• Genomics & Informatics
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• v.5 no.3
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• pp.102-106
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• 2007

Radiofrequency (RF) radiation at the frequency of mobile phones has been not reported to induce cellular responses in in vitro and in vivo models. We exposed HEI-OC1, conditionally-immortalized mouse auditory cells, to RF radiation to characterize cellular responses to 1763 MHz RF radiation. While we could not detect any differences upon RF exposure, whole-genome expression profiling might provide the most sensitive method to find the molecular responses to RF radiation. HEI-OC1 cells were exposed to 1763 MHz RF radiation at an average specific absorption rate (SAR) of 20 W/kg for 24 hr and harvested after 5 hr of recovery (R5), alongside sham-exposed samples (S5). From the whole-genome profiles of mouse neurons, we selected 9 differentially-expressed genes between the S5 and R5 groups using information gain-based recursive feature elimination procedure. Based on support vector machine (SVM), we designed a prediction model using the 9 genes to discriminate the two groups. Our prediction model could predict the target class without any error. From these results, we developed a prediction model using biomarkers to determine the RF radiation exposure in mouse auditory cells with perfect accuracy, which may need validation in in vivo RF-exposure models.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.95-102
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• 1985

An efficient numerical scheme for assessing the two-dimensional diffusion problem for modelling impurity profile in semiconductor is described. 4 unique combination of ADI (Al-ternating Direction Bmplicit) method and Gauss Elimination has resulted in a reduction of CPU time for most diffusion processes by a factor of 3, compared to other iteration schemes such as SOR (Successive Over-Relaxation) or Stone's iterative method without additional storage re-quirement. Various numerical schemes were compared for 2-D as well as 1-0 diffusion profile in terms of their CPU time while retaining the magnitude of relative error within 0.001%. good agree-ment between 1-D and 2-D simulation profile as well as between 1-D simulation profile and experiment has been obtained.

• Journal of Korean Society of Archives and Records Management
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• v.16 no.2
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• pp.29-55
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• 2016

Korean public organizations create electronic documents through electronic document management systems under the e-Government scheme. A majority of these public documents are saved in vendor-dependent file formats, mainly HWP. Vendor-dependent formats can be opened only with specific software, which requires purchase. As the license does not guarantee compatibility between past and future versions, interoperability problems occur in long-term preservation, which need to be solved. Any error from the elimination of styles or no matching elements in document definition during conversion from vendor-dependent formats to the XML-based standard exchange format leads to file open failure or the modification of original documents. This study introduces the Open Document Format (ODF) and investigates the effects of adopting ODF in the creation, exchange, management, and preservation of public records.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3A
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• pp.235-243
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• 2009

In this paper, we investigate the cognitive and cooperative communication scheme to improve the spectral efficiency in multiuser OFDMA systems using wireless relays. First, we propose the frame structure in which the efficient frequency reuse scheme with the cognitive technique is performed to increase the system throughput. And in the case where the THP (Tomlinson-Harashima preceding) is used for the elimination of interference from the relay, we derive the effective signal to noise ratio of the link largely affected by the channel quantization error. From the system level simulation results, it is shown that the proposed cognitive and cooperative communication scheme increases the overall system performance including the feedback overhead.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.75-82
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• 2004

A metrological atomic force microscope (M-AFM) was developed fur the length measurements of nanometer range, through the modification of a commercial AFM. To eliminate nonlinearity and crosstalk of the PZT tube scanner of the commercial AFM, a two-axis flexure hinge scanner employing built-in capacitive sensors is used for X-Y motion instead of PZT tube scanner. Then two-dimensional displacement of the scanner is measured using two-axis heterodyne laser interferometer to ensure the meter-traceability. Through the measurements of several specimens, we could verify the elimination of nonlinearity and crosstalk. The uncertainty of length measurements was estimated according to the Guide to the Expression of Uncertainty in Measurement. Among several sources of uncertainty, the primary one is the drift of laser interferometer output, which occurs mainly from the variation of refractive index of air and the thermal stability. The Abbe error, which is proportional to the measured length, is another primary uncertainty source coming from the parasitic motion of the scanner. The expanded uncertainty (k =2) of length measurements using the M-AFM is √(4.26)$^2$+(2.84${\times}$10$^{-4}$ ${\times}$L)$^2$(nm), where f is the measured length in nm. We also measured the pitch of one-dimensional grating and compared the results with those obtained by optical diffractometry. The relative difference between these results is less than 0.01 %.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.195-200
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• 2006

The conventional discrete circuit for ABS/TCS system was examined and the problems of the system were analyzed by computer simulation. In order to improve the performance of ABS/TCS system, interface IC which has error compensation, comparator and under voltage lock-out circuit was designed and their electrical characteristics were investigated. The voltage regulator was included to compensate the temperature variation in the temperature range from $-20^{\circ}C$ to $120^{\circ}C$ for automobile environment. ABS and brake signal were separated using the duty factor of same frequency or different frequencies. UVLO(Under Voltage Lock-Out) circuit and constant current circuit were applied for the elimination of noise, and protection circuit was applied to cut the excess current off. Layout for IC fabrication was designed to enhance the electrical performance of ABS/TCS system. Layout was consisted of 11 masks, arrayed effectively 8 pads to reduce the current loss. We can see that the result of layout simulation was better than the result of bread board.

