• 한국측량학회지
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• 제26권6호
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• pp.549-559
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• 2008

본 연구에서는 다양한 조건 하에서의 Bernese와 TGO와의 처리결과 비교를 통하여 상용 소프트웨어의 한계와 정밀측위에 대한 응용성을 검증하였다. 이를 위하여 전국규모의 세 가지의 관측데이터와 그 보다 작은 두 가지의 지역 데이터를 선정하여 망을 구성하고 Bernese와 TGO를 사용하여 기선해석 및 망조정을 통해 성과를 산출하여 소프트웨어별, 기선거리 및 망규모별, 관측시간별, 고정점 수별로 비교분석을 실시하였다. 소프트웨어 간 비교에서는 학술연구용 소프트웨어의 정확도가 우수하였다. 비록 GPS 관련 기술이 발달하면서 수신기의 정확도가 향상되었고 이에 병행하여 상용 소프트웨어도 발전을 거듭해왔으나 학술연구용 소프트웨어와의 평균성과차이를 볼 때 크지는 않지만 엄연한 차이가 존재했다. 따라서 가장 정밀한 위치정보가 요구될 때는, 특히 기선벡터가 큰 경우에는 필히 학술연구용 소프트웨어를 사용하여야 할 것이다.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• 제47권6호
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• pp.438-444
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• 2021

Objectives: Loss of the interdental papilla is multi-factorial and creates a multitude of problems. Autogenous connective tissue/biomaterial-based regeneration has been attempted for decades to reconstitute the black space created due to the loss of papilla. The aim of this present study was to regenerate papillary recession defects using an amnion-chorion membrane (ACM) allograft and to evaluate the clinical outcome up to six months postoperatively. Materials and Methods: Twenty patients with 25 Nordland and Tarnow's Class I/II interdental papillary recession defects were treated with ACM and coronal advancement of the gingivo-papillary unit via a semilunar incision on the labial aspect followed by a sulcular incision in the area of interest. A photographic image analysis was carried out using the GNU Image Manipulation software program from the baseline to three and six months postoperatively. The black triangle height (BTH) and the black triangle width (BTW) were calculated using the pixel size and were then converted into millimeters. The mean and standard deviation values were determined at baseline and then again at three and six months postoperatively. The probability values (P<0.05 and P≤0.01) were considered statistically significant and highly significant, respectively. An analysis of variance and post hoc Bonferroni test were carried out to compare the mean values. Results: Our evaluation of the BTH and BTW showed a statistically and highly significant difference from the baseline until both three and six months postoperatively (P=0.01). A post hoc Bonferroni test disclosed a statistically significant variance from the baseline until three and six months postoperatively (P<0.05) and a non-significant difference from three to six months after the procedure (P≥0.05). Conclusion: An ACM allograft in conjunction with a coronally advanced flap could be a suitable minimally invasive alternative for papillary regeneration.

• 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.

• Journal of Radiation Protection and Research
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• 제46권3호
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• pp.83-97
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• 2021

Background: The lifetime risk of lung cancer incidence due to radiation for nonsmokers is overestimated because of the use of the average cancer baseline risk among a mixed population, including smokers. In recent years, the generalized multiplicative (GM)-excess relative risk (ERR) model has been developed in the life span study of atomic bomb survivors to consider the joint effect of radiation and smoking. Based on this background, this paper discusses the issues of radiation risk assessment considering smoking in two parts. Materials and Methods: In Part 1, we proposed a simple method of estimating the baseline risk for nonsmokers using current smoking data. We performed sensitivity analysis on baseline risk estimation to discuss the birth cohort effects. In Part 2, we applied the GM-ERR model for Japanese smokers to calculate lifetime attributable risk (LAR). We also performed a sensitivity analysis using other ERR models (e.g., simple additive (SA)-ERR model). Results and Discussion: In Part 1, the lifetime baseline risk from mixed population including smokers to nonsmokers decreased by 54% (44%-60%) for males and 24% (18%-29%) for females. In Part 2, comparison of LAR between SA- and GM-ERR models showed that if the radiation dose was ≤200 mGy or less, the difference between these ERR models was within the standard deviation of LAR due to the uncertainty of smoking information. Conclusion: The use of mixed population for baseline risk assessment overestimates the risk for lung cancer due to low-dose radiation exposure in Japanese males.

