Relevant bibliographies by topics / Global Partition Methods

Academic literature on the topic 'Global Partition Methods'

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Published: 6 September 2023

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Journal articles on the topic "Global Partition Methods"

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HU, TIANMING, JINZHI XIONG, and GENGZHONG ZHENG. "SIMILARITY-BASED COMBINATION OF MULTIPLE CLUSTERINGS." International Journal of Computational Intelligence and Applications 05, no. 03 (September 2005): 351–69. http://dx.doi.org/10.1142/s1469026805001660.

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Consensus clustering refers to combining multiple clusterings over a common set of objects into a single consolidated partition. After introducing the distribution-based view of partitions, we propose a series of entropy-based distance functions for comparing various partitions. Given a candidate partition set, consensus clustering is then formalized as an optimization problem of searching for a centroid partition with the smallest distance to that set. In addition to directly selecting the local centroid candidate, we also present two combining methods for the global centroid based on the new similarity determined by the whole candidate set. The centroid partition is likely to be top/middle-ranked in terms of closeness to the true partition. Finally we evaluate its effectiveness on both artificial and real datasets, with candidates from either the full space or the subspace.
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ZHAO, YAN, YIYU YAO, and JINGTAO YAO. "LEVEL-WISE CONSTRUCTION OF DECISION TREES FOR CLASSIFICATION." International Journal of Software Engineering and Knowledge Engineering 16, no. 01 (February 2006): 103–26. http://dx.doi.org/10.1142/s0218194006002690.

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A partition-based framework is presented for a formal study of classification problems. An information table is used as a knowledge representation, in which all basic notions are precisely defined by using a language known as the decision logic language. Solutions to, and solution space of, classification problems are formulated in terms of partitions. Algorithms for finding solutions are modelled as searching in a space of partitions under the refinement order relation. We focus on a particular type of solutions called conjunctively definable partitions. Two level-wise methods for decision tree construction are investigated, which are related to two different strategies: local optimization and global optimization. They are not in competition with, but are complementary to each other. Experimental results are reported to evaluate the two methods.
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Efendiev, Yalchin, Juan Galvis, and M. Sebastian Pauletti. "Multiscale Finite Element Methods for Flows on Rough Surfaces." Communications in Computational Physics 14, no. 4 (October 2013): 979–1000. http://dx.doi.org/10.4208/cicp.170512.310113a.

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AbstractIn this paper, we present the Multiscale Finite Element Method (MsFEM) for problems on rough heterogeneous surfaces. We consider the diffusion equation on oscillatory surfaces. Our objective is to represent small-scale features of the solution via multiscale basis functions described on a coarse grid. This problem arises in many applications where processes occur on surfaces or thin layers. We present a unified multiscale finite element framework that entails the use of transformations that map the reference surface to the deformed surface. The main ingredients of MsFEM are (1) the construction of multiscale basis functions and (2) a global coupling of these basis functions. For the construction of multiscale basis functions, our approach uses the transformation of the reference surface to a deformed surface. On the deformed surface, multiscale basis functions are defined where reduced (1D) problems are solved along the edges of coarse-grid blocks to calculate nodal multiscale basis functions. Furthermore, these basis functions are transformed back to the reference configuration. We discuss the use of appropriate transformation operators that improve the accuracy of the method. The method has an optimal convergence if the transformed surface is smooth and the image of the coarse partition in the reference configuration forms a quasiuniform partition. In this paper, we consider such transformations based on harmonic coordinates (following H. Owhadi and L. Zhang [Comm. Pure and Applied Math., LX(2007), pp. 675-723]) and discuss gridding issues in the reference configuration. Numerical results are presented where we compare the MsFEM when two types of deformations are used for multiscale basis construction. The first deformation employs local information and the second deformation employs a global information. Our numerical results show that one can improve the accuracy of the simulations when a global information is used.
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Yao, Hongtai, Xianpei Wang, Le Zhao, Meng Tian, Zini Jian, Li Gong, and Bowen Li. "An Object-Based Markov Random Field with Partition-Global Alternately Updated for Semantic Segmentation of High Spatial Resolution Remote Sensing Image." Remote Sensing 14, no. 1 (December 29, 2021): 127. http://dx.doi.org/10.3390/rs14010127.

