• Journal of the Korean GEO-environmental Society
• /
• v.21 no.12
• /
• pp.5-10
• /
• 2020

In this study, the evolution of soil engineering property values according to excavation was analyzed through the inverse analysis for the OO deep excavation site located in Incheon. The stiffness of the ground was updated by comparing the horizontal wall deformation of the excavation support wall calculated by the finite element analysis at each stage of excavation and the value measured using an inclinometer. The updated stiffness was used to predict the response of the excavation support wall in the next excavation step. The finite element analysis method using the Hardening Soil model was used, and the stratum where the excavation support wall is located was selected as the stratum for the inverse analysis. The inverse analysis results showed that the stiffness value at the stiffness value at the initial stage of excavation is larger than the stiffness used in the original design. As the excavation proceeds, the stiffness calculated through the second inverse analysis was found to decrease compared to the value derived by the first inverse analysis. Therefore, it can be stated that the deformation of the excavation support wall can be accurately calculated through finite element analysis when an appropriate stiffness value is input according to the excavation stage.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.1
• /
• pp.195-201
• /
• 2014

In this study, face recognition system was designed based on polynomial Radial Basis Function Neural Networks(pRBFNNs) pattern classifier using 2-directional 2-dimensional principal component analysis algorithm. Existing one dimensional PCA leads to the reduction of dimension of image expressed by the multiplication of rows and columns. However $(2D)^2PCA$(2-Directional 2-Dimensional Principal Components Analysis) is conducted to reduce dimension to each row and column of image. and then the proposed intelligent pattern classifier evaluates performance using reduced images. The proposed pRBFNNs consist of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with the aid of fuzzy c-means clustering. In the conclusion part of rules. the connection weight of RBFNNs is represented as the linear type of polynomial. The essential design parameters (including the number of inputs and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. Using Yale and AT&T dataset widely used in face recognition, the recognition rate is obtained and evaluated. Additionally IC&CI Lab dataset is experimented with for performance evaluation.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.6
• /
• pp.713-723
• /
• 2019

Due to the climate change and various rainfall pattern, it is difficult to estimate a rainfall criterion which cause inundation for urban drainage districts. It is necessary to examine the result of inundation analysis by considering the detailed topography of the watershed, drainage system, and various rainfall scenarios. In this study, various rainfall scenarios were considered with the probabilistic rainfall and Huff's time distribution method in order to identify the rainfall characteristics affecting the inundation of the Hyoja drainage basin. Flood analysis was performed with SWMM and two-dimensional inundation analysis model and the parameters of SWMM were optimized with flood trace map and GA (Genetic Algorithm). By linking SWMM and two-dimensional flood analysis model, the fitness ratio between the existing flood trace and simulated inundation map turned out to be 73.6 %. The occurrence of inundation according to each rainfall scenario was identified, and the rainfall criterion could be estimated through the logistic regression method. By reflecting the results of one/two dimensional flood analysis, and AWS/ASOS data during 2010~2018, the rainfall criteria for inundation occurrence were estimated as 72.04 mm, 146.83 mm, 203.06 mm in 1, 2 and 3 hr of rainfall duration repectively. The rainfall criterion could be re-estimated through input of continuously observed rainfall data. The methodology presented in this study is expected to provide a quantitative rainfall criterion for urban drainage area, and the basic data for flood warning and evacuation plan.

• Journal of Biomedical Engineering Research
• /
• v.41 no.2
• /
• pp.107-119
• /
• 2020

The deep neural networks (DNN) that can replicate the behavior of the human expert who recognizes the characteristics of ECG waveform have been developed and studied to analyze ECG. However, although the existing DNNs can not provide the explanations for their decisions, those trials have attempted to determine whether patients have certain diseases or not and those decisions could not be accepted because of the absence of relating theoretical basis. In addition, these DNNs required a lot of training data to obtain sufficient accuracy in spite of the difficulty in the acquisition of relating clinical data. In this study, a small-sized continuous data processing DNN (C-DNN) was suggested to determine the simple characteristics of ECG wave that were not required additional explanations about its decisions and the C-DNN can be easily trained with small training data. Although it can analyze small input data that was selected in narrow region on whole ECG, it can continuously scan all ECG data and find important points such as start and end points of P, QRS and T waves within a short time. The star and end points of ECG waves determined by the C-DNNs were compared with the results performed by human experts to estimate the accuracies of the C-DNNs. The C-DNN has 150 inputs, 51 outputs, two hidden layers and one output layer. To find the start and end points, two C-DNNs were trained through deep learning technology and applied to a parameter acquisition algorithms. 12 lead ECG data measured in four patients and obtained through PhysioNet was processed to make training data by human experts. The accuracy of the C-DNNs were evaluated with extra data that were not used at deep learning by comparing the results between C-DNNs and human experts. The averages of the time differences between the C-DNNs and experts were 0.1 msec and 13.5 msec respectively and those standard deviations were 17.6 msec and 15.7 msec. The final step combining the results of C-DNN through the waveforms of 12 leads was successfully determined all 33 waves without error that the time differences of human experts decision were over 20 msec. The reliable decision of the ECG wave's start and end points benefits the acquisition of accurate ECG parameters such as the wave lengths, amplitudes and intervals of P, QRS and T waves.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.4
• /
• pp.13-19
• /
• 2016

