• Toxicological Research
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• v.28 no.4
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• pp.269-277
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• 2012

The purpose of this study was to understand the mechanism of cardiovascular disease (CVD) caused by exposure to hazardous chemicals. We investigated changes in the symptoms of metabolic syndrome, which is strongly related to CVD, and in levels of other CVD risk factors, with a special emphasis on the roles of catecholamines and oxidative stress. The results revealed that neither body mass index (BMI) nor waist and hip circumferences were associated with exposure to hazardous chemicals. Among metabolic syndrome criteria, only HDL-cholesterol level increased on exposure to hazardous chemicals. Levels of epinephrine (EP) and norepinephrine (NEP) were not influenced by exposure to hazardous chemicals; however, the total antioxidative capacity (TAC) reduced because of increased oxidative stress. Both hazardous chemical exposure level and metabolite excretion were related to EP, NEP, and the oxidative stress index (OSI). Logistic regression analysis with these factors as independent variables and metabolic syndrome criteria as dependent variables revealed that EP was associated with blood pressure, and NEP with metabolic syndrome in the chemical-exposed group. In conclusion, the results suggest that reactive oxygen species generated and oxidative stress due to exposure to hazardous chemicals act as mediators and cause changes in the physiological levels of EP and NEP to increase blood pressure. This ultimately leads to the development of CVD through increase in cholesterol, triglyceride, and blood glucose levels by lipid peroxidation.

• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.136-143
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• 2006

Contemporary society demands the ability to cope with the change competitively to the designer which is being accelerated of change and various media are emerging. The web design field which is one of the core design industry field of the contemporary society is needing the conversion from manufacturing technology specialization into creative design development composition. Generally, creative design development ability can be learned by studying. So, creativity development education is needed to develop creative design. Creative thought training is perceived as the core condition for competitive design and the education method for this is being proceeded multiply. But the study for design concept is lacking concretely. By this, this paper is to study the model which helps setting the design concept deduction creatively by instigating new ways of thought. The concept development process suggested in the study procedure systemizes the course for creative web design concept deduction and expects it to be utilized in design development to reinforce competitiveness.

• Journal of Engineering Education Research
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• v.24 no.5
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• pp.38-45
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• 2021

The CanSat was designed as an educational satellite simulation program that implements the overall system of the satellite such as the command processing unit, the communication unit, and the power unit in a structure of the size of a can. In particular, the training effect is very excellent because the trainee can learn a process similar to the actual satellite development process by designing, manufacturing, testing, and launching. Republic of Korea Air Force Academy has been using the CanSat production kit used by the domestic can satellite contest experience department for education, but since it was produced based on PCB, it was impossible to show creativity and operation was restricted even with small mistakes. In this paper, we analyze the existing CanSat kit and propose a new educational CanSat kit that can be used in creative engineering design and practice subjects that will be reorganized into a regular course from 2021, and a lesson plan. In conclusion, by using the proposed CanSat kit for lectures, it is possible to achieve educational purposes and effects, improve lecture satisfaction, and provide stable instruction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.119-127
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• 2019

In this study, we investigated the application of deep learning to the manufacturing process of traffic and road signs which are constituting the road layer in map production with 1 / 1,000 digital topographic map. Automated classification of road traffic sign images was carried out through construction of training data for images acquired by using transfer learning which is used in image classification of deep learning. As a result of the analysis, the signs of attention, regulation, direction and assistance were irregular due to various factors such as the quality of the photographed images and sign shape, but in the case of the guide sign, the accuracy was higher than 97%. In the digital mapping, it is expected that the automatic image classification method using transfer learning will increase the utilization in data acquisition and classification of various layers including traffic safety signs.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.37-47
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• 2021

In this paper, we propose a new deep learning model for tongue segmentation with improved accuracy compared to the existing model by diversifying the receptive field in the U-net. Methods such as parallel convolution, dilated convolution, and constant channel increase were used to diversify the receptive field. For the proposed deep learning model, a tongue region segmentation experiment was performed on two test datasets. The training image and the test image are similar in TestSet1 and they are not in TestSet2. Experimental results show that segmentation performance improved as the receptive field was diversified. The mIoU value of the proposed method was 98.14% for TestSet1 and 91.90% for TestSet2 which was higher than the result of existing models such as U-net, DeepTongue, and TongueNet.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.137-142
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• 2021

