• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.305-308
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• 2001

In this paper, we realized a transceiver system for short distance communication with a commercial RF module working in ISM band and a microprocessor. Also we measured system performance by transmitting baseband data in a building and then we compared the demodulated 긴ta bits with stored data bits in a PC connected with demodulator. The RF module in the experiments works oかy in the bandwidth, 424MHz - 429MHz. with FM mode. The signal level degrades as the distance between transmitter and receiver increases we measured the signal level and bit error in the building of engineering college of our university. we present the measured data with various locations in the building. and the data may be used in design short distance network in a building.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1065-1073
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• 2002

A new damage identification technique using static displacement data is developed to assess the structural integrity of bridge structures. In the conventional damage assessment techniques using dynamic response, it is usually difficult to obtain a significant natural frequencies variation from the measured data because the natural frequencies variation is intrinsically not sensitive to the damage of a bridge. In this proposed identification method, the stiffness reduction of the bridges can be estimated using the static displacement data measured periodically and a specific loading test is not required. The static displacement data due to the dead load of the bridge structure can be measured by devices such as a laser displacement sensor. In this study, structural damage is represented by the reduction in the elastic modulus of the element. The damage factor of the element is introduced to estimate the stiffness reduction of the bridge under consideration. Finally, the proposed algorithm is verified using various numerical simulation and compared with other damage identification method. Also, the effect of noise and number of damaged elements on the identification are investigated. The results show that the proposed algorithm is efficient for damage identification of the bridges.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.881-886
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• 2004

This paper presents the inverse dynamic analysis of the wheel loader manipulator based on the experimental data. A three dimensional rigid multi-body model of the wheel loader manipulator was built up. The inverse dynamic analysis for the typical operation mode was carried out by the ADAMS program. In order to verify the analysis result with the measured one, the hydraulic pressure and displacements of the cylinders were measured and the inverse dynamic analysis was carried out using experimental data. From the results of the analysis and measurement, it was concluded that the computational driving force showed good agreement with the measured one.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.47-50
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• 2000

DC Gummel-Poon SPICE model parameter extraction program has been implemented. This program extracts the parameters from measured data using Levenberg-Marquardt algorithm. Measured data consist of forward and reverse Gummel plot, forward and reverse output characteristics and RE and RC measurements.

• Smart Structures and Systems
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• v.30 no.6
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• Ocean and Polar Research
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• v.30 no.2
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• pp.149-158
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• 2008

The characteristic analysis of the estimated population parameters, i.e., standard deviation and error bound of coastal pollutant concentrations (hereafter PC, i.e., COD, TN, and TP concentrations), was carried out by using environmental data with different sampling frequency in Lake Shihwa and Incheon coastal zone. The results clearly show that standard deviation of the PC increases as its mean value increases. The error bounds of the annual mean values based on seasonally measured DO concentrations and PC data in Incheon coastal zone were estimated as ranges 2.26 mg/l, $0.68{\sim}0.86\;mg/l$, $0.62{\sim}0.80\;mg/l$, and $0.074{\sim}0.082\;mg/l$, respectively. In terms of annual mean of the DO concentration and PC in Lake Shihwa, the error bounds based on monthly measured data from 1997 to 2003 were also estimated as ranges 4.0 mg/l, 3.0 mg/l, $0.5{\sim}1.0\;mg/l$, and 0.05 mg/l, respectively. The error bound on the basis of real-time monitoring data is $7{\sim}13%$ only as compared to that of monthly measured data.

• Journal of Korean Society of Water and Wastewater
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• v.17 no.4
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• pp.495-502
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• 2003

In order to modify incorrect flow data in the sewage system, the method using the stage-discharge relation and hydraulic characteristic curve of sewer pipe are applied. The modified data were verified with field measured data and the infiltration analysis using the modified data was carried out. When flowrate were measured using the flow-meter in fair weather, the stage data were comparatively consistent but velocity data were very poor for the most part. Therefore, it was recommended that sewage flowrate variation characteristic curve and infiltration were computed using the modified data on the basis of stage data. Especially, in the case of using the hydraulic characteristic curve, extrapolation results of the rainy season flowrate using regression curve on the basis of the data in fair weather were also reasonable.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.6
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• pp.25-31
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• 2009

In this study, pollutant loads delivery ratio by flow duration in Hwangryoung A watershed was estimated. The delivery ratio was estimated with measured data by Ministry of Environment(MOE) and the regression equation based on geomorphic parameters. Eight day interval flow data measured by the MOE were converted to daily flow to calculate daily load and flow duration curve by correlating data of neighboring station which has daily flow data. Regression equation developed by previous study was tested to study watershed and found to be satisfactory. The delivery ratios estimated by two methods were compared. For the case of Biochemical oxygen demand(BOD), the delivery ratios of low flow condition were 7.6 and 15.5% by measured and regression equation, respectively. Also, the delivery ratios of Total phosphorus(T-P) for normal flow condition were 13.3 and 6.3% by measured and regression equation, respectively.

• Korean Journal of Occupational Health Nursing
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• v.21 no.3
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• pp.317-325
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• 2012

Purpose: This study was to examine the effects of noise block on anxiety and vital sign of gynecologic laparoscopic surgery. Methods: The data were collected from March to May 2011. Participants were sixty patients with gynecologic laparoscopic surgery, divided into 30 of experimental group and 30 of control group at C University hospital located in I city. The day before surgery, demographic data, trait-state anxiety and vital signs were measured at ward. After noise block, the data were measured using VAS anxiety and vital signs before anesthesia and in recovery room. And then state anxiety and vital signs were measured in ward after surgery. The data were analyzed by $x^2$-test, t-test, repeated measured ANOVA and Bonferroni comparison method using SPSS/WIN 19.0. Results: After conducting noise block program, the experimental group showed significant decrease in state anxiety and heart rate compared to those of the control group. But there were not significant differences in VAS anxiety, systolic pressure and diastolic pressure between two groups. Conclusion: This program can be regarded as an effective nursing intervention for the management of anxiety with gynecologic laparoscopic surgery.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.17-20
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• 2001

In this paper, we realized a transceiver system for short distance communication with a commercial RF module working in ISM band. Also we measured system performance by transmitting baseband data in a building and then we compared the demodulated data bits with stored data bits in a PC connected with demodulator. The RF module In the experiments works only in the bandwidth of 424MHz-429MHz. The signal level degrades as the distance between transmitter and receiver increases. We measured the signal level and bit error and present the measured results with various locations in the building. And it is concluded that the measured data may be used in the design of short distance network in a building.