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Author Correction: Landscape-scale benefits of protected areas for tropical biodiversity

Nature 2024年第8009期628卷 E5页

作者： Jedediah F Brodie Jayasilan Mohd-Azlan Cheng Chen Oliver R Wearn Mairin C M Deith James G C Ball Eleanor M Slade David F R P Burslem Shu Woan Teoh Peter J Williams An Nguyen Jonathan H Moore Scott J Goetz Patrick Burns Patrick Jantz Christopher R Hakkenberg Zaneta M Kaszta Sam Cushman David Coomes Olga E Helmy Glen Reynolds Jon Paul Rodríguez Walter Jetz Matthew Scott Luskin Division of Biological Sciences University of Montana Missoula MT USA. jedediah.brodie@umontana.edu. Wildlife Biology Program University of Montana Missoula MT USA. jedediah.brodie@umontana.edu. Institute of Biodiversity and Environmental Conservation Universiti Malaysia Sarawak Kota Samarahan Malaysia. jedediah.brodie@umontana.edu. Institute of Biodiversity and Environmental Conservation Universiti Malaysia Sarawak Kota Samarahan Malaysia. Department of Forest Resources Management University of British Columbia Vancouver British Columbia Canada. Biodiversity Research Centre University of British Columbia Vancouver British Columbia Canada. Fauna and Flora International-Vietnam Programme Hanoi Vietnam. Institute for the Oceans and Fisheries University of British Columbia Vancouver British Columbia Canada. Department of Plant Sciences and Conservation Research Institute University of Cambridge Cambridge UK. Asian School of the Environment Nanyang Technological University Singapore Singapore. School of Biological Sciences University of Aberdeen Aberdeen UK. Wildlife Biology Program University of Montana Missoula MT USA. Division of Biological Sciences University of Montana Missoula MT USA. Leibniz Institute for Zoo and Wildlife Research Berlin Germany. School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China. School of Environmental Sciences University of East Anglia Norwich UK. School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff AZ USA. Department of Biological Sciences Northern Arizona University Flagstaff AZ USA. Wildlife Conservation Research Unit Department of Biology University of Oxford Oxford UK. School of Forestry Northern Arizona University Flagstaff AZ USA. Aldo Leopold Wilderness Research Institute United States Department of Agriculture Forest Service Rocky Mountain Research Station Missoula MT USA. The South East Asia Rainforest Research Partn

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An interview based study of pioneering experiences in teaching and learning complex systems in higher education

arXiv

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arXiv 2018年

作者： Lizier, Joseph T. Harré, Michael S. Mitchell, Melanie DeDeo, Simon Finn, Conor Lindgren, Kristian Lizier, Amanda L. Sayama, Hiroki Centre for Complex Systems Complex Systems Research Group Faculty of Engineering and IT University of Sydney NSW Australia Department of Computer Science Portland State University PortlandOR United States Santa Fe Institute Santa FeNM United States School of Informatics and Computing Indiana University BloomingtonIN United States Department of Social and Decision Sciences Carnegie Mellon University PittsburghPA United States CSIRO Data 61 MarsfieldNSW Australia Department of Space Earth and Environment Chalmers University of Technology Göteborg Sweden School of Education University of Technology Sydney NSW Australia Center for Collective Dynamics of Complex Systems Department of Systems Science and Industrial Engineering Binghamton University State University of New York NY United States

Due to the interdisciplinary nature of complex systems as a field, students studying complex systems at University level have diverse disciplinary backgrounds. This brings challenges (e.g. wide range of computer programming skills) but also opportunities (e.g. facilitating interdisciplinary interactions and projects) for the classroom. However, there is little published regarding how these challenges and opportunities are handled in teaching and learning Complex systems as an explicit subject in higher education, and how this differs in comparison to other subject areas. We seek to explore these particular challenges and opportunities via an interview-based study of pioneering teachers and learners (conducted amongst the authors) regarding their experiences. We compare and contrast those experiences, and analyse them with respect to the educational literature. Our discussions explored: approaches to curriculum design, how theories/models/frameworks of teaching and learning informed decisions and experience, how diversity in student backgrounds was addressed, and assessment task design. We found a striking level of commonality in the issues expressed as well as the strategies to handle them, for example a significant focus on problem-based learning, and the use of major student-led creative projects for both achieving and assessing learning outcomes. Copyright © 2018, The Authors. All rights reserved.

