• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. 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, total misclassification cost is more affected by FNE rather than FPE. 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 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Journal of Aquaculture
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• v.11 no.3
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• pp.371-380
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• 1998

This study has been conducted to develop the techniques for spat production of the sun and moon scallop from January 1995 to December 1996. With the adult scallops collected from the Sogwipo area, spawning induction and larvae rearing were attempted several times and monthly changes of GSI were also monitored during the experimental period. The results obtained wre as follows. 1. GSI started to increase from June and showed the maximum value of 22.17 and 14.98 in female and male respectively in November, and then gradually decreased from December. 2. Spawning induction by heating method turned out to the most efficient way showing the responding rate of 64.8~91.5%. The responding temperature was $21.4~26.4{\circ}C$ which was $3.1~8.5{\circ}C$ increased from the rearing temperature of $16.3~18.3{\circ}C$. An average number of eggs spawned was $9.2{\times}10^5$ 3. the average size of eggs after fertilization was about $72{\mu}m$ in diameter. The first polar body discharge, blastula formation, and trochopore larvae appearance occurred 30 mininutes, 18 hours, and 22 hours after fertilization respectively. 4. Settling rates in various collectors were similar one another, whereas pouring larvae in the mesh was the most efficient way for larval setting. 5. The spates grew to be 1mm in their shell length for the first 50 days after fertilization and 9.6mm in 135days. 6. Correlation between shell length (SL) of the spat and the number of days (X) after spat settlement could be expressed as $SL=257.75e ^{0.0272x}$(r=0.9100).

• Journal of the Korean Professional Engineers Association
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• v.29 no.2
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• pp.15-23
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• 1996

With the ever-increasing importance of high-speed information in society as we move towards the 21 st century, telecommunication laboratories of advanced nations are pressing forward with research and development aimed at implementing its W & P(Visual Intelligent and Personal) services and construction of a new network to support them. In legals to the former, based on a long-term view of technological and market trends, those laboratories are researching and developing services that will make possible an effective progression from the development of services that answer to potential needs towards the full-scale implementation of VI & P services. In regards to the latter, these laboratories are responding in a flexible manner to the increasing diversity and disposal of the communications environment by separating the network into a transmission system and a versatile information control/conversion -ion system and laboratories are working at enhancing the performance of both. Within these board aims, the laboratories are currently focusing our attention in three areas : the technology for a high-speed broadband transmission system featuring optical frequency multiplexing and ATM techniques, network and software technologies for advanced information control and conversion, and technology for constructing a new access network that can provide a comprehensive range of multimedia services. This article describes the laboratories' concept of how VI & P services will develop in the future, and the latest trends in the field of communications. It also describes the ideal configuration of the new network and discusses the important technological aspects of how it is to be constructed. Finally, it presents the results of the laboratories'recent research which include some innovative work, point out the areas requiring future investigation.

• Atmosphere
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• v.15 no.1
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• pp.47-57
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• 2005

Extending the success of the Tropical Rainfall Measuring Mission (TRMM), the spaceborne measurement of precipitation by Global Precipitation Measurement (GPM) is initiated. The GPM consists of a core satellite which will have a dual-frequency precipitation radar (DPR) and a constellation of small satellites equipped with microwave radiometers. The GPM is inherently a global program. Responding to the GPM plan, many other nations are much interested in participating in the GPM team or simply utilizing GPM products aiming at the development of meteorological technology. Korea can fully function its role if Korea is selected as a CAL/VAL site for the GPM because Korea maintains a well-established dense rain gauge network (AWS), precipitation radars, and the Haenam super site for surface observation. In this feasibility study, the necessities of the GPM project in the context of academical and social backgrounds and associated international and domestic activities are investigated. And GPM-related core technologies and application areas are defined. As a result, it is found that GPM will represent a great opportunity for us because of its ability to provide not only much enhanced three-hourly global rain products but also very useful tools for the enhancement of weather forecasting capabilities, management of water resources, development and implementation of monitoring techniques for severe weather phenomena, agricultural managements and climate application. Furthermore, rain retrieval and CAL/VAL technologies obtained during the involvement in the international GPM project will serve as basic knowledges to run our own geostationary satellite program.

• The Journal of Bigdata
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• v.4 no.2
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• pp.23-34
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• 2019

Recently, the crime that utilizes the digital platform is continuously increasing. About 140,000 cases occurred in 2015 and about 150,000 cases occurred in 2016. Therefore, it is considered that there is a limit handling those online crimes by old-fashioned investigation techniques. Investigators' manual online search and cognitive investigation methods those are broadly used today are not enough to proactively cope with rapid changing civil crimes. In addition, the characteristics of the content that is posted to unspecified users of social media makes investigations more difficult. This study suggests the site-based collection and the Open API among the content web collection methods considering the characteristics of the online media where the infringement crimes occur. Since illegal content is published and deleted quickly, and new words and alterations are generated quickly and variously, it is difficult to recognize them quickly by dictionary-based morphological analysis registered manually. In order to solve this problem, we propose a tokenizing method in the existing dictionary-based morphological analysis through WPM (Word Piece Model), which is a data preprocessing method for quick recognizing and responding to illegal contents posting online infringement crimes. In the analysis of data, the optimal precision is verified through the Vote-based ensemble method by utilizing a classification learning model based on supervised learning for the investigation of illegal contents. This study utilizes a sorting algorithm model centering on illegal multilevel business cases to proactively recognize crimes invading the public economy, and presents an empirical study to effectively deal with social data collection and content investigation.

