• Archives of Plastic Surgery
• /
• 제34권1호
• /
• pp.134-136
• /
• 2007

Purpose: Erysipelas is a bacterial infection of the dermis and hypodermis, mostly of streptococcal origin, and erysipelas of upper extremity following breast cancer treatment has never been reported in the Korean literature. Methods: 39-year-old female presented to our hospital complaining of fever and painful swelling of her left upper extremity. She had a history of breast cancer and was treated with breast conserving surgery with axillary lymph node dissection, chemotherapy, and radiation. On physical examination, her left upper extremity showed vesicle, bullae, local heatness and erythema with well-defined margin. With these distinctive features of a skin lesion, we gave a diagnosis of erysipelas and started treatment with intravenous antibiotics. Results: Resolution of the signs and symptoms of erysipelas occurred after 7 days of treatment. Conclusion: The diagnosis of erysipelas with distinctive feature of skin lesion is essential and we emphasize that the prevention of any trauma are very important in these patients for prophylactic measures.

• 정보과학회지
• /
• 제1권1호
• /
• pp.72-74
• /
• 1983

Traditionally, polynomials have been used to approximte functions with prescribed values at a number of points(called the knots) on a given interal on the real line. The method of splines recently developed is more flexible. It approximates a function in a piece-wise fashion, by means of a different polynomial in each subinterval. The cubic spline gas ets origins in beam theory. It possessed continuous first and second deriatives at the knots and is characterised by a minimum curvature property which es rdlated to the physical feature of minimum potential energy of the supported beam. Translated into mathematical terms, this means that between successive knots the approximation yields a third-order polynomial sith its first derivatives continuous at the knots. The minimum curvature property holds good for each subinterval as well as for the whole region of approximation This means that the integral of the square of the second derivative over the entire interval, and also over each subinterval, es to be minimized. Thus, the task of determining the spline lffers itself as a textbook problem in discrete computer programming, since the integral of ghe square of the second derivative can be obviously recognized as the criterion function whicg gas to be minimized. Starting with the initial value of the function and assuming an initial solpe of the curve, the minimum norm property of the curvature makes sequential decision of the slope at successive knots (points) feasible. It is the aim of this paper to derive the cubic spline by the methods of computer programming and show that the results which is computed the all the alues in each subinterval of the spline approximations.

• Nuclear Engineering and Technology
• /
• 제52권5호
• /
• pp.1008-1012
• /
• 2020

In order to make reasonable design for the improvement of comprehensive mechanical properties of RAFM steels, the design system with both machine learning and high-throughput optimization algorithm was established. As the basis of the design system, a dataset of RAFM steels was compiled from previous literatures. Then, feature engineering guided random forests regressors were trained by the dataset and NSGA II algorithm were used for the selection of the optimal solutions from the large-scale solution set with nine composition features and two treatment processing features. The selected optimal solutions by this design system showed prospective mechanical properties, which was also consistent with the physical metallurgy theory. This efficiency design mode could give the enlightenment for the design of other metal structural materials with the requirement of multi-properties.

• Journal of the Optical Society of Korea
• /
• 제17권4호
• /
• pp.328-335
• /
• 2013

Due to the rapid advancement of auto-refractor technology, most optometry shops provide refraction services. Despite their speed and convenience, the measurement values provided by auto-refractors include a significant degree of error due to psychological and physical factors. Therefore, there is a need for repetitive testing to obtain a smaller mean error value. However, even repetitive testing itself might not be sufficient to ensure accurate measurements. Therefore, research on a method of measurement that can complement auto-refractor measurements and provide confirmation of refraction results needs to be conducted. The customized optometry model described herein can satisfy the above requirements. With existing technologies, using human eye measurement devices to obtain relevant individual optical feature parameters is no longer difficult, and these parameters allow us to construct an optometry model for individual eyeballs. They also allow us to compute visual images produced from the optometry model using the CODE V macro programming language before recognizing the diffraction effects visual images with the neural network algorithm to obtain the accurate refractive diopter. This study attempts to combine the optometry model with the back-propagation neural network and achieve a double check recognition effect by complementing the auto-refractor. Results show that the accuracy achieved was above 98% and that this application could significantly enhance the service quality of refraction.

• 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.