• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.176-183
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• 2005

The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1230-1242
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• 1993

In a case of mushroom (Lentinus Edodes L.) , visual features are crucial for grading and the quantitative evaluation of the growth state. The extracted quantitative visual features can be used as a performance index for the drying process control or used for the automatic sorting and grading task. First, primary external features of the front and back sides of mushroom were analyzed. And computer vision based algorithm were developed for the extraction and measurement of those features. An automatic thresholding algorithm , which is the combined type of the window extension and maximum depth finding was developed. Freeman's chain coding was modified by gradually expanding the mask size from 3X3 to 9X9 to preserve the boundary connectivity. According to the side of mushroom determined from the automatic recognition algorithm size thickness, overall shape, and skin texture such as pattern, color (lightness) ,membrane state, and crack were quantified and measured. A portion of t e stalk was also identified and automatically removed , while reconstructing a new boundary using the Overhauser curve formulation . Algorithms applied and developed were coded using MS_C language Ver, 6.0, PC VISION Plus library functions, and VGA graphic function as a menu driven way.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.210-218
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• 2004

Poly(ADP-ribose)polymerase-1 (PARP-1) is a nuclear enzyme involved in various physical functions related to genomic repair, and PARP inhibitors have therapeutic application in a variety of neurological diseases. Docking and the QSAR (quantitative structure-activity relationships) studies for 52 PARP-1 inhibitors were conducted using FlexX algorithm, comparative molecular field analysis (CoMFA), and hologram quantitative structure-activity relationship analysis (HQSAR). The resultant FlexX model showed a reasonable correlation (r$^{2}$ = 0.701) between predicted activity and observed activity. Partial least squares analysis produced statistically significant models with q$^{2}$ values of 0.795 (SDEP=0.690, r$^{2}$=0.940, s=0.367) and 0.796 (SDEP=0.678, r$^{2}$ = 0.919, s=0.427) for CoMFA and HQSAR, respectively. The models for the entire inhibitor set were validated by prediction test and scrambling in both QSAR methods. In this work, combination of docking, CoMFA with 3D descriptors and HQSAR based on molecular fragments provided an improved understanding in the interaction between the inhibitors and the PARP. This can be utilized for virtual screening to design novel PARP-1 inhibitors.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.205-215
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• 2017

The brain magnetic resonance images (MRI) is an important imaging biomarker in Alzheimer's disease (AD) as the cerebral atrophy has been shown to strongly associate with cognitive symptoms. The decrease of volume estimates in different structures of the medial temporal lobe related to memory correlates with the decline of cognitive functions in neurodegenerative diseases. During the past decades several methods have been developed for quantifying the disease related atrophy of hippocampus from MRI. Special effort has been dedicated to separate AD and mild cognitive impairment (MCI) related modifications from normal aging for the purpose of early detection and prediction. We trained a multi-class support vector machine (SVM) with probabilistic outputs on a sample (n = 58) of 20 normal controls (NC), 19 individuals with MCI, and 19 individuals with AD. The model was then applied to the cross-validation of same data set which no labels were known and the predictions. This study presents data on the association between MRI quantitative parameters of hippocampus and its quantitative structural changes examination use on the classification of the diseases.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.251-258
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• 2017

According to recent studies by scientists about how to search for food, homes and the mates, it is found that the gradient information plays a key role. From cells to insects and large animals, they mostly either have special sensing organism or use a strategy to measure the gradient. Use of a perturbation as an additional input is introduced for sensor signal processing in order to get the gradient information. Different from typical approach, which calculates the gradient from differentiation, the proposed processing is done by a form of integration, thus it is very robust to noise. Discrete time domain analyses are given for one, two and three input functions for the estimation of the gradients. The amplitude and the frequency of the perturbation are two important parameters for this approach. A quantitative index to measure the effects of the amplitude is developed based on the linear regression analysis. The frequency of the perturbation is to be selected high enough to finish one period of the perturbation before the property is changed significantly with respect to time. Another quantitative index is proposed for guiding the selection of the frequency.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• Journal of Life Science
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• v.31 no.2
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• pp.115-125
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• 2021

