scholarly journals A Cluster Analysis Methodology for the Categorization of Soil Samples for Forensic Sciences Based on Elemental Fingerprint

2021 ◽  
pp. 1-20
Author(s):  
Camila Maione ◽  
Nattane Luíza da Costa ◽  
Fernando Barbosa ◽  
Rommel Melgaço Barbosa
Keyword(s):  
Cluster Analysis ◽  
Soil Samples ◽  
Forensic Sciences ◽  
Analysis Methodology ◽  
Elemental Fingerprint

scholarly journals Advancing Health-Related Cluster Analysis Methodology: Quantification of Pairwise Activity Cluster Similarities

2015 ◽  
Vol 12 (3) ◽  
pp. 395-401
Author(s):  
Katia Ferrar ◽  
Carol Maher ◽  
John Petkov ◽  
Tim Olds
Keyword(s):  
Cluster Analysis ◽  
New Zealand ◽  
Health Behavior ◽  
Time Use ◽  
Research Process ◽  
Vector Length ◽  
Analysis Methodology ◽  
Health Related ◽  
Activity Cluster ◽  
Time Use Research

Background:To date, most health-related time-use research has investigated behaviors in isolation; more recently, however, researchers have begun to conceptualize behaviors in the form of multidimensional patterns or clusters.Methods:The study employed 2 techniques: radar graphs and centroid vector length, angles and distance to quantify pairwise time-use cluster similarities among adolescents living in Australia (N = 1853) and in New Zealand (N = 679).Results:Based on radar graph shape, 2 pairs of clusters were similar for both boys and girls. Using vector angles (VA), vector length (VL) and centroid distances (CD), 1 pair for each sex was considered most similar (boys: VA = 63°, VL = 44 and 50 units, and CD = 48 units; girls: VA = 23°, VL = 65 and 85 units, and CD = 36 units). Both methods employed to determine similarity had strengths and weaknesses. Conclusions: The description and quantification of cluster similarity is an important step in the research process. An ability to track and compare clusters may provide greater understanding of complex multidimensional relationships, and in relation to health behavior clusters, present opportunities to monitor and to intervene.

scholarly journals Interpretaciones sobre la lluvia de polen en la región de San Luis Potosí, México

2017 ◽  
pp. 53 ◽  
Author(s):  
Socorro Lozano-García
Keyword(s):  
Cluster Analysis ◽  
Soil Samples ◽  
The State ◽  
Oak Forest ◽  
Vegetation Types ◽  
High Pollen ◽  
Clear Separation ◽  
San Luis ◽  
San Luis Potosi ◽  
San Luis Potosí

In a region located mainly in the State of San Luis Potosí, México, floristic and soil samples were taken, in order to obtain palynological spectra. The comparison between the floristic results and the palynological spectra corresponding to eight types of vegetation, shows that there are taxa such as Pinus and Quercus with a high pollen representation (RP) in most of the spectra. There were some, such as the grasses that exhibited a normal RP. Also, low values of RP were detected in some taxa typical of sucrubland. A cluster analysis was applied to forty-seven soil samples and yielded a clear separation between a) oak forest and chaparral, and b) other vegetation types.

Case Study of Cluster Analysis in Intercity Passenger Rail Planning and Marketing

2011 ◽  
Author(s):  
Ben Sperry ◽  
Curtis Morgan
Keyword(s):  
Cluster Analysis ◽  
Development Planning ◽  
Lessons Learned ◽  
Service Planning ◽  
Service Development ◽  
Valuable Insight ◽  
Passenger Rail ◽  
Analysis Methodology ◽  
Rail Service

