• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.335-339
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• 2003

The estimation of seawater intrusion into deep aquifers has been becoming an important subject in terms of site characterization for geological disposal of radioactive waste. Conventional direct-current resistivity methods have been used for ground water explorations and recently have been applied to environmental problems. However, electromagnetic methods are more practical and useful for such a deep investigation. We consider audio-frequency magnetotelluric (AMT) and surface-to-borehole electromagnetic (EM) tomography methods as promising tools for the investigation of deep aquifer. These methods were tested in the Hasunuma area, Chiba Prefecture, Japan. Although the study area is in an urban area, high-quality AMT data were acquired, which was mainly accomplished by night-time data recording and remote-reference data processing. One-dimensional inversion results of the AMT data revealed two extremely conductive zones, which is consistent with the electrical conductivity profile of pore water in core samples. It can be interpreted as the seawater intrusions into both zones. However, the chemical analysis of the groundwater sampled in the deep zone suggests that this groundwater must be fossil seawater that had been confined during sedimentation processes. In addition, the permeability coefficient of the deep layer is very low. Thus the deep conductive zone corresponds to the fossil seawater regarded as being difficult to flow.

• 소성∙가공
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• 제24권1호
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• pp.5-12
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• 2015

In the current study, fundamental deep drawing characteristics of Ti-6Al-4V alloy sheets were investigated to establish the effect of processing conditions on large size square deep drawn cups. To accomplish this study, FE-simulations (Abaqus) were performed to determine optimum blank size, friction coefficient, the gap between punch and die, etc. The simulated processing parameters were verified experimentally. Based on the FE-simulation results, deep drawing was performed with various blank holding loads and sample sizes. In order to improve the formability of Ti-6Al-4V sheet, various lubricant methods were evaluated. Tensile tests and thickness measurements were conducted on the formed sheets. Processing parameters including blank holding force, lubricants, and optimum blank size, were selected to achieve improved drawing quality. With the optimum processing condition, a $200mm{\times}200mm$ cup was deep drawn successfully.

• 정보관리학회지
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• 제34권4호
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• pp.7-32
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• 2017

최근 들어 다양한 분야에서 딥러닝이 혁신적인 기계학습 기법으로 급속하게 확산되고 있다. 이 연구에서는 딥러닝 연구동향을 분석하기 위해서 자아 중심 주제 인용분석 기법을 변형하여 응용해보았다. 이를 위해 Web of Science에서 'deep learning'으로 탐색하여 검색된 문헌 중 소수의 씨앗 문헌으로부터 인용 관계를 통해 분석 대상 문헌을 확보하는 방법을 시도하였다. 씨앗 문헌을 인용하는 최근 논문들을 딥러닝 분야의 현행 연구를 반영하는 자아 문헌집합으로 설정하였다. 자아 문헌으로부터 빈번히 인용된 선행 연구들은 딥러닝 분야의 연구 주제를 나타내는 인용 정체성 문헌집합으로 설정하였다. 자아 문헌집합에 대해서는 공저 네트워크 분석을 비롯한 정량적 분석을 실시하여 주요 국가와 연구 기관을 파악하였다. 인용 정체성 문헌들에 대해서는 동시인용 분석을 실시하고, 도출된 문헌 군집을 인용하는 주요 키워드인 인용 이미지 키워드를 파악하여 주요 문헌과 주요 연구 주제를 밝혀내었다. 마지막으로 특정 주제에 대한 인용 영향력이 성장하는 추세를 반영하는 인용 성장지수 CGI를 제안하고 측정하여 딥러닝 분야의 선도 연구 주제가 변화하는 동향을 밝혔다.

