• Applied Chemistry for Engineering
• /
• v.9 no.4
• /
• pp.486-490
• /
• 1998

Pt/C powder which was used as electrocatalyst in a Phosphoric Acid Fuel Cell(PAFC) was fabricated by colloid method. It was reported that the sulfur from reductant, $Na_2S_2O_4$, worked as a poison against catalyst during long term operation. To remove these sulfurs, we try to treat Pt/C powder by three different methods. First, we tried to remove the sulfur according to temperature and time in $H_2$ atmosphere. As the heat treatment temperature is raised up, the effect of the removal is increased but the electrode performance is decreased because of the growth of Pt particle size. The optimal heat treatment temperature is $400^{\circ}C$, the size of Pt particle is approximately $35{\sim}40{\AA}$ and the electrode performance is $360mA/cm^2$ at 0.7 V. At $400^{\circ}C$, even though the time of heat treatment is extended, size of Pt, amounts of remaining sulfur and electrode performance is almost constant. Secondly, when we removed in a crucible at $900^{\circ}C$ the removal of the sulfur was not better, but the size of Pt particle, approximately $80{\AA}$, was smaller than that of heat treatment in $H_2$ atmosphere at $900^{\circ}C$. Lastly we treated with solvents such as acetone, benzene, and carbon disulfide. It was observed that sulfur components were removed partly by extraction with solvents, the electrode performances were similar each other.

• Journal of the Korea Society of Computer and Information
• /
• v.5 no.2
• /
• pp.30-36
• /
• 2000

The hidden node plays a role of the functional units that classifies the features of input pattern in the given question. Therefore, a neural network that consists of the number of a suitable optimum hidden node has be on the rise as a factor that has an important effect upon a result. However there is a problem that decides the number of hidden nodes based on back-propagation learning algorithm. If the number of hidden nodes is designated very small perfect learning is not done because the input pattern given cannot be classified enough. On the other hand, if designated a lot, overfitting occurs due to the unnecessary execution of operation and extravagance of memory point. So, the recognition rate is been law and the generality is fallen. Therefore, this paper suggests a method that decides the number of neural network node with feature information consisted of the parameter of learning algorithm. It excludes a node in the Pruning target, that has a maximum value among the feature value obtained and compares the average of the rest of hidden node feature value with the feature value of each hidden node, and then would like to improve the learning speed of neural network deciding the optimum structure of the multi-layer neural network as pruning the hidden node that has the feature value smaller than the average.

• Journal of Korean Society of Forest Science
• /
• v.104 no.4
• /
• pp.632-639
• /
• 2015

Working in the forest would require a wide range of skills and experience for specific tasks which involve with a high level of risks to worker's safety. However, there has been a concern on the current standard wage system for forest workers because it does not effectively reflect the characteristics of typical working conditions in the forest. In addition, the current standard wages for forestry workers was estimated based on the construction industry's wage system. Therefore, the purpose of this study is to assess a current wage system through the mail survey method and to develop a new wage system for forest worker which effectively reflects skill sets and experience required for successful completion of the work in the forest. We mailed the survey questionnaire consisting of 19 questions to 659 forest workers and received 188 responses resulting in a 28.5% response rate. The results showed that the current average optimal wages of forest worker, special worker and feller were 97,680won/day, 127,559won/day and 152,403won/day, respectively though there were variations depending on the regions. In developing the new standard wage system, this study suggest the current work types(worker, special worker and feller) could be divided into 5 work types (forest-environment workers, forest operations in beginner, forest operations in intermediate, forest operations in advanced and forest equipment operator) reflecting specialty of forest operation thereby stabilizing the new wage system for forest workers.

• Journal of Korea Port Economic Association
• /
• v.28 no.3
• /
• pp.27-44
• /
• 2012

The offshore wind farm is increasingly attractive as one of future energy sources all over the world. In addition, the capacity of an offshore wind turbine gets larger and its physical characteristics are big and heavy. In this regard, a special port is necessary to assemble, store, and transport the offshore wind systems, supporting to form the offshore wind farms. Thus, this study aims to provide a policy maker which evaluation factors can significantly affect to the optimal site selection of a offshore wind port. For this, Fuzzy-AHP method is applied to capture the relative weights. The results of this study can be summarized as follows. Five criteria in level I was defined such as the accumulation factor, the regional factor, the economic factor, the location factor, and the consortium factor. Of these, the accumulation factor(37.4%), the location factor(34.2%), and the economic factor( 24.5%) were analyzed by major factors. In level II, three assessment items of each factor were selected so that total fifteen items were formed. To sum up, the site selection of offshore wind port should consider the density of the wind industry, cargo volume of securing the economic operation of terminals, the development degree of offshore wind related industry, and the proximity to the offshore wind farms. In other words, the construction of offshore wind port should be paid attention to considering not only the proximity to offshore wind farms but also the preference of turbine manufacturing companies.

