• Korean Journal of Radiology
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• v.23 no.2
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• pp.264-270
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• 2022

Objective: This study aimed to investigate the usefulness of bone single-positron emission tomography/computed tomography (SPECT/CT) of the hip in predicting the later occurrence of avascular necrosis (AVN) after slipped capital femoral epiphysis (SCFE) or femoral neck fracture in pediatric patients. The quantitative parameters of SPECT/CT useful in predicting AVN were identified. Materials and Methods: Twenty-one (male:female, 10:11) consecutive patients aged < 18 years (mean age ± standard deviation [SD], 11.0 ± 2.7 years) who underwent surgery for SCFE or femoral neck fracture and postoperative bone SPECT/CT were included. The maximum standardized uptake value (SUV), mean SUV, and minimum SUV of the femoral head were measured. The ratios of the maximum SUV, mean SUV, and minimum SUV of the affected femoral head to the contralateral side were determined. Patients were followed up for > 1 year after the surgery. The SPECT/CT parameters were compared between patients who developed AVN and those who did not. The accuracy of SPECT/CT parameters for predicting AVN was assessed. Results: Six patients developed AVN. There was a significant difference in the ratio of the mean SUV among patients who developed AVN (mean ± SD, 0.8 ± 0.3) and those who did not (1.1 ± 0.2, p = 0.018). However, there were no significant differences in the ratios of the maximum and minimum SUV between the groups (all p = 0.205). For the maximum, mean, and minimum SUVs, no significant differences were observed between the groups (p = 0.519, 0.733, and 0.470, respectively). The cutoff mean SUV ratio of 0.87 yielded a 66.7% sensitivity and 93.2% specificity for predicting AVN. Conclusion: Quantitative bone SPECT/CT is useful for evaluating femoral head viability in pediatric patients with SCFE or femoral neck fractures. Clinicians should consider the high possibility of later AVN development in patients with a decreased mean SUV ratio.

• Korean Journal of Radiology
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• v.20 no.5
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• pp.791-800
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• 2019

Objective: To compare various models of diffusion-weighted imaging including monoexponential apparent diffusion coefficient (ADC), biexponential (fast diffusion coefficient [D_f], slow diffusion coefficient [D_s], and fraction of fast diffusion), stretched-exponential (distributed diffusion coefficient and anomalous exponent term [α]), and kurtosis (mean diffusivity and mean kurtosis [MK]) models in the differentiation of renal solid masses. Materials and Methods: A total of 81 patients (56 men and 25 women; mean age, 57 years; age range, 30-69 years) with 18 benign and 63 malignant lesions were imaged using 3T diffusion-weighted MRI. Diffusion model selection was investigated in each lesion using the Akaike information criteria. Mann-Whitney U test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. Results: Goodness-of-fit analysis showed that the stretched-exponential model had the highest voxel percentages in benign and malignant lesions (90.7% and 51.4%, respectively). ADC, D_s, and MK showed significant differences between benign and malignant lesions (p < 0.05) and between low- and high-grade clear cell renal cell carcinoma (ccRCC) (p < 0.05). α was significantly lower in the benign group than in the malignant group (p < 0.05). All diffusion measures showed significant differences between ccRCC and non-ccRCC (p < 0.05) except D_f and α (p = 0.143 and 0.112, respectively). α showed the highest diagnostic accuracy in differentiating benign and malignant lesions with an area under the ROC curve of 0.923, but none of the parameters from these advanced models revealed significantly better performance over ADC in discriminating subtypes or grades of renal cell carcinoma (RCC) (p > 0.05). Conclusion: Compared with conventional diffusion parameters, α may provide additional information for differentiating benign and malignant renal masses, while ADC remains the most valuable parameter for differentiation of RCC subtypes and for ccRCC grading.

