• Korean Journal of Radiology
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• v.24 no.10
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• pp.1006-1016
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• 2023

Objective: Computed tomography (CT) is an established method for the diagnosis, staging, and treatment of multiple myeloma. Here, we investigated the potential of photon-counting detector computed tomography (PCD-CT) in terms of image quality, diagnostic confidence, and radiation dose compared with energy-integrating detector CT (EID-CT). Materials and Methods: In this prospective study, patients with known multiple myeloma underwent clinically indicated whole-body PCD-CT. The image quality of PCD-CT was assessed qualitatively by three independent radiologists for overall image quality, edge sharpness, image noise, lesion conspicuity, and diagnostic confidence using a 5-point Likert scale (5 = excellent), and quantitatively for signal homogeneity using the coefficient of variation (CV) of Hounsfield Units (HU) values and modulation transfer function (MTF) via the full width at half maximum (FWHM) in the frequency space. The results were compared with those of the current clinical standard EID-CT protocols as controls. Additionally, the radiation dose (CTDIvol) was determined. Results: We enrolled 35 patients with multiple myeloma (mean age 69.8 ± 9.1 years; 18 [51%] males). Qualitative image analysis revealed superior scores (median [interquartile range]) for PCD-CT regarding overall image quality (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), edge sharpness (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), image noise (4.0 [4.0-4.0] vs. 3.0 [3.0-4.0]), lesion conspicuity (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), and diagnostic confidence (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]) compared with EID-CT (P ≤ 0.004). In quantitative image analyses, PCD-CT compared with EID-CT revealed a substantially lower FWHM (2.89 vs. 25.68 cy/pixel) and a significantly more homogeneous signal (mean CV ± standard deviation [SD], 0.99 ± 0.65 vs. 1.66 ± 0.5; P < 0.001) at a significantly lower radiation dose (mean CTDIvol ± SD, 3.33 ± 0.82 vs. 7.19 ± 3.57 mGy; P < 0.001). Conclusion: Whole-body PCD-CT provides significantly higher subjective and objective image quality at significantly reduced radiation doses than the current clinical standard EID-CT protocols, along with readily available multi-spectral data, facilitating the potential for further advanced post-processing.

• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.

• Korean Journal of Radiology
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• v.20 no.4
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• pp.662-670
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• 2019

Objective: A developmental venous anomaly (DVA) is a vascular malformation of ambiguous clinical significance. We aimed to quantify the susceptibility of draining veins (χ_vein) in DVA and determine its significance with respect to oxygen metabolism using quantitative susceptibility mapping (QSM). Materials and Methods: Brain magnetic resonance imaging of 27 consecutive patients with incidentally detected DVAs were retrospectively reviewed. Based on the presence of abnormal hyperintensity on T2-weighted images (T2WI) in the brain parenchyma adjacent to DVA, the patients were grouped into edema (E+, n = 9) and non-edema (E-, n = 18) groups. A 3T MR scanner was used to obtain fully flow-compensated gradient echo images for susceptibility-weighted imaging with source images used for QSM processing. The χ_vein was measured semi-automatically using QSM. The normalized χ_vein was also estimated. Clinical and MR measurements were compared between the E+ and E- groups using Student's t-test or Mann-Whitney U test. Correlations between the χ_vein and area of hyperintensity on T2WI and between χ_vein and diameter of the collecting veins were assessed. The correlation coefficient was also calculated using normalized veins. Results: The DVAs of the E+ group had significantly higher χ_vein (196.5 ± 27.9 vs. 167.7 ± 33.6, p = 0.036) and larger diameter of the draining veins (p = 0.006), and patients were older (p = 0.006) than those in the E- group. The χ_vein was also linearly correlated with the hyperintense area on T2WI (r = 0.633, 95% confidence interval 0.333-0.817, p < 0.001). Conclusion: DVAs with abnormal hyperintensity on T2WI have higher susceptibility values for draining veins, indicating an increased oxygen extraction fraction that might be associated with venous congestion.

