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Dynamic Spatial-Temporal Imputation network With Missing Features for Traffic Data Imputation

IEEE Internet of Things Journal 2025年

作者： Li, Hao Han, Shiyuan Yang, Min Liu, Jie Zhou, Jin Zhang, Tong Chen, C. L. Philip Shandong Women’s University School of Artificial Intelligence Jinan250399 China University of Jinan Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan250022 China South China University of Technology School of Computer Science and Engineering Guangzhou510641 China

Missing traffic data caused by sensor failures or communication errors significantly hinders the efficiency of downstream tasks in Intelligent Transportation Systems (ITS), such as the critical functions of traffic monitoring and decision-making. Since missing data contains important information, it is essential to extract dynamic spatial-temporal correlations in traffic processes by incorporating these missing features. Motivated by these concerns, a novel Dynamic Spatial-Temporal Imputation network with Missing Features (DSTMIN) is proposed to accurately impute traffic data. DSTMIN comprises an embedding layer, a Mask Attention module (MA), and a Fusion Graph Convolution module (FGC). Specifically, an embedding layer is designed to accurately represent the distribution of missing data, thereby capturing both temporal features and missing features. Furthermore, in order to effectively capture the temporal correlations, MA integrates the missing features to emphasize the significance of observed data and reduce the adverse effects caused using incomplete data. To capture spatial correlations, FGC constructs the spatial graphs and model dynamic spatial correlations from traffic subsequences and the missing-data graph in the presence of missing features. The proposed DSTMIN is adequately evaluated to demonstrate its superior performance on two datasets, which achieves a remarkable 20% reduction in imputation error compared to state-of-the-art methods. © 2014 IEEE.

关键词： Street traffic control

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Energy-Efficient Virtual Machine Placement in Data Centers Via Accelerated Genetic Algorithm with Improved Fitness Computation

SSRN

引用

SSRN 2021年

作者： Hormozi, Elham Hu, Shuwen Ding, Zhe Tian, Yu-Chu Wang, You-Gan Yu, Zu-Guo Zhang, Weizhe School of Computer Science Queensland University of Technology GPO Box 2434 BrisbaneQLD4001 Australia School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQLD4001 Australia Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan Xiangtan411105 China School of Cyberspace Science Harbin Institute of Technology Harbin China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen China Queensland University of Technology

Energy efficiency basically refers to how effectively energy can be utilised or consumed by any virtualised data centre giving cloud administrations. Since Genetic Algorithm (GA) is an acceptable method to solve the VM placement problem, this research formulates the Virtual Machine (VM) placement problem as a constrained optimisation problem. A considerable amount of residual resources is available for each new VM allocation, however they are distributed across multiple active PMs, rendering them inefficient. Our research focuses on improving a data centre’s energy and time efficiency by devising a technique to decrease PM’s residual resources and make them more valuable. As the most time consuming element of a GA is calculating the fitness function, this paper presents a new fitness function to simplify the fitness function calculation in GA. The results are compared to the standard GA and First Fit Decreasing (FFD) algorithm. The findings reveals a 8% energy savings for our GA compared to FFD and a 66% reduction in our GA execution time compared to the standard GA for virtualised data centres. The simulation experiments are conducted on small-, medium- and large-scale of the google data centre to demonstrate the effectiveness of our GA. © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

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Fully secure decentralized ciphertext-policy attribute-based encryption in standard model 14th

Fully secure decentralized ciphertext-policy attribute-based...

引用

14th International Conference on Information security and Cryptology, Inscrypt 2018

作者： Ma, Chuangui Ge, Aijun Zhang, Jie Army Aviation Institute Beijing China Key Laboratory of Cryptologic Technology and Information Security Ministry of Education Shandong University Jinan China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9783030142339

In this paper, we introduce a new multi-authority ciphertext policy attribute-based encryption (MA-CP-ABE) system. In our system, there are multiple central authorities (CAs) and attribute authorities (AAs). The CAs will not need to coordinate or even be aware of each other, and so do the AAs. In particular, we present two constructions that will be proved secure in the standard model. Our first scheme is fully secure under static assumptions in composite-order bilinear group, and can work for any monotone access structure. The second one achieves constant size ciphertexts for AND-gate policy in prime-order group. The security can be proved under the decisional linear (DLIN) assumption. © 2019, Springer Nature Switzerland AG.

