• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.39-48
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• 2023

This study was conducted to provide a solution to the problem of sizing errors occurring in online purchases due to discrepancies and non-standardization in clothing sizes. This paper discusses an implementation approach for a machine learning-based recommender system capable of providing personalized sizes to online consumers. We trained multiple validated collaborative filtering algorithms including Non-Negative Matrix Factorization (NMF), Singular Value Decomposition (SVD), k-Nearest Neighbors (KNN), and Co-Clustering using purchasing data derived from online commerce and compared their performance. As a result of the study, we were able to confirm that the NMF algorithm showed superior performance compared to other algorithms. Despite the characteristic of purchase data that includes multiple buyers using the same account, the proposed model demonstrated sufficient accuracy. The findings of this study are expected to contribute to reducing the return rate due to sizing errors and improving the customer experience on e-commerce platforms.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.13-19
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• 1995

A dual purpose robot automation system is developed for both arc welding and spot welding by one robot within a cell. The need for automation of both arc welding and spot welding processes is urgent while the production volume is not so big as to accommodate separate stations for the two processes. Also, space is too narrow for separate stations to be settled down in the factory. A spot welding robot is chosen and the functions for arc welding are implemented in-house at cost of advanced functions. For the spot welding, a single pole type gun is used and the robot has to push down the plate to be wolded, which causes the robot positioning error. Therefore, position error compensation algorithm is developed. The basic functions for the arc welding processes are implemented using the digital I/O board of robot controller, PLC, and A/D conversion PCB. The weaving pattern is taught in meticulously by manual teach. A fixture unit is also developed for dual purpose. The main aspects of the system is presented in this paper especially in the design and implementation procedure. The signal diagrams and sequence logic diagrams are also included. The outcome of the dual purpose welding cell is the increased productivity and good production stability which is indispensable for production volume prediction. Also, it leads to reduction of manufacturing lead time.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.154-160
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• 1996

The control of diamond turning is usually achieved through a laser-interferometer feedback of slide position. The limitation of this control scheme is that the feedback signal does not account for additional dynamics of the tool post and the material removal process. If the tool post is rigid and the material removal process is relatively static, then such a non-collocated position feedback control scheme may surfice. However, as the accuracy requirement gets tighter and desired surface cnotours become more complex, the need for a direct tool-tip sensing becomes inevitable. The physical constraints of the machining process prohibit any reasonable implementation of a tool-tip motion measurement. It is proposed that the measured force normal to the face of the workpiece can be filtered through an appropriate admittance transfer function to result in the estimated dapth of cut. This can be compared to the desired depth of cut to generate the adjustment control action in additn to position feedback control. In this work, the design methodology on the admittance model-based control with a conventional controller is presented. The recursive least-squares algorithm with forgetting factor is proposed to identify the parameters and update the cutting process in real time. The normal cutting forces are measured to identify the cutting dynamics in the real diamond turning process using the precision dynamoneter. Based on the parameter estimation of cutting dynamics and the admitance model-based nanodynamic control scheme, simulation results are shown.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.580-581
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• 2021

There are various Location-Based Services(LBS) that apply GPS technology in mobile devices such as smart-phone and tablet. In this paper, we designed non-face-to-face oriented LBS software in the reality that non-face-to-face services are increasing due to COVID-19. The proposed model searches location information for trading goods or services and utilizes information identified in real time. The proposed scheduling and priority control algorithm provides efficient service allocations and simulation was performed based on web/app to verify this. While commercialized LBS platforms focus on used goods transactions, the designed method is different in that it provides non-face-to-face services and not-direct transactions between individuals. It provides a wide range of transactions and services to users such as small business owners and franchises.

• The Journal of Bigdata
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• v.7 no.2
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• pp.103-111
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• 2022

There are many institutions, organizations, and sites related to responding to infectious diseases, but as the pandemic situation such as COVID-19 continues for years, there are many changes in the initial and current aspects, and accordingly, policies and response systems are evolving. As a result, regional gaps arise, and various problems are scattered due to trust, distrust, and implementation of policies. Therefore, in the process of analyzing social data including information transmission, Twitter data, one of the major social media platforms containing inaccurate information from unknown sources, was developed to prevent facts in advance. Based on social data, which is unstructured data, an algorithm that can automatically detect infectious disease threats is developed to create an objective basis for responding to the infectious disease crisis to solidify international competitiveness in related fields.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.25-37
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• 2019

