• Korean Journal of Construction Engineering and Management
• /
• v.8 no.3
• /
• pp.76-86
• /
• 2007

Construction development work invents profit as those finalize object, and a make or break success of project depends on correct analysis and forecast business feasibility at project early. Business feasibility study would be decision-making under precarious situation because is connoting uncertainty that is future. estimate at present visual point essentially. Under uncertainty, a decision-making method is based on probability theory of statistics, but business feasibility study had applied with not feasibility study by probabilistic decision method but it by determinism derision method so far. Therefore in this study doing decision-making by a probability theory method for successful project at early business feasibility study, it present a probabilistic study method that use simulation that can supply a little more correct and reliable data to decision-maker As result, a probabilistic study method is more suitable than deterministic study method as technique for a financial feasibility study of construction development work. Making good use of this probabilistic study method at important business or careful decision-making, because efficient Judgment that is based accuracy and authoritativeness may become available.

• Journal of the Korean Society of Safety
• /
• v.30 no.4
• /
• pp.151-158
• /
• 2015

Usually risk assessment is performed for the safety of diverse industries though, many kinds of risks cannot be analyzed effectively by using classical probability models due to lack of experience data and impreciseness of human decision making. For these reasons, fuzzy risk assessment utilizing subjective judgment and experience of skillful experts has been considered as a solution. In this study, to comprehend the relationship between conventional fuzzy theory and human conceptual images on risks, linguistic variables were reviewed with reference to fuzzy membership functions, especially in the Korean language. As interviewees, about a hundred people including students as well as safety engineers voluntarily participated. The research results showed that most people were in favor of adjective expressions decorated with adverbs rather than naive expressions such as "high" or "low", and that directly translated linguistic variables were not appropriate for the Korean people in risk assessment as far. Therefore, with consideration of the selection tendency by the Korean people in linguistic variables, it could be concluded that 5 level expressions would be most favorable for linguistic variables in risk assessments in Korea.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.2
• /
• pp.83-90
• /
• 2015

Almost of current Automatic Incident Detection(AID) algorithms involve the vulnerability that detects the traffic accident in open road or in tunnel as the traffic jam not as the traffic accident. This paper proposes the improved accident detection algorithm to enhance the detection probability based on accident detection algorithms applied in open roads. The improved accident detection algorithm provides the preliminary judgment of potential accident by detecting the stopped object by Gaussian Mixture Model. Afterwards, it measures the detection area is divided into blocks so that the occupancy rate can be determined for each block. All experimental results of applying the new algorithm on a real incident was detected image without error.

• Nuclear Engineering and Technology
• /
• v.53 no.4
• /
• pp.1331-1344
• /
• 2021

This study is to evaluate the seismic capacity of the fire-damaged cabinet facility in a nuclear power plant (NPP). A prototype of an electrical cabinet is modeled using OpenSees for the numerical simulation. To capture the nonlinear behavior of the cabinet, the constitutive law of the material model under the fire environment is considered. The experimental record from the impact hammer test is extracted trough the frequency-domain decomposition (FDD) method, which is used to verify the effectiveness of the numerical model through modal assurance criteria (MAC). Assuming different temperatures, the nonlinear time history analysis is conducted using a set of fifty earthquakes and the seismic outputs are investigated by the fragility analysis. To get a threshold of intensity measure, the Monte Carlo Simulation (MCS) is adopted for uncertainty reduction purposes. Finally, a capacity estimation model has been proposed through the investigation, which will be helpful for the engineer or NPP operator to evaluate the fire-damaged cabinet strength under seismic excitation. This capacity model is presented in terms of the High Confidence of Low Probability of Failure (HCLPF) point. The results are validated by the proper judgment and can be used to analyze the influences of fire on the electrical cabinet.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.21 no.1
• /
• pp.149-164
• /
• 2023

As part of the safety case development for generic disposal sites in Korea, it is necessary to develop generic assessment models using various geosphere-biosphere interfaces (GBIs) and potentially exposed groups (PEGs) that reflect the natural environmental characteristics and the lifestyles of people in Korea. In this study, a unique modeling strategy was developed to systematically construct and select Korean generic biosphere assessment models. The strategy includes three process steps (combination, screening, and experts' scoring) for the biosphere system conditions. First, various conditions, such as climate, topography, GBIs, and PEGs, were combined in the biosphere system. Second, the combined calculation cases were configured into interrelation matrices to screen out some calculation cases that were highly unlikely or less significant in terms of the exposure dose. Finally, the selected calculation cases were prioritized based on expert judgment by scoring the knowledge, probability, and importance. The results of this study can be implemented in the development of biosphere assessment models for Korean generic sites. It is believed that this systematic methodology for selecting the candidate calculation cases can contribute to increasing the confidence of future site-specific biosphere assessment models.

