Gotowe bibliografie tematyczne / Advanced Cluster Analysis

Spis treści

  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji
  6. Raporty organizacyjne

Gotowa bibliografia na temat „Advanced Cluster Analysis”

Autor: Grafiati
Data publikacji: 27 lipca 2024
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Advanced Cluster Analysis"

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Feng, Guohuan, Junchen Lin, and Keyi Wang. "Researches Advanced in Clustering Algorithms." Highlights in Science, Engineering and Technology 16 (November 10, 2022): 168–77. http://dx.doi.org/10.54097/hset.v16i.2498.

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Clustering is a technique to find the intrinsic structure between data and is a fundamental problem in many data-driven application fields. Currently, clustering is generally modeled as an unsupervised learning task, aiming to mine similar features between different samples and cluster samples with similar features into clusters. Ideally, objects in the same cluster are expected to be similar in the clustering results, while objects in different clusters are quite different. This study summarizes the research status of clustering algorithms in recent years. Specifically, the relevant critical
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DAGIM, S., E. V. PUSTOVALOV, A. N. FEDORETS, and A. M. FROLOV. "EXPLORING AMORPHOUS ALLOYS: ADVANCED ELECTRON MICROSCOPY AND CLUSTER ANALYSIS." Computational nanotechnology 11, no. 1 (2024): 112–20. http://dx.doi.org/10.33693/2313-223x-2024-11-1-112-120.

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In this study, we explored the atomic structure and orderliness of amorphous alloys through advanced electron microscopy and analytical techniques. Amorphous alloys, characterized by disordered atomic structures, exhibit promising applications in technology. The research addresses a crucial knowledge gap by investigating cluster distribution, particle arrangement, and orderliness within the amorphous matrix. High-resolution electron microscopy (HREM) images are analyzed using diverse algorithms and software tools. The study establishes a correlation between angles approaching 180 degrees and i
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Yadav, Pradeep Kumar, R. S. Sikarwar, Badal Verma, Sushma Tiwari, and D. K. Shrivastava. "Genetic Divergence for Grain Yield and Its Components in Bread Wheat (Triticum aestivum L.): Experimental Investigation." International Journal of Environment and Climate Change 13, no. 5 (2023): 340–48. http://dx.doi.org/10.9734/ijecc/2023/v13i51776.

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The present investigation Comprises 34 advanced breeding lines including checks of bread wheat and experiment was conducted in a complete randomized block design with three replications at the research farm department of genetics and plant breeding, RVSKVV, B.M. College of Agriculture, Khandwa during Rabi season (November 2021 to April 2022) for estimation of the multivariate analysis of divergence. The advanced breeding lines were grouped into seven clusters. Cluster III contained the highest number of advanced breeding lines(12) and clusters V, VI, and VII contained the lowest (1 each). The
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Ochilov, Ilhom. "Improvement of financial analysis of cluster activities." BIO Web of Conferences 140 (2024): 06007. http://dx.doi.org/10.1051/bioconf/202414006007.

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This research paper addresses the critical need for an advanced framework to elevate the financial analysis of cluster activities. Clusters, defined as geographically proximate groups of interconnected companies and associated institutions in a particular field, have emerged as key drivers of economic growth. However, the existing financial analysis methods often fall short in capturing the complex dynamics and interdependencies within these clusters. The paper delves into the current challenges and limitations of conventional financial analysis in the context of cluster activities. It highlig
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Siddika, A., A. K. M. Aminul Islam, M. G. Rasul, M. A. K. Mian, and J. U. Ahmed. "GENETIC DIVERSITY IN ADVANCED GENERATION OF VEGETABLE PEA (Pisum sativum L.)." Bangladesh Journal of Plant Breeding and Genetics 27, no. 1 (2015): 9–16. http://dx.doi.org/10.3329/bjpbg.v27i1.23972.

