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Research Square 2022年

作者： Alliche, Mounir Rebhi, Redha Inc, Mustafa Kidar, Ali Menni, Younes Ameur, Houari Lorenzini, Giulio Alsharif, Sameer Althobaiti, Ahmed Aly, Ayman A. Department of Mechanical Engineering Faculty of Technology University Yahia Fares of Medea Medea26000 Algeria Department of Computer Engineering Biruni University Istanbul Turkey Department of Mathematics Science Faculty Firat University Elazig23119 Turkey Department of Medical Research China Medical University Hospital China Medical University Taichung40402 Taiwan Faculty of Exact Sciences and Informatics Ziane Achour University of Djelfa Algeria Faculty of Technology Ziane Achour University of Djelfa Algeria Unit of Research on Materials and Renewable Energies Department of Physics Faculty of Sciences Abou Bekr Belkaid University P.O. Box 119 Tlemcen13000 Algeria Department of Technology University Centre of Naama - Salhi Ahmed P.O. Box 66 Naama 45000 Algeria Department of Engineering and Architecture University of Parma Parco Area Delle Scienze 181/A Parma43124 Italy Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Mechanical Engineering College of Engineering Taif University Taif21944 Saudi Arabia

Combustion-chamber is a critical component of the propulsion engine, which is widely used in the space industry and aeronautics. The goal of this article is to perform a numerical-analysis on the combustion process using a liquid-type propellant. The steps that must be followed until total combustion is achieved are emphasized. It concerns the fuel feeding phase, its injection and the combustion operation. The amount of combustion products and the energy generated are evaluated. It has been shown that the liquid propellant may present an efficient alternative fuel than the kerosene. In addition, the temperature of combustion does not exceed a certain limit to avoid structural problems in the chamber. The parametric survey allowed determining the range of the most influence factors, including the pressure, mixture richness, velocity and flow rates of injection for the fuel and oxidizer. The number and type of injectors revealed a considerable influence on the velocity and flow rates of injection. To maximize thrust force and system propulsion, a careful selection of chamber material and ignition methods is required. A thorough inspection on the issues of walls cooling showed the necessary survey of maximum temperatures that may be reached during the combustion. Finally, an investigation of the thermal exchange through the walls will be very interesting. © 2022, CC BY.

关键词： Surveys

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Relationship among state reopening policies, health outcomes and economic recovery through first wave of the COVID-19 pandemic in the U.S

arXiv

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arXiv 2021年

作者： Ligo, Alexandre K. Mahoney, Emerson Cegan, Jeffrey Trump, Benjamin D. Jin, Andrew S. Kitsak, Maksim Keenan, Jesse Linkov, Igor US Army Corps of Engineers Engineer Research and Development Center ConcordMA United States University of Virginia Department of Engineering Systems and Environment CharlottesvilleVA United States Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Carnegie Mellon University Department of Engineering and Public Policy PittsburghPA United States Tulane University School of Architecture New OrleansLA United States

State governments in the U.S. have been facing difficult decisions involving tradeoffs between economic and health-related outcomes during the COVID-19 pandemic. Despite evidence of the effectiveness of government-mandated restrictions mitigating the spread of contagion, these orders are stigmatized due to undesirable economic consequences. This tradeoff resulted in state governments employing mandates at widely different ways. We compare the different policies states implemented during periods of restriction ("lockdown") and reopening with indicators of COVID-19 spread and consumer card spending at each state during the first "wave" of the pandemic in the U.S. between March and August 2020. We find that while some states enacted reopening decisions when the incidence rate of COVID-19 was minimal or sustained in its relative decline, other states relaxed socioeconomic restrictions near their highest incidence and prevalence rates experienced so far. Nevertheless, all states experienced similar trends in consumer card spending recovery, which was strongly correlated with reopening policies following the lockdowns and relatively independent from COVID-19 incidence rates at the time. Our findings suggest that consumer card spending patterns can be attributed to government mandates rather than COVID-19 incidence in the states. We estimate the recovery in states that reopened in late April was more than the recovery in states that did not reopen in the same period – 15% for consumer card spending and 18% for spending by high income households. This result highlights the important role of state policies in minimizing health impacts while promoting economic recovery and helps planning effective interventions in subsequent waves and immunization efforts. © 2021, CC BY.

关键词： SARS

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Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging

arXiv

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arXiv 2020年

作者： Ahmadi, Samim Hauffen, Jan Christian Kästner, Linh Jung, Peter Caire, Giuseppe Ziegler, Mathias Bundesanstalt für Materialforschung und -prüfung Berlin Germany Chair Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Berlin Institute of Technology Berlin Germany Chair Communication and Information Theory Berlin Institute of Technology Berlin Germany

Block-sparse regularization is already well-known in active thermal imaging and is used for multiple measurement based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. To avoid time-consuming manually selected regularization parameter, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging. © 2020, CC BY.

