• Journal of Soil and Groundwater Environment
• /
• v.12 no.5
• /
• pp.19-32
• /
• 2007

In Korea, there have been various methods of estimating groundwater recharge which generally can be subdivided into three types: baseflow separation method by means of groundwater recession curve, water budget analysis based on lumped conceptual model in watershed, and water table fluctuation method (WTF) by using the data from groundwater monitoring wells. However, groundwater recharge rate shows the spatial-temporal variability due to climatic condition, land use and hydrogeological heterogeneity, so these methods have various limits to deal with these characteristics. To overcome these limitations, we present a new method of estimating recharge based on water balance components from the SWAT-MODFLOW which is an integrated surface-ground water model. Groundwater levels in the interest area close to the stream have dynamics similar to stream flow, whereas levels further upslope respond to precipitation with a delay. As these behaviours are related to the physical process of recharge, it is needed to account for the time delay in aquifer recharge once the water exits the soil profile to represent these features. In SWAT, a single linear reservoir storage module with an exponential decay weighting function is used to compute the recharge from soil to aquifer on a given day. However, this module has some limitations expressing recharge variation when the delay time is too long and transient recharge trend does not match to the groundwater table time series, the multi-reservoir storage routing module which represents more realistic time delay through vadose zone is newly suggested in this study. In this module, the parameter related to the delay time should be optimized by checking the correlation between simulated recharge and observed groundwater levels. The final step of this procedure is to compare simulated groundwater table with observed one as well as to compare simulated watershed runoff with observed one. This method is applied to Mihocheon watershed in Korea for the purpose of testing the procedure of proper estimation of spatio-temporal groundwater recharge distribution. As the newly suggested method of estimating recharge has the advantages of effectiveness of watershed model as well as the accuracy of WTF method, the estimated daily recharge rate would be an advanced quantity reflecting the heterogeneity of hydrogeology, climatic condition, land use as well as physical behaviour of water in soil layers and aquifers.

• Asia pacific journal of information systems
• /
• v.19 no.2
• /
• pp.117-137
• /
• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.11 no.2
• /
• pp.61-71
• /
• 2009

Most deciduous trees in temperate zone are dormant during the winter to overcome cold and dry environment. Dormancy of deciduous fruit trees is usually separated into a period of rest by physiological conditions and a period of quiescence by unfavorable environmental conditions. Inconsistent and fewer budburst in pear orchards has been reported recently in South Korea and Japan and the insufficient chilling due to warmer winters is suspected to play a role. An accurate prediction of the flowering time under the climate change scenarios may be critical to the planning of adaptation strategy for the pear industry in the future. However, existing methods for the prediction of budburst depend on the spring temperature, neglecting potential effects of warmer winters on the rest release and subsequent budburst. We adapted a dormancy clock model which uses daily temperature data to calculate the thermal time for simulating winter phenology of deciduous trees and tested the feasibility of this model in predicting budburst and flowering of Niitaka pear, one of the favorite cultivars in Korea. In order to derive the model parameter values suitable for Niitaka, the mean time for the rest release was estimated by observing budburst of field collected twigs in a controlled environment. The thermal time (in chill-days) was calculated and accumulated by a predefined temperature range from fall harvest until the chilling requirement (maximum accumulated chill-days in a negative number) is met. The chilling requirement is then offset by anti-chill days (in positive numbers) until the accumulated chill-days become null, which is assumed to be the budburst date. Calculations were repeated with arbitrary threshold temperatures from $4^{\circ}C$ to $10^{\circ}C$ (at an interval of 0.1), and a set of threshold temperature and chilling requirement was selected when the estimated budburst date coincides with the field observation. A heating requirement (in accumulation of anti-chill days since budburst) for flowering was also determined from an experiment based on historical observations. The dormancy clock model optimized with the selected parameter values was used to predict flowering of Niitaka pear grown in Suwon for the recent 9 years. The predicted dates for full bloom were within the range of the observed dates with 1.9 days of root mean square error.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.13 no.3
• /
• pp.187-197
• /
• 2010

Carbon dioxide Capture and Storage(CCS) is regarded as one of the most promising options to response climate change. CCS is a three-stage process consisting of the capture of carbon dioxide($CO_2$), the transport of $CO_2$ to a storage location, and the long term isolation of $CO_2$ from the atmosphere for the purpose of carbon emission mitigation. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the $CO_2$ mixture captured from the power plants and steel making plants contains many impurities such as $N_2$, $O_2$, Ar, $H_2O$, $SO_2$, $H_2S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification, transport and injection processes. In order to design a reliable $CO_2$ marine geological storage system, it is necessary to analyze the impact of these impurities on the whole CCS process at initial design stage. The purpose of the present paper is to compare and analyse the relevant physical property models including BWRS, PR, PRBM, RKS and SRK equations of state, and NRTL-RK model which are crucial numerical process simulation tools. To evaluate the predictive accuracy of the equation of the state for $CO_2-SO_2$ mixture, we compared numerical calculation results with reference experimental data. In addition, optimum binary parameter to consider the interaction of $CO_2$ and $SO_2$ molecules was suggested based on the mean absolute percent error. In conclusion, we suggest the most reliable physical property model with optimized binary parameter in designing the $CO_2-SO_2$ mixture marine geological storage process.

