• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.176-180
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• 2004

The ST-segment that the beginning part of T wave is the important diagnostic parameter to finding myocardial ischemia. Abnormal ST appears in two types. One is the level change, and the other is the pattern change. In this paper, we describe the monitoring of abnormal ST using PC based system. Hardware of this system consists of transmitter, receiver and PC. The function of transmitter is measuring ECG in three channels which are selected manually and transmitting the data to receiver by digital radio way. Connection with receiver and PC is by RS232C, and the data received on the PC is analyzed automatically by ECG analysis algorithm and saved to file. In the algorithm part for detecting abnormal ST, ST-segments are approximated by a polynomial. This method can detect all of the deviation and pattern change of ST-segment regardless the change in the heart rate or sampling rate. To gain algorithm reliability, the method rejects distorted polynomial approximation by calculation the difference between the approximated ST-segment and original ST-segment. In pre-signal processing, the wavelet transformation separates high frequency bands including QRS complex from the original ECG. Consequently, the process improves the performance of detecting each feature points.

• Journal of Biomedical Engineering Research
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• v.12 no.2
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• pp.89-98
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• 1991

This study is concerned on the automation for cell diagnosis which has better objectivity and speed of test than human beings. Diagnosis is on the basis of shape change of abnormal Cells. Used parameters are nucleus area, nucleus perimeter, nucleus shape, cytoplasm area, nucleus/cytoplsm ratio, which was obtained using image processing technics. A new mode method is proposed on the automatic threshold selection for superior process time compared with Otsu's. Contour of the cytoplasm of abnormal cell is obtained using me- dian filter and sorel operator. The mask to get only original shape of abnormal cells is formed uslng the contour filling algorithm. In the result the normal cells are separated from the abnormal cells and the abnormal cells can be distinguished through screwing of abnormal cell's image with reference data to judge abnormal cells. Owing to this study the number of inspections which the pathologists should examine will be decreased and the time for inspection will be shortened.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.317-330
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• 2013

The yield of rice production is affected severely by abnormal weather events, such as flood, drought, high temperature etc. The objective of this paper is to assess impacts of abnormal weather events on rice production, using a panel model which analyzes both cross-section data and ti- me series data. Abnormal weather is defined as the weather event which goes beyond the range of ${\pm}2{\sigma}$ from the average of a weather factor. The result of an analysis on impacts of high temperature on rice production showed that the yield of rice was decreased 5.8% to 16.3% under the conditions of extremely high temperature, and it was decreased 8.8 to 20.8% under the conditions of both extremely high and heavy rain. Adaptation strategies, development of new varieties enduring high temperature and heavy rain, adaptation of crop insurance, modernization of irrigation facilities are needed to minimize the impacts of abnormal weather on rice production, and to stabilize farmers' income.

• Journal of the Korean Ceramic Society
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• v.39 no.1
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• pp.21-25
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• 2002

Effect of abnormal grain growth and heat treatment time on the electrical properties of donor-doped semiconductive BaTiO$_3$ceramics was examined. La-doped BaTiO$_3$ceramics was sintered at 134$0^{\circ}C$ for different times from 10 to 600 min in order to change the volume fraction of the abnormal grains in samples. As a result, samples with different volume fraction of abnormal grain growth from 22 to 100% were prepared. The samples were annealed at 120$0^{\circ}C$ for various times. The resistivity of the sam-ples at room and above Curie temperature was examined. The complex impedance measurement as functions of the volume fraction of abnormal grains and annealing time was conducted. Separation of complex impedance semicircle was observed in a sample in which abnormal and fine grains coexist. The results are discussed from a viewpoint of microstructure-property relationship.

