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Time series forecast of sales volume based on XGBoost

Journal of Physics: Conference Series 2021年第1期1873卷

作者： Lingyu Zhang Wenjie Bian Wenyi Qu Liheng Tuo Yunhai Wang 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.

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Improving The Biodegradability of Rice Straw by Electrochemical Pretreatment

SSRN

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SSRN 2022年

作者： Sun, Shaohua Zhang, Yuanyuan Yang, Zhaoyang Liu, Chunmei Zuo, Xiaoyu Tang, Yang Wan, Pingyu Liu, Yanping Li, Xiujin Coulon, Frederic Hu, Qing Yang, Xiao Jin State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology 15 Beisanhuan East Road Chaoyang District Beijing100029 China Beijing City Environmental Pollution Control and Resource Reuse Engineering Center Beijing University of Chemical Technology 15 Beisanhuan East Road Chaoyang District Beijing100029 China National Fundamental Research Laboratory of New Hazardous Chemicals Assessment and Accident Analysis Beijing University of Chemical Technology Beijing100029 China School of Water Energy and Environment Cranfield University Cranfield MK43 0AL United Kingdom School of Environmental Science and Engineering South University of Science and Technology Guangdong Shenzhen518055 China Beijing Huanding Environmental Big Data Institute No. 1 Wangzhuang Road Beijing100083 China

In this study, the efficacy of three different pretreatments of rice straw including alkaline hydrogen peroxide (NaOH-H2O2), electrochemically produced NaOH-H2O2 (eNaOH-H2O2) and electrohydrolysis (EH) was investigated. All three pretreatments allowed to reach 80% of total biogas production within 23 and 25 days which was 3 to 5 days faster compared to conventional NaOH pretreatment. The cumulative biogas production was enhanced by 8%, 22% and 14% for NaOH-H2O2, eNaOH-H2O2 and EH, respectively compared to traditional treatment. The eNaOH-H2O2 pretreatment decreased the crystallinity of cellulose and created a porous surface vein, thus promoting microbial degradation of lignocellulose. The findings of this study demonstrate that electrochemical pretreatment provides a promising approach for efficiently utilizing rice straw biomass to produce renewable electricity. © 2022, The Authors. All rights reserved.

关键词： Oxidation

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Generative Adversarial Networks for Image Super-Resolution: A Survey

arXiv

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arXiv 2022年

作者： Tian, Chunwei Zhang, Xuanyu Zhu, Qi Zhang, Bob Lin, Jerry Chun-Wei School of Software Northwestern Polytechnical University the National Engineering Laboratory for Integrated Aero-space-Ground-Ocean Big Data Application Technology 1 Dongxiang Rd Shaanxi Xi’an710129 China School of Software Northwestern Polytechnical University 1 Dongxiang Rd Shaanxi Xi’an710129 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics 101 Section 2 Kuang-Fu Road Jiangsu Nanjing China PAMI Research Group University of Macau 101 Section 2 Kuang-Fu Road Macao999078 China Department of Computer Science Western Norway University of Applied Sciences Bergen Norway

Single image super-resolution (SISR) has played an important role in the field of image processing. Recent generative adversarial networks (GANs) can achieve excellent results on low-resolution images with small samples. However, there are little literatures summarizing different GANs in SISR. In this paper, we conduct a comparative study of GANs from different perspectives. We first take a look at developments of GANs. Second, we present popular architectures for GANs in big and small samples for image applications. Then, we analyze motivations, implementations and differences of GANs based optimization methods and discriminative learning for image super-resolution in terms of supervised, semi-supervised and unsupervised manners, where these GANs are analyzed via integrating different network architectures, prior knowledge, loss functions and multiple tasks. Next, we compare performance of these popular GANs on public datasets via quantitative and qualitative analysis in SISR. Finally, we highlight challenges of GANs and potential research points for SISR. © 2022, CC BY-NC-ND.

