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Journal articles on the topic 'Euclidean distances'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Cubukcu, K. Mert, and Hatcha Taha. "Are Euclidean Distance and Network Distance Related ?" Environment-Behaviour Proceedings Journal 1, no. 4 (2016): 167. http://dx.doi.org/10.21834/e-bpj.v1i4.137.

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Although spatial distance is a very important concept for a wide variety of disciplines including social, natural, and information sciences, the methods used to measure spatial distance are not directly expressed and fully explained. In this study, we calculate and compare Euclidean distances and network distances for 10 randomly selected European cities. On the contrary to the findings reported in past research, we find that there is not a global straight forward relation between the Euclidian distance and network distance.© 2016. The Authors. Published for AMER ABRA by e-International Publis

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AICHHOLZER, OSWIN, FRANZ AURENHAMMER, DANNY Z. CHEN, D. T. LEE, and EVANTHIA PAPADOPOULOU. "SKEW VORONOI DIAGRAMS." International Journal of Computational Geometry & Applications 09, no. 03 (1999): 235–47. http://dx.doi.org/10.1142/s0218195999000169.

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On a tilted plane T in three-space, skew distances are defined as the Euclidean distance plus a multiple of the signed difference in height. Skew distances may model realistic environments more closely than the Euclidean distance. Voronoi diagrams and related problems under this kind of distances are investigated. A relationship to convex distance functions and to Euclidean Voronoi diagrams for planar circles is shown, and is exploited for a geometric analysisis and a plane-sweep construction of Voronoi diagrams on T. An output-sensitive algorithm running in time O(n log h) is developed, where

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Rodríguez-Larralde, Alvaro. "Genetic distance estimated through surname frequencies of 37 counties from the state of Lara, Venezuela." Journal of Biosocial Science 25, no. 1 (1993): 101–10. http://dx.doi.org/10.1017/s0021932000020344.

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SummaryGenetic distances between all possible pairs of counties (n = 37) in the state of Lara, Venezuela were calculated using surname frequencies and the Euclidean distance as estimator. In general, Euclidean distances were smaller between counties closer together, and the product moment correlation between geographic and Euclidean distances was 0·49 (p < 0.02). The results suggest that, in Lara, geographic distance has been an important determinant of genetic structure, although topography and roadways also have had an important influence upon this structure.

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Fearn, Tom. "Mahalanobis and Euclidean Distances." NIR news 21, no. 1 (2010): 12–14. http://dx.doi.org/10.1255/nirn.1167.

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Hajdu, András, Lajos Hajdu, and Robert Tijdeman. "Approximation of the Euclidean Distance by Chamfer Distances." Acta Cybernetica 20, no. 3 (2012): 399–417. http://dx.doi.org/10.14232/actacyb.20.3.2012.3.

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Karachurina, Liliya B., and Nikita V. Mkrtchyan. "The experience of calculating distances between different types of settlements in Russia to assess the range of population migration." Vestnik of Saint Petersburg University. Earth Sciences 68, no. 3 (2023): 418–42. http://dx.doi.org/10.21638/spbu07.2023.301.

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The problem of measuring distances in migration is not trivial, but important, for example, for delimiting the concepts of population migration and housing mobility. In conditions of limited access to detailed spatial data, researchers solve this issue in different ways. Only a few countries, such as Sweden, have the ability to calculate migration distances between point locations using Euclidean distance (in a straight line). In this article, as applied to Russia, the measure of correspondence between Euclidean distances and real distances along transport routes is investigated. For this purp

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Vijay, Sujith. "Eleven Euclidean distances are enough." Journal of Number Theory 128, no. 6 (2008): 1655–61. http://dx.doi.org/10.1016/j.jnt.2007.08.016.

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Sinha, Hari Om Sharan. "Enhancement of “Technique for Order Preference by Similarity to Ideal Solution” Approach for Evaluating the Web Sources to Select as External Source for Web Warehousing." International Journal of Natural Computing Research 6, no. 1 (2017): 1–16. http://dx.doi.org/10.4018/ijncr.2017010101.

