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arXiv 2021年

作者： Gajamannage, Kelum Park, Yonggi Paffenroth, Randy Jayasumana, Anura P. Department of Mathematics and Statistics Texas A&M University–Corpus Christi Corpus ChristiTX78412 United States Department of Mathematical Sciences Department of Computer Science Data Science Program Worcester Polytechnic Institute WorcesterMA01609 United States Department of Electrical and Computer Engineering Colorado State University Fort CollinsCO80525 United States

Learning dynamics of collectively moving agents such as fish or humans is an active field in research. Due to natural phenomena such as occlusion and change of illumination, the multi-object methods tracking such dynamics might lose track of the agents where that might result fragmentation in the constructed trajectories. Here, we present an extended deep autoencoder (DA) that we train only on fully observed segments of the trajectories by defining its loss function as the Hadamard product of a binary indicator matrix with the absolute difference between the outputs and the labels. The trajectories of the agents practicing collective motion is low-rank due to mutual interactions and dependencies between the agents that we utilize as the underlying pattern that our Hadamard deep autoencoder (HDA) codes during its training. The performance of our HDA is compared with that of a low-rank matrix completion scheme in the context of fragmented trajectory reconstruction. © 2021, CC BY.

关键词： Learning systems

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Theoretical background of innovation in services in small and medium-sized enterprises: literature mapping

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Journal of Innovation and Entrepreneurship 2020年第1期9卷 1-26页

作者： de Oliveira Sousa, Saymon Ricardo da Silva, Wesley Vieira da Veiga, Claudimar Pereira Zanini, Roselaine Ruviaro Statistics Department Federal University of Santa Maria – UFSM Building 13 Office 1205 C – CCNE Roraima Ave 1000 Santa Maria RS Brazil Department of General Applied Administration Federal University of Parana – UFPR Lathório Meissner Ave 632 Curitiba PR Brazil Post-Graduation Program of Production Engineering Federal University of Santa Maria UFSM Roraima Ave 1000 Santa Maria 97105-100 RS Brazil

The aim of this study was to map the innovation of services in small and medium-sized enterprises, as reported on the Web of Science and SCOPUS databases, using a structured review, involving 121 papers published between 1946 and 2019. There has been an increase in the number of studies in recent years, covering 23 countries on six continents, with the UK representing 48.78% of the studies. Patterns in the use of methods applied in research were identified, as well as a conceptual structure of the field. The main areas of science were finance, marketing, energy, and green engineering. The study makes an original contribution to the literature, highlighting the interest in the expansion of knowledge among the academic community, in addition to enabling a deeper analysis of the relation between the evaluated constructs. © 2020, The Author(s).

关键词： Innovation in services Literature mapping Small and medium-sized enterprises Systematic literature review

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Periodicity Scoring of Time Series Encodes Dynamical Behavior of the Tumor Suppressor p53 ⁎ ⁎

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IFAC-PapersOnLine 2021年第9期54卷 488-495页

作者： Caroline Moosmüller Christopher J. Tralie Mahdi Kooshkbaghi Zehor Belkhatir Maryam Pouryahya José Reyes Joseph O. Deasy Allen R. Tannenbaum Ioannis G. Kevrekidis C. Moosmüller and C. Tralie contributed equally to this work Department of Mathematics University of California San Diego La Jolla CA 92093 USA Department of Medical Physics Memorial Sloan-Kettering Cancer Center NY USA Department of Chemical and Biomolecular Engineering Johns Hopkins University Baltimore MD 21218 USA Department of Mathematics and Computer Science Ursinus College Collegeville PA USA Program in Applied and Computational Mathematics Princeton University NJ USA School of Engineering and Sustainable Development De Montfort University Leicester UK Cancer Biology and Genetics Program and Computational and Systems Biology Program Memorial Sloan-Kettering Cancer Center New York NY 10065 USA and Department of Systems Biology Harvard Medical School Boston MA 02115 USA Departments of Computer Science and Applied Mathematics & Statistics Stony Brook University NY USA

