• KIEAE Journal
• /
• v.14 no.4
• /
• pp.119-125
• /
• 2014

This study investigated the effects of pipe network materials and distance on system performance utilizing unused energy sources in large-scale horticulture facility. For this, the modeling was performed with a 100 m long and 100 m wide rectangular shaped glass house having an area of 1ha ($10,000m^2$) using EnergyPlus software. The heat sources considered were air source, geothermal heat, power plant waste heat, sea water heat, and river water. The temperature variation of the fluid with regard to pipe material and distance from the heat source and the resultant heat pump electricity consumptions were calculated. It turned out that the fluid temperature reaching the heat pump increased as the distance from the heat source increased in case of sea water and river water, which have higher temperatures than the surrounding soil, improving the heat pump efficiency. It was vice versa in case of the power plant waste heat. In addition, pipe material of PVC showed the smallest effect on the system performance variation due to the lowest thermal conductivity, compared to PB and HDPE.

• Journal of Korea Port Economic Association
• /
• v.36 no.2
• /
• pp.53-62
• /
• 2020

The maritime and port logistics industry is closely related to global trade and economic activity, especially for Korea, which is highly dependent on trade. As the largest port in Korea, Busan Port processes 75% of the country's container cargo; the port is therefore extremely important in terms of the country's national competitiveness. Port container cargo volume forecasts influence port development and operation strategies, and therefore require a high level of accuracy. However, due to unexpected and sudden changes in the port and maritime transportation industry, it is difficult to increase the accuracy of container volume forecasting using existing time series models. Among deep learning models, this study uses the LSTM model to enhance the accuracy of container cargo volume forecasting for Busan Port. To evaluate the model's performance, the forecasting accuracies of the SARIMA and LSTM models are compared. The findings reveal that the forecasting accuracy of the LSTM model is higher than that of the SARIMA model, confirming that the forecasted figures fully reflect the actual measurement figures.

• Journal of Advanced Marine Engineering and Technology
• /
• v.38 no.9
• /
• pp.1075-1080
• /
• 2014

This study aims at dedicating to relevant technology fields by suggesting design methods of structures and estimating their safety in relation to substructure for offshore wind power requiring high safety to various environment conditions. Especially, with respect to 5MW Offshore Wind Power System, this study will provide information about major wind directions and duration in combination with the developing wave climate at the test field. Therefore, connections between wind fields and approaching wave trains will be estimated and their intensity, direction and time shift will be pointed out. Furthermore, the local pressure distribution of breaking waves will be investigated by physical and numerical modeling. The currently applied structural and fatigue assessment of support structures for offshore wind energy converters is based on common design rules. Normally, constructions in structural engineering are treated as limited, single structures. This means that varying aspects of manufacturing are considered by high safety factors.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.3
• /
• pp.56-62
• /
• 2001

In this paper, we adopt a missing data theory to speech recognition. It can be used in order to maintain high performance of speech recognizer when the missing data occurs. In general, hidden Markov model (HMM) is used as a stochastic classifier for speech recognition task. Acoustic events are represented by continuous probability density function in continuous density HMM(CDHMM). The missing data theory has an advantage that can be easily applicable to this CDHMM. A marginalization method is used for processing missing data because it has small complexity and is easy to apply to automatic speech recognition (ASR). Also, a spectral subtraction is used for detecting missing data. If the difference between the energy of speech and that of background noise is below given threshold value, we determine that missing has occurred. We propose a new method that examines the reliability of detected missing data using voicing probability. The voicing probability is used to find voiced frames. It is used to process the missing data in voiced region that has more redundant information than consonants. The experimental results showed that our method improves performance than baseline system that uses spectral subtraction method only. In 452 words isolated word recognition experiment, the proposed method using the voicing probability reduced the average word error rate by 12％ in a typical noise situation.

• Journal of the Korean Solar Energy Society
• /
• v.29 no.6
• /
• pp.81-87
• /
• 2009

The purpose of this study is to evaluate of the outdoor thermal environment by building scale and block type as variable factors. In this study, 18 cases of office in central business district that have different condition are compared about their surface temperature, HIP(Heat Island Potential), and MRT(Mean Radiant Temperature). They are simulated with 3-dimension numerical simulation software named Hoyano-model. The output results contain visualized distribution chart and numerical data. The results of evaluation are as follows. (1)The surface temperature of the building becomes higher as building coverage ratio is higher but floor area ratio is lower. In same conditions, unified block type is maximum $3.2^{\circ}C$ higher than divided block type. (2)HIP shows different daily pattern as block type. During daytime, divided block type is much higher than unified block type but after sunset, it is changed. (3)MRT shows different distribution pattern as sunlight moves expecially at noon. (4)As the results of this study, cases that have high floor area ratio condition show lower surface temperature by tendency to stay low indoor temperature in office building and big rate of windows on building surface.

• Journal of the Korean Society of Safety
• /
• v.24 no.3
• /
• pp.54-58
• /
• 2009

A substitute energy development has been required due to the exhaust of the fossil fuel and an environmental problem. Consequently, possible technologies producing hydrogen from water that does not release carbon is a very promising technology. Also, Iodine-Sulfur(IS) thermochemical water decomposition is one of the promising processes that are used to produce hydrogen efficiently using the high temperature gas-cooled reactor(HTGR) as an energy source that is possible to supply heat over 900$^{\circ}C$. In this study, to make a initiating events identification for the IS process, Master Logic Diagram(MLD) is used and 9 initiating events that cause a leakage of the chemical material are identified. Also, 6 events are identified among 9 initiating events above and are quantified using event tree.