Power-line communication (PLC) has influenced smart grid development. In addition, PLC has also been instrumental in current research on internet-of-things (IoT). Due to the implementation of PLC in smart grid and IoT environments, strides have been made in PLC and its combination with the wireless system to form a hybrid communication system. Also, PLC has evolved from a single-input-single-output (SISO) configuration to multiple-input-multiple-output (MIMO) configuration system, and from a point-to-point communication system to cooperative communication systems. In this work, we extend a MIMO wireless two-way amplify-and-forward (AF) cooperative communication system to a hybrid PLC and wireless (PLC/W) system configuration. We then maximize the weighted sum-rate for the hybrid PLC/W by optimizing the precoders at each node within the hybrid PLC/W system. The sum-rate problem was found to be non-convex, therefore, an iterative algorithm is used to find the optimal precoders that locally maximize the system sum-rate. For our simulation results, we compare our proposed hybrid PLC/W configuration to a PLC only and wireless only configuration at each node. Due to an improvement in system diversity, the hybrid PLC/W configuration outperformed the PLC only and wireless only system configurations in all simulation results presented in this paper.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.65-71
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• 2023

In this paper, we design and implement the Walking Life Festival application, which is based on the Android platform and provides information about domestic travel destinations and regional festivals in South Korea. This application utilizes various sensors found in smartphones, including the Step Counter sensor, Step Detector sensor, Acceleration sensor, and GPS sensor. Additionally, it makes use of Google Map API and Public Open API to offer information about domestic travel destinations and local festivals. The application also incorporates an automatic login feature using the Shared Preference API. When storing login information in the database, it encrypts the input plaintext data using a hash algorithm. For Google Maps integration, it creates objects using the Google.maps.LatLngBounds() method and extends the location information through the extends method. Furthermore, this application contributes to the activation of the domestic tourism industry by notifying users about the timing of local festivals related to domestic travel destinations, thus increasing their opportunities to participate in these festivals.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.873-879
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• 2023

This study explored the use of artificial intelligence(AI) to detect foreign bodies in chest X-ray images. Medical imaging, especially chest X-rays, plays a crucial role in diagnosing diseases such as pneumonia and lung cancer. With the increase in imaging tests, AI has become an important tool for efficient and fast diagnosis. However, images can contain foreign objects, including everyday jewelry like buttons and bra wires, which can interfere with accurate readings. In this study, we developed an AI algorithm that accurately identifies these foreign objects and processed the National Institutes of Health chest X-ray dataset based on the YOLOv8 model. The results showed high detection performance with accuracy, precision, recall, and F1-score all close to 0.91. Despite the excellent performance of AI, the study solved the problem that foreign objects in the image can distort the reading results, emphasizing the innovative role of AI in radiology and its reliability based on accuracy, which is essential for clinical implementation.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1763-1770
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• 2023

The availability of high-resolution satellite image time series data has led to an increase in change detection research. Various methods are being studied, such as satellite image pixel and object-level change detection algorithms, as well as algorithms that apply deep learning technology. In this paper, we propose a QGIS plugin-based system to enhance the utilization of these useful results and present an actual implementation case. The proposed system is a system for intensive change detection and monitoring of areas of interest, and we propose a convenient system expansion method for algorithms to be developed in the future. Furthermore, it is expected to contribute to the construction of satellite image utilization systems by presenting the basic structure of commercialization of change detection research.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.61-68
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• 2024

Despite the continuous efforts to mitigate pedestrian accidents at crosswalks, the problem persist. Vulnerable groups, including the elderly and disabled individuals are at a risk of being involved in traffic incidents. This paper proposes the implementation of object detection algorithm using the YOLO v5 model specifically for pedestrians using assistive devices like wheelchairs and crutches. For this research, data was collected and utilized through image crawling, Roboflow, and Mobility Aids datasets, which comprise of wheelchair users, crutch users, and pedestrians. Data augmentation techniques were applied to improve the model's generalization performance. Additionally, ensemble techniques were utilized to mitigate type 2 errors, resulting in 96% recall rate. This demonstrates that employing ensemble methods with a single YOLO model to target transportation-disadvantaged individuals can yield accurate detection performance without overlooking crucial objects.