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International Joint Conference on Neural Networks, IJCNN 2005

作者： Holmstrom, Lars Santiago, Roberto Lendaris, George G. NW Computational Intelligence Laboratory Portland State University Portland OR 97201 Systems Science Ph.D. Program Department of Systems Science and Electrical and Computer Engineering

ISBN: (纸本)0780390482

Mathematical models are often used in system identification applications. The dynamics of most systems, however, change over time and the sources of these changes cannot always be directly determined or measured. To maintain model accuracy, it is desirable to design system identifiers that can adapt to these dynamical shifts. We use reinforcement learning to train an agent to recognize dynamical changes in a modeled system and to estimate new parameter values for the model. The subsequent actions of this agent are characterized as "moving" the parameterized model on an optimal trajectory in model parameter space. It is found that this method is capable of quickly and accurately discerning the correct parameter values. © 2005 IEEE.

关键词： Identification (control systems)

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Improving a web usability inspection technique using qualitative and quantitative data from an observational study

Improving a web usability inspection technique using qualita...

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SBES 2009 - 23rd Brazilian Symposium on Software engineering

作者： Conte, Tayana Vaz, Verônica Massolar, Jobson Mendes, Emilia Travassos, Guilherme Horta Manaus Brazil Systems Engineering and Computer Science Program COPPE UFRJ Rio de Janeiro Brazil Computer Science Department University of Auckland Auckland New Zealand

ISBN: (纸本)9780769538440

We have proposed a checklist-based usability inspection technique (WDP - Web Design Perspectives-Based Usability Evaluation) specific for Web applications' usability evaluation and we are following an experimentation-based methodology to support its development and improvement. This paper describes an observational study conducted, aimed at eliciting how inspectors apply the WDP technique. We discuss the quantitative and qualitative results of the result and their impact on improving the WDP technique. We analyzed the qualitative data using the procedures from the Grounded Theory (GT) method. © 2009 IEEE.

关键词： Inspection

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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Propositional dynamic logic with storing, recovering and parallel composition

Propositional dynamic logic with storing, recovering and par...

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作者： Benevides, Mario R.F. De Freitas, Renata Petrucio, Viana Computer Science Department Systems and Computer Engineering Program Federal University of Rio de Janeiro Brazil Institute of Mathematics Fluminense Federal University Brazil

This work extends Propositional Dynamic Logic (PDL) with parallel composition operator and four atomic programs which formalize the storing and recovering of elements in data structures. A generalization of Kripke semantics is proposed that instead of using set of possible states it uses structured sets of possible states. This new semantics allows for representing data structures and using the five new operator one is capable of reasoning about the manipulation of these data structures. The use of the new language (PRSPDL) is illustrated with some examples. We present sound and complete set of axiom schemata and inference rules to prove all the valid formulas for a restricted fragment called RSPDLo. © 2011 Elsevier B.V. All rights reserved.

关键词： Data structures

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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DARTS-Drone and Artificial Intelligence Reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline Resilience

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International Journal of Disaster Risk science 2022年第5期13卷 810-821页

作者： Premkumar Ravishankar Seokyon Hwang Jing Zhang Ibrahim X.Khalilullah Berna Eren-Tokgoz Department of Industrial and Systems Engineering Lamar UniversityBeaumontTX 77710USA Construction Management Program Lamar UniversityBeaumontTX 77710USA Department of Computer Science Lamar UniversityBeaumontTX 77710USA

The need for safe operation and effective maintenance of pipelines grows as oil and gas demand ***,it is increasingly imperative to monitor and inspect the pipeline system,detect causes contributing to developing pipeline damage,and perform preventive maintenance in a timely ***,pipeline inspection is performed at pre-determined intervals of several months,which is not sufficiently robust in terms of *** research proposes a drone and artificial intelligence reconsolidated technological solution(DARTS) by integrating drone technology and deep learning *** solution is aimed to detect the targeted potential root problems-pipes out of alignment and deterioration of pipe support system-that can cause critical pipeline failures and predict the progress of the detected problems by collecting and analyzing image data *** test results show that DARTS can be effectively used to support decision making for preventive pipeline maintenance to increase pipeline system s afety and resilience.

