• Journal of Astronomy and Space Sciences
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• v.15 no.1
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• pp.119-138
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• 1998

Recently measurements of atmospheric trace gases from satellite are vigorous. So the development of its data processing algorithm is important. In this study, retrievalof vertical ozone profile from the atmospheric transmittance measured by satellite solar occultation method and its sensitivity to temperature and pressure are investigated. The measured transmittance from satellite is assumed to be given by the limb path transmittance simulated using annual averaged Umkehr data for Seoul. The limb path transmittance between wavelengths $9.89{\mu}m$ and $10.2{\mu}m$ is simulated with respect to tangent heights using the ozone data of HALOE SIDS(Hallogen Occultation Experiment Simulated Instrument Data Set) as an initial profile. Other input data such as pressure and temperature are also from HALOE SIDS. Vertical ozone profile is correctly retrieved from the measured transmittance by onion-peeling method from 50km to 11km tangent heights with the vertical resolution of 3km. The bias error of $\pm0.001$ in measured transmittance, the forced error of $\pm3K$ in each layer temperature, and the forced $\pm3%$ error in each layer pressure are assumed for sensitivity tests. These errors are based on the ADEOS/ILAS error limitation. The error in ozone amount ranges from -6.5% to +6.9% due to transmittance error, from -9.5% to +10.5% due to temperature error, and from -5.1% to +5.4% due to pressure error, respectively. The present study suggests that accurate vertical ozone profile can be retrieved from satellite solar occultation method. Accuracy of vertical temperature profile is especially important in the retrieval of vertical ozone profile.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.47-52
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• 2005

Obstructive Sleep Apnea (OSA) is a representative symptom of sleep disorder caused by the obstruction of upper airway. Because OSA causes not only excessive daytime sleepiness and fatigue, hypertension and arrhythmia but also cardiac arrest and sudden death during sleep in the severe case, it is very important to detect the occurrence and the frequency of OSA. OSA is usually diagnosed through the laboratory-based Polysomnography (PSG) which is uncomfortable and expensive. Therefore researches to improve the disadvantages of PSG are needed and studies for the detection of OSA using only one or two parameters are being made as alternatives to PSG. In this paper, we developed an algorithm for the detection of OSA based on Heart Rate Variability (HRV). The proposed method is applied to the ECG data sets provided from PhysioNet which consist of learning set and training set. We extracted features for the detection of OSA such as average and standard deviation of 1 minute R-R interval, power spectrum of R-R interval and S-peak amplitude from data sets. These features are applied to the input of neural network. As a result, we obtained sensitivity of $89.66\%$ and specificity of $95.25\%$. It shows that the features suggested in this study are useful to detect OSA.

• The Korean Journal of Nuclear Medicine
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• v.32 no.1
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• pp.20-31
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• 1998

A robust algorithm to disclose and display the difference of ictal and interictal perfusion may facilitate the detection of ictal hyperfusion foci. Diagnostic performance of localizing epileptogenic zones with subtracted SPECT images was compared with the visual diagnosis using ictal and interictal SPECT, MR, or PET. Ietal and interictal Tc-99m-HMPAO cerebral perfusion SPECT images of 48 patients(pts) were processed to get parametric subtracted images. Epileptogenic foci of all pts were diagnosed by seizure free state after resection of epileptogenic zones. In subtraction SPECT, we used normalized difference ratio of pixel counts(ictal-interictal)/interictal ${\times}100%$) after correcting coordinates of ictal and interictal SPECT in semi-automatized 3-dimensional fashion. We found epileptogenic zones in subtraction SPECT and compared the performance with visual diagnosis of ictal and interictal SPECT, MR and PET using post-surgical diagnosis as gold standard. The concordance of subtraction SPECT and ictal-interictal SPECT was moderately good(kappa=0.49). The sensitivity of ictal-interictal SPECT was 73% and that of subtraction SPECT 58%. Positive predictive value of ictal-interictal SPECT was 76% and that of subtraction SPECT was 64%. There was no statistical difference between sensitivity or positive predictive values of subtraction SPECT and ictal-interictal SPECT, MR or PET. Such was also the case when we divided patients into temporal lobe epilepsy and neocortical epilepsy. We conclude that subtraction SPECT we produced had equivalent diagnostic performance compared with ictal-interictal SPECT in localizing epileptogenic zones. Additional value of these subtraction SPECT in clinical interpretation of ictal and interictal SPECT should be further evaluated.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.25-31
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction. Although PCA has been applied in many areas successfully, it is sensitive to outliers due to the use of sum-square-error. Several variants of PCA have been proposed to resolve the noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA2, however, still can fall into a local optimum due to equal initial membership values for all data points. Another reason comes from the fact that RF-PCA2 is based on sum-square-error although fuzzy memberships are incorporated. In this paper, a variant of RF-PCA2 called RF-PCA3 is proposed. The proposed algorithm is based on the objective function of RF-PCA2. RF-PCA3 augments RF-PCA2 with the objective function of PCA and initial membership calculation using data distribution, which make RF-PCA3 to have more chance to converge on a better solution than that of RF-PCA2. RF-PCA3 outperforms RF-PCA2, which is demonstrated by experimental results.

