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JMIRx Med 2021年第3期2卷

作者： Andrei Lobiuc Mihai Dimian Olga Sturdza Roxana Filip Mihai Covasa Department of Human Health and Development College of Physical Exercise and Sport Stefan cel Mare University of Suceava Suceava Romania Department of Computers Electronics and Automation College of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava Romania Integrated Center for Research Development and Innovation in Advanced Materials Nanotechnologies and Distributed Systems for Fabrication and Control Stefan cel Mare University of Suceava Suceava Romania Suceava County Emergency Hospital Suceava Romania

Formulation and Numerical Solution for Fractional Order Time Optimal control Problem Using Pontryagin's Minimum Principle

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IFAC-PapersOnLine 2017年第1期50卷 9224-9229页

作者： Tabatabaei S.S. Yazdanpanah M.J. Tavazoei M.S. Electrical Engineering Department Amirkabair University of Technology (Tehran Polytechnic) Tehran Iran Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Electrical Engineering Department Sharif University of Technology Tehran Iran

The main purpose of this paper is to use variational calculus and Pontryagin's minimum principle to propose a solution scheme for time optimal control problem stated on the fractional systems defined in the sense of Caputo. After deriving the necessary optimality conditions, a novel numerical solution is used to solve the problem. Afterwards, a simple case study shows the effectiveness of the proposed method. © 2017

关键词： Non-integer Order Calculus Pontryagin's Minimum Principle Time Optimal control Variational Calculus

Design of microresonators to minimize thermal noise below the standard quantum limit

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arXiv 2019年

作者： Sharifi, S. Banadaki, Y.M. Cullen, T. Veronis, G. Dowling, J.P. Corbitt, T. Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States School of Electrical Engineering & Computer Science Louisiana State University Baton RougeLA70803 United States Center for Computation and Technology Louisiana State University Baton RougeLA70808 United States Hearne Institute for Theoretical Physics Louisiana State University Baton RougeLA70803 United States Department of Computer Science Southern University Baton RougeLA70813 United States

We present a design for a new microresonator whose geometry is optimized to maximize subStandard Quantum Limit (SQL) performance. The new design is predicted to have thermal noise well below the SQL across a broad range of frequencies when operated at 10K. The performance of this designed microresonator will allow it to serve as a test-bed for quantum non-demolition measurements, and to open new regimes of precision measurement that are relevant for many practical sensing applications, including advanced gravitational wave detectors. Copyright © 2019, The Authors. All rights reserved.

关键词： Resonators

Self-adaptation of chimera states

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Physical Review E 2019年第1期99卷 010201(R)-010201(R)页

作者： Nan Yao Zi-Gang Huang Hai-Peng Ren Celso Grebogi Ying-Cheng Lai Department of Applied Physics Xi'an University of Technology Xi'an 710048 China The Key Laboratory of Biomedical Information Engineering of Ministry of Education National Engineering Research Center of Health Care and Medical Devices The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs and Institute of Health and Rehabilitation Science School of Life Science and Technology Xi'an Jiaotong University Xi'an 710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen Aberdeen AB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of “intelligence” in achieving robustness through self-adaptation. The behavior can be exploited for the controlled generation of chimera states with their coherent component placed in any desired spatial region of the system.

关键词： Chimera states Collective dynamics Coupled oscillators Chaos & nonlinear dynamics

Hybrid optimal theory and predictive control for power management in hybrid electric vehicle

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arXiv 2018年

作者： Uthaichana, Kasemsak DeCarlo, Raymond Bengea, Sorin Žefran, Miloš Pekarek, Steve Department of Electrical Engineering Chiang Mai University Chiang Mai Thailand School of Electrical and Computer Engineering Purdue University West LafayetteIN United States Control Systems Group Research Center United Technologies East HartfordCT United States Department of Electrical and Computer Engineering University of Illinois at Chicago ChicagoIL United States

