Relevant bibliographies by topics / Discrete Neighborhood

Academic literature on the topic 'Discrete Neighborhood'

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Published: 10 March 2023

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Journal articles on the topic "Discrete Neighborhood"

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Quillian, Lincoln. "A Comparison of Traditional and Discrete-Choice Approaches to the Analysis of Residential Mobility and Locational Attainment." ANNALS of the American Academy of Political and Social Science 660, no. 1 (June 9, 2015): 240–60. http://dx.doi.org/10.1177/0002716215577770.

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This article contrasts traditional modeling approaches and discrete-choice models as methods to analyze locational attainment—how individual and household characteristics (such as race, socioeconomic status, age) influence the characteristics of neighborhoods of residence (such as racial composition and median income). Traditional models analyze attributes of a neighborhood as a function of the characteristics of the households within them; discrete-choice methods, on the other hand, are based on dyadic analysis of neighborhood attributes and household characteristics. I outline two problems with traditional approaches to residential mobility analysis that may be addressed through discrete-choice analysis. I also discuss disadvantages of the discrete-choice approach. Finally, I use data from the Panel Study of Income Dynamics to estimate residential mobility using traditional locational attainment and discrete-choice models; I show that these produce similar estimates but that the discrete-choice approach allows for estimates that examine how multiple place characteristics simultaneously guide migration. Substantively, these models reveal that the disproportionate migration of black households into lower-income tracts amounts to sorting of black households into black tracts, which on average are lower income.
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Mishachev, Nikolay Mikhailovich, and Anatoliy Mikhailovich Shmyrin. "DISCRETE SYSTEMS AND NEIGHBORING STRUCTURES." Tambov University Reports. Series: Natural and Technical Sciences, no. 123 (2018): 473–78. http://dx.doi.org/10.20310/1810-0198-2018-23-123-473-478.

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In the article, neighborhood structures (digraphs of a special type) are defined and their relationship with discrete control systems is discussed. The archetypes of the neighborhood structures and the control systems corresponding to these archetypes are listed.
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Huang, Song, Na Tian, and Zhicheng Ji. "Particle swarm optimization with variable neighborhood search for multiobjective flexible job shop scheduling problem." International Journal of Modeling, Simulation, and Scientific Computing 07, no. 03 (August 23, 2016): 1650024. http://dx.doi.org/10.1142/s1793962316500240.

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The simulation on benchmarks is a very simple and efficient method to evaluate the performance of the algorithm for solving flexible job shop scheduling model. Due to the assignment and scheduling decisions, flexible job shop scheduling problem (FJSP) becomes extremely hard to solve for production management. A discrete multi-objective particle swarm optimization (PSO) and simulated annealing (SA) algorithm with variable neighborhood search is developed for FJSP with three criteria: the makespan, the total workload and the critical machine workload. Firstly, a discrete PSO is designed and then SA algorithm performs variable neighborhood search integrating two neighborhoods on public critical block to enhance the search ability. Finally, the selection strategy of the personal-best individual and global-best individual from the external archive is developed in multi-objective optimization. Through the experimental simulation on matlab, the tests on Kacem instances, Brdata instances and BCdata instances show that the modified discrete multi-objective PSO algorithm is a promising and valid method for optimizing FJSP with three criteria.
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Chen, Guantao, Jian Shen, and Raphael Yuster. "Second Neighborhood via First Neighborhood in Digraphs." Annals of Combinatorics 7, no. 1 (June 2003): 15–20. http://dx.doi.org/10.1007/s000260300001.

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Namgung, Mi, and Gulsah Akar. "Influences of Neighborhood Characteristics and Personal Attitudes on University Commuters’ Public Transit Use." Transportation Research Record: Journal of the Transportation Research Board 2500, no. 1 (January 2015): 93–101. http://dx.doi.org/10.3141/2500-11.

