Relevant bibliographies by topics / Neighborhood refinement

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Neighborhood refinement'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Neighborhood refinement"

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Walton, Emily. "“It's Not Just a Bunch of Buildings”: Social Psychological Investment, Sense of Community, and Collective Efficacy in a Multiethnic Low–Income Neighborhood." City & Community 15, no. 3 (September 2016): 231–63. http://dx.doi.org/10.1111/cico.12189.

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This analysis of social life in a poor, multiethnic public housing neighborhood presents an opportunity for refinement of social disorganization theory. Drawing on data from interviews, focus groups, and participant observations among residents, I find that this neighborhood exhibits substantial collective efficacy, despite social disorganization theory's predictions that the structural conditions of high poverty and racial and ethnic diversity result in low collective efficacy. I explicate two social psychological investment strategies—sense of ownership and symbolic representation—that appear to facilitate a sense of community and ultimately collective efficacy, helping to explain this apparent anomaly. I argue that even in the presence of structural disadvantage, having a strong sense of community provides a basis for beneficial action on behalf of the collective because it constitutes a source of shared expectations about values and norms in the neighborhood. These findings suggest refinements to the social disorganization framework, but also provide foundational ideas for policy interventions that may improve the social lives of residents in disadvantaged neighborhoods.
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McCormack, Gavin R., Autumn Nesdoly, Dalia Ghoneim, and Tara-Leigh McHugh. "Realtors’ Perceptions of Social and Physical Neighborhood Characteristics Associated with Active Living: A Canadian Perspective." International Journal of Environmental Research and Public Health 17, no. 23 (December 7, 2020): 9150. http://dx.doi.org/10.3390/ijerph17239150.

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Realtors match home-seekers with neighborhoods that have built and social characteristics they desire to pursue active lifestyles. Studies have yet to explore realtors’ perspectives on neighborhood design that supports active living. Using qualitative description, our study was to explore the perceptions and understandings of neighborhood design (walkability, healthy, bike-ability, vibrancy, and livability) among urban residential realtors. Nineteen (6 men; 13 women; average age 48 years) self-identified residential realtors from Calgary, Edmonton, and Lethbridge (Canada) completed semi-structured telephone interviews. Content analysis identified themes from the interview data. Specifically, walkability was described as: perceived preferences, destinations and amenities, and connections; a healthy community was described as: encourages outdoor activities, and promotes social homogeneity; bike-ability was described as: bike-ability attributes, and was controversial; vibrancy was described as: community feel, and evidence of life; and livability was described as: subjective, and preferences and necessities. Our findings can inform the refinement of universal definitions and concepts used to in neighborhood urban design.
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Kwon, Ern, Jinkee Lee, Gun Kwon, and Mi Kim. "A Refinement of Schwarz–Pick Lemma for Higher Derivatives." Mathematics 7, no. 1 (January 13, 2019): 77. http://dx.doi.org/10.3390/math7010077.

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In this paper, a Schwarz–Pick estimate of a holomorphic self map f of the unit disc D having the expansion f ( w ) = c 0 + c n ( w − z ) n + … in a neighborhood of some z in D is given. This result is a refinement of the Schwarz–Pick lemma, which improves a previous result of Shinji Yamashita.
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ALZIARY, B., and P. L. LIONS. "A GRID REFINEMENT METHOD FOR DETERMINISTIC CONTROL AND DIFFERENTIAL GAMES." Mathematical Models and Methods in Applied Sciences 04, no. 06 (December 1994): 899–910. http://dx.doi.org/10.1142/s0218202594000492.

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We develop here a simple method for the computation of value functions of deterministic optimal control or differential games problems which allows to refine locally a grid and reduce memory space. Given an approximation of optimal trajectories, one can solve the associated Hamilton-Jacobi equation in a tubular neighborhood with state-constraints boundary conditions. We study here the validity of such an approach and we illustrate it on various examples.
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Haffert, S. Y., E. H. Por, C. U. Keller, M. A. Kenworthy, D. S. Doelman, F. Snik, and M. J. Escuti. "The Single-mode Complex Amplitude Refinement (SCAR) coronagraph." Astronomy & Astrophysics 635 (March 2020): A56. http://dx.doi.org/10.1051/0004-6361/201731615.

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We present the monochromatic lab verification of the newly developed SCAR coronagraph that combines a phase plate (PP) in the pupil with a microlens-fed single-mode fiber array in the focal plane. The two SCAR designs that have been measured, create respectively a 360 degree and 180 degree dark region from 0.8–2.4λ∕D around the star. The 360 SCAR has been designed for a clear aperture and the 180 SCAR has been designed for a realistic aperture with central obscuration and spiders. The 360 SCAR creates a measured stellar null of 2–3 × 10−4, and the 180 SCAR reaches a null of 1 × 10−4. Their monochromatic contrast is maintained within a range of ±0.16λ∕D peak-to-valley tip-tilt, which shows the robustness against tip-tilt errors. The small inner working angle and tip-tilt stability makes the SCAR coronagraph a very promising technique for an upgrade of current high-contrast instruments to characterize and detect exoplanets in the solar neighborhood.
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Koz, Alper, and Ufuk Efe. "Geometric- and Optimization-Based Registration Methods for Long-Wave Infrared Hyperspectral Images." Remote Sensing 13, no. 13 (June 24, 2021): 2465. http://dx.doi.org/10.3390/rs13132465.

