• International Journal of Highway Engineering
• /
• v.20 no.2
• /
• pp.119-126
• /
• 2018

PURPOSES : The purpose of this study is to develop a crash prediction model at signalized intersections, which can capture the randomness and uncertainty of traffic accident forecasting in order to provide more precise results. METHODS : The authors propose a random parameter (RP) approach to overcome the limitation of the Count model that cannot consider the heterogeneity of the assigned locations or road sections. For the model's development, 55 intersections located in the Daejeon metropolitan area were selected as the scope of the study, and panel data such as the number of crashes, traffic volume, and intersection geometry at each intersection were collected for the analysis. RESULTS : Based on the results of the RP negative binomial crash prediction model developed in this study, it was found that the independent variables such as the log form of average annual traffic volume, presence or absence of left-turn lanes on major roads, presence or absence of right-turn lanes on minor roads, and the number of crosswalks were statistically significant random parameters, and this showed that the variables have a heterogeneous influence on individual intersections. CONCLUSIONS : It was found that the RP model had a better fit to the data than the fixed parameters (FP) model since the RP model reflects the heterogeneity of the individual observations and captures the inconsistent and biased effects.

• Journal of Labour Economics
• /
• v.36 no.1
• /
• pp.45-62
• /
• 2013

In this study, we revisit an empirical literature has found that neighborhood income inequality lowers people's likelihood of contributing public goods in terms of volunteering. We contribute to the literature by explicitly addressing the issues of larger and improper neighborhood choice with a census-type data and endogenous neighborhood location with some unique features of 2009 Social Survey Data by Statistics Korea. The results have confirmed that income heterogeneity lowers people's volunteering.

• Asian-Australasian Journal of Animal Sciences
• /
• v.12 no.6
• /
• pp.846-849
• /
• 1999

Angus postweaning daily gain (PWDG) were analyzed to investigate heterogeneous variance by sex. A set of data (16,239 records) was divided into six sub-data sets according to level of environment. REML estimation was conducted by a multitrait model, where PWDG in each sex was treated as a separate trait. Estimates showed diversity among environmental levels, where the heritability for heifers was high in good environment but low in poor environment. The bull's estimates varied among environmental levels. The largest heterogeneity of phenotypic variance between sexes was estimated in a data set of the poor environment level. The genetic correlations between the heifer's PWDG and the bull's PWDG were high in the good environment and low in the poor environment (-0.17). The results suggest existence of genotype by sex interaction in the poor environment.

• Journal of the Korean Statistical Society
• /
• v.36 no.1
• /
• pp.129-148
• /
• 2007

Frailty estimates from the proportional hazards frailty model often lead us to conjecture the heterogeneity in frailty such that the variance of the frailty varies over different covariate groups (e.g. male group versus female group). For such systematic heterogeneity in frailty, we consider a regression model for the variance components in the proportional hazards frailty model, denoted by the MLFM. However, in many cases, the observed data do not show any statistically significant preference between the homogeneous frailty model and the heterogeneous frailty model. In this paper, we propose a Bayesian model averaging procedure with the reversible jump Markov chain Monte Carlo which selects the appropriate model automatically. The resulting regression coefficient estimate ignores the model uncertainty from the frailty distribution in view of Bayesian model averaging (Hoeting et al., 1999). Finally, the proposed model and the estimation procedure are illustrated through the analysis of the kidney infection data in McGilchrist and Aisbett (1991) and a simulation study is implemented.

• Asian Journal of Innovation and Policy
• /
• v.10 no.3
• /
• pp.294-315
• /
• 2021

Since the division of South and North Korea in 1945, there has been little exchange in science and technology, despite some interchange in a few fields including the chemistry area. Accordingly, the difference in scientific and technological terminology between the two Koreas has become intensified. This is because North Korea carried out a campaign to purify the Korean language and blocked the inflow of foreign words. They also tried to convert into their own North Korean terms in many fields. This circumstance in North Korea aggravated the heterogeneity of inter-Korean scientific and technological terms. In particular, the heterogeneity of chemical terminology has worsened due to the different characteristics of the technology donor countries such as the United States and Japan in South Korea, and China and the Soviet Union in North Korea between the two Koreas and the different way of technological development. The purpose of this study is to collect chemical terminology data used in two Koreas and analyze similarities and differences. Through comparative analysis of inter-Korean terminology in the chemical field, it can be possible to recognize how the chemical terms between the two Koreas have changed since the division and the degree of heterogeneity based on different technical systems and language policies. The outcome of this study would present basic data on the unification of chemical terminology in preparation for before and after unification, and contribute to communication and academic exchange between researchers in the inter-Korean scientific and technological fields, including chemistry.

