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applied Set-Valued Analysis and Optimization 2023年第2期5卷 265-283页

作者： Jiang, Xin Sun, Yifan Andersen, Martin S. Vandenberghe, Lieven Department of Industrial and Systems Engineering Lehigh University BethlehemPA18015-1582 United States Department of Computer Science Stony Brook University Stony BrookNY11794-2424 United States Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States

We present an algorithm for computing the minimum-rank positive semidefinite completion of a sparse matrix with a chordal sparsity pattern. This problem is tractable, in contrast to the minimumrank positive semidefinite completion problem for general sparsity patterns. We also present a similar algorithm for the Euclidean distance matrix completion with minimum embedding dimension. The two algorithms use efficient recursions over a clique tree associated with the chordal sparsity pattern. As an application, we use the minimum-rank completion method as a rounding technique to convert the solution of a sparse semidefinite optimization problem with non-unique solutions to an optimal solution of lower rank. In experiments with semidefinite relaxations of optimal power flow problems, the minimum-rank completion often results in solutions of lower rank than the solutions computed by interior-point solvers. ©2023 applied Set-Valued Analysis and Optimization.

关键词： Electric load flow

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Multi-Agent Economic Modeling Automation Technologies 9

Multi-Agent Economic Modeling Automation Technologies

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9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Zhukova, Aleksandra A. Pilnik, Nikolai P. Kamenev, Ivan G. Iusup-Akhunov, Batyrzhan B. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Modelling in Economic Social and Ecological Systems Vavilov st. 44 building 2 Moscow119333 Russia Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Modelling of Economic Systems Vavilov st. 44 building 2 Moscow119333 Russia Hse University Faculty of Economic Sciences Department of Applied Economics Pokrovsky Bulvar 11 Moscow109028 Russia Fsbeihe Bauman Moscow State Technical University Department of Fundamental Sciences-11 2nd Baumanskaya street 5-1 Moscow05005 Russia The Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology 9 Institutskiy per. Moscow Region Dolgoprudny141701 Russia

ISBN: (纸本)9798350311402

Complex economic models often describe the agent's decisions, i.e. choice of some controlled variables in accordance with criteria set by agents. Unlike purely statistical ones, agent-based models allow to describe processes with different modes, in which the agent's behavior changes quali-tatively when the environment (including the actions of other agents) change. The practical use of mathematical models of complex systems with a number of interacting agents is limited by complexity of their construction and possible errors when dealing with multitude of expressions. computer tools, such as the 'Ecomod' system discussed in the article, can substantially reduce the time spent on model creation and processing, and help to coordinate the work of several researchers on the model. © 2023 IEEE.

关键词： Autonomous agents

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Thermal-Aware Channel Capacity

Thermal-Aware Channel Capacity

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IEEE International Symposium on Information Theory

作者： Yeow Meng Chee Tuvi Etzion Kees A. Schouhamer Immink Tuan Thanh Nguyen Van Khu Vu Jos H. Weber Eitan Yaakobi Department of Industrial Systems Engineering and Management National University of Singapore Singapore Department of Computer Science Technion — Israel Institute of Technology Haifa Israel Turing Machines Inc. Rotterdam The Netherlands Science Mathematics and Technology Cluster Singapore University of Technology and Design Singapore Department of Applied Mathematics Delft University of Technology Delft The Netherlands

High temperatures in electronic devices have a negative effect on their performance. Various techniques have been proposed and studied to address and combat this thermal challenge. To guarantee that the peak temperature of the devices will be bounded by some maximum temperature, the transmitted signal has to satisfy some *** this motivation, we study the constrained channel that only accepts sequences that satisfy prescribed thermal constraints. The main goal in this paper is to compute the capacity of this channel. We provide the exact capacity of the channel with some certain parameters and we also present some bounds on the capacity in various ***, we consider the model that multiple wires are available to use and find out the smallest number of wires required to satisfy the thermal constraints.

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Embodied Runtime Monitoring of Learning-enabled Robot Perception Components

Embodied Runtime Monitoring of Learning-enabled Robot Percep...

