• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.48-66
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• 2024

According to the three amended Laws of the Data Economy and the Data Industry Act of Korea, systems for pseudonymous data integration and Data Safe Zones have been operated separately by selected agencies, eventually causing a burden of use in SMEs, startups, and general users because of complicated and ineffective procedures. An over-stringent pseudonymization policy to prevent data breaches has also compromised data quality. Such trials should be improved to ensure the convenience of use and data quality. This paper proposes a prototype system of the Integrated Data Safe Zone based on redesigned and optimized pseudonymization workflows. Conventional workflows of pseudonymization were redesigned by applying the amended guidelines and selectively revising existing guidelines for business process redesign. The proposed prototype has been shown quantitatively to outperform the conventional one: 6-fold increase in time efficiency, 1.28-fold in cost reduction, and 1.3-fold improvement in data quality.

• Journal of Gastric Cancer
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• v.24 no.3
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• pp.327-340
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• 2024

Purpose: Results of initial endoscopic biopsy of gastric lesions often differ from those of the final pathological diagnosis. We evaluated whether an artificial intelligence-based gastric lesion detection and diagnostic system, ENdoscopy as AI-powered Device Computer Aided Diagnosis for Gastroscopy (ENAD CAD-G), could reduce this discrepancy. Materials and Methods: We retrospectively collected 24,948 endoscopic images of early gastric cancers (EGCs), dysplasia, and benign lesions from 9,892 patients who underwent esophagogastroduodenoscopy between 2011 and 2021. The diagnostic performance of ENAD CAD-G was evaluated using the following real-world datasets: patients referred from community clinics with initial biopsy results of atypia (n=154), participants who underwent endoscopic resection for neoplasms (Internal video set, n=140), and participants who underwent endoscopy for screening or suspicion of gastric neoplasm referred from community clinics (External video set, n=296). Results: ENAD CAD-G classified the referred gastric lesions of atypia into EGC (accuracy, 82.47%; 95% confidence interval [CI], 76.46%-88.47%), dysplasia (88.31%; 83.24%-93.39%), and benign lesions (83.12%; 77.20%-89.03%). In the Internal video set, ENAD CAD-G identified dysplasia and EGC with diagnostic accuracies of 88.57% (95% CI, 83.30%-93.84%) and 91.43% (86.79%-96.07%), respectively, compared with an accuracy of 60.71% (52.62%-68.80%) for the initial biopsy results (P<0.001). In the External video set, ENAD CAD-G classified EGC, dysplasia, and benign lesions with diagnostic accuracies of 87.50% (83.73%-91.27%), 90.54% (87.21%-93.87%), and 88.85% (85.27%-92.44%), respectively. Conclusions: ENAD CAD-G is superior to initial biopsy for the detection and diagnosis of gastric lesions that require endoscopic resection. ENAD CAD-G can assist community endoscopists in identifying gastric lesions that require endoscopic resection.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.3
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• pp.105-115
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• 2024

In coastal structure design incorporating revetments, the assessment of wave overtopping discharge relies on hydraulic model experiments. Numerous empirical formulas have been developed to predict overtopping discharge based on quantitative data from these experiments. Typically, for revetment structures aimed at mitigating wave overtopping, crest height is determined by considering the maximum amplitude of the design wave, resulting in a relatively high freeboard compared to wave heights. However, achieving complete prevention of all wave overtopping would require the crown wall to have substantial crest heights, rendering it economically impractical. Therefore, the concept of limiting discharge has been introduced in the design of revetment structures, aiming to restrict wave overtopping discharge to an acceptable level. Consequently, many coastal structures in real-world settings feature relatively lower freeboard heights than incident wave heights. This study investigated wave overtopping discharge on rubble-mound breakwaters with relatively low freeboard heights through hydraulic model experiments. Furthermore, it conducted a comparative analysis of the predictive capabilities of existing empirical formulas for estimating overtopping discharge using experimental data.

• Dementia and Neurocognitive Disorders
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• v.23 no.1
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• pp.22-29
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• 2024

Background and Purpose: Alzheimer's disease (AD) is a neurodegenerative disease characterized by a progressive decline in cognition and performance of daily activities. Recent studies have attempted to establish the relationship between AD and sleep. It is believed that patients with AD pathology show altered sleep characteristics years before clinical symptoms appear. This study evaluated the differences in sleep characteristics between cognitively asymptomatic patients with and without some amyloid burden. Methods: Sleep characteristics of 76 subjects aged 60 years or older who were diagnosed with subjective cognitive decline (SCD) but not mild cognitive impairment (MCI) or AD were measured using Fitbit^® Alta HR, a wristwatch-shaped wearable device. Amyloid deposition was evaluated using brain amyloid plaque load (BAPL) and global standardized uptake value ratio (SUVR) from fluorine-18 florbetaben positron emission tomography. Each component of measured sleep characteristics was analyzed for statistically significant differences between the amyloid-positive group and the amyloid-negative group. Results: Of the 76 subjects included in this study, 49 (64.5%) were female. The average age of the subjects was 70.72±6.09 years when the study started. 15 subjects were classified as amyloid-positive based on BAPL. The average global SUVR was 1.598±0.263 in the amyloid-positive group and 1.187±0.100 in the amyloid-negative group. Time spent in slow-wave sleep (SWS) was significantly lower in the amyloid-positive group (39.4±13.1 minutes) than in the amyloid-negative group (49.5±13.1 minutes) (p=0.009). Conclusions: This study showed that SWS is different between the elderly SCD population with and without amyloid positivity. How SWS affects AD pathology requires further research.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.19-32
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• 2023

The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.326-334
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• 2024

