• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.101-119
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• 2022

Existing algal bloom monitoring is based on field sampling, and there is a limit to understanding the spatial distribution of algal blooms, such as the occurrence and spread of algae, due to local investigations. In this study, algal bloom monitoring was performed using an unmanned aerial vehicle and multispectral sensor, and data on the distribution of algae were provided. For the algal bloom monitoring site, data were acquired from the Mulgeum·Mae-ri site located in the lower part of the Nakdong River, which is the areas with frequent algal bloom. The Chlorophyll-a(Chl-a) value of field-collected samples and the Chl-a estimation formula derived from the correlation between the spectral indices were comparatively analyzed. As a result, among the spectral indices, Maximum Chlorophyll Index (MCI) showed the highest statistical significance(R²=0.91, RMSE=8.1mg/m³). As a result of mapping the distribution of algae by applying MCI to the image of August 05, 2021 with the highest Chl-a concentration, the river area was 1.7km², the Warning area among the indicators of the algal bloom warning system was 1.03km²(60.56%) and the Algal Bloom area occupied 0.67km²(39.43%). In addition, as a result of calculating the number of occurrence days in the area corresponding to the "Warning" in the images during the study period (July 01, 2021~November 01, 2021), the Chl-a concentration above the "Warning" level was observed in the entire river section from 12 to 19 times. The algal bloom monitoring method proposed in this study can supplement the limitations of the existing algal bloom warning system and can be used to provide information on a point-by-point basis as well as information on a spatial range of the algal bloom warning area.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.145-158
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• 2023

Constructed wetlands (CWs) are effective technologies for urban wastewater management, utilizing natural physico-chemical and biological processes to remove pollutants. This study employed a bibliometric analysis approach to investigate the progress and future research trends in the field of CWs. A comprehensive review of 100 most-recently published and open-access articles was performed to analyze the performance of CWs in treating wastewater. Spain, China, Italy, and the United States were among the most productive countries in terms of the number of published papers. The most frequently used keywords in publications include water quality (n=19), phytoremediation (n=13), stormwater (n=11), and phosphorus (n=11), suggesting that the efficiency of CWs in improving water quality and removal of nutrients were widely investigated. Among the different types of CWs reviewed, hybrid CWs exhibited the highest removal efficiencies for BOD (88.67%) and TSS (95.67%), whereas VSSF, and HSSF systems also showed high TSS removal efficiencies (83.25%, and 78.83% respectively). VSSF wetland displayed the highest COD removal efficiency (71.82%). Generally, physical processes (e.g., sedimentation, filtration, adsorption) and biological mechanisms (i.e., biodegradation) contributed to the high removal efficiency of TSS, BOD, and COD in CW systems. The hybrid CW system demonstrated highest TN removal efficiency (60.78%) by integrating multiple treatment processes, including aerobic and anaerobic conditions, various vegetation types, and different media configurations, which enhanced microbial activity and allowed for comprehensive nitrogen compound removal. The FWS system showed the highest TP removal efficiency (54.50%) due to combined process of settling sediment-bound phosphorus and plant uptake. Phragmites, Cyperus, Iris, and Typha were commonly used in CWs due to their superior phytoremediation capabilities. The study emphasized the potential of CWs as sustainable alternatives for wastewater management, particularly in urban areas.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.189-198
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• 2024

Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.136-146
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• 2024

This paper introduces the seismic facies classification and mapping of igneous bodies found in the sedimentary sequences of the Yellow Sea shelf area of Korea. In the research area, six extrusive and three intrusive types of igneous bodies were found in the Late Cretaceous, Eocene, Early Miocene, and Quaternary sedimentary sequences of the northeastern, southwestern and southeastern sags of the Gunsan Basin. Extrusive igneous bodies include the following six facies: (1) monogenetic volcano (E.mono) showing cone-shape external geometry with height less than 200 m, which may have originated from a single monogenetic eruption; (2) complex volcano (E.comp) marked by clustered monogenetic cones with height less than 500 m; (3) stratovolcano (E.strato) referring to internally stratified lofty volcanic edifices with height greater than 1 km and diameter more than 15 km; (4) fissure volcanics (E.fissure) marked by high-amplitude and discontinuous reflectors in association with normal faults that cut the acoustic basement; (5) maar-diatreme (E.maar) referring to gentle-sloped low-profile volcanic edifices with less than 2 km-wide vent-shape zones inside; and (6) hydrothermal vents (E.vent) marked by upright pipe-shape or funnel-shape structures disturbing sedimentary sequence with diameter less than 2 km. Intrusive igneous bodies include the following three facies: (1) dike and sill (I.dike/sill) showing variable horizontal, step-wise, or saucer-shaped intrusive geometries; (2) stock (I.stock) marked by pillar- or horn-shaped bodies with a kilometer-wide intrusion diameter; and (3) batholith and laccoliths (I.batho/lac) which refer to gigantic intrusive bodies that broadly deformed the overlying sedimentary sequence.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Economic and Environmental Geology
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• v.52 no.6
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• pp.541-554
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• 2019

