• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.669-676
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• 2017

Recently, due to the importance of information security, security vulnerability analysis and various information protection technologies and security systems are being introduced as a countermeasure against cyber-attacks in new as well as existing buildings, and information security studies on high-rise buildings are also being conducted. However, security system introduction and research are generally performed from the viewpoint of general IT systems and security policies, so there is little consideration of the infrastructure of the building. In particular, the BAS or building infrastructure, is a closed system, unlike typical IT systems, but has unique structural features that accommodate open functions. Insufficient understanding of these system structures and functions when establishing a building security policy makes the information security policies for the BAS vulnerable and increases the likelihood that all of the components of the building will be exposed to malicious cyber-attacks via the BAS. In this paper, we propose an architecture reference model that integrates three different levels of BAS structure (from?) different vendors. The architectures derived from this study and the security characteristics and vulnerabilities at each level will contribute to the establishment of security policies that reflect the characteristics of the BAS and the improvement of the safety management of buildings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.520-525
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• 2019

Mines are an important infrastructure for securing resources, but safety problems can arise in the course of operation. Recently, the mining process is very complicated due to the large scale and mechanization. Therefore, it is necessary to construct accurate geospatial information on mine for systematic and safe mine operation. The geospatial information construction using the existing total station has a disadvantage that a lot of work time is required because the target must be collimated and measured. In this study, the data of the mines were acquired with the total station and the 3D laser scanner, and the mine spatial information was constructed by using the shape based registration method. By using the static scanner data of some area applying the reference point surveying result of the total station, it was possible to construct the accurate result on the wide area acquired by the mobile scanner effectively. Also, the accuracy of the constructed geospatial information was evaluated and the deviation of mean 0.083m was shown. Point cloud products constructed through the research can contribute to the efficiency improvement of mine management by enabling quantitative analysis such as visualization of mine shape, distance, area and slope, and automation of drawing creation for cross section shape.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• Journal of Industrial Convergence
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• v.16 no.1
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• pp.21-26
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• 2018

The Seaborne Trade Volume accounts for 97% of the total. This means that the port operation management system can improve port efficiency, reducing operating costs, and the manager who manages all operations at the port needs to check and respond quickly when delays of work and equipment support is needed. Based on the real-time location information confirmation of yard automation equipment used the existing system GPS, the real-time location information confirmation system is a GPS system of the tablet, rather than a port operation system that monitors location information for the entered information, depending on the completion of the task or the start of the task. Network configurations also reduce container processing delays by using commercial LTE services that do not have shading due to containers in the yard also reduce container processing delays. Trough introduction of smart devices using Android or IOS and container processing scheduling utilizing artificial intelligence, we will build a minimum delay system with Smart Device usage of container processing applications and optimization of container processing schedule. The adoption of smart devices and the minimization of container processing delays utilizing artificial intelligence are expected to improve the quality of port services by confirming the processing containers in real time to consumers who are container information demanders.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.242-248
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• 2019

This study was conducted to examine the effects of a smart home (electronic control unit, ECU) on the performance and satisfaction of activities of daily living of wheelchair users. A total of 15 wheelchair users (10 patients with spinal cord injury and 5 patients with stroke) were investigated. Smart homes were equipped with ECU technology, which consisted of automation of furniture and products. The products and facilities were integrated and controlled by a smart device or voice. Performance and satisfaction of activities of daily living were measured by the Canadian Occupational Performance Measure (COPM) before and after residence in a smart home. All participants showed a higher COPM (performance score ${\geq}3$, satisfaction score ${\geq}4$) during residence in a smart home compared to residence in the current home. In addition, the COPM scores differed significantly before and after residence in a smart home. These results provide evidence of the applicability of smart homes based on high technology. However, additional studies of more smart home participants should be conducted to improve the quality of the results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.446-452
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• 2021

