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arXiv 2020年

作者： Wu, Xiongwei Li, Qiang Li, Xiuhua Leung, Victor C.M. Ching, P.C. Department of Electronic Engineering Faculty of Engineering Chinese University of Hong Kong Shatin Hong Kong School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Peng Cheng Laboratory Shenzhen518052 China School of Big Data and Software Engineering Chongqing University Chongqing401331 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Explosive growth of mobile data demand may impose a heavy traffic burden on fronthaul links of cloud-based small cell networks (C-SCNs), which deteriorates users’ quality of service (QoS) and requires substantial power consumption. This paper proposes an efficient maximum distance separable (MDS) coded caching framework for a cache-enabled C-SCNs, aiming at reducing long-term power consumption while satisfying users’ QoS requirements in short-term transmissions. To achieve this goal, the cache resource in small-cell base stations (SBSs) needs to be reasonably updated by taking into account users’ content preferences, SBS collaboration, and characteristics of wireless links. Specifically, without assuming any prior knowledge of content popularity, we formulate a mixed timescale problem to jointly optimize cache updating, multicast beamformers in fronthaul and edge links, and SBS clustering. Nevertheless, this problem is anti-causal because an optimal cache updating policy depends on future content requests and channel state information. To handle it, by properly leveraging historical observations, we propose a two-stage updating scheme by using Frobenius-Norm penalty and inexact block coordinate descent method. Furthermore, we derive a learning-based design, which can obtain effective tradeoff between accuracy and computational complexity. Simulation results demonstrate the effectiveness of the proposed two-stage framework. Copyright © 2020, The Authors. All rights reserved.

关键词： Electric power utilization

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Stability Analysis of An e-SEIR System in Network Society

Stability Analysis of An e-SEIR System in Network Society

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2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018

作者： Ge, Shao-Ting Liu, Zhimin Kang, Lijuan Yuan, Zhenxiang Yao, Guanan Lin, Ruoxuan Qingdao University College of Data Science and Software Engineering Qingdao China Qingdao Technical College School of Information Qingdao China

ISBN: (纸本)9781728105512

We analyzed the a discrete-time e-SEIR system, which represents the computer virus propagation model in network society. Firstly, we derive two kinds of equilibriums for the model. Secondly, we obtain sufficient stability condition for the no-disease equilibrium using the first Lyapunov stability method. Lastly, we obtain stability conditions for the disease equilibrium using disc theory. © 2018 IEEE.

关键词： Digital control systems

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Unsupervised Learning-Guided Accelerated Discovery of Alkaline Anion Exchange Membranes for Fuel Cells

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Angewandte Chemie 2023年第19期135卷

作者： Dr. Xiuyang Zou Guodong Xu Pengda Fang Dr. Weizheng Li Zhiyu Jin Dr. Siyu Guo Yin Hu Prof. Meisheng Li Ji Pan Prof. Zhe Sun Prof. Feng Yan Jiangsu Engineering Laboratory of Novel Functional Polymeric Materials Jiangsu Key Laboratory of Advanced Negative Carbon Technologies College of Chemistry Suzhou Key Laboratory of Soft Material and New Energy College of Chemistry Chemical Engineering and Materials Science Soochow University Suzhou 215123 China Contribution: Data curation (supporting) Contribution: Formal analysis (equal) Contribution: Formal analysis (supporting) Contribution: Validation (equal) Contribution: Methodology (supporting) School of Chemistry and Chemical Engineering Jiangsu Key Laboratory for Chemistry of Low-Dimensional Materials Huaiyin Normal University Huaian 223300 China Contribution: Software (equal) Contribution: Software (supporting) Contribution: Conceptualization (equal) Contribution: Conceptualization (lead)

