• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.3
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• pp.147-153
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• 2013

There exist various types of the WEC (Wave Energy Converter), and among them, the point absorber is the most popularly investigated type. However, it is difficult to find examples of systematically measured data analysis for the design of the point absorber type of power buoy in the world. The study investigates the wave load acting on the point absorber type resonance power buoy wave energy extraction system proposed by Kweon et al. (2010). This study analyzes the time series spectra with respect to the three-year wave data (2002.05.01~2005.03.29) measured using the pressure type wave gage at the seaside of north breakwater of Hupo harbor located in the east coast of the Korean peninsula. From the analysis results, it could be deduced that monthly wave period and wave height variations were apparent and that monthly wave powers were unevenly distributed annually. The average wave steepness of the usual wave was 0.01, lower than that of the wind wave range of 0.02-0.04. The mode of the average wave period has the value of 5.31 sec, while mode of the wave height of the applicable period has the value of 0.29 m. The occurrence probability of the peak period is a bi-modal type, with a mode value between 4.47 sec and 6.78 sec. The design wave period can be selected from the above four values of 0.01, 5.31, 4.47, 6.78. About 95% of measured wave heights are below 1 m. Through this study, it was found that a resonance power buoy system is necessary in coastal areas with low wave energy and that the optimal design for overcoming the uneven monthly distribution of wave power is a major task in the development of a WEF (Wave Energy Farm). Finding it impossible to express the average spectrum of the usual wave in terms of the standard spectrum equation, this study proposes a new spectrum equation with three parameters, with which basic data for the prediction of the power production using wave power buoy and the fatigue analysis of the system can be given.

• Journal of the Korea Organic Resources Recycling Association
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• v.16 no.2
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• pp.47-56
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• 2008

The objective of this research is to evaluate the optimum recycling methods for the sewage sludge cakes at different microwave power-settings and for different periods of time. The dehydrated sewage sludge cakes used in this study was obtained from N wastewater treatment plan in the P City. The beginning drying processes were carried out in a microwave oven with 2,450 MHz frequency and power ranges of 1kW to 4 kW. The continuous conveyer drying system was also operated with 2,450 MHz frequency and power setting, ranging from of 1 kW to 6 kW. Initial moisture content of the sewage cake is 78~80%, and the moisture content decreased rapidly up to 0.2~2(wt%) within short periods due to breaking the cell walls. This study is also conducted to evaluate the characteristics of sewage sludge cakes with respect to important physical parameters effect on the thermal kinetics for evaporation water in the sludge which are operation times, moisture contents, drying rates, input amounts, flow rates and calorific values. It takes 60 minutes and 120 minutes to reach the critical moisture contents with power setting of 4 kW for 3kg/min and 6kg/min of the flow rates respectively. It takes 120 minutes and 110 minutes to reach the critical moisture contents with flow rates of 2.5 cm/min and sludge input of 6kg/min for the power settings of 4 kW and 6 kW respectively. The most effective value of the power for drying the sludge is 4 kW. Operation with 6kg/min and 4kW on 2cm of the sludge thickness can be effectively and inexpensively to reach the critical moisture contents, when you compare 2cm of the sludge thickness with 1cm and 3cm of the sludge thickness.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.35-47
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• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.125-140
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• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.

• Korean Journal of Ecology and Environment
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• v.52 no.4
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• pp.293-305
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• 2019

In this study we investigated the effect of a floating photovoltaic (FPV) system in Cheongpung Lake on water quality. The FPV with a tilt angle of 33° covered ca. 0.04% of surface area (97 ㎢) of Chungju Lake. The water qualities of the whole lake before and after installation of FPV were first compared. DO, BOD, TOC, and Chl-a of the whole lake were increased, while conductivity decreased after installation period at the significance level of 0.05. This change was probably due to the increased influx of nutrients by 40% resulting from increased precipitation during the same period. We also measured water quality parameters on May and Nov. 2017 at the FPV center (FPVC) and nearby control sites, and compared water quality. The result showed that the FPVC and nearby sites were not significantly different (p>0.05), demonstrating that the FPV does not cause a decline of water quality. The water temperature, light intensity, and phytoplankton community were also measured. The water temperature was not different between the sites, while the light intensity decreased to 27~50%. Despite reduced light intensity at FPVC, the phytoplankton standing crops and the number of species were not significantly different (p>0.05). However, in the early November samples, standing crops was significantly higher in FPVC than control with periphytic diatoms belonging to Aulacoseira genus being dominant. This may be due to the temporal water body behavior or local retention of current by FPV system. This study may provide a measure of future installation of a FPV system.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.8 no.3
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• pp.285-294
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• 2003

