• Korean Journal of Artificial Intelligence
• /
• v.12 no.2
• /
• pp.1-7
• /
• 2024

In this paper, we compare three models (logistic regression, Random Forest, and XGBoost) for predicting stroke occurrence using data from the Korea National Health and Nutrition Examination Survey (KNHANES). We evaluated these models using various metrics, focusing mainly on recall and F1 score to assess their performance. Initially, the logistic regression model showed a satisfactory recall score among the three models; however, it was excluded from further consideration because it did not meet the F1 score threshold, which was set at a minimum of 0.5. The F1 score is crucial as it considers both precision and recall, providing a balanced measure of a model's accuracy. Among the models that met the criteria, XGBoost showed the highest recall rate and showed excellent performance in stroke prediction. In particular, XGBoost shows strong performance not only in recall, but also in F1 score and AUC, so it should be considered the optimal algorithm for predicting stroke occurrence. This study determines that the performance of XGBoost is optimal in the field of stroke prediction.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.105-108
• /
• 2006

Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every you. However, the aim of our study understands the influence of meteorological factors (air and water temperature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations). Finally our purpose is support to the prediction information for the possible red tide occurrence by coastal meteorological information and contribute to reduce the red tide disaster by the prediction technique for red tide.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.4
• /
• pp.844-853
• /
• 2005

Red tide(harmful algae) in the Korean Coastal Waters has a given a given damage to the fishery every year. However, the aim of our study understands the influence of meteorological factors (air and water temperature, precipitation sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations. Finally our purpose is support to the prediction information for the possible red tide occurrence by coastal meteorological information and contribute to reduce the red tide disaster by the prediction technique for red tide.

• Journal of the Ergonomics Society of Korea
• /
• v.5 no.2
• /
• pp.27-31
• /
• 1986

There has been a growing interest in the application of biorhythm theory to programmes of accident prevention and performance prediction. In order for biorhythm to be applie to practice its validity and reliability should be established. This paper reported the results of three different set of data, and these data were tabulated and analysed in various ways. The basic method of analysis consisted of stat- istical comparision of actual frequences of occurrence from the collected data with those frequencies which would be expected if biorhythm had no effect. The results of the occurrence data indicated that no definite evidence in support of the influence of the fundamentals could be detected. Actual frequencies of occurrence from the collected data were not significantly different them those expected assuming random occurrence.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.656-656
• /
• 2002

It is studied on the relationship between the occurrence of red tide(Chlorophyll-a concentration by the in-situ and satellite data) and the meteorological factors (precipitation, air temperature, sunshine and winds) in the coastal areas in the South Sea of Korea. In summer and early-fall which frequently occurred the red tide, the precipitation above 213mm had directly influence on the occurrence of red tide because it carried the nutritive substance which originated from the land into the coastal areas. Then air temperature kept up generally high values as 23~26$^{\circ}C$, and sunshine with 187~198hours and wind velocity with 3.1~7.9m/s showed not directly the relationship on the occurrence of red tide.

• Korean Journal of Remote Sensing
• /
• v.19 no.1
• /
• pp.21-30
• /
• 2003

It was studied the relationship between the red tide occurrence and the meteorological and oceanographic factors, the choice of potential area for red tide occurrence, and the satellite monitoring for red tide. From 1990 through 2001, the red tide continuously appeared and the number of red tide occurrence increased every year. Then, the red tide bloomed during the periods of July and August. An important meteorological factor governing the mechanisms of the increasing in number of red tide occurrence was heavy precipitation. Oceanographic factors of favorable marine environmental conditions for the red tide formation included warm water temperature, low salinity, high suspended solid, low phosphorus, low nitrogen. A common condition for the red tide occurrence was heavy precipitation 2∼4 days earlier, and the favorable conditions for the red tide formation were high air temperature, proper sunshine and light winds for the day in red tide occurrence. From satellite images, it was possible to monitor the spatial distributions and concentrations of red tide. It was founded the potential areas for red tide occurrence in August 2000 by CIS conception: Yeosu∼Dolsan coast, Gamak bay, Namhae coast, Marado coast, Goheung coast, Deukryang bay, respectively.

