• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.434-449
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• 2019

In this study, we develop a new cross-shore sediment module which takes the effect of infra-gravity waves of bound mode, and boundary layer streaming on the sediment transport into account besides the well-known asymmetry and under-tow. In doing so, the effect of individual random waves occurring during the unit observation period of 1 hr on sediment transport is also fully taken into account. To demonstrate how the individual random waves would affect the sediment transport, we numerically simulate the non-linear shoaling process of random wavers over the beach of uniform slope. Numerical results show that with the consistent frequency Boussinesq Eq. the application of which is lately extended to surf zone, we could simulate the saw-tooth profile observed without exception over the surf zone, infra-gravity waves of bound mode, and boundary-layer streaming accurately enough. It is also shown that when yearly highest random waves are modeled by the equivalent nonlinear uniform waves, the maximum cross-shore transport rate well exceeds the one where the randomness is fully taken into account as much as three times. Besides, in order to optimize the free parameter K involved in the long-shore sediment module, we carry out the numerical simulation to trace the yearly shoreline change of Mang-Bang beach from 2017.4.26 to 2018.4.20 as well, and proceeds to optimize the K by comparing the traced shoreline change with the measured one. Numerical results show that the optimized K for Mang-Bang beach would be 0.17. With K = 0.17, via yearly grand circulation process comprising severe erosion by consecutively occurring yearly highest waves at the end of October, and gradual recovery over the winter and spring by swell, the advance of shore-line at the northern and southern ends of Mang-Bang beach by 18 m, and the retreat of shore-line by 2.4 m at the middle of Mang-Bang beach can be successfully duplicated in the numerical simulation.

• Journal of the Korean Wood Science and Technology
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• v.43 no.6
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• pp.851-860
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• 2015

The objective of this study was to manufacture the wood based roughage using lumber from thinning of oak and pitch pine (Pinus rigida). And the study also aimed to investigate a feed value evaluation of wood based roughages. To investigate the optimization condition of steam-digestion treatment for roughage, the wood chips of oak and pitch pine were steam-digestion treated at $160^{\circ}C$ under pressure 6 atm depending on treatment times (60 min, 90 min and 120 min) followed by the content of essential oils analyzed. The essential oil content of steam-digestion treated roughages for 90 min and 120 min were under 0.1 mL/kg. The evaluation of feed value was carried out from steam-digestion treated roughages for 90 min through feed chemical composition analysis, NRC (National research Council) modeling, ruminal degradability analysis and relative economic value analysis. The feed chemical compositions including DM (dry mater), CP (crude protein), EE (ether extract), NDF (neutral detergent fiber), ADF (acid detergent fiber), ADL (acid detergent lignin), NFC (nonfiber carbohydrate) in oak roughage were 95.4, 1.36, 3.11, 90.05, 83.85, 17.33, 6.50%, respectively, and in pitch pine roughage were 94.37, 1.33, 5.48, 87.89, 86.88, 30.56, 6.32%, respectively. Both roughages showed low level of protein and very high level of NDF. The TDN (total digestible nutrient) levels using NRC (2001) model in oak and pitch pine roughages were 40.55, 31.22%, respectively. The ruminal in situ dry matter degradability was higher in oak roughage (23.84%) than in pitch pine roughage (10.02%). The economic values of oak and pitch pine rough-ages were 235, and 210 \, respectively.

• Journal of Radiation Protection and Research
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• v.33 no.1
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• pp.13-20
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• 2008

The flow rate measurements in a multi-phase flow pipeline were evaluated quantitatively by means of a clamp-on sealed radioisotope based on a cross correlation signal processing technique. The flow rates were calculated by a determination of the transit time between two sealed gamma sources by using a cross correlation function following FFT filtering, then corrected with vapor fraction in the pipeline which was measured by the ${\gamma}$-ray attenuation method. The pipeline model was manufactured by acrylic resin(ID. 8 cm, L=3.5 m, t=10 mm), and the multi-phase flow patterns were realized by an injection of compressed $N_2$ gas. Two sealed gamma sources of $^{137}Cs$ (E=0.662 MeV, ${\Gamma}$ $factor=0.326\;R{\cdot}h^{-1}{\cdot}m^2{\cdot}Ci^{-1}$) of 20 mCi and 17 mCi, and radiation detectors of $2"{\times}2"$ NaI(Tl) scintillation counter (Eberline, SP-3) were used for this study. Under the given conditions(the distance between two sources: 4D(D; inner diameter), N/S ratio: $0.12{\sim}0.15$, sampling time ${\Delta}t$: 4msec), the measured flow rates showed the maximum. relative error of 1.7 % when compared to the real ones through the vapor content corrections($6.1\;%{\sim}9.2\;%$). From a subsequent experiment, it was proven that the closer the distance between the two sealed sources is, the more precise the measured flow rates are. Provided additional studies related to the selection of radioisotopes their activity, and an optimization of the experimental geometry are carried out, it is anticipated that a radioisotope application for flow rate measurements can be used as an important tool for monitoring multi-phase facilities belonging to petrochemical and refinery industries and contributes economically in the light of maintenance and control of them.

