• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.33-38
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• 2021

In order to manufacture a lightweight medical radiation shielding sheet, a new shielding material was studied. We tried to verify the possibility of a shielding material by mixing egg shell powder, which is thrown away as food waste at home, with a polymer material. Existing lightweight materials satisfy eco-friendly conditions, but there are difficulties in the economics of shielding materials due to the cost of the material refining process. This study aims to solve this problem by using egg shells, which are household waste. A 3 mm-thick shielding sheet was fabricated using HDPE, a polymer material, and particle distribution within the cross-section of the shielding sheet was also verified. The shape of the particles was rough and there were voids between the particles, and the average weight per unit area was 1.5 g/cm². The shielding performance was around 20% in the low energy area and 10% in the high energy area, showing the possibility of a low-dose medical radiation shielding body.

• Journal of Information Technology Applications and Management
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• v.28 no.3
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• pp.49-58
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• 2021

Due to the increasing interest in wellness aroused by the aging population and the pursuing feature of active old age, Korean elderly set importance on long life with their healthy condition. Following the change in the paradigm of the medical delivery system from hospital-oriented, treatment-oriented to personal-centered and self-care, Service design application of Smart Healthcare for the elderly became valuable. Smart Healthcare is a healthcare service provided through the fusion of ICT technologies including mobile/wearable devices, IoT, big data, and information technology, and it is utilized to prevent diseases managing abundant health information and living habits. As a methodology for delivering such Smart Healthcare to the elderly, Service design can be adopted. Therefore, this study would like to present the perquisites of Smart Healthcare design for the elderly through analyzing the results from in-depth interview methods between the elderly and medical staff. As a result of this study, guidelines for Service design application of health vulnerability management for the elderly utilizing smart phones were presented. Therefore, this study presented four prerequisites composed of 'high level of supplementation and ethical decision making', 'improvement of inequality in accessibility and experience', 'resolving problems in policy implementation' and 'user-friendliness' for the Smart Healthcare service design for the elderly. Overall, Service design is expected to play an innovative role in improving the quality of life for the elderly through the process of collecting and delivering information on Smart Healthcare centered on the experience of the elderly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1046-1052
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• 2021

Artificial intelligence is being applied in various industrial fields to the development of the fourth industry and the construction of high-performance computing environments. In the medical field, deep learning learning such as cancer, COVID-19, and bone age measurement was performed using medical images such as X-Ray, MRI, and PET and clinical data. In addition, ICT medical fusion technology is being researched by applying smart medical devices, IoT devices and deep learning algorithms. Among these techniques, medical image-based deep learning learning requires accurate finding of medical image biomarkers, minimal loss rate and high accuracy. Therefore, in this paper, we would like to compare and analyze the performance of the Cross-Entropy function used in the image classification algorithm of the loss function that derives the loss rate in the chest X-Ray image-based deep learning learning process.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.63-71
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• 2022

Barometers have been used to calculate altitude, and with the development of technology, barometer which had a large volume have now been reduced to about centimeter-level. The altitude calculation using barometer is proceeded using the relationship between reference sea level pressure and the pressure obtained by barometer, and for this, pre-calibration of the barometer is essential. In addition, the barometer has a certain level of bias from actual pressure due to production, and many smartphone manufacturers correct it during the manufacturing process, but it is difficult to correct errors caused by environmental variables. In this paper, we extended methodology of correcting barometer using static reference station to moving drone, and it was possible to calculate the altitude more accurately.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.381-392
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• 2021

In this study, we perform deep learning-based object detection analysis on eight types of buildings defined by the digital map topography standard code, leveraging images taken with UAV (Unmanned Aerial Vehicle). Image labeling was done for 509 images taken by UAVs and the YOLO (You Only Look Once) v5 model was applied to proceed with learning and inference. For experiments and analysis, data were analyzed by applying an open source-based analysis platform and algorithm, and as a result of the analysis, building objects were detected with a prediction probability of 88% to 98%. In addition, the learning method and model construction method necessary for the high accuracy of building object detection in the process of constructing and repetitive learning of training data were analyzed, and a method of applying the learned model to other images was sought. Through this study, a model in which high-efficiency deep neural networks and spatial information data are fused will be proposed, and the fusion of spatial information data and deep learning technology will provide a lot of help in improving the efficiency, analysis and prediction of spatial information data construction in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.126-139
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• 2023

At present, naked-eye 3D appears more and more commonly on the facades of urban buildings. It brings an incredible visual experience to the audience by simulating the natural 3D 3D space effect. At the same time, it also creates enormous commercial value for city publicity and commercial advertisements. There is much research on naked-eye 3D visual effects, but for right-angle LED screens. Right-angle LED screen's brand-new expression method that has only become popular in recent years, how to convey a realistic naked-eye 3D effect through two LED screens combined at right angles has become a problem worth exploring. To explore the whole design ideas and production process of the naked-eye 3D impact of the right-angle LED screen, this paper is a preliminary study aimed at understanding the performance principle and expression features. Before the case analysis, first, understand the standard virtual 3D space construction techniques. Combining it with the optical illusion phenomenon, according to the expression principle of the naked-eye 3D effect of the right-angle LED screen, it can be summarized into seven expressions: Shadow, Color contrast, Background structure line, Magnify object, Object out of bounds, Object floating, Fusion of picture and background. By analyzing the optical illusion phenomenon used in the case, we summarized the main performance characteristics of the naked eye 3D effect. The emergence of right-angle LED screens breaks the limitation of a single plane of optical illusion art, perfectly combines building facades with naked-eye 3D visual effects, and provides designers with a brand-new creative platform. Understanding its production principles and main expressive features can help designers enter this innovative platform better.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.71-78
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• 2022

