• The Korean Journal of Air & Space Law and Policy
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• v.29 no.1
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• pp.33-66
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• 2014

While the numbers of overseas travelers has been increased rapidly each year, the numbers of passengers in the aircraft also has continued to be increased gradually. In the mist of these increasing numbers, such accidents as threatening an aircraft safety like riot, aircraft hijacking and terrorism have happened constantly. In these circumstances, South Korean government has prescribed "Aviation on Security Act" in accordance with the Convention on International Civil Aviation and other international agreements. This act aims to prevent illegal activities and illegal items on the aircraft to ensure the safety and security of civil aviation. However, this act is not sufficiently regulating all the illegal crimes and illegal items on the flight. For the worse, there is a lack of effective supervisory capacity. Likewise, the inherent problems of the current laws relating to the prevention of the illegal items on the aircraft are appearing on the surface continually. Above all, illegal items on the aircraft are directly connected to the issue of aviation safety and security as well as a safe utilization of the flight service. Thus, when there occurs a serious accident on board, it surely would be led to a huge economic loss not mentioning the loss of lives following the accident. Therefore safety of the flight passengers cannot be guaranteed without ensuring the safety of aircraft facilities and good supervisory mechanism of illegal items on the aircraft. Accordingly, establishing a safe operation order tends to influence economy and tourism of a country in no small measure. Therefore, it is an urgent issue to settle down a reasonable and adequate supervisory regulations regarding the prevention of the illegal items on the aircraft. Consequently, in this article, I studied on a reasonal and effective mechanism to control the prevention of the illegal items and illegal acts on the aircraft in order to ensure a safety and security of civil aircraft.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.3
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• pp.192-207
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• 2006

Today, the SSL protocol has been used as core part in various computing environments or security systems. But, the SSL protocol has several problems, because of the rigidity on operating. First, SSL protocol brings considerable burden to the CPU utilization so that performance of the security service in encryption transaction is lowered because it encrypts all data which is transferred between a server and a client. Second, SSL protocol can be vulnerable for cryptanalysis due to the key in fixed algorithm being used. Third, it is difficult to add and use another new cryptography algorithms. Finally. it is difficult for developers to learn use cryptography API(Application Program Interface) for the SSL protocol. Hence, we need to cover these problems, and, at the same time, we need the secure and comfortable method to operate the SSL protocol and to handle the efficient data. In this paper, we propose the SSL component which is designed and implemented using CBD(Component Based Development) concept to satisfy these requirements. The SSL component provides not only data encryption services like the SSL protocol but also convenient APIs for the developer unfamiliar with security. Further, the SSL component can improve the productivity and give reduce development cost. Because the SSL component can be reused. Also, in case of that new algorithms are added or algorithms are changed, it Is compatible and easy to interlock. SSL Component works the SSL protocol service in application layer. First of all, we take out the requirements, and then, we design and implement the SSL Component, confidentiality and integrity component, which support the SSL component, dependently. These all mentioned components are implemented by EJB, it can provide the efficient data handling when data is encrypted/decrypted by choosing the data. Also, it improves the usability by choosing data and mechanism as user intend. In conclusion, as we test and evaluate these component, SSL component is more usable and efficient than existing SSL protocol, because the increase rate of processing time for SSL component is lower that SSL protocol's.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.09a
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• pp.21-36
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• 2005

Although the main geology of Korea consists of granite and gneiss, it Is not uncommon to encounter anisotropy Phenomena in crosshole radar tomography even when the basement is crystalline rock. To solve the anisotropy Problem, we have developed and continuously upgraded an anisotropic inversion algorithm assuming a heterogeneous elliptic anisotropy to reconstruct three kinds of tomograms: tomograms of maximum and minimum velocities, and of the direction of the symmetry axis. In this paper, we discuss the developed algorithm and introduce some case histories on the application of anisotropic radar tomography in Korea. The first two case histories were conducted for the construction of infrastructure, and their main objective was to locate cavities in limestone. The last two were performed In a granite and gneiss area. The anisotropy in the granite area was caused by fine fissures aligned in the same direction, while that in the gneiss and limestone area by the alignment of the constituent minerals. Through these case histories we showed that the anisotropic characteristic itself gives us additional important information for understanding the internal status of basement rock. In particular, the anisotropy ratio defined by the normalized difference between maximum and minimum velocities as well as the direction of maximum velocity are helpful to interpret the borehole radar tomogram.

