• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.119-131
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• 2016

Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.

• Journal of the Korean Society of Radiology
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• v.14 no.2
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• pp.157-168
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• 2020

Advancements in segmentation methodology has made automatic segmentation of brain structures using structural images accurate and consistent. One method of automatic segmentation, which involves registering atlas information from template space to subject space, requires a high quality atlas with accurate boundaries for consistent segmentation. The Allen Mouse Brain Atlas, which has been widely accepted as a high quality reference of the mouse brain, has been used in various segmentations and can provide accurate coordinates and boundaries of mouse brain structures for tractography. Through probabilistic tractography, diffusion tensor images can be used to map comprehensive neuronal network of white matter pathways of the brain. Comparisons between neural networks of mouse and human brains showed that various clinical tests on mouse models were able to simulate disease pathology of human brains, increasing the importance of clinical mouse brain studies. However, differences between brain size of human and mouse brain has made it difficult to achieve the necessary image quality for analysis and the conditions for sufficient image quality such as a long scan time makes using live samples unrealistic. In order to secure a mouse brain image with a sufficient scan time, an Ex-vivo experiment of a mouse brain was conducted for this study. Using FSL, a tool for analyzing tensor images, we proposed a semi-automated segmentation and tractography analysis pipeline of the mouse brain and applied it to various mouse models. Also, in order to determine the useful signal-to-noise ratio of the diffusion tensor image acquired for the tractography analysis, images with various excitation numbers were compared.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.21-29
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• 2016

Cell segmentation is an important but time-consuming and laborious task in biological image analysis. An automated, robust, and fast method is required to overcome such burdensome processes. These needs are, however, challenging due to various cell shapes, intensity, and incomplete boundaries. A precise cell segmentation will allow to making a pathological diagnosis of tissue samples. A vast body of literature exists on cell segmentation in microscopy images [1]. The majority of existing work is based on input images and predefined feature models only - for example, using a deformable model to extract edge boundaries in the image. Only a handful of recent methods employ data-driven approaches, such as supervised learning. In this paper, we propose a novel data-driven cell segmentation algorithm for bright-field microscopy images. The proposed method minimizes an energy formula defined by two dictionaries - one is for input images and the other is for their manual segmentation results - and a common sparse code, which aims to find the pixel-level classification by deploying the learned dictionaries on new images. In contrast to deformable models, we do not need to know a prior knowledge of objects. We also employed convolutional sparse coding and Alternating Direction of Multiplier Method (ADMM) for fast dictionary learning and energy minimization. Unlike an existing method [1], our method trains both dictionaries concurrently, and is implemented using the GPU device for faster performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.409-415
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• 2020

Low-flow mortar injection method grouting technology was selected and the traffic area was preserved as much as possible in order to secure safety for road traffic when the outflow and subsidence of landfill occurred due to ground-water, and etc. In particular, the current existing method was newly improved since there are risks of damage such as hydraulic fracturing at the lower part of the road, spilling of soil particles on steep slopes, and bumps on the road due to excessive injection pressure during construction. This study was carried out at the site of reinforcement work on the road as a maintenance work for the danger zone for collapse of the steep slope of the 00 hill, which was ordered from the 00 city 00 province. The improved low-flow mortar type grouting method adopted a new automated grouting management system and especially, it composites the method for grouting conditions decision by high-pressure pre-grouting test and injection technology by AGS-controlled and studied about grouting effect analysis by using new technology. By applying the improved low-flow mortar type grouting method, it was possible to lay the groundwork for road maintenance work such as the prevention of subsidence of old roads, uneven subsidence of buildings and civil engineering structures, and of soil leakage of ground-water spills. Furthermore, the possibility of application on future grouting work not only for just construction that prevents subsidence of old roads but also for various buildings and civil engineering structures such as railroads, subways, bridges, underground structures, and boulder stone and limestone areas was confirmed.

• Journal of Mushroom
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• v.11 no.1
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• pp.32-35
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• 2013

The purpose of this study is to the Gyeongbuk area of mushroom exports by increasing exports strategy, and export support for establishing a policy analysis of the factors that you can take advantage of the basic information to get. Mushroom industry has made a rapid growth over the past 20 years in Korea. Gyeongbuk province mushroom exports account for about half of the country, enoki and total exports in 2009, and 81%, increased to 14% in 2010 and 2010, the maximum exports (9,415 tons) and the maximum exports (14,840 grand)was recorded. King oyster mushroom to represent the Netherlands in Europe, exports were higher exports to China is negligible. In the case of China in 2001, 5 spots automated mushroom factory, production, but only 8,000 tons in 2011, 652 mushroom factory, production of 1,100,000 tons very quickly grew.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.45-55
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• 2020

Due to the development of information and communication technology, the number of new / variant malicious codes is increasing rapidly every year, and various types of malicious codes are spreading due to the development of Internet of things and cloud computing technology. In this paper, we propose a malware analysis method based on string information that can be used regardless of operating system environment and represents library call information related to malicious behavior. Attackers can easily create malware using existing code or by using automated authoring tools, and the generated malware operates in a similar way to existing malware. Since most of the strings that can be extracted from malicious code are composed of information closely related to malicious behavior, it is processed by weighting data features using text mining based method to extract them as effective features for malware analysis. Based on the processed data, a model is constructed using various machine learning algorithms to perform experiments on detection of malicious status and classification of malicious groups. Data has been compared and verified against all files used on Windows and Linux operating systems. The accuracy of malicious detection is about 93.5%, the accuracy of group classification is about 90%. The proposed technique has a wide range of applications because it is relatively simple, fast, and operating system independent as a single model because it is not necessary to build a model for each group when classifying malicious groups. In addition, since the string information is extracted through static analysis, it can be processed faster than the analysis method that directly executes the code.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.401-412
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• 2020

