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Correction: A meta-classification-based approach for outlier identification in GNSS networks

GPS Solutions 2025年第2期29卷 1-1页

作者： Suraci, Stefano Sampaio de Oliveira, Leonardo Castro Klein, Ivandro Goldschmidt, Ronaldo Ribeiro Rofatto, Vinicius Francisco Defense Engineering Department Military Institute of Engineering Leonardo Castro de Oliveira Rio de Janeiro Brazil Defense Engineering Program Military Institute of Engineering Rio de Janeiro Brazil Graduate Program in Geodetic Sciences Federal University of Paraná Curitiba Brazil Dept. of Civil Construction Federal Institute of Santa Catarina Florianopolis Brazil Systems and Computing Program Military Institute of Engineering Rio de Janeiro Brazil Institute of Geography Federal University of Uberlândia Monte Carmelo Brazil

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A study on medical imaging equipment productivity and utilization

A study on medical imaging equipment productivity and utiliz...

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61st Annual Conference and Expo of the Institute of Industrial Engineers

作者： Hu, Mengqi Industrial Engineering Program School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85281 United States

ISBN: (纸本)9780983762409

The importance of efficient utilization of expensive imaging equipment has been brought to full public attention by the current health care debates. In particular, the use of imaging equipments such as Computed Tomography (CT), Mammography (MG) and Magnetic Resonance Imaging (MRI) is known to contribute to the rising cost with health care. Though medical practices and research attempt to address this issue through measuring and improving imaging equipment productivity, the analysis has mainly focused on enterprise (hospital, clinical) level instead of operational (examination) level. This is due to the lack of technical data available from medical imaging. We have recently developed and implemented an enterprise wide imaging dose tracking system for Mayo Clinic which enables a comprehensive study on imaging equipment utilization. In this research, we first propose three standardized productivity metrics to study the imaging equipment productivity. Design of experiment is then conducted to identify significant factors affecting equipment productivity and utilization. The insights can be gained for medical administrators to better allocate resource and schedule resource utilization that in turn may reduce health care expenses.

关键词： Health care

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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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StBlocks: Visual programming for data structures 18

StBlocks: Visual programming for data structures

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18th Annual Conference on Information Technology Education, SIGITE 2017

作者： Almanza, Daniel F. Del Toro, Manuel F. Urrego, Ricardo A. Feijóo, Pedro G. De La Rosa, Fernando Program of Systems Engineering Universidad El Bosque Bogotá D.C. Colombia Systems and Computing Engineering Department Universidad de los Andes Bogotá D.C. Colombia

ISBN: (纸本)9781450351003

The Data Structures course is common in systems engineering and Computer Science programs, providing a fundamental basis for professional training in these disciplines. This course presents a great pedagogical challenge, due to the high complexity in the algorithms studied and the levels of abstraction that it requires. Considering that the traditional pedagogical approach is sometimes not adequate to ease understanding of the structures covered in the course, we propose the development of DStBlocks as a playful and visual tool for the design and programming of data structures. Through this document we emphasize the context to be intervened and the problem to be solved, indicating the progress corresponding to the project. At the end we present the work which will be held in a near future, indicating how we are going to measure learning variables according to the project's objectives. © 2017 Copyright is held by the owner/author(s).

关键词： Data structures

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U-Net and SegNet performances on lesion segmentation of breast ultrasonography images

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Research on Biomedical engineering 2021年第2期37卷 171-179页

作者： Vianna, Pedro Farias, Ricardo de Albuquerque Pereira, Wagner Coelho Biomedical Engineering Program COPPE/Federal University of Rio de Janeiro Av. Horácio Macedo 2030 Room H327 Rio de JaneiroRJ Brazil Systems and Computing Engineering Program COPPE/Federal University of Rio de Janeiro Rio de JaneiroRJ Brazil

