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Fairness-Aware Budgeted Edge Server Placement for Connected Autonomous Vehicles

IEEE Transactions on Mobile computing 2025年第6期24卷 4762-4776页

作者： Wu, Jintao Xu, Xiaolong Cui, Guangming Zhang, Yiwen Qi, Lianyong Dou, Wanchun Cai, Zhipeng Nanjing University of Information Science & Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software Nanjing210044 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Nanjing University of Information Science & Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software China Nanjing University State Key Laboratory for Novel Software Technology China Anhui University School of Computer Science and Technology Anhui230031 China College of Computer Science and Technology Qingdao266580 China Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China Georgia State University Department of Computer Science United States

Mobile edge computing (MEC) considerably enhances the capabilities and performance of connected autonomous vehicles (CAVs) by deploying edge servers (ESs) on roadside units (RSUs) near CAVs, thereby ensuring low-latency services. Given the constrained and costly nature of ES resources (computing, storage, and bandwidth), equitable ES utilization is critical for CAV operations. However, fairness considerations are often overlooked in current budgeted edge server placement (ESP) strategies, potentially worsening resource imbalances and compromising user experience. This paper investigates the fairness-aware budgeted edge server placement (FESP) problem within RSUs, proving its NP-hardness. To address FESP, we first propose FESP-O, an integer programming-based optimal approach for small-scale problems, followed by FESP-APX, an approximation approach for large-scale scenarios that provides near-optimal solutions. We analyze the time complexity and approximation ratio of our proposed algorithms and validate their efficacy through experiments on real-world datasets. Extensive experimental results demonstrate significant performance improvements over baseline and state-of-the-art methods, indicating practical suitability and efficiency. © 2002-2012 IEEE.

关键词： Integer linear programming

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A qualitative and quantitative study of color emotion using valence-arousal

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Frontiers of Computer Science 2012年第4期6卷 469-476页

作者： Shangfei WANG Rui DING Key Lab of Computing and Communicating Software of Anhui Province School of Computer Science and TechnologyUniversity of Science and Technology of ChinaHefei 230027China

This paper describes qualitative and quantita- tive analysis of color emotion dimension expression using a standard device-independent colorimetric system. To collect color emotion data, 20 subjects are required to report their emotion responses, using a valence-arousal emotion model, to 52 color samples that are chosen from CIELAB Lch color spaces. Qualitative analysis, including analysis of variance （ANOVA）, Pearson＇s correlation and Spearman＇s rank cor- relation, shows that significant differences exist between re- sponses to achromatic and chromatic stimuli, but there are no significant differences between chromatic samples. There is a positive linear relationship between lightness/chroma and valence-arousal dimensions. Subsequently, several clas- sic predictors are used to quantitatively predict emotion in- duced by color attributes. Furthermore, several explicit color emotion models are developed by using multiple linear re- gression with stepwise and pace regression. Experimental results show that chroma and lightness have stronger effects on emotions than hue, which is consistent with our qualitative results and other psychological studies. Arousal has greater predictive value than valence.

关键词： color emotion valence and arousal qualitative quantitative

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A Power Control Scheme for Target Localization in WSN

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电子学报(英文版) 2008年第3期17卷 443-448页

作者： GU Yu ZHAO Baohua Department of Computer Science University of Science and Technology of China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230027 China

In this paper, we focus on the target tracking problem in sensor networks and propose an Powersaving target localization scheme (PSTL) based on a conjecture model that reflects the moving pattern of a target, and also a corresponding two-step communication protocol between Base station (BS) and sensors. BS executes a query mechanism to determine which sensors should be used for detailed information according to a limited amount of data received from sensors. This scheme reduces both energy consumption and communication bandwidth requirement, prolongs the lifetime of the wireless sensor networks. Simulation results indicate that it can achieve a high accuracy while saving a large amount of energy.

关键词：无线传感器网络功率控制目标定位推测模型

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Minimum-Energy Broadcast Trees in All-Wireless Networks

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电子学报(英文版) 2008年第2期17卷 227-230页

作者： HU Tian ZHAO Baohua Department of Computer Science University of Science and Technology of China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230027 China

This paper focuses on the problem of constructing the minimum-energy broadcast trees in all-wireless networks. We proposed a greedy algorithm called Greedy maximum-branch replacement algorithm (GMBR) to decrease the total power of the broadcast tree further. This algorithm can be developed to a distributed one easily. Compared with the previous algorithms, GMBR was proved to have better performance, especially when the propagation loss exponent and the network size become larger.

关键词：最小能量广播天线网络技术性能

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Spontaneous facial expression recognition based on feature point tracking

Spontaneous facial expression recognition based on feature p...

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International Conference on Image and Graphics

作者： He, Shan Wang, Shangfei Lv, Yanpeng Key Lab of Computing and Communicating Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9780769545417

In recent years, facial expression recognition has attracted a lot of attention because of its importance in human-computer interaction. However, most previous work has focus on posed expression. In this paper, we propose a spontaneous facial expression recognition method based on feature point tracking. First, all expression sequences are normalized according to their pupils' coordinates. Second, 23 points are labeled manually in the onset and apex frames. Then Kalman filter is used for tracking. Two kinds of features, point displacement features and points distance variation features, are extracted. Finally, Hidden Markov Model is employed as classifier. Experiments have been conducted on the spontaneous facial expression database of USTC-NVIE. The results indicate that Kalman filter point tracking method could detect the right place of points, and the points distance variation features are more suitable than the point displacement features for the facial expression recognition. © 2011 IEEE.

