• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.30-38
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• 2017

In this paper, we propose an underwater acoustic sensor fault detection method for passive sonar systems. In general, a passive sonar system displays processed results of array signals obtained from tens of the acoustic sensors as a two-dimensional image such as displays for broadband or narrowband analysis. Since detection result display in the operation software is to display the accumulated result through the array signal processing, it is difficult to determine the possibility where signal may be contaminated by the fault or failure of a single channel sensor. In this paper, accordingly, we propose a detection method based on the analysis of RMSCR (Root Mean Square Crossing-Rate), and the processing techniques for the faulty sensors are analyzed. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured by using signals acquired from real array being operated in several coastal areas. Besides, we compare performance of fault processing techniques. From the experiments, it is shown that the proposed method works well in underwater environments with high average RMS, and mute (set to zero) shows the best performance with regard to fault processing techniques.

• Imaging Science in Dentistry
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• v.47 no.3
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• pp.165-174
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• 2017

Purpose: This study was performed to investigate the influence of object shape and distance from the center of the image on the volumetric accuracy of cone-beam computed tomography (CBCT) scans, according to different parameters of tube voltage and current. Materials and Methods: Four geometric objects(cylinder, cube, pyramid, and hexagon) with predefined dimensions were fabricated. The objects consisted of Teflon-perfluoroalkoxy embedded in a hydrocolloid matrix (Dupli-Coe-Loid TM; GC America Inc., Alsip, IL, USA), encased in an acrylic resin cylinder assembly. An Alphard Vega Dental CT system (Asahi Roentgen Ind. Co., Ltd, Kyoto, Japan) was used to acquire CBCT images. OnDemand 3D (CyberMed Inc., Seoul, Korea) software was used for object segmentation and image analysis. The accuracy was expressed by the volume error (VE). The VE was calculated under 3 different exposure settings. The measured volumes of the objects were compared to the true volumes for statistical analysis. Results: The mean VE ranged from -4.47% to 2.35%. There was no significant relationship between an object's shape and the VE. A significant correlation was found between the distance of the object to the center of the image and the VE. Tube voltage affected the volume measurements and the VE, but tube current did not. Conclusion: The evaluated CBCT device provided satisfactory volume measurements. To assess volume measurements, it might be sufficient to use serial scans with a high resolution, but a low dose. This information may provide useful guidance for assessing volume measurements.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.736-745
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• 2020

Objective: To identify the initial chest computed tomography (CT) findings and clinical characteristics associated with the course of coronavirus disease 2019 (COVID-19) pneumonia. Materials and Methods: Baseline CT scans and clinical and laboratory data of 72 patients admitted with COVID-19 pneumonia (39 men, 46.2 ± 15.9 years) were retrospectively analyzed. Baseline CT findings including lobar distribution, presence of ground glass opacities, consolidation, linear opacities, and lung severity score were evaluated. The outcome event was recovery with hospital discharge. The time from symptom onset to discharge or the end of follow-up (for those remained hospitalized) was recorded. Data were censored in events such as death or discharge without recovery. Multivariable Cox proportional hazard regression was used to explore the association between initial CT, clinical or laboratory findings, and discharge with recovery, whereby hazard ratio (HR) values < 1 indicated a lower rate of discharge at four weeks and longer time until discharge. Results: Thirty-two patients recovered and were discharged during the study period with a median length of admission of 16 days (range, 9 to 25 days), while the rest remained hospitalized at the end of this study (median, 17.5 days; range, 4 to 27 days). None died during the study period. After controlling for age, onset time, lesion characteristics, number of lung lobes affected, and bilateral involvement, the lung severity score on baseline CT (> 4 vs. ≤ 4 [reference]: adjusted HR = 0.41 [95% confidence interval, CI = 0.18-0.92], p = 0.031) and initial lymphocyte count (reduced vs. normal or elevated [reference]: adjusted HR = 0.14 [95% CI = 0.03-0.60], p = 0.008) were two significant independent factors that influenced recovery and discharge. Conclusion: Lung severity score > 4 and reduced lymphocyte count at initial evaluation were independently associated with a significantly lower rate of recovery and discharge and extended hospitalization in patients admitted for COVID-19 pneumonia.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.4
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• pp.257-267
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• 2014

