• Journal of the Korean Institute of Rural Architecture
• /
• v.25 no.2
• /
• pp.1-8
• /
• 2023

This study reveals the absence of standard design guidelines by region through investigation and analysis centered on public design cases by region in Jeollabuk-do and design elements that can reflect the integration, identity, and diversity of public design in each region by five regions. Through this, the following conclusions could be obtained. First, to improve the quality of street facilities in Jeollabuk-do, the design elements (design motif, color, pattern) applicable to the standard design were analyzed by dividing them into five regions. As a design motif, it was possible to extract patterns containing straight lines, sophistication, dignity, and smartness. In the Northeast region, it is comfortable with the motif of the mountain ridge reflecting geographical characteristics, and it can be extracted elements that contain warm and natural colors. In the southeastern region, patterns that reflect design elements were extracted by applying safe, lively, and peaceful colors with the design motif of curves that blend nature and agriculture. In the southwestern region, design pattern elements that highlight nature, history, and culture were extracted with various cultural assets and natural greenery as motifs. Lastly, in the Saemangeum region, the ocean flow and greenery could be used as a design motif to reflect a positive, clear, future-oriented image in the design spot zones by region. Second, based on the standard design elements (design motive, color, pattern) by region extracted for the standard design development of street facilities in each region in Jeollabuk-do, an integrated zone(Form, structure, material, color, functional element) to which regional design guidelines can be applied. Third, an integrated zone (form, structure, material, color, functional elements) was composed. In addition, design spot zones (patterns and colors in city and county units) that can contain the diversity and identity of each region were designated. By designating design spot zones (patterns and colors in city and county units) that can contain the diversity and identity of each region, standard design development plans (integrated pillars, jaywalking prevention fences, roundabouts (urban type, rural type), street trees) Eight standard designs, including protective covers, street planters, flat benches, light benches, visual media for user guidance, and parking zones for personal mobile devices) were presented.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.51 no.6
• /
• pp.61-74
• /
• 2023

The concept of "green infrastructure" emphasizes the close relationship between natural and urban social systems, thereby providing services that protect the ecological environment and improve the quality of human life. The Green View Index(GVI) is an important indicator for measuring the supply of urban green space and contains more 3D spatial elements concerning the green space ratio. This study focused on an area within the Third Ring Road in the city of Chengdu, Sichuan Province, China. The purposes of this study were three-fold. First, this study analyzed the spatial distribution characteristics of the GVI in urban streets and its correlation with the urban park green space system using Street View image data. Second to analyze the characteristics of low GVI streets were analyzed. Third, to analyze the connectivity between road traffic and street GVI using space syntax were analyzed. This study found that the Street GVI was higher in the southwestern part of the study area than in the northeastern part. The spatial distribution of the street GVI correlated with urban park green space. Second, the street areas with low GVI are mainly concentrated in areas with dense commercial facilities, areas with new construction, areas around elevated roads, roads below Class 4, and crossroads areas. Third, the high integration and low GVI areas were mainly concentrated within the First Ring Road in the city as judged by the concentration of vehicles and population. This study provides base material for future programs to improve the GVI of streets in Chengdu, Sichuan Province.

• Progress in Medical Physics
• /
• v.21 no.1
• /
• pp.16-21
• /
• 2010

To acquire good image quality and to minimize unnecessary radiation dose to patients, it is important to ensure that the radiopharmaceutical administered is accurately measured. Quality control of radionuclide calibrators should be performed to achieve these goals. The purpose of this study is to support the quality control of radionuclide calibrators in nuclear medicine centers and to investigate the level of measurement accuracy of the radionuclide calibrators. 58 radionuclide calibrators from 45 nuclear medicine centers, 74 radionuclide calibrators from 58 nuclear medicine centers, and 60 radionuclide calibrators from 45 nuclear medicine centers were tested with I-131, Tc-99m and I-123, respectively. The results showed that 81% of calibrators for I-131, 61% of calibrators for Tc-99m and 67% of calibrators for I-123 were within ${\pm}5%$. 17% of calibrators for I-131, 20% of calibrators for Tc-99m and 15% of calibrators for I-123 had a deviation in the range 5%< $|{\Delta}|{\leq}10%$. 2% of calibrators for I-131, 19% of calibrators for Tc-99m and 18% of calibrators for I-123 had a deviation of $|{\Delta}|$ >10%. Follow-up measurements were performed on the calibrators whose error exceeded the ${\pm}10%$ limit. As a result, some of the calibrator showed an improvement and their deviation decreased below the ${\pm}10%$ limit. The results have shown that such comparisons are necessary to improve the accuracy of the measurement and to identify malfunctioning radionuclide calibrators.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.4
• /
• pp.363-373
• /
• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Industry Promotion Research
• /
• v.6 no.3
• /
• pp.9-17
• /
• 2021