• Tuberculosis and Respiratory Diseases
• /
• v.67 no.2
• /
• pp.105-112
• /
• 2009

Background: Solitary pulmonary nodules (SPN) are encountered incidentally in 0.2% of patients who undergo chest X-ray or chest CT. Although SPN has malignant potential, it cannot be treated surgically by biopsy in all patients. The first stage is to determine if patients with SPN require periodic observation and biopsy or resection. An important early step in the management of patients with SPN is to estimate the clinical pretest probability of a malignancy. In every patient with SPN, it is recommended that clinicians estimate the pretest probability of a malignancy either qualitatively using clinical judgment or quantitatively using a validated model. This study examined whether Bayesian analysis or multiple logistic regression analysis is more predictive of the probability of a malignancy in SPN. Methods: From January 2005 to December 2008, this study enrolled 63 participants with SPN at the Kangnam Sacred Hospital. The accuracy of Bayesian analysis and Bayesian analysis with a FDG-PET scan, and Multiple logistic regression analysis was compared retrospectively. The accurate probability of a malignancy in a patient was compared by taking the chest CT and pathology of SPN patients with <30 mm at CXR incidentally. Results: From those participated in study, 27 people (42.9%) were classified as having a malignancy, and 36 people were benign. The result of the malignant estimation by Bayesian analysis was 0.779 (95% confidence interval [CI], 0.657 to 0.874). Using Multiple logistic regression analysis, the result was 0.684 (95% CI, 0.555 to 0.796). This suggests that Bayesian analysis provides a more accurate examination than multiple logistic regression analysis. Conclusion: Bayesian analysis is better than multiple logistic regression analysis in predicting the probability of a malignancy in solitary pulmonary nodules but the difference was not statistically significant.

• The Journal of the Korea Contents Association
• /
• v.12 no.8
• /
• pp.29-36
• /
• 2012

In CCPM Technique, as the buffer size calculation method, the Cut and Paste(C&P) method and the Root Square Error (RSE) method for all tasks carried out the same treatment, without considering the actual situation and characteristics of the task, the lack of reasonable judgment, is too simple and hasty. In this paper, taking into account the limitations of existing methods, a new method of buffer sizing method based on statistical analysis was introduced. It makes statistical analysis for the relationship between each worker and a variety of tasks, and use the information to predict the next task time. In order to verify the effectiveness of the new method, according to different task difficulty and the number of tasks set up the project. Use C&P, RSE method and new methods to predict the time of the project. Through Monte Carlo Simulation to simulate the project time, a comparison of three methods of performance. The results show that the new method can achieve the managers expect the probability of completion, and for those tasks can be completed ahead of schedule, the new method can save project time.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.9 no.4
• /
• pp.169-176
• /
• 2005

An analysis of the annual frequency of collapse(AF) is performed for each bridge pier exposed to ship collision. From this analysis, the impact lateral resistance can be determined for each pier. The bridge pier impact resistance is selected using a probability-based analysis procedure in which the predicted annual frequency of bridge collapse, AF, from the ship collision risk assessment is compared to an acceptance criterion. The analysis procedure is an iterative process in which a trial impact resistance is selected for a bridge component and a computed AF is compared to the acceptance criterion, and revisions to the analysis variables are made as necessary to achieve compliance. The distribution of the AF acceptance criterion among the exposed piers is generally based on the designer's judgment. In this study, the acceptance criterion is allocated to each pier using allocation weights based on the previous predictions.

• Science of Emotion and Sensibility
• /
• v.20 no.2
• /
• pp.161-170
• /
• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.2 s.302
• /
• pp.9-18
• /
• 2005

Flicker is the 'variation in brightness or he perceived won stimulation by intermittent or temporally non uniform light'. This phenomenon is blown as the cause of eye strain and headaches. Many researchers are dedicated to reducing this phenomenon. The flicker phenomenon also exists in PDP as some other display types, and is a critical problem in 50 Hz PDP. However, it is difficult to define flicker by more than one subjective judgment. So, an objective measurement of flicker is necessary and convenient for research on displays. In this paper, a computational prediction model is proposed which is used to predict luminance flicker (not chromatic flicker) by giving a quantitative output that describes the probability of occurrence of flicker. Through this work, we expected to provide a practical tool for flicker-free design in PDP.