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The main concern of this paper is to evaluate the web sources, which are to be selected as external data sources for web warehousing. In order to identify the web sources, they are evaluated on the ground of their multiple features. For it, Multi Criteria Decision Making (MCDM) approach has been used. Here, among all the MCDM approach, the focus is on “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) approach and proposing an enhancement in this method. The conventional TOPSIS approach uses Euclidean Distance to measure the similarity. Here, Jeffrey Divergence has been

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Guzmán Naranjo, Matías, and Gerhard Jäger. "Euclide, the crow, the wolf and the pedestrian: distance metrics for linguistic typology." Open Research Europe 3 (July 2, 2024): 104. http://dx.doi.org/10.12688/openreseurope.16141.2.

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It is common for people working on linguistic geography, language contact and typology to make use of some type of distance metric between lects. However, most work so far has either used Euclidean distances, or geodesic distance, both of which do not represent the real separation between communities very accurately. This paper presents two datasets: one on walking distances and one on topographic distances between over 8700 lects across all macro-areas. We calculated walking distances using Open Street Maps data, and topographic distances using digital elevation data. We evaluate these distan

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Marques, Samuel de França, Renan Favero, and Cira Souza Pitombo. "Should We Account for Network Distances or Anisotropy in the Spatial Estimation of Missing Traffic Data?" TRANSPORTES 31, no. 1 (2023): e2822. http://dx.doi.org/10.58922/transportes.v31i1.2822.

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In light of the unavailability of traffic volume data for all road segments, the scientific literature proposes estimating this variable using spatial interpolators. However, most of the methods found use the Euclidean distance between the database points as a proximity measure, in addition to ignoring the anisotropy of the phenomenon. Thus, the objective of the present study was to apply Ordinary Kriging (OK) with network distances and anisotropic OK in traffic volume data on highways in the state of São Paulo (Brazil), comparing its results to the traditional isotropic approach with Euclidea

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Coscia, Michele. "Generalized Euclidean Measure to Estimate Network Distances." Proceedings of the International AAAI Conference on Web and Social Media 14 (May 26, 2020): 119–29. http://dx.doi.org/10.1609/icwsm.v14i1.7284.

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Estimating the distance covered by a propagation phenomenon on a network is an important task: it can help us estimating the infectiousness of a disease or the effectiveness of an online viral marketing campaign. However, so far the only way to make such an estimate relies on solving the optimal transportation problem, or by adapting graph signal processing techniques. Such solutions are either inefficient, because they require solving a complex optimization problem; or fragile, because they were not designed with this problem in mind. In this paper, we propose a new generalized Euclidean appr

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De Santis, Gustavo, and Massimo Mucciardi. "From Euclidean distances to APC models." Quality & Quantity 51, no. 2 (2016): 829–46. http://dx.doi.org/10.1007/s11135-016-0442-y.

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Morin, Léo, Pierre Gilormini, and Katell Derrien. "Generalized Euclidean Distances for Elasticity Tensors." Journal of Elasticity 138, no. 2 (2019): 221–32. http://dx.doi.org/10.1007/s10659-019-09741-z.

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Jeon, Heonbae, Soonbong Lee, Hongseon Kim, Seung Bum Soh, and Seongmoon Kim. "Portfolio Evaluation with the Vector Distance Based on Portfolio Composition." Mathematics 11, no. 1 (2023): 221. http://dx.doi.org/10.3390/math11010221.