The distributions of trace metals in the East Sea were investigated during the R/V Lavrentyev cruise (July 2009) in which four transects from Russia shore to South were conducted to collect 25 surface water samples. The total dissolved concentrations of Cu and Ni were measured using ICP-MS, DRC-e. In the coastal area, their concentrations of Russia shore (Cu, 1.51; Ni, 1.82 nM) were 1.9 times for Cu and 2.0 times for Ni lower than Korea shore (Cu, 2.87; Ni, 3.71 nM). In the subregion, their concentrations of Warm region (Cu, 3.03; Ni, 2.28 nM) were higher for Cu than Cold region (Cu, 2.04; Ni, 2.28 nM). The distributions of Cu and Ni concentrations were divided by lowest level at $10^{\circ}C$ of water temperature. In this study period, the surface water temperatures of Russia shore and Japan basin were lower than $10^{\circ}C$ and them of Ulleung basin and Sakhalin shore were higher. Below $10^{\circ}C$, Cu and Ni concentrations increased when surface water temperatures decreased. Above $10^{\circ}C$, their concentrations increased with temperature, which showed highest concentrations in the Ulleung basin, directly influenced by flux from East Korean Warm Current. By comparing with other sea areas (Western Mediterranean, Atlantic), Cu concentrations in the East Sea were a little higher and Ni concentrations were lower. Particularly as the level of Cu in the offshore in the Ulleung basin were higher than in the coastal area, We can suggest that the atmospheric flux of Cu is relatively important in this area.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.4
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• pp.275-284
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• 2008

Purpose: We intended to evaluate myocardial oxygen consumption ($MVO_2)$ by applying recirculation correction and modified one-compartment model to have a reference range of $MVO_2$ in normal young population and to reveal the effect of recirculation on time-activity curve (TAC). Materials and Methods: In nine normal male volunteers with mean age of $26.3{\pm}4.0$, $MVO_2$ was estimated with 925 MBq (25mCi) of $^{11}C$-Acetate (Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea) and PET/CT (Biograph 6, Siemens Medical Solution, Germany). Analysis software such as $MATLAB^{(R)}$ v7.1 (Mathworks, Inc., United States), $Excel^{(R)}$ 2007 (Microsoft, United States), and $SPSS^{(R)}$ v12.0 (Apache Software Foundation, United States) were used. Twenty three frames were of $12{\times}10$, $5{\times}60$, $3{\times}120$, $2{\times}300's$ duration, respectively. The modified one-compartmental model and the recirculation correction method were applied. Statistical analysis was performed by using Test of Normality, ANOVA and Post-Hoc (Scheffe's) analysis, and p-value less than 0.05 was considered as significant. Results: The normal reference ranges of $MVO_2$ were presented as $3.18-4.64\;{\times}\;10^{-4}\;ml/g/sec$, $1.91-3.94\;{\times}\;10^{-4}\;ml/g/sec$, $4.31-6.40\;{\times}\;10^{-4}\;ml/g/sec$, $2.84-4.53\;{\times}\;10^{-4}\;ml/g/sec$ and $3.42-5.00\;{\times}\;10^{-4}\;ml/g/sec$ in the septum, the inferior wall, the lateral wall, the anterior wall and the entire wall, respectively. In addition, it was noted that the dual exponentiality of the clearance curve is due to the recirculation effect and that the characteristic of the curve is essentially mono-exponential. Conclusion: $^{11}C$-Acetate is a radiotracer worthwhile to assess $MVO_2$. Re-circulated $^{11}C$ can influence TAC of $^{11}C$ in myocadia and so the recirculation correction must be considered when measuring $MVO_2$.

• Journal of radiological science and technology
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• v.29 no.4
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• pp.249-255
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• 2006

