scholarly journals Extension of Colijn-Plazotta tree shape distance metric to unrooted trees

2018 ◽  
Author(s):  
Alexey Anatolievich Morozov
Keyword(s):  
Phylogenetic Tree ◽  
Euclidean Distance ◽  
Tree Topology ◽  
Proof Of Concept ◽  
Distance Metric ◽  
Tree Shape ◽  
Single Pass ◽  
The Difference ◽  
Shape Distance ◽  
Labeling Scheme

Colijn-Plazotta tree shape labeling scheme allows to describe an arbitrary phylogenetic tree topology by recursively labeling all nodes from tips to root with integers. The multisets of these labels can then be used to estimate the difference between topologies using eg Euclidean distance. In this work I propose an extension of the labeling scheme (and thus a distance metric) to unrooted trees, which is achieved by labeling all rooted subtrees within a given tree. To avoid exhaustively enumerating the subtrees, the labels are collected into a dependency graph and calculated in a single pass. A proof-of-concept implementation is available at https://github.com/synedraacus/metrics.

scholarly journals Possibility of Human Gender Recognition Using Raman Spectra of Teeth

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3983
Author(s):  
Ozren Gamulin ◽  
Marko Škrabić ◽  
Kristina Serec ◽  
Matej Par ◽  
Marija Baković ◽  
...  
Keyword(s):  
Raman Spectra ◽  
Principal Component ◽  
Support Vector ◽  
Gender Recognition ◽  
Proof Of Concept ◽  
Male And Female ◽  
Tooth Type ◽  
Tooth Apex ◽  
The Difference

Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof-of-concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigated. Raman spectra were recorded from male and female molars and premolars on two distinct sites, tooth apex and anatomical neck. Recorded spectra were sorted into suitable datasets and initially analyzed with principal component analysis, which showed a distinction between spectra of male and female teeth. Then, reduced datasets with scores of the first 20 principal components were formed and two classification algorithms, support vector machine and artificial neural networks, were applied to form classification models for gender recognition. The obtained results showed that gender recognition with Raman spectra of teeth is possible but strongly depends both on the tooth type and spectrum recording site. The difference in classification accuracy between different tooth types and recording sites are discussed in terms of the molecular structure difference caused by the influence of masticatory loading or gender-dependent life events.

scholarly journals Analysis of the Difference between the Euclidean Distance and the Actual Road Distance in Brazil

2014 ◽  
Vol 3 ◽  
pp. 876-885 ◽  
Author(s):  
Daniel Neves Schmitz Gonçalves ◽  
Carolinne de Morais Gonçalves ◽  
Tássia Faria de Assis ◽  
Marcelino Aurélio da Silva
Keyword(s):  
Euclidean Distance ◽  
The Difference ◽  
Road Distance

scholarly journals Evaluation of Atmospheric Effects on Interferograms Using DEM Errors of Fixed Ground Points

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2336 ◽  
Author(s):  
Takashi Nonaka ◽  
Tomohito Asaka ◽  
Keishi Iwashita
Keyword(s):  
Phase Noise ◽  
Atmospheric Effects ◽  
Sar Images ◽  
Single Pass ◽  
Digital Elevation ◽  
Total Phase ◽  
Disaster Monitoring ◽  
The Difference ◽  
Elevation Model ◽  
Interferometric Sar

High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms.

scholarly journals Hierarchical dinucleotide distribution in genome along evolution and its effect on chromatin packing

2021 ◽  
Vol 4 (8) ◽  
pp. e202101028
Author(s):  
Zhicheng Cai ◽  
Yueying He ◽  
Sirui Liu ◽  
Yue Xue ◽  
Hui Quan ◽  
...  
Keyword(s):  
Phylogenetic Tree ◽  
Chromatin Structure ◽  
Distribution Patterns ◽  
Length Scales ◽  
Multi Scale ◽  
Topologically Associating Domain ◽  
Domain Boundaries ◽  
Chromatin Packing ◽  
The Difference ◽  
Genomic Length

Dinucleotide densities and their distribution patterns vary significantly among species. Previous studies revealed that CpG is susceptible to methylation, enriched at topologically associating domain boundaries and its distribution along the genome correlates with chromatin compartmentalization. However, the multi-scale organizations of CpG in the linear genome, their role in chromatin organization, and how they change along the evolution are only partially understood. By comparing the CpG distribution at different genomic length scales, we quantify the difference between the CpG distributions of different species and evaluate how the hierarchical uneven CpG distribution appears in evolution. The clustering of species based on the CpG distribution is consistent with the phylogenetic tree. Interestingly, we found the CpG distribution and chromatin structure to be correlated in many different length scales, especially for mammals and avians, consistent with the mosaic CpG distribution in the genomes of these species.

