• Journal of the Korean GEO-environmental Society
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• v.13 no.3
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• pp.29-37
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• 2012

This study is to find out the characteristics of the behavior of Geosyntehtic Reinforced Retaining Earth Wall(GRREW) through the laboratory experiment with the reduced-scale model, and to verify the effect of reinforcement by materials of GRREW. The loading tests after combining nonwoven geosynthetic, re-bar mesh nets and drainage blocks respectively among the components of the GRREW were performed in three cases of their slopes. In the cases of the behavior analysis including all of the components of the GRREW, the maximum horizontal displacement was generated 8.4mm at the location of 0.57H in the slope of 1:0.3; 3.8mm at the location of 0.57H in the slope of 1:0.6; 3.6mm at the location of 0.86H in the slope of 1:1.0. On average, the horizontal displacements of the GRREW were reduced by 83.8% against those of the original slopes. Lastly, seepage analysis and slope stability analysis were performed by modelling section of field, to confirm the effect of installation of drainage block in GRREW. We can confirm to compare increasing the slope safe factor and decreasing ground water in accordance with drainage blocks.

• Journal of Fisheries and Marine Sciences Education
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• v.6 no.2
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• pp.183-189
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• 1994

1970년 이후 우리나라는 산업화로 인하여 사회구조와 가정구조가 크게 변화 되었다. 도시집중화로 인한 각종 공해 발생, 교통난, 인구이동의 문제를 비롯하여 그리고 핵가족화로 인한 가부장적 권위상실 및 가정교육부재, 청소년 비행등 수 많은 문제가 야기되었다. 특히 핵가족화로 발생된 심각한 사회문제는 전통윤리의 붕괴와 가정교육의 부재현상을 발생 시켰다. 이와같은 문제발생에 관한 선행연구를 종합해보면 첫째, 핵가족화로 인해 발생한 가족규모의 축소현상으로 자녀들의 다면적 인격형성에 결손을 초래하여 성장후 독립심과 의지가 약하고 고집이 세며 이기적이고 자기중심적인 성향이 되어 사회생활에 부적응 현상을 초래하게 되었다고 한다. 그 이유는 다면적 인간관계의 결여로 상호 협조하고 사랑을 교환한 경험 부족과 외동자녀에 대한 부모의 관심이 자녀의 욕구에만 집중되어 자녀종속적인 태도가 크게 적용하였기 때문이다. 둘째는 산업화 사회에서의 부부동시 사회참여가 자녀양육에 어머니와의 애착형성이 결여되어 모성실조를 겪게 된 문제를 들 수 있다. 어머니와 자녀간의 애착형성이 결여 됨으로 발생되는 문제는 지적 정체현상과 정서발달의 장애가 주 원인이 되어 감정 통제력이 약해서 공격적 행동이나 반 사회적 행동으로 확대되어 청소년문제 발생의 원이 되고 있음을 시사하고있다. 세째로 산업화사회와 경쟁력 조장을 들 수 있다. 산업사회를 개방사회, 경재력사회 혹은 능력사회라하여 고학력위주의 선발형태가 입시경쟁을 부추기고 있으며 그에 따라 많은 청소년들과 학부모들이 상위 지향적인 심리가 작용하여 자녀들의 입시경쟁에만 집중하게 되었다. 이러한 원인으로 인하여 인간교육 즉 가정교육을 외면하여 반도덕적, 반사회적 문제를 야기하게 하였다. 특히 전통적 가정윤리가 붕괴되어 부모에 대한 효관의 약화, 부부간의 애정약화 및 물질지향적인 사고가 이혼률을 증가시켜 가정붕괴를 가져왔다. 이상에서 논의된 자녀교육의 부재가 자녀들의 지적 정서적 문제로 확대되어 산업화사회의 모순점을 노출시키고 있음을 알 수 있다. 이와같은 문제를 해결하기 위한 대안으로 연구자가 제시하는 방안은 훌륭한 가정교육을 위해서 우선되어야 하는것은 부모자신의 인격적 개인완성을 제안하였다. 인격의 완성은 양심과 행동이 일체하는 사람을 지칭한다. 다음은 서로 위하여 사는 삶을 영위하는 인격체가 되어 양심의 법에 따르는 삶, 타인을 위하여 사는 삶을 자녀들에게 보여줌으로서 반두라의 모델링 교육을 제안하였다. 마지막으로 오늘날과 같은 암기위주의 경쟁교육이 아니라 타고난 잠재성 개발에 주력하는 교육으로, 적성과 소질을 개발하는 창조적 산 교육장을 마련하여 주고 또한 그것을 뒷바침하는 가정윤리교육의 회복이 무엇보다도 이 시대가 절실히 요구하는 바람직한 교육이라 하겠다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2002.03b
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• pp.127-141
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• 2002

