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2nd International Conference on Eco engineering Development 2018, ICEED 2018

作者： Anual, M.T. Sahroni, T.R. Akmal, S. Nasution, F.A. Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Faculty of Manufacturing Engineering Innovative Software System and Services Research Group Centre for Advanced Computing Technology Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia

This paper presents the design and analysis of welding fixtures based on transient thermal analysis. Welding fixtures is designed to hold and support the workpiece securely during the welding process. The heat transformation from the workpiece could lead the temperature rises and impacts to the welding fixtures. Therefore, the study introduces the development of welding fixtures as one of a safety measure prevents the welder from injury while handling welding process. The conceptual design of welding fixtures and material were applied to conduct the simulation. Transient thermal analysis was performed on temperature and total heat flux by using computer aided engineering software. The result shows the analysis of equivalent stress, total deformation, factors of safety, fatigue life and fatigue damage. Furthermore, the equivalent stress failure theory used to predict yielding in welding fixture design. The design of welding fixtures and material selection were proposed to hold and support the workpiece securely. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Heat flux

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Towards an Experiment Line on software Inspection with Human Computation

Towards an Experiment Line on Software Inspection with Human...

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International Workshop on Conducting Empirical Studies in Industry (CESI)

作者： Stefan Biffl Marcos Kalinowski Dietmar Winkler Information & Software Engineering Technische Universität Wien Vienna Austria Experimental and Applied Software Engineering Research Group Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Rio de Janeiro Brazil Christian Doppler Laboratory for Security and Quality Improvement in the Production System Lifecycle Technische Universitat Wien Vienna Austria

software Inspection is an important approach to find defects in software engineering (SE) artifacts. While there has been extensive research on traditional software inspection with pen-and-paper materials, modern SE poses new environments, methods, and tools for the cooperation of software engineers. Technologies, such as Human Computation (HC), provide tool support for distributed and tool-mediated work processes. However, there is little empirical experience on how to leverage HC for software inspection. In this vision paper, we present the context for a research program on this topic and introduce the preliminary concept of a theory-based ex-periment line to facilitate designing experiment families that fit together to answer larger questions than individual experiments. We present an example feature model for an experiment line for Soft-ware Inspection with Human Computation and discuss its expected benefits for the research program, including the coordination of research, design and material reuse, and aggregation facilities.

关键词： Inspection software Tools Computational modeling Analytical models Task analysis software engineering

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Deriving architecture design variants for system optimization from design space descriptions expressed using a UML profile

Deriving architecture design variants for system optimizatio...

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2017 International Symposium on Model-Driven Approaches for Simulation engineering, Mod4Sim 2017, Part of the 2017 Spring Simulation Multi-Conference, SpringSim 2017

作者： Wichmann, Alexander Bedini, Francesco Maschotta, Ralph Zimmermann, Armin Technische Universität Ilmenau Department of Computer Science and Automation System and Software Engineering Group PO-Box 100 565 Ilmenau98684 Germany

ISBN: (纸本)9781510838260

In complex (dynamic) systems, models are usually too complex for a direct evaluation, and simulation is the method of choice (indirect optimization). Another aspect is the structure of the design space for complex system. In a recent paper of the authors, an approach is presented for design space description with a UML profile-based description of architectural variations of complex dynamic systems. In order to execute a simulation of a system variant, one has to be chosen based on the used heuristic, and specified in a standardized way to be used for constructing the actual simulation model with the use of a library of template models. This paper approaches a method to automatically generated individual UML object models from the design space specification for a given parameter selection. ©2017 Society for Modeling & Simulation International (SCS).

