• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4666-4672
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• 2011

Performance of NOx removal in SCR(Selective Catalytic Reduction) process depends on such various factors as catalyst factors (catalyst composition, catalyst form, space velocity, etc.), temperature of exhaust gas, and velocity distribution of exhaust gas. Especially the flow uniformity of gas stream flowing into the catalyst layer is believed to be the most important factor to influence the performance. In this research, the flow characteristics of a SCR process at design stage was simulated, using 3-dimensional numerical analysis method, to confirm the uniformity of the gas stream. In addition, the effects of guide vanes, baffles, and perforated plates on the flow uniformity for the inside and catalyst layer of the reactor were studied in order to optimize the flow uniformity inside the SCR reactor. It was found that the installation of a guide vane at the inlet duct L-tube part and the installation of a baffle at the upper part is very effective in avoiding chaneling inside the reactor. It was also found that additional installation of a perforated plate at the lower part of the potential catalyst layer buffers once more the flow for very uniform distribution of the gas stream.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.3-10
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• 2014

Direct conversion receiver(DCR) gets noticed for integration and cost reduction of wireless communication systems instead of the heterodyne receiver which uses complex filter. But DCR has several factors in performance degradation. One of them is I/Q imbalance phenomenon, that is amplitude and phase mismatch between real and imaginary part of receiver. Accordingly, researches are being carried to improve the I/Q imbalance problem. However, the tendency of the broaden bandwidth of communication systems, low pass filter(LPF) mismatch problem affects severely in I/Q mismatch phenomenon at the DCR. To study this problem, we generated 10MHz broadband signal and shifted it ${\pm}8MHz$ from the center frequency. The signal is affected by LPF mismatch and it appears as frequency selective distortion. Thus, LPF mismatch model is added to I/Q imbalance model which conventionally dealt with amplitude and phase mismatches. In addition, we proposed the compensation method for each factors of mismatch. As the simulation results, the proposed I/Q mismatch compensator resolves the frequency selective distortion which occurred by the existing LPF mismatch.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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• pp.351-356
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• 1996

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• Journal of Platform Technology
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• v.9 no.3
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• pp.3-17
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• 2021

Advanced persistent threat (APT) attacks are attacks aimed at a particular entity as a set of latent and persistent computer hacking processes. These APT attacks are usually carried out through various methods, including spam mail and disguised banner advertising. The same name is also used for files, since most of them are distributed via spam mail disguised as invoices, shipment documents, and purchase orders. In addition, such Infostealer attacks were the most frequently discovered malicious code in the first week of February 2021. CDR is a 'Content Disarm & Reconstruction' technology that can prevent the risk of malware infection by removing potential security threats from files and recombining them into safe files. Gartner, a global IT advisory organization, recommends CDR as a solution to attacks in the form of attachments. There is a program using CDR techniques released as open source is called 'Dangerzone'. The program supports the extension of most document files, but does not support the extension of HWP files that are widely used in Korea. In addition, Gmail blocks malicious URLs first, but it does not block malicious URLs in mail systems such as Naver and Daum, so malicious URLs can be easily distributed. Based on this problem, we developed a 'Dangerzone' program that supports the HWP extension to prevent APT attacks, and a Chrome extension that performs URL checking in Naver and Daum mail and blocking banner ads.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.112-125
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• 2021

Marine spatial planning(MSP) designates the marine as nine kinds of use zones for the systematic and rational management of marine spaces. One of them is the fishery protection zone, which is necessary for the sustainable production of fishery products, including the protection and fosterage of fishing activities. This study intends to quantitatively identify the fishing activity space, one of the elements necessary for the designation of fisheries protection zones, by mapping of fishery activities using V-Pass data and deriving the fishery activity concentrated zone. To this end, pre-processing of V-Pass data was performed, such as constructing a dataset that combines static and dynamic information, calculating the speed of fishing vessels, extracting fishing activity points, and removing data in non-fishing activity zone. Finally, using the selected V-Pass point data, a fishery activity map was made by kernel density estimation, and the concentrated space of fishery activity was analyzed. In addition, it was confirmed that there is a difference in the spatial distribution of fishing activities according to the type of fishing vessel and the season. The pre-processing technique of large volume V-Pass data and the mapping method of fishing activities performed through this study are expected to contribute to the study of spatial characteristics evaluation of fishing activities in the future.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.58-69
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• 2018

