• Journal of the Korean Chemical Society
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• v.60 no.1
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• pp.34-38
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• 2016

In this paper, zinc oxide nanoparticles (ZnO NPs) were synthesized using the sonochemical method, where equimolar amounts of zinc acetate dehydrate and sodium hydroxide were separately dissolved in deionized water, and then mixed for 30 min under magnetic stirring. The resultant white gel was sonicated for 60, 120, 180, 240, and 360 min with magnetic stirring. The obtained precipitates were centrifuged, repeatedly washed with ethanol to remove ionic impurities, and dried at 50 ℃ for 24 h. The formation of pure NPs was confirmed by X-ray diffraction, and their crystallinity and crystal phases were analyzed as well. Structural investigation was carried out by field-emission scanning electron microscopy (FE-SEM). The photocatalysis behavior of the ZnO NPs was investigated in a dark room under UV irradiation, using Rhodamine B. Spherical, rod, and flower-like ZnO NPs could be obtained by adjusting the sonication time, as observed by FE-SEM. The flower-like ZnO NPs exhibited excellent photocatalytic activity.

• The KIPS Transactions:PartD
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• v.17D no.2
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• pp.87-102
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• 2010

A vast amount of traffic data is produced every day from detection devices but this data includes a considerable amount of errors and missing values. Moreover, this information is periodically deleted before it could be used as important analysis information. Therefore, this paper discusses the implementation of an integrated traffic history database system that continuously stores the traffic data as a multidimensional model and increases the validity and completeness of the data via a flow of processing steps, and provides a what-if analysis function. The implemented system provides various techniques to correct errors and missing data patterns, and a what-if analysis function that enables the analysis of results under various conditions by allowing the flexible definition of various process related environment variables and combinations of the processing flows. Such what-if analysis functions dramatically increase the usability of traffic data but are not provided by other traffic data systems. Experimantal results for cleaning the traffic history data showed that it provides superior performance in terms of validity and completeness.

• Korean journal of applied entomology
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• v.46 no.2
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• pp.175-182
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• 2007

Two fruit moths of the oriental fruit moth, Grapholita molesta (Busck), and the peach fruit moth, Carposina sasakii (Matsumura), infest apples in Korea by internally feeding behavior. C. sasakii is a quarantine insect pest from some other countries importing Korean apples. G. molesta is not a quarantine insect pest, but can be incorrectly identified as C. sasakii especially when it is found inside apple fruits at its larval stages because it is not easy to identify the two species by morphological characters alone. This incomplete identification results in massive economical loss by fruits needlessly destroyed or turned away at border inspection stations of the importing nations. This difficulty can be overcome by molecular DNA markers. Several polymorphic regions of mitochondrial DNA of both species were sequenced and used for developing specific striction sites and polymerase chain reaction (PCR) primers. Based on these sequences, three diagnostic PCR-restriction fragment length polymorphism (RFLP) sites were detected and validated for their practical uses. Also, species-specific PCR primers were devised to develop diagnostic PCR method for identifying the internal feeders.

• Spatial Information Research
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• v.22 no.3
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• pp.71-77
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• 2014

There are numbers of unpredictable risk factors in the disaster scenes such as fire, explosion and fail to early life-saving or holding the flames which can lead to massive damage. In particular, fire-fighters who arrive on the scene within 5 minutes after dispatching, have a limitation to get aware to the situation of scene fully, because of immediate deploy to disaster scene with limited information. This situation may lead to disturbance that fire-fighters perform effective fire-fighting activities, to put fire-fighter's life at risk by misjudge the situation. Previous domestic and International studies focused vulnerability for spatial area or features which can damage to life and property in the event of anticipated. In this study, we have been developed fire-fighting vulnerable zone model that can analyze comprehensively hindrance factors for fire-fighting activities targeting whole life cycle of fire-fighting activities from dispatch to fire suppression or life-saving. In addition, we have been given shape to finality and applicability for our model by defining the new concept of fire-fighting vulnerable zone which can be distinguished from the concept of fire vulnerable area in previous studies. The results of this study can be used to analysis fire-fighting vulnerable zone type analysis, establish fire-fighting policies and improve the performance of decision-making process.

