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arXiv 2024年

作者： Evans, Matthew L. Bergsma, Johan Merkys, Andrius Andersen, Casper W. Andersson, Oskar B. Beltrán, Daniel Blokhin, Evgeny Boland, Tara M. Balderas, Rubén Castañeda Choudhary, Kamal Díaz, Alberto Díaz García, Rodrigo Domínguez Eckert, Hagen Eimre, Kristjan Montero, María Elena Fuentes Krajewski, Adam M. Mortensen, Jens Jørgen Duarte, José Manuel Nápoles Pietryga, Jacob Qi, Ji de Jesús Trejo Carrillo, Felipe Vaitkus, Antanas Yu, Jusong Zettel, Adam de Castro, Pedro Baptista Carlsson, Johan Cerqueira, Tiago F.T. Divilov, Simon Hajiyani, Hamidreza Hanke, Felix Jose, Kevin Oses, Corey Riebesell, Janosh Schmidt, Jonathan Winston, Donald Xie, Christen Yang, Xiaoyu Bonella, Sara Botti, Silvana Curtarolo, Stefano Draxl, Claudia Cobas, Luis Edmundo Fuentes Hospital, Adam Liu, Zi-Kui Marques, Miguel A.L. Marzari, Nicola Morris, Andrew J. Ong, Shyue Ping Orozco, Modesto Persson, Kristin A. Thygesen, Kristian S. Wolverton, Chris Scheidgen, Markus Toher, Cormac Conduit, Gareth J. Pizzi, Giovanni Gražulis, Saulius Rignanese, Gian-Marco Armiento, Rickard Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium Matgenix SRL 185 Rue Armand Bury Gozée6534 Belgium École Polytechnique Fédérale de Lausanne Avenue de Forel 3 Lausanne1015 Switzerland Institute of Biotechnology Life Sciences Center Vilnius University Sauletekio av. 7 VilniusLT-10257 Lithuania SINTEF P.O. Box 4760 Torgarden TrondheimNO-7465 Norway Materials Design and Informatics unit Department of Physics Chemistry and Biology Linköping University Sweden Baldiri i Reixac 10-12 Barcelona08028 Spain Tilde Materials Informatics Straßmannstraße 25 Berlin10249 Germany Materials Platform for Data Science Sepapaja 6 Tallinn15551 Estonia Computational Atomic-Scale Materials Design Technical University of Denmark Kgs. Lyngby Denmark Av. Miguel de Cervantes 120 Complejo Industrial Chihuahua Chihuahua Chih. 31136 Mexico Material Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Center for Extreme Materials Duke University DurhamNC27708 United States École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Universidad Autónoma de Chihuahua Facultad de Ciencias Quimicas Chihuahua31125 Mexico Department of Materials Science and Engineering The Pennsylvania State University University ParkPA16802 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of NanoEngineering University of California 9500 Gilman Drive La Jolla San DiegoCA92093-0448 United States National Institute for Materials Science 1-2-1 Sengen Ibaraki Tsukuba305-0047 Japan Dassault Systèmes Germany GmbH Am Kabellager 11-13 Cologne51063 Germany CFisUC Department of Physics University of Coimbra Rua Larga Coimbra3004-516 Portugal Dassault Systèmes 22 Science Park CB4 0FJ United Kingdom Theory of Condensed Matter Cavendis

The Open databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development. © 2024, CC BY.

关键词： Electronic data interchange

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Recovery and repair schemes for shift-XOR regenerating codes

arXiv

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arXiv 2019年

作者： Fu, Ximing Yang, Shenghao Xiao, Zhiqing School of Science and Engineering Chinese University of Hong Kong Shenzhen China University of Science and Technology of China China School of Science and Engineering Chinese University of Hong Kong Shenzhen Guangdong518172 China Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology Chinese University of Hong Kong Shenzhen Guangdong518172 China Shenzhen Research Institute of Big Data Shenzhen Guangdong518172 China Tsinghua University

