• Journal of the Korean Institute of Educational Facilities
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• v.26 no.6
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• pp.3-17
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• 2019

During adolescence, youths may experience many unexpected changes due to sudden variances. At that time, youths were found to show rebellious or abnormal behaviors due to psychological wounds. These are often caused by psychological wounds oriented at home or at school, which may make some problems in adolescents' self-respect and attachment. In this study, we plan to conduct an analysis of the case of the interior therapy of educational facilities through TBRI (Trust-Based Relational Intervention) to discover how psychological therapy for youths is applied to an interior environment. The cases analysis are conducted based on the three principles of TBRI and the twenty seven detailed keywords within each principle. The research method is oriented on the research of literature focusing on TBRI-related external studies and domestic/external studies of interior therapy. The ranges of the case study are studied in six educational facilities retrieved and extracted from the website 'Archdaily' and from the 2019 Journal of the Korean Institute of Educational Facilities. The research article are concluded that TBRI's principles were applied to shape, finish material, color, lighting, furniture layout, plan layout, sculpture, and built-in-furniture by analyzing the interior therapy of educational facilities according to the elements of TBRI.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.219-219
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• 2013

The effect of an electron blocking layer (EBL) on V-I curves in GaN/InGaN multiple quantum well is investigated. For the first time, we found that curves were intersected at 3.012 V and analyzed the reason for intersection. The forward voltage in LEDs with an p-AlGaN EBL is larger than without p-AlGaN EBL at low injection current because the Mg doping efficiency for p-GaN layer was higher than that of p-AlGaN layer. However, the forward voltage in LEDs with an p-AlGaN EBL is smaller than without p-AlGaN EBL at high injection current because the carriers overflow from the active layer when injection current increases in LEDs without p-AlGaN EBL and in case of LED with p-AlGaN EBL, the carriers are blocked by EBL.

• Transactions of Materials Processing
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• v.11 no.6
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• pp.487-494
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• 2002

A new method of optimal blank shape design using the initial nodal velocity (INOV) has been proposed for the drawings of arbitrary shaped cups. With the given information of tool shape and the final product shape, corresponding initial blank shape has been found from the motion of boundary nodes. Although the sensitivity method, the past work of the present authors, has been proved to be excellent method to find optimal blank shapes, the method has a problem that a couple of deformation analysis is required at each design step and it also exhibits an abnormal behaviors in the rigid body rotation prevailing region. In the present method INOV, only a single deformation analysis per each design stage is required. Drawings of practical products as well as oil-pan, have been chosen as the examples. At every case the optimal blank shapes have been obtained only after a few times of modification without predetermined deformation path. The deformed shape with predicted optimal blank almost coincides with the target shape at every case. Through the investigation the INOV is found to be very effective in the arbitrary shaped drawing process design.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.520-537
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• 2019

This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.

• Parasites, Hosts and Diseases
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• v.57 no.3
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• pp.243-248
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• 2019

The purpose of this study was 2-fold: 1) to investigate the prevalence of gastrointestinal parasite infection in cats reared in Daegu, Republic of Korea and 2) to assess the efficacy and safety of a topical emodepside/praziquantel formulation for cats with parasitic infections. The gastrointestinal parasite infections were examined microscopically using the flotation method. Of 407 cats, 162 (39.8%) were infected by at least one gastrointestinal parasite, including Toxocara cati (63.0%), Toxascaris leonina (31.5%), Taenia taeniaeformis (3.7%), and Cystoisospora felis (1.9%). None of the infected animals had multiple infections. When the data were analyzed according to sex, age, and type of cat, stray cats showed statistically higher prevalence than companion cats (P<0.05). On the 5th day after treatment, no parasitic eggs were detected using microscopic examination. In addition, no adverse effects, such as abnormal behaviors and clinical symptoms, were observed in the cats treated with the drug. These results quantify the prevalence of gastrointestinal parasites in cats in Daegu, Republic of Korea, and show that topical emodepside/praziquantel is a safe and effective choice for treating the parasitic infections in cats.

