Kim, Jong-Gyu;Sagong, Myung;Lee, Jun S.;Lee, Yong-Joo
KSCE Journal of Civil and Environmental Engineering Research
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v.26
no.4C
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pp.255-264
/
2006
The auxiliary reinforcement method is normally applied to prevent a possible collapse of the tunnel face where the ground condition is not favorable or geologic information is not sufficient. Recently, several engineering approaches have been made to choose the effective reinforcement methods using expert system such as neural network and fuzzy theory field, among others. Even if the expert system has offered many decision aid tools to properly select the reinforcement method, the quantitative assessment items are not easy to estimate and this is why the data mining technique, widely used in the field of social science, medical treatment, banking and agriculture, is introduced in this study. Using decision tree together with PDA, the decision aids for reinforcement method based on field construction data are created to derive the field rules and future study will be concentrated on the application of the proposed methods in a variety of underground development cases.
The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.8
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pp.94-104
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2018
This purpose of this study is to extract the perceptual types of Organizational Citizenship Behavior(OCB) conceptual domain. OCB is a employee behavior that goes above and beyond the call of duty, that is discretionary and not explicitly recognized by the employing organization's formal reward system, and that contributes to organizational effectiveness. But, as is generally known, OCB is such a fuzzy concept that many researchers have been questioning the exact conceptual domain of OCB. In this context, we try to applicate Q-methodology to find more effective way of explaining the conceptual domain of OCB. Q-sample was constructed by a thorough review on the relevant literature, and P-sample is 14 employees of an manufacturing company. In conclusion, we find three types of the conceptual domain of OCB, that is coworker-oriented, organization-orienteded, and work-orienteed type. The paper ends with suggestions for future research directions.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.10
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pp.625-632
/
2018
This study was done to reduce total energy demand based on resource shortage problems and to provide improvement points for more efficient adjustment of the high insulation standards for saving energy in Korea. The demand sensitivity was fully considered by varying the slope of each building. The energy performance of the building was maximized by the introduction of outdoor air at night. A final low-energy building model was developed with the two measures combined, and the short-term operation of the night-fuzzy ventilation system was simulated. The result showed a reduction of about 6 to 7 percent compared to the base model. The results could have many implications in terms of the need to conduct demand sensitivity analyses in architectural design.
Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R2 = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R2 = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.
In order to achieve the low complexity and area, power in the design of Optical Image Stabilization (OIS) suitable for the smart phone, this paper presents the following design explorations, such as; optimization of gyroscope sampling rate, simple and accurate gyroscope filters, and reduced operating frequency of motion compensation, optimized bit width in ADC and DAC, evaluation of noise effects due to PWM driving. In experiments of gyroscope sampling frequencies, it is found that error values are unvaried in the frequency above 5KHz. The gyroscope filter is efficiently designed by combining the Fuzzy algorithm, to illustrate the reasonable compensation for the angle and phase errors. Further, in the PWM design, the power consumption of 2MHz driving is shown to decrease up to 50% with respect to the linear driving, and the imaging noises are reduced in the driving frequency above 2MHz driving frequency. The operating frequency could be reduced to 5KHz in controller and 10KHz in driver, respectively, in the motion compensation. For ADC and DAC, the optimized exploration experiments verify the minimum bit width of 11bits in ADC as well as 10bits in DAC without the performance degradation.
The purpose of the water distribution system is gradually changing to increase the flexibility for responding to various abnormal situations. In addition, it is essential to improve resilience through preparing emergency plans against water supply failure. The most efficient way is emergency interconnections which supply water from interconnected adjacent blocks. To operate successful interconnections, it is essential to evaluate the supply performance in spatial and temporal aspects. The spatial and temporal aspects are dominated by its interconnected pipes and interconnected reservoirs respectively. In this study, an emergency interconnection scenario where problem occurred in reservoir 1 at 0:00hr in A city, Korea. An Advanced-Pressure Driven Analysis model was used to simulate the volume and inflow volume of the interconnected reservoirs. Based on the hydraulic analysis results, a multi-dimensional evaluation of the supply performance was conducted by applying possible water supply range indicator (PWSRI) and possible water supply temporal indicator (PWSTI) which are based on fuzzy membership functions. As a result, it was possible to evaluate the supply performance on the sides of consumers in spatio-temporal aspects and to review whether established plans mitigate the damage as intended. It is expected to be used for decision making on structural and non-structural emergency plan to improve the performance of an emergency interconnection.
Zemansky, Gil;Hong, Yoon-Seeok Timothy;Rose, Jennifer;Song, Sung-Ho;Thomas, Joseph
Proceedings of the Korea Water Resources Association Conference
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2011.05a
/
pp.18-18
/
2011
Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.
BACKGROUND: This research has investigated the residue patterns of insecticide flubendiamide on three species of peaches with different surface forms, and the residue amounts of them when mixed with a spreader. METHODS AND RESULTS: Pesticide used for field application on peaches was 20% flubendiamide of suspension concentrate(SC) and was sprayed at a recommended rate. The residue amounts of flubendiamide in peach were analyzed by HPLC equipped with UV detector. After the observation with a microscope, the rank of fuzz amount on peach's surface was Kurakatawase, Wolmi in descending order and Cheonhong did not have any fuzz. The residue amounts of flubendiamide were 0.54 mg/kg for Kurakatawase, 0.43 mg/kg for Wolmi and 0.10 mg/kg for Cheonhong, respectively. When flubendiamide was used with a spreader, polyoxy ethylene methylpoly siloxane, the residue amount for Kurakatawase barely changed at 0.55 mg/kg regardless of mixing with a spreader, and at 0.53 mg/kg for Wolmi. In Cheonhong, the residue amount was 0.48 mg/kg, which increased by 4.8 times due to the use of a spreader. CONCLUSION: This result indicates that the residue amounts of flubendiamde were affected by the surface forms of peaches, and in the presence of a spreader the residue amount did not increase in fuzzy species, but was affected greatly for species without fuzz.
Journal of the Institute of Electronics Engineers of Korea CI
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v.41
no.3
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pp.1-10
/
2004
Quite many papers about moving objects database (MOD) have been Published. Most of them are concerning of improving efficiency of updating policy, but none of them talks about verification of system's requirements. No matter how efficient updating policy is employed, a system designer still has to verify if the MOD satisfies user's requirement at the beginning of system lifestyle. For example, if a MOD serves n moving objects, then the designer must verity if it can update information for n moving objects and provide new information to moving objects within specified time limit. For the purpose of requirement analysis of MODs, we build a Petri net model for MOD using Design/CPN, and then we show how to verify whether the MOD satisfies user's requirements by simulation. The contribution of this paper is providing a simulation model for requirement analysis of MOD for the first time. The model is expansion of our previous fuzzy-timing Petri net model. The distance-based updating policy, and distributed database management system are reflected in this model and system analysis for moving objects is considered. It is built in Design/CPN so that the simulation can be automatically performed. The application of our model is not limited to requirement analysis, it is useful to study other MOD design issues, such as the trade-offs between update cost and information accuracy, and between the tim interval needed for updating database and MOD system resources, etc.
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