• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.11
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• pp.965-972
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• 2016

This paper presents results of flight experiments on a navigation algorithm including multiplicative extended Kalman filter for estimating attitude of the guided munition. The filter describes orientation of aircraft by data fusion with low-cost sensors where measurement update is done by multiplication, rather than addition, which is suitable for quaternion representation. In determining attitude from vector observations, the existing approach utilizes a 3-axis accelerometer as a 2-axis inclinometer by measuring gravity to estimate pitch and roll angles, while GNSS velocity is used to derive heading of the vehicle. However, during accelerated maneuvers such as coordinated flight, the accelerometer provides inadequate inclinometer measurements. In this paper, the measurement update process is newly defined to complement the vulnerability by using different vector observations. The acceleration measurement is considered as a result of a centrifugal force and gravity during turning maneuvers and used to estimate roll angle. The effectiveness of the proposed method is verified through flight experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.1-9
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• 2020

As pet dogs rapidly increase in number, abandoned and lost dogs are also increasing in number. In Korea, animal registration has been in force since 2014, but the registration rate is not high owing to safety and effectiveness issues. Biometrics is attracting attention as an alternative. In order to increase the recognition rate from biometrics, it is necessary to collect biometric images in the same form as much as possible-from the face. This paper proposes a method to determine whether a dog is facing front or not in a real-time video. The proposed method detects the dog's eyes and nose using deep learning, and extracts five types of directional face information through the relative size and position of the detected face. Then, a machine learning classifier determines whether the dog is facing front or not. We used 2,000 dog images for learning, verification, and testing. YOLOv3 and YOLOv4 were used to detect the eyes and nose, and Multi-layer Perceptron (MLP), Random Forest (RF), and the Support Vector Machine (SVM) were used as classifiers. When YOLOv4 and the RF classifier were used with all five types of the proposed face orientation information, the face recognition rate was best, at 95.25%, and we found that real-time processing is possible.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.278-286
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• 2022

In this study, a 33-mode Free-Flooded Ring (FFR) transducer was designed to apply piezoelectric single crystal PIN-PMN-PT, which has high piezoelectric constants and electromechanical coupling coefficient. To ensure low-frequency high transmitting sensitivity characteristics with a small size of FFR transducer, the commercial FFR transducer based on piezoelectric ceramics was compared. To develop the FFR transducer with broadband characteristics, a piezoelectric segmented ring structure inserted with inactive elements was applied. The oil-filled structure was applied to minimize the change of acoustic characteristics of the ring transducer. It was verified that the transmitting voltage response, underwater impedance, and beam pattern matched the finite element numerical simulation results well through an acoustic test. The difference in the transmitting voltage response between the measured and the simulated results is about 1.3 dB in cavity mode and about 0.3 dB in radial mode. The fabricated FFR transducer had a higher transmitting voltage response compared to the commercial transducer, but the diameter was reduced by about 17 %. From this study, it was confirmed that the feasibility of a single crystal-applied FFR transducer with compact size and high-power characteristics. The effectiveness of the performance prediction by simulation was also confirmed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.230-238
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• 2023

Small and medium-sized food manufacturing enterprises are largely reliant on manual labor, from inputting raw materials to palletizing the final product. Recently, there has been a trend toward smartness and digitization through the implementation of robotics and sensor data technology. In this study, we examined the effectiveness of improvement through 3D simulation on two repetitive work processes within a food manufacturing company. These processes involve workers whose speed cannot match the capacity of the applied equipment. Two manual processes were selected: the weighing and packing process performed by workers after skewer assembly, and the manual batch process of counting randomly delivered frozen foods, packing (both internal and external), and palletizing. The production volume, utilization rate, and number of workers were chosen as verification indicators. As a result of the simulation for improving the 3D process, production increased by 13.5% and 56.8% compared to the existing process, respectively. This was particularly evident in the process of applying palletizing robots. In both processes, as the utilization rate and number of input workers decreased, robots could replace tasks with high worker fatigue, thereby reducing work overload. This study demonstrates the potential to visually compare the process flow improvement using 3D simulations and confirms the possibility of pre-validation for improvement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1038-1048
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• 2019

Recently, various systems have been developed to support ship navigation safety. In order to verify the usefulness of such a system, it is most ideal to try it on a real vessel, but there are many difficulties. As an alternative, usability verification methods applied with modelling and simulation (M&S) techniques are required such as FMSS, which is closest to reality, is very expansive to construct, and there needs the specialized operator. For this reason, this paper proposes a method to verify the navigation safety support system by modeling and simulation techniques based on the Discrete Event System Specification (DEVS) formalism. As a first step, we designed the navigation simulation architecture based on the SES/MB framework, and details on modelling ship core equipment and navigator agents based on the DEVS. Through this, we are able to implement the navigation simulation system for vessels, and evaluate the effectiveness of navigation safety support elements such as collision avoidance, etc. using developed scenarios.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.17-26
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• 2023

