• Korean Journal of Clinical Laboratory Science
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• v.54 no.2
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• pp.79-94
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• 2022

Due to the highly contagious nature and severity of the respiratory diseases caused by COVID-19, economical and accurate tests are required to better monitor and prevent the spread of this contagion. As the structural and molecular properties of SARS-CoV-2 were being revealed during the early stage of the COVID-19 pandemic, many manufacturers of COVID-19 diagnostic kits actively invested in the design, development, validation, verification, and implementation of diagnostic tests. Currently, diagnostic tests for SARS-CoV-2 are the most widely used and validated techniques for rapid antigen, and immuno-serological assays for specific IgG and IgM antibody tests and molecular diagnostic tests. Molecular diagnostic assays are the gold standard for direct detection of viral RNA in individuals suspected to be infected with SARS-CoV-2. Antibody-based serological tests are indirect tests applied to determine COVID-19 prevalence in the community and identify individuals who have obtained immunity. In the future, it is necessary to explore technical problems encountered in the early stages of global or regional outbreaks of pandemics and provide future directions for better diagnostic tests. This article evaluates the commercially available and FDA-approved molecular and immunological diagnostic assays and analyzes their performance characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.597-606
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• 2020

Because the USV(Unmanned Surface Vehicle) is capable of remote control or autonomous navigation at sea, it can secure the superiority of combat power while minimizing human losses in a future combat environment. To plan the technology for the development of USV, the trend analysis of related technology and the selection of promising technology should be preceded, but there has been little research in this area. The purpose of this paper was to measure and evaluate the technology trends quantitatively. For this purpose, this study analyzed the technology trends and selected promising/declining technologies using topic modeling of papers and patent data. As a result of topic modeling, promising technologies include control and navigation, verification/validation, autonomous level, mission module, and application technology, and declining technologies include underwater communication and image processing technology. This study also identified new technology areas that were not included in the existing technology classification, e.g., technology related to research and development of USV, artificial intelligence, launch/recovery, and operation, such as cooperation with manned and unmanned systems. The technology trends and new technology areas identified through this study may be used to derive key technologies related to the development of the USV and establish appropriate R&D policies.

• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.605-614
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• 2006

The success of a software development project can be determined by the use of QCD. And as a software's size and complexity increase, the importance of early quality assurance rises. Therefore, more effort should be given to prevention, as opposed to correction. In order to provide a framework for the prevention of defects, defect detection activities such as peer review and testing, along with analysis of previous defects, is required. This entails a systematization and use of quality data from previous development efforts. FMEA, which is utilized for system safety assurance, can be applied as a means of software defect prevention. SW-FMEA (Software Failure Mode Effect Analysis) attempts to prevent defects by predicting likely defects. Presently, it has been applied to requirement analysis and design. SW-FMEA utilizes measured data from development activities, and can be used for defect prevention on both the development and management sides, for example, in planning, analysis, design, peer reviews, testing, risk management, and so forth. This research discusses about related methodology and proposes defect prevention model based on SW-FMEA. Proposed model is extended SW-FMEA that focuses on system analysis and design. The model not only supports verification and validation effectively, but is useful for reducing defect detection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.230-238
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• 2023

Small and medium-sized food manufacturing enterprises are largely reliant on manual labor, from inputting raw materials to palletizing the final product. Recently, there has been a trend toward smartness and digitization through the implementation of robotics and sensor data technology. In this study, we examined the effectiveness of improvement through 3D simulation on two repetitive work processes within a food manufacturing company. These processes involve workers whose speed cannot match the capacity of the applied equipment. Two manual processes were selected: the weighing and packing process performed by workers after skewer assembly, and the manual batch process of counting randomly delivered frozen foods, packing (both internal and external), and palletizing. The production volume, utilization rate, and number of workers were chosen as verification indicators. As a result of the simulation for improving the 3D process, production increased by 13.5% and 56.8% compared to the existing process, respectively. This was particularly evident in the process of applying palletizing robots. In both processes, as the utilization rate and number of input workers decreased, robots could replace tasks with high worker fatigue, thereby reducing work overload. This study demonstrates the potential to visually compare the process flow improvement using 3D simulations and confirms the possibility of pre-validation for improvement.

