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Machine Learning Approaches in Polymer science:Progress and Fundamental for a New

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SmartMat 2025年第1期6卷 102-142页

作者： 482.T.-S.Lin C.W.ColeyH.Mochigaseet al.“Bigsmiles:A Structurally-Based Line Notation for Describing Macromolecules"ACs Central Science 5no.9(2019):1523-1531.483.J.Wu and M.Gu“Perfecting Liquid-State Theories With Machine Intelligence"Journal of Physical Chemistry Letters 14no.47(2023):10545-10552.484.M.Rubinstein and R.H.ColbyPolymer Physics(Oxford University Press2003).485.M.E.DeagenB.Dalle-CortN.J.RebelloT.S.LinD.J.Walshand B.D.Olsen“Machine Translation Between BigSMILES Line Notation and Chemical Structure Diagrams"Macromolecules 57no.1(2023):42-53.486.S.M.McDonaldE.K.AugustineQ.LannersC.RudinL.Catherine Brinsonand M.L.Becker“Applied Machine Learning as a Driver for Polymeric Biomaterials Design"Nature Communications 14no.1(2023):4838.487.B.HuA.Linand L.C.Brinson“Tackling Structured Knowledge Extraction From Polymer Nanocomposite Literature as an NER/RE Task With seq2seq"Integrating Materials and Manufacturing Innovation 13no.3(2024):656-668.488.P.V.CoveneyE.R.Doughertyand R.R.Highfield“Big Data Need Big Theory Too"Philosophical Transactions of the Royal Society A:MathematicalPhysical and Engineering Sciences 374no.2080(2016):201601 489.M.Tang R.ZhangS.Liet al.“Towards a Supertough Thermo-plastic Polyisoprene Elastomer Based on a Biomimic Strategy"Angewandte Chemie International Edition557no.48(2018):15836-15840.490.M.Z.Naser“An Engineer's Guide to Explainable Artificial Intel-ligence and Interpretable Machine Learning:Navigating CausalityForced Goodnessand the False Perception of Inference"Automation in Construction 129(2021):103821 .491.T.K.Patra V.MeenakshisundaramJ.H.Hungand D.S.Simmons“Neural-Network-Biased Genetic Algorithms for Materials Design:Evolutionary Algorithms That LearnACS Combinatorial Science 19no.2(2017):96-107.

Machine learning(ML),material genome,and big data approaches are highly overlapped in their strategies,algorithms,and *** can target various definitions,distributions,and correlations of concerned physical parameters in given polymer systems,and have expanding applications as a new paradigm indispensable to conventional *** inherent advantages in building quantitative multivariate correlations have largely enhanced the capability of scientific understanding and discoveries,thus facilitating mechanism exploration,target prediction,high-throughput screening,optimization,and rational and inverse *** article summarizes representative progress in the recent two decades focusing on the design,preparation,application,and sustainable development of polymer materials based on the exploration of key physical parameters in the composition-process-structure-property-performance *** integration of both data-driven and physical insights through ML approaches to deepen fundamental understanding and discover novel polymer materials is categorically *** the construction and application of robust ML models,strategies and algorithms to deal with variant tasks in polymer science are still in rapid *** challenges and prospects are then *** believe that the innovation in polymer materials will thrive along the development of ML approaches,from efficient design to sustainable applications.

