• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.543-551
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• 2006

Recently efforts to extract information about forests by using remote sensing techniques for efficient forest management have progressed actively. In terms of extraction of tree information using single remote sensing data, however, the accuracy of tree recognition and the quantity of extracted information is limited. The objective of this study is to carry out tree modeling in domestic environment applying the latest core technique for tree modeling using color aerial photographs and LiDAR data and to estimate the result of tree modeling. A small-scale coniferous forest was investigated in Daejeon. It was 0.77 that the $R^2$ of accuracy test of tree numbers that estimated with color aerial photography and LiDAR data. In terms of tree height, there was no difference between the estimated value and the field measurements in the case of the group accuracy test of the recently unchanged area. Moreover $R^2$ was 0.83 in the case of the individual accuracy test.

• Korean Journal of Bronchoesophagology
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• v.3 no.1
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• pp.70-78
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• 1997

The development of preneoplastic and neoplastic squamous cell proliferations of body sites such as the skin, female lower genital tract, and larynx is strongly associated with specific types of human papillomaviruses (HPV). Antitumor $CD^{8+}$ cells recognize peptide antigens presented on the surface of tumor cells by major histocompatibility complex (MHC) class I molecules. The MHC class I molecule is a heterodimer composed of an integral membrane glycoprotein designated the alpha chain and a noncovalently associated, soluble protein called beta-2-microglobulin( $\beta$ -2-m). Loss of $\beta$-2-m generally eliminates antigen recognition by antitumor $CD^{8+}$ T cells. We evaluated the expression of $\beta$-2-m as a potential means of tumor escape from immune recognition and the presence of HPV DNA as a cause of laryngeal squamous cell carcinomas (SCCs). Laryngeal SCCs (n=39) were analyzed for MHC class I expression by immunohistochemistry and for presence of HPV by in situ hybridization technique. The results were as follows : 1) HPV DNA was detected in 10 (25.64%) out of 39 cases in laryngeal squamous cell carcinomas. 2) MHC class I down-regulation (heterogenous and negative expression) in HPV positive lesions was higher than HPV negative lesions. 3) The expression of MHC class I was related to cellular differentiation regardless of T-stage and nodal involvement. In conclusion, HPV was thought to be the etiological factor of SCC of larynx, and we found that the down-regulation of MHC class I was a common phenomenon In laryngeal SCC and may provide a way for tumor cells to escape from immune surveillance.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1260-1268
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• 2018

To improve fuel performance and specific characteristics of long storage and moving through fuel systems additives should be added in kerosene type aviation turbine fuel (AVTUR) such as antioxidant, fuel system icing inhibitor (FSII), electric conductivity improvers and so on. The dosage of additives has to be analyzed qualitatively and quantitatively due to inspect the quality of abnormal fuel and distinguish other petroleum products. Multi-dimensional GC-MS (MDGC-MS) with Deans switching technique are applied the determination of antioxidant and FSII, which are added with AVTUR containing complex mixture of hydrocarbons. Antioxidant and FSII in the range of 2.5-20 mg/L was quantitatively and qualitatively analyzed using MDGC-MS and the detection limit was about twice as low as that of the 1-dimensional GC-MS results. The method in this study has been higher peak resolution compared with GC-MS and could be simultaneously analyzed different two additives without sample pre-treatment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.35-42
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• 2019

Nut fasteners that require ultra-precise control are required in the overall manufacturing industry including electronic products that are currently developing with the automobile industry. Important performance factors when tightening nuts include loosening due to insufficient fastening force, breakage due to excessive fastening, Tightening torque and angle are required to maintain and improve the assembling quality and ensure the life of the product. Nut fasteners, which are now marketed under the name Nut Runner, require high torque and precision torque control, precision angle control, and high speed operation for increased production, and are required for sophisticated torque control dedicated to high output BLDC motors and nut fasteners. It is demanded to develop a high-precision torque control driver and a high-speed, low-speed, high-response precision speed control system, but it does not satisfy the high precision, high torque and high speed operation characteristics required by customers. Therefore, in this paper, we propose a control technique of BLDC motor variable speed control and nut runner based on vector control and torque control based on coordinate transformation of d axis and q axis that can realize low vibration and low noise even at accurate tightening torque and high speed rotation. The performance results were analyzed to confirm that the proposed control satisfies the nut runner performance. In addition, it is confirmed that the pattern is programmed by One-Stage operation clamping method and it is tightened to the target torque exactly after 10,000 [rpm] high speed operation. The problem of tightening torque detection by torque ripple is also solved by using disturbance observer Respectively.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1555-1565
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• 2018

