• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3034-3055
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• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• Journal of Agricultural Extension & Community Development
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• v.16 no.1
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• pp.69-98
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• 2009

This study empirically studies the effects of Agricultural Technology Service Center's educational program for farmers on their incomes. The educational program for farmers has widely been managed in discourse and policy in Korea. In 2008, Agricultural Technology Service Center managed 88 educational program for farmers, where 6,409 farmers received a certificate. While there are important studies, most of them have concentrated on qualitative analysis and noneconomic effects to an educational program for farmers. This study tried to analyze whether or not there is an economic effect of an educational program for farmers, focusing on the relationship between the educational program for farmers and their income status. Multilevel models (or hierarchical linear models) were applied to this study. Multilevel model is a quantitative model of parameters that vary at more than one level and show hierarchical structures between levels. This study particularly accentuates that an educational program for farmers is more meaningful when it can raise farmers' incomes by region and by educational program for farmers.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.310-319
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• 1995

We represent graphically the relationship of hierachical log linear models by regarding the values of the likelihood ratio statistics as the squared norm of the corresponding vectors. Right angled triangles, tetrahedrons, and modified polyhedrons are used for graphical description. We find that the angle between the two vectors depends on the coefficient of determination and the partial coefficent of determination. Thess graphical descriptions could be applied to the model selection method.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.373-388
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• 2016

Purpose: This paper suggests a hierarchical time delay model to evaluate failure risks in FMEA(failure modes and effects analysis). In place of the conventional RPN(risk priority number), a more reasonable and objective risk metric is proposed under hierarchical failure cause structure considering time delay between a failure mode and its causes. Methods: The structure of failure modes and their corresponding causes are analyzed together with the time gaps between occurrences of causes and failures. Assuming the severity of a failure depends on the length of the delayed time for corrective action, a severity model is developed. Using the expected severity, a risk priority metric is defined. Results: For linear and quadratic types of severity, nice forms of expected severity are derived and a meaningful metric for risk evaluation is defined. Conclusion: The suggested REM(risk evaluation metric) provides a more reasonable and objective risk measure than the conventional RPN for FMEA.

• Korean Journal of Childcare and Education
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• v.20 no.2
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• pp.83-103
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• 2024

Objective: This study aimed to investigate the effects of children's characteristics and childcare teachers' attributes on the frequency and level of imaginative play in two-year-old classrooms. Methods: The study involved 191 toddlers, their mothers, and 32 teachers from childcare centers. Toddler characteristics encompassed temperament along with demographic variables such as gender and age. Teacher' attributes related to play included playfulness, play-support belief, and interactions with toddlers. Data analysis was conducted using SPSS 22.0 and HLM 8.2 software, employing basic analysis, hierarchical linear analysis, and hierarchical regression analysis. Results: First, as toddlers' age increased, both the frequency and level of their imaginative play increased. Second, individual-level model analysis revealed a positive effect of toddlers' extroversion on the level of imaginative play. Third, the class-level model results indicated that teachers' emotions had a negative effect, whereas their encouragement positively influenced the level of imaginative play. Conclusion/Implications: The significance of this study lies in its utilization of a multilayered model analysis, which offers a more robust examination of variable influences by accounting for hierarchical data structures.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.29-34
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• 2008

This study examines the effects of information and communication technologies on individual performance. The literature has paid a considerable amount of attention to social influence as a determinant of individual behavior. We combine task-technology fit with concepts from adaptive structuration theory to specify social influence. In our model, we suggest that individuals should receive support from proper social construction to have additional performance improvement. Empirical data from 317 individuals across 43 teams in 10 companies is used to assess the theoretical model. Our theoretical model received support from the data.

• Korean Journal of Occupational Health Nursing
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• v.29 no.3
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• pp.173-183
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• 2020

Purpose: The purpose of this study was to identify factors associated with the mental health-related quality of life (MHQoL) of Korean workers. Methods: This was a cross-sectional study of 192 Korean pay workers who worked in the Daegu and Gyeongbuk Province, Korea. Data were collected from May 15 to July 2, 2019, through selfreported questionnaires. The survey had a total of 87 questions including individual, organizational, and psychosocial factors. MHQoL was measured using short form-36 version 1. Data were divided into four domains of MHQoL and analyzed using a hierarchical linear regression model. Results: From the hierarchical linear regression analysis, when the psychosocial factors were included in the regression model, the R² change in the four domains of MHQoL increased significantly by 19~47%. A common predicting factor associated with the four domains of MHQoL was identified as perceived stress symptoms. Other factors affecting MHQoL showed slight differences in each domain. Conclusion: Based on the study results, it is necessary to monitor the psychosocial symptoms to improve MHQoL of Korean workers. Considering each factor affecting the four areas of MHQoL, workplace-based interventions to improve MHQoL should be provided to workers.

• Korean Journal of Social Welfare
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• v.68 no.1
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• pp.5-22
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• 2016

We examined how public social expenditure and individual socio-demographic factors affect individual voluntary activities(volunteering, giving). Hierarchical linear model(HLM) was employed to a nested data set with 37,648 individual subjects and 16 local governments in Korea. HLM analyses yield an insignificant direct effect of public expenditure to volunteering and giving, while individual factors all have significant effects on them. Finally, this study discussed why public social expenditure factor does not have significant influence in this data, and suggested policy implications for promoting volunteering and giving.

• Asia Marketing Journal
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• v.22 no.3
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• pp.1-28
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• 2020

With the development of information and communication technology and spread of smart devices, online information exchange has become a daily routine. Accordingly, the management and utilization of online word of mouth (WOM) has become an important issue for companies. Numerous studies have examined the impact of online WOM on firm performance. This study analyzes the impact of negative word of mouth (NWOM) on firm value, considering the influence of corporate social responsibility (CSR) activity and research and development (R&D) investment. Using a hierarchical linear model, we find that 1) NWOM has a negative impact on firm value, 2) CSR activities do not significantly influence this impact, and 3) R&D investment reduces this negative impact. This study contributes by demonstrating the effect of NWOM on firm value, examining the influence of CSR activities and R&D investment on the impact of NWOM, and confirming that the hierarchical linear model can be applied effectively to panel data in empirical studies. As a practical implication, companies must prevent and manage NWOM, whose impact, when caused by an unavoidable incident, can be alleviated by proactively announcing that the company is striving for competitiveness, for instance, by investing in R&D.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.193-200
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• 2000

Modelling the dependence via random effects in censored multivariate survival data has recently received considerable attention in the biomedical literature. The random effects models model not only the conditional survival times but also the conditional hazard rate. Systematic likelihood inference for the models with random effects is possible using Lee and Nelder's (1996) hierarchical-likelihood (h-likelihood). The purpose of this presentation is to introduce Ha et al.'s (2000a,b) inferential methods for the random effects models via the h-likelihood, which provide a conceptually simple, numerically efficient and reliable inferential procedures.