检索结果-内蒙古大学图书馆

16th International Conference on Numerical Modeling of Space Plasma Flows, ASTRONUM 2024

作者： Singh, Talwinder Colella, Phillip Van-Straalen, Brian Bozhart, Chris Pogorelov, Nikolai V. Department of Physics & Astronomy Georgia State University AtlantaGA30303 United States Applied Numerical Algorithms Group Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Electrical Engineering and Computer Science Department University of California Berkeley BerkeleyCA94720 United States Department of Space Science The University of Alabama in Huntsville HuntsvilleAL35805 United States Center for Space Plasma and Aeronomic Research The University of Alabama in Huntsville HuntsvilleAL35805 United States

We present the HelioCubed, a high-order magnetohydrodynamic (MHD) code designed for modeling the inner heliosphere. The code is designed to achieve 4th order accuracy both in space and in time. In addition, HelioCubed can perform simulations on mapped grids, such as those based on cubed spheres, which makes it possible to overcome stability limitations caused by the geometrical singularity at the polar axis of a spherical grid, thus enabling substantially larger time steps. HelioCubed has been developed using the high-level Proto library, ensures performance portability across CPU and GPU architectures, and supports back-end implementations, e.g., CUDA, HIP, OpenMP, and MPI. The code is compatible with the HDF5 library, which facilitates seamless data handling for simulations and boundary conditions derived from semi-empirical and MHD models of the solar corona. While presenting the results of preliminary simulations, we demonstrate that our simulations are indeed performed with 4th order of accuracy. Our approach ensures that HelioCubed solves the MHD equations preserving the radial flow to machine round-off error even on cubed-sphere grids. Solar wind simulations are performed using the boundary conditions provided by the Wang-Sheeley-Arge coronal model of the ambient solar wind. It also allows us to to simulate coronal mass ejections using observation-driven flux rope models. These capabilities make HelioCubed a versatile and powerful tool to advance heliophysics research and space weather forecasting. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Mesh generation

来源：评论

学校读者我要写书评

暂无评论

Technical Debt Management: The Road Ahead for Successful software Delivery

Technical Debt Management: The Road Ahead for Successful Sof...

引用

software engineering: Future of software engineering (ICSE-FoSE), IEEE/ACM International Conference on

作者： Paris Avgeriou Ipek Ozkaya Alexander Chatzigeorgiou Marcus Ciolkowski Neil A. Ernst Ronald J. Koontz Eltjo Poort Forrest Shull Dept. of Computing Science University of Groningen Groningen The Netherlands Software Engineering institute Carnegie Mellon University Pittsburgh PA USA Dept. of Applied informatics University of Macedonia Thessaloniki Greece QAware GmbH München Germany Department of Computer Science University of Victoria Victoria Canada The Boeing Company Mesa AZ USA CGI Rotterdam The Netherlands

Technical Debt, considered by many to be the ‘silent killer’ of software projects, has undeniably become part of the everyday vocabulary of software engineers. We know it compromises the internal quality of a system, either deliberately or inadvertently. We understand Technical Debt is not all derogatory, often serving the purpose of expediency. But, it is associated with a clear risk, especially for large and complex systems with extended service life: if we do not properly manage Technical Debt, it threatens to “bankrupt” those systems. software engineers and organizations that develop software-intensive systems are facing an increasingly more dire future state of those systems if they do not start incorporating Technical Debt management into their day to day practice. But how? What have the wins and losses of the past decade of research and practice in managing Technical Debt taught us and where should we focus next? In this paper, we examine the state of the art in both industry and research communities in managing Technical Debt; we subsequently distill the gaps in industrial practice and the research shortcomings, and synthesize them to define and articulate a vision for what Technical Debt management looks like five years hence.

关键词：

来源：评论

学校读者我要写书评

暂无评论

BiLSTM with Data Augmentation using Interpolation Methods to Improve Early Detection of Parkinson Disease 15

BiLSTM with Data Augmentation using Interpolation Methods to...

