Relevant bibliographies by topics / Trajectory search

Academic literature on the topic 'Trajectory search'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Trajectory search"

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Xie, Dong, Feifei Li, and Jeff M. Phillips. "Distributed trajectory similarity search." Proceedings of the VLDB Endowment 10, no. 11 (August 2017): 1478–89. http://dx.doi.org/10.14778/3137628.3137655.

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Tedjopurnomo, David Alexander, Xiucheng Li, Zhifeng Bao, Gao Cong, Farhana Choudhury, and A. K. Qin. "Similar Trajectory Search with Spatio-Temporal Deep Representation Learning." ACM Transactions on Intelligent Systems and Technology 12, no. 6 (December 31, 2021): 1–26. http://dx.doi.org/10.1145/3466687.

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Similar trajectory search is a crucial task that facilitates many downstream spatial data analytic applications. Despite its importance, many of the current literature focus solely on the trajectory’s spatial similarity while neglecting the temporal information. Additionally, the few papers that use both the spatial and temporal features based their approach on a traditional point-to-point comparison. These methods model the importance of the spatial and temporal aspect of the data with only a single, pre-defined balancing factor for all trajectories, even though the relative spatial and temporal balance can change from trajectory to trajectory. In this article, we propose the first spatio-temporal, deep-representation-learning-based approach to similar trajectory search. Experiments show that utilizing both features offers significant improvements over existing point-to-point comparison and deep-representation-learning approach. We also show that our deep neural network approach is faster and performs more consistently compared to the point-to-point comparison approaches.
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Shao, Xiao Fang, and Hong Chen. "Directional Search for Spiral Trajectory Extraction." Applied Mechanics and Materials 713-715 (January 2015): 577–80. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.577.

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Spiral trajectory curves often occur in modern production lines. In this paper we propose a curve inference method for spiral trajectory extraction. Based on the tensor voting result of the original images, the method performs a post-processing stage and a directional neighborhood searching process which takes into account the turning angle of the pixels on a certain curve. At last the method is tested on several real images.
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Chen, Wei, Lei Zhao, Jia-Jie Xu, Guan-Feng Liu, Kai Zheng, and Xiaofang Zhou. "Trip Oriented Search on Activity Trajectory." Journal of Computer Science and Technology 30, no. 4 (July 2015): 745–61. http://dx.doi.org/10.1007/s11390-015-1558-6.

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Chen, Mingming, Ning Wang, Guofeng Lin, and Jedi S. Shang. "Network-Based Trajectory Search over Time Intervals." Big Data Research 25 (July 2021): 100221. http://dx.doi.org/10.1016/j.bdr.2021.100221.

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Qi, Shuyao, Dimitris Sacharidis, Panagiotis Bouros, and Nikos Mamoulis. "Snapshot and continuous points-based trajectory search." GeoInformatica 21, no. 4 (August 17, 2016): 669–701. http://dx.doi.org/10.1007/s10707-016-0267-9.

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Zhao, Peng, Weixiong Rao, Chengxi Zhang, Gong Su, and Qi Zhang. "SST: Synchronized Spatial-Temporal Trajectory Similarity Search." GeoInformatica 24, no. 4 (April 28, 2020): 777–800. http://dx.doi.org/10.1007/s10707-020-00405-y.

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Wang, Hongzhi, and Amina Belhassena. "Parallel trajectory search based on distributed index." Information Sciences 388-389 (May 2017): 62–83. http://dx.doi.org/10.1016/j.ins.2017.01.016.

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Psiaki, M. L., and K. H. Park. "Parallel solver for trajectory optimization search directions." Journal of Optimization Theory and Applications 73, no. 3 (June 1992): 519–46. http://dx.doi.org/10.1007/bf00940054.

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Alexandropoulos, Stamatios-Aggelos N., Panos M. Pardalos, and Michael N. Vrahatis. "Dynamic search trajectory methods for global optimization." Annals of Mathematics and Artificial Intelligence 88, no. 1-3 (August 27, 2019): 3–37. http://dx.doi.org/10.1007/s10472-019-09661-7.

