• 한국안광학회지
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• 제12권4호
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• pp.71-76
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• 2007

본 연구의 목적은 RGP콘택트렌즈 착용 시 나타날 수 있는 증상에 관한 안경사의 이해도를 조사하는 것인데, RGP 콘택트렌즈 착용 시의 나타날 수 있는 증상에 대한 이해도가 높다면 적응증상과 이상증상을 구분하고 해결하여 RGP콘택트렌즈의 착용성공률을 보다 높여 줄 것이기 때문이다. 96명의 안경사를 대상으로 설문지를 통해 RGP콘택트렌즈 처방에 사용되는 기기 사용방법 및 경험, RGP콘택트렌즈 착용 시 나타날 수 있는 증상 등에 대한 이해수준을 조사하였다. 결과는 RGP콘택트렌즈 착용 시 증상에 대한 정확한 이해력이 상당히 낮은 수준으로 조사되었고, 정확한 처방을 위해 이론교육 및 실습교육 등이 더 강화되어야 한다.

• Asia-Pacific Journal of Atmospheric Sciences
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• 제54권4호
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• pp.527-544
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• 2018

This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the $3.7{\mu}m$ and $10.8{\mu}m$ channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation-maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.

• Journal of Construction Engineering and Project Management
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• 제10권1호
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• pp.1-15
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• 2020

With the increased dependence on subcontracting in the construction industry, the operational relationship between main contractors and subcontractor plays an imperative role in successful project delivery. Consequently, improving this relationship increases the probability of project success and enhancing project performance. A wide range of research has confirmed that partnering improves the main contractor-subcontractor relationship. Though the positive impact of partnering on project performance is supported by a plethora of evidence, the guiding theory on practical partnering process steps is limited. The study aimed at improving subcontracting in the construction industry through a partnering process relevant to Zambia guided by factors obtained from industry expects. Questionnaire surveys and Semi-structured interview were adopted to investigate the perception of construction industry professionals and academics towards the main contractor-subcontractor relationship along with improvement factors. The findings showed that the relationship between main contractors and subcontractors on most projects in Zambia is unsatisfactory therefore justifying attention. Top factors that can enhance the main contractor-subcontractor relationship were identified. From the factors deduced and guidelines on partnering best practices, a project partnering model was developed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• 한국경영과학회지
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• 제18권1호
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• pp.119-126
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• 1993

We study a manufacturing process that is quite common in semiconductor wafer fabrication of semiconductor chip production. A machine is used to process a job consisting of J wafers. Each job requires a setup, and the i$_{th}$ setup for a job is sucessful with probability P$_{i}$. The setup is prone to failure, which results in the loss of expensive wafers. Therefore, a tiral run is first conducted on a small batch. If the set up is successful, the test is passed and the balance of the job can be processed. If the setup is unsuccessful, the exposed wafers are lost to scrap and the mask is realigned. The process then repeats on the balance of the job. We call this as send-ahead policy and consider general policies in which the number of wafers that are sent shead depend on the cost of the raw wafer, the sequence of success probabilities, and the balance of the job. We model this process and determine the expected number of good wafers per job,the expected time to process a job, and the long run average throughput. An algorithm to minimize the cost per good wafer subject to a demand constraint is provided.d.d.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2007년도 정기학술발표대회 논문집
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• pp.599-602
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• 2007

사회간접자본시설에 대한 투자는 국가 경쟁력 강화에 필요한 인프라 구축을 위해 필수 불가결한 국가적 과제이다. SOC투자에 소요되는 재원을 국가 재정으로만 부담하는 것에는 한계가 있다. 따라서 정부는 민간투자사업 제도를 도입하여 적극 장려하고 있으며, 그 결과 2006년 계획 중인 8조3천억 원 사업 중 45개 사업 3조8천억 원이 이미 고시되었다. 그러나 급격한 증가에도 불구하고 BTL사업의 운영 및 선정과정에서 많은 문제점을 드러내고 있으며, 이러한 문제점들은 민간투자사업의 성공적 추진에 걸림돌이 되고 있다. 따라서 본 연구에서는 다음과 같이 BTL사업자의 효율적인 운영 및 선정방안을 제시하였다. 비용 및 견적요인에 대한 사전조사를 통한 물가변동에 따른 공사비 상승을 파악해야하고, 건설사업 관리기법 활용 극대화하여 본사와 현장간의 언어소통 극대화하고 업무 일원화 및 세분화시켜야 할 것이며, 사업시행자 선정 절차단계를 보완해야 한다.