• Food Science and Preservation
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• v.24 no.5
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• pp.623-630
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• 2017

Functional compounds including flavonoids, anthocyanins, polyphneols and antioxidants were extracted from blue honeysuckle (Lonicera caerulea L.) using highly efficient microwave-assisted extraction. And extraction process was modeled and optimized according to response surface methodology (RSM). The independent variables ($X_n$) were ethanol concentration ($X_1$: 0, 25, 50, 75, 100%), irradiation time ($X_2$: 1, 3, 5, 7, 9 min), and microwave power ($X_3$: 60, 120, 180, 240, 300 W). Dependent variables ($Y_n$) were total flavonoid contents ($Y_1$), total anthocyanin contents ($Y_2$), total polyphenol contents ($Y_3$) and antioxidant activity ($Y_4$). Four-dimensional response surface plots were generated based on the fitted second-order polynomial models to get optimal conditions. Estimated optimal conditions for 4 responses were ethanol concentration of 54-72%, irradiation time of 7.1-7.6 min, and microwave power of 243-251 W. Ridge analysis predicted the maximal responses of total flavonoid content, total anthocyanin content, total polyphenol content and antioxidant activity were 38.00 mg RE/g, 6.80 mg CGE/g, 14.90 mg GAE/g, 89.10%, respectively. Verification experiment was carried out at predicted optimal conditions and experimental values for total flavonoid content, total anthocyanin content, total polyphenol content and antioxidant activity were 38.10 mg RE/g, 6.72 mg CGE/g, 14.91 mg GAE/g and 89.13%, respectively. No significant difference was observed between predicted and experimental values, indicating good fitness of fitted model and successful application of RSM.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1219-1230
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• 2008

Stream inflows induced by flood runoffs have a higher density than the ambient reservoir water because of a lower water temperature and elevated suspended sediment(SS) concentration. As the propagation of density currents that formed by density difference between inflow and ambient water affects reservoir water quality and ecosystem, an understanding of reservoir density current is essential for an optimization of filed monitoring, analysis and forecast of SS and nutrient transport, and their proper management and control. This study was aimed to quantify the characteristics of inflow density current including plunge depth($d_p$) and distance($X_p$), separation depth($d_s$), interflow thickness($h_i$), arrival time to dam($t_a$), reduction ratio(${\beta}$) of SS contained stream inflow for different flood magnitude in Daecheong Reservoir with a validated two-dimensional(2D) numerical model. 10 different flood scenarios corresponding to inflow densimetric Froude number($Fr_i$) range from 0.920 to 9.205 were set up based on the hydrograph obtained from June 13 to July 3, 2004. A fully developed stratification condition was assumed as an initial water temperature profile. Higher $Fr_i$(inertia-to-buoyancy ratio) resulted in a greater $d_p,\;X_p,\;d_s,\;h_i$, and faster propagation of interflow, while the effect of reservoir geometry on these characteristics was significant. The Hebbert equation that estimates $d_p$ assuming steady-state flow condition with triangular cross section substantially over-estimated the $d_p$ because it does not consider the spatial variation of reservoir geometry and water surface changes during flood events. The ${\beta}$ values between inflow and dam sites were decreased as $Fr_i$ increased, but reversed after $Fr_i$>9.0 because of turbulent mixing effect. The results provides a practical and effective prediction measures for reservoir operators to first capture the behavior of turbidity inflow.