Recovery and repair schemes are proposed for shift-exclusive-or (shift-XOR) product-matrix (PM) regenerating codes, which outperform those of the existing PM codes in terms of both communication and computation costs. In particular, for the minimum bandwidth regenerating (MBR) codes, our recovery and repair schemes have the optimal transmission bandwidth, zero decoding auxiliary data space and lower time complexity;for the minimum storage regenerating (MSR) codes, our recovery and repair schemes have smaller transmission bandwidth, smaller decoding auxiliary data space and lower time complexity. Moreover, our schemes involve only XOR operations in recovery and repair and are practical for system implementation. Technically, a procedure is first proposed for solving a system of shift-XOR equations, which plays a similar fundamental role as Gaussian elimination for solving systems of linear equations, and is of independent interest. The recovery and repair of shift-XOR MBR/MSR codes are then decomposed into a sequence of systems of shift-XOR equations, and hence can be solved by a sequence of calls to the procedure for solving a system of shift-XOR equations. As the decomposition of the recovery and repair depends only on the PM construction, but not the specific shift and XOR operations, our recovery and repair schemes can be extended to other MBR/MSR codes using the PM construction. Copyright © 2019, The Authors. All rights reserved.

关键词： Matrix algebra

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Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings

arXiv

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arXiv 2020年

作者： Yu, Liang Sun, Yi Xu, Zhanbo Shen, Chao Yue, Dong Jiang, Tao Guan, Xiaohong College of Automation & College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing210003 China Systems Engineering Institute Ministry of Education Key Lab for Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an710049 China college of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210003 China Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Wuhan National Laboratory for Optoelectronics School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China

In commercial buildings, about 40%-50% of the total electricity consumption is attributed to Heating, Ventilation, and Air Conditioning (HVAC) systems, which places an economic burden on building operators. In this paper, we intend to minimize the energy cost of an HVAC system in a multi-zone commercial building under dynamic pricing with the consideration of random zone occupancy, thermal comfort, and indoor air quality comfort. Due to the existence of unknown thermal dynamics models, parameter uncertainties (e.g., outdoor temperature, electricity price, and number of occupants), spatially and temporally coupled constraints associated with indoor temperature and CO2 concentration, a large discrete solution space, and a non-convex and non-separable objective function, it is very challenging to achieve the above aim. To this end, the above energy cost minimization problem is reformulated as a Markov game. Then, an HVAC control algorithm is proposed to solve the Markov game based on multi-agent deep reinforcement learning with attention mechanism. The proposed algorithm does not require any prior knowledge of uncertain parameters and can operate without knowing building thermal dynamics models. Simulation results based on real-world traces show the effectiveness, robustness and scalability of the proposed algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Nonlinear Prediction with Deep Recurrent Neural networks for Non-Blind Audio Bandwidth Extension

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China Communications 2018年第4期15卷 72-85页

作者： Lin Jiang Ruimin Hu Xiaochen Wang Weiping Tu Maosheng Zhang National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan 430072 China Institute of Big Data and internet Innovation Hunan University of Commerce Changsha 410205 China Software College East China University of Technology Nanchang 330013 China Collaborative Innovation Center for Economics crime investigation and prevention technology Jiangxi Province Nanchang 330103China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan 430072 China Collaborative Innovation Center of Geospatial Technology Wuhan 430079 China

Non-blind audio bandwidth extension is a standard technique within contemporary audio codecs to efficiently code audio signals at low bitrates. In existing methods, in most cases high frequencies signal is usually generated by a duplication of the corresponding low frequencies and some parameters of high frequencies. However, the perception quality of coding will significantly degrade if the correlation between high frequencies and low frequencies becomes weak. In this paper, we quantitatively analyse the correlation via computing mutual information value. The analysis results show the correlation also exists in low frequency signal of the context dependent frames besides the current frame. In order to improve the perception quality of coding, we propose a novel method of high frequency coarse spectrum generation to improve the conventional replication method. In the proposed method, the coarse high frequency spectrums are generated by a nonlinear mapping model using deep recurrent neural network. The experiments confirm that the proposed method shows better performance than the reference methods.