关键词： Cryptography

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OSAF_e: One-Stage Anchor Free Object Detection Method Considering Effective Area 9th

OSAF_e: One-Stage Anchor Free Object Detection Method Consid...

引用

9th International Conference on Artificial Intelligence and Mobile Services, AIMS 2020, held as part of the Services Conference Federation, SCF 2020

作者： Zhang, Yong Zhang, Lizong Rao, Zhihong Duan, Guiduo Wang, Chunyu School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China China Electronic Technology Cyber Security Co. Ltd. Chengdu610000 China Trusted Cloud Computing and Big Data Key Laboratory of Sichuan Province Chengdu611731 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9783030596040

The task of object detection is to identify the bounding box of the object and its corresponding category in images. In this paper, we propose a new one-stage anchor free object detection algorithm OSAF_e, with the consideration of effective mapping area. A feature extraction network is used to obtain high level feature, and the true bounding box of the object in the original image is mapped to the grid of feature map, in order to perform category prediction and bounding box regression. The proposed algorithm is evaluated with the Pascal Voc dataset, and the experiments indicate that it has a better result. © 2020, Springer Nature Switzerland AG.

关键词： Object detection

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Sustainable Wireless networks via Reconfigurable Intelligent Surfaces (RISs): Overview of the ETSI ISG RIS

arXiv

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arXiv 2024年

作者： Liu, Ruiqi Zheng, Shuang Wu, Qingqing Jiang, Yifan Zhang, Nan Liu, Yuanwei Di Renzo, Marco Alexandropoulos, George C. The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen China Wireless and Computing Research Institute ZTE Corporation Shenzhen China The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China The School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Panepistimiopolis Ilissia Athens15784 Greece

Reconfigurable Intelligent Surfaces (RISs) are a novel form of ultra-low power devices that are capable to increase the communication data rates as well as the cell coverage in a cost- and energy-efficient way. This is attributed to their programmable operation that enables them to dynamically manipulate the wireless propagation environment, a feature that has lately inspired numerous research investigations and applications. To pave the way to the formal standardization of RISs, the European Telecommunications Standards Institute (ETSI) launched the Industry Specification Group (ISG) on the RIS technology in September 2021. This article provides a comprehensive overview of the status of the work conducted by the ETSI ISG RIS, covering typical deployment scenarios of reconfigurable metasurfaces, use cases and operating applications, requirements, emerging hardware architectures and operating modes, as well as the latest insights regarding future directions of RISs and the resulting smart wireless environments. © 2024, CC BY-NC-ND.

关键词： Standardization

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A local descriptor with physiological characteristic for finger vein recognition

arXiv

引用

arXiv 2020年

作者： Zhang, Liping Li, Weijun Ning, Xin Institute of Semiconductors Chinese Academy of Sciences Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology School of Microelectronics University of Chinese Academy of Sciences Cognitive Computing Technology Joint Laboratory Wave Group Beijing China

Local feature descriptors exhibit great superiority in finger vein recognition due to their stability and robustness against local changes in images. However, most of these are methods use general-purpose descriptors that do not consider finger vein-specific features. In this work, we propose a finger vein-specific local feature descriptors based physiological characteristic of finger vein patterns, i.e., histogram of oriented physiological Gabor responses (HOPGR), for finger vein recognition. First, prior of directional characteristic of finger vein patterns is obtained in an unsupervised manner. Then the physiological Gabor filter banks are set up based on the prior information to extracte the physiological responses and orientation. Finally, to make feature has robustness against local changes in images, histogram is generated as output by dividing the image into non-overlapping cells and overlapping blocks. Extensive experimental results on several databases clearly demonstrate that the proposed method outperforms most current state-of-the-art finger vein recognition methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Gabor filters

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On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation

arXiv

引用

arXiv 2020年

作者： Li, Jianing Lan, Yanyan Guo, Jiafeng Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

The goal of text generation models is to fit the underlying real probability distribution of text. For performance evaluation, quality and diversity metrics are usually applied. However, it is still not clear to what extend can the quality-diversity evaluation reflect the distribution-fitting goal. In this paper, we try to reveal such relation in a theoretical approach. We prove that under certain conditions, a linear combination of quality and diversity constitutes a divergence metric between the generated distribution and the real distribution. We also show that the commonly used BLEU/Self-BLEU metric pair fails to match any divergence metric, thus propose CR/NRR as a substitute for quality/diversity metric pair. Copyright © 2020, The Authors. All rights reserved.

