• Korean Journal of Heritage: History & Science
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• v.33
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• pp.210-255
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• 2000

This study aims to classify the framework and arrangement of interior columns (Naeju) which are used in single-story Buddhist halls into several types, and to develop a theory on the process of changes among those types. Since interior columns are building materials which hold up the roof structure and make partitions in the interior space of halls, their framework and arrangement is closely linked to the development of building technology and is expected to reflect new architectural needs. The kinds of interior columns classified by the shape of framework are goju, chaduju, oepyonju, naepyonju. The arrangement of interior columns can he classified by two methods: One which counts the number of the interior column arrangements in a hall, and the other whose classification relates with the side wall columns - Jeongchibup and yijubup. With the combination of these classifications, we can divide the framework and arrangement of interior columns into 8 types From the remains of Korean and Chinese Architecture, we can presume that before the late-Goryo period, jeongchibup had always been applied in the construction of Buddhist halls, and gamju(column reducing) had only been used in examples of small scale. After the founding of Choseon Kingdom, however, national policy had weakened the economic power of Buddhist temples. Because of that, large-scale outdoor Buddhist mass was replaced by small-scale indoor mass, and for this reason, though the scale of Buddhist halls became smaller, the need for a broad interior space became stronger. Thus in early-Choseon period, reduction of interior columns became widely spread. Those types of framework and arrangement of interior columns where yijubup was applied were developed because the rear interior columns arrangements, in order to expand the interior space, have moved backward. Among these types, yiju-goju and yiju-chaduju were developed for the Buddhist halls with paljak roof(hipped-gabled roof), where the load of their side eaves caused structural problems at the side walls. And oepyonju type was for the small-scale and middle-scale Buddhist halls which needed more interior space but didn't want the extension of roof structure. From the local and periodic distribution of each types, we can conclude that the types jeongchi-goju, jeongchi-chaduju and yiju-chaduju have been settled as typical technique of local carpenters. Oepyonju was developed later than the other types, but for its merit of low cost, it became a popular type across the nation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.93-103
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• 2021

Despite the efforts of financial authorities in conducting the direct management and supervision of collection agents and bond-collecting guideline, the illegal and unfair collection of debts still exist. To effectively prevent such illegal and unfair debt collection activities, we need a method for strengthening the monitoring of illegal collection activities even with little manpower using technologies such as unstructured data machine learning. In this study, we propose a classification model for illegal debt collection that combine machine learning such as Support Vector Machine (SVM) with a rule-based technique that obtains the collection transcript of loan companies and converts them into text data to identify illegal activities. Moreover, the study also compares how accurate identification was made in accordance with the machine learning algorithm. The study shows that a case of using the combination of the rule-based illegal rules and machine learning for classification has higher accuracy than the classification model of the previous study that applied only machine learning. This study is the first attempt to classify illegalities by combining rule-based illegal detection rules with machine learning. If further research will be conducted to improve the model's completeness, it will greatly contribute in preventing consumer damage from illegal debt collection activities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.52-60
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• 2021

The aim of this study was to derive a new trend by analyzing installations using 3D printing that are out of the limits of size and design according to the trends of developing 3D printing technology. This paper classified the types of installations using 3D printing and analyzed them with two trends: the trend of design and the trend of output. The trends of installations using 3D printing derived from this study are as follows. First, as the implementation of design through an algorithm is accomplished, the transformation appears with the atypical design that is prominent in complex expression. Second, Robotics and FDM 3D Printing is fused, which is changing the existing paradigm. Therefore, the production and utilization of installations using 3D printing proceeded at a faster pace through the interaction between the algorithm design method and freeform 3D printing technology. This study was conducted on installations using 3D printing around the world and played a basic role in the research on the production of installations using 3D printing along with domestic 3D printing technology to be developed in the future. Follow-up studies in various aspects, such as materials and combination methods, will be needed.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.121-133
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• 2021

Suspended Solids (SS) generated in rivers are mainly introduced from non-point pollutants or appear naturally in the water body, and are an important water quality factor that may cause long-term water pollution by being deposited. However, the conventional method of measuring the concentration of suspended solids is labor-intensive, and it is difficult to obtain a vast amount of data via point measurement. Therefore, in this study, a model for measuring the concentration of suspended solids based on remote sensing in the Nakdong River was developed using Sentinel-2 data that provides high-resolution multi-spectral satellite images. The proposed model considers the spectral bands and band ratios of various wavelength bands using a machine learning model, Support Vector Regression (SVR), to overcome the limitation of the existing remote sensing-based regression equations. The optimal combination of variables was derived using the Recursive Feature Elimination (RFE) and weight coefficients for each variable of SVR. The results show that the 705nm band belonging to the red-edge wavelength band was estimated as the most important spectral band, and the proposed SVR model produced the most accurate measurement compared with the previous regression equations. By using the RFE, the SVR model developed in this study reduces the variable dependence compared to the existing regression equations based on the single spectral band or band ratio and provides more accurate prediction of spatial distribution of suspended solids concentration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.320-330
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• 2020