关键词： Artifcial intelligence Asset management Drone application Midstream industry Pipeline resilience Predictive maintenance

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An alternative QoS architecture for the IEEE 802.16 Standard 06

An alternative QoS architecture for the IEEE 802.16 Standard

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2nd Conference on Future Networking Technologies, CoNEXT'06

作者： De Moraes, Luís Felipe M. Maciel, Paulo Ditarso Systems Engineering and Computer Science Program - COPPE/UFRJ HighSpeed Networks Laboratory RAVEL Rio de Janeiro RJ Brazil

In this paper, we propose an alternative QoS architecture for the IEEE 802.16 Standard, that incorporates a priority based packet scheduling and a new traffic shaping. For this, we present the ideas of a traffic condi... 详细信息

ISBN: (纸本)1595934561

关键词： Quality of service

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Feasibility study of Information Technology Investment (a case study of ODOO ERP: Project Management Module Implementation in Indonesia Based Company) 10

Feasibility study of Information Technology Investment (a ca...

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10th International Conference on ICT for Smart Society, ICISS 2019

作者： Jingga, Fredy Kosala, Raymond Supangkat, Suhono Harso Ranti, Benny School of Information Systems Bina Nusantara University Computer Science Department BINUS Graduate Program-Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9781728148809

IT Governance are one of the needs in managing Enterprise Level IT. This study shows part of the decision domain of IT Governance Help, which are IT Investment and Prioritization. The purpose of this study is to determine feasibility of implementation open source ERP system Odoo project management module that replaces current system based on operational, economic, and technical aspects. The method used are Fit/Gap Analysis and Cost Benefit model using economic impact worksheet. The analysis is done by comparing the requirement with features owned by current system and Odoo ERP system. This research resulted that Odoo ERP System is feasible in the 3 aspects, the operational feasibility Odoo reaching 72% Fit, the economic feasibility with ROI of 84%, and technical feasibility indicating the technical requirement can be fulfilled by leasing AWS server. The conclusion is the open source ERP system Odoo project management module is feasible to be applied in terms of 3 aspects that have been studied, those are operational, economic, and technical. © 2019 IEEE.

关键词： Cost benefit analysis

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Safe adaptation in context-aware feature models 12

Safe adaptation in context-aware feature models

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4th International Workshop on Feature-Oriented Software Development, FOSD'12

作者： Marinho, Fabiana G. Andrade, Rossana M.C. Costa, Paulo A.S. Maia, Paulo H.M. Vidal, Vania M.P. Werner, Claudia Department of Computer Science Federal University of Ceará Fortaleza Brazil Group of Computer Network Software Engineering and Systems - GREat Federal University of Ceará Fortaleza Brazil Systems Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781450313094

Software product lines, usually described using feature models, have proven to be a feasible solution to develop mobile and context-aware applications. These applications use con- text information to provide services and data for their users from anywhere and at any time. However, building feature models for mobile and context-aware software product lines demands advanced skills of software engineers, since it comprises system and context information. Moreover, to guarantee a correct application execution, these models must be thoroughly specified, composed and verified to check whether some composition and adaptation rules are violated. Although this is an important task, there is a lack of formalization of such rules, which makes it difficult to use those rules for feature models verification. In this paper, we propose an approach to prevent defects in context-aware feature models and in their product reconfiguration based on formal methods. To validate our work, we developed a prototype to check the correctness of context-aware feature models. Copyright 2012 ACM.

关键词： Formal methods

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Dynamic Sampling-Based Meta-Learning Using Multilingual Acoustic Data for Under-Resourced Speech Recognition

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IEEE Access 2024年 12卷 106070-106083页

作者： Hsieh, I-Ting Wu, Chung-Hsien Zhao, Zhe-Hong National Cheng Kung University Graduate Program of Multimedia Systems and Intelligent Computing Tainan70101 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan

Under-resourced automatic speech recognition (ASR) has become an active field of research and has experienced significant progress during the past decade. However, the performance of under-resourced ASR trained by existing methods is still far inferior to high-resourced ASR for practical applications. In this paper, speech data from languages that share the most phonemes with the under-resourced language are selected as supplementary resources for meta-training based on the Model-Agnostic Meta-Learning (MAML) strategy. Besides supplementary language selection, this paper proposes a dynamic sampling method instead of the original random sampling method to select support and query sets for each task in MAML to improve meta-training performance. In this study, Taiwanese is selected as the under-resourced language, and the speech corpus of five languages, including Mandarin, English, Japanese, Cantonese, and Thai, are chosen as supplementary training data for acoustic model training. The proposed dynamic sampling approach uses phonemes, pronunciation, and speech recognition models as the basis to determine the proportion of each supplementary language to select helpful utterances for MAML. For evaluation, with the selected utterances from each supplementary language for meta-training, we obtained a Word Error Rate of 20.24% and a Syllable Error Rate of 8.35% for Taiwanese ASR, which were better than the baseline model (26.18% and 13.99%) using only the Taiwanese corpus and other methods. © 2013 IEEE.

关键词： Speech recognition

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