The conversation analysis approach of using audio and video recordings of naturally occurring conversation contrasts with other methods of collecting data in the social and cognitive sciences. This paper intends to describe the ways in which conversation analysts collect their data suitable for analysis, including the steps involved in preparing to record, the recording of naturally occurring social interaction, and also the processing of recordings after they have been made. Before actually making the recordings, researchers must first choose what type of conversation they will collect and what device to use. Researchers also need to obtain consent for recording from the participants in a conversation analytic study. While making the recordings, researchers must figure out many practical issues such as who, when, how, what, how much, and where to record. After recording, researchers need to store data in audio or video formats. Researchers also archive it, using codes for identification that facilitate later finding, quoting and retrieving of any file. This paper focuses on these choices as they are made before, during, and after recordings and places specific emphasis on the effects these choices have on the recordings. It also illuminates how these techniques are closely related to the methodological and theoretical assumptions of the conversation analysis approach.

This study examined the relevance of impact factors using survey data, standardized mortality rates, and medical utilization rates of study subjects in the Namhae and Hadong regions. The study subjects were found to have lived in the area for more than 20 years, and in terms of lifestyle, they did not smoke, but the rate of drinking was high and showed little exercise. As a result of analysis through logistic regression analysis, it was found that angina pectoris, myocardial infarction and anemia were affected by exercise status, and allergic rhinitis disease showed significant results depending on the presence of smoking. The standardized mortality rate of men in chronic lower respiratory tract diseases in the Namhae and Hadong regions was higher than in the nation. In the case of allergic rhinitis, both men and women in Namhae were slightly lower than those in Nation, and in Hadong, both men and women were higher than in Nation.

저작권법이 2011. 12. 2. 개정되어 공정이용 조항이 도입되었다. 이로써 저작물의 통상적인 이용 방법과 충돌하지 아니하고 저작권자의 정당한 이익을 부당하게 해치지 않는 경우에 해당하면 저작물을 이용할 수 있게 되었다. 공정이용 해당 여부를 판단하는 데에는 이용의 목적 및 성격, 저작물의 종류 및 용도, 이용된 부분이 저작물 전체에서 차지하는 비중과 그 중요성, 저작물의 이용이 그 저작물의 현재 시장 또는 가치나 잠재적인 시장 또는 가치에 미치는 영향 등을 고려하여야 한다. 미국 사례로서 선거운동에서 이용허락 없는 원음악저작물을 사용한 경우와 국내 사례로서 실제 골프코스를 화면에 재현하여 스크린 골프장 운영업체에 제공한 경우, 박람회에서 이용허락 없이 홍보 동영상을 재생한 경우, 방송사의 시험문제를 비판하기 위하여 대상 문항을 인터넷에 게시한 경우, 노동착취 행위를 알리는 과정에서 작가를 조롱하기 위하여 예술작품을 복제한 경우를 소개하고 이를 통해 실제 사례에서 위와 같은 판단 요소가 어떻게 고려되는지 살펴보았다. 한편 인공지능의 빅데이터 활용에도 공정이용조항이 적용될 수 있다. 공정이용조항은 저작권 제한 사유를 구체적⋅개별적으로 열거한 것이 아니라 일반적⋅포괄적으로 규정하고 있으므로, 인공지능과 같이 빠르게 발전하는 기술에 따른 다양한 저작물 이용 형태까지도 적시에 파악하여 저작권자와 이용자 또는 일반 공중 사이의 이익을 합리적으로 조율할 수 있다는 장점이 있다. 이때에는 위와 같은 법률상의 고려요소와 함께 저작권자의 권리 보호를 위한 합리적인 노력 내지 조치의 존부, 산재된 이득의 집적 효과, 그로 인한 이해당 사자들이 얻는 이익 또는 불이익의 정도 등을 종합적으로 고려하여야 한다. 그러나 공정이용조항은 인공지능의 빅데이터 활용을 가능하게 하는 임시적인 방편에 불과하다. 예측가능성을 제공하여 기술 발전을 도모하기 위해서는 텍스트 및 데이터 마이닝에 관한 입법적 조치가 요구된다. 입법 과정에서는 4차 산업혁명 시대에 있어 인공지능의 적극적 활용을 위한 제도적 장치 마련의 필요성이라는 측면과 함께, 산재된 저작권의 경미한 이용에서 비롯된 재산적 가치의 이전에 대한 보상의 필요성이라는 측면까지도 충분히 고려되어야 할 것이다.