This paper presents a nonlinear-model based hybrid optimal control technique to compute a suboptimal power-split strategy for power/energy management in a parallel hybrid electric vehicle (PHEV). The power-split strategy is obtained as model predictive control solution to the power management control problem (PMCP) of the PHEV, i.e., to decide upon the power distribution among the internal combustion engine, an electric drive, and other subsystems. A hierarchical control structure of the hybrid vehicle, i.e., supervisory level and local or subsystem level is assumed in this study. The PMCP consists of a dynamical nonlinear model, and a performance index, both of which are formulated for power flows at the supervisory level. The model is described as a bi-modal switched system, consistent with the operating mode of the electric ED. The performance index prescribing the desired behavior penalizes vehicle tracking errors, fuel consumption, and frictional losses, as well as sustaining the battery state of charge (SOC). The power-split strategy is obtained by first creating the embedded optimal control problem (EOCP) from the original bi-modal switched system model with the performance index. Direct collocation is applied to transform the problem into a nonlinear programming problem. A nonlinear predictive control technique (NMPC) in conjunction with a sequential quadratic programming solver is used to compute suboptimal numerical solutions to the PMCP. Methods for approximating the numerical solution to the EOCP with trajectories of the original bi-modal PHEV are also presented in this paper. The usefulness of the approach is illustrated via simulation results on several case studies. Copyright © 2018, The Authors. All rights reserved.

关键词： Nonlinear systems

Semi-global leader-following output consensus of discrete-time linear multi-agent systems with input saturation

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Semi-global leader-following output consensus of discrete-ti...

2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018

作者： Shi, Liangren Li, Yuanlong Lin, Zongli Brown, Charles L. Innovation Center Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Automation Shanghai Jiao Tong University China Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 CharlottesvilleVA22904-4743 United States

ISBN: (纸本)9781538668689

We consider the problem of semi-global leader-following output consensus for a group of agents, consisting of a leader agent and some follower agents, which are described by discrete-time linear systems and connected on a directed network. For each follower agent, a distributed observer is built that estimates the state of the leader. Based on the estimates of the leader state and the solution of a parameterized algebraic Riccati equation, we design low gain consensus protocols that are shown to solve the semi-global output consensus problem as long as the leader agent is reachable globally on the network. Numerical simulation shows the performance of the proposed consensus protocols. © 2018 IEEE.

关键词： Multi agent systems

Optimal Dynamic Lyapunov Function and The Largest Estimation of Domain of Attraction

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IFAC-PapersOnLine 2017年第1期50卷 2645-2650页

作者： Monfared M.N. Yazdanpanah M.J. Department of Electrical Engineering Faculty of Electrical Biomedical and Mechatronic Qazvin Branch Islamic Azad University Qazvin Iran Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

Estimation of the domain of attraction is one of the major difficulties in the analysis of any nonlinear control system. Exact expression of a candidate Lyapunov function is indispensable for the estimation. The optimal Lyapunov function which helps to estimate the domain of attraction exactly is acquired by solving a partial differential equation that is not solvable easily for all of the systems. In this paper, an algebraic equation is proposed instead of the partial differential equation to acquire optimal Lyapunov function. The key tool for this purpose is dynamic Lyapunov function which makes it possible to have an analytic expression of a family of candidate Lyapunov functions that are parametric and functional. The parameters and functions would be selected such that the optimal Lyapunov function is achieved. As the second contribution of this paper, the problem of optimality in the sense of the largest elliptical estimation of region of attraction would be followed up. Using a linear matrix inequality technique and a special criterion it is shown that dynamic Lyapunov function can leads to a larger elliptical estimation than that of the conventional Lyapunov function. © 2017

关键词： Domain of Attraction Lyapunov function Nonlinear System

Robust medical instrument segmentation challenge 2019

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arXiv 2020年

作者： Roβ, Tobias Reinke, Annika Full, Peter M. Wagner, Martin Kenngott, Hannes Apitz, Martin Hempe, Hellena Filimon, Diana Mindroc Scholz, Patrick Tran, Thuy Nuong Bruno, Pierangela Arbelaéz, Pablo Bian, Gui-Bin Bodenstedt, Sebastian Bolmgren, Jon Lindström Bravo-Sánchez, Laura Chen, Hua-Bin González, Cristina Guo, Dong Halvorsen, Pål Heng, Pheng-Ann Hosgor, Enes Hou, Zeng-Guang Isensee, Fabian Jha, Debesh Jiang, Tingting Kirtac, Kadir Jin, Yueming Kletz, Sabrina Leger, Stefan Li, Zhixuan Maier-Hein, Klaus H. Ni, Zhen-Liang Riegler, Michael A. Schoeffmann, Klaus Shi, Ruohua Speidel, Stefanie Stenze, Michael Twick, Isabell Wang, Gutai Wang, Jiacheng Wang, Liansheng Wang, Lu Zhang, Yujie Zhou, Yan-Jie Zhu, Lei Wiesenfarth, Manuel Kopp-Schneider, Annette Müller-Stich, Beat P. Maier-Hein, Lena Heidelberg Germany University of Heidelberg Germany Heidelberg Germany Department of General Heidelberg University Hospital Visceral and Transplant Surgery Heidelberg Germany caresyntax Berlin Germany University of Chinese Academy Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China SimulaMet Oslo Norway Tromsø Norway Oslo Norway School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Partner Site Dresden Heidelberg Germany Faculty of Medicine and University Hospital Carl Gustav Carus Technische Universität Dresden Dresden Germany Dresden Germany Universidad de Los Andes Bogotá Colombia Peking University Peking China Department of Computer Science School of Informatics Xiamen University Xiamen China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong German Cancer Research Center Division of Biostatistics Heidelberg Germany Institute of Information Technology Klagenfurt University Austria

Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and roboticassisted interventions. While numerous methods for detecting, segmenting and tracking of medical instruments based on endoscopic video images have been proposed in the literature, key limitations remain to be addressed: Firstly, robustness, that is, the reliable performance of state-of-the-art methods when run on challenging images (e.g. in the presence of blood, smoke or motion artifacts). Secondly, generalization;algorithms trained for a specific intervention in a specific hospital should generalize to other interventions or institutions. In an effort to promote solutions for these limitations, we organized the Robust Medical Instrument Segmentation (ROBUST-MIS) challenge as an international benchmarking competition with a specific focus on the robustness and generalization capabilities of algorithms. For the first time in the field of endoscopic image processing, our challenge included a task on binary segmentation and also addressed multi-instance detection and segmentation. The challenge was based on a surgical data set comprising 10,040 annotated images acquired from a total of 30 surgical procedures from three different types of surgery. The validation of the competing methods for the three tasks (binary segmentation, multi-instance detection and multi-instance segmentation) was performed in three different stages with an increasing domain gap between the training and the test data. The results confirm the initial hypothesis, namely that algorithm performance degrades with an increasing domain gap. While the average detection and segmentation quality of the best-performing algorithms is high, future research should concentrate on detection and segmentation of small, crossing, moving and transparent instrument(s) (parts). Copyright © 2020, The Authors. All rights reserved.

关键词： Endoscopy

The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients

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arXiv 2021年

作者： Baheti, Bhakti Chakrabarty, Satrajit Akbari, Hamed Bilello, Michel Wiestler, Benedikt Schwarting, Julian Calabrese, Evan Rudie, Jeffrey Abidi, Syed Mousa, Mina Villanueva-Meyer, Javier Fields, Brandon K.K. Kofler, Florian Shinohara, Russell Takeshi Iglesias, Juan Eugenio Mok, Tony C.W. Chung, Albert C.S. Wodzinski, Marek Jurgas, Artur Marini, Niccolò Atzori, Manfredo Müller, Henning Grosbröhmer, Christoph Siebert, Hanna Hansen, Lasse Heinrich, Mattias P. Canalini, Luca Klein, Jan Gerken, Annika Heldmann, Stefan Hering, Alessa Hahn, Horst K. Meng, Mingyuan Bi, Lei Feng, Dagan Kim, Jinman Zeineldinal, Ramy A. Karar, Mohamed E. Mathis-Ullrich, Franziska Burgert, Oliver Abderezaei, Javid Pionteck, Aymeric Chopra, Agamdeep Kurt, Mehmet Yan, Kewei Yan, Yonghong Tang, Zhe Ma, Jianqiang Nasser, Sahar Almahfouz Kurian, Nikhil Cherian Meena, Mohit Shamsi, Saqib Sethi, Amit Tustison, Nicholas J. Avants, Brian B. Cook, Philip Gee, James C. Tian, Lin Greer, Hastings Niethammer, Marc Hoopesar, Andrew Hoffmannas, Malte Dalcaar, Adrian V. Christodoulidis, Stergios Estiene, Théo Vakalopoulou, Maria Paragios, Nikos Marcus, Daniel S. Davatzikos, Christos Sotiras, Aristeidis Menze, Bjoern Bakas, Spyridon Waldmannstetter, Diana Division of Computational Pathology Department of Pathology and Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Department of Electrical and Systems Engineering Washington University in St. Louis St. LouisMO United States GE HealthCare San RamonCA United States University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Mallinckrodt Institute of Radiology Washington University School of Medicine St. LouisMO United States Institute for Informatics Data Science & Biostatistics Washington University School of Medicine St. LouisMO United States Department of Bioengineering Santa Clara University Santa ClaraCA United States Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Computer Science TUM School of Computation Information and Technology Technical University of Munich Munich Germany Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Munich Germany Department of Nuclear Medicine University Hospital Regensburg Regensburg Germany University Hospital Regensburg Regensburg Germany Department of Radiology & Biomedical Imaging University of California San FranciscoCA United States Department of Radiology Duke University Medical Center DurhamNC United States Department of Radiology University of California San DiegoCA United States Helmholtz AI Helmholtz Munich Neuherberg Germany Penn Statistics in Imaging and Visualization Center Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Philadelphia United States Massachusetts General Hospital Harvard Medical School United States Centre for Medical Imaging Computing University College London United Kingdom The Hong Kong University of Science and Technology Hong Kong University of Applied Sciences West