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Dissertations / Theses on the topic "Trajectory search"

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Niiya, Craig K. (Craig Koji). "An application of the A* search to trajectory optimization." Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/42444.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1990.
Title as it appears in the M.I.T. Graduate List, June, 1990: An application of the A* search technique to trajectory optimization.
Includes bibliographical references (leaves 87-88).
by Craig K. Niiya.
M.S.
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Tejedor, Vincent. "Random walks and first-passage properties : trajectory analysis and search optimization." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2012. http://tel.archives-ouvertes.fr/tel-00721294.

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Les propriétés de premier passage en général, et parmi elles le temps moyen de premier passage (MFPT), sont fréquemment utilisées dans les processus limités par la diffusion. Les processus réels de diffusion ne sont pas toujours Browniens : durant les dernières années, les comportements non-Browniens ont été observés dans un nombre toujours croissant de systèmes. Les milieux biologiques sont un exemple frappant où ce genre ce comportement a été observé de façon répétée. Nous présentons dans ce manuscrit une méthode basée sur les propriétés de premier passage permettant d'obtenir des informations sur le processus réel de diffusion, ainsi que sur l'environnement où évolue le marcheur aléatoire. Cette méthode permet de distinguer trois causes possibles de sous-diffusion : les marches aléatoires en temps continu, la diffusion en milieu fractal et le mouvement brownien fractionnaire. Nous étudions également l'efficacité des processus de recherche sur des réseaux discrets. Nous montrons comment obtenir les propriétés de premier passage sur réseau afin d'optimiser ensuite le processus de recherche, et obtenons un encadrement général du temps moyen de premier passage global (GMFPT). Grâce à ces résultats, nous estimons l'impact sur l'efficacité de recherche de plusieurs paramtres, notamment la connectivité de la cible, la mobilité de la cible ou la topologie du réseau.
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Gois, Francisco Nauber Bernardo. "Search-based stress test : an approach applying evolutionary algorithms and trajectory methods." Universidade de Fortaleza, 2017. http://dspace.unifor.br/handle/tede/103338.