引用

15th Federated Conference on computer science and Information Systems, FedCSIS 2020

作者： Abayomi-Alli, Olusola O. Damasevicius, Robertas Maskeliunas, Rytis Abayomi-Alli, Adebayo Kaunas University of Technology Department of Software Engineering Kaunas Lithuania Vytautas Magnus University Department of Applied Informatics Kaunas Lithuania Federal University of Agriculture Department of Computer Science Abeokuta Nigeria

ISBN: (纸本)9788395541674

The lack of dopamine in the human brain is the cause of Parkinson disease (PD) which is a degenerative disorder common globally to older citizens. However, late detection of this disease before the first clinical diagnosis has led to increased mortality rate. Research effort towards the early detection of PD has encountered challenges such as: small dataset size, class imbalance, overfitting, high false detection rate, model complexity, etc. This paper aims to improve early detection of PD using machine learning through data augmentation for very small datasets. We propose using Spline interpolation and Piecewise Cubic Hermite Interpolating Polynomial (Pchip) interpolation methods to generate synthetic data instances. We further investigate on reducing dimensionality of features for effective and real-time classification while considering computational complexity of implementation on real-life mobile phones. For classification we use Bidirectional LSTM (BiLSTM) deep learning network and compare the results with traditional machine learning algorithms like Support Vector Machine (SVM), Decision Tree, Logistic regression, KNN and Ensemble bagged tree. For experimental validation we use the Oxford Parkinson disease dataset with 195 data samples, which we have augmented with 571 synthetic data samples. The results for BiLSTM shows that even with a holdout of 90%, the model was still able to effectively recognize PD with an average accuracy for ten rounds experiment using 22 features as 82.86%, 97.1%, and 96.37% for original, augmented (Spline) and augmented (Pchip) datasets, respectively. Our results show that proposed data augmentation schemes have significantly (p © 2020 Polish Information Processing Society - as it is since 2011.

关键词： Interpolation

来源：评论

学校读者我要写书评

暂无评论

A Video-based Study on Perceived Intelligence, Subjective Performance and Trust under Variation of Prior Information given to Users in Autonomous Driving

A Video-based Study on Perceived Intelligence, Subjective Pe...

引用

IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO

作者： Kolja Kü hnlenz Ute Schmid Barbara Kü hnlenz Department of Electrical Engineering and Computer Science Robotics Research Lab Coburg University of Applied Sciences and Arts Coburg Germany Cognitive Systems Group University of Bamberg Bamberg Germany Academic Center for Sciences and Humanities Coburg University of Applied Sciences and Arts Coburg Germany

This paper presents results from a video-based study on the impact of prior information on the user experience dimensions perceived intelligence, subjective performance, and trust in autonomous driving. A simulated autonomous driving situation is presented to test participants, while they are given different prior information in terms of descriptions of the autonomous vehicle and its integration in a network of intelligent vehicles. Significant differences of the tested user experience dimensions are revealed underlining the importance of information provided to the potential users and towards the criticality of information regarding the introduction of intelligent technology in general.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep deterministic uncertainty for semantic segmentation

arXiv

引用

arXiv 2021年

作者： Mukhoti, Jishnu van Amersfoort, Joost Torr, Philip H.S. Gal, Yarin Oxford Applied & Theoretical Machine Learning Group Department of Computer Science University of Oxford Oxford United Kingdom Torr Vision Group Department of Engineering Science University of Oxford Oxford United Kingdom

We extend Deep Deterministic Uncertainty (DDU) (Mukhoti et al., 2021), a method for uncertainty estimation using feature space densities, to semantic segmentation. DDU enables quantifying and disentangling epistemic and aleatoric uncertainty in a single forward pass through the model. We study the similarity of feature representations of pixels at different locations for the same class and conclude that it is feasible to apply DDU location independently, which leads to a significant reduction in memory consumption compared to pixel dependent DDU. Using the DeepLab-v3+ architecture on Pascal VOC 2012, we show that DDU improves upon MC Dropout and Deep Ensembles while being significantly faster to compute. Copyright © 2021, The Authors. All rights reserved.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Chances and Challenges of Chatgpt and Similar Models for Education in M&S 23

Chances and Challenges of Chatgpt and Similar Models for Edu...

引用

Proceedings of the Winter Simulation Conference

作者： Andreas Tolk Philip Barry Margaret L. Loper Ghaith Rabadi William T. Scherer Levent Yilmaz The MITRE Corporation Modeling and Analysis Innovation Center Charlottesville USA L3Harris Corporation Mission Analysis Group Herndon USA Georgia Tech Research Institute Georgia Institute of Technology Atlanta USA University of Central Florida School of Modeling Simulation and Training Orlando USA University of Virgina Department of Systems and Information Engineering Charlottesville USA Auburn University Samuel Ginn College of Engineering Computer Science and Software Engineering Auburn USA

ISBN: (纸本)9798350369663

This position paper summarizes the inputs of a group of experts from academia and industry presenting their view on chances and challenges of using ChatGPT within Modeling and Simulation education. The experts also address the need to evaluate continuous education as well as education of faculty members to address scholastic challenges and opportunities while meeting the expectation of industry. Generally, the use of ChatGPT is encouraged, but it needs to be embedded into an updated curriculum with more emphasis on validity constraints, systems thinking, and ethics.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Industrial Productivity through AI-Driven Systematic Literature Reviews 19

Enhancing Industrial Productivity through AI-Driven Systemat...

