• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.477-482
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• 2020

The human visual cortex has the characteristic that reacts sensitively to stimuli with special directional or temporal frequency changes while it is insensitive to selective stimuli of spatial phases. In this paper we implemented the model of complex cell using an image estimation iterative algorithm by Gabor wavelet transform. The performance of implemented model evaluated the consistency between the physiological experimental results in related papers. The implemented model is limited in the complete model of the receptive field in the retina where simple cells and complex cells are distributed together. But the implemented model express the reaction of the complex cells from the point of view of the detection of corners and edges.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.1004-1012
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• 2020

We present a novel content-preserving seam estimation algorithm for real-time high-resolution video stitching. Seam estimation is one of the fundamental steps in image/video stitching. It is to minimize visual artifacts in the transition areas between images. Typical seam estimation algorithms are based on optimization methods that demand intensive computations and large memory. The algorithms, however, often fail to avoid objects and results in cropped or duplicated objects. They also lack temporal consistency and induce flickering between frames. Hence, we propose an efficient and temporarily-consistent seam estimation algorithm that utilizes a straight line. The proposed method also uses convolutional neural network-based instance segmentation to locate seam at out-of-objects. Experimental results demonstrate that the proposed method produces visually plausible stitched videos with minimal visual artifacts in real-time.

• Korean Journal of Culture and Social Issue
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• v.15 no.4
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• pp.565-589
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• 2009

The present study explored the major components of adaptive game behavior among adolescents in Korea. Based on relevant research and a pilot testing, an Adaptive Game Use Scale (AGUS) was developed and validated. A stratified sampling procedure was used to draw a representative sample, and a total of 600 male and female students from middle schools and high schools in various regions participated in the study. Factor analyses revealed 7 facets of adaptive game behavior, including experiencing vitality, expanding life experience, making good use of leisure time, experiencing flow, exercising control, experiencing self-esteem, maintaining and expanding social network. Internal consistency and temporal stability(4 weeks) of the scale were both high. A confirmatory factor analysis indicated that a 7-factor hierarchical model fits well with the data. Moreover, additional analyses suggested that AGUS and game addiction are conceptually distinct. Correlational analyses also indicated that AGUS has good discriminant validity and concurrent validity. Implications of the findings and future directions were discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.312-320
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• 2023

Recently, there has been an increasing attempt to replace defect detection inspections in the manufacturing industry using deep learning techniques. However, obtaining substantial high-quality labeled data to enhance the performance of deep learning models entails economic and temporal constraints. As a solution for this problem, semi-supervised learning, using a limited amount of labeled data, has been gaining traction. This study assesses the effectiveness of semi-supervised learning in the defect detection process of manufacturing using the MixMatch algorithm. The MixMatch algorithm incorporates three dominant paradigms in the semi-supervised field: Consistency regularization, Entropy minimization, and Generic regularization. The performance of semi-supervised learning based on the MixMatch algorithm was compared with that of supervised learning using defect image data from the metal casting process. For the experiments, the ratio of labeled data was adjusted to 5%, 10%, 25%, and 50% of the total data. At a labeled data ratio of 5%, semi-supervised learning achieved a classification accuracy of 90.19%, outperforming supervised learning by approximately 22%p. At a 10% ratio, it surpassed supervised learning by around 8%p, achieving a 92.89% accuracy. These results demonstrate that semi-supervised learning can achieve significant outcomes even with a very limited amount of labeled data, suggesting its invaluable application in real-world research and industrial settings where labeled data is limited.

• Journal of the Korean earth science society
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• v.21 no.3
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• pp.287-301
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• 2000

In order to investigate the factors and processes affecting the vertical distributions of ozone, we analyzed the ozone profile data measured using ozonesonde from 1995 to 1997 at Pohang city, Korea. In the course of our study, we analyzed temporal and spatial distribution characteristics of ozone at four different heights: surface (100m), troposphere (10km), lower stratosphere (20km), and middle stratosphere (30km). Despite its proximity to a local, but major, industrial complex known as Pohang Iron and Steel Co. (POSCO), the concentrations of surface ozone in the study area were comparable to those typically observed from rural and/or unpolluted area. In addition, the findings of relative enhancement of ozone at this height, especially between spring and summer may be accounted for by the prevalence of photochemical reactions during that period of year. The temporal distribution patterns for both 10 and 20km heights were quite compatible despite large differences in their altitudes with such consistency as spring maxima and summer minima. Explanations for these phenomena may be sought by the mixed effects of various processes including: ozone transport across two heights, photochemical reaction, the formation of inversion layer, and so on. However, the temporal distribution pattern for the middle stratosphere (30km) was rather comparable to that of the surface. We also evaluated total ozone concentration of the study area using Brewer spectrophotometer. The total ozone concentration data were compared with those derived by combining the data representing stratospheric layers via Umkehr method. The results of correlation analysis showed that total ozone is negatively correlated with cloud cover but not with such parameter as UV-B. Based on our study, we conclude that areal characteristics of Pohang which represents a typical coastal area may be quite important in explaining the distribution patterns of ozone not only from surface but also from upper atmosphere.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.291-300
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• 2013

Typhoon simulation method is widely used to estimate sea surface wind speeds during the typhoon periods. Holland (1980) model has been regarded to provide relatively better results for observed wind data. JTWC or RSMC best track data are available for typhoon modeling, but these data show slightly different because the data generation process are different. In this paper, a Newton-Raphson method is used to solve the two nonlinear equations based on the Holland model that is formed by the two typhoon parameters, i.e. the longest radius of 25 m/s and 15 m/s wind speeds, respectively. The solution is the radius of maximum wind speed which is of importance for typhoon modeling. This method is based on the typhoon wind profile of JMA and it shows that Holland model appears to fit better the characteristics of typhoons on the temporal and spatial changes than that of the other models. In case of using RSMC best track data, the method suggested in this study shows better and more reasonable results for the estimation of radius of maximum wind speed because the consistency of the input data is assured.