This paper proposes an algorithm for 3D object detection by processing point cloud data of 3D LiDAR. Unlike 2D LiDAR, 3D LiDAR-based data was too vast and difficult to process in three dimensions. This paper introduces various studies based on 3D LiDAR and describes 3D LiDAR data processing. In this study, we propose a method of processing data of 3D LiDAR using clustering techniques for object detection and design an algorithm that fuses with cameras for clear and accurate 3D object detection. In addition, we study models for clustering 3D LiDAR-based data and study hyperparameter values according to models. When clustering 3D LiDAR-based data, the DBSCAN algorithm showed the most accurate results, and the hyperparameter values of DBSCAN were compared and analyzed. This study will be helpful for object detection research using 3D LiDAR in the future.

• Journal of Gastric Cancer
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• v.23 no.1
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• pp.224-249
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• 2023

Gastric cancer is heterogeneous in morphology, biology, genomics, and treatment response. Alterations in human epidermal growth factor receptor 2 (HER2) overexpression, microsatellite instability (MSI) status, programmed death-ligand 1 (PD-L1) levels, and fibroblast growth factor receptor 2 (FGFR2) can be used as biomarkers. Since the combination of fluoropyrimidine/platinum plus trastuzumab that was investigated in the ToGA trial was approved as a standard of care in HER2-positive patients in 2010, no other agents showed efficacy in the first- (HELOISE, LOGiC, JACOB trials) and second- (TyTAN, GATSBY, T-ACT trials) line treatments. Despite the success in treating breast cancer, various anti-HER2 agents, including a monoclonal antibody (pertuzumab), an antibody-drug conjugate (ADC; trastuzumab emtansine [T-DM1]), and a small molecule (lapatinib) failed to translate into clinical benefits until the KEYNOTE-811 (first-line) and DESTINY-Gastri01 (≥second-line) trials were conducted. The incorporation of HER2-directed treatment with immune checkpoint inhibitors in the form of a monoclonal antibody or ADC is now approved as a standard treatment. Despite the promising results of new agents (engineered monoclonal antibodies, bi-specific antibodies, fusion proteins, and small molecules) in the early phase of development, the management of HER2-positive gastric cancer requires further optimization to achieve precision medicine with a chemotherapeutic backbone. Treatment resistance is a complex process that can be overcome using a combination of chemotherapy, targeted agents, and immune checkpoint inhibitors, including novel agents. HER2 status must be reassessed in patients undergoing anti-HER2 treatment with disease progression after the first-line treatment. As a general guideline, patients who need systemic treatment should receive chemotherapy plus targeted agents, anti-angiogenic agents, immune checkpoint inhibitors, or their combinations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2278-2291
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• 2023

Imported ornamental fish should be quarantined because they can have dangerous diseases depending on their habitat. The quarantine requires a lot of time because quarantine officers collect various information on the imported ornamental fish. Inefficient quarantine processes reduce its work efficiency and accuracy. Also, long-time quarantine causes the death of environmentally sensitive ornamental fish and huge financial losses. To improve existing quarantine systems, information on ornamental fish was collected and structured, and a server was established to develop quarantine performance support software equipped with a text search engine. However, the long names of ornamental fish in general can cause many typos and time bottlenecks when we type search words for the target fish information. Therefore, we need a technique that can correct typos. Typical typo character calibration compares input text with all characters in a calibrated candidate text dictionary. However, this approach requires computational power proportional to the number of typos, resulting in slow processing time and low calibration accuracy performance. Therefore, to improve the calibration accuracy of characters, we propose a fusion system of simple Artificial Neural Network (ANN) models and character preprocessing methods that accelerate the process by minimizing the computation of the models. We also propose a typo character generation method used for training the ANN models. Simulation results show that the proposed typo character correction system is about 6 times faster than the conventional method and has 10% higher accuracy.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.450-453
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• 2002

In radiotherapy treatment planning, it is critical to deliver the radiation dose to tumor and protect surrounding normal tissue. Recent developments in functional imaging and radiotherapy treatment technology have been raising chances to control tumor saving normal tissues. A brain phantom which could be used for image registration technique of CT-MR and CT-SPECT images using surface matching was developed. The brain phantom was specially designed to obtain imaging dataset of CT, MR, and SPECT. The phantom had an external frame with 4 N-shaped pipes filled with acryl rods, Pb rods for CT, MR, and SPECT imaging, respectively. 8 acrylic pipes were inserted into the empty space of the brain phantom to be imaged for geometric evaluation of the matching. For an optimization algorithm of image registration, we used Downhill simplex algorithm suggested as a fast surface matching algorithm. Accuracy of image fusion was assessed by the comparison between the center points of the section of N-shaped bars in the external frame and the inserted pipes of the phantom and minimized cost functions of the optimization algorithm. Technique with partially transparent, mixed images using color on gray was used for visual assessment of the image registration process. The errors of image registration of CT-MR and CT-SPECT were within 2mm and 4mm, respectively. Since these errors were considered within a reasonable margin from the phantom study, the phantom is expected to be used for conventional image registration between multimodal image datasets..