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Versatile Test Reactor Open Digital engineering Ecosystem

Insight 2022年第1期25卷 56-60页

作者： Ritter, Christopher Browning, Jeren Suyderhoud, Peter Hays, Ross Marshall, AnnMarie Han, Kevin Ashbocker, Taylor Darrington, John Nelson, Lee Idaho National Laboratory Department of Digital Systems & Engineering Versatile Test Reactor Program Idaho FallsID83401 United States Pivotal Solutions 3 Grace Avenue Suite 162 Great NeckNY11021 United States North Carolina State University Department of Civil and Environmental Engineering and Department of Computer Science University of Illinois at Urbana-Champaign 205 N. Mathews Ave. UrbanaIL61801 United States

Modern design of nuclear facilities represents unique challenges: enabling the design of complex advanced concepts, supporting geographically dispersed teams, and supporting first-of-a-kind system development. Errors made early in design can introduce silent errors. These errors can cascade causing unknown risk of complex engineering programs. The Versatile Test Reactor (VTR) program uses digital-engineering principles for design, procurement, construction, and operation to reduce risk and improve efficiencies. Digital engineering is an integrated, model-based approach which connects proven digital tools such as building information management (BIM), project controls, and systems-engineering software tools into a cohesive environment. The VTR team hypothesizes using these principals can lead to similar risk and cost reductions and schedule efficiencies observed in other engineering industries. This research investigates the use of a digital engineering ecosystem in the design of a 300-MWt sodium-cooled fast reactor. This ecosystem was deployed to over 200 engineers and used to deliver the conceptual design of the VTR. We conclude that initial results show significant reductions in user latency (1000x at peak use), the possibility of direct finite-element-analysis (FEA) integrations to computer-aided design (CAD) tools, and nuclear reactor system design descriptions (SDDs) that we can fully link throughout design in data-driven requirements-management software. These early results led to the VTR maintaining milestone performance during the COVID-19 pandemic. © 2022 by Idaho National Laboratory. Published by INCOSE with permission.

关键词： Software testing

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Design approach for additive manufacturing in spare part supply chains

arXiv

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arXiv 2020年

作者： de Brito, Filipe Marinho da Cruz Júnior, Gélson Frazzon, Enzo Morosini Basto, João Pedro Tavares Vieira Alcalá, Symone Gomes Soares School of Electrical Mechanical and Computer Engineering Federal University of Goiás GoiâniaGoiás74605-010 Brazil INESC P&D Brasil São Paulo11055-300 Brazil Graduate Program in Production Engineering Department of Production Engineering and Systems Federal University of Santa Catarina Florianópolis88040-900 Brazil Department of Industrial Engineering and Management Faculty of Engineering University of Porto Porto4200-465 Portugal INESC TEC - Technology Faculty of Engineering University of Porto Porto4200-465 Portugal Production Engineering Faculty of Sciences and Technology Federal University of Goiás Aparecida de Goiânia Goiás74968-755 Brazil

In the current industrial revolution, additive manufacturing (AM) embodies a promising technology that can enhance the effectiveness, adaptability, and competitiveness of supply chains (SCs). Moreover, it facilitates the development of distributed SCs, thereby enhancing product availability, inventory levels, and lead time. However, the wide adoption of AM in industrial SCs creates various challenges, leading to new difficulties for SC design. In this context, this paper proposes a new design approach to AM SCs using optimization methods. More specifically, the proposed approach, comprising the pmedian and mixed-integer linear programming models, considers the decision of deploying productive resources (3D printers) in specific locations of generic spare part SCs. The approach was evaluated in a real-world use case of an elevator maintenance service provider. The obtained results demonstrated the promising capabilities of the proposed design approach in managing the challenges arising from the forthcoming widespread use of 3D printers in manufacturing SCs. © 2020, CC-BY-NC-ND.

关键词： 3D printers

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Clarifying Assumptions about Artificial Intelligence before Revolutionising Patent Law

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GRUR International 2022年第4期71卷 295-321页

作者： Kim, Daria Alber, Maximilian Kwok, Man Wai Mitrovic, Jelena Ramirez-Atencia, Cristian Perez, Jesus Alberto Rodriguez Zille, Heiner Max Planck Institute for Innovation and Competition Munich Germany Charite Institute of Pathology Berlin Germany Chinese University of Hong Kong Department of Physics (Formerly) Hong Kong BMBF Program for Women in AI Faculty of Computer Science and Mathematics Chair of Data Science University of Passau Germany Department of Computer Systems Universidad Politecnica de Madrid Spain School of Computing Science College of Science and Engineering University of Glasgow United Kingdom Faculty of Computer Science Otto von Guericke University Magdeburg Germany