• Journal of Soil and Groundwater Environment
• /
• v.9 no.4
• /
• pp.1-7
• /
• 2004

To choose a organic acid and in-organic acid composite which is the most effective in soil-flushing process cleaning lead-contaminated sites, lead removal rates were investigated in the experiments with some organic acids; 0.01M of EDTA showed the highest lead-extraction rate ($69.4\%$) compared to the other organic acids. Furthermore, the lead removal rates were measured with 0.01M of EDIA and 0.1M of in-organic acid ; a EDTA and boric acid composite showed the highest lead-extraction rate ($68.8\%$) at pH5 compared to the other composites. As the concentration of boric acid was increased from 0.1M to 0.4M in a 0.01M of EDTA and boric acid composite, lead removal rate was decreased from $68\%\;to\;45\%$. But as the concentration of EDTA was increased from 0.01M to 0.04M in a EDTA and 0.1M of boric acid composite, permeability was decreased from $6.98{\times}10^{-4}cm/sec$ (0.01M of EDTA) to $5.99{\times}10^{-4}cm/sec$ (0.04M of EDTA). However, permeability was increased from $4.41{\times}10^{-4}cm/sec$ (0.03M of EDTA) to $6.26{\times}10^{-4}cm/sec$ (0.03M of EDTA and 0.1M of boric acid composite). indicating EDTA could increase lead dissolution/extraction rate and decrease permeability. In this system, lead remediation rate is the function of lead dissolution rate from soils and permeability of the composite into soils, and the optimized [EDTA]/[Boric acid] ratio is [0.01M]/[0.1M].

• Journal of Soil and Groundwater Environment
• /
• v.6 no.3
• /
• pp.53-59
• /
• 2001

There is a lot of method to manage the insanitary landfill but vertical cutoff walls have been widespreadly used and were installed into the subsurface to act as a barrier to horizontal groundwater flow, The stabilized material such as specialized cement or mixed soil with additives has been generally applied for the materials of the deep soil mixing barrier in korea. The amount of the stabilized material is dependent on the field conditions, because the mixing ratio of the material and the field soil should achieve a requirement in the coefficient of permeability, lower than 1.0$\times$$10^{7}$cm/sec. This study determined the quantity and optimized function ratio of the stabilized material in the formation process of the mixed barrier that was added with stabilized material on the field soil classified into SW-SC under USCS (Unified Soil Classification System). After that the fly ash and lime were selected as an additives an that could improve the function of the stabilized material and then the method to improve the functional progress in the usage of putting into the stabilized material as an appropriate ratio was studied and reviewed. The author used the flexible-wall permeameter for measuring the permeability and unconfined compressive strength tester for compressive strength, and in the view of environmental engineering the absorption test of heavy metals and leaching test regulated by Korean Waste Management Act were performed. As the results, the suitable mixing ratio of the stabilized material in the deep soil mixing barrier was determined as 13 percent. To make workability easy, the ratio of stabilized material and water was proven to be 1 : 1.5. With the results, the range of the portion of the additives(fly ash : lime= 70 : 30) was proven to be 20-40% for improving the function of the stabilized material, lowering of permeability. In heavy metal absorption assessment of the mixing barrier system with the additives, the result of heavy metal absorption was proved to be almost same with the case of the original stabilized material; high removal efficiency of heavy metals. In addition, the leaching concentration of heavy metals from the leaching test for the environmental hazard assessment showed lower than the regulated criteria.

• Journal of Bio-Environment Control
• /
• v.13 no.1
• /
• pp.51-55
• /
• 2004

The most commonly used inorganic nutrient compositions such as Murashige & Skoog medium have been optimized for heterotrophic growth. Therefore, they may not be optimal for photomixotrophic and photoautotrophic growth of plantlets. In photomixotrophic micropropagation, emdium sugar level is often lowered, while light and $CO_2$ levels in vessel are raised, and chlorophyllous explants are used to facilitate photosynthetic carbon acquisition. In a factorial experiment effect of addition (+) and omission(_) of organic materials (OM, 0.5 g ${\cdot}$ $m^{-3}$ each of thiamine, nicotinic acid and pyridoxine and 100 ${\cdot}$ $m^{-3}$ myo-inositiol) combined with three sucrose levels (0, 15, and 30 kg ${\cdot}$ $m^{-3}$) was tested on the growth of potato plantlets. Each of nodal cuttings with a leaf was cultured on 0.1${\times}$$10^{-4}m^{-3}$) MS agar ( 8 kg ${\cdot}$ $m^{-3}$) medium (pH 5.80 before autoclave) in glass test tubes (100 mm${\times}$25mm) capped with a sheet of transparent film with a 6 mm diameter gas permeable filter (5.1 air exchanges ${\cdot}$$h^{-1}$). Cultures were maintained in a room for 27 days at $23^{\circ}C$, 50% RH, 350-450${\mu}mol\;{\codt}\;mol^{-1}CO_2$, 16 h ${\cdot}$ $d^{-1}$ photoperiod at 13${\mu}mol\;{\codt}\;m\;{\codt}\;s^{-1}$ PPFD provided by white cool fluorescent lamps. Growth of potato plantlet in the +OM and -OM treatments were similar, while medium pH was 0.2 scale lower in the latter. Dry weight, % dry matter, and stem diameter enhanced, while shoot to root dry weight ratio, leaf area, chlorophyll concentration per gram dry weight, and medium pH decreased with increasing initial sucrose level. Interaction between OM and sucrose levels was observed in shoot length and medium pH. Results indicate that OM can be omitted from the medium without detrimental effect while addition of sucrose was beneficial for the photomixotrophic growth of potato plantlets under raised light and $CO_2$.

