scholarly journals Two Dimensional Cluster Analysis of Air Quality by Time and Area

2008 ◽  
Vol 17 (5) ◽  
pp. 517-524
Author(s):  
Seong-Seung Wee ◽  
Jae-Hoon Kim ◽  
Chi-Kyung Ahn ◽  
Byong-Su Choi ◽  
Dae-Seon Kim
Keyword(s):  
Cluster Analysis ◽  
Air Quality ◽  
Two Dimensional

The Loyal Traveler: Examining a Typology of Service Patronage

1997 ◽  
Vol 35 (4) ◽  
pp. 2-10 ◽  
Author(s):  
Mark P. Pritchard ◽  
Dennis R. Howard
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Service Providers ◽  
Two Dimensional ◽  
Composite Measure ◽  
The Third ◽  
Dimensional Matrix ◽  
Repeat Purchase ◽  
Clear Support

The first goal of this study was to determine whether Day's (1969) measure of loyalty could be extended to better understand travel service patronage. Findings provide clear support that this composite measure, of repeat purchase and loyal attitude, is an effective approach to distinguishing the loyal traveler. A cluster analysis that combined scores on the composite measure from 428 travelers supported a two-dimensional matrix that identified four types of loyalty: true, spurious, latent, and low. This accomplished the study's second purpose by confirming that the four distinct levels of loyalty exist in a variety of service settings. Discriminant analysis was used to achieve the third objective — To identify those characteristics that differentiate the truly loyal patron. The resulting profile found this traveler to be a highly satisfied, symbolically involved consumer drawn to those services that exhibit an empathetic, caring concern for their patrons. These findings generate a much clearer understanding of how service providers can measure and manage their returning patrons.

scholarly journals Examining Patterns of Air Quality Perception: A Cluster Analysis for Southern Chilean Cities

SAGE Open ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 215824401986356 ◽  
Author(s):  
Àlex Boso ◽  
Boris Álvarez ◽  
Christian Oltra ◽  
Álvaro Hofflinger ◽  
Arturo Vallejos-Romero ◽  
...  
Keyword(s):  
Health Care ◽  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Health Risks ◽  
Public Perception ◽  
Emotional Responses ◽  
Sociodemographic Factors ◽  
Southern Chile ◽  
Las Casas

Various medium-sized cities in southern Chile are saturated by air pollution caused by woodsmoke. In this study, we developed a segmentation model to assess the public’s perceptions, understanding of health risks and emotional responses to poor air quality. To date, this is the first segmentation model dealing with public perception in cities contaminated by woodsmoke. A survey ( N = 489) was conducted in Temuco and Padre las Casas, Chile, which included questions regarding attitudes, sociodemographic factors, and health care behaviors, to obtain information for mitigation initiatives. Through a cluster analysis, three population segments were identified that related differently to environmental pollution, which were constructed based on seven psychosocial variables. Different sociodemographic profiles and self-reported behavioral patterns were found, which should guide policies aimed at improving air quality in cities contaminated by pollution from wood-burning stoves.

scholarly journals Cognitive and Emotional Aspects of Cupping Therapy

2020 ◽  
Vol 10 (3) ◽  
pp. 144 ◽  
Author(s):  
Minyoung Hong ◽  
In-Seon Lee ◽  
Yeonhee Ryu ◽  
Junsuk Kim ◽  
Younbyoung Chae
Keyword(s):  
Cluster Analysis ◽  
Healthy Volunteers ◽  
Cupping Therapy ◽  
Emotional States ◽  
Two Dimensional ◽  
Fear Of Pain ◽  
Public Attention ◽  
Emotional Aspects ◽  
Psychophysical Analysis ◽  
Valence And Arousal

Cupping therapy has recently gained public attention and is widely used in many regions. Some patients are resistant to being treated with cupping therapy, as visually unpleasant marks on the skin may elicit negative reactions. This study aimed to identify the cognitive and emotional components of cupping therapy. Twenty-five healthy volunteers were presented with emotionally evocative visual stimuli representing fear, disgust, happiness, neutral emotion, and cupping, along with control images. Participants evaluated the valence and arousal level of each stimulus. Before the experiment, they completed the Fear of Pain Questionnaire-III. In two-dimensional affective space, emotional arousal increases as hedonic valence ratings become increasingly pleasant or unpleasant. Cupping therapy images were more unpleasant and more arousing than the control images. Cluster analysis showed that the response to cupping therapy images had emotional characteristics similar to those for fear images. Individuals with a greater fear of pain rated cupping therapy images as more unpleasant and more arousing. Psychophysical analysis showed that individuals experienced unpleasant and aroused emotional states in response to the cupping therapy images. Our findings suggest that cupping therapy might be associated with unpleasant-defensive motivation and motivational activation. Determining the emotional components of cupping therapy would help clinicians and researchers to understand the intrinsic effects of cupping therapy.