引用

19th International Conference on Web Information Systems and Technologies, WEBIST 2023

作者： Coelho, Jaqueline Gutierri Bispo, Guilherme Dantas Vergara, Guilherme Fay Saiki, Gabriela Mayumi Serrano, André Luiz Marques Weigang, Li Neumann, Clovis Martins, Patricia Helena de Oliveira, Welber Santos Albarello, Angela Brigida Casonatto, Ricardo Accorsi Missel, Patrícia de Medeiros Junior, Roberto de Oliveira Gomes, Jefferson Rosano-Peña, Carlos da Costa, Caroline Cabral F. Latitude Decision Making Technologies Lab University of Brasilia Campus Darcy Ribeiro Brasilia Brazil Projectum Research Group for Math. Methodologies Applied to Management University of Brasilia Brasilia Brazil SENAI National Service of Industrial Learning Federal District Brazil Department of Production Engineering Faculty of Technology University of Brasília Federal District Brazil Department of Computer Science University of Brasilia Federal District Brazil Department of Economics University of Brasília Federal District Brazil UNITEC Innovation and Technology Unit National Service of Industrial Learning Federal District Brazil Department of Electrical University of Brasilia Federal District Brazil Department of Administration University of Brasilia Federal District Brazil

ISBN: (纸本)9789897586729

The advent of Artificial Intelligence (AI) has opened up new possibilities for improving productivity in various industry sectors. In this paper, we propose a novel framework aimed at optimizing systematic literature reviews (SLRs) for industrial productivity. By combining traditional keyword selection methods with AI-driven classification techniques, we streamline the review process, making it more efficient. Leveraging advanced natural language processing (NLP) approaches, we identify six key sectors for optimization, thereby reducing workload in less relevant areas and enhancing the efficiency of SLRs. This approach helps conserve valuable time and resources in scientific research. Additionally, we implemented four machine learning models for category classification, achieving an impressive accuracy rate of over 75%. The results of our analyses demonstrate a promising pathway for future automation and refinements to boost productivity in the industry. Copyright © 2023 by SCITEPRESS - science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Modelling smart energy consumption with hybrid demand management in off-grid electrical system considering techno-economic indices

Science and Technology for Energy Transition (STET)

引用

science and Technology for Energy Transition (STET) 2024年第1期79卷

作者： Rui-Ming, Fang Liao, Qiangqiang Askar, Shavan Pallathadka, Harikumar Sapaev, I.B. Baldaniya, Lalji Chahar, Mamata Saini, Suman Kapila, Ish Jewahery, Hassan Farhan, Mohsen Aued Mohmmedi, M. Information Systems Engineering Department Erbil Technical Engineering College Erbil Polytechnic University Erbil Iraq Manipur International University Manipur Imphal India Department Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Institute National Research University Tashkent Uzbekistan Scientific Researcher University of Tashkent for Applied Sciences Str. Gavhar 1 Tashkent100149 Uzbekistan Scientific Researcher Western Caspian University Baku Azerbaijan Marwadi University Research Centre Department of Pharmacy Faculty of Health Science Marwadi University Gujarat Rajkot360003 India Deparment of Chemistry NIMS Institute of Engineering & Technology NIMS University Rajasthan Jaipur India Department of Applied Sciences Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab Jhanjeri140307 India Centre for Research Imapct & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Computer Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Babylon Babylon Iraq Department of Management Al-Nisour University College Nisour Seq. Karkh Baghdad Iraq Department of Electrical Engineering Islamic Azad University Branch of Central Tehran Tehran Iran

This study proposes day-ahead power scheduling for electrical systems in off-grid mode, emphasizing consumer involvement. Bi-Demand Side Management (DSM) approaches like strategic conversion and demand shifting are proposed for consumer involvement. Multiple objectives are modelled to voltage profile improvement and reduce the operation energy cost. The non-dominated solutions of the voltage of buses and operation energy cost are generated by enhanced epsilon-constraint technique, simultaneously. The General Algebraic Modeling System (GAMS) software is proposed for solving optimization problems. A combination of decision-making methods like weight sum and fuzzy procedures are implemented for finding optimal solution non-dominated solutions. The proposed method's effectiveness is confirmed through numerical simulations carried out on several case studies that utilize the 33-bus electrical system. The findings illustrate the substantial effectiveness of demand-side participation in improving power dispatch and the optimal rate of multiple objectives. By using DSM, operation cost is reduced by 21.58% and the voltage index is improved by 13.36% than the lack of implementing DSM. © The Author(s), published by EDP sciences, 2024.

