• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.773-777
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• 2009

In recent years, the field of synthesizing voice has been developed rapidly, and the technologies such as reading aloud an email or sound guidance of a car navigation system are used in various scenes of our life. The sound quality is monotonous like reading news. It is preferable for a text such as a novel to be read by the voice that expresses emotions wealthily. Therefore, we have been trying to develop a system reading aloud novels automatically that are expressed clear emotions comparatively such as juvenile literature. At first it is necessary to identify emotions expressed in a sentence in texts in order to make a computer read texts with an emotionally expressive voice. A method on the basis of the meaning interpretation that utilized artificial intelligence technology for a method to specify emotions of texts is thought, but it is very difficult with the current technology. Therefore, we propose a method to determine only emotion every sentence in a novel by a simpler way. This method determines the emotion of a sentence according to an emotion that words such as a verb in a Japanese verb sentence, and an adjective and an adverb in a adjective sentence, have. The emotional characteristics that these words have are prepared beforehand as a emotional words dictionary by us. The emotions used here are seven types: "joy," "sorrow," "anger," "surprise," "terror," "aversion" or "neutral."

• The Korean Journal of Mycology
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• v.31 no.2
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• pp.117-119
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• 2003

A stem rot of eggplant (Solanum melongena) was found in experimental field of Gyeongsangnam-do Agricultural Research and Extension Services, Korea. The typical symptoms of the disease were stem rot, crown rot, wilt or blight. Upper parts of the infected stems were mostly blighted and white turf of fungal mycelium mats was spread over lesions. Sclerotia were farmed on the stems near soil line. The sclerotia of the fungus eadily were produced in artificial media such as PDA at $30^{\circ}C$. The sclerotia were globoid, $1.0{\sim}3.4mm$ in diameter and brown in color. The optimum temperature for growth of the fungus was about $30^{\circ}C$. The typical clamp connections were found in the hypha formed on PDA, and was $3.8{\sim}10.6{\mu}m$ in size. On the basis of mycological characteristics and pathogenecity test, the fungus was identified as Sclerotium rolfsii. This is the first report of stem rot of eggplant caused by Sclerotium rolfsii in Korea.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2009.04a
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• pp.295-303
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• 2009

The annals of Joseon dynasty, especially the volumes of King SeJong(1418-1450 A.D.), were heavily deteriorated by fungi. Investigations on the deteriorating and foxing fungi were carried out. Fungal structures on the beeswax, which were coated on the both side of Han-Ji, were suspected to be involved in the deterioration, and were observed by SEM. Isolation and culturing of these fungi were tried by scrubing swab samples and placing on the artificial media. Culture-independent approaches were used to identify the fungal strains associated with damages of beeswax and foxing of the paper by the analyses based on DNA sequences data from the specific ITS region of rDNA regions. In addition, well-known paper staining fungi(PSF), i.e., Aspergillus terreus var. terreus, Fusarium oxysporum, Chaetomium globosum, Cladosporium cladosporioides, and Alternaria solani, were compared in the mycelial growth and stain on beeswax and papers under different environmental conditions (temperature, light, moisture, etc). Fungal strains isolated from the air samples in the storage room and shelves were identified as Irpex sp., Arthrinium sacchari, Cladosporium tenuissimum, Aspergillus sclerotiorum, Sistotrema brinkmannii, and Hypoxylon bovei var. microsporum The isolated strains were compared in growth and stain patterns on beeswax and papers(Han-Ji, Hwa-Ji, and Yang-Ji) whether these can cause damage or foxing on the annals or not.

• Plant Biotechnology Reports
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• v.3 no.4
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• pp.277-283
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• 2009

One of the limitations to conducting maize Agrobacterium-mediated transformation using explants of immature zygotic embryos routinely is the availability of the explants. To produce immature embryos routinely and continuously requires a well-equipped greenhouse and laborious artificial pollination. To overcome this limitation, an Agrobacterium-mediated transformation system using explants of type II embryogenic calli was developed. Once the type II embryogenic calli are produced, they can be subcultured and/or proliferated conveniently. The objectives of this study were to demonstrate a stable Agrobacterium-mediated transformation of maize using explants of type II embryonic calli and to evaluate the efficiency of the protocol in order to develop herbicide-resistant maize. The type II embryogenic calli were inoculated with Agrobacterium tumefaciens strain C58C1 carrying binary vector pTF102, and then were subsequently cultured on the following media: co-cultivation medium for 1 day, delay medium for 7 days, selection medium for $4{\times}14$ days, regeneration medium, and finally on germination medium. The T-DNA of the vector carried two cassettes (Ubi promoter-EPSPs ORF-nos and 35S promoter-bar ORF-nos). The EPSPs conferred resistance to glyphosate and bar conferred resistance to phosphinothricin. The confirmation of stable transformation and the efficiency of transformation was based on the resistance to phosphinothricin indicated by the growth of putative transgenic calli on selection medium amended with $4mg\;1^{-1}$ phosphinothricin, northern blot analysis of bar gene, and leaf painting assay for detection of bar gene-based herbicide resistance. Northern blot analysis and leaf painting assay confirmed the expression of bar transgenes in the $R_1$ generation. The average transformation efficiency was 0.60%. Based on northern blot analysis and leaf painting assay, line 31 was selected as an elite line of maize resistant to herbicide.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.3
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• pp.53-63
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• 2014