Purpose: Screening is the predominant strategy for the early detection of breast cancer. However, image analysis depends on the experience of the radiologist, inserting subjective factors in the evaluation of findings. Most biopsies performed on women with suspicious lesions on breast imaging tests show benignity. This medical technique is invasive and consumes time and resources;therefore, there is a demand to reduce these unnecessary procedures. Computer-aided diagnostics has been increasingly used as a second-reader tool lately, decreasing the diagnostic uncertainty of specialists. Based on this fact, the development of such systems is crucial and can be accomplished by the refinement of its steps, i.e., more accurate segmentation and classification. Considering this scenario, the present work describes the implementation of two well-known convolutional neural networks, U-Net and SegNet, for the segmentation of lesions found in breast ultrasonography. Defining which architecture is most appropriate for this task can ultimately help in reducing the number of biopsies performed. Methods: Convolutional neural networks are used in segmentation by classifying each pixel in an image, based on self-trained weights. Using a dataset of 2054 images, obtained in partnership with the National Cancer Institute, we compared the automatic segmentation performed by the networks with a manual segmentation made by a specialist. Results: Among the two proposed architectures, U-Net obtained better results in this task, obtaining a dice coefficient of 86.3%, and took 68.3% less training time than the SegNet, which achieved a dice score of 81.1%. Conclusion: The two networks can segment ultrasound images with useful accuracy depending on their configuration, with U-Net being faster to train and more accurate. © 2021, Sociedade Brasileira de Engenharia Biomedica.

关键词： Semantic Segmentation

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PPM-HC: A method for helping project portfolio management based on topic hierarchy learnings

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International Journal of Business Intelligence and Data Mining 2021年第3期18卷 364-382页

作者： Pinto, Ricardo A.M. Bernardini, Flavia Marcacini, Ricardo M. Graduate Program in Industrial Engineering and Computing Systems Fluminense Federal University Jardim Bela Vista Rio das OstrasRJ Brazil Computing Institute Fluminense Federal University São Domingos NiteróiRJ Brazil Information Systems Federal University of Mato Grosso do Sul P.O. Box 210 Três LagoasMS Brazil

The projects categorisation is a crucial step in the project portfolio management (PPM). Categorising projects allows the organisation to identify categories with a lack or excess of projects, according to its strategic objectives. In this work, we present a new method for project portfolio management based on hierarchical clustering (PPM-HC) to organise the projects at several levels of abstraction. In the PPM-HC, similar projects are allocated to the same clusters and subclusters. PPM-HC automatically learns an understandable topic hierarchy from the project portfolio dataset, thereby facilitating the (human) task of exploring, analysing and prioritising the projects of the organisation. We also proposed a card sorting-based technique which allows the evaluation of the projects categorisation using an intuitive visual map. We carried out an experimental evaluation based on a benchmark dataset and we also presented a real-world case study. The results show that the proposed PPM-HC method is promising. © 2021 Inderscience Enterprises Ltd.

关键词： Investments

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Minimum maximum-degree publish-subscribe overlay network design

Minimum maximum-degree publish-subscribe overlay network des...

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作者： Onus, Melih Richa, Andréa W. Department of Computer Engineering Bilkent University Ankara 06560 Turkey Computer Science and Engineering Program School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85281 United States

Designing an overlay network for publish/subscribe communication in a system where nodes may subscribe to many different topics of interest is of fundamental importance. For scalability and efficiency, it is important to keep the degree of the nodes in the publish/subscribe system low. It is only natural then to formalize the following problem: Given a collection of nodes and their topic subscriptions, connect the nodes into a graph that has least possible maximum degree in such a way that for each topic t, the graph induced by the nodes interested in t is connected. We present the first polynomial-time logarithmic approximation algorithm for this problem and prove an almost tight lower bound on the approximation ratio. Our experimental results show that our algorithm drastically improves the maximum degree of publish/subscribe overlay systems. We also propose a variation of the problem by enforcing that each topic-connected overlay network be of constant diameter while keeping the average degree low. We present three heuristics for this problem that guarantee that each topic-connected overlay network will be of diameter 2 and that aim at keeping the overall average node degree low. Our experimental results validate our algorithms, showing that our algorithms are able to achieve very low diameter without increasing the average degree by much. © 2011 IEEE.