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Registration of long-wave infrared (LWIR) hyperspectral images with their thermal and emissivity components has until now received comparatively less attention with respect to the visible near and short wave infrared hyperspectral images. In this paper, the registration of LWIR hyperspectral images is investigated to enhance applications of LWIR images such as change detection, temperature and emissivity separation, and target detection. The proposed approach first searches for the best features of hyperspectral image pixels for extraction and matching in the LWIR range and then performs a global registration over two-dimensional maps of three-dimensional hyperspectral cubes. The performances of temperature and emissivity features in the thermal domain along with the average energy and principal components of spectral radiance are investigated. The global registration performed over whole 2D maps is further improved by blockwise local refinements. Among the two proposed approaches, the geometric refinement seeks the best keypoint combination in the neighborhood of each block to estimate the transformation for that block. The alternative optimization-based refinement iteratively finds the best transformation by maximizing the similarity of the reference and transformed blocks. The possible blocking artifacts due to blockwise mapping are finally eliminated by pixelwise refinement. The experiments are evaluated with respect to the (i) utilized similarity metrics in the LWIR range between transformed and reference blocks, (ii) proposed geometric- and optimization-based methods, and (iii) image pairs captured on the same and different days. The better performance of the proposed approach compared to manual, GPU-IMU-based, and state-of-the-art image registration methods is verified.
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Singh, Saransh, Farangis Ram, and Marc De Graef. "Application of forward models to crystal orientation refinement." Journal of Applied Crystallography 50, no. 6 (November 3, 2017): 1664–76. http://dx.doi.org/10.1107/s1600576717014200.

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Two approaches are proposed for the refinement of electron diffraction pattern indexing. The approaches require two basic ingredients: an accurate physics-based forward model and an algorithm to search the local orientation neighborhood. Forward models for electron backscatter diffraction (EBSD) and electron channeling pattern (ECP) modalities are coupled with either a multi-resolution brute-force search algorithm or a bound optimization by quadratic approximation algorithm. The efficacy of the methods is evaluated for varying levels of error in the pattern projection center. The EBSD modality shows an orientation improvement when the projection center error is within ±1% of the full detector width, whereas the ECP modality shows improvement up to a ±5% error. The algorithms are applied to an experimental EBSD scan for partially recrystallized 90/10 brass; the results show that the refinement is necessary to remove the artifacts introduced by the discrete sampling nature of the dictionary indexing method. Finally, a pattern center correction factor is derived for orientations obtained from dictionary indexing for large-area EBSD scans.
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Sinai, Ya G., and A. B. Soshnikov. "A refinement of Wigner's semicircle law in a neighborhood of the spectrum edge for random symmetric matrices." Functional Analysis and Its Applications 32, no. 2 (April 1998): 114–31. http://dx.doi.org/10.1007/bf02482597.

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Kuprat, Andrew, Denise George, Eldon Linnebur, Harold Trease, and R. Kent Smith. "Moving Adaptive Unstructured 3-D Meshes in Semiconductor Process Modeling Applications." VLSI Design 6, no. 1-4 (January 1, 1998): 373–78. http://dx.doi.org/10.1155/1998/15828.

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The next generation of semiconductor process and device modeling codes will require 3-D mesh capabilities including moving volume and surface grids, adaptive mesh refinement and adaptive mesh smoothing. To illustrate the value of these techniques, a time dependent process simulation model was constructed using analytic functions to return time dependent dopant concentration and time dependent SiO2 volume and surface velocities. Adaptive mesh refinement and adaptive mesh smoothing techniques were used to resolve the moving boron dopant diffusion front in the Si substrate. The adaptive mesh smoothing technique involves minimizing the L2 norm of the gradient of the error between the true dopant concentration and the piecewise linear approximation over the tetrahedral mesh thus assuring that the mesh is optimal for representing evolving solution gradients. Also implemented is constrained boundary smoothing, wherein the moving SiO2/Si interface is represented by moving nodes that correctly track the interface motion, and which use their remaining degrees of freedom to minimize the aforementioned error norm. Thus, optimal tetrahedral shape and alignment is obtained even in the neighborhood of a moving boundary. If desired, a topological “reconnection” step maintains a Delaunay mesh at all times. The combination of adaptive refinement, adaptive smoothing, and mesh reconnection gives excellent front tracking, feature resolution, and grid quality for finite volume/finite element computation.
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Wang, Cai Ling, Chun Xia Zhao, and Jing Yu Yang. "Local Upsampling Fourier Transform for High Accuracy Image Rotation Estimation." Advanced Materials Research 268-270 (July 2011): 1488–93. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1488.