As a higher standard for food consumption is required, the consumption of chicken meat that can satisfy the subdivided food preferences is increasing. In March 2003, the quality criteria for chicken carcasses notified by the Livestock Quality Assessment Service suggested quality grades according to fecal contamination and the size and weight of blood and bruises. On the other hand, it is too difficult for human inspection to qualify mass products, which is key to maintaining consistency for grading thousands of chicken carcasses. This paper proposed the computer vision algorithm as a non-destructive inspection, which can identify chicken carcass parts according to the detailed standards. To inspect the chicken carcasses conveyed at high speed, the image calibration was involved in providing robustness to the side effect of external lighting interference. The separation between chicken and background was achieved by a series of image processing, such as binarization based on Expectation Maximization, Erosion, and Labeling. In terms of shape analysis of chicken carcasses, the features are presented to reveal geometric information. After applying the algorithm to 78 chicken carcass samples, the algorithm was effective in segmenting chicken carcass against a background and analyzing its geometric features.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.530-536
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• 2021

This paper presents the performance measurement results of a hybrid sheet with both shielding and heat dissipation functions developed by laminating copper mesh sheets and natural graphite sheets, which are used widely as electromagnetic shielding and heat-dissipating materials in electronic devices, without a pressure-sensitive adhesive (PSA). The results were compared by measuring the vertical and horizontal thermal conductivity with two other products to confirm the heat dissipation performance. A radiation emission test confirmed the electromagnetic shielding performance using a 3m electromagnetic anechoic chamber according to the CISPR 11 standard. In the case of vertical thermal conductivity, the proposed hybrid sheet was approximately 8.63 times higher than that of an aluminum sheet with heat dissipation coating and 18.7 times higher than that of a copper sheet laminated with artificial graphite with PSA. The proposed hybrid sheet was approximately 0.64 times that of the sheet, and approximately 1.76 times that of the heat-dissipated aluminum sheet in case of horizontal thermal conductivity. Measurements after applying each sheet in the same heat source revealed the proposed hybrid sheet to have the best heat dissipation performance. The radiation emission test showed that significantly radiation noise had been removed.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.1-9
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• 2023

Research using AI and big data is also being actively conducted in the health and medical fields such as disease diagnosis and treatment. Most of the existing research data used cohort data from research institutes or some patient data. In this paper, the difference in the prediction rate of survival and the factors affecting survival between breast cancer patients in their 40~50s and other age groups was revealed using health insurance review claim data held by the HIRA. As a result, the accuracy of predicting patients' survival was 0.93 on average in their 40~50s, higher than 0.86 in their 60~80s. In terms of that factor, the number of treatments was high for those in their 40~50s, and age was high for those in their 60~80s. Performance comparison with previous studies, the average precision was 0.90, which was higher than 0.81 of the existing paper. As a result of performance comparison by applied algorithm, the overall average precision of Decision Tree, Random Forest, and Gradient Boosting was 0.90, and the recall was 1.0, and the precision of multi-layer perceptrons was 0.89, and the recall was 1.0. I hope that more research will be conducted using machine learning automation(Auto ML) tools for non-professionals to enhance the use of the value for health insurance review claim data held by the HIRA.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.59-73
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• 2023

In the era of the 4th Industrial Revolution, manufacturing is the implementation of smart factories through digital transformation, and refers to consumer-centered intelligent factories that combine next-generation digital new technologies and manufacturing technologies beyond the existing factory automation level. In order to successfully settle such a smart factory, it is necessary to train professionals. However, education for smart factories is difficult to have actual field mechanical facilities or overall production processes. Therefore, there is a need for a system that can visualize and control the flow and process of logistics at the actual production site. In this paper, the logistics flow of the actual site was implemented as a small FMS, a physical system, and the production process was implemented as a digital system. In real-time synchronization of the physical system and the digital system, the location of AGV and materials, and the process state can be monitored to see the flow of logistics and process processes at the actual manufacturing site. The developed digital twin system can be used as an effective educational system for training manpower in smart factories.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.