• 대한산업공학회지
• /
• 제30권1호
• /
• pp.58-64
• /
• 2004

In order to determine the level of safety on highway driving, the relationship between the psychophysiological signal and driving condition was investigated. In particular, a Demand-Effort model was conceptualized and used in this study to diagnose the suitability of driving by reading the patterns of psychophysiological signals. To run the model, threshold values were determined to categorize the high, moderate and low level of effort. To examine the sensitivity of the model, a cross-validation process was performed by collecting additional data. Further investigation need to be conducted to improve the sensitivity of the model for practical application.

• Korean Journal of Radiology
• /
• 제23권12호
• /
• pp.1260-1268
• /
• 2022

Objective: To propose standardized MRI-proton density fat fraction (PDFF) cutoff values for diagnosing hepatic steatosis, evaluated using contemporary PDFF measuring methods in a large population of healthy adults, using histologic fat fraction (HFF) as the reference standard. Materials and Methods: A retrospective search of electronic medical records between 2015 and 2018 identified 1063 adult donor candidates for liver transplantation who had undergone liver MRI and liver biopsy within a 7-day interval. Patients with a history of liver disease or significant alcohol consumption were excluded. Chemical shift imaging-based MRI (CS-MRI) PDFF and high-speed T2-corrected multi-echo MR spectroscopy (HISTO-MRS) PDFF data were obtained. By temporal splitting, the total population was divided into development and validation sets. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance of the MRI-PDFF method. Two cutoff values with sensitivity > 90% and specificity > 90% were selected to rule-out and rule-in, respectively, hepatic steatosis with reference to HFF ≥ 5% in the development set. The diagnostic performance was assessed using the validation set. Results: Of 921 final participants (624 male; mean age ± standard deviation, 31.5 ± 9.0 years), the development and validation sets comprised 497 and 424 patients, respectively. In the development set, the areas under the ROC curve for diagnosing hepatic steatosis were 0.920 for CS-MRI-PDFF and 0.915 for HISTO-MRS-PDFF. For ruling-out hepatic steatosis, the CS-MRI-PDFF cutoff was 2.3% (sensitivity, 92.4%; specificity, 63.0%) and the HISTO-MRI-PDFF cutoff was 2.6% (sensitivity, 88.8%; specificity, 70.1%). For ruling-in hepatic steatosis, the CS-MRI-PDFF cutoff was 3.5% (sensitivity, 73.5%; specificity, 88.6%) and the HISTO-MRI-PDFF cutoff was 4.0% (sensitivity, 74.7%; specificity, 90.6%). Conclusion: In a large population of healthy adults, our study suggests diagnostic thresholds for ruling-out and ruling-in hepatic steatosis defined as HFF ≥ 5% by contemporary PDFF measurement methods.

• Tuberculosis and Respiratory Diseases
• /
• 제83권2호
• /
• pp.122-131
• /
• 2020

Hypersensitivity Pneumonitis (HP) one of the most common interstitial lung diseases (ILDs) is characterized by exposure to an inhaled inciting antigen that leads to a host immunologic reaction determining interstitial inflammation and architectural distortion. The underlying pathogenetic mechanisms are unclear. The absence of international shared diagnostic guidelines and the lack of a "gold-standard" test for HP combined with the presence of several clinical and radiologic overlapping features makes it particularly challenging to differentiate HP from other ILDs, also in expert contests. Radiology is playing a more crucial role in this process; recently the headcheese sign was recognized as a more specific for chronic-HP than the extensive mosaic attenuation. Several classification proposals and diagnostic models have been advanced by different groups, with no prospective validation. Therapeutic options for HP have been limited to antigen avoidance and immunosuppressant drugs over the last decades. Several questions about this condition remain unanswered and there is a need for more studies.

• Safety and Health at Work
• /
• 제13권4호
• /
• pp.408-414
• /
• 2022

Background: This study aimed to determine and define the elements of an Fatigue Risk Management System (FRMS) diagnostic tool to assist an organization in systematically assessing its level of implementation of an FRMS. Methods: A modified Delphi process was used involving 16 participants with expertise in sleep science, chronobiology, and fatigue risk management within occupational settings. The study was undertaken in two stages 1) review of elements and definitions; 2) review of statements for each element. Each stage involved an iterative process, and a consensus rule of ≥ 60% was applied to arrive at a final list of elements, definitions, and statements. Results: Stage 1: a review of elements (n = 12) and definitions resulted in a final list of 14 elements and definitions with a consensus of ≥ 60% achieved after 2 Delphi rounds. Stage 2: a review of statements (n = 131) resulted in a final list of 119 statements with a consensus of ≥ 60% achieved after 2 Delphi rounds. Conclusion: The final FRMS diagnostic tool will enable an organization to systematically assess the level of implementation of their current FRMS and identify gaps and opportunities to reduce risk.

• 한국분무공학회지
• /
• 제5권4호
• /
• pp.12-32
• /
• 2000

The recent trends in numerical simulation of various spray phenomena are reviewed in this article. Major subtopics are atomization/breakup, collision/coalescence, wall collision, interfacial transfer, droplet dispersion, two-phase injection and spray combustion. Each submodel has been under continuous refinement and validation against more extensive data base by advanced laser diagnostic techniques. Most uncertainty in current spray simulations come from these physical submodels, not from excessive computational constraints.