The Taebaeksan Zone of the Okcheon Belt is a prominent fold-thrust belt, preserving evidence for overlapped polyphase and diachronous orogenic events during crustal evolution of the Korean Peninsula. The Pyeongchang-Jeongseon area of the northwestern Taebaeksan Zone is fault-bounded on the western Jucheon and southern Yeongwol areas, showing lateral variations in stratigraphy and structural geometries. For better understanding these geological characteristics of the northwestern Taebaeksan Zone, we have studied the structural geometry of the Pyeongchang-Jeongseon area. For this, we have firstly carried out the SHRIMP U-Pb age analysis of the age-unknown sedimentary rock to clarify stratigraphy for structural interpretation. The results show the late Carboniferous to middle Permian dates, indicating that it is correlated to the Upper Paleozoic Pyeongan Supergroup. In addition to this, we interpreted the geometric relationships between structural elements from the detailed field investigation of the study area. The major structure of the northwestern Taebaeksan Zone is the regional-scale Jeongseon Great syncline, having NE-trending hinge with second-order folds such as the Jidongri and Imhari anticlines and the Nambyeongsan syncline. Based on the stereographic and down-plunge projections of the structureal elements, the structural geometry of the Jeongseon Great syncline can be interpreted as a synformal culmination, plunging slightly to the south at its southern area, and north at the northern area. The different map patterns of the northern and southern parts of the study area should be resulted in different erosion levels caused by the plunging hinges. Considering the Jeongseon Great syncline is the major structure that constrains the distribution of the Paleozoic strata of the Pyeongchang and Jeongseon areas, the symmetric repetition of the lower Paleozoic Joseon Supergroup in both limbs should be re-examined by structural mapping of the Hangmae and Hoedongri formations in the Pyeongchang and Jeongseon areas.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.11-21
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• 2015

As growing interest in Human-Computer Interaction(HCI), research on HCI has been actively conducted. Also with that, research on Natural User Interface/Natural User eXperience(NUI/NUX) that uses user's gesture and voice has been actively conducted. In case of NUI/NUX, it needs recognition algorithm such as gesture recognition or voice recognition. However these recognition algorithms have weakness because their implementation is complex and a lot of time are needed in training because they have to go through steps including preprocessing, normalization, feature extraction. Recently, Kinect is launched by Microsoft as NUI/NUX development tool which attracts people's attention, and studies using Kinect has been conducted. The authors of this paper implemented hand-mouse interface with outstanding intuitiveness using the physical features of a user in a previous study. However, there are weaknesses such as unnatural movement of mouse and low accuracy of mouse functions. In this study, we designed and implemented a hand mouse interface which introduce a new concept called 'Virtual monitor' extracting user's physical features through Kinect in real-time. Virtual monitor means virtual space that can be controlled by hand mouse. It is possible that the coordinate on virtual monitor is accurately mapped onto the coordinate on real monitor. Hand-mouse interface based on virtual monitor concept maintains outstanding intuitiveness that is strength of the previous study and enhance accuracy of mouse functions. Further, we increased accuracy of the interface by recognizing user's unnecessary actions using his concentration indicator from his encephalogram(EEG) data. In order to evaluate intuitiveness and accuracy of the interface, we experimented it for 50 people from 10s to 50s. As the result of intuitiveness experiment, 84% of subjects learned how to use it within 1 minute. Also, as the result of accuracy experiment, accuracy of mouse functions (drag(80.4%), click(80%), double-click(76.7%)) is shown. The intuitiveness and accuracy of the proposed hand-mouse interface is checked through experiment, this is expected to be a good example of the interface for controlling the system by hand in the future.