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We propose a novel portfolio evaluation method, a distance-based approach, which directly evaluates the portfolio composition rather than portfolio returns. In this approach, we consider a portfolio as an estimator for an in-sample tangency portfolio, which we define as the optimal reference portfolio. We then evaluate the portfolio by computing its vector distance to the optimal reference portfolio. In search of the proper distance-based performance measure, we choose four representative vector distances and compare their suitability as a new portfolio performance measure. Through extensive s

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AÇIKGÖZ, Abdulaziz. "On Directed Length Ratios in the Lorentz-Minkowski Plane." Cumhuriyet Science Journal 44, no. 4 (2023): 733–40. http://dx.doi.org/10.17776/csj.1133780.

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The linear structure of the Lorentz-Minkowski plane is almost the same as Euclidean plane. But, there is one different aspect. These planes have different distance functions. So, it can be interesting to study the Lorentz analogues of topics that include the distance concept in the Euclidean plane. Thus, in this study, we show that the relationship between Euclidean and Lorentz distances is given depending on the slope of the line segment. Following, we investigate Lorentz analogues of Thales’ theorem, Angle Bisector theorems, Menelaus’ theorem and Ceva’s theorem.

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Ayorinde, Adenola F., Bola O. Oboh, and Olubunmi A. Otubanjo. "Differentiation of some populations of Aedes aegypti (Diptera: Culicidae) in three areas of Lagos State, Nigeria, using wing morphometry." International Journal of Tropical Insect Science 36, no. 04 (2016): 171–76. http://dx.doi.org/10.1017/s1742758416000151.

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AbstractDiversity amongst the different populations is one of the problems in the control of medically important mosquitoes. Wing morphometry was used to identify within-species variation amongst some populations ofAedes aegyptiin three areas of Lagos State, Nigeria. Ten landmarks on the right wing of adult femaleAe. aegyptimosquitoes were digitized using TPSdig software. Relative distances of the veins and interpoints were calculated as well as the Euclidean distances based on these relative distances. In three (50%) of the interpoints, the relative distances were significant (P&lt;0.05)

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CHAN, TIMOTHY M. "ON ENUMERATING AND SELECTING DISTANCES." International Journal of Computational Geometry & Applications 11, no. 03 (2001): 291–304. http://dx.doi.org/10.1142/s0218195901000511.

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Given an n-point set, the problems of enumerating the k closest pairs and selecting the k-th smallest distance are revisited. For the enumeration problem, we give simpler randomized and deterministic algorithms with O(n log n+k) running time in any fixed-dimensional Euclidean space. For the selection problem, we give a randomized algorithm with running time O(n log n+n2/3k1/3 log 5/3n) in the Euclidean plane. We also describe output-sensitive results for halfspace range counting that are of use in more general distance selection problems. None of our algorithms requires parametric search.

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Guzmán Naranjo, Matías, and Gerhard Jäger. "Euclide, the crow, the wolf and the pedestrian: distance metrics for linguistic typology." Open Research Europe 3 (June 21, 2023): 104. http://dx.doi.org/10.12688/openreseurope.16141.1.

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It is common for people working on linguistic geography, language contact and typology to make use of some type of distance metric between lects. However, most work so far has either used Euclidean distances, or geodesic distance, both of which do not represent the real separation between communities very accurately. This paper presents two datasets: one on walking distances and one on topographic distances between over 8700 lects across all macro-areas. We calculated walking distances using Open Street Maps data, and topographic distances using digital elevation data. We evaluate these distan

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Bouanchaud, Paul, Peter M. Macharia, Eden G. Demise, and Doreen Nakimuli. "Comparing modelled with self-reported travel time and the used versus the nearest facility: modelling geographic accessibility to family planning outlets in Kenya." BMJ Global Health 7, no. 5 (2022): e008366. http://dx.doi.org/10.1136/bmjgh-2021-008366.

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IntroductionGeographic access to family planning (FP) services has been characterised through a variety of proximity metrics. However, there is little evidence on the validity of women’s self-reported compared with modelled travel time to an FP outlet, or between different distance measures.MethodsWe used data from four urban sites in Kenya. A longitudinal FP outlet census was directly linked with data from cross-sectional FP user surveys. We combined characteristics of outlet visited to obtain FP, transport mode, self-reported travel time and location of households and outlets with data on ro

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Balajee, R., and M. S. DhanaRajan. "Determination Of Euclidean Distances For Symmetry Molecules." International Journal on Applied Bio-Engineering 4, no. 2 (2010): 34–39. http://dx.doi.org/10.18000/ijabeg.10068.

