• Journal of the Korea Institute of Building Construction
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• v.12 no.6
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• pp.648-663
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• 2012

With recent attempts to improve quality and productivity, the prefabrication manufacturing system has been occupying an increasing share of the construction area. To minimize site work, material is more frequently being produced and partially assembled at a plant, and then installed at a site. For this reason, the production process is being divided and the materials are being delivered to the site after passing through multiple plants. With these changes in the production process, the materials delivery plan is becoming an important management point. In particular, as road transportation using trucks has a 71 percent share of the domestic transportation market, selecting the proper transportation path is important when delivering materials and equipment to a site. But the management system at the project design phase to calculate the delivery cost by considering the production process of the pre-fab material and the $CO_2$ emission at the material delivery phase is currently lacking. This study suggests a process design model for assembly production of the pre-fab material and transportation logistics based on carbon emission. The suggested model can be helpful to optimize the location of the intermediate plant. It is expected to be utilized as a basic model at the project plan and design phase when subcontractors make decisions on items such as materials procurement, selecting the production method, and choosing the location of the assembly plant.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.101-113
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• 1995

The past three decades have witnessed a tremendous growth is the literature on location proble. A mathematical formulation of uncapacitated plant location problem and the k-median as an integer program has proven very fruitful in the derivation of solution methods. Most of the successful algorithms for the problem are based on so-called "strong" linear programming relaxation. This is due to the fact that the strong linear programming relaxation provides a tight lower bound. In this paper we investigate the phenomenon with a structural analysis of the problem.e problem.

• Korean Journal of Plant Taxonomy
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• v.49 no.4
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• pp.380-384
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• 2019

A newly naturalized plant, Viola palmata L., was found in Uljin-gun, Changwon-si, and Yangsan-si. It belongs to the subsect. Boreali-Americanae (W. Becker) Gil-Ad of the sect. Nosphinium W. Becker, which is known to be from North America, with subsequent introduction into Europe. In Korea, this species is considered to have been introduced by freight transportation through the port of Busan, after which its distribution area expanded. We propose the new Korean name 'Chang-won-je-bi-kkot' based on the location at which it was initially collected in Korea. We also provide descriptions of the morphological characters along with photographs, illustrations, and a distribution map of Viola palmata.

• Journal of Plant Biotechnology
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• v.2 no.2
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• pp.89-96
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• 2000

For large DNA fragment transformation in dicots and monocots, BIBAC2 vector system was applied to Arabidopsis thaliana and Oryza sativa L. cv. Jinmi as a model plant, respectively. For Arabidopsis, the Th1 gene in T23L3 BAC clone whose size is about 90 kb was used as the target gene source for transformation. Because T23L3 BAC clone was originally constructed in pBelloBAC11, the target gene was reconstructed into BIBAC2. As the results of reconstruction, 476 colonies were survived in selection medium containing 40 mg/L kanamycin. In colony hybridization analysis, 24 out of 476 colonies exhibited positive signals. In the pulsed-field gel electrophoresis analysis, 11 out of 24 positive clones exhibited the band at the location of 90 kb. In Southern hybridization, positive signal band at the location of 90 kb was observed in all 11 transformants. Using these verified clones, Agrobacterium-mediated transformation was applied to Arabidopsis thaliana th1-201 mutant for genetic complementation test. Twelve thousands T$_1$ seeds were harvested, and antibiotic selection test is being analyzed to verify whether these seeds were transformed. for rice, COR356 that contains 150 kb human genomic DNA in a BIBAC2 vector was used as the target gene. As the results of transformation, 151 out of 210 co-cultivated calli were survived in selection medium containing 5 mg/L hygromycin, and 45 out of 151 survived calli were regenerated into plants. Transformation efficiency was 21.6%. Progeny test using 71 seeds is being analyzed now. These results provide the potential that large DNA fragments can be transferred into both dicots and monocot by Agrobacterium-mediate d transformation system.

