• The Research Journal of the Costume Culture
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• v.8 no.1
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• pp.30-39
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• 2000

The purpose of this study were to 1) identify types and levels of production environments, 2) classify apparel manufacturers based on production environments and 3) investigate relationship between characteristics of apparel manufacturers and production environment. Apparel manufacturer's characteristics included product line and the number of employees. For this study, the questionnaires were administered to 215 apparel manufacturers in seoul and Kyung-gi region from Feb. to Mar. 1998. Employing a sample of 201, data were analyzed by factor analysis, descriptive statistics, cluster analysis, cluster analysis, discriminant Analysis, and multivariate analysis of variance. The following are the results of this study : 1. The production environment was identified as three types such as complexity of product environment, uncertainty of demand/supply environment and uncertainty of worker environment. 2. Based on three types of the production environment, apparel manufacturers were classified into stable group, uncertain group and complicated group. 3. With respect to product line, men's wear manufacturers were lied the most high complexity of product environment, casual wear and knit wear were lied the most frequently uncertainty of worker environment. With respect to the number employees, apparel manufacturers comprising 50∼99 employees were lied the most high complexity of product environment, while those comprising 100∼299 employees the most high demand/supply environment.

• International Journal of Safety
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• v.8 no.1
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• pp.24-31
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• 2009

An effective assessment for decommissioning safety of nuclear facilities requires basic knowledge about possible risks, characteristics of potential hazards, and comprehensive understanding of the associated cause-effect relationships within a decommissioning for nuclear facility. This paper proposes an approach to develop the hierarchical structure and hazards of dealing with improving the complexity and uncertainty for decommissioning safety assessment of nuclear facilities and the resolutions are proposed to improve the complexity and uncertainty for decommissioning safety assessment of nuclear facilities. These resolutions can provide a comprehensive view of the risks in the decommissioning activities of a nuclear facility.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.209-219
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• 2022

Purpose : The purpose of this study was two-fold: to investigate the effects of uncertainty and depression on the quality of life (QoL) of elderly people with chronic diseases and to provide basic data on the physical, emotional, and psychological factors affecting their QoL in the field of physical therapy. Methods : A questionnaire covering uncertainty, depression, and QoL was distributed among 320 elderly people. Pearson's correlation analysis was performed to examine the correlation between uncertainty (ambiguity, complexity, inconsistency, and unpredictability), depression, and QoL (physical, psychological, social, and living environment domains) of the respondents; furthermore, multiple regression analysis was performed to identify the factors affecting the QoL of the respondents with a chronic disease. Results : The sub-factors of uncertainty and QoL-"complexity and social domain" (r=-.295, p<.001), "complexity and living environment domain" (r=-.302, p<.001), and "inconsistency and living environment domain" (r=-.360, p<.001)-showed a negative (-) correlation, as did depression and the sub-factors of QoL-"depression and physical domain" (r=-.782, p<.001), "depression and psychological domain" (r=-.876, p<.001), "depression and social domain" (r=-.668, p<.001), and "depression and living environment domain" (r=-.731, p<.001). The factors affecting QoL were complexity (𝛽=-.122, p<.001), inconsistency (𝛽=-.102, p=.002), unpredictability (𝛽=.112, p<.001), and depression (𝛽=-.850, p<.001). The relative influence of the independent variables was in the order of depression, complexity, unpredictability, and inconsistency, and the explanatory power was 77.1 % (F=215.853, p<.001). Conclusion : It is important to help the elderly with chronic diseases reduce the negative impact on their quality of life by helping them gain support from their families and medical professionals and by increasing their understanding through communication so that they can transition from negative emotions to positive emotions of opportunity.