• Herbal Formula Science
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• v.31 no.4
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• pp.215-230
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• 2023

Objectives : Schisandra chinensis (Turcz.) Baill contains many nutrients and exhibits high physiological functions. It has been shown that Schisandra seed and pamace contains more nutrients than fruits and thus have higher antioxidant efficacy. In this study, seed and pamace of Schisandra chinensis (Turcz.) Baill (SPSC) were treated with hot-melt extrudate (HME) extrusion to produce water-soluble nanoparticles. Methods : SPSC was treated with HME to prepare nanoparticles. In this process, excipients (hydroxypropyl methylcellulose, pullulan, 2-hydroxylpropyl-beta-cyclodextrin, lecithin) were added to prepare a hydrophilic polymer matrix. To compare and analyze the antioxidant effect and schizandrin content, total flavonoid content, total phenol content and ABTS assay were measured. To confirm the effect of increasing the water solubility of the particles, particle size and water solubility index measurements were performed. The molecular of the material was analyzed using Fourier transform infrared spectroscopy (FT-IR). Results : The particle size of HME extrudates decreased, while total phenols, flavonoids, schizandrin, antioxidant effect, and solubility increased. Through FT-IR, it was confirmed that the SPSC and the extrudate exhibit the same chemical properties. In addition, it was confirmed that when extracted with water, it exhibited a higher antioxidant effect than the ethanol extract. Conclusions : HME technology increased the solubility of SPSC, which are processing by-products, and improved their antioxidant effect to a higher degree. It was confirmed that SPSC could be used as an eco-friendly, high value-added material.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.35-40
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• 2024

In this paper, we validate the practicality of the OnePIC app implemented in the previous study by analyzing the execution and storage performance. The OnePIC app is a camera app that allows you to get a photo with a desired focus after taking photos focused on various places. To evaluate performance, we analyzed distance focus shooting time and object focus shooting time in detail. The performance evaluation was measured on actual smartphone. Distance focus shooting time for 5 photos was around 0.84 seconds, the object detection time was around 0.19 seconds regardless of the number of objects and object focus shooting time for 5 photos was around 4.84 seconds. When we compared the size of a single All-in-JPEG file that stores multi-focus photos to the size of the JPEG files stored individually, there was no significant benefit in storage space because the All-in-JPEG file size was subtly reduced. However, All-in-JPEG has the great advantage of managing multi-focus photos. Finally, we conclude that the OnePIC app is practical in terms of shooting time, photo storage size, and management.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.4
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• pp.427-432
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• 2024

The polymer crystallization process, promoting the formation of ferroelectric β-phase, is essential for developing polyvinylidene fluoride (PVDF)-based high-performance piezoelectric energy harvesters. However, traditional high-temperature annealing is unsuitable for the manufacture of flexible piezoelectric devices due to the thermal damage to plastic components that occurs during the long processing times. In this study, we investigated the feasibility of introducing a flash lamp annealing that can rapidly induce the β-phase in the PVDF layer while avoiding device damage through selective heating. The flash light-irradiated PVDF films achieved a maximum β-phase content of 76.52% under an applied voltage of 300 V and an on-time of 1.5 ms, a higher fraction than that obtained through thermal annealing. The PVDF-based piezoelectric energy harvester with the optimized irradiation condition generates a stable output voltage of 0.23 V and a current of 102 nA under repeated bendings. These results demonstrate that flash lamp annealing can be an effective process for realizing the mass production of PVDF-based flexible electronics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.93-105
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• 2024

Purpose: This study aims to quantitatively determine the impact on nearby risidents by selecting the amount of chemicals emitted from the workplace among the substances subject to the chemical emission plan and predicting the concentration with the atmospheric diffusion program. Method: The selection of research materials considered half-life, toxicity, and the presence or absence of available monitoring station data. The areas discharged from the materials to be studied were selected as the areas to be studied, and four areas with floating populations were selected to evaluate health risks. Result: AERMOD was executed after conducting terrain and meteorological processing to obtain predicted concentrations. The health hazard assessment results indicated that only dichloromethane exceeded the threshold for children, while tetrachloroethylene and chloroform appeared at levels that cannot be ignored for both children and adults. Conclusion: Currently, in the domestic context, health hazard assessments are conducted based on the regulations outlined in the "Environmental Health Act" where if the hazard index exceeds a certain threshold, it is considered to pose a health risk. The anticipated expansion of the list of substances subject to the chemical discharge plan to 415 types by 2030 suggests the need for efficient management within workplaces. In instances where the hazard index surpasses the threshold in health hazard assessments, it is judged that effective chemical management can be achieved by prioritizing based on considerations of background concentration and predicted concentration through atmospheric dispersion modeling.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.23-48
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• 2024

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.