This paper examines several widespread assumptions about artificial intelligence, particularly machine learning, that are often taken as factual premises in discussions on the future of patent law in the wake of 'artificial ingenuity'. The objective is to draw a more realistic and nuanced picture of the human-computer interaction in solving technical problems than where 'intelligent' systems autonomously yield inventions. A detailed technical perspective is presented for each assumption, followed by a discussion of pertinent uncertainties for patent law. Overall, it is argued that implications of machine learning for the patent system in its core tenets appear far less revolutionary than is often posited. © 2022 Published by OUP and CH Beck on behalf of GRUR e.V.

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SkinSource: A Data-Driven Toolbox for Predicting Touch-Elicited Vibrations in the Upper Limb

SkinSource: A Data-Driven Toolbox for Predicting Touch-Elici...

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International Symposium on Haptic Interfaces for Virtual Environment and Teleoperator systems (HAPTICS)

作者： Neeli Tummala Gregory Reardon Simone Fani Dustin Goetz Matteo Bianchi Yon Visell the Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara CA USA the Media Arts and Technology Program University of California Santa Barbara Santa Barbara CA USA the School of Biological and Health Systems Engineering Arizona State University Tempe AZ USA the Soft Robotics for Human Cooperation and Rehabilitation Lab Instituto Italiano di Tecnologia Geneva GE Italy the Department of Mechanical Engineering University of California Santa Barbara Santa Barbara CA USA the Department of Information Engineering University of Pisa PI Italy the Department of Biological Engineering University of California Santa Barbara Santa Barbara CA USA

Vibrations transmitted throughout the hand and arm during touch contact play a central role in haptic science and engineering but are challenging to model or experimentally characterize. Here, we present SkinSource, a data-driven toolbox for predicting skin vibrations across the upper limb in response to user-specified input forces. The toolbox leverages impulse response measurements that encode the physics of vibration transmission across the hands and arms of four participants and provides software tools for analyzing the predicted skin responses. We show that the SkinSource predictions closely match experimental measurements and confirm the underlying assumption of linear vibration transmission in the skin. We also demonstrate through several usage examples how SkinSource can act as a versatile computational platform for haptic research applications, such as characterizing vibrotactile transmission in the skin, engineering haptic interfaces, and investigating touch perception.

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INTEGRATION OF SHIP CONTROL-systems FOR TOTAL SHIP SURVIVABILITY

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NAVAL ENGINEERS JOURNAL 1992年第4期104卷 114-116页

作者： SIMPSON, HL FAMME, JB TAYLOR, B Joseph Famme:is the manager of marine systems CAE-Link Silver Spring Maryland. Mr. Famme joined Link in 1983 where he is responsible for developing marine products including digital control and monitoring systems for ships and submarines. Prior to joining Link then Commander Famme served in the U.S. Navy in all shipboard assignments including command of an FF-1052 class frigate. His engineering duties included supervising new construction sea trials and major mid-life ship overhauls. Mr. Famme has written concept papers defining architectures for future platform control systems and has worked within the simulation industry to introduce the use of distributed computer-based systems for training. He is currently working with various naval organizations and shipbuilding companies to develop the next generation of integrated digital control systems for ships and submarines. Barry Taylor:is the manager of marine systems at CAE Electronics Montreal Canada. CAE is currently supplying the integrated control systems for four classes of ships: the Canadian Patrol Frigate the DDH-280 the USN MHC-51 Minehunter and the SA'AR 5 corvette under construction at Litton - Ingalls Shipbuilding. Prior to joining CAE Electronics in 1987 then Commander Taylor served in the Canadian Navy as an engineering duty officer. His tours included sea duty as the engineering officer on five ships and shore duty assignments including one in the Directorate responsible for ship machinery control systems in the Canadian Navy. Commander Taylor was also the program manager for the Shipboard Integrated Machinery Control System Advanced Development Model (SHINMACS ADM). He has had numerous papers published on integrated ship control systems.

Effective damage control in naval ships has always been an important element of the naval combat equation. After receipt of battle damage, the ship's offensive operational capability depends upon its ability to support or restore vital systems. This in turn depends on the degree of initial damage, the damage control readiness condition of the ship, and effectiveness of the crew in applying the ship's damage control doctrine. In addition to conventional shell, mine, and torpedo threats, the speed and lethality of modern weapon systems presents an increased requirement for damage control readiness. New technology for the monitoring and control of the ship's hull, mechanical, electrical, and damage control (HME&DC) systems is now available with the potential for improving damage control readiness and for aiding the ship's commander in executing his damage control doctrine. This paper will describe the evolution of ship control systems, and discuss the application of current ship control systems technologies to damage control. It will recommend an optimum approach to meeting the requirements of damage control readiness posed by modern day threats, working within the U.S. Navy concept called Total Ship Survivability (TSS).