• Journal of the Korean Society of Radiology
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• v.11 no.1
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• pp.9-17
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• 2017

A high degree of precision and accuracy in Gamma Knife Radiosurgery(GKRS) is a fundamental requirement for therapeutical success. Elaborate radiation delivery and dose gradients with the steep fall-off of radiation are clinically applied thus necessitating a dedicated Quality Assurance(QA) program in order to guarantee dosimetric and geometric accuracy and reduce all the risk factors that can occur in GKRS. In this study, as a part of QA we verified the accuracy of single-shot dose profiles used in the algorithm of Gamma Knife Perfexion(PFX) treatment planning system employing Variable Ellipsoid Modeling Technique(VEMT). We evaluated the dose distributions of single-shots in a spherical ABC phantom with diameter 160 mm on Gamma Knife PFX. The single-shots were directed to the center of ABC phantom. Collimating configurations of 4, 8, and 16 mm sizes along x, y, and z axes were studied. Gamma Knife PFX treatment planning system being used in GKRS is called Leksell GammaPlan(LGP) ver 10.1.1. From the verification like this, the accuracy of GKRS will be doubled. Then the clinical application must be finally performed based on precision and accuracy of GKRS. Specifically the width at the 50% isodose level, that is, Full-Width-of-Half-Maximum(FWHM) was verified under such conditions that a patient's head is simulated as a sphere with diameter 160mm. All the data about dose profiles along x, y, and z axes predicted through VEMT were excellently consistent with dose profiles from LGP within specifications(${\leq}1mm$ at 50% isodose level) except for a little difference of FWHM and PENUMBRA(isodose level: 20%~80%) along z axis for 4 mm and 8mm collimating configurations. The maximum discrepancy of FWHM was less than 2.3% at all collimating configurations. The maximum discrepancy of PENUMBRA was given for the 8 mm collimator along z axis. The difference of FWHM and PENUMBRA in the dose distributions obtained with VEMT and LGP is too small to give the clinical significance in GKRS. The results of this study are considered as a reference for medical physicists involved in GKRS in the whole world. Therefore we can work to confirm the validity of dose distributions for all collimating configurations determined through the regular preventative maintenance program using the independent verification method VEMT for the results of LGP and clinically assure the perfect treatment for patients of GKRS. Thus the use of VEMT is expected that it will be a part of QA that can verify and operate the system safely.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.79-87
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• 2021

Because active interactions occur among vegetation, hydrology, and geomorphology in riparian systems, any changes in one of these factors can significantly affect the other two. In this study, we evaluated these interactions at four sites (two in Gajeong and two in Hahan) along the Seomjin-gang River that was substantially devastated by an extreme flood in 2020. We examined the relationship between the riparian vegetation and the hydraulic characteristics of the flood using remote sensing, hydraulic modeling, and field surveys combined. The evaluation results showed that the floods caused a record-breaking rise of up to 43.1 m above sea level at the Yeseong-bridge stage gauge station (zero elevation 27.4 m) located between the Gajeong and Hahan sites, with the shear stress being four times higher in Hahan than in Gajeong. Additionally, the water level during the flood was estimated to be a maximum of 1 m higher depending on the location in the presence of riparian plants. Furthermore, both sites underwent extensive biological damage due to the flood, with 78-80% loss in vegetation, with preferential damage observed in large willow species, compared to Quercus acutissima. The above findings imply that all plant species exhibit different vulnerabilities towards extreme floods and do not induce similar behavior towards events causing a disturbance. In conclusion, we developed strategies for effectively managing riparian trees by minimizing flood hazards that could inevitably cause damage.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.

