• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.59-68
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• 1998

Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

• Korean Journal of Construction Engineering and Management
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• v.1 no.3 s.3
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• pp.124-134
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• 2000

In construction projects, the design information, which should contain accurate product information in a systematic way, needs to be applicable through the life-cycle of projects. However, paper-based 2D drawings and relevant documents has difficulties in communicating and sharing the owner's and architect's intention and requirement effectively and building a corporate knowledge base through on-going projects due to Tack of interoperability between specific task or function-oriented software and handling massive information. Meanwhile, computer and information technologies are being developed so rapidly that the practitioners are even hard to adapt them into the industry efficiently. 3D modeling capabilities in CAD systems are enormously developed and enables users to associate 3D models with other relevant information. However, this still requires a great deal of efforts and costs to have all the design information represented in CAD system, and the sophisticated system is difficult to manage. This research focuses on the transition period from 2D-based design Information management to 3D-based, which means co-existence of 2D and 3D-based management. This research proposes a model of a compound system of 2D and 3D-based CAD system which presents the general design information using 3D model integrating with 2D CAD drawings for detailed design information. This research developed an integrated information management system for design and specification by associating 2D drawings and 3D models, where 2D drawings represents detailed design and parts that are hard to express in 3D objects. To do this, related management processes was analyzed to build an information model which in turn became the basis of the integrated information management system.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.101-107
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• 2016

Due to the recent advancement in digital imaging technology, development of intervention equipment has become generalize. Video arbitration procedure is a process to insert a tiny catheter and a guide wire in the body, so in order to enhance the effectiveness and safety of this treatment, the high-quality of x-ray of image should be used. However, the increasing of radiation has become the problem. Therefore, the studies to improve the performance of x-ray detectors are being actively processed. Moreover, this intervention is based on the reference of the angiographic imaging and 3D medical image processing. In this paper, we propose a guidance system to support this intervention. Through this intervention, it can solve the problem of the existing 2D medical images based vessel that has a formation of cerebrovascular disease, and guide the real-time tracking and optimal route to the target lesion by intervention catheter and guide wire tool. As a result, the system was completely composed for medical image acquisition unit and image processing unit as well as a display device. The experimental environment, guide services which are provided by the proposed system Brain Phantom (complete intracranial model with aneurysms, ref H+N-S-A-010) was taken with x-ray and testing. To generate a reference image based on the Laplacian algorithm for the image processing which derived from the cerebral blood vessel model was applied to DICOM by Volume ray casting technique. $A^*$ algorithm was used to provide the catheter with a guide wire tracking path. Finally, the result does show the location of the catheter and guide wire providing in the proposed system especially, it is expected to provide a useful guide for future intervention service.

• Korean Journal of Food Science and Technology
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• v.37 no.3
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• pp.484-491
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• 2005

Quantitative microbial risk assessment (QMRA) analyzes potential hazard of microorganisms on public health and offers structured approach to assess risks associated with microorganisms in foods. This paper addresses specific risk management questions associated with Staphylococcus aureus in kimbab and improvement and dissemination of QMRA methodology, QMRA model was developed by constructing four nodes from retail to table pathway. Predictive microbial growth model and survey data were combined with probabilistic modeling to simulate levels of S. aureus in kimbab at time of consumption, Due to lack of dose-response models, final level of S. aureus in kimbeb was used as proxy for potential hazard level, based on which possibility of contamination over this level and consumption level of S. aureus through kimbab were estimated as 30.7% and 3.67 log cfu/g, respectively. Regression sensitivity results showed time-temperature during storage at selling was the most significant factor. These results suggested temperature control under $10^{\circ}C$ was critical control point for kimbab production to prevent growth of S. aureus and showed QMRA was useful for evaluation of factors influencing potential risk and could be applied directly to risk management.