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This study examined the links between attitudes, the built environment, and travel behavior on the basis of data from the Ohio State University's 2012 Campus Transportation Survey. The analysis results indicated that attitudes might have explained travel behavior better than the built environment. Survey respondents were asked questions about their attitudes on public transit use, and their answers were grouped into new attitudinal factors by using principal component analysis. Then, new neighborhood categories were created by K-means cluster analysis by means of built-environment and land use variables (population density, employment density, housing density, median age of structures, percentage of single-family housing, and intersection density). As a result of this analysis, discrete neighborhood categories, such as urban high-density and residential neighborhoods, and urban low-density and mixed-use neighborhoods, were created. Then, differences in attitudes toward public transit were analyzed across these new neighborhood categories. Binary logit models were estimated to determine the influence of these neighborhood categories as well as personal attitudes on public transit use after sociodemographic characteristics were controlled for. The results indicated that attitudes were more strongly associated with travel behavior than with neighborhood characteristics. The findings of this study will aid in the formation of a better understanding of public transit use by highlighting the effects of attitudes and neighborhood characteristics in transit use as well as differences in attitudes between neighborhood types.
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WISEHEART, REBECCA, SUNJUNG KIM, LINDA J. LOMBARDINO, and LORI J. P. ALTMANN. "Indexing effects of phonological representational strength on rapid naming using rime neighborhood density." Applied Psycholinguistics 40, no. 2 (October 30, 2018): 253–77. http://dx.doi.org/10.1017/s0142716418000565.

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AbstractA long-standing hypothesis is that rapid automatized naming (RAN) measures access to phonological representations stored in long-term memory, but this has been difficult to test experimentally because phonological representations are mental constructs not easily operationalized. Here, we provide a method to test this theory using rime neighborhood density as an index of phonological representational strength. Thirty adults completed four picture-naming tasks orthogonalized for item composition (repeating vs. nonrepeating) and presentation format (discrete vs. serial). Each task was presented in two dichotomous conditions of rime neighborhood density (dense and sparse). There was no effect of rime neighborhood density on naming speed in the discrete nonrepeated (confrontation naming) task. However, rime neighborhood density significantly facilitated naming speed for serial repeated (i.e., RAN), discrete repeated, and serial nonrepeated tasks (ps<.03). The effect was weakest for confrontation naming (d=0.14) and strongest for both discrete and serial RAN tasks (ds=1.01), suggesting that repeating items, not serial presentation, makes RAN uniquely sensitive to manipulations of rime neighborhood density and, by proxy, phonological representations.
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Li, Tianjun. "Local discrete symmetry in the brane neighborhood." Physics Letters B 528, no. 1-2 (February 2002): 149–55. http://dx.doi.org/10.1016/s0370-2693(02)01185-1.

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Marchand-Maillet, Stéphane, and Yazid M. Sharaiha. "Discrete Convexity, Straightness, and the 16-Neighborhood." Computer Vision and Image Understanding 66, no. 3 (June 1997): 316–29. http://dx.doi.org/10.1006/cviu.1996.0521.

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Sedykh, I. A. "FORECASTING THE GROUNDWATER LEVEL OF CEMENT RAW MATERIALS DEPOSIT BASED ON DYNAMIC NEIGHBORHOOD MODELS." Vestnik of Don State Technical University 18, no. 3 (September 29, 2018): 326–32. http://dx.doi.org/10.23947/1992-5980-2018-18-3-326-332.

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Introduction. The development of a mathematical model for the groundwater level of a deposit of cement raw materials located in the Zadonian-Yelets aquifer, which is the principal domestic water supply source for the city of Lipetsk, is considered. Therefore, it is necessary to provide ongoing monitoring and to have the possibility to predict the water level under the field development. The work objectives are the identification and study of a dynamic neighborhood model with variable hierarchical neighborhoods of the groundwater level that enables to adequately predict value of the water level in the examined wells.Materials and Methods. The definition of a dynamic neighborhood model with variable hierarchical neighborhoods is given, differing by time-varying double-level neighborhood communications between the first- and second-level nodes. At each next discrete instant of time, the neighborhood model nodes change their state under the influence of the online parameters and node states included in their neighborhood. As a subcase, we consider a model with line state recalculation functions. Parametric identification of the dynamic neighborhood model consists in finding the system parameters for each second-level node, and is based on the ordinary least squares.Research Results. A linear dynamic neighborhood model with variable hierarchical neighborhoods for predicting the groundwater level in a cement raw material deposit located in the Zadonian-Yelets aquifer is developed. The software using C++ is developed for the parametric identification and simulation of the functioning of the dynamic neighborhood model under consideration. It enables to determine parameters of the node state recalculation functions for a given structure, and also to predict the model behavior in the operation process. A hierarchical structure is given, and a parametric identification of the linear dynamic neighborhood model of the groundwater level is carried out. After the parametric identification on the teaching data selection, the mathematical model is checked on the test sample.Discussion and Conclusions. The obtained average ratio errors of the identification and forecast suggest the developed model validity and enable to recommend it for predicting the underground water level of a cement raw materials deposit.
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Chen, Xueyu, Minghua Wan, Hao Zheng, Chao Xu, Chengli Sun, and Zizhu Fan. "A New Bilinear Supervised Neighborhood Discrete Discriminant Hashing." Mathematics 10, no. 12 (June 17, 2022): 2110. http://dx.doi.org/10.3390/math10122110.

