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International Conference on ENERGY and ENVIRONMENT (CIEM)

作者： Fadila Tahiri Abdelkader Harrouz Virgil Dumbrava Patrice Wira M.Amine Hartani Technology and Sciences Department LDDI Laboratory Adrar Algeria Department of Hydrocarbon and Renewable Energy LDDI Laboratory Adrar Algeria Department of Electric Power Systems Polytechnic University of Bucharest Buchrest Roumanie Institute for Research in Computer Science Mathematics Automation and Signal Mulhouse France

The purpose of this research paper is to explore different approaches to maximize power point tracking (MPPT) in photovoltaic (PV) systems. In this work, we evaluate and compare incremental conductance (InC) and fuzzy logic control techniques. To extract the highest amount of power, a DC/DC boost converter is employed between the PV system and the load. Traditional MPPT techniques like InC have demonstrated limitations in effectively identifying and precisely tracking the highest peak, leading to significant power losses, Therefore, a proposed approach called fuzzy logic control is recommended, which provides several advantages including robustness against parameter variations, minimal distortion in current output, and superior reference tracking. Simulation results conducted in MATLAB confirm that the suggested control method effectively reduces steady-state fluctuations and achieves improved tracking of the maximum power point with reduced power losses compared to InC control.

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Cooperative Clustering Techniques For Space Network Scalability

Cooperative Clustering Techniques For Space Network Scalabil...

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IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW)

作者： Yael Kirkpatrick Rachel Dudukovich Prash Choksi Dominick Ta Mathematics Department Massachusetts Institute of Technology Cambridge MA Cognitive Signal Processing Branch NASA Glenn Research Center Cleveland OH Computer Science University of Houston-Clear Lake Houston TX Computer Science University of Washington Seattle WA

Routing in the space internet must face many unique challenges - from unplanned disconnections and interruptions to predictable intermittent connectivity due to high network mobility and long propagation delays. NASA’s current approach to such routing is Contact Graph Routing (CGR), using a graph formed of prescheduled communication contacts to compute routes through the network. While this approach manages to tackle issues of connectivity and propagation delays, it is a global approach that requires continuous knowledge of the entire network. In a potential future Solar Space Internet (SSI) such an approach on its own cannot scale to large networks with thousands of members. In this paper we propose clustering as a solution to CGR scalability. Clustering has been used in many networking problems as a way to subdivide the network and allow for localized routing and better scalability. Using techniques from graph theory and game theory, we explore various existing clustering algorithms and adapt them to the Contact Graph Routing setting. We propose a way to combine multiple algorithms to create a Delay Tolerant Clustering Protocol (DTCP). In addition, we explore the underlying networking mechanisms such as multicast, neighbor discovery, and software defined networking that may be used to enable DTCP.

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Projectile trajectory estimation: performance analysis of an Extended Kalman Filter and an Imperfect Invariant Extended Kalman Filter

Projectile trajectory estimation: performance analysis of an...

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International Conference on Systems and Control (ICSC)

作者： Alicia Roux Sébastien Changey Jonathan Weber Jean-Philippe Lauffenburger Research Institute in Computer Science Mathematics Automation and Signal University of Haute-Alsace Mulhouse France French-German Research Institute of Saint-Louis Saint-Louis France

ISBN: (纸本)9781665407830

This paper compares two nonlinear Kalman filters to estimate a projectile trajectory: an Extended Kalman Filter (EKF) and an Imperfect Right-Invariant Extended Kalman Filter (Imperfect R-IEKF). For this purpose, only an Inertial Measurement Unit (IMU), composed by an accelerometer and a gyrometer embedded in the projectile is considered. In addition, a misalignment between the IMU and the projectile is used as an observation. Both filters share the same evolution and measurement models.A nonlinear observability analysis is performed and suggests that the EKF creates a false observability contrary to the Imperfect R-IEKF. Furthermore, evaluated on 100 mortar fire simulations, the Imperfect R-IEKF is considerably more accurate than the EKF to estimate a projectile trajectory. These observations on accuracy and observability are explained by the Imperfect R-IEKF design, i.e. an EKF based on a nonlinear error and an update step based, in part, on an exponential application.

关键词： Measurement units Navigation Mortar Projectiles Neural networks Estimation Trajectory

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research on Path Planning of Mobile Robot Based on Reinforcement Learning

Research on Path Planning of Mobile Robot Based on Reinforce...