• Journal of IKEEE
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• v.15 no.2
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• pp.179-189
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• 2011

This paper presents an SVC based multi-channel transmission technique. Transmission of high definition multimedia and its service efficiency can be significantly improved by the proposed method. In this method, the HD stream is divided into the two layer streams, i.e., a base layer stream and an enhancement layer stream. The divided streams are transmitted through a primary channel and an auxiliary channel, respectively. The proposed technique provides a noble mode switching technique which enables a seamless service of HD multimedia even under the conditions of abrupt and intermittent deterioration of the auxiliary channel. When the enhancement layer stream is disrupted by the channel monitoring in the mode switching algorithm, the algorithm works further to maintain the spatial and time resolution of the HD multimedia by upsampling and interpolating the base layer stream, consequently serving for the non disrupted play of the media. Moreover, the adoption of an adaptive switching algorithm significantly reduces the frequency of channel disruption avoiding the unnecessary switching for the short period variations of the channel. The feasibility of the proposed technique is verified through the simulation study with an example application to the simultaneous utilization of both Ku and Ka bands for HD multimedia broadcasting service. The rainfall modeling and the analysis of the satellite channel attenuation characteristics are performed to simulate the quality of service performance of the proposed HD broadcasting method. The simulation results obtained under a relatively poor channel (weather) situations show that the average lasting period of enhancement layer service is extended from 9.48[min] to 23.12[min] and the average switching frequency is reduced from 3.84[times/hour] to 1.68[times/hour]. It is verified in the satellite example that the proposed SVC based transmission technique best utilizes the Ka band channel for the service of HD broadcasting, although it is characterized by its inherent weather related poor reliability causing severe limitations in its independent application.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.384-398
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• 2015

In this paper, the high-resolution Weather Research and Forecasting/Noah-MultiParameterization (WRF/Noah-MP) modeling system is configured for the Cheongmicheon Farmland site in Korea (CFK), and its performance in land and atmospheric simulation is evaluated using the observed data at CFK during the 2014 special observation period (21 August-10 September). In order to explore the usefulness of turning on Noah-MP dynamic vegetation in midterm simulations of surface and atmospheric variables, two numerical experiments are conducted without dynamic vegetation and with dynamic vegetation (referred to as CTL and DVG experiments, respectively). The main results are as following. 1) CTL showed a tendency of overestimating daytime net shortwave radiation, thereby surface heat fluxes and Bowen ratio. The CTL experiment showed reasonable magnitudes and timing of air temperature at 2 m and 10 m; especially the small error in simulating minimum air temperature showed high potential for predicting frost and leaf wetness duration. The CTL experiment overestimated 10-m wind and precipitation, but the beginning and ending time of precipitation were well captured. 2) When the dynamic vegetation was turned on, the WRF/Noah-MP system showed more realistic values of leaf area index (LAI), net shortwave radiation, surface heat fluxes, Bowen ratio, air temperature, wind and precipitation. The DVG experiment, where LAI is a prognostic variable, produced larger LAI than CTL, and the larger LAI showed better agreement with the observed. The simulated Bowen ratio got closer to the observed ratio, indicating reasonable surface energy partition. The DVG experiment showed patterns similar to CTL, with differences for maximum air temperature. Both experiments showed faster rising of 10-m air temperature during the morning growth hours, presumably due to the rapid growth of daytime mixed layers in the Yonsei University (YSU) boundary layer scheme. The DVG experiment decreased errors in simulating 10-m wind and precipitation. 3) As horizontal resolution increases, the models did not show practical improvement in simulation performance for surface fluxes, air temperature, wind and precipitation, and required three-dimensional observation for more agricultural land spots as well as consistency in model topography and land cover data.

• Journal of the Korean Society for Marine Environment & Energy
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• v.11 no.4
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• pp.191-198
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• 2008

To design a reliable $CO_2$ marine geological storage system, it is necessary to perform numerical process simulation using thermodynamic equation of state. $CO_2$ capture process from the major point sources such as power plants, transport process from the capture sites to storage sites and storage process to inject $CO_2$ into the deep marine geological structure can be simulate with numerical modeling. The purpose of this paper is to compare and analyse the relevant equations of state including ideal, BWRS, PR, PRBM and SRK equation of state. We also studied the effect of thermodynamic equation of state in designing the compression and transport process. As a results of comparison of numerical calculations, all relevant equation of state excluding ideal equation of state showed similar compression behavior in pure $CO_2$. On the other hand, calculation results of BWRS, PR and PRBM showed totally different behavior in compression and transport process of captured $CO_2$ mixture from the oxy-fuel combustion coal-fired plants. It is recommended to use PR or PRBM in designing of compression and transport process of $CO_2$ mixture containing NO, Ar and $O_2$.

