• Journal of Soil and Groundwater Environment
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• v.22 no.3
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• pp.1-9
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• 2017

The numerical analysis of groundwater flow is indispensable for predicting problems associated with water resource development, civil works, environmental hazards, and nuclear power plant construction. Korea lacks public regulatory procedures and guidelines for groundwater flow modeling, especially in nuclear facility sites, which makes adequate evaluation difficult. Feasible step-by-step guidelines are also unavailable. Consequently, reports on groundwater flow modeling have low-grade quality and often present controversial opinions. Additionally, without public guidelines, maintaining consistency in reviewing reports and enforcing laws is more challenging. In this study, the guidelines for groundwater flow modeling were reviewed for three countries - the United States (Documenting Groundwater Modeling at Sites Contaminated with Radioactive Substances), Canada (Guidelines for Groundwater Modelling to Assess Impacts of Proposed Natural Resource Development Activities), and Australia (Australian Groundwater Modelling Guidelines), with the aim of developing groundwater flow modeling regulatory guidelines that can be applied to nuclear facilities in Korea, in accordance with the Groundwater Act, Environmental Impact Assessment Act, and the Nuclear Safety Act.

• Proceedings of the Korean Geotechical Society Conference
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• 1993.10b
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• pp.235-247
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• 1993

The 62 m span Olympic lee Hockey cavern in Gjovik, Norway, is located in jointed gneiss of average RaD = 70% and has a rock cover of only 25 to 50m, thus posing challenging design p problems. The investigations prior to construction included two types of stress measurements, cross-hole seismic tomography, special coe logging, Q-system classification and numerical modelling with UDEC-BB. Predicted maximum deformations were 4 to 8 mm; surprisingly small due to the high horizontal stresses recorded. Extensometer (MPBX) installations from the surface prior to construction, precision surface levelling and MPBX installed from inside the cavern give a combined measure of maximum deformations in the range 7 to 8 mm with the 62 m span fully e excavated, and three adjacent caverns for the Postal Services also completed.

• Toxicological Research
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• v.33 no.3
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• pp.173-182
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• 2017

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.

• 기술발표회
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• s.2006
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• pp.45-53
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• 2006

Top-Down Construction Method has been considered as the steadiest and the most reasonable method of construction since 1984 when it was applied to LG Da-Dong building and its usage in the field construction has since grown rapidly. With increased cases, engineers not only pursue their studies of R & D continuously but also develop various technical methods based on Top-Down Construction in an era of rapid technological change to adopt them to the field construction. Top-Down Construction meets the needs of these challenging points, such as reduction and eliminates of temporary equipment for supporting permanent structures on the ground, improved method of construction, shortening construction periods, cost reduction, and allows for minimal environmental impact.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.283-287
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• 2010

Stochastic simulation of hydrologic data has been widely developed for several decades. However, despite the several advances made in literature still a number of limitations and problems remain. In the current study, some stochastic simulation approaches tackling some of the existing problems are discussed. The presented models are based on nonparametric techniques such as block bootstrapping, and K-nearest neighbor resampling (KNNR), and kernel density estimate (KDE). Three different types of the presented stochastic simulation models are (1) Pilot Gamma Kernel estimate with KNNR (a single site case) and (2) Enhanced Nonparametric Disaggregation with Genetic Algorithm (a disaggregation case). We applied these models to one of the most challenging and critical river basins in USA, the Colorado River. These models are embedded into the hydrological software package, Pros and cons of the models compared with existing models are presented through basic statistics and drought and storage-related statistics.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.9
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• pp.723-730
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• 2016

This paper presents a cable-driven hydraulic actuator named Cable Rod Hydraulic Actuator (CRHA). The cable actuating system is attractive for designing a compact joint in robotic applications since it can be installed remotely from the joint. Recently, cable rods have been used in pneumatic area for inertia reduction. However, designing cable rods in hydraulics is challenging because it is difficult to achieve flexibility and endurance simultaneously under high pressure conditions. In this paper, the cable rod, which consists of a cable and jacket, is proposed to meet both requirements. To design the CRHA, we determined the design parameters, such as cylinder size, and selected the cable rod's material by friction and leakage test. Finally, comparisons experiments about step and frequency responses with conventional hydraulic actuators were performed to assess feasibility for robotic joints, and the results show that the proposed system has good bandwidth and fast response as robotic joints.