关键词： audio coding non-blind audiobandwidth extension context correlation deeprecurrent neural network

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An Authentication Scheme Using Identity-based Encryption & Blockchain

An Authentication Scheme Using Identity-based Encryption & B...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Beini Zhou Hui Li Li Xu Shenzhen Key Lab of Information Theory & Future Network Arch Future Network PKU Lab of National Major Research Infrastructure PKU Inst. of Big Data Technology

Identity-based encryption is a key distribution system in which the public key of a user is derived directly from his identity information. Compared with PKI, Identity-based encryption simplifies key management issue, but it still suffers from drawbacks inkey escrow and private key delivering. Motivated by this, we propose an improved key distribution solution called BIBE by integrating the technique of blockchain into the identity-based encryption. Specifically, we split the nodes in the chain to complete user authentication and private key protection, respectively. Furthermore, the two sides complete the mutual identity authentication with the identity information key pairs obtained from BIBE. Additionally, to prevent network attack, we employ timestamps, random numbers and hash algorithm in the process of identification. Through the rigorous and mathematical analysis, the proposed scheme demonstratesa far better performance on correctness, safety and efficiency.

关键词： Authentication Production Encryption Computers Identity-based encryption

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Comparison of Research on Social Media in China and Foreign Countries Based on Bibliometric Analysis

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Journal of Physics: Conference Series 2020年第1期1616卷

作者： Peng Yunan Wang Zongshui Feng Yueyang Yang shengqin School of Economics and Management Beijing Information Science and Technology University Beijing 100192 China Beijing Key Lab of Green Development and Decision Based on Big Data Beijing 100192 China

This paper aims to compare the similarities and differences of Chinese and foreign research on social media. Cluster analysis, co-word analysis and social network analysis have been used to compare the research trends, content relevance and network structure of research on social media. (1) Similarities: Social media is a hot topic for scholars both in China and foreign countries; the development of social network technology leads to many new areas; social media research tends to study privacy, commerciality and service; hotspots of social media research in China and foreign countries both include social media, platform and social network. (2) Difference: Chinese research mainly focuses on big data, Wechat and Weibo, while foreign research mainly focuses on Facebook, Twitter and other kinds of social network media; Chinese research is clustered while foreign research is extensive; Chinese research pays more attention on macroscopic perspectives, such as media convergence, big data and libraries; foreign research tends to microcosmic perspectives, such as emotional analysis, crisis information dissemination, social media marketing.

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Heralded amplification of single-photon entanglement with polarization feature

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Frontiers of physics 2018年第5期13卷 241-249页

作者： Yu-Yu Jin Sheng-Xian Qin Hao Zu Lan Zhou Wei Zhong Yu-Bo Sheng School of Science Nanjing University of Posts and Telecommunications Nanjing 210003 China New Energy Technology Engineering Laboratory of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing 210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing 210003 China Institute of Signal Processing Transmission Nanjing University of Posts and Telecommunications Nanjing 210003 China

Heralded noiseless amplification is beneficial in overcoming transmission photon loss in a noisy quantum channel. We propose a single-photon-assisted heralded noiseless amplification protocol of the single- photon entanglement （SPE）, where the single-photon qubit has an arbitrary unknown polarization feature. We focus on both the complete and partial photon loss during the transmission process. After the amplification, the parties can recover the pure less-entangled SPE into a maximally entangled SPE and increase its fidelity. Moreover, the polarization feature of the single-photon qubit will be well preserved and not be leaked. Our protocol can be realized under our current experimental condition. Based on the features above, our protocol may be useful in the quantum secure communication schemes that encode information in the polarization degree of freedom of photons.

