• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.601-606
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• 2020

In this paper, we designed a microstrip patch antenna that can be applied to the Wimax/LTE 5G system among wireless media usable in coastal ships. The substrate of the proposed antenna is FR-4 (er=4.3), the size is 22 mm × 30 mm, and it can be used in the 3.5 GHz and 5.8 GHz bands of Wimax/LTE 5G by constructing a simple structure using a microstrip patch antenna. CST Microwave Studio 2014 was used for simulation, and the gain of the simulation result is 2.41dB at 2.4 GHz and 3.96 dB at 3.5 GHz. S-Parameter also showed a result of less than -10 dB (VSWR 2:1) in the desired frequency band, and designed a small variable and a miniaturized antenna so that the antenna can be used in mobile phones or electronic devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.377-383
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• 2021

Recently, in accordance with the 4th industrial revolution, The use of autonomous mobile robots for flexible logistics transfer is increasing in factories, the warehouses and the service areas, etc. In large factories, many manual work is required to use Simultaneous Localization and Mapping(SLAM), so the need for the improved mobile robot autonomous driving is emerging. Accordingly, in this paper, an algorithm for mapless navigation that travels in an optimal path avoiding fixed or moving obstacles is proposed. For mapless navigation, the robot is trained to avoid fixed or moving obstacles through Deep Q Network (DQN) and accuracy 90% and 93% are obtained for two types of obstacle avoidance, respectively. In addition, DQN requires a lot of learning time to meet the required performance before use. To shorten this, the target size change algorithm is proposed and confirmed the reduced learning time and performance of obstacle avoidance through simulation.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.333-338
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• 2020

This paper proposes an augmented reality-based electronic circuit education system as a way for electronic circuit education, which is the basis of ICT convergence technology field. It consists of a hardware module that can identify the actual circuit and a mobile educational content that can check the current flow, input, output, and measured value by applying augmented reality technology. An experiment was conducted on image recognition, which is the main performance, for the purpose of stable operation of the system, and as the experimental method the recognition rate was measured by changing the distance between the hardware module and the mobile device to a certain interval. As a result of the experiment, the recognition rate was 100 percent at a distance of 25[Cm] or higher, and it was confirmed that the recognition rate decreased by 12% at a distance below 25[Cm], which can be said to be the effect of an error that results in image loss taken due to close distance. In the future, we plan to apply the education system presented in this paper to classes, which increases the efficiency of classes and improve students' interest and understanding of the subject.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.819-824
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• 2021

As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.4
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• pp.1-9
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• 2021

This study was to investigate the types of emergencies transported by the Southwestern Coast Guard, the need for telemedicine guidance, and the perception and attitude of smart glasses as a communication method targeting 31 coast guards. A relatively high frequency and training requirement were confirmed for bleeding, abrasion, and abdominal pain. The demand for telemedicine guidance on medication and triage was higher, and the perceived usefulness and attitude scores for the use of smart glasses were 3.76±0.61 and 3.64±0.45, respectively. A moderate correlation between perceived usefulness and attitude toward smart glasses was confirmed (r=.630, p<.01). With the development of technology, it is time to actively introduce new devices such as smart glasses.

• Research in Community and Public Health Nursing
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• v.32 no.4
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• pp.555-565
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• 2021

Purpose: This study was conducted to develop the contents of disaster nursing education in community health nursing at universities. Methods: To validate contents, the Delphi method was used. We categorized two domains(indirect disaster management and direct disaster management) and developed 48 draft items. This study applied two round surveys and 23 experts participated in this study. The content validity was calculated using content validity ratio and coefficient of variation. Results: Indirect disaster management domain was composed of three categories including 12 items: 1) Understanding of the disaster, 2) disaster management system, and 3) response by disaster stage and recovery. Direct disaster management domain was composed of nine categories including 30 items: 1) Ethical considerations, 2) communication in disasters, 3) nursing activity by disaster stage, 4) emergency nursing in disasters, 5) patient severity classification in disasters, 6) disaster nursing for vulnerable groups, 7) disaster nursing for victims, 8) psychosocial nursing and health in disasters, and 9) cases of disaster nursing in communities. Conclusion: This Delphi study identified the contents of disaster nursing education curriculum, and confirmed the validity for disaster education program in community health nursing. Based on the results, it will be helpful for training the disaster nursing and improving the competency on disaster nursing of the nursing students.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.159-166
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• 2022

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.389-395
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• 2022

Because of improvement of deep learning techniques, deep learning using computer vision such as classification, detection and segmentation has also been used widely at many fields. Expecially, automatic driving is one of the major fields that applies computer vision systems. Also there are a lot of works and researches to combine multiple tasks in a single network. In this study, we propose the network that predicts the individual depth of pedestrians and vehicles. Proposed model is constructed based on YOLOv3 for object detection and Monodepth for depth estimation, and it process object detection and depth estimation consequently using encoder and decoder based on hard parameter sharing. We also used attention module to improve the accuracy of both object detection and depth estimation. Depth is predicted with monocular image, and is trained using self-supervised training method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.333-340
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• 2022

The COVID-19 has made everyone anxious and people need to keep their distance. It is necessary to conduct collective assessment and screening of college students' mental health in the opening season of every year. This study uses and trains a multi-layer perceptron neural network model for deep learning to identify facial emotions. After the training, real pictures and videos were input for face detection. After detecting the positions of faces in the samples, emotions were classified, and the predicted emotional results of the samples were sent back and displayed on the pictures. The results show that the accuracy is 93.2% in the test set and 95.57% in practice. The recognition rate of Anger is 95%, Disgust is 97%, Happiness is 96%, Fear is 96%, Sadness is 97%, Surprise is 95%, Neutral is 93%, such efficient emotion recognition can provide objective data support for capturing negative. Deep learning emotion recognition system can cooperate with traditional psychological activities to provide more dimensions of psychological indicators for health.

• The Research Journal of the Costume Culture
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• v.30 no.3
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• pp.414-428
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• 2022

The goal of this study was to develop a curriculum based on practice and job competency, reflecting opinions on the required job competence of nail practitioners and professionals related to nail beauty. Through in-depth interviews with nail experts, the research focuses on developing nail beauty competency-based curriculum and curriculum profiles that reflect practitioners' needs of job competence in the field. In-depth interviews with 11 field experts and surveys of 154 people were conducted to develop a competency-based curriculum for beginner nail hairdressers. The results of this study show that the existing 38 National Competency Standards (NCS) job competencies were reduced to 21 job competencies. In addition, based on the common opinions of experts who reflect the current trend, two tasks on "eyelashes" and "waxing" were added, and they were modified and supplemented with 23 core competencies. The development of a competency-based curriculum and educational programs for nail beauty was performed based on the requirements of the core competencies investigated and the development of a systematic map for the core competencies of beginner nail technicians and hairdressers. In conclusion, the need for professional education and training for nail hairdressers is growing, and it can be seen that a curriculum building multi-faceted abilities is needed for their qualifications as experts. This study found that it is necessary to develop interpersonal communication skills that include marketing elements other than practical skills such as personality and customer response methods in the nail beauty curriculum.