• Journal of Veterinary Clinics
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• v.31 no.1
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• pp.40-45
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• 2014

Abalone herpes-like virus (AbHV) is a fatal disease of abalones that impose severe economic impacts on the industry of infected regions due to high mortality. The aim of this study was to quantify the risk of introducing AbHV into Korea through the importation of live abalones for human consumption by import risk analysis (IRA). Monte Carlo simulation models were developed to provide estimates of the probability that a ton of imported abalone contains at least one AbHV-infected individual, using historical trade data and relevant literatures. A sensitivity analysis with 5,000 iterations was also conducted to determine the extent to which input parameters affect the outcome of the model. Although many uncertainties were present in the data, the results indicated that, if 5,000 tons of abalone were imported from a hypothetical exporting country with low prevalence of AbHV (model 1), there would be at least one AbHV-infected abalones in 4,816 of those tons (96.3%), while there would be at least one AbHV-infected abalones in 100% of those tons imported from country with high prevalence (model 2). Sensitivity analysis indicated that for model 1, prevalence was the strongest influence factor on the predicted number of infections. For model 2, background mortality and washing to reduce the risk of surface contamination during processing were the major contributing factors. Risk management strategies need to be enforced to reduce the risk of AbHV introduction in that at least one infected abalone would remain in a consignment from country even with a low prevalence of AbHV infection. The methodology and the results presented here will contribute to improve the development of AbHV management program, and with more accurate data this IRA model will aid science-based decision-making on mitigation strategies to reduce the risk of AbHV introduction in Korea.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.137-145
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• 2020

Providing safety training to construction workers is essential to reduce safety accidents at the construction site. With the prosperity of visualization technologies, Immersive Virtual Reality (IVR) has been adopted for construction safety training by providing interactive learning experiences in a virtual environment. Previous research efforts on IVR-based training have found that the level of fidelity of interaction between real and virtual worlds is one of the important factors contributing to the sense of presence that would affect training performance. Various interactive devices that link activities between real and virtual worlds have been applied in IVR-based training, ranging from existing computer input devices (e.g., keyboard, mouse, joystick, etc.) to specially designed devices such as high-end VR simulators. However, the need for high-fidelity interactive devices may hinder the applicability of IVR-based training as they would be more expensive than IVR headsets. In this regard, this study aims to understand the impact of the level of fidelity of interactive devices in the sense of presence in a virtual environment and the training performance during IVR-based forklift safety training. We conducted a comparative study by recruiting sixty participants, splitting them into two groups, and then providing different interactive devices such as a keyboard for a low fidelity group and a steering wheel and pedals for a high-fidelity group. The results showed that there was no significant difference between the two groups in terms of the sense of presence and task performance. These results indicate that the use of low-fidelity interactive devices would be acceptable for IVR-based safety training as safety training focuses on delivering safety knowledge, and thus would be different from skill transferring training that may need more realistic interaction between real and virtual worlds.

• Journal of Korea Port Economic Association
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• v.28 no.4
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• pp.79-98
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• 2012

There is scant of research regarding the efficiency measurement of the ship management business. This paper aims to analyze the relative efficiency within the Korean Major Ship management corporations, to select the relatively low effective companies, and to suggest the improvement strategies for those. As a research methodology, Data Envelopment Analysis (DEA) applied to the top 20 corporations among Korean and Foreign Shipping Liners in Korea. To draw out the efficiency of targeted terminals, the number of ship managed is used as an input variables while, the number of crews and the total sales are utilized as an output variables. As a result. Haeyoung Maritime services is the most efficient corporations in Foreign Shipping Liners. Among Korean Shipping Liners, Panstar Shipping, Korea Lines, STX marine and Woolim Shipping are relatively efficient corporations which are scored BCC 1.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.3
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• pp.395-406
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• 2015

This research carried out an analysis on input cost and leakage reduction effect by leakage reduction method, focusing on the project for establishing an optimal water pipe network management system in the Taebaek region, which has been executed annually since 2009. Based on the result, optimal cost-benefit analysis models for water distribution network rehabilitation project were developed using DEA(data envelopment analysis) and multiple regression analysis, which have been widely utilized for efficiency analysis in public and other projects. DEA and multiple regression analysis were carried out by applying 4 analytical methods involving different ratios and costs. The result showed that the models involving the analytical methods 2 and 4 were of low significance (which therefore were excluded), and only the models involving the analytical methods 1 and 3 were suitable. From the result it was judged that the leakage management method to be executed with the highest priority for the improvement of revenue water ratio was installation of pressure reduction valve, followed by replacement of water distribution pipe, replacement of water supply pipe, and then leakage detection and repair; and that the execution of leakage management methods in this order would be most economical. In addition, replacement of water meter was also shown to be necessary in case there were a large number of defective water meters.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.10 no.S_3
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• pp.113-119
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• 2001