关键词： Kalman filters

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A spontaneous facial expression recognition method using head motion and AAM features

A spontaneous facial expression recognition method using hea...

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2010 2nd World Congress on Nature and Biologically Inspired computing, NaBIC 2010

作者： Lv, Yanpeng Wang, Shangfei Key Lab of Computing and Communicating Software of AnHui Province School of Computer Science and Technology University of Science and Technology of China HeFei AnHui China

ISBN: (纸本)9781424473762

Facial expression recognition by artificial intelligence has become a hotspot and produced promising results in recent years. However, most recent work focuses on posed expressions whose involved muscles and dynamics are different from those of spontaneous ones. So this paper proposed a novel two-layer approach, combining dynamic head motion features with static appearance features, to recognize spontaneous expressions. Different from other methods, our method improved an existing eyes location algorithm and explored new head motion features calculated from locations of pupils to recognize fear firstly, and then used appearance features extracted by the AAM algorithm to recognize the remaining images. Comparative experiments on the natural visible and infrared facial expression database (NVIE) show the effectiveness of our approach. © 2010 IEEE.

关键词： Location

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A real-time attitude recognition by eye-tracking 11

A real-time attitude recognition by eye-tracking

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3rd International Conference on Internet Multimedia computing and Service, ICIMCS 2011

作者： Lv, Yanpeng Wang, Shangfei Shen, Peijia Key Lab. of Computing and Communicating Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781450309189

Attitude, which is the outward manifestation of human psychology information, is inevitable in everyday situation. Attitude recognition by artificial intelligence has become a hotspot and produced promising results in recent years. In this paper, we propose an attitude recognition method based on eye-tracking. We first improve the eye location algorithm in OpenCV and assume that the trajectory of eyes-center is the same with that of head. Then using eye location method, the center of eyes is calculated. By analysis of displacement of eyes' centers in each two successive frames, sub-result is obtained. The final result is determined by voting algorithm. Experimental results indicate that this method could recognize positive and negative attitudes in real time. We applied our method to "KeJia", an intelligent service robot and it worked well. © 2011 ACM.

关键词： Eye tracking

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Emotional music generation using interactive genetic algorithm

Emotional music generation using interactive genetic algorit...

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International Conference on Computer Science and software Engineering, CSSE 2008

作者： Zhu, Hua Wang, Shangfei Wang, Zhen Key Lab. of Computing and Communicating Software of Anhui Province Department of Computer Science University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9780769533360

This paper proposes an approach to generate emotional music using Interactive Genetic Algorithm. Performance rules are described by the KTH rule system. Different emotional expressions can be modeled by using selections of rules and rule weights. Interactive Genetic Algorithm is applied to optimize rule weights based on users' subjective evaluation. Users can get their satisfied emotional music with the help of GA, although they have no profound knowledge for composition. Two kinds of emotional music with the states of happy and sad are obtained finally. The Sheffé's method of paired comparisons is carried out to estimate the effectiveness of generated music. In the confidence interval of 99%, the music generated by the proposed approach are more approbatory than that generated by the expert, both for the emotion of happy and sad. © 2008 IEEE.

关键词： Genetic algorithms

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引用

9th International Symposium on Neural Networks, ISNN 2012

作者： Wang, Shangfei He, Shan Zhu, Hua Key Lab. of Computing and Communicating Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (数字)9783642313622

ISBN: (纸本)9783642313615

This paper proposes a novel approach to search for the optimal combination of a measure function and feature weights using an evolutionary algorithm. Different combinations of measure function and feature weights are used to construct the searching space. Genetic Algorithm is applied as an evolutionary algorithm to search for the candidate solution, in which the classification rate of the K-Nearest Neighbor classifier is used as the fitness value. Three experiments are carefully designed to show the attractiveness of our approach. In the first experiment, an artificial data set is constructed to verify the effectiveness of the proposed approach by testing whether it could find the optimal combination of measure function and feature weights which satisfy the data set. In the second experiment, data sets from the University of California at Irvine are employed to verify the general applicability of the method. Finally, a prostate cancer data set is used to show its effectiveness on high-dimensional data. © 2012 Springer-Verlag.

关键词： Genetic algorithms

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Emotion recognition from thermal infrared images using deep Boltzmann machine

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Frontiers of Computer Science 2014年第4期8卷 609-618页

作者： Shangfei WANG Menghua HE Zhen GAO Shan HE Qiang JI School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Lab of Computing and Communicating Software of Anhui Province Hefei 230027 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180-3590 USA

Facial expression and emotion recognition from thermal infrared images has attracted more and more attentions in recent years. However, the features adopted in current work are either temperature statistical parameters extracted from the facial regions of interest or several hand-crafted features that are commonly used in visible spectrum. Till now there are no image features specially designed for thermal infrared images. In this paper, we propose using the deep Boltzmann machine to learn thermal features for emotion recognition from thermal infrared facial images. First, the face is located and normalized from the thermal infrared im- ages. Then, a deep Boltzmann machine model composed of two layers is trained. The parameters of the deep Boltzmann machine model are further fine-tuned for emotion recognition after pre-tralning of feature learning. Comparative experimental results on the NVIE database demonstrate that our approach outperforms other approaches using temperature statistic features or hand-crafted features borrowed from visible domain. The learned features from the forehead, eye, and mouth are more effective for discriminating valence dimension of emotion than other facial areas. In addition, our study shows that adding unlabeled data from other database during training can also improve feature learning performance.

关键词： emotion recognition thermal infrared images deep Boltzmann machine

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