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The Markov random field (MRF) method is widely used in remote sensing image semantic segmentation because of its excellent spatial (relationship description) ability. However, there are some targets that are relatively small and sparsely distributed in the entire image, which makes it easy to misclassify these pixels into different classes. To solve this problem, this paper proposes an object-based Markov random field method with partition-global alternately updated (OMRF-PGAU). First, four partition images are constructed based on the original image, they overlap with each other and can be reconstructed into the original image; the number of categories and region granularity for these partition images are set. Then, the MRF model is built on the partition images and the original image, their segmentations are alternately updated. The update path adopts a circular path, and the correlation assumption is adopted to establish the connection between the label fields of partition images and the original image. Finally, the relationship between each label field is constantly updated, and the final segmentation result is output after the segmentation has converged. Experiments on texture images and different remote sensing image datasets show that the proposed OMRF-PGAU algorithm has a better segmentation performance than other selected state-of-the-art MRF-based methods.
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Zabotin, Vladislav V., and Pavel A. Chernyshevskij. "Continuous global optimization of multivariable functions based on Sergeev and Kvasov diagonal approach." Zhurnal Srednevolzhskogo Matematicheskogo Obshchestva 24, no. 4 (December 31, 2022): 399–418. http://dx.doi.org/10.15507/2079-6900.24.202204.399-418.

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Abstract. One of modern global optimization algorithms is method of Strongin and Piyavskii modified by Sergeev and Kvasov diagonal approach. In recent paper we propose an extension of this approach to continuous multivariable functions defined on the multidimensional parallelepiped. It is known that Sergeev and Kvasov method applies only to a Lipschitz continuous function though it effectively extends one-dimensional algorithm to multidimensional case. So authors modify We modify mentioned method to a continuous functions using introduced by Vanderbei ε-Lipschitz property that generalizes conventional Lipschitz inequality. Vanderbei proved that a real valued function is uniformly continuous on a convex domain if and only if it is ε-Lipschitz. Because multidimensional parallelepiped is a convex compact set, we demand objective function to be only continuous on a search domain. We describe extended Strongin’s and Piyavskii’s methods in the Sergeev and Kvasov modification and prove the sufficient conditions for the convergence. As an example of proposed method’s application, at the end of this article we show numerical optimization results of different continuous but not Lipschitz functions using three known partition strategies: “partition on 2”, “partition on 2N” and “effective”. For the first two of them we present formulas for computing a new iteration point and for recalculating the ε-Lipschitz constant estimate. We also show algorithm modification that allows to find a new search point on any algorithm’s step.
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Guo, Tan, Fulin Luo, Yule Duan, Xinjian Huang, and Guangyao Shi. "Rethinking Representation Learning-Based Hyperspectral Target Detection: A Hierarchical Representation Residual Feature-Based Method." Remote Sensing 15, no. 14 (July 19, 2023): 3608. http://dx.doi.org/10.3390/rs15143608.

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Representation learning-based hyperspectral target detection (HTD) methods generally follow a learning paradigm of single-layer or one-step representation residual learning and the target detection on original full spectral bands, which, in some cases, cannot accurately distinguish the target pixels from variable background pixels via one-round of the detection process. To alleviate the problem and make full use of the latent discriminate characteristics in different spectral bands and the representation residual, this paper proposes a level-wise band-partition-based hierarchical representation residual feature (LBHRF) learning method for HTD with a parallel and cascaded hybrid structure. Specifically, the LBHRR method proposes to partition and fuse different levels of sub-band spectra combinations, and take full advantages of the discriminate information in representation residuals from different levels of band-partition. The highlights of this work include three aspects. First, the original full spectral bands are partitioned in a parallel level-wise manner to obtain the augmented representation residual feature through level-wise band-partition-based representation residual learning, such that the global spectral integrity and contextual information of local adjacent sub-bands are flexibly fused. Second, the SoftMax transformation, pooling operation, and augmented representation residual feature reuse among different layers are equipped in cascade to enhance the learning ability of the nonlinear and discriminant hierarchical representation residual features of the method. Third, a hierarchical representation residual feature-based HTD method is developed in an efficient stepwise learning manner instead of back-propagation optimization. Experimental results on several HSI datasets demonstrate that the proposed model can yield promising detection performance in comparison to some state-of-the-art counterparts.
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Lu, Zhigang, and Hong Shen. "An accuracy-assured privacy-preserving recommender system for internet commerce." Computer Science and Information Systems 12, no. 4 (2015): 1307–26. http://dx.doi.org/10.2298/csis140725056l.

