• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.28-43
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• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of IKEEE
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• v.27 no.1
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• pp.116-121
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• 2023

In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (10⁸ or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 10⁸. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.242-275
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• 2022

This study tries to reveal the structure of the "Kisun"(senior envoy ship) taken by senior envoys for the 10^th to 12^th visits to Japan from the perspective of professional shipbuilding engineering focusing on the theory of the ship in the travel logs of royal envoys to Japan (Sahaengrok) written by Joseon Tongsinsa that includes 12 visits to Japan for about 200 years from 1607 to 1811. The results of the study showed that the size of Kisun for the 10^th to 12^th envoy visits was 19 Pa (把) and a half in length and 6 Pa (把) and 2 Cheok (尺) in width. The height of the Sampan was found to be 2 Pa (把) and 1 Cheok (尺) based on records in Gyemisusarok and Jeungjeonggyorinji. The structure of Kisun was different for each visit but, it was found that Kisun was mainly composed of a main deck, bow (bow plate, stem plate), stern (stern plate), Sampan, Meonge (support), Garyong (support), Sinbang, Gungji, deck, two masts and sail, Gurejjak (mast support), Panok, stern Panok, Taru, dodger, anchor reel, stairs, rail, rudder, oar, and anchor. In addition, wood and iron nails were used together for connection. It was also found that the sail was made of herbage and cotton. This study found that Kisun, which was operated for the 10^th and 12^th envoy visits, was big in terms of length and height among the Joseon Tongsinsa fleet to show the authority and dignity of Joseon and that it had passages outside on the sides of the vessel and paddles were located between the sides and Panok structure and rails were installed on four sides on the Panok, improving stability and linear beauty. The walls of Panok were decorated with the royal Dancheong pattern and fancy murals. In addition, it was found that they wished for a safe voyage by drawing a demon face on the bow. Therefore, it was revealed that Kisun, which was taken by envoys as recorded in travel logs, was made by the state and equipped with structures and functions that enabled international voyages.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.35-48
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• 2022

Fish assemblage of total 325 of Korean peninsula estuaries were surveyed to analyze the characteristics of community structure and diversity by sea areas for three years from 2016 to 2018. The scale (stream width) of Korean estuaries were various (14~3,356 m), and 68.9% of all estuaries showed salinity of less than 2 psu. Total 149 species classified into 52 families of fish were identified, and the dominant and sub-dominant species were Tribolodon hakonensis (relative abundance, RA, 12.5%) and Mugil cephalus (RA, 9.5%), respectively. The estuary of the Korean Peninsula had different physical and chemical habitat environments depending on the sea area, and accordingly, fish community structure also showed statistically significant differences (PERMANOVA, Pseudo-F=26.69, P=0.001). In addition, the NMDS (nonmetric multidimensional scaling) results showed the patterns that indicating fish community difference by sea areas, even though low community similarity within sea area (SIMPER, 21.79~26.39%). The estuaries of east sea areas were distinguished from the others in the aspects of which, the higher importance of migratory fishes and endangered species, and that of brackish species were characterized at south sea estuaries. However, the estuaries of west sea showed higher importance of species that have a relation with freshwater (primary freshwater species, exotic species), which is the result that associating with the lower salinity of west sea estuaries because of the high ratio of closed estuaries(78.2%). The SIMPER analysis, scoring the contribution rates of species to community similarity, also showed results corresponding to the tendency of different fish community structures according to each sea area. So far, In Korea, most studies on fish communities in estuaries have been conducted in a single estuary unit, which made it difficult to understand the characteristics of estuaries at the national level, which are prerequisite for policy establishment. In present study, we are providing fish community structure characteristics of Korean estuaries in a national scale, including diversity index, habitat salinity ranges of major species, distribution of migratory species. We are expecting that our results could be utilized as baseline information for establishing management policies or further study of Korean estuaries.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.60-75
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• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.363-371
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• 2023