• Journal of the Korea Concrete Institute
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• v.24 no.4
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• pp.369-379
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• 2012

The collapse of concrete structures by extreme loads such as impact, explosion, and blast from terrorist attacks causes severe property damage and human casualties. Concrete has excellent impact resistance to such extreme loads in comparison with other construction materials. Nevertheless, existing concrete structures designed without consideration of the impact or blast load with high strain rate are endangered by those unexpected extreme loads. In this study, to improve the impact resistance, the static and impact behaviors of concrete beams caste with steel fiber reinforced concrete (SFRC) with 0~1.5% (by volume) of 30 mm long hooked steel fibers were assessed. Test results indicated that the static and impact resistances, flexural strength, ductility, etc., were significantly increased when higher steel fiber volume fraction was applied. In the case of the layered concrete (LC) beams including greater steel fiber volume fraction in the tensile zone, the higher static and impact resistances were achieved than those of the normal steel fiber reinforced concrete beam with an equivalent steel fiber volume fraction. The impact test results were also compared with the analysis results obtained from the single degree of freedom (SDOF) system anaysis considering non-linear material behaviors of steel fiber reinforced concrete. The analysis results from SDOF system showed good agreement with the experimental maximum deflections.

• Journal of the Korean Applied Science and Technology
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• v.33 no.2
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• pp.374-384
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• 2016

Concern about air pollution is gradually rising up in domestic and foreign, automotive and fuel researchers are trying to reduce vehicle exhaust emissions, through a lot of approaches, which consist of new engine design and innovative after-treatment systems, using clean (eco-friendly alternative) fuels and fuel quality improvement. This research is proceeding by two main issues : exhaust emissions and PM particle emissions of gasoline vehicle. Exhaust emissions, non-regulated emissions and PM (particulate matter) particles of automotive are causing many problems which ambient pollution and harmful effects on the human body. The main particulate fraction of automotive exhaust emissions consists of small particles. Because of their small size, inhaled particles can easily penetrate deep into the lungs. The rough surfaces of these particles make it easier for them to combine with other toxins in the environment. Thus, the hazards of particle inhalation are increased. Based on the oxygenated fuel additive types (MTBE, Bio-ETBE, Bio-ethanol, Bio-butanol), this paper discussed the influence of oxygen contents on gasoline vehicle exhaust emissions, non-regulated emissions and nano-particle emissions. Also, this paper assessed exhaust emission characteristics at 2 type test modes. The test modes were FTP-75 and HWFET. All measurement items be verified less than the value of regulated emissions. It could be known difference increase and decrease by each measurement item depending on increase the oxygen contents.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.722-729
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• 2010

Prediction problems are widely used in medical domains. For example, computer aided diagnosis or prognosis is a key component in a CDSS (Clinical Decision Support System). SVMs with nonlinear kernels like RBF kernels, have shown superior accuracy in prediction problems. However, they are not preferred by physicians for medical prediction problems because nonlinear SVMs are difficult to visualize, thus it is hard to provide intuitive interpretation of prediction results to physicians. Nomogram was proposed to visualize SVM classification models. However, it cannot visualize nonlinear SVM models. Localized Radial Basis Function (LRBF) was proposed which shows comparable accuracy as the RBF kernel while the LRBF kernel is easier to interpret since it can be linearly decomposed. This paper presents a new tool named VRIFA, which integrates the nomogram and LRBF kernel to provide users with an interactive visualization of nonlinear SVM models, VRIFA visualizes the internal structure of nonlinear SVM models showing the effect of each feature, the magnitude of the effect, and the change at the prediction output. VRIFA also performs nomogram-based feature selection while training a model in order to remove noise or redundant features and improve the prediction accuracy. The area under the ROC curve (AUC) can be used to evaluate the prediction result when the data set is highly imbalanced. The tool can be used by biomedical researchers for computer-aided diagnosis and risk factor analysis for diseases.