关键词： Multiobjective optimization

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A Causal Roadmap for Generating High-Quality Real-World Evidence

arXiv

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arXiv 2023年

作者： Dang, Lauren E. Gruber, Susan Lee, Hana Dahabreh, Issa Stuart, Elizabeth A. Williamson, Brian D. Wyss, Richard Díaz, Iván Ghosh, Debashis Kıcıman, Emre Alemayehu, Demissie Hoffman, Katherine L. Vossen, Carla Y. Huml, Raymond A. Ravn, Henrik Kvist, Kajsa Pratley, Richard Shih, Mei-Chiung Pennello, Gene Martin, David Waddy, Salina P. Barr, Charles E. Akacha, Mouna Buse, John B. van der Laan, Mark Petersen, Maya Department of Biostatistics University of California BerkeleyCA United States TL Revolution CambridgeMA United States Office of Biostatistics Office of Translational Sciences Center for Drug Evaluation and Research U.S. Food and Drug Administration Silver SpringMD United States Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Department of Mental Health Johns Hopkins Bloomberg School of Public Health BaltimoreMD United States Biostatistics Division Kaiser Permanente Washington Health Research Institute SeattleWA United States Division of Pharmacoepidemiology and Pharmacoeconomics Brigham and Women’s Hospital Harvard Medical School BostonMA United States Division of Biostatistics Department of Population Health New York University Grossman School of Medicine New YorkNY United States Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Microsoft Research RedmondWA United States Global Biometrics and Data Management Pfizer Inc. New YorkNY United States Department of Epidemiology Mailman School of Public Health Columbia University New YorkNY United States Syneos Health Clinical Solutions Amsterdam Netherlands Syneos Health Clinical Solutions MorrisvilleNC United States Novo Nordisk Søborg Denmark AdventHealth Translational Research Institute OrlandoFL United States Cooperative Studies Program Coordinating Center VA Palo Alto Health Care System Palo AltoCA United States Department of Biomedical Data Science Stanford University StanfordCA United States Division of Imaging Diagnostics and Software Reliability Office of Science and Engineering Laboratories Center for Devices and Radiological Health U.S. Food and Drug Administration Silver SpringMD United States Global Real World Evidence Group Moderna CambridgeMA United States National Center for Advancing Translational Sciences BethesdaMD United States G

Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized controlled trials with outcomes assessed using RWD to fully observational studies. Yet many RWE study proposals lack sufficient detail to evaluate adequacy, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. The Causal Roadmap is an explicit, itemized, iterative process that guides investigators to pre-specify analytic study designs;it addresses a wide range of guidance within a single framework. By requiring transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on pre-specified criteria, the Roadmap can help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend the Causal Roadmap framework for use by clinical and translational researchers, with companion papers demonstrating application of the Causal Roadmap for specific use cases. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

