• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.39-46
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• 2019

This paper investigates the importance of various environmental factors that have a strong influence on strawberry yields grown in greenhouse using the pattern recognition methods. The environmental factors influencing the production of strawberries were six factors such as average inside temperature, average inside humidity, average $CO_2$ level, average soil temperature, cumulative solar radiation, and average illumination. The results of analyzing the observed data using Dynamic Time Warping (DTW) showed that the most significant factor influencing the strawberry production was average soil temperature, average inside humidity, and cumulative solar radiation. Second, the results of analyzing the observed data using Multidimensional Scaling (MDS) showed that the most influential factors on the strawberry yields, such as average $CO_2$ level, average inside humidity, and average illumination were differently given for each farms. However, these results are based on the distance in 3D space and can be deduced from the fact that there is not a large difference between these distances. Therefore, in order to increase the harvest of strawberries cultivated in the farms, it is necessary to manage the environmental factors such as thoroughly controlling the humidity and maintaining the concentration of $CO_2$ constantly by ventilation of the greenhouse.

• Journal of Distribution Science
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• v.19 no.2
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• pp.15-24
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• 2021

Purpose: The research is to find out the perception of consumers for the convenience store (c - store) image in an emerging market, with a sample from Ho Chi Minh City. Research design, data, and methodology: Data were collected using a 24 - item structured questionnaire into six factors, namely: store atmospheric, merchandise, supplementary service, customer convenience, sales personnel, promotion. Five hundred consumers shopped at the different c - stores were collected for a multidimensional scaling technique that creates a perceptual map illustrating of c - store image. Results: The results point out that consumers' perception of a different c - store is different. The trend of c- stores are focusing on the dimensions of the function aspect. The customers also put their attention on the psychological dimension, which, in this case, is customer convenience with a sharp point. Almost all stores are bad on store atmospheric in customer- based. Conclusions: The modern retail store chains need to focus on elements to create a store image positioning and improve the perceptions of the consumers towards the store. Besides, customers not only visit the stores, not due to its convenient location, mass media or shopping experience, but also a strong identity for the store's brand image.

• The Journal of Economics, Marketing and Management
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• v.10 no.2
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• pp.1-13
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• 2022

Purpose: The findings are expected to be used as basic data for policy establishment for systematic support and upbringing of small and medium-sized suppliers through the current status and characteristics of the industrial structure of the MRO consumable materials industry as a whole and the market trend. Research design, data, and methodology: This survey is conducted in 2019 mainly for companies that operate consumable materials delivery business, and the survey size is about 25,000 in advance (selected) and about 2,000 in the main survey. Using cluster analysis and multidimensional scaling, we derive the visualization of the homogeneous grouping of cases and the relationship structure between them. Results: Based on the attributes of reason for not having an online trading system, it is classified into three and four clusters for industry and company size, respectively, and the feature and pattern of each individual can be are relatively evaluated and visualized. Conclusions: Small and medium-sized consumable material suppliers specialize in products rather than fierce pricing strategies or external expansion strategies and it is more effective to establish a plan to promote the growth of both large and small enterprises through cooperation with large corporations.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.167-173
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• 2023

This paper investigates several methods of visualizing high-dimensional data in a low-dimensional space. At first, principal component analysis and multidimensional scaling are briefly introduced as linear approaches, and then kernel principal component analysis, self-organizing map, locally linear embedding, Isomap, Laplacian Eigenmaps, and local multidimensional scaling are introduced as nonlinear approaches. In particular, t-SNE, which is widely used but relatively unfamiliar in the field of statistics, is described in more detail. We also present a simple example for several methods, including t-SNE. Finally, we provide a review of several recent studies pointing out the limitations of t-SNE and discuss the future research problems presented.

• Journal of the korean academy of Pediatric Dentistry
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• v.37 no.2
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• pp.159-167
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• 2010

The purpose of this study was to identify patterns of caries in the dentition of preschool children using cluster analysis and multidimensional scaling. 815 preschool children aged 36-71 months old were examined for caries experience. The first four clusters in the cluster analysis were (1) molars, (2) upper incisors, (3) lower 1st molars, and (4) upper 1st molars in teeth, (1) occlusal surfaces of lower molars and upper 2nd molars, (2) mesial surfaces of upper central incisors, (3) occlusal surfaces of lower 1st molars, and (4) separation between occlusal surfaces of upper and lower 2nd molars in tooth surfaces, and (1) proximal surfaces of upper anterior teeth, (2) occlusal surfaces of lower molars, (3) buccolingual surfaces of upper anterior teeth and (4) buccolingual, proximal, and occlusal surfaces of upper molars and buccolingual and proximal surfaces of lower molars in tooth surfaces groups. In the multidimensional scaling analysis, teeth could be divided into lower 1st molars, upper 1st molars, upper central incisors, upper lateral incisors, lower 2nd molars, upper 2nd molars, and the rest(canines, lower incisors), tooth surfaces could be divided into occlusal surfaces of lower molars, mesial surfaces of upper central incisors, occlusal surfaces of upper molars, and the rest, and tooth surface groups could be divided into proximal surfaces of upper anterior teeth, buccolingual surfaces of upper anteiror teeth, occlusal surfaces of lower molars, and the rest in the order of the distance from others. In the cluster analysis and the multidimensional scaling analysis, caries patterns were different according to the age.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.67-75
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• 2018

