• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.4
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• pp.754-763
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• 2001

The purpose of this study was to examine: 1) the differences in the automation level by company characteristics(i.e., product category, product type, firm size); 2) the effects of company context(i.e., environmental uncertainty, task uncertainty) on the automation level; and 3) the effect of the automation level on manufacturing performance(i.e., quality, flexibility, time, cost). Data were collected from a mail survey. Four hundred eighty two questionaries were mailed to apparel manufacturers nationwide, and 60 responses were analyzed. The results revealed that: 1) mens and womens wear manufacturers and large manufacturers(i.e., the number of employees, sales volume) showed higher automation level; 2) environmental complexity positively affected the automation level; and 3) the automation level had a positive effect only on quality performance.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1869-1870
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• 2008

현재의 상황인지 컴퓨팅(Context-aware Computing)은 센서로부터 전달받는 상황정보가 완벽하다는 가정을 하고 있으며 따라서, 이에 근거한 상황인지는 불확실성(Uncertainty)을 제대로 다루지 못하고 있는 실정이다. 또한 상황인지 컴퓨팅에서 상황 정보를 표현하는데 주로 사용되고 있는 온톨로지(Ontology) 모델링 역시 현실 세계의 불확실성을 다루기에는 한계가 있다. 본 논문은 선행 연구인 온톨로지 기반의 홍수 상황인지 처리에서 발생할 수 있는 불확실성을 탐지하고 이를 해결하기 위한 방안을 제안한다. 홍수 상황인지를 위한 센서 종류와 수량을 보강하고 기 설계된 온톨로지 모델의 추론 과정 보완을 통하여 홍수 상황인지의 불확실성을 최소화한다. 이는 홍수 상황인지 뿐만 아니라 일반적인 온톨로지 기반의 상황인지 u-서비스에 응용할 수 있다.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.81-93
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• 2005

This paper models supply chain uncertainties in the dynamic Newsboy Problem context. The system consists of one supplier and one retailer who place an order to the supplier every period. Demand uncertainty is modeled as stochastic period demand, and supply uncertainty as the uncertainty in quantities delivered by the supplier. The supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of $(1-\beta)$ We formulate the problem as a dynamic programming problem and derive the first-order optimality condition. Through a numerical study, we measure the extent to which the cost decrease due to the reduction in supply uncertainty depends on the level of demand uncertainty. One of the most important findings In this paper is that this cost decrease is relatively small if demand uncertainty is kept high, and vice versa. We also backup this numerical result by analyzing the distribution of ending Inventory under the supply and demand uncertainties.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.4
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• pp.47-58
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• 2021

This study explores the relationship among perceived uncertainty, transaction characteristics, supplier capability, and supply chain performance through theoretical review in the context of increasing uncertainty such as COVID-19 in the supply chain. Based on comprehensive literature review, it was concluded that transaction characteristics and supplier capability affect perceived uncertainty, and supply chain performance can be affected by perceived uncertainty. These findings are meaningful in that we can estimate how to reduce uncertainty of the supply chain under the same pandemic situation.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.305-311
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• 2014

Recently, though it was developed several services using the context-awareness technology of IoT, there exist also obstacles for high quality service. Specifically it is short the study for uncertainty of context-awareness. This study focused on understanding the effect of frequency interference among several environmental factors for location determination to increase precision of location determination. It was found that frequency interference between devices using 2.4Ghz frequency effect on the location determination precision. It was resulted that frequency interference increase the error of location determination precision. Then, we confirmed that it was required the suitable compensation method corresponding to frequency interference.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.781-785
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• 2009

We can constantly gather personal life log from developed mobile device. However, gathered personal life log in mobile environment have a large amount log and uncertainty such as uncertainty of mobile environment, limited capacity and battery of mobile device. Tagging task using a landmark such as a key word should be required to overcome the above problem and to manage personal life log. In this paper, we propose new tagging method and a life log tagging interface using high level context recognizer based on probability. The new tagging method extract high level context such as landmark of life log using recognizer which is modeled from bayesian network and recommend recognized high level context to user using tagging interface. Finally user can directly do tagging task to life log. This task is a special feature in our process. As the result of experiments in task support level which include usability, level of a goal, function and leading, we achieved a feeling of satisfaction of 81%.

