• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.285-295
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• 2022

The trapping efficacy of five commercially available sex pheromones manufactured in Korea, the Netherlands, North America, China, and Costa Rica was evaluated to determine the population dynamics of Spodoptera frugiperda and Mythimna loreyi and their relationships with the weather parameters of maize fields in Miryang, Gyeongnam Province, Korea in 2019. The results show that the sex pheromone manufactured in Costa Rica were more efficient at capturing S. frugiperda and M. loreyi than those manufactured in other countries. The lowest number of S. frugiperda moths were captured using sex pheromones manufactured in the Netherlands. We noted that more than four population peaks of both the moth species and weather parameters influenced the moth population dynamics in Miryang. A positive relationship was observed between the population of S. frugiperda and weather parameters, such as mean temperature, rainfall, and relative humidity, for sex pheromones manufactured in Korea. Furthermore, a positive relationship was recorded between the population of M. loreyi and wind speed for the sex pheromone manufactured in Korea. The results of this study suggest that the sex pheromones manufactured in Costa Rica are the best solution for the efficient capture of S. frugiperda and M. loreyi under typical weather conditions in the southern parts of Korea. In addition, the outcomes of this study are discussed in terms of population dynamics and integrated pest management for S. frugiperda and M. loreyi as alternatives to chemical management by maize producers. Further studies related to the continuous improvement in the capture efficiency of both moth species using sex pheromones are now needed.

• Korean Journal of Optics and Photonics
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• v.34 no.3
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• pp.106-116
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• 2023

In this paper, we designed a coaxial dual camera incorporating two optical systems-one for the visible rays and the other for far-infrared ones-with the aim of capturing images in both wavelength ranges. The far-infrared system, which uses an uncooled detector, has a sensor array of 640×480 pixels. The visible ray system has 1,945×1,097 pixels. The coaxial dual optical system was designed using a hot mirror beam splitter to minimize heat transfer caused by infrared rays in the visible ray optical system. The optimization process revealed that the final version of the dual camera system reached more than 90% of the fusion performance between two separate images from dual systems. Multiple rigorous testing processes confirmed that the coaxial dual camera we designed demonstrates meaningful design efficiency and improved image conformity degree compared to existing dual cameras.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.481-486
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• 2014

This study aims at enhancing the performance of file-referring octree, suggested by Han(2014), for efficiently querying huge 3D point clouds, acquired by the 3D terrestrial laser scanning. Han's method(2014) has revealed a problem of heavy declining in query speed, when if it was applied on a very long tunnel, which is the lengthy and narrow shaped anisometric structure. Hereupon, the shape of octree has been analyzed of its influence on the query efficiency with the testing method of generating an independent octree in each isometric subdivision of 3D object boundary. This method tested query speed and main memory usage against the conventional single octree method by capturing about 300 million points in a very long tunnel. Finally, the testing method resulted in which twice faster query speed is taking similar size of memory. It is also approved that the conclusive factor influencing the query speed is the destination level, but the query speed can still increase with more proximity to isometric bounding shape of octree. While an excessive unbalance of octree shape along each axis can heavily degrade the query speed, the improvement of octree shape can be more effectively enhancing the query speed than increasement of destination level.

• Korean Journal of Microbiology
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• v.39 no.3
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• pp.128-134
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• 2003

Transformation-associated recombination (TAR) cloning is based on co-penetration into yeast spheroplasts of genomic DNA along with TAR vector DNA that contains 5'- and 3'-sequences (hooks) specific for a gene of interest, followed by recombination between the vector and the human genomic DNA to establish a circular YAC. Typically, the frequency of recombinant insert capture is 0.01-1% for single-copy genes by TAR cloning. To further refine the TAR cloning technology, we determined the effect of GC content on target hooks required for gene isolation utilizing the $Tg\cdot\AC$ mouse transgene as the targeted region. For this purpose, a set of vectors containing a B1 repeated hook and Tg AC-specific hooks of variable GC content (from 18 to 45%) was constructed and checked for efficiency of transgene isolation by radial TAR cloning. Efficiency of cloning decreased approximately 2-fold when the TAR vector contained a hook with a GC content ～${\leq}23$% versus ～40%. Thus, the optimal GC content of hook sequences required for gene isolation by TAR is approximately 40%. We also analyzed how the distribution of high GC content (65%) within the hook affects gene capture, but no dramatic differences for gene capturing were observed.