Extra-oral imaging techniques such as Panoramic X-rays (PXs) and Cone Beam Computed Tomography (CBCT) are the most preferred imaging modalities in dental clinics owing to its patient convenience during imaging as well as their ability to visualize entire teeth information. PXs are preferred for routine clinical treatments and CBCTs for complex surgeries and implant treatments. However, PXs are limited by the lack of third dimensional spatial information whereas CBCTs inflict high radiation exposure to patient. When a PX is already available, it is beneficial to reconstruct the 3D oral structure from the PX to avoid further expenses and radiation dose. In this paper, we propose 3DentAI - an U-Net based deep learning framework for 3D reconstruction of oral structure from a PX image. Our framework consists of three module - a reconstruction module based on attention U-Net for estimating depth from a PX image, a realignment module for aligning the predicted flattened volume to the shape of jaw using a predefined focal trough and ray data, and lastly a refinement module based on 3D U-Net for interpolating the missing information to obtain a smooth representation of oral cavity. Synthetic PXs obtained from CBCT by ray tracing and rendering were used to train the networks without the need of paired PX and CBCT datasets. Our method, trained and tested on a diverse datasets of 600 patients, achieved superior performance to GAN-based models even with low computational complexity.

• Korean Journal of Optics and Photonics
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• v.35 no.4
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• pp.175-183
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• 2024

Research into optical signal processing using photonic integrated circuits (PICs) has been actively pursued in various fields, including optical communication, optical sensors, and quantum optics. Among the materials used in PIC fabrication, polymers have attracted significant interest due to their unique characteristics. To fabricate polymer-based PICs, establishing an accurate manufacturing process for the cross-sectional structure of an optical waveguide is crucial. For stable device performance and high yield in mass production, a process with high reproducibility and a wide tolerance for variation is necessary. This study proposes an efficient method for fabricating polymer optical-waveguide devices by introducing the atomic layer deposition (ALD) process. Compared to conventional photoresist or metal-film deposition methods, the ALD process enables more precise fabrication of the optical waveguide's core structure. Polyimide optical waveguides with a core size of 1.8 × 1.6 ㎛² are fabricated using the ALD process, and their propagation losses are measured. Additionally, a multimode interference (MMI) optical-waveguide power-splitter device is fabricated and characterized. Throughout the fabrication, no cracking issues are observed in the etching-mask layer, the vertical profiles of the waveguide patterns are excellent, and the propagation loss is below 1.5 dB/cm. These results confirm that the ALD process is a suitable method for the mass production of high-quality polymer photonic devices.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.335-347
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• 2024

Open-vocabulary 3D point cloud instance segmentation (OV-3DIS) is a challenging visual task to segment a 3D scene point cloud into object instances of both base and novel classes. In this paper, we propose a novel model Open3DME for OV-3DIS to address important design issues and overcome limitations of the existing approaches. First, in order to improve the quality of class-agnostic 3D masks, our model makes use of T3DIS, an advanced Transformer-based 3D point cloud instance segmentation model, as mask proposal module. Second, in order to obtain semantically text-aligned visual features of each point cloud segment, our model extracts both 2D and 3D features from the point cloud and the corresponding multi-view RGB images by using pretrained CLIP and OpenSeg encoders respectively. Last, to effectively make use of both 2D and 3D visual features of each point cloud segment during label assignment, our model adopts a unique feature ensemble method. To validate our model, we conducted both quantitative and qualitative experiments on ScanNet-V2 benchmark dataset, demonstrating significant performance gains.

• Korean Journal of Optics and Photonics
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• v.35 no.4
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• pp.150-156
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• 2024

One of the key factors in research regarding long-distance laser beam propagation, as in free-space optical communication or laser power transmission, is the transmission efficiency of the laser beam. As a way to improve efficiency, we perform extensive numerical simulations of the effect of modifying the laser beam's profile, especially replacing the fundamental Gaussian beam with a super-Gaussian beam. Numerical simulations of the transmitted power in the ideal diffraction-limited beam diameter determined by the optical system of the transmitter, after about 1-km propagation, reveal that the second-order super-Gaussian beam can yield superior performance to that of the fundamental Gaussian beam, in both single-channel and coherently combined multi-channel laser transmitters. The improvement of the transmission efficiency for a 1-km propagation distance when using a second-order super-Gaussian beam, in comparison with a fundamental Gaussian beam, is estimated at over 1.2% in the singlechannel laser transmitter, and over 4.2% and over 4.6% in coherently combined 3- and 7-channel laser transmitters, respectively. For a range of the propagation distance varying from 750 to 1,250 m, the improvement in transmission efficiency by use of the second-order super-Gaussian beam is estimated at over 1.2% in the single-channel laser transmitter, and over 4.1% and over 4.0% in the coherently combined 3- and 7-channel laser transmitters, respectively. These simulation results will pave the way for future advances in the generation of higher-order super-Gaussian beams and the development of long-distance optical energy-transfer technology.

• Korean Journal of Optics and Photonics
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• v.35 no.4
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• pp.157-163
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• 2024

We developed a 3-channel fiber laser with a common seed and a phase control system for laser beam combining through a diffractive optical element. Beam combining was performed by adjusting the angles of the beams incident on the diffractive optical elements, and the phase of each beam was controlled to maximize the intensity of the combined laser beam. The power of the 3-channel laser before passing through the diffractive optical elements is about 65 mW. The power of the combined beam varied between 2.9 mW and 48.3 mW depending on the phase change of each channel. Through phase control, the output of the combined beam can be maintained at 42 mW for more than 91.8% of the total time. It is expected that higher combining efficiency can be achieved by improving the transmittance of the diffractive optical elements and the performance of the phase control system.