• 무역학회지
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• 제46권2호
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• pp.19-38
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• 2021

This study aims to analyze the foreign asset leverage effect on Korean oil & gas companies' foreign profits and to maintain the appropriate foreign asset volume for reducing exchange risk. For a long time, large Korean companies, including oil companies, overheld foreign currency liabilities. For this reason, most large companies have been burdened to hedge exchange risk and this excess limit holding deteriorated total profit and reduced foreign currency asset management efficiency. Our paper proceeds in presenting a three-stage analysis considering diversified exchange risk factors through estimation on transformation of foreign transactions a/c including annual trends of foreign asset and industry specifics. We also supplement incomplete the estimation method through a practical hedging case investigation. Our research parts are differentiated on the analyzing four periods considering period-specifics The FER value of the oil firms ranged from -0.3 to +2.3 over the entire period. The results of the FER Value are volatile and irregular; those results do not represent the industry standard comparative index. The Korean oil firms are over the credit limit without accurate prediction and finance high interest rate funds from foreign-owned banks on the basis on a biased relationship. Since the IMF crisis, liabilities of global firms have decreased. Above all, oil firms need to finance a minimum limit without opportunity losses on the demand forecast and prepare for uncertainty in the market. To reduce exchange risk from the over-the-limit position, we must consider factors that affect the corporate exchange risk on the entire business process, including the contract phase.

• 한국ITS학회 논문지
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• 제22권6호
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• pp.230-245
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• 2023

자율주행 기술의 발전과 함께 자율주행차(automated vehicle, AV)의 안전성 평가의 중요성이 증가하고 있다. 이에 따라 효율적인 안정성 평가를 진행하기 위해 AV가 주행 중 직면할 수 있는 상황을 사전에 정의한 평가 시나리오를 활용하고 있다. 그러나 기존에 활용되는 시나리오는 짧은 구간 내에서 한정적인 상황만을 다루고 있다. 따라서, 실제 도로에서 발생하는 연속적인 상황을 평가하지 못한다는 한계가 존재한다. 이에 본 연구에서는 AV의 안전성을 강도 높게 평가하기 위해 단일 시나리오를 다양한 기하구조가 존재하는 도로 전체 구간을 대상으로 연속적인 평가가 가능한 다중 시나리오로 변환하고자 한다. 특히, 시나리오를 연결하는 조건을 정의하고, 변환된 다중 시나리오를 상황, 범위, 실험 시나리오로 발전시키는 구체적인 방법론을 제시하였으며, 시뮬레이션으로 다중 시나리오를 구현하여 검증하였다.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• 대한원격탐사학회지
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• 제40권3호
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• 수산해양기술연구
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• 제60권1호
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• pp.71-79
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• 2024

In compliance with environmental regulations at sea and the introduction of unmanned autonomous ships, electric propulsion ships are garnering significant attention. Induction machines used as propulsion electric motor (PEM) have maintenance advantages, but speed control is very complicated and difficult. One of the most commonly used techniques for speed control is DTC (direct torque control). DTC is simple in the reference frame transformation and the stator flux calculation. Meanwhile, two-level and three-level voltage source inverters (VSI) are predominantly used. The three-level VSI has more flexibility in voltage space vector selection compared to the two-level VSI. In this paper, speed is controlled using the DTC method based on the specifications of the PEM. The speed controller employs a PI controller with anti-windup functionality. In addition, the characteristics of the two-level VSI and three-level VSI are compared under identical conditions. It was confirmed through simulation that proper control of speed and torque has been achieved. In particular, the torque ripple was small and control was possible with a low DC voltage at low speed in the three-level VSI. The study confirmed that the application of DTC, using a three-level VSI, contributes to enhancing the system's response performance.