• Journal of the Korean Ceramic Society
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• v.32 no.5
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• pp.587-593
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• 1995

Abnomal grain growth behavior of BaTiO3 ceramics was investigated with addition of seed grains. It was foudn that the nucleation rate of abnormal grain was constant and growth of abnormal grain was linearly increased with sitnering time, regardless of amount of seed grains. These facts were also confirmed by fitting of the volume fraction of abnormal grain vs. sintering time using Avrami type equation (n=4). It was suggested that seed grains did not change the nucleation rate or growth mechanism of abnormal grain but increase the number of abnormal grains at initial stage of sintering and then it led to fine microstructure of BaTiO3 ceramics.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.707-713
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• 2014

The purpose of this article is analyzing the economic impacts of abnormal climate on total revenue of red pepper in Korea, with employing the equilibrium displacement model. Our simulation results show the rate of yield change, price change, and total revenue change according to the climate change scenarios. In th case of by RCP 8.5 Scenario, red pepper production volume would be expected to decrease by 77.2% compared to 2012 while price increasing by 29.6%. As a result, total revenue to be returned to farmers would be reduced by 47.6% than it was in 2012. In contrast, total revenue would be expected to decline by 29.6% according to RCP 4.5 scenario.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.43-49
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• 2023

Since 2018, due to climate change, heat waves and cold waves have caused gradual damage to social infrastructure. Since the damage caused by cold weather has increased every year due to climate change in recent 4 years, the damage that was limited to a specific area is now appearing all over the country, and a lot of efforts are being concentrated from experts in various fields to minimize this. However, it is not easy to study real-time observation of sudden abnormal low temperature in existing studies to reflect local characteristics in discontinuously measured data. In this study, based on the weather-related data that affects the occurrence of cold-weather damage, we developed an algorithm pattern that can identify the time when abnormal cold temperatures occurred after searching for weather patterns at the time of cold-weather damage. The results of this study are expected to be of great help to the related field in that it is possible to confirm the time when the abnormal low temperature occurs due to the data generated in real time without relying on the past data.

• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.244-250
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• 1999

This study aimed to analyze the effect of the change in CP class of a firm on the abnormal yield of its stock price. As a result, it was found that the change in CP class of a firm had an effect on the abnormal yield. That is. the abnormal yield rose when the class of CP rose while it dropped when the class of CP dropped. And it was analyzed that the class of CP in the firm in which its current net gain was great while it dropped in the firm in which the current net gain was small. And it was found that the CP class of the firm with the high debt to equity ratio rose when the CP class of the firm changed, whereas it rose in the firm with the low debt to equity ratio. But it was found that the size of majority shareholders equity rate in a firm, the size of corporate value of the firm, the size of cash flow of the firm and the size of the burden of financial costs of the firm were not related to the abnormal yield of its stock price. This study has its significance in analyzing the effect of the information on the change in CP class of the firm on the capital market. But it has its limitations in the sample firm and the selection of the point in time of disclosure.

• Journal of Climate Change Research
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• v.5 no.3
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• pp.257-266
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• 2014

This study aims to understand abnormal climate caused by impacts of climate change and to suggest the direction of urban planning focusing on adaptation to climate change. The study consists of theory consideration and case study(Chicago, Philadelphia, Seattle). As a result, the main impacts of climate change faced by urban areas are heat wave, precipitation, and drought. To prevent these impacts, it is important to prepare methods of urban planning as followings: planning for land use, park and green considering the climate patterns, establishing and managing water resources systems similar to the nature, securing renewable energy resources, and transportation facilities and exterior space with proof against climate. It is especially necessary to introduce infrastructures related to storm water, green roof, shading tree planting, green space, and permeable pavement. Finally, in order to realize urban planning for adaptation to climate change, it is needed to make the detailed and specific goal and strategy for the climate change adaptation plan and to extend the scope from the goals to an action plan, a detailed plan, and a design guideline.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.731-737
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• 2014

This paper presents abnormal behavior detection in crowd within surveillance video. We have defined below two cases as a abnormal behavior; first as a sporadically spread phenomenon and second as a sudden running in same direction. In order to detect these two abnormal behaviors, we first extract the motion vector and propose a new descriptor which is combined MHOF(Multi-scale Histogram of Optical Flow) and DCHOF(Directional Change Histogram of Optical Flow). Also, binary classifier SVM(Support Vector Machine) is used for detection. The accuracy of the proposed algorithm is evaluated by both UMN and PETS 2009 dataset and comparisons with the state-of-the-art method validate the advantages of our algorithm.