关键词： Students

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Characterizing the analogy between hyperbolic embedding and community structure of complex networks

arXiv

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arXiv 2018年

作者： Faqeeh, Ali Osat, Saeed Radicchi, Filippo MACSI Department of Mathematics and Statistics University of Limerick Limerick Ireland Center for Complex Networks and Systems Research School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Quantum Complexity Science Initiative Skolkovo Institute of Science and Technology Skoltech Building 3 Moscow143026 Russia

We show that the community structure of a network can be used as a coarse version of its embedding in a hidden space with hyperbolic geometry. The finding emerges from a systematic analysis of several real-world and synthetic networks. We take advantage of the analogy for reinterpreting results originally obtained through network hyperbolic embedding in terms of community structure only. First, we show that the robustness of a multiplex network can be controlled by tuning the correlation between the community structures across different layers. Second, we deploy an efficient greedy protocol for network navigability that makes use of routing tables based on community structure. Copyright © 2018, The Authors. All rights reserved.

关键词： Complex networks

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A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem

A simulation-based benders' cuts generation for the joint wo...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Mengyi Zhang Andrea Matta Arianna Alfieri Giulia Pedrielli Department of Mechanical Engineering Politecnico di Milano Milan ITALY Department of Management Engineering Politecnico di Torino Turin ITALY School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA

The Discrete Event Optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. This work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. The optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.

关键词： Workstations Optimization Resource management Mathematical model Computational modeling Numerical models

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How do machine-generated questions compare to human-generated questions?

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Research and Practice in Technology Enhanced Learning 2016年第1期11卷 1-28页

作者： Zhang, Lishan VanLehn, Kurt School of Computing Informatics Decision System Engineering Arizona State University Tempe AZ United States

Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply biology instructors with questions for college students in introductory biology classes, two algorithms were developed. One generates questions from a formal representation of photosynthesis knowledge. The other collects biology questions from the web. The questions generated by these two methods were compared to questions from biology textbooks. Human students rated questions for their relevance, fluency, ambiguity, pedagogy, and depth. Questions were also rated by the authors according to the topic of the questions. Although the exact pattern of results depends on analytic assumptions, it appears that there is little difference in the pedagogical benefits of each class, but the questions generated from the knowledge base may be shallower than questions written by professionals. This suggests that all three types of questions may work equally well for helping students to learn. © 2016, The Author(s).

关键词： Atomic Predicate Biology Student Knowledge Base Question Schema Seed Pair

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An environment for sustainable research software in Germany and beyond: Current state, open challenges, and call for action