关键词： Probability distributions

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Attention-Based Interaction Trajectory Prediction 9th

Attention-Based Interaction Trajectory Prediction

引用

9th International Conference on Artificial Intelligence and Mobile Services, AIMS 2020, held as part of the Services Conference Federation, SCF 2020

作者： Liu, Zhe Zhang, Lizong Rao, Zhihong Liu, Guisong School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China China Electronic Technology Cyber Security Co. Ltd. Chengdu610000 China Trusted Cloud Computing and Big Data Key Laboratory of Sichuan Province Chengdu611731 China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan528402 China

ISBN: (纸本)9783030596040

Trajectory prediction is a hot topic in the field of computer vision and has a wide range of applications. Trajectory prediction refers to predicting the future trajectory of a target based on its past trajectory. This paper proposes a method based on graph neural network and attention mechanism, in order to update trajectory characteristics by implement global pedestrian interaction. And, a direct relationship between history and future is introduced with the attention module for reducing error propagation. The method was evaluated on several real-world crowd datasets, the results demonstrate the effectiveness of our method. © 2020, Springer Nature Switzerland AG.

关键词： Trajectories

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ICT at TREC 2019: Fair Ranking Track 28

ICT at TREC 2019: Fair Ranking Track

引用

28th Text REtrieval Conference, TREC 2019

作者： Wang, Meng Zhang, Haopeng Liang, Fuhuai Feng, Bin Zhao, Di CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

In this paper, we will introduce our work in the 2019 TREC fair ranking task. In temporal academic search, more and more people choose to pay attention to the fairness constraints of ranking. The purpose of this task is to provide fairness exposure to different groups of authors, where the definition of group is diverse, such as based on demographics, height, topics, etc. For this reason, the model we design should consider the fairness of the ranking results while ensuring the relevance of the ranking results. We will show how to use our model to achieve the relevance of query results, then adjust the overall ranking results according to the fairness of documents, and finally achieve the relevance and fairness of document ordering. This paper will introduce the framework and methods of the fair ranking system, as well as the experimental results. © 2019 28th Text REtrieval Conference, TREC 2019 - Proceedings. All Rights Reserved.

关键词：

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Peripheral-free device pairing by randomly switching power

arXiv

引用

arXiv 2020年

作者： Shao, Zhijian Weng, Jian Zhang, Yue Wu, Yongdong Li, Ming Weng, Jiasi Luo, Weiqi Yu, Shui College of Informatin Science and Technology College of Cyber security National Joint Engineering Research Center of Network Security Detection and Protection Technology Guangdong Key Laboratory of Data Security and Privacy Preserving Jinan University Guangzhou510632 China University of Technology Sydney UltimoNSW Australia

The popularity of Internet-of-Things (IoT) comes with security concerns. Attacks against wireless communication venues of IoT (e.g., Man-in-the-Middle attacks) have grown at an alarming rate over the past decade. Pairing, which allows the establishment of the secure communicating channels for IoT devices without a prior relationship, is thus a paramount capability. Existing secure pairing protocols require auxiliary equipment/peripheral (e.g., displays, speakers and sensors) to achieve authentication, which is unacceptable for low-priced devices such as smart lamps. This paper studies how to design a peripheral-free secure pairing protocol. Concretely, we design the protocol, termed SwitchPairing, via out-of-box power supplying chargers and on-board clocks, achieving security and economics at the same time. When a user wants to pair two or more devices, he/she connects the pairing devices to the same power source, and presses/releases the switch on/off button several times. Then, the press and release timing can be used to derive symmetric keys. We implement a prototype via two CC2640R2F development boards from Texas Instruments (TI) due to its prevalence. Extensive experiments and user studies are also conducted to benchmark our protocol in terms of efficiency and security. Copyright © 2020, The Authors. All rights reserved.

关键词： Internet of things

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