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Next Research 2024年第2期1卷

作者： Philippe Adolphe Moulum Jean Jacques Mandeng Charles Hubert Kom Laboratory of Computer and Automatic Engineering (LGIA) Advanced Technical Teachers’ Training College Douala Cameroon Laboratory of Technology and Applied Sciences (LTSA) University Institute of Technology Douala Cameroon Laboratory of Electronics Electrical Automation and Telecommunication (LEEAT) Higher National Polytechnic School Douala Cameroon Laboratory of Signals Images and Systems (LSIS) Higher Technical Teachers’ Training College Ebolowa Cameroon

In this paper, a solution for optimal PMU placement in the southern Cameroon interconnected grid (SIG) is proposed to the issue of dynamic stability within the network. The power system under consideration relies on SCADA parameter monitoring, which offers unsynchronized measurements and inconsistent state estimation of the grid. Moreover, SCADA system's data scan rate hinders its efficiency in capturing the dynamic and transient behaviours in the power grid. The Approach in this research is based on the integer linear programming (ILP) considering the effect of a group of zero-injection buses (ZIBs). Subsequently, a comparative analysis is conducted to evaluate the performance of the ILP method in terms of the number of PMUs, the number of buses observable from one or more nodes, and the sum of redundancy index (SORI) in comparison to other optimization algorithms. The results obtained using MATLAB 2020a demonstrate that the ILP method, considering the effect of a group of ZIBs and the SORI, provides the most optimal solution. Furthermore, a PMU-based dynamic stability assessment is performed, validating the improvement of the visibility of voltage signals.

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SUPERVISED MACHINE LEARNING FOR EFFECTIVE MISSILE LAUNCH BASED ON BEYOND VISUAL RANGE AIR COMBAT SIMULATIONS

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arXiv 2022年

作者： Dantas, Joao P.A. Costa, Andre N. Medeiros, Felipe L.L. Geraldo, Diego Maximo, Marcos R.O.A. Yoneyama, Takashi Decision Support Systems Subdivision Institute for Advanced Studies Trevo Cel Av Jose A. A. do Amarante 1 Putim SP Sao Jose dos Campos12228-001 Brazil Computer Science Division Aeronautics Institute of Technology Praca Marechal Eduardo Gomes 50 Vila das Acacias SP Sao Jose dos Campos12228-900 Brazil Electronic Engineering Division Aeronautics Institute of Technology Praca Marechal Eduardo Gomes 50 Vila das Acacias SP Sao Jose dos Campos12228-900 Brazil

This work compares supervised machine learning methods using reliable data from constructive simulations to estimate the most effective moment for launching missiles during air combat. We employed resampling techniques to improve the predictive model, analyzing accuracy, precision, recall, and f1-score. Indeed, we could identify the remarkable performance of the models based on decision trees and the significant sensitivity of other algorithms to resampling techniques. The models with the best f1-score brought values of 0.379 and 0.465 without and with the resampling technique, respectively, which is an increase of 22.69%. Thus, if desirable, resampling techniques can improve the model's recall and f1-score with a slight decline in accuracy and precision. Therefore, through data obtained through constructive simulations, it is possible to develop decision support tools based on machine learning models, which may improve the flight quality in BVR air combat, increasing the effectiveness of offensive missions to hit a particular target. Copyright © 2022, The Authors. All rights reserved.

关键词： Decision trees

Bionic Tracking: Using Eye Tracking to Track Biological Cells in Virtual Reality 16th

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Bionic Tracking: Using Eye Tracking to Track Biological Cell...

Workshops held at the 16th European Conference on computer Vision, ECCV 2020

作者： Günther, Ulrik Harrington, Kyle I. S. Dachselt, Raimund Sbalzarini, Ivo F. Center for Advanced Systems Understanding Görlitz Germany Center for Systems Biology Dresden Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany Faculty of Computer Science Technische Universität Dresden Dresden Germany Cluster of Excellence Physics of Life Technische Universität Dresden Dresden Germany Virtual Technology and Design University of Idaho MoscowID United States HHMI Janelia Research Campus AshburnVA United States

ISBN: (纸本)9783030664145

We present Bionic Tracking, a novel method for solving biological cell tracking problems with eye tracking in virtual reality using commodity hardware. Using gaze data, and especially smooth pursuit eye movements, we are able to track cells in time series of 3D volumetric datasets. The problem of tracking cells is ubiquitous in developmental biology, where large volumetric microscopy datasets are acquired on a daily basis, often comprising hundreds or thousands of time points that span hours or days. The image data, however, is only a means to an end, and scientists are often interested in the reconstruction of cell trajectories and cell lineage trees. Reliably tracking cells in crowded three-dimensional space over many time points remains an open problem, and many current approaches rely on tedious manual annotation or curation. In the Bionic Tracking approach, we substitute the usual 2D point-and-click interface for annotation or curation with eye tracking in a virtual reality headset, where users follow cells with their eyes in 3D space in order to track them. We detail the interaction design of our approach and explain the graph-based algorithm used to connect different time points, also taking occlusion and user distraction into account. We demonstrate Bionic Tracking using examples from two different biological datasets. Finally, we report on a user study with seven cell tracking experts, highlighting the benefits and limitations of Bionic Tracking compared to point-and-click interfaces. © 2020, Springer Nature Switzerland AG.