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Recommender systems, tool for predicting users? potential preferences by computing history data and users? interests, show an increasing importance in various Internet applications such as online shopping. As a well-known recommendation method, neighbourhood-based collaborative filtering has attracted considerable attentions recently. The risk of revealing users? private information during the process of filtering has attracted noticeable research interests. Among the current solutions, the probabilistic techniques have shown a powerful privacy preserving effect. The existing methods deploying probabilistic methods are in three categories, one [19] adds differential privacy noises in the covariance matrix; one [1] introduces the randomisation in the neighbour selection process; the other [29] applies differential privacy in both the neighbour selection process and covariance matrix. When facing the k Nearest Neighbour (kNN) attack, all the existing methods provide no data utility guarantee, for the introduction of global randomness. In this paper, to overcome the problem of recommendation accuracy loss, we propose a novel approach, Partitioned Probabilistic Neighbour Selection, to ensure a required prediction accuracy while maintaining high security against the kNN attack. We define the sum of k neighbours? similarity as the accuracy metric ?, the number of user partitions, across which we select the k neighbours, as the security metric ?. We generalise the k Nearest Neighbour attack to the ?k Nearest Neighbours attack. Differing from the existing approach that selects neighbours across the entire candidate list randomly, our method selects neighbours from each exclusive partition of size k with a decreasing probability. Theoretical and experimental analysis show that to provide an accuracy-assured recommendation, our Partitioned Probabilistic Neighbour Selection method yields a better trade-off between the recommendation accuracy and system security.
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Lin, Lijuan, Licheng Xing, Qingquan Jia, and Xuerui Zhang. "Research on the Partition Method Based on the Observation Points of Voltage Distortion in Harmonic Optimization." Journal of Physics: Conference Series 2253, no. 1 (April 1, 2022): 012005. http://dx.doi.org/10.1088/1742-6596/2253/1/012005.

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Abstract With the use of a large number of power electronic equipment, the harmonics in the power grid are becoming more and more serious. There are many methods for harmonic mitigation and optimization such as Global network Optimization. When there are many nodes, the global network optimization method is more complicated. Considering the problem of large numbers of harmonic injection nodes in the power grid, this paper proposes a method of clustering the voltage distortion nodes according to correlation, and using the characteristic nodes to describe the harmonic voltage distortion in the region to mitigate harmonic voltage. This method is based on the observation data of the voltage distortion of the nodes for dynamic selection and grouping. The results show that this method meets the needs of Global network Optimization. The data processing methods used in this paper such as feature extraction methods and time series interpolation optimization can effectively reduce the data dimension, and get better optimization effect.
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Cotillard, Aurélie, Soline Chaumont, Mathilde Saccareau, Nicole S. Litwin, Diana Gutierrez Lopez, Julien Tap, Franck Lejzerowicz, et al. "Unsupervised Diet Partitions Better Explain Variations of the Gut Microbiome Compared to Individual Dietary Markers in U.S. Adults of the American Gut Project Cohort." Current Developments in Nutrition 5, Supplement_2 (June 2021): 397. http://dx.doi.org/10.1093/cdn/nzab038_009.