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IEEE International Conference on Automation science and Engineering (CASE)

作者： Deebul Nair Sathwik Panchangam Miguel A. Olivares-Mendez Nico Hochgeschwender Institute for Artificial Intelligence and Autonomous Systems Bonn-Rhein-Sieg University of Applied Sciences Sankt Augustin Germany Space Robotics Research Group (SpaceR) Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg Department of Mathematics and Computer Science University of Bremen Germany

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Monitoring during runtime, the estimated uncertainty from learning-enabled robot perception components, is a vital tool for assuring and evaluating model correctness. By utilizing different uncertainty estimation methods, monitors exploit the perceived sensor data and predictions generated by the perception model to make informed decisions, such as in safety-critical situations. In robotics, informed decisions should be aligned with embodied information regarding space and time. We argue and show that runtime monitors of learning-enabled components can be made more robust by including the embodiment information of the robot. However, it remains challenging to build uncertainty-based runtime monitors with embodiment information using only real-world datasets, which are tedious to collect. To this end, we propose a solution that leverages simulation-based datasets to characterize expected uncertainty estimates with robot embodiment. By constructing a nominal runtime monitor model based on simulated datasets, we establish a reference for the expected uncertainty along with the embodiment information that can be subsequently used to monitor real-world deployed perception components. We demonstrate the zero-shot sim-to-real transfer of our approach on a Kinova Gen3 manipulator picking task, for which the runtime monitor reliability model was trained using simulation-based data containing embodiment information of distance from the object being selected.

关键词： Runtime Uncertainty Computational modeling Estimation Predictive models Robot sensing systems Manipulators Reliability engineering Data models Monitoring

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The Use of Covariate Adjustment in Randomized Controlled Trials: An Overview

arXiv

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arXiv 2023年

作者： Van Lancker, Kelly Bretz, Frank Dukes, Oliver Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium Novartis Pharma AG Basel Switzerland Section for Medical Statistics Center for Medical Statistics Informatics and Intelligent Systems Medical University of Vienna Vienna Austria

There has been a growing interest in covariate adjustment in the analysis of randomized controlled trials in past years. For instance, the U.S. Food and Drug Administration recently issued guidance that emphasizes the importance of distinguishing between conditional and marginal treatment effects. Although these effects coincide in linear models, this is not typically the case in other settings, and this distinction is often overlooked in clinical trial practice. Considering these developments, this paper provides a review of when and how to utilize covariate adjustment to enhance precision in randomized controlled trials. We describe the differences between conditional and marginal estimands and stress the necessity of aligning statistical analysis methods with the chosen estimand. Additionally, we highlight the potential misalignment of current practices in estimating marginal treatment effects. Instead, we advocate for the utilization of standardization, which can improve efficiency by leveraging the information contained in baseline covariates while remaining robust to model misspecification. Finally, we present practical considerations that have arisen in our respective consultations to further clarify the advantages and limitations of covariate adjustment. © 2023, CC BY.

关键词： Efficiency

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FRRI: A novel algorithm for fuzzy-rough rule induction

arXiv

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arXiv 2024年

作者： Bollaert, Henri Palangetić, Marko Cornelis, Chris Greco, Salvatore Slowiński, Roman Department of Applied Mathematics Computer Science and Statistics Ghent University Krijgslaan 281 S9 Ghent9000 Belgium Faculty of Economics University of Catania Italy Institute of Computing Science Poznań University of Technology Poznań60-956 Poland Systems Research Institute Polish Academy of Sciences Warsaw01-447 Poland

Interpretability is the next frontier in machine learning research. In the search for white box models - as opposed to black box models, like random forests or neural networks - rule induction algorithms are a logical and promising option, since the rules can easily be understood by humans. Fuzzy and rough set theory have been successfully applied to this archetype, almost always separately. As both approaches offer different ways to deal with imprecise and uncertain information, often with the use of an indiscernibility relation, it is natural to combine them. The QuickRules [20] algorithm was a first attempt at using fuzzy rough set theory for rule induction. It is based on QuickReduct, a greedy algorithm for building decision superreducts. QuickRules already showed an improvement over other rule induction methods. However, to evaluate the full potential of a fuzzy rough rule induction algorithm, one needs to start from the foundations. Accordingly, the novel rule induction algorithm, Fuzzy Rough Rule Induction (FRRI), we introduce in this paper, uses an approach that has not yet been utilised in this setting. We provide background and explain the workings of our algorithm. Furthermore, we perform a computational experiment to evaluate the performance of our algorithm and compare it to other state-of-the-art rule induction approaches. We find that our algorithm is more accurate while creating small rulesets consisting of relatively short rules. © 2024, CC BY-NC-ND.