In this paper we analyze the dynamical behavior of the tumor suppressor protein p53, an essential player in the cellular stress response, which prevents a cell from dividing if severe DNA damage is present. When this response system is malfunctioning, e.g. due to mutations in p53, uncontrolled cell proliferation may lead to the development of cancer. Understanding the behavior of p53 is thus crucial to prevent its failing. It has been shown in various experiments that periodicity of the p53 signal is one of the main descriptors of its dynamics, and that its pulsing behavior (regular vs. spontaneous) indicates the level and type of cellular stress. In the present work, we introduce an algorithm to score the local periodicity of a given time series (such as the p53 signal), which we call Detrended Autocorrelation Periodicity Scoring (DAPS). It applies pitch detection (via autocorrelation) on sliding windows of the entire time series to describe the overall periodicity by a distribution of localized pitch scores. We apply DAPS to the p53 time series obtained from single cell experiments and establish a correlation between the periodicity scoring of a cell’s p53 signal and the number of cell division events. In particular, we show that high periodicity scoring of p53 is correlated to a low number of cell divisions and vice versa. We show similar results with a more computationally intensive state-of-the-art periodicity scoring algorithm based on topology known as Sw1PerS. This correlation has two major implications: It demonstrates that periodicity scoring of the p53 signal is a good descriptor for cellular stress, and it connects the high variability of p53 periodicity observed in cell populations to the variability in the number of cell division events.

关键词： Systems biology cellular systems time series modeling bioinformatics computational biology

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Machine learning based non-Newtonian fluid model with molecular fidelity

arXiv

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arXiv 2020年

作者： Lei, Huan Wu, Lei Weinan, E. Department of Computational Mathematics Science & Engineering Department of Statistics & Probability Michigan State University MI48824 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University NJ08544 United States

We introduce a machine-learning-based framework for constructing continuum non-Newtonian fluid dynamics model directly from a micro-scale description. Polymer solution is used as an example to demonstrate the essential ideas. To faithfully retain molecular fidelity, we establish a micro-macro correspondence via a set of encoders for the micro-scale polymer configurations and their macro-scale counterparts, a set of nonlinear conformation tensors. The dynamics of these conformation tensors can be derived from the micro-scale model and the relevant terms can be parametrized using machine learning. The final model, named the deep non-Newtonian model (DeePN2), takes the form of conventional non-Newtonian fluid dynamics models, with a new form of the objective tensor derivative. Numerical results demonstrate the accuracy of DeePN2. Copyright © 2020, The Authors. All rights reserved.

关键词： Viscous flow

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Integrated data envelopment analysis, multi-criteria decision making, and cluster analysis methods: Trends and perspectives

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Decision Analytics Journal 2023年 8卷

作者： de Oliveira, Maiquiel Schmidt Steffen, Vilmar de Francisco, Antonio Carlos Trojan, Flavio Academic Department of Physics Statistics and Mathematics (DAFEM) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Francisco Beltrão Paraná 85602-863 Brazil Academic Departments of Engineering (DAENG) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Francisco Beltrão 85602-863 Paraná Brazil Academic Department of Electronics (DAELE) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Ponta Grossa 84017-220 Paraná Brazil Post-Graduate Program in Production Engineering (PPGEP) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Ponta Grossa 84017-220 Paraná Brazil

Data Envelopment Analysis (DEA), Multi-criteria Decision Analysis (MCDA), and Cluster Analysis (CA) are techniques widely used to help decision-makers determine the solution to problems with multiple and often conflicting criteria. This study presents a comprehensive review of the literature on the DEA, MCDA, and CA models to identify existing and potential applications and future development trends. To this end, the Methodi Ordinatio was applied to determine which publications have the greatest impact, considering articles in three databases: Scopus, ScienceDirect, and Web of Science. We pair the techniques two by two since no results were found to integrate the three techniques. The results point to a portfolio with 490 articles, in which approximately 43.87% of the articles combine DEA and MCDA techniques for solving efficiency and productivity analysis problems. © 2023 The Author(s)

关键词： Cluster analysis Combined decision techniques Data envelopment analysis Literature review Methodi ordinatio Multi-criteria decision making

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Technology integration in mechanical engineering vocational education: engineering mathematics and engineering physics

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AIP Conference Proceedings 2023年第1期2720卷