关键词： Generative adversarial networks

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Space technology:A powerful tool for safeguarding world heritage

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The Innovation 2023年第3期4卷 27-28页

作者： Lei Luo Jie Liu Francesca Cigna Damian Evans Mario Hernandez Deodato Tapete Peter Shadie Athos Agapiou Abdelaziz Elfadaly Min Chen Lanwei Zhu Bihong Fu Ruixia Yang Shahina Tariq Mohamed Ouessar Rosa Lasaponara Xinyuan Wang Huadong Guo International Research Center of Big Data for Sustainable Development Goals(CBAS) Beijing 100094China Key Laboratory of Digital Earth Science Aerospace Information Research Institute(AIR)Chinese Academy of Sciences(CAS)Beijing 100094China International Centre on Space Technologies for Natural and Cultural Heritage(HIST)Under the Auspices of UNESCO Beijing 100094China Institute of Atmospheric Sciences and Climate(ISAC) National Research Council(CNR)00133 RomeItaly École Française d’Extreme-Orient 22 Avenue du Président Wilson75116 ParisFrance International Society for Digital Earth(ISDE) Mexico CityMexico Italian Space Agency(ASI) 00133 RomeItaly Blue Mountains World Heritage Institute 16 Dunmore LaneKatoombaNSW 2780Australia Earth Observation Cultural Heritage Research Lab Department of Civil Engineering and GeomaticsCyprus University of TechnologyPO Box 503296 Limassol 3036Cyprus National Authority for Remote Sensing and Space Sciences Cairo 1564Egypt Key Laboratory of Virtual Geographic Environment Ministry of Education of PRCNanjing Normal UniversityNanjing 210023China COMSATS University Islamabad(CUI) Islamabad 45550Pakistan Institut des Regions Arides(IRA)-Medenine Medenine 4119Tunisia Institute of Methodologies for Environmental Analysis(IMAA) CNRC.da Santa LojaTito Scalo85050 PotenzaItaly

WORLD HERITAGE AND SPACE technology The Convention Concerning the Protection of the World Cultural and Natural Heritage(WHC),adopted by United Nations Educational,Scientific and Cultural Organization(UNESCO)on November 16,1972,aims to ensure the identification,protection,conservation,presentation,and transmission to future generations of the world’s cultural and natural *** WHC works toward these goals by emphasizing the Outstanding Universal Value(OUV)of heritage sites and the unique contribution such places can make to conservation and human development agendas.1 As of the end of January 2023,theWHC has been signed by 194 state parties,covering 1,157 sites(including 900 cultural,218 natural,and 39 mixed properties),55 of which are considered to be in *** sites,totaling an area of more than 370 million hectares are designated as World Heritage(WH)sites(https://***/en/list/).WH sites have played a significant role in the sustainable development of society globally and helped effectively maintain and preserve the cultural diversity and global biodiversity of the Earth.

关键词： heritage maintain SPACE

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Robust frequent directions with application in online learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2019年第1期20卷

作者： Luo Luo Cheng Chen Zhihua Zhang Wu-Jun Li Tong Zhang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China National Engineering Lab for Big Data Analysis and Applications School of Mathematical Sciences Peking University Beijing China National Key Laboratory for Novel Software Technology Collaborative Innovation Center of Novel Software Technology and Industrialization Department of Computer Science and Technology Nanjing University Nanjing China Computer Science & Mathematics Hong Kong University of Science and Technology Hong Kong

The frequent directions (FD) technique is a deterministic approach for online sketching that has many applications in machine learning. The conventional FD is a heuristic procedure that often outputs rank deficient matrices. To overcome the rank deficiency problem, we propose a new sketching strategy called robust frequent directions (RFD) by introducing a regularization term. RFD can be derived from an optimization problem. It updates the sketch matrix and the regularization term adaptively and jointly. RFD reduces the approximation error of FD without increasing the computational cost. We also apply RFD to online learning and propose an effective hyperparameter-free online Newton algorithm. We derive a regret bound for our online Newton algorithm based on RFD, which guarantees the robustness of the algorithm. The experimental studies demonstrate that the proposed method outperforms state-of-the-art second order online learning algorithms.

