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

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.91-100
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• 2010

According to the recent increase in air traffic a more efficient air traffic flow control is required. This paper proposes the algorithm for efficient air traffic flow control. Aeronautical communication environment is different from the common communication environment since it needs a direct communication between stations (or airplanes) and requires a strict priority for safety message. Moreover, the wide area for basic service causes high propagation delay. In this paper, by using existing CSMA/CA Media Access Control (MAC) protocol, we set the message priorities according to air traffic condition (congestion airport area, approach control area, En route area, and ocean area). This prioritization scheme enables the data transmission with higher access probability. Simulation results confirm that our protocol shows better performance in terms of channel efficiency and success probability compared to exisiting CSMA/CA protocol.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.735-742
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• 2007

In this study, a methodology which is based on segments and minimum outsets to estimate the reliability of a real water distribution system efficiently and accurately is suggested. The current reliability assessment models based on minimum cutset consider a pipe as only area impacted by a pipe failure which incurs underestimation of pipe failure impact. In contrary, the suggested methodology adopts "segment" and "unintended isolation" with the hydraulic pressure failure area to define the actual service interruption area in a water distribution system due to a pipe failure, which is different from the Previous reliability estimating methodologies. In addition, a minimum cutset is defined as a single segment incurring abnormal operating conditions and the success mode approach is used to account for the probability of multiple failure combinations of minimum outsets. The model considers numbers and locations of on-off valves when the service interruption area is defined. Once the methodology is applied to a real water distribution system, it is possible to define actual service interruption areas and using the defined areas, the reliability of the water distribution system is estimated reliably, compared with the previous reliability assessment methodologies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3486-3491
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• 2012

The purpose of this study was to examine the variables of success in the national dental hygienist licence examination at D college. The subjects in this study were 120 dental hygiene juniors at D college located in Gangwon Province. The collected data were analyzed by the statistical package SPSS WIN 13.0 and a R2.13.2 program, and $x^2$(Chi-square) test, regression analysis, multiple linear regression analysis and logistic regression analysis were utilized. The findings of the study were as follows: 1. There was a tendency that the pass rate was higher among the students who were more satisfied with their major, whose academic standing was higher and who scored higher in trial examinations. 2. There was a positive correlation between academic standing and trial exam scores. 3. When their academic standing and satisfaction level with major were the same, an increase of one point in trial exams led to a 1.141-fold rise in the probability of passing the national exam. In this study, trial exam scores were identified as the variable to exert the largest influence on success in the national dental hygienist qualification exam. Therefore more intensive guidance should be provided for students who make a preparation for the national exam yet score low in trial exams.

• Journal of the Korean Regional Science Association
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• v.9 no.2
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• pp.103-119
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• 1993

This research examines the spatial development of rural industrial estates (Nong-gong Jigu) in Chonbuk province and gives insight into the strategies for economic development in the entire region. Selected location factors which are likely to pull new investment into the estates are examined by using questionnaires. Few loction factors except nonlocal factors can be found in explaining why location choices are made. The irrelevance of the analysis based on location factors suggests that an alternative approach should analyze changes in the spatial development of the rural industrial estates. Such an alternative is to understand the dynamics of the spatial organization of production by focusing on characteistics of plant closing in the rural industrial estates. To take into account of the characteristics of plant closing we provide the hypothesized relationships between employment size, organizational structure, inter and intra industrial linkage, characteristics of production processes, and availability of local labor market and the likelihood of closing. A logit model is then made to identify the selected factors which might influence the probability of plant closing. The results from the logit analysis and their implications suggest that the policy should be more concerned with the characteristics of firms, such as size and ownership, as well as of the local labor markets. Given that the Chonbuk region has experienced rapid population decline, together with its poor industrial base, it seems that the success of the policy in the declined rural areas in less certain.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.3
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• pp.235-241
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• 2012