• The Plant Pathology Journal
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• v.39 no.4
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• pp.319-334
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• 2023

Plant disease is an important factor affecting crop yield. With various types and complex conditions, plant diseases cause serious economic losses, as well as modern agriculture constraints. Hence, rapid, accurate, and early identification of crop diseases is of great significance. Recent developments in deep learning, especially convolutional neural network (CNN), have shown impressive performance in plant disease classification. However, most of the existing datasets for plant disease classification are a single background environment rather than a real field environment. In addition, the classification can only obtain the category of a single disease and fail to obtain the location of multiple different diseases, which limits the practical application. Therefore, the object detection method based on CNN can overcome these shortcomings and has broad application prospects. In this study, an annotated apple leaf disease dataset in a real field environment was first constructed to compensate for the lack of existing datasets. Moreover, the Faster R-CNN and YOLOv3 architectures were trained to detect apple leaf diseases in our dataset. Finally, comparative experiments were conducted and a variety of evaluation indicators were analyzed. The experimental results demonstrate that deep learning algorithms represented by YOLOv3 and Faster R-CNN are feasible for plant disease detection and have their own strong points and weaknesses.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.144-156
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• 2018

Level 3 Probabilistic Safety Assessment (PSA) is performed for the risk assessment that calculates radioactive material dispersion to the environment. This risk assessment is performed with a tool of MELCOR Accident Consequence Code System (MACCS2 or WinMACCS). For the off-site consequence analysis of multi-unit nuclear power plant (NPP) accident, the single location (Center Of Mass, COM) method has been usually adopted with the assumption that all the NPPs in the nuclear site are located at the same COM point. It was well known that this COM calculation can lead to underestimated or overestimated radionuclide concentration. In order to overcome this underestimation or overestimation of radionuclide concentrations in the COM method, Multiple Location (ML) method was developed in this study. The radionuclide concentrations for the individual NPPs are separately calculated, and they are summed at every location in the nuclear site by the post-processing of radionuclide concentrations that is based on two-dimensional Gaussian Plume equations. In order to demonstrate the efficiency of the ML method, radionuclide concentrations were calculated for the six-unit NPP site, radionuclide concentrations of the ML method were compared with those by COM method. This comparison was performed for conditions of constant weather, yearly weather in Korea, and four seasons, and the results were discussed. This new ML method (1) improves accuracy of radionuclide concentrations when multi-unit NPP accident occurs, (2) calculates realistic atmospheric dispersion of radionuclides under various weather conditions, and finally (3) supports off-site emergency plan optimization. It is recommended that this new method be applied to the risk assessment of multi-unit NPP accident. This new method drastically improves the accuracy of radionuclide concentrations at the locations adjacent to or very close to NPPs. This ML method has a great strength over the COM method when people live near nuclear site, since it provides accurate radionuclide concentrations or radiation doses.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.295-300
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• 1998

In this paper, a real time diagnostic algorithm fur estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. When the decision from ADM is concluded as the impact signal, the beginning time of burst-type signal, which the impact signal has usually such a form in time domain, provides the necessary data fur IEM. IEM by use of the arrival time method estimates the impact location of loose parts. The overall results of the estimated impact location are displayed on a computer monitor by the graphical mode and numerical data composed of the impact point, and thereby a plant operator can recognize easily the status of the impact event. This algorithm can perform the diagnosis process automatically and hence the operator's burden and the possible operator's error due to lack of expert knowledge of impact signals can be reduced remarkably. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

• Mycobiology
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• v.31 no.1
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• pp.9-18
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• 2003

A total of 82 genera and 271 species of soil-inhabiting fungi including saprobic, nematode-trapping, and arbuscular mycorrhizal but plant pathogenic fungi published hitherto in South Korea are listed with the information on geographic location, habitat, vegetation when available, and relevant literatures.

• Management Science and Financial Engineering
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• v.5 no.2
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• pp.25-41
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• 1999

This paper generalizes the classic two-stage multicommodity distribution system design problem to the one that includes plant locations as well as distribution center locations. Accommodating plant location leads to subproblems which are mixed are mixed integer. Hence. no LP-type subproblems are avail-able, and therefore standard Benders decomposition no longer applies. We develop new solution method which combines an integer L-shaped method with Benders decomposition to suit the purpose, and pre-sent the test results.

• Korean Journal of Plant Resources
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• v.32 no.5
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• pp.463-470
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• 2019

Wild-simulated ginseng is requires standard establishment on location environment for long-term and eco-friendly cultivation. The this study was carried out to investigate the correlation between growth characteristics and location environment of wild-simulated ginseng for selection of suitable cultivation area. Samples were collected from a 9 site of wild-simulated cultivation area and examined growth characteristics and location environment. Correlation coefficient between growth characteristics and location environment was analyzed using Spearman's rank correlation. The growth of wild-simulated ginseng was shown significantly higher in Geochang and Hamyang cultivation area. The results of correlation analysis was shown significantly correlation with percentage of conifer, total diameter at breast height, soil pH, K, Ca and Mg. The results of this study was clearly investigated the correlation between growth characteristics and location environment of wild-simulated ginseng, which is considered to will provide understanding for selection suitable cultivation area of wild-simulated ginseng.