Observation data measured at Ieodo Ocean Research Station (IORS) have been utilized in oceanographic and atmospheric studies since 2003. Sea level data observed at the IORS have not been paid attention as compared with many other variables such as aerosol, radiation, turbulent flux, wind, wave, fog, temperature, and salinity. Total sea level rises at the IORS (5.6 mm yr−1 ) from both satellite and tide-gauge observations were higher than those in the northeast Asian marginal seas (5.4 mm yr−1 ) and the world (4.6 mm yr−1 ) from satellite observation from 2009 to 2018. The rates of thermosteric, halosteric, and steric sea level rises were 2.7-4.8, −0.7-2.6, 2.3-7.4 mm yr−1 from four different calculating methods using observations. The rising rate of the steric sea level was higher than that of the total sea level in the case with additional data quality control. Calculating the non-steric sea level was not found to yield meaningful results, despite the ability to calculate non-steric sea level by simply subtracting the steric sea level from total sea level. This uncertainty did not arise from the data analysis but from a lack of good data, even though tide, temperature, and salinity data were quality controlled two times by Korea Hydrographic and Oceanography Agency. The status of the IORS data suggests that the maintenance management of observation systems, equipment, and data quality control should be improved to facilitate data use from the IORS.

2017년 미국 DOE 주도하에 수행된 국제공동 복합모드운반시험 중 도로트럭운반시험, 연안항해시험, 대서양항해시험에서 측정된 가속도 및 변형률 데이터를 분석하였다. 먼저 각 운반모드 별로 발생한 하중이 전달경로에 따라 하중이 증폭되는지 감쇄되는지가 조사되었다. 그 결과 운반모드 및 하중경로 내 어떤 부분이냐에 따라 발생한 하중이 모의핵연료집합체에 전달되는 특성이 다름을 확인하였다. 그리고 변형률 데이터를 분석하여 육상 및 해상운반동안 발생한 변형률이 사용후핵연료에 건전성에 미치는 영향을 파악하였다. 그 결과 측정된 변형률은 사용후핵연료의 건전성에는 영향을 미치지 못하는 정도로 작은 크기임을 확인하였다. 본 연구에서 분석된 가속도와 피로평가 결과는 예정된 국내 정상운반시험조건에서의 운반시험에 유용한 기초자료로 활용될 것이다.

The purpose of this study was to investigate the current status of chronic diseases according to obesity in the elderly older than age 65 using data from the 7th Korea National Health and Nutrition Examination Survey (2016~2018). The subjects of the survey were 3,245 elderly older than age 65 who participated in the health survey and nutrition survey, 45.8% of the subjects were males and 54.2% of the subjects were female. 37.5% of all the elderly were obese, and the females (42.4%) were more obese than the males (31.8%) (p<0.001). Diabetes, hypertension, and hypertriglyceridemia had a similar prevalence of 24.6%, 63.0%, and 12.7% in males and females, respectively. Hypercholesterolemia was higher in the elderly females (44.2%) than in the elderly males (24.9%) (p<0.001). Through the logistic regression analysis, it was found that the prevalence of chronic diseases was higher in obesity than normal in elderly males and females (p<0.001). The total food intake increased from ‘under weight’ to ‘obesity’ in males (p<0.01) and females (p<0.001). In the case of the elderly males, the higher the degree of obesity, the higher the energy intake (p<0.05), and ‘pre-obesity’ consumed the most energy in elderly females. As a result of this study, the higher the obesity rate of the elderly, the higher the prevalence of chronic diseases.