This study presented the build-up of three-dimensional soil pollution map for precise analysis. To do this, survey on the existing pollutant region on Dongnae-gu, Busan that is the study subject, showed that it tended to produce 0.72 clusters. So, this study suggested to investigate center of $1km{\times}1km $ grid and, as the results of comparing the pollution map that input pollution figure values based on the actually investigation point showed precise results. And, it divided the standard of pollution into 5 levels in surface and underground space and the map was built up using IDW interpolation against the amount of polluted substance. The pollution of ground surface, flow of polluted substance, coefficient of permeability and ground water level that are 504 geotechnical informations were selected as the influential parameters in pollution analysis of underground space, and it calculated that to 0~20 points by dividing the characteristics. It enables the build-up of pollution map of ground surface-underground with depth that considers the characteristics of soil layers and it is considered that it is possible to analyze the general infiltration. And, it was considered that it enables more accurate forecast about influential analysis per depth and pollution of underground water.

• Korean Journal of Agricultural Science
• /
• v.30 no.2
• /
• pp.175-183
• /
• 2003

Fruit and vegetables are subjected to complex dynamic stresses in the transportation environment. During a long journey from the production area to markets, there is always some degree of vibration present. Vibration inputs are transmitted from the vehicle through the packaging to the fruit. Inside, these cause sustained bouncing of fruits against each other and container wall. These steady state vibration input may cause serious fruit injury, and this damage is particularly severe whenever the fruit inside the package is free to bounce, and is vibrated at its resonance frequency. The determination of the resonance frequencies of the fruit and vegetables may help the packaging designer to determine the proper packaging system providing adequate protection for the fruit, and to understand the complex interaction between the components of fruit when they relate to expected transportation vibration inputs. Instrumentation and technologies are described for determining the vibration response characteristics of the fruits with frequency range 3 to 150 Hz. The computer program for controlling the vibration exciter and the function generator and for measuring the vibration response characteristics of the fruits was developed. The resonance frequency of the pear ranged from 64.5 to 72.2 Hz and the amplitude at resonance was between 1.78 and 2.21 G-rms. The resonance frequency and amplitude at resonance decreased with the increase of the sample mass, and they were slightly affected by mechanical properties such as bioyield deformation and rupture deformation. Regression analysis was performed among the relatively high correlated parameters from the results of correlation coefficient analysis.

• Journal of the Korean Institute of Gas
• /
• v.20 no.5
• /
• pp.9-16
• /
• 2016

Buried pipe system is subject to leak or rupture due to internal and external defects with age. Especially, if the pipeline is designed for pressurized gas, the leak can wreak a devastating on its surrounding area. The current method of setting up underground gas pipeline is based on OGP criteria of applying one tenth of the inner pipe pressure. The criteria is applied irrespective of their burial depth or pipe's properties. At times, even the whole safety measures are totally ignored. Considering the magnitude of possible damage from a gas leakage, a precise analytical tool for the risk assessment is urgently needed. The study was conducted to assess possible scenarios of gas accidents and to develop a computer model to minimize the damage. The data from ETA was analyzed intensively, and the model was developed. The model is capable of predicting jet fire influence area with comprehensive input parameters, such as burial depth. The model was calibrated and verified by the historic accident data from Edison Township, New Jersey, the United States. The statistical model was also developed to compare the results of the model in this study and the existing OGP model. They were in good agreement with respect to damage predictions, such as radiation heat coming from 10 meters away from the heat source of gas flame.

