• Journal of Distribution Science
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• v.13 no.8
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• pp.97-104
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• 2015

Purpose - This study examines the positive impact of the social distance between producers and users of online content, investigating and analyzing the most popular Web content. In addition, it tries to elicit the matching effect that appears when the individuals'cultural background is consistent with social distance. Research design, data, and methodology - We collected and analyzed actual data about 4,981 videos clips on YouTube, looking at six countries in order to verify the content of this study. Based on the results of the data analysis, the study conducted behavioral measurements on popularity, social distance, culture, and user engagement. The unit of analysis was the content and we collected information about the content producers and the content records. We controlled the views, comments, likes, calendar dates, and ages in the empirical models. The data was collected in 2011, with the records coming from South Korea, Japan, China, U.S., German, and France. A total of 4,980 elements were analyzed in the model. The empirical model estimated is the bivariate negative binomial distribution (NBD) model. Results - It turns out that there is a possibility that the matching effect can be diminished by variables that reflect the psychological involvement of user engagement. This study proposes academic and practical implications based on these research results. This research shows the positive effect of social distance between users and producers on the increased performance of the online content. We find the effect of social distance to be a stronger tendency in collectivism. The collectivists follow their sense of friendship and intimacy in their culture and, the social congruence effect can be found there as well. The effect, however, could erode in a social case where users are motivated by strong intrinsic and psychological factors. In addition, user engagement complicates the process of user decision making regarding the information. Conclusions - This study examines how the differential effects of social distance caused by culture could disappear through user commitment as a complicated user motivation. Some potential implications are as follows. First, a firm in the collectivism culture has to communicate based on the social distance. In fact, most online channels do not have a function that indicates the social distance as measured by favorites or subscribers. This function could help increase the performance of the content in online channels, but this increasing effect can only be found in a collectivist culture. Based on this, the firms have to communicate and announce to users the actual social distance between users and producers. Second, firms should develop a system that discovers the social distance and culture and shows these measures to users and producers, since the congruence effect between social distance and culture is found only for low user engagement. The firms can take the advantage of the congruence effect only for the development of the social distance and culture visualized system.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.411-421
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• 2023

This paper provides a new estimation equation based on the concept of a minimum distance between the empirical and theoretical distribution functions under the most widely used progressive Type-II censoring scheme. For illustrative purposes, simulated and real datasets from a three-parameter Weibull distribution are analyzed. For comparison, the most popular estimation methods, the maximum likelihood and maximum product of spacings estimation methods, are developed together. In the analysis of simulated datasets, the excellence of the provided estimation method is demonstrated through the degree of the estimation failure of the likelihood-based method, and its validity is demonstrated through the mean squared errors and biases of the estimators obtained from the provided estimation equation. In the analysis of the real dataset, two types of goodness-of-fit tests are performed on whether the observed dataset has the three-parameter Weibull distribution under the progressive Type-II censoring scheme, through which the performance of the new estimation equation provided is examined.

• Journal of KSNVE
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• v.8 no.5
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• pp.814-820
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• 1998

Vibration data from two blasting sites were analyzed to determine the sufficient sample number for blasting vibration estimation. Most important result is that much more than 30 sample data and succeeding measurement are necessary to estimate confident blasting vibration level and to determine limit scaled distance.

• Journal of Distribution Science
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• v.14 no.7
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• pp.63-70
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• 2016

Purpose - The purpose of this study was to examine the variations in emotions during vacation and to explore if such variations depend on psychological distance perceived by vacationers. We proposed that there are changes in affect balance during the course of vacation as well as the mental construal of psychological distance. Research Design, Data, and Methodology - Repeated measures ANOVA was used to examine the variation in emotion and psychological distance of 66 holiday makers who were traveling to different destination for vacation. Data were collected in 2 months with the help of a travel agency. Results - We find that there are variations in emotions during the vacation at different points in time as well as perceived psychological distance. Also we find some evidence that suggests emotional happiness does depend on perceived mental distance to some extent. Conclusion - Our study replicates the findings of previous studies in a novel way and illustrates the robustness of the nature of emotions during vacation and indicates certain time points where the happiness of vacationers can be enhanced. Perceived psychological distance do have an effect on how happy an individual feels during the vacation.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.170-178
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• 2012