Without insight into the correlation between the structure and properties, anion exchange membranes (AEMs) for fuel cells are developed usually using the empirical trial and error method or simulation methods. Here, a virtual module compound enumeration screening (V-MCES) approach, which does not require the establishment of expensive training databases and can search the chemical space containing more than 4.2×10 5 candidates was proposed. The accuracy of the V-MCES model was considerably improved when the model was combined with supervised learning for the feature selection of molecular descriptors. Techniques from V-MCES, correlating the molecular structures of the AEMs with the predicted chemical stability, generated a ranking list of potential high stability AEMs. Under the guidance of V-MCES, highly stable AEMs were synthesized. With understanding of AEM structure and performance by machine learning, AEM science may enter a new era of unprecedented levels of architectural design.

关键词： Alkaline Stability Anion Exchange Membranes Degradation Prediction Machine Learning Material Genomics

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A case study of MapReduce-based expressway traffic data analysis and service system

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International Journal of Internet Manufacturing and Services 2020年第4期7卷 278-289页

作者： Liu, Jia Hong, Zhilong Mo, Tong Ding, Weilong Zhang, Jian Li, Weiping Li, Haochen Henan Expressway Network Monitoring Charge Communication Service Co. Ltd. Henan China School of Software and Microelectronics Peking University Beijing China Data Engineering Institute North China University of Technology Beijing China School of Economics and Management Beijing Information Science and Technology University Beijing China College of Science China Agricultural University Beijing China

The scale of expressway information networking is constantly expanding. Currently the existing analysis system is still built on the relational database. Traffic data produced by the system has reached a data volume of 3 million items monthly. The performance requirements, including high concurrency, massive throughput, visualisation and scalability, are difficult to be satisfied. The expressway traffic data analysis system (ETDAS) is designed to meet the needs of the collection, analysis and visualisation of increasing expressway traffic data by means of the distributed frameworks. The new system is expected to help regulate the road network traffic flow, reduce traffic congestion, and provide analytical support for the optimisation strategy of road network. ETDAS has been deployed online. © 2020 Inderscience Enterprises Ltd.

关键词： MapReduce

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Active Sites Decorated Nonpolar Pore-Based MOF for One-step Acquisition of C2H4and Recovery of C3H6

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Angewandte Chemie 2023年第43期135卷

作者： Dr. Gang-Ding Wang Dr. Yong-Zhi Li Dr. Wen-Juan Shi Prof. Lei Hou Prof. Yao-Yu Wang Prof. Zhonghua Zhu Key Laboratory of Synthetic and Natural Functional Molecule of the Ministry of Education College of Chemistry & Materials Science Northwest University Xi'an 710069 P. R. China Contribution: Data curation (lead) Investigation (lead) Methodology (equal) Writing - original draft (lead) Contribution: Data curation (equal) Formal analysis (equal) Writing - review & editing (supporting) Contribution: Formal analysis (equal) Software (equal) Contribution: Software (lead) Supervision (lead) Writing - review & editing (lead) Contribution: Formal analysis (equal) Resources (equal) School of Chemical Engineering The University of Queensland Brisbane 4072 Australia

Herein, a 2-fold interpenetrated metal-organic framework (MOF) Zn-BPZ-TATB with accessible N/O active sites in nonpolar pore surfaces was reported for one-step C 2 H 4 purification from C 2 H 6 or C 3 H 6 mixtures as well as recovery of C 3 H 6 from C 2 H 6 /C 3 H 6 /C 2 H 4 mixtures. The MOF exhibits the favorable C 2 H 6 and C 3 H 6 uptakes (>100 cm 3 g −1 at 298 K under 100 kPa) as well as selective adsorption of C 2 H 6 and C 3 H 6 over C 2 H 4 . The C 3 H 6 - and C 2 H 6 -selective feature were investigated detailedly by experimental tests as well as sorption kinetic studyies. Molecular modelling revealed the multiple interactions between C 3 H 6 or C 2 H 6 molecules and methyl groups as well as triazine rings in pores. Zn-BPZ-TATB not only can directly generate 323.4 L kg −1 and 15.4 L kg −1 of high-purity (≥99.9 %) C 2 H 4 from C 3 H 6 /C 2 H 4 and C 2 H 6 /C 2 H 4 mixtures, but also provide a large high-purity (≥99.5 %) C 3 H 6 recovery capacity of 60.1 L kg −1 from C 3 H 6 /C 2 H 4 mixtures. More importantly, the high-purity C 3 H 6 (≥99.5 %) and C 2 H 4 (≥99.9 %) with the productivities of 38.2 and 12.7 L kg −1 can be simultaneously obtained from C 2 H 6 /C 3 H 6 /C 2 H 4 mixtures through a single adsorption/desorption cycle.