• Management & Information Systems Review
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• v.34 no.5
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• pp.213-231
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• 2015

In this paper, I examine whether the listed companies in Korea tend to manage operating cash flows upward via classification shifting after the adoption of K-IFRS. As proxies for cash flow management, I derive a measure of abnormal operating cash flows borrowing from Lee(2012). Alternative proxies include a series of categorical variables designed to identify the types of classification shifting of interest and dividend payments among others, in the statement of cash flows. Higher level of estimated abnormal operating cash flows, and the classification of interest/dividend payments in non-operating activity sections are considered to indicate the managerial intention to maximize reported operating cash flows. I consider several potential incentives to manage operating cash flows, which include financial distress, the credit rating proximity to investment/non-investment cutoff threshold, avoidance of negative or decreasing operating cash flows relative to previous period and so forth. In a series of empirical analyses, I do not find evidence in support of the opportunistic classification shifting explanation, inconsistent with several previous literature in Korea. In contrast, I observe negative associations between the CFO management proxies and selected incentives, which suggest that the classification is likely to represent above average cash flow performance rather than opportunistic motives exercised to maximize reported operating cash flows. I reckon that this observation is, in part, driven by the K-IFRS requirement to maintain temporal consistency in classifying interest and dividend receipts/payments in cash flow statement.

• Ocean and Polar Research
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• v.42 no.3
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• pp.195-210
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• 2020

The observed time series from the Korea Ocean Research Stations (KORS) in the Yellow and East China Seas (YECS) have various sources of noise, including bio-fouling on the underwater sensors, intermittent depletion of power, cable leakage, and interference between the sensors' signals. Besides these technical issues, intricate waves associated with background tidal currents tend to result in substantial oscillations in oceanic time series. Such technical and environmental issues require a regionally optimized automatic quality control (QC) procedure. Before the achievement of this ultimate goal, we examined the approach of the Ocean Observatories Initiative (OOI)'s standard QC to investigate whether this procedure is pertinent to the KORS. The OOI QC consists of three categorized tests of global/local range of data, temporal variation including spike and gradient, and sensor-related issues associated with its stuck and drift. These OOI QC algorithms have been applied to the water temperature time series from the Ieodo station, one of the KORS. Obvious outliers are flagged successfully by the global/local range checks and the spike check. Both stuck and drift checks barely detected sensor-related errors, owing to frequent sensor cleaning and maintenance. The gradient check, however, fails to flag the remained outliers that tend to stick together closely, as well as often tend to mark probably good data as wrong data, especially data characterized by considerable fluctuations near the thermocline. These results suggest that the gradient check might not be relevant to observations involving considerable natural fluctuations as well as technical issues. Our study highlights the necessity of a new algorithm such as a standard deviation-based outlier check using multiple moving windows to replace the gradient check and an additional algorithm of an inter-consistency check with a related variable to build a standard QC procedure for the KORS.

• Anxiety and mood
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• v.12 no.2
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• pp.103-112
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• 2016

Objective : This study was conducted to examine the reliability and validity of the Measure of Constructs Underlying Perfectionism-Korean version (M-CUP-K). Methods : Two hundred and six normal subjects completed a battery of measures including M-CUP-K, Frost Multidimensional Perfectionism Scale-Korean version (FMPS-K), and Beck Depression Inventory (BDI). Psychometric properties of the M-CUP-K were analyzed. Results : The principal component analysis for construct validity resulted in 56 items composed of 6 factors (factor 1 : Dissatisfaction-Reactivity to Mistakes; factor 2 : Order-Details and Checking ; factor 3 : Satisfaction ; factor 4 : High standards ; factor 5 : Perceived Pressure from Others-Perfectionism toward Others ; factor 6 : Black and White Thinking about Tasks and Activities), compared to the original version. The M-CUP-K total and subscale scores were more strongly correlated with those of the other perfectionism-specific measure, FMPS-K, with a correlation of 0.822 (convergent validity) than with those of the nonspecific depression measure (discriminant validity). The Cronbach's ${\alpha}$ value for internal consistency of M-CUP-K was in an excellent range (r=0.872-0.935). The test-retest reliability for external validity suggested a good temporal stability with a total score correlation of 0.827. Conclusion : This study revealed that the M-CUP-K has good reliability and validity. Therefore, the M-CUP-K can be used as a promising measure of perfectionism in Korea.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.53-71
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• 2006

In order to cope with the rapidly changing product development environment, individual manufacturing enterprises are forced to collaborate with each other through establishing a virtual organization. In collaboration, designated organizations work together for mutual gain based on product data interoperability. However, product data interoperability is not fully facilitated due to semantic inconsistency among product data models of individual enterprises. In order to overcome the semantic inconsistency problem, this paper proposes a reference ontology, Reference Domain Ontology(RDO), and a methodology for product data interoperability with semantic consistency using RDO. RDO describes semantics of product data model and metamodel for all application domains in a virtual organization. Using RDO, application domains in a virtual organization can easily understand the product data models of others. RDO is agile and temporal such that it is created with the formation of a virtual organization, copes with changes of the organization, and disappears with the vanishment of the organization. RDO is built by a hybrid approach of top-down using a upper ontology and bottom-up based on the merging of ontologies of application domains in a virtual organization. With this methodology, every domain in a virtual organization can achieve product data model interoperability without model transformation.