To construct a ship, blocks of various sizes must be moved and erected . In this process, lugs are used such that they match the block fastening method and various functions suitable for the characteristics of each shipyard facility. The sizes and shapes of the lugs vary depending on the weight and shape of the block structures. The structure is reinforced by welding the doubling pads to compensate for insufficient rigidity around the holes where the shackle is fastened. As for the method of designing lugs according to lifting loading conditions, a simple calculation based on the beam theory and structural analysis using numerical modeling are performed. In the case of the analytical method, a standardized evaluation method must be established because results may differ depending on the type of element and modeling method. The application of this ambiguous methodology may cause serious safety problems during the process of moving and turning-over blocks. In this study , the effects of various parameters are compared and analyzed through numerical structural analysis to determine the modeling conditions and evaluation method that can evaluate the actual structural response of the lug. The modeling technique that represents the plate part and weld bead around the lug hole provides the most realistic behavior results. The modeling results with the same conditions as those of the actual lug where only the weld bead is connected to the main body of the lug, showed a lower ulimated strength compared with the results obtained by applying the MPC load. The two-dimensional shell element is applied to reduce the modeling and analysis time, and a safety working load was verified to be predicted by reducing the thickness of the doubling pad by 85%. The results of the effects of various parameters reviewed in the study are expected to be used as good reference data for the lug design and safe working load prediction.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6B
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• pp.565-575
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• 2011

The purpose of this study was to quantitatively evaluate the expression of both multi-metric qualitative habitat evaluation index (QHEI) and biological integrity index (IBI) for artificial structures eco-artificial fish reef (EAFR) for fishes asylum and habitat. Especially, both experimental evaluation and biological verification were performed in Water and Environmental Center's outdoor test-bed of Korea Institute of Construction Technology located in Andong-city, Gyeongsangbuk-do. The experimental conditions reflecting the situation of domestic river include the flow rate (e.g., $0.0{\sim}1.5m\;s^{-1}$), the width (e.g., 1.0~3.0 m), the depth (e.g., 0.05~0.70 m), and variable bed materials. Both QHEI and IBI were monitored for 8 months from May to December 2010. Whereas QHEI values were highest at experimental points of the E~F with an average of 83.1, those were lowest at B~C with an average of 78.1. However, QHEI values inside EAFR were more than 98.9, regardelss of space and time, and indicated more than the highest good of the state (Good) in the habitat. Overally, IBI values showed similar trend with QHEI, but were 44.2 in the winter dry season, compared to 32.8 of QHEI values. IBI values Also, IBI values inside EAFR were greater than those at the experimental channel by 5.7 to 11.4% and 18.7 to 34.8% in flow and stagnant conditions, respectively, indicating that EAFR can secure asylum and habitat for fish during the dry season. For comprehensive aquatic ecosystem assessment, the experimental channel showed generally fair conditions (Fair~Good), whereas EAFR showed good conditions (Good), suggesting that EAFR can be applied to aquatic ecosystem restoration and improvement.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.2
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• pp.63-75
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• 2013

The Inner Port Phase 2 area of the Pyeongtaek-Dangjin Port is enclosed by a total of three permeable sea-walls, and the disposal site to the east of the Inner Port Phase 2 is also enclosed by two permeable sea-walls. The maximum tidal range measured in the Inner Port Phase 2 and in the disposal site in May 2010 is 4.70 and 2.32 m, respectively. It reaches up to 54 and 27%, respectively of 8.74 m measured simultaneously in the exterior. Regression formulas between the difference of hydraulic head and the rate of interior water volume change, are induced. A three-dimensional numerical hydrodynamic model for the Asan Bay is constructed incorporating a module to compute water discharge through the permeable sea-walls at each computation time step by employing the formulas. Hydrodynamics for the period from 13th to 27th May, 2010 is simulated by driving forces of real-time reconstructed tide with major five constituents($M_2$, $S_2$, $K_1$, $O_1$ and $N_2$) and freshwater discharges from Asan, Sapkyo, Namyang and Seokmoon Sea dikes. The skill scores of modeled mean high waters, mean sea levels and mean low waters are excellent to be 96 to 100% in the interior of permeable sea-walls. Compared with the results of simulation to obstruct the flow through the permeable sea-walls, the maximum current speed increases by 0.05 to 0.10 m/s along the main channel and by 0.1 to 0.2 m/s locally in the exterior of the Outer Sea-wall of Inner Port. The maximum bottom shear stress is also intensified by 0.1 to 0.4 $N/m^2$ in the main channel and by more than 0.4 $N/m^2$ locally around the arched Outer Sea-wall. The module developed to compute the flow through impermeable seawalls can be practically applied to simulate and predict the advection and dispersion of materials, the erosion or deposion of sediments, and the local scouring around coastal structures where large-scale permeable sea-walls are maintained.