• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 추계학술대회 논문집
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• pp.340-345
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• 2003

This study, as a basic study for establishing a influence forecasting/estimating model when drain the deep sea water to the ocean after using it, carried out studies as follows; 1) estimating the amount of river discharge and pollutant loads inflowing into the developing region of deep sea water in East Sea, Korea 2) a field observation of tidal current, vertical distribution of water temperature and salinity, and 3-D numerical experiment of tidal current to analysis physical oceanographic status. The amount of river discharge flowing into the study area was estimated about $462.6{times}10^{3}m^{3}/day$ of daily mean in 2002 year. annual mean pollutant load of COD, TN and TP were estimated 7.02 ton-COD/day, 4.06 ton-TN/day and 0.39 ton/day, respectively. Field observation of tidal current results usually show about $20{\sim}40cm/sec$ of current velocity at the surface layer, it indicated a tendency that the current velocity decreases under 20cm/sec as the water depth increases. We could find a stratification within approximately the depth of 30m in field observation area, and the depth increases. We could find a stratification within approximately the depth of 30m in field observation area, and the differences of water temperature and salinity between the surface layer and bottom layer were about $18^{\circ}C$ and 0.8 psu, respectively. On the other hand, we found that there was a definite as the water mass of deep sea water about 34 psu of salinity.

• 한국전산구조공학회논문집
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• 제27권4호
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• pp.305-312
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• 2014

콘크리트 깊은 보의 전단강도 산정을 위해 현행 미국콘크리트학회(ACI) 및 캐나다표준규격협회(CSA), 유럽콘크리트위원회(CEB-FIP)의 설계기준은 스트럿-타이 모델을 이용할 것을 제안하고 있지만 설계의 품질이 설계자가 구성한 트러스 모델 적합성에 크게 좌우된다는 특징을 가지고 있다. 따라서 본 논문에서는 내부 트러스 모델에 따른 현행 ACI, CSA 및 CEB-FIP의 콘크리트 깊은 보 설계기준의 타당성을 홍성걸 등에 의해 제안된 콘크리트 소성학에 근거한 전단강도식의 예측치와 비교함으로써 평가한다. 비교 결과 ACI, CSA 및 CEB-FIP의 스트럿-타이 모델에 의해 설계된 깊은 보의 경우 내부 트러스 모델이 전단강도 예측에 중요한 영향을 미치는 것으로 나타났으며 CEB-FIP의 경우 가장 높은 스트럿 강도 예측치를 보였다.

• 한국식품영양학회지
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• 제21권4호
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• pp.592-598
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• 2008

Deep sea water is found more than 200 m under the surface. As no sunlight reaches, no photosynthesis takes place, and it has very little organic matter or bacteria. In addition, deep sea water maintains a consistently low temperature throughout the year, and it does not mix with the water found closer to the surface, which means that its cleanliness is preserved. It is a long-term mature sea water resource that is rich in minerals. This paper examined the physical characteristics and the uses of deep sea water, a subject that has been attracting a great deal of public attention recently, together with the current status of domestic research into it and the direction of research in the USA and Japan, focusing on the existing literature. The aim of this paper was to provide are source to researchers in the field. Since the 1970s, scientists around the world have recognized the importance of deep sea water, and have been conducting research into it. In the USA, deep sea water has been researched with the view of its application to cooling, alternative energy, farming, and the development of new materials. In Japan, about 10 local self-governing bodies are currently promoting research and business relating to deep sea water, which has resulted in a number of products that have been released to the market. In Korea, the ministry of land transport and marine affairs has been studying deep sea water since 2000, and full-scale national R&D projects have been performed by 24 organizations, including KORDI, through industrial/academic cooperation. Large companies are participating in deep sea water research projects in several ways. A study of data foundusing NDSL relating to domestic studies of deep sea water found 50 theses, 177 domestic patents, 6 analyses, 2 reports, and 2 etc. in other areas.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.97-97
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• 2021

Hydrometeorological variables contain highly complex system for temporal revolution and it is quite challenging to illustrate the system with a temporal linear and nonlinear models. In recent years, deep learning algorithms have been developed and a number of studies has focused to model the complex hydrometeorological system with deep learning models. In the current study, we investigated the temporal structure inside deep learning models for the hydrometeorological variables such as streamflow and climate indices. The results present a quite striking such that each hidden unit of the deep learning model presents different dependence structure and when the number of hidden units meet a proper boundary, it reaches the best model performance. This indicates that the deep dependence structure of deep learning models can be used to model selection or investigating whether the constructed model setup present efficient or not.

• 대한소아치과학회지
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• 제51권1호
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• pp.1-10
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• 2024

Deep learning algorithms are becoming more prevalent in dental research because they are utilized in everyday activities. However, dental researchers and clinicians find it challenging to interpret deep learning studies. This review aimed to provide an overview of the general concept of deep learning and current deep learning research in dental radiographic image analysis. In addition, the process of implementing deep learning research is described. Deep-learning-based algorithmic models perform well in classification, object detection, and segmentation tasks, making it possible to automatically diagnose oral lesions and anatomical structures. The deep learning model can enhance the decision-making process for researchers and clinicians. This review may be useful to dental researchers who are currently evaluating and assessing deep learning studies in the field of dentistry.