• 대한기계학회논문집A
• /
• 제39권1호
• /
• pp.37-43
• /
• 2015

압전소자(Piezoelectric transducer, PZT)는 구조물의 안정성 평가를 목적으로 하는 구조 건전성 모니터링 기법(Structural Health Monitoring, SHM)의 센서(sensor) 및 구동기(actuator)로 많이 활용되고 있다. 사용되는 센서 및 구동기의 성능을 사전에 파악하고, 잔존수명 및 결함을 탐지하는 센서 자가 진단법은 안정적인 SHM의 결과를 얻기 위해 매우 중요한 절차이다. 본 연구에서는 Admittance 값을 기반으로 한 센서 자가 진단절차를 통하여 압전체 센서의 결함을 탐지하였으며, 센서 진단과정에 영향을 줄 수 있는 접합층 및 온도 등의 영향인자에 대해 실험적 분석을 실시하였다. 분석 결과 Admittance와 온도 및 접착제의 상관관계를 파악할 수 있었으며, admittance를 기반으로 한 센서 자가 진단 절차를 통해 센서의 접착상태와 접착제의 성능평가가 가능함을 검증하였다.

• 정보교육학회논문지
• /
• 제21권6호
• /
• pp.675-690
• /
• 2017

4차 산업혁명 시대를 맞이하여 증거기반의 교육정책을 위해, 전국단위의 진단평가 데이터를 수집하기 위한 시스템을 구축 활용하고 있다. 본 연구는 이러한 전국 단위 초 중생이 활용하고 있는 진단평가관리시스템의 사용성 개선을 도울 수 있는 휴리스틱스 개발을 목적으로 하였다. 이를 위해 Nielsen의 기본 휴리스틱스를 비롯하여 교육적 목적에 종속적으로 개발된 휴리스틱스에 대한 선행연구를 기반으로 유사시스템인 진단 보정학습시스템의 사용성 문제를 분석함으로써 휴리스틱스 초안을 개발하였다. 이는 델파이 방법을 통해 15명의 전문가에 의해 2회의 타당화 과정을 수행함으로써 수정 보완되었고 최종안이 도출되었다. 본 연구는 교육 맥락에서 사용성 평가도구를 제공함으로써 전국단위의 관계자(교사 등)와 학생들이 활용하는 시스템의 사용성 개선을 위한 기반을 마련하였다는데 의의가 있다.

• International Journal of Advanced Culture Technology
• /
• 제8권4호
• /
• pp.64-76
• /
• 2020

Purpose: Several screening tools have been developed to identify sarcopenia in rural community-dwelling older adults. We aimed to compare the diagnostic accuracy of two such tools, namely the SARC-F and SARC-CalF assessments. Methods: This cross-sectional study on 388 community-dwelling older adults comprised 254 women and 134 men with a mean age of 77.8 ± 6.26 year in Korea. We assessed muscle mass, muscle strength, and physical performance using a bioimpedance analysis device, hydraulic hand dynamometer, and 4 m gait speed test, respectively. Three widely-used diagnostic criteria [the Asian Working Group for Sarcopenia (AWGS), European Working Group on Sarcopenia in Older People, and the International Working Group on Sarcopenia] were applied. Sensitivity and specificity analyses were performed on the SARC-CalF and SARC-F tests. We used receiver-operating characteristic curves and the area under the curves (AUCs) to compare the diagnostic accuracy of the assessments with regard to sarcopenia. Results: An analysis using four sets of diagnostic criteria showed that the prevalence of sarcopenia was 27.6% to 41.0%. Using the AWGS 2019 criteria as a reference standard, the SARC-CalF had a sensitivity of 83.02% and a specificity of 53.71% in the entire study population, whereas the SARC-F had a sensitivity of 79.87% and a specificity of 41.92%. The AUCs for the SARC-CalF and SARC-F tests were 0.725 (95% confidence interval 0.678-0.769) and 0.645 (95% confidence interval 0.595-0.693), respectively (p<001). In the analyses using the other three diagnostic criteria, similarity was also confirmed. Conclusion: SARC-CalF showed better sensitivity than did SARC-F when diagnosing sarcopenia in rural community-dwelling older adults. Further studies are needed to verify this finding in different populations.

• Korean Journal of Radiology
• /
• 제21권7호
• /
• pp.869-879
• /
• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.

• Animal Bioscience
• /
• 제37권3호
• /
• pp.522-535
• /
• 2024

Objective: Transition period is considered from 3 weeks prepartum to 3 weeks postpartum, characterized with dramatic events (endocrine, metabolic, and physiological) leading to occurrence of production diseases (negative energy balance/ketosis, milk fever etc). The objectives of our study were to analyze the periodic concentration of serum beta-hydroxy butyric acid (BHBA), glucose and oxidative markers along with identification, and validation of the putative markers of negative energy balance in buffaloes using in-silico and quantitative real time-polymerase chain reaction (qRT-PCR) assay. Methods: Out of 20 potential markers of ketosis identified by in-silico analysis, two were selected and analyzed by qRT-PCR technique (upregulated; acetyl serotonin o-methyl transferase like and down regulated; guanylate cyclase activator 1B). Additional two sets of genes (carnitine palmotyl transferase A; upregulated and Insulin growth factor; downregulated) that have a role of hepatic fatty acid oxidation to maintain energy demands via gluconeogenesis were also validated. Extracted cDNA (complementary deoxyribonucleic acid) from the blood of the buffaloes were used for validation of selected genes via qRTPCR. Concentrations of BHBA, glucose and oxidative stress markers were identified with their respective optimized protocols. Results: The analysis of qRT-PCR gave similar trends as shown by in-silico analysis throughout the transition period. Significant changes (p<0.05) in the levels of BHBA, glucose and oxidative stress markers throughout this period were observed. This study provides validation from in-silico and qRT-PCR assays for potential markers to be used for earliest diagnosis of negative energy balance in buffaloes. Conclusion: Apart from conventional diagnostic methods, this study improves the understanding of putative biomarkers at the molecular level which helps to unfold their role in normal immune function, fat synthesis/metabolism and oxidative stress pathways. Therefore, provides an opportunity to discover more accurate and sensitive diagnostic aids.