arXiv

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arXiv 2023年

作者： Li, Jianning Zhou, Zongwei Yang, Jiancheng Pepe, Antonio Gsaxner, Christina Luijten, Gijs Qu, Chongyu Zhang, Tiezheng Chen, Xiaoxi Li, Wenxuan Wodzinski, Marek Friedrich, Paul Xie, Kangxian Jin, Yuan Ambigapathy, Narmada Nasca, Enrico Solak, Naida Melito, Gian Marco Vu, Viet Duc Memon, Afaque R. Schlachta, Christopher De Ribaupierre, Sandrine Patel, Rajnikant Eagleson, Roy Chen, Xiaojun Mächler, Heinrich Kirschke, Jan Stefan de la Rosa, Ezequiel Christ, Patrick Ferdinand Li, Hongwei Bran Ellis, David G. Aizenberg, Michele R. Gatidis, Sergios Küstner, Thomas Shusharina, Nadya Heller, Nicholas Andrearczyk, Vincent Depeursinge, Adrien Hatt, Mathieu Sekuboyina, Anjany Löffler, Maximilian Liebl, Hans Dorent, Reuben Vercauteren, Tom Shapey, Jonathan Kujawa, Aaron Cornelissen, Stefan Langenhuizen, Patrick Ben-Hamadou, Achraf Rekik, Ahmed Pujades, Sergi Boyer, Edmond Bolelli, Federico Grana, Costantino Lumetti, Luca Salehi, Hamidreza Ma, Jun Zhang, Yao Gharleghi, Ramtin Beier, Susann Sowmya, Arcot Garza-Villarreal, Eduardo A. Balducci, Thania Angeles-Valdez, Diego Souza, Roberto Rittner, Leticia Frayne, Richard Ji, Yuanfeng Ferrari, Vincenzo Chatterjee, Soumick Dubost, Florian Schreiber, Stefanie Mattern, Hendrik Speck, Oliver Haehn, Daniel John, Christoph Nürnberger, Andreas Pedrosa, João Ferreira, Carlos Aresta, Guilherme Cunha, António Campilho, Aurélio Suter, Yannick Garcia, Jose Lalande, Alain Vandenbossche, Vicky Van Oevelen, Aline Duquesne, Kate Mekhzoum, Hamza Vandemeulebroucke, Jef Audenaert, Emmanuel Krebs, Claudia van Leeuwen, Timo Vereecke, Evie Heidemeyer, Hauke Röhrig, Rainer Hölzle, Frank Badeli, Vahid Krieger, Kathrin Gunzer, Matthias Chen, Jianxu van Meegdenburg, Timo Dada, Amin Balzer, Miriam Fragemann, Jana Jonske, Frederic Rempe, Moritz Malorodov, Stanislav Bahnsen, Fin H. Seibold, Constantin Jaus, Alexander Marinov, Zdravko Jaeger, Paul F. Stiefelhagen, Rainer Santos, Ana Sofia Lindo, Mariana Ferreira, André Alves, Victor Kamp, Michael Abourayya, Amr Nensa, Felix Hörst, Fabian Brehmer, Alexander Hein Girardetstraße 2 Essen45131 Germany Graz University of Technology Inffeldgasse 16c Graz8010 Austria Graz Austria The Department of Computer Science Johns Hopkins University Malone Hall 3400 N Charles St BaltimoreMD21218 United States Rte Cantonale Lausanne1015 Switzerland The Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Sierre Switzerland Department of Biomedical Engineering University of Basel Hegenheimermattweg Allschwil167C CH-4123 Switzerland The Boston College 140 Commonwealth Ave Chestnut HillMA02467 United States University Hospital B7-200 339 Windermere Road LondonN6A 5A5 Canada The Department of Radiology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai200240 China The Research Center for Connected Healthcare Big Data ZhejiangLab Zhejiang Hangzhou311121 China The Faculty of Statistics Technical University Dortmund August-Schmidt-Straße 1 Dortmund44227 Germany The Institute of Mechanics Graz University of Technology Kopernikusgasse 24/IV Graz8010 Austria The Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China The Department of Cardiac Surgery Medical University Graz Auenbruggerplatz 29 Graz8036 Austria The Department of Diagnostic and Interventional Radiology University Hospital Giessen Justus-Liebig-University Giessen Klinikstraße 33 Giessen35392 Germany The Department of Mechanical Engineering Mehran University of Engineering and Technology Jamshoro Sindh76062 Pakistan The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Geschäftsführender Oberarzt Abteilung für Interventionelle und Diagnostische Neuroradiologie Universitätsklinikum der Technischen Universität München Ismaningerstr. 22 München81675 Germany icometrix Kolonel Be

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://***/ and https://***/Jianningli/*** Codes 68T01 © 2023, CC BY.

关键词： Large dataset

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Incorporating AEGIS autonomous science into mars science laboratory rover mission operations 15th

Incorporating AEGIS autonomous science into mars science lab...

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15th International Conference on Space Operations, SpaceOps 2018