The purpose of this study was to present specific standards for landscape planning and construction applicable to landscaping areas in various historical sites. The results are as follows: First, the types of historical sites are classified according to their preservation status and processing techniques, and the classification according to their status is divided into those that have been buried underground, such as those that have been exposed to the ground, such as buildings and structures, and those that have a reputation or a record of the sites. The classification according to the wartime processing technique was classified by such techniques as closures that isolate the site, penetration that can be seen on the site, and overlays where a separate protection facility is installed on the site. Second, the principles of landscape planning for display of historical sites are divided into the items that make up the historical site, surface treatment of the sites, tree planting, and installation of facilities. If the site is not a circular space, the area separating the space by different materials between the components is required. In the event that preservation of the historical site is required, it is deemed desirable to use the soil, and to do so, the use of grasses and shrubs is effectively considered to be effective. The introduction of plants and plants should be considered according to the nature of the space. Depending on the area and nature of the monument, the facility is required to take a cautious approach by reviewing its influence on the landscape and the additional excavation of the monument. Third, the readjustment method derived as a result of looking at the landscaping principle in the historical site space was classified as conservation of status, installation of protection facilities, burial, restoration, relocation, and reproduction. Preservation of the status quo is essential for limited landscape planning and should not affect the prototype of existing relics. The protection facility shall be installed where necessary to protect the relics, and when the soil is formed, the surface treatment shall be required to remove trees that could damage the site and prevent soil and soil oil from being lost after the site. The restoration shall establish a landscaping plan according to the circular preservation based on the clues to the circle. The transfer requires a landscaping plan to create an environment similar to the outer space of an existing site and should be able to highlight the value or location of the original site. The reenactment should have a landscaping plan to revive the landscape and atmosphere of the past for the now-defunct remains. Fourth, landscaping can simultaneously satisfy the preservation of excavation sites and the increase in exhibition effects. In order to protect the traces of the past and vitalize the site of the ruins today, specific measures are required, the creation of a park for historical sites that preserve the functions and value of the relics, and the formation of a shape of linked contents can be suggested as alternatives.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.469-487
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• 2007

Grain-Size Trend Analysis is the methodology to identify net sediment transport pathways, based on the assumption that the movement of sediment from the source to deposit leaves the identifiable spatial pattern of mean, sorting, and skewness of grain size. It can easily be implemented with low cost, so it has great potentials to contribute to geomorphological research, whereas it can also be used inadequately without recognition of its limitations. This research aims to compare three established methods of grain-size trend analysis to search for the adequate way of application, and also suggest the research tasks needed in improving this methodology 1D pathway method can corporate the field experience into analyzing the pathway, provide the useful information of depositional environments through X-distribution, and identify the long-term trend effectively. However, it has disadvantage of the dependence on subjective interpretation, and a relatively coarse temporal scale. Gao-Collins's 2D transport vector method has the objective procedure, has the capability to visualize the transport pattern in 2D format, and to identify the pattern at a finer temporal scale, whereas characteristic distance and semiquantitative filtering are controversial. Le Roux's alternative 2D transport vector method has two improvement of Gao-Collins's in that it expands the empirical rules, considers the gradient of each parameters as well as the order, and has the ability to identify the pattern at a finer temporal scale, while the basic concepts are arbitrary and complicated. The application of grain sire trend analysis requires the selection of adequate method and the design of proper sampling scheme, based on the field knowledge of researcher, the temporal scale of sediment transport pattern targeted, and information needed. Besides, the relationship between the depth of sample and representative temporal scale should be systematically investigated in improving this methodology.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.1-8
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• 2017

As the IT environment becomes more sophisticated, various threats and their associated serious risks are increasing. Threats such as DDoS attacks, malware, worms, and APT attacks can be a very serious risk to enterprises and must be efficiently managed in a timely manner. Therefore, the government has designated the important system as the main information communication infrastructure in consideration of the impact on the national security and the economic society according to the 'Information and Communication Infrastructure Protection Act', which, in particular, protects the main information communication infrastructure from cyber infringement. In addition, it conducts management supervision such as analysis and evaluation of vulnerability, establishment of protection measures, implementation of protection measures, and distribution of technology guides. Even now, security consulting is proceeding on the basis of 'Guidance for Evaluation of Technical Vulnerability Analysis of Major IT Infrastructure Facilities'. There are neglected inspection items in the applied items, and the vulnerability of APT attack, malicious code, and risk are present issues that are neglected. In order to eliminate the actual security risk, the security manager has arranged the inspection and ordered the special company. In other words, it is difficult to check against current hacking or vulnerability through current system vulnerability checking method. In this paper, we propose an efficient method for extracting diagnostic data regarding the necessity of upgrading system vulnerability check, a check item that does not reflect recent trends, a technical check case for latest intrusion technique, a related study on security threats and requirements. Based on this, we investigate the security vulnerability management system and vulnerability list of domestic and foreign countries, propose effective security vulnerability management system, and propose further study to improve overseas vulnerability diagnosis items so that they can be related to domestic vulnerability items.