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Soares, José. "Approximating Euclidean distances by small degree graphs." Discrete & Computational Geometry 11, no. 2 (1994): 213–33. http://dx.doi.org/10.1007/bf02574005.

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Jiang, Jian-lin, and Ya Xu. "Minisum location problem with farthest Euclidean distances." Mathematical Methods of Operations Research 64, no. 2 (2006): 285–308. http://dx.doi.org/10.1007/s00186-006-0084-2.

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Midler, Jean-Claude. "Non-Euclidean Geographic Spaces: Mapping Functional Distances." Geographical Analysis 14, no. 3 (2010): 189–203. http://dx.doi.org/10.1111/j.1538-4632.1982.tb00068.x.

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Swanepoel, Konrad J. "Unit Distances and Diameters in Euclidean Spaces." Discrete & Computational Geometry 41, no. 1 (2008): 1–27. http://dx.doi.org/10.1007/s00454-008-9082-x.

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K, Bonya, Twum S. B, and Etwire C. J. "A Revised TOPSIS with Weighted Euclidean Distances." IOSR Journal of Mathematics 21, no. 3 (2025): 14–28. https://doi.org/10.9790/0661-2103031428.

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Multi-Criteria Decision Making (MCDM) techniques have attracted significant attention from researchers and professionals across diverse industries due to their ability to effectively evaluate, assess, and rank alternatives. However, choosing the most suitable MCDM method for a specific problem can be challenging, especially when several methods appear equally applicable. Among these methods, the Technique for Order of Performance by Similarity to Ideal Solution (TOPSIS) is widely used, leading researchers to propose various improved versions. This research focuses on enhancing the traditional

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JANG, SEOK-WOO, and SANG-HONG LEE. "NEURO-FUZZY SYSTEM FOR DETECTING PD PATIENTS BASED ON EUCLID DISTANCE, FFT, AND PCA." Journal of Mechanics in Medicine and Biology 20, no. 09 (2020): 2040017. http://dx.doi.org/10.1142/s0219519420400175.

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This study proposes a method to distinguish between healthy people and Parkinson’s disease patients using sole pressure sensor data, neural network with weighted fuzzy membership (NEWFM), and preprocessing techniques. The preprocessing techniques include fast Fourier transform (FFT), Euclidean distance, and principal component analysis (PCA), to remove noise in the data for performance enhancement. To make the features usable as inputs for NEWFM, the Euclidean distances between the left and right sole pressure sensor data were used at the first step. In the second step, the frequency scales of

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Wang, Jing, and Kehan Chen. "Classification of ancient glassware based on K-means and decision trees." Highlights in Science, Engineering and Technology 58 (July 12, 2023): 94–104. http://dx.doi.org/10.54097/hset.v58i.10033.

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In this paper, the relation between the chemical composition of different types of glass objects was analyzed, and the differences between the chemical compositions were used to classify the glass objects, mainly by K-means, decision tree, and Euclidean distance analysis. For the classification of glass artifacts, this article analyzed the chemical composition of different types of glass artifacts and the changes of chemical composition before and after weathering, and then obtained the differences of chemical composition of different types of glass artifacts to obtain the classification law.

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Margolang, Khairul Fadhli, Muhammad Mizan Siregar, Sugeng Riyadi, and Zakarias Situmorang. "Analisa Distance Metric Algoritma K-Nearest Neighbor Pada Klasifikasi Kredit Macet." Journal of Information System Research (JOSH) 3, no. 2 (2022): 118–24. http://dx.doi.org/10.47065/josh.v3i2.1262.