关键词： frequent directions matrix approximation online Newton algorithm online convex optimization sketching

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NTIRE 2023 Challenge on Light Field Image Super-Resolution: dataset, Methods and Results

arXiv

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arXiv 2023年

作者： Wang, Yingqian Wang, Longguang Liang, Zhengyu Yang, Jungang Timofte, Radu Guo, Yulan Jin, Kai Wei, Zeqiang Yang, Angulia Guo, Sha Gao, Mingzhi Zhou, Xiuzhuang Van Duong, Vinh Huu, Thuc Nguyen Yim, Jonghoon Jeon, Byeungwoo Liu, Yutong Cheng, Zhen Xiao, Zeyu Xu, Ruikang Xiong, Zhiwei Liu, Gaosheng Jin, Manchang Yue, Huanjing Yang, Jingyu Gao, Chen Zhang, Shuo Chang, Song Lin, Youfang Chao, Wentao Wang, Xuechun Wang, Guanghui Duan, Fuqing Xia, Wang Wang, Yan Xia, Peiqi Wang, Shunzhou Lu, Yao Cong, Ruixuan Sheng, Hao Yang, Da Chen, Rongshan Wang, Sizhe Cui, Zhenglong Chen, Yilei Lu, Yongjie Cai, Dongjun An, Ping Salem, Ahmed Ibrahem, Hatem Yagoub, Bilel Kang, Hyun-Soo Zeng, Zekai Wu, Heng National University of Defense Technology China Aviation University of Air Force China University of Würzburg Germany ETH Zürich Switzerland The Shenzhen Campus of Sun Yat-Sen University Sun Yat-Sen University China Bigo Technology Pte. Ltd Singapore Smart Medical Innovation Lab Beijing University of Posts and Telecommunications China Global Explorer Ltd. Suzhou China National Engineering Research Center of Visual Technology School of Computer Science Peking University China School of Artificial Intelligence Beijing University of Posts and Telecommunications China Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of University of Science and Technology of China China School of Electrical and Information Engineering Tianjin University China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Beijing Normal University China Toronto Metropolitan University Canada Beijing Institute of Technology China Shenzhen MSU-BIT University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beihang Hangzhou Innovation Institute Yuhang China Faculty of Applied Sciences Macao Polytechnic University China School of Communication and Information Engineering Shanghai University China School of Information and Communication Engineering Chungbuk National University Korea Republic of Guangdong University of Technology China

In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development. Compared with single image SR, the major challenge of LF image SR lies in how to exploit complementary angular information from plenty of views with varying disparities. In total, 148 participants have registered the challenge, and 11 teams have successfully submitted results with PSNR scores higher than the baseline method LF-InterNet [1]. These newly developed methods have set new state-of-the-art in LF image SR, e.g., the winning method achieves around 1 dB PSNR improvement over the existing state-of-the-art method DistgSSR [2]. We report the solutions proposed by the participants, and summarize their common trends and useful tricks. We hope this challenge can stimulate future research and inspire new ideas in LF image SR. © 2023, CC BY-SA.

关键词： Image enhancement

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Designing preamplifier for sensing atmospheric electrostatic field strength via supercapacitive sensor

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Journal of Physics: Conference Series 2020年第1期1607卷

作者： Changhao Wu Yi Xiong Wei Zeng National Engineering Research Center for Agro-Ecological Big Data Analysis and Application School of Electronics and Information Engineering Anhui University Hefei 230601 People's Republic of China Science and Technology Institute Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing and Finishing Wuhan Textile University Wuhan 430073 People's Republic of China School of Physics and Technology MOE Key Laboratory of Artificial Micro- and Nano-Structures and Center for Electron Microscopy Wuhan University Wuhan 430072 People's Republic of China