• KSBB Journal
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• v.22 no.6
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• pp.409-413
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• 2007

Polydiacetylene(PDA)-based sensors possess a number of properties that can be successfully applied for label-free detection system. PDA is one of the most attractive color-generating materials, with growing applications as sensors. Here we introduce various PDA-based devices, used as biosensor, chemosensor, thermosensor, and optoelectronics sensor. In general, PDA liposomes and films are closely packed and properly designed for polymerization via 1,4-addition reaction to form an ene-yne alternating polymer chain. PDA-based two/three dimensional structures have been used for colorimetric or fluorescent devices, sensing biological as well as chemical components. This color-generating material also present a very high charge carrier mobility, allowing its application as field-effect transistor (FET). The immobilized PDA structures or films have distinct advantages for the detection of low concentration target molecules over the aqueous solution-based detection systems. In the present review, reported detection methods by using various PDA structures are summarized with updated references.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.349-353
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• 2019

우리나라는 전 국토의 70%가 산지이고 하천경사가 다른 나라에 비해 상대적으로 급하여 홍수 관리에 매우 불리한 조건을 가지고 있으며, 특히 홍수기간의 집중호우 및 돌발홍수는 인명과 재산의 막대한 피해를 입히고 있다. 최근은 기후변화로 인하여 극심한 홍수, 가뭄 등 재해의 발생빈도가 증가하는 추세로 기후변화의 영향을 최소화할 수 있는 수재해 방재관리가 필요한 상황이다. 중 대하천의 경우에는 비교적 수재해 방재관리가 잘 이루어지고 있으나, 소하천(일부 중하천 포함)의 경우에는 취약한 구조를 보이고 있다. 특히 홍수기간(7월~9월)의 인명과 재산의 피해는 주로 소하천 위주로 발생하고 있으며, 사전 사후의 체계적인 대응이 이루어지지 못하고 있다. 수재해 방재관리를 위해서는 일차적으로 수문자료의 획득에 있으며, 그 이후 해당유역에 적합한 수재해 대응을 위한 체계적인 방법론과 방재시스템 개발 운영이 수반되어야 안전한 방재관리를 할 수 있다. 따라서 수재해 방재관리 체계를 구축하기 위해서는 중 소규모 유역 단위를 대상으로 지속적이고 신뢰성 있는 자료의 획득과 축적이 중요하므로 중 소규모 유역 단위의 대표성 있는 시험유역의 운영은 매우 의미가 있다고 볼 수 있다. 본 논문에서는 한국건설기술연구원에서 운영하는 설마천 시험유역(유역면적 $8.48km^2$, 유로경사 2.15%, 경기도 파주시 적성면 소재)의 신뢰성 높은 2018년 관측자료를 이용하여 강우특성, 유출특성, 증발산량과 지하수 함양량 산정 등 수문특성을 분석하였으며, 2017년 관측결과와 비교하였다. 강우특성 분석으로는 호우사상 분리, 주요 호우사상 분석, 지속기간별 최대강우량, 시간분포 등이 있다. 2018년은 2017년보다 최대 강우지속기간은 작게, 평균 강우지속기간은 크게 나타나며, 최대 강우강도와 평균 강우강도도 크게 나타나는 호우의 특징을 보인다. 2018년 지속기간별 최대강우량의 경우 지속기간 1시간까지는 2017년과 유사한 패턴을 보이나 그 이후는 많은 강우량을 보인다. 2018년의 하천유출률은 58.1%로 2017년 연간 유출률인 64.8% 보다는 적은 유출률을 보인다. 이의 원인으로는 연간 총강우량은 2017년보다 397.9mm 많으나 2018년의 7월~8월 집중호우기간의 강우량이 2017년 7월~8월 강우량보다 적어 하천유출에 적게 기여한 결과로 판단된다. 2018년의 증발산량(555.8mm)과 지하수 함양량(32.0mm)은 2017년의 증발산량(328.8mm)과 지하수 함양량(24.8mm)보다 크게 나타나는 것으로 분석되었다. 이와 같이 산정된 수문자료는 수재해 방재와 유역의 물순환 과정 규명을 위한 기초자료로 매우 유용하게 활용될 수 있으며, 수재해 방재관리를 위한 의사결정 과정에 중요한 역할을 할 수 있으므로 지속적인 시험유역의 운영은 매우 필요하다.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.301-310
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• 2006

