• 천문학회지
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• 제52권1호
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• pp.23-30
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• 2019

The KVN(Korean VLBI Network)-style simultaneous multi-frequency receiving mode is demonstrated to be promising for mm-VLBI observations. Recently, other Very long baseline interferometry (VLBI) facilities all over the globe start to implement compatible optics systems. Simultaneous dual/multi-frequency VLBI observations at mm wavelengths with international baselines are thus possible. In this paper, we present the results from the first successful simultaneous 22/43 GHz dual-frequency observation with KaVA(KVN and VERA array), including images and astrometric results. Our analysis shows that the newly implemented simultaneous receiving system has brought a significant extension of the coherence time of the 43 GHz visibility phases along the international baselines. The astrometric results obtained with KaVA are consistent with those obtained with the independent analysis of the KVN data. Our results thus confirm the good performance of the simultaneous receiving systems for the nonKVN stations. Future simultaneous observations with more global stations bring even higher sensitivity and micro-arcsecond level astrometric measurements of the targets.

• 기록학연구
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• 제27호
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• pp.3-33
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• 2011

한국에서 기록관리법이 시행된 지 10년이 지났지만, 여전히 한국의 국가기록관리는 저발전 상태에 있다. 비록 참여정부에서 '국가 기록관리 혁신'을 추진하여 많은 성과가 있었지만, 특히 기록관이 실질적으로 기능하고 있는 공공기관의 사례를 찾기는 매우 어려운 실정이다. 현재의 기록관 구조는 구제도적 요소가 강하게 잔존하고 있는 불안정한 체제이기 때문이다. 정부 수립 이후 50여 년 동안 공공기관에서 기록관리 업무는 문서과 역할을 담당했던 총무과가 담당하였고, 그것은 주로 처리과에서 생산된 일부 기록에 대한 인수와 서고관리에 한정되었다. 2007년 개정 기록관리법에서 자료관을 기록관으로 그 명칭을 변경하고, '기획관리 부서 또는 총무부서'에 기록관을 설치하도록 규정했으나, 대부분의 기관이 여전히 총무부서 내에 문서과와 기록관을 편제하여 종전과 같이 형식적으로 운영하고 있다. 기록관리법이 시행된 지 10년이 되었지만, '문서과(Records Office)-기록관(Records Center)-보존기록관(Archives)' 체제로 이어지는 전문화된 기록관리 체계는 형성되지 못하고 있는 실정이다. 이와 같은 원인은 어디에서 비롯되는 것일까? 본고는 이러한 문제의 근원을 기록관을 둘러싼 환경적 요인 즉 역사적 배경을 비롯해서 기록관 구조, 기록 전문직, 기록관리 방법론 등 기록관 체제의 내적 구조에서 그 원인을 찾고자 했다. 아울러 기록관 체제의 정상적인 발전을 위해서는 기록관 체제를 문서과와 기록관으로 명확하게 분리하여 기록관의 독립성을 보장하고, 기록관리 프로세스를 비롯한 방법론의 전문화가 필요함을 지적하였다. 아울러 외적으로는 기록공동체의 연대와 협력을 바탕으로 '최선의 기록관리 실무'를 축적하여 기록관의 기록관리 업무를 표준화하는 것을 주요한 과제로 설정하였다.

• 지적과 국토정보
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• 제49권1호
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• pp.123-144
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• 2019

본 연구의 목적은 최근 감소하고 있는 우리나라 인구 증감 현상에 대해 지역 및 주택 시장 특성을 통해 인구 증감 요인을 파악하는 데 있다. 전국 85개시의 최근 5년간 지역별 인구 증가율 평균을 종속 변수로 하고 최근 5년 간 지역 및 주택 시장 특성 요인 변수들의 평균을 독립변수로 하는 다중회귀를 분석 방법으로 활용하였다. 분석결과, 최근 5년 간 지역별 인구 증가율에 유의미한 영향을 미친 지역 및 주택 시장 변수는 출산율, 고용률, 생산 가능 인구 증가율, 아파트 비율, 분양권 전매 비율, 아파트 거래 회전 증가율, 천인당 사업체 수 등이었으며 최근 5년 간 지역별 인구가 증가한 지역으로는 서울과 광역시를 제외한 수도권 일부와 비수도권 지방 중 공공 기관 이전(혁신도시), 택지개발 등이 있는 지역들이었다. 따라서 분석 결과를 종합할 때 지역의 인구를 증가시키기 위해서는 안정된 일자리와 그와 연계된 적절한 주택 공급이 전제 되어야 함을 의미한다. 본 연구의 이러한 연구 결과는 인구감소를 겪고 있는 지방 중소도시 등 수도권 이외 지역 등을 위한 정부 차원에서 지역 균형발전을 위한 정책적 시사점을 제시하였다는 점에 연구의 의의가 있다고 할 수 있다.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.150-158
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• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• 한국인터넷방송통신학회논문지
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• 제23권1호
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• pp.83-92
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• 2023

