• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.147-161
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• 2011

Korea is surrounded by sea on three sides. This country has been supplied with a variety of aquaculture products cultivated on shores. There have recently been a lot of studies to have better understanding of the correct location and quantity of aquaculture farms for seaweed, ear shells and fish that cover a wide area of sea. And it is necessary to use the geographic information system and remote sensing to detect the aquaculture farms in order to effectively manage them. This study uses higher resolution aerial images(25 centimeters) than satellite images of 2~2.5-meter resolution that have been ever used, to conduct an accuracy detection of aquaculture farming facilities. It chooses as the case study area the Wando region that has aquaculture farms for seaweed, ear shells and fish. Aerial photos of the island were obtained in this study and an image correction of them was conducted. A spatial database was then constructed in this study and the detection of aquaculture farming facilities was performed. An analysis of facilities inside and outside the permitted areas reveals that there has been an increase in the facilities of seaweed and ear shell aquaculture farms outside the permitted areas. And also it tells that because the facilities of fish aquaculture farms have turned into those of ear shell aquaculture farms, there has been a decrease in permitted facilities, facilities detected on the basis of aerial images, and facilities outside the permitted area. It will be necessary to continuously control and manage the unpermitted facilities, regarding the increase in the facilities inside and outside the permitted area for seaweed and ear shell aquaculture farms. Because the facilities of aquaculture farms cover a wide range of areas(sea) in this manner, it is more effective to depend on high resolution aerial images than a field survey to detect and calculate the facilities. This study comes up with a plan for using aerial images to detect the location and the quantity of the fish aquaculture facilities and then effectively manage them.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.4
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• pp.211-219
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• 2006

The UET(ultrasound excited thermography) for the ,eat-time diagnostics of the object employs an infrared camera to image defects of the surface and subsurface which are locally heated using high-frequency putted ultrasonic excitation. The dissipation of high-power ultrasonic energy around the feces of the defects causes an increase In temperature. The defect's image appears as a hot spot (bright IR source) within a dark background field. The UET for nondestructive diagnostic and evaluation is based on the image analysis of the hot spot as a local response to ultrasonic excited heat deposition. In this paper the applicability of VET for fast imaging of defect is described. The ultrasonic energy is injected into the sample through a transducer in the vertical and horizontal directions respectively. The voltage applied to the transducer is measured by digital oscilloscope, and the waveform are compared. Measurements were performed on four kinds of materials: SUS fatigue crack specimen(thickness 14mm), PCB plate(1.8 mm), CFRP plate(3 mm) and Inconel 600 plate (1 mm). A high power ultrasonic energy with pulse durations of 250ms Is injected into the samples in the horizontal and vertical directions respectively The obtained experimental result reveals that the dissipation loss of the ultrasonic energy In the vertical injection is less than that in the horizontal direction. In the cafe or PCB, CFRP, the size of hot spot in the vortical injection if larger than that in horizontal direction. Duration time of the hot spot in the vertical direction is three times as long as that in the horizontal direction. In the case of Inconel 600 plate and SUS sample, the hot spot in the horizontal injection was detected faster than that in the vertical direction

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6C
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• pp.285-293
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• 2012

The surface tension, which is generated in the unsaturated soils, increases the stiffness of the soils. The objective of this study is to estimate the effect of the surface tension, which varies according to the temperature, on the shear wave velocity. Nine specimens, which have the different degree of saturation (0%, 2.5%, 5%, 10%, 20%, 40%, 60%, 80%, 100%), are prepared by using sand-silt mixtures. Experiments are carried out in a nylon cell designed for the measurement of shear waves. A pair of bender elements, which are used for the generation and detection of shear waves, is installed as a cross-hole type. The shear waves are continuously monitored and measured as the temperature of specimens decreases from $15^{\circ}C$ to $1^{\circ}C$. The results show that shear wave velocities of the fully saturated and fully dried specimens change a little bit as the temperatures of specimens decrease. However, the shear wave velocities of the specimens with the degree of saturations of 2.5%, 5%, 10%, 20%, 40%, 60% and 80% continuously increase as temperature decreases from $15^{\circ}C$ to $1^{\circ}C$. Furthermore, a fully saturated specimen is dried at the temperature of $70^{\circ}C$ in order to observe the shear waves according to degree of saturation. The shear wave velocities measured at the temperature of $70^{\circ}C$ are generally lower than those measured at temperature of $15^{\circ}C$. This study demonstrates that the dependence of shear wave velocities on the temperature according to the degree of saturation should be taken into account in both laboratory and field tests.

• Korean Journal of Veterinary Service
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• v.38 no.2
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• pp.127-136
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• 2015

A simultaneous determination method was developed for nine preservatives (benzoic acid, sorbic acid, dehydroacetic acid, methyl-, ethyl-, isopropyl-, propyl-, isobutyl- and butyl-parabens) in sausage by liquid chromatography with electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS). Each parameter was established by multiple reaction monitoring in negative mode. Separation was achieved on a phenyl-hexyl ($2.5{\mu}m$, $2.1{\times}150mm$, Waters) with A-20 mM ammonium acetate containing 0.1% acetic acid in water, B-Acetonitrile as mobile phase with gradient mode at a flow rate of 0.3 mL/min. The developed method was validated for specificity, linearity, accuracy and precision in sausages samples. Linearity was over 0.998 with calibration curve of the mixed standards. The mean recoveries from sausages fortified at the level of 2.0~10.0 mg/L were in range of 98.60~109.16% with RSDs lower than 8.93%. The limits of detection (LOD) and the limits of quantification (LOQ) were in the range between 0.0003~0.085 mg/L and 0.01~0.257 mg/L, respectively. Intra-day precision and inter-day precision were 0.45~6.16% and 2.81~13.33%, respectively. Using presently developed determination method, 33 field sausage samples from Gwangju city in Korea were screened over nine preservatives. As a result, no preservatives were detected in all samples.

