• Nuclear Engineering and Technology
• /
• 제53권3호
• /
• pp.776-792
• /
• 2021

Conventional integral effect test facilities were constructed to enable the precise observation of thermal-hydraulic phenomena and reactor behaviors under postulated accident conditions to prove reactor safety. Although these facilities improved the understanding of thermal-hydraulic phenomena and reactor safety, applications of new technologies and their performance tests have been limited owing to the cost and large scale of the facilities. Various nuclear technologies converging 4th industrial revolution technologies such as artificial intelligence, drone, and 3D printing, are being developed to improve plant management strategies. Additionally, new conceptual passive safety systems are being developed to enhance reactor safety. A new integral effect test facility having a noticeable scaling ratio, i.e., the (UNIST reactor innovation loop (URI-LO), is designed and constructed to improve the technical quality of these technologies by performance and feasibility tests. In particular, the URI-LO, which is constructed using a transparent material, enables better visualization and provides physical insights on multidimensional phenomena inside the reactor system. The facility design based on three-level approach is qualitatively validated with preliminary analyses, and its functionality as a test facility is confirmed through a series of experiments. The design feature, design validation, functionality test, and future utilization of the URI-LO are introduced.

• 한국컴퓨터정보학회논문지
• /
• 제24권6호
• /
• pp.1-9
• /
• 2019

Hard disks, which have long been used as secondary storage in computing systems, are increasingly being replaced by solid state drives (SSDs), due to their relatively fast data input / output speeds and small, light weight. SSDs that use NAND flash memory as a storage medium are significantly different from hard disks in terms of physical operation and internal operation. In particular, there is a feature that data overwrite can not be performed, which causes erase operation before writing. In order to solve this problem, a hot data for frequently updating a data for a specific page is distinguished from a cold data for a relatively non-hot data. Hot data identification helps to improve overall performance by identifying and managing hot data separately. Among the various hot data identification methods known so far, there is a technique of recording consecutive write requests by using a Bloom filter and judging the values by hot data. However, the Bloom filter technique has a problem that a new bit array must be generated every time a set of items is changed. In addition, since it is judged based on a continuous write request, it is possible to make a wrong judgment. In this paper, we propose a method using a counting filter for accurate hot data verification. The proposed method examines consecutive write requests. It also records the number of times consecutive write requests occur. The proposed method enables more accurate hot data verification.

• 교육시설 논문지
• /
• 제26권5호
• /
• pp.25-36
• /
• 2019

School gymnasium is a multi-purpose large space building for various events and physical education activities, and is a facility that requires an approach to the desirable structural design, besides mechanical problems of structure against loads. For the integrated structure design concerning the architectural features, the major considerations of gymnasium planning that are the internal and external shape of the gymnasium, the space scale with structure members, the structural efficiency by members weight reduction and openness of the gymnasium space will have to take into account in the structural planning. From this point of view, the several cases of the school gymnasium were investigated and the parametric analyses were performed to the models using the various structural system. The parameters were the composition elements of structure system that are profile of structure, rigidity of member, connection and anchorage and stability. At the result, It was presented that the profile of structure member was the most influential factor to structural efficiency and the effect of the form and space of gymnasium. Also the design informations of structure design having the various feature of form and space were presented for the initial gymnasium planning.

• 전기전자학회논문지
• /
• 제25권1호
• /
• pp.212-217
• /
• 2021

Premature contraction arrhythmia is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Most of arrhythmia clasification methods have been developed with the primary objective of the high detection performance without taking into account the computational complexity. Also, personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Therefore it is necessary to design efficient method that classifies arrhythmia by analyzing the persons's physical condition and decreases computational cost by accurately detecting minimal feature point based on only QRS features. We propose method for personalized specific classification of premature contraction arrhythmia based on QRS features in smart healthcare environments. For this purpose, we detected R wave through the preprocessing method and SOM and selected abnormal signal sets.. Also, we developed algorithm to classify premature contraction arrhythmia using QRS pattern, RR interval, threshold for amplitude of R wave. The performance of R wave detection, Premature ventricular contraction classification is evaluated by using of MIT-BIH arrhythmia database that included over 30 PVC(Premature Ventricular Contraction) and PAC(Premature Atrial Contraction). The achieved scores indicate the average of 98.24% in R wave detection and the rate of 97.31% in Premature ventricular contraction classification.

• 한국가시화정보학회지
• /
• 제20권2호
• /
• pp.70-77
• /
• 2022

Skeletal muscle tissues feature cellular heterogeneity, including differentiated myofibers, myoblasts, and satellite cells. Thanks to the presence of undifferentiated myoblasts and satellite cells, skeletal muscle tissues can self-regenerate after injury. In skeletal muscle regeneration, the collective motions among these cell types must play a significant role, but little is known about the dynamic collective behavior during the regeneration. In this study, we constructed in vitro platform to visualize the migration behavior of skeletal muscle cells in specific conditions that mimic the biochemical environment of injured skeletal muscles. We then visualized the spatiotemporal distribution of stresses arising from the differential collectiveness in the cellular clusters under different conditions. From these analyses, we identified that the heterogeneous population of muscle cells exhibited distinct collective migration patterns in the injury-mimicking condition, suggesting selective activation of a specific cell type by the biochemical cues from the injured skeletal muscles.