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Made available in DSpace on 2019-03-30T00:01:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-09-22
Some software systems must respond to thousands or millions of concurrent requests. These systems must be properly tested to ensure that they can function correctly under the expected load. Performance degradation and consequent system failures usually arise in stressed conditions. Stress testing subjects the program to heavy loads. Stress tests di¿er from other kinds of testing in that the system is executed on its breakpoints, forcing the application or the supporting infrastructure to fail. The search for the longest execution time is seen as a discontinuous, nonlinear, optimization problem, with the input domain of the system under test as a search space. In this context, search-based testing is viewed as a promising approach to verify timing constraints. Search-based software testing is the application of metaheuristic search techniques to generate software tests. The test adequacy criterion is transformed into a ¿tness function and a set of solutions in the search space is evaluated with respect to the ¿tness functionusingametaheuristic. Search-basedstresstestinginvolves¿ndingthebest-andworst-case executiontimestoascertainwhethertimingconstraintsareful¿lled. ServiceLevelAgreements (SLAs) are documents that specify realistic performance guarantees as well as penalties for non-compliance. SLAsaremadebetweenprovidersandcustomersthatincludeservicequality, resourcescapability,scalability,obligations,andconsequencesincaseofviolations. Satisfying SLAisofgreatimportanceandachallengingissue. Themainmotivationofthisthesisisto¿nd theadequateresponsetimeofSLAsusingStressTesting. Thisthesisaddressesthreeapproaches insearch-basedstresstests. First,HybridmetaheuristicusesTabuSearch,SimulatedAnnealing, andGeneticAlgorithmsinacollaborativemanner. Second,anapproachcalledHybridQusesa reinforcementlearningtechniquetooptimizethechoiceofneighboringsolutionstoexplore,reducingthetimeneededtoobtainthescenarioswiththelongestresponsetimeintheapplication. The best solutions found by HybridQ were on average 5.98% better that achieved by the Hybrid approach without Q-learning. Third, the thesis investigates the use of the multi-objective NSGA-II,SPEA2,PAESandMOEA/Dalgorithms. MOEA/Dmetaheuristicsobtainedthebest hypervolume value when compared with other approaches. The collaborative approach using MOEA/D and HybridQ improves the hypervolume values obtained and found more relevant workloadsthanthepreviousexperiments. AtoolnamedIAdapter,aJMeterpluginforperformingsearch-basedstresstests,wasdevelopedandusedtoconductalltheexperiments. Keywords: Search-based Testing, Stress Testing, Multi-objective metaheuristics, Hybrid metaheuristics,ReinforcementLearning.
Alguns sistemas de software devem responder a milhares ou milhões de requisições simultâneos. Tais sistemas devem ser devidamente testados para garantir que eles possam funcionar corretamente sob uma carga esperada. Normalmente, a degradação do desempenho e consequentes falhas do sistema geralmente ocorrem em condições de estresse. No teste de estresse o sistema é submetido a cargas de trabalho acima dos resquistos não funcionais estabelecidos. Os testes de estresse diferem de outros tipos de testes em que o sistema é executado em seus pontos de interrupção, forçando o aplicativo ou a infra-estrutura de suporte a falhar. Testes de estresse podem ser vistos como um problema de otimização descontínuo, não-linear, comodomínio de entrada do sistema em test ecomo espaço de busca. Neste contexto,ostestes baseados em busca (search-based tests) são vistos como uma abordagem promissora para veri¿car as restrições de tempo. O teste de software baseado em busca é a aplicação de técnicas de pesquisa metaheurística para gerar testes de software. O critério de adequação do teste é transformado em uma função objetivo e um conjunto de soluções no espaço de busca é avaliado em relação à função objetivo usando uma metaheurística. Otestedeestressebaseadoembusca envolve encontrar os tempos de execução melhores e piores para veri¿car se as restrições de tempo são cumpridas. Os acordos de nível de serviço (SLA) são documentos que especi¿cam garantias de desempenho realistas, bem como penalidades por incumprimento. Os SLAs são feitos entre provedores e clientes que incluem qualidade do serviço, capacidade de recursos, escalabilidade, obrigações e consequencias em caso de violação. Satisfazer o SLA é de grande importância e um problema desa¿ador. A principal motivação desta tese é encontrar o tempo de resposta adequado dos SLAs usando teste de estresse. Esta tese apresenta três abordagens em testes de estresse baseados em busca. Primeiro, a metaheurística híbrida usa Tabu Search, Simulated Annealing e Algoritmos Genéticos de forma colaborativa. Em segundo lugar, uma abordagem chamada HybridQ usa uma técnica de aprendizado de reforço para otimizar a escolha de soluções vizinhas para explorar, reduzindo o tempo necessário para obter os cenários com o tempo de resposta mais longo na aplicação. As melhores soluções encontradas pelo HybridQ foram em média 5,98 % melhores que alcançadas pela abordagem híbrida sem Qlearning. Em terceiro lugar, a tese investiga o uso dos algoritmos multi-objetivos NSGA-II, SPEA2, PAES e MOEA/D. A metaheurística MOEA/D obteve o melhor valor de hipervolume quando comparada com outras abordagens. A abordagem colaborativa usand oMOEA/DeHybridQ melhora os valores de hipervolume obtidos e encontrou workloads mais relevantes do que as experiências anteriores. Uma ferramenta chamada IAdapter, um plugin JMeter para realizar testes de esforço baseados em busca, foi desenvolvida e usada para realizar todas as experiências. Palavras-chave: Search-basedTesting,StressTesting,Multi-objective metaheuristics,Hybridmetaheuristics,ReinforcementLearning
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Bykov, Yuri. "Time-predefined and trajectory-based search : single and multiobjective approaches to exam timetabling." Thesis, University of Nottingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289449.

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Bilal, Mohd. "A Heuristic Search Algorithm for Asteroid Tour Missions." Thesis, Luleå tekniska universitet, Rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-71361.