• Journal of The Geomorphological Association of Korea
• /
• v.19 no.2
• /
• pp.81-98
• /
• 2012

This research aims 1) to analyse the spatial occurrence of red soils, in Korea 2) to predict their spatial distribution using terrain analyses, and 3) to interpret results from the perspective of pedogeomorphological processes. Red soils (often called red-yellow soils) in Korea are frequently found on welldrained plains and gently sloping areas. These soils are widely believed paleo-soils that were formed under hot and humid climatic conditions in the past. The spatial distribution of red soils was derived from the soil map of Korea, and a DEM based soil prediction was developed, based on a continuity equation to depict water and material flows over the landscape. About 64.5% of the red soil occurrence can be explained by the prediction. Close examinations between surveyed and predicted red soil maps show few distinctive spatial features. Granitic erosional plains at the inland of Korea show comparatively low occurrence of red soils, which might indicate active geomorphological processes within the basins. The occurrence of red soils at limestone areas is more abundant than that of the predicted, indicating the influence of parent materials on the formation of red soils. At and around lava plateau at Cheulwon and Youncheon, the occurrence of red soils is underestimated, which might partly be explained by the existence of loess-like surface deposits. There are also distinctive difference of prediction results between northern and southern parts of Korea (divided by a line between Seosan and Pohang). The results of this research calls for more detailed field-based investigations to understand forming processes of red soils, focusing on the spatial heterogeneity of pedological processes, the influence of parent materials, and difference in uplift patterns of the Korean peninsula.

• Journal of dental hygiene science
• /
• v.9 no.4
• /
• pp.419-426
• /
• 2009

The occurrence of toothache signals the malfunction in oral health, which allows the detection of any abnormal condition in the oral cavity at an early stage to prevent the condition from worsening, and thus can act as a preventive measure. This study has looked into the status of oral health management in relation to toothache through the structured survey administered to 235 college students. Based on the survey results, this study aimed at comparing the toothache occurrence prediction between regression analysis and CART model in order to clarify the relationship between the factors of oral health management habits that contribute to toothache occurrence. According to the result, there was a difference between the present health status and the health status of the past year depending on the presence or non-presence of toothache occurrence (p<0.05). There was a difference in the regularity of meal time depending on the presence non-presence of toothache occurrence from the dietary habits of the research subjects (p<0.05). As for the presence or non-presence of toothache occurrence from the oral hygiene habits of the research subject, there was a difference between the occurrence and nonoccurrence of bleeding during brushing or flossing (p<0.05). According to the results of regression analysis, no factors were signifiant in the relationship with the presence or non-presence of toothache occurrence from the status of life habits and oral hygiene habits. 70% of the researched group was randomly selected as the sample for generating an analytical model and the remaining 30% was used as the sample for generating an evaluation model. According to the results of CART model, the occurrence of toothache was higher in the case of irregular meal time and poor current health condition than the case of average or satisfactory health condition. The above results imply that CART model is very useful technique in predicting toothache occurrence compared to regression analysis, and suggests that CART model could be very useful in predicting other oral diseases including toothache.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.321-328
• /
• 2024

This paper designs a disease prediction algorithm to diagnose migraine among the types of diseases in advance by learning algorithms using machine learning-based time series analysis. This study utilizes patient data statistics, such as electroencephalogram activity, to design a prediction algorithm to determine the onset signals of migraine symptoms, so that patients can efficiently predict and manage their disease. The results of the study evaluate how accurate the proposed prediction algorithm is in predicting migraine and how quickly it can predict the onset of migraine for disease prevention purposes. In this paper, a machine learning algorithm is used to analyze time series of data indicators used for migraine identification. We designed an algorithm that can efficiently predict and manage patients' diseases by quickly determining the onset signaling symptoms of disease development using existing patient data as input. The experimental results show that the proposed prediction algorithm can accurately predict the occurrence of migraine using machine learning algorithms.

• The Journal of Engineering Geology
• /
• v.14 no.2
• /
• pp.211-222
• /
• 2004

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The seven landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The seven factors consist of two topographic factors and five geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 90.74% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.