• Journal of Service Research and Studies
• /
• v.13 no.4
• /
• pp.97-112
• /
• 2023

Background: In modern society, the importance of Public Design has become increasingly significant in contributing to the enhancement of urban functionality and the quality of life of citizens. Smart Public Facilities have played a pivotal role in enriching user experience by improving accessibility, convenience, and safety, and in elevating the value of the city. This research recognizes the importance of Public Facilities and explores the potential of Smart Public Facilities in solving urban challenges and progressing towards sustainable and Inclusive cities. Method: The literature review comprehensively examines existing theories and research results on Smart Public Facilities. The case study analyzes actual examples of Smart Public Facilities implemented in cities both domestically and internationally, drawing out effects, user satisfaction, and areas for improvement. Through analysis and discussion, the results of the case studies are evaluated, discussing the potential development of Smart Public Facilities. Results: Smart Public Facilities have been found to bring positive changes in various aspects such as urban management, energy efficiency, safety, and information accessibility. In terms of urban management, they play a crucial role in optimization, social Inclusiveness, environmental protection, fostering citizen participation, and promoting technological innovation. These changes create a new form of urban space, combining physical space and digital technology, enhancing the quality of life in the city. Conclusion: This research explores the implications, current status, and functions of Smart Public Facilities in service and design aspects, and their impact on the urban environment and the lives of citizens. In conclusion, Smart Public Facilities have brought about positive changes in the optimization of urban management, enhancement of energy efficiency, increased information accessibility, User-Centric design, increased interaction, and social Inclusiveness. Technological innovation and the integration of Public Facilities have made cities more efficient and proactive, enabling data-based decision-making and optimized service delivery. Such developments enable the creation of new urban environments through the combination of physical space and digital technology. The advancement of Smart Public Facilities indicates the direction of urban development, where future cities can become more intelligent, proactive, and User-Centric. Therefore, they will play a central role in Public Design and greatly contribute to improving the urban environment and the quality of life of citizens.

• Journal of Bio-Environment Control
• /
• v.32 no.4
• /
• pp.434-441
• /
• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.1
• /
• pp.173-185
• /
• 2015

This study aims to investigate the characteristics and types of car accidents and establish a prediction model by analyzing 456 car accidents having occurred in the 11 tunnels in Busan, through statistical analysis techniques. The results of this study can be summarized as below. As a result of analyzing the characteristics of car accidents, it was found that 64.9% of all the car accidents took place in the tunnels between 08:00 and 18:00, which was higher than 45.8 to 46.1% of the car accidents in common roads. As a result of analyzing the types of car accidents, the car-to-car accident type was the majority, and the sole-car accident type in the tunnels was relatively high, compared to that in common roads. Besides, people at the age between 21 and 40 were most involved in car accidents, and in the vehicle type of the first party to car accidents, trucks showed a high proportion, and in the cloud cover, rainy days or cloudy days showed a high proportion unlike clear days. As a result of analyzing the principal components of car accident influence factors, it was found that the first principal components were road, tunnel structure and traffic flow-related factors, the second principal components lighting facility and road structure-related factors, the third principal factors stand-by and lighting facility-related factors, the fourth principal components human and time series-related factors, the fifth principal components human-related factors, the sixth principal components vehicle and traffic flow-related factors, and the seventh principal components meteorological factors. As a result of classifying car accident spots, there were 5 optimized groups classified, and as a result of analyzing each group based on Quantification Theory Type I, it was found that the first group showed low explanation power for the prediction model, while the fourth group showed a middle explanation power and the second, third and fifth groups showed high explanation power for the prediction model. Out of all the items(principal components) over 0.2(a weak correlation) in the partial correlation coefficient absolute value of the prediction model, this study analyzed variables including road environment variables. As a result, main examination items were summarized as proper traffic flow processing, cross-section composition(the width of a road), tunnel structure(the length of a tunnel), the lineal of a road, ventilation facilities and lighting facilities.