Academic literature on the topic 'Topological change detection'

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Journal articles on the topic "Topological change detection"

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KUBOTA, NAOYUKI, HIROYUKI KOJIMA, NAOHIDE AIZAWA, and DALAI TANG. "DYNAMIC TOPOLOGICAL VISUALIZATION OF CHANGE IN PERCEPTUAL INFORMATION OF PARTNER ROBOTS." International Journal of Information Acquisition 05, no. 03 (September 2008): 247–58. http://dx.doi.org/10.1142/s0219878908001673.

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This paper proposes a method for topologically visualizing the perceptual information of a partner robot. First, we explain the methods for human detection, human motion extraction, and object recognition. Next, we explain the perceptual system of the robot based on the detected human and objects. We propose a topological visualization method based on a spring-mass-damper system according to the perceptual information. Finally, we show several experimental results of the proposed method, and the proposed method enables a human to understand what the robot perceives in the interaction with the human and environment.
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Wang, Xianghai, Wei Cheng, Yining Feng, and Ruoxi Song. "TSCNet: Topological Structure Coupling Network for Change Detection of Heterogeneous Remote Sensing Images." Remote Sensing 15, no. 3 (January 20, 2023): 621. http://dx.doi.org/10.3390/rs15030621.

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With the development of deep learning, convolutional neural networks (CNNs) have been successfully applied in the field of change detection in heterogeneous remote sensing (RS) images and achieved remarkable results. However, most of the existing methods of heterogeneous RS image change detection only extract deep features to realize the whole image transformation and ignore the description of the topological structure composed of the image texture, edge, and direction information. The occurrence of change often means that the topological structure of the ground object has changed. As a result, these algorithms severely limit the performance of change detection. To solve these problems, this paper proposes a new topology-coupling-based heterogeneous RS image change detection network (TSCNet). TSCNet transforms the feature space of heterogeneous images using an encoder–decoder structure and introduces wavelet transform, channel, and spatial attention mechanisms. The wavelet transform can obtain the details of each direction of the image and effectively capture the image’s texture features. Unnecessary features are suppressed by allocating more weight to areas of interest via channels and spatial attention mechanisms. As a result of the organic combination of a wavelet, channel attention mechanism, and spatial attention mechanism, the network can focus on the texture information of interest while suppressing the difference of images from different domains. On this basis, a bitemporal heterogeneous RS image change detection method based on the TSCNet framework is proposed. The experimental results on three public heterogeneous RS image change detection datasets demonstrate that the proposed change detection framework achieves significant improvements over the state-of-the-art methods.
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Feilhauer, J., M. Zelent, Zhiwang Zhang, J. Christensen, and M. Mruczkiewicz. "Unidirectional spin-wave edge modes in magnonic crystal." APL Materials 11, no. 2 (February 1, 2023): 021104. http://dx.doi.org/10.1063/5.0134099.

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We present a numerical demonstration of magnonic crystals hosting unidirectional, topologically protected edge states. The magnonic crystal is formed of dipolarly coupled Permalloy triangles. We show that due to the geometry of the block, the size of the structure can be scaled up. In addition, edge states can be found over a wide frequency range. Experimental detection of edge excitations in the considered system can be done with state-of-the-art techniques. Thus, we demonstrate a proof-of-concept magnonic Chern topological insulator nanostructure with simple geometry feasible for experimental realization. Furthermore, by tuning the strength of the perpendicular magnetic field, we induce a topological phase transition, which results in the change of direction of the topological edge state. Then, we demonstrate the magnonic switch based on this effect.
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Wang, Xiaodong, Dongbao Zhao, Xingze Li, Nan Jia, and Li Guo. "Change Detection and Incremental Updates for Multi-Source Road Networks Considering Topological Consistency." ISPRS International Journal of Geo-Information 14, no. 1 (December 24, 2024): 2. https://doi.org/10.3390/ijgi14010002.

