• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1181-1188
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• 2021

When abnormal events occur in a nuclear power plant, operators must conduct appropriate abnormal operating procedures. It is burdensome though for operators to choose the appropriate procedure considering the numerous main plant parameters and hundreds of alarms that should be judged in a short time. Recently, various research has applied deep-learning algorithms to support this problem by classifying each abnormal condition with high accuracy. Most of these models are trained with simulator data because of a lack of plant data for abnormal states, and as such, developed models may not have tolerance for plant data in actual situations. In this study, two approaches are investigated for a deep-learning model trained with simulator data to overcome the performance degradation caused by noise in actual plant data. First, a preprocessing method using several filters was employed to smooth the test data noise, and second, a data augmentation method was applied to increase the acceptability of the untrained data. Results of this study confirm that the combination of these two approaches can enable high model performance even in the presence of noisy data as in real plants.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.6
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• pp.381-389
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• 2021

Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis.

• Journal of IKEEE
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• v.27 no.4
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• pp.617-623
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• 2023

With the evolution of communication networks, there is a growing demand for stable high-speed data connections to support services relying on large-capacity data. The increasing volume of packet data aggregated from user devices underscores the significance of quality diagnostics for the backhaul network, an intermediate link transmitting data to the core network. This paper conducts empirical research on techniques to diagnose issues within the backhaul network through practical case studies, through diagnosing various factors such as circuit bandwidth, speed disparities within switches, network segment-specific buffer sizes, routing policies, among other factors that could potentially cause RTT (Round Trip Time) delays and performance degradation.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.121-138
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• 2024

Artificial intelligence is crucial to manufacturing productivity. Understanding the difficulties in producing disruptions, especially in linear feed robot systems, is essential for efficient operations. These mechanical tools, essential for linear movements within systems, are prone to damage and degradation, especially in the LM guide, due to repetitive motions. We examine how explainable artificial intelligence (XAI) may diagnose wafer linear robot linear rail clearance and ball screw clearance anomalies. XAI helps diagnose problems and explain anomalies, enriching management and operational strategies. By interpreting the reasons for anomaly detection through visualizations such as Class Activation Maps (CAMs) using technologies like Grad-CAM, FG-CAM, and FFT-CAM, and comparing 1D-CNN with 2D-CNN, we illustrates the potential of XAI in enhancing diagnostic accuracy. The use of datasets from accelerometer and torque sensors in our experiments validates the high accuracy of the proposed method in binary and ternary classifications. This study exemplifies how XAI can elucidate deep learning models trained on industrial signals, offering a practical approach to understanding and applying AI in maintaining the integrity of critical components such as LM guides in linear feed robots.

• Journal of Oral Medicine and Pain
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• v.30 no.1
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• pp.15-23
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• 2005

Mucin glycoproteins are the primary carriers of the oligosaccharide moieties that constitute the blood group substances in human saliva. The aim of this study was to determine whether or not the conversion of either the A or B blood group antigens to the H antigen can occur during the degradation process of stored saliva samples. Forty subjects (20 subjects in each A and B blood group) identified as secretors were enrolled in this study. Fresh whole saliva samples and their clarified supernatants were stored at room temperature for 1 week. The conversion of the blood group antigens was detected by SDS-PAGE and immunoblotting. Among the subjects showing the conversion in whole saliva, glandular saliva samples were obtained from 8 subjects (4 subjects in each A and B blood group). Submandibular-sublingual saliva (SMSL) and a mixture of SMSL and parotid saliva (PS) were stored at room temperature for 1 week. The conversion of the blood group antigens was detected by the same method. The obtained results were as follows: 1. In the clarified samples of whole saliva, the A antigen was detected as being either intact (5%) or degraded molecules (95%) after the 1 week period. Conversion of the A antigen to the H antigen was detected in 5 subjects (25%). In the unclarified samples, the A antigen was either detected as degraded molecules (90%) or was not detected (10%). Conversion of the antigen had occurred in 4 subjects (20%). 2. In the clarified samples of whole saliva, the B antigen was detected as intact (20%) or as degraded molecules (65%) or was not detected (15%) after the 1 week period. Conversion of the B antigen to the H antigen was detected in 7 subjects (35%). In the unclarified samples, the B antigen was detected as intact (5%) or as degraded molecules (65%), or was not detected (30%). Conversion of the antigen was observed in 2 subjects (10%). 3. In the glandular saliva samples, only one of the four subjects displayed an antigenic conversion from the A to H antigen or from the B to H antigen. The conversion had occurred in both the SMSL samples and the SMSL and PS mixture. No degradation of the antigens was detected in the other three samples of the A or B blood groups, nor was there any conversion. The results demonstrated that conversion of the blood group antigens could occur in saliva, and suggested that the enzymes responsible for the conversion are present in saliva. Further studies on the origin and activity of the specific glycosidases in saliva as well as quantitative measurements of the antigenic conversion will be needed.

• Structural Engineering and Mechanics
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• v.65 no.3
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• pp.303-314
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• 2018

Shear walls are a typical member under a complex stress state and have complicated mechanical properties and failure modes. The separated-elements model Genetic Evolutionary Structural Optimization (GESO), which is a combination of an elastic-plastic stress method and an optimization method, has been introduced in the literature for designing such members. Although the separated-elements model GESO method is well recognized due to its stability, feasibility, and economy, its adequacy has not been experimentally verified. This paper seeks to validate the adequacy of the separated-elements model GESO method against experimental data and demonstrate its feasibility and advantages over the traditional elastic stress method. Two types of reinforced concrete shear wall specimens, which had the location of an opening in the middle bottom and the center region, respectively, were utilized for this study. For each type, two specimens were designed using the separated-elements model GESO method and elastic stress method, respectively. All specimens were subjected to a constant vertical load and an incremental lateral load until failure. Test results indicated that the ultimate bearing capacity, failure modes, and main crack types of the shear walls designed using the two methods were similar, but the ductility indexes including the stiffness degradation, deformability, reinforcement yielding, and crack development of the specimens designed using the separated-elements model GESO method were superior to those using the elastic stress method. Additionally, the shear walls designed using the separated-elements model GESO method, had a reinforcement layout which could closely resist the actual critical stress, and thus a reduced amount of steel bars were required for such shear walls.