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Since the discovery of Ceres, asteroids have been of immense scientific interest and intrigue. They hold answers to many of the fundamental questionsabout the formation and evolution of the Solar System. Therefore, a missionsurveying the asteroid belt with close encounter of carefully chosen asteroidswould be of immense scientific benefit. The trajectory of such an asteroidtour mission needs to be designed such that asteroids of a wide range ofcompositions and sizes are encountered; all with an extremely limited ∆Vbudget.This thesis presents a novel heuristic algorithm to optimize trajectoriesfor an asteroid tour mission with close range flybys (≤ 1000 km). The coresearch algorithm efficiently decouples combinatorial (i.e. choosing the asteroids to flyby)and continuous optimization (i.e. optimizing critical maneuversand events) of what is essentially a mixed integer programming problem.Additionally, different methods to generate a healthy initial population forthe combinatorial optimization are presented.The algorithm is used to generate a set of 1800 feasible trajectories withina 2029+ launch frame. A statistical analysis of these set of trajectories isperformed and important metrics for the search are set based on the statistics.Trajectories allowing flybys to prominent families of asteroids like Flora andNysa with ∆V as low as 4.99 km/s are obtained.Two modified implementations of the algorithm are presented. In a firstiteration, a large sample of trajectories is generated with a limited numberof encounters to the most scientifically interesting targets. While, a posteriori, trajectories are filled in with as many small targets as possible. Thisis achieved in two different ways, namely single step extension and multiplestep extension. The former fills in the trajectories with small targets in onestep, while the latter optimizes the trajectory by filling in with one asteroid per step. The thesis also presents detection of asteroids for successfullyperforming flybys. A photometric filter is developed which prunes out badlyilluminated asteroids. The best trajectory is found to perform well againstthis filter such that nine out of the ten planned flybys are feasible.
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Gu, Tianyu. "Improved Trajectory Planning for On-Road Self-Driving Vehicles Via Combined Graph Search, Optimization & Topology Analysis." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/794.

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Trajectory planning is an important component of autonomous driving. It takes the result of route-level navigation plan and generates the motion-level commands that steer an autonomous passenger vehicle (APV). Prior work on solving this problem uses either a sampling-based or optimization-based trajectory planner, accompanied by some high-level rule generation components.
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Verkuil, Robert(Robert H. ). "Applicability of deep learning approaches to non-convex optimization for trajectory-based policy search." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121761.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 75-76).
Trajectory optimization is a powerful tool for determining good control sequences for actuating dynamical systems. In the past decade, trajectory optimization has been successfully used to train and guide policy search within deep neural networks via optimizing over many trajectories simultaneously, subject to a shared neural network policy constraint. This thesis seeks to understand how this specific formulation converges in comparison to known globally optimal policies for simple classical control systems. To do so, results from three lines of experimentation are presented. First, trajectory optimization control solutions are compared against globally optimal policies determined via value iteration on simple control tasks. Second, three systems built for parallelized, non-convex optimization across trajectories with a shared neural network constraint are described and analyzed. Finally, techniques from deep learning known to improve convergence speed and quality in non-convex optimization are studied when applied to both the shared neural networks and the trajectories used to train them.
by Robert Verkuil.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Raquet, John F. (John Foster). "Six degree of freedom trajectory planner for spacecraft proximity operations using an A* node search." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/17287.

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Fang, Zhicheng. "Trajectory-based systematic framework for obtaining sub-paths." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/232642/1/Zhicheng_Fang_Thesis.pdf.

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This thesis develops a systematic framework to identify sub-paths using trajectories, which includes data preparation, raw sub-path generation, progression ratio evaluation and commonality factor-based final sub-path extraction. The results of the empirical study based on real traffic data in Brisbane Australia demonstrate the validity of the methodology, which has significant value for the identification of key corridors.
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Kimball, Nicholas. "Utilizing Trajectory Optimization In The Training Of Neural Network Controllers." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2071.