关键词： Cytology

A 2-bit graphene encoder based on the plasmon-induced transparency effect and its sensing characteristics

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Results in Physics 2024年 59卷

作者： Zhu, Aijun Li, Zongteng Hou, Weigang Yang, Xinghua Cheng, Lei Hu, Cong Qiao, Fei Mahapatra, Rabi Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology Guilin 541004 China Shanxi Key Laboratory of Advanced Semiconductor Optoelectronic Devices and Integrated Systems Jincheng Shanxi 048000 China Institute of Intelligent Communication and Network Security Chongqing University of Posts and Telecommunications Chongqing 400000 China College of Science Beijing Forestry University Beijing 100083 China Jincheng Research Institute of Opto-mechatronics Industry Jincheng Shanxi 048000 China Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips Guangxi Normal University Guilin 541004 China Department of Electronic Engineering Tsinghua University Beijing 100084 China Department of Computer Science and Engineering Texas A&M University College Station 77843-3112 TX United States

A 2-bit encoder based on the plasmon-induced transparency (PIT) effect was proposed and investigated in the range from 2 to 7 THz. The Lorentz oscillation coupling model was utilized to confirm the simulation. By tuning the Fermi levels of cross1 and cross2, the 2-bit encoder was achieved. And the minimum MD was 94.73 %, the minimum ER was 12.77 dB, and the maximum IL was 0.32 dB. As a sensor, the structure had a sensitivity of up to 2.33 THz/RIU. In addition, due to the insensitivities to incidence angle and polarization angle, the encoder could be utilized to complex environments. Therefore, these results reveals that our work is significant in terahertz encoders, optical switches, sensors, slow light devices, and modulators. © 2024 The Author(s)

关键词： 2-bit encoder Metamaterial Plasmon-induced transparency (PIT) effect Plasmonic-graphene Terahertz (THz)

Satellite-based InSAR Geodesy and Collocation with GNSS

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Procedia computer Science 2024年 239卷 2329-2340页

作者： Juraj Papco Matus Bakon Lukas Kubica Gabika Belicova Branislav Droscak Martin Ferianc Martin Rovnak Antonio M. Ruiz Joaquim J. Sousa Department of Theoretical Geodesy and Geoinformatics Faculty of Civil Engineering Slovak University of Technology in Bratislava Radlinskeho 11 813 62 Bratislava Slovakia insar.sk Ltd Konstantinova 3 080 01 Presov Slovakia Department of Finance Accounting and Mathematical Methods Faculty of Management and Business University of Presov Konstantinova 16 080 01 Presov Slovakia Department of Engineering School of Sciences and Technology Universidade de Trás-os-Montes e Alto Douro Quinta de Prados 5000-801 Vila Real Portugal Geodetic and Cartographic Institute Bratislava Chlumeckeho 4 827 45 Bratislava Slovakia Department of Cartographic Geodetic and Photogrammetry Engineering University of Jaén Campus Las Lagunillas s/n 23071 Jaén Spain Center for Advanced Studies in Earth Sciences Energy and Environment (CEACTEMA) University of Jaén Campus Las Lagunillas s/n 23071 Jaén Spain Research Group RNM-282 Microgeodesia Jaén University of Jaén Campus Las Lagunillas s/n 23071 Jaén Spain Institute for Systems and Computer Engineering Technology and Science INESC-TEC 4200-465 Porto Portugal

Satellite radar interferometry (InSAR) enables large-scale monitoring of displacement with precision akin to ground-based methods. Using measurements from Sentinel-1 satellites, persistent scatterer networks cover areas up to hundreds of kilometers in size. One of the current challenges for the InSAR community is to tie these networks into a current and country-specific global terrestrial reference system through collocation with other geodetic techniques, especially Global Navigation Satellite systems (GNSS). In this work, an optimal procedure for assessing a suitable collocation properties for InSAR and GNSS techniques is discussed, along with the proposal for the methodology to determine the spatial relationship between the reference points of both techniques. The study analyzes three collocation stations in Slovakia using their radar backscattering characteristics. InSAR achieves an intrinsic accuracy of up to 1 mm but has uncertainties several orders of magnitude larger in 3D space. A collocation of InSAR measurements with GNSS can tie relative InSAR displacement estimates to an absolute reference frame.

