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作者： Nishiyama, Daiki Fukuchi, Kazuto Akimoto, Youhei Sakuma, Jun Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba-shi305-8577 Japan RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan Department of Computer Science Faculty of Engineering Information and Systems University of Tsukuba Tsukuba-shi305-8577 Japan

In real world applications of multiclass classification models, misclassification in an important class (e.g., stop sign) can be significantly more harmful than in other classes (e.g., no parking). Thus, it is crucial to improve the recall of an important class while maintaining overall accuracy. For this problem, we found that improving the separation of important classes relative to other classes in the feature space is effective. Existing methods that give a class-sensitive penalty for cross-entropy loss do not improve the separation. Moreover, the methods designed to improve separations between all classes are unsuitable for our purpose because they do not consider the important classes. To achieve the separation, we propose a loss function that explicitly gives loss for the feature space, called class-sensitive additive angular margin (CAMRI) loss. CAMRI loss is expected to reduce the variance of an important class due to the addition of a penalty to the angle between the important class features and the corresponding weight vectors in the feature space. In addition, concentrating the penalty on only the important class hardly sacrifices separating the other classes. Experiments on CIFAR-10, GTSRB, and AwA2 showed that CAMRI loss could improve the recall of a specific class without sacrificing accuracy. In particular, compared with GTSRB's second-worst class recall when trained with cross-entropy loss, CAMRI loss improved recall by 9%. © 2023 The Institute of Electronics, Information and Communication Engineers.

关键词： Deep learning

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Optimized feature selection for initial launch in dynamic software product lines 20

Optimized feature selection for initial launch in dynamic so...

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20th International Conference on Enterprise Information systems, ICEIS 2018

作者： De Sousa Santos, Ismayle Junior, Evilasio Costa De Castro Andrade, Rossana Maria Dos Santos Neto, Pedro De Alcântara Rocha, Leonardo Sampaio Werner, Claudia Maria Lima De Souza, Jerffeson Texeira Department of Computer Science Federal University of Ceará Fortaleza Brazil Department of Computer Science Federal University of Piauí Teresina Brazil Science and Tecnology Center State University of Ceará Fortaleza Brazil Computer Systems Engineering Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9789897582981

A Dynamic Software Product Line (DSPL) allows the generation of products that can adapt dynamically according to changes in requirements or environment at runtime. This runtime adaptation is often made by the activation and deactivation of features, introducing a cost (e.g., an overhead regarding resource consumption). To reduce this cost, a solution is the partial product configuration at the static binding time. Thus, in DSPLs, one challenge is the feature selection to define which features should be bound permanently before the initial launch and which features should be bound at runtime. In this paper, we address this challenge presenting a graph model formulation to the feature selection problem for the initial launch in DSPLs that considers both static and dynamic binding. This model allows the application of efficient optimization algorithms to solve the problem. We also present a proof of concept showing that the model can be used to generate optimized solutions to the feature selection problem for initial launch in DSPLs. © 2018 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Multiobjective optimization

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IoE Knowledge Flow Model in Smart Cities

IoE Knowledge Flow Model in Smart Cities

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2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Paes, Vitor C. Pessoa, Clinton H. M. Farias Da Costa, Viviane C. Oliveira, Luiz F. S. De Souza, Jano M. Federal University of Rio de Janeiro Systems Engineering and Computer Science Program Rio de Janeiro Brazil Federal Institute of Rio de Janeiro Niterói Brazil

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

With a growing demand for new technologies, concepts such as the Internet of Everything (IoE) - in which smart sensors (humans and machines) connect, communicate, and share information from the surrounding environment - are gaining notoriety. Thus, this study focuses on developing a knowledge flow model in the IoE scenario for Smart Cities, including how knowledge is disseminated in these intelligent environments in human-to-machine interactions. The study considers a knowledge-based taxonomy defined for IoE environments and supports the full realization of IoE applications through a knowledge management strategy. The proposed IoE Knowledge Flow Model contributes to identification of knowledge flows related to IoE architecture layers in smart city applications. © 2022 IEEE.