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Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum system, it learns an effective policy up to three times faster than the other algorithms. In the cartpole system, it learns an effective policy up to nearly fifteen times faster than the other algorithms.
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Books on the topic "Trajectory search"

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McCray, Ken, and KDC Publishing. In Search of a Faith Mentor: The Discovery Will Change the Trajectory and Quality of Your Life. KDC Enterprises LLC, 2022.

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Trencsényi, Balázs, Michal Kopeček, Luka Lisjak Gabrijelčič, Maria Falina, Mónika Baár, and Maciej Janowski. In Search of a New Ideology. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198829607.003.0006.

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The chapter shows that despite the adoption of Western norms in the official sphere, the populist criticism of this pro-European trajectory with its concomitant economic and administrative policies became increasingly central to domestic politics. The “culture wars” erupting in the late 1990s and early 2000s were rooted in the radicalization of conservativism, questioning the legitimacy of post-transition regimes. In turn, the left also underwent a profound reconfiguration, with the mainstream post-communists becoming fervent advocates of liberalization and the emerging new left, feminism, and environmentalism becoming increasingly anti-liberal. The book closes with an overview of the symbolic geographical debates on Europeanness, and also registers the growth of Euroskepticism after 2000. Critically engaging with the application of postcolonial theory in discussions on the region’s relationship to the West it also points to the cyclical occurrences of discourses on “catching up” and alienation which seem to indicate a longue durée regional pattern.
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United States. National Aeronautics and Space Administration., ed. A six degree of freedom, plume-fuel optimal trajectory planner for spacecraft proximity operations using an A* node search. Cambridge, Mass: Charles Stark Draper Laboratory, Inc., 1994.

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Faiz, Asma. In Search of Lost Glory. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197567135.001.0001.

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This book traces the trajectory of Sindhi nationalism in its quest for lost glory. It examines the Sindhi nationalist movement through its various stages, ranging from pre-partition identity construction in pursuit of the separation of Sindh from Bombay, to the post-partition travails of a community which lost its identity and its capital as a result of the arrival of millions of migrants from India (Muhajirs) and of the actions of an over-bearing central government. Going beyond the state and its power play, the book examines the long history of Sindhi-Muhajir contestation for resources in the post-partition period. The book develops a comprehensive profile of the agency of nationalist parties in Sindh, including the Sindhudesh detour and the later fragmentation of the Jiye Sind movement, which was followed by the emergence of new parties. The author also analyzes the dual role of the Pakistan Peoples Party (PPP) as an ethnic entrepreneur inside the province while operating as a federal party outside Sindh. The book covers nationalist contention at three levels: the struggle for power between Sindh and a dominant Centre; the inter-ethnic conflict between Sindhis and Muhajirs; and the intra-ethnic contestation between the Sindhi nationalists themselves and the PPP.
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Hilliard, Kathleen. Finding Slave Voices. Edited by Mark M. Smith and Robert L. Paquette. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199227990.013.0032.

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The aims of this article are twofold. First, it traces the broad contours of the historiography, examining the myriad ways in which scholars have come to incorporate the slave perspective in studies of slavery. Having established the general trajectory of this search through the 1970s, it examines the ways in which slaves' voices have led scholars to important insights in one particular area of study — the political, social, and economic implications of the slaves' internal economy.
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Hughes, Christopher W. Japan’s Remilitarization and Constitutional Revision. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252037894.003.0007.

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This chapter reevaluates the use of remilitarization in order to understand the contemporary trajectory of Japanese security policy and to demonstrate its strengths. The application of the term “remilitarization” can provide a powerful analytical and theoretical framework to discern the nature and significance of Japan's changing security policy. First, the concept of remilitarization assists in identifying those military components present in all societies, including Japan, that are subject to contestation and thus open the way to substantive change in military security policy. Second, the concept of remilitarization as a dynamic process over time is an important reminder to search for the possibilities of significant change in a society's military stance.
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Mukherjee, Supriya. Indian Historical Writing since 1947. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199225996.003.0026.