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Feature extraction is an important part of perceptual hashing. How to compress the robust features of images into hash codes has become a hot research topic. Converting a two-dimensional image into a one-dimensional descriptor requires a higher computational cost and is not optimal. In order to maintain the internal feature structure of the original two-dimensional image, a new Bilinear Supervised Neighborhood Discrete Discriminant Hashing (BNDDH) algorithm is proposed in this paper. Firstly, the algorithm constructs two new neighborhood graphs to maintain the geometric relationship between samples and reduces the quantization loss by directly constraining the hash codes. Secondly, two small rotation matrices are used to realize the bilinear projection of the two-dimensional descriptor. Finally, the experiment verifies the performance of the BNDDH algorithm under different feature types, such as image original pixels and a Convolutional Neural Network (CNN)-based AlexConv5 feature. The experimental results and discussion clearly show that the proposed BNDDH algorithm is better than the existing traditional hashing algorithm and can represent the image more efficiently in this paper.
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Dissertations / Theses on the topic "Discrete Neighborhood"

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Huggins, Christopher M. "Returning Home: Residential mobility, neighborhood context and recidivism." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250277592.

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Irwin, Mary Elizabeth (Molly). "The Impact of Race and Neighborhood on Child Maltreatment: A Multi-Level Discrete Time Hazard Analysis." Cleveland, Ohio : Case Western Reserve University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1246634898.

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Thesis(Ph.D.)--Case Western Reserve University, 2009
Title from PDF (viewed on 2009-11-23) Department of Social Welfare Includes abstract Includes bibliographical references and appendices Available online via the OhioLINK ETD Center
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Sands, William Alvah. "Phylogenetic Inference Using a Discrete-Integer Linear Programming Model." University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1492783280743802.

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Lapucci, Matteo, and Marco Sciandrone. "Theory and algorithms for sparsity constrained optimization problems." Doctoral thesis, 2022. http://hdl.handle.net/2158/1258429.

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This dissertation is concerned with mathematical optimization problems where a sparsity constraint appears. The sparsity of the solution is a valu- able requirement in many applications of operations research. Several classes of very different approaches have been proposed in the literature for this sort of problems; when the objective function is nonconvex, in presence of difficult additional constraints or in the high-dimensional case, the problem shall be addressed as a continuous optimization task, even though it naturally has an intrinsic combinatorial nature. Within this setting, we first review the existing knowledge and the theoretical tools concerning the considered problem; we try to provide a unified view of parallel streams of research and we propose a new general stationarity condition, based on the concept of neighborhood, which somehow allows to take into account both the continuous and the combinatorial aspects of the problem. Then, after a brief overview of the main algorithmic approaches in the related literature, we propose suitable variants of some of these schemes that can be effectively employed in complex settings, such as the nonconvex one, the derivative-free one or the multi-objective one. For each of the proposed algorithms we provide a detailed convergence analysis showing that these methods enjoy important theoretical guarantees, in line with the state-of-the-art algorithms. Afterwards, exploiting the newly introduced concept of stationarity, we propose a completely novel algorithmic scheme that, combining continuous local searches and discrete moves, can be proved to guarantee stronger theoretical properties than most approaches from the literature and to exhibit strong exploration capabilities in a global optimization perspective. All the proposed algorithms have finally been experimentally tested on a benchmark of relevant problems from machine learning and decision science applications. The computational results show the actual quality of the proposed methods when practically employed.
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Books on the topic "Discrete Neighborhood"

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Publishers, Museum. Notebook: Neighborhood Nymphs, Come Discreet Nymphs Laboulie in These Places Arrayed with His Glasses, Shows Himself to Your Glances in Uncovered Masses a Young Journalist Who. Independently Published, 2020.