• Progress in Medical Physics
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• v.17 no.4
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• pp.238-245
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• 2006

To assess the ability of an extravasation defection accessory (EDA) to detect the clinically important extravascular Injection of iodinated contrast material that was delivered with an automated mechanical power injector. The purpose of this study was to assess the ability of this device during clinically important episodes of extravasation. The EDA system was composed of a strain gage, an amplifier and a computer-based system. In the rabbit experimental cases, there were seven true-positive cases (range of the extravasation volumes: $14{\sim}23 ml$). The algorithm results showed seven true-positive cases (range of the extravasation volumes: $7{\sim}16ml$), nineteen true-negative cases, two false-positive cases and no false-negative cases. The EDA system had a sensitivity of 100% and a specificity of 90% for the detection of clinically important extravasation. The EDA system had good sensitivity for the detection of clinically important extravasation and the EDA system has the clinical potential for the early detection of extravasation of the contrast medium that is administered with power injectors.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.2
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• pp.115-124
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• 2017

This study was to develop the balance insole system for detecting and improving the muscle imbalance of left and right side in lower limbs. We were to verify the validation of balance insole system by analyzing the strategy of muscular activities and foot pressure according to sound feedback. We developed the balance insole based FSR sensor modules for estimating the muscle imbalance using detecting foot pressure. The insole system was FPCB have 8-spot FSR sensor with sensitivity range of 64-level. The participants were twenty peoples who have muscle strength differences in left and right legs over 20%. We measured the muscular activity and foot pressure of left and right side of lower limbs in various gait environment for verifying the improvement effect of muscle imbalance according to sound feedback. They performed gait in slope at 0, 5, 10, 15% and velocity at 3, 4, 5km/h. The result showed that the level of muscle imbalance reduced within 30% for sound feedback of balance insole system contrast to high level of muscle imbalance at 169.9~246.8% during normal gait for increasing slope and velocity. This study found the validation of balance insole system with sound feedback stimulus. Also, we thought that it is necessary to research on the sensitivity of foot area, detection of muscle imbalance and processing algorithm of correction threshold spot.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.639-646
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• 2017

The purpose of this study is to present the algorithm to minimize the image noise caused by deterioration of high X-ray container inspection equipment and the faulty detection sensors, and to improvement quality of the container inspection images using MATLAB Toolbox. The daily checking images for the container inspection were used with the subject images and the noise caused by the horizontal and vertical images was evaluated with Root Mean Square (RMS) method, which is the most basic evaluation method of digital radiation image. Also, quality of the improved images was evaluated compared to quality of the orignal images. As a result, all RMS value of the improved images was lower then the original images by a mean of 13.5% in the horizontal images and 18.2% in the vertical images respectively. Also so did RMS value of the improved container images, by a mean of 13.4% in the horizontal images and 19.1% in the vertical images respectively. These findings can be verified objectively and visually and they would help the reading process of the container images be effective in Korea Customs Service.

• Journal of Veterinary Clinics
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• v.24 no.2
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• pp.77-81
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• 2007

Diagnostic performance of polymerase chain reaction (PCR) for detecting Dirofilaria immitis in dogs was evaluated when no gold standard test was employed. An enzyme-linked immunosorbent assay test kit (SnapTM, IDEXX, USA) with unknown parameters was also employed. The sensitivity and specificity of the PCR from two-population model were estimated by using both maximum likelihood using expectation-maximization (EM) algorithm and Bayesian method, assuming conditional independence between the two tests. A total of 266 samples, 133 samples in each trial, were randomly retrieved from the heartworm database records during the year 2002-2004 in a university animal hospital. These data originated from the test results of military dogs which were brought for routine medical check-up or testing for heartworm infection. When combined 2 trials, sensitivity and specificity of the PCR was 96.4-96.7% and 97.6-98.8% in EM and 94.4-94.8% and 97.1-98% in Bayesian. There were no statistical differences between estimates. This finding indicates that the PCR assay could be useful screening tool for detecting heartworm antigen in dogs. This study was provided further evidences that Bayesian approach is an alternative approach to draw better inference about the performance of a new diagnostic test in case when either gold test is not available.

• Journal of Soil and Groundwater Environment
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• v.13 no.3
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• pp.37-44
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• 2008

Soil ecology has important roles in global ecosystems. However, soil ecological quality information is being ignored when assessing ecological impact of construction actions. And methods for classifying and assessing soil ecological quality have been very little established in comparison to those for animal and plant ecosystems. In this study, it was examined whether soil ecological quality information has influence on determining an eco-friendly route for a road construction project. For this, sensitivity analysis was systematically performed by varying the relative significance (weights) of soil ecological quality information among natural environmental and ecological factors. When the weight of soil ecological quality was greater than just 14%, the soil ecological quality information significantly influenced the determination of the eco-friendly routes for a specific road construction project. This demonstrates that soil ecological quality information has to be considered for more reliable environmental impact assessment, and also supports the validity of use of soil ecological quality information and its mapping technique in planning and siting of eco-friendly construction projects.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.