• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.360-366
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• 2022

This paper presents a AI model structure for restoring Korean traditional palace photographs, which remain only black-and-white photographs, to color photographs using Pix2Pix, one of the adversarial generative neural network techniques. Pix2Pix consists of a combination of a synthetic image generator model and a discriminator model that determines whether a synthetic image is real or fake. This paper deals with an artificial intelligence model by adjusting a receptive field of the discriminator, and analyzes the results by considering the characteristics of the ancient palace photograph. The receptive field of Pix2Pix, which is used to restore black-and-white photographs, was commonly used in a fixed size, but a fixed size of receptive field is not suitable for a photograph which consisting with various change in an image. This paper observed the result of changing the size of the existing fixed a receptive field to identify the proper size of the discriminator that could reflect the characteristics of ancient palaces. In this experiment, the receptive field of the discriminator was adjusted based on the prepared ancient palace photos. This paper measure a loss of the model according to the change in a receptive field of the discriminator and check the results of restored photos using a well trained AI model from experiments.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.3
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• pp.35-41
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• 2023

In this study, silicon sludge generated in semiconductor manufacturing process is recycled and applied as materials for pigments and paints. In detail, metallic impurities are removed from silicon sludge to obtain plate-like silicon sludge powder (SW-sludge), which is then coated with titanium dioxide via sol-gel method (TCS-sludge). SW-sludge and TCS-sludge are dispersed in hydrophilic transparent varnish and sprayed onto glass substrates to observe the possibility for the application as materials for pigments and paints. Notably, the applicability of TCS-sludge-based paint is improved compared to SW-sludge-based paint after the titanium dioxide coating. Moreover, the color of TCS-sludge-based paint turns into white. Accordingly, it is confirmed that the applicability and hydrophilicity are improved by the presence of outer titanium dioxide layer. In this regard, it is expected that the recycled TCS-sludge may be a future material for the application as pigments and paints.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.197-206
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• 2009

The medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image classification and retrieval system is necessary. The medical image classification and retrieval system can improve efficiency in a medical diagnosis by providing disease-related images and can be useful in various medical practices by checking diverse cases. However, it is difficult to understand the meanings contained in images because the existing image classification and retrieval system has handled superficial information only. Therefore, a medical image classification system which can classify medical images by analyzing the relation among the elements of the image as well as the superficial information has been required. In this paper, we propose the method for learning and classification of brain MRI, in which the superficial information as well as the spatial information extracted from images are used. The superficial information of images, which is color, shape, etc., is called low-level image information and the logical information of the image is called high-level image information. In extracting both low-level and high-level image information in this paper, the anatomical names and structure of the brain have been used. The low-level information is used to give an anatomical name in brain images and the high-level image information is extracted by analyzing the relation among the anatomical parts. Each information is used in learning and classification. In an experiment, the MRI of the brain including disease have been used.

• Animal Bioscience
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• v.36 no.7
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• pp.991-1002
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• 2023

Objective: This study aimed to elucidate the underlying gene regions responsible for productive, phenotypic or adaptive traits in different ecological types of Tibetan sheep and the discovery of important genes encoding valuable traits. Methods: We used whole-genome resequencing to explore the genetic relationships, phylogenetic tree, and population genetic structure analysis. In addition, we identified 28 representative Tibetan sheep single-nucleotide polymorphisms (SNPs) and genomic selective sweep regions with different traits in Tibetan sheep by fixation index (Fst) and the nucleotide diversity (θπ) ratio. Results: The genetic relationships analysis showed that each breed partitioned into its own clades and had close genetic relationships. We also identified many potential breed-specific selective sweep regions, including genes associated with hypoxic adaptability (MTOR, TRHDE, PDK1, PTPN9, TMTC2, SOX9, EPAS1, PDGFD, SOCS3, TGFBR3), coat color (MITF, MC1R, ERCC2, TCF25, ITCH, TYR, RALY, KIT), wool traits (COL4A2, ERC2, NOTCH2, ROCK1, FGF5, SOX9), and horn phenotypes (RXFP2). In particular, a horn-related gene, RXFP2, showed the four most significantly associated SNP loci (g. 29481646 A>G, g. 29469024 T>C, g. 29462010 C>T, g. 29461968 C>T) and haplotypes. Conclusion: This finding demonstrates the potential for genetic markers in future molecular breeding programs to improve selection for horn phenotypes. The results will facilitate the understanding of the genetic basis of production and adaptive unique traits in Chinese indigenous Tibetan sheep taxa and offer a reference for the molecular breeding of Tibetan sheep.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.115-125
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• 2019

In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.96-109
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• 2024

The purpose of this study is to propose a method for evaluating the similarity of Show gardens using Deep Learning models, specifically VGG-16 and ResNet50. A model for judging the similarity of show gardens based on VGG-16 and ResNet50 models was developed, and was referred to as DRG (Deep Recognition of similarity in show Garden design). An algorithm utilizing GAP and Pearson correlation coefficient was employed to construct the model, and the accuracy of similarity was analyzed by comparing the total number of similar images derived at 1st (Top1), 3rd (Top3), and 5th (Top5) ranks with the original images. The image data used for the DRG model consisted of a total of 278 works from the Le Festival International des Jardins de Chaumont-sur-Loire, 27 works from the Seoul International Garden Show, and 17 works from the Korea Garden Show. Image analysis was conducted using the DRG model for both the same group and different groups, resulting in the establishment of guidelines for assessing show garden similarity. First, overall image similarity analysis was best suited for applying data augmentation techniques based on the ResNet50 model. Second, for image analysis focusing on internal structure and outer form, it was effective to apply a certain size filter (16cm × 16cm) to generate images emphasizing form and then compare similarity using the VGG-16 model. It was suggested that an image size of 448 × 448 pixels and the original image in full color are the optimal settings. Based on these research findings, a quantitative method for assessing show gardens is proposed and it is expected to contribute to the continuous development of garden culture through interdisciplinary research moving forward.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Korean Chemical Engineering Research
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• v.62 no.1
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• pp.27-35
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• 2024