• 한국의류산업학회지
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• 제26권1호
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• pp.65-77
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• 2024

This study aimed to propose effective ways to integrate CLO into educational settings by conducting a comparative analysis of pattern functions in YUKA and CLO, specifically focusing on skirt prototypes and variations. CLO, being a 3D virtual sample CAD tool, is mainly used in education to facilitate the creation of 3D virtual clothing. In order to explore the applicability of CLO's pattern functions in pattern education, CAD education experts were asked to produce two types of skirt prototypes and two skirt variations. Subsequently, in-depth interviews were conducted. In addition, the skirt pattern creation process was recorded on video and used for comparative analysis of YUKA and CLO pattern functions. The comparison revealed that CLO provides the pattern tools necessary for drafting skirt prototypes. The learning curve for acquiring the skills necessary for drafting and transforming skirt prototypes was found to be relatively shorter for CLO compared to YUKA. In addition, due to CLO's surface-based pattern drawing method, it is difficult to move or copy only specific parts of the outline, and there are some limitations in drawing right angle lines. In the pattern transformation process, CLO's preview function proved to be advantageous, and it was highly rated on user convenience due to the intuitive UI. Thus, CLO shows promise for pattern drafting education and is deemed to have high scalability as it is directly linked to 3D virtual clothing.

• Korean Chemical Engineering Research
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• 제43권4호
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• pp.503-510
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• 2005

본 연구는 졸-겔법을 이용하여 복합 알루미나를 제조하였고, 다양한 첨가제의 첨가에 의한 복합 알루미나의 열적 안정성을 고찰하였다. $1,200^{\circ}C$에서 소성시킨 복합 알루미나의 열적 안정성은 사용된 첨가제에 따라서 $Si{\fallingdotseq}La$ > Ti > $Ba{\fallingdotseq}Ce$ > Y > $Zr{\fallingdotseq}Mg$ 순으로 나타났다. 특히 실리카 첨가시 ${\alpha}$-알루미나로의 상전이 온도를 $150^{\circ}C$이상 높여 $1,200^{\circ}C$에서 소성 후에도 ${\gamma}$-형에서 ${\delta}$-형의 알루미나 상을 유지함을 알 수 있었고, 비표면적이 $3m^2/g$인 ${\alpha}$-알루미나에 비해 $71m^2/g$(비표면적) 범위까지 증가됨을 보였다. 이러한 알루미나 입자의 특성변화는 실리카 첨가 알루미나의 경우 고온으로 소성시 Si-O-Al의 결합의 증가로 인하여 알루미나의 상전이를 지연시키는 결과로 나타나고, 란타늄 첨가 알루미나의 경우 $LaAlO_3$ 구조의 존재로 인해 알루미나의 입자간 소결을 지연시킴을 알 수 있었다. 또한 란타늄 첨가시 $1,000^{\circ}C$ 이하에서 소성시킨 경우 란타늄이 알루미나 표면에 $La_2O_3$ 구조로 존재하나 $1,000^{\circ}C$ 이상에서는 $LaAlO_3$의 perovskite 구조로 존재하고, $1,300^{\circ}C$ 이상에서는 $LaAl_{11}O_{18}$의 magneto-plumbite 구조로 존재함을 XRD와 XPS 분석 결과에 의해 확인할 수 있었다.

• 대한원격탐사학회지
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• 제39권6_1호
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• pp.1211-1224
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• 2023

구름은 광학위성을 이용한 국토 관측 및 재난 대응, 변화 탐지 등 지표의 현상을 관측하는데 있어 많은 어려운 문제를 야기한다. 구름의 존재는 영상 처리 단계 뿐만 아니라 최종적으로는 데이터의 품질에 영향을 미치므로 이를 반드시 식별하고 제거하는 과정이 필요하다. 따라서 본 연구에서는 위성영상 내 구름의 분광패턴에 가장 근접한 화소를 탐색 및 추출해 최적의 임계값을 선정하고 임계값을 바탕으로 구름 산출물을 제작하는 일련의 과정을 자동으로 수행하는 새로운 구름 탐지 기법을 개발하고자 하였다. 구름 탐지 기법은 크게 세 단계로 구성된다. 첫 번째 단계에서는 Digital Number (DN) 단위 영상을 대기상층 반사율 단위로 변환하는 과정을 수행한다. 두 번째 단계에서는 대기상층 반사율 영상을 이용하여 Hue-Value-Saturation (HSV) 변환 및 삼각형 임계 처리, 최대우도 분류 등의 전처리를 적용하고 각 영상별로 초기 구름 마스크 생성을 위한 임계값을 결정한다. 세번째 후처리 단계에서는 생성된 초기 구름 마스크에 포함된 노이즈를 제거하고 구름 경계 및 내부를 개선한다. 구름 탐지를 위한 실험 자료로 구름의 공간적, 계절적 분포의 다양성을 보여주는 4~11월 시기에 한반도 지역에서 촬영된 국토위성 L2G 영상을 사용하였다. 제안 방법의 성능을 검증하기 위해 단일 임계화 방법으로 생성된 결과를 비교하였다. 실험 결과, 제안 방법은 기존 방법과 비교하여 전처리 과정을 통해 각 영상의 방사학적 특성을 고려할 수 있어 보다 정확하게 구름을 검출할 수 있었다. 또한, 구름 개체를 제외한 나머지 밝은 물체(판넬식 지붕, 콘크리트 도로, 모래 등)의 영향을 최소화하는 결과를 보여주었다. 제안 방법은 기존 방법 대비 F1-score 기준으로 30% 이상의 개선된 결과를 보여주었으나 눈이 포함된 특정 영상에서 한계점이 있었다.