Typically, we needs enormous national budget for the flood control project and so the project usually has big influence on the national economy. Therefore, the reliable estimation of flood damage is the key issue for the economic analysis of the flood control project. This study aims to provide a GIS based technique for distributed flood damage estimation. We consider two aspects of engineering and economic sides, which are the inundation analysis and MD-FDA (Multi-Dimensional Flood Damage Analysis), for the flood damage assessment. We propose the analysis framework and data processing using GIS for assessing flood damages. The proposed methodology is applied to the flood control channel project for flood disaster prevention in Mokgamcheon/Dorimcheon streams and this study presents the detailed GIS database and the assessment results of flood damages. This study may have the worth in improving practical usability of MD-FDA and also providing research direction for combining economic side with the engineering aspect. Also this distributed technique will help decision-making in evaluating the feasibility of flood damage reduction programs for structural and nonstructural measures.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.206-223
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• 2023

The introduction of Smart technologies such as Artificial Intelligence(AI) systems are have a powerful impact in a variety of industry fields. Some experts predict that smart technology will completely change people's daily life and work styles, causing technological innovation, productivity improvement, and discovery and emergence of new fields. On the one hand, this vision cannot ignore negative views and concerns. Despite many social debates about employment, such as job loss and rising unemployment, there have not been many studies based on employee experience that provide a fundamental solution to the conflict between AI and employment. Therefore, this study finds out the effects and related factors of AI concierge robots for hotel employees, focusing on the hotel industry, and how employees' perceptions of AI concierge robots affect user resistance and turnover intention. This study, conducted a questionnaire survey of 322 hotel employees who had experience working with AI concierge robots in China, and used SPSS and SmartPLS statistical analysis programs to draw conclusions. We found that hotel employees' perceptions of AI concierge robots were significantly related to user resistance and turnover intention, and this association was related to employee self-efficacy, perceived organizational support, quality of AI services and new tasks. In addition, it was found that the quality of AI concierge robots directly or indirectly had the greatest influence on user resistance and turnover intention. The findings of this study provide theoretical implications for academia and practical implications for industry practitioners.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.391-398
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• 2023

In this paper, a penalized maximum likelihood estimation (PMLE) method that applies a penalty to increase the accuracy of a basis-screening-based Kriging model (BSKM) is introduced. The maximum order and set of basis functions used in the BSKM are determined according to their importance. In this regard, the cross-validation error (CVE) for the basis functions is employed as an indicator of importance. When constructing the Kriging model (KM), the maximum order of basis functions is determined, the importance of each basis function is evaluated according to the corresponding maximum order, and finally the optimal set of basis functions is determined. This optimal set is created by adding basis functions one by one in order of importance until the CVE of the KM is minimized. In this process, the KM must be generated repeatedly. Simultaneously, hyper-parameters representing correlations between datasets must be calculated through the maximum likelihood evaluation method. Given that the optimal set of basis functions depends on such hyper-parameters, it has a significant impact on the accuracy of the KM. The PMLE method is applied to accurately calculate hyper-parameters. It was confirmed that the accuracy of a BSKM can be improved by applying it to Branin-Hoo problem.