• Journal of Korean Society of Forest Science
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• v.78 no.4
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• pp.401-411
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• 1989

The embryos of Pinus taeda, P. rigida, and P. taeda ${\times}$ rigida were cultured for adventitious shoot regeneration in vitro. Culture media were modified from Gresshoff and Doy (MGD), Murashige and Skoog (MMS), Lloyd and McCown (MLM), and Schenk and Hildebrandt (MSH). NAA was added to initiation media at a concentration of 0.1 or 0.01 mg/l. BAP was used at the concentrations of 0.1. 0.5, 1, 2, or 5mg/l. Each explant was induced for 3-4 weeks on solid medium. All explants were cultured up to 16 weeks. Illumination was about $1506{\pm}540lux$ at the level of the tissues in the growth room with a temperature of $25{\pm}2^{\circ}C$. A 16-hour photoperiod per 24 hours was used. Half-strength medium was used for all the subcultures. For shoot production by loblolly pine, MMS, MLM, or MSH is preferred with 5 mg/l BAP with either 0.1 or 0.01 mg/l NAA. For shoot production by pitch pine, MMS, MLM, or MSH is recommended with 2 or 5 mg/l BAP with 0.1 mg/l NAA. For shoot production by the hybrid pine, MMS or MLM is more effective with 1, 2 or 5 mg/l BAP with 0.1 mg/l NAA. There were no differences recognized among the species tried in the patterns of bud formation and shoot development. Different composition of media, in major and minor salts or possibly in vitamins, should be tested for the two developmental stages of adventitious shoots ; the induction of shoot buds and the elongation of them into shoots.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.