• Journal of agriculture & life science
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• v.44 no.2
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• pp.75-84
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• 2010

The growth of food industry has not increased the demand for domestically produced agricultural products as raw materials. This is because the prices of domestic agricultural products are expensive relative to the imported ones and domestic products are hard to be supplied consistently. Thus the connection between domestic agriculture and food industry must begin with the investigation of appropriate items that have potentials to be used as raw materials for food industry. There have been many policies that support regional agriculture such as the policy that fosters regional cluster for agriculture. These policies can contribute to instigate the connection between agriculture and food industry. The infra prepared by the supporting policies and the facilities that food companies are operating can be used together for both agriculture and food industry. The complementary utilizations of the infra and facilities may encourage the connection between agriculture and food industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.1-9
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• 2020

In highly complex EPC(engineering, procurement, construction)-based manufacturing processes such as shipbuilding and marine plants, it is essential to prepare a way to enable organic working at the site referring to each other's detailed working data for collaboration between partner companies. However, companies cannot share the progress of the sites including working information in real-time due to the use of SW unique to each company and the complex site management system. As a result, the construction process is delayed, and resources are used inefficiently. This study developed a neutral data generation algorithm that can apply the working information in various file formats to a collaborative manufacturing process. In addition, this study verified the accuracy of the algorithm by applying the developed algorithm to the manufacturing process of piping in shipbuilding and marine plants, developing the SW for visualization of working information using the generated neutral data, and comparing the coordinate, shape & dimension and the kind, number, and spec. of BOM. The result confirmed that the accuracy of the coordinate of the neutral data was 99%, and that of the shape & dimension of the neutral data and BOM Spec. was both 100%. It is thought that this study can be used for overcoming the restrictions in information sharing due to the development of informatization at companies and maximizing the share of working file information in a complex manufacturing process.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.346-355
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• 2020

This study proposed a new optimization-based decision model for an enterprise resource planning and production scheduling of a pharmaceutical intermediates manufacturing plant. To do this work, we first define the inflow and outflow information as well as the model structure, and develop an optimization model to minimize the production time (i.e., makespan) using a mixed integer linear programing (MILP). The unique feature of the proposed model is that the optimal process scheduling is established based on real-time resource logistics information using a radio frequency identification (RFID) technology, thereby theoretically requiring no material inventories. essential information for process operation, such as the required amount of raw materials and estimated arrival timing to manufacturing plant, is used as logistics constraints in the optimization model to yield the optimal manufacturing scheduling to satisfy final production demands. We illustrated the capability of the proposed decision model by applying the optimization model to two scheduling problems in a real pharmaceutical intermediates manufacturing process. As a result, the optimal production schedule and raw materials order timing were identified to minimize the makespan while satisfying all the product demands.

• Information Systems Review
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• v.16 no.3
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• pp.191-214
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• 2014

In this study, based on Privacy Calculus Model, we study whether users' intention of continuous use of closed-type SNS is affected by information privacy concern. In addition, we propose a model that studies if the major factors of the intention of continuous use which are trust, satisfaction and benefits could control the information privacy concern's effect on the intention of use. As a result, companies have to consider protecting the psychological privacy and information privacy of the individual when they design SNS.

• Journal of Life Science
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• v.33 no.6
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• pp.471-480
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• 2023

This study was designed to evaluate the anti-inflammatory effects of Rumohra adiantiformis extracts fermented with Bovista plumbea mycelium (B-RAE) in LPS-stimulated RAW 264.7 cells. The total polyphenol and total flavonoid content of B-RAE were 379.26±7.77 mg/g and 50.85±3.08 mg/g, respectively. The results of measuring the antioxidant activity of B-RAE showed that it scavenges 2, 2-diphenyl-1-picrylhydrazyl (DPPH), 2, 2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS), and superoxide anion radical in a dose-dependent manner. B-RAE inhibited nitric oxide (NO) production in a dose-dependent manner without affecting cell viability. The gene expression of pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-lβ (IL-1β), and IL-6 was measured using real time quantitative reverse transcription PCR (qRT-PCR). We found that, compared to the LPS-treated group, B-RAE significantly reduced the mRNA levels of the pro-inflammatory cytokines in a concentration-dependent manner. The expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), the phosphorylation of transcription factors such as nuclear factor-κB (NF-κB), and the mitogen-activated protein kinase (MAPK) signaling pathway proteins were assessed using Western blot analysis. We found that B-RAE significantly suppressed the expression of iNOS and COX-2, but their expression was increased by LPS treatment. In addition, the phosphorylation of NF-κB and IκB, which was increased by LPS treatment, was reduced with B-RAE treatment. The effect of B-RAE on the phosphorylation of the MAPK signaling pathway proteins was measured, and the phosphorylation of extracellular signal-regulated kinase (ERK) and the p38 MAPK proteins decreased in a dose-dependent manner, while the phosphorylation of c-Jun N-terminal kinase (JNK) increased. These anti-inflammatory effects of B-RAE may thus have been achieved through the high antioxidant activity, the inhibition of NO production through the suppression of iNOS and COX-2 expression, the inhibition of the NF-κB pathway, and the suppression of pro-inflammatory cytokine expression.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.466-466
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• 2017

