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Nanoscale 2024年第9期16卷 4919页

作者： Michael A Casasanta G M Jonaid Liam Kaylor William Y Luqiu Maria J Solares Mariah L Schroen William J Dearnaley Jarad Wilson Madeline J Dukes Deborah F Kelly Department of Biomedical Engineering Pennsylvania State University University Park PA 16802 USA. Debkelly@psu.edu. Materials Research Institute Pennsylvania State University University Park PA 16802 USA. Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Molecular Cellular and Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Department of Electrical and Computer Engineering Duke University Durham NC 27708 USA. RayBiotech Life Peachtree Corners GA 30092 USA. Applications Science Protochips Inc. Morrisville NC 27560 USA.

Expression of concern for 'Microchip-based structure determination of low-molecular weight proteins using cryo-electron microscopy' by Michael A. Casasanta , , 2021, , 7285-7293, https://***/10.1039/D1NR00388G.

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Role of hole transport layers in normal and inverted bulk heterojunction organic solar cells: A light intensity dependent capacitance-voltage analysis

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Materials science in Semiconductor Processing 2025年 198卷

作者： Shailendra Kumar Gupta Durgesh C. Tripathi Amit Kumar Neha Garg Chinmay K. Gupta Vandana Yadav Sandeep Sharma Sanjeev Kumar Ashish Garg Amity School of Physical Sciences Amity University Punjab IT City Sector 82A Mohali 140308 India The Zispel Nano Electronic Center Department of Electrical Engineering Technion-Israel Institute of Technology Haifa 32000 Israel Clarendon Laboratory Department of Physics University of Oxford Oxford OX1 3PU United Kingdom Department of Computer Science and Engineering Manav Rachna International Institute of Research and Studies Faridabad 121004 India Department of Physics National Post Graduate College Barhalganj 273402 Gorakhpur India Physics Department Punjab Engineering College (Deemed to be University) Chandigarh 160012 India Department of Sustainable Energy Engineering Indian Institute of Technology Kanpur Kanpur 208016 India Chandrakanta Kesavan Center for Energy Policy and Climate Solutions Indian Institute of Technology Kanpur Kanpur 208016 India

In organic solar cells (OSC) hole transport layers (HTL) are essential for boosting the power conversion efficiency (PCE); therefore, it is crucial to determine the underlying mechanisms. In the present manuscript, we report a study that examines the effects of two HTL such as PEDOT:PSS and MoO 3 , on the electrical characteristics of P3HT:PC 61 BM (active layer) based bulk heterojunction (BHJ) in normal (ITO/PEDOT:PSS/P3HT:PCBM/Al) and inverted (ITO/ZnO/P3HT:PCBM/MoO 3 /Ag) configurations. Current density-voltage ( J-V ) and illumination intensity dependent capacitance-voltage ( C-V) measurements have been performed and compared for with and without HTL (PEDOT:PSS in normal and MoO 3 in inverted) devices. Results suggest that the extracted photovoltaic parameters (short circuit current density ( J sc ), open circuit voltage ( V oc ) and fill factor ( FF )) of HTL containing devices are superior to without HTL devices in both normal and inverted OSC, due to unfavourable charge carrier accumulation and band bending in HTL free devices. Such charge build-up at active layer/anode interface generates photovoltage contributing as loss factor to PCE and has been investigated in C-V characteristics measured under varied illumination intensities (0/dark, 50 and 100 mWcm −2 ). Parameters such as built-in-voltage (V bi ), effective built-in-voltage (V bi, eff ), accumulated carrier concentration and surface photovoltage (V spv = V bi, eff - V bi ) are extracted as a function of illumination intensity. Our findings reveal that HTL free devices, in both conventional and inverted OSCs structures, marked with low J sc , V oc and FF values generate higher SPV . The SPV calculation method used here has been proven to be crucial in recommending a suitable HTL for OSC device architectures.

关键词： Bulk heterojunction Capacitance-voltage Surface photo-voltage Carrier accumulation

Ultrafast optical modulation of Dirac electrons in gated single-layer graphene

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Physical Review B 2020年第24期101卷 245408-245408页

作者： Ikufumi Katayama Kei-ichi Inoue Yusuke Arashida Yang Wu Hyunsoo Yang Taiki Inoue Shohei Chiashi Shigeo Maruyama Tadaaki Nagao Masahiro Kitajima Jun Takeda Department of Physics Graduate School of Engineering Science Yokohama National University Tokiwadai 79-5 Hodogaya-ku Yokohama 240-8501 Japan Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 117576 Singapore Department of Mechanical Engineering The University of Tokyo Hongo 7-3-1 Bunkyo-ku Tokyo 113-8656 Japan Energy Nano Engineering Laboratory National Institute of Advanced Industrial Science and Technology Namiki 1-2-1 Tsukuba Ibaraki 305-8564 Japan International Center for Materials Nanoarchitectonics (MANA) National Institute of Materials Science Namiki 1-1 Tsukuba Ibaraki 305-0044 Japan Department of Condensed Matter Physics Hokkaido University Sapporo Hokkaido 060-0810 Japan

