• Journal of muscle and joint health
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• v.28 no.2
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• pp.79-90
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• 2021

Purpose: The purpose of this review was to analyze the effectiveness of complementary and alternative therapies (CAT) as nursing interventions for patients with osteoarthritis (OA). Methods: A systematic literature review was conducted using the PRISMA statement guidelines. To search for studies related to the effects of CAT applied as nursing care in OA patients, a combination of the keywords 'osteoarthritis,' 'complementary and alternative therapy,' and 'nursing care' were used. Finally, 12 articles retrieved from five electronic databases were included for the analysis. Results: Twelve studies were classified into seven interventions: Tai chi exercise, yoga, qigong, massage. flax seed compress, music, and meditation relaxation, administered by a nurse, and were RCTs. Outcome variables used for pain evaluation were WOMAC and VAS. The duration of interventions varied from 2 to 12 weeks. All twelve interventions had a positive effect on the outcome variables. Conclusion: CAT applied in nursing care for patients with OA significantly reduced pain and improved mobility. When planning a nursing intervention program, it is recommended to combine multiple therapies, considering the duration of effects. In addition, it is recommended to design the study as an RCT to secure the evidence for practical application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.571-576
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• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.526-532
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• 2022

With the development of IoT technology, image processing is being utilized in various fields such as image analysis, image recognition, medical industry, and factory automation. Noise is generated in image data from causes such as defect in transmission line. Image noise must be removed because it damages the performance of the image processing application program. Salt and Pepper noise is a representative type of image noise, and various studies have been conducted to remove Salt and Pepper noise. Widely known methods include A-TMF, AFMF, and SDWF. However, as the noise density increases, the performance deteriorates. Thus, this paper proposes an algorithm that performs filtering using a fuzzy logic weight mask only in case of noise after noise determination. In order to prove the noise removal performance of the proposed algorithm, an experiment was performed on images with 10% to 90% noise added and the PSNR was compared.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.907-913
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• 2022

Approximately 70% of smartphone users around the world use Android operating system-based smartphones, and malicious apps targeting these Android platforms are constantly increasing. Google has provided "Google Play Protect" to respond to the increasing number of Android targeted malware, preventing malicious apps from being installed on smartphones, but many malicious apps are still normal. It threatens the smartphones of ordinary users registered in the Google Play store by disguising themselves as apps. However, most people rely on antivirus programs to detect malicious apps because the average user needs a great deal of expertise to check for malicious apps. Therefore, in this paper, we propose a method to classify unnecessary malicious permissions of apps by using only the categories and permissions that can be easily confirmed by the app, and to easily detect malicious apps through the classified permissions. The proposed method is compared and analyzed from the viewpoint of undiscovered rate and false positives with the "commercial malicious application detection program", and the performance level is presented.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.14-26
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• 2022

Recently, according to the severity of air pollution, interest in air pollution is increasing. The IoT based fine dust monitoring system proposed in this paper allows the measurement and monitoring of fine dust, volatile organic compounds, carbon dioxide, etc., which are the biggest causes affecting the human body among air environmental pollution. The proposed system consisted of a device that measures atmospheric environment information, a server system for storing and analyzing measured information, an integrated monitoring management system for administrators and smart phone applications for users to enable visualization analysis of atmospheric environment information in real time. In addition, the effectiveness of the proposed fine dust monitoring system based on the Internet of Things was verified by using the response speed of the system, the transmission speed of the sensor data, and the measurement error of the sensor. The fine dust monitoring system based on the Internet of Things proposed in this paper is expected to increase user convenience and efficiency of the system by visualizing the air pollution condition after measuring the air environment information with portable fine dust measuring device.

• Composites Research
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• v.34 no.6
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• pp.337-344
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• 2021

In this study, the progressive failure behavior of the composite fan blade dovetail element under tensile loading is numerically investigated through finite element(FE) simulation. The accuracy of prediction by FE simulation is verified through tensile testing. The dovetail element is one of the joints for coupling the fan blade with the disk in a turbofan engine. The dovetail element is usually made of a metal material such as titanium, but the application of composite material is being studied for weight reduction reasons. However, manufacturing defects such as drop-off ply and resin pocket inevitably occur in realizing complex shapes of the fan blade made by composite materials. To investigate the effect of these manufacturing defects on the composite fan blade dovetail element, we performed numerical simulation with FE model to compare the prediction of the FE model and the tensile test results. At this time, the cohesive zone model is used to simulate the delamination behavior. Finally, we found that FE simulation results agree with test results when considering thermal residual stress and through-thickness compression enhancement effect.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.219-227
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• 2022

Students are always preparing for remote classes while taking face-to-face classes due to COVID-19. However, it is true that the class satisfaction with distance learning is not high for students and teachers. The idea that even if remote classes are conducted at home, it would be nice to have classes together like real ones, the need for a virtual world education program that utilizes augmented reality and virtual reality based on the metaverse has emerged. However, there are very few studies that teachers try to apply them to their classes. In this study, a metaverse application curriculum was presented for elementary science and 'space' domains. To implement the metaverse, ZEPETO and COSPACIS EDU were used. In the analysis of content creation with students and evaluation with schoolmates, this study showed that the concentration of learning was increased and creativity improved in the 'real', 'individual', and 'society' domains.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.115-122
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• 2020

In Korea, the agricultural machinery market has been generally on the rise, and particularly the demand for the diverse agricultural machine is increasing due to the radical changes in agriculture, such as a high supply of the advanced and automated agricultural machine and an increase in aged or female farmer population. Therefore, this study analyzes the technical trends in the precision agricultural machine domestically and globally to guide the direction of development of the ICT-based machine. The investigation of the precision agricultural machine in this study focuses on the production technology through analyzing the trends in sensor-related technology, the decision-making research, variable treatment technology, and academic publication. The result shows that information processing technology including the sensor and the decision-making requires various measurement factors and the established technologies are continually being developed.

• Journal of The Korean Association of Information Education
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• v.26 no.2
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• pp.141-151
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• 2022

Recently, basic literacy education related to digital literacy and data literacy has been emphasized for students who will live in a rapidly developing future digital society. Accordingly, demand for education to improve big data and data literacy is also increasing in general universities and universities of education as basic knowledge. Therefore, this study designed and applied big data analysis courses for pre-service teachers and analyzed the impact on data literacy. As a result of analyzing the interest and understanding of the input program, it was confirmed that it was an appropriate form for the level of pre-service teachers, and there was a significant improvement in competencies in all areas of 'knowledge', 'skills', and 'values and attitudes' of data literacy. It is hoped that the results of this study will contribute to enhancing the data literacy of students and pre-served teachers by helping with systematic data literacy educational research.