关键词： InSAR geodesy collocation GNSS

Heliocentric Distance Dependence of Zodiacal Light Observed by Hayabusa2#

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arXiv 2023年

作者： Tsumura, Kohji Matsuura, Shuji Sano, Kei Iwata, Takahiro Yano, Hajime Kitazato, Kohei Takimoto, Kohji Yamada, Manabu Morota, Tomokatsu Kouyama, Toru Hayakawa, Masahiko Yokota, Yasuhiro Tatsumi, Eri Matsuoka, Moe Sakatani, Naoya Honda, Rie Kameda, Shingo Suzuki, Hidehiko Cho, Yuichiro Yoshioka, Kazuo Ogawa, Kazunori Shirai, Kei Sawada, Hirotaka Sugita, Seiji Department of Natural Sciences Faculty of Science and Engineering Tokyo City University Tokyo158-8557 Japan Department of Physics School of Science and Technology Kwansei Gakuin University Hyogo669-1337 Japan Department of Space Systems Engineering School of Engineering Kyushu Institute of Technology Fukuoka804-8550 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Kanagawa252-5210 Japan Department of Space and Astronautical Science The Graduate University of Advanced Studies Kanagawa240-0193 Japan Department of Computer Science and Engineering The University of Aizu Fukushima965-8580 Japan Planetary Exploration Research Center Chiba Institute of Technology Chiba275-0016 Japan Department of Earth and Planetary Science University of Tokyo Tokyo113-0033 Japan Digital Architecture Research Center National Institute of Advanced Industrial Science and Technology Tokyo135-0064 Japan Instituto de Astrofisica de Canarias University of La Laguna Tenerife Spain Geological Survey of Japan National Institute of Advanced Industrial Science and Technology Ibaraki305-8567 Japan Center for Data Science Ehime University Ehime790-8577 Japan Rikkyo University Tokyo171-8501 Japan Meiji University Kanagawa214-8571 Japan Department of Complexity Science and Engineering University of Tokyo Chiba277-8561 Japan JAXA Space Exploration Center Japan Aerospace Exploration Agency Kanagawa252-5210 Japan Kobe University Hyogo657-8501 Japan

Zodiacal light (ZL) is sunlight scattered by interplanetary dust particles (IDPs) at optical wavelengths. The spatial distribution of IDPs in the Solar System may hold an important key to understanding the evolution of the Solar System and material transportation within it. The number density of IDPs can be expressed as n(r) ∼ r−α, and the exponent α ∼ 1.3 was obtained by previous observations from interplanetary space by Helios 1/2 and Pioneer 10/11 in the 1970s and 1980s. However, no direct measurements of α based on ZL observations from interplanetary space outside Earth’s orbit have been performed since then. Here, we introduce initial results for the radial profile of the ZL at optical wavelengths observed over the range 0.76-1.06 au by ONC-T aboard the Hayabusa2# mission in 2021-2022. The ZL brightness we obtained is well reproduced by a model brightness, although there is a small excess of the observed ZL brightness over the model brightness at around 0.9 au. The radial power-law index we obtained is α = 1.30 ± 0.08, which is consistent with previous results based on ZL observations. The dominant source of uncertainty arises from the uncertainty in estimating the diffuse Galactic light (DGL). © 2023, CC BY.

关键词： Orbits

Beyond Cuts in Small Signal Scenarios Enhanced Sneutrino Detectability Using Machine Learning

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arXiv 2021年

作者： Alvestad, Daniel Fomin, Nikolai Kersten, Jörn Maeland, Steffen Strümke, Inga Department of Mathematics and Physics University of Stavanger Stavanger4021 Norway Department of Physics and Technology University of Bergen Bergen5020 Norway Korea Institute for Advanced Study Seoul02455 Korea Republic of Western Norway University of Applied Sciences Bergen5063 Norway Department of Computer Science Norwegian University of Science and Technology Trondheim7034 Norway Department of Holistic Systems SimulaMet Oslo0167 Norway

We investigate enhancing the sensitivity of new physics searches at the LHC by machine learning in the case of background dominance and a high degree of overlap between the observables for signal and background. We use two different models, XGBoost and a deep neural network, to exploit correlations between observables and compare this approach to the traditional cut-and-count method. We consider different methods to analyze the models’ output, finding that a template fit generally performs better than a simple cut. By means of a Shapley decomposition, we gain additional insight into the relationship between event kinematics and the machine learning model output. We consider a supersymmetric scenario with a metastable sneutrino as a concrete example, but the methodology can be applied to a much wider class of models. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

