• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.27-37
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• 2011

The IDS/IPS(Intrusion Detection/Prevention System) has been widely deployed to protect the internal network against internet attacks. Reducing the packet inspection time is one of the most important challenges of improving the performance of the IDS/IPS. Since the IDS/IPS needs to match multiple patterns for the incoming traffic, we may have to apply the multiple pattern matching schemes, some of which use finite automata, while the others use the shift table. In this paper, we first show that the performance of those schemes would degrade with various kinds of pattern sets and payload, and then propose a hybrid multiple pattern matching scheme which combines those two schemes. The proposed scheme is organized to guarantee an appropriate level of performance in any cases. The experimental results using real traffic show that the time required to do multiple pattern matching could be reduced effectively.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.63-72
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• 2010

In the future warfare, the importance of the counter-fire operation is increasing. The counter-fire operation is divided into offensive counter-fire operation and defensive counter-fire operation. Reviewing the researches done so far, the detection asset of offensive counter-fire operation called UAV(Unmanned Aerial Vehicle) and its operational effectiveness analysis is continually progressing. However, the analysis of the detection asset of defensive counterfire called Target Acquisition Radar(TAR) and its quantitative operational effectiveness are not studied yet. Therefore, in this paper, we studied operational effectiveness of TAR using C2 Theory & MANA Simulation model, and showed clear quantitative analysis results by comparing both cases of using TAR and not using TAR.

• Journal of the Korean Geographical Society
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• v.47 no.4
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• pp.606-624
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• 2012

The main objective of this paper is to provide an adequate and comprehensive review of what has been done in South Korea in the field of geospatial analysis and modeling. This review focuses on spatial data analysis and spatial statistics, spatial optimization, and geosimulation among various aspects of the field. It is recognized that geospatial analysis and modeling in South Korea got through the initial stage during the 1990s when computer and analytical cartography and GIS were introduced, moved to the growth stage during the first decade of the $21^{st}$ century when there was a surge of relevant researches, and now is heading for its maturity stage. In spatial data analysis and spatial statistics, various topics have been addressed for spatial point pattern data, areal data, geostatistical data, and spatial interaction data. In spatial optimization, modeling and applications related to facility location problems, districting problems, and routing problems have been mostly researched. Finally, in geosimulation, while most of research has focused on cellular automata, studies on agent-based model and simulation are in beginning stage. Among all these works, some have fostered methodological advances beyond simple applications of the standard techniques.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.178-185
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• 2013

Forest fires are expected to increase in severity and frequency under global climate change and thus better understanding of fire dynamics is critical for mitigation and adaptation. Researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed various simulation models to reproduce forest fire spread dynamics. However, these models have limitations in the fire spreading because of the complicated factors such as fuel types, wind, and moisture. In this study, we suggested a simple model considering the wind effect and two different fuel types. The two fuels correspond to susceptible tree and resistant tree with different probabilities of transferring fire. The trees were randomly distributed in simulation space with a density ranging from 0.0 (low) to 1.0 (high). The susceptible tree had higher value of the probability than the resistant tree. Based on the number of burnt trees, we then carried out the sensitivity analysis to quantify how the forest fire patterns are affected by wind and tree density. The statistical analysis showed that the total tree density had greatest effect on the forest fire spreading and wind had the next greatest effect. The density of the susceptible tree was relatively lower factor affecting the forest fire. We believe that our model can be a useful tool to explore forest fire spreading patterns.

• Cartoon and Animation Studies
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• s.33
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• pp.55-78
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• 2013

The issues on the representation of digital images, the uncanny is not considered aesthetically but must be overcome. It seems that the future of visual media using digital images, depends on the development and advancement of the digital technology. However, the Brothers Quay regarded as unique and experimental animators, focus their attention towards the past rather than the future. They trace back to the origin of the media, reproducing, manipulating, and representing gestures in oder to restore the shock and thrill delivered in film and animation. The Brothers Quay explore the uncanny of gestures through the mechanism of medium. They work in a wide range of genres, from animation, live action to dance film. The creaking spasms, which create the feeling that the movement does not belong to this world, and the strange gestures, reveals the flicker of the still projection and make audiences recognize gestures in the true meaning of the word. While they animate live actors and dead objects like automata, the hidden desires are revealed over screen. In this paper, focusing on the works of Brothers Quay, I tried to explore the uncanny of gesture based on Freud's and Jentsch' theory of uncanny.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1999-2007
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• 2013

The key characteristics of two-lane-and-two-way traffic flow are platoon and overtaking caused by low-speed vehicle such as truck. In order to develop two-way traffic flow model comprised of CF(car-following) and overtaking model, it is essential to develop a car-following model which is suitable to two-way traffic flow. Short distance between vehicles is caused when a high-speed vehicle tailgates and overtakes foregoing low-speed vehicle on two-way road system. And a vehicle following low-speed vehicle decides to overtake the front low-speed vehicle using suitable space within the headway distribution of opposite traffic flow. For this reason, a two-way CF model should describes not only running within short gap but also headway distribution. Additionally considering domestic two-way-road size, there is a on-going need for large-network simulation, but there are few studies for two-way CF model. In this paper, a two-way CA model is developed, which explains two-way CF behavior more realistic and can be applied for large road network. The experimental results show that the developed model mimics stop-and-go phenomenon, one of features of congested traffic flow, and efficiently generates the distribution of headway. When the CF model is integrated with overtaking model, it is, therefore, expected that two-way traffic flow can be explained more realistically than before.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.669-680
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• 2001