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Twenty five advanced lines among them twelve lines obtained from the cross between Edible Podded Pea and IPSA Motorsuty-1, nine obtained from the cross between Local White and IPSA Motorsuty-3 and five parental lines were included to measure genetic diversity. The field experiment was conducted at the research farm, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh. Analysis of variance showed significant differences among the genotypes for all characters. Multivariate analysis based 14 agronomic characters indicated that the 26 genotypes fell into five distant clu
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Streur, Megan, Sarah J. Ratcliffe, David Callans, M. Benjamin Shoemaker, and Barbara Riegel. "Atrial fibrillation symptom clusters and associated clinical characteristics and outcomes: A cross-sectional secondary data analysis." European Journal of Cardiovascular Nursing 17, no. 8 (2018): 707–16. http://dx.doi.org/10.1177/1474515118778445.

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Background: Symptom clusters among adults with atrial fibrillation have previously been identified but no study has examined the relationship between symptom clusters and outcomes. Aims: The purpose of this study was to identify atrial fibrillation-specific symptom clusters, characterize individuals with each cluster, and determine whether symptom cluster membership is associated with healthcare utilization. Methods: This was a cross-sectional secondary data analysis of 1501 adults from the Vanderbilt Atrial Fibrillation Registry with verified atrial fibrillation. Self-reported symptoms were m
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Sánchez, José Luis Ausejo, Patricia Elena Ramos La Rosa, Damaris Faviola Medina Palma, Gleny Amelia Ching Campos, and Yolanda Emperatriz Maguiña Poma. "What topics are investigated in circular economy research? A co-word analysis using hierarchical clustering." Iberoamerican Journal of Science Measurement and Communication 5, no. 1 (2025): 1–11. https://doi.org/10.47909/ijsmc.1623.

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Objective. We analyzed the most researched topics related to the circular economy. To this end, we used a bibliometric approach, generating thematic maps that group the most used terms in the scientific literature. Design/Methodology/Approach. The present study focused on hierarchical clustering analysis to identify and understand interrelated themes in circular economy research. Adopting Ward's method, the analysis was performed without predetermining the number of groups. The data set was extracted from the Scopus database. Author keywords and keywords plus were used for the study. Results/D
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Dalcin, Thais, Alsones Balestrin, and Eduardo Künzel Teixeira. "Start-Up Cluster Development: A Multi-Case Analysis in the Brazilian Context." International Journal of Innovation and Technology Management 14, no. 06 (2017): 1750035. http://dx.doi.org/10.1142/s0219877017500353.

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This paper aims to contribute to knowledge on start-up cluster development by describing the core resource configurations in the development trajectory of start-up clusters in an emergent country. This research involves two start-up clusters in the Brazilian context. The results provide a framework formed by four stages that indicates the trajectory of start-up cluster development from the basic level, in which the most evident resources are tangible and endogenous, to the more advanced level, which comprises intangible and exogenous resources. In the fourth stage, start-up clusters improve re
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Randler, Christoph. "An Analysis of Heterogeneity in German Speaking Birdwatchers Reveals Three Distinct Clusters and Gender Differences." Birds 2, no. 3 (2021): 250–60. http://dx.doi.org/10.3390/birds2030018.

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The purpose of this study was to segment birdwatchers into clusters. Members from a wide range of bird related organizations, from highly specialized birders as well as Facebook bird group members were studied to provide a diverse dataset (n = 2766; 50.5% men). Birding specialization was measured with a battery of questionnaires. Birding specialization encompassed the three constructs of skill/competence, behavior, personal and behavioral commitment. Additionally, involvement, measured by centrality to lifestyle, attraction, social bonding, and identity, was used. The NbClust analyses showed t
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Meijer, Ilse, Marc M. Terpstra, Oscar Camara, Henk A. Marquering, Nerea Arrarte Terreros, and Joris R. de Groot. "Unsupervised Clustering of Patients Undergoing Thoracoscopic Ablation Identifies Relevant Phenotypes for Advanced Atrial Fibrillation." Diagnostics 15, no. 10 (2025): 1269. https://doi.org/10.3390/diagnostics15101269.