• 시스템엔지니어링학술지
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• 제19권2호
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• 한국통신학회논문지
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• 제37A권9호
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• pp.746-752
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• 2012

SVC 계층형 비디오는 기본 계층과 확장 계층으로 구성되어 있으며 기본 계층의 정상적인 복호 없이는 확장계층의 복호가 불가능하다는 특징을 가지고 있다. 따라서, SVC 비디오 전송에서 수신 비디오의 품질 향상을 위해서는 기본 계층의 성공적인 전송이 중요한 요소로서 작용한다. 본 논문에서는 다중 릴레이를 통해서 전송되는 시스템에서, 비디오의 품질 향상을 위해 계층형 비디오의 중요도에 따라서 복호 성공 확률을 향상시키기 위한 네트워크 코딩 방법을 제안한다. 제안하는 비디오 데이터 중요도 인지 네트워크 코딩 방식을 수식적으로 분석 및 실험하여 그 결과를 보이고, 또한 릴레이의 수에 따른 비디오 품질의 성능 변화를 보였다.

• 한국통신학회논문지
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• 제19권4호
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• pp.605-613
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• 1994

본 논문에서는 CSMA 다중 access 방식으로 분산 무선 통신망을 구현할 때 다중 access 방식의 성능을 비교하였다. 또한 숨겨진 노드가 존재하거나 전자파 장애로 인한 CSMA방식의 성능 저하의 원인을 개설 할 수 있는 프로토콜을 제안하여 성능을 개선하였다. 숨겨진 노드가 존재하는 상황에서 CSMA의 방식을 개선하기 위해 중앙 집중식망에서 ISMA(Idle Signal Multiple Access), BTMA(Busy Tone Multiple Access), BCMA(Busy Channel Multiple Access)등 과 같은 채널 access 방식을 사용하였다. 본 논문에서는 중앙 집중식이 아닌 분산이면서 독립적인 노드로 통신하는 환경에서 숨겨진 노드가 존재하거나 전자파 방애로 인한 노드들이 있는 경우 성능 개선을 위해 프로토콜을 제안하였다. 새로운 프로토콜을 이용하여 컴퓨터 모의실험(simulation)을 함으로써 처리율(throughput)과 전송성공 확률이 실질적으로 개선됨을 확인하였다. 모의실험은 OPNET simulator를 사용하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권3호
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• pp.941-955
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• 2015

In dual-channel networks (DCNs), all frequency hopping (FH) sequences used for data channels are chosen from the original FH sequence used for the control channel by shifting different initial phases. As the number of data channels increases, the hitting frequency point problem becomes considerably serious because DCNs is non-orthogonal synchronization network and FH sequences are non-orthogonal. The increasing severity of the hitting frequency point problem consequently reduces the resource utilization efficiency. To solve this problem, we propose a novel hitting frequency point collision avoidance method, which consists of a sequence-selection strategy called sliding correlation (SC) and a collision avoidance strategy called keeping silent on hitting frequency point (KSHF). SC is used to find the optimal phase-shifted FH sequence with the minimum number of hitting frequency points for a new data channel. The hitting frequency points and their locations in this optimal sequence are also derived for KSHF according to SC strategy. In KSHF, the transceivers transmit or receive symbol information not on the hitting frequency point, but on the next frequency point during the next FH period. Analytical and simulation results demonstrate that unlike the traditional method, the proposed method can effectively reduce the number of hitting frequency points and improve the efficiency of the code resource utilization.