In order to effectively obtain the signal from sensor, the analogy signal needs to be amplified and then converted into a digital signal for matching to the sensor characteristics. With a supercapacitive electric field sensor based on graphene aerogel, the response current signal from the electric field sensor is weak and unstable. Herein, a high gain and low noise preamplifier is developed, and an amplifier circuit with double T-type feedback network is proposed to reduce the Johnson noise for the amplifier. This design can reduce the thermal noise of resistance by using the smaller resistance under the same gain, and it can effectively reduce the interference of peak noise by adding the feedback capacitance, so as to improve the detection accuracy. The simulation results show that under the same gain condition, the Johnson noise can be reduced by 46% and the detection accuracy can be improved by 12% compared with the traditional T-type feedback network.

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Wide Band-Gap Polymer Donors Functionalized with Unconventional Carbamate Side Chains for Polymer Solar Cells

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Angewandte Chemie 2022年第50期134卷

作者： Jie Tang Chentong Liao Yuwei Duan Xiaopeng Xu Min Deng Liyang Yu Ruipeng Li Qiang Peng School of Chemical Engineering College of Chemistry and State Key Laboratory of Polymer Materials Engineering Sichuan University Chengdu 610065 P. R. China Contribution: Conceptualization (equal) Data curation (lead) Formal analysis (lead) Methodology (lead) Contribution: Data curation (equal) Formal analysis (equal) Methodology (equal) Key Laboratory of Applied Surface and Colloid Chemistry of Ministry of Education Shaanxi Key Laboratory for Advanced Energy Devices Shaanxi Engineering Lab for Advanced Energy Technology School of Materials Science & Engineering Shaanxi Normal University Xi'an 710119 P. R. China Contribution: Data curation (supporting) Formal analysis (supporting) Contribution: Conceptualization (supporting) Data curation (supporting) Formal analysis (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Methodology (supporting) Contribution: Conceptualization (supporting) Formal analysis (supporting) Investigation (supporting) Supervision (supporting) Writing - original draft (lead) Writing - review & editing (supporting) National Synchrotron Light Source II Brookhaven National Lab Suffolk Upton NY 11973 USA Contribution: Conceptualization (lead) Project administration (lead) Supervision (lead) Validation (lead) Writing - review & editing (lead)

Side-chain engineering with heteroatoms is not only effective in tuning frontier molecular orbitals, but also possible for forming secondary bonds which can be utilized to planarize the molecular backbone, hence, improving the photon absorption as well as charge-transport abilities of polymer solar-cell (PSC) materials. Herein, two types of unconventional side chains, namely carboxylate and carbamate, containing various heteroatoms are introduced to the thiophene bridges in high performance benzodithiophene (BDT) based donor polymers to from the novel polymers PTzTz-C and PTzTz-N, respectively. In these polymers, non-covalent O⋅⋅⋅S and N⋅⋅⋅H interactions induce a high tendency to aggregation. In a ternary-blend PSC with PTzTz-N added to the high-performance D18 : BTP-eC9 blend, complimentary absorption and improved thin-film morphology were observed with a top power conversion efficiency of 18.76 %, which is an improvement of almost 5 % over the D18 : BTP-eC9 binary blends.

关键词： Carbamate Conformation Locks Donor Polymer Solar Cells

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Versatile hydrogel based on polyvinyl alcohol/chitosan/regenerated silk fibroin

引用

Journal of Physics: Conference Series 2021年第1期2011卷

作者： Qinyue Sun Jizhu Fu Heng Zhang Huihui Yang Yumin Wang Yi Xiong Wei Zeng Faniu Wang Chao Xu National Engineering Research Center for Agro-Ecological Big Data Analysis & Application School of Electronics and Information Engineering Anhui University Hefei 230601 Anhui People's Republic of China School of Physics and Technology MOE Key Laboratory of Artificial Micro- and Nano-Structures and Center for Electron Microscopy Wuhan University Wuhan 430072 Hubei People's Republic of China Science and Technology Institute Key Laboratory of Textile Fiber and Products Ministry of Education Laboratory for Electron Microscopy Wuhan Textile University Wuhan 430073 Hubei People's Republic of China