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A high accuracy rotation angle estimation algorithm based on Local Upsampling Fourier Transform (LUFT) is developed in this paper. The LUFT uses a hierarchical strategy to estimate the rotation, which consists of a transformation of rotation to translation, a fast coarse rotation estimation and a robust refinement stage as well. The coarse rotation is estimated through the conventional Phase Only Correlation (POC), then, it is refined by the resampling technique within a local neighborhood in frequency domain. Furthermore, as will be shown in many experiments, the LUFT can achieve high accuracy rotation estimation, where the accuracy is tunable to some extent. Specially, it is efficient and robust to noise.
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Dissertations / Theses on the topic "Neighborhood refinement"

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Gashler, Michael S. "Advancing the Effectiveness of Non-Linear Dimensionality Reduction Techniques." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3216.

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Data that is represented with high dimensionality presents a computational complexity challenge for many existing algorithms. Limiting dimensionality by discarding attributes is sometimes a poor solution to this problem because significant high-level concepts may be encoded in the data across many or all of the attributes. Non-linear dimensionality reduction (NLDR) techniques have been successful with many problems at minimizing dimensionality while preserving intrinsic high-level concepts that are encoded with varying combinations of attributes. Unfortunately, many challenges remain with existing NLDR techniques, including excessive computational requirements, an inability to benefit from prior knowledge, and an inability to handle certain difficult conditions that occur in data with many real-world problems. Further, certain practical factors have limited advancement in NLDR, such as a lack of clarity regarding suitable applications for NLDR, and a general inavailability of efficient implementations of complex algorithms. This dissertation presents a collection of papers that advance the state of NLDR in each of these areas. Contributions of this dissertation include: • An NLDR algorithm, called Manifold Sculpting, that optimizes its solution using graduated optimization. This approach enables it to obtain better results than methods that only optimize an approximate problem. Additionally, Manifold Sculpting can benefit from prior knowledge about the problem. • An intelligent neighbor-finding technique called SAFFRON that improves the breadth of problems that existing NLDR techniques can handle. • A neighborhood refinement technique called CycleCut that further increases the robustness of existing NLDR techniques, and that can work in conjunction with SAFFRON to solve difficult problems. • Demonstrations of specific applications for NLDR techniques, including the estimation of state within dynamical systems, training of recurrent neural networks, and imputing missing values in data. • An open source toolkit containing each of the techniques described in this dissertation, as well as several existing NLDR algorithms, and other useful machine learning methods.
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Book chapters on the topic "Neighborhood refinement"

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Cantarell, Sébastien, Ajoy K. Datta, and Franck Petit. "Self-Stabilizing Atomicity Refinement Allowing Neighborhood Concurrency." In Lecture Notes in Computer Science, 102–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45032-7_8.

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Vorozhtsov, E. V., and N. N. Yanenko. "Difference Solution Refinement in the Neighborhood of Strong Discontinuities." In Methods for the Localization of Singularities in Numerical Solutions of Gas Dynamics Problems, 222–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-61271-8_6.

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Conference papers on the topic "Neighborhood refinement"

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Valejo, Alan, Jorge Valverde-Rebaza, Brett Drury, and Alneu de Andrade Lopes. "Multilevel refinement based on neighborhood similarity." In the 18th International Database Engineering & Applications Symposium. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2628194.2628227.

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Nejat, Amir, Pooya Mirzabeygi, Masoud Shariat-Panahi, and Ehsan Mirzakhalili. "Heat Transfer Enhancement Across a Pair of Confined Cylinders Using Improved Particle Swarm Optimization Algorithm." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-88833.

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The dissipation of the heat generated by electronic devices is the key issue in design and development of such products. The trend, especially in the computer industries, has been reducing the size and increasing the computing power of the electronic elements. Studies have indicated that the thermal performance of a micro-channel depends on its geometric parameters and flow conditions. Many techniques have been developed to enhance the performance of confined elliptical cylinders while minimizing the momentum loss. In this paper, a new robust optimization technique is presented. This new technique is an improved Particle Swarm Optimization (PSO) algorithm in which diversity is actively preserved by avoiding overcrowded clusters of particles and encouraging broader exploration. Adaptively varying “territories” are formed around promising individuals to prevent many of the lesser individuals from premature clustering and encouraged them to explore new neighborhoods based on a hybrid self-social metric. Also, a new social interaction scheme is introduced which guided particles towards the weighted average of their “elite” neighbors’ best found positions instead of their own personal bests. The case study in this paper is a two dimensional incompressible flow of non-Newtonian power-law fluid over a pair of elliptical tandem cylinders confined in a channel. A new curve parameterization named Class-Shape-Refinement-Transformation method is used to modify the shape of the confined cylinders, and its control points are adopted as the design variables. Furthermore, final solutions obtained from the Territorial Particle Swarm Optimization algorithm reveal an evident improvement over the test case cylinder across all objective functions presented.
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