• Journal of mucopolysaccharidosis and rare diseases
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• v.4 no.1
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• pp.14-20
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• 2018

Mucopolysaccharidoses (MPSs) are a group of rare inherited metabolic disorders caused by specific lysosomal enzyme deficiencies leading to the sequential degradation of glycosaminoglycans, causing substrate accumulation in various cells and tissues and progressive multiple organ dysfunction. The rare disease medical care team at Mackay Memorial Hospital in Taiwan has been dedicated to the study of MPSs for more than 20 years. Since 1999, more than 50 academic papers focusing on MPSs have been published in international medical journals. Topics of research include the following items regarding MPSs: incidence, natural history, clinical manifestations, gene mutation characteristics, cardiac function, bone mineral density, sleep studies, pulmonary function tests, hearing assessments, percutaneous endoscopic gastrostomy, anesthetic experience, imaging analysis, special biochemical tests, laboratory diagnostics, global expert consensus conferences, prenatal diagnosis, new drug clinical trials, newborn screening, and treatment outcomes. Of these published academic research papers, more than half were cross-domain, cross-industry, and international studies with results in cooperation with experts from European, American and other Asian countries. A cross-specialty collaboration platform was established based on high-risk population screening criteria with the acronym "BECARE" (Bone and joints, Eyes, Cardiac and central nervous system, Abdomen and appearance, Respiratory system, and Ear, nose, and throat involvement). Through this platform, orthopedic surgeons, rheumatologists, ophthalmologists, cardiologists, rehabilitation physicians, gastroenterologists, otorhinolaryngologists, and medical geneticists have been educated with regards to awareness of suspected cases of MPSs patients to allow for a further confirmative diagnosis of MPSs. Because of the progressive nature of the disease, an early diagnosis and early multidisciplinary therapeutic interventions including surgery, rehabilitation programs, symptom-based treatments, hematopoietic stem cell transplantation, and enzyme replacement therapy, are very important.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.1
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• pp.62-67
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• 2005

Recently, polymer insulators that are used for high voltage applications have some advantages such as light weight, small size, vandalism resistance, hydrophobicity and easy making process. During outdoor service of polymer insulators, the surface of the insulating material is frequently subjected to moisture and contamination that lead to dry band arcing. Their tracking resistance, erosion resistance, end sealing and shed design are very important because dry band arcing causes degradation of polymer surface. Aging test to estimate life property of polymer insulator is executed through several international standard such as IEC 61109 and CEA tracking wheel test, but is not getting clear conclusion yet. There are two methods in the diagnosis method of polymer insulator such as off-line and on-line. The diagnosis methods in off-line are external condition analysis by the eye, contaminant analysis on surface, surface analysis, pollution withstand voltage test, power frequency flashover voltage test, lightning impulse flashover test, tensile fracture load test and flexural load test. Polymer material is also investigated it's tracking resistance by adding surface active agent in IEC 587. In this paper, the tracking performance of polymer insulator with salt solution which is added surface active agent. The diagnosis of insulator sample has been analyzed by leakage current and visual examination, STRI guide and thermal image camera.

• Journal of Conservation Science
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• v.38 no.4
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• pp.314-326
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• 2022

Investigation of conservation status, optical survey, infrared thermography, and ultrasonic examination were performed on Avalokitesvara Bodhisattva mural and Buddhist Monk Bodhidharma mural to determine the conservation status and physical properties. As a result of investigation of conservation status, the types of damage are largely divided into the wall and finishing layer damage, painting layer degradation, damage due to restoration materials, stains and contamination, and biological damage. As a result of the optical survey, drawing, stains, and repainted site were confirmed. Result of the infrared thermography, the delamination of the finishing layer was confirmed, and some locations and shapes of the wooden lath inside the wall were identified. The result of the 3D scanning, the deviation, and the separation of the wall was confirmed. As a result of ultrasonic examination, it was confirmed that the physical properties of the mural were identified and the ultrasonic speed was relatively low due to physical damage such as delamination and exfoliation of the finishing layer and cracking. Ultrasonic speed values were also high in some wall cracks or delamination, and it was confirmed by the infrared thermography results that the wooden lath inside the wall was located in those parts. It was possible to understand that the wooden lath inside the walls affects the ultrasonic speed during the ultrasonic examination. Therefore, management through periodic inspection of the relevant elements is necessary, and a countermeasure for damage that may occur in the future should be prepared along with intensive monitoring of the major damage identified in this diagnosis result.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3236-3240
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• 2007

This paper describes the results of steam turbine performance tests. The objectives of performance test is to exactly evaluate the degradation(decrease in performance) of the coal-fired steam turbine generator in order to provide plant information to help performance engineers identify problems, improve performance, and make economic decisions about scheduling maintenance and optimizing operation. To achieve these goals, the periodic thermal performance tests have been carried out since the initial operation period, 1997. We made the calculation program and guidelines for the tests and developed the performance index of the turbine cycle on the basis of the ASME PTC. By comparing the performance changes throughout the whole operation period, we confirmed the performance reliabilities of the turbine and its conditions.