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This chapter focuses on Indian historical writing. The end of colonial rule in 1947 was a turning point in Indian historical writing and culture. History emerged as a professional discipline with the establishment of new state-sponsored institutions of research and teaching. Attached to the institutionalization was the political imperative of a newly independent nation in search of a coherent and comprehensive historical narrative to support its nation-building efforts. At the same time, there was a desire to establish an autonomous Indian perspective, free of colonial constraints and distortions. In this, post-independence historiography owed much to earlier strands of nationalist historiography. During the first two decades after independence, three main trajectories of historical writing emerged: an official and largely secular nationalist historiography, a cultural nationalist historiography with strong religious overtones, and a critical Marxist trajectory based on analyses of social forms.
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Gunter, Barrie. The Study of Online Relationships and Dating. Edited by William H. Dutton. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199589074.013.0009.

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This chapter, which investigates a range of evidence about online dating behaviour, and a synthesis of approaches to research in this area, also evaluates the nature of the market and the experiences of those who have engaged in online dating. Further issues linked with patterns of online self-disclosure and self-presentation, and concerns about deception in online dating, are then assessed. Corporate data have indicated that the online dating business is mostly on an upward trajectory. Data show greater age difference tolerance of online daters and a willingness to adopt a broader selection of partners compared with offline-only daters. Many online dating site users increasingly fail to be fully engaged by sites that offer search opportunities for partner matches using check-box profiling. The issues of deception and trust in relation to personal profiles have been regarded as problematic factors that could cause tension among online daters.
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Zhou, Taomo. Migration in the Time of Revolution. Cornell University Press, 2019. http://dx.doi.org/10.7591/cornell/9781501739934.001.0001.

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This book examines how two of the world's most populous countries interacted between 1945 and 1967, when the concept of citizenship was contested, political loyalty was in question, identity was fluid, and the boundaries of political mobilization were blurred. The book asks probing questions of this important period in the histories of the People's Republic of China and Indonesia. What was it like to be a youth in search of an ancestral homeland that one had never set foot in, or an economic refugee whose expertise in private business became undesirable in one's new home in the socialist state? What ideological beliefs or practical calculations motivated individuals to commit to one particular nationality while forsaking another? As the book demonstrates, the answers to such questions about “ordinary” migrants are crucial to a deeper understanding of diplomatic relations between the two countries. The book argues that migration and the political activism of the ethnic Chinese in Indonesia were important historical forces in the making of governmental relations between Beijing and Jakarta after World War II. It highlights the agency and autonomy of individuals whose life experiences were shaped by but also helped shape the trajectory of bilateral diplomacy. These ethnic Chinese migrants and settlers were, the book contends, not passively acted upon but actively responding to the developing events of the Cold War. The book bridges the fields of diplomatic history and migration studies by reconstructing the Cold War in Asia as social processes from the ground up.
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Book chapters on the topic "Trajectory search"

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Qi, Shuyao, Panagiotis Bouros, Dimitris Sacharidis, and Nikos Mamoulis. "Efficient Point-Based Trajectory Search." In Advances in Spatial and Temporal Databases, 179–96. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22363-6_10.

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Chen, Wei, Lei Zhao, Xu Jiajie, Kai Zheng, and Xiaofang Zhou. "Ranking Based Activity Trajectory Search." In Web Information Systems Engineering – WISE 2014, 170–85. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11749-2_14.

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Ma, Xiang, Xu Chen, Ashfaq Khokhar, and Dan Schonfeld. "Motion Trajectory-Based Video Retrieval, Classification, and Summarization." In Video Search and Mining, 53–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12900-1_3.

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Lee, Ki-Young, Chae-Hun Lim, Jeong-Joon Kim, Sun-Jin Oh, and Jeong-Jin Kang. "Similar Trajectory Search for Video Data." In Communications in Computer and Information Science, 222–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35600-1_33.

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Guo, Kaiyang, Rong-Hua Li, Shaojie Qiao, Zhenjun Li, Weipeng Zhang, and Minhua Lu. "Efficient Order-Sensitive Activity Trajectory Search." In Lecture Notes in Computer Science, 391–405. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68783-4_27.