• 한국식품영양학회지
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• 제22권2호
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• pp.261-271
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• 2009

Deep sea water exists at depths of over 200m under the sea. As no sunlight reaches it, photosynthesis does not take place within it, and it contains no organic matter. In addition, its temperature is maintained at a stable low level throughout the year, so it does not get mixed with the sea water on the surface. It contains a large amount of nutritious salts, whose cleanness is maintained. It is a marine resource that has matured for a long period of time. Research into deep sea water, which started in the 1970s, has been made around the whole world, including the USA and Japan. In Korea, research has been active in this area since 2000. As there has been a good amount of research into industrial applications for deep sea water, since 1993, patents for the relevant technologies have been applied. This paper intends to provide a resource to researchers of deep sea water, by summarizing of all domestic deep sea water-related patents applied with Korean Intellectual Property Office from 1993 to 2008. This research was conducted using a computer and KIPRIS Database owned by the Korea Institute of Patent Information. 'Deep sea water' was used as the search keyword. A total of 222 Korean patents relating to deep sea water have been registered on the basis of IPC. Of these, 126 patents relate to the manufacturing and the treatment of foods, foodstuffs, or non-alcoholic beverages(A23L), while 50 patents relate to the production for medical, dental, or cosmetic purposes(A61K). 38 patents relate to water purification, treatment of wastewater, sewage and sludge (C02F), while 8 patents relate to fishery and farming(A01K). In summary, it was found that studies for the practical use of deep sea water have been conducted in relation to the manufacturing and the treatment of foods, foodstuffs, beverages, and cosmetics.

• 한국해양공학회지
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• 제26권1호
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• pp.78-83
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• 2012

The abundant nutrients contained in deep seawater are delivered by natural upwellings from the deep sea to the surface sea. However, the natural upwelling phenomenon is limited to specific areas of the sea; in other areas, the thermocline separates the surface sea from the lower layer. Thus, the surface layer is often deficient in nutritive salts, causing the deterioration of its primary productivity and ultimately leading to an imbalance in the marine ecosystem. Without a consistent supply of nitrogenous nutritive salts, they are absorbed by phytoplankton, resulting in a considerable problem in primary productivity. To solve this issue, a floating type of artificial upwelling system is suggested to artificially pump up, distribute, and diffuse deep seawater containing rich nutritive salts. The key technologies for developing such a floating artificial upwelling system are a floating offshore structure with a large diameter riser, self-supplying energy system, density current generating system, method for estimating the emission and absorption of CO2, and way to evaluate the primary production variation. Strengthening the primary production of the sea by supplying deep seawater to the sea surface will result in a sea environment with abundant fishery resources.

• E2M - 전기 전자와 첨단 소재
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• 제8권4호
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• pp.426-433
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• 1995

Effect of boron in GaAs have been investigated by photo induced current transient spectroscopy(PICTS). The starting material was undoped liquid encapsulated Czochralski(LEC) semi insulating GaAs and boron ion implantation at 150keV energy was conducted with dose of 10$\^$12/ and 10$\^$13/ions/cm$\^$2/. In ion implanted samples, the peaks related arsenic vacancy(V$\_$As/) were decreased but complex lattice defect was increased with annealing temperature. U band was observed at ion implanted(10$\^$13/ ions/cm$\^$2/) and thermally treated(550.deg. C) sample. More negative peak was detected after annealing at temperature between 600 and 700.deg. C. The measurement of dark current showed that the formation of B$\_$GA/-V$\_$As/, complex defect and complex lattice defect by ion implantation were a reasonable explanation for the decrease in dark current.

• 한국정보전자통신기술학회논문지
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• 제11권5호
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• pp.521-530
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• 2018

본 논문에서 제안하는 "농산물 생산성 향상을 위한 딥러닝 기반 농업 의사결정 시스템"에서는 정밀농업을 지원하는 농장의 위치 정보를 기반으로 기상 정보를 수집하고, 수집한 기상 정보와 농작물의 실시간 데이터를 이용하여, 작물의 현재 상태를 예측하고 그 결과를 농장 관리인에게 알려준다. 제안하는 시스템은 첫째, 정밀농업을 지원하는 농장의 위치 정보를 기반으로 기상 정보를 수집하는 ICM(Information Collection System)을 설계하고, 둘째, 딥러닝 알고리즘을 기반으로 현재 날씨에 따라 농장 토지의 탄소, 수소, 산소, 질소, 수분 함유량이 재배하고 있는 작물에 적합특정 작물을 재배하기 좋은 상태인지 판단하는 DRCM(Deep learning based Risk Calculation Module)을 설계하고, 셋째, DRCM의 결과를 기반으로 사용자에게 작물의 상태를 점검할 것을 알려주는 메시지를 전송하는 RNM(Risk Notification Module)을 설계한다. 제안하는 시스템은 기존의 시스템과 비교하였을 때, 데이터양의 증가로 인해 발생하는 정확도 감소 비율이 낮고, 분석 단계에 비지도학습을 적용하기 때문에 안정성을 향상 시킬 수 있다. 결과적으로 농장 데이터 분석 성공률이 약 5.15%가량 향상되었고, 환경 변화에 따른 작물 성장의 위험한 상태정보 다양하게 적용하였을 때, 위험한 상태정보에 대하여 상세하게 추론할 수 있었다. 이는 다양한 내 외부 환경으로부터 발생할 수 있는 작물의 질병을 미연에 예방할 수 있고, 작물이 성장하는데 최적화된 환경을 제공할 수 있는 효과를 나타낸다.