지하공간의 개발과 지하공간의 굴착으로 인한 지표수 및 지하수 시스템의 변화나 굴착면 주위의 지하수 유동 체계의 변화는 터널내로의 지하수 유입, 지표수 고갈을 가져온다. 또한 터널 상부의 지반에서 현지응력의 변화로 인한 지하수 유출은 지표침하, 하천수 및 계곡수 고갈을 발생시킬 수 있다. 그러나, 터널설계 시 비용 및 시간, 현장의 진입조건 등의 제약으로 상세한 지반조사의 실시가 이루어지지 않을 때가 있다. 또한, 터널 공사가 진행되는 중에는 공사기간과 공사비 때문에 별도의 지반조사를 하지 않는다. 그 대신에 터널 막장에서 실시하는 Face Mapping을 토대로 공사를 진행하며, 대규모 위험요소가 발견되지 않는 이상 별도의 비용과 시간을 투입하여 추가 지질 및 지반 조사를 실시하는 경우는 매우 드물다. 연구지역의 지질은 경상분지내 백악기 하양층군의 퇴적암류, 이를 관입/분출한 불국사화강암류 및 제3기 화산암류, 전기 에오세 연일층군에 대비되는 퇴적암류로 구성되어 있다. 이들을 피복하는 제4기 충적 퇴적층은 주로 단층곡과 동측 지괴의 선상지 및 하천을 따라 분포한다. 연구지역에는 폭 100 m 이상의 대규모 단층대가 발달하였으며 제4기 단층운동으로 인한 단층파쇄대가 존재한다. 퇴적암 분포지역에서는 반복층서가 관찰되며 소규모 단층, 단열, 변형띠 등이 연속적으로 발달해 있다. 본 연구에서는 터널공사에 의한 지하수 변화를 확인하기 위하여 현장추적자 시험과 수질분석 및 지하수 모델링을 실시하였다. 현장 수질 분석에 의한 지표수와 지하수 간의 수질의 차이를 보면, 알칼리도를 제외한 대부분의 수질 항목이 서로 유사성을 보인다. 전기전도도(EC), TDS, 알칼리도의 경우 지표수의 수원지에서 터널 내부로 유입이 일어나고 있다. 이는 터널 공사의 영향으로 판단되며, 현장에서 실시한 추적자 시험에서는 추적자의 이동 시간이 매우 빨라 지표 수원지로부터 지표수가 터널내부로 빠른 속도(10시간 이내)로 유입된다고 판단된다. 지하수 모델링 결과, 정상류 상태에서는 지하수가 북동쪽의 높은 고도에서 서남쪽의 낮은 고도로 흐르는 것으로 확인되며, 가뭄시에도 지하수 함양으로 지하수가 고갈되지는 않는 것으로 나타났다. 부정류 상태 모델링 결과, 일일 평균 $32.49m^3$의 지하수가 터널 내부로 유입되는 것으로 산정되었다. 이 양은 터널 내부뿐만 아니라 터널 공사 현장 주위로도 지하수 유출이 일어나고 있음을 지시한다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.17-25
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• 2011

At the computer games, we can experience a variety of environments using a virtual object. It is similar to that be trained in War-game simulator of the defense. Actual soldiers and a computer-generated virtual group(Computer Generated Force: CGF) in 3-D virtual battlefield environment are training. However, path finding algorithm, one of the techniques of simulation models, to the current level only considers the shortest time path. So, this current level at the special situation of the army in the battlefield for selecting the optimal path is limited. The focus of this paper is to select the least-cost path using the deadline with several different mission conditions(METT+TC). For the only shortest time path algorithm and the least-cost path algorithm using dealine,($d_t$, one of METT+TC elements), Its usefulness is verifying the change of the move spent time(t) for all possible paths and the fighting power of the combat troops(Troops ability, a) through a comparison of the total cost of moves(c(t)). According to the results, when considering the deadline, the proposed algorithm saves about 62.5% of the maximum cost.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1022-1030
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• 2006

The location awareness is an important part of many ubiquitous computing systems, but a perfect location system does not exist yet in spite of many researches. Among various location tracking systems, we choose the RFID system due to its wide applications. However, the sensed RSSI signal is too sensitive to the direction of a RFID reader antenna, the orientation of a RFID tag, the human interference, and the propagation media situation. So, the existing location tracking method in spite of using the particle filter is not working well. To overcome this shortcoming, we suggest a robust location tracking method with a double layered structure, where the first layer coarsely estimates a tag's location in the block level using a regression technique or the SVM classifier and the second layer precisely computes the tag's location, velocity and direction using the particle filter technique. Its layered structure improves the location tracking performance by restricting the moving degree of hidden variables. Many extensive experiments show that the proposed location tracking method is so precise and robust to be a good choice for implementing the location estimation of a person or an object in the ubiquitous computing. We also validate the usefulness of the proposed location tracking method by implementing it for a real-time people monitoring system in a noisy and complicate workplace.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.159-159
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• 2017