• Korean Journal of Radiology
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• v.20 no.1
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• pp.114-125
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• 2019

Objective: Segmented cardiac cine magnetic resonance imaging (MRI) is the gold standard for cardiac ventricular volumetric assessment. In patients with difficulty in breath-holding or arrhythmia, this technique may generate images with inadequate quality for diagnosis. Real-time cardiac cine MRI has been developed to address this limitation. We aimed to assess the performance of retrospective electrocardiography-gated real-time cine MRI at 3T for left ventricular (LV) volume and mass measurement. Materials and Methods: Fifty-one patients were consecutively enrolled. A series of short-axis cine images covering the entire left ventricle using both segmented and real-time balanced steady-state free precession cardiac cine MRI were obtained. End-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF), and LV mass were measured. The agreement and correlation of the parameters were assessed. Additionally, image quality was evaluated using European CMR Registry (Euro-CMR) score and structure visibility rating. Results: In patients without difficulty in breath-holding or arrhythmia, no significant difference was found in Euro-CMR score between the two techniques (0.3 ± 0.7 vs. 0.3 ± 0.5, p > 0.05). Good agreements and correlations were found between the techniques for measuring EDV, ESV, EF, SV, and LV mass. In patients with difficulty in breath-holding or arrhythmia, segmented cine MRI had a significant higher Euro-CMR score (2.3 ± 1.2 vs. 0.4 ± 0.5, p < 0.001). Conclusion: Real-time cine MRI at 3T allowed the assessment of LV volume with high accuracy and showed a significantly better image quality compared to that of segmented cine MRI in patients with difficulty in breath-holding and arrhythmia.

• Korean Journal of Radiology
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• v.1 no.1
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• pp.25-32
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• 2000

Objective: The purpose of our study was to determine the ability of H-1 MR spectroscopy (MRS) to lateralize the lesion in patients with hippocampal sclerosis. Materials and Methods: Twenty healthy volunteers and 25 patients with intractable temporal lobe epilepsy whose MR imaging diagnosis was unilateral hippocampal sclerosis were included. This diagnosis was based on the presence of unilateral atrophy and/or high T2 signal intensity of the hippocampus. Single-voxel H-1 MRS was carried out on a 1.5-T unit using PRESS sequence (TE, 136 msec). Spectra were obtained from hippocampal areas bilaterally with volumes of interest (VOIs) of 6.0 cm³ and 2.25 cm³ in healthy volunteers, and of either 6.0 cm³ (n = 14) or 2.25 cm³ (n = 11) in patients. Metabolite ratios of NAA/Cho and NAA/Cr were calculated from relative peak height measurements. The capability of MRS to lateralize the lesion and to detect bilateral abnormalities was compared with MR imaging diagnosis as a standard of reference. Results: In healthy volunteers, NAA/Cho and NAA/Cr ratios were greater than 0.8 and 1.0, respectively. In patients, the mean values of these ratios were significantly lower on the lesion side than on the contralateral side, and lower than those of healthy volunteers (p < .05). The overall correct lateralization rate of MRS was 72% (18/25); this rate was lower with a VOI of 6.0 cm³ than of 2.25 cm³ (64% versus 82%, p < .05). Bilateral abnormalities on MRS were found in 24% (6/25) of cases. Conclusion: Although its rate of correct lateralization is low, single-voxel H-1 MRS is a useful and promising diagnostic tool in the evaluation of hippocampal sclerosis, particularly for the detection of bilateral abnormalities. To improve the diagnostic accuracy of H-1 MRS, further investigation, including the use of a smaller VOI and measurement of the absolute amount of metabolites, are needed.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.29-38
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• 2024