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Chinese automation Congress (CAC)

作者： Maoyuan Ji Jianxing Li Shanqiang Li Zhenyu Liu Jiang Song Lisang Liu Fujian Industrial Automation Technology Research and Development Center Fujian Institute of Engineering Fuzhou China Department of Computer Science and Mathematics Fujian Institute of Engineering Fuzhou China

With the continuous change of artificial intelligence technology, the study of path planning for mobile robots is no longer limited to traditional path algorithms. Reinforcement learning, as an artificial intelligence algorithm with excellent performance in the field of path planning, has also gradually become the object of research on path planning. In order to find a fast path from the starting point to the end point of a mobile robot in a complex environment, reinforcement learning is used to find a valid path by sensing the environment and continuously receiving rewarding feedback through a method of trial and error learning like humans. Therefore, this paper selects two algorithms to verify their effectiveness on the basis of building a two-dimensional grid map. The final experimental results show that both reinforcement learning algorithms can eventually avoid obstacles and plan a valid path in a complex environment through continuous learning iterations. Q-Learning also reduces the path distance by 10% and the number of convergence iterations by 82% compared to Sarsa.

关键词： Training Q-learning Simulation Buildings Robot sensing systems Path planning Sensors

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Tomo-NeRL: tomographic neural representation learning for implicit CT image reconstruction

Tomo-NeRL: tomographic neural representation learning for im...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoqin Tang Boheng Tan Yuanhao Guo Xianping Yu Jake Kendrick Mark Reynolds College of Computer and Information Science Southwest University Chongqing China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Research Institute of Highway Ministry of Transport Beijing China School of Physics Mathematics and Computing The University of Western Australia Perth Australia Centre for Advanced Technologies in Cancer Research (CATCR) Perth Australia

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

CT image reconstruction is a challenging inverse problem of estimating image intensities from sensor signals. While deep learning-based methods hold promise, they are typically classified into fully-supervised, self-supervised, and case-by-case approaches, each offering distinct advantages and limitations. Among these, case-by-case reconstruction techniques, exemplified by models like NeRP, provide the advantage of flexible data-sampling and image sizes, making them well-suited for the complex CT inverse problem. However, existing case-by-case models encounter difficulties in achieving precise reconstructions, particularly in sparse-view scenarios. To address this limitation, we propose tomo-NeRL, a novel implicit reconstruction model that incorporates tomographic information of individual pixels within the reconstruction network. By harnessing this tomo-graphic data for implicit inverse learning, tomo-NeRL enhances reconstruction quality while effectively mitigating artifacts. The core innovation of tomo-NeRL lies in defining and extracting tomographic insights, such as visual characteristics and spatial variations specific to tomographic imaging, from the sinogram data for individual pixels. Moreover, our work introduces an adaptive inversion framework that amalgamates tomographic information from diverse projection angles, constructing a latent feature space that enhances the reconstruction process. Extensive experiments unequivocally showcase tomo-NeRL’s outstanding reconstruction performance, excelling in artifact suppression and detail preservation, especially in sparse-view scenarios.

关键词： Representation learning Visualization Technological innovation Inverse problems Computed tomography Training data Tomography Reconstruction algorithms Data mining Image reconstruction

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Human Body Motion Tracking for Rehabilitation

Human Body Motion Tracking for Rehabilitation

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IEEE International Conference on Intelligent Engineering Systems (INES)

作者： Moraru Andrei Eva-H. Dulf Lehel Dénes-Fazakas Levente Kovacs Department of Automation And Applied Informatics Faculty of Automation and Computer Science Technical University of Cluj-Napoca Cluj-Napoca Romania Obuda University University Research and Innovation Center Physiological Controls Research Center Obuda University John von Neumann Faculty of Informatics Biomatics and Applied Artificial Intelligence Institute Obuda University Applied Informatics and Applied Mathematics Doctoral School Obuda University

ISBN: (数字)9798350367591

ISBN: (纸本)9798350367607

Human body motion tracking is a key technique in robotics, virtual reality and other human–computer interaction fields, for interactive mixed reality applications. Human motion tracking for rehabilitation is widely discussed by researchers in the last period, being motivated by the increased number of patients with motor function disability. For such patients rehabilitation is an important step to restore their functional capability to normal or close to normal. To reach this target, a patients’ activities need to be continuously monitored, and subsequently corrected. This involves accurate identification, tracking, and post-processing of movement. This paper thus proposes an open loop real time angle computation algorithm designed in Matlab®. Its efficacy was tested using an Arduino Nano® coupled with the MPU-6050 as the Inertial Measurement Units (IMU). The advantages of the proposed algorithm are presented by comparison with the already existing and widely used methods.