• Journal of the Korean Society of Visualization
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• v.17 no.2
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• pp.10-16
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• 2019

Considering the role of viscosity in the hemorheology, the characteristics of non-Newtonian fluid are important in the pulsatile blood flows. Stenosis, with an abnormal narrowing of the vessel, contributes to block blood flows to downstream tissue and lead to plaque rupture. Therefore, systematic analysis of blood flow around stenosed vessels is crucial. In this study, non-Newtonian behaviors of blood analog fluids around the micro-stenosis with 60 % severity in diameter of $500{\mu}m$ was examined by using CFX under the pulsatile flow conditions with the period of 10 s. Viscosity information of two non-Newtonian fluids were obtained by fitting the value of normal blood and highly viscous blood. As the Newtonian fluid, the water at room temperature was used. During the pulsatile phase, wall shear stress (WSS) is highly oscillated. In addition, high viscous solution gives rise to increases the variation in the WSS around the micro-stenosis. Highly oscillating WSS enhance increasing tendency of plaque instability or rupture and damage of the tissue layer. These results, related to the influence on the damage to the endothelium or stenotic lesion, may help clinicians understand relevant mechanisms.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.700-703
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• 2021

Infrared cameras are widely used in recent research for automatic monitoring the abnormal behaviors of the pig. However, when deployed in real pig farms, infrared cameras always get polluted due to the harsh environment of pig farms which negatively affects the performance of pig monitoring. In this paper, we propose a real-time noise-robust infrared camera-based pig automatic monitoring system to improve the robustness of pigs' automatic monitoring in real pig farms. The proposed system first uses a preprocessor with a U-Net architecture that was trained as a GAN generator to transform the noisy images into clean images, then uses a YOLOv5-based detector to detect pigs. The experimental results show that with adding the preprocessing step, the average pig detection precision improved greatly from 0.639 to 0.759.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.142-148
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• 2023

In Modern days, Self-driving for modern people is an absolute necessity for transportation and many other reasons. Additionally, after the outbreak of COVID-19, driving by oneself is preferred over other means of transportation for the prevention of infection. However, due to the constant exposure to stressful situations and chronic fatigue one experiences from the work or the traffic to and from it, modern drivers often drive under drowsiness which can lead to serious accidents and fatality. To address this problem, we propose a drowsy driving prevention learning model which detects a driver's state of drowsiness. Furthermore, a method to sound a warning message after drowsiness detection is also presented. This is to use MoveNet to quickly and accurately extract the keypoints of the body of the driver and Dense Neural Network(DNN) to train on real-time driving behaviors, which then immediately warns if an abnormal drowsy posture is detected. With this method, we expect reduction in traffic accident and enhancement in overall traffic safety.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.494-510
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• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.

• Journal of dental hygiene science
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• v.7 no.4
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• pp.225-233
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• 2007

This study, to investigate the job burnout and coping behaviors that clinical dental hygienists feel in the work process, has collected 322 clinical dental hygienists working in Daegu, Kyungbuk province, and Ulsan and had a conclusion as follows. 1. The average of area job burnout and coping behaviors were as follows; emotional burnout, 3.26, cynical manners, 2.63, the declination of job efficiency, 2.58, the total average, 2.82. 2. The average of area were as follows; active coping, 3.36, passive coping, 2.95, and the total average, 3.19. 3. The difference of job burnout relating to general characteristics was shown that the lower education level and age they were in, the significantly higher the declination of job efficiency and burnout area were. The unmarried had significantly higher points at cynical manners, the declination of job efficiency and burnout. Besides, the introspective had significantly higher points at emotional exhaustion, cynical manners, and burnout area. 4. The difference of job burnout related to working circumstance was shown that those with short working experience and those in charge of the general treatment showed significantly high points at the declination of job efficiency. And the less annual salary, the significantly higher points at cynical manners, the declination of job efficiency and burnout area. 5. In the correlation between job burnout and coping method, burnout area has a significantly normal correlation with active coping and coping area, whereas, it has significantly abnormal correlation with passive coping. 6. As for the difference of area burnout relating to coping behaviors, in coping area A group(under average) had significantly higher points than B group(over average) at the declination of job efficiency and burnout area. From the above results, it was proved that the clinical dental hygienists in younger age, with shorter work experience and less annual salary, no marital spouse had higher points at burnout and passive coping.