This study analyzed the health characteristics and comorbidity of adult men aged 40 years by dividing them into a control group of those without any disease related to fine dust and a patient group with one or more diseases related to fine dust in areas with high levels of fine dust pollution using the sixth and seventh Korea National Health and Nutrition Examination Survey (2013-2017). Among the general characteristics, the mean age of the patient group was significantly older than that of the control group (p<0.001), and in terms of the health-related characteristics, the frequency of breakfast consumption in the patient group was higher than in the control group (p<0.043). The body measurements were similar in the patient and control groups. Regarding the prevalence of comorbidity, the patient group showed a higher prevalence of hypertension, dyslipidemia, stroke, myocardial infarction, heart failure, and diabetes than the control group, but the differences were not statistically significant. On the other hand, the prevalence of other cancers (except stomach cancer, liver cancer, colorectal cancer, breast cancer, and cervical cancer) in the patient group was higher than in the control group (p<0.05). In terms of the clinical characteristics, the glycated hemoglobin levels in the patient group were significantly higher than in the control group (p<0.048). Information on nutrition and health in areas with frequent occurrences of fine dust was obtained through the study results, which can be used as basic data for measures of health and diet management against diseases that will increase in relation to fine dust.

Recently, there is growing interest in studying the dietary patterns that affect the risk of circulatory system diseases (CSDs). We investigated the relationship between CSDs and dietary patterns through a follow-up study in Korea (2001-2016). The participants of this study were obtained from the Korean Genome and Epidemiology Study (KoGES). This study was a large community-based cohort study (the Ansan-Ansung areas) conducted to assess the effects of various factors, especially diet, on the onset of chronic diseases among the Korean population aged 40-69 yrs. Baseline data were collected from 2001 to 2002, and follow-up studies were performed every 2 yrs, with over 7 follow-up studies performed (2015-2016). Three dietary patterns were identified using factor analysis: “vegetable and seafood (men)/soup and stew (women)” pattern, “sweet foods and breads-rice cake” pattern, and “multigrain rice and cooked white rice” pattern. None of the dietary patterns were significantly associated with the risk of CSDs in either men or women. Our follow-up study is meaningful as it investigated whether the dietary patterns of individuals according to sex affects the development of CSDs.

The distribution of wild boar (Sus scropa) in the Republic of Korea was forecasted using environmental factors. A species distribution model was applied with the standard normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), solar zenith angle (SUNZ), daytime land surface temperature (dTemp), and nighttime land surface temperature (nTemp). Understanding wild boar distribution is important for controlling African swine fever (ASF) because the disease could be endemic in wild boar or spread from wild boars to domestic pigs. Among the five predictors, the NDVI was the most influencing factor for the wild boar distribution. The relative contributions of the predictors were 67.4 for NDVI, 16.9 for dTemp, 10.5 for SUNZ, 4.4 for EVI, and 0.8 for nTemp. The area size under the receiver-operating curve of the receiver-operating characteristics for the current model was 0.62, but the real wild boar observation data overlapped with the predicted high-density wild boar distribution area. The wild boar distribution density was relatively higher in Gangwon-do, Gyeongsangbuk-do, Gyeongsangnam-do, and Jeollanam-do. Given the ASF epidemics, contact between ASF-infected animals and ASF-susceptible animals in high-density wild boar distribution areas should be prevented by long-range fencing or active surveillance.

After decades of vigorous development, data mining technology has achieved fruitful theoretical and application results. As a highly applicable subject, data mining technology has penetrated into various fields of the national economy, and has aroused great attention from academia and industry. A large amount of chart data is stored in the electronic chart database, and its application is very extensive, providing a valuable decision basis for managers in all walks of life. It is of great significance to establish a complete data management mechanism based on data mining technology. The traditional data analogy extraction technology, because of the data association index and the poor ability of data association, leads to the difference between the extraction data and the target data. Therefore, the application of data mining technology on electronic chart data management is studied. Data mining technology uses rough set to obtain the basic information of electronic chart data management according to similarity function, mining electronic chart data management association rules; through the comprehensive evaluanon data system of electronic chart data management, building rule base, setting up the evaluation index of electronic chart data management, achieving the similarity evaluation of the mining results. Experimental test results: compared with the traditional data analogy extraction technology, the results obtained by data mining technology have higher similarity with the target data and meet the requirements of electronic chart data management acquisition. It can be seen that this technology is more suitable for the application of electronic chart data management

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.