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Abstract Objectives Eating habits have been shown to impact the gut microbiome. Here we aimed to define several types of dietary patterns in a U.S. adult cohort and test their associations with the gut microbiome. Methods Using supervised and unsupervised approaches, we built dietary patterns based on a food frequency questionnaire of the American Gut Project database. Focusing on 1800 adult participants living in the United States, we defined patterns as partitions (groups of participants) or factors (combinations of food variables) driven by specific dietary criteria: fibers, proteins, Healthy Eating Index (HEI 2010), food items, food groups and micronutrients. We then associated these patterns with 16S gut microbiome data for 744 participants, excluding those reporting antibiotic intake in the last year or specific diseases. Analyses were adjusted for age, sex and BMI. Results Compared to individual features like fibers and proteins, or to factors representing reduced numbers of features, five unsupervised partitions based on food groups were best associated with gut microbiome beta-diversity. Two partitions presented a lower consumption of animal products, with one being almost completely exclusive and the other, close to a flexitarian diet, presenting the best diet quality as measured by HEI. A third one consisted mostly of participants under low carbohydrate diets with nearly no consumption of starchy foods or sweet products. Finally, the last two partitions presented Western-like diets with increased consumption of mixed dishes, sweet products and refined cereals, one of them being more diverse with increased nuts and whole cereals. Gut microbiome alpha-diversity was slightly increased in the flexitarian partition compared to the most westernized one. Strikingly, the low carbohydrate partition was associated with low levels of the Bifidobacterium genus. Conclusions We showed in a U.S. adult cohort that a global diet may be more associated with gut microbiome variations than individual features like fibers or proteins. Five diet partitions were identified and their specific associations with gut microbiome were studied. These results confirm the importance to consider diet as a whole when studying gut microbiota diversity. Funding Sources Danone Research.
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Wang, Yuexin, Guangcai Feng, Zhixiong Feng, Yuedong Wang, Xiuhua Wang, Shuran Luo, Yinggang Zhao, and Hao Lu. "An MT-InSAR Data Partition Strategy for Sentinel-1A/B TOPS Data." Remote Sensing 14, no. 18 (September 13, 2022): 4562. http://dx.doi.org/10.3390/rs14184562.

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The Sentinel-1A/B satellite launched by European Space Agency (ESA) in 2014 provides a huge amount of free Terrain Observation by Progressive Scans (TOPS) data with global coverage to the public. The TOPS data have a frame width of 250 km and have been widely used in surface deformation monitoring. However, traditional Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) methods require large computer memory and time when processing full resolution data with large width and long strips. In addition, they hardly correct atmospheric delays and orbital errors accurately over a large area. In order to solve these problems, this study proposes a data partition strategy based on MT-InSAR methods. We first process the partitioned images over a large area by traditional MT-InSAR method, then stitch the deformation results into a complete deformation result by correcting the offsets of adjacent partitioned images. This strategy is validated in a flat urban area (Changzhou City in Jiangsu province, China), and a mountainous region (Qijiang in Chongqing City, China). Compared with traditional MT-InSAR methods, the precision of the results obtained by the new strategy is improved by about 5% for Changzhou city and about 15% for Qijiang because of its advantage in atmospheric delay correction. Furthermore, the proposed strategy needs much less memory and time than traditional methods. The total time needed by the traditional method is about 20 h, and by the proposed method, is about 8.7 h, when the number of parallel processing is 5 in the Changzhou city case. The time will be further reduced when the number of parallel processes increases.
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Dissertations / Theses on the topic "Global Partition Methods"

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Simpson, Robert. "Enrichment of the boundary element method through the partition of unity method for fracture analysis using local and global formulations." Thesis, Durham University, 2010. http://etheses.dur.ac.uk/305/.

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The present thesis proposes an innovative technique of applying enrichment to the Boundary Element Method to allow accurate analysis of 2D crack problems. An overview of fracture mechanics is given, with particular emphasis given to numerical methods and the techniques used to extract the highly important stress intensity factors - a measure of the singularity of a crack tip. The Boundary Element Method framework is described and later, the implementation of the new technique of enrichment is defined in detail. Finally, several crack problems are used to verify the accuracy of the method where the results are shown to compare very favourably with other well-established numerical methods.
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Bhatt, Vikram. "Stability Preserving Bisection Algorithms in Reaction-Diffusion Complex Networks." Thesis, 2020. https://etd.iisc.ac.in/handle/2005/4424.