The efficiency tests of automatic positioning transmitter (APT) using satellite on life jacket were carried out to minimize casualties of fishermen and to make system optimization for effective SAR (Search and Rescue) operation. As the result of the tests, average position was equaled on the comparison between SPOT using low earth orbit satellite and DGPS (Differential Global Positining System), but standard deviation of DGPS for latitude and longitude were 66.4% and 46.3% smaller than those of SPOT. The position precision of SPOT was almost two times lower than LGT using geostationary satellite to compare 95% circular error probability. However, the success rate of receiver for SPOT was revealed as 86.5~94.1% on the experiments in the South Sea and the West Sea and it was 4.5 times higher than LGT. Therefore, SPOT is expected to contribute greatly to the rapid rescue of victim.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.44.3-45
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• 2016

In this study, we identify 307 the geosynchronous magnetopause crossing (GMC) using geosynchronous satellite observation data from 1996 to 2010 as well as make an observational test of magnetopause location models using the identified events. For this, we consider three models: Petrinec and Russell (1996), Shue et al. (1998), and Lin et al. (2010). To evaluate the models, we estimate a Probability of Detection (PoD) and a Critical Success Index (CSI) as a function of year. To examine the effect of solar cycle phase, we consider three different time periods: (1) ascending phase (1996-1999), (2) maximum phase (2000-2002), and (3) descending phase (2003-2008). Major results from this study are as follows. First, the PoD values of all models range from 0.6 to 1.0 for the most of years. Second, the PoD values of Lin et al. (2010) are noticeably higher than those of the other models. Third, the CSI values of all models range from 0.3 to 0.6 and those of Shue et al. (1998) are slightly higher than those of the other models. Fourth, the predicted magnetopause radius based on Lin et al.(2010) well match the observed one within one earth radius, while that on Shue et al. (1998) overestimate the observed one by about 2 earth radii. Fifth, the PoD and CSI values of all the models are better for the solar maximum phase than those for the other phases, implying that the models are more optimized for the phase.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.133-140
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• 2018

In electronic warfare(EW), low probability of intercept(LPI) radar signal is a survival technique. Accordingly, identification techniques of the LPI radar waveform have became significant recently. In this paper, classification and extracting parameters techniques for 7 intrapulse modulated radar signals are introduced. We propose a technique of classifying intrapulse modulated radar signals using Convolutional Neural Network(CNN). The time-frequency image(TFI) obtained from Choi-William Distribution(CWD) is used as the input of CNN without extracting the extra feature of each intrapulse modulated radar signals. In addition a method to extract the intrapulse radar modulation parameters using binary image processing is introduced. We demonstrate the performance of the proposed intrapulse radar waveform identification system. Simulation results show that the classification system achieves a overall correct classification success rate of 90 % or better at SNR = -6 dB and the parameter extraction system has an overall error of less than 10 % at SNR of less than -4 dB.

• Biomolecules & Therapeutics
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• v.21 no.1
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• pp.10-20
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• 2013

Prostate cancer is one of the most prevalent non-skin related cancers. It is the second leading cause of cancer deaths among males in most Western countries. If prostate cancer is diagnosed in its early stages, there is a higher probability that it will be completely cured. Prostatic acid phosphatase (PAP) is a non-specific phosphomonoesterase synthesized in prostate epithelial cells and its level proportionally increases with prostate cancer progression. PAP was the biochemical diagnostic mainstay for prostate cancer until the introduction of prostate-specific antigen (PSA) which improved the detection of early-stage prostate cancer and largely displaced PAP. Recently, however, there is a renewed interest in PAP because of its usefulness in prognosticating intermediate to high-risk prostate cancers and its success in the immunotherapy of prostate cancer. Although PAP is believed to be a key regulator of prostate cell growth, its exact role in normal prostate as well as detailed molecular mechanism of PAP regulation is still unclear. Here, many different aspects of PAP in prostate cancer are revisited and its emerging roles in other environment are discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.