• STI Policy Review
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• v.9 no.1
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• pp.77-98
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• 2018

In the past few decades, the importance of dynamics of University-Industry Linkage(UIL) in strengthening national and regional innovation competency and global competitiveness has been progressively more acknowledged. However, establishing an effective UIL for a better economic development is still a challenging endeavor in Ethiopia, particularly in Tigray region. This study is aimed at assessing the status of UIL and in order to achieve such aim it analyzed the determinants of firms' intensity of interaction with the Mekelle University (MU) and the effect of the intensity of interaction on the relevant firms' innovation performance. The findings of the study showed that the status of UIL between the firms and the university in Tigray region was at an infant stage. The study also found that firm size, firm age (startups) and government supports have had a significant effect on firms' intensity of interaction with the MU. However, the firms' intensity of interaction with the MU did not have any significant effect on the firms' innovation performance. In contrast, cooperation with customers, other groups and suppliers, firm size, firm age, and in-house R&D activities were found to have a significant effect on the firms' innovation performance. In conclusion, the acquisition of knowledge and technology from university does not have an important role in firms' innovation performance in the studied region. Consequently, the government should design effective strategies and assign responsible bodies to implement the strategies, create awareness, and organize both firms and university to meet and work together in order to enhance firms' innovation performance.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.3
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• pp.387-419
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• 2021

The challenges facing companies and institutions surrounding civil nuclear decommissioning are diverse and many, none more so than those faced in the United Kingdom. The UK's Generation I nuclear power plants and early research facilities have left a 'Nuclear Legacy' which is in urgent need of management and clean-up. Sellafield is quite possibly the most ill-famed nuclear site in the UK. This complex and challenging site houses much of what is left from the early days of nuclear research in the UK, including early nuclear reactors (Windscale Piles, Calder Hall, and the Windscale Advanced Gas Cooled Reactor) and the UK's early nuclear weapons programme. Such a legacy now requires careful management and planning to safely deal with it. This task falls on the shoulders of the Nuclear Decommissioning Authority (NDA). Through a mix of prompt and delayed decommissioning strategies, key developments in R&D, and the implementation of site licenced companies to enact decommissioning activities, the NDA aims to safety, and in a timely manner, deal with the UK's nuclear legacy. Such approaches have the potential to influence and shape other such approaches to nuclear decommissioning activities globally, including in Korea.

• New & Renewable Energy
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• v.17 no.1
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• pp.19-32
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• 2021

Photovoltaic (PV) panels are generally treated as the most dependable components of PV systems; therefore, investigations are necessary to understand and emphasize the degradation of PV cells. In almost all specific deprivation models, humidity and temperature are the two major factors that are responsible for PV module degradation. However, even if the degradation mode of a PV module is determined, it is challenging to research them in practice. Long-term response experiments should thus be conducted to investigate the influences of the incidence, rates of change, and different degradation methods of PV modules on energy production; such models can help avoid lengthy experiments to investigate the degradation of PV panels under actual working conditions. From the review, it was found that the degradation rate of PV modules in climates where the annual average ambient temperature remained low was -1.05% to -1.16% per year, and the degree of deterioration of PV modules in climates with high average annual ambient temperatures was -1.35% to -1.46% per year; however, PV manufacturers currently claim degradation rates of up to -0.5% per year.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.6
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• pp.591-601
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• 2021

Recently, infrared object detection(IOD) has been extensively studied due to the rapid growth of deep neural networks(DNN). Adversarial attacks using imperceptible perturbation can dramatically deteriorate the performance of DNN. However, most adversarial attack works are focused on visible image recognition(VIR), and there are few methods for IOD. We propose deep learning-based adversarial attacks for IOD by expanding several state-of-the-art adversarial attacks for VIR. We effectively validate our claim through comprehensive experiments on two challenging IOD datasets, including FLIR and MSOD.