• Advances in aircraft and spacecraft science
• /
• v.5 no.2
• /
• pp.225-237
• /
• 2018

The difficulties of satellite vibration testing are due to the commonly expressed qualification requirements being incompatible with the limited performance of the entire controlled system (satellite + interface + shaker + controller). Two features cause the problem: firstly, the main satellite modes (i.e., the first structural mode and the high and low tank modes) are very weakly damped; secondly, the controller is just too basic to achieve the expected performance in such cases. The combination of these two issues results in oscillations around the notching levels and high amplitude beating immediately after the mode. The beating overshoots are a major risk source because they can result in the test being aborted if the qualification upper limit is exceeded. Although the abort is, in itself, a safety measure protecting the tested satellite, it increases the risk of structural fatigue, firstly because the abort threshold has been already reached, and secondly, because the test must restart at the same close-resonance frequency and remain there until the qualification level is reached and the sweep frequency can continue. The beat minimum relates only to small successive frequency ranges in which the qualification level is not reached. Although they are less problematic because they do not cause an inadvertent test shutdown, such situations inevitably result in waiver requests from the client. A controlled-system analysis indicates an operating principle that cannot provide sufficient stability: the drive calculation (which controls the process) simply multiplies the frequency reference (usually called cola) and a function of the following setpoint, the ratio between the amplitude already reached and the previous setpoint, and the compression factor. This function value changes at each cola interval, but it never takes into account the sensor signal phase. Because of these limitations, we firstly examined whether it was possible to empirically determine, using a series of tests with a very simple dummy, a controller setting process that significantly improves the results. As the attempt failed, we have performed simulations seeking an optimum adjustment by finding the Least Mean Square of the difference between the reference and response signal. The simulations showed a significant improvement during the notch beat and a small reduction in the beat amplitude. However, the small improvement in this process was not useful because it highlighted the need to change the reference at each cola interval, sometimes with instructions almost twice the qualification level. Another uncertainty regarding the consequences of such an approach involves the impact of differences between the estimated model (used in the simulation) and the actual system. As limitations in the current controller were identified in different approaches, we considered the feasibility of a new controller that takes into account an estimated single-input multi-output (SIMO) model. Its parameters were estimated from a very low-level throughput. Against this backdrop, we analyzed the feasibility of an LQG control in cancelling beating, and this article highlights the relevance of such an approach.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.15 no.4
• /
• pp.297-313
• /
• 2009

Long-term trends and distribution patterns of water quality were investigated in the Gunsan coastal areas of Yellow Sea, Korea from 1972 to 2006. Water samples were collected at 6 stations and physicochemical parameters were analyzed including water temperature, salinity, suspended solids(SS), chemical oxygen demand(COD), dissolved oxygen(DO) and nutrients. Spatial distribution patterns of temperature, DO and SS were not clear among stations but the seasonal variations were distinct except COD and SS. The trend analysis by principal component analysis(PCA) during 24 years revealed the significant variations in water quality in the study area. Spatial water qualities were clearly classified into 3 clusters by PCA; station cluster 1, 2~4, and 5~6. Annual water qualities were clearly classified into 4 surface water clusters and 5 bottom water clusters by PCA. By this multi-variate analysis. The annual trends were summarized as follows; Salinity, pH and DO tended to increase since late 1970's, COD to increase since 1987, and SS to decrease and nutrients to increase in Gunsan coastal waters due to the input of fresh water from land same as in Kyoungin coastal area, Asan coastal area and Choensoo bay.

• Journal of the Korean earth science society
• /
• v.23 no.7
• /
• pp.565-574
• /
• 2002

Based on previous investigations of aerial photographs and topographical surveys, this study focuses on the sedimentologic features of the Daebudo area including sedimentation processes, sedimentary facies and hydrologic conditions of the erosional coast. A total of 137 surface sediments and one core (by hand auger) sediment were obtained to interpret the depositional environment of the erosional coast in the macro-tidal coast. Surface sediments are distributed from sandy gravel (sG) to silt (Z). Textural parameters are characterized not only by coarse, poorly sorted, positive skewed and multi-modal distribution in the supra-tidal flat, but also finer, relatively well-sorted, symmetric distribution in the intertidal flat. According to the C/M diagram, sediment transport modes of study area are characterized by the mixed mode of suspension and bedload in the upper-, middle-tidal flat and by uniform suspension in the lower-tidal flat due to tidal effect. Vertical sediment distribution of the core, collected near shoreline, shows coarsening-upward, poorly sorted pattern by the input of detritus resulting from coastal erosion. Considering the sedimentological features of the study area, it appears to be composed of a coastal zone changed by not only artificial reclamation, but also by natural processes such as strong wave action due to typhoons and storms during high water level and long/short-term sea level rising. As a result, tide-dominated erosional coasts show that the shore is affected by local, temporal and hydrological conditions near high tide level and that the intertidal flat is represented by a general tide-dominated sedimentary environment.