作者： Francis, Raymond Estlin, Tara Doran, Gary Gaines, Daniel Johnstone, Stephen Montaño, Suzanne Peret, Laurent Mousset, Valérie Gasnault, Olivier Frydenvang, Jens Wiens, Roger C. Schaffer, Steven Pavri, Betina Verma, Vandana Chattopadhyay, Debarati Bornstein, Benjamin Mittal, Nimisha Deflores, Lauren Jet Propulsion Laboratory Machine Learning and Instrument Autonomy Research Group California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory Artificial Intelligence Research Group California Institute of Technology PasadenaCA91109 United States Intelligence and Space Research Division Los Alamos National Laboratory Los AlamosNM87545 United States Telespazio France FIMOC Toulouse France FIMOC Centre National d’Études Spatiales Toulouse France FIMOC Institut de Recherche en Astrophysique et Planétologie Université de Toulouse CNRS CNES UPS France Natural History Museum of Denmark University of Copenhagen Copenhagen Denmark Los Alamos National Laboratory Intelligence and Space Research Division Los AlamosNM87545 United States Jet Propulsion Laboratory Artificial Intelligence Research Group California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory Instrument Operations Engineering Group California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory Robot Operations Group California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory Planning and Sequencing Systems Group California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory Electronics and Software Section California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory Science Planning Group California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory Instrument System Engineering Group California Institute of Technology PasadenaCA91109 United States

ISBN: (数字)9781624105623

ISBN: (纸本)9781624105623

The AEGIS (Autonomous Exploration for Gathering Increased Science) intelligent targeting software system has been in use on the Mars Science Laboratory (MSL) mission since 2016. The system allows on-board autonomous selection of targets for the ChemCam remote geochemistry instrument based on analysis of images taken by the rover. This paper describes the deployment of AEGIS to MSL and the operational use of the system since rollout to science operations in May of 2016. We describe how MSL Science Operations have adapted to include autonomous target selection, both in procedures and in exploration strategies, and how mission planners and scientists have used AEGIS autonomy to enhance their work on the MSL mission. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Rovers

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Automated Toll Collection system based on Vehicle Type Classification using Sparse-Filtered Convolutional Neural Networks with Layer-Skipping Strategy (SF-CNNLS)

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Journal of Physics: Conference Series 2018年第1期1061卷

作者： Suryanti Awang Nik Mohamad Aizuddin Nik Azmi Soft Computing & Intelligent System Research Group (SPINT) Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Pahang Malaysia

Automated Toll Collection system (ATCS) is one of the technologies to fulfill the Intelligent Transportation system's (ITS) aim in providing an efficient road and transportation infrastructure at the expressway. This paper is aimed to provide an accurate and efficient ATCS based on a vehicle type classification method rather than the current implementation of toll collection that rely on sensor-based and human observation. To fulfill the aim, we proposed to implement SF-CNNLS framework to extract vehicle's features and classify it into class 1 (passenger vehicle), class 2 (lorry) and class 4 (taxi). This ATCS is aimed to enhance the efficiency of the toll collection in Malaysia. The biggest challenge in this research is how to discriminate features of class 4 as a different class of class 1 since both classes have almost identical features. However, with our proposed method, we able to classify the vehicle with the average accuracy of 90.83 %. We tested our method using a frontal view of a vehicle from the self-obtained database (SPINT) taken using mounted-camera at the toll booth and compare the classification performance with a benchmark database named BIT.

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Finding Database Contention Hotspots under Large-Scale Workloads——A Big Data Approach

Finding Database Contention Hotspots under Large-Scale Workl...

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2016 IEEE International Conference on Big Data Analysis

作者： An Lei Ping Sun Weixiong Rao Hong Min Gong Su Zhenhua Dong School of Software Engineering Tongji University IBM T.J.Watson Research Center IBM System and Technology Group

Database plays an important role in transactional information systems. One significant performance impacting factor is data lock contention in transaction processing. In order to guide betterdatabase design, we propose a novel solution to identify contention hotspots displayed in DBMS transaction logs. To analyze the large volume of data collected in the transaction log, our solution employees bigdata engine Spark for better computation performance and scalability. A novel algorithm is also introduced to optimize computation for analyzing hotspots in the distributed cluster. The experimental results from a benchmark OLTP workload demonstrate the effectiveness and high scalability of our solution.

关键词： database contention relation database system transaction log Spark

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Transient Thermal Analysis of Welding Fixtures Design

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IOP Conference Series: Earth and Environmental Science 2018年第1期195卷

作者： M T Anual T R Sahroni S Akmal F A Nasution Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Faculty of Manufacturing Engineering Innovative Software System & Services Research Group Centre for Advanced Computing Technology Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia. Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480

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