• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권10호
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• pp.329-336
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• 2014

플랜트 공사 현장에서 파이프 스풀은 플랜트 설비의 가장 중요한 요소이다. 현재 플랜트 공사장에서 파이프 스풀 관리는 수기 작성을 통해 적재 위치 및 작업 내역을 관리하고 있다. 그러나 현재 현장에서는 작업자의 임의적인 파이프 스풀의 이동과 제작 또는 설치해야 할 파이프 스풀을 찾지 못했을 경우 비슷한 파이프 스풀을 가지고 와 다시 제작하는 현상이 발생하고 있다. 이에 파이프 스풀의 위치를 정확하게 알 수 없기 때문에 파이프 스풀을 찾기 위한 인건비와 시간이 소요되며, 분실에 대한 관리가 되지 않는 상황이다. 이에 파이프 스풀에 UHF RFID 태그를 부착하고 차량에 UHF RFID 리더 및 안테나를 장착하여 파이프 스풀의 위치를 찾을 수 있는 시스템을 제안한다. 제안된 시스템을 활용하여 현장 테스트를 진행한 결과 98% 이상의 위치 정보 인식이 가능했으며, 손실된 2%의 미 인식 태그는 작업자에 의한 보정을 통해 100%의 관리가 가능함을 확인할 수 있었다. 향후 제안된 시스템 도입으로 인건비와 분실 파이프에 대한 관리가 원활하게 이루어질 뿐만 아니라 특정 공간에 적재되어있는 물품관리에도 활용될 것으로 전망한다.

• 화훼연구
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• 제18권4호
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• pp.256-260
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• 2010

본 연구는 직삽 양액재배에 의한 '신마'품종의 절화품질 향상시키고자 양액 pH조정 비료종류와 모수포 관리 및 지베렐린처리 효과를 알아보기 위해 실시하였다. 모수포 관리에 따른 절화장은 무처리(관행) 103 cm에 비해 모수포관리(온도,일장) 처리가 114 cm로 가장 컸고, 꽃잎수도 무처리(관행) 259개/송이에 비해 모수포관리(온도, 일장) 처리가 298개로 가장 많았고, 절화중은 모수포관리(온도,일장) 처리가 102g/본 가장 무겁게 나타났다. 엽록소(SPAD-value)는 영양관리(몰비아 500배)처리가 57.2로 가장 높게 나타났다. 지베렐린처리 농도와 살포시기에 따른 절화장은 무처리(관행) 103 cm에 비해 지베렐린 1,000배 개화 60일전 처리가 121 cm로 가장 컸고, 꽃잎수도 무처리(관행) 259개/송이에 비해 지베렐린 500배로 개화60일전 처리가 308개로 가장 많았고, 절화중은 2,000배 개화60일전 처리가 110.7 g/본 가장 무겁게 나타났다. 하지만 꽃목길이는 관행(무처리) 3.5 cm에 비해 500배 개화45일전 처리 10.4 cm와 1,000배 개화45일전 처리가 9.7 cm로 도장하는 경향이었다.

• Journal of Forest and Environmental Science
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• 제36권2호
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• pp.91-112
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• 2020

In Ethiopia, dry land vegetation including the fairly intact lowland and western escarpment woodlands occupy the largest vegetation resource of the country. These forests play a central role in environmental regulation and socio-economic assets, yet they received less scientific attention than the moist forests. This study evaluated the woody plant species composition, population structure and carbon sequestration potential of the A. senegal woodland across three distance gradients from the settlements. A total of 45 sample quadrants were laid along a systematically established nine parallel transect lines to collect vegetation and soil data across distance gradients from settlement. Mature tree dry biomass with DBH>2.5 cm was estimated using allometric equations. A total of 41 woody plant species that belong to 20 families were recorded and A. senegal was the dominant species with 56.4 IVI value. Woody plant species diversity, density and richness were significantly higher in the distant plots compared to the nearest plots to settlement (p<0.05). The cumulative DBH class distribution of all individuals had showed an interrupted inverted J-shape population pattern. There were 19 species without seedlings, 15 species without saplings and 14 species without both seedlings and saplings. A significant above ground carbon (5.3 to 12.7 ton ha^-1), root carbon (1.6 to 3.6 ton ha^-1), soil organic carbon (35.6 to 44.5 ton ha^-1), total carbon stock (42.5 to 60.7 ton ha^-1) and total carbon dioxide equivalent (157.7 to 222.8 ton ha^-1) was observed consistently with an increasing of distance from settlement (p<0.05). Distance from settlement had significant and positive correlation with species diversity and carbon stock at 0.64^⁎⁎ and 0.78^⁎⁎. Disturbance intensity may directly influence the variation of species composition, richness and density along the A. senegal woodland. The sustainability of the A. senegal woodland needs urgent protection, conservation and restoration.

• The Plant Pathology Journal
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• 제21권4호
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• pp.369-376
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• 2005

Turnip mosaic virus (TuMV) is an infectious viral pathogen on the cruciferous crops, predominantly Chinese cabbage (Brassica campestris subsp. pekinensis) and radish (Raphanus sativus). On the basis of the symptom development in selective differential hosts from indicator host species, Chinese cabbage and Korean radish inbred lines, the representative eight isolates of TuMV were divided into two major groups/or six types. Group I includes Th 1, Ca-ad7, and Cj-ca2-1 isolates, while group II includes the other isolates (rg-pfl, r 9-10, Rhcql-2, Stock and Mustard). According to the molecular phylogenetic analysis, these isolates, however, divided into two groups and two independent isolates. Phylogenetic analysis indicated that four isolates (Tu 1, r9-10, Stock and Rh-cql-2) formed a distinct phylogenetic group, and the other two isolates (Ca-ad7 and Cj-ca2-1) also formed another group. Mustard and rg-pfl isolates did not seem to have any relationship with these two groups. Taken together, these results indicated that virulence differentiation on host plants, molecular phylogenetic analysis of the nucleotide and the deduced amino acid of TuMV coat proteins did not show any relationship. The multi-resistant lines, Wonyae 20026 and BP058 in Chinese cabbage represent valuable genetic materials that can be used for crucifer breeding programs on TuMV resistance, but not in Korean radish.

