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Related papers: A Basic Model of KBS Software

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Component selection is considered one of hard tasks in Component Based Software Engineering (CBSE). It is difficult to find the optimal component selection. CBSE is an approach that is used to develop a software system from pre-existing…

Software Engineering · Computer Science 2014-08-27 Weam Gaoud Alghabban , M. Rizwan Jameel Qureshi

Despite increased adoption and advances in machine learning (ML), there are studies showing that many ML prototypes do not reach the production stage and that testing is still largely limited to testing model properties, such as model…

In this paper, we present the Gaussian process regression as the predictive model for Quality-of-Service (QoS) attributes in Web service systems. The goal is to predict performance of the execution system expressed as QoS attributes given…

Networking and Internet Architecture · Computer Science 2013-05-09 Jakub M. Tomczak , Jerzy Swiatek , Krzysztof Latawiec

Cell-free massive multiple-input multiple-output (MIMO) is a potential key technology for fifth generation wireless communication networks. A mixed quality-of-service (QoS) problem is investigated in the uplink of a cell-free massive MIMO…

Signal Processing · Electrical Eng. & Systems 2018-06-20 Manijeh Bashar , Kanapathippillai Cumanan , Alister G. Burr , Hien Quoc Ngo , H. Vincent Poor

Bayesian calibration of black-box computer models offers an established framework to obtain a posterior distribution over model parameters. Traditional Bayesian calibration involves the emulation of the computer model and an additive model…

Machine Learning · Statistics 2018-10-30 Sébastien Marmin , Maurizio Filippone

This empirical investigation elucidates the limitations of deterministic, unidimensional productivity heuristics by operationalizing the SPACE framework through extensive repository mining. Utilizing a dataset derived from open-source…

Software Engineering · Computer Science 2025-11-27 Sanchit Kaul , Kevin Nhu , Jason Eissayou , Ivan Eser , Victor Borup

This study aims to investigate the utilization of Bayesian techniques for the calibration of micro-electro-mechanical systems (MEMS) accelerometers. These devices have garnered substantial interest in various practical applications and…

Signal Processing · Electrical Eng. & Systems 2023-06-13 Oliver Dürr , Po-Yu Fan , Zong-Xian Yin

Explicit quantification of uncertainty in engineering simulations is being increasingly used to inform robust and reliable design practices. In the aerospace industry, computationally-feasible analyses for design optimization purposes often…

Fluid Dynamics · Physics 2019-11-13 Jayant Mukhopadhaya , Brian T. Whitehead , John F. Quindlen , Juan J. Alonso

This paper presents an ontology-based approach for the design of a collaborative business process model (CBP). This CBP is considered as a specification of needs in order to build a collaboration information system (CIS) for a network of…

Software Engineering · Computer Science 2015-10-01 Frederick Benaben , Vatcharaphun Rajsiri , Jean-Pierre Lorré , Hervé Pingaud

The System Usability Scale (SUS) is a short, survey-based approach used to determine the usability of a system from an end user perspective once a prototype is available for assessment. Individual scores are gathered using a 10-question…

Methodology · Statistics 2021-01-26 Nicholas Clark , Matthew Dabkowski , Patrick Driscoll , Dereck Kennedy , Ian Kloo , Heidy Shi

Modern AESA technology enables RF systems to not only perform various radar, communication and electronic warfare tasks on a single aperture, but even to execute multiple tasks concurrently. These capabilities increase system complexity and…

Signal Processing · Electrical Eng. & Systems 2025-03-06 Sebastian Durst , Kilian Barth , Tobias Müller , Pascal Marquardt

Optimal design is a critical yet challenging task within many applications. This challenge arises from the need for extensive trial and error, often done through simulations or running field experiments. Fortunately, sequential optimal…

Machine Learning · Computer Science 2025-03-25 Xubo Yue , Raed Al Kontar , Albert S. Berahas , Yang Liu , Blake N. Johnson

Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design. Existing benchmarks focus primarily on generating single-part CAD models and evaluate them…

Artificial Intelligence · Computer Science 2026-05-28 Xiaoyu Dong , Zhi Li , Xiao-Ming Wu

K-means is a classical clustering algorithm with wide applications. However, soft K-means, or fuzzy c-means at m=1, remains unsolved since 1981. To address this challenging open problem, we propose a novel clustering model, i.e.…

Machine Learning · Computer Science 2020-11-23 Yujian Li , Bowen Liu , Zhaoying Liu , Ting Zhang

Software engineering is continuously facing the challenges of growing complexity of software packages and increased level of data on defects and drawbacks from software production process. This makes a clarion call for inventions and…

Software Engineering · Computer Science 2016-11-15 R. Selvarani , T. R. Gopalakrishnan Nair , V. Kamakshi Prasad

We introduce an efficient parametric model checking (ePMC) method for the analysis of reliability, performance and other quality-of-service (QoS) properties of software systems. ePMC speeds up the analysis of parametric Markov chains…

Software Engineering · Computer Science 2018-12-27 Radu Calinescu , Colin Paterson , Kenneth Johnson

Recent advances in objective-based uncertainty quantification (objective-UQ) have shown that such a goal-driven approach for quantifying model uncertainty is extremely useful in real-world problems that aim at achieving specific objectives…

Optimization and Control · Mathematics 2021-12-10 Hyun-Myung Woo , Youngjoon Hong , Bongsuk Kwon , Byung-Jun Yoon

Knowledge-based biomedical data science (KBDS) involves the design and implementation of computer systems that act as if they knew about biomedicine. Such systems depend on formally represented knowledge in computer systems, often in the…

Artificial Intelligence · Computer Science 2022-09-13 Tiffany J. Callahan , Harrison Pielke-Lombardo , Ignacio J. Tripodi , Lawrence E. Hunter

On top of machine learning models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and…

Machine Learning · Computer Science 2024-03-28 Venkat Nemani , Luca Biggio , Xun Huan , Zhen Hu , Olga Fink , Anh Tran , Yan Wang , Xiaoge Zhang , Chao Hu

We introduce MOS, a software application designed to facilitate the deployment, integration, management, and analysis of mathematical optimization models. MOS approaches mathematical optimization at a higher level of abstraction than…

Optimization and Control · Mathematics 2022-10-11 James Hubert Merrick , Tomás Tinoco De Rubira
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