Recent policy and regulatory initiatives have established new momentum for intercity passenger rail among planners, policymakers, and the general public. As a result, there is a great interest in developing new passenger rail lines and expanding existing routes in intercity corridors across the country. Moving forward, there exists a need to understand how current passenger rail services are being utilized, who is riding them, and what changes could be implemented to existing routes to attract ridership — as well as to document lessons learned from existing lines that can aid service development planning for newly proposed routes. In this paper, cluster analysis is applied to passenger survey data obtained in 2007 from riders of three Amtrak routes in the state of Michigan, USA. Cluster analysis is a multivariate data analysis method used extensively in marketing and customer profile research which seeks to identify similarities among potential customers that are not immediately evident using traditional grouping techniques. Data used in the formation of the passenger clusters include traveler alternatives to the passenger rail service and the importance of service attributes, on-board activities, and station amenities. These variables and other data from the passenger survey are then used to characterize the identified clusters in terms of what kinds of passengers are in each cluster and how these passengers benefit from the rail service. The passenger clusters are also analyzed for their potential response to service improvements such as reduced travel time, increased service frequencies, or improved intermodal connections. The findings of this case study can be applied in a number of activities related to intercity passenger rail service planning for existing as well as proposed routes. The findings provide valuable insight into the needs and preferences of current passengers and can be used to formulate strategies for equipment investments or the development of new on-board amenities. From a policy perspective, passengers’ preferences for alternative travel modes in the absence of the rail service reveal how the rail service supports intercity mobility for each of the clusters. Finally, from the cluster profile, potential strategies to attract new riders can be identified. The results show that clustering analysis methodology applied in this case study is a valuable tool for intercity passenger rail planning.

A multivariate analysis of alluvial terrace soils of the clarendon and cranebrook formations, Nepean River, NSW

Soil Research ◽  
1988 ◽  
Vol 26 (2) ◽  
pp. 243 ◽  
Author(s):  
G Atkinson
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Principal Component ◽  
Soil Samples ◽  
The Other ◽  
Soil Profiles ◽  
Alluvial Terrace ◽  
Southern Boundary ◽  
Alluvial Terraces

The techniques of cluster analysis and principal component analysis (PCA) were applied to soils data from two Pleistocene alluvial terraces on the Nepean River, N.S.W., the Clarendon and Cranebrook Formations, to address issues raised in the literature regarding their stratigraphic relationships. A total of 160 profiles were sampled at four fixed depths to 1 8 m. Profiles were located in four 1000 by 400 m sample areas, two on each terrace. Soil samples were analysed for colour, pH, and 2.8 M HCl extractable Fe2+, Mn2+, Na2+, K+, Ca2+ and Mg2+. Data were analysed by using whole profiles as the soil entities. One branch of the dendrogram resulting from the cluster analysis contained soil profiles exclusively from sample areas on the Cranebrook Formation, whilst the other branch contained profiles exclusively from sample areas on the Clarendon Formation. Soils typical of the Lowlands Formation, Londonderry Clay and minor subdivisions within the terraces could be distinguished on the dendrogram. Similar subdivisions could also be observed on a PCA scattergram. The Clarendon and Cranebrook Formations are complex units which contain minor terrace features. Each has a distinctly different suite of soils which is consistent with their continued designation as separate stratigraphic units. The Lowlands Formation can be separated from the Cranebrook Formation upstream of Castlereagh and the Clarendon Formation should have its southern boundary to the Londonderry Clay moved north towards Richmond and its stratigraphy redefined.

scholarly journals Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt

2021 ◽  
Vol 13 (4) ◽  
pp. 1824
Author(s):  
Mohamed K. Abdel-Fattah ◽  
Elsayed Said Mohamed ◽  
Enas M. Wagdi ◽  
Sahar A. Shahin ◽  
Ali A. Aldosari ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Soil Quality ◽  
Quality Index ◽  
Principal Component ◽  
Component Analysis ◽  
Soil Samples ◽  
Western Desert ◽  
Geographical Information ◽  
Soil Quality Index

Soil quality assessment is the first step towards precision farming and agricultural management. In the present study, a multivariate analysis and geographical information system (GIS) were used to assess and map a soil quality index (SQI) in El-Fayoum depression in the Western Desert of Egypt. For this purpose, a total of 36 geo-referenced representative soil samples (0–0.6 m) were collected and analyzed according to standardized protocols. Principal component analysis (PCA) was used to reduce the dataset into new variables, to avoid multi-collinearity, and to determine relative weights (Wi) and soil indicators (Si), which were used to obtain the soil quality index (SQI). The zones of soil quality were determined using principal component scores and cluster analysis of soil properties. A soil quality index map was generated using a geostatistical approach based on ordinary kriging (OK) interpolation. The results show that the soil data can be classified into three clusters: Cluster I represents about 13.89% of soil samples, Cluster II represents about 16.6% of samples, and Cluster III represents the rest of the soil data (69.44% of samples). In addition, the simulation results of cluster analysis using the Monte Carlo method show satisfactory results for all clusters. The SQI results reveal that the study area is classified into three zones: very good, good, and fair soil quality. The areas categorized as very good and good quality occupy about 14.48% and 50.77% of the total surface investigated, and fair soil quality (mainly due to salinity and low soil nutrients) constitutes about 34.75%. As a whole, the results indicate that the joint use of PCA and GIS allows for an accurate and effective assessment of the SQI.