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Reaction-Diffusion complex networks are ubiquitous in many pragmatic models of network of interacting nodes with individual dynamics, such as social interactions, neuronal functions, transportation models, ecological systems and metabolic reactions. In particular case of reaction-diffusion network, with two different agents interacting together by specifi ed inter-node dynamics, coupling between nodes and uniform rate of di usion, under type I instability the network is stable only, Fiedler value(second smallest eigenvalue of Laplacian operator) is greater than certain threshold. Given stable complex network along with dynamics, we want to fi nd partition such that dynamics on the resultant daughter networks are sustainable. These partitions are of practical interest in many real life situations. For example, consider meta-population dynamics of species on ecological network in population habitats. Too often habitats are fragmented by artifi cial invasion (industrial corridors, road and railway networks) of human activities or due to stochastic reasons(genetic, environmental and demographic conditions) which results in extinction of even dominant species. Thus deserving study of existence of minimal cut partition and stability on the resultant networks while preserving the population of species on the partitioned networks. It is well-known in the literature that balanced graph partition problem is NP-complete. Various approximation algorithms and heuristics are used to generate sufficiently good quality local optimum solutions. In this work, we propose a theoretical model of reaction-diffusion network with two different species and study properties of linearized stability and co-existential equilibrium. We argue, pre-existing graph (static) bisection algorithms cannot be used to partition live complex network, such that resultant components have sustainable dynamics. Thus, we design a iterative heuristic algorithm of O(jV j3) time complexity based on Weyl's perturbation theorem, to partition the network into stable components. Throughout the experiments, our test bed for various algorithms are DIMACS10 graph datasets. We exploit, the spectral properties of Laplacian operator(specially algebraic connectivity or Fiedler value) and dynamics of the network topology. Since calculation of eigenvalues are expensive and prone to perturbation in every iteration, we search for further alternatives by looking at the parallels of heuristic graph bisection algorithms. We study various existing global partition algorithms(spectral bisection, multilevel recursive methods etc.) for graph bisection and incorporate results in our algorithm to increase quality of the partitions. Further down the line, we explore various meta-heuristic local search methods such as Kerninghan-Lin, Fiduccia-Mattheyses etc., and incorporate data structures for constant time retrieval of gain of vertices in our algorithm. Simulated annealing is well-known idea in statistical mechanics and motivated by motion of high degrees of freedom of system in presence of heat sink. Due to similarities between combinatorial optimization problem with exponential search space and physical system with high degree of freedom, we propose an adaptation of simulated annealing algorithm to our stability preserving bisection objective. Our empirical results shows that, although the algorithms converges in reasonable time for small graphs but su ers from polynomial growth of execution time with respect to size of graph. In the second part, we present two important theorems regarding the stability of reaction-diffusion network and characterize it completely in terms of external and internal costs, thus avoiding the need for calculation for eigenvalues. Using these theorems and above experimental results, we design a linear time heuristic of O(jV j + jEj) time complexity for stability preserving partition which shows signi cant improvement in partition quality.
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Books on the topic "Global Partition Methods"

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A course in analytic number theory. Providence, Rhode Island: American Mathematical Society, 2014.

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Book chapters on the topic "Global Partition Methods"

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Horst, Reiner, and Hoang Tuy. "Successive Partition Methods." In Global Optimization, 286–370. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-662-02598-7_7.

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Horst, Reiner, and Hoang Tuy. "Successive Partition Methods." In Global Optimization, 286–370. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-02947-3_7.

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Horst, Reiner, and Hoang Tuy. "Successive Partition Methods." In Global Optimization, 295–380. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03199-5_7.

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Žilinskas, Antanas. "Partition-Based Bayesian Global Optimization Methods." In Encyclopedia of Optimization, 1–3. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-54621-2_762-1.

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Zhigljavsky, Anatoly, and Antanas Žilinskas. "Bi-objective Decisions and Partition-Based Methods in Bayesian Global Optimization." In SpringerBriefs in Optimization, 41–88. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64712-4_2.

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Aref, Samin, Mahdi Mostajabdaveh, and Hriday Chheda. "Heuristic Modularity Maximization Algorithms for Community Detection Rarely Return an Optimal Partition or Anything Similar." In Computational Science – ICCS 2023, 612–26. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36027-5_48.