Multidimensional scaling (MDS) is an exploratory analysis of multivariate data to represent the dissimilarity among objects in the geometric low-dimensional space. However, a general MDS map only shows the information of objects without any information about variables. In this study, we used MDS based on the algorithm of Torgerson (Theory and Methods of Scaling, Wiley, 1958) to visualize some clusters of objects in categorical data. For this, we convert given data into a multiple indicator matrix. Additionally, we added the information of levels for each categorical variable on the MDS map by applying the partition method of Shin et al. (Korean Journal of Applied Statistics, 28, 1171-1180, 2015). Therefore, we can find information on the similarity among objects as well as find associations among categorical variables using the proposed MDS map.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.1-14
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• 2004

Visualization of documents will help users when they do search similar documents. and all research in information retrieval addresses itself to the problem of a user with an information need facing a data source containing an acceptable solution to that need. In various contexts. adequate solutions to this problem have included alphabetized cubbyholes housing papyrus rolls. microfilm registers. card catalogs and inverted files coded onto discs. Many information retrieval systems rely on the use of a document surrogate. Though they might be surprise to discover it. nearly every information seeker uses an array of document surrogates. Summaries. tables of contents. abstracts. reviews, and MARC recordsthese are all document surrogates. That is, they stand infor a document allowing a user to make some decision regarding it. whether to retrieve a book from the stacks, whether to read an entire article, etc. In this paper another type of document surrogate is investigated using a grouping method of term list. lising Multidimensional Scaling Method (MDS) those surrogates are visualized on two-dimensional graph. The distances between dots on the two-dimensional graph can be represented as the similarity of the documents. More close the distance. more similar the documents.

• Science of Emotion and Sensibility
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• v.24 no.3
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• pp.71-80
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• 2021

Previous studies using facial expressions have revealed valence and arousal as two core dimensions of affective space. However, it remains unknown if the two dimensional structure is consistent across ages. This study investigated affective dimensions using six facial expressions (angry, disgusted, fearful, happy, neutral, and sad) at three ages (young, middle-aged, and old). Several studies previously required participants to directly rate subjective similarity between facial expression pairs. In this study, we collected indirect measures by asking participants to decide if a pair of two stimuli conveyed the same emotions. Multidimensional scaling showed that "angry-disgusted" and "sad-disgusted" pairs are similar at all three ages. In addition, "angry-sad," "angry-neutral," "neutral-sad," and "disgusted-fearful" pairs were similar at old age. When two faces in a pair reflect the same emotion, "sad" was the most inaccurate in old age, suggesting that the ability to recognize "sad" decreases with old age. This study suggested that the general two-core dimension structure is robust across all age groups with the exception of specific emotions.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.47-62
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• 2022

Previous emotion studies revealed the two core affective dimensions of valence and arousal using affect-eliciting stimuli, such as pictures, music, and videos. Autonomous sensory meridian response (ASMR), a type of stimuli that has emerged recently, produces a sense of psychological stability and calmness. We explored whether ASMR could be represented on the core affect dimensions. In this study, we used three affective types ASMR (negative, neutral, and positive) as stimuli. Auditory ASMR videos were used in Study 1, while auditory and audiovisual ASMR videos were used in Study 2. Participants were asked to rate how they felt about the ten adjectives using five-point Likert scales. Multidimensional scaling (MDS) and classification analyses were performed. The results of the MDS showed that distinctions between auditory and audiovisual ASMR videos were represented well in the valence dimension. Additionally, the results of the classification showed that affective conditions within and across individuals for within- and cross-modalities. Thus, we confirmed that the affective representations for individuals could be predicted and that the affective representations were consistent between individuals. These results suggest that ASMR videos, including other affect-eliciting videos, were also located in the core affect dimension space, supporting the core affect theory (Russell, 1980).

• Science of Emotion and Sensibility
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• v.26 no.2
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• pp.25-38
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• 2023

Among the discussions on affective representation, the first is to explain the affective representation in the dimensions, and the second is to explain the affective representation according to the modality. In previous studies, to explain affective representation, valence models (signed valence, unsigned valence) and Modality-generality models (modality-general, modality-specific) were presented. In this study, we compared models presented in the previous study using the recently published ASMR to confirm which models explain affective representation well. The data used in this study were behavioral rating values collected by Kim & Kim (2022), and these were obtained for ASMR stimuli that were divided into three affective types (negative, neutral, and positive) and two modalities (auditory and audiovisual). Then, a multidimensional scaling, a representational similarity analysis with a two-way repeated measures ANOVA, and a multiple regression analysis with a two-way repeated measures ANOVA were performed. The results revealed that signed valence and modality-general distinguished between affective types of stimuli better than unsigned valence and modality-specific. Similar to the results of multidimensional scaling, the results of a representational similarity analysis and a multiple regression also showed that the signed valence and modality-general significantly explained affective representation better than the unsigned valence and the modality-specific. These results suggest that the model in which positive and negative are located at the opposite ends of the one dimension explains the affective representation of ASMR well, and that the affective representation was consistent regardless of modality.