GIS환경에서 도시모형(urban model)의 적용을 목적으로 사회·경제적 데이터(socio-economic data)를 활용하는 과정은 도시현상이 갖는 복잡성과 변동성으로 인해 하나의 특정시간에서의 상황을 그대로 저장한 형태인 스냅샷 모형(snapshot model)만으로는 효율적인 공간분석의 실행이 불가능하다. 또한 도시모형을 적용하는 과정에서 GIS의 대상이 되는 공간, 속성, 시간의 정의는 분석목적에 따라 다르게 정의되어질 수 있으며 이에 따라 상이한 결과가 도출될 수 있다. 본 연구는 30년 간의 부산시 인구분포의 동적 변화과정 관측을 위해 시간개념을 결합한 Temporal GIS를 구축하고 이를 활용하여 인구밀도모형 및 접근성모형을 적용하는 과정을 통해 보다 효율적이고 다양한 결과를 제시할 수 있는 GIS 활용방안을 제시하고자 하였다. 흔히 공간현상의 계량화와 통계적 기법의 적용을 위한 데이터 처리과정은 많은 오차와 오류를 유발할 수 있다. 이러한 문제의 해결을 위해서는 우선적으로 분석목적에 맞는 데이터의 정의(Data Definition), 적용하고자 하는 모형(Model)의 유용성 검증, 적절한 분석단위의 설정, 결과해석의 객관적 접근 등이 요구된다. 이와 더불어 변동성 파악을 위한 시계열 자료의 효율적 처리를 위한 방법론이 마련되어져야 한다. 즉, GIS환경에서의 도시모형의 적용에 따른 효율성과 효과성의 극대화를 위해서는 분석목적에 맞는 데이터모델의 설정과 공간DB의 구축방법이 이루어져야 하며 분석가능한 데이터의 유형에 대한 충분한 고려와 적용과정에서 분석결과에 중대한 영향을 미칠 수 있는 요소들을 미리 검증하여 결정하는 순환적 의사결정과정이 필요하다., 표준패턴을 음표와 비음표의 두개의 그룹으로 나누어 인식함으로써 DP 매칭의 처리 속도를 개선시켰고, 국소적인 변형이 있는 패턴과 특징의 수가 다른 패턴의 경우에도 좋은 인식률을 얻었다.r interferon alfa concentrated solution can be established according to the monograph of EP suggesting the revision of Minimum requirements for biological productss of e-procurement, e-placement, e-payment are also investigated.. monocytogenes, E. coli 및 S. enteritidis에 대한 키토산의 최소저해농도는 각각 0.1461 mg/mL, 0.2419 mg/mL, 0.0980 mg/mL 및 0.0490 mg/mL로 측정되었다. 또한 2%(v/v) 초산 자체의 최소저해농도를 측정한 결과, B. cereus, L. mosocytogenes, E. eoli에 대해서는 control과 비교시 유의적인 항균효과는 나타나지 않았다. 반면에 S. enteritidis의 경우는 배양시간 4시간까지는 항균활성을 나타내었지만, 8시간 이후부터는 S. enteritidis의 성장이 control 보다 높아져 배양시간 20시간에서는 control 보다 약 2배 이상 균주의 성장을 촉진시켰다.차에 따른 개별화 학습을 가능하게 할 뿐만 아니라 능동적인 참여를 유도하여 학습효율을 높일 수 있을 것으로 기대된다.향은 패션마케팅의 정의와 적용범위를 축소시킬 수 있는 위험을 내재한 것으로 보여진다. 그런가 하면, 많이 다루어진 주제라

• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.4
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• pp.19-26
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• 2012

For a seismic design or performance evaluation of a structure, an experimental investigation on a scale model of the structure or numerical analysis based on the finite element model is considered. Regarding the numerical analysis, a three-dimensional finite element analysis is performed if a high accuracy of the results is required, while a sensitivity or fragility analysis which uses huge seismic ground motions leads to the use of a lumped-mass stick model. The conventional modeling technique to build the lumped-mass stick model calculates the amount of the lumped mass by considering the geometric shape of the structure, like a tributary area. However, the eigenvalues of the conventional model obtained through such a calculation are normally not the same as those of the actual structure. In order to overcome such a deficiency, in this study, a new lumped mass stick model is proposed. The model is named the "frequency adaptive-lumped-mass stick model." It provides the same eigenvalues and similar dynamic responses as the actual structure. A non-prismatic column is considered as an example, and its natural frequencies as well as the dynamic performance of the new lumped model are compared to those of the full-finite element model. To investigate the damping effect on the new model, 1% to 5% of the critical damping ratio is applied to the model and the corresponding results are also compared to those of the finite element model.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.563-568
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• 2007