Calcium-dependent protein kinases (CDPKs) are known to be involved in regulating plant responses to abiotic stresses such as salinity, cold temperature and dehydration,. Although CDPKs constitute a large multigene family consisting of 31 genes in rice, only a few rice CDPKs' functions have been identified. Therefore, in order to elucidate the functions of OsCPK11 in rice, this study was intended to focus on the expression pattern analysis of OsCPK11 in wild type and ND0001 oscpk11 mutant plants under these abiotic stresses. For the salt, cold and drought stress treatment, seedlings were exposed to 200 mM NaCl, 4℃ and 20% PEG 6,000, respectively. RT-PCR and quantitative real-time PCR were performed to determine the expression patterns of OsCPK11 in wild type and ND0001 mutant plants. RT-PCR results showed that OsCPK11 transcripts in the wild type and heterozygous mutant were detected, but not in the homozygous mutant. Real-time PCR results showed that relative expression of OsCPK11 of wild type plants was increased and reached to the highest level at 24 hr, at 6 hr and at 24 hr under salt, cold and drought stress conditions, respectively. Relative expression of OsCPK11 of ND0001 homozygous plant was significantly reduced compared to that of wild type. These results suggested that oscpk11 homozygous mutant knocks out OsCPK11 and OsCPK11 might be involved in salt, cold and drought stress signaling by regulating its gene expression.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.259-265
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• 2024

In order to improve the SW convergence capabilities of university undergraduate students, methods to evaluate undergraduate students' code design capabilities should be researched along with the development of related courses. In previous studies, there were qualitative evaluation methods and quantitative relative evaluation methods for code results. In the quantitative relative evaluation method, the number of problem decomposition depth, number of function reuses, and number of functions were measured and evaluated. In this study, an evaluation method that was not presented in previous studies was proposed using the problem of presenting the number of input and output information types when designing code. The evaluation problems proposed in this paper applied up to three types of input information and three types of output information. Through this, five code design evaluation questions were presented and a method to quantitatively calculate code design scores was proposed. Codes from 100 student respondents were collected and analyzed through courses that applied the proposed evaluation method. Through result analysis, the number of problem decomposition depths was proportional to the number of types of input information, the number of function reuses was proportional to the number of types of output information, and the number of functions showed a correlation that was proportional to the total number of types of input and output information. Lastly, by analyzing the distribution of evaluation scores of 100 respondents, we demonstrated that the code design evaluation method according to the five input/output information condition evaluation problems is effective.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.116-129
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• 2020

Resilience is defined as the intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations or functions with the related systems under both expected and unexpected conditions. Resilience engineering is a relatively new paradigm for safety management that focuses on how to cope with complexity under pressure or disturbance to achieve successful functioning. This study aims to develop a quantitative resilience model for severe accident response organizations of nuclear power plants using the Analytic Hierarchy Process (AHP) method. First, we investigated severe accident response organizations based on a radiation emergency plan in the Korean case and developed a qualitative resilience model for the organizations with resilience-influencing factors, which have been identified in the author's previous studies. Then, a quantitative model for entire severe accident response organizations was developed by using the Analytic Hierarchy Process (AHP) method with a tool for System Dynamics. For applying the AHP method, several experts who are working on implementing, regulating or researching the severe accident response participated in collecting their expertise on the relative importance between all the possible relations in the model. Finally, a sensitivity analysis was carried out to discuss which factors have the most influenceable on resilience.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.6
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• pp.97-114
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• 2019

This study aims to analyze the effect of urban ecosystem restoration projects by evaluating the short-term restoration performance of the project sites, from both qualitative and quantitative evaluations. In this study, for the qualitative evaluation, we derived the evaluation frame from previous studies and literature. For the quantitative evaluation, the changes in ecological connectivity after the restoration project were described using landscape permeability and network analysis. In addition, changes in habitat quality after the restoration project were evaluated by using InVEST Habitat Quality Model. These evaluations were applied to the three natural madang (ecological restoration) projects and two ecosystem conservation cooperation projects. As a result, three categories, 10 indicators, and 13 sub-indicators were derived from literature as the evaluation frame for this study. In the case of quantitative evaluation of restoration performance, habitat quality increased by 45% and ecological connectivity by 37% in natural-madang, and habitat quality by about 12% and ecological connectivity by about 19% in ecosystem conservation cooperation projects. This implies that the ecological restoration project can increase the ecological connectivity and the habitat quality of degraded sites even in a short period of time by improving the land-cover and land use. The results by applying the evaluation frame indicated that ecological and environmental factors and the ecological functions were improved by the restoration works, even though the magnitude of performances were diverse depending on the specific evaluation items, project type, and site characteristics. This study clarified that the success of ecological restoration project should be assessed by both of the short-term and long-term goals, which can be achieved by the maintenance and sustainable management, respectively.