A Common Methodology

2016 ◽  
Vol 7 (2) ◽  
pp. 74-87
Author(s):  
Sunny L. Munn
Keyword(s):  
Cluster Analysis ◽  
Organizational Culture ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Organizational Structures ◽  
Work Life ◽  
Class Analysis ◽  
Analysis Methodology ◽  
The Common ◽  
The Impact

Organizational structures are comprised of an organizational culture created by the beliefs, values, traditions, policies and processes carried out by the organization. The work-life system in which individuals use work-life initiatives to achieve a work-life balance can be influenced by the type of organizational culture within one's workplace, for example a structured, rigid culture in which employees are afraid to ask questions versus a flexible, open culture where discussion is encouraged. Grouping methodologies such as cluster analysis or latent class analysis can be used to create typologies of organizational culture. The focus of this paper is to deconstruct the common methodology of cluster analysis used to identify typologies of organizational culture in the NSCW Study and the NOS Study, which set out to identify the impact of organizational culture on the use and existence of work-life benefits for individuals and organizations, respectively (Munn, 2012). The paper discusses the cluster analysis methodology in detail as well as another grouping methodology – latent class analysis - as a means to understanding the place of organizational culture in work-life research. The theoretical contributions of using cluster analysis to create typologies of organizational culture and the implications for workforce research are discussed.

The technique of applying cluster analysis when Performing graduate qualification work by students St. Petersburg University of the Ministry of Internal Affairs of Russia

2020 ◽  
Vol 2020 (1) ◽  
pp. 208-217
Author(s):  
Aleksander Litvinenko ◽  
Lyudmila Bolshakova
Keyword(s):  
Cluster Analysis ◽  
University Students ◽  
Point Of View ◽  
Analysis Method ◽  
Advantages And Disadvantages ◽  
Analysis Methodology ◽  
Cluster Analysis Method ◽  
Relationship Of ◽  
The Relationship

The relevance of the topic have determined by needs of ensuring the quality of graduation qualifications by university students. This aim have to achieved, inter alia, using methods of mathematical and statistical analysis. The article discusses the practical application of the cluster analysis methodology by university students in the Graduation qualification work. The authors have analysed advantages and disadvantages of this method and determined the boundaries of its use. From a methodological point of view, it have interested to justify the boundaries of the Cluster analysis method application. Attention is to drawn the particular problems formulation the solution of which involves achieving the aim of cluster analysis. The authors describe the stages of clustering have identified with using the ascending hierarchical method. The article describes the basic rules and the sequence of using the STATISTICA package with the English version to solve the specific problem of clustering a large number of objects. As an example, the task of clustering eleven subjects of the Northwestern Subject of Russia in order to identify similar features of their innovative development. The authors emphasize the importance of using the method in terms of identifying the general properties of objects in allocated clusters. The regularities that describe the relationship of individual groups of objects are also substantial

scholarly journals Elemental composition of surface soils in Nature Park Shumen Plateau and Shumen City, Bulgaria

2018 ◽  
Vol 5 (2) ◽  
pp. 68-76
Author(s):  
Vanya Koleva ◽  
Teodora Koynova ◽  
Asya Dragoeva ◽  
Nikolay Natchev
Keyword(s):  
Heavy Metals ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Elemental Composition ◽  
Principal Component ◽  
Component Analysis ◽  
Soil Samples ◽  
Surface Soils ◽  
Nature Park ◽  
And Cluster Analysis