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Data mining is a method that can classify data into different classes based on the features in the data. With data mining, non-performance loan categories can be classified based on data on lending from cooperatives to their members. This study uses K-Nearest Neighbor to classify non-performance loan categories with various distance metric variations such as Chebyshev, Euclidean, Mahalanobis, and Manhattan. The evaluation results using 10-fold cross-validation show that the Euclidean distance has the highest accuracy, precision, F1, and sensitivity values compared to other distance metrics.

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Margolang, Khairul Fadhli, Muhammad Mizan Siregar, Sugeng Riyadi, and Zakarias Situmorang. "Analisa Distance Metric Algoritma K-Nearest Neighbor Pada Klasifikasi Kredit Macet." Journal of Information System Research (JOSH) 3, no. 2 (2022): 118–24. http://dx.doi.org/10.47065/josh.v3i2.1262.

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Data mining is a method that can classify data into different classes based on the features in the data. With data mining, non-performance loan categories can be classified based on data on lending from cooperatives to their members. This study uses K-Nearest Neighbor to classify non-performance loan categories with various distance metric variations such as Chebyshev, Euclidean, Mahalanobis, and Manhattan. The evaluation results using 10-fold cross-validation show that the Euclidean distance has the highest accuracy, precision, F1, and sensitivity values compared to other distance metrics.

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Jeszenszky, Péter, Philipp Stoeckle, Elvira Glaser, and Robert Weibel. "Exploring global and local patterns in the correlation of geographic distances and morphosyntactic variation in Swiss German." Journal of Linguistic Geography 5, no. 2 (2017): 86–108. http://dx.doi.org/10.1017/jlg.2017.5.

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Using data from a Swiss German dialect syntax survey, this study aims to explore, in a spatially differentiated manner, the correlation between dialectal variation and geographic distances. A linguistic distance was expressed by a measure aggregated from 60 survey questions. To operationalize the possibility of language contact, Euclidean distance, as well as travel times in 2000, 1950 and 1850 between survey sites were used. Going beyond previous work by others, we also explore the covariation of geographic and linguistic distances at the local level, focusing on spatial subsets and individua

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Rook, Ashley, Mathews M. John, Allison Post, and Mehdi Razavi. "Alcohol Ablation of Cardiac Tissues Quantified and Evaluated Using CIELAB Euclidean Distances." Texas Heart Institute Journal 47, no. 4 (2020): 265–70. http://dx.doi.org/10.14503/thij-19-7140.

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Ethanol solubilizes cell membranes, making it useful for various ablation applications. We examined the effect of time and alcohol type on the extent of ablation, quantified as Euclidean distances between color coordinates. We obtained biopsy punch samples (diameter, 6 mm) of left atrial appendage, atrial, ventricular, and septal tissue from porcine hearts and placed them in transwell plates filled with ethanol or methanol for 10, 20, 30, 40, 50, or 60 min. Control samples were taken for each time point. At each time point, samples were collected, cut transversely, and photographed. With use o

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Yohannes, Yohannes, and Muhammad Ezar Al Rivan. "Penggunaan Global Contrast Saliency dan Histogram of Oriented Gradient Sebagai Fitur untuk Klasifikasi Jenis Hewan Mamalia." PETIR 13, no. 1 (2020): 80–85. http://dx.doi.org/10.33322/petir.v13i1.908.

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Mammal type can be classified based on the face. Every mammal’s face has a different shape. Histogram of Oriented Gradient (HOG) used to get shape feature from mammal’s face. Before this step, Global Contrast Saliency used to make images focused on an object. This process conducts to get better shape features. Then, classification using k-Nearest Neighbor (k-NN). Euclidean and cityblock distance with k=3,5,7 and 9 used in this study. The result shows cityblock distance with k=9 better than Euclidean distance for each k. Tiger is superior to others for all distances. Sheep is bad classified.