Fire is difficult to achieve good performance in image detection using deep learning because of its high irregularity. In particular, there is little data on fire detection in underground utility facilities, which have poor light conditions and many objects similar to fire. These make fire detection challenging and cause low performance of deep learning models. Therefore, this study proposed a fire detection model using deep learning and estimated the performance of the model. The proposed model was designed using a combination of a basic convolutional neural network, Inception block of GoogleNet, and Skip connection of ResNet to optimize the deep learning model for fire detection under underground utility facilities. In addition, a training technique for the model was proposed. To examine the effectiveness of the method, the trained model was applied to fire images, which included fire and non-fire (which can be misunderstood as a fire) objects under the underground facilities or similar conditions, and results were analyzed. Metrics, such as precision and recall from deep learning models of other studies, were compared with those of the proposed model to estimate the model performance qualitatively. The results showed that the proposed model has high precision and recall for fire detection under low light intensity and both low erroneous and missing detection capabilities for things similar to fire.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.131-143
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• 2022

The lunar exploration autonomous vehicle operates based on the lunar topography information obtained from real-time image characterization. For highly accurate topography characterization, a large number of training images with various background conditions are required. Since the real lunar topography images are difficult to obtain, it should be helpful to be able to generate mimic lunar image data artificially on the basis of the planetary analogs site images and real lunar images available. In this study, we aim to artificially create lunar topography images by using the location information-based style transfer algorithm known as Wavelet Correct Transform (WCT2). We conducted comparative experiments using lunar analog site images and real lunar topography images taken during China's and America's lunar-exploring projects (i.e., Chang'e and Apollo) to assess the efficacy of our suggested approach. The results show that the proposed techniques can create realistic images, which preserve the topography information of the analog site image while still showing the same condition as an image taken on lunar surface. The proposed algorithm also outperforms a conventional algorithm, Deep Photo Style Transfer (DPST) in terms of temporal and visual aspects. For future work, we intend to use the generated styled image data in combination with real image data for training lunar topography objects to be applied for topographic detection and segmentation. It is expected that this approach can significantly improve the performance of detection and segmentation models on real lunar topography images.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.2
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• pp.85-94
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• 2022

The mixed cropping system is a centuries-old cropping technique widely practiced in farmers' fields worldwide. Increased plant diversity enhances farmland biodiversity, which improves grain yield and quality. However, the effect of growing different rice cultivars simultaneously has rarely been investigated. In the present study, six glutinous rice cultivars were selected, and two mixture cultivation methods were determined according to plant height, grain yield, and color. Colored and glutinous rice are used for specific purposes by consumers because of their color and nutritive value. Six glutinous rice varieties, including aromatic and colored rice, were included in the combination interplanting trials. The results showed that, compared with the corresponding monocropping systems, almost all combinations of the mixed cropping systems had advantages in yield-related traits. Compared with monocropping systems, mixed cropping systems increased the number of panicles per plant and maturation rate by 20% and 10%, respectively. An increase of 18-20% grain yield was observed in mixed cropping plots compared with that in plots which grew only a single rice variety. Some rice varieties, such as green colored rice 'Nogwonchall' and black colored rice 'Chungpunghukhayangchall', exhibited 18-22% increased yield when they were planted in combinations. The high yields were primarily owing to improved light interception and reduced lodging, although other factors (for example, reduced severity of disease) may have also contributed.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.261-269
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• 2021

Without any validation of the incompressible assumption, most of previous studies on cavitation flow and its noise have utilized numerical methods based on the incompressible Reynolds Average Navier-Stokes (RANS) equations because of advantage of its efficiency. In this study, to investigate the effects of the flow compressibility on the Tip Vortex Cavitation (TVC) flow and noise, both the incompressible and compressible simulations are performed to simulate the TVC flow, and the Ffowcs Williams and Hawkings (FW-H) integral equation is utilized to predict the TVC noise. The DARPA Suboff submarine body with an underwater propeller of a skew angle of 17 degree is targeted to account for the effects of upstream disturbance. The computation domain is set to be same as the test-section of the large cavitation tunnel in Korea Research Institute of Ships and Ocean Engineering to compare the prediction results with the measured ones. To predict the TVC accurately, the Delayed Detached Eddy Simulation (DDES) technique is used in combination with the adaptive grid techniques. The acoustic spectrum obtained using the compressible flow solver shows closer agreement with the measured one.

• Journal of the Korean Society of Floral Art and Design
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• no.43
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• pp.39-56
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• 2020

This study is on the creation of floral art works based on the intuitive insight acquired by methodological process of ruminating the experienced meaningful events of the artists utilizing sensible perception. The researcher used the narration and visualization techniques. The narration process adopted the writing technique of subjective impression, emotion, stream of consciousness to capture sensations of subconscious state, which were applied in three steps of 'the exploration of experiences', 'the concretion of experiences', and 'the creation of meaning out of experiences'. The visualization process adopted collection, selection, classification, and interpretation of related images, which were applied in three methods of 'the creation of images', 'the utilization of intuition', and 'the perception through remembering'. Finally 5 art works of 'Hammock is Good', 'At the Rooftop with Warm Sunshine', 'Standing at the Waterside Alone', 'Dizziness at Hot Sand Field', and 'Having Good Time at a Botanical Garden'were created through the combination of these two methods mentioned above and complementary research and writing. The meaningfulness of this research lies in presenting methodological approaches of utilizing narration and visualization of experiences in art creation process.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.