In this paper, we propose a several smoothing techniques are compared and applied to increase the application of the LSTM-based learning model and its effectiveness. The applied smoothing technique is Savitky-Golay, exponential smoothing, and weighted moving average. Through this study, the LSTM algorithm with the Savitky-Golay filter applied in the preprocessing process showed significant best results in prediction performance than the result value shown when applying the LSTM model to Bitcoin data. To confirm the predictive performance results, the learning loss rate and verification loss rate according to the Savitzky-Golay LSTM model were compared with the case of LSTM used to remove complex factors from Bitcoin price prediction, and experimented with an average value of 20 times to increase its reliability. As a result, values of (3.0556, 0.00005) and (1.4659, 0.00002) could be obtained. As a result, since crypto-currencies such as Bitcoin have more volatility than stocks, noise was removed by applying the Savitzky-Golay in the data preprocessing process, and the data after preprocessing were obtained the most-significant to increase the Bitcoin prediction rate through LSTM neural network learning.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.341-352
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• 2022

The wave of a knowledge and information society led by AI, Big Data, and so on is having an all-round impact on our way of life. Therefore the Ministry of Education is in a hurry to strengthen Digital Literacy, including AI and SW Education, by improving the curriculum that can cultivate basic knowledge and capabilities to respond to changes in the future society. It can be seen that establishing a foundation for cultivating Digital Literacy through all subjects and improving basic and in-depth learning in new technology fields such as AI linked to the information curriculum is an essential part for future society. However, research on each content for cultivating Digital and AI literacy is relatively active, while research on teaching and learning strategies is insufficient. Therefore in this study, a CT-based Digital and AI teaching and learning strategy that can foster that was developed and Delphi expert verification was conducted, and the final teaching and learning strategy was completed after evaluating instructor usability and analyzing learner effectiveness.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.373-382
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• 2024

This study attempted to identify the relationship between nursing competency, clinical reasoning competence, and empathy ability according to the center of enneagram power for nursing students. The subjects of the study were 218 students enrolled in the department of nursing at two universities located in one region, data collection was conducted from 16 October to 27 October 2023. Data analysis was performed using SPSS/WIN version 26.0 program, descriptive statistics, and difference verification were analyzed by t-test, ANOVA, pearson's correlation coefficient, Results, The enneagram personality type of the subjects of this study was the most common type 9. And in the enneagram center of power, the instinct-centered type had the highest nursing competence, the thought-centered type had the highest clinical reasoning competence, and the emotion-centered type had the highest empathy ability. In addition, nursing competence and clinical reasoning competence showed a significant positive correlation, and clinical reasoning competence and empathy ability were also found to be positively correlated. Therefore, it is important to continue to develop and apply individualized competency building programs that reflect personality type tests to nursing students. In addition, the higher the empathy ability, the higher the clinical reasoning competence, so it is thought that it is necessary to develop a standardized curriculum that can improve nursing competence and clinical reasoning competence and verify its effectiveness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.542-550
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• 2020

A stream serve the functions of different water utilization, flood control, and the environment, and contributes to the development of national life and culture. On the other hand, it is difficult to efficiently evaluate various projects, such as effectiveness verification and comparison between projects, because the evaluation procedures and evaluation techniques of projects are not uniform and different for each institution. Therefore, a standardization technology was developed for a post-assessment of stream projects that can recognize stream problems and comprehensively evaluate stream-related projects. To this end, various projects, such as project evaluation techniques, national R&D projects, and social welfare projects, were compared and analyzed, and the standardization stages of the project were first suggested. In addition, based on the standardization stage, the evaluation indices for each stage were derived to develop an evaluation table that can evaluate stream-related projects comprehensively. Finally, it is possible to prevent the repeated use of failure factors in the planned projects.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.616-631
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• 2015

This study proposes a mobile Augmented Reality (AR)-based "word card" learning tool for children aged 3 to 5. First, this study suggests a learning structure to improve motivation and immersion of learning, Secondly, it designs and implements the user interface applying the proposed learning structure. Also, it designs a content management tool supporting the production of the content so that instructors can easily manage the contents for various learners. This study is conducted by four steps - reference research, design of "word card" learning content for the learner, design of content management tool for the instructor and the effectiveness verification of the proposed content. The proposed content was designed based on an education content architecture for enhancement of immersion and motivation to study. Moreover, it includes an 'AR content management tool for instructor' designed to easily update AR education content. The class for six children aged 3 to 5 was given to validate the enhancement of immersion to study. Experiment results showed that the proposed content enhanced the study immersion and that special interaction design for early children was necessary.