• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.1
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• pp.52-56
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• 2018

Extracorporeal shockwave therapy has been widely spread out showing an excellent efficacy compared to traditional medicinal treatments, interventional procedures or surgeries for diseases of tendons and musculoskeletal system. Major performance tests of extracorporeal shockwave therapy consist of pressure, energy flux, concentration, and effective amount of energy on the focus area of shockwave according to IEC 61846. Shockwave should be irradiated accurately to the lesion area to improve the performance of extracorporeal shockwave therapy, which makes it necessary to add the relevant section, IEC 60601-2-36 (12.1.101. Precision of Target Markers and Target Locations). International standards of extracorporeal shockwave therapy have been prepared based on European and western people. Thus, we need to conduct many studies on Korean patients to improve the quality of extracorporeal shockwave therapy and to develop the medical industry. In addition, the performance evaluation of extracorporeal shockwave therapy which has been prepared according to international standards should be additionally modified and supplemented corresponding to the Korean circumstances.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.6
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• pp.551-557
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• 2009

A development of smart materials is becoming a prominent issue on present industries. A smart material, included in functions, is needed for micro fabrication. A shape memory alloy(SMA) in a smart material is best known material. Ni-Ti alloy, composed of nikel and titanium is one of the best shape memory alloy(SMA). Nitinol SMA is used for a lot of high tech industry such as aero space, medical device, micro actuator, sensor system. However, Ni-Ti SMA is difficult to process to make a shape and fabrications as traditional machining process. Because nitinol SMA, that is contained nikel content more than titanium content, has similar physical characteristics of titanium. In this paper, the characteristics of ECM grooving process for nitinol SMA are investigated by experiments. The experiments in this study are progressed for power, gap distance and machining time. The characteristics are found each part. Fine shape in work piece can be found on conditions; current 6A, duty factor 50%, gap distance 15%, gap distance $15{\mu}m$, machining time 10min.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.368-372
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• 2021

The article identifies the features of the digital culture of modern society in the dynamics of its impact on the education sector, identifies the main directions of digitalization education, an objective analysis is presented, the possibilities of examination as a scientific assessment are determined "Digital reforms" of education, the role of traditional values of educational culture in expertise and improvement digital innovations in the education system, identified the main contradictions in the development of digital culture, to determine the directions of its improvement. The article describes the three main components of information technology as a complex of hardware, software and a system of organizational and methodological support; the description of analog and digital information technologies is presented. The authors list the most common multifunctional office applications and IT tools; the advantages of using IT in the educational process are highlighted.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.323-328
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• 2021

Diagnostic models are required. Data augmentation is one of the best ways to improve deep learning performance. Traditional augmentation techniques that modify image brightness or spatial information are difficult to achieve great results. To overcome this, a generative adversarial network (GAN) technology that generates virtual data to increase deep learning performance has emerged. GAN can create realistic-looking fake images by competitive learning two networks, a generator that creates fakes and a discriminator that determines whether images are real or fake made by the generator. GAN is being used in computer vision, IT solutions, and medical imaging fields. It is essential to secure additional learning data to advance deep learning-based fault diagnosis solutions in the power industry where facilities are strictly maintained more than other industries. In this paper, we propose a method for generating power facility images using GAN and a strategy for improving performance when only used a small amount of data. Finally, we analyze the performance of the augmented image to see if it could be utilized for the deep learning-based diagnosis system or not.

• Advances in nano research
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• v.17 no.2
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• pp.109-124
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• 2024

In the era of smart manufacturing, precise prediction of springback-a common issue in ultra-thin sheet metal forming- and forming limits are critical for ensuring high-quality production and minimizing waste. This paper presents a novel approach that leverages the Internet of Things (IoT) and Artificial Neural Networks (ANN) to enhance springback and forming limits prediction accuracy. By integrating IoT-enabled sensors and devices, real-time data on material properties, forming conditions, and environmental factors are collected and transmitted to a central processing unit. This data serves as the input for an ANN model, which is trained with crystal plasticity simulations and experimental data to predict springback with high precision. Our proposed system not only provides continuous monitoring and adaptive learning capabilities but also facilitates real-time decision-making in manufacturing processes. Experimental results demonstrate significant improvements in prediction accuracy compared to traditional methods, highlighting the potential of IoT and ANN integration in advancing smart manufacturing. This approach promises to revolutionize quality control and operational efficiency in the industry, paving the way for more intelligent and responsive manufacturing systems.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.607-615
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• 2009

There has recently been a trend that IT industry is united with traditional industries such as military, aviation, automobile, and medical industry. Therefore, embedded software which controls hardware of the system should guarantee the high reliability, availability, and maintainability. To guarantee these properties, there are many attempts to develop the embedded software based on COTS (Commercial Off The Shelf) hardware components. However, it can cause additional faults due to software/hardware interactions beside general software faults in this methodology. We called the faults, Linkage Fault. These faults have high severity that makes overall system shutdown although their occurrence frequency is extremely low. In this paper, we propose a new software reliability model which considers those linkage faults in embedded software development with COTS hardware components. We use the Bayesian Analysis and Markov Chain Monte-Cairo method to validate the model. In addition, we analyze real linkage fault data to support the results of the theoretical model.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.417-424
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• 2015