The Matched Field Processing (MFP) is an estimation method for a source range and depth based on the prediction of sound propagation. However, as the frequency increases, the prediction inaccuracy of sound propagation increases, making it difficult to estimate the source position. Recently proposed, the Frequency-Difference Matched Field Processing (FD-MFP) is known to be robust even if there is a mismatch by applying a frequency-difference autoproduct extracted from the auto-correlation of a high frequency signal. In this paper, in order to evaluate the performance of the FD-MFP using a horizontal line array, simulations were conducted in the environment of the East Sea of Korea. In the area of Bottom Bounce (BB) and Convergence Zone (CZ) where detection of a sound source is possible at a long range, and the results of localization were analyzed. According to the the FD-MFP simulations of horizontal line array, the accuracy of localization is similar or degraded compared to the conventional MFP due to diffracted field and mismatch of sound speed. There was no clear result from the simulations conforming that the FD-MFP was more robust to mismatch than the conventional MFP.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.87-97
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• 2024

This study analyzed the water shortage hotspot areas in South Korea using spatial clustering analysis for water shortage estimates in 2030 of the Master Plans for National Water Management. To identify the water shortage cluster areas, we used water shortage data from the past maximum drought (about 50-year return period) and performed spatial clustering analysis using Local Moran's I and Getis-Ord Gi*. The areas subject to spatial clusters of water shortage were selected using the cluster map, and the spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The results indicated that one cluster (lower Imjin River (#1023) and neighbor) in the Han River basin and two clusters (Daejeongcheon (#2403) and neighbor, Gahwacheon (#2501) and neighbor) in the Nakdong River basin were found to be the hotspot for water shortage, whereas one cluster (lower Namhan River (#1007) and neighbor) in the Han River Basin and one cluster (Byeongseongcheon (#2006) and neighbor) in the Nakdong River basin were found to be the HL area, which means the specific area have high water shortage and neighbor have low water shortage. When analyzing spatial clustering by standard watershed unit, the entire spatial clustering area satisfied 100% of the statistical criteria leading to statistically significant results. The overall results indicated that spatial clustering analysis performed using standard watersheds can resolve the variable spatial unit problem to some extent, which results in the relatively increased accuracy of spatial analysis.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.39-47
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• 2024

In this study, physical property tests and standard consolidation tests were conducted on the marine clay of Busan New Port and North Port, the middle and lower reaches of the Nakdong River including Gimhae and Yangsan, and Ulsan regions. The moisture content, a property unrelated to sample disturbance with small individual test errors, was used for regression analysis with the compression index, virgin compression index, consolidation coefficient, expansion index, and secondary compression index, among others. Subsequently, the correlation and accuracy were evaluated. Upon analyzing the correlation between the moisture content, void ratio, and liquid limit commonly used physical properties for calculating compression indexes, it was confirmed that the liquid limit had the lowest correlation. Through a linear regression analysis of the consolidation constants using the current moisture content in the natural state, a high correlation was demonstrated. Relationship equations were then presented to determine settlement and settlement time. This study suggests that moisture content can be utilized as an alternative for evaluating and calculating consolidation constants when examining ground settlement in sedimentary clays distributed in the Busan and Gyeongnam regions.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.19-23
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• 2024

Patients with amputations of both hands need prosthetic hands that serve both cosmetic and functional purposes, and research on prosthetic hands using electromyography of remaining muscles is active, but there is still the problem of high cost. In this study, an artificial prosthetic hand was manufactured and its performance was evaluated using low-cost parts and software such as a surface electromyography sensor, machine learning software Edge Impulse, Arduino Nano 33 BLE, and 3D printing. Using signals acquired with surface electromyography sensors and subjected to digital signal processing through Edge Impulse, the flexing movement signals of each finger were transmitted to the fingers of the prosthetic hand model through training to determine the type of finger movement using machine learning. When the digital signal processing conditions were set to a notch filter of 60 Hz, a bandpass filter of 10-300 Hz, and a sampling frequency of 1,000 Hz, the accuracy of machine learning was the highest at 82.1%. The possibility of being confused between each finger flexion movement was highest for the ring finger, with a 44.7% chance of being confused with the movement of the index finger. More research is needed to successfully develop a low-cost prosthetic hand.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.121-129
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• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.