• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1349-1365
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• 2020

In recent years, in the fields of smart cities and digital twins, research on model generation is increasing due to the advantage of acquiring actual 3D coordinates by using point clouds. In addition, there is an increasing demand for a solid model that can easily modify the shape and texture of the building. In this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. Accordingly, in this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. In the first step, the ground points were removed through the planarity analysis of the point cloud. In the second step, building area was extracted from the ground removed point cloud. In the third step, detailed structural area of the buildings was extracted. In the fourth step, the shape of 3D building models with 3D coordinate information added to the extracted area was created. In the last step, a 3D building solid model was created by giving texture to the building model shape. In order to verify the proposed method, we experimented using point clouds extracted from unmanned aerial vehicle images using commercial software. As a result, 3D building shapes with a position error of about 1m compared to the point cloud was created for all buildings with a certain height or higher. In addition, it was confirmed that 3D models on which texturing was performed having a resolution of less than twice the resolution of the original image was generated.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.133-142
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• 2021

With the recent advancements of deep learning, companies such as smart home, healthcare, and intelligent transportation systems are utilizing its functionality to provide high-quality services for vehicle detection, emergency situation detection, and controlling energy consumption. To provide reliable services in such sensitive systems, deep learning models are required to have high accuracy. In order to develop a deep learning model for analyzing previously mentioned services, developers should utilize the state of the art deep learning models that have already been verified for higher accuracy. The developers can verify the accuracy of the referenced model by validating the model on the dataset. For this validation, the developer needs structural information to document and apply deep learning models, including metadata such as learning dataset, network architecture, and development environments. In this paper, we propose a description language that represents the network architecture of the deep learning model along with its metadata that are necessary to develop a deep learning model. Through the proposed description language, developers can easily verify the accuracy of the referenced deep learning model. Our experiments demonstrate the application scenario of a deep learning description document that focuses on the license plate recognition for the detection of illegally parked vehicles.

• Korean Journal of Environment and Ecology
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• v.35 no.4
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• pp.387-397
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• 2021

This study aims to present reference data necessary for developing evaluation indicators to analyze the actual resilience of purchased land by investigating the factors that affect the restoration of the purchased land in the riparian zone and quantitatively calculating its importance. The main results are as follows. Firstly, this study identified 34 potential resilience factors through a literature review encompassing domestic and overseas studies and derived seven ecological responsiveness factors, six physical responsiveness factors, and four managerial responsiveness factors through the Delphi survey. Secondly, reliability analysis and Analytic Hierarchy Process (AHP) analysis derived the following important factors: structural stability of the vegetation restored in the purchased land, species diversity of wildlife, structural stability of wildlife, the size of restored wetland after purchase, number of plant species, and the land cover status adjacent to the purchased land. The study results are expected to be helpful information for ecological restoration and management plans reflecting reinforcing factors for resilience at each stage of land purchase, restoration, and management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.59-66
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• 2021

Humans mainly recognize surrounding objects using visual and auditory information among the five senses (sight, hearing, smell, touch, taste). Major research related to the latest object recognition mainly focuses on analysis using image sensor information. In this paper, after emitting various chirp audio signals into the observation space, collecting echoes through a 2-channel receiving sensor, converting them into spectral images, an object recognition experiment in 3D space was conducted using an image learning algorithm based on deep learning. Through this experiment, the experiment was conducted in a situation where there is noise and echo generated in a general indoor environment, not in the ideal condition of an anechoic room, and the object recognition through echo was able to estimate the position of the object with 83% accuracy. In addition, it was possible to obtain visual information through sound through learning of 3D sound by mapping the inference result to the observation space and the 3D sound spatial signal and outputting it as sound. This means that the use of various echo information along with image information is required for object recognition research, and it is thought that this technology can be used for augmented reality through 3D sound.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.36-42
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• 2021

With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.