• 한국전산구조공학회논문집
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• 제26권2호
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• pp.165-171
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• 2013

동하중을 고려하는 구조해석은 전산자원과 시간측면에서 상당한 어려움이 따르기 때문에 외력을 이상적인 정하중으로 가정하는 것이 일반적이다. 그러나 정하중 조건으로 해석된 결과는 구조물의 안전설계 측면에서 충분한 신뢰를 주기 어렵다. 최근에는, 동하중의 영향을 받는 구조물의 효과적인 구조해석을 위해 동하중을 등가정하중으로 변환하는 기법이 제안되어 왔다. 이 기법은 최적화를 통해 구속조건을 만족하는 최소의 등가정하중을 구하는데, 구속조건은 임계시간의 변위를 사용하고, 등가정하중 분포 자유도는 경험적으로 선정하여 왔다. 그러나 안전설계 관점에서는 응력 구속조건을 적용하는 것이 타당하며, 경험적 자유도 선정은 몇 개의 자유도에 과도한 하중이 부과되거나 구조물의 거동에 영향력이 없는 자유도들이 선정될 가능성이 있다. 본 연구에서는 등가응력 구속조건을 고려하는 등가정하중 최적화 방법을 제안하고, 축소시스템 개념을 도입한 주자유도, 구속조건 요소 자유도, 외부하중 자유도로 구성되는 등가정하중 분포 자유도의 구성방법을 제안한다. 수치예제에서는 제안된 방법으로 구해진 등가정하중을 사용하여 등가응력을 구하고 동하중 해석 결과와 비교함으로써 제안된 방법을 통한 구조해석 방법이 구조안전성 측면에서 타당함을 보인다.

• IMMUNE NETWORK
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• 제1권2호
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• pp.151-161
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• 2001

Background: Inactivation in p53 tumor suppressor gene through a point mutation and deletion is one of the most frequent genetic changes found in human cancer, with 50% of an incidence. This high rate of mutation mostly suggests that the gene plays a central role in the development of cancer and the mutations detected so far were found in exons 5 to 8. Mutation of p53 locus produced accumulation of abnormal p53 protein, and negative regulation of cell proliferation and transcriptional activation as a suppressor of transformation were lost. In addition, inhibition of its normal cellular function of wild-type by mutant is an important step in tumorigenesis. Method: 4 colon cancer cell lines (SNU C1, C2A, C4, C5) were examined for mutation in exons 5 to 8 of the p53 tumor suppressor gene by PCR-SSCP analysis and expression pattern by western blotting and immunoprecipitation. p53-mediated transactivation ability were examined by CAT assay and base substitution of p53 in SNU C2A cell were detected by DNA sequencing. Results: 1) SNU C2A cell and SNU C5 cell were detected mobility shifts each in exon 5 and exon 7 of p53 gene by the PCR-SSCP method, implicating being of p53 mutation. 2) 3 colon cancer cell lines (SNU C1, SNU C2A, SNU C5) expressed wild type and mutant type p53 protein. 3) In northern blot experiment, SNU C2A and SNU C5 cell expressed high level of p53 mRNA. 4) Results of p53-mediated transactivation in colon cancer cell lines by CAT assay represented only SNU C2A cell has transcriptional activity. 5) DNA sequencing in SNU C2A cell showed missense mutation in codon 179 of one allele, histidine to arginine and wild type p53 in the other allele. Conclusion: Colon cancer cell lines showed correlation with mutation in p53 gene and accumulation of abnormal p53 protein. Colon cancer cell SNU C2A retained p53-mediated transactivation as heterozygous p53 with one mutant allele in 179 codon and the other wild-type allele.