• Journal of the Korean Society of Safety
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• v.39 no.3
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• pp.75-83
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• 2024

Accurately assessing and managing risks in any endeavor is crucial. Risk assessment in engineering translates the abstract concept of risk into actionable strategies for systematic risk management. However, risk validation is met with significant skepticism, particularly concerning the uncertainty of probability. This study aims to address the aforementioned uncertainty in a multitude of ways. Firstly, instead of relying on deterministic probability, it acknowledges uncertainty and presents a probabilistic interval. Secondly, considering the uncertainty interval highlighted in OREDA, it delineates the bounds of the probabilistic interval. Lastly, it investigates how much explanatory power deterministic probability has within the defined probabilistic interval. By utilizing fault tree analysis (FTA) and integrating confidence intervals, a probabilistic risk assessment was conducted to scrutinize the explanatory power of deterministic probability. In this context, explanatory power signifies the proportion of probability within the probabilistic risk assessment interval that lies below the deterministic probability. Research results reveal that at a 90% confidence interval, the explanatory power of deterministic probability decreases to 73%. Additionally, it was confirmed that explanatory power reached 100% only with a probability application 36.9 times higher.

• Economic and Environmental Geology
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• v.37 no.1
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• pp.49-59
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• 2004

The concectration and distribution of contaminants obtained from a contaminated land investigation or an environmental geochemistry survey constitutes the basis of a decision-making process on environmental policies or of scientific researches. As the quality of data determines the reliability of the result, the investigation plan should be adjusted according to the purpose of the investigation. In general, the effort to improve the data quality had been focused mainly on the QA/QC procedures in laboratories. The rapid progress of analytical instrument has also contributed toward improving the analytical precision to a sacrificable degree. Nevertheless, in many cases, it is not the analytical precision that needs improvement for the better precision of overall measurement process: it is rather during the sampling process in the field that is responsible for the poor precision. To assess the data quality on a measured value, ISO recommends to provide information on "measurement uncertainty" along with the measured value. The measurement uncertainty in an environmental measurement context can be explained as the statistical number that expresses the degree of the uncertainty stemming from the sampling and analytical procedures. There is a cost involved in order to improve the precision of sampling and analytical methods so as to decrease the degree of measurement uncertainty. The economical point of compromise in an investigation planning can be achieved when the allowable degree of uncertainty has been set before-hand. The investigation can then be planned accordingly not to exceed the uncertainty limit. Furthermore, if the measurement uncertainty estimated from the preliminary investigation can be separated into sampling and analytical uncertainties, it can be used as a criterion where the resources for the investigation should be allotted cost-effectively to reinforce the weakest link of the whole investigation process. This paper aims to present a method of estimating the level of measurement uncertainty of a measured contamination concentration at a site used as an example and to show how the estimated uncertainty can be applied to serve the particular purpose of an investigation.

• Child Health Nursing Research
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• v.4 no.2
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• pp.207-220
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• 1998

The purpose of this study was to build a substantive theory about the experience of the maternal uncertainty in childhood chronic illness. The qualitative research method used was grounded theory. The interviewees were 12 mothers who have cared for a child who had chronic illness. The data were collected through in-depth interviews with audiotape recording done by the investigator over a period of nine months. The data were analyzed simutaneously by a constant comparative method in which new data were continuously coded into categories and properties according to Strauss and Corbin's methodology. The 34 concepts were identified as a result of analyzing the grounded data. Ten categories emerged from the analysis. The categories were lack of clarity, unpredictability, unfamiliarity, negative change, anxiety, devotion normalization and burn-out. Causal conditions included : lack of clarity, unpredictability, unfamiliarity and change ; central phenomena : anxiety, being perplexed ; context. seriousness of illness, support ; intervening condition : belief action/interaction strategies devotion, overprotection ; consequences : normalization, burn-out. These categories were synthesized into the core concept-anxiety. The process of experiencing uncertainty was 1) Entering the world of uncertainty, 2) Struggling in the tunnel of uncertainty, 3) Reconstruction of the situation of uncertainty. Four hypotheses were derived from the analysis : (1) The higher the lack of clarity, unpredictability, unfamiliaity, change, the higher the level of uncertainty (2) The more serious the illness and the less the support, the higher the level of uncertainty. (3) The positive believes will influence the devoted care and normalization of the family life. Through this substantive theory, pediatric nurses can understand the process of experiencing maternal uncertainty in childhood chronic illness. Further research to build substantive theories to explain other uncertainties may contribute to a formal theory of how normalization is achieved in the family with chronically ill child.