关键词： quantum communication single-photon entanglement quantum state amplification polarization feature

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A hybrid algorithm based on ILP and genetic algorithm for time-aware test case prioritization

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Journal of Southeast University(English Edition) 2018年第1期34卷 28-35页

作者： Sun Jiaze Wang Gang School of Computer Science and Technology Xi’anUniversity of Posts and TelecommunicatioosXi’an 710121China Shaanxi Key Laboratory of Network Data Intelligent Processing X’an University of Posts and TelecommunicationsX’an 710121China

To solve the problem of time-awarc test case prioritization,a hybrid algorithm composed of integer linear programming and the genetic algorithm(ILP-GA)is ***,the test case suite which cm maximize the number of covered program entities a d satisfy time constraints is selected by integer linea ***,the individual is encoded according to the cover matrices of entities,and the coverage rate of program entities is used as the fitness function and the genetic algorithm is used to prioritize the selected test *** typical open source projects are selected as benchmark *** and method are selected as program entities,and time constraint percentages a e 25%and 75%.The experimental results show that the ILP-GA convergence has faster speed and better stability than ILP-additional and IP-total in most cases,which contributes to the detection of software defects as early as possible and reduces the software testing costs.

关键词： test case prioritization integer linear programming(I LP) genetic algorithm time constraint

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Stacked Cross Refinement network for Edge-Aware Salient Object Detection

Stacked Cross Refinement Network for Edge-Aware Salient Obje...

引用

International Conference on Computer Vision (ICCV)

作者： Zhe Wu Li Su Qingming Huang School of Computer Science and Technology University of Chinese Academy of Sciences (UCAS) Beijing China Key Lab of Big Data Mining and Knowledge Management UCAS Beijing China Key Lab of Intell. Info. Process. Inst. of Comput. Tech. CAS Beijing China Peng Cheng Laboratory ShenZhen China

ISBN: (数字)9781728148038

ISBN: (纸本)9781728148045

Salient object detection is a fundamental computer vision task. The majority of existing algorithms focus on aggregating multi-level features of pre-trained convolutional neural networks. Moreover, some researchers attempt to utilize edge information for auxiliary training. However, existing edge-aware models design unidirectional frameworks which only use edge features to improve the segmentation features. Motivated by the logical interrelations between binary segmentation and edge maps, we propose a novel Stacked Cross Refinement network (SCRN) for salient object detection in this paper. Our framework aims to simultaneously refine multi-level features of salient object detection and edge detection by stacking Cross Refinement Unit (CRU). According to the logical interrelations, the CRU designs two direction-specific integration operations, and bidirectionally passes messages between the two tasks. Incorporating the refined edge-preserving features with the typical U-Net, our model detects salient objects accurately. Extensive experiments conducted on six benchmark datasets demonstrate that our method outperforms existing state-of-the-art algorithms in both accuracy and efficiency. Besides, the attribute-based performance on the SOC dataset show that the proposed model ranks first in the majority of challenging scenes. Code can be found at https://***/wuzhe71/SCAN.

关键词： Image edge detection Task analysis Feature extraction Object detection Image segmentation Silicon Computational modeling

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Channel Estimation for Ambient Backscatter Communication Systems with Massive-Antenna Reader

arXiv

引用

arXiv 2019年

作者： Zhao, Wenjing Wang, Gongpu Atapattu, Saman He, Ruisi Liang, Ying-Chang Beijing Key Lab of Transportation Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Department of Electrical and Electronic Engineering University of Melbourne ParkvilleVIC3010 Australia Center for Intelligent Networking and Communications University of Electronic Science and Technology of China Chengdu China

—Ambient backscatter, an emerging green communication technology, has aroused great interest from both academia and industry. One open problem for ambient backscatter communication (AmBC) systems is channel estimation for a massive-antenna reader. In this paper, we focus on channel estimation problem in AmBC systems with uniform linear array (ULA) at the reader which consists of large number of antennas. We first design a two-step method to jointly estimate channel gains and direction of arrivals (DoAs), and then refine the estimates through angular rotation. Additionally, Cramér-Rao lower bounds (CRLBs) are derived for both the modulus of the channel gain and the DoA estimates. Simulations are then provided to validate the analysis, and to show the efficiency of the proposed approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Backscattering

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