Registration of longitudinal brain Magnetic Resonance Imaging (MRI) scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been considerable progress in developing general-purpose medical image registration techniques, they have not yet attained the requisite precision and reliability for this task, highlighting its inherent complexity. Here we describe the Brain Tumor Sequence Registration (BraTS-Reg) challenge, as the first public benchmark environment for deformable registration algorithms focusing on estimating correspondences between pre-operative and follow-up scans of the same patient diagnosed with a diffuse brain glioma. The challenge was conducted in conjunction with both the IEEE International Symposium on Biomedical Imaging (ISBI) 2022 and the International Conference on Medical Image Computing and computer-Assisted Intervention (MICCAI) 2022. The BraTS-Reg data comprise de-identified multi-institutional multi-parametric MRI (mpMRI) scans, curated for size and resolution according to a canonical anatomical template, and divided into training, validation, and testing sets. Clinical experts annotated ground truth (GT) landmark points of anatomical locations distinct across the temporal domain. The training data with their GT annotations, were publicly released to enable the development of registration algorithms. The validation data, without their GT annotations, were also released to allow for algorithmic evaluation prior to the testing phase, which only allowed submission of containerized algorithms for evaluation on hidden hold-out testing data. Quantitative evaluation and ranking was based on the Median Euclidean Error (MEE), Robustness, and the determinant of the Jacobian of the displacement field. The top-ranked methodologies yielded similar performance across all evaluation metrics and shared several methodological commonalities, including pre-alignment, deep neural networks, inverse consistency

关键词： Magnetic resonance imaging

Emergence of the First Strains of SARS-CoV-2 Lineage B.1.1.7 in Romania: Genomic Analysis

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JMIRx med 2021年第3期2卷 e28049页

作者： Andrei Lobiuc Mihai Dimian Olga Sturdza Roxana Filip Mihai Covasa Department of Human Health and Development College of Physical Exercise and Sport Stefan cel Mare University of Suceava Suceava Romania. Department of Computers Electronics and Automation College of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava Romania. Integrated Center for Research Development and Innovation in Advanced Materials Nanotechnologies and Distributed Systems for Fabrication and Control Stefan cel Mare University of Suceava Suceava Romania. Suceava County Emergency Hospital Suceava Romania.

BACKGROUND:The United Kingdom reported the emergence of a new and highly transmissible SARS-CoV-2 variant (B.1.1.7) that rapidly spread to other countries. The impact of this new mutation-which occurs in the S protein-on infectivity, virulence, and current vaccine effectiveness is still under evaluation. OBJECTIVE:The aim of this study is to sequence SARS-CoV-2 samples of cases in Romania to detect the B.1.1.7 variant and compare these samples with sequences submitted to GISAID. METHODS:SARS-CoV-2 samples were sequenced and amino acid substitution analysis was performed using the CoV-GLUE platform. RESULTS:We have identified the first cases of the B.1.1.7 variant in samples collected from Romanian patients, of which one was traced to the region of the United Kingdom where the new variant was originally sequenced. Mutations in nonstructural protein 3 (Nsp3; N844S and D455N) and ORF3a (L15F) were also detected, indicating common ancestry with UK strains as well as remote connections with strains from Nagasaki, Japan. CONCLUSIONS:These results indicate, for the first time, the presence and characteristics of the new variant B.1.1.7 in Romania and underscore the need for increased genomic sequencing in patients with confirmed COVID-19.

关键词： COVID-19 Romania case study epidemiology genetics genome impact infectious disease lineage mutation sequencing spread strain transmission variant virology virus