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Vector road networks are vital components of intelligent transportation systems and electronic navigation maps. There is a pressing need for efficient and rapid dynamic updates for road network data. In this paper, we propose a series of methods designed specifically for geometric change detection and the topological consistency updating of multi-source vector road networks without relying on complicated road network matching. For geometric change detection, we employ buffer analysis to compare various sources of vector road networks, differentiating between newly added, deleted, and unchanged road features. Furthermore, we utilize road shape similarity analysis to detect and recognize partial matching relationships between different road network sources. For incremental updates, we define topology consistency and propose three distinct methods for merging road nodes, aiming to preserve the topological integrity of the road network to the greatest extent possible. To address geometric conflicts and topological inconsistencies, we present a fusion and update method specifically tailored for partially matched road features. In order to verify the proposed methods, a road central line network with a scale of 1:10000 from the official institution is employed to geometrically update the commercial navigation road network of a similar scale in the remote area. The experiment results indicate that our method achieves an impressive 91.7% automation rate in detecting geometric changes for road features. For the remaining 8.3% of road features, our method provides suggestions on potential geometric changes, albeit necessitating manual verification and assessment. In terms of the incremental updating of the road network, approximately 89.2% of the data can be seamlessly updated automatically using our methods, while a minor 10.8% requires manual intervention for road updates. Collectively, our methods expedite the updating cycle of vector road network data and facilitate the seamless sharing and integrated utilization of multi-source road network data.
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Yu, Lanlan, Biao Wang, Luojie Huang, Zhen Dai, Yang Yang, Yan Chen, and Ping Li. "Detecting change points in dynamic networks by measuring cluster stability." International Journal of Modern Physics C 32, no. 09 (May 18, 2021): 2150123. http://dx.doi.org/10.1142/s0129183121501230.

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Clustering patterns are ubiquitously present in a variety of networked systems, and may change with the evolution of network topology. Probing into the cluster structures can shed light on the change of the entire network, especially those sudden changes emerging in the process of network evolution. Though abundant researches have been done in detecting the changes of dynamic networks, more precisely, change points at which the network topology experiences abrupt changes, most of the existing methods focus on local changes (e.g. edges change) that are commonly mixed with noise, giving rise to high false positive reports. Different from the previous work, here we inspect the topological changes from mesoscale clusters of dynamic networks, which will reduce the perturbation of link variation to detection accuracy. Towards this end, we look for the invariant clusters of nodes during the observation window in dynamic networks and propose a new measure to quantify the stability of node clusters with respect to the invariant clustering patterns. Then the change of dynamic networks at mesoscale can be captured by comparing the variations of stability measures. In the light of the proposed measurement, we design a change-point detection algorithm and conduct extensive experiments on synthetic and real-life datasets to demonstrate the effectiveness of our method. The results show the outperformance of our method in identifying change points, compared to several baseline methods.
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Gu, Kongjing, Liang Yan, Xiang Li, Xiaojun Duan, and Jingjie Liang. "Change point detection in multi-agent systems based on higher-order features." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 11 (November 2022): 111102. http://dx.doi.org/10.1063/5.0126848.

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Change point detection (CPD) for multi-agent systems helps one to evaluate the state and better control the system. Multivariate CPD methods solve the [Formula: see text] time series well; however, the multi-agent systems often produce the [Formula: see text] dimensional data, where [Formula: see text] is the dimension of multivariate observations, [Formula: see text] is the total observation time, and [Formula: see text] is the number of agents. In this paper, we propose two valid approaches based on higher-order features, namely, the Betti number feature extraction and the Persistence feature extraction, to compress the [Formula: see text]-dimensional features into one dimension so that general CPD methods can be applied to higher-dimensional data. First, a topological structure based on the Vietoris–Rips complex is constructed on each time-slice snapshot. Then, the Betti number and persistence of the topological structures are obtained to separately constitute two feature matrices for change point estimates. Higher-order features primarily describe the data distribution on each snapshot and are, therefore, independent of the node correspondence cross snapshots, which gives our methods unique advantages in processing missing data. Experiments in multi-agent systems demonstrate the significant performance of our methods. We believe that our methods not only provide a new tool for dimensionality reduction and missing data in multi-agent systems but also have the potential to be applied to a wider range of fields, such as complex networks.
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Shao, Pan, Wenzhong Shi, Zhewei Liu, and Ting Dong. "Unsupervised Change Detection Using Fuzzy Topology-Based Majority Voting." Remote Sensing 13, no. 16 (August 10, 2021): 3171. http://dx.doi.org/10.3390/rs13163171.