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A Novel Texture Generation Super Resolution Model

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Procedia Computer science 2019年 162卷 924-931页

作者： Biao Li Yong Shi Sujuan Li Bo Wang Zhiquan Qi Jiabin Liu School of Economics and Management University of Chinese Academy of Sciences Beijing 101408 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology University of Nebraska at Omaha NE 68182 USA Department of Otology the First Affiliated Hospital of Zhengzhou University No. 1 eastern Jianshe road Zhengzhou Henan 450052 China School of Information Technology and Management University of International Business and Economics Beijing 100029 China Department of Computer Science and Engineering Texas A&M University TX 77843 USA

Recently, super-resolution methods pursue visual pleasant details attract more attention in academic circle. Unlike former accurate driving models, they leverage new losses measured the difference of features extracting from a pre-trained deep learning model. Moreover, the popular GANs structure are introduced to approach better outputs. In general, these new visual feeling promoting losses are constrained by the learning ability of model and effected by the weakness of GANs. In order to address these problems, we propose a novel SR method to generating abundant details. Based on former SR methods and texture generated models, we combine new model constructure and integrated loss function to achieve our goal. The new constructure derives from the very thought that more information from the LR input leads to more accurate results. The new integrated loss try to decrease the weakness of each one by corresponding loss.. Experiments show that our model achieves higher quality generations than former methods.

关键词： Super Resolution Multi Scale Smooth Loss Visual Quality

Accumulated gradient normalization 9

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Accumulated gradient normalization

9th Asian Conference on Machine Learning, ACML 2017

作者： Hermans, Joeri R. Spanakis, Gerasimos Möckel, Rico Department of Electrical Engineering and Computer Science Liège University Belgium Department of Data Science and Knowledge Engineering Maastricht University Netherlands

This work addresses the instability in asynchronous data parallel optimization. It does so by introducing a novel distributed optimizer which is able to efficiently optimize a centralized model under communication constraints. The optimizer achieves this by pushing a normalized sequence of first-order gradients to a parameter server. This implies that the magnitude of a worker delta is smaller compared to an accumulated gradient, and provides a better direction towards a minimum compared to first-order gradients, which in turn also forces possible implicit momentum fluctuations to be more aligned since we make the assumption that all workers contribute towards a single minima. As a result, our approach mitigates the parameter staleness problem more effectively since staleness in asynchrony induces (implicit) momentum, and achieves a better convergence rate compared to other optimizers such as asynchronous easgd and dynsgd, which we show empirically. © 2017 J.R. Hermans, G. Spanakis & R. Möckel.

关键词： Optimization

NaCdSb: An Orthorhombic Zintl Phase with Exceptional Intrinsic Thermoelectric Performance

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Angewandte Chemie 2022年第3期135卷

作者： Kai Guo Yuting Zhang Song Yuan Qinghang Tang Chen Lin Pengfei Luo Jiong Yang Shusheng Pan Li-Dong Zhao Guofeng Cheng Jiye Zhang Jun Luo School of Physics and Materials Science Guangzhou University Guangzhou 510006 China Research Center for Advanced Information Materials (CAIM) Huangpu Research & Graduate School of Guangzhou University Sino-Singapore Guangzhou Knowledge City Huangpu District Guangzhou 510555 China Contribution: Conceptualization (lead) Formal analysis (equal) Writing - original draft (lead) School of Materials Science and Engineering Shanghai University 99 Shangda Road Shanghai 200444 China Contribution: Data curation (equal) Investigation (equal) Validation (lead) Contribution: Data curation (lead) Formal analysis (equal) Materials Genome Institute Shanghai University 99 Shangda Road Shanghai 200444 China Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology Wuhan University Wuhan 430072 China Contribution: Investigation (equal) Contribution: Investigation (equal) Methodology (supporting) Contribution: Investigation (equal) Writing - review & editing (supporting) School of Materials Science and Engineering Beihang University Beijing 100191 China Contribution: Methodology (equal) Writing - review & editing (equal) Analysis & Testing Center for Inorganic Materials Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai 200050 China Contribution: Formal analysis (equal) Investigation (supporting) Contribution: Data curation (equal) Writing - review & editing (supporting) Contribution: Supervision (lead) Writing - review & editing (equal)