이 연구의 목적은 일반고등학교를 대상으로 빅데이터 기반의 인공지능을 활용한 창의교육 프로그램을 개발하고, 그 효과성을 알아보는 것이다. 연구의 목적을 달성하기 위해 일반계 고등학교 1학년 학생을 대상으로 빅데이터 기반 인공지능 교육프로그램을 개발하였고, 학교 현장 수업과 전문가를 통한 타당화 과정을 실시하였다. 고등학생들의 창의적 문제해결력 및 수업 만족도를 측정하기 위해 프로그램 적용 전·후에 창의적 문제해결력 검사를 실시하였고, 프로그램 후에는 수업 만족도 검사를 적용 및 분석하였다. 이 연구의 결과는 다음과 같다. 첫째, 빅데이터 기반 인공지능 교육프로그램이 '실행', '여학생과 남학생의 차이'를 제외한 '문제발견 및 분석', '아이디어 생성', '실행계획', '설득과 소통', '혁신성향'의 독립표본 t 검정에서 고등학교 1학년 학생의 창의적 문제해결력 향상에 효과가 있는 것을 확인하였다. 둘째, 수업 후에 실시한 수업 만족도 검사에서 '만족도', '흥미도', '참여도', '지속성'의 평균은 3.56 ~ 3.92이며 전체 평균은 3.78로 나타났다. 따라서 이 연구에서 개발한 빅데이터 기반 인공지능 교육프로그램의 수업 효과가 있는 것을 확인하였다.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.39-48
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• 2022

The main purpose of the work is to analyze modern innovative educational practices in the field of culture and art and their effectiveness in the context of the spread of digitalization trends. The study used general scientific theoretical methods of analysis, synthesis, analogy, comparative, induction, deduction, reductionism, and a number of others, allowing you to fully understand the pattern of modern modernization processes in a long historical development and demonstrate how the rejection of the negativity of progress allows talented artists to realize their own potential. The study established the advantages and disadvantages of involving innovative technologies in the educational process on the example of European experience and outlined possible ways of implementing digitalization processes in Ukrainian institutions of higher education, formulated the main difficulties encountered by teachers and students in the use of technological innovation in the pandemic. The rapid development of digital technologies has had a great impact on the sphere of culture and art, both visual, scenic, and musical in all processes: creation, reproduction, perception, learning, etc. In the field of art education, there is a synthesis of creative practices with digital technologies. In terms of music education, these processes at the present stage are provided with digital tools of specially developed software (music programs for composition and typing of musical text, recording, and correction of sound, for quality listening to the whole work or its fragments) for training programs used in institutional education and non-institutional learning as a means of independent mastering of the theory and practice of music-making, as well as other programs and technical tools without which contemporary art cannot be imagined. In modern stage education, the involvement of video technologies, means of remote communication, allowing realtime adjustment of the educational process, is actualized. In the sphere of fine arts, there is a transformation of communicative forms of interaction between the teacher and students, which in the conditions of the pandemic are of two-way communication with the help of information and communication technologies. At this stage, there is an intensification of transformation processes in the educational industry in the areas of culture and art.

• 벤처창업연구
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• 제16권6호
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• pp.157-175
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• 2021

본 연구는 기술보증기금이 2017년부터 2019년까지 기술평가를 통하여 보증 지원한 기술 중소기업 중 3,214개 기업을 대상으로 4차 산업혁명 기업과 일반 중소기업으로 구분한 후 경영 특성이 고성장 기업 결정에 미치는 영향을 실증 분석하였다. 고성장 기업 판단은 OECD(2007)의 정의를 적용하여 최근 2년간 매출액 증가율이 연간 평균 20% 이상인 기업이다. 표본 대상의 두집단이 비정규분포를 따르고 있어 Mann-Whitney U test 비모수 검증으로 평균치 차이 분석을 하였다. 또한 정규성 가정이 덜 엄격한 이변량 로지스틱 회귀분석을 실시하였다. 독립변수는 대표자 역량, 인적자본 역량, 기술혁신 역량, 기본 특성, 지역더미, 기술수준 더미이다. 이에 대응하는 하위변수는 대표자 학력, 대표자 동업종 경험 수준, 상시 종업원, 연구 인력, 지식 재산권 수, 연구개발 투자금액, 기업 업력, 총자산, 지역_수도권, 지역_중부권, 기술수준_첨단기술, 기술수준_중기술이다. 분석결과, 4차 산업혁명 기업은 대표자 동업종 경험수준, 상시종업원, 기업업력, 총자산, 기술수준_첨단기술의 연구가설이 지지되었다. 일반 중소기업은 대표자 동업종 경험수준, 연구인력, 총자산, 지역_수도권의 연구가설이 지지되었다.