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Background/Objectives: The rate of recurrence after ablation for atrial fibrillation (AF) is considerable. Risk stratification for AF recurrence after ablation remains incompletely developed. Unsupervised clustering is a machine learning technique which might provide valuable insights in AF recurrence by identifying patient clusters using numerous clinical characteristics. We hypothesize that unsupervised clustering identifies patient clusters with different clinical phenotypes, including AF type and cardiovascular morbidities, and ablation outcomes. Methods: Baseline and procedural characteri
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Rozprawy doktorskie na temat "Advanced Cluster Analysis"

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Yiu, Man-lung. "Advanced query processing on spatial networks." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36279365.

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Yiu, Man-lung, and 姚文龍. "Advanced query processing on spatial networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36279365.

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Lärkefjord, Vivianne Cecilia Jennifer. "Rural Development, Equine Businesses in Vaggeryd’s Municipality : Empirical Analysis and Outlook." Thesis, Jönköping University, JIBS, Economics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-12013.

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<p>Vaggeryd is a rural municipality and wants to develop its rural areas. Therefore Vaggeryd’s municipality wants to become a cluster region within the equus industries and hence become an equine municipality where equestrians can live and run their businesses as well as providing for equine activities and competitions. The reason why it is interesting to create a cluster region is because it comes with benefits for the companies and it helps developing the regional economy (Enright, 1998; Porter, 2000). “Clusters lower barriers to new business formation that improve the environment for produc
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Fang, Zaili. "Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/40090.

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Model and variable selection have attracted considerable attention in areas of application where datasets usually contain thousands of variables. Variable selection is a critical step to reduce the dimension of high dimensional data by eliminating irrelevant variables. The general objective of variable selection is not only to obtain a set of cost-effective predictors selected but also to improve prediction and prediction variance. We have made several contributions to this issue through a range of advanced topics: providing a graphical view of Bayesian Variable Selection (BVS), recovering s
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Zhang, Yiqun. "Advances in categorical data clustering." HKBU Institutional Repository, 2019. https://repository.hkbu.edu.hk/etd_oa/658.

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Categorical data are common in various research areas, and clustering is a prevalent technique used for analyse them. However, two challenging problems are encountered in categorical data clustering analysis. The first is that most categorical data distance metrics were actually proposed for nominal data (i.e., a categorical data set that comprises only nominal attributes), ignoring the fact that ordinal attributes are also common in various categorical data sets. As a result, these nominal data distance metrics cannot account for the order information of ordinal attributes and may thus inappr
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Kanodia, Juveria. "Structural advances for pattern discovery in multi-relational databases /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/978.

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Zoll, Marcel Christian Robert. "A search for solar dark matter with the IceCube neutrino detector : Advances in data treatment and analysis technique." Doctoral thesis, Stockholms universitet, Fysikum, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-125341.

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There is compelling observational evidence for the existence of dark matter in the Universe, including our own Galaxy, which could possibly consist of weakly interacting massive particles (WIMPs) not contained in the standard model (SM) of particle physics. WIMPs may get gravitationally trapped inside heavy celestial bodies of ordinary matter. The Sun is a nearby candidate for such a capture process which is driven by the scattering of WIMPs on its nuclei. Forming an over-density at the Sun's core the WIMPs would self-annihilate yielding energetic neutrinos, which leave the Sun and can be dete
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CHUANG, HUI-WEN, and 莊惠雯. "The Study of Concept Advanced Interpretive Structure Analysis and Remedial Instruction on Time Concepts for Each Cluster of Second Graders." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/37600516865595542321.

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碩士<br>國立臺中教育大學<br>數學教育學系在職進修教學碩士學位班<br>97<br>The purposes of this research is to understand the learning situation of the pupils in time concepts, and to apply the concept advanced interpretive structural modeling (CAISM) to analyze the knowledge structure about these time concepts for second graders. The researcher also adopts the fuzzy cluster analysis to discuss the properties of the knowledge structure among each cluster of pupils. Then, the researcher selects two pupils from each cluster as a sample to receive individualized remedial instruction. After the instruction, the pupils take the
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Muhammad, Arshad M. "Advances in clustering based on inter-cluster mapping." Thesis, 2016. http://hdl.handle.net/1959.7/uws:37999.