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Remote sensing change detection (CD) plays an important role in Earth observation. In this paper, we propose a novel fusion approach for unsupervised CD of multispectral remote sensing images, by introducing majority voting (MV) into fuzzy topological space (FTMV). The proposed FTMV approach consists of three principal stages: (1) the CD results of different difference images produced by the fuzzy C-means algorithm are combined using a modified MV, and an initial fusion CD map is obtained; (2) by using fuzzy topology theory, the initial fusion CD map is automatically partitioned into two parts: a weakly conflicting part and strongly conflicting part; (3) the weakly conflicting pixels that possess little or no conflict are assigned to the current class, while the pixel patterns with strong conflicts often misclassified are relabeled using the supported connectivity of fuzzy topology. FTMV can integrate the merits of different CD results and largely solve the conflicting problem during fusion. Experimental results on three real remote sensing images confirm the effectiveness and efficiency of the proposed method.
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Qu, Song, Yuqing Du, Mu Zhu, Guan Yuan, Jining Wang, Yanmei Zhang, and Xiangyu Duan. "Dynamic Community Detection Based on Evolutionary DeepWalk." Applied Sciences 12, no. 22 (November 11, 2022): 11464. http://dx.doi.org/10.3390/app122211464.

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To fully characterize the evolution process of the topological structure of dynamic communities, we propose a dynamic community detection based on Evolutionary DeepWalk (DEDW) for the high-dimensional data and dynamic characteristics. First, DEDW solves the problem of data sparseness in the process of dynamic network data representation through graph embedding. Then, DEDW uses the DeepWalk algorithm to generate node embedding feature vectors based on the characteristics of the stable change of the community structure; finally, DEDW integrates historical network structure information to generate evolutionary graph features and implements dynamic community detection with the K-means algorithm. Experiments show that DEDW can mine the time-smooth change characteristics of dynamic communities, solve the problem of data sparseness in the process of node embedding, fully consider historical structure information, and improve the accuracy and stability of dynamic community detection.
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Tribot-La-Spiere, M. "Естественнонаучные и философские аспекты единства живописи и музыки: взгляд через призму искусственного интеллекта." Studia Culturae, no. 57 (December 26, 2023): 97. http://dx.doi.org/10.31312/2310-1245-2023-57-97-106.

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This article discusses a philosophical description of the unity of painting and music through the prism of the natural-science phenomenon of the generation of phonon oscillations by the surface of a painting surface. A method is proposed for using artificial intelligence in the automated detection of phonon oscillations, which consists in a matrix recording of dynamic two-dimensional light scattering, convolution of the matrix into topological indices, and sonification of the change in indices over time. We have developed the new method for controlling surface phonon oscillations based on diffuse reflection kinetics. The specialized software “Vidan” records the kinetics of changes with 10 topological indices, which reflects the propagation of a phonon wave on the surface during capture and inelastic scattering of secondary cosmic rays [3]. To control the state of the surface, either the fingerprint of 10 topological descriptors is used (this analysis is automated through the “Atrium” remote software), or a spectral analysis of the distribution of descriptor values in time is carried out. In art the method was used for generation the "digital" passport (including the topological descriptors) of new paintings in order to control the appearance of copies. The algorithm for converting phonon oscillations of a painting leads to the generation of a unique melody. In this case, the main part of the creative activity belongs not to the composer, but to artificial intelligence, which generates a melody based on the chemical composition of the paint material of the picture and the method of applying the painting layer (that is, the artist's "hands"). The material heritage of the painter's work continues to generate new works of art “offline”, while artificial intelligence acts only as a way of detecting and sonification of the natural vibrations of the surface of the picture. It is shown that each painting generates its own unique melody. This uniqueness made it possible to propose an original system for checking the authenticity of works of art: for new works of artists. A cloud-based automated control system "Atrium" has been implemented, which allows tracking any logistical movements of the picture and the change of owner according to the topological musical digital passport of the picture generated by its surface.
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Soroush, M. Z., K. Maghooli, N. F. Pisheh, M. Mohammadi, P. Z. Soroush, and P. Tahvilian. "Detection of Change to SSVEPs Using Analysis of Phase Space Topological Features: A Novel Approach." Neurophysiology 51, no. 3 (May 2019): 180–90. http://dx.doi.org/10.1007/s11062-019-09811-x.