• Archives of design research
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• v.17 no.4
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• pp.211-222
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• 2004

During the 1980s, Textile design achieved a remarkable growth in creating aesthetic effect and in establishing its standing by responding to demands of the time effectively and seeking changes proactively. This was a period when Textile design constructed its modern concept as it was attempting a qualitative improvement through advanced technology, high class, and differentiation. The advent of advanced materials through the development of textile engineering, employment of craft techniques to further cultural and artistic orientation, and restoration of decorativeness in pursuit of sensitivity, all these developments of the 1980s contributed to the rise of above characteristics. In this study, attempts are made to grasp the new trend of Textile design during the 1980s and to review diverse methods of aesthetic creation and plastic possibility which this trend presented for the Textile, and thus to recognize the role of Textile design and its importance in a new light. The new trend of Textile design during the 1980s can be summarized as follows: 1) An appreciation of the creative aspect of the Textile. As attempts are made to emphasize visual and sensitive aspects of the medium, Textile tended to become an object of art itself. 2) A new awareness of the representative and plastic capacity of the fiber material. As attempts are made to develope the creative potential of the Textile, representation of the material tended to become more diversified. 3) A recognition of the Textile as a proper means to deliver the spirit of the time. As the medium accommodates and fuses diverse cultures including traditional culture, more emphasis was place on cultural contents of the Textile. In the process of pursuing these changes, Textile design of the 1980s has also contributed to the creation of new values, laying the groundwork for its emergence as an advanced high value-added industry.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1581-1588
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• 2017

Recently, circulating ransomware is becoming intelligent and sophisticated through a spreading new viruses and variants, targeted spreading using social engineering attack, malvertising that circulate a large quantity of ransomware by hacking advertising server, or RaaS(Ransomware-as-a- Service), from the existing attack way that encrypt the files and demand money. In particular, it makes it difficult to track down attackers by bypassing security solutions, disabling parameter checking via file encryption, and attacking target-based ransomware with APT(Advanced Persistent Threat) attacks. For remove the threat of ransomware, various detection techniques are developed, but, it is very hard to respond to new and varietal ransomware. Accordingly, in this paper, find out a making Signature-based Detection Patterns and problems, and present a pattern automation model of ransomware detecting for responding to ransomware more actively. This study is expected to be applicable to various forms in enterprise or public security control center.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.1-8
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• 2016

Current indoor intrusion detection and location tracking methods have the weakness in seamless operations in tracking the objective because the object must possess a communicating device and the limitation of the single cell size (approximate $100cm{\times}100cm$) exits. Also, the utilization of CCTV technologies show the shortcomings in tracking when the object disappear the area where the CCTV is not installed or illumination is not enough for capturing the scene (e.g. where the context-awarded system is not installed or low illumination presents). Therefore, in this paper we present an improved in-door tracking system based on sensor networks. Such system is built on a simulated scenario and enables us to detect and extend the area of surveillance as well as actively responding the emergency situation. Through simulated studies, we have demonstrated that the proposed system is capable of supplementing the shortcomings of signal cutting, and of estimating the location of the moving object. We expect the study will improve the better analysis of the intruder behavior, the more effective prevention and flexible response to various emergency situations.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1605-1613
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• 2020

The tidal channel is a coastal sedimentary terrain that plays the most important role in the formation and development of tidal flats, and is considered a very important index for understanding and distribution of tidal flat sedimentation/erosion terrain. The purpose of this study is to understand the changes in tidal channels by a period after the opening of the floodgate of the seawall in the reclaimed land of Sihwa Lake using KOMPSAT high-resolution multispectral satellite image data and to evaluate the applicability and efficiency of high-resolution satellite images. KOMPSAT 2 and 3 images were used for extraction of the tidal channels' lineaments in 2009, 2014, and 2019 and were applied to supervised classification method based on Principal Component Analysis (PCA), Artificial Neural Net (ANN), Matched Filtering (MF), and Spectral Angle Mapper (SAM) and band ratio techniques using Normalized Difference Water Index (NDWI) and MF/SAM. For verification, a numerical map of the National Geographic Information Service and Landsat 7 ETM+ image data were utilized. As a result, KOMPSAT data showed great agreement with the verification data compared to the Landsat 7 images for detecting a direction and distribution pattern of the tidal channels. However, it has been confirmed that there will be limitations in identifying the distribution of tidal channels' density and providing meaningful information related to the development of the sedimentary process. This research is expected to present the possibility of utilizing KOMPSAT image-based high-resolution remote exploration as a way of responding to domestic intertidal environmental issues, and to be used as basic research for providing multi-platform-image-based convergent thematic maps and topics.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.