• 한국노년학
• /
• v.40 no.1
• /
• pp.73-89
• /
• 2020

This study validates an abridged version of the age integration scale by Chung et al. (2015), which constitutes sub-dimensions of age flexibility and age heterogeneity-from Riley et al. (1994)-and observes disparities in the perception of age integration among different socio-cultural characteristics. This study analyzed 1,433 people in the "Age Integration and Generation Integration Survey" data, with the support of the Social Science Competency Enhancement Project (SSK) (supported by the Korea Research Foundation). This paper analyzed the data using exploratory factor analysis, confirmatory factor analysis, multiple-group factor analysis, and a compare means test. The results are as follows. First, the scale was abridged to 13 items from 28, of which eight items concern age heterogeneity and five concern age flexibility. Second, the multi-group analysis did not show a significant difference among younger, middle, and older age groups, therefore allowing the scale to be used among all age groups. Third, when sociocultural characteristics were observed, younger adults showed differences in their levels of age integration, age heterogeneity, and age flexibility regarding their residential area. Middle-aged adults showed dif f erences in their levels of age integration, age heterogeneity, and age flexibility regarding their residential area and social status. Older adults showed differences in their level of age integration regarding their residential area, education level, and social status. They also showed differences in the level of age flexibility regarding their residential area and social status and differences in the level of age heterogeneity regarding their residential area and education. Based on the results of the study, political and practical measures to promote perception on age integration in the future were suggested.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.12
• /
• pp.2212-2220
• /
• 2006

Recently enterprises introduce EAI systems and legacy business which already obtained for data integration among legacy systems. EAI systems in cooperative transaction environment can be expected efficient retrieval as sharing and integrating. However existing legacy systems have to introduce particular EAI solution because it is difficult to adjust standard technology to EAI due to be managed independently without considering interoperability. For solving these problems we use metadata registry using data integration. Various types, semantic specification data heterogeneity and heterogeneity of systems, however, are occurred. Therefore retrieval system based on XMDR(extended Meta-Data Registry) for data interoperability in the web environment are proposed in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.5
• /
• pp.1223-1237
• /
• 2024

Autonomous vehicles use onboard sensors to sense the surrounding environment. In complex autonomous driving scenarios, the detection and recognition capabilities are constrained, which may result in serious accidents. An efficient way to enhance the detection and recognition capabilities is establishing collaborations with the neighbor vehicles. However, the collaborations introduce additional challenges in terms of the data heterogeneity, communication cost, and data privacy. In this paper, a novel personalized federated learning framework is proposed for addressing the challenges and enabling efficient collaborations in autonomous driving environment. For obtaining a global model, vehicles perform local training and transmit logits to a central unit instead of the entire model, and thus the communication cost is minimized, and the data privacy is protected. Then, the inference similarity is derived for capturing the characteristics of data heterogeneity. The vehicles are divided into clusters based on the inference similarity and a weighted aggregation is performed within a cluster. Finally, the vehicles download the corresponding aggregated global model and train a personalized model which is personalized for the cluster that has similar data distribution, so that accuracy is not affected by heterogeneous data. Experimental results demonstrate significant advantages of our proposed method in improving the efficiency of collaborative perception and reducing communication cost.

• Journal of Information Technology Applications and Management
• /
• v.15 no.1
• /
• pp.43-65
• /
• 2008

This study investigates the effects of business environment on the e-business strategy and performance of venture firms. The development of the research model is based on the empirical studies on the strategy literature. The data from the survey was analyzed using Partial Least Squares(PLS). For Daedeok Valley Venture Firms, product innovation differentiation strategy is affected by environmental uncertainty. And, cost leadership strategy tend to be influence by environmental uncertainty. Finally, venture firm's performance is effected by cost leadership strategy and marketing differentiation strategy. However, for in Hsinchu Science Park Venture Firms, product innovation differentiation strategy is affected by environmental uncertainty and heterogeneity. And, marketing differentiation strategy is enhanced by environment uncertainty and industry growth. In addition, cost leadership strategy tend to be influence by environmental uncertainty and heterogeneity. Finally, venture firm's performance is effected by cost leadership strategy and product innovation differentiation strategy.

• International journal of advanced smart convergence
• /
• v.5 no.1
• /
• pp.16-22
• /
• 2016

The database integration is being emphasized to one way of the companies collaboration. To database integration, companies are use like one database what their own, it can be provided more efficient service to customer. However, there exist some difficulty to database integration. that is the database security and database heterogeneity problems. In this paper, we proposed the MapReduce based p2p DBaaS hub system to solve database heterogeneity problem. The proposed system provides an environment for companies in the P2P cloud to integrate a database of each other. The proposed system uses DBaaS Hub for a collection of data in the P2P cloud, and use MapReduce for integrating the collected data.