• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.306-315
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• 2014

The purpose of this study in the case of stress recognition, the lower the age was, as they had a spouse, the higher they got educated, and the worse their subjective health state was, the higher the stress recognition appeared. this study selected 6,227 adults over the age of 19 from the 5th first-year data of Korean National Health and Nutrition Examination Survey(KNHNES)conducted by KCDC(Korea Centers for Disease Control and Prevention)in 2010. In the case of experience of depression symptoms, female subjects experienced more depression symptoms than male ones; study subjects aged between 19 and 54 years experienced more; the worse their subjective health state was, the more they experienced; and in the case of non-education about diabetics, those who did physical activity more than four days experienced more symptoms. In the case of suicide ideation, female subjects ideation suicide more than male ones; as they had no spouse, the lower they got educated, the worse their subjective health state was, and as they never did physical activity, they more experienced suicide ideation. Then, it is expected that the results of this study can contribute to chronic-disease patients'leading a much healthier life in the future.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.142-148
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• 2023

The National Agency for Quality Assurance in Higher Education plays a crucial role in education in Ukraine, as an independent entity creates and ensures quality standards of higher education, which allow to properly implement the educational policy of the state, develop the economy and society as a whole.The purpose of the article: to reveal the crucial role of the National Agency for Quality Assurance in Higher Education to create quality management of higher education institutions, to show its mechanism as an independent entity that creates and ensures quality standards of higher education. and society as a whole. The mission of the National Agency for Quality Assurance in Higher Education is to become a catalyst for positive changes in higher education and the formation of a culture of its quality. The strategic goals of the National Agency are implemented in three main areas: the quality of educational services, recognition of the quality of scientific results, ensuring the systemic impact of the National Agency. The National Agency for Quality Assurance in Higher Education exercises various powers, which can be divided into: regulatory, analytical, accreditation, control, communication.The effectiveness of the work of the National Agency for Quality Assurance in Higher Education for 2020 has been proved. The results of a survey conducted by 183 higher education institutions of Ukraine conducted by the National Agency for Quality Assurance in Higher Education are shown. Emphasis was placed on the development of "Recommendations of the National Agency for Quality Assurance in Higher Education regarding the introduction of an internal quality assurance system." The international activity and international recognition of the National Agency for Quality Assurance in Higher Education are shown.

• English Language & Literature Teaching
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• v.17 no.3
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• pp.273-290
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• 2011

This paper presents a case study involving one Korean primary school student and people around him in order to explore the reading process in English of a young Korean EFL learner and to investigate the social context in which his reading takes place. Six participants were included in the study (one primary school student and five adult participants). The student participant was asked to read a text in English and translate what he read into Korean and the teacher participants were asked to listen to the student's reading. Semi-structured interview was used to collect data from the student as well as five adult participants (his private tutor, his parent, his state school teacher, and two other state school teachers). The analysis reveals four characteristics of the way a young EFL learner approaches reading: word-by-word reading, disconnected word recognition, selective use of cues, and lack of awareness of difficulties. The four characteristics of Kilsu's reading suggest that reading can become a wild guessing game for young foreign learners, if they give selective attention to unimportant cues while reading. The pedagogical implications of this study are also discussed to help teachers designing reading lessons for young learners.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.11
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• pp.1035-1042
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• 1998

After the 1990's, a computer-aided partial discharge(PD) measurement system was referred in part of aging diagnosis using digital signal processing as the new technology has been studied. The PD patterns and relevant information for pattern recognition are discussed in PD research area, because discharge quantity(q), the number of discharge pulse(n) and the applied boltage phase($\varphi$) was combined with the system information of the aging state. This paper investigates the discharge phase and quantity, as well as the number of discharge(n) with regard to discharge signals generated in power cable. therefore, according to characteristic analysis on the distribution of $\varphi$, q and n, it is able to apply in the aging analysis of power cable which visual observation is impossible and distribution change of discharge signals offers much information for risk degree on aging progress of insulation materials.