• Journal of Plant Biotechnology
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• v.39 no.1
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• pp.33-48
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• 2012

As a scientific curiosity to understand the structure and the function of crops and experimental efforts to apply it to plant breeding, genetic maps have been constructed in various crops. Especially, in the case of Brassica crop, genetic mapping has been accelerated since genetic information of model plant $Arabidopsis$ was available. As a result, the whole $B.$ $rapa$ genome (A genome) sequencing has recently been done. The genome sequences offer opportunities to develop molecular markers for genetic analysis in $Brassica$ crops. RFLP markers are widely used as the basis for genetic map construction, but detection system is inefficiency. The technical efficiency and analysis speed of the PCR-based markers become more preferable for many form of $Brassica$ genome study. The massive sequence informative markers such as SSR, SNP and InDels are also available to increase the density of markers for high-resolution genetic analysis. The high density maps are invaluable resources for QTLs analysis, marker assisted selection (MAS), map-based cloning and comparative analysis within $Brassica$ as well as related crop species. Additionally, the advents of new technology, next-generation technique, have served as a momentum for molecular breeding. Here we summarize genetic and genomic resources and suggest their applications for the molecular breeding in $Brassica$ crop.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.409-415
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• 2018

The development of smart devices has brought about significant changes in daily life and one of the most significant changes is the virtual reality zone. Virtual reality is a technology that creates the illusion that a 3D high-resolution image has already been created using a display device just like it does in itself. Unrealized subjects are forced to rely on audiovisual materials, resulting in a decline in the concentration of practices and the quality of classes. It used virtual reality to develop effective teaching materials for radiology students. In order to produce a video clip bridge using virtual reality, a radiology clinic was selected to conduct two exposures from July to September 2017. The video was produced taking into account the radiology and work flow chart and filming was carried out in two separate locations : in the computerized tomography unit and in the LINAC room. Prior to filming the scenario and the filming route were checked in advance to facilitate editing of the video. Modeling and mapping was performed in a PC environment using the Window XP operating system. Using two leading virtual reality camera Gopro Hero, CC pixels were produced using a 4K UHD, Adobe, followed by an 8 megapixel resolution of $3,840{\times}2,160/4,096{\times}2,160$. Total regeneration time was performed in about 5 minutes during the production of using virtual reality to prevent vomiting and dizziness. Currently developed virtual reality radiation and educational contents are being used to secure the market and extend the promotion process to be used by various institutions. The researchers will investigate the satisfaction level of radiation and educational contents using virtual reality and carry out supplementary tasks depending on the results.

• Economic and Environmental Geology
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• v.45 no.1
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• pp.31-40
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• 2012

This paper examined the characteristics of ductile and brittle structural elements with detailed mapping by lithofacies classification to clarify the relationship between the geological structure and the geochemical high-grade uranium anormal zone and to provide the basic information on the flow of groundwater in the eastern area of Shinbo mine, Jinan-gun, Jeollabuk-do, Korea. It indicates that this area is mainly composed of Precambrian quartzite, metapelite, metapsammite, which show a zonal distribution of mainly ENE-WSW trend, and age unknown pegmatite and Cretaceous porphyry which intrude them. But the Cretaceous Jinan Group which unconformably covers them, contrary to assumption, could not be observed. The main ductile deformation structures of Precambrian metasedimentary rocks were formed at least through three phases of deformation [ENE striking regional foliation (D1) -> ENE or EW striking crenulation foliation (D2) -> WNW or EW trending open, tight, kink folds (D3)]. The predominant orientation of S1 regional foliation strikes ENE and dips south, being similar to the zonal distribution of Precambrian metasedimentary rocks. Most predominant orientation of high-angled brittle fracture (dip angle ${\geq}45^{\circ}$) [ENE (frequency: 24.3%) > NS (23.9%) > (N)NW (18.8%) > WNW (16.9%) > NE (16.1%) fracture sets in descending frequency order], which is closely related to the flow of groundwater, strikes ENE and dips south. It also agrees with the zonal distribution of metasedimentary rocks and the predominant orientation of S1 regional foliation. The next one strikes NS and dips east or west. Considering the controlling factor of the geochemical uranium anormal zone in the Shinbo mine and its eastern areas from the above structural data. the uranium source rock in these areas might be pegmatite and the geochemical uranium anormal zone in the Sinbo mine area could be formed by an secondary enrichment through the flow of pegmatite aquifer's groundwater into the Sinbo mine area like the previous research's result.