• Journal of Distribution Research
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• v.17 no.5
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• pp.85-111
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• 2012

Introduction : The purpose of this study was to examine the relationship between perceptual characteristics of consumers and intent of relational continuance for PB(Private Brand) products in discount stores. This study was conducted as an empirical study based on survey. For the empirical study, factors of PB products as characteristics perceived by consumers such as perceived quality, store image, brand image and perceived value were deduced from preceding studies. The effect of such factors on intent of relational continuance mediated by brand trust and brand equity of PB products was structurally examined. Research Model : Based on theory analysis and hypotheses, constructed a Structural Equation Model(SEM). The research model is shown in Figure 1. Research Method : This paper is based on s qualitative study of selected literature and empirical data. The survey for empirical study was carried out on consumers in Gyeonggi and Busan between January 2012 and May 2012. 300 surveys were distributed and 253 (84.3%) of them were returned. After excluding omissions and insincere responses, 245 surveys (81.6%) were used for final analysis as effective samples. Result : First of all, the Reliability was carried out for instrument used. The lower limit of 0.7 for Cronbach's Alpha as suggested by Hair et al. (1998). And Construct validity was established by carrying out exploratory factor analysis by Varimax rotation for all. Four factor result for the consumer's perceptual characteristics of PB Products, two mediating factors and one dependent factor. All constructs included in research framework have acceptable validity and reliability. Table 1 shows the factor loading, eigen value, explained variance and Cronbach's alpha for each factor. In order to assure validity of constructs, I implemented Confirmatory Factor Analysis (CFA), using AMOS 20.0. In confirmatory factor analysis, researcher can take control over the specification of indicators for each factor by hypothesizing that a specific factor is loaded with the relevant indicators. Moreover, CFA is particularly useful in the validation of scale for the measurement of specific construct. CFA result summarized Table 2 shows that the fit measures of all constructs fulfill the recommended level and loadings are significant. To test causal relationship between constructs in the research model, used AMOS 20.0 that provides a graphic module as method for analysing Structural Equation Modeling. The result of hypothesis test is shown in Table 3. As a result of empirical study, perceived quality, brand image and perceived value as selected attributes for PB products showed significantly positive (+) effect on brand trust and brand equity. Furthermore, brand trust and brand equity showed significantly positive (+) effect on intent of relational continuance. However, store image of discount stores selling the PB products was analyzed to have positive (+) effect on brand trust and no significant effect on brand equity. Discussion : Based on the results of this study, the relationship between overall quality, store image, brand image and value perceived by consumers about PB products and intent of relational continuance was structurally verified as being mediated by brand trust and brand equity. Looking at the results, a strategic approach that maximizes brand trust and equity value for PB products by large discount stores is required on top of basic efforts to improve quality, brand image and value of PB products in order to maximize consumer's intent of relational continuance and to continuously attract repeated purchase of products.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1905-1919
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains are adjusted by the expert who has much experience in the ASP. The ASP model based on $Matlab^{(R)}5.3/Simulink^{(R)}3.0$ is developed in this paper. The performance of the model is tested by IWA(International Water Association) and COST(European Cooperation in the field of Scientific and Technical Research) data that include steady-state results during 14 days. The advantage of the developed model is that the user can easily modify or change the controller by the help of the graphical user interface. The ASP model as a typical nonlinear system can be used to simulate and test the proposed controller for an educational purpose. Various control methods are applied to the ASP model and the control results are compared to apply the proposed intelligent control strategy to a real ASP. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method. The proposed setpoints changer based on the fuzzy logic shows a better performance and robustness under disturbances. The objective function can be defined and included in the proposed control strategy to improve the effluent water quality and to reduce the operating cost in a real ASP.