The research of occupational injury for safety and health is a comparatively recent occurrence. As labor activities took place regarding to employee concerns in industrial uprising, human resources health was tried to enhanced as a labor safety subject. Noticing that traditional statistics approach has limitations in learning future forecasting and major factors causing occupational injuries in each industry, Korean Government initiated a quantitative systematic simulation model project to analyze how the annual injury rate has been dropped and stays in a level for recent years. From this motivation and the project, system dynamics models have been developed to explain the mechanisms for reducing annual injury rate, and the mechanisms quantitatively. The main cause effects for the reduction of annual injury rate were due to the government driven investment on safety facilities. In overall viewpoint the gain achievable from these efforts has been reached a saturated level. However, it could reduce the annual injury rate if you chose the industry and size carefully. The model for forecasting, major injury factors, safety budget and allocation are introduced and analyzed, and Analyzing occupational injury related factors can also reduce employee injury and disease related costs, including medical care, quit, and disability assistance costs.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.299-304
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• 2019

Recently, the development of rehabilitation medical technology has resulted in an increased interest in speech therapy equipment. In particular, research on articulation therapy for communication disorders is being actively conducted. Existing methods for the diagnosis and treatment of speech disorders have many limitations, such as traditional tactile perception tests and methods based on empirical judgment of speech therapists. Moreover, the position and tension of the tongue are key factors of speech disorders with regards to articulation. This is a very important factor in the distinction of Korean characters such as lax, fortis, and aspirated consonants. In this study, we proposed a Korean electropalatography (EPG) system to easily measure and monitor the position and tension of the tongue in articulation treatment and diagnosis. In the proposed EPG system, a sensor was fabricated using an AgCl electrode and biocompatible silicon. Furthermore, the measured signal was analyzed by implementing the bio-signal processing module and monitoring program. In particular, the bio-signal was measured by inserting it into the palatal from an experimental control group. As a result, it was confirmed that it could be applied to clinical treatment in speech therapy.

• Journal of Sasang Constitutional Medicine
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• v.25 no.4
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• pp.306-319
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• 2013

Objectives The purpose of this study was to find correlations between gastrointestinal disorders, pain, sleep disorder, fatigue, and to figure out characteristics of fatigue in Sasang Constitution using medical devices data. Methods Sixty three subjects were divided into fatigue group and non-fatigue group, both groups had to undergo blood tests, questionnaire, Sasang constitutional analysis tool (SCAT), pulse wave analyzer examination, heart rate variability examination, nail fold capillary microscopic examination. Results 1) The results of questionnaire about fatigue, gastrointestinal disorder, pain, sleep disorder, quality of life had significant differences between fatigue and non-fatigue groups. 2) Soeumin had more serious gastrointestinal problem and Soyangin had more serious sleep disorder in fatigue groups than non-fatigue groups. 3) According to blood test results, there was no difference between fatigue and non-fatigue groups. 4) Elastic parameter of pulse wave analyzer and nail fold capillary microscopic examination showed significant differences between fatigue and non-fatigue groups in Soyangin. Conclusions We reach the conclusion that fatigue is usually accompanied by gastrointestinal disorder, pain, sleep disorder, deterioration in the quality of life. In Soeumin, treating gastrointestinal disorders can be helpful for treatment of fatigue. In Soyangin, improving sleep disorder may be more effective way to treat fatigue.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2480-2496
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• 2020

Considering that high-dose X-ray radiation during CT scans may bring potential risks to patients, in the medical imaging industry there has been increasing emphasis on low-dose CT. Due to complex statistical characteristics of noise found in low-dose CT images, many traditional methods are difficult to preserve structural details effectively while suppressing noise and artifacts. Inspired by the deep learning techniques, we propose a densely connected residual network (DCRN) for low-dose CT image noise cancelation, which combines the ideas of dense connection with residual learning. On one hand, dense connection maximizes information flow between layers in the network, which is beneficial to maintain structural details when denoising images. On the other hand, residual learning paired with batch normalization would allow for decreased training speed and better noise reduction performance in images. The experiments are performed on the 100 CT images selected from a public medical dataset-TCIA(The Cancer Imaging Archive). Compared with the other three competitive denoising algorithms, both subjective visual effect and objective evaluation indexes which include PSNR, RMSE, MAE and SSIM show that the proposed network can improve LDCT images quality more effectively while maintaining a low computational cost. In the objective evaluation indexes, the highest PSNR 33.67, RMSE 5.659, MAE 1.965 and SSIM 0.9434 are achieved by the proposed method. Especially for RMSE, compare with the best performing algorithm in the comparison algorithms, the proposed network increases it by 7 percentage points.