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AbstractCommunity detection is a fundamental problem in computational sciences with extensive applications in various fields. The most commonly used methods are the algorithms designed to maximize modularity over different partitions of the network nodes. Using 80 real and random networks from a wide range of contexts, we investigate the extent to which current heuristic modularity maximization algorithms succeed in returning maximum-modularity (optimal) partitions. We evaluate (1) the ratio of the algorithms’ output modularity to the maximum modularity for each input graph, and (2) the maximum similarity between their output partition and any optimal partition of that graph. We compare eight existing heuristic algorithms against an exact integer programming method that globally maximizes modularity. The average modularity-based heuristic algorithm returns optimal partitions for only 19.4% of the 80 graphs considered. Additionally, results on adjusted mutual information reveal substantial dissimilarity between the sub-optimal partitions and any optimal partition of the networks in our experiments. More importantly, our results show that near-optimal partitions are often disproportionately dissimilar to any optimal partition. Taken together, our analysis points to a crucial limitation of commonly used modularity-based heuristics for discovering communities: they rarely produce an optimal partition or a partition resembling an optimal partition. If modularity is to be used for detecting communities, exact or approximate optimization algorithms are recommendable for a more methodologically sound usage of modularity within its applicability limits.
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Zhang, Yongqiang, Shuang Liu, Xiaosong Yang, Daming Shi, and Jian Jun Zhang. "Sign-Correlation Partition Based on Global Supervised Descent Method for Face Alignment." In Computer Vision – ACCV 2016, 281–95. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54187-7_19.

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Knirck, Jason. "Confederates, Boers, or Silesians?" In Ireland and Partition, 15–32. Liverpool University Press, 2021. http://dx.doi.org/10.3828/liverpool/9781949979879.003.0002.

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Irish nationalists and the British government each sought analogies from world history to contextualize Ireland’s partition. The British alternated between arguing that Ireland contained two nations that could only be brought together under Britain’s aegis and claiming that the United Kingdom was a single nation that Irish nationalists were trying to sunder using the methods of the American Confederacy. Irish nationalists rejected such comparisons and instead sought procedural guidance in some of the Versailles plebiscites, particularly one in Upper Silesia. At the outset of the Irish revolution, references to the international context of partition focused on whether Ireland was a single nation entitled to self-determination. By the time the Boundary Commission actually met, that idealistic rhetoric had faded, replaced by limited invocations of legal precedent regarding the Versailles plebiscites. Studying the partition issue in this context demonstrates the rise and fall of Wilsonianism as well as the Irish transition from heady revolutionary days to the more quotidian aspects of post-revolutionary governance. It also demonstrates the new global frameworks in which the Irish Free State moved, as prior to independence most analogies offered for Ireland were to places within the British Empire, while by the mid-1920s such analogies invoked other European regions.
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K., Lakshmi, Karthikeyani Visalakshi N., Shanthi S., and Parvathavarthini S. "Clustering Mixed Datasets Using K-Prototype Algorithm Based on Crow-Search Optimization." In Developments and Trends in Intelligent Technologies and Smart Systems, 191–210. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3686-4.ch010.

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Data mining techniques are useful to discover the interesting knowledge from the large amount of data objects. Clustering is one of the data mining techniques for knowledge discovery and it is the unsupervised learning method and it analyses the data objects without knowing class labels. The k-prototype is the most widely-used partitional clustering algorithm for clustering the data objects with mixed numeric and categorical type of data. This algorithm provides the local optimum solution due to its selection of initial prototypes randomly. Recently, there are number of optimization algorithms are introduced to obtain the global optimum solution. The Crow Search algorithm is one the recently developed population based meta-heuristic optimization algorithm. This algorithm is based on the intelligent behavior of the crows. In this paper, k-prototype clustering algorithm is integrated with the Crow Search optimization algorithm to produce the global optimum solution.
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McDaid, Maev, and Brian Christopher Nelis. "State (In)action and Feminist Resistance to the Denial of Abortion Rights in Northern Ireland." In Feminist Responses to Injustices of the State and its Institutions, 55–75. Policy Press, 2022. http://dx.doi.org/10.1332/policypress/9781529207286.003.0003.

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This chapter explores how reproductive rights were denied in both the legal jurisdictions after partition in Ireland and how the state institutions stonewalled legislation. It examines how ‘biopower’ of the Church reached into almost all aspects of life and was thoroughly gendered and served as a disciplining force for the working class. It explores how activists confronted the inaction of the state(s), forcing bodily autonomy onto the legislative agenda. Through a range of methods, many with a focus on personal testimony, campaigns served to neutralize the grip of Church and state institutions. These had previously monopolized debate through narratives of ‘deviance’ and ‘shame’. While abortion was legalized in the south of Ireland and decriminalized in the north of Ireland, the denial of access in many areas remains. At a time when access to abortion is being threatened globally it is clear that only sustained confrontation with the state will secure provision of comprehensive reproductive healthcare services.
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Conference papers on the topic "Global Partition Methods"

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Wang, Yilin, Nan Cao, Teng Zhang, Xuanhua Shi, and Hai Jin. "Scalable Optimal Margin Distribution Machine." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/485.