Many Zintl phases are promising thermoelectric materials owning to their features like narrow band gaps, multiband behaviors, ideal charge transport tunnels, and loosely bound cations. Herein we show a new Zintl phase NaCdSb with exceptional intrinsic thermoelectric performance. Pristine NaCdSb exhibits semiconductor behaviors with an experimental hole concentration of 2.9×10 18 cm −3 and a calculated band gap of 0.5 eV. As the temperature increases, the hole concentration rises gradually and approaches its optimal one, leading to a high power factor of 11.56 μW cm −1 K −2 at 673 K. The ultralow thermal conductivity is derived from the small phonon group velocity and short phonon lifetime, ascribed to the structural anharmonicity of Cd−Sb bonds. As a consequence, a maximum zT of 1.3 at 673 K has been achieved without any doping optimization or structural modification, demonstrating that NaCdSb is a remarkable thermoelectric compound with great potential for performance improvement.

关键词： Electron-Crystal NaCdSb Phonon-Glass Thermoelectric Properties Zintl Phase

What does twitter tell us about tourists’ mobility behavior? A case study on tourists in the Netherlands and Belgium 21

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What does twitter tell us about tourists’ mobility behavior...

21st Pacific Asia Conference on Information Systems: Societal Transformation Through IS/IT, PACIS 2017

作者： Habib, Mena B. Krol, Nynke C. Department of Data Science and Knowledge Engineering Maastricht University Netherlands Statistics Netherlands1 Netherlands

Social media has made a big impact on the tourism industry. Tourists are increasingly sharing their personal experiences of a particular touristic site scene using social media. Studying tourists’ movement behavior should support the tourism industry with more statistics and information regarding tourism demand. It would also provide policy makers with another data source on tourists and their movements. In this paper, we propose a set of heuristics to identify tourists on Twitter. We also utilized both textual contents and geolocation information of Tweets posted by tourists visiting The Netherlands and Belgium to provide a near real scenario for the tourists’ travel route made during their stay in The Netherlands and Belgium. Finally, we induce and visualize some useful statistics regarding the tourists’ visiting behavior in The Netherlands and Belgium. © PACIS 2017.

关键词： Social networking (online)

Fully-convolutional intensive feature flow neural network for text recognition

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arXiv 2019年

作者： Zhang, Zhao Tang, Zemin Zhang, Zheng Wang, Yang Qin, Jie Wang, Meng School of Computer Science and Technology Soochow University China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer and Information Hefei University of Technology Hefei China Bio-Computing Research Center Harbin Institute of Technology Shenzhen518055 China Inception Institute of Artificial Intelligence Abu Dhabi United Arab Emirates

The Deep Convolutional Neural Networks (CNNs) have obtained a great success for pattern recognition, such as recognizing the texts in images. But existing CNNs based frameworks still have several drawbacks: 1) the traditaional pooling operation may lose important feature information and is unlearnable;2) the traditional convolution operation optimizes slowly and the hierarchical features from different layers are not fully utilized. In this work, we address these problems by developing a novel deep network model called Fully-Convolutional Intensive Feature Flow Neural Network (IntensiveNet). Specifically, we design a further dense block called intensive block to extract the feature information, where the original inputs and two dense blocks are connected tightly. To encode data appropriately, we present the concepts of dense fusion block and further dense fusion operations for our new intensive block. By adding short connections to different layers, the feature flow and coupling between layers are enhanced. We also replace the traditional convolution by depthwise separable convolution to make the operation efficient. To prevent important feature information being lost to a certain extent, we use a convolution operation with stride 2 to replace the original pooling operation in the customary transition layers. The recognition results on large-scale Chinese string and MNIST datasets show that our IntensiveNet can deliver enhanced recognition results, compared with other related deep models. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

s-LWSR: Super lightweight super-resolution network

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arXiv 2019年

作者： Li, Biao Liu, Jiabin Wang, Bo Qi, Zhiquan Shi, Yong School of Economics and Management University of Chinese Academy of Sciences Beijing101408 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China School of Information Technology and Management University of International Business and Economics Beijing100029 China Department of Computer Science and Engineering Texas A&M University College StationTX77843 United States College of Information Science and Technology University of Nebraska OmahaNE68182 United States