关键词： Mean square error

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Crack identification using extended IsoGeometric analysis and particle swarm optimization 7th

Crack identification using extended IsoGeometric analysis an...

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7th International Conference on Fracture Fatigue and Wear, FFW 2018

作者： Khatir, Samir Wahab, Magd Abdel Benaissa, Brahim Köppen, Mario Department of Electrical Energy Metals Mechanical Constructions and Systems Faculty of Engineering and Architecture Ghent University Ghent Belgium Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan

ISBN: (纸本)9789811304101

The eXtended isogeometric analysis (X-IGA) combined with Particle swarm optimization (PSO) is used for crack identification in twodimensional linear elastic problems based on inverse problem. The application of fracture mechanics test under mode II loading is performed. The X-IGA possesses the advantages of the combination between eXtended Finite Element Method (X-FEM) and the Isogeometric Analysis (IGA). The objective function minimizes the gap between the calculated and measured displacements. Convergence studies at various positions of crack on the plate are calculated and the results shows that the proposed technique can detect damage with minimum accuracy 95% for the position and maximum accuracy 98%. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Inverse problem PSO and crack identification and plate 2D XIGA

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Elastic waves in periodically anisotropic heterogeneous media: bridge the gap between rigorous and phenomenological approaches

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Journal of Physics: Conference Series 2024年第25期2647卷 252034-252034页

作者： I. Andrianov V. Danishevskyy J. Kaplunov Y. Kirichek Chair and Institute of General Mechanics RWTH Aachen University 18 Eilfschornstein-strasse Aachen 52062 Germany Prydniprovska State Academy of Civil Engineering and Architecture 24a Architect Oleg Petrov street Dnipro 49005 Ukraine School of Computer Science and Mathematics Keele University Keele ST55BG UK 4 Faculty of Civil Engineering and Geosciences Delft University of Technology 1 Stevinweg Delft 2628CN The Netherlands

Despite the growing capacity of computer codes, analytical solutions are still of great interest. As a rule, they are based on certain asymptotic approximations. In our work, we use a two-scale asymptotic procedure. Anti-plane shear waves in a layered medium are studied. To clarify the basics of the methodology, we restrict ourselves with a layered membrane. For long-wave case we obtained solutions for periodic and anti-periodic modes. We analyse them in the low- and high-contrast cases. The results obtained can be generalized for complex multiscale heterogeneous media and structures. They are useful for bridging the gap between mathematically rigorous and phenomenological approaches in dynamics of heterogeneous materials. They also can be implicated as benchmarks for numerical modelling.

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Stabilization of THz waves using chaos supremacy

Stabilization of THz waves using chaos supremacy

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International Conference on Smart Green Technology in electrical and Information Systems (ICSGTEIS)

作者： Fumiyoshi Kuwashima Mona Jarrahi Semih Cakmakyapan Kenji Wada Masanobu Haraguchi Yuki Kawakami Takeshi Moriyasu Osamu Morikawa Kazuyoshi Kurihara Hideaki Kitahara Takashi Furuya Makoto Nakajima Masahiko Tani Dep. of Electr. and Electron. Eng. Fukui University of Technology Fukui Japan Electrical and Computer Eng. UCLA Los Angeles CA USA Dep. of Physics and Electronics Osaka Metropolitan University Osaka Japan Industrial and Social Science Grad. Sch. of Tech. Tokushima Univ. Tokushima Japan Dep. of Elec. and Inf. Eng. Natl. Inst. of Tech. Fukui Col. Fukui Japan Faculty of Engineering University of Fukui Fukui Japan Chair of Liberal Arts Japan Coast Guard Academy Kure Japan School of Education University. of Fukui Fukui Japan FIR-UF University of Fukui Fukui Japan Inst. of Laser Engineering Osaka Univ. Osaka Japan

We apply the chaos supremacy of laser chaos system to the high stabilization of THz waves. Stability was demonstrated by down converting the optical beats between laser longitudinal modes in the THz domain to the radio frequency domain and comparing a conventional free running CW laser diode to a chaotically oscillating laser diode. Because of their exceptional stability, chaotically oscillating lasers are attractive options for optical pump sources in terahertz time-domain spectroscopy systems.

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Robust Few-Shot Pose Estimation of Articulated Robots using Monocular Cameras and Deep-Learning-based Keypoint Detection

Robust Few-Shot Pose Estimation of Articulated Robots using ...