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Dissertations / Theses on the topic "Topological change detection"

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Jiang, Jixiang. "Specifying and Detecting Topological Changes to an Areal Object." Fogler Library, University of Maine, 2009. http://www.library.umaine.edu/theses/pdf/JiangJ2009.pdf.

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Gaide, Maxime. "Modélisation et rejeu basés sur des règles." Electronic Thesis or Diss., Chasseneuil-du-Poitou, Ecole nationale supérieure de mécanique et d'aérotechnique, 2024. http://www.theses.fr/2024ESMA0026.

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La construction d’un objet complexe est un processus fastidieux, impliquant des cycles successifs d’essais et de corrections. Pour alléger la difficulté de la conception, les systèmes de modélisation paramétrique actuels proposent une fonctionnalité de rejeu permettant de regénérer un objet grâce à l’édition de ses paramètres. Cependant, ce processus nécessite soit une détection des changements topologiques basée sur une analyse complète de l’objet modifié, ce qui est coûteux ; soit ces changements sont codés explicitement dans les opérations, ce qui peut être source d’erreurs. Pour répondre à ces limites, nos travaux se concentrent sur le développement d’un système de modélisation basé sur des règles, permettant de rejouer un processus constructif, notamment avec l’ajout, la suppression et le déplacement d’opérations. Nous considérons des opérations formalisées par des règles de transformation de graphe Jerboa. Notre première contribution est une analyse syntaxique des opérations permettant de détecter les changements topologiques (création, scission, fusion, etc.). Cette analyse des règles est statique et indépendante des objets auxquels celles-ci sont appliquées. Ainsi, les changements topologiques peuvent être détectés et suivis automatiquement. Dans certains cas définis, une analyse localisée au sein de l’objet permet de confirmer ou non les changements détectés. La seconde contribution s’appuie sur notre approche de détection des changements topologiques pour proposer un mécanisme de rejeu. Un processus constructif est une suite d’opérations appliquées sur des entités topologiques spécifiques. Rejouer un processus constructif nécessite de résoudre le problème classique de la nomination persistante des entités topologiques dans un modèle géométrique. Pour répondre à ce problème, nous proposons une reconstitution de l’historique des entités topologiques référencées dans le processus constructif. Chaque entité possède une histoire unique qui l’identifie. Grâce à ce mécanisme, nous proposons un référencement robuste des entités topologiques lors du rejeu. Notre troisième contribution vise à étendre notre mécanisme de rejeu aux scripts de règles qui permettent de construire des opérations complexes à l’aide de structures de contrôles. Nous proposons pour cela d’utiliser les scripts Jerboa avec des structures de contrôles classiques telles que les itérations et les alternatives. Nous proposons une extension de notre mécanisme de rejeu pour inclure ces structures de contrôle, offrant ainsi une plus grande flexibilité dans la modélisation et la gestion des opérations complexes
Designing a complex object is a tedious process involving repeated cycles of trial and error. In order to alleviate such a difficulty in the designing process, current parametric modelling systems offer some reevaluation mechanism sallowing a user to rebuild an object based on the editing of its parameters. However, such a process requires either processing an entire mesh in order to detect topological changes, which is computationally expensive, or hard-coding the changes in the modelling operations, which is computationally efficient but increases the risks to introduce detection errors. To address these limitations, our works focus on the development of a rule-based modelling system dedicated to the reevaluation of modelling processes. In particular, this system allows the addition, deletion and reordering of the operations defining those processes. We consider operations formalised with Jerboa’s graph transformation rules. Our first contribution is the syntactic analysis of the operations allowing for the detection of topological changes (creation, split, merge, and so on). These analyses are statically performed on rules, independently of the object onto which they are being applied. Thus, topological changes can be automatically detected and tracked. In some defined cases, a localised analysis performed within the object can assert whether the event has occurred or not. Our second contribution makes use of our topological changes detection approach in order to offer a reevaluation mechanism. Considering that a modelling process is a record of operations sequentially applied on specific topological entities, reevaluating a modelling process first requires solving the long-standing problem of persistently naming topological entities in a geometric model. To achieve this goal, we offer to reconstitute the histories of topological entities referenced within a modelling process. Each entity can be identified through its history, which is unique. With this mechanism, we reference topological entities in a robust way throughout reevaluation. Our third contribution aims to extend our reevaluation mechanism to include scripts of rules which can be used to create more complex operations. The Jerboa script language makes it possible to create such scripts with usual control structures such as alternatives and iterations. We extend our reevaluation mechanism by including these control structures, hence, enabling the user with greater versatility in modelling and managing complex operations
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Lin, Yu-Hsiang, and 林昱享. "Scene Change Detection and Topological Map Construction Using Omnidirectional Image Sequences." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/42802399464870601675.