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Mielke, Paul W., and Kenneth J. Berry. "Multivariate Multiple Regression Analyses: A Permutation Method for Linear Models." Psychological Reports 91, no. 1 (2002): 3–9. http://dx.doi.org/10.2466/pr0.2002.91.1.3.

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A multivariate extension of a univariate procedure for the analysis of experimental designs is presented. A Euclidean-distance permutation procedure is used to evaluate multivariate residuals obtained from a regression algorithm, also based on Euclidean distances. Applications include various completely randomized and randomized block experimental designs such as one-way, Latin square, factorial, nested, and split-plot designs, with and without covariates. Unlike parametric procedures, the only required assumption is the randomization of subjects to treatments.

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Böröczky, Károly, and Zsolt Lángi. "On the relative distances of six points in a plane convex body." Studia Scientiarum Mathematicarum Hungarica 42, no. 3 (2005): 253–64. http://dx.doi.org/10.1556/sscmath.42.2005.3.1.

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Let C be a convex body in the Euclidean plane. By the relative distance of points p and q we mean the ratio of the Euclidean distance of p and q to the half of the Euclidean length of a longest chord of C parallel to pq. In this note we find the least upper bound of the minimum pairwise relative distance of six points in a plane convex body.

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Li, Dan, and Xin Bao Li. "A Modified Version of the K-Means Algorithm Based on the Shape Similarity Distance." Applied Mechanics and Materials 457-458 (October 2013): 1064–68. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.1064.

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K-means Algorithm is a popular method in cluster analysis, and it is most based on the Euclidean distance. In this paper, a modified version of the K-means algorithm based on the shape similarity distance (SSD-K-means) is presented. The shape similarity distance is one kind of non-metric distance measure for similarity estimation based on the characteristic of differences. To demonstrate the effectiveness of the method we proposed, this new algorithm has been tested on three shape data datasets. Experiment results prove that the performance of the SSD-K-means is better than those of the classi

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Yenisetty, Pavan, and Pankaj Bahadure. "Measuring Accessibility to Various ASFs from Public Transit using Spatial Distance Measures in Indian Cities." ISPRS International Journal of Geo-Information 9, no. 7 (2020): 446. http://dx.doi.org/10.3390/ijgi9070446.

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Nowadays, accessibility to facilities is one of the most discussed issues in sustainable urban planning. In the current research, two spatial distance accessibility measures were applied to evaluate the accessibility to amenities, services, and facilities (ASFs) from public transit (PT) by walking distance in six Indian cities. The first stage accounts for distance measures using the Euclidean distance with a new methodical approach derived from the built-up area with a spatial resolution of 30 m from Landsat data, and for the network distance method, the actual road distances using OpenStreet

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Pereira, R., X. Mestre, and D. Gregoratti. "Consistent Estimation of a Class of Distances Between Covariance Matrices." IEEE TRANSACTIONS ON INFORMATION THEORY 70, no. 11 (2024): 8107–32. https://doi.org/10.1109/TIT.2024.3464678.

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This work considers the problem of estimating the distance between two covariance matrices directly from the data. Particularly, we are interested in the family of distances that can be expressed as sums of traces of functions that are separately applied to each covariance matrix. This family of distances is particularly useful as it takes into consideration the fact that covariance matrices lie in the Riemannian manifold of positive definite matrices, thereby including a variety of commonly used metrics, such as the Euclidean distance, Jeffreys' divergence, and the log-Euclidean distance. Mor

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Rayner, D. Chris, Michael Bowling, and Nathan Sturtevant. "Euclidean Heuristic Optimization." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (2011): 81–86. http://dx.doi.org/10.1609/aaai.v25i1.7815.