• KSBB Journal
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• v.17 no.1
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• pp.73-79
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• 2002

The method to optimize the microbial production of ethanol from CO using Clostridium ljungdahlii was developed. The kinetic parameter study on CO conversion with Clostridium ljungdahlii was carried out and maximum CO conversion rate of 37.14 mmol/L-hr-O.D. and $K_{m}$ / of 0.9516 atm were obtained. It was observed that method of two stage fermentation, which consists of cell growth stage and ethanol production stage, was effective to produce ethanol. When pH was shifted from 5.5 to 4.5 and ammonium solution was supplied to culture media as nitrogen source at ethanol production stage, the concentration of ethanol produced was increased 20 times higher than that without shift. Ethanol production from CO in a fermenter with Clostridium ljungdahlii was optimized and the concentration of ethanol produced was 45 g/L and maximun ethanol productivity was 0.75 g ethanol/L-hr.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.37-50
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• 2020

Information security has become an important issue in the world. Various information and communication technologies, such as the Internet of Things, big data, cloud, and artificial intelligence, are developing, and the need for information security is increasing. Although the necessity of information security is expanding according to the development of information and communication technology, interest in information security investment is insufficient. In general, measuring the effect of information security investment is difficult, so appropriate investment is not being practice, and organizations are decreasing their information security investment. In addition, since the types and specification of information security measures are diverse, it is difficult to compare and evaluate the information security countermeasures objectively, and there is a lack of decision-making methods about information security investment. To develop the organization, policies and decisions related to information security are essential, and measuring the effect of information security investment is necessary. Therefore, this study proposes a method of constructing an investment portfolio for information security measures using game theory and derives an optimal defence probability. Using the two-person game model, the information security manager and the attacker are assumed to be the game players, and the information security countermeasures and information security threats are assumed as the strategy of the players, respectively. A zero-sum game that the sum of the players' payoffs is zero is assumed, and we derive a solution of a mixed strategy game in which a strategy is selected according to probability distribution among strategies. In the real world, there are various types of information security threats exist, so multiple information security measures should be considered to maintain the appropriate information security level of information systems. We assume that the defence ratio of the information security countermeasures is known, and we derive the optimal solution of the mixed strategy game using linear programming. The contributions of this study are as follows. First, we conduct analysis using real performance data of information security measures. Information security managers of organizations can use the methodology suggested in this study to make practical decisions when establishing investment portfolio for information security countermeasures. Second, the investment weight of information security countermeasures is derived. Since we derive the weight of each information security measure, not just whether or not information security measures have been invested, it is easy to construct an information security investment portfolio in a situation where investment decisions need to be made in consideration of a number of information security countermeasures. Finally, it is possible to find the optimal defence probability after constructing an investment portfolio of information security countermeasures. The information security managers of organizations can measure the specific investment effect by drawing out information security countermeasures that fit the organization's information security investment budget. Also, numerical examples are presented and computational results are analyzed. Based on the performance of various information security countermeasures: Firewall, IPS, and Antivirus, data related to information security measures are collected to construct a portfolio of information security countermeasures. The defence ratio of the information security countermeasures is created using a uniform distribution, and a coverage of performance is derived based on the report of each information security countermeasure. According to numerical examples that considered Firewall, IPS, and Antivirus as information security countermeasures, the investment weights of Firewall, IPS, and Antivirus are optimized to 60.74%, 39.26%, and 0%, respectively. The result shows that the defence probability of the organization is maximized to 83.87%. When the methodology and examples of this study are used in practice, information security managers can consider various types of information security measures, and the appropriate investment level of each measure can be reflected in the organization's budget.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Journal of the Korean Society of Radiology
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• v.13 no.6
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• pp.879-887
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• 2019

The purpose of this study is to establish a physiological injection protocol according to body weight, in order to minimize amount of contrast medium and optimize contrast enhancement in pediatric patients performing thoracic CT examinations. The 80 pediatric patients under the age of 10 were studied. Intravenous contrast material containing 300 mgI/ml was used. The group A injected with a capacity of 1.5 times its weight, and groups B, C and D added 5 to 15 ml of normal saline with a 10% decrease in each. The physiologic model which can be calculated by weight about amount of injection of contrast medium and normal saline, flow rate and delay time were applied. To assess image quality, measured average HU value and SNR of superior vena cava, pulmonary artery, ascending and descending aorta, right and left atrium, right and left ventricle. CT numbers of subclavian vein and superior vena cava were compared to identify the effects of reducing artifacts due to normal saline. Comparing SNR according to the contrast medium injection protocol, significant differences were found in superior vena cava and pulmonary artery, descending aorta, right and left ventricle, and CT numbers showed significant differences in all organs. In particular, B group with a 10% decrease in contrast medium and an additional injection of saline showed a low degree of contrast enhancement in groups with a decrease of more than 20%. In addition, the group injected with normal saline greatly reduced contrast enhancement of subclavian vein and superior vena cava, and the beam hardening artifact by contrast medium was significantly attenuated. In conclusion, the application of physiological protocol for injection of contrast medium in pediatric thoracic CT examinations was able to reduce artifacts by contrast medium, prevent unnecessary use of contrast medium and improve the effect of contrast enhancement.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.175-195
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• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.