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Optimal margin Distribution Machine (ODM) is a newly proposed statistical learning framework rooting in the novel margin theory, which demonstrates better generalization performance than the traditional large margin based counterparts. Nonetheless, it suffers from the ubiquitous scalability problem regarding both computation time and memory as other kernel methods. This paper proposes a scalable ODM, which can achieve nearly ten times speedup compared to the original ODM training method. For nonlinear kernels, we propose a novel distribution-aware partition method to make the local ODM trained on each partition be close and converge faster to the global one. When linear kernel is applied, we extend a communication efficient SVRG method to accelerate the training further. Extensive empirical studies validate that our proposed method is highly computational efficient and almost never worsen the generalization.
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Iwamoto, Tatsuya, Dana Miranda, James Banfield, Jake Yang, and Belgacem Hizoum. "Enhanced Natural Circulation Modeling in the GNF BWR Core Simulator AETNA02 for ESBWR." In 2016 24th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/icone24-61036.

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GE Hitachi Nuclear Energy’s (GEH) next evolution of Boiling Water Reactor (BWR) technology is the Economic Simplified Boiling Water Reactor (ESBWR). The ESBWR is a natural circulation reactor which employs numerous passive safety features while simultaneously offering a large power output for a relatively small plant footprint. The ESBWR is characterized with shortened fuel length and a tall, partitioned chimney region above the core to promote natural circulation core flow. The ESBWR is studied with Global Nuclear Fuel (GNF)’s advanced core-simulator AETNA02. AETNA02 is a static, three-dimensional coupled nuclear-thermal hydraulic computer program representing a BWR core. The new GNF lattice-physics core simulator package LANCR02/AETNA02 consists of the two-dimensional method of characteristics based lattice code, LANCR02, which generates cross sections over a range of plant conditions and passes them to the three neutron energy group coarse mesh nodal diffusion code AETNA02. For the thermal hydraulic solution, AETNA02 includes a model which explicitly solves for the flow in each channel, water rod, and bypass region which accompanies a fuel channel. For the solution of a natural circulation plant like the ESBWR, AETNA02 utilizes the Automatic Plant Thermal Hydraulics (APTH) model which includes models for the core, the chimney region, the separator, the dryer, and the downcomer. AETNA02 iterates on the fuel channel flow and the pressure drop by modeling each chimney partition explicitly with fuel channels and bypasses mapped to it in addition to a bypass mixing model for the chimneys. This is relevant because the peripheral channels (low power) will have a lower void fraction while the central channels (higher power) will have a higher void fraction. Thus, the chimneys connected to these channels will each have a different hydrostatic head. To verify and validate each of the APTH component models, code-to-code comparisons are performed with the GEH TRACG04 code as well as data comparisons with experiments. The TRACG04 computer program is a best-estimate two-fluid transient code. Code-to-code comparisons of the two different methods (two-fluid model in TRACG04 versus drift flux model in AETNA02) are made. In addition, this study attempts to quantify the impact on the core flow distribution that will affect the calculated thermal margins, including the Critical Power Ratio (CPR). The impact of the multiple chimney (MC) versus the single chimney (SC) model is studied. The multiple chimney partition modeling provides additional detail to the core flow distribution that is not considered in the single chimney model. The results confirm and add confidence that the multiple chimney partition modeling will provide improved accuracy in the ESBWR core design.
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Artemenko, S., and V. Mazur. "Thermodynamic and Phase Behavior of Supercritical Water: Environmentally Significant Organic Chemical Mixtures." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59453.