• 대한조선학회논문집
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• 제56권6호
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• pp.473-479
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• 2019

Welding is one of the most popular joining methods and most welding quality estimation methods are executed using joined material. This paper propose welding quality estimation methods using dynamic current, voltage and resistance which are obtained during welding in real time. There are many kinds of welding method. Among them, we focused on the projection welding and gathered dynamic characteristics from two different types of projection welding. For image learning, graphs are drawn using obtained current, voltage and resistance, and the graphs are converted to images. The images are labeled with two sub-categories - normal and defect. For deep learning of images obtained from welding, Convolutional Neural Network (CNN) is applied, and Tensorflow was used as a framework for deep learning. With two resistance welding test datasets, we conclude that the Convolutional Neural Network helps in predicting the welding quality.

• Computers and Concrete
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• 제16권3호
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• pp.357-380
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• 2015

In this study, a simple indeterminate strut-tie model which reflects complicated characteristics of the ultimate structural behavior of continuous reinforced concrete deep beams was proposed. In addition, the load distribution ratio, defined as the fraction of applied load transferred by a vertical tie of truss load transfer mechanism, was proposed to help structural designers perform the analysis and design of continuous reinforced concrete deep beams by using the strut-tie model approaches of current design codes. In the determination of the load distribution ratio, a concept of balanced shear reinforcement ratio requiring a simultaneous failure of inclined concrete strut and vertical steel tie was introduced to ensure the ductile shear failure of reinforced concrete deep beams, and the primary design variables including the shear span-to-effective depth ratio, flexural reinforcement ratio, and compressive strength of concrete were reflected upon. To verify the appropriateness of the present study, the ultimate strength of 58 continuous reinforced concrete deep beams tested to shear failure was evaluated by the ACI 318M-11's strut-tie model approach associated with the presented indeterminate strut-tie model and load distribution ratio. The ultimate strength of the continuous deep beams was also estimated by the experimental shear equations, conventional design codes that were based on experimental and theoretical shear strength models, and current strut-tie model design codes. The validity of the proposed strut-tie model and load distribution ratio was examined through the comparison of the strength analysis results classified according to the primary design variables. The present study associated with the indeterminate strut-tie model and load distribution ratio evaluated the ultimate strength of the continuous deep beams fairly well compared with those by other approaches. In addition, the present approach reflected the effects of the primary design variables on the ultimate strength of the continuous deep beams consistently and reasonably. The present study may provide an opportunity to help structural designers conduct the rational and practical strut-tie model design of continuous deep beams.

• 한국해양공학회지
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• 제19권1호
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• pp.14-19
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• 2005

As a basic study for establishing the input conditions of a forecasting/estimating model, used for deep-sea water drainage to the ocean, this study was carried out as follows: 1) estimating the amount of river discharge and pollutant loads into the developing region of deep sea water in the East Sea, Korea, 2) a field observation of tidal current, vertical water temperature, and salinity distribution, 3) 3-D numerical experiment of tidal current to analyze the physical oceanographic status. The amount of river discharge flowing into this study area was estimated at about $462.7{\times}103 m\^3/day$ of daily mean in 2002. Annual mean pollutant load of COD, TN, and TP were estimated at 7.02 ton-COD/day, 4.06 ton-TN/day, and 0.39 ton/day, respectively. Field observation of tidal current normally shows 20-40cm/sec of current velocity at the surface layer, and it decreases under 20cm/sec as the water depth increases. We also found a stratification condition at around 30m water depth in the observation area. The differences in water temperature and salinity, between the surface layer and the bottom layer, were about 18 C and 0.8 psu, respectively. On the other hand, we found a definite trend of 34 psu salinity water mass in the deep sea region.

• 한국지구과학회지
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• 제23권3호
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• pp.259-269
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• 2002

북서태평양과 동해에서 채취된 4개의 코어는 퇴적구조, 생물교란정도와 내부침식면을 기준으로 과거 1만년 부근에서 상부와 하부로 구분된다. 특히, 시코쿠분지의 코어 KT94-10 상부퇴적물은 낮은 퇴적율, 높은 생물교란작용, 내부침식면, 사엽층리 등으로 특징지워지는데, 이러한 퇴적특징의 조합은 저탁류퇴적층이나 반원양성 퇴적물과는 다른 저층류퇴적물로 해석된다. 그러나 하부는 저층류의 영향을 받은 퇴적층이 관찰되지 않고, 생흔화석만 관찰되는 무구조 니질층의 특징을 보인다. 한편 동해 코어(95PC3)에서는 어떠한 저층류 관련 퇴적물도 관찰되지 않는다. 상부는 생물교란 니질층으로, 하부는 엽층리 니질층으로 구성되어 있으며 환원적 환경을 표시하는 황철석을 포함하고 있다. 결과적으로 북서태평양과 동해 코어의 퇴적특징은 심층류순환이 10,000년 전부터 빨라졌음을 표시하고 있다. 또 같은 시기일지라도, 심층수순환은 동해보다 북서태평양이 더 활발함을 보여주고 있다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 기술교육위원회 창립총회 및 학술대회 의료기기전시회
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• pp.52-59
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• 2001

The photoluminescence and the photo-current from p-type GaN films were investigated on both room- and low-temperatures for various Mg doping concentrations. At a low Mg doping level, there exists a photoluminescence center of the donor and the acceptor pair transition of the 3.28-eV band. This center is correlated with the defects for a shallow donor of the VGa and for an acceptor of MgGa. The acceptor level shows the binding energy of 0.2-0.25 eV, which was observed by the photon energy of the photo-current signal of 3.02-3.31 eV. At a high Mg doping level, there is a photoluminescence center of a deep donor and an acceptor pair transition of the 2.76-eV blue band. This center is attributed to the defect structures of MgGa-VN for the deep donor and MgGa for the acceptor. For low. doped samples, thermal annealing provides an additional photo-current signal for an unoccupied deep acceptor levels of 0.87-1.35 eV above valence band, indicating the p-type activation.