• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2018.11a
• /
• pp.191-192
• /
• 2018

국내 해운회사의 외국인 선원 증가로 의사소통의 어려움, 작업 생산성 감소, 긴급상황 발생 시 대처곤란, 문화적 충돌이 선상폭력으로 이어지는 등 많은 문제점이 발생하고 있다. 또한, 조기하선으로 인한 젊은 층의 관리자급 해기사 부족 및 고령화 가속, 해운선사들의 저임금 외국인선원 선호로 우리나라 해기전승(해기지식의 전달) 단절 초래, IMO 권고에 따른 승선기간의 단축(규격화)으로 육상 타 직종에 비해 상대적으로 낮은 급여, 재승선의 불확실성 및 해기사의 계약직화로 인한 해상직 기피 등으로 인해 해운경쟁력 약화가 두드러지고 있다. 이 연구에서는 우리나라 해운경쟁력 향상을 위한 해결책의 하나로 한국의 우수한 선원 교육 훈련 시스템을 접목한 북한선원 양성체계 구축방안을 고찰하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2018.11a
• /
• pp.289-291
• /
• 2018

본 발표는 대한민국 선원의 의사소통 역량 및 글로벌 역량 강화를 위해 해수부에서 실시한 "선상 의사소통능력 강화방안" 사업을 통해 개발된 한국형 해사영어 커리큘럼의 수립 과정과 그에 따른 컨텐츠 제작 과정을 공유하고, 향후 개발 방향을 모색하기 위함이다. 따라서 본 발표를 통해 커리큘럼을 수립을 위한 선행 연구 과정(국제해사기구, 국제민간항공기구 및 국제항로표지협회 등의 국제 가이드라인 검토 및 분석, 특수목적영어 교육훈련기법 외), 교육 커리큘럼 수립(IMO 해사영어모델코스 및 표준해사통신용어 분석 및 재편성), 교육 컨텐츠 구성(실제 선사 유관 자료의 수집 및 데이터베이스 구축), 교육 훈련 교재 개발(교재, 학생용 워크북, 교사용 워크북, 음원) 등의 과정을 순차적으로 소개하고, 이에 대한 결과물을 공유하며, 향후 발전 방향을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.05a
• /
• pp.761-763
• /
• 2008

최근 온라인교육의 필요성이 높아지고 요구 수준이 커짐에 따라 교육 서비스를 제공하는 시스템의 지능화된 처리능력이 필요하다. 퍼지신경회로망은 각각의 가중치(weight)를 갖는 채널로 연결한 망형태의 계산모델이다. 퍼지신경회로망을 학습시스템에 적용하여 학습자의 문항테스트 결과에서 학습과정을 재설정 할 수 있는 출력 값을 생성한다. 적응형 학습시스템은 퍼지신경회로망을 적용하여 개별화된 강의 코스로 학습을 진행하고 결과의 feedback을 통해 학습자의 최적 커리큘럼을 찾아내는 방법을 구현하였다.

• Journal of the Korea Convergence Society
• /
• v.12 no.6
• /
• pp.9-16
• /
• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.6
• /
• pp.1049-1060
• /
• 2009

The expansion of volatility in Korean Stock Market made it more difficult for the individual to invest directly and increased the weight of indirect investment through a fund. The purpose of this study is to construct the EIF(enhanced index fund) model achieves an excessive return among several types of fund. For this purpose, this paper propose portfolio optimization model to manage an index fund by using GA(genetic algorithm), and apply the trading amount and the closing price of standard index to earn an excessive return add to index fund return. The result of the empirical analysis of this study suggested that the proposed model is well represented the trend of KOSPI 200 and the new investment strategies using this can make higher returns than Buy-and-Hold strategy by an index fund, if an appropriate number of stocks included.

• Korean Journal of Agricultural Science
• /
• v.11 no.2
• /
• pp.270-277
• /
• 1984

The effects of factors of natural air drying were evaluated by the simulation model for rough rice drying. The factors were airflow rate, harvest date, initial moisture content and weather conditions. For simulation, the RICEDRY (Chang et al., 1983) was used. Then, the applicability of the model and the feasibility of rough rice drying by natural air were tested under the tropical weather conditions of Costa Rica.