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Broilo, Mattia, Nicola Piotto, Giulia Boato, Nicola Conci, and Francesco G. B. De Natale. "Object Trajectory Analysis in Video Indexing and Retrieval Applications." In Video Search and Mining, 3–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12900-1_1.

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Anjum, Nadeem, and Andrea Cavallaro. "Trajectory Clustering for Scene Context Learning and Outlier Detection." In Video Search and Mining, 33–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12900-1_2.

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Zheng, Jianbing, Shuai Wang, Cheqing Jin, Ming Gao, Aoying Zhou, and Liang Ni. "Trajectory Similarity Search with Multi-level Semantics." In Algorithms and Architectures for Parallel Processing, 602–19. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95391-1_38.

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Tao, Jiachun, Zhicheng Pan, Junhua Fang, Pingfu Chao, Pengpeng Zhao, and Jiajie Xu. "Misty: Microservice-Based Streaming Trajectory Similarity Search." In Service-Oriented Computing, 155–70. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20984-0_11.

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Tangpattanakul, Panwadee, Anupap Meesomboon, and Pramin Artrit. "Optimal Trajectory of Robot Manipulator Using Harmony Search Algorithms." In Recent Advances In Harmony Search Algorithm, 23–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-04317-8_3.

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Conference papers on the topic "Trajectory search"

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Amini, Shahriyar, A. J. Brush, John Krumm, Jaime Teevan, and Amy Karlson. "Trajectory-aware mobile search." In the 2012 ACM annual conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2207676.2208644.

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Pelekis, Nikos, Ioannis Kopanakis, Gerasimos Marketos, Irene Ntoutsi, Gennady Andrienko, and Yannis Theodoridis. "Similarity Search in Trajectory Databases." In 14th International Symposium on Temporal Representation and Reasoning (TIME'07). IEEE, 2007. http://dx.doi.org/10.1109/time.2007.59.

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Wang, Haibo, and Kuien Liu. "User oriented trajectory similarity search." In the ACM SIGKDD International Workshop. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2346496.2346513.

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Frentzos, Elias, Kostas Gratsias, and Yannis Theodoridis. "Index-based Most Similar Trajectory Search." In 2007 IEEE 23rd International Conference on Data Engineering. IEEE, 2007. http://dx.doi.org/10.1109/icde.2007.367927.

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Tiakas, Eleftherios, Apostolos Papadopoulos, Alexandros Nanopoulos, Yannis Manolopoulos, Dragan Stojanovic, and Slobodanka Djordjevic-Kajan. "Trajectory Similarity Search in Spatial Networks." In 2006 10th International Database Engineering and Applications Symposium (IDEAS'06). IEEE, 2006. http://dx.doi.org/10.1109/ideas.2006.48.

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Lin-Yu Tseng and Chun Chen. "Multiple trajectory search for multiobjective optimization." In 2007 IEEE Congress on Evolutionary Computation. IEEE, 2007. http://dx.doi.org/10.1109/cec.2007.4424940.

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Teng, Yiping, Zhan Shi, Fanyou Zhao, Guohui Ding, Li Xu, and Chunlong Fan. "Signature-Based Secure Trajectory Similarity Search." In 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2021. http://dx.doi.org/10.1109/trustcom53373.2021.00043.

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Yin, Wenjin, Jingyuan Zhang, and Jitao Li. "The maneuver search and the maneuver search trajectory framework of search heavy torpedo." In Seventh International Symposium on Precision Mechanical Measurements, edited by Liandong Yu. SPIE, 2016. http://dx.doi.org/10.1117/12.2216374.

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Zheng, Bolong, Nicholas Jing Yuan, Kai Zheng, Xing Xie, Shazia Sadiq, and Xiaofang Zhou. "Approximate keyword search in semantic trajectory database." In 2015 IEEE 31st International Conference on Data Engineering (ICDE). IEEE, 2015. http://dx.doi.org/10.1109/icde.2015.7113349.

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Shang, Shuo, Ruogu Ding, Bo Yuan, Kexin Xie, Kai Zheng, and Panos Kalnis. "User oriented trajectory search for trip recommendation." In the 15th International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2247596.2247616.

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