arXiv

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arXiv 2020年

作者： Anzt, Hartwig Bach, Felix Druskat, Stephan Löffler, Frank Loewe, Axel Renard, Bernhard Y. Seemann, Gunnar Struck, Alexander Achhammer, Elke Aggarwal, Piush Appel, Franziska Bader, Michael Brusch, Lutz Busse, Christian Chourdakis, Gerasimos Dabrowski, Piotr W. Ebert, Peter Flemisch, Bernd Friedl, Sven Fritzsch, Bernadette Funk, Maximilian D. Gast, Volker Goth, Florian Grad, Jean-Noël Hermann, Sibylle Hohmann, Florian Janosch, Stephan Kutra, Dominik Linxweiler, Jan Muth, Thilo Peters-Kottig, Wolfgang Rack, Fabian Raters, Fabian H.C. Rave, Stephan Reina, Guido Reißig, Malte Ropinski, Timo Schaarschmidt, Joerg Seibold, Heidi Thiele, Jan P. Uekerman, Benjamin Unger, Stefan Weeber, Rudolf Germany Innovative Computing Lab University of Tennessee KnoxvilleTN United States Department of English Studies Friedrich Schiller University Jena Germany Germany Department of Computer Science Humboldt-Universität zu Berlin Germany Heinz Nixdorf Chair for Distributed Information Systems Friedrich Schiller University Jena Germany Michael Stifel Center Jena Germany Center for Computation and Technology Louisiana State University Baton Rouge United States Germany Robert Koch Institute Berlin Germany Hasso Plattner Institute Faculty of Digital Engineering University of Potsdam Germany Institute for Experimental Cardiovascular Medicine University Heart Centre Freiburg Bad Krozingen Germany Faculty of Medicine University of Freiburg Freiburg Germany Matters of Activity. Image Space Material. Cluster of Excellence at Humboldt-Universität zu Berlin Germany Technische Universität München Germany Language Technology Lab Universität Duisburg-Essen Germany Germany Department of Informatics Technical University of Munich Germany Technische Universität Dresden Germany Deutsches Krebsforschungszentrum Heidelberg Germany Scientific Computing in Computer Science Technical University Munich Germany School of Computing Communication and Business Hochschule für Technik und Wirtschaft Berlin Germany Center for Bioinformatics Saar Saarland Informatics Campus Germany Institute for Modelling Hydraulic and Environmental Systems University of Stuttgart Germany Berlin Institute of Health Germany Scientific Computing Alfred Wegener Institute Helmholtz Center for Polar and Marine Research Bremerhaven Germany Max-Planck-Gesellschaft e.V. Institut für Theoretische Physik und Astrophysik Universität Würzburg Germany Institut für Computerphysik University of Stuttgart Germany University Library University of Stuttgart Germany Universität Bremen Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany European Molecular Biology Laboratory Heidelb

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of sustainable research software practices. In particular, we recommend strategies and measures to create an environment for sustainable research software, with the ultimate goal to ensure that software-driven research is valid, reproducible and sustainable, and that software is recognized as a first class citizen in research. This paper is the outcome of two workshops run in Germany in 2019, at deRSE19 - the first International Conference of Research Software Engineers in Germany - and a dedicated DFG-supported follow-up workshop in Berlin. Copyright © 2020, The Authors. All rights reserved.

关键词： Software design

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Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface

arXiv

引用

arXiv 2018年

作者： Raza, Haider Rathee, Dheeraj Zhou, Shang-Ming Cecotti, Hubert Prasad, Girijesh School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom School of Computing and Intelligent Systems Ulster University Magee campus Derry Londonderry United Kingdom Farr Institute of Health Informatics Research Swansea University Swansea United Kingdom Department of Computer Science California State University Fresno FresnoCA United States

The non-stationary nature of electroencephalography (EEG) signals makes an EEG-based brain-computer interface (BCI) a dynamic system, thus improving its performance is a challenging task. In addition, it is well-known that due to non-stationarity based covariate shifts, the input data distributions of EEG-based BCI systems change during inter- and intra-session transitions, which poses great difficulty for developments of online adaptive data-driven systems. Ensemble learning approaches have been used previously to tackle this challenge. However, passive scheme based implementation leads to poor efficiency while increasing high computational cost. This paper presents a novel integration of covariate shift estimation and unsupervised adaptive ensemble learning (CSE-UAEL) to tackle non-stationarity in motor-imagery (MI) related EEG classification. The proposed method first employs an exponentially weighted moving average model to detect the covariate shifts in the common spatial pattern features extracted from MI related brain responses. Then, a classifier ensemble was created and updated over time to account for changes in streaming input data distribution wherein new classifiers are added to the ensemble in accordance with estimated shifts. Furthermore, using two publicly available BCI-related EEG datasets, the proposed method was extensively compared with the state-of-the-art single-classifier based passive scheme, single-classifier based active scheme and ensemble based passive schemes. The experimental results show that the proposed active scheme based ensemble learning algorithm significantly enhances the BCI performance in MI classifications. Copyright © 2018, The Authors. All rights reserved.