scholarly journals An Efficient Algorithm for Maximizing Range Sum Queries in a Road Network

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Tien-Khoi Phan ◽  
HaRim Jung ◽  
Ung-Mo Kim
Keyword(s):  
Efficient Algorithm ◽  
Road Network ◽  
Euclidean Distance ◽  
Optimal Location ◽  
External Memory ◽  
Distance Metric ◽  
Network Database ◽  
Road Network Database

Given a set of positive-weighted points and a query rectangler(specified by a client) of given extents, the goal of a maximizing range sum (MaxRS) query is to find the optimal location ofrsuch that the total weights of all the points covered byrare maximized. All existing methods for processing MaxRS queries assume the Euclidean distance metric. In many location-based applications, however, the motion of a client may be constrained by an underlying (spatial) road network; that is, the client cannot move freely in space. This paper addresses the problem of processing MaxRS queries in a road network. We propose the external-memory algorithm that is suited for a large road network database. In addition, in contrast to the existing methods, which retrieve only one optimal location, our proposed algorithm retrieves all the possible optimal locations. Through simulations, we evaluate the performance of the proposed algorithm.

The level of socio-economic development of regions in Poland

2021 ◽  
Vol 66 (11) ◽  
pp. 27-47
Author(s):  
Jakub Kubiczek ◽  
Martyna Bieleń
Keyword(s):  
Economic Development ◽  
Environmental Protection ◽  
Euclidean Distance ◽  
Data Bank ◽  
Linear Ordering ◽  
Economic Policies ◽  
Local Data ◽  
Taxonomic Analysis ◽  
Socio Economic Development ◽  
The Difference

The development of regions within one country is an uneven process. States seek to reduce internal inequalities between particular regions through the implementation of appropriate economic policies, as is the case of Poland. The aim of the study is to evaluate the level of socio-economic development of regions in Poland (voivodships) in the years 2013– 2019. For this purpose, a taxonomic analysis based on Hellwig’s development measure was conducted and the Euclidean distance was applied to assess the difference between the obtained pattern and particular voivodships. On the basis of data provided by the Local Data Bank of Statistics Poland and through linear ordering, two rankings of voivodships were created: one reflecting their socio-economic development excluding environmental protection aspects and the other focusing solely on the issue of environmental protection. Low values of the coefficient of variation relating to a part of the analysed variables indicated that the development level of voivodships in the analysed period is in many respects very similar. The variables crucial for determining the differences between voivodships show that Mazowieckie Voivodship occupies high positions in both rankings (and is the leader in the ranking of socio-economic development excluding environmental protection aspects), while Warmińsko-Mazurskie Voivodship is characterised by a low level of development illustrated by both rankings.

scholarly journals Joint Geosequential Preference and Distance Metric Factorization for Point-of-Interest Recommendation

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chunyang Liu ◽  
Chao Liu ◽  
Haiqiang Xin ◽  
Jian Wang ◽  
Jiping Liu ◽  
...  
Keyword(s):  
Metric Space ◽  
Matrix Factorization ◽  
Euclidean Distance ◽  
Large Scale ◽  
Inner Product ◽  
Interaction Matrix ◽  
Distance Metric ◽  
Point Of Interest ◽  
Poi Recommendation ◽  
Real World Datasets

Point-of-interest (POI) recommendation is a valuable service to help users discover attractive locations in location-based social networks (LBSNs). It focuses on capturing users’ movement patterns and location preferences by using massive historical check-in data. In the past decade, matrix factorization has become a mature and widely used technology in POI recommendation. However, the inner product of latent vectors adopted in matrix factorization methods does not satisfy the triangle inequality property, which may limit the expressiveness and lead to suboptimal solutions. Besides, the extreme sparsity of check-in data makes it challenging to capture users’ movement preferences accurately. In this paper, we propose a joint geosequential preference and distance metric factorization framework, called GeoSeDMF, for POI recommendation. First, we introduce a distance metric factorization method that is capable of learning users’ personalized preferences from a position and distance perspective in the metric space. Specifically, we convert the user-POI interaction matrix into a distance matrix and factorize it into user and POI dense embeddings. Additionally, we measure users’ personalized preference for the POI by using the Euclidean distance metric instead of the inner product. Then, we model the users’ geospatial preference by applying a geographic weight coefficient and model the users’ sequential preference by using the Euclidean distance of continuous check-in locations. Moreover, a pointwise loss strategy and AdaGrad algorithm are adopted to optimize the positions and relationships of users and POIs in a metric space. Finally, experimental results on three large-scale real-world datasets demonstrate the effectiveness and superiority of the proposed method.

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