• The Korean Journal of Applied Statistics
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• v.28 no.4
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• pp.763-779
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• 2015

This study estimate the adequate replacement rate of retirement income by income brackets and suggests roles of pension and non-pension income sources to achieve it for each income bracket. Priori research focused on elderly poverty; however, there has been little discussion about an adequate income level for retirement. We calculate an adequate income replacement rate separately for the poor, middle, and high income group as well as the average level of replacement rate for all groups. We also investigate the gap between the adequate income replacement rates and realized rates, and propose roles for each income source to curtail the gap. It is essential to recognize that the adequate income for retirement is unable to be met only by an annuity. To emove the gap, it is vital to utilize non-pension income although annuity is a primary source for retirement. Especially, the public and private pension plays a role to overcome poverty and live affluent in retirement, respectively.

• Journal of Biomedical Engineering Research
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• v.38 no.3
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• pp.111-115
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• 2017

Blood pressure is one of the important vital signs for monitoring the medical condition of a patient. Automated NIBP(non-invasive blood pressure) monitoring devices calculate systolic and diastolic blood pressures from the oscillation in cuff pressure caused by a pulsation of an artery. To validate the NIBP devices, we developed a simulator to supply the oscillometric waveforms obtained from human subjects. The simulator provided pressure pulses to device-under-test and device readings were compared to the auscultatory references. Fully automated simulation system including OCR(optical character recognition) were developed and used for NIBP monitoring devices. The validation results using the simulator agreed well with previous clinical validation. More validation studies using the standardized oscillometric waveforms would be required for the replacement of clinical trials to validate a new automated NIBP monitoring device.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.21 no.4
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• pp.423-432
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• 2014

Purpose: This study was done to evaluate effectiveness of deep breathing exercise as a postoperative intervention to prevent pulmonary complications. Methods: A search of databases from 1990 to 2012 was done including MEDLINE, EMBASE, CINAHL, Cochrane Library and eight Korean databases. Ten studies met eligibility criteria. Researchers trained in systematic review, independently assessed the methodological quality of selected studies using the Cochrane's risk of bias tool. Data were analyzed using RevMan 5.2 program. Results: Among ten RCTs in four studies, deep breathing exercise was compared with an instrument using interventions such as incentive spirometry, in the other four studies deep breathing exercise was compared with non-intervention, and in last two studies bundles of interventions including coughing and early ambulation were assessed. A significant difference was found between deep breathing exercise group and non-intervention group. The odds ratio (OR) of occurrence of pulmonary complications for deep breathing exercise versus non-intervention was 0.30. However, there was no significant difference between deep breathing exercise group and incentive spirometry group (OR=1.22). Conclusion: Deep breathing exercise is vital to improving cost-effectiveness and efficiency of patient care in preventing postoperative pulmonary complications. For evidence-based nursing, standardized guidelines for deep breathing in postoperative care should be further studied.

• Radiation Oncology Journal
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• v.31 no.1
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• pp.34-40
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• 2013

Purpose: To evaluate the predictive factors of radiation pneumonitis (RP) and associated changes in pulmonary function after definitive concurrent chemoradiotherapy (CCRT) in patients with non-small cell lung cancer (NSCLC). Materials and Methods: Medical records of 60 patients with NSCLC who received definitive CCRT were retrospectively reviewed. Dose volumetric (DV) parameters, clinical factors, and pulmonary function test (PFT) data were analyzed. RP was graded according to the CTCAE ver. 4.0. Percentage of lung volume that received a dose of threshold (Vdose) and mean lung dose (MLD) were analyzed for potential DV predictors. PFT changes were calculated as the difference between pre-RT and post-RT values at 3, 6, and 12 months after RT. Results: Twenty-two patients (37%) developed grade ${\geq}2$ RP. Among clinical factors, tumor location in lower lobe was associated with RP. Among the DV parameters, only MLD >15 Gy was associated with grade ${\geq}2$ RP. There were statistically significant decreases in PFT at all points compared with pre-RT values in grade ${\geq}2$ RP group. MLD was associated with forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1) changes at 6 and 12 months. V10 was associated with FVC changes at 12 months. V20 and V30 were associated with FEV1 changes at 6 months and FVC changes at 12 months. Conclusion: After definitive CCRT in patients with NSCLC, MLD >15 Gy and lower lobe tumor location were predictors of grade ${\geq}2$ RP. Pulmonary functions were decreased after CCRT and the magnitude of changes was associated with DV parameters.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2008.05a
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• pp.1-46
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• 2008