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Book chapters on the topic "Discrete Neighborhood"

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Chastel, S., P. Colantoni, and A. Bretto. "Displaying Image Neighborhood Hypergraphs Line-Graphs." In Discrete Geometry for Computer Imagery, 124–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45986-3_11.

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Nagy, Benedek. "Geometry of Neighborhood Sequences in Hexagonal Grid." In Discrete Geometry for Computer Imagery, 53–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11907350_5.

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Brimberg, Jack, Nenad Mladenović, Raca Todosijević, and Dragan Urošević. "Variable Neighborhood Descent for the Capacitated Clustering Problem." In Discrete Optimization and Operations Research, 336–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44914-2_27.

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Schmitt, Frank, and Lutz Priese. "Vanishing Point Detection with an Intersection Point Neighborhood." In Discrete Geometry for Computer Imagery, 132–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04397-0_12.

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Normand, Nicolas, Robin Strand, Pierre Evenou, and Aurore Arlicot. "Path-Based Distance with Varying Weights and Neighborhood Sequences." In Discrete Geometry for Computer Imagery, 199–210. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19867-0_17.

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Levanova, Tatyana, and Alexander Gnusarev. "Variable Neighborhood Search Approach for the Location and Design Problem." In Discrete Optimization and Operations Research, 570–77. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44914-2_45.

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Frosini, A., C. Picouleau, and S. Rinaldi. "Reconstructing Binary Matrices with Neighborhood Constraints: An NP-hard Problem." In Discrete Geometry for Computer Imagery, 392–400. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79126-3_35.

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Afric, Petar, Adrian Satja Kurdija, Lucija Sikic, Marin Silic, Goran Delac, Klemo Vladimir, and Sinisa Srbljic. "Population-Based Variable Neighborhood Descent for Discrete Optimization." In Artificial Intelligence and Mobile Services – AIMS 2019, 1–12. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23367-9_1.

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Hajdu, András, and Lajos Hajdu. "On the Lattice Structure of Subsets of Octagonal Neighborhood Sequences in ℤn." In Discrete Geometry for Computer Imagery, 211–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11907350_18.

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Mossel, Elchanan, and Jiaming Xu. "Seeded Graph Matching via Large Neighborhood Statistics." In Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 1005–14. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2019. http://dx.doi.org/10.1137/1.9781611975482.62.

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Conference papers on the topic "Discrete Neighborhood"

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Cruz-Chavez, Marco Antonio, Alina Martinez-Oropeza, and Sergio A. Serna Barquera. "Neighborhood Hybrid Structure for Discrete Optimization Problems." In 2010 IEEE Electronics, Robotics and Automotive Mechanics Conference (CERMA). IEEE, 2010. http://dx.doi.org/10.1109/cerma.2010.24.

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Berenbrink, Petra, Colin Cooper, Robert Elsässer, Tomasz Radzik, and Thomas Sauerwald. "Speeding up random walks with neighborhood exploration." In Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2010. http://dx.doi.org/10.1137/1.9781611973075.115.

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Combs, C. Donald. "The Digital Patient and the Digital Neighborhood: Implications for Modeling and Simulation in Healthcare." In SIGSIM-PADS '21: SIGSIM Conference on Principles of Advanced Discrete Simulation. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3437959.3459247.

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Khuller, Samir, Manish Purohit, and Kanthi K. Sarpatwar. "Analyzing the Optimal Neighborhood: Algorithms for Budgeted and Partial Connected Dominating Set Problems." In Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973402.123.

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Ghiglia, Dennis C., and Gary A. Mastin. "A Cellular Automata Method for Phase Unwrapping." In Signal Recovery and Synthesis. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/srs.1986.fc2.