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We pose the problem of constructing good search heuristics as an optimization problem: minimizing the loss between the true distances and the heuristic estimates subject to admissibility and consistency constraints. For a well-motivated choice of loss function, we show performing this optimization is tractable. In fact, it corresponds to a recently proposed method for dimensionality reduction. We prove this optimization is guaranteed to produce admissible and consistent heuristics, generalizes and gives insight into differential heuristics, and show experimentally that it produces strong heuri

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A. Leonardo, Patrick, Mahfud Arifin, and Shantosa Yudha Siswanto. "Penerapan Euclidean Distance untuk analisis driver variable Perubahan Penggunaan Lahan dari Jarak Jalan di Sub-DAS Cikapundung." soilrens 22, no. 1 (2024): 61–66. https://doi.org/10.24198/soilrens.v22i1.57248.

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The Cikapundung Sub-watershed is part of the Upper Citarum Watershed, with its catchment area covering West Bandung Regency, Bandung City, and Bandung Regency. The increasing land use activities in the Cikapundung Sub-watershed have driven significant development activities in the upper areas of the subwatershed. One of the factors influencing this development is the road network, which affects the accessibility of an area, known as the driver variable. The creation of this driver variable requires GIS analysis using the Euclidean distance module, which calculates the distance from the roads.

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Cazzaro, Mirco, Francesca Scolamacchia, Paolo Mulatti, and Nicola Ferrè. "Development of a tool to calculate distance for veterinary epidemiological applications." AGILE: GIScience Series 5 (May 30, 2024): 1–4. http://dx.doi.org/10.5194/agile-giss-5-19-2024.

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Abstract. The transmission of infectious diseases is intricately linked to spatiotemporal proximity. Spatial data used in veterinary epidemiology to depict the distribution of disease events typically encompasses pairwise distances between two locations. The Euclidean method is commonly employed to compute such distances. We have developed a tool capable of calculating pairwise distances, considering factors such as orography, the road network, or the land use, given a set of points representing farms or outbreak sites where samples have been collected. The outcome is a three dimensional objec

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Jiang, Yueyu, Puoya Tabaghi, and Siavash Mirarab. "Learning Hyperbolic Embedding for Phylogenetic Tree Placement and Updates." Biology 11, no. 9 (2022): 1256. http://dx.doi.org/10.3390/biology11091256.

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Phylogenetic placement, used widely in ecological analyses, seeks to add a new species to an existing tree. A deep learning approach was previously proposed to estimate the distance between query and backbone species by building a map from gene sequences to a high-dimensional space that preserves species tree distances. They then use a distance-based placement method to place the queries on that species tree. In this paper, we examine the appropriate geometry for faithfully representing tree distances while embedding gene sequences. Theory predicts that hyperbolic spaces should provide a drast

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Song, Haifeng, Lvqing Bi, Bo Hu, Yingying Xu, and Songsong Dai. "New Distance Measures between the Interval-Valued Complex Fuzzy Sets with Applications to Decision-Making." Mathematical Problems in Engineering 2021 (March 5, 2021): 1–9. http://dx.doi.org/10.1155/2021/6685793.

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As a generalization of complex fuzzy set (CFS), interval-valued complex fuzzy set (IVCFS) is a new research topic in the field of CFS theory, which can handle two different information features with the uncertainty. Distance is an important tool in the field of IVCFS theory. To enhance the applicability of IVCFS, this paper presents some new interval-valued complex fuzzy distances based on traditional Hamming and Euclidean distances of complex numbers. Furthermore, we elucidate the geometric properties of these distances. Finally, these distances are used to deal with decision-making problem i

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Komjáth, Péter, and James Schmerl. "GRAPHS ON EUCLIDEAN SPACES DEFINED USING TRANSCENDENTAL DISTANCES." Mathematika 58, no. 1 (2011): 1–9. http://dx.doi.org/10.1112/s0025579311001999.

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Ohsawa, Yoshiaki, Naoya Ozaki, and Frank Plastria. "Equity-Efficiency Bicriteria Location with Squared Euclidean Distances." Operations Research 56, no. 1 (2008): 79–87. http://dx.doi.org/10.1287/opre.1070.0502.