• Korean Journal of Heritage: History & Science
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• v.40
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• pp.387-411
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• 2007

The analysis of ancient DNA (aDNA) has become increasingly considerable anthropological, archaeological, biological and public interest. Although this approach is complicated by the natural damage and exogenous contamination of a DNA, archaeologists and biologists have attempted to understand issues such as human evolutionary history, migration and social organization, funeral custom and disease, and even evolutionary phylogeny of extinct animals. Polymerase chain reaction(PCR) is powerful technique that analyzes DNA sequences from a little extract of an ancient specimen. However, deamination and fragmentation are common molecular damages of aDNA and cause enzymatic inhibition in PCR for DNA amplification. Besides, the deamination of a cytosine residue yielded an uracil residue in the ancient template, and results in the misincorporation of an adenine residue in PCR. This promotes a consistent substitution (cytosine thymine, guanine adenine) to original nucleotide sequences. Contamination with exogenous DNA is a major problem in aDNA analysis, and causes oversight as erroneous conclusion. This report represents serious problems that DNA modification and contamination are the main issues in result validation of aDNA analysis. Now, we introduce several criterions suggested to authenticate reliance of aDNA analysis by many researchers in this field.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.569-582
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• 2023

In recent years, the service life of major SOC facilities in south korea has exceeded 30 years, and rapid aging is expected within the next 10 years. This has led to a growing recognition of the need for proactive maintenance of these facilities. Consequently, there have been numerous research efforts to introduce smart inspection technologies into maintenance. However, the current system relies primarily on manpower for safety inspections and diagnostics, and on-site surveys rely on visual inspections. Manpower inspections can be time-consuming, and subjective errors may occur during result analysis. In the case of tunnels, there are disadvantages, such as the loss of social overhead capital due to partial closures during inspections. Therefore, institutionalizing smart safety inspections is essential, considering specific measures like using advanced equipment and updating qualifications for experts. Furthermore, it is necessary to verify and validate safety inspection results using advanced equipment before instituting changes. This could be achieved through national-level official research programs and the operation of verification and validation institutions. If smart inspection technology is introduced into maintenance, routine inspections of SOC facilities, such as tunnels, will become feasible. As a result, maintenance technology capable of early detection and proactive response to safety incidents caused by changes in facility conditions is anticipated.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.491-505
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• 2020

The purpose of this study is to develop an evaluation index that can assess the Army training program of Green Camp. The result of the evaluation index phased-developed with the CIPP model is summarized below. First, the literature review with documents relevant to program evaluation, Green Camp field research, and expert discussions were used to select factors considered for evaluation and develop a preliminary evaluation area and item for the four areas within the CIPP evaluation model. Second, an initial survey targeting Green Camp and soldiers in the Capital Defense Command examined the preliminary reliability·validity, and the Focused Group discussions were used to supplement the evaluation index. Third, secondary surveys were conducted in four battalions in Gangwon-do and third surveys targeted officers from twelve different corps and personnels related to the Green Camp which verified descriptive statistics analysis, exploratory factor analysis, and correlation analysis in version SPSS 24. Fourth, with the validation verification procedure, 16 evaluation area and 36 evaluation index was confirmed. Fifth, the 36 evaluation index developed was subdivided into 57 indexes and the Delphi method was applied through the policy expert to formulate 43 generalized indexes. The significance of this phased research approach was considered for the institutionalization of the usage of scientific evaluation(index) and development in policy process.

• Journal of The Korean Association For Science Education
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• v.33 no.5
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• pp.995-1006
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• 2013

The purposes of this study were to develop an instrument to measure high school students' systems thinking and to validate the scale. The scale of systems thinking was made up for 5 factors - systems thinking, mental model, shared vision, personal mastery, and team learning through analyses of related literature. Six items per factor were constructed and the scale consisted of a total of 30 items for the pretest. After exploratory factor analysis, the number of total items was reduced to 20 items. For the main test, 280 students were sampled from high school and analyzed valid cases were 260 students. The finding of the exploratory factor analysis indicated 5 factors in the model, and 4 items per single factor. The result of confirmatory factor analysis was generally appropriate and acceptable (5 factor model: $x^2/df$=1.275, TLI=.946, CFI=.959, RMSEA=.033). The reliability for 20 items turned out to be reliable because the Cronbach's alphas were .840 and .604~.723 per each factor. This study should be expanded to various school levels and should be standardized for further research. The subsequent studies regarding diverse learning program development and implementation and the verification on the students' impact within the developed program can be recommended.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.