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Cellular automata are simple, discrete mathematical systems that can exhibit complex behavior resulting from collective effects of a large number of cells, each of which evolve in discrete time steps according to rather simple local neighborhood rules.
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Luo, Xin, Xiao-Ya Yin, Liqiang Nie, Xuemeng Song, Yongxin Wang, and Xin-Shun Xu. "SDMCH: Supervised Discrete Manifold-Embedded Cross-Modal Hashing." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/349.

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Cross-modal hashing methods have attracted considerable attention. Most pioneer approaches only preserve the neighborhood relationship by constructing the correlations among heterogeneous modalities. However, they neglect the fact that the high-dimensional data often exists on a low-dimensional manifold embedded in the ambient space and the relative proximity between the neighbors is also important. Although some methods leverage the manifold learning to generate the hash codes, most of them fail to explicitly explore the discriminative information in the class labels and discard the binary constraints during optimization, generating large quantization errors. To address these issues, in this paper, we present a novel cross-modal hashing method, named Supervised Discrete Manifold-Embedded Cross-Modal Hashing (SDMCH). It can not only exploit the non-linear manifold structure of data and construct the correlation among heterogeneous multiple modalities, but also fully utilize the semantic information. Moreover, the hash codes can be generated discretely by an iterative optimization algorithm, which can avoid the large quantization errors. Extensive experimental results on three benchmark datasets demonstrate that SDMCH outperforms ten state-of-the-art cross-modal hashing methods.
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Ali, Thamallah, Sakly Anis, and M'Sahli Faouzi. "Multi-objective predictive control using discrete TS fuzzy systems and a modified dynamic neighborhood PSO." In 2015 12th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2015. http://dx.doi.org/10.1109/ssd.2015.7348178.

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Mathew, Deepthy, C. Sathish Kumar, and K. Anita Cherian. "Application of discrete orthonormal Stockwell transform and local neighborhood patterns for leaf disease classification in banana." In 2021 International Conference on Communication, Control and Information Sciences (ICCISc). IEEE, 2021. http://dx.doi.org/10.1109/iccisc52257.2021.9484860.

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Osabay, Eneko, Esther Villar-Rodriguezy, and Javier Del Seryz. "A Coevolutionary Variable Neighborhood Search Algorithm for Discrete Multitasking (CoVNS): Application to Community Detection over Graphs." In 2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2020. http://dx.doi.org/10.1109/ssci47803.2020.9308447.

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Schuster, Reinhard, Klaus-Peter Thiele, Thomas Ostermann, and Martin Schuster. "A Discrete SIR Model with Spatial Distribution on a Torus for COVID-19 Analysis using Local Neighborhood Properties." In 14th International Conference on Health Informatics. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010252504750482.

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Reports on the topic "Discrete Neighborhood"

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Bedoya-Maya, Felipe, Lynn Scholl, Orlando Sabogal-Cardona, and Daniel Oviedo. Who uses Transport Network Companies?: Characterization of Demand and its Relationship with Public Transit in Medellín. Inter-American Development Bank, September 2021. http://dx.doi.org/10.18235/0003621.

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Transport Network Companies (TNCs) have become a popular alternative for mobility due to their ability to provide on-demand flexible mobility services. By offering smartphone-based, ride-hailing services capable of satisfying specific travel needs, these modes have transformed urban mobility worldwide. However, to-date, few studies have examined the impacts in the Latin American context. This analysis is a critical first step in developing policies to promote efficient and sustainable transport systems in the Latin-American region. This research examines the factors affecting the adoption of on-demand ride services in Medellín, Colombia. It also explores whether these are substituting or competing with public transit. First, it provides a descriptive analysis in which we relate the usage of platform-based services with neighborhood characteristics, socioeconomic information of individuals and families, and trip-level details. Next, factors contributing to the election of platform-based services modeled using discrete choice models. The results show that wealthy and highly educated families with low vehicle availability are more likely to use TNCs compared to other groups in Medellín. Evidence also points at gender effects, with being female significantly increasing the probability of using a TNC service. Finally, we observe both transit complementary and substitution patterns of use, depending on the context and by whom the service is requested.
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