关键词： Electroencephalography

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J-Measure Based Pruning for Advancing Classification Performance of Information Entropy Based Rule Generation

J-Measure Based Pruning for Advancing Classification Perform...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Han Liu Mihaela Cocea Weili Ding School of Computer Science and Informatics Cardiff University Queen’s Buildings 5 The Parade Cardiff United Kingdom School of computing University of Portsmouth Buckingham Building Lion Terrace Portsmouth United Kingdom Laboratory of Pattern Recognition and Intelligent Systems Key Laboratory of Industrial Computer Control Engineering of Heibei Provience Yanshan University Qinghuangdao China

ISBN: (纸本)9781538652152

Learning of classification rules is a popular approach of machine learning, which can be achieved through two strategies, namely divide-and-conquer and separate-and-conquer. The former is aimed at generating rules in the form of a decision tree, whereas the latter generates if-then rules directly from training data. From this point of view, the above two strategies are referred to as decision tree learning and rule learning, respectively. Both learning strategies can lead to production of complex rule based classifiers that overfit training data, which has motivated researchers to develop pruning algorithms towards reduction of overfitting. In this paper, we propose a J-measure based pruning algorithm, which is referred to as Jmean-pruning. The proposed pruning algorithm is used to advance the performance of the information entropy based rule generation method that follows the separate and conquer strategy. An experimental study is reported to show how Jmean-pruning can effectively help the above rule learning method avoid overfitting. The results show that the use of Jmean-pruning achieves to advance the performance of the rule learning method and the improved performance is very comparable or even considerably better than the one of C4.5.

关键词： decision trees Learning systems Training data Entropy Information entropy Machine learning Machine learning algorithms

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Non-negative dictionary learning with pairwise partial similarity constraint

Non-negative dictionary learning with pairwise partial simil...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xu Zhou Pak Lun Kevin Ding Baoxin Li School of Computing Informatics Decision System Engineering Arizona State University Tempe AZ USA Arizona State University Tempe AZ US

ISBN: (纸本)9781509060689

Discriminative dictionary learning has been widely used in many applications such as face retrieval / recognition and image classification, where the labels of the training data are utilized to improve the discriminative power of the learned dictionary. This paper deals with a new problem of learning a dictionary for associating pairs of images in applications such as face image retrieval. Compared with a typical supervised learning task, in this case the labeling information is very limited (e.g. only some training pairs are known to be associated). Further, associated pairs may be considered similar only after excluding certain regions (e.g. sunglasses in a face image). We formulate a dictionary learning problem under these considerations and design an algorithm to solve the problem. We also provide a proof for the convergence of the algorithm. Experiments and results suggest that the proposed method is advantageous over common baselines.

关键词： Dictionaries Face Training Machine learning Optimization Labeling Convergence

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Vacuity aware falsification for MTL request-response specifications

Vacuity aware falsification for MTL request-response specifi...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Adel Dokhanchi Shakiba Yaghoubi Bardh Hoxha Georgios Fainekos School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ U.S.A Department of Computer Science Southern Illinois University Carbondale IL U.S.A

We propose a method to improve the automated test case generation for Metric Temporal Logic (MTL) falsification for Cyber-Physical systems (CPS). In this work, we focus on request-response MTL specifications. That is, specifications that consist of at least one antecedent and a corresponding consequent. Test case generation is particularly difficult for these specifications since the consequent is only considered if the antecedent is satisfied. Therefore, we propose a method that first targets the antecedent in the specification. We show that our framework can improve upon existing falsification methods on a number of benchmark problems.

关键词： Measurement Robustness Testing Semantics Safety Gears Modeling

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