This study was carried out to investigate the growth responses of medicinal plants such as Glehnia littoralis, Cryptotaenia japonica, Angelica gigas, Reynoutria japonica, Saururus chinensis, Houttuynia cordata, Ligularia fischeri, and Aralia cordata under 70%-shading and full sunlight conditions on a rooftop condition using artificial soil as a growth media. Glehnia littoralis, Cryptotaenia japonica, Ligularia fischeri, Saururus chinensis, and Houttuynia cordata showed better growth on plant height, leaf length, leaf width, petiole length and leaf number under full sunlight conditions on a rooftop condition. Cryptotaenia japonica and Houttuynia cordata had high value of Hunter's a (red-green) under full sunlight, while had lower value of L(lightness) and b(blue-yellow) than those of 70% shading condition. As an index of plant stress response, Glehnia littoralis, Reynoutria japonica, Houttuynia cordata, Ligularia fischeri showed Fv/Fm values 0.79~0.84 under full sunlight in August, indicating low stress on plant growth. Therefore they seemed to be suitable medicinal plats for rooftop conditions. Ligularia fischeri and Reynoutria japonica showed better growth under 70% shading treatment in August, while showed high growth response under full sunlight conditions in September. The 70% shading treatment was effective for the growth of Angelica gigas, Reynoutria japonica, and Aralia cordata. Angelica gigas and Reynoutria japonica, however, showed better plant growth under full sunlight during summer. The results showed that Glehnia littoralis, Cryptotaenia japonica, Ligularia fischeri, Saururus chinensis, and Houttuynia cordat seemed to be suitable medicinal plants for rooftop garden where there is a full sunlight condition.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.19-26
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• 2020

This paper proposes a framework for creating acrobatic scenes such as soccer ball lifting using various users' videos. The proposed method can generate a desired result within a few seconds using a general video of user recorded with a mobile phone. The framework of this paper is largely divided into three parts. The first is to analyze the posture by receiving the user's video. To do this, the user can calculate the pose of the user by analyzing the video using a deep learning technique, and track the movement of a selected body part. The second is to analyze the movement trajectory of the selected body part and calculate the location and time of hitting the object. Finally, the trajectory of the object is generated using the analyzed hitting information. Then, a natural object lifting scenes synchronized with the input user's video can be generated. Physical-based optimization was used to generate a realistic moving object. Using the method of this paper, we can produce various augmented reality applications.

• The Korean Journal of Mycology
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• v.31 no.1
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• pp.14-21
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• 2003

This study was carried out to obtain the basic data on artificial culture of Lampteromyces japonicus. Favorable media for mycerial growth were glucose peptone medium, malt yeast extract, yeast malt peptone, potato dextrose medium. The optimum conditions for the mycelial growth were $30^{\circ}C$ and pH 6.0. Dextrose as a carbon source was favorable to mycelial growth. The optimal dextrose concentration was 1.2%. As nitrogen sources, yeast extract, $(NH_4)_2HPO_4$ and 0.2% for glutamine. The mineral salts of $Al_2(SO_4)_3{\cdot}14H_2O$ were effective and the optimal concentration was 0.1 M.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2471-2478
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• 2020

Pumps are essential machinery in the various industries. With the development of high-speed and large-scale pumps, especially high energy density, high requirements have been imposed on the vibration and noise performance of pumps, and cavitation is an important source of vibration and noise excitation in pumps, so it is necessary to improve pumps cavitation performance. The modern pump optimization design method mainly adopts parameterization and artificial intelligence coupling optimization, which requires direct correlation between geometric parameters and pump performance. The existing cavitation performance calculation method is difficult to be integrated into multi-objective automatic coupling optimization. Therefore, a fast prediction method for pump cavitation performance is urgently needed. This paper proposes a novel cavitation prediction method based on impeller pressure isosurface at single-phase media. When the cavitation occurs, the area of pressure isosurface S_iso increases linearly with the NPSH_a decrease. This demonstrates that with the development of cavitation, the variation law of the head with the NPSH_a and the variation law of the head with the area of pressure isosurface are consistent. Therefore, the area of pressure isosurface S_iso can be used to predict cavitation performance. For a certain impeller blade, since the area ratio R_s is proportional to the area of pressure isosurface S_iso, the cavitation performance can be predicted by the R_s. In this paper, a new cavitation performance prediction method is proposed, and the feasibility of this method is demonstrated in combination with experiments, which will greatly accelerate the pump hydraulic optimization design.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.83-89
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• 2012

Natural Vegetation cover, which is very important earth resource, has been significantly altered by humans in some manner. Since this has currently resulted in a significant effect on global climate, various studies on vegetation environment including forest have been performed and the results are utilized in policy decision making. Remotely sensed data can detect, identify and map vegetation cover change based on the analysis of spectral characteristics and thus are vigorously utilized for monitoring vegetation resources. Among various vegetation indices extracted from spectral reponses of remotely sensed data, NDVI is the most popular index which provides a measure of how much photosynthetically active vegetation is present in the scene. In this study, for change detection in vegetation cover, a Multi-layer Perceptron Network (MLPN) as a nonparametric approach has been designed and applied to MODIS/Aqua vegetation indices 16-day L3 global 250m SIN Grid(v005) (MYD13Q1) data. The feature vector for change detection is constructed with the direct NDVI diffenrence at a pixel as well as the differences in some subset of NDVI series data. The research covered 5 years (2006-20110) over Korean peninsular.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.1-10
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• 2018

This study is to seek to find the importance of next digital marketing factors by using AHP method and analyze comparison between an advertising expert and a non-advertising expert. In results, the relative importance ranking is as follows; combination (0.26), transformation (0.259), optimization (0.243), and technology (0.238). The relative importance ranking of sub-factors is as follows: artificial intelligence and maching learning (0.086), big data (0.085), and contents curation (0.060). While the relative importance of combination and optimization for an advertising expert is higher than for non-advertising expert, the relative importance of transformation and technology for non-advertising is higher than for an advertising expert. This study provides managerial implication to build digital strategy based on these result.