关键词： Overlay networks

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Converting engineering faculty to educators of entrepreneurs

Converting engineering faculty to educators of entrepreneurs

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114th Annual ASEE Conference and Exposition, 2007

作者： Gassert, John D. Blessing, Jeffrey Schmedeman, Larry Fennigkoh, Larry Milwaukee School of Engineering United States AIMBE United States IEEE ABET EAC Program Management Information Systems Program Milwaukee School of Engineering United States United States Association for Computing Machinery Computer Society Rader School of Business Milwaukee School of Engineering United States MSOE's Biomedical Engineering Program

Including concepts of entrepreneurship in an engineering education is nothing new. It would be difficult to find a university that does not offer several courses or specific programs in entrepreneurship. However, finding large numbers of engineering programs that have fully incorporated entrepreneurship into their undergraduate engineering curricula is a far greater challenge. With the growth of outsourcing and global competition, it is imperative that engineering faculty be more than just educators of technically competent engineers. It is important that they be educators of entrepreneurs. This paper will describe a workshop that took initial steps to convince engineering faculty of the importance of educating engineering entrepreneurs and integrating entrepreneurship into an engineering curriculum. It will describe the workshop agenda, the assessment process used to measure if there was a change in faculty attitude, and the preliminary assessment results. © American Society for engineering Education, 2007.

关键词： engineering education

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Specialized reporting of article review - SRAR Method 4

Specialized reporting of article review - SRAR Method

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4th IEEE World engineering Education Conference, EDUNINE 2020

作者： Rojas, Julio Ernesto Quispe Tuesta, Julio Enrique Quispe Universidad Nacional Pedro Ruiz Gallo Computing and Electronics Departament Lambayeque Peru Universidad Nacional Tecnologica de Lima sur Systems Engineering Program Lima Peru

ISBN: (纸本)9781728166384

The professional training of the engineering student must be innovated in order to meet the accreditation criterion and with the requirement of the university law that requires presenting an investigation to obtain the bachelor's degree and another to obtain the professional degree of engineer. In order to develop in students, the skills to search for scientific and technological articles, and the critical skills to evaluate documents and extract the main ideas from them in relation to a particular topic, the SRAR method or specialized report review method has been proposed. It has been applied during five academic semesters in the electronic engineering telephone systems course, with satisfactory results. The SRAR method has six stages:*** of the SRAR method and proposed topic, 2. Initial bibliographic search, 3. Autonomous training, 4. Selection of articles for review, 5. Study and evaluation of articles 6. Writing of specialized report for review of articles. © 2020 IEEE.

关键词： Students

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Work in Progress: Semi-Dual apprenticeship for the development of skill in professional training of the engineer 4

Work in Progress: Semi-Dual apprenticeship for the developme...

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4th IEEE World engineering Education Conference, EDUNINE 2020

ISBN: (纸本)9781728166384

The development of competencies in the professional training of an engineer includes: knowledge, skills and attitudes. For the development of skills, laboratory practices with physical equipment, virtual systems and remote systems are alternatives;the practices in the place of work performance through technical visits or pre-professional practices in the factories and maintenance workshops. Dual learning includes the participation of students in theoretical sessions in the center of studies and practical sessions of the installation and maintenance of machines and equipment in factories and workshops. The semidual learning proposal considers 50% of the practical sessions in the laboratories of the study center and 50% in the facilities of the industrial company. The experience of the application in the course of electrical machines is reported, where the application of the Semi-dual learning method in five academic semesters was planned, from 2019 - 1 to 2021 - 1, to date it was applied in the semester 2019 1, with satisfactory results. © 2020 IEEE.

关键词： Professional aspects

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