关键词： Decision trees

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3-D Deep Learning-Based Item Classification for Belt Conveyors Targeting Packaging and Logistics 25th

3-D Deep Learning-Based Item Classification for Belt Conveyo...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Park, Ho-min Kang, Byungkon Van Messem, Arnout De Neve, Wesley Center for Biotech Data Science Ghent University Global Campus Incheon Korea Republic of Department of Computer Science The State University of New York Korea Incheon Korea Republic of IDLab Department of Electronics and Information Systems Ghent University Ghent Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium

ISBN: (纸本)9783030687984

In this study, we apply concepts taken from the fields of Artificial Intelligence (AI) and Industry 4.0 to a belt conveyor, a key tool in the packaging and logistics industries. Specifically, we present an item classification model built for belt conveyors, helping the conveyor control system to recognize items while minimizing its impact on the conveyor design and the movement of items. To that end, we followed a three-pronged approach. First, we converted a size measurement system into a 3-D shape reconstruction system by recycling a belt conveyor prototype developed in a previous study. Secondly, we transformed a scanned point cloud that varies in size, given the use of variable-length items, into a point cloud with a fixed size. Thirdly, we constructed three different end-to-end 3-D point cloud classification models, with the Dynamic Graph Convolutional Neural Network (DGCNN) model coming out on top when considering accuracy, response time, and training stability. © 2021, Springer Nature Switzerland AG.

关键词： Belt conveyors

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Rule-based expert system supporting Individual Education-and-Therapeutic Program composition in SYSABA 26

Rule-based expert system supporting Individual Education-and...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2022

作者： Kolodziejczyk, Joanna Grzegorczyk-Dluciak, Nela Kuliga, Ewa Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Polish Association of Behavioral Therapy Os. Wysokie 7 Krakow31-819 Poland

System for applied Behavioral Analysis (SYSABA) is a freeware web-based software developed in Poland that aids therapists who work with developmentally disordered children. A pioneer in Poland application is adapted to applied Behavior Analysis (ABA) methodology and is compliant with the Polish Regulation of the Ministry of Education. A part of SYSABA is a module that helps compose a compliant with Polish regulations and ABA methodology, the Individual Education-and-Therapeutic Program (pol. IPET). This development process is guided by an expert system, including specialists' knowledge of the subject. The IPET composition is demanding and time-consuming, and the decisions made by the therapist will influence the treatment results. Because there are many paths to the final curriculum, the decision-making module in SYSABA was designed to improve and standardize the process. The paper provides details of the IPETs expert module design in SYSABA. The expert knowledge of long-term supervisors was expressed in a set of regulations and constraints supplying a rule-based expert system. The unstructured expertise was translated into a logical SYSABA two-level framework. Thirty-six rules guiding skill and behavior curricula were created. The effectiveness of the expert system was confirmed by a survey after one year of SYSABA usage. © 2022 The Authors. Published by Elsevier B.V.

关键词： Expert systems

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Practical Study of Selected Multi-Criteria Methods Comparison 26

Practical Study of Selected Multi-Criteria Methods Compariso...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2022

作者： Wieckowski, Jakub Szyjewski, Zdzislaw Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Institute of Management University of Szczecin ul. Cukrowa 8 Szczecin71-004 Poland

Multi-Criteria Decision Analysis (MCDA) methods enable a comprehensive analysis of decision options to identify the most preferred values. However, the abundance of these techniques, using different transformations in the calculations, can cause a divergence of results. However, the resulting rankings should be as consistent and reliable as possible. In this paper, we used the TOPSIS, COPRAS, SPOTIS, and COMET methods to examine the consistency of their results in the practical problem of laptop evaluation. The rankings were then compared with the reference ranking. The research showed that among the methods listed, the COPRAS method's results differed the most from the others. In turn, this technique ensured a ranking in line with the reference ranking. Based on the results, it can be established that the methods used are characterized by high consistency of results. © 2022 The Authors. Published by Elsevier B.V.

关键词： Preferred numbers

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Comparative analyses of multi-criteria methods in supplier selection problem 26

Comparative analyses of multi-criteria methods in supplier s...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2022

作者： Paradowski, Bartosz Szyjewski, Zdzislaw Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Institute of Management University of Szczecin ul. Cukrowa 8 Szczecin71-004 Poland

The ever-growing interest in multi-criteria decision-making methods requires research that would compare them with each other as the decision-makers would need help choosing the appropriate method. It is important to highlight the differences between them, because using different methods may result in discrepancies in the obtained rankings. Additionally, it is worthwhile for the research to take into account the problems whose solution is extremely valuable. To this end, we present a comparison of five multi-criteria decision-making methods: TOPSIS, VIKOR, COMET, SPOTIS, and MARCOS in the supplier selection problem. The conducted research showed significant differences in the evaluation of the preferences of the alternatives and some discrepancies in the obtained rankings. © 2022 The Authors. Published by Elsevier B.V.

关键词： Decision making

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