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Data mining involves searching for certain patterns and facts about the structure of data within large complex datasets. Data mining can reveal valuable and interesting relationships which can improve the operations of business, health and many other disciplines. Extraction of hidden patterns and strategic knowledge from large datasets which are stored electronically, is therefore a challenge faced by many organizations. One commonly used technique in data mining for producing useful results is cluster analysis. A basic issue in cluster analysis is deciding the optimal number of clusters for
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Książki na temat "Advanced Cluster Analysis"

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ADMA 2008 (2008 Chengdu, China). Advanced data mining and applications: 4th international conference, ADMA 2008, Chengdu, China, October 8-10, 2008, proceedings. Springer, 2008.

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ADMA 2008 (2008 Chengdu, China). Advanced data mining and applications: 4th international conference, ADMA 2008, Chengdu, China, October 8-10, 2008, proceedings. Springer, 2008.

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Changjie, Tang, ed. Advanced data mining and applications: 4th international conference, ADMA 2008, Chengdu, China, October 8-10, 2008, proceedings. Springer, 2008.

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Cao, Longbing. Advanced Data Mining and Applications: 6th International Conference, ADMA 2010, Chongqing, China, November 19-21, 2010, Proceedings, Part II. Springer Berlin Heidelberg, 2010.

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Zhou, Shuigeng. Advanced Data Mining and Applications: 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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International Federation of Classification Societies. Conference. Classification, clustering and data analysis: Recent advances and applications. Springer, 2002.

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Sugato, Basu, Davidson Ian 1971-, and Wagstaff Kiri, eds. Constrained clustering: Advances in algorithms, theory, and applications. Chapman & Hall/CRC, 2008.

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International Federation of Classification Societies. Conference. Advances in data science and classification: Proceedings of the 6th Conference of the International Federation of Classification Societies (IFCS-98), Università "La Sapienza", Rome, 21-24 July, 1998. Springer, 1998.

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Ling, Charles X., Nick Cercone, Xiaofang Zhou, Xue Li, and Changjie Tang. Advanced Data Mining and Applications: 4th International Conference, ADMA 2008, Chengdu, China, October 8-10, 2008, Proceedings. Springer, 2008.

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Wang, Sen, Jianxin Li, Shuliang Wang, Xue Li, and Shaowen Qin. Advanced Data Mining and Applications: 15th International Conference, ADMA 2019, Dalian, China, November 21–23, 2019, Proceedings. Springer, 2019.

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Części książek na temat "Advanced Cluster Analysis"

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Aggarwal, Charu C. "Cluster Analysis: Advanced Concepts." In Data Mining. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14142-8_7.

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Yokoyama, Satoru. "Improving Algorithm for Overlapping Cluster Analysis." In Advanced Studies in Behaviormetrics and Data Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2700-5_20.

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Zhang, Ke-Bing, Mehmet A. Orgun, and Kang Zhang. "HOV3: An Approach to Visual Cluster Analysis." In Advanced Data Mining and Applications. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11811305_35.

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Ettetuani, Boutaina, Ahmed Moussa, and Rajaa Chahboune. "Functional Cluster Analysis of Glomerular Disease." In Advanced Intelligent Systems for Sustainable Development (AI2SD’2020). Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90633-7_99.

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Ah-Pine, Julien. "Cluster Analysis Based on the Central Tendency Deviation Principle." In Advanced Data Mining and Applications. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03348-3_5.

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Fujii, Keisuke. "Predictive Analysis and Play Evaluation with Machine Learning." In SpringerBriefs in Computer Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1445-5_3.

