• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1353-1355
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• 1996

This paper presents classification of high impedance fault pattern using linear prediction coefficients. A feature of neutral phase current is extracted by the linear predictive coding. This feature is classified into faults by a multilayer perceptron neural network. Neural network successfully classifies test data into three faults and one normal state.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.498-500
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• 2019

Point cloud is a flexible set of points that can provide a scalable geometric representation which can be applied in different computer graphic task. We propose a method based on EdgeConv and densely connected layers to aggregate the features for better classification. Our proposed approach shows significant performance improvement compared to the state-of-the-art deep neural network-based approaches.

• Journal of Navigation and Port Research
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• v.27 no.3
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• pp.321-327
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• 2003

The Memorandum of Understanding (MOU) is the document of intent signed between the Port States Control(PSC) to undertake a uniform as agreed. Though the MOU is not a legally binding, in case where the agreed items are violated without a just cause, the denunciation will follow. International Maritime Organization (IMO) and regional MOUs have been making amendments and reinforcing the relevant requirements, so that port State Authorities can effectively eradicate the substandard vessels. However, the various problems have arisen due to the existence of different requirements of each MOU, the lack of information exchange between each MOU, the lack of uniform PSC implementation within the same MOU and the lack of adequate system due to the short history of MOUs. In this paper, the MOU records for three years (1999∼2001) were analyzed according to each MOU, type of ship, deficiency code, classification society, the number of inspected ships and the number of detained ships to assess the problems (Statistics during 2002 will be published after August 2003). The purpose of this study is to help better understand the PSC activities within each MOU and to establish effective countermeasures by grasping the problems that exist in the PSC at present.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.91-97
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• 2022

Pipes transport and supply fuel in various categories; however, corrosion occurs because of the external environment, impurities are mixed in the fuel, and substances leak to the outside, which can lead to serious accidents. Therefore, in this study, inspection equipment using a laser scanner was manufactured to classify conditions according to the degree of corrosion of the outer wall of the pipe, and the corrosion height and maximum value of the pipe were obtained from the surface information. Using the k-means method, it was classified into four states, and the standard of the average height and maximum height of corrosion for each state was derived.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.49-60
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• 2006

We propose a method to use a state transition model so that the sensing object can be distinguished through classification of signal patterns sensed by a sensor array. Focusing on the design of the model that is able to distinguish the sensed object more exactly, we present an idea in which the modeling elements, 'states' and 'transitions' are defined as each same-sized angle intervals into which the angle interval $(-\frac{\pi}{2},\frac{\pi}{2})$ is divided and the angle differences between adjacent signal values on sampling signal value sequence value sequence sensed from the sensor array in the uniform time interval, respectively. In addition we show the usefulness of our model through experiments.

• Journal of the Korean Chemical Society
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• v.59 no.4
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• pp.320-335
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• 2015

The purpose of this study was to identify the concepts of elementary school teachers related to three states of matter from activities of classifying various materials in life. The subjects were 25 teachers majored in primary science education at a graduate college of education and 10 teachers of elementary school located in a metropolitan city. A questionnaire and observation related to classification activities, and interviews were carried out and analyzed them qualitatively and quantitatively. From the analysis, we found that most elementary school teachers understood the classification criteria of three states of matter through macroscopic viewpoints and experienced difficulties in determining the state of mixture materials. After discussion of the classification results, the teachers’ concept was changed. But, when performing classification activity on the basis of the newly created concepts, it has not reached its results agreed. The result of this study shows that process of concept of science has been agreed in the same way to all people is not easy. Therefore, the teacher education programs to make possible to improve the ability capable of classifying the states of the various matters and to understand the nature of classification is required. In addition, deep discussion on the classification of the mixture is also necessary.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.3
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• pp.540-547
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• 2009