Dipterocarps or Dipterocarpaceae is a commercially important timber producing and dominant keystone tree family in the rain forests of Borneo. Borneo's landscape is changing at an unprecedented rate in recent years which affects this important biodiversity. This paper attempts to model the natural occurrence (distribution including those areas with natural forests before being converted to other land uses as opposed to current distribution) of dipterocarp species in Sarawak which is important for forest biodiversity conservation and management. Local modeling method of Inverse Distance Weighting was compared with commonly used statistical method (Binary Logistic Regression) to build the best natural distribution models for three genera (12 species) of dipterocarps. Database of species occurrence data and pseudoabsence data were constructed and divided into two halves for model building and validation. For logistic regression modeling, climatic, topographical and edaphic parameters were used. Proxy variables were used to represent the parameters which were highly (p>0.75) correlated to avoid over-fitting. The results show that Inverse Distance Weighting produced the best and consistent prediction with an average accuracy of over 80%. This study demonstrates that local interpolation method can be used for the modeling of natural distribution of dipterocarp species. The Inverse Distance Weighted was proven a better method and the possible reasons are discussed.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.926-940
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• 2018

In clustering-based approaches, cluster heads closer to the sink are usually burdened with much more relay traffic and thus, tend to die early. To address this problem, distance-aware clustering approaches, such as energy-efficient unequal clustering (EEUC), that adjust the cluster size according to the distance between the sink and each cluster head have been proposed. However, the network lifetime of such approaches is highly dependent on the distribution of the sensor nodes, because, in randomly distributed sensor networks, the approaches do not guarantee that the cluster energy consumption will be proportional to the cluster size. To address this problem, we propose a novel approach called CACD (Clustering Algorithm Considering node Distribution), which is not only distance-aware but also node density-aware approach. In CACD, clusters are allowed to have limited member nodes, which are determined by the distance between the sink and the cluster head. Simulation results show that CACD is 20%-50% more energy-efficient than previous work under various operational conditions considering the network lifetime.

• Journal of Urban Science
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• v.11 no.2
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• pp.9-17
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• 2022

The purpose of this study is to develop an index for evaluating the function of a new motorway using the travel distance frequency distribution (TLFD) calculated using the vehicle travel route big data, and to overcome the limitations of the evaluation through the existing traffic volume. The mobility evaluation index of motorways was developed by applying it to the TLFD data table in 2019. The smaller the value of the mobility evaluation index of the link is calculated, the more it is a link with mainly short-distance travel, and the higher the value of the mobility evaluation index, the more it means a link with mainly long-distance travel. The accessibility evaluation index was calculated through the result of the mobility evaluation index of all motorways developed, and all motorways were grouped into three groups using K-means clustering. Group A was found to exist inside a large city and consisted of motorways with many short-distance traffic, Group B was investigated as acting as an arterial between groups, and Group C was classified as a motorway consisting mainly of long-distance traffic connecting large cities and large cities. This study is significant in developing a new motorway function evaluation index that can overcome the limitations of motorway function evaluation through the existing traffic volume. It is expected that this study can be a reasonable comprehensive indicator in the operation and planning process of motorways.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.815-823
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• 2012

In this paper reliability growth model in which the operating time between successive failure is a continuous random variable is proposed. This model is for Burr type XII distribution with two parameters which is discussed in two versions: the order statistics and non-homogeneous Poisson process. The two software reliability measures are obtained. The performance for two versions of the suggested model is tested on real data set by U-plot and Y-plot using Kolmogorov distance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.135-143
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• 2012

This paper suggests the optimal blood distribution center algorithm that satisfies the minimum total transportation cost and within the allowable distribution time $T^*$. Zhang and Yang proposes shifting the location of each point that has less than the average distance of two maximum distance points from each point. But they cannot decide the correct facility location because they miscompute the shortest distance. This algorithm computes the shortest distance $l_{ij}$ from one area to another areas. Then we select the $v_i$ area to thecandidate distribution center location such that $_{max}l_{ij}{\leq}L^*$ and the $v_i$ such that $l_{ij}-L^*$ area that locates in ($v_i,v_k$) and ($v_j,v_l$) from $P_{ij}=v_i,v_k,{\cdots},v_l,v_j$ path and satisfies the $_{max}l_{ij}{\leq}L^*$ condition. Finally, we decide the candidate distribution area that has minimum transportation cost to optimal distribution area.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.57-67
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• 2019

Income distribution is a major concern in economic theory. In regional economics, it is often of interest to compare income distributions in different regions. Traditional methods often compare the income inequality of different regions by assuming parametric forms of the income distributions, or using summary statistics like the Gini coefficient. In this paper, we propose a nonparametric procedure to test for heterogeneity in income distributions among different regions, and a K-means clustering procedure for clustering income distributions based on energy distance. In simulation studies, it is shown that the energy distance based method has competitive results with other common methods in hypothesis testing, and the energy distance based clustering method performs well in the clustering problem. The proposed approaches are applied in analyzing data from China Health and Nutrition Survey 2011. The results indicate that there are significant differences among income distributions of the 12 provinces in the dataset. After applying a 4-means clustering algorithm, we obtained the clustering results of the income distributions in the 12 provinces.