• Fire Science and Engineering
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• v.26 no.1
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• pp.61-67
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• 2012

In the three-phase power system using the three-phase motor, when any one-phase is open-phase, the unbalanced current flows and the single-phase power supplied by power supply produces overcurrent to motor coil. As a result, the enormous damage and electrical fire can be given to the power system. Recently, the thermal over-current relay (THR) or electronic motor protection relay (EMPR) is mostly used as the open-phase detection device of the three-phase motor. When the over-current or overheat of electric line is generated, it detects and operates circuit breaker, but there is the defect that the sensing speed is slow, the operation can be sometimes failed, and the precision is decreased. In order to improve these problems, this paper is proposed a new control circuit topology for openphase protection using semiconductor devices. Therefore, the proposed open-phase protection device (OPPD) enhances the sensing speed and precision, and has the advantage of simple fitting in the three-phase motor control panel in the field, as it manufactures into small size and light weight. As a result, the proposed OPPD protects the three-phase motor, minimizes the electrical fire from openphase, and contributes for the stable driving of the power system. The performance and confidence of the proposed OPPD is confirmed by a great variety of the experiments of operation characteristic.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.115-116
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• 2012

The demand for flexible electronic systems such as wearable computers, E-paper, and flexible displays has increased due to their advantages of excellent portability, conformal contact with curved surfaces, light weight, and human friendly interfaces over present rigid electronic systems. This seminar introduces three recent progresses that can extend the application of high performance flexible inorganic electronics. The first part of this seminar will introduce a RRAM with a one transistor-one memristor (1T-1M) arrays on flexible substrates. Flexible memory is an essential part of electronics for data processing, storage, and radio frequency (RF) communication and thus a key element to realize such flexible electronic systems. Although several emerging memory technologies, including resistive switching memory, have been proposed, the cell-to-cell interference issue has to be overcome for flexible and high performance nonvolatile memory applications. The cell-to-cell interference between neighbouring memory cells occurs due to leakage current paths through adjacent low resistance state cells and induces not only unnecessary power consumption but also a misreading problem, a fatal obstacle in memory operation. To fabricate a fully functional flexible memory and prevent these unwanted effects, we integrated high performance flexible single crystal silicon transistors with an amorphous titanium oxide (a-TiO2) based memristor to control the logic state of memory. The $8{\times}8$ NOR type 1T-1M RRAM demonstrated the first random access memory operation on flexible substrates by controlling each memory unit cell independently. The second part of the seminar will discuss the flexible GaN LED on LCP substrates for implantable biosensor. Inorganic III-V light emitting diodes (LEDs) have superior characteristics, such as long-term stability, high efficiency, and strong brightness compared to conventional incandescent lamps and OLED. However, due to the brittle property of bulk inorganic semiconductor materials, III-V LED limits its applications in the field of high performance flexible electronics. This seminar introduces the first flexible and implantable GaN LED on plastic substrates that is transferred from bulk GaN on Si substrates. The superb properties of the flexible GaN thin film in terms of its wide band gap and high efficiency enable the dramatic extension of not only consumer electronic applications but also the biosensing scale. The flexible white LEDs are demonstrated for the feasibility of using a white light source for future flexible BLU devices. Finally a water-resist and a biocompatible PTFE-coated flexible LED biosensor can detect PSA at a detection limit of 1 ng/mL. These results show that the nitride-based flexible LED can be used as the future flexible display technology and a type of implantable LED biosensor for a therapy tool. The final part of this seminar will introduce a highly efficient and printable BaTiO3 thin film nanogenerator on plastic substrates. Energy harvesting technologies converting external biomechanical energy sources (such as heart beat, blood flow, muscle stretching and animal movements) into electrical energy is recently a highly demanding issue in the materials science community. Herein, we describe procedure suitable for generating and printing a lead-free microstructured BaTiO3 thin film nanogenerator on plastic substrates to overcome limitations appeared in conventional flexible ferroelectric devices. Flexible BaTiO3 thin film nanogenerator was fabricated and the piezoelectric properties and mechanically stability of ferroelectric devices were characterized. From the results, we demonstrate the highly efficient and stable performance of BaTiO3 thin film nanogenerator.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.3
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• pp.101-108
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• 2020

Since the performance of deep learning techniques has recently been proven in the field of image processing, there are many attempts to perform classification, analysis, and detection of images using such techniques in various fields. Among them, the expectation of medical image analysis software, which can serve as a medical diagnostic assistant, is increasing. In this study, we are attention to the capsule endoscope image, which has a large data set and takes a long time to judge. The purpose of this paper is to distinguish the gastrointestinal landmarks and to estimate the gastrointestinal transition location that are common to all patients in the judging of capsule endoscopy and take a lot of time. To do this, we designed CNN-based Classifier that can identify gastrointestinal landmarks, and used it to estimate the gastrointestinal transition location by filtering the results. Then, we estimate gastrointestinal transition location about seven of eight patients entered the suspected gastrointestinal transition area. In the case of change from the stomach to the small intestine(pylorus), and change from the small intestine to the large intestine(ileocecal valve), we can check all eight patients were found to be in the suspected gastrointestinal transition area. we can found suspected gastrointestinal transition area in the range of 100 frames, and if the reader plays images at 10 frames per second, the gastrointestinal transition could be found in 10 seconds.