Literatura académica sobre el tema "NP aggregation"
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Artículos de revistas sobre el tema "NP aggregation"
Wu, Xinghuo, Zhiwei Liao, Kun Wang, Wenbin Hua, Xianzhe Liu, Yu Song, Yukun Zhang, Shuhua Yang y Cao Yang. "Targeting the IL-1β/IL-1Ra pathways for the aggregation of human islet amyloid polypeptide in an ex vivo organ culture system of the intervertebral disc". Experimental & Molecular Medicine 51, n.º 9 (septiembre de 2019): 1–16. http://dx.doi.org/10.1038/s12276-019-0310-7.
Texto completoAminfar, Habib, Nayyer Razmara y Mousa Mohammadpourfard. "Molecular Dynamics Study of Aggregation in Nanofluid Flow: Effects of Liquid–Nanoparticle Interaction Strength and Particles Volume Fraction". International Journal of Applied Mechanics 07, n.º 01 (febrero de 2015): 1550010. http://dx.doi.org/10.1142/s1758825115400104.
Texto completoHelman, Paul. "A family of NP-complete data aggregation problems". Acta Informatica 26, n.º 5 (marzo de 1989): 485–99. http://dx.doi.org/10.1007/bf00289148.
Texto completoKataoka, Keita, Kazuhiro Nakabayashi, Chen-Tsyr Lo y Hideharu Mori. "Threonine-Based Stimuli-Responsive Nanoparticles with Aggregation-Induced Emission-Type Fixed Cores for Detection of Amines in Aqueous Solutions". Polymers 14, n.º 7 (27 de marzo de 2022): 1362. http://dx.doi.org/10.3390/polym14071362.
Texto completoNestele, Jeremy A., Anne-Katrin Rohlfing, Valerie Dicenta, Alexander Bild, Daniela Eißler, Frederic Emschermann, Marcel Kremser et al. "Characterization of GPVI- or GPVI-CD39-Coated Nanoparticles and Their Impact on In Vitro Thrombus Formation". International Journal of Molecular Sciences 23, n.º 1 (21 de diciembre de 2021): 11. http://dx.doi.org/10.3390/ijms23010011.
Texto completoDomingos, Dayane Gonzaga, Rosana Oliveira Henriques, Jéssica Antunes Xavier, Nelson Libardi Junior y Rejane Helena Ribeiro da Costa. "Increasing activated sludge aggregation by magnetite nanoparticles addition". Water Science and Technology 79, n.º 5 (11 de febrero de 2019): 993–99. http://dx.doi.org/10.2166/wst.2019.055.
Texto completoRobinson, D. A., J. Duay, A. M. Kondajji y K. J. Stevenson. "Mechanistic aspects of hydrazine-induced Pt colloid instability and monitoring aggregation kinetics with nanoparticle impact electroanalysis". Faraday Discussions 193 (2016): 293–312. http://dx.doi.org/10.1039/c6fd00121a.
Texto completoBroumi, Said, Irfan Deli y Florentin Smarandache. "Neutrosophic Parametrized Soft Set Theory and its Decision Making". International Frontier Science Letters 1 (julio de 2014): 1–10. http://dx.doi.org/10.18052/www.scipress.com/ifsl.1.1.
Texto completoSchroer, Martin A., Po-Sheng Hu, Natalia Tomasovicova, Marianna Batkova, Katarina Zakutanska, Po-Yi Wu y Peter Kopcansky. "Dependence of the Nanoscale Composite Morphology of Fe3O4 Nanoparticle-Infused Lysozyme Amyloid Fibrils on Timing of Infusion: A Combined SAXS and AFM Study". Molecules 26, n.º 16 (11 de agosto de 2021): 4864. http://dx.doi.org/10.3390/molecules26164864.
Texto completoDICKINSON, Natalie T., Elliott K. JANG y Richard J. HASLAM. "Activation of cGMP-stimulated phosphodiesterase by nitroprusside limits cAMP accumulation in human platelets: effects on platelet aggregation". Biochemical Journal 323, n.º 2 (15 de abril de 1997): 371–77. http://dx.doi.org/10.1042/bj3230371.