关键词： Naval Vessels

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Highly accurate model for prediction of lung nodule malignancy with ct scans

arXiv

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arXiv 2018年

作者： Causey, Jason Zhang, Junyu Ma, Shiqian Jiang, Bo Qualls, Jake Politte, David G. Prior, Fred Zhang, Shuzhong Huang, Xiuzhen Department of Computer Science Arkansas State University JonesboroAR72467 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin N.T. Hong Kong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Mallinckrodt Institute of Radiology Washington University St. LouisMO63110 United States Department of Biomedical Informatics University of Arkansas for Medical Sciences Little RockAR72205 United States UALR/UAMS Joint Graduate Program in Bioinformatics Little RockAR72204 United States

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://***/NoduleX. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Development of Low-Temperature Doping Process in Cdse-Nanocrystal Thin Films for Flexible Electronic and Optoelectronic Devices

SSRN

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SSRN 2022年

作者： Lee, Yong Min Jung, Byung Ku Ahn, Junhyuk Park, Taesung Shin, Chanho Ng, Tse Nga Kim, In Soo Choi, Ji-Hyuk Oh, Soong Ju Department of Semiconductor Systems Engineering Korea University Seoul02841 Korea Republic of Department of Materials Science and Engineering Korea University Seoul02841 Korea Republic of Materials Science Engineering Program Department of Electrical and Computer Engineering University of California San Diego La Jolla CA92093 United States Nanophotonics Research Center Korea Institute of Science and Technology Seoul02792 Korea Republic of Department of Converging Science and Technology KHU KIST Seoul02447 Korea Republic of Resources Utilization Research Center Korea Institute of Geoscience and Mineral Resources Daejeon34132 Korea Republic of

We introduce an effective surface-doping strategy for CdSe nanocrystals (NCs) by examining the size-dependency of the doping behavior. A CdSe NC thin-film transistor (TFT) is fabricated via a doping process with InCl3 treatment followed by an annealing process. Spectroscopic and electronic device characterization reveal that smaller NCs are more effectively doped than larger NCs at all annealing temperatures. This is attributed to the larger specific surface area, where the dopant can be more readily coordinated. The degenerate behavior of a 3.3-nm CdSe-NC TFT appears at a lower temperature than that of larger NC TFTs. We achieve a high electron mobility and on-to-off current ratio of 1.79 cm2/Vs and 5.2 × 105, respectively, in a low-temperature annealing process (150 °C) with 3.3-nm CdSe NCs. This facilitates the fabrication of a flexible CdSe-NC TFT, which is demonstrated on a polyethylene terephthalate substrate with an Al2O3 dielectric layer using atomic layer deposition. The flexible 3.3-nm CdSe-NC TFT is successfully fabricated even at 150 °C, with a high on-to-off current ratio and low hysteresis at a low operation voltage, which is impossible for larger CdSe-NC TFTs. © 2022, The Authors. All rights reserved.

关键词： Nanocrystals

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Mrf-Former: A Multi-Scale Resolution Fusion Approach for Addressing Scale Discrepancies in Remote Sensing Image Change Detection

SSRN

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SSRN 2024年

作者： Yang, Hualin Ouyang, Jiarui Cheng, Junhao Zhang, Wen Li, Hui Li, Xiying Chen, Calvin Yu-Chian Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518107 China - Preferred Program Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong Provincial Key Laboratory of Intelligent Transportation System Sun Yat-sen University Guangzhou China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518107 China Institute of Artificial Intelligence Guangzhou University Guangzhou China

Dealing with resolution variations in dual-temporal remote sensing images is challenging due to differences in sensor capabilities, altitudes, footprints, resampling, and data fusion. Conventional methods for different-resolution change detection struggle to effectively address these challenges, primarily due to insufficient consideration of global and local feature interactions. In this paper, we propose a novel change detection model that leverages the power of multi-scale resolution fusion(MRF). By incorporating the MRF-Block, our approach extracts hierarchical multi-scale features from the input data, enabling effective capture of contextual information at various granularities. This facilitates improved handling of resolution disparities and promotes interactions between global and local features. Experimental evaluations conducted on diverse datasets, demonstrate the effectiveness of our proposed model in achieving accurate change detection in dual-temporal remote sensing imagery, even in scenarios characterized by varying resolutions. Code is available on-line at https://***/yanghl1914/MRF-Former. © 2024, The Authors. All rights reserved.