There needs disease-predictable signs in order to enable preventive diagnosis and therapy. Then traditional Chinese medicine applies various medical diagnostic equipments used in western medicine to diagnosing sub-healthy state. But such data are not originated from inherent oriental medicine, and not obtained easily in ordinary clinical practice. This paper is to provide synopsis of the ante-disease diagno-therapeutics partly and to show predictable data based on the facial shapes and signs, especially of gall bladder's versus bladder's body and masculine versus feminine shape. Ante-disease means not only the complete healthy state, but also the state unseen any symptoms in macrographically in the course of outbreak of disease. It contains two stages, first one is the former state of disease and second one is untransmitted state of disease. The patterns of ante-disease consist of latent disease, pre-disease, transmission type like senescent syndrome, abnormal reactive syndrome(變證), syndrome of transmission and transmutation. The classification with gall bladder and bladder type manifests the differences of shape, color and size of each organ in comparison of the universal and standard figures of the human being. On the other hand, the classification with masculine and feminine shape contrasts the innate sexual difference and the shape, characteristics originated from in itself. These two classification theories have their own pathologic types and syndrome types with each disease so that disease-predictable data can be constructed based on such a relationship. In addition, this diagnostic method by facial shapes and signs is able to be applied to whole stages from prenatal to present state of disease even if the cause and inducement are not clear. Ante-disease diagno-theraputic system by Gall Bladder's versus Bladder's Body and Masculine versus Feminine Shape is getting more important in the chronic and internal disease in comparison of the acute and traumatic disease. So this study is able to make up for the limit of diagnosis on ante-disease in the field of oriental medicine clinic.

• Korean Journal of Oriental Medicine
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• v.18 no.3
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• pp.119-126
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• 2012

1. Objectives Sasang constitutional medicine is unique in Korean traditional medicine. It diagnoses and treats patients based on his/her Sasang constitution (SC). Skin properties have been used as an effective diagnostic component in the classification of SC types in clinics. In this paper, we investigated the SC-based health relevance of skin elasticity and wrinkle properties. 2. Methods The skin elasticity and wrinkle of forearm and dorsal hand were measured in 299 elderly female subjects. To determine the subject's Sasang constitution, we adopted the classification results from a newly developed SC diagnostic tool. The health states of the subjects were scored by two Korean traditional medical doctors, by whom each subject was categorized either into the healthy state or the unhealthy state. 3. Results As a result, the elasticity hysteresis of forearm (E_HYS), the visco-elasticity (VE_MEAN), and the wrinkle frequency energy of backhand (W_HAND) showed significant differences between Taeum-in group and Soeum-in group. In case of the Soeum-in on unhealthy state, VE_MEAN was decreased significantly (p<.05). W_HAND and W_ARM_H of the healthy Taeum-in were less than those of the unhealthy Taem-in. 4. Conclusions In this study we showed that, for an elderly female population, skin elasticity and viscosity were significantly different not only between each SC type but also between healthy group and unhealthy group in each constitution. In particular, Soeum-in subjects were inferred to be superior in retaining skin softness when they were healthy, and Taeum-in subjects were easy to lose their firmness of skin surface when they became unhealthy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.357-365
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• 2022

Refrigerant mischarging is one of the most frequently occurring failure modes in air conditioners, and both undercharging and overcharging degrade cooling performance. Therefore, it is important to accurately determine the amount of charged refrigerant. In this study, a support vector machine (SVM) model was developed to multi-classify the refrigerant mischarge through steady-state identification via fuzzy clustering techniques. For steady-state identification, a fuzzy clustering algorithm was applied to the air conditioner operation data using the difference between moving averages. The identification results using the proposed method were compared with those using existing steady-state determination techniques studied through the inversed Fisher's discriminant ratio (IFDR). Subsequently, the main features were selected using minimum redundancy maximum relevance (mRMR) considering the correlation among candidate features, and an SVM multi-classification model was devised using the derived features. The proposed method achieves satisfactory accuracy and robustness from test data collected in the new domain.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.940-952
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• 2020

The Alzheimer's disease (AD) is a neurodegenerative disease commonly found in the elderly individuals. It is one of the most common forms of dementia; patients with AD suffer from a degradation of cognitive abilities over time. To correctly diagnose AD, compuated-aided system equipped with automatic classification algorithm is of great importance. In this paper, we propose a novel deep learning based classification algorithm that takes advantage of MRI biomarker images including brain areas of hippocampus and cerebrospinal fluid for the purpose of improving the AD classification performance. In particular, we develop a new approach that effectively applies MRI biomarker patch images as input to 3D Deep Convolution Neural Network. To integrate multiple classification results from multiple biomarker patch images, we proposed the effective confidence score fusion that combine classification scores generated from soft-max layer. Experimental results show that AD classification performance can be considerably enhanced by using our proposed approach. Compared to the conventional AD classification approach relying on entire MRI input, our proposed method can improve AD classification performance of up to 10.57% thanks to using biomarker patch images. Moreover, the proposed method can attain better or comparable AD classification performances, compared to state-of-the-art methods.