关键词： Crystal Structure Ethylene Purification Gas Adsorption and Separation Metal–Organic Framework Microporous Materials

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A study on the uncertainty of convolutional layers in deep neural networks

arXiv

引用

arXiv 2020年

作者： Shen, Haojing Chen, Sihong Wang, Ran Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University ShenzhenGuangdong518060 China College of Mathematics and Statistics Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China

This paper shows a Min-Max property existing in the connection weights of the convolutional layers in a neural network structure, i.e., the LeNet. Specifically, the Min-Max property means that, during the back propagation-based training for LeNet, the weights of the convolutional layers will become far away from their centers of intervals, i.e., decreasing to their minimum or increasing to their maximum. From the perspective of uncertainty, we demonstrate that the Min-Max property corresponds to minimizing the fuzziness of the model parameters through a simplified formulation of convolution. It is experimentally confirmed that the model with the Min-Max property has a stronger adversarial robustness, thus this property can be incorporated into the design of loss function. This paper points out a changing tendency of uncertainty in the convolutional layers of LeNet structure, and gives some insights to the interpretability of convolution. © 2020, CC-BY.

关键词： Convolution

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Incorporating Hidden Layer representation into Adversarial Attacks and Defences

arXiv

引用

arXiv 2020年

作者： Shen, Haojing Chen, Sihong Wang, Ran Wang, Xizhao Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Guangdong Shenzhen518060 China The College of Mathematics and Statistics Shenzhen University Shenzhen518060 China The Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China

In this paper, we propose a defence strategy to improves adversarial robustness incorporating hidden layer representation. The key of this defence strategy aims to compress or filter input’s information including adversarial perturbation. And this defence strategy can be regarded as an activation function which can be applied any kind of neural networks. We also prove theoretically the effectiveness of this defense strategy under certain conditions. Besides, incorporating hidden layer representation we propose three types of adversarial attacks to generate three types of adversarial examples, respectively. The experiments show that our defence method can significantly improve the adversarial robustness of deep neural networks which achieves the state-of-the-art performance even though we do not adopt adversarial training. © 2020, CC BY.

关键词： Deep neural networks

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NERank+: a graph-based approach for entity ranking in document collections

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计算机科学前沿 2018年第3期12卷 504-517页

作者： Chengyu WANG Guomin ZHOU Xiaofeng HE Aoying ZHOU Shanghai Key Laboratory of Trustworthy Computing School of Computer Science and Software EngineeringEast China Normal University Shanghai 200062 China Department of Computer and Information Technology Zhejiang Police College Hangzhou 310053 China School of Data Science and Engineering East China Normal University Shanghai 200062 China

Most entity ranking research aims to retrieve a ranked list of entities from a Web corpus given a user *** rank order of entities is determined by the relevance between the query and contexts of ***,entities can be ranked directly based on their relative importance in a document collection,independent of any *** this paper,we introduce an entity ranking algorithm named NERank+.Given a document collection,NERank+ first constructs a graph model called Topical Tripartite Graph,consisting of document,topic and entity *** design separate ranking functions to compute the prior ranks of entities and topics,respectively.A meta-path constrained random walk algorithm is proposed to propagate prior entity and topic ranks based on the graph *** evaluate NERank+ over real-life datasets and compare it with *** results illustrate the effectiveness of our approach.

