• Journal of the Korean Institute of Gas
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• v.22 no.5
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• pp.107-113
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• 2018

While accident data are used to show alertness to accidents or to review similar cases, the analysis of nature of accident data its association with surrounding environment is very insufficient. Therefore, it is very necessary to demonstrate the possibility of an accident for a particular region by developing analysis techniques with the related accident data. The purpose of this study is to develop an analysis model and implement a system that produces regional accident probability based on historical weather information data and accident and reporting data. In other words, the system is designed and developed to create models by k-NN and decision tree algorithms with optional user-environment variables based on the probability between weather and accidents about many particular region of Korea. In the future, the models developed in this study are intended to be used to analyze and calculate the risk of a more narrow area.

• Journal of Korea Technology Innovation Society
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• v.16 no.1
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• pp.303-322
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• 2013

A relevance of supporting business of technology financing for technologically innovative SMEs is strongly required for its continuous expansion and development. This study analyzes empirically whether the selection of recipient firms from technology financing have been performed in accordance with its objectives and purposes. Results show that the probability of receiving technology financing is more likely to increase with higher technology rankings and higher operating income ratio. On the other hand, the probability of obtaining financing might be decreased gradually, as the size of capital and age of the firm are increasing. Results also show that technology rankings and firm's major characteristics are found to affect significantly on the decision-making of technology financing. Several useful comments are suggested to improve the relevance of the technology financing since the correct classification rate, which explains the appropriateness of the model, is not at high level. In addition, technology rankings are not uncorrelated with the amount of financing in regression analysis. These research results will contribute to ensure the appropriateness and credibility of the technology financing decision-making.

• Korean Journal of Adult Nursing
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• v.17 no.3
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• pp.464-473
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• 2005

Purpose: The purpose of this study was to evaluate and compare the predictive ability of three mortality scoring systems; Acute Physiology and Chronic Health Evaluation(APACHE) III, Simplified Acute Physiology Score(SAPS) II, and Mortality Probability Model(MPM) II in discriminating in-hospital mortality for intensive care unit(ICU) patients with spontaneous intracerebral hemorrhage. Methods: Eighty-nine patients admitted to the ICU at a university hospital in Daejeon Korea were recruited for this study. Medical records of the subject were reviewed by a researcher from January 1, 2003 to March 31, 2004, retrospectively. Data were analyzed using SAS 8.1. General characteristic of the subjects were analyzed for frequency and percentage. Results: The results of this study were summarized as follows. The values of the Hosmer-Lemeshow's goodness-of-fit test for the APACHE III, the SAPS II and the MPM II were chi-square H=4.3849 p=0.7345, chi-square H=15.4491 p=0.0307, and chi-square H=0.3356 p=0.8455, respectively. Thus, The calibration of the MPM II found to be the best scoring system, followed by APACHE III. For ROC curve analysis, the areas under the curves of APACHE III, SAPS II, and MPM II were 0.934, 0.918 and 0.813, respectively. Thus, the discrimination of three scoring systems were satisfactory. For two-by-two decision matrices with a decision criterion of 0.5, the correct classification of three scoring systems were good. Conclusion: Both the APACHE III and the MPM II had an excellent power of mortality prediction and discrimination for spontaneous intracerebral hemorrhage patients in ICU.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.1-9
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• 1990

The performance of noncoherent FH/FSK system in the presence of multitone jamming and noise is analyged. Random and the structured jammings are considered as a multitone jamming model. The probability density function is derived and then optimum decision rule is applied to determine error probability of each cases. As a result, error probabilities of random and structured multitone jamming are shown as a function of number of jamming tones, jamming to signal power ratio, jamming signal phase and one jamming tone power to signal power ratio under Worst-case Jamming interference. It is found that error probability is maximam when one jamming tone power to signal power ratio is 1. Also we know that error performance of random and structured jamming is almost equal.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.97-103
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• 2012

In this paper, we propose a novel voice activity detection (VAD) algorithm to effectively distinguish speech from nonspeech in various noisy environments. Global speech absence probability (GSAP) derived from likelihood ratio (LR) based on the statistical model is widely used as the feature parameter for VAD. However, the feature parameter based on conventional GSAP is not sufficient to distinguish speech from noise at low SNRs (signal-to-noise ratios). The presented VAD algorithm utilizes GSAP based on Teager energy (TE) as the feature parameter to provide the improved performance of decision for speech segments in noisy environment. Performances of the proposed VAD algorithm are evaluated by objective test under various environments and better results compared with the conventional methods are obtained.

• Journal of Aerospace System Engineering
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• v.11 no.4
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• pp.22-29
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• 2017

A study is performed for the effective detection method of a fault which is occurred during operation in a small turbojet engine with non-linear characteristics used by unmanned air vehicle. For this study the non-linear dynamic model of the engine is derived from transient thermodynamic cycle analysis. Also for inducing real operation conditions the controller is developed associated with unscented Kalman filter to estimate noises. Sequential probability ratio test is introduced as a real time method to detect a fault which is manipulated for simulation as a malfunction of rotational speed sensor contaminated by large amount of noise. The method applied to the fault detection during operation verifies its effectiveness and high feasibility by showing good and definite decision performances of the fault.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.373-383
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• 2006

The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.

• The Korean Journal of Food And Nutrition
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• v.29 no.6
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• pp.952-961
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• 2016

The objective of this study is to examine the effects of consumer beliefs regarding three food certifications on their behavioral intention and the behavioral intention biases to purchase (purchasing intention biases) certified agricultural products as predicted by a subjective probability model. The food certifications used for this study are 'Organic food', 'Traceability system of food products,' and 'Hazard Analysis Critical Control Point (HACCP)'. Tofu (bean curd) was selected as being representative of agricultural food products, for the purposes of this study. In 2016, we surveyed 243 consumers regarding the strength of their belief regarding their prior beliefs relative to each certification, as well as the strength of their intention to purchase certified tofu based on their belief strengths for this study. The study resulted in the following findings: Firstly, consumers hold more than two different prior beliefs for each of the three certifications included in this study. Consumers' prior beliefs regarding these certifications have an impact on their consideration as to whether they plan to buy those certified agricultural products. Secondly, consumers try to persuade themselves to ensure that their particular belief about the product's certification could lead to a purchasing decision regarding that agricultural product.

• Journal of Korean Society of Forest Science
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• v.76 no.4
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• pp.390-396
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• 1987

The model and its example were provided to predict wood production for a district forest planning. The method of Gentan probability is widely accepted for the prediction of wood production. The suggested model is different in the decision of cutting age distribution from that of Prof. Suzuki; the former can use either Weibull distribution or Gamma distribution, but the latter is possible only by Gamma distribution. This developed system can be used not only for establishing a district forest planning, but also for providing forest management information, such as periodic harvest volume, growing stock, labor requirement, and so forth.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.53-62
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• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.