Abstract Anthropogenic activities cause environmental pollution and alter biogeochemical cycles. Soils in cities and their vicinity are exposed to different pollutants. Nature Park Shumen Plateau is a protected area situated in the proximity of Shumen (Bulgaria). The aim of this research was to compare elemental composition of surface soil samples from Nature Park with two areas in Shumen city. Soil samples from seven sites on the territory of Nature Park and from two urban sites were collected. The elemental composition of the samples was determined using Energy Dispersive X-Ray Fluorescence technique. Principal component analysis and cluster analysis were performed to interpret the complex data. The content of 24 elements was determined: Br, Y, Zr, Mo, Ag, Cd, Sn, Sb, I, Cs, Ba, La, Ce Si, K, Ca, Ti, Mn, Fe, Cu, Zn, Rb, Sr, and Pb. Results presented here and previously showed that concentrations of heavy metals Cu, Zn, Cd and Pb are below the upper limit according to Bulgarian legislation. Concentrations of Mn and Fe in samples from Nature Park were comparable to the literature data reported for unpolluted areas. Principal component analysis and cluster analysis show similarity of the content of 24 elements between samples from Nature Park and from Shumen city. These findings are in accordance with our previous positive results from Allium-test: cytogenetic endpoints showed a presence of harmful compounds in Nature Park soils. The content of heavy metals in the surface soils studied show a lack of environmental risk for Nature Park. However, a similar distribution pattern of the investigated elements in the park and two anthropologically influenced areas in Shumen city indicated a potential hazard in Nature Park.

scholarly journals Ground beetle (Coleoptera, Carabidae) communities as natural indicators of ecosystem restoration on the terminated fly ash dump of the thermoelectric power station (Novosibirsk, Russia)

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Alexey N. Bespalov ◽  
Ivan P. Belanov
Keyword(s):  
Cluster Analysis ◽  
Fly Ash ◽  
Thermoelectric Power ◽  
Soil Cover ◽  
Ground Beetle ◽  
Gravimetric Method ◽  
Ground Beetles ◽  
Soil Samples ◽  
Birch Forest ◽  
Power Station

The aim of the study. The aim of the study was to reveal regularities in the development of ground beetles (Coleoptera, Carabidae)’ communities, to determine their species peculiarities as dependent on soil formation rate and soil ecology in the ecosystems developed on the terminated fly ash dump of the thermoelectric power station over nine years of restoration. Location and time of the study. The main object of the study was a terminated fly ash dump No.1 of the thermoelectric power station No.5 in Novosibirsk, Russia. (54°59' NL, , 83°03' EL). Soil samples were collected in 2019, whereas the ground beetles were collected in 2017 and 2019. Methodology. Six study sites, corresponding to the fly ash dump sedimentation zones, were chosen. The undisturbed white birch forest and clover-brome meadow were chosen as controls representing mature climax ecosystems. Soil cover, developing on the fly ash dump after its termination, was described according to the soil classification of technogenic landscapes, and was shown to consist of various types of embryozems (Technosols). Soil water content on each study site was measured in 0–5cm layer by gravimetric method. Soil samples were collected in May 2019. To collect ground beetles five traps were placed on each study site, each trap filled up to 1/3 of its volume with 4% acetic acid for fixing the trapped beetles. The beetles were collected in May–June 1017 and in June–July 2019. The data obtained were used to calculate α-biodiversity indices and perform cluster analysis using PAST v.3.09 software. Main results. Altogether 74 species of the ground beetle we found: 60 species of ground beetles were identified in the revegetating fly ash dump areas, with 48 species found at the sites amended with potentially fertile substrate (PFS), and 35 species found at the sites without PFS addition. The control sites under birch forest and meadow had 14 and 10 species, respectively. Thus the ground beetles’ abundance in the reclaimed area was almost 3 times greater than in the non-reclaimed area (973 specimens vs. 347). Cluster analysis discriminated three groups in the studied fly ash dump sites, namely dry non-reclaimed sites, dry PFS sites and moist sites. Soil cover of the studied fly ash dump was represented by initial, organic matter accumulating, humus-accumulating and sod embryozems (Technosols). Conclusion. Over nine years of spontaneous restoration at the terminated fly ash dump of the thermoelectric power station species rich and abundant communities of ground beetles were formed. These communities differed significantly from those at the adjacent undisturbed climax ecosystems used for comparison. Species richness and dynamic density of ground beetles was shown to increase from the control sites to non-reclaimed sites and PFS-reclaimed sites. The autonomous position in the catena was found to be occupied by the less evolutionary developed embryozem type, whereas downwards along the catena, i.e. with increasing soil moisture content, identified soil types belonged to higher evolutionary order. Therefore technical recultivation with fly ash dump overlaying with potentially fertile substrate or fertile soil allow accelerating soil cover development, as well as the development of an entire biogeocenosis.

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