• Smart Structures and Systems
• /
• 제28권6호
• /
• pp.811-825
• /
• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• Smart Structures and Systems
• /
• 제30권4호
• /
• pp.385-395
• /
• 2022

Detecting cracks on a concrete structure is crucial for structural maintenance, a crack being an indicator of possible damage. Conventional crack detection methods which include visual inspection and non-destructive equipment, are typically limited to a small region and require time-consuming processes. Recently, to reduce the human intervention in the inspections, various researchers have sought computer vision-based crack analyses: One class is filter-based methods, which effectively transforms the image to detect crack edges. The other class is using deep-learning algorithms. For example, convolutional neural networks have shown high precision in identifying cracks in an image. However, when the objective is to classify not only the existence of crack but also the types of cracks, only a few studies have been reported, limiting their practical use. Thus, the presented study develops an image processing procedure that detects cracks and classifies crack types; whether the image contains a crazing-type, single crack, or multiple cracks. The properties and steps in the algorithm have been developed using field-obtained images. Subsequently, the algorithm is validated from additional 227 images obtained from an open database. For test datasets, the proposed algorithm showed accuracy of 92.8% in average. In summary, the developed algorithm can precisely classify crazing-type images, while some single crack images may misclassify into multiple cracks, yielding conservative results. As a result, the successful results of the presented study show potentials of using vision-based technologies for providing crack information with reduced human intervention.

• 대한의용생체공학회:의공학회지
• /
• 제44권5호
• /
• pp.329-335
• /
• 2023

Perceived age is defined as age estimated based on physical appearance. Perceived age is an important indicator of the overall health status of the elderly. This is because people who appear older tend to have higher rates of morbidity and mortality than people of the same chronological age. Although perceived age is an important indicator, there is a lack of objective methods to quantify perceived age. In this paper, we construct a quantified perceived age model from face images using a convolutional neural network. The face images are enlarged to super-resolution and the skin, an important feature in perceived age, is made clear. Moreover, through Tanh-polar transformation, the central area of the face occupies a relatively larger area than the boundary area, helping the neural network better recognize facial skin features. The experimental results show mean absolute error (MAE) of 6.59, showing that the proposed model is superior to existing method.

• 대한의용생체공학회:의공학회지
• /
• 제45권2호
• /
• pp.75-80
• /
• 2024

This research investigates the influence of chair tilt functionality on biometric signals and user comfort, addressing the ergonomic challenges posed by modern sedentary lifestyles. Through an experimental study involving eight male participants, the impact of chair tilt on electromyography (EMG), heart rate, metabolic rate, pressure distribution, and distance between the lumbar spine and the lumbar support part of the chair was measured across different seating postures. The study utilized chairs with both synchronous and non-synchronous tilt mechanisms to explore how adjustments in chair design affect user comfort and physiological responses during prolonged sitting. Key findings suggest that chair tilt functionality can significantly reduce muscle activity and energy expenditure, enhancing user comfort and potentially mitigating health risks associated with prolonged sedentary behavior. Notably, the study revealed a preference among participants for chairs that aligned the rotational center of the tilt with the hip joint, highlighting the importance of this ergonomic feature in enhancing user comfort. Additionally, the research proposes a novel methodology for assessing seating comfort through the analysis of both biometric and physical signals, providing valuable insights for the development of ergonomic chair designs focused on user health and comfort.

• 전자통신동향분석
• /
• 제39권1호
• /
• pp.83-94
• /
• 2024

There have been continuous requirements for developing more reliable energy storage systems that could address unsolved problems in conventional lithium-ion batteries (LIBs) and thus be a proper option for large-scale applications like energy storage system (ESS). As a promising solution, aqueous metal-ion batteries (AMIBs) where water is used as a primary electrolyte solvent, have been emerging owing to excellent safety, cost-effectiveness, and eco-friendly feature. Particularly, AMIBs adopting mutivalence metal ions (Ca²⁺, Mg²⁺, Zn²⁺, and Al³⁺) as mobile charge carriers has been paid much attention because of their abundance on globe and high volumetric capacity. In this research trend review, one of the most popular AMIBs, zinc-ion batteries (ZIBs), will be discussed. Since it is well-known that ZIBs suffer from various (electro) chemical/physical side reactions, we introduce the challenges and recent advances in the study of ZIBs mainly focusing on widening the electrochemical window of aqueous electrolytes as well as improving electrochemical properties of cathode, and anode materials.