• 전자공학회논문지
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• 제53권3호
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• pp.124-131
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• 2016

분광법을 이용한 많은 응용에서 스펙트럼 데이터의 기준선 보정은 분석 시스템의 성능을 좌우하는 매우 중요한 과정이다. 기준선은 많은 경우에 육안 검사로 매개변수를 선택하여 추정한다. 이 과정은 매우 주관적이고 특히 대량의 데이터인 경우 지루한 작업을 동반하므로 좋은 분석 결과를 보장하기 어렵다. 이러한 이유로 기준선 보정에서 최적의 매개변수를 자동으로 선택하기 위한 객관적인 방법이 필요하다. 이전의 연구에서 PLS(penalized least squares) 방법에 새로운 가중 방식을 도입하여 기준선을 추정하는 arPLS(asymmetrically reweighted PLS) 방법을 제안하였다. 본 연구에서는 arPLS 방법에서 최적의 매개변수를 자동으로 선택하는 방법을 제안한다. 이 방법은 가능한 매개변수의 범위에서 추정한 기준선의 적응도와 평활도를 계산한 다음 정규화한 적응도와 평활도의 합이 최소가 되는 매개변수를 선택한다. 경사 기준선, 곡선 기준선, 이중 곡선 기준선의 모의실험 데이터와 실제 라만 스펙트럼을 이용한 실험에서 제안한 방법이 기준선 보정을 위한 최적 매개변수의 선택에 효과적으로 적용될 수 있음을 확인하였다.

• 전기전자학회논문지
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• 제24권4호
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• pp.1011-1016
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• 2020

We propose a framework called Stacked Gated Recurrent Unit - Infrequent Residual Analysis (SG-IRA) that detects anomalies in time-series data that can be trained on streams of raw sensor data without any pre-labeled dataset. To enable such unsupervised learning, SG-IRA includes an estimation model that uses a stacked Gated Recurrent Unit (GRU) structure and an analysis method that detects anomalies based on the difference between the estimated value and the actual measurement (residual). SG-IRA's residual analysis method dynamically adapts the detection threshold from the population using frequency analysis, unlike the baseline model that relies on a constant threshold. In this paper, SG-IRA is evaluated using the industrial control systems (ICS) datasets. SG-IRA improves the detection performance (F1 score) by 5.9% compared to the baseline model.

• 전기학회논문지P
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• 제60권4호
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• pp.236-240
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• 2011

Currently one of the most importance issues in industrial sector is energy cost and energy efficiency. The manufacturing plants especially have made many efforts to reduce energy cost by implementing maintenances. But in many cases, they are not aware that how much energy could be saved more. If we know the best energy consumption, which signifies energy baseline, we can control the intensity of maintenances. One way to obtain the baseline is using proper statistics from a specific plant, a sector of industry. Energy bandwidth signifies the gap between actual Specific Energy Consumption(SEC) of a certain plant and minimum SEC of the best plant, and estimate energy saving potential(ESP) is a result of bandwidth analysis. We chose a model plant and implemented some maintenance for a year, and then we obtained ESP. Additionally we could determine the decreased amount of carbon emissions from the plant using Carbon Emissions Factor(CEF) by Intergovernmental Panel on Climate Change(IPCC).

• 한국소음진동공학회논문집
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• 제11권5호
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• pp.108-122
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• 2001

As bridge design is advancing toward the performance-based design. it becomes increasingly important to monitor and re-evaluate the long-term structural performance of bridges. Such information is essential in developing performance criteria for design. In this research. sensor systems for long-term structural performance monitoring have been installed on two highway bridges. Pre1iminary vibration measurement and data analysis have been performed on these instrumented bridges. On one bridge, ambient vibration data have been collected. based on which natural frequencies and mode shapes have been extracted using various methods and compared with those obtained by the preliminary finite element analysis. On the other bridge, braking and bumping vibration tests have been carried out using a water truck In addition to ambient vibration tests. Natural frequencies and mode shapes have been derived and the results by the breaking and bumping vibration tests have been compared. For the development of a three dimensional baseline finite element model, the new methodology using a neural network is proposed. The proposed one have been verified and applied to develop the baseline model of the bridge.

• 전기학회논문지
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• 제58권10호
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• pp.1842-1848
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• 2009

This paper summarizes a data modeling for developing the baseline network analysis software of the Korean energy management system (EMS). The study is concentrated on the following aspects. First, the data for operating the each application software are extracted. Some of the EMS network application softwares are selected for basis model. Those are based on the logical functions of each software and are not considered the other softwares. Second, the common data are extracted for equipment model and topological structure of power system in Korea. We propose the application common model(ACM) that can be applied whole EMS network application softwares. The ACM model includes the hierarchy and non-hierarchy power system structure, and is connected each other using the direct and indirect link. Proposed database model is tested using the Korea Electric Power Corporation(KEPCO) system. The real time SCADA data are provided for the test. Through the test, we verified that the proposed database structure can be effectively used to accomplish the Korean EMS system.

• 대한인간공학회지
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• 제31권2호
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.