Childcare teacher experience emotional labor that suppresses, exaggerates, controls and regulates their emotions in order to produce the positive image required in the nursery field. The working environment for infants and toddlers has a problem of lowering the quality of life as a cause of psychological exhaustion of the emotional labor childcare teacher. Because singing helps to improve the quality of human life, research is needed to enable emotional labor childcare teacher to recover from psychological exhaustion and plan a positive life in the process of self-care. First, how is the psychological exhaustion of the emotional labor childcare teacher through song psychotherapy? Second, how is the process of self-care of the emotional labor childcare teacher through song psychotherapy? The study was conducted from March 2017 to May 2020, and through qualitative case studies, data such as in-depth interviews, direct observations, and participation observations were collected at the ○○○ daycare center for 50 minutes every 12 sessions. Based on the above findings, the following conclusions were drawn: First, through singing psychotherapy, emotional labor and childcare staff were able to discover, understand, recognize, face, communicate, and insight into their will to live, psychologically exhausted themselves. Emotional support from others can reduce the experience of emotional depletion and demonstrate a recovery of experience and an improvement in achievement due to frustration at work. Second, the self-care of the emotional labor child care teacher through song psychotherapy proved the temporal, spatial, relational, and emotional caring process, while maintaining the balance between caring for others and caring for oneself, body, mind, and spirituality are organic change. In this study, the psychological exhaustion and self-care process provides an opportunity to discover the essence of life, explore and express one's inner self, take care of others and oneself in a balanced manner, and provide insights for a whole person and healthy self. It is significant in providing opportunities to improve the quality of life through growth.

• Journal of Broadcast Engineering
• /
• v.26 no.4
• /
• pp.453-462
• /
• 2021

A lot of license plate data is required for car number recognition. License plate data needs to be balanced from past license plates to the latest license plates. However, it is difficult to obtain data from the actual past license plate to the latest ones. In order to solve this problem, a license plate recognition study through deep learning is being conducted by creating a synthetic license plates. Since the synthetic data have differences from real data, and various data augmentation techniques are used to solve these problems. Existing data augmentation simply used methods such as brightness, rotation, affine transformation, blur, and noise. In this paper, we apply a style transformation method that transforms synthetic data into real-world data styles with data augmentation methods. In addition, real license plate data are noisy when it is captured from a distance and under the dark environment. If we simply recognize characters with input data, chances of misrecognition are high. To improve character recognition, in this paper, we applied the DeblurGANv2 method as a quality improvement method for character recognition, increasing the accuracy of license plate recognition. The method of deep learning for license plate detection and license plate number recognition used YOLO-V5. To determine the performance of the synthetic license plate data, we construct a test set by collecting our own secured license plates. License plate detection without style conversion recorded 0.614 mAP. As a result of applying the style transformation, we confirm that the license plate detection performance was improved by recording 0.679mAP. In addition, the successul detection rate without image enhancement was 0.872, and the detection rate was 0.915 after image enhancement, confirming that the performance improved.