The ability to control filler performance and fines retention is vital in the development of both filled and non filled grades, respectively. This is very important when achieving the desired sheet structure necessary to maximize machine performance and end user demands. A narrow balance exists in attaining the desired retention and formation particularly in systems with heavier ash loads and producing paper and paper board on higher speed high shear equipment. A new generation of both cationic and anionic micropolymer technologies has been developed. These water based chemistries are volatile organic compound (VOC) and alkyphenol ethoxylate (APE) free. When these novel micropolymers are applied with linear poly-acrylamide or in conjunction with inorganic microparticle technologies (such as silica or swellable minerals), substantial increases in drainage, fibre retention and ash retention are observed. These improvements have been observed not only in high filled wood and non wood containing grades such as fine paper and super calendared sheets (SCA), but also in low filled newsprint grades. Of particular note is the drainage improvement seen with the application of the cationic micropolymers in unbleached packaging grades with poly-acrylamide.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.253-262
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• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1044-1051
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• 2019

Objective: Recent studies have implied that gene expression has high tissue-specificity, and therefore it is essential to investigate gene expression in a variety of tissues when performing the transcriptomic analysis. In addition, the gradual increase of long non-coding RNA (lncRNA) annotation database has increased the importance and proportion of mapped reads accordingly. Methods: We employed simple statistical models to detect the sexually biased/dimorphic genes and their conjugate lncRNAs in 40 RNA-seq samples across two factors: sex and tissue. We employed two quantification pipeline: mRNA annotation only and mRNA+lncRNA annotation. Results: As a result, the tissue-specific sexually dimorphic genes are affected by the addition of lncRNA annotation at a non-negligible level. In addition, many lncRNAs are expressed in a more tissue-specific fashion and with greater variation between tissues compared to protein-coding genes. Due to the genic region lncRNAs, the differentially expressed gene list changes, which results in certain sexually biased genes to become ambiguous across the tissues. Conclusion: In a past study, it has been reported that tissue-specific patterns can be seen throughout the differentially expressed genes between sexes in cattle. Using the same dataset, this study used a more recent reference, and the addition of conjugate lncRNA information, which revealed alterations of differentially expressed gene lists that result in an apparent distinction in the downstream analysis and interpretation. We firmly believe such misquantification of genic lncRNAs can be vital in both future and past studies.

• Journal of the Korean Dietetic Association
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• v.27 no.1
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• pp.35-44
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• 2021

This study analyzed the intake of calories and nutrients based on the consumption of black beans. The survey was conducted on 124 college students (male: 42, female: 82), of whom 63.7% (79 students) were consumers of black beans. The calorie intake of the black bean intake group (1599.81±555.48 kcal) was significantly higher than that of the non-black bean intake group (1259.99±507.58 kcal) (P<0.01). The black bean intake group also showed a significantly higher intake of crude protein (P<0.05), plant protein (P<0.01), animal protein (P<0.05), crude fiber (P<0.001), plant calcium (P<0.001), plant iron (P<0.001), zinc (P<0.01), vitamin B2 (P<0.01), vitamin C (P<0.01), vitamin E (P<0.01) and folic acid (P<0.001) compared to the non-black bean intake group. There was a positive correlation between the frequency of black bean intake and crude fiber (P<0.05), plant calcium (P<0.05), plant iron (P<0.05), and folic acid (P<0.05). Overall, the black bean intake group was more likely to eat black sesame 13.82 times (95% CI=5.37, 35.55), white beans 10.79 times (95% CI=3.53, 33.02), mung beans 7.22 times (95% CI=2.58, 20.23), and brown rice 4.72 times (95% CI=1.88, 11.84), than the non-black bean intake group. In conclusion, we believe that black beans constitute a vital food ingredient that is necessary to provide Korean college students with a well-balanced diet.

• Tuberculosis and Respiratory Diseases
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• v.84 no.2
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• pp.115-124
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• 2021

Background: This study aimed to determine the parameters for worsening oxygenation in non-severe coronavirus disease 2019 (COVID-19) pneumonia. Methods: This retrospective cohort study included cases of confirmed COVID-19 pneumonia in a public hospital in South Korea. The worsening oxygenation group was defined as that with SpO₂ ≤94% or received oxygen or mechanical ventilation (MV) throughout the clinical course versus the non-worsening oxygenation group that did not experience any respiratory event. Parameters were compared, and the extent of viral pneumonia from an initial chest computed tomography (CT) was calculated using artificial intelligence (AI) and measured visually by a radiologist. Results: We included 136 patients, with 32 (23.5%) patients in the worsening oxygenation group; of whom, two needed MV and one died. Initial vital signs and duration of symptoms showed no difference between the two groups; however, univariate logistic regression analysis revealed that a variety of parameters on admission were associated with an increased risk of a desaturation event. A subset of patients was studied to eliminate potential bias, that ferritin ≥280 ㎍/L (p=0.029), lactate dehydrogenase ≥240 U/L (p=0.029), pneumonia volume (p=0.021), and extent (p=0.030) by AI, and visual severity scores (p=0.042) were the predictive parameters for worsening oxygenation in a sex-, age-, and comorbid illness-matched case-control study using propensity score (n=52). Conclusion: Our study suggests that initial CT evaluated by AI or visual severity scoring as well as serum markers of inflammation on admission are significantly associated with worsening oxygenation in this COVID-19 pneumonia cohort.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.