A Photovoltaic power streetlight is a system that uses solar energy to charge a secondary battery and then uses it for night lighting through a lamp, and can be configured as a standalone or grid-connected type by installing an LED streetlight at the load end. The energy generated through the solar cell module can be charged to the secondary battery through the charge/discharge control device, and then the LED street light can be turned on and off by comparing the power generation voltage and the charging voltage according to the monitoring of solar radiation, or by setting a specific time after sunset or sunrise. Based on these contents, this paper designed and manufactured a simulated solar power streetlight for education using new and renewable energy utilization and storage functions. Using these educational equipment, students can 1) understand the flow of energy change using renewable energy including sunlight as electric energy, 2) understand new and renewable energy, and cultivate basic design and manufacturing application power of related products, 3) The use of new and renewable energy through power conversion and strengthening of practical training and analysis through hardware production can be instilled.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.12
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• pp.43-53
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• 2019

The construction industry has made great strides in the past decades by utilizing computer programs including CAD. However, compared to other manufacturing sectors, labor productivity is low due to the high proportion of workers' knowledge-based task in addition to simple repetitive task. Therefore, the knowledge-based task efficiency of workers should be improved by recognizing the visual information of computers. A computer needs a lot of training data, such as the ImageNet project, to recognize visual information. This study, aim at proposing building facade datasets that is efficiently constructed by quickly collecting building facade data through portal site road view and automatically labeling using deep learning as part of construction of image dataset for visual recognition construction by the computer. As a method proposed in this study, we constructed a dataset for a part of Dongseong-ro, Daegu Metropolitan City and analyzed the utility and reliability of the dataset. Through this, it was confirmed that the computer could extract the significant facade information of the portal site road view by recognizing the visual information of the building facade image. Additionally, In contribution to verifying the feasibility of building construction image datasets. this study suggests the possibility of securing quantitative and qualitative facade design knowledge by extracting the facade design knowledge from any facade all over the world.

• Journal of Environmental Health Sciences
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• v.46 no.6
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• pp.702-709
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• 2020

Objectives: Hand sanitizer is made with ethyl alcohol as the main ingredient. Problems related to the use of hand sanitizers and cases of harm caused by the use of hand sanitizers are occurring. This study investigated the usage behavior and recognition level of people using hand sanitizer and identified the chemical components listed in the component label of hand sanitizer. In addition, the methanol and isopropanol contained in hand sanitizer were quantified using HS-GC-MSD. Methods: The investigation of the behavior and recognition of hand sanitizer usage was conducted through a survey of 143 college students and adults. The components marked on 34 types of hand sanitizers were investigated, and methanol and isopropanol concentrations were analyzed using the HS-GC-MSD method. Results: According to the survey, 57% of respondents use hand sanitizers two to three times per day, 92.3% of them do so when in public places and 41.3% of them do so at home. Ethanol, purified water, carbomer, glycerin, and triethanolamine were the ingredients listed in the hand sanitizer. Among the 34 samples, methanol and isopropyl alcohol were detected in 33 samples, the concentration range for methanol was ND-567 ppm, and the concentration range of isopropyl alcohol was ND-2121 ppm. Conclusion: The results of this study have shown that hand sanitizers are being used constantly every day, and methanol, which is not included in the marked content, was detected in a significant concentration compared to wet tissue. It has been found that maintenance of hand sanitizer manufacturing standards and training on how to use them are needed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.36-43
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• 2021

In this research, the accuracy of YOLO v3 algorithm in object detection during AGV (Automated Guided Vehicle) operation was investigated. First of all, AGV with 2D LiDAR and stereo camera was prepared. AGV was driven along the route scanned with SLAM (Simultaneous Localization and Mapping) using 2D LiDAR while front objects were detected through stereo camera. In order to evaluate the accuracy of YOLO v3 algorithm, recall, AP (Average Precision), and mAP (mean Average Precision) of the algorithm were measured with a degree of machine learning. Experimental results show that mAP, precision, and recall are improved by 10%, 6.8%, and 16.4%, respectively, when YOLO v3 is fitted with 4000 training dataset and 500 testing dataset which were collected through online search and is trained additionally with 1200 dataset collected from the stereo camera on AGV.