• Smart Structures and Systems
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• v.29 no.2
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.4
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• pp.153-163
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• 2022

Purpose : The purpose of this study was to investigate the differences between uncertainty of chronic diseases and quality of life with regard to elderly people. Methods : The participants of this study were 350 elderly people, aged over 65 years. The collected data were analyzed using the SPSS Window program and the general characteristics of the participants and sub-domains of quality of life were analyzed by several frequency analyses and descriptive statistics such as mean, standard deviation, skewness, and kurtosis. Further, the differences between the sub-domains of uncertainty and sub-domains of quality of life were analyzed through independent t-test and one-way ANOVA. In order to reach conclusive results, post-test was analyzed by the Scheffe test. In addition, Pearson's correlation analysis was performed to determine the correlation between the target categories. A significance level of 𝛼=.05 was used to verify statistical significance. Results : As a result of examining "uncertainty" with respect to general characteristics, such as older age, low educational background, and chronic diseases, it was observed that the more intense these factors became, the more the level of uncertainty increased. In addition, it was also noted that except "accompanying diseases" in social domain, the participants enjoyed a high level of quality of life. The correlation was noted between domains of complexity and sociality (p<.01), domains of inconsistency and sociality (p<.01), domains of complexity and living environment (p<.01), domains of inconsistency and living environment (p<.01), and total score of uncertainty and total quality of life (p<.01). Conclusion : In this study, differences were found between "uncertainty" and "quality of life" of elderly people; the correlation between the sub-domains based on general traits was found to be negative (-). This suggests that objective evidence can be presented for the prevention of diseases by using mental health programs for the elderly in future.

• Asia pacific journal of information systems
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• v.11 no.2
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• pp.141-158
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• 2001

This paper examines the effects of environmental uncertainty, structural decentralization, formalization, complexity and task interdependence on the information sharing through information system. 197 firms in Korea are surveyed and analyzed to investigate the relationship between the contextual variables and the information sharing. The result of multiple regression analysis shows that task interdependence, structural decentralization, complexity are significant factors to influence on the Information Sharing. Also, additional analysis shows that task interdependence, structural decentralization are major factors in service industry, and task interdependence, structural complexity are in manufacturing industry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.861-880
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• 2023

Semantic segmentation of road scene is the key technology of autonomous driving, and the improvement of convolutional neural network architecture promotes the improvement of model segmentation performance. The existing convolutional neural network has the simplification of learning knowledge and the complexity of the model. To address this issue, we proposed a road scene semantic segmentation algorithm based on multi-task collaborative learning. Firstly, a depthwise separable convolution atrous spatial pyramid pooling is proposed to reduce model complexity. Secondly, a collaborative learning framework is proposed involved with saliency detection, and the joint loss function is defined using homoscedastic uncertainty to meet the new learning model. Experiments are conducted on the road and nature scenes datasets. The proposed method achieves 70.94% and 64.90% mIoU on Cityscapes and PASCAL VOC 2012 datasets, respectively. Qualitatively, Compared to methods with excellent performance, the method proposed in this paper has significant advantages in the segmentation of fine targets and boundaries.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1735-1740
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• 2005

In this paper, ways of improving the performances of roundabouts under the assumption that the Advanced Vehicle System is proposed. The situation on a road contains uncertainty and complexity caused by different vehicles having different directions and time-varying traffic flow. This sort of system with high uncertainty is called Multi Agent System (MAS). The MAS is a collective system, including numbers of agents and performs high diversity of the configuration as well as it has nonlinear property and complexity. Hence it is difficult to analyze and control the multi-agent system. A roundabout can be considered as an MAS with numbers of moving vehicles. So it must be difficult to use a centralized control technique to all vehicles in an intersection. Therefore, to improve the performances of roundabouts, multi-agents flow control algorithm for vehicles in Roundabouts using 'self-organization' technique is proposed.

• Educational Technology International
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• v.21 no.1
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• pp.69-95
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• 2020

The purpose of this research is to analyze the predictive powers of the five technostress creators - techno-overload, techno-invasion, techno-complexity, techno-insecurity, and techno-uncertainty - in job satisfaction and teacher efficacy of primary school teachers in Korea when they incorporated mobile technology into teaching. A questionnaire was designed to measure the level of teacher's stress from technology, job satisfaction and teacher efficacy. Data were collected from 164 teachers. Multiple regression analysis was conducted to explain which area of technostress led to varying degrees of job satisfaction and teacher efficacy. The results showed that techno-complexity alone predicted both job satisfaction and teacher efficacy. The reason why techno-complexity was the only predictor is that teachers would have first needed to understand how to incorporate mobile technology into teaching, before feeling overloaded, invaded, insecure, or uncertain about it, meaning techno-complexity precedes other constructs. Therefore, the only stress factor that affected them was how to understand the complexity of mobile technology. This calls for adequate training and support from schools and governments in order for the teachers to fully incorporate technology into teaching.