Fermi level dependence of ultrafast optical responses of single-layer graphene has been investigated using sub-10-fs pump-probe spectroscopy under bias voltages. We observe the ultrafast thermalization of photoexcited carriers, whose dynamics can be modulated via bias-induced change of the Fermi level. The relaxation time and the amplitude of the electronic response are maximized when the Fermi level reaches approximately half of the excitation photon energy. From the analysis of the pump-pulse-induced optical conductivity change, we find that the bias-induced blocking of the relaxation pathways and the pump-induced change of the electronic temperature and the Fermi level significantly contribute to the observed ultrafast optical modulation. The results demonstrate the controllability of the ultrafast optical responses in single-layer graphene, which could be useful for future ultrafast electro-optic graphene devices.

关键词： Carrier dynamics Carrier generation & recombination Optical conductivity Ultrafast optics Graphene

Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

Moiré hyperbolic metasurfaces

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arXiv 2020年

作者： Hu, Guangwei Krasnok, Alex Mazor, Yarden Qiu, Cheng-Wei Alù, Andrea Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Photonics Initiative Advanced Science Research Center City University of New York 85 St. Nicholas Terrace New YorkNY10031 United States Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical Engineering City College of New York New YorkNY10031 United States

Recent advances in twistronics of low-dimensional materials, such as bilayer graphene and transition-metal dichalcogenides, have enabled a plethora of unusual phenomena associated with moiré physics. However, several of these effects require demanding manipulation of superlattices at the atomic scale, such as the careful control of rotation angle between two closely spaced atomic lattices. Here, we study moiré hyperbolic plasmons in pairs of hyperbolic metasurfaces (HMTSs), unveiling analogous phenomena at the mesoscopic scale. HMTSs are known to support confined surface waves collimated towards specific directions determined by the metasurface dispersion. By rotating two evanescently coupled HMTSs with respect to one another, we unveil rich dispersion engineering, topological transitions at magic angles, broadband field canalization, and plasmon spin-Hall phenomena. These findings open remarkable opportunities to advance metasurface optics, enriching it with moiré physics and twistronic concepts. Copyright © 2020, The Authors. All rights reserved.

关键词： Surface waves

Training of Physical Neural Networks

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arXiv 2024年

作者： Momeni, Ali Rahmani, Babak Scellier, Benjamin Wright, Logan G. McMahon, Peter L. Wanjura, Clara C. Li, Yuhang Skalli, Anas Berloff, Natalia G. Onodera, Tatsuhiro Oguz, Ilker Morichetti, Francesco del Hougne, Philipp Le Gallo, Manuel Sebastian, Abu Mirhoseini, Azalia Zhang, Cheng Marković, Danijela Brunner, Daniel Moser, Christophe Gigan, Sylvain Marquardt, Florian Ozcan, Aydogan Grollier, Julie Liu, Andrea J. Psaltis, Demetri Alù, Andrea Fleury, Romain Lausanne Switzerland Microsoft Research 198 Cambridge Science Park CambridgeCB4 0AB United Kingdom Rain AI San Francisco United States Department of Applied Physics Yale University CT United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Max Planck Institute for the Science of Light Staudtstraße 2 Erlangen91058 Germany Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States FEMTO-ST Institute Optics Department CNRS University Bourgogne Franche-Comté Besançon25030 Cedex France Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom NTT Physics and Informatics Laboratories NTT Research Inc. Sunnyvale United States Lausanne Switzerland Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Milan Italy Univ Rennes CNRS IETR UMR 6164 RennesF-35000 France IBM Research Europe– Zurich Rüschlikon8803 Switzerland Department of Computer Science Stanford University United States Google DeepMind 1600 Amphitheatre Parkway Mountain ViewCA94043 United States Unité Mixte de Physique CNRS/Thales CNRS Thales Université Paris-Saclay Palaiseau France Laboratoire Kastler Brossel Sorbonne Université École Normale Supérieure Collège de France CNRS UMR 8552 Paris France Laboratoire Albert Fert CNRS Thales UniversitéParis-Saclay Palaiseau91767 France Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States Lausanne Switzerland Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research area with small-scale laboratory demonstrations, they are arguably one of the most underappreciated important opportunities in modern artificial intelligence (AI). Could we train AI models 1000x larger than current ones? Could we do this and also have them perform inference locally and privately on edge devices, such as smartphones or sensors? Research over the past few years has shown that the answer to all these questions is likely "textityes, with enough research": PNNs could one day radically change what is possible and practical for AI systems. To do this will however require rethinking both how AI models work, and how they are trained – primarily by considering the problems through the constraints of the underlying hardware physics. To train PNNs at large scale, many methods including backpropagation-based and backpropagation-free approaches are now being explored. These methods have various trade-offs, and so far no method has been shown to scale to the same scale and performance as the backpropagation algorithm widely used in deep learning today. However, this is rapidly changing, and a diverse ecosystem of training techniques provides clues for how PNNs may one day be utilized to create both more efficient realizations of current-scale AI models, and to enable unprecedented-scale models. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