Versatile sensors have broad application prospects in human motion detection, health monitoring, wearable electronic devices and flexible electronic skin and other emerging fields. In this work, the enhanced hydrogel was prepared by freezing and thawing process with calcium ion crosslinking. This composite material shows excellent flexibility and elasticity, and after being cut in half, it can automatically heal well in a short time without external force. It shows great potential in flexible and wearable devices.

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Reports of the AAAI 2014 conference workshops

Reports of the AAAI 2014 conference workshops

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作者： Albrecht, Stefano V. Barreto, André M. S. Braziunas, Darius Buckeridge, David L. Cuayáhuitl, Heriberto Dethlefs, Nina Endres, Markus Farahmand, Amir-Massoud Fox, Mark Frommberger, Lutz Ganzfried, Sam Guillet, Sébastien Gil, Yolanda Hunter, Lawrence E. Jhala, Arnav Kersting, Kristian Konidaris, George Lecue, Freddy McIlraith, Sheila Natarajan, Sriraam Noorian, Zeinab Poole, David Ronfard, Rémi Saffiotti, Alessandro Shaban-Nejad, Arash Srivastava, Biplav Tesauro, Gerald Uceda-Sosa, Rosario Van Den Broeck, Guy Van Otterlo, Martijn Wallace, Byron C. Weng, Paul Wiens, Jenna Zhang, Jie School of Informatics University of Edinburgh United Kingdom Department of Applied and Computational Mathematics Brazilian National Laboratory Brazil Big Data Group Kobo Inc. Brazil Department of Epidemiology and Biostatistics McGill University Canada School of Mathematical and Computer Sciences Heriot-Watt University in Edinburgh United Kingdom University of Augsburg Germany Carnegie Mellon University United States University of Toronto Canada Cognitive Systems Group University of Bremen Germany LIARA UQAC Chicoutimi Canada Information Sciences Institute University of Southern California Computer Science Department United States Center for Computational Pharmacology University of Colorado School of Medicine United States Department of Computational Media University of California Santa Cruz United States Computer Science Department Technical University of Dortmund Germany MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA United States IBM Research - Smarter Cities Technology Centre Dubline Ireland School of Informatics and Computing Indiana University United States Department of Computer Science University of Saskatchewan Canada University of British Columbia Canada INRIA University of Grenoble France Orebro University Sweden McGill Clinical and Health Informatics Group McGill University Canada IBM Research United States Cognitive Computing Department IBM Research Yorktown HeightsNY United States Computer Science Department Katholieke Universiteit Leuven Belgium Cognitive Artificial Intelligence Department Radboud University Nijmegen Netherlands University of Texas Austin United States Pierre and Marie Curie University Paris France University of Michigan United States School of Computer Engineering Nanyang Technological University Singapore

The AAAI-14 Workshop program was held Sunday and Monday, July 27-28, 2014, at the Québec City Convention Centre in Québec, Canada. The AAAI-14 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Artificial Intelligence and Robotics;Artificial Intelligence applied to Assistive Technologies and Smart Environments;Cognitive Computing for Augmented Human Intelligence;Computer Poker and Imperfect Information;Discovery Informatics;Incentives and Trust in Electronic Communities;Intelligent Cinematography and Editing;Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action, and Communication;Modern Artificial Intelligence for Health Analytics;Multiagent Interaction Without Prior Coordination;Multidisciplinary Workshop on Advances in Preference Handling;Semantic Cities - Beyond Open data to Models, Standards, and Reasoning;Sequential Decision Making with big data;Statistical Relational AI;and the World Wide Web and Public Health Intelligence. This article presents short summaries of those events. © 2015, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Decision making

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