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碩士
國立中正大學
電機工程研究所
100
Place recognition and location are important problems in mobile robotic research. In this thesis, we present a novel scene recognition technique that resembles human thinking-"scene change detection".Our semantic scene descriptor is based on SURF and Extend-HCT features.We build a scene change judgment system by analyzing parameter of Extend-HCT codewords.Then we use our algorithm to mark the interested regions and construct the topological map after the autonomous mobile robot passing through an unknown path.For a robot to have a topological map in an unknown environment is just like voyaging in the vast sea with compass.In the future, if a robot goes through this environment again, it can use the topological map which we built before, and assist the robot for place recognition, location and navigation tasks.
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Books on the topic "Topological change detection"

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Kenyon, Ian R. Quantum 20/20. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198808350.001.0001.

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This text reviews fundametals and incorporates key themes of quantum physics. One theme contrasts boson condensation and fermion exclusivity. Bose–Einstein condensation is basic to superconductivity, superfluidity and gaseous BEC. Fermion exclusivity leads to compact stars and to atomic structure, and thence to the band structure of metals and semiconductors with applications in material science, modern optics and electronics. A second theme is that a wavefunction at a point, and in particular its phase is unique (ignoring a global phase change). If there are symmetries, conservation laws follow and quantum states which are eigenfunctions of the conserved quantities. By contrast with no particular symmetry topological effects occur such as the Bohm–Aharonov effect: also stable vortex formation in superfluids, superconductors and BEC, all these having quantized circulation of some sort. The quantum Hall effect and quantum spin Hall effect are ab initio topological. A third theme is entanglement: a feature that distinguishes the quantum world from the classical world. This property led Einstein, Podolsky and Rosen to the view that quantum mechanics is an incomplete physical theory. Bell proposed the way that any underlying local hidden variable theory could be, and was experimentally rejected. Powerful tools in quantum optics, including near-term secure communications, rely on entanglement. It was exploited in the the measurement of CP violation in the decay of beauty mesons. A fourth theme is the limitations on measurement precision set by quantum mechanics. These can be circumvented by quantum non-demolition techniques and by squeezing phase space so that the uncertainty is moved to a variable conjugate to that being measured. The boundaries of precision are explored in the measurement of g-2 for the electron, and in the detection of gravitational waves by LIGO; the latter achievement has opened a new window on the Universe. The fifth and last theme is quantum field theory. This is based on local conservation of charges. It reaches its most impressive form in the quantum gauge theories of the strong, electromagnetic and weak interactions, culminating in the discovery of the Higgs. Where particle physics has particles condensed matter has a galaxy of pseudoparticles that exist only in matter and are always in some sense special to particular states of matter. Emergent phenomena in matter are successfully modelled and analysed using quasiparticles and quantum theory. Lessons learned in that way on spontaneous symmetry breaking in superconductivity were the key to constructing a consistent quantum gauge theory of electroweak processes in particle physics.
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Book chapters on the topic "Topological change detection"

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Jiang, Jixiang, and Michael Worboys. "Preliminaries for Topological Change Detection Using Sensor Networks." In GeoSensor Networks, 112–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02903-5_11.

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Abera Kolech, Birhanu. "Magnetic Skyrmions and Quasi Particles: A Review on Principles and Applications." In History of Magnetic Skyrmions - From Physics to Applications [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.110448.