Fuel gases such as methane and propane are used in explosion hazardous area of domestic plants and can form non-uniform mixtures with the influence of process conditions due to leakage. The fire-explosion risk assessment using literature data measured under uniform mixtures, damage prediction can be obtained the different results from actual explosion accidents by gas leaks. An explosion characteristics such as explosion pressure and flame velocity of non-uniform gas mixtures with concentration change similar to that of facility leak were examined. The experiments were conducted in a closed 0.82 m long stainless steel duct with observation recorded by color high speed camera and piezo pressure sensor. Also we proposed the quantification method of non-uniform mixtures from a regression analysis model on the change of concentration difference with time in explosion duct. For the non-uniform condition of this study, the area of flame surface enlarged with increasing the concentration non-uniform in the flame propagation of methane and was similar to the wrinkled flame structure existing in a turbulent flame. The time to peak pressure of methane decreased as the non-uniform increased and the explosion pressure increased with increasing the non-uniform. The ranges of K_G (Deflagration index) of methane with the concentration non-uniform were 1.30 to 1.58 [MPa·m/s] and the increase rate of K_G was 17.7% in methane with changing from uniform to non-uniform.

• Journal of Acupuncture Research
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• v.17 no.1
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• pp.27-41
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• 2000

The meridian system is the most essential and basic connecting structure that maintains the vital activities of viscera and bowels by connecting them with each part of body's surface. Doctors can understand the healthy condition, and the region and deficiency-excessiveness of disease by observing the condition of Qi flowing. Deficiency and excessiveness could be differentiated by various symptoms expressed in meridian system. Especially there could be several clues like pain, heat-cold, protuberance-depression, change of color and shine in the line of channel leads to the judgment of deficiency-excessiveness The diagnosis of deficiency and excessiveness can be generalized by quantification of elastic status in skin surface along the meridian system. By comparing data from measurement of elastic condition with those from traditional deficiency and excessiveness, it could be utilized for the development of oriental medicine. All biological activities in the human body are based on meridian system according to the oriental medicine. Also the meridian system is viewed as basic and essential structure connecting internal viscera and each part of body. The areas of expressed channel phenomena are muscle to bone, muscle to muscle and bone to bone. These areas are called depression where meridian system is present and any changing state on those points can be measured. It could be difficult in diagnosing the reaction of meridian system because doctor can depend on his own judgment. Therefore, it is necessary to quantify and indexate channel reactions. To quantify the channel reactions, specially manufactured instrument was used to quantify the protuberance and depression to differentiate the deficiency and excessiveness. The results follow as below; 1. The elastic index measurement by the equipment proved a pattern of agreement showing the values that ranged within standard deviation 0.05kgf/cm throughout the experiment except few cases' measurement in CV-17. 2. To evaluate the state of deficiency & excessiveness of elastic index measurements in frontal point, elastic index measurements in the front paint were compared to the elastic index measured surrounding the point within 2.5 cm. Such result of indexing procedure was closely matched to the concept of palpitation. 3. If the elastic index values in the surrounding front point closely located to the elastic index values in the front point, the judgement on the state of deficiency and excessiveness was delayed. Otherwise, it was judged as deficiency or excessiveness. 4. Out of total 12 cases of comparing the elastic index values to the elastic index values in the surrounding front point, Three to nine front points were judged as either in the state of deficiency or excessiveness. 5. Among the nine front points judged as either in the state of deficiency or excessiveness, Four cases were matched to the electric index measured by EAV that evaluating the internal organs by five different phases. If more clinical cases are accumulated, it is expected to systematically theorize and improve the concept of deficiency and excessiveness in the internal organs using the front point.

• Korean Journal of Environment and Ecology
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• v.22 no.6
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• pp.679-690
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• 2008

The objectives of this study are to investigate and analyze the vegetation structure and population dynamics of Berchemia racemosa habitats in the Weolmyung park in Gunsan city, and base on that to seek the ecological habitat conservation plan for the Berchemia racemosa. In results, the Berchemia racemosa habitats are located at $81{\sim}93$ meters above the sea level, in steep seaside slope of a mountain. The soil texture are silt loam mainly and soil pH were $4.1{\sim}5$. The vascular plants in the Berchemia racemosa habitats has been analyzed as 61 taxa; 33 families, 51 genera, 54 species, 6 varieties, and 1 forms. Berchemia racemosa as a Specific plant species by floral region was the class V. Berchemia racemosa habitats were classified into 7 vegetation communities of Quercus serrata community(A1), Alnus firm a community(A2), Platycarya strobilacea community(A3), Robinia pseudoacacia community(A4) and 3 Pinus densiflora communities(B1, B2, B3). The importance value of Berchemia racemosa were 30%(A1), 15%(A2), 27%(A3), 65%(A4), 18%(B1), 45%(B2) and 35%(B3) on shrubs layer and 12, 27, 20, 18, 11, 18, 21 % on herb layer. The constant companion species with Berchemia racemosa were Stephanandra incisa and Ligustrum obtusifolium. Total 103 populations appear in the 7 Berchemia racemosa habitats. Their spatial distribution pattern were clumped for the most part. The average height was 133cm, the root color diameter was 4.4cm and the ramification branch number was 9.4. From the results of this study, it is suggested the continued monitoring and the active protection measures for the Berchemia racemosa habitats.