关键词： Target tracking Quaternions Virtual reality Patient rehabilitation Sensor fusion Time measurement Sensor systems

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Nature Inspired Optimization Algorithms in Fractional Order Controller Design

Nature Inspired Optimization Algorithms in Fractional Order ...

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IEEE International Conference on Intelligent Engineering Systems (INES)

作者： Eva-H. Dulf Alexandru George Berciu Lehel Dénes-Fazakas Levente Kovacs Department of Automation And Applied Informatics Faculty of Automation and Computer Science Technical University of Cluj-Napoca Cluj-Napoca Romania Obuda University University Research and Innovation Center Physiological Controls Research Center Obuda University John von Neumann Faculty of Informatics Biomatics and Applied Artificial Intelligence Institute Obuda University Applied Informatics and Applied Mathematics Doctoral School Obuda University

ISBN: (数字)9798350367591

ISBN: (纸本)9798350367607

Fractional-order PID (FOPID) controllers have gained increasing interest in control theory in recent years, mainly to improve the performance and stability of complex systems. FOPID controllers are a generalization of classical PID controllers that have both integral and derivative orders of fractional order. This means that instead of having three tuning parameters as in classical PID, there are two additional degrees of freedom to achieve the control objectives. At the same time, the structure of the PID controller, so valued in industrial applications, is retained. A preferred method for designing FOPID controllers is the use of optimization algorithms. Different objective functions are used, such as the integral of the square error (ISE), the integral of the absolute error (IAE), the integral of the time-weighted absolute error (ITAE) or the integral of the time-weighted square error (ITSE), which must be minimized in order to adjust the five unknown parameters of the FOPID controller. There are several papers discussing different optimization methods and objective functions for different applications, but there are no general recommendations to help engineers choose the right method for their design. The present research compares three of the most well-known nature-inspired optimization techniques from the point of view of a FOPID controller design tool, using all the above enumerated objective functions. The analysis is realized both for processes with large time constants (such as thermal processes) and for dynamic systems (such as mechatronic processes), presenting the advantages and disadvantages of each method.

关键词： Transient response Heuristic algorithms Sociology Linear programming Stability analysis Thermal analysis Statistics

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Individualized brain mapping for navigated neuromodulation

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Chinese Medical Journal 2024年第5期137卷 508-523页

作者： Chaohong Gao Xia Wu Xinle Cheng Kristoffer Hougaard Madsen Congying Chu Zhengyi Yang Lingzhong Fan Sino–Danish College University of Chinese Academy of SciencesBeijing 100190China Brainnetome Center National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China Department of Applied Mathematics and Computer Science Technical University of DenmarkKongens Lyngby 2800Denmark Danish Research Centre for Magnetic Resonance Centre for Functional and Diagnostic Imaging and ResearchCopenhagen University Hospital Amager and HvidovreHvidovre 2650Denmark CAS Center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Health and Life Sciences University of Health and Rehabilitation SciencesQingdaoShandong 266000China

The brain is a complex organ that requires precise mapping to understand its structure and *** atlases provide a powerful tool for studying brain circuits,discovering biological markers for early diagnosis,and developing personalized treatments for neuropsychiatric *** techniques,such as transcranial magnetic stimulation and deep brain stimulation,have revolutionized clinical therapies for neuropsychiatric ***,the lack of fine-scale brain atlases limits the precision and effectiveness of these *** in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation ***,the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized *** article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles,advantages,disadvantages,and future trends of these *** article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

关键词： Brain atlas Individualization Navigated neuromodulation Multimodal magnetic resonance imaging Transcranial magnetic stimulation Deep brain stimulation

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Total Domination, Separated-Cluster, CD-Coloring: Algorithms and Hardness

arXiv

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arXiv 2023年

作者： Antony, Dhanyamol Sunil Chandran, L. Gayen, Ankit Gosavi, Shirish Jacob, Dalu School of Data Science Indian Institute of Science Education and Research Thiruvananthapuram Kerala 695551 India Computer Science and Automation department Indian Institute of Science Karnataka Bengaluru560012 India Départment d'informatique École normale supérieure de Lyon France Department of Mathematics Indian Institute of Technology Delhi New Delhi110016 India