• 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.

• KIEE International Transactions on Power Engineering
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• v.4A no.1
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• pp.33-41
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• 2004

Knowledge of partial discharge (PD) is important to accurately diagnose and predict the condition of insulation. The PD phenomenon is highly complex and seems to be random in its occurrence. This paper indicates the possible use of chaos theory for the recognition and distinction concerning PD signals. Chaos refers to a state where the predictive abilities of a systems future are lost and the system is rendered aperiodic. The analysis of PD using deterministic chaos comprises of the study of the basic system dynamics of the PD phenomenon. This involves the construction of the PD attractor in state space. The simulation results show that the variance of an orthogonal axis in an attractor of chaos theory increases according to the magnitude and the number of PDs. However, it is difficult to clearly identify the characteristics of the PDs. Thus, we calculated the magnitude on an orthogonal axis in an attractor using singular value decomposition (SVD) and principal component analysis (PCA) to extract the numerical characteristics. In this paper, we proposed the condition monitoring method for gas insulated switchgear (GIS) using SVD for efficient calculation of the variance. Thousands of simulations have proven the accuracy and effectiveness of the proposed algorithm.

• Nuclear Engineering and Technology
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• v.52 no.6
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• pp.1188-1200
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• 2020

In this paper, we consider a SDMS (Self-Diagnostic Monitoring System) for a reciprocating pump for the purpose of not only diagnosis but also prognosis. We have replaced a multi class estimator that selects only the most probable one with a multi label estimator such that we are able to see the state of each of the components. We have introduced a measure called certainty so that we are able to represent the symptom and its state. We have built a flow loop for a reciprocating pump system and presented some results. With these changes, we are not only able to detect both the dominant symptom as well as others but also to monitor how the degree of severity of each component changes. About the dominant ones, we found that the overall recognition rate of our algorithm is about 99.7% which is slightly better than that of the former SDMS. Also, we are able to see the trend and to make a base to find prognostics to estimate the remaining useful life. With this we hope that we have gone one step closer to the final goal of prognosis of SDMS.

• Nuclear Engineering and Technology
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• v.52 no.7
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• pp.1436-1442
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• 2020

Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.237-244
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• 2016

There are two destinations to aware the risk of common life. Recognition of the condition of pedestrian's own and the environmental factor awareness both are beneficial for risk awareness. It is good way of advancing the crime prevention effectivity that including IoT technology at the crime prevention research. The purpose of this research is that advanced way of crime prevention with multi-sensor data fusion of the condition of pedestrian and environmental factors. The 3-axis acceleration sensor is available to recognize the gait and the illumination sensor also useful to infer the road state. This research suggest a novel way of assess these factors and the result is the degree of danger.

• Journal of Sensor Science and Technology
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• v.29 no.1
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• pp.68-73
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• 2020

This paper proposes an asynchronous circuit design methodology using a new Single Gate Sleep Convention Logic (SG-SCL) with advantages such as low area overhead, low power consumption compared with the conventional null convention logic (NCL) methodologies. The delay-insensitive NCL asynchronous circuits consist of dual-rail structures using {DATA0, DATA1, NULL} encoding which carry a significant area overhead by comparison with single-rail structures. The area overhead can lead to high power consumption. In this paper, the proposed single gate SCL deploys a power gating structure for a new {DATA, SLEEP} encoding to achieve low area overhead and low power consumption maintaining high performance during DATA cycle. In this paper, the proposed methodology has been evaluated by a liquid state machine (LSM) for pattern and digit recognition using FPGA and a 0.18 ㎛ CMOS technology with a supply voltage of 1.8 V. the LSM is a neural network (NN) algorithm similar to a spiking neural network (SNN). The experimental results show that the proposed SG-SCL LSM reduced power consumption by 10% compared to the conventional LSM.