关键词： Remote sensing

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AIR-CUSHION LANDING CRAFT NAVIGATION

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NAVAL ENGINEERS JOURNAL 1985年第4期97卷 248-260页

作者： GRAHAM, HR KIM, JC BAND, EGU FOWLER, AW Herbert R. Graham:received his degrees of B.S. in 1951 and M.S. in 1958 in aeronautical engineering from the Massachusetts Institute of Technology and the California Institute of Technology respectively. He also attended the Harvard Graduate School of Business Administration. He is presently a task manager at TRW Inc. McLean Virginia responsible for landing craft air cushion (LCAC) engineering support. Since joining TRW in 1967 he has had several technical project management and system engineering responsibilities in amphibious ships transportation and energy. He was responsible for the preliminary engineering design and cost estimates for tracked air cushion vehicles (TACVs). He has been active in several professional societies including ASNE and served as vice-chairman Los Angeles Section American Institute of Aeronautics and Astronautics. John C. Kim:received his degrees of B.S. in electrical engineering Tri-State University 1959 M.S. in electrical engineering Michigan State University 1960 and Ph.D. in electrical engineering Michigan State University. He is presently a senior staff engineer with TRW Inc. McLean Virginia where his technical experience has included communications system engineering and navigation system analysis. Since joining TRW in 1969 he has held numerous positions including section head project manager and department manager. His previous employment includes E-Systems/Melpar Division and Honeywell. Dr. Kim has been active in the IEEE Washington Chapter activities which included secretary vice-chairman and chairman of Systems Science and Cybernetics Group. Edward G.U. Band:received a B.S. degree in mechnical engineering in 1946 and a D.I.C in aeronautical engineering in 1947 at the City and Guilds College of London University. In 1951 he received an M.S. degree from Stevens Institute of Technology in fluid dynamics. After a career in the aircraft industry in England Canada and the U.S.A. he spent several years teaching in Chile and at Webb Institute of Naval Archi

Air cushion vehicles (ACVs) have operated successfully on commercial routes for about twenty years. The routes are normally quite short; the craft are equipped with radar and radio navigation aids and maintain continuous contact with their terminals. Navigation of these craft, therefore, does not present any unusual difficulty. The introduction of air cushion vehicles into military service, however, can present a very different picture, especially when external navigation aids are not available and the craft must navigate by dead reckoning. This paper considers the problems involved when navigating a high-speed air cushion vehicle by dead reckoning in conditions of poor visibility. A method is presented to assess the ACV's navigational capability under these circumstances. A figure of merit is used to determine the sensitivity of factors which affect navigation such as the range of visibility, point-to-point distance, speed, turning radius and accuracy of onboard equipment. The method provides simplistic but adequate answers and can be used effectively to compare the-capability and cost of alternative navigation concepts.

关键词： AIR CUSHION VEHICLES

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Fair Patient Model: Mitigating Bias in the Patient Representation Learned from the Electronic Health Records

arXiv

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arXiv 2023年

作者： Sivarajkumar, Sonish Huang, Yufei Wang, Yanshan Intelligent Systems Program School of Computing and Information University of Pittsburgh PittsburghPA United States Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA United States Department of Health Information Management University of Pittsburgh PittsburghPA United States Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Clinical and Translational Science Institute University of Pittsburgh PittsburghPA United States

Objective: To pre-train fair and unbiased patient representations from Electronic Health Records (EHRs) using a novel weighted loss function that reduces bias and improves fairness in deep representation learning models. Methods: We defined a new loss function, called weighted loss function, in the deep representation learning model to balance the importance of different groups of patients and features. We applied the proposed model, called Fair Patient Model (FPM), to a sample of 34,739 patients from the MIMIC-III dataset and learned patient representations for four clinical outcome prediction tasks. Results: FPM outperformed the baseline models in terms of three fairness metrics: demographic parity, equality of opportunity difference, and equalized odds ratio. FPM also achieved comparable predictive performance with the baselines, with an average accuracy of 0.7912. Feature analysis revealed that FPM captured more information from clinical features than the baselines. Conclusion: FPM is a novel method to pre-train fair and unbiased patient representations from EHR data using a weighted loss function. The learned representations can be used for various downstream tasks in healthcare and can be extended to other domains where bias and fairness are important. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep learning

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