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The importance of equation of state models is fundamental to new technologies such as supercritical water oxidation for the destruction of organic pollutants. In order to be able to perform hazard and risk assessments, the parameters ofthermodynamic models are considered as information characteristics of chemicals that store the knowledge on their thermodynamic, phase and environmental behavior. Considering the extremely large number of existing chemicals, it is obvious that there is need for developing theoretically sound methods for the prompt estimation of their phase behavior in aquatic media at supercritical conditions. Recent developments of the global phase equilibria studies of binary mixtures provide some basic ideas of how the required methods can be developed based on global phase diagrams for visualization of the phase behavior of mixtures. The mapping of the global equilibrium surface in the parameter space of the equation of state (EoS) model provides the most comprehensive system of criteria for predicting binary mixture phase behavior. The main types of phase behavior for environmentally significant organic chemicals in aqueous environments are considered using structure-property correlations for the critical parameters of substances. Analytic expressions for azeotropy prediction for cubic EoS are derived. A local mapping concept is introduced to describe thermodynamically consistently the saturation curve of water. The classes of environmentally significant chemicals (polycyclic aromatic hydrocarbons - PAH, polychlorinated biphenyls - PCB, polychlorinated dibenzo-p-dioxins and furans, and selected pesticides) are considered and main sources of the property data are examined. Vapor pressure, heat of vaporization, and critical parameter estimations for pure components were chosen for seeking a correlation between the octanol–water partition coefficients KOW and the EoS binary interaction parameters - k12. The assessment of thermodynamic and phase behavior of representatives for different pollutants is given.
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Xin, Xu, Zeng Shengqiang, Sun Zhaolin, Zhang Yumei, Nie Hongshan, and Li Tiegen. "Multi-source Spatial Data Code on the Global Partition Method." In 2010 International Conference on Intelligent System Design and Engineering Application (ISDEA). IEEE, 2010. http://dx.doi.org/10.1109/isdea.2010.41.

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Fang, Dong, Yu-Chih Huang, Zhiguo Ding, Giovanni Geraci, Shin-Lin Shieh, and Holger Claussen. "Lattice Partition Multiple Access: A New Method of Downlink Non-Orthogonal Multiuser Transmissions." In GLOBECOM 2016 - 2016 IEEE Global Communications Conference. IEEE, 2016. http://dx.doi.org/10.1109/glocom.2016.7841947.

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Dong, Cai, Li Man-chun, Wei Wei, Hu Wei, and Chen Qian. "An Intelligent Method of Partition of Urban Fringe - A Case Study in Nanjing City." In 2009 WRI Global Congress on Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/gcis.2009.357.

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Song, Jiho, Cheoljon Jang, Kyungin Cho, Seungryeol Go, and Jongwha Chong. "Timing driven global router with a pin partition method for 3D stacked integrated circuits." In 2014 International Symposium on Consumer Electronics (ICSE). IEEE, 2014. http://dx.doi.org/10.1109/isce.2014.6884325.

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Groth, Stefan, Daniel Grünewald, Jürgen Teich, and Frank Hannig. "A runtime system for finite element methods in a partitioned global address space." In CF '20: Computing Frontiers Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3387902.3392628.

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Haoming, Dou, Lang Minggang, Zhang Han, and She Ding. "Analysis and Improvement of Flow Field Calculation in Thermal Hydraulic Program for High Temperature Gas-Cooled Reactor." In 2022 29th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/icone29-92090.

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Abstract The flow field calculation plays a crucial role in thermal-hydraulic calculation of High Temperature Gas-cooled Reactor (HTGR). While using the thermal-hydraulic program for HTGR to calculate the low-flow condition, the calculation of the helium pressure field distribution in the reactor core is difficult to converge, which may lead to the non-physical pressure oscillation. The analysis and improvement of flow field calculation to alleviate this non-physical oscillation is of great significance for HTGR thermal-hydraulic design. In this work, the factors affecting the flow field calculation are analyzed. The approximation assumptions of horizontal cavity modeling and the using of Gauss-Seidel (GS) partition point iteration method leading to the flow field calculation is sensitive to round-off error. For the reason of GS partition point iterative method suffers from the slow convergence rate, and may even non-convergence in some conditions, a global direct method is developed in this paper to solve the whole flow field directly to pursue strong stability and high convergence rate. Compared with original method, the numerical results show that the newly developed algorithm achieves faster convergence rate and stricter convergence results.
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Du, Juan. "A Method for the Global Photographic Clarity based on Multifocal Pre-treatment of Partitioned View." In 2020 5th International Conference on Communication, Image and Signal Processing (CCISP). IEEE, 2020. http://dx.doi.org/10.1109/ccisp51026.2020.9273495.

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