Domination and coloring are two classic problems in graph theory. In this paper, our major focus is on the CD-coloring problem, which incorporates the flavors of both domination and coloring in it. Let G be an undirected graph without isolated vertices. A proper vertex coloring c : V (G) → {1, 2, ..., k} of G is said to be a cd-coloring, if for each color class Cj, where j ∈ {1, 2, ..., k}, with respect to c, there exists a vertex vj in G such that Cj ⊆ N(vj). The minimum integer k for which there exists a cd-coloring of G using k colors is called the cd-chromatic number of G, denoted as χcd(G). A set S ⊆ V (G) is said to be a total dominating set, if any vertex in G has a neighbor in S. The total domination number of G, denoted as γt(G), is defined to be the minimum integer k such that G has a total dominating set of size k. A set S ⊆ V (G) is said to be a separated-cluster (also known as sub-clique) if no two vertices in S lie at a distance exactly 2 in G. The separated-cluster number of G, denoted as ωs(G), is defined to be the maximum integer k such that G has a separated-cluster of size k. In this paper, we contribute to the literature connecting CD-coloring with Total Domination and Separated-Cluster. (i) It is known that Total Domination is NP-complete for cubic graphs and triangle-free subcubic graphs. We strengthen this result by proving that both the problems CD-Coloring and Total Domination are NP-complete, and do not admit any subexponential-time algorithms on triangle-free d-regular graphs, for each fixed integer d ≥ 3, assuming the Exponential Time Hypothesis. (ii) For any graph G, it is easy to see that χcd(G) ≥ ωs(G). Analogous to the well-known notion of 'perfectness', we introduce the notion of 'cd-perfectness'. We prove a sufficient condition for a graph G to be cd-perfect (i.e. χcd(H) = ωs(H), for any induced subgraph H of G). Our sufficient condition turns out to be necessary for certain graph classes (like triangle-free graphs). (iii) The notio

关键词： Undirected graphs

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GraphReg: Dynamical Point Cloud Registration with Geometry-aware Graph signal Processing

arXiv

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arXiv 2023年

作者： Zhao, Mingyang Ma, Lei Jia, Xiaohong Yan, Dong-Ming Huang, Tiejun Institute of Automation Cas Beijing China The Baai and Institute for Artificial Intelligence Peking University Beijing China National Biomedical Imaging Center Peking University China National Engineering Research Center of Visual Technology School of Computer Science Peking University China The Academy of Mathematics and Systems Science Cas Ucas Beijing China The Nlpr Institute of Automation Cas School of Ai Ucas Beijing China

This study presents a high-accuracy, efficient, and physically induced method for 3D point cloud registration, which is the core of many important 3D vision problems. In contrast to existing physics-based methods that merely consider spatial point information and ignore surface geometry, we explore geometry aware rigid-body dynamics to regulate the particle (point) motion, which results in more precise and robust registration. Our proposed method consists of four major modules. First, we leverage the graph signal processing (GSP) framework to define a new signature, i.e., point response intensity for each point, by which we succeed in describing the local surface variation, resampling keypoints, and distinguishing different particles. Then, to address the shortcomings of current physics-based approaches that are sensitive to outliers, we accommodate the defined point response intensity to median absolute deviation (MAD) in robust statistics and adopt the X84 principle for adaptive outlier depression, ensuring a robust and stable registration. Subsequently, we propose a novel geometric invariant under rigid transformations to incorporate higher-order features of point clouds, which is further embedded for force modeling to guide the correspondence between pairwise scans credibly. Finally, we introduce an adaptive simulated annealing (ASA) method to search for the global optimum and substantially accelerate the registration process. We perform comprehensive experiments to evaluate the proposed method on various datasets captured from range scanners to LiDAR. Results demonstrate that our proposed method outperforms representative state-of-the-art approaches in terms of accuracy and is more suitable for registering large-scale point clouds. Furthermore, it is considerably faster and more robust than most competitors. Our implementation is publicly available at https://***/zikai1/GraphReg. Copyright © 2023, The Authors. All rights reserved.

关键词： Simulated annealing

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