Surface sediments(0~5 cm) were sampled from 22 stations in Ulsan Bay, one of the most highly industrialized regions in Korea, in November 2000. The sediment samples were analyzed for their polycyclic aromatic hydrocarbon(PAH) content using a gas chromatography coupled to a mass spectrometer detector(GC/MSD). The total PAH concentrations in the sediments varied from 14 to 7108 ng/g dry weight with a mean value of 1052 ng/g dry weight. The level of carcinogenic PAHs ranged from 6 to 2396 ng/g dry weight with a mean value of 433 ng/g dry weight. The highest PAH concentrations in the sediments from Ulsan Bay were found at Station U8, whereas the lowest levels were observed at Stations U2 and U 17. The PAH distribution exhibited a decreasing gradient from the inner basin to the outer bay. The predominant contributors to the aromatic ring groups of the 16 PAHs were four- and five-ring groups, such as fluoranthene, pyrene, benzo[a]anthracene, chrysene, benzor[b]fluoranthene, benzor[k]fluoranthene and benzo[a]pyrene, while two- and three-ring aromatics, like naphthalene, acenapthylene, acenaphthene, fluorene, phenanthrene and anthracene, only exhibited a low concentration. The molecular indices for phenanthrene/anthracene and fluoranthen/pyrene were used to Identify the origin of the PAH contamination in the sediments. The results indicated that the PAH contamination in Ulsan Bay was mostly Pyrolytic in origin with a Petrogenic input adjacent to Ulsan and Jangsuengpo harbor.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.239-244
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• 2013

This paper presents a design of the CMOS LDO regulator with a UVLO protection function for a high speed PMIC. Proposed LDO regulator circuit consists of a BGR reference circuit, an error amplifier and a power transistor and so on. UVLO block between the power transistor and the power supply is added for a low input protection function. Also, UVLO block showed normal operation with turn-off voltage of 2.7V and turn-on voltage of 4 V in condition of 5 V power supply. Proposed circuit generated fixed 3.3 V from a supply of 5V. From SPICE simulation results using a $1{\mu}m$ high voltage CMOS technology, simulation results were 5.88 mV/V line regulation and 27.5 uV/mA load regulation with load current 0 mA to 200 mA.

• Journal of Computing Science and Engineering
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• v.4 no.1
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• pp.80-95
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• 2010

In order to truly integrate e-Learning system into regular curriculum at a university, mobile access to Learning Management Systems has to be enabled. Mobile devices have the potential to be integrated into the classroom, because they contain unique characteristics such as portability, social interactivity, context sensitivity, connectivity and individuality. Adoption of Learning Management Systems by students is still on the low rate, mostly because of poor usability of existing e-Learning systems. Our initial research has confirmed this hypothesis. Usability issue is rising to the higher level on the mobile platform, because of the mobile devices' limited screen size, input interfaces and bandwidth, and also because of the context of use. Our second hypothesis was that it is wrong to consider a mobile device as a surrogate for desktop or laptop personal computer (PC). By just adopting the existing Learning Management System on mobile devices with adaptive technologies such as Google proxy, we do not acquire the satisfactory results. Usability can prove to be even lower compared to desktop application. One possible solution to the problem could be development of rich client applications for today's mobile devices that would raise the usability to a higher level. We developed a PocketPC prototype application by using user-centered design principles, which we presented as a third alternative in usability research conducted among university students. Results gathered in such a way have confirmed that development of e-Learning system, in order to be widely accepted by students, needs to have the user(student) in the center of development process.

• Journal of Forest and Environmental Science
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• v.19 no.1
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• pp.48-68
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• 2003

There have been some problems of high labor. low productivity in the existing systems of bonsai cultivation. This study was conducted to cultivate a large quantity of hig-quality bonsai through the development of bottom irrigation system and management method. Bonsai placed on the FRP bed were grown very well by bottom irrigation system compared with direct watering and sprinkler system. It was concluded that bottom irrigation system was possible to reduce considerable manual labor and produce mass production of high-quality bonsai within shorter periods. This research was finally found that the growth was significantly better and earlier production was certain in the vinyl house, had another advantage which could cultivate less cold-resistant species and therefore broadened a range of species selection for market supply. Cultivation techniques by the use of vinyl house and bottom irrigation system developed was quite effective for early production of bonsai as well as for high productive and value added. This project developed a new practical techniques and systems which can make mass and early production of bonsai with high quality through input of less labor. Interest in bonsai is now expanding in landscape horticulture and other fields concerned, and bonsai export of our country is also increasing. Results from this research will make a great contribution to enhancing of bonsai cultivator's competitive position in world markets and to improving of their annual income.