• Journal of Korean Society of Rural Planning
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• v.28 no.1
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• pp.57-69
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• 2022

Crop classification is very important for estimating crop yield and figuring out accurate cultivation area. The purpose of this study is to classify crops harvested in fall in Idam-ri, Goesan-gun, Chungcheongbuk-do by using unmanned aerial vehicle (UAV) images and support vector machine (SVM) model. The study proceeded in the order of image acquisition, variable extraction, model building, and evaluation. First, RGB and multispectral image were acquired on September 13, 2021. Independent variables which were applied to Farm-Map, consisted gray level co-occurrence matrix (GLCM)-based texture characteristics by using RGB images, and multispectral reflectance data. The crop classification model was built using texture characteristics and reflectance data, and finally, accuracy evaluation was performed using the error matrix. As a result of the study, the classification model consisted of four types to compare the classification accuracy according to the combination of independent variables. The result of four types of model analysis, recursive feature elimination (RFE) model showed the highest accuracy with an overall accuracy (OA) of 88.64%, Kappa coefficient of 0.84. UAV-based RGB and multispectral images effectively classified cabbage, rice and soybean when the SVM model was applied. The results of this study provided capacity usefully in classifying crops using single-period images. These technologies are expected to improve the accuracy and efficiency of crop cultivation area surveys by supplementing additional data learning, and to provide basic data for estimating crop yields.

• Advances in concrete construction
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• v.14 no.3
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• pp.185-194
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• 2022

For producing cement and concrete, the construction field has been encouraged by the usage of industrial soil waste (or) secondary materials since it decreases the utilization of natural resources. Simultaneously, for ensuring the quality, the analyses of the strength along with durability properties of that sort of cement and concrete are required. The prediction of strength along with other properties of High-Performance Concrete (HPC) by optimization and machine learning algorithms are focused by already available research methods. However, an error and accuracy issue are possessed. Therefore, the Enhanced Deep Neural Network (EDNN) based strength along with durability prediction of HPC was utilized by this research method. Initially, the data is gathered in the proposed work. Then, the data's pre-processing is done by the elimination of missing data along with normalization. Next, from the pre-processed data, the features are extracted. Hence, the data input to the EDNN algorithm which predicts the strength along with durability properties of the specific mixing input designs. Using the Switched Multi-Objective Jellyfish Optimization (SMOJO) algorithm, the weight value is initialized in the EDNN. The Gaussian radial function is utilized as the activation function. The proposed EDNN's performance is examined with the already available algorithms in the experimental analysis. Based on the RMSE, MAE, MAPE, and R² metrics, the performance of the proposed EDNN is compared to the existing DNN, CNN, ANN, and SVM methods. Further, according to the metrices, the proposed EDNN performs better. Moreover, the effectiveness of proposed EDNN is examined based on the accuracy, precision, recall, and F-Measure metrics. With the already-existing algorithms i.e., JO, GWO, PSO, and GA, the fitness for the proposed SMOJO algorithm is also examined. The proposed SMOJO algorithm achieves a higher fitness value than the already available algorithm.

• Smart Structures and Systems
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• v.33 no.3
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• pp.189-199
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• 2024

To properly extract the strain components under varying operational conditions is very important in bridge health monitoring. The abnormal sensor readings can be correctly identified and the expected operational performance of the bridge can be better understood if each strain components can be accurately quantified. In this study, strain components under varying load conditions, i.e., temperature variation and live-load variation are evaluated based on field strain measurements collected from a real concrete box-girder bridge. Temperature-induced strain is mainly regarded as the trend variation along with the ambient temperature, thus a smoothing technique based on the wavelet packet decomposition method is proposed to estimate the temperature-induced strain. However, how to effectively extract the vehicle-induced strain is always troublesome because conventional threshold setting-based methods cease to function: if the threshold is set too large, the minor response will be ignored, and if too small, noise will be introduced. Therefore, an autoencoder framework is proposed to evaluate the vehicle-induced strain. After the elimination of temperature and vehicle-induced strain, the left of which, defined as the model error, is used to assess the operational performance of the bridge. As empirical techniques fail to detect the degraded state of the structure, a clustering technique based on Gaussian Mixture Model is employed to identify the damage occurrence and the validity is verified in a simulation study.

• Journal of radiological science and technology
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• v.30 no.1
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• pp.1-6
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• 2007

This study is to decrease compound noise in x-ray films. This study compared Signal to noise ratio(SNR), Peak signal to noise ratio(PSNR), Mean square error(MSE) to surface of the earth. In addition, we evaluated noise elimination effect according to the kernel size of Median filter. This experiments show that some filters are useful by finding image that is near in circle image comparing circle picture with each processed picture. In noise power value, when cutoff frequency was compared with other filters of cutoff frequency. Cutoff frequency of $2/3\pi{\sim}3/4\pi$ is good and it shows good SNR and PSNR. Therefore, it can display high filter effect. As Median Filter's Kernel size grows SNR value gets bigger, which shows better filter effect. Most pictures are distorted after filter application in medical treatment image. It is important to keep spatial resolution in most medical images. Visual estimation as well as quantitative indicators should be necessary for a better image.