作者： Rochmad Novian Inderanata Thomas Sukardi Putu Sudira Tuti Purwaningsih Slamet Priyanto Doctoral Program Student in Technology and Vocational Education Yogyakarta State University Yogyakarta Indonesia Mechanical Engineering Education Department Yogyakarta State University Yogyakarta Indonesia Technology and Vocational Education Graduate Schools Yogyakarta State University Yogyakarta Indonesia Statistics Department Universitas Islam Indonesia Yogyakarta Indonesia Mechanical Engineering Vocational Education Department Universitas Sarjanawiyata Tamansiswa Yogyakarta Indonesia

Technology integration has been applied in the industrial world for the production process, distribution, employment to worker training. The training in Vocational Education is expected to facilitate every learning with various technological transformations that develop. engineering Mathematics and engineering Physics are lessons that must be given to vocational students as a vocational basis. This study aims to explore the impact of using technology in vocational learning. This study uses qualitative research methods, with an emic approach. The theories used are: (1) Critical Theory from Max Horkheimer and Theodor W. Adorno regarding assumptions; (2) Technology Acceptance Model (TAM) theory regarding perceived usefulness and perceived ease of use; and (3) the concept of Ki Hadjar Dewantara’s teachings about “ngerti”, “ngroso” and “nglakoni". The results of this study are: (1) the integration of technology provides benefits to student learning activities seen from the critical theory that learning theory is not boring so that students become more active to take part in learning engineering mathematics and engineering physics; (2) the integration of technology in learning provides positive emotions for students in terms of the perceived benefits and perceived ease of use both from the software and hardware devices they have to solve problems in engineering mathematics and engineering physics; (3) technology integration benefits students’ curiosity about "ngerti", "ngroso" and "nglakoni" according to the concept of Ki Hadjar Dewantara’s teachings seen from seeing the lecturer in explaining the material, demonstrating software and hardware devices, viewing, remember and mark, and imitate implementation in everyday life.

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A systematic review of the literature on video assistant referees in soccer: Challenges and opportunities in sports analytics

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Decision Analytics Journal 2023年 7卷

作者： de Oliveira, Maiquiel Schmidt Steffen, Vilmar Trojan, Flavio Academic Department of Physics Statistics and Mathematics (DAFEM) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Francisco Beltrão Paraná 85602-863 Brazil Academic Department of Engineering (DAENG) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Francisco Beltrão Paraná 85602-863 Brazil Academic Department of Electronics (DAELE) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Ponta Grossa Paraná 84017-220 Brazil Post-graduate Program in Production Engineering (PPGEP) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Ponta Grossa Paraná 84017-220 Brazil

Refereeing in sports is about fairness. The referee's job is to balance what the player with the ball thinks is fair with what the player trying to take the ball thinks is fair. Referees are judges on those two opposite opinions. Football (soccer) has massive global appeal and fan interest. Some football championships now use Video Assistant Referees (VAR) to help the referees make correct decisions. This study reviews the literature on VAR in football using the Methodi Ordinatio. Methodi Ordinatio is a methodology used to select and rank relevant scientific papers combining the impact factor, number of citations, and year of publication. We present a case study about the distance the VAR officials cover in the main Brazilian football championship (Brazilian Serie A). This study adopts the p-medians method to analyse the impact of opening VAR operation rooms in the distance covered by the professionals travelling to officiate matches. The locations of VAR operation rooms were obtained, and applying these locations in the first ten rounds of the Brazilian Serie A season 2021 would possibly reduce about 70% of the distance covered by the VAR officials travelling compared to the total distance performed. © 2023 The Author(s)

关键词： Decision-aid technology Distance minimization Methodi ordinatio p-medians Soccer Sports analytics Video assistant referee

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VLSI Design of Tree-Based Inference for Low-Power Learning Applications

VLSI Design of Tree-Based Inference for Low-Power Learning A...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Brunno A. Abreu Mateus Grellert Sergio Bampi Graduate Program in Microelectronics (PGMICRO) INF-UFRGS Federal University of Rio Grande do Sul Porto Alegre Brazil Department of Informatics and Statistics − INE Federal University of Santa Catarina (UFSC) Florianópolis Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

The use of Machine Learning techniques in battery-powered devices has increased in recent years. Therefore, evaluating power-accuracy trade-offs of inference models has become important. This work explores decision trees architectures, analyzing the effects of model complexity and approximation in power and accuracy. By quantizing the inputs to limited widths, we increased the accuracy of the models in up to 8.7% compared to precise cases. In terms of power, the variation in model complexity was more significant than in input width, as we obtained reductions of up to 97% by decreasing the tree depth, compared to 88% when decreasing the width.