Detection of subtle ground deformation of volcanoes plays an important role in evaluating the risk and possibility of volcanic eruptions. Ground-fixed observation equipment is difficult to maintain and cost-inefficient. In contrast, satellite remote sensing can regularly monitor at low cost. In this paper, following the study of Chadwick et al. (2006), which applied the interferometric SAR (InSAR) technique to the Sierra Negra volcano, Galapagos. In order to investigate the deformation of the volcano before 2005 eruption, the recent activities of this volcano were analyzed using Sentinel-1, the latest SAR satellite. We obtained the descending mode Sentinel-1A SAR data from January 2017 to January 2018, applied the Persistent Scatter InSAR, and estimated the depth and expansion quantity of magma in recent years through the Mogi model. As a result, it was confirmed that the activity pattern of volcano prior to the eruption in June 2018 was similar to the pattern before the eruption in 2005 and was successful in estimating the depth and expansion amount. The results of this study suggest that satellite SAR can characterize the activity patterns of volcano and can be possibly used for early monitoring of volcanic eruption.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.47-60
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• 2018

Today's unmanned technology, which is being used in various industries, is expected to be able to make autonomous judgements as autonomous technology matures, in the long run aspects. In order to improve the usability of unmanned system in the military field, it is necessary to develop a technique for systematically and quantitatively analyzing the efficiency and effectiveness of the unmanned system by means of a substitute for the tasks performed by humans. In this paper, we propose the method of representing rule-based tactical behavior and modeling manned and unmanned reconnaissance agents that can effectively analyze the path alternatives which is required for the future armored cavalry to establish a reconnaissance mission plan. First, we model the unmanned ground vehicle, small tactical vehicle, and combatant as an agent concept. Next, we implement the proposed agent behavior rules, e.g., maneuver, detection, route determination, and combatant's dismount point selection, by NetLogo. Considering the conditions of maneuver, enemy threat elements, reconnaissance assets, appropriate routes are automatically selected on the operation area. It is expected that it will be useful in analyzing unmanned ground system effects by calculating reconnaissance conducted area, time, and combat contribution ratio on the route.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.339-346
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• 2018

Cyanazine is a member of the triazine family of herbicides. Cyanazine is used as a pre- and post-emergence herbicide for the control of annual grasses and broadleaf weeds. This experiment was conducted to establish a determination method for cyanazine, as domestic unregistered pesticide, residue in major agricultural commodities using HPLC-DAD/MS. Cyanazine was extracted with acetone from representative samples of five raw products which comprised apple, green pepper, Kimchi cabbage, hulled rice and soybean. The extract was diluted with saline water and partitioned to dichloromethane for remove polar extractive in the aqueous phase. For the hulled rice and soybean samples, n-hexane/acetonitrile partition was additionally employed to remove non-polar lipids. The extract was finally purified by optimized florisil column chromatography. On a $C_{18}$ column in HPLC, cyanazine was successfully separated from co-extractives of sample, and sensitively quantitated by diode array detection at 220 nm. Accuracy and precision of the proposed method was validated by the recovery experiment on every major agricultural commodity samples fortified with cyanazine at 3 concentration levels per agricultural commodity in each triplication. Mean recoveries were ranged from 83.6 to 93.3% in five major representative agricultural commodities. The coefficients of variation were all less than 10%, irrespective of sample types and fortification levels. Limit of quantitation(LOQ) of cyanazine was 0.02 mg/kg as verified by the recovery experiment. A confirmatory method using LC/MS with selected-ion monitoring(SIM) technique was also provided to clearly identify the suspected residue.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.93-103
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• 2021

Despite the efforts of financial authorities in conducting the direct management and supervision of collection agents and bond-collecting guideline, the illegal and unfair collection of debts still exist. To effectively prevent such illegal and unfair debt collection activities, we need a method for strengthening the monitoring of illegal collection activities even with little manpower using technologies such as unstructured data machine learning. In this study, we propose a classification model for illegal debt collection that combine machine learning such as Support Vector Machine (SVM) with a rule-based technique that obtains the collection transcript of loan companies and converts them into text data to identify illegal activities. Moreover, the study also compares how accurate identification was made in accordance with the machine learning algorithm. The study shows that a case of using the combination of the rule-based illegal rules and machine learning for classification has higher accuracy than the classification model of the previous study that applied only machine learning. This study is the first attempt to classify illegalities by combining rule-based illegal detection rules with machine learning. If further research will be conducted to improve the model's completeness, it will greatly contribute in preventing consumer damage from illegal debt collection activities.

• Korean Chemical Engineering Research
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• v.59 no.1
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• pp.68-76
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• 2021

As hazardous chemicals are releasing in process industries such as chemical & petro-chemical plants, the importance of initial responses has been always emphasized. However, little attention of quantitative analysis of the consequence by different initial responses during releasing of the chemicals has been done. The main objective of current paper is to investigate the effects of initial responses for the release accidents of hydrofluoric acid. For this, a simplified equation that can easily calculate the effect distance by varying concentrations of hydrofluoric acid was firstly deduced. In addition, a causal loops for the initial response steps using the system dynamics technique was constructed during release of 50% hydrofluoric acid. The effect distances according to different scenarios of the initial actions were also quantitatively analyzed by applying the simplified equation to the causal map. As a result, the highest reduction rate on the maximum effect distance was obtained with 'start time of action after leak detection' being about 87% while the lowest was 'arrival time of professional response team' being about 50%, as expected. It is expected that the results gained from the current study can be helpful as of basics of the initial response to the workplace, dealing with the hydrofluoric acid.