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Ensemble Filter Scenario Based Control on Linearized Power System Manifold

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Ensemble Filter Scenario Based Control on Linearized Power S...

International Conference on System Reliability and science (ICSRS)

作者： Bahri Uzunoğlu Department of Electrical Engineering Computational and data-enabled science and engineering in energy systems Uppsala University Sweden Department of Mathematics Florida State University USA

ISBN: (数字)9798350354508

ISBN: (纸本)9798350354515

This article integrates the widely recognised ensemble filters that are employed for power system state estimation and their ensemble scenarios to controls for power systems linearised on manifolds. The approach has the effect of directly providing constraint scenarios for any optimal real-time fast power system management for any ensemble-based state estimator used in the power system, thereby reducing the computational task for both radial and meshed power systems and addressing the computational needs of stochastic external state parameter that is not controlled by the grid operator. New and unparalleled obstacles have surfaced in the recent past for power systems. Tighter guidelines for grid reliability and service quality, the growing spread of electric mobility that has given rise to a new class of intermittent loads with distinct spatiotemporal patterns, and the growing use of distributed microgenerators from renewable power sources-which are frequently characterised by unpredictable behavior-are some of these challenges. For proof of concept, the method is shown on a simple example.

关键词： Manifolds Renewable energy sources Uncertainty Decision making Transforms Power systems Spatiotemporal phenomena Kalman filters Reliability State estimation

Droplet formation simulation using mixed finite elements

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arXiv 2023年

作者： Nathawani, Darsh K. Knepley, Matthew G. Computational and Data-Enabled Science and Engineering University at Buffalo BuffaloNY14260 United States Department of Computer Science and Engineering University at Buffalo BuffaloNY14260 United States

Droplet formation happens in finite time due to the surface tension force. The linear stability analysis is useful to estimate droplet size but fails to approximate droplet shape. This is due to a highly non-linear flow description near the point where the first pinch-off happens. A one-dimensional axisymmetric mathematical model was first developed by Eggers and Dupont[2] using asymptotic analysis. This asymptotic approach to the Navier-Stokes equations leads to a universal scaling explaining the self-similar nature of the solution. Numerical models for the one-dimensional model were developed using the finite difference[2] and finite element method[3]. The focus of this study is to provide a robust computational model for one-dimensional axisymmetric droplet formation using the Portable, Extensible Toolkit for Scientific Computation (PETSc). The code is verified using the Method of Manufactured Solutions (MMS) and validated using previous experimental studies done by Zhang and Basaran[4]. The present model is used for simulating pendant drops of water, glycerol, and paraffin wax, with an aspiration of extending the application to simulate more complex pinch-off phenomena. © 2023, CC BY.

关键词： Linear stability analysis

Mesoscale Wind Farm Placement via Linear Optimization Constrained by Power System and Techno-economics

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Journal of Modern Power Systems and Clean Energy 2021年第2期9卷 356-366页

作者： Ali Erduman Bahri Uzunoglu Bedri Kekezoglu Ali Durusu the Electrical Engineering Department Hakkari UniversityHakkari30000 Turkey Department of Engineering Sciences Department of Electrical EngineeringComputational and Data-enabled Science and Engineering in Energy SystemsUppsala University75121 UppsalaSweden Department of Mathematics Florida State UniversityTallahasseeFL 32310USA the Electrical Engineering Department Yildiz Technical UniversityIstanbul34220 Turkey

The objective of this study is to develop a wind farm placement and investment methodology based on a linear optimization *** problem has a major significance for the investment success for the projects of renewable energy such as wind *** this study,a mesoscale approach is adopted whereby the wind farm location is investigated in comparison with a microscale approach where the location of each individual turbine is *** study focuses on the placement of a wind farm by economical optimization constrained by the power system,wind resources,and *** optimization is introduced in this context at the power system which is constrained by wind farm planning.

关键词： Generation expansion grid integration mesoscale wind farm linear optimization wind power

Emergency Care Patient Prediction using Electronic Health Records (EHR) data: An End-to-End Machine Learning Pipeline

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Emergency Care Patient Prediction using Electronic Health Re...