Purpose: The diagnostic utility of fluorine-18 2-deoxy-D-glucose positron emission tomograhpy ($^{18}F-FDG $PET) for the non-invasive differentiation of focal lung lesions originated from cancer or inflammation disease by combined visual image interpretation and semi-quantitative uptake value analysis has been documented. In general, Standardized Uptake Value(SUV) is used to diagnose lung disease. But SUV does not contain dynamic information of lung tissue for the glucose. Therefore, this study was undertaken to hypothesis that analysis of dynamic kinetics of focal lung lesions base on $^{18}F-FDG$ PET may more accurately determine the lung disease. So we compared Time Activity Curve(TAC), Standardized Uptake Value-Dynamic Curve(SUV-DC) graph pattern with Glucose Metabolic Rate(MRGlu) from Patlak analysis. Methods: With lung disease, 17 patients were examined. They were injected with $^{18}F-FDG$ over 30-s into peripheral vein while acquisition of the serial transaxial tomographic images were started. For acquisition protocol, we used twelve 10-s, four 30-s, sixteen 60-s, five 300-s and one 900-s frame for 60 mins. Its images were analyzed by visual interpretation TAC, SUV-DC and a kinetic analysis(Patlak analysis). The latter was based on region of interest(ROIs) which were drawn with the lung disease shape. Each optimized patterns were compared with itself. Results: In TAC patterns, it hard to observe cancer type with inflammation disease in early pool blood area but over the time cancer type slope more remarkably increased than inflammation disease. SUV-DC was similar to TAC pattern. In the result of Patlak analysis, In time activity curve of aorta, even though inflammation disease showed higher blood activity than cancer, at first as time went by, blood activity of inflammation disease became the lowest. However, in time activity curve of tissue, cancer had the highest uptake and inflammation disease was in the middle. Conclusion: Through the examination, TAC and SUV-DC could approached the results that lung cancer type and inflammation disease type has it's own difference shape patterns. Also, it has outstanding differentiation between cancer type and inflammation in Patlak and MRGlu analysis. Through these analysis methods, it will helpful to separation lung disease.

• Childhood Kidney Diseases
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• v.14 no.1
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• pp.42-50
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• 2010

Purpose : The clinical characteristics and associated anomalies in children with solitary kidney (SK) were analyzed retrospectively. Methods : Total 38 children diagnosed to have SK at our hospital between December 1989 and December 2009 were recruited, and the clinical records including imaging studies were retrospectively reviewed. SK was defined as unilateral renal agenesis by imaging studies only, and patients with regression of unilateral dysplastic kidney were excluded. Results : Among total 38 patients, 12 were male. The median age at the diagnosis of SK was 6.5 months (at birth-13 years). SK was detected by prenatal ultrasonography in 14 patients and during work-up for renal or urinary tract diseases in 13 (including urinary tract infection in 7). In 10 patients, SK was detected incidentally. Anomalies in the SK were noted in 17 patients including vesicoureteral reflux in 11. Other anomalies in the genitourinary tract were present in 16 patients, and multi-organ-involving syndromes or chromosomal anomalies were detected in 9. The mean duration of follow-up was 9 years (9 months-20 years). Two patients developed chronic renal failure during follow-up, and the median serum creatinine concentration of the remaining 36 at their last follow-up was 0.6 mg/dL. Conclusion : SK may be isolated and clinically asymptomatic; it is frequently accompanied by other anomalies in genitourinary tract and other organs, some of which can induce progressive renal dysfunction. Early recognition of associated anomalies with SK and regular follow-up is recommended to reduce long-term risk.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.339-348
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• 2019

The purpose of this study was to investigate the effect of carotid artery ultrasound Respectively. The carotid intima-media thickness is known to have a significant correlation with cardiovascular disease and cerebrovascular disease. We investigated the relationship between carotid intima - media thickness, body mass index, waist circumference, the blood lipid value, fasting blood glucose, glycated hemoglobin, and blood pressure using carotid artery ultrasound. The carotid artery ultrasound was considered to be abnormality of IMT thickness over 0.8 mm and the presence or absence of atherosclerotic plaque was evaluated. Serological tests were used to compare the geologic value, fasting blood glucose level, and glycated hemoglobin. As a result, waist circumference (=.022), low density cholesterol (=.004), fasting blood glucose level (.019), and glycemic index (.002) were analyzed as predictors of atherosclerosis. In the ROC curve analysis, sensitivity was 87.80% (95% CI: 73.8-95.9), specificity was 41.67% (95% CI: 30.2-53.9), sensitivity was 78.05% (95% CI: 62.4-89.4) in low density lipoprotein, Specificity was 50.00% (95% CI: 38.0-62.0), sensitivity was 73.11% (95% CI: 57.1-85.8), specificity was 61.11 (95% CI: 48.9-72.4) and sensitivity was 82.93%-91.8) and a specificity of 43.06% (31.4-55.3). In logistic regression analysis, the risk of atherosclerosis was 0.248 times at waist circumference (WC)> 76 cm, 3.475 times at low-density lipoprotein (LDL-C) ${\geq}124mg/dL$, 0.618 at HbA1c> 5.4% It appeared as a times. We suggest that prospective study of carotid artery ultrasound should be performed for the effective prevention of cardiovascular diseases.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.