关键词： entity ranking Topical Tripartite Graph prior rank estimation meta-path constrained random walk

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Rely-Guarantee Reasoning about Messaging System for Autonomous Vehicles

Rely-Guarantee Reasoning about Messaging System for Autonomo...

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Theoretical Aspects of software engineering (TASE)

作者： Wenjing Xu Yongwang Zhao Dianfu Ma YuXin Zhang Qian Xiao State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang Univerisity Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China State Key Laboratory of Automotive Simulation and Control College of Automotive Engineering Jilin University Jilin China School of Computer Science and Technology Guizhou University Guiyang China

Messaging system as a communicating infrastructure is a safety-critical component of autonomous vehicles. For the purpose of safety certification of Level 4 autonomous driving systems, its necessary to provide a formally verified specification of messaging systems. This paper presents a realistic case study using the PiCore rely-guarantee framework to formally verify the DGPS (Differential Global Positioning System) of UISEE autonomous driving systems. We first create an axiom model of messaging systems by extending PiCore, which is reusable for concrete applications. The model supports dynamic configuration of message buffers as well as the automatic generation of the rely and guarantee conditions for compositional reasoning. It is instantiated when developing the formal specification of DGPS. Then, we use the rely-guarantee proof system of PiCore to verify the functional correctness and invariant of DGPS. The specification and its proof provide a strong evidence for the ongoing safety certification of DGPS.

关键词： Cognition Safety Formal specifications Vehicle dynamics Autonomous vehicles Certification Global Positioning System

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Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future Prospects

arXiv

引用

arXiv 2021年

作者： Ahmad, Muhammad Shabbir, Sidrah Roy, Swalpa Kumar Hong, Danfeng Wu, Xin Yao, Jing Khan, Adil Mehmood Mazzara, Manuel Distefano, Salvatore Chanussot, Jocelyn Department of Computer Science National University of Computer and Emerging Sciences Islamabad Chiniot-Faisalabad Campus Chiniot35400 Pakistan Dipartimento di Matematica e Informatica-MIFT University of Messina Messina98121 Italy Pakistan The Department of Computer Science and Engineering Jalpaiguri Government Engineering College West Bengal 735102 India The Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China The School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Fractional Signals and Systems Beijing100081 China The Institute of Data Science and Artificial Intelligence Innopolis University Innopolis 420500 Russia Institute of Software Development and Engineering Innopolis University Innopolis420500 Russia The Univ. Grenoble Alpes CNRS Grenoble INP GIPSA-Lab Grenoble38000 France

Hyperspectral Imaging (HSI) has been extensively utilized in many real-life applications because it benefits from the detailed spectral information contained in each pixel. Notably, the complex characteristics i.e., the nonlinear relation among the captured spectral information and the corresponding object of HSI data make accurate classification challenging for traditional methods. In the last few years, Deep Learning (DL) has been substantiated as a powerful feature extractor that effectively addresses the nonlinear problems that appeared in a number of computer vision tasks. This prompts the deployment of DL for HSI classification (HSIC) which revealed good performance. This survey enlists a systematic overview of DL for HSIC and compared state-of-the-art strategies of the said topic. Primarily, we will encapsulate the main challenges of traditional machine learning for HSIC and then we will acquaint the superiority of DL to address these problems. This survey breakdown the state-of-the-art DL frameworks into spectral-features, spatial-features, and together spatial-spectral features to systematically analyze the achievements (future research directions as well) of these frameworks for HSIC. Moreover, we will consider the fact that DL requires a large number of labeled training examples whereas acquiring such a number for HSIC is challenging in terms of time and cost. Therefore, this survey discusses some strategies to improve the generalization performance of DL strategies which can provide some future guidelines. © 2021, CC BY.

关键词： Surveys

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