International Conference on Future Internet of Things and Cloud (FiCloud)

作者： Maruful Abedin Sumon Tor A. Kwemebe Venkata K. Melapu Md Mohiuddin Hasan Computational Data-Enabled Science and Engineering Jackson State University Jackson USA Department of Mathematics and Computer Science Jackson State University Jackson USA Computer Science and Engineering Jackson State University Jackson USA

Using electronic health records (EHR) data for predicting the condition of patients who are in need of emergency care is a promising application of machine learning. With the help of machine learning, complex problems of identification of patterns can be solved with ease and accuracy when proper machine learning model is implemented. This paper uses EHR data to build an end-to-end machine learning pipeline for predicting the outcome of emergency care patients. As a machine learning process, the pipeline includes data preprocessing, feature engineering, model selection, data set training and testing, evaluation, and deployment. By using EHR data in this pipeline, the model has been trained and tested on a large dataset of many patients information with different types of machine learning algorithms to improve and get the best prediction accuracy. This pipeline can aid in managing primary care patients efficiently and effectively with the implementation of best suitable machine learning algorithm at the time of urgency. By implementing the model on the EHR dataset, an accuracy of more than $75 \%$ is obtained which indicates the efficiency of the machine learning process in the process of identifying patients who need the emergency care more than the general patients when taken to the primary care or emergency.

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A Comparison of Global Sensitivity Methods for Power Systems

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A Comparison of Global Sensitivity Methods for Power Systems

International Conference on System Reliability and science (ICSRS)

作者： Ruilong Yue Hui Duan Giray Ökten Bahri Uzunoğlu Department of Mathematics Florida State University USA Department of Electrical Engineering Computational and Data-Enabled Science and Engineering in Energy Systems Uppsala University Sweden

The sensitivity of power system operations uncertainties that originate from distributed renewable generation, natural disasters like hurricanes, and changing loads such as vehicle charging needs careful engineering for reliable, resilient and robust power systems. The power system is a global sensitivity problem since each input uncertainty varies the output and all the variables simultaneously that have higher order interactions between inputs, unlike local sensitivity. The article assesses and compares the global sensitivity methods of Sobol’ sensitivity indices, the activity scores of the active subspace method, and Shapley values, to assess the importance of input parameters in the IEEE 14-bus modified test system. The limitations and advantages of each approach are illustrated to reduce the complexity of the model by performing uncertainty quantification for the output by global sensitivity indices in the IEEE 14-bus modified test system.

关键词： Renewable energy sources Sensitivity Uncertainty Wind power generation Reliability engineering Hurricanes Safety

Fixation probability in evolutionary dynamics on switching temporal networks

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arXiv 2023年

作者： Bhaumik, Jnanajyoti Masuda, Naoki Department of Mathematics State University of New York BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States

Population structure has been known to substantially affect evolutionary dynamics. Networks that promote the spreading of fitter mutants are called amplifiers of selection, and those that suppress the spreading of fitter mutants are called suppressors of selection. Research in the past two decades has found various families of amplifiers while suppressors still remain somewhat elusive. It has also been discovered that most networks are amplifiers of selection under the birth-death updating combined with uniform initialization, which is a standard condition assumed widely in the literature. In the present study, we extend the birth-death processes to temporal (i.e., time-varying) networks. For the sake of tractability, we restrict ourselves to switching temporal networks, in which the network structure deterministically alternates between two static networks at constant time intervals or stochastically in a Markovian manner. We show that, in a majority of cases, switching networks are less amplifying than both of the two static networks constituting the switching networks. Furthermore, most small switching networks, i.e., networks on six nodes or less, are suppressors, which contrasts to the case of static networks. © 2023, CC BY.