• Proceedings of the Acoustical Society of Korea Conference
• /
• autumn
• /
• pp.121-124
• /
• 2001

음성 합성기의 합성음의 자연감을 높이기 위해 자연음에 내재하는 정확한 운율 법칙을 구하여 음성합성 시스템에서 이를 구현해 주어야 한다 무제한 어휘 음성합성 시스템의 문-음성 합성기에서 필요한 운율 법칙은 언어학적 정보를 이용해 구하거나, 자연음에서 추출하고 있다 그러나 추출한 운율 법칙이 자연음에 내재하는 모든 운율 법칙을 반영하지 못했거나, 잘못 구현되는 경우에는 합성음의 자연성이 떨어지게 된다. 이런 점을 고려하여 본 논문에서는 한국어 자연음을 분석하여 추출한 운율 정보를 인공 신경망이 학습하도록 하고 훈련을 마친 인공 신경망에 문장을 입력하고, 출력으로 나오는 운율 정보와 자연음의 운율 정보를 비교한 결과 제안한 인공 신경망이 자연음에 내재하고 있는 운율을 학습할 수 있음을 알 수 있었다. 운율의 3대 요소는 피치 , 지속시간, 크기의 변화이다. 제안한 인공 신경망이 한국어 문장의 음소 열을 입력으로 받아들이고, 각 음소의 지속시간에 따른 피치변화와 크기 변화를 출력으로 내보내면 자연음을 분석해 구한 각 음소의 운율 정보인 목표 패턴과 출력 패턴 의 오차를 최소화하도록 인공 신경망의 가중치를 조절할 수 있도록 설계하였다. 지속시간에 따른 각 음소의 피치와 크기 변화를 학습시키기 위해 피치 및 크기 인공 신경망을 구성하였다. 이들 인공 신경망을 훈련시키기 위해 먼저 음소 균형 문장 군을 구축하여야 하고, 이들 언어 자료를 특정 화자가 일정 환경에서 읽고 이를 녹음하여 , 분석하여 구한운율 정보를 운율 데이터베이스로 구축하였다. 문장 내의 각 음소에 대해 지속 시간과 피치 변화 그리고 크기 변화를 구하고, 곡선 적응 방법을 이용하여 각 변화 곡선에 대한 다항식 계수와 초기 값을 구해 운율 데이터베이스를 구축한다. 이 운율 데이터베이스의 일부는 인공 신경망을 훈련시키는데 이용하고, 나머지로 인공 신경망의 성능을 평가하여 인공 신경망이 운율 법칙을 학습할 수 있었다. 언어 자료의 문장 수를 늘리고 발음 횟수를 늘려 운율 데이터베이스를 확장하면 인공 신경망의 성능을 높일 수 있고, 문장 내의 음소의 수를 감안하여 인공 신경망의 입력 단자의 수는 계산량과 초분절 요인을 감안하여 결정해야 할 것이다

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.12 no.1
• /
• pp.57-64
• /
• 2008

Generally, organic paint on steel towers can guarantee durability in normal condition but occasionally shows its deterioration on the power line tower and electric power facilities, exposed to light(ultra violet) or heat. The objective of this study is to develope the inorganic paint material based on fluid silicic acid for steel electric power facilities. For the purpose, optimal mixture proportion is derived through 6 preliminary test and, additionally physical and durability performance test are carried out for selected specimens. The performances of developed organic paint material is similar to those of organic paint material. If resistance to chemical attack is improved, the developed inorganic paint is evaluated to replace the organic paint and obtain wide application.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.36 no.12
• /
• pp.1585-1590
• /
• 2012

Engineering plastics are used in instrument panels, interior trim, and other vehicle applications, and the thermomechanical behaviors of plastic materials are strongly influenced by many environmental factors such as temperature, sunlight, and rain. As the material properties change, the mechanical parts create unexpected noise. In this study, the dynamic mechanical property changes of plastics used in automobiles are measured to investigate the temperature effects. Viscoelastic properties such as the glass transition temperature and storage modulus and loss factor under temperature and frequency sweeps were measured. The data were compared with the original ones before aging to analyze the behavior changes. It was found that as the temperature increased, the storage modulus decreased and the loss factor increased slightly.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.26 no.11
• /
• pp.1672-1681
• /
• 2002

To evaluate the thermal environments and the workload of farmers in the rice field in summer, this study investigated rice farmers' physiological, psychological responses, work postures, work clothes, air temperature and air humidity during the spraying pesticide in the rice field. Five career farmers (3 males, 2 females) volunteered as the subjects. During the spraying pesticide in the rice field, physiological responses were monitored continuously. The results were as follows. l. Farmers wore only raincoats not pesticide-proof clothing. 2. The value of WBGT, rectal temperature($T_{re}$), mean skin temperature(${\={T}}_{sk}$) were $24.9∼28.9^{\circ}C,\;37.8({\pm}0.3)^{\circ}C\;and\;33.6({\pm}0.6)^{\circ}C$, respectively. Clothing microclimate temperature($T_{cl}$) on the chest and back were $32.5({\pm}2.6)^{\circ}C\;and\;33.6({\pm}2.6)^{\circ}C$, respectively(p<0.00l). Humidity inside of the clothing ($H_{cl}$) was over 80%RH and heart rate(HR) was 112(${\pm}27$)bpm. We evaluated that the spraying pesticide was 'heavy work' by the Tre and HR. To four subjective questionnaires, all farmers expressed 'hard, hot, humid and uncomfortable' without individual difference at the end of works. We suggested that 1) the spraying pesticide in the rice field was a heavy work, 2) because the workload of farmers in the raincoat/pesticide-proof clothing can't be evaluated by only WBGT, assessors should measure physiological, psychological responses as well as thermal environments, 3) to alleviate farmers' heat strain, clothing manufacturers must consider not only the improvement of textile materials and clothing weight but also the designing of personal cooling equipment.