Cluster analysis and multiplet pattern recognition in two-dimensional NMR spectra

1990 ◽  
Vol 89 (3) ◽  
pp. 543-552
Author(s):  
Klaus-Peter Neidig ◽  
Rainer Saffrich ◽  
Michael Lorenz ◽  
Hans Robert Kalbitzer
Keyword(s):  
Cluster Analysis ◽  
Pattern Recognition ◽  
Nmr Spectra ◽  
Two Dimensional

A Cluster Analysis of PM2.5 Using CMAQ Model Results for Representativeness of Air Quality Monitoring Networks in Busan, Korea

2020 ◽  
Author(s):  
Woo-Sik Jung ◽  
Woo-Gon Do
Keyword(s):  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Monitoring Network ◽  
Hierarchical Cluster ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Monitoring Networks ◽  
Monitoring Stations

<p><strong>With increasing interest in air pollution, the installation of air quality monitoring networks for regular measurement is considered a very important task in many countries. However, operation of air quality monitoring networks requires much time and money. Therefore, the representativeness of the locations of air quality monitoring networks is an important issue that has been studied by many groups worldwide. Most such studies are based on statistical analysis or the use of geographic information systems (GIS) in existing air quality monitoring network data. These methods are useful for identifying the representativeness of existing measuring networks, but they cannot verify the need to add new monitoring stations. With the development of computer technology, numerical air quality models such as CMAQ have become increasingly important in analyzing and diagnosing air pollution. In this study, PM2.5 distributions in Busan were reproduced with 1-km grid spacing by the CMAQ model. The model results reflected actual PM2.5 changes relatively well. A cluster analysis, which is a statistical method that groups similar objects together, was then applied to the hourly PM2.5 concentration for all grids in the model domain. Similarities and differences between objects can be measured in several ways. K-means clustering uses a non-hierarchical cluster analysis method featuring an advantageously low calculation time for the fast processing of large amounts of data. K-means clustering was highly prevalent in existing studies that grouped air quality data according to the same characteristics. As a result of the cluster analysis, PM2.5 pollution in Busan was successfully divided into groups with the same concentration change characteristics. Finally, the redundancy of the monitoring stations and the need for additional sites were analyzed by comparing the clusters of PM2.5 with the locations of the air quality monitoring networks currently in operation.</strong></p><p><strong>This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(2017R1D1A3B03036152).</strong></p>

Statistical approach in cluster analysis of two-dimensional quasicrystals

2005 ◽  
Vol 61 (3) ◽  
pp. 350-357 ◽  
Author(s):  
Aleksandra Dąbrowska ◽  
Bartłomiej Kozakowski ◽  
Janusz Wolny
Keyword(s):  
Cluster Analysis ◽  
Statistical Approach ◽  
Two Dimensional

Solving Secure Problems for Wireless Sensor Networks Using Clustering and OKS

2013 ◽  
Vol 818 ◽  
pp. 230-236
Author(s):  
Yu Quan Zhang
Keyword(s):  
Cluster Analysis ◽  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Connectivity ◽  
Wireless Sensor ◽  
Two Dimensional ◽  
Wsn Security

A secure scheme for wireless sensor network is presented through dividing sensing area into clusters and using the overlap key sharing (OKS) concept in this paper. The two-dimensional sensing square is divided into a number of small squares called cells, four of which consist of a cluster called logical group. The overlap key sharing protocol creates long bit clusters as the key cluster pools and distributes a sub-group to store every sensor as the key cluster. Analysis and comparison demonstrate this scheme enhances the WSN security, realizes the flexile secure grades for WSNs, and has good network connectivity.

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