scholarly journals Application of Cluster Analysis in Research on the Spatial Dimension of Penalised Behaviour

2021 ◽  
Vol 94 ◽  
pp. 97-120
Author(s):  
Andrzej Porębski
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster ◽  
Spatial Dimension ◽  
Sociology Of Law ◽  
Large Dataset ◽  
Objective Criterion ◽  
Administrative Division ◽  
Administrative Units ◽  
The City ◽  
Crime Reports

This paper is focused on some of the possibilities of the use of cluster analysis (clustering) in criminology and the sociology of law. Cluster analysis makes it possible to divide even a large dataset into a specified number of subsets in such a way that the resulting subsets are as homogenous as possible, and at the same time differ from each other substantially. When analysing geographical data, e.g. describing the location of crimes, the result of cluster analysis is a division of a territory into a certain number of coherent areas based on an objective criterion. The division of the territory under study into smaller parts is more insightful when the clustering method is applied compared to an arbitrary division into official administrative units. The paper provides a detailed description of hierarchical cluster analysis methods and an example of using the Ward’s hierarchical method and the k-means combinational method to divide data on crime reports in the city of Baltimore between 2014 and 2019. The analysis demonstrates that the resulting division differs considerably from the administrative division of Baltimore, and that increasing the number of groups emerging as a result of cluster analysis leads to an increase of variance of variables describing the structure of crime in individual parts of the city. The divisions obtained using clustering are used to verify the hypothesis on differences in crime structure in different areas of Baltimore. The main aim of the paper is to encourage the use of modern methods of data analysis in social sciences and to present the usefulness of cluster analysis in criminology and the sociology of law research.

scholarly journals Proposed method for delimiting spatial structure on the example of agriculture types in Poland

2020 ◽  
Vol 49 (49) ◽  
pp. 7-18
Author(s):  
Łukasz Wiśniewski ◽  
Robert Perdał ◽  
Roman Rudnicki
Keyword(s):  
Cluster Analysis ◽  
Agricultural Development ◽  
Classification Methods ◽  
Third Order ◽  
The Third ◽  
Random Forest Method ◽  
Multi Stage ◽  
Administrative Division ◽  
Administrative Units ◽  
Level 2

AbstractThis work presents the results of research on the identification of types of Polish agriculture. Polish gminas (the third-order administrative division of the country sometimes referred to as “communes” or “municipalities”, until 2016 – according to Local Administrative Units – LAU level 2) have been divided into three types, characterised by low, medium or high levels of agricultural development, with 10 sub-types. A multi-stage typological procedure was used, employing two classification methods: k-mean cluster analysis and the random forest method. Twelve diagnostic attributes were used that comprehensively characterise Polish agriculture. The results show the diversity of this sector of the economy, which should be taken into account when planning its future development.

DRSA: a non-hierarchical clustering algorithm using k-NN graph and its application in vegetation classification

2015 ◽  
pp. 125-138 ◽  
Author(s):  
I. V. Goncharenko
Keyword(s):  
Cluster Analysis ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Clustering Algorithms ◽  
Protein Structures ◽  
Hierarchical Cluster ◽  
Vegetation Classification ◽  
K Nearest Neighbor ◽  
Neighbor Graph ◽  
Nearest Neighbor Graph

In this article we proposed a new method of non-hierarchical cluster analysis using k-nearest-neighbor graph and discussed it with respect to vegetation classification. The method of k-nearest neighbor (k-NN) classification was originally developed in 1951 (Fix, Hodges, 1951). Later a term “k-NN graph” and a few algorithms of k-NN clustering appeared (Cover, Hart, 1967; Brito et al., 1997). In biology k-NN is used in analysis of protein structures and genome sequences. Most of k-NN clustering algorithms build «excessive» graph firstly, so called hypergraph, and then truncate it to subgraphs, just partitioning and coarsening hypergraph. We developed other strategy, the “upward” clustering in forming (assembling consequentially) one cluster after the other. Until today graph-based cluster analysis has not been considered concerning classification of vegetation datasets.

Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

2020 ◽  
Vol 10 ◽  
Author(s):  
Nikunj D. Patel ◽  
Niranjan S. Kanaki
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Quality Evaluation ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Attenuated Total Reflectance ◽  
Chemometric Methods ◽  
Total Reflectance ◽  
Fingerprint Region ◽  
Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

Extraordinary circumstances: Covid-19 – Italian Serie A scenario

2021 ◽  
pp. 175433712110192
Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Round Robin ◽  
The Past ◽  
Novel Approach ◽  
Round Robin Tournaments

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.

scholarly journals Sexual behaviour patterns and STI risk: results of a cluster analysis among men who have sex with men in Portugal

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e033290
Author(s):  
Karel Blondeel ◽  
Sonia Dias ◽  
Martina Furegato ◽  
Armando Seuc ◽  
Ana Gama ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Sexual Behaviour ◽  
Hierarchical Cluster ◽  
Risk Behaviour ◽  
Sexual Partners ◽  
Hiv Positive ◽  
Research Approach ◽  
Cross Sectional ◽  
Combination Prevention ◽  
Sex With Men

ObjectivesPortugal has the highest HIV incidence rate in Western Europe. The proportion assigned to sexual contact between men recently increased to more than 30% of all HIV infections. Men who have sex with men (MSM) are vulnerable to the acquisition of other sexually transmitted infections (STIs), increasing the per-contact risk of HIV infection. Building on syndemic theory, the aim of this analysis was to identify patterns of current sexual behaviour in MSM, and explore their relationship with self-reported current, past STI diagnoses and HIV positive serostatus.DesignA cross-sectional behavioural survey was conducted in Portugal among MSM, using a community-based participatory research approach. Hierarchical cluster analysis was used to identify patterns including behavioural and demographic factors.ResultsThe analysis resulted in six clusters. Three clusters showed higher rates of current STI diagnosis (ranging from 11.7% to 17.1%), past STI diagnosis (ranging from 25.5% to 41.5%) and HIV positive serostatus (ranging from 13.0% to 16.7%). From the three clusters scoring lower on current and past STI and HIV diagnoses, one was characterised by a high number of sexual partners (62% had more than 12 partners in the last year), a high proportion (94.6%) of frequent visits to gay venues to meet sexual partners and high alcohol use (46.1%). The other two clusters scored lower on high risk sexual behaviour.ConclusionFactors other than sexual behaviour appear to reinforce the vulnerability to STIs and HIV of some MSM in this study, suggesting a syndemic of STIs, HIV and other adverse conditions. More research is needed to better understand the drivers of the STI/HIV epidemic in Portuguese MSM, using a concept that goes beyond risk behaviour, to develop effective combination prevention interventions.

scholarly journals An Examination of Subway Sex Offense Modus Operandi: A Case of Seoul, South Korea

2020 ◽  
Vol 17 (23) ◽  
pp. 8979
Author(s):  
Taeyoung Kim ◽  
Seung Yeop Paek ◽  
Julak Lee
Keyword(s):  
South Korea ◽  
Sex Offenses ◽  
Script Analysis ◽  
Police Official ◽  
Case Files ◽  
Subway Stations ◽  
Official Crime ◽  
Sex Offense ◽  
The City ◽  
Crime Reports

Subway sex offenses are a serious issue in the nations around world, but existing research has failed to explore the offense types or patterns systematically. In order to fill this gap, the authors employed Crime Script Analysis (CSA) to examine the two most common subway sex offenses in Seoul, South Korea. Specifically, the authors assessed the reasoning behind the steps taken to prepare for, carry out, and complete harassment and surreptitious recording. The offenses committed in the subway stations around the city of Seoul were analyzed based on the interviews with the subway police, official crime reports, and crime case files. Drawing from the findings, theoretical and practical implications are discussed.

scholarly journals A Tournament Approach to Price Discovery in the U.S. Cattle Market

2020 ◽  
pp. 1-16
Author(s):  
Jeffrey Wright ◽  
Man-Keun Kim ◽  
Hernan A. Tejeda ◽  
Hwa-Neyon Kim
Keyword(s):  
Cluster Analysis ◽  
Futures Markets ◽  
Hierarchical Cluster ◽  
Correction Model ◽  
Cattle Markets ◽  
Price Leader ◽  
Dynamic Relationships ◽  
Cattle Market ◽  
The U.S

Abstract The dominant market where information is discovered plays the role of price leader providing substantial market information to other markets. This study investigates the dynamic relationships of 30 cattle markets across regions, cattle types, and cash/futures markets. The comparison of many markets, using an error correction model, is accomplished with the introduction of a tournament with a hierarchical cluster analysis, which allows us to conclude that the leading price for the U.S. cattle markets is discovered in the futures markets for both feeder and fed cattle.

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