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To Trust or Not to Trust: Evolutionary Dynamics of an Asymmetric N-player Trust Game

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arXiv 2023年

作者： Soo Lim, Ik. Masuda, Naoki School of Computing and Mathematical Sciences University of Greenwich LondonSE10 9LS United Kingdom Department of Mathematics and Computational and Data-Enabled Science and Engineering Program State University of New York Buffalo United States

Trusting others and reciprocating the received trust with trustworthy actions are fundaments of economic and social interactions. The trust game (TG) is widely used for studying trust and trustworthiness and entails a sequential interaction between two players, an investor and a trustee. It requires at least two strategies or options for an investor (e.g. to trust versus not to trust a trustee). According to the evolutionary game theory, the antisocial strategies (e.g. not to trust) evolve such that the investor and trustee end up with lower payoffs than those that they would get with the prosocial strategies (e.g. to trust). A generalisation of the TG to a multiplayer (i.e. more than two players) TG was recently proposed. However, its outcomes hinge upon two assumptions that various real situations may substantially deviate from: (i) investors are forced to trust trustees and (ii) investors can turn into trustees by imitation and vice versa. We propose an asymmetric multiplayer TG that allows investors not to trust and prohibits the imitation between players of different roles;instead, investors learn from other investors and the same for trustees. We show that the evolutionary game dynamics of the proposed TG qualitatively depends on the nonlinearity of the payoff function and the amount of incentives collected from and distributed to players through an institution. We also show that incentives given to trustees can be useful and sufficient to cost-effectively promote trust and trustworthiness among self-interested players. © 2023, CC BY.

关键词： Dynamics

Temporal Motifs for Financial Networks: A Study on Mercari, JPMC, and Venmo Platforms

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arXiv 2023年

作者： Liu, Penghang Acharyya, Rupam Tillman, Robert E. Kimura, Shunya Masuda, Naoki Sarıyüce, Ahmet Erdem Department of Computer Science and Engineering University at Buffalo United States Amazon Web Services United States Optum Labs United States Mercari Inc. Japan Department of Mathematics University at Buffalo United States Computational and Data-Enabled Science and Engineering Program University at Buffalo United States

Understanding the dynamics of financial transactions among people is critically important for various applications such as fraud detection. One important aspect of financial transaction networks is temporality. The order and repetition of transactions can offer new insights when considered within the graph structure. Temporal motifs, defined as a set of nodes that interact with each other in a short time period, are a promising tool in this context. In this work, we study three unique temporal financial networks: transactions in Mercari, an online marketplace, payments in a synthetic network generated by J.P. Morgan Chase, and payments and friendships among Venmo users. We consider the fraud detection problem on the Mercari and J.P. Morgan Chase networks, for which the ground truth is available. We show that temporal motifs offer superior performance than a previous method that considers simple graph features. For the Venmo network, we investigate the interplay between financial and social relations on three tasks: friendship prediction, vendor identification, and analysis of temporal cycles. For friendship prediction, temporal motifs yield better results than general heuristics, such as Jaccard and Adamic-Adar measures. We are also able to identify vendors with high accuracy and observe interesting patterns in rare motifs, like temporal cycles. We believe that the analysis, datasets, and lessons from this work will be beneficial for future research on financial transaction networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Finance

Social network analysis of manga: similarities to real-world social networks and trends over decades

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arXiv 2023年

作者： Sugishita, Kashin Masuda, Naoki Department of Transdisciplinary Science and Engineering Tokyo Institute of Technology Tokyo152-8550 Japan Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Center for Computational Social Science Kobe University Kobe657-8501 Japan

Manga, Japanese comics, has been popular on a global scale. Social networks among characters, which are often called character networks, may be a significant contributor to their popularity. We collected data from 162 popular manga that span over 70 years and analyzed their character networks. First, we found that many of static and temporal properties of the character networks are similar to those of real human social networks. Second, the character networks of most manga are protagonist-centered such that a single protagonist interacts with the majority of other characters. Third, the character networks for manga mainly targeting boys have shifted to denser and less protagonist-centered networks and with fewer characters over decades. Manga mainly targeting girls showed the opposite trend except for the downward trend in the number of characters. The present study, which relies on manga data sampled on an unprecedented scale, paves the way for further population studies of character networks and other aspects of comics. Copyright © 2023, The Authors. All rights reserved.

关键词： Population statistics