Genetic Algorithms are optimization algorithm that mimics biological evolution to solve optimization problems. Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex fitness landscapes. Hybrid genetic algorithm that is combined with local search called learning can sustain the balance between exploration and exploitation. The genetic traits that each individual in the population learns through evolution are transferred back to the next generation, and when this learning is combined with genetic algorithm we can expect the improvement of the search speed. This paper proposes a genetic algorithm based Cellular Learning with accelerated learning capability for function optimization. Proposed Cellular Learning strategy is based on periodic and convergent behaviors in cellular automata, and on the theory of transmitting to offspring the knowledge and experience that organisms acquire in their lifetime. We compared the search efficiency of Cellular Learning strategy with those of Lamarckian and Baldwin Effect in hybrid genetic algorithm. We showed that the local improvement by cellular learning could enhance the global performance higher by evaluating their performance through the experiment of various test bed functions and also showed that proposed learning strategy could find out the better global optima than conventional method.

• Cartoon and Animation Studies
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• s.34
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• pp.129-165
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• 2014

K-pop performances are in the center of the contemporary popular arts and cultural industry, and implicitly reveal the way that our society views the body and the time-space. This paper explores the motif of automaton in the K-pop idol group ShiNee's stage performance of 'Everybody' and the song's music video. At the same time, the paper relates the motif with the automaton of the digital era-that is, the sense of time-space in digital animations. The motif of the automaton has its origins in the mythical forms related to the animation, and is related to the human desire to create humanlike forms. Also, this motif is closely linked to the aesthetical meaning of the animation, being played in different variations since the beginning of the animation. This paper explores the tradition of automaton motif in culture and the arts, and look into the cases in which the history of the relationship between the media and body performance harboring the automaton motif has been displayed in 19th century ballet or modern body expressional arts. In addition, this paper will compare and analyze representative contemporary works that reveal digital viewpoint and the choreography of 'Everybody', and compare other works that stand in similar aesthetic tradition, investigating the influence of digital animation reflected in the K-pop idol and its aesthetic and social undertones.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.147-154
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• 2018

Natural language processing (NLP) is an emerging research area in which we study how machines can be used to perceive and alter the text written in natural languages. We can perform different tasks on natural languages by analyzing them through various annotational tasks like parsing, chunking, part-of-speech tagging and lexical analysis etc. These annotational tasks depend on morphological structure of a particular natural language. The focus of this work is part-of-speech tagging (POS tagging) on Hindi language. Part-of-speech tagging also known as grammatical tagging is a process of assigning different grammatical categories to each word of a given text. These grammatical categories can be noun, verb, time, date, number etc. Hindi is the most widely used and official language of India. It is also among the top five most spoken languages of the world. For English and other languages, a diverse range of POS taggers are available, but these POS taggers can not be applied on the Hindi language as Hindi is one of the most morphologically rich language. Furthermore there is a significant difference between the morphological structures of these languages. Thus in this work, a POS tagger system is presented for the Hindi language. For Hindi POS tagging a hybrid approach is presented in this paper which combines "Probability-based and Rule-based" approaches. For known word tagging a Unigram model of probability class is used, whereas for tagging unknown words various lexical and contextual features are used. Various finite state machine automata are constructed for demonstrating different rules and then regular expressions are used to implement these rules. A tagset is also prepared for this task, which contains 29 standard part-of-speech tags. The tagset also includes two unique tags, i.e., date tag and time tag. These date and time tags support all possible formats. Regular expressions are used to implement all pattern based tags like time, date, number and special symbols. The aim of the presented approach is to increase the correctness of an automatic Hindi POS tagging while bounding the requirement of a large human-made corpus. This hybrid approach uses a probability-based model to increase automatic tagging and a rule-based model to bound the requirement of an already trained corpus. This approach is based on very small labeled training set (around 9,000 words) and yields 96.54% of best precision and 95.08% of average precision. The approach also yields best accuracy of 91.39% and an average accuracy of 88.15%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.88-95
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• 2009

This paper presents a traffic pattern matching hardware that can be used in high performance network applications. The presented hardware is designed for a contents security system which is to block various kinds of information drain or intrusion activities. The hardware consists of two parts: the header lookup and string pattern matching parts. For implementing the header lookup part in hardware, the TCAMs(ternary CAMs) are popularly used. Since the TCAM approach is inefficient in terms of the hardware and memory costs and the power consumption, however, we adopt and modify an alternative approach based on the comparator arrays and the HiCuts tree. Our implementation results, using Xilinx FPGA XC4VSX55, show that our design can reduce the usage of the FPGA slices by about 26%, and the Block RAM by about 58%. In the design of string pattern matching part, we design and use a hashing module based on cellular automata, which is hardware efficient and consumes less power by adaptively changing its configuration to reduce the collision rates.