스마트 시설환경은 대표적으로 원예, 축산 분야 등 여러 형태의 농업현장에 정보 통신 및 데이터 분석 기술을 도입하고 있는 시설화된 생산 환경이라 할 수 있다. 근래에 하드웨어적으로 급증한 스마트 시설환경에서 생산되는 방대한 생육/환경 데이터를 올바르고 적합하게 사용하기 위해서는 일반 산업 현장과는 차별화 된 분석기법이 요구된다고 할 수 있다. 소프트웨어 공학 분야에서 연구된 빅데이터 처리 기술을 기계적으로 농업 분야의 빅데이터에 적용하기에는 한계가 있을 수 있다. 시설환경 내/외부의 다양한 환경 변수는 시계열 데이터의 난해성, 비가역성, 불특정성, 비정형 패턴 등에 기인하여 예측 모델 연구가 매우 난해한 대상이기 때문이라 할 수 있다. 본 연구에서는 근래에 관심이 급증하고 있는 인공신경망 연구 소프트웨어인 Tensorflow (www.tensorflow.org)와 대표적인 Open source인 OpenNN (www.openn.net)을 스마트 시설환경 환경변수 상호간 상관성 분석에 응용하였다. 해당 소프트웨어 라이브러리의 운영환경을 살펴보면 Tensorflow 는 Linux(Ubuntu 16.04.4), Max OS X(EL capitan 10.11), Windows (x86 compatible)에서 활용가능하고, OpenNN은 별도의 운영환경에 대한 바이너리를 제공하지 않고 소스코드 전체를 제공하므로, 해당 운영환경에서 바이너리 컴파일 후 활용이 가능하다. 소프트웨어 개발 언어의 경우 Tensorflow는 python이 기본 언어이며 python(v2.7 or v3.N) 가상 환경 내에서 개발이 수행이 된다. 주의 깊게 살펴볼 부분은 이러한 개발 환경의 제약으로 인하여 Tensorflow의 주요한 장점 중에 하나인 고속 연산 기능 수행이 일부 운영 환경에 국한이 되어 제공이 된다는 점이다. GPU(Graphics Processing Unit)의 제공하는 하드웨어 가속기능은 Linux 운영체제에서 활용이 가능하다. 가상 개발 환경에 운영되는 한계로 인하여 실시간 정보 처리에는 한계가 따르므로 이에 대한 고려가 필요하다. 한편 근래(2017.03)에 공개된 Tensorflow API r1.0의 경우 python, C++, Java언어와 함께 Go라는 언어를 새로 지원하여 개발자의 활용 범위를 매우 높였다. OpenNN의 경우 C++ 언어를 기본으로 제공하며 C++ 컴파일러를 지원하는 임의의 개발 환경에서 모두 활용이 가능하다. 특징은 클러스터링 플랫폼과 연동을 통해 하드웨어 가속 기능의 부재를 일부 극복했다는 점이다. 상기 두 가지 패키지를 이용하여 2016년 2월부터 5월 까지 충북 음성군 소재 딸기 온실 내부에서 취득한 온도, 습도, 조도, CO2에 대하여 Large-scale linear model을 실험적(시간단위, 일단위, 주단위 분할)으로 적용하고, 인접한 세그먼트의 환경변수 예측 모델링을 수행하였다. 동일한 조건의 학습을 수행함에 있어, Tensorflow가 개발 소요 시간과 학습 실행 속도 측면에서 매우 우세하였다. OpenNN을 이용하여 대등한 성능을 보이기 위해선 병렬 클러스터링 기술을 활용해야 할 것이다. 오프라인 일괄(Offline batch)처리 방식의 한계가 있는 인공신경망 모델링 기법과 현장 보급이 불가능한 고성능 하드웨어 연산 장치에 대한 대안 마련을 위한 연구가 필요하다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.341-350
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• 2006

The sand table training is one of the most effective training method in military operations which can accomplish missions such as simulation and rehearsal without limitations related to time, space, money and so on. Previous sand table training has many problems like that the sand table cannot represent real field condition because of its physical properties. So, it is hard to be preserved and impossible to include much of information into them. In this paper, we make an approach based on Augmented Reality(AR) to solve these problems and propose an efficient military training briefing tool with virtual sand table environment described as actual battle field Virtual Tactical Map(VTM) can realize a virtual military training with simple action like moving marker or tangible interface by hand. Real-time state information of VTM gives us more organic intelligence for entire situation. Tangible AR interface provides users with a contents authoring tool that is natural, intuitive and easy to deal with as interaction between user in real world and system that augmented real world with virtual object. VTM is a newly designed military training briefing tools. A military training content can be reproduced and it is possible that user uses this content later. Thus, it shows us potential possibilities of AR applications on military leaning field.