• Journal of Environmental Science International
• /
• v.19 no.5
• /
• pp.647-653
• /
• 2010

The objectives of this research are to evaluate and compare the oxygen transfer coefficients($K_{La}$) in both a general bubbles reactor and a micro-nano bubbles reactor for effective operation in sewage treatment plants, and to understand the effect on microbial kinetic parameters of biomass growth for optimal biological treatment in sewage treatment plants when the micro-nano bubbles reactor is applied. Oxygen transfer coefficients($K_{La}$) of tap water and effluent of primary clarifier were determined. The oxygen transfer coefficients of the tap water for the general bubbles reactor and micro-nano bubbles reactor were found to be 0.28 $hr^{-1}$ and 2.50 $hr^{-1}$, respectively. The oxygen transfer coefficients of the effluent of the primary clarifier for the general bubbles reactor and micro-nano bubbles reactor were found be to 0.15 $hr^{-1}$ and 0.91 $hr^{-1}$, respectively. In order to figure out kinetic parameters of biomass growth for the general bubbles reactor and micro-nano bubbles reactor, oxygen uptake rates(OURs) in the saturated effluent of the primary clarifier were measured with the general bubbles reactor and micro-nano bubbles reactor. The OURs of in the saturated effluent of the primary clarifier with the general bubbles reactor and micro-nano bubbles reactor were 0.0294 mg $O_2/L{\cdot}hr$ and 0.0465 mg $O_2/L{\cdot}hr$, respectively. The higher micro-nano bubbles reactor's oxygen transfer coefficient increases the OURs. In addition, the maximum readily biodegradable substrate utilization rates($K_{ms}$) for the general bubbles reactor and micro-nano bubbles reactor were 3.41 mg COD utilized/mg active VSS day and 7.07 mg COD utilized/mg active VSS day, respectively. The maximum specific biomass growth rates for heterotrophic biomass(${\mu}_{max}$) were calculated by both values of yield for heterotrophic biomass($Y_H$) and the maximum readily biodegradable substrate utilization rates($K_{ms}$). The values of ${\mu}_{max}$ for the general bubbles reactor and micro-nano bubbles reactor were 1.62 $day^{-1}$ and 3.36 $day^{-1}$, respectively. The reported results show that the micro-nano bubbles reactor increased air-liquid contact area. This method could remove dissolved organic matters and nutrients efficiently and effectively.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.1
• /
• pp.96-107
• /
• 2015

VANET technologies provide real-time traffic information for mitigating traffic jam and preventing traffic accidents, as well as in-vehicle infotainment service through Telematics/Intelligent Transportation System (ITS). Due to the rapid increasement of various requirements, the vehicle communication with a limited resource and the fixed frame architecture of the conventional techniques is limited to provide an efficient communication service. Therefore, a new flexible operation depending on the surrounding situation information is required that needs an adaptive design of the network architecture and protocol for efficiently predicting, distributing and sharing the context-aware information. In this paper, Vehicle-to-Infrastructure (V2I) based on communication between vehicle and a Road Side Units (RSU) and Vehicle-to-Vehicle (V2V) based on communication between vehicles are effectively combined in a new MAC architecture and V2I and V2V vehicles collaborate in management. As a result, many vehicles and RSU can use more efficiently the resource and send data rapidly. The simulation results show that the proposed method can achieve high resource utilization in accordance. Also we can find out the optimal transmission relay time and 2nd relay vehicle selection probability value to spread out V2V/V2I collaborative schedule message rapidly.

• Journal of Navigation and Port Research
• /
• v.44 no.3
• /
• pp.187-194
• /
• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.

• Journal of Korean Society of Water and Wastewater
• /
• v.33 no.5
• /
• pp.353-366
• /
• 2019

This research proposes an optimal flushing operation technique in an effort to prevent secondary water pollutions and accidents in aged pipes, and to improve the cleaning effect of unidirectional flushing. Water flow directions were analyzed using EPANET 2.0, while flushing and air scouring experiments in forward and reverse directions were performed in the field. In 42 experiments, average residual chlorine concentration and turbidity were improved after cleaning compared to before cleaning. It was found that even when the same cleaning method was used, further improvement of cleaning effect was possible by applying air injection and reverse direction cleaning techniques. By means of one-way ANOVA(Analysis of variance), it was also possible to statistically verify the need of actively utilizing air injection and reverse direction cleaning. Based on correlation between turbidity and TSS, the total amount of suspended solids removal was estimated for 874 flushing operations and 194 air scouring operations. The result showed that air scouring used more discharge water than flushing by an average of $4.9m^3$ yet with larger amounts of suspended solids removal by an average of 145.9 g. The result of analysis on turbidity values from 887 flushing operations showed low cleaning effect of unidirectional flushing for the pipes with diameters over 300 mm. In addition, the turbidity values measured during cleaning showed an increasing tendency as pipe age increased. The methodology and results of this research are expected to contribute to the efficient maintenance and improvement of water quality in water distribution networks. Follow-up research involving the measurement of water quality at regular time intervals during cleaning would allow a more accurate comparison of discharge water quality characteristics and cleaning effects between different cleaning methods. To this end, it is considered necessary to develop a standardized manual that can be used in the field and to provide relevant trainings.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.10
• /
• pp.391-398
• /
• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.1
• /
• pp.28-34
• /
• 2019

Solar energy is one of the most abundant renewable energy sources on Earth but there are restrictions on the use of solar thermal energy due to the time-discrepancy between the solar-rich season and heating demand. In Europe and Canada, a seasonal solar thermal energy storage (SSTES), which stores the abundant solar heat in the summer and uses the heat for the winter heating load, is used. Recently, SSTES has been introduced in Korea and empirical studies are actively underway. In this study, a $2,000m^2$ flat plate type solar collector and $20,000m^2$ of borehole thermal energy storage (BTES) were studied for a greenhouse in Hwaseong City, which has a heating load of 2,164 GJ/year. To predict the dynamic performance of the system over time, it was simulated using the TRNSYS 18 program, and the solar fraction of the system with the control conditions was investigated. As a result, the solar BTES system proposed in this study showed an average solar fraction of approximately 60% for 5 years when differential temperature control was applied to both collecting solar thermal energy and discharging BTES. The proposed system simplified the configuration and control method of the solar BTES system and secured its performance.