• Journal of the Korean Society of Radiology
• /
• v.17 no.6
• /
• pp.881-887
• /
• 2023

This study aims to analyze the development and current trends of AI-based medical imaging devices commercialized in South Korea. As of September 30, 2023, there were a total of 186 AI-based medical devices licensed, certified, and reported to the Korean Ministry of Food and Drug Safety, of which 138 were related to imaging. The study comprehensively examined the yearly approval trends, equipment types, application areas, and key functions from 2018 to 2023. The study found that the number of AI medical devices started from four products in 2018 and grew steadily until 2023, with a sharp increase after 2020. This can be attributed to the interaction between the advancement of AI technology and the increasing demand in the medical field. By equipment, AI medical devices were developed in the order of CT, X-ray, and MR, which reflects the characteristics and clinical importance of the images of each equipment. This study found that the development of AI medical devices for specific areas such as the thorax, cranial nerves, and musculoskeletal system is active, and the main functions are medical image analysis, detection and diagnosis assistance, and image transmission. These results suggest that AI's pattern recognition and data analysis capabilities are playing an important role in the medical imaging field. In addition, this study examined the number of Korean products that have received international certifications, particularly the US FDA and European CE. The results show that many products have been certified by both organizations, indicating that Korean AI medical devices are in line with international standards and are competitive in the global market. By analyzing the impact of AI technology on medical imaging and its potential for development, this study provides important implications for future research and development directions. However, challenges such as regulatory aspects, data quality and accessibility, and clinical validity are also pointed out, requiring continued research and improvement on these issues.

• Journal of Internet Computing and Services
• /
• v.25 no.1
• /
• pp.99-107
• /
• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.10
• /
• pp.303-308
• /
• 2020

The ReLU(Rectified Linear Unit) function has been dominantly used as a standard activation function in most deep artificial neural network models since it was proposed. Later, Leaky ReLU, Swish, and Mish activation functions were presented to replace ReLU, which showed improved performance over existing ReLU function in image classification task. Therefore, we recognized the need to experiment with whether performance improvements could be achieved by replacing the RELU with other activation functions in the super resolution task. In this paper, the performance was compared by changing the activation functions in EDSR model, which showed stable performance in the super resolution task. As a result, in experiments conducted with changing the activation function of EDSR, when the resolution was converted to double, the existing activation function, ReLU, showed similar or higher performance than the other activation functions used in the experiment. When the resolution was converted to four times, Leaky ReLU and Swish function showed slightly improved performance over ReLU. PSNR and SSIM, which can quantitatively evaluate the quality of images, were able to identify average performance improvements of 0.06%, 0.05% when using Leaky ReLU, and average performance improvements of 0.06% and 0.03% when using Swish. When the resolution is converted to eight times, the Mish function shows a slight average performance improvement over the ReLU. Using Mish, PSNR and SSIM were able to identify an average of 0.06% and 0.02% performance improvement over the RELU. In conclusion, Leaky ReLU and Swish showed improved performance compared to ReLU for super resolution that converts resolution four times and Mish showed improved performance compared to ReLU for super resolution that converts resolution eight times. In future study, we should conduct comparative experiments to replace activation functions with Leaky ReLU, Swish and Mish to improve performance in other super resolution models.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.17 no.2
• /
• pp.78-83
• /
• 2013

Purpose: SPECT/CT, a combination of SPECT and CT, is capable of expressing the results of attenuation correction on images biased by automatic program. As a result, this research evaluates the usefulness of images with CT attenuation correction, using various phantoms and images of patients. Materials and Methods: From July of 2012 to September of 2012, this research was conducted on the contrast, spatial resolution, and images of patients. We studied the contrast with IEC body phantom and Jaszczak phantom, while the spatial resolution was evaluated with NEMA triple line phantom. Further, a comparative study was carried out on the quality of the images, on the difference between the images before and after the CT attenuation correction. Results: Compared the differences between the contrast before and after the CT attenuation correction in IEC body phantom. The contrast was improved by 33.6% at minimum, 89.8% at maximum. In case of Jaszczak Phantom, the contrast was enhanced by 9.9% at minimum, 27.8% at maximum. In NEMA Triple line phantom, the resolution was raised by 4.5% in average: 4.4% in horizontal, 4.5% in vertical. In Anthropomorphic Torso Phantom, the perfusion score of the interior wall with the most severe attenuation was measured to be 29.4%. In the experiment carried out on myocardial perfusion SPECT/CT patients, 9% improvement was discovered in the interior wall, where the most dramatic attenuation occurred, after the CT attenuation correction. Conclusion: SPECT/CT proved its clinical usefulness by enabling the acquisition of images with enhanced contrast and spatial resolution compare to the ones resulted from SPECT.