This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3548-3556
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• 2015

In order to fulfill the needs of reliable and economically feasible foundation, engineers should consider not only the working load that can endure extreme conditions but also apprehending precise behavior of continuous dynamic load while designing the foundation of offshore wind power generators. To actualize the foundation, a model pile was made in miniature. Also, calibration chamber was made and a 500mm height of sand-bed was made to perform "static lateral load experiment" and "repetitive loading experiment", total of two Lateral load tests. As a result, in Static Lateral load test, the bigger length/diameter of model pile led an increase in load displacement. However, when performing "Cyclic Lateral load test", the increase in number of under loading led the decrease in horizontal displacement from each repeated lateral load. While performing Static Lateral load test and repeated loading experiment, we could observe the decreasing in the rate of ultimate lateral load capacity increase of the pile. Also, it turned out that the higher relative density of the ground, the lower ultimate lateral load capacity by repeated horizontal loading.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.684-693
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• 2021

Purpose: The purpose is to establish a safe facility environment from abnormal voltages such as lightning by developing a smart land resistance measuring device that can acquire real-time land resistance data using Arduino. Method: This paper studied design models and application cases by developing a land resistance acquisition and analysis system with Arduino and a power line communication (PLC) system. Some sites in the wind power generation complex in Gyeongsangnam-do were selected as test beds, and real-time land resistance data applied with new technologies were obtained. The electrode arrangement adopted a smart electrode arrangement using a combination of a Wenner four electrode arrangement and a Schlumberger electrode arrangement. Result: First, the characteristic of this technology is that the depth of smart multi-electrodes is organized differently to reduce the error range of the acquired data even in the stratigraphic structure with specificity between floors. Second, IT convergence technology was applied to enable real-time transmission and reception of information on land resistance data acquired from smart ground electrodes through the Internet of Things. Finally, it is possible to establish a regular management system and analyze big data accumulated in the server to check the trend of changes in various elements, and to model the optimal ground algorithm and ground system design for the IT convergence environment. Conclusion: This technology will reduce surge damage caused by lightning on urban infrastructure underlying the 4th industrial era and design an optimized ground system model to protect the safety and life of users. It is also expected to secure intellectual property rights of pure domestic technology to create jobs and revitalize our industry, which has been stagnant as a pandemic in the post-COVID-19 era.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.109-119
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• 2022

The computational efficiency of reverse time migration (RTM) based on numerical modeling is not secured due to the high-frequency band of several hundred Hz or higher for data acquired through a three-dimensional (3D) ultra-high-resolution (UHR) seismic survey. Therefore, this study develops an RTM program to derive high-quality 3D geological structures using UHR seismic data. In the traditional 3D RTM program, an excitation amplitude technique that stores only the maximum amplitude of the source wavefield and a domain-limiting technique that minimizes the modeling area where the source and receivers are located were used to significantly reduce memory usage and calculation time. The program developed through this study successfully derived a 3D migration image with a horizontal grid size of 1 m for the 3D UHR seismic survey data obtained from the Korea Institute of Geoscience and Mineral Resources in 2019, and geological analysis was conducted.

• Journal of Environmental Impact Assessment
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• v.32 no.4
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• pp.203-213
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• 2023

The AERMOD model was the most used, accounting for 89.0%, based on the analysis of the environmental impact assessment reports published in the Environmental Impact Assessment Information Support System (EIASS) between 2021 and 2022. The mismatch of versions between AERMET and AERMOD was found to be 25.3%. There was the operational time discrepancy of 50.6% from industrial complexes, urban development projects between used in the model and applied in estimating pollutant emissions. The results of applying various versions of the AERMET and AERMOD models to both area sources and point sources in both simple and complex terrain in the Gunsan area showed similar values after AERMOD version 12 (15181). Emissions are assessed as 24-hour operation, and the predicted concentration in both simple and complex terrain when using the variable emission coefficient option that applies an 8-hour daytime operation in the model is lowered by 37.42% ~ 74.27% for area sources and by 32.06% ~ 54.45% for point sources. Therefore, to prevent the error in using the variable emission coefficient, it is required to clearly present the emission calculation process and provide a detailed explanation of the composition of modeling input data in the environmental impact assessment reports. Also, thorough reviews by special institutions are essential.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.