• 대한간호학회지
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• 제53권4호
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• pp.468-479
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• 2023

Purpose: This study aimed to evaluate the use of the respiratory rate oxygenation (ROX) index, ROX-heart rate (ROX-HR) index, and saturation of percutaneous oxygen/fraction of inspired oxygen ratio (SF ratio) to predict weaning from high-flow nasal cannula (HFNC) in patients with respiratory distress in a pediatric intensive care unit. Methods: A total of 107 children admitted to the pediatric intensive care unit were enrolled in the study between January 1, 2017, and December 31, 2021. Data on clinical and personal information, ROX index, ROX-HR index, and SF ratio were collected from nursing records. The data were analyzed using an independent t-test, χ² test, Mann-Whitney U test, and area under the curve (AUC). Results: Seventy-five (70.1%) patients were successfully weaned from HFNC, while 32 (29.9%) failed. Considering specificity and sensitivity, the optimal cut off points for predicting treatment success and failure of HFNC oxygen therapy were 6.88 and 10.16 (ROX index), 5.23 and 8.61 (ROX-HR index), and 198.75 and 353.15 (SF ratio), respectively. The measurement of time showed that the most significant AUC was 1 hour before HFNC interruption. Conclusion: The ROX index, ROX-HR index, and SF ratio appear to be promising tools for the early prediction of treatment success or failure in patients initiated on HFNC for acute hypoxemic respiratory failure. Nurses caring for critically ill pediatric patients should closely observe and periodically check their breathing patterns. It is important to continuously monitor three indexes to ensure that ventilation assistance therapy is started at the right time.

• 여성건강간호학회지
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• 제29권2호
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• pp.137-145
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• 2023

Purpose: This non-randomized study was performed to evaluate the effects of music therapy on labor pain, the childbirth experience, and self-esteem in women during vaginal delivery. Methods: In total, 136 primiparous women over 37 weeks of gestation receiving epidural analgesia during vaginal delivery were recruited via convenience sampling. To minimize diffusion effects, data from the control group (n=71) were collected first (April 2020 to March 2021), followed by data from the music group (n=65; April 2021 to May 2022). Participants in the music group listened to classical music during labor, while the control group was offered usual care (no music). Labor pain was measured using a numeric rating scale (NRS), and self-esteem and childbirth experience were collected using self-report questionnaires. Data were analyzed using the independent t-test, chi-square test and Cronbach's α coefficients. Results: The overall pain level (NRS) at baseline was 0 in both groups. Mothers in the music therapy group had lower levels of latent pain (t=1.95, p=.005), active pain (t=3.69, p<.001) and transition-phase pain (t=7.07, p<.001) than the control group. A significant difference was observed between the two groups, and the music therapy group expressed more positive perceptions of the childbirth experience (t=-1.36, p=.018). For self-esteem, the experimental group's score was slightly higher, but without a statistically significant difference from the control group. Conclusion: Using music therapy during labor decreased labor pain and improved the childbirth experience. Music therapy can be clinically recommended as a non-pharmacological, safe, and easy method for nursing care in labor.

• Korean Journal of Radiology
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• 제23권12호
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• pp.1269-1280
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• 2022

Objective: This study aimed to evaluate the usefulness of quantitative indices obtained from deep learning analysis of gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and their longitudinal changes in predicting decompensation and death in patients with advanced chronic liver disease (ACLD). Materials and Methods: We included patients who underwent baseline and 1-year follow-up MRI from a prospective cohort that underwent gadoxetic acid-enhanced MRI for hepatocellular carcinoma surveillance between November 2011 and August 2012 at a tertiary medical center. Baseline liver condition was categorized as non-ACLD, compensated ACLD, and decompensated ACLD. The liver-to-spleen signal intensity ratio (LS-SIR) and liver-to-spleen volume ratio (LS-VR) were automatically measured on the HBP images using a deep learning algorithm, and their percentage changes at the 1-year follow-up (ΔLS-SIR and ΔLS-VR) were calculated. The associations of the MRI indices with hepatic decompensation and a composite endpoint of liver-related death or transplantation were evaluated using a competing risk analysis with multivariable Fine and Gray regression models, including baseline parameters alone and both baseline and follow-up parameters. Results: Our study included 280 patients (153 male; mean age ± standard deviation, 57 ± 7.95 years) with non-ACLD, compensated ACLD, and decompensated ACLD in 32, 186, and 62 patients, respectively. Patients were followed for 11-117 months (median, 104 months). In patients with compensated ACLD, baseline LS-SIR (sub-distribution hazard ratio [sHR], 0.81; p = 0.034) and LS-VR (sHR, 0.71; p = 0.01) were independently associated with hepatic decompensation. The ΔLS-VR (sHR, 0.54; p = 0.002) was predictive of hepatic decompensation after adjusting for baseline variables. ΔLS-VR was an independent predictor of liver-related death or transplantation in patients with compensated ACLD (sHR, 0.46; p = 0.026) and decompensated ACLD (sHR, 0.61; p = 0.023). Conclusion: MRI indices automatically derived from the deep learning analysis of gadoxetic acid-enhanced HBP MRI can be used as prognostic markers in patients with ACLD.