Deep learning (DL) architectures for super-resolution (SR) normally contain tremendous parameters, which has been regarded as the crucial advantage for obtaining satisfying performance. However, with the widespread use of mobile phones for taking and retouching photos, this character greatly hampers the deployment of DL-SR models on the mobile devices. To address this problem, in this paper, we propose a super lightweight SR network: s-LWSR. There are mainly three contributions in our work. Firstly, in order to efficiently abstract features from the low resolution image, we build an information pool to mix multi-level information from the first half part of the pipeline. Accordingly, the information pool feeds the second half part with the combination of hierarchical features from the previous layers. Secondly, we employ a compression module to further decrease the size of parameters. Intensive analysis confirms its capacity of trade-off between model complexity and accuracy. Thirdly, by revealing the specific role of activation in deep models, we remove several activation layers in our SR model to retain more information for performance improvement. Extensive experiments show that our s-LWSR, with limited parameters and operations, can achieve similar performance to other cumbersome DL-SR methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Chemical activation

Advances in Machine Learning for the Behavioral sciences

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arXiv 2019年

作者： Kliegr, Tomáš Bahník, Štěpán Fürnkranz, Johannes Department of Information and Knowledge Engineering Faculty of Informatics and Statistics University of Economics Prague Czech Republic Department of Management Faculty of Business Administration University of Economics Prague Czech Republic Computational Data Analytics Group Department of Computer Science Johannes Kepler Universität Linz Altenbergerstraße 66B Linz4040 Austria

The areas of machine learning and knowledge discovery in databases have considerably matured in recent years. In this article, we briefly review recent developments as well as classical algorithms that stood the test of time. Our goal is to provide a general introduction into different tasks such as learning from tabular data, behavioral data, or textual data, with a particular focus on actual and potential applications in behavioral sciences. The supplemental appendix to the article also provides practical guidance for using the methods by pointing the reader to proven software implementations. The focus is on R, but we also cover some libraries in other programming languages as well as systems with easy-to-use graphical interfaces. Copyright © 2019, The Authors. All rights reserved.

关键词： data mining

An efficient approach for geo-multimedia cross-modal retrieval

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arXiv 2018年

作者： Zhu, Lei Long, Jun Zhang, Chengyuan Chen, Ruipeng Yuan, Xinpan Yang, Zhan School of Information Science and Engineering Central South University China Big Data and Knowledge Engineering Institute Central South University China School of Computer Hunan University of Technology China

Due to the rapid development of mobile Internet techniques, cloud computation and popularity of online social networking and location-based services, massive amount of multimedia data with geographical information is generated and uploaded to the Internet. In this paper, we propose a novel type of cross-modal multimedia retrieval called geo-multimedia cross-modal retrieval which aims to search out a set of geo-multimedia objects based on geographical distance proximity and semantic similarity between different modalities. Previous studies for cross-modal retrieval and spatial keyword search cannot address this problem effectively because they do not consider multimedia data with geo-tags and do not focus on this type of query. In order to address this problem efficiently, we present the deffinition of kNN geo-multimedia cross-modal query at the first time and introduce relevant conceptions such as cross-modal semantic representation space. To bridge the semantic gap between different modalities, we propose a method named cross-modal semantic matching which contains two important component, i.e., CorrProj and LogsTran, which aims to construct a common semantic representation space for cross-modal semantic similarity measurement. Besides, we designed a framework based on deep learning techniques to implement common semantic representation space construction. In addition, a novel hybrid indexing structure named GMR-Tree combining geo-multimedia data and R-Tree is presented and a efficient kNN search algorithm called kGMCMS is designed. Comprehensive experimental evaluation on real and synthetic dataset clearly demonstrates that our solution outperforms the-stateof-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Location based services