Diffusion-Induced Barrier Coverage of Multi-Layer Robotic Sensing Networks With Adaptive Scheduling Strategy

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International Journal of Robust and Nonlinear Control 2025年

作者： Fan, Pengyang Zhai, Chao Zhang, Hehong School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China Engineering Research Center of Intelligent Technology for Geo-exploration Ministry of Education China University of Geosciences Wuhan China College of Computer and Data Science Fuzhou University Fuzhou China

The timely identification of external intruders is crucial to the protection of concerned regions or targets against malicious attacks. Multi-agent barrier coverage provides a powerful framework for the effective deployment of sensor networks to monitor baleful intruders. This paper aims to address the barrier coverage problem of robotic sensing networks by developing a multi-layer coverage formulation. Inspired by gas diffusion, a group of robotic sensors are scattered to expand the coverage territory from a gathering spot. With the assistance of a divide-and-conquer scheme, a distributed control algorithm is proposed to partition the defence barrier into multiple curve segments and integrate it with intruder monitoring. By adaptively scheduling robotic sensors among multi-layer networks, it contributes to maximizing the joint detection probability of sensing networks against external intruders. Moreover, theoretical analysis is conducted to acquire sufficient conditions for elevating the detection quality of a multi-layer sensing network. Finally, numerical simulations and robotic experiments are carried out to demonstrate the effectiveness of the proposed barrier coverage approach. © 2025 John Wiley & Sons Ltd.

关键词： Distributed parameter control systems

Feature Guided Path Redirection for VR Navigation

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Feature Guided Path Redirection for VR Navigation

IEEE Annual International Symposium Virtual Reality

作者： Antong Cao Lili Wang Yi Liu Voicu Popescu State Key Laboratory of Virtual Reality Technology and Systems Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Beijing China Department of Computer Science Purdue University United States

ISBN: (数字)9781728156088

ISBN: (纸本)9781728156095

Path redirection for virtual reality (VR) navigation allows the user to explore a large virtual environment (VE) while the VR application is hosted in a limited physical space. Static mapping redirection methods deform the virtual scene to fit the physical space. The challenge is to deform the virtual scene in a reasonable way, making the distortions friendly to the user’s visual perception. In this paper we propose a feature-guided path redirection method that finds and takes into account the visual features of 3D virtual scenes. In a first offline step, a collection of view-independent and view-dependent visual features of the VE are extracted and stored in a visual feature map. Then, in a second offline step, the navigation path is deformed to fit in the confines of the available physical space through a mass-spring system optimization, according to distortion sensitive factors derived from the visual feature map. Finally, a novel detail preserving rendering algorithm is employed to preserve the original visual detail as the user navigates the VE on the redirected path. We tested our method on several scenes, where our method showed a reduced VE 3D mesh distortion, when compared to the path redirection methods without feature guidance.

关键词： Visualization Distortion Feature extraction Geometry Navigation Three-dimensional displays Legged locomotion

Large-scale hyperspectral image clustering using contrastive learning

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arXiv 2021年

作者： Cai, Yaoming Zhang, Zijia Liu, Yan Ghamisi, Pedram Li, Kun Liu, Xiaobo Cai, Zhihua School of Computer Science China University of Geosciences Wuhan430074 China Helmholtz Institute Freiberg for Resource Technology Freiberg09599 Germany Vienna1030 Austria College of Electronic Science and Technology National University of Defense Technology Changsha410073 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China

Clustering of hyperspectral images is a fundamental but challenging task. The recent development of hyperspectral image clustering has evolved from shallow models to deep and achieved promising results in many benchmark datasets. However, their poor scalability, robustness, and generalization ability, mainly resulting from their offline clustering scenarios, greatly limit their application to large-scale hyperspectral data. To circumvent these problems, we present a scalable deep online clustering model, named Spectral-Spatial Contrastive Clustering (SSCC), based on self-supervised learning. Specifically, we exploit a symmetric twin neural network comprised of a projection head with a dimensionality of the cluster number to conduct dual contrastive learning from a spectral-spatial augmentation pool. We define the objective function by implicitly encouraging withincluster similarity and reducing between-cluster redundancy. The resulting approach is trained in an end-to-end fashion by batch-wise optimization, making it robust in large-scale data and resulting in good generalization ability for unseen data. Extensive experiments on three hyperspectral image benchmarks demonstrate the effectiveness of our approach and show that we advance the state-of-the-art approaches by large margins. Copyright © 2021, The Authors. All rights reserved.

关键词： Spectroscopy