• Clean Technology
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• v.25 no.1
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• pp.19-32
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• 2019

As regional air pollution gets worse by the sulfur oxides emitted from various types of vessels passing through the many countries, the International Maritime Organization establishes the emission control areas and regulates sulfur dioxide in those areas. In order to satisfy these regional regulations, the fuel selection method and the exhaust gas post-treatment device are applied to the ships. Due to the economic reasons, the post-treatment method of exhaust gas for reducing the amount of sulfur oxides discharged is mainly preferred. The scrubber which is dominantly used in the ships are the spray type system where the sprayed liquid drops used for capturing the soluble sulfur dioxides in the exhaust gas. The performance of the spray type system depends on the size distribution of the sprayed droplets. In order to evaluate this performance, we designed counterflow type scrubber and cyclone scrubber and evaluated the desulfurization efficiency and the amount of droplet evaporation according to the size of each droplet by using computational fluid dynamics. The Eulerian-Eulerian analysis method was used because the scrubber had a gas-liquid two-phase flow inside the scrubber. When the diameter of the droplet was $100{\mu}m$, $300{\mu}m$, $500{\mu}m$ and $700{\mu}m$. As a result, both of scrubbers showed high desulfurization efficiency and low evaporation amount at $500{\mu}m$ and $700{\mu}m$.

• Journal of Radiation Protection and Research
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• v.39 no.4
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• pp.199-205
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• 2014

In the field of neutron detections, $^3He$ gas, the so-called "the gold standard," is the most widely used material for neutron detections because of its high efficiency in neutron capturing. However, from variable causes since early 2009, $^3He$ is being depleted, which has maintained an upward pressure on its cost. For this reason, the demands for $^3He$ replacements are rising sharply. Research into neutron converting materials, which has not been used well due to a neutron detection efficiency lower than the efficiency of $^3He$, although it can be chosen for use in a neutron detector, has been highlighted again. $^{10}B$, which is one of the $^3He$ replacements, such as $BF_3$, $^6Li$, $^{10}B$, $Gd_2O_2S$, is being researched by various detector development groups owing to a number of advantages such as easy gamma-ray discrimination, non-toxicity, low cost, etc. One of the possible techniques for the detection is an indirect neutron detection method measuring secondary radiation generated by interactions between neutrons and $^{10}B$. Because of the mean free path of alpha particle from interactions that are very short in a solid material, the thickness of $^{10}B$ should be thin. Therefore, to increase the neutron detection efficiency, it is important to make a $^{10}B$ thin film. In this study, we fabricated a $^{10}B$ thin film that is about 60 um in thickness for neutron detection using well-known technology for the manufacturing of a thin electrode for use in lithium ion batteries. In addition, by performing simple physical tests on the conductivity, dispersion, adhesion, and flexibility, we confirmed that the physical characteristics of the fabricated $^{10}B$ thin film are good. Using the fabricated $^{10}B$ thin film, we made a proportional counter for neutron monitoring and measured the neutron pulse height spectrum at a neutron facility at KAERI. Furthermore, we calculated using the Monte Carlo simulation the change of neutron detection efficiency according to the number of thin film layers. In conclusion, we suggest a fabrication method of a $^{10}B$ thin film using the technology used in making a thin electrode of lithium ion batteries and made the $^{10}B$ thin film for neutron detection using suggested method.

• Information Systems Review
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• v.12 no.1
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• pp.189-207
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• 2010

We applied IT ecosystem analysis to Smart Grid system in this paper and thereby compared various arguments about Smart Grid technologies against the reality of the power generation and distribution in South Korea with a special attention to the power distribution side. Our work attempts to propose policy implications in the government-level based on a firm-level analysis using the framework of the competitive strategy and advantage. The Smart Grid initiative is expected to enhance the efficiency in the power generation and distribution. In addition, the Smart Grid initiative aims at capturing the opportunities in the electric power business such as parts, components, supplies, and system products in the global arena. Prerequisites of smart distribution system include building infrastructure based on smart distribution parts, information systems, communication technologies, and developing various application programs and interfaces that would interact with the consumers. Consumers are expected to play an integral role by changing their consumption patterns in response to dynamic pricing and quality choices enabled by the smart distribution technologies. In order to induce the consumers to participate actively in the program, firms and policy makers should consider providing consumers economic incentives and proper education for better understanding of new technologies. Our work helps policy makers and firm better understand the nature of technology and stakeholders for the successful implementation of smart distribution technologies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.111-122
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• 2015

This study purposed on introducing a new automated solution for detecting railway tracks and reconstructing track models from the mobile laser scanning data. The proposed solution completes following procedures; the study initiated with detecting a potential railway region, called Region Of Interest (ROI), and approximating the orientation of railway track trajectory with the raw data. At next, the knowledge-based detection of railway tracks was performed for localizing track candidates in the first strip. In here, a strip -referring the local track search region- is generated in the orthogonal direction to the orientation of track trajectory. Lastly, an initial track model generated over the candidate points, which were detected by GMM-EM (Gaussian Mixture Model-Expectation & Maximization) -based clustering strip- wisely grows to capture all track points of interest and thus converted into geometric track model in the tracking by detection framework. Therefore, the proposed railway track tracking process includes following key features; it is able to reduce the complexity in detecting track points by using a hypothetical track model. Also, it enhances the efficiency of track modeling process by simultaneously capturing track points and modeling tracks that resulted in the minimization of data processing time and cost. The proposed method was developed using the C++ program language and was evaluated by the LiDAR data, which was acquired from MMS over an urban railway track area with a complex railway scene as well.