Texto completoTesis sobre el tema "NP aggregation"
Cao, Xue-Zheng, Holger Merlitz, Chen-Xu Wu, Goran Ungar y Jens-Uwe Sommer. "A theoretical study of dispersion-to-aggregation of nanoparticles in adsorbing polymers using molecular dynamics simulations". Royal Society of Chemistry, 2016. https://tud.qucosa.de/id/qucosa%3A36333.
Texto completoBrancotte, Bryan. "Agrégation de classements avec égalités : algorithmes, guides à l'utilisateur et applications aux données biologiques". Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112184/document.
Texto completoThe rank aggregation problem is to build consensus among a set of rankings (ordered elements). Although this problem has numerous applications (consensus among user votes, consensus between results ordered differently by different search engines ...), computing an optimal consensus is rarely feasible in cases of real applications (problem NP-Hard). Many approximation algorithms and heuristics were therefore designed. However, their performance (time and quality of product loss) are quite different and depend on the datasets to be aggregated. Several studies have compared these algorithms but they have generally not considered the case (yet common in real datasets) that elements can be tied in rankings (elements at the same rank). Choosing a consensus algorithm for a given dataset is therefore a particularly important issue to be studied (many applications) and it is an open problem in the sense that none of the existing studies address it. More formally, a consensus ranking is a ranking that minimizes the sum of the distances between this consensus and the input rankings. Like much of the state-of-art, we have considered in our studies the generalized Kendall-Tau distance, and variants. Specifically, this thesis has three contributions. First, we propose new complexity results associated with cases encountered in the actual data that rankings may be incomplete and where multiple items can be classified equally (ties). We isolate the different "features" that can explain variations in the results produced by the aggregation algorithms (for example, using the generalized distance of Kendall-Tau or variants, pre-processing the datasets with unification or projection). We propose a guide to characterize the context and the need of a user to guide him into the choice of both a pre-treatment of its datasets but also the distance to choose to calculate the consensus. We finally adapt existing algorithms to this new context. Second, we evaluate these algorithms on a large and varied set of datasets both real and synthetic reproducing actual features such as similarity between rankings, the presence of ties and different pre-treatments. This large evaluation comes with the proposal of a new method to generate synthetic data with similarities based on a Markov chain modeling. This evaluation led to the isolation of datasets features that impact the performance of the aggregation algorithms, and to design a guide to characterize the needs of a user and advise him in the choice of the algorithm to be use. A web platform to replicate and extend these analyzes is available (rank-aggregation-with-ties.lri.fr). Finally, we demonstrate the value of using the rankings aggregation approach in two use cases. We provide a tool to reformulating the text user queries through biomedical terminologies, to then query biological databases, and ultimately produce a consensus of results obtained for each reformulation (conqur-bio.lri.fr). We compare the results to the references platform and show a clear improvement in quality results. We also calculate consensus between list of workflows established by experts in the context of similarity between scientific workflows. We note that the computed consensus agree with the expert in a very large majority of cases
Kuo, Tung-Wei y 郭桐惟. "Construction of Data Aggregation Trees with Minimum Energy Cost in Wireless Sensor Networks : NP-Completeness and Approximation Algorithms". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/28746415043469926968.
Texto completoCapítulos de libros sobre el tema "NP aggregation"
Ghedjati, Fatima y Safa Khalouli. "A Hybrid Meta-Heuristic to Solve a Multi-Criteria HFS Problem". En Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance, 252–74. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2086-5.ch009.
Texto completoActas de conferencias sobre el tema "NP aggregation"
Kuo, Tung-Wei y Ming-Jer Tsai. "On the construction of data aggregation tree with minimum energy cost in wireless sensor networks: NP-completeness and approximation algorithms". En IEEE INFOCOM 2012 - IEEE Conference on Computer Communications. IEEE, 2012. http://dx.doi.org/10.1109/infcom.2012.6195659.
Texto completoFan, Yi, Nan Li, Chengqian Li, Zongjie Ma, Longin Jan Latecki y Kaile Su. "Restart and Random Walk in Local Search for Maximum Vertex Weight Cliques with Evaluations in Clustering Aggregation". En Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/87.
Texto completoInformes sobre el tema "NP aggregation"
Chefetz, Benny, Baoshan Xing, Leor Eshed-Williams, Tamara Polubesova y Jason Unrine. DOM affected behavior of manufactured nanoparticles in soil-plant system. United States Department of Agriculture, enero de 2016. http://dx.doi.org/10.32747/2016.7604286.bard.
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