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Abstract This chapter examines the important role of machine learning in sports predictive analysis and play evaluation. It covers a spectrum of techniques, from traditional result analysis to advanced machine learning approaches, addressing key areas such as game result, event, and trajectory prediction, as well as action and space evaluation in team sports. The chapter introduces various datasets and methodologies, highlighting the evolution from rule-based systems to deep learning models. It explores how these techniques are applied to classify plays, cluster similar behaviors, extract mean
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Yuan, Lin, Zhijie Xu, Zhujun Li, et al. "Cluster Analysis of Scrna-Seq Data Combining Bioinformatics with Graph Attention Autoencoders and Ensemble Clustering." In Advanced Intelligent Computing in Bioinformatics. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5692-6_6.

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El-Shorbagy, M. A., A. Y. Ayoub, I. M. El-Desoky, and A. A. Mousa. "A Novel Genetic Algorithm Based k-means Algorithm for Cluster Analysis." In The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74690-6_10.

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Chang, Te-Min, Sin-Jin Lin, and Ming-Fu Hsu. "An integrated data transformation, cluster determination, and data envelopment analysis for advanced decision making." In System Innovation for a World in Transition. CRC Press, 2023. http://dx.doi.org/10.1201/9781003460763-49.

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Taşdemir, Kadim, and Erzsébet Merényi. "Cluster Analysis in Remote Sensing Spectral Imagery through Graph Representation and Advanced SOM Visualization." In Discovery Science. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88411-8_25.

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Streszczenia konferencji na temat "Advanced Cluster Analysis"

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Xu, Zhiqi, Sijiang Zhang, Yanwen Xu, Dexiang Yang, Zhanhai Zhang, and Hongyu Li. "Cluster Analysis for Transformer On-load Tap Changer Contacts Fault Identification." In 2024 IEEE 5th International Conference on Advanced Electrical and Energy Systems (AEES). IEEE, 2024. https://doi.org/10.1109/aees63781.2024.10872432.

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Li, Zengpeng, Kun Luo, Wanjun Sun, and Kai Wang. "Design of Oxide-coated Ru Cluster Electrodes and Performance Analysis in Zinc-air Batteries." In 2024 IEEE 5th International Conference on Advanced Electrical and Energy Systems (AEES). IEEE, 2024. https://doi.org/10.1109/aees63781.2024.10872467.

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Kim, Heeju, Min Cheol Kim, and Geun Young Yeom. "Dry development characteristics and surface analysis of spin-coated tin oxo cluster using Cl2 radical plasma." In Advanced Etch Technology and Process Integration for Nanopatterning XIV, edited by Efrain Altamirano-Sánchez and Nihar Mohanty. SPIE, 2025. https://doi.org/10.1117/12.3051628.

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Schlake, Georg Stefan, and Christian Beecks. "Validating Arbitrary Shaped Clusters - A Survey." In 2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2024. http://dx.doi.org/10.1109/dsaa61799.2024.10722773.

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Zhakubayev, Alibek, and Greg Hamerly. "Beta k-Means: Accelerating k-Means Using Probabilistic Cluster Filtering." In 2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2024. http://dx.doi.org/10.1109/dsaa61799.2024.10722834.

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Ayriyan, Alexander, Gheorghe Adam, Sanda Adam, Vladimir Korenkov, Alexey Lutsenko, and Valery Mitsyn. "CICC JINR Cluster 2008 Performance Improvement." In XII Advanced Computing and Analysis Techniques in Physics Research. Sissa Medialab, 2009. http://dx.doi.org/10.22323/1.070.0054.

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Shahapure, Ketan Rajshekhar, and Charles Nicholas. "Cluster Quality Analysis Using Silhouette Score." In 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2020. http://dx.doi.org/10.1109/dsaa49011.2020.00096.

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Luo, X. Q. "Parallel computing on a PC cluster." In ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH: VII International Workshop; ACAT 2000. AIP, 2001. http://dx.doi.org/10.1063/1.1405325.

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Furukawa, Masako, Yoshitomo Yaginuma, and Tsuneo Yamada. "Cluster Analysis of Learners Based on Video Annotations." In 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2018. http://dx.doi.org/10.1109/iiai-aai.2018.00193.