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Skyrmions are topologically nontrivial, magnetic quasiparticles that are characterized by a topological charge. The field of magnetic skyrmions has been actively investigated across a wide range of topics during the last two decades. We mainly reviewed and discussed magnetic skyrmions, and quasiparticles: reviews on principles and applications. We concentrated on theoretical discoveries and advances in magnetic skyrmions, topological effects, the skyrmion Hall effect, and the dynamics of skyrmions. The skyrmion Hall effect causes a transverse deflection of skyrmions when they are driven by currents, whereas the first additional contribution to the Hall effect of electrons in the presence of a topologically non-trivial spin texture may become beneficial for detecting skyrmions. This means that when a current is applied along the racetrack, skyrmions are pushed toward the edge, causing pinning or possibly the loss of data. This is one of the reasons why there is currently no prototype for a spintronic device based on skyrmions. The anti-ferromagnetic and ferrimagnetic skyrmions were then discussed in relation to spintronics. Finally, we reviewed several potential applications based on magnetic skyrmions, including skyrmion race track memory, a skyrmion logical device, a skyrmion magnonic crystal, and skyrmion-based radio frequency devices.
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Conference papers on the topic "Topological change detection"

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Jiang, Huaqing, Yumiao Li, Xiaojun Ying, Kun Yin, Hui Yu, and Wanshu Xiong. "Sensitive Refractive Index Response based on Two Types of Valley Hall Topological Edge States." In Frontiers in Optics, JD4A.78. Washington, D.C.: Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.jd4a.78.

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A novel topological insulator cavity utilizing two types of edge states is proposed. Due to the slow light effect, its transmission spectrum is anticipated to undergo significant changes depending on the pure medium occupying the cavity region. This innovation holds promise for applications in refractive index detection within the THz band.
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Su, Chang, and Aishy Amer. "Topological-Stabilization Based Threshold Quantization for Robust Change Detection." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4379318.

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Nourani-Vatani, N., and C. Pradalier. "Scene change detection for vision-based topological mapping and localization." In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iros.2010.5652556.

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Min-Liang Wang and Huei-Yung Lin. "A hull census transform for scene change detection and recognition towards topological map building." In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iros.2010.5652817.

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Makenova, Nailia A., Feodor Kanev, Valerii Aksenov, Igor Veretekhin, Feodor Starikov, Yurii Dolgopolov, and Aleksander Kopalkin. "Detection of an optical vortex topological charge and coordinates." In XXIV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, edited by Oleg A. Romanovskii and Gennadii G. Matvienko. SPIE, 2018. http://dx.doi.org/10.1117/12.2504323.

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Tang, Ao, feng shen, Bin Lan, YingJian Ge, Jian Li, and YiHui Duan. "Measuring the topological charge of vortex beams by using Shack-Hartmann wavefront sensor with sector microlens array." In Sixth Symposium on Novel Photoelectronic Detection Technology and Application, edited by Huilin Jiang and Junhao Chu. SPIE, 2020. http://dx.doi.org/10.1117/12.2565218.

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Giustolisi, O., Z. Kapelan, and D. Savic. "Detecting Topological Changes in Large Water Distribution Networks." In Water Distribution Systems Analysis 2008. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41024(340)75.

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Myers, Audun, and Firas A. Khasawneh. "Dynamic State Analysis of a Driven Magnetic Pendulum Using Ordinal Partition Networks and Topological Data Analysis." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22441.

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Abstract The use of complex networks for time series analysis has recently shown to be useful as a tool for detecting dynamic state changes for a wide variety of applications. In this work, we implement the commonly used ordinal partition network to transform a time series into a network for detecting these state changes for the simple magnetic pendulum. The time series that we used are obtained experimentally from a base-excited magnetic pendulum apparatus, and numerically from the corresponding governing equations. The magnetic pendulum provides a relatively simple, non-linear example demonstrating transitions from periodic to chaotic motion with the variation of system parameters. For our method, we implement persistent homology, a shape measuring tool from Topological Data Analysis (TDA), to summarize the shape of the resulting ordinal partition networks as a tool for detecting state changes. We show that this network analysis tool provides a clear distinction between periodic and chaotic time series. Another contribution of this work is the successful application of the networks-TDA pipeline, for the first time, to signals from non-autonomous nonlinear systems. This opens the door for our approach to be used as an automatic design tool for studying the effect of design parameters on the resulting system response. Other uses of this approach include fault detection from sensor signals in a wide variety of engineering operations.
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Jiang, Jixiang, and Michael Worboys. "Detecting basic topological changes in sensor networks by local aggregation." In the 16th ACM SIGSPATIAL international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1463434.1463440.

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Giustolisi, Orazio, Zoran Kapelan, and Dragan Savic. "A Simulation Model for Detecting Topological Changes in a Water Distribution Network." In World Environmental and Water Resources Congress 2007. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40927(243)504.

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