• East Asian Economic Review
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• 제16권4호
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• pp.363-394
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• 2012

WTO Government Procurement Agreement (GPA) was designed to liberalize and expand trade in government procurement. Revised GPA was implemented in 1996 and the latest revision was completed (but not yet implemented) in 2012, but as a plurilateral agreement. Since the end of the UR, there has been attempts by various WTO members to liberalize trade in the government procurement market - through an expansion of Parties who are signatories to GPA, and through a negotiated agreement on transparency in government procurement. The attempt to expand the Parties who are signatories to the GPA - attempt to increase the width of the coverage of the agreement - has been somewhat successful, but I argue that the goal should be to further liberate the government procurement markets of the current Party members - to reduce thresholds and other barriers which limit market access even to other GPA members, in other words, to increase the depth of coverage. Taking cue from Korea's FTA, I propose a two-level liberalization of the government procurement market under the GPA: A "light" level which would be the same as the current level of liberalization; and a "deep" level with lower thresholds and less exemptions. I argue that, as seen in Korea, with FTAs, many GPA Parties already have multiple levels of liberalization (i.e, spaghetti-bowl effect of FTAs), but by limiting the levels of liberalization to two, we can seek the best of deep liberalization but reduce the spaghetti-bowl effect.

• 한국융합학회논문지
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• 제10권6호
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• pp.235-242
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• 2019

최근 딥러닝을 비롯한 인공지능 기술의 활용이 다양한 분야에서 활발해지고 있으며, 특히 딥러닝 기술 기반의 객체 인식 및 검출에 뛰어난 성능을 보이는 여러 알고리즘들이 발표되고 있다. 이에 본 논문에서는 사용자의 편의성이 효과적으로 반영된 모바일 헬스케어 애플리케이션 구현에 대한 적절한 방향성을 제시하고자 한다. 기존의 피트니스 애플리케이션들에 대한 이용 만족도 연구 및 모바일 헬스케어 애플리케이션에 대한 현황을 파악하여, 이로부터 피트니스 애플리케이션 시장에서의 생존과 우위를 확보하는 동시에, 최근 주목 받고 있는 인공지능 기술의 효과적인 적용에 의한 성능 개선을 통해 기존 이용자 유지 및 확대를 도모하고자 한다.

• 전력전자학회논문지
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• 제26권1호
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• pp.1-8
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• 2021

For the safe and reliable operation of lithium-ion batteries in electric vehicles or energy storage systems, having accurate information of the battery, such as the state of charge (SOC), is essential. Many different techniques of battery SOC estimation have been developed, such as the Kalman filter. However, when this filter is applied to multiple batteries, it has difficulty maintaining the accuracy of the estimation over all cells owing to the difference in parameter values of each cell. The difference in the parameter of each cell may increase as the operation time accumulates due to aging. In this paper, a novel deep neural network (DNN)-based SOC estimation method for multi-cell application is proposed. In the proposed method, DNN is implemented to determine the nonlinear relationships of the voltage and current at different SOCs and temperatures. In the training, the voltage and current data obtained at different temperatures during charge/discharge cycles are used. After the comprehensive training with the data obtained from the cycle test with a cell, the resulting algorithm is applied to estimate the SOC of other cells. Experimental results show that the mean absolute error of the estimation is 1.213% at 25℃ with the proposed DNN-based SOC estimation method.