• Journal of Environmental Science International
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• v.30 no.8
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• pp.605-612
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• 2021

Supply electrical conductivity (EC) concentration of the nutrition solution is an important factor in the absorption of nutrients by plants and the management of the root zone, as it can control the vegetative/reproductive growth of a plant. Paprika usually undergoes its reproductive and vegetative growth simultaneously. Therefore, ensuring proper growth of the plant leads to increased yield of paprika. In this study, growth characteristics of paprika were examined according to the EC concentration of a coir and a rockwool substrate. The supply EC was 1.0, 2.0, and 4.0 mS·cm^-1 applied at the initial stages of the growth using the rockwool (commonly used by paprika farmers) and the coir substrate with a chip and dust ratio of 50:50 and 70:30. For up to 16 weeks of paprika growth, EC concentrations of 1.0 and 2.0 mS·cm^-1 were found to have a greater effect on the growth than EC at 4.0 mS·cm^-1. The normality (marketable) rate of fruit, the soluble solid content, and paprika growth showed that the coir was generally better than the rockwool regardless of the supply EC concentration. The values of the yield per plant at an EC concentration of 4.0 mS·cm^-1 was mostly similar at 1.6 kg (coir 50:50), 1.5 kg (coir 70:30) and 1.5 kg (rockwool), but the yield of the rockwool was 88%, which was lower than 98% and 94% yield of the coir substrate. Therefore, this concludes that coir substrate is more effective than rockwool at improving paprika productivity. The results also suggest that the use of coir substrate for paprika has many benefits in terms of reducing production costs and preventing environmental destruction during post-processing.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.318-325
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• 2021

The objective of this study was to identify the effect of zebularine, a DNA methylation inhibitor, on the chromosomal association between homoeologous chromosomes in the wheat genetic background. Zebularine at a final concentration of 10 µM was used to treat the spikes of the double monosomic wheat addition line (DMA) with one Leymus mollis chromosome and one Leymus racemosus chromosome, both of which were in a homoeologous relationship. In late prophase, zebularine led to chromosome breakage in the Leymus homoeologous chromosomes. Chromosome breakage caused an increase in the frequency of chromosomal associations between the Leymus homoeologous chromosomes. Ordinary DMA showed 65 cells (35.3%) with chromosomal associations and 119 cells (64.7%) with no association, whereas treated DMA showed 102 cells (60.0%) with chromosomal associations and 67 cells (39.4%) with no association. In diakinesis, the Leymus bivalent showed a chromosomal association in the whole euchromatic region. In metaphase, the Leymus bivalent showed association in the whole chromosomal region, unlike other Leymus bivalents with partial chromosomal association. Chromosomal association by chromosome breakage occurred not only between Leymus chromosomes but also between Leymus and wheat chromosomes. The frequency of other chromosomal association (such as fusion and insert) was increased. Chromosome breakage by zebularine treatment is a useful method at the chromosome level as the spores with others are hereditary stable, although the homologous index (h) was not significantly different between ordinary DMA and treated DMA. It is necessary to study how to control zebularine treatment with a more stable concentration for chromosome breakage during meiosis.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.183-199
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• 2022

With the consumption of smart phone content increasing rapidly, the short clip market in China is rapidly growing. TikTok, a short clip platform, has achieved great business success. However, there is not much research done on TikTok platform from the customers' perspective. To this end, this study aimed to verify the relationship between the social network characteristics on the TikTok platform, attachment toward the TikTok platform, user participation, social identity, psychological distance and reuse intention through an empirical investigation. In August 2021, a survey was conducted on consumers on the subject of TikTok platform in China. The results of the study are as follows. First, the social network characteristics significantly affected the user participation and the attachment. Second, both the attachment and the user participation had a significant impact on reuse intention. Third, user participation had a significant impact on attachment. Fourth, social identity played a significant moderating role in the relationship between social network characteristics and user participation. Fifth, Psychological distance played a significant moderating role in the relationship between social network characteristics and attachment. The results of this study are expected to provide theoretical and practical implications for research on TikTok platform.

• Korean Journal of Food Science and Technology
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• v.54 no.3
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• pp.264-271
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• 2022

In this study, the nutritional properties of sterilized and non-heat-pressed raw perilla oil (SRPO) were studied and its potential as a functional food was evaluated. The copper, cobalt, and calcium levels were high in sterilized and SRPO. The total polyphenol content and ABTS radical scavenging activity were the highest in SRPO, whereas nitrite scavenging activity was the highest in 45℃ cold pressed perilla oil (CPPO). The above results confirmed that sterilized and non-heat-pressed perilla oil had high mineral and total polyphenol contents, as well as ABTS radical scavenging activity and nitrite scavenging ability. The peroxide value of SRPO decreased as the storage period increased, and the acid value of low-temperature pressed perilla oil over 65℃ (LPPO) significantly increased. This work also provided an opportunity to develop a new method for manufacturing perilla oil, and it is hoped that these experiments will form a basis for the commercialization of perilla oil.