关键词： Complexity theory Hardware Integrated circuit modeling Training Analytical models Decision trees Quantization (signal)

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An integrated data envelopment analysis framework for operational efficiency assessment in Brazilian international airports

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Decision Analytics Journal 2024年 12卷

作者： de Oliveira, Maiquiel Schmidt Steffen, Vilmar Krukoski, Franklin Angelo Mezoni, Maressa Fontana Trojan, Flávio Academic Department of Physics Statistics and Mathematics (DAFEM) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Paraná Francisco Beltrão 85602-863 Brazil Post-Graduate Program in Production Engineering (PPGEP) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Paraná Ponta Grossa 84017-220 Brazil Academic Departments of Engineering (DAENG) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Paraná Francisco Beltrão 85602-863 Brazil State University of Western Parana (UNIOESTE) Rua Maringá 1200 Francisco Beltrão 85605-010 Brazil Academic Department of Electronics (DAELE) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Paraná Ponta Grossa 84017-220 Brazil

International airports play a significant role in a country's economic development. We propose an integrated framework for operational efficiency analysis using Data Envelopment Analysis, Windows Analysis, and Malmquist Index to identify inefficiencies and areas of improvement in the air transportation industry. This study analyzed 23 Brazilian international airports from 2010 to 2021, using the DEA Window Analysis (DEAWA) combined with the Index (MI). The airports were grouped geographically in southern Brazil. The integration of these methods brought an important insight to the evaluation processes, even for those previously analyzed using DEA. The analyses found that COVID-19 potently influenced the drop in the efficiency index. No airport was fully efficient over the analyzed periods. Private airports achieved an efficiency index slightly higher than public ones, but the difference of the efficiency index by public–private management type is not clear. This type of analysis provides a strategic and comparative tool, making it possible to understand better the weaknesses of the air transportation system. © 2024 The Author(s)

关键词： Airports management COVID-19 Data envelopment analysis Efficiency index Malmquist index Window analysis

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The Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging 23rd

The Constrained Network-Based Statistic: A New Level of Infe...

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23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Noble, Stephanie Scheinost, Dustin Department of Radiology and Biomedical Imaging Yale University New HavenCT United States Department of Biomedical Engineering Yale University New HavenCT United States Department of Statistics and Data Science Yale University New HavenCT United States Interdepartmental Neuroscience Program Yale University New HavenCT United States Child Study Center Yale University New HavenCT United States

ISBN: (纸本)9783030597276

Neuroimaging research aimed at dissecting the network organization of the brain is poised to flourish under major initiatives, but converging evidence suggests more accurate inferential procedures are needed to promote discovery. Inference is typically performed at the cluster level with a network-based statistic (NBS) that boosts power by leveraging known dependence within the local neighborhood. However, existing NBS methods overlook another important form of dependence—shared membership in large-scale brain networks. Here, we propose a new level of inference that pools information within predefined large-scale networks: the Constrained Network-Based Statistic (cNBS). We evaluated sensitivity and specificity of cNBS against existing standard NBS and threshold-free NBS by resampling task data from the largest openly available fMRI database: the Human Connectome Project. cNBS was most sensitive to effect sizes below medium, which accounts for the majority of ground truth effects. In contrast, threshold-free NBS was most sensitive to higher effect sizes. Ground truth maps showed grouping of effects within large-scale networks, supporting the relevance of cNBS. All methods controlled FWER as intended. In summary, cNBS is a promising new level of inference for promoting more valid inference, a critical step towards more reproducible discovery in neuroscience. © 2020, Springer Nature Switzerland AG.

关键词： statistics

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