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Javadi, Bahman, Mohammad K. Akbari, Jemal H. Abawajy, and Saeid Nahavandi. "Multi-Cluster Computing Interconnection Network Performance Modeling and Analysis." In 2006 International Conference on Advanced Computing and Communications. IEEE, 2006. http://dx.doi.org/10.1109/adcom.2006.4289862.

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Raporty organizacyjne na temat "Advanced Cluster Analysis"

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Mishra, Ashok K., Jaweriah Hazrana, Takashi Yamano, Noriko Sato, and Babur Wasim Arif. Adoption of Farm Mechanization for Clean Air: Evidence from Farm Trials in Pakistan. Asian Development Bank, 2024. https://doi.org/10.22617/wps240587-2.

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Many rice farmers burn stubble and straw after harvest, which worsens air pollution. This study examines the impact of training on the adoption of advanced rice harvesting technologies that reduce the need for crop burning. The study uses data from a cluster randomized controlled trial in Pakistan. The results reveal that the training program improved the farm performance of rice growers. The cost–benefit analysis shows that farmers who received the training and used improved mechanical rice harvesting generated higher profits, an average gain of PRs19,784 per acre. The results highlight the p
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Bonnett, Michaela, Angela Ladetto, Meaghan Kennedy, Jasmine Fernandez, and Teri Garstka. Network Analysis of a Mobility Ecosystem in Detroit, MI. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/hejw8941https://www.orangesparkleball.com/innovation-library-blog/2024/5/30/sunbelt2024-network-analysis-of-a-mobility-ecosystem-in-detroit-mi.

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Network Analysis of a Mobility Ecosystem in Detroit, MI Background As part of a new initiative from the Global Epicenter of Mobility (GEM), organizations across many sectors in Detroit, MI, and surrounding counties are collaboratively investing in transforming the local legacy mobility industry into an inclusive advanced mobility cluster over the next 3 years. At the start of this initiative, in partnership with the research team at the Detroit Regional Partnership, a social network analysis was conducted to map the relationship between the foundational 24 organizations, the greater coalition,
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Bonnett, Michaela, Angela Ladetto, Meaghan Kennedy, Jasmine Fernandez, and Teri Garstka. Network Analysis of a Mobility Ecosystem in Detroit, MI. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/hejw8941.

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Network Analysis of a Mobility Ecosystem in Detroit, MI Background As part of a new initiative from the Global Epicenter of Mobility (GEM), organizations across many sectors in Detroit, MI, and surrounding counties are collaboratively investing in transforming the local legacy mobility industry into an inclusive advanced mobility cluster over the next 3 years. At the start of this initiative, in partnership with the research team at the Detroit Regional Partnership, a social network analysis was conducted to map the relationship between the foundational 24 organizations, the greater coalition,
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Ross, Elizabeth, Gregory Pogue, Jill Engel-Cox, and Thushara Gunda. Community Archetypes in the Permian Basin and their Relationship to Energy Resources. Permian Energy Development Lab, 2024. http://dx.doi.org/10.70223/aftg267.

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The Permian Energy Development Lab (PEDL) is a new research coalition in West Texas and Southeastern New Mexico, managed by a consortium of higher education, public sector, civic, community, and philanthropic organizations . PEDL’s mission is to catalyze advanced energy research, prepare new energy professionals and entrepreneurs, and create value for energy communities. To meet the three parts of this mission, a comprehensive facts-based understanding of the diverse communities within the large Permian region, not relying on impressions or preconceptions, is essential. Therefore, this report
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Playing the long game: Experimenting Smart Specialisation in the Basque Country 2016-2019. Universidad de Deusto, 2019. http://dx.doi.org/10.18543/ajzo9759.

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Smart specialization strategies (RIS3) represent arguably the most ambitious regional innovation policy ever launched in the EU and as such have posed a major challenge for governments. While developing a smart specialization strategy has not been an entirely new adventure for the Basque Country, which has consistently pursued an industrial strategy over more than thirty years, there is enough novelty in the RIS3 process to pose a challenge even for mature regional innovation policy systems. This report builds on previous analysis of the early implementation of the Basque Country RIS3 (Arangur
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