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International Conference on Robot Intelligence Technology and Applications (RiTA)

作者： Jens Lambrecht Chair Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Technische Universitt Berlin Berlin Germany

Camera-based pose estimation is a necessity for flexible applications in robotics, especially interaction between robots and mobile entities. Inspired by recent advancements in human pose estimation based on Convolutional Neural Networks, it is aspired to substitute the usage of artificial marker by automatically detecting inherent keypoints of the robot representing its 2D skeleton model. In addition, current encoder readings of the robot are utilized establishing the corresponding 3D skeleton model through forward kinematics. With the help of these 2D - 3D point correspondences, an estimation of the translation and orientation deviation between robot and camera is derived solving the perspective-n-point problem. An adequate approach for markerless keypoint detection of an UR5 robot is presented and evaluated in terms of precision and pose dispersion considering a dynamically moving robot. The promising results show that the novel method works robustly and reliably as a few-shot approach and copes with false positives as well as with partly occlusions and non-detected keypoints. Further potential is identified regarding enhancing the accuracy through the use of synthetic data.

关键词： Robot kinematics Cameras Pose estimation Robot vision systems Three-dimensional displays Two dimensional displays

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Estimation of the Left Ventricle Volume Using Semantic Segmentation

Estimation of the Left Ventricle Volume Using Semantic Segme...

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International Symposium on Electronics in Marine (ELMAR)

作者： Marija Habijan Hrvoje Leventić Irena Galić Danilo Babin Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia imec-TELIN-IPI Faculty of Engineering and Architecture Ghent University Belgium

The left ventricle (LV) volume is a major indicator of heart disease. Current clinical procedure for volume estimation from magnetic resonance (MR) images include manual inspection by the experienced cardiologists, which is often a time-consuming process. This paper presents an automated method for LV volume estimation at two points in the time. The method consists of training a convolutional neural network (CNN) with the MR images from the Sunnybrook dataset. After that, the trained model is used to predict left ventricular segments in MR images from the Kaggle dataset. From predicted segments, the ventricular volumes at end-systole (ESV) and end-diastole (EDV) are calculated using numerical integration. The obtained results estimate the ESV and EDV with a mean absolute error of 14.688 and 19.222 mL, respectively.

关键词： Image segmentation Heart Training Volume measurement Magnetic resonance imaging Tensile stress Predictive models

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Augmented-Reality-Based Visualization of Navigation Data of Mobile Robots on the Microsoft Hololens - Possibilities and Limitations

arXiv

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arXiv 2019年

作者： Kästner, Linh Lambrecht, Jens Chair Industry Grade Networks and Clouds Department Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany

— The demand for mobile robots has rapidly increased in recent years due to the flexibility and high variety of application fields comparing to static robots. To deal with complex tasks such as navigation, they work with high amounts of different sensor data making it difficult to operate with for non-experts. To enhance user understanding and human robot interaction, we propose an approach to visualize the navigation stack within a cutting edge 3D Augmented Reality device - the Microsoft Hololens. Therefore, relevant navigation stack data including laser scan, environment map and path planing data are visualized in 3D within the head mounted device. Based on that prototype, we evaluate the Hololens in terms of computational capabilities and limitations for dealing with huge amount of real-time data. Results show that the Hololens is capable of a proper visualization of huge amounts of sensor data. We demonstrate a proper visualization of navigation stack data in 3D within the Hololens. However, there are limitations when transferring and displaying different kinds of data simultaneously. Copyright © 2019, The Authors. All rights reserved.

关键词： Visualization

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Towards the Usage of Synthetic Data for Marker-Less Pose Estimation of Articulated Robots in RGB Images

Towards the Usage of Synthetic Data for Marker-Less Pose Est...

引用

International Conference on Advanced Robotics (ICAR)

作者： Jens Lambrecht Linh Kästner Chair Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Technische Universität Berlin Berlin Germany

Pose estimation is a necessity for many applications in robotics incorporating interaction between the robot and external camera-equipped devices, e.g. mobile robots or Augmented Reality devices. In the practice of monocular cameras, one mostly takes advantage of pose estimation through fiducial marker detection. We propose a novel approach for marker-less robot pose estimation through monocular cameras utilizing 2D keypoint detection and 3D keypoint determination through readings from the encoders and forward kinematics. In particular, 2D-3D point correspondences enable the pose estimation through solving the Perspective-n-Point problem for calibrated cameras. The method does not rely on any depth data or initializations. The robust 2D keypoint detection is implemented by modern Convolutional Neural Networks trained on different dataset configurations of real and synthetic data in order to quantitatively evaluate robustness, precision and data efficiency. We demonstrate that the method provides robust pose estimation for random joint poses and benchmark the performance of different (synthetic) dataset configurations. Furthermore, we compare the accuracies to marker pose estimation and give an outlook towards enhancements and realtime capability.

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