To select an appropriate sampler for the environmental monitoring survey in coastal waters of Saemangeum, Jeollabuk-do, a macrobenthic sampling was conducted in April 2002. Employed samplers were dredge (type Charcot), a semi-quantitative sampler and Smith-McIntyre (SM) and van Veen grab (VV) as quantitative ones. One haul was tried for dredge and 3 replicates (0.1 ㎡${\times}$3) for SM and W at each of 11 stations. Comparisons of sediment volume in sampler bucket and of precision of biological parameters (i.e., density, biomass, species number and diversity index, H') were made between SM and VV. Sediment volume was significantly different (SM > VV) at p-value of 0.0050 (paired t-test) and, in average, 3 replicate samples of SM and VV satisfied a precision level of 0.2 by applying 4th root transformation. Patterns of observed and expected species numbers and H' were compared. Dredge-VV samples showed higher affinity than any other pair. Several dominant species in the area were underestimated in dredge samples (e.g., polychaete Heteromastus filiformis. Aricidea assimilis etc.). Quantifying the agreement pattern of multi-species responses was accomplished by estimating correlations between similarity matrices. Correlation between dredge and VV was slightly higher, but near-per-fect matches were found in general. Different ranks and composition among principal species lists were presumably linked to the effect of penetration depth that differs among samplers. Lower level of some species' abundance in VV samples (ca. 50％ compared with those of SM) was explained in this context. It seem appropriate to regard the effect as a probable cause of relatively higher correlations in dredge-VV, Overall bio-logica1 features indicated that a better choice could be SM in situations of requiring high data quality. The others work well, however, on observing and defining faunal characteristics and their capability cannot be questionted if we do not expect a first-order quality.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Journal of the Korean Applied Science and Technology
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• v.34 no.3
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• pp.683-693
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• 2017

Transport biofuels have been recognized as a promising means to resolve the following issues like global warming, oil depletion and environmental pollutions. Among various biofuels, biodiesel has several advantages such as less emission of air pollutants and higher cetane values compared to diesel oil. Demand for biodiesel in Korea is increasing that leads to higher dependence on the imported feedstocks. Therefore, it is important to utilize the waste materials collected domestically for biodiesel production. Food waste oil collected in waste treatment facility has not been used for biodiesel production due to high free fatty contents in the oil. In this work, biodiesel conversion of food waste oil by Amberlyst 15 was studied. Synthetic and actual food waste oils have been used in the study. First, the effects of the major operating parameters including reaction temperature, methanol to oil molar ratio and catalyst loading on the conversion rates and yields were determined with synthetic waste oil. Kinetic modelling work was also done to determine the activation energy of the reaction. From the work, optimization reaction conditions were determined to be 383K, 1: 26.1 for methanol molar ratio to oil, 10 wt.% for catalyst loading and 360 min for reaction time. Activation energy of the reaction is determined to be 29.75 kJ/mol, lower than those reported in the previous works. So the solid catalyst, Amberlyst 15, was more efficient for esterification than the solid catalysts employed in the other works. Agitation rates have the negligible effects on the conversion rates and yields. With the identified optimization conditions, conversion of the actual food waste oil was also carried out. The esterification yield of actual food waste oil in 60 min was 13% lower than that of synthetic waste oil but the final yields in 240 min were similar each other, 98.12% for synthetic oil and 97.62% for actual waste oil.

• Journal of the Korea Organic Resources Recycling Association
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• v.22 no.4
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• pp.21-27
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• 2014

Pig slurry has been considered as environmental waste to be treated in an appropriate manner. Moreover, water-born pollution loads by agricultural non-point source(NPS) pollution are expected to become intensified due to ongoing precipitation change. This study was conducted to develop a best management practice to reduce NPS pollution load by agricultural activity with pig manure compost. An eco-friendly way, small drainage pond, was suggested in this study to avoid direct drainage of agricultural runoffs and eventually reduce the amount of pollutants discharged into the surrounding aqua-environment. A small pond($12m^2$) was constructed at the corner of a rice paddy field($17,15m^2$) located in Suwon, Korea. Water was allowed to drain only via a small drainage pond. Sampling was repeatedly made at two locations, one from an entrance and the other from an exit of a pond, during the rice cultivation period(May to October, 2013). Generally, sampling was made only when runoff water drained through a pond, such as during and/or after rain(irrigation). The water quality analysis showed that all quality parameters(SS, $COD_{Mn}$, T-N, and T-P) were improved as water passed through the pond. The amount of runoff water was reduced by 67.8%. Suspended solids and $COD_{Mn}$ concentrations were reduced by 79.8% and 71.9%, respectively. In case of T-N and T-P amounts, the reduction rates were 73.6% and 74.9%, respectively. Our data implies that agricultural NPS pollution from rice paddy fields with pig manure-based fertilizer can be effectively managed when an appropriate drainage water management practice is imposed.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.