityChongqing 400010China

Background:Fluorescence microscopy has increasingly promising applications in life *** bibliometrics-based review focuses on deep learning assisted fluorescence microscopy imaging ***:Papers on this topic retrieved by Core Collection on Web of Science between 2017 and July 2022 were used for the *** addition to presenting the representative papers that have received the most attention,the process of development of the topic,the structure of authors and institutions,the selection of journals,and the keywords are analyzed in detail in this ***:The analysis found that this topic gained immediate popularity among scholars from its emergence in 2017,gaining explosive growth within three *** phenomenon is because deep learning techniques that have been well established in other fields can be migrated to the analysis of fluorescence *** 2020 onwards,this topic tapers off but has attracted a few stable research groups to tackle the remaining *** this topic has been very popular,it has not attracted scientists from all over the *** USA,China,Germany,and the UK are the key players in this *** analysis and clustering are applied to understand the different focuses on this ***:Based on the bibliometric analysis,the current state of this topic to date and future perspectives are summarized at the end.

关键词： deep learning fluorescence microscopy signal-to-noise ratio convolutional neural network cell segmentation

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Graph Condensation for Inductive Node Representation Learning 40

Graph Condensation for Inductive Node Representation Learnin...

引用

40th IEEE International Conference on data engineering, ICDE 2024

作者： Gao, Xinyi Chen, Tong Zang, Yilong Zhang, Wentao Hung Nguyen, Quoc Viet Zheng, Kai Yin, Hongzhi The University of Queensland Brisbane Australia Kaiserslautern Germany Peking University Beijing China National Engineering Laboratory for Big Data Analysis and Applications Beijing China Griffith University Gold Coast Australia University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350317152

Graph neural networks (GNNs) encounter significant computational challenges when handling large-scale graphs, which severely restricts their efficacy across diverse applications. To address this limitation, graph condensation has emerged as a promising technique, which constructs a small synthetic graph for efficiently training GNNs while retaining performance. However, due to the topology structure among nodes, graph condensation is limited to condensing only the observed training nodes and their corresponding structure, thus lacking the ability to effectively handle the unseen data. Consequently, the original large graph is still required in the inference stage to perform message passing to inductive nodes, resulting in substantial computational demands. To overcome this issue, we propose mapping-aware graph condensation (MCond), explicitly learning the one-to-many node mapping from original nodes to synthetic nodes to seamlessly integrate new nodes into the synthetic graph for inductive representation learning. This enables direct information propagation on the synthetic graph, which is much more efficient than on the original large graph. Specifically, MCond employs an alternating optimization scheme with innovative loss terms from transductive and inductive perspectives, facilitating the mutual promotion between graph condensation and node mapping learning. Extensive experiments demonstrate the efficacy of our approach in inductive inference. On the Reddit dataset, MCond achieves up to 121.5× inference speedup and 55.9× reduction in storage requirements compared with counterparts based on the original graph. © 2024 IEEE.

关键词： Condensation

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Image Recognition of Concrete Electromagnetic Flaw Detection Based on Improved YOLOv7 24

Image Recognition of Concrete Electromagnetic Flaw Detection...

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7th International Conference on Image and Graphics Processing, ICIGP 2024

作者： Yuan, Shuai Yuan, Ze He, Kai School of Computer Science and Engineering Shenyang Jianzhu University China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction China Shenyang Branch of National Special Computer Engineering Technology Research Center China School of Electrical and Control Engineering Shenyang Jianzhu University China

ISBN: (纸本)9798400716720

Owing to the invisibility characteristics of the interiors of concrete structures, nondestructive testing technologies are commonly employed to detect internal damage. Electromagnetic flaw detection technology, as a prominent nondestructive testing method, offers capabilities of strong penetration and precise imaging. However, the output images produced by this detection technology are usually reliant on subjective human judgment, and existing automatic detection algorithms have limitations in terms of accuracy. To enhance the accuracy of electromagnetic flaw detection images, this paper proposes improved YOLOv7 based detection method. First of all, the ACBlock convolution module is introduced to replace the original 3×3 convolution kernel for alleviating the loss of edge feature information caused by the sampling operation of the backbone network MP module. Next, in order to have more focus on the semantic features of small targets, a global attention mechanism (GAMAttention) is incorporated into the algorithm. Then, the FReLU activation function is adopted to enhance the algorithm sensitivity to image space. Finally, experiments are conducted on a self-created concrete flaw detection image dataset to illustrate the efficiency of the proposed algorithm. The results show that the mean Average Precision (mAP) value achieved by the improved algorithm is 95.85%. which has a significant improvement of 13.89% in comparison with the pre-improved YOLOv7 algorithm and surpasses other algorithms in the same domain. These findings represent that the proposed algorithm effectively enhances the accuracy of concrete electromagnetic flaw detection image detection. © 2024 ACM.

关键词： Nondestructive examination

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Differentiable Feature Aggregation Search for Knowledge Distillation

arXiv

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arXiv 2020年

作者： Guan, Yushuo Zhao, Pengyu Wang, Bingxuan Zhang, Yuanxing Yao, Cong Bian, Kaigui Tang, Jian Peking University China Technology Inc National Engineering Laboratory for Big Data Analysis and Applications DiDi AI Labs

Knowledge distillation has become increasingly important in model compression. It boosts the performance of a miniaturized student network with the supervision of the output distribution and feature maps from a sophisticated teacher network. Some recent works introduce multi-teacher distillation to provide more supervision to the student network. However, the effectiveness of multi-teacher distillation methods are accompanied by costly computation resources. To tackle with both the efficiency and the effectiveness of knowledge distillation, we introduce the feature aggregation to imitate the multi-teacher distillation in the single-teacher distillation framework by extracting informative supervision from multiple teacher feature maps. Specifically, we introduce DFA, a two-stage Differentiable Feature Aggregation search method that motivated by DARTS in neural architecture search, to efficiently find the aggregations. In the first stage, DFA formulates the searching problem as a bi-level optimization and leverages a novel bridge loss, which consists of a student-to-teacher path and a teacher-to-student path, to find appropriate feature aggregations. The two paths act as two players against each other, trying to optimize the unified architecture parameters to the opposite directions while guaranteeing both expressivity and learnability of the feature aggregation simultaneously. In the second stage, DFA performs knowledge distillation with the derived feature aggregation. Experimental results show that DFA outperforms existing distillation methods on CIFAR-100 and CINIC-10 datasets under various teacher-student settings, verifying the effectiveness and robustness of the design. Copyright © 2020, The Authors. All rights reserved.

关键词： Distillation

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