• Journal of Korea Game Society
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• v.11 no.2
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• pp.57-68
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• 2011

This study