关键词： Demand response

来源：评论

学校读者我要写书评

暂无评论

Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside"

arXiv

引用

arXiv 2024年

作者： Santina, Cosimo Della Corbato, Carlos Hernandez Sisman, Burak Leiva, Luis A. Arapakis, Ioannis Vakalellis, Michalis Vanderdonckt, Jean D’Haro, LuisFernando Manzi, Guido Becchio, Cristina Elamrani, Aïda Alirezaei, Mohsen Castellano, Ginevra Dimarogonas, Dimos V. Ghosh, Arabinda Haesaert, Sofie Soudjani, Sadegh Stroeve, Sybert Verschure, Paul Bacciu, Davide Deroy, Ophelia Bahrami, Bahador Gallicchio, Claudio Hauert, Sabine Sanz, Ricardo Lanillos, Pablo Iacca, Giovanni Sigg, Stephan Gasulla, Manel Steels, Luc Sierra, Carles Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany Department of Computer Science University of Luxembourg Luxembourg 4 Telefónica I+D Spain AEGIS IT Research GmbH Germany Université catholique de Louvain Belgium Speech Technology and Machine Learning Group ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain Alien Venture Studio Alien Technology Transfer Rome Italy Hamburg Germany Institut Jean Nicod École Normale Supérieure Paris France Research Technology and Development Department Digital Industry Software Helmond Netherlands Department of Information Technology Uppsala University Uppsala Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for Software Systems Kaiserslautern Germany Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Amsterdam Netherlands Donders Centre for Neuroscience Radboud University Nijmegen Netherlands Computer Science Department University of Pisa Pisa Italy Faculty of Philosophy Philosophy of Science The Study of Religion Ludwig Maximilian University of Munich Munich Germany School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Autonomous Systems Laboratory Universidad Politécnica de Madrid Spain Madrid Spain Department of Information Engineering and Computer Science University of Trento Trento Italy Department of Information and Communications Engineering Aalto University Espoo Finland Department of Electronic Engineering Universitat Politècnica de Catalunya Barcelona Spain Studio Stelluti Brussels Belgium Barcelona Spain

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices that are connected with projects funded by the EIC Pathfinder Challenge called "Awareness Inside", a nonrecurring call for proposals within Horizon Europe that was designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems. © 2024, CC BY.

关键词： Robotics

来源：评论

学校读者我要写书评

暂无评论

Multi-Dimensional Research software Categorization

引用

Computing in science and engineering 2025年

作者： Hasselbring, Wilhelm Druskat, Stephan Bernoth, Jan Betker, Philine Felderer, Michael Ferenz, Stephan Hermann, Ben Lamprecht, Anna-Lena Linxweiler, Jan Prat, Arnau Rumpe, Bernhard Schoening-Stierand, Katrin Yang, Shinhyung Kiel University Kiel24098 Germany Berlin12489 Germany University of Potsdam Potsdam14476 Germany Helmholtz Centre for Infection Research Department for Epidemiology Brunswick Germany University of Cologne Cologne51147 Germany Carl von Ossietzky Universität Oldenburg Department of Computer Science Oldenburg26129 Germany Secure Software Engineering Group TU Dortmund Dortmund44227 Germany TU Braunschweig Braunschweig38106 Germany Braunschweig38108 Germany RWTH Aachen University Germany University of Hamburg Hub of Computing and Data Science Hamburg22761 Germany

Research software has been categorized in different contexts to serve different goals. We start with a look at what research software is, before we discuss the purpose of research software categories. We propose a multi-dimensional categorization of research software. We present a template for characterizing such categories. As selected dimensions, we present our proposed role-based, readiness-based, developer-based, and dissemination-based categories. Since our work has been inspired by various previous efforts to categorize research software, we discuss them as related works. We characterize all these categories via the previously introduced template, to enable a systematic comparison. We report on the multi-dimensional categorization of selected research software examples. © 1999-2011 IEEE.

关键词： Aerospace engineering Analytical models Data collection Data models Data visualization Monitoring Numerical models software software development management software engineering

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：