Two-dimensional pentagonal material Penta-PdPSe: A first-principle study

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arXiv 2021年

作者： Bafekry, Asadolah Fadlallah, M.M. Faraji, M. Shafique, A. Jappor, H.R. Abdolhoseini Sarsari, I. Ang, Yee Sin Ghergherehchi, M. Department of Radiation Application Shahid Beheshti University Tehran*** Iran Department of Physics Faculty of Science Benha University Benha13518 Egypt Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Department of Physics Lahore University of Management Sciences Lahore Pakistan Department of Physics College of Education for Pure Sciences University of Babylon Hilla Iraq Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Cluster Singapore University of Technology and Design Singapore487372 Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Low-symmetry Penta-PdPSe with intrinsic in-plane anisotropy synthesized successfully [P. Li et al., Adv. Mater., 2102541 (2021)]. Motivated by this experimental discovery, we investigate the structural, mechanical, electronic, optical and thermoelectric properties of PdPSe monolayer via density functional theory calculations. The phonon dispersion, molecular dynamics simulation, the cohesive energy mechanical properties of the penta-PdPSe monolayer is verified to confirm its stability. The phonon spectrum represents a striking gap between the high-frequency and the low-frequency optical branches and an out-of-plane flexure mode with a quadratic dispersion in the long-wavelength limit. The Poisson’s ratio indicates that penta-PdPSe is a brittle monolayer. The pendaPdPSe monolayer is an indirect semiconductor with bandgap of 1.40 (2.07) eV using PBE (HSE06) functional. Optical properties simulation suggests that PdPSe is capable of absorbing a substantial range of visible to ultraviolet light. Band alignment analysis also reveals the compatibility of PdPSe for water splitting photocatalysis application. By combining the electrical and thermal transport properties of PdPSe, we show that a high PF is achievable at room temperature, thus making PdPSe a candidate material for thermoelectric application. Our findings reveal the strong potential of penta-PdPSe monolayer for a wide array of applications, including optoelectronic, water splitting and thermoelectric device applications. © 2021, CC BY.

关键词： Monolayers

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

Impact of Intention to Use to a Document Management System (Case Study Approach) 3

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Impact of Intention to Use to a Document Management System (...

3rd international Conference on Information Management and Technology, ICIMTech 2018

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

ISBN: (纸本)9781538658215

Document management system makes user to access information anytime and anywhere. The purpose of this research is to analyze what variables have impact on the intention to use of document management system. To achieve the objectives conducted by identification problem on the research model developed from the model of Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology to the use of document management system. Furthermore, the data obtained from the respondents tested outer model, inner model test, hypothesis test and to produce a comprehensive analysis will be conducted Importance Performance Analysis. This research will result in a comprehensive analysis and able to provide recommendations and solutions for improvement from the implementation DMS has been done earlier. © 2018 IEEE.

关键词： Information services

Requirements specification and evaluation for transient faults in communication protocols based on RT-FRIDA framework

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IFAC-PapersOnLine 2018年第10期51卷 76-81页

作者： Roque, Alexandre S. Nunes, Gerson L. Freitas, Edison P. Pereira, Carlos E. Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul UFRGS Porto Alegre Brazil Computer Science and Engineering Department Regional Integrated University of High Uruguay and Missions URI Santo Angelo Brazil

This paper presents an evaluation of requirements specification for two critical real-time control systems, which depends of industrial communications protocols. It is proposed the use of aspect-oriented modeling (AOM) to map transient fault behaviors in design phases, with RT-FRIDA framework extended for fault modeling capabilities. Requirements specification for an Active suspension control system and for a fault detection control system applied in agricultural implements was made as case study. Faults are specified as non-functional requirements and evaluated applying a quantitative softgoal weight method. Results presented indicates aspect-oriented fault modeling as an important ally to specify faults that have potential to degrade performance of real-time control systems. © 2016

关键词： Suspensions (components) Active suspension systems Agricultural implements Control systems Fault detection Fault tree analysis Interactive computer systems Network protocols Real time control Real time systems Specifications Active suspension control Aspect oriented Aspect Oriented Modeling Industrial communications Non functional requirements Requirements analysis Requirements specifications Transient faults