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Solymosi, Jozsef, and Csaba D. Toth. "Distinct Distances in Homogeneous Sets in Euclidean Space." Discrete & Computational Geometry 35, no. 4 (2006): 537–49. http://dx.doi.org/10.1007/s00454-006-1232-4.

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Aykin, Turgut, and A. J. G. Babu. "Multifacility location problems on a sphere." International Journal of Mathematics and Mathematical Sciences 10, no. 3 (1987): 583–95. http://dx.doi.org/10.1155/s0161171287000693.

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A unified approach to multisource location problems on a sphere is presented. Euclidean, squared Euclidean and the great circle distances are considered. An algorithm is formulated and its convergence properties are investigated.

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Wahyuningsih, Sri, Elida Novita, Rufiani Nadzirah, and Tiara Dwi Nadila. "IDENTIFIKASI SEBARAN SUMBER PENCEMAR TERHADAP KUALITAS AIR SUNGAI BEDADUNG SEGMEN KECAMATAN BALUNG - WULUHAN MENGGUNAKAN METODE JARAK EUCLIDEAN." Jurnal Purifikasi 23, no. 2 (2025): 47–52. https://doi.org/10.12962/purifikasi.v23i2.460.

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The Bedadung River is one of the largest rivers located in Jember Regency, flowing through the Balung andWuluhan districts. Along the river, the community utilizes land use such as residential areas, rice fields,plantations, and cement factories for various needs. Community activities around the river generate waste that has the potential to degrade the water quality of the Bedadung River. This study aims to analyze the impact of the proximity of pollution sources on river water quality by mapping the distance between land-use sources and research locations using the Euclidean Distance method.

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Wang, Jiancheng, Yajing Guan, Yang Wang, et al. "Establishing an Efficient Way to Utilize the Drought Resistance Germplasm Population in Wheat." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/489583.

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Drought resistance breeding provides a hopeful way to improve yield and quality of wheat in arid and semiarid regions. Constructing core collection is an efficient way to evaluate and utilize drought-resistant germplasm resources in wheat. In the present research, 1,683 wheat varieties were divided into five germplasm groups (high resistant, HR; resistant,R; moderate resistant, MR; susceptible,S; and high susceptible, HS). The least distance stepwise sampling (LDSS) method was adopted to select core accessions. Six commonly used genetic distances (Euclidean distance, Euclid; Standardized Eucli

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Ma, Xinwei, Yuchuan Jin, and Mingjia He. "Measuring Bikeshare Access/Egress Transferring Distance and Catchment Area around Metro Stations from Smartcard Data." Information 9, no. 11 (2018): 289. http://dx.doi.org/10.3390/info9110289.

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Metro–bikeshare integration is considered a green and efficient travel model. To better develop such integration, it is necessary to monitor and analyze metro–bikeshare transfer characteristics. This paper measures access and egress transferring distances and catchment areas based on smartcard data. A cubic regression model is conducted for the exploration of the 85th access and egress network-based transferring distance around metro stations. Then, the independent samples t-test and one-way analysis of variance (ANOVA) are used to explore access and egress transfer characteristics in demograp

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Palupi, Retno, Diyan Ayuk Yulianna, and SM Santi Winarsih. "Analisa Perbandingan Rumus Haversine Dan Rumus Euclidean Berbasis Sistem Informasi Geografis Menggunakan Metode Independent Sample t-Test." JITU : Journal Informatic Technology And Communication 5, no. 1 (2021): 40–47. http://dx.doi.org/10.36596/jitu.v5i1.494.

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Comparative Analysis of the Haversine Formula and the Euclidean Formula based on Geographical Information Systems which aims to analyze and compare the measurement results of the two formulas whether there are significant differences to the distance measured based on geographic information systems. Research objects used to collect distance data are several bank offices in the city of Solo. The method used in this research is to create a geographic information system application using web-based programming using the PHP (Pearl Hypertext Prepocessor) programming language, with the MySQL database

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