• 한국정보처리학회논문지
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• 제6권9호
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• pp.2281-2293
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• 1999

원전 감시, 공정 제어, 주식 시장 관리 및 통신 데이터 관리 등은 시간 개념을 갖는 데이터의 관리와 효율적인 데이터 처리를 위한 능동적 규칙 처리 기능을 동시에 필요로 한다. 그 동안 능동 데이터베이스 시스템에 시간 개념 지원을 확장하려는 연구소들은 다소 있었지만 시간지원 데이터베이스를 바탕으로 한 능동 데이터베이스에 관한 연구는 아직 많지 않다. 더욱이 실제 응용분야에 적용시키려는 노력은 찾아보기 어렵다. 이 논문은 이원시간지원 데이터베이스에 바탕을 둔 능동적 시간지원 데이터베이스 시스템에서의 능동적 시간지원 규칙 모델을 제시하였다. 아울러 제시된 규칙모델에 의한 규칙언어와 실행의미를 설명하고 원전 감시 시스템에 대한 적용 예를 보여주었다.

• Industrial Engineering and Management Systems
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• 제9권4호
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• pp.303-311
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• 2010

In the last few years growing interest has been dedicated to supply chain management. Modeling complexity is added to supply chain coordination problem by accounting for reverse logistics activities. The objective of this paper is to extend inventory model of manufacturing factory with respect to the production of raw material of forward logistics and recycling material of reverse logistics. The proposed model is applied to a plastic recycling process plant located in Taiwan. The case study improvement scheme shows when the recycling rate of recycling material increases from 15% to 50%, the total inventory cost of manufacturing factory decreases by 12.82%, safety stock volume decreases by 41.19% and the reorder quantity is down by 50.96%. This paper finds whether the results of the model can reach the economic profit through quantitative analysis and encourages companies integrate reverse logistics into the supply chain system.

• The Plant Pathology Journal
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• 제18권5호
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• pp.284-287
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• 2002

The antifungal activity of super reductive water (SRW) against plant pathogenic fungi was examined to extend its application to integrated pest management (IPM) for plant diseases. Diluted solutions ($\times$1/10, $\times$1/25, and $\times$1/50) of SRW inhibited fungal growth of kiwifruit soft rot pathogen, Diaporthe actinidiae, in a concentration dependent manner, When kiwifruits were inoculated on wounds with mycelium blocks, stock and diluted solutions successfully inhibited the disease development. In addition to the high pH of the SRW, fungistatic activity was also considered as the cause of the antifungal effect against the pathogen. Whereas conidial germination of Magnaporthe grisea was not affected by the diluted SRW solutions, appressorium formation was significantly inhibited in a concentration dependent manner, With little harmfulness to human health and environment SRW could be used to control plant pathogenic fungi, particularly appressorium-forming fungal pathogens.

• 한국경영과학회지
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• 제1권1호
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• 한국건설관리학회논문집
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• 제25권5호
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• pp.41-54
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• 2024

본 연구에서는 프리캐스트 콘크리트(Precast Concrete; PC) 제작공장의 원자재 재고관리를 위한 세 가지 재고관리 정책, 정량 발주 방식, 정기 발주 방식, (s, S) 발주 방식의 성능을 비교·분석한다. 보다 현실적인 결론의 도출을 위해, 복수 원자재를 사용하는 PC 제작공장의 전체 공정을 대상으로 원자재 수요 및 공급 측면의 변동성을 고려하여 개발된 성능평가 도구인 ARENA 시뮬레이션 모델을 활용하였다, 성능 비교를 위해, 먼저 세 가지 재고관리 정책에 대해 경제적주문량(Economic Order Quantity; EOQ)을 초깃값으로 하여 OptQuest를 통해 재주문점, 주문량, 목표수준 및 주문주기 모수를 최적화하였다. 최적화 결과, 수요 및 공급 측면의 변동성을 고려하지 않는 EOQ 방식에 비해 재고관리 비용을 평균 97.28% 감소시킬 수 있었다. 이후, 프로젝트 발생 주기, 원자재 조달기간, 단위 품절비용 등 세 가지 영향 요인을 설정한 후 세 가지 재고관리 정책에 대한 성능 비교 실험을 수행하였다. 실험 결과, 실시간 또는 매일 재고수준을 파악하여 주문 시점을 결정하는 정량 발주 방식과 (s, S) 발주 방식의 재고관리 비용이 고정 주문주기를 갖는 정기 발주 방식보다 각각 30.6%와 27.9% 낮게 나타났다. 또한, 재고관리 비용은 프로젝트 발생 주기를 제외한 원자재 조달기간과 단위 품절 비용 요인에 의해 영향을 받는 것으로 나타났지만, 그 차이는 2.17%와 2.09%로 수요 및 공급의 변동성 대응을 위한 모수 최적화 과정으로 인해 크지 않았다.

• 대한산업공학회지
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• 제39권1호
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.