• The Korean Journal of Applied Statistics
• /
• v.34 no.3
• /
• pp.461-475
• /
• 2021

Hidden Markov model (HMM) is a statistical model in which the system consists of two elements, hidden states and observable results. HMM has been actively used in various fields, especially for time series data in the financial sector, since it has a variety of mathematical structures. Based on the HMM theory, this research is intended to apply the domestic KOSPI200 stock index as well as the prediction of global stock indexes such as NIKKEI225, HSI, S&P500 and FTSE100. In addition, we would like to compare and examine the differences in results between the HMM and support vector regression (SVR), which is frequently used to predict the stock price, due to recent developments in the artificial intelligence sector.

• Journal of Life Science
• /
• v.32 no.8
• /
• pp.601-610
• /
• 2022

P. tenebrifer (PT) belongs to the Diptera order and Stratiomyidae family. Recently, insect industry have been focused as food, animal feed and environmental advantages. γ-aminobutyric acid (GABA) and melatonin have been associated with regulating sleep and depression. GABA is the primary inhibitory neurotransmitter and is synthesized via biotransformation of monosodium glutamate (MSG) to GABA by lactic acid bacteria. In this study, we first used a GABA-enhanced PT extract, wherein GABA was enhanced by feeding MSG to PT. The underlying mechanisms preventing stress and insomnia were investigated in a corticosterone (CORT)-induced endoplasmic reticulum (ER) stress and chronic restraint stress (CRS)-exposed mouse model, as well as in pentobarbital (45 mg/kg)-induced sleep behaviors in mice. In the present study, the GABA peak was detected in high-performance liquid chromatography-evaporative light scattering detector (HPLC-ELSD) analysis and showed in Ptecticus tenebrifer water extract (PTW) but not in non-PTW extract. The results showed that PTW and Ptecticus tenebrifer with 70% ethanol extract (PTE) exerted neuroprotective effects by protecting against CORT-induced downregulation of phosphorylated extracellular signal-regulated kinase 1/2 (ERK1/2) and cAMP-response element binding protein (CREB) expression. In addition, PTW (300 mg/kg) significantly reduced CORT levels in CRS-exposed mice. Furthermore, PTW (100 and 300 mg/kg) significantly reduced sleep latency and increased total sleep duration in pentobarbital (45 mg/kg)-induced sleeping behaviors, which was related to serum melatonin levels. In conclusion, our results suggest that PTW exerts anti-stress and sleep-enhancing effects by regulating serum CORT and melatonin levels.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.23 no.8
• /
• pp.698-706
• /
• 2013

Structural vibration induced by excitation forces under turbulent boundary layer is investigated in terms of the numerical analysis in this paper. Since the responses of structures excited by the wall pressure fluctuation(WPF) are described by the power spectral density functions, they are calculated and reviewed theoretically for finite and infinite length beams. For the use of numerical approaches, the WPF needs to be discretized but conventional finite element method is not much effective for that purpose because the WPF lose the spatial correlation characteristics. As an alternative numerical technique for WPF modelling, a wavenumber domain finite element approach, called waveguide finite element method, is examined here for infinite length beams. From the comparison between the numerical and theoretical results, it was confirmed that the WFE method can effectively and easily cope with the excitation from WPF and hence the suitable approach.

• Journal of Internet Computing and Services
• /
• v.8 no.6
• /
• pp.127-133
• /
• 2007

The u-learning environment has been developed through a number of iterations, and has now been formally evaluated, through analysis of student learning results and the use of quantitative and qualitative measures, Generally, for advance learning effect and analysis of student learning results, the most learning system be use to the item analysis method. But, nowadays, it has using the IRT(Item Response Theory) instead of the item analysis method, The IRT adopts explicit models for the probability of each possible response to a test. Therefore, I proposed the lightweight component based u-learning system using the IRT. Applied device of u-learning is PDA which is in Windows mobile 5.0 environments.