This study analyzed the causes of warehouse fires using a creative problem-solving technique called TRIZ. It identified preventive measures by applying 4M. The results are as follows. First, this study examined the inconsistency among the causes of warehouse fires using TRIZ. Second, it analyzed human factors and fire prevention measures in warehouses such as safety standards for managers, and methods for the promotion of safety consciousness among workers, and for the reinforcement of construction technology for sandwich panel workers. Third, it identified the mechanical and facility factors and fire prevention measures in warehouses such as safety facilities, the expanded installation of safety devices, the adoption and development of fire suppression equipment, and the deployment of methods to improve the fire resistance of sandwich panels. Fourth, it presented working and environmental factors and fire prevention measures in warehouses such as the tightening of safety precautions and the supervision of working methods, and setting fire partitions both in loading places and based on performance-based design. Finally, it proposed managerial factors and fire prevention measures in warehouses such as specific targeting for firefighting with low fire hazards, reviewing the material quality regulations of non-combustible or higher for sandwich panels in the specific target of firefighting that cannot apply fire safety standards, installing sprinklers in cold storage, and mandating the installation of automated facilities with retroactive application regardless of the floor area in the warehouse with a sandwich panel structure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.551-564
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• 2016

Earthworks are the fundamental steps in a construction job, and are mainly comprised of smaller tasks performed by construction machinery. The productivity of the construction job can be improved by optimizing excavation, filling, and other such operations. Earthworks involve a lot of mechanical work performed by the collaboration between various kinds of construction equipment, which in turn leads to higher fuel consumption. Actual earthworks depend mostly on the intuition and experience of the driver of the machines, thus leading to inefficiency and environmental problems caused by unnecessary emission of carbon, Recently automated and information-oriented technologies are consistently being researched towards the improvement of efficiency of earthworks in the construction industry. The present research involves the introduction and understanding of the decision-making elements of heuristics which can be applied to the earthwork planning. A method is also suggested for creating an effective work path for construction machine to perform task packages (TP) for cutting and filling processes. A simulation test is performed to verify the effectiveness of suggested methods in terms of space interference and total moving distance of construction equipment.

• Journal of Biosystems Engineering
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• v.28 no.6
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• pp.517-524
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• 2003

There have been worldwide research and development efforts to automate various processes of bio-production and those efforts will be expanded with priority given to tasks which require high intensive labor or produce high value-added product and tasks under hostile environment. In the field of bio-production capabilities of the versatility and robustness of automated system have been major bottlenecks along with economical efficiency. This paper introduces a new concept of automation based on tole-operation, which can provide solutions to overcome inherent difficulties in automating bio-production processes. Operator(farmer), computer, and automatic machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. Among processes of greenhouse watermelon cultivation tasks such as pruning, watering, pesticide application, and harvest with loading were chosen based on the required labor intensiveness and functional similarities to realize the proposed concept. The developed system was composed of 5 major hardware modules such as wireless remote monitoring and task control module, wireless remote image acquisition and data transmission module, gantry system equipped with 4 d.o.f. Cartesian type robotic manipulator, exchangeable modular type end-effectors, and guided watermelon loading and storage module. The system was operated through the graphic user interface using touch screen monitor and wireless data communication among operator, computer, and machine. The proposed system showed practical and feasible way of automation in the field of volatile bio-production process.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.4
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• pp.294-302
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• 2019

As a series of fundamental researches on the development of an automatic identification monitoring system for fishing gear. Firstly, the study on the installation method of automated identification buoy for the coastal improvement net fishing net with many loss problems on the west coast was carried out. Secondly, the study was conducted find out how to install an automatic identification buoy for coastal gill net which has the highest loss rate among the fisheries. GPS for fishing was used six times in the coastal waters around Seogwipo city in Jeju Island to determine the developmental status and underwater behavior to conduct a field survey. Next, a questionnaire was administered in parallel on the type of loss and the quantity and location of fishing gear to be developed and the water transmitter. In the field experiment, the data collection was possible from a minimum of 13 hours, ten minutes to a maximum of 20 hours and ten minutes using GPS, identifying the development status and underwater behavior of the coastal gillnet fishing gear. The result of the survey showed that the loss of coastal net fishing gear was in the following order: net (27.3%), full fishing gear (24.2%), buoys, and anchors (18.2%). The causes were active algae (50.0%), fish catches (33.3%) and natural disasters (12.5%). To solve this problem, the installation method is to attach one and two electronic buoys to top of each end of the fishing gear, and one underwater transmitter at both ends of the float line connected to the anchor. By identifying and managing abnormal conditions such as damage or loss of fishing gear due to external factors such as potent algae and cutting of fishing gear, loss of fishing gear can be reduced. If the lost fishing gear is found, it will be efficiently collected.