关键词： Internet of Everything

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Combining function points software estimation model with ADISSA methodology for systems analysis and design 7

Combining function points software estimation model with ADI...

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7th Israeli Conference on computer systems and Software engineering, ICCSSE 1996

作者： Shoval, Peretz Feldman, Ofer Information Systems Program Dept.of Industrial Engineering and Management Israel Dept.of Mathematics and Computer Science Ben-Gurion University of Negev Beer-Sheva84105 Israel

ISBN: (纸本)0818675365

The study proposes a combination of the function points model for software estimation with the ADISSA methodology for systems analysis and design. This combined approach, which is supported by a software tool, enables one to estimate various software metrics, such as size, effort, and duration, in the early stages of systems development, by basing them on the products of a thorough system analysis and design process. © 1996 IEEE.

关键词： Project management

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Generalized evidence pre-propagated importance sampling for hybrid bayesian networks

Generalized evidence pre-propagated importance sampling for ...

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AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference

作者： Yuan, Changhe Druzdzel, Marek J. Department of Computer Science and Engineering Mississippi State University Mississippi State MS 39762 Intelligent Systems Program School of Information Sciences University of Pittsburgh Pittsburgh PA 15260

ISBN: (纸本)1577353234

In this paper, we first provide a new theoretical understanding of the Evidence Pre-propagated Importance Sampling algorithm (EPIS-BN) (Yuan & Druzdzel 2003;2006b) and show that its importance function minimizes the KL-divergence between the function itself and the exact posterior probability distribution in Polytrees. We then generalize the method to deal with inference in general hybrid Bayesian networks consisting of deterministic equations and arbitrary probability distributions. Using a novel technique called soft arc reversal, the new algorithm can also handle evidential reasoning with observed deterministic variables. Copyright © 2007, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Bayesian networks

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High Resolution of City-Level Climate Simulation by GPU with Multi-physical Phenomena 18th

High Resolution of City-Level Climate Simulation by GPU with...

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18th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2021

作者： Watanabe, Koei Kikuchi, Kohei Boku, Taisuke Sato, Takuto Kusaka, Hiroyuki Master’s Program in Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukubashi Japan Center for Computational Sciences University of Tsukuba Tsukubashi Tennodi Japan

ISBN: (纸本)9783030935702

In this paper, we describe the Graphics Processing Unit (GPU) implementation of our City-LES code on detailed large eddy simulations, including the multi-physical phenomena on fluid dynamics, heat absorption and reflection by surface and building materials, cloud effects, and even sunlight effect. Because a detailed simulation involving these phenomena is required for analyses at the street level and several meters of resolution, the computation amount is enormous, and ordinary CPU computation cannot provide sufficient performance. Therefore, we implemented the entire code on GPU clusters with large-scale computing. We applied OpenACC coding to incrementally implement relatively easy programming and eliminate data transfers between the CPU and GPU memories. Based on this research, we determined that the elimination of data transfers is effective, even in the case where a part of the code execution on the GPU is slower than the CPU, owing to the absence of spatial parallelism. The objective of this study is to perform a complete climate simulation on a few square-kilometers field around the Tokyo Station, considering the finest resolution of the original highlighted area of the Marathon race in the Olympic Games Tokyo 2020. We successfully transferred the entire code to the GPU to provide approximately eight times the performance of CPU-only computation on multi-GPU per node with a large scale cluster. © 2022, IFIP International Federation for Information Processing.

关键词： Graphics processing unit

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Leverage from Blockchain in Commodity Exchange: Asset-Backed Token with Ethereum Blockchain Network and Smart Contract 4th

Leverage from Blockchain in Commodity Exchange: Asset-Backed...

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4th International Conference on Smart Trends for Computing and Communications, SmartCom 2020

作者： Richard Heryadi, Yaya Lukas Trisetyarso, Agung Information Systems Department School of Information Systems Bina Nusantara University Jakarta11840 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara Univesity Jakarta11840 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (纸本)9789811552236

Ethereum is one of the most popular blockchain platforms with a high number of adoption in the blockchain world today. Ethereum token (ERC-20) can tokenize any real-world object while it is also possible to exchange the token across the network participants. This utility from the token drives many blockchain enthusiasts to create decentralized applications. ERC-20 token could be used to collect project funds, decision voting, or even can be used to provide investment platforms for people that want to hedge the volatility of the currency with buying an asset that is back to back with the crypto-token. This research shows the main characteristics of asset-backed token and its implementation on a complete end-to-end "digitalization assets system" (assets buy and assets redemption). The result shows that asset-backed token needs support from government and other legalizing parties to verify the legitimacy of the asset that backing the token itself. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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The influence of human capabilities in effort estimation of business processes modeling projects

The influence of human capabilities in effort estimation of ...

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5th International Conference on Research and Practical Issues of Enterprise Information systems, CONFENIS 2011

作者： Dutra, José Roberto De Barros, Márcio O. Santoro, Flávia Maria Magdaleno, Andréa M. Cappelli, Claudia Nunes, Vanessa Klussman, Felipe Postgraduate Information Systems Program UNIRIO Brazil NP2Tec Research and Practice Group in Information Technology UNIRIO Rio de Janeiro RJ Brazil COPPE UFRJ Systems Engineering and Computer Science Program Rio de Janeiro RJ Brazil

ISBN: (纸本)9780415631310

Business processes modeling projects are increasingly widespread in organizations, which usually invest much in hiring expert consultants to do such job. These consultants come from various organizations, and have different experiences on how to perform the same activity. This paper analyzes how human-related capabilities influence the effort required to conduct a business process modeling project and discusses the results obtained from about 50 projects executed in a large Brazilian company. © 2012 Taylor & Francis Group, London.

关键词： systems engineering

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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

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Applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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Physics-informed neural networks for modeling water flows in a river channel

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第3期5卷 1001-1015页

作者： Nazari, Luis Fernando Camponogara, Eduardo Seman, Laio Oriel Department of Mathematics Federal Institute of Education Science and Technology Catarinense Rio do Sul89160-202 Brazil Department of Automation and Systems Engineering Federal University of Santa Catarina Florianopolis88040-900 Brazil Program in Applied Computer Science Universidade Do Vale Do Itajai Itajai88302-901 Brazil

The impacts incurred by floods regularly affect the planets population, inflicting social and economic problems. Optimal control strategies based on reservoir management may aid in controlling floods and mitigating the resulting damage. To this end, an accurate dynamic representation of water systems is needed. In practice, flood control strategies rely on hydrological forecasting models obtained fromconceptual or data-drivenmethods. Encouraged by recent works, this research proposes a novel surrogate model for water flow in a river channel based on physics-informed neural networks (PINNs). This approach achieved promising results regarding the assimilation of real-data measurements and the parameter identification of differential equations that govern the underlying dynamics. This article investigates PINN performance in a simulated environment built directly from a configuration of the Saint-Venant equations. The objective is to create a suitable model with high prediction accuracy and scientifically consistent behavior for use in real-Time applications. The experiments revealed promising results for hydrological modeling and presented alternatives to solve the main challenges found in conventional methods while assisting in synthesizing real-world representations. Impact Statement-The research seeks to contribute to the hydrological modeling area with a surrogate model based on physicsinformed neural networks (PINNs) to water flow in a watershed. In practice, thesemodels use conceptual or *** models to reach the precision provided by themethodology use large numbers of physical parameters. These parameters can demand deep knowledge about the environment and are possibly hard to identify in a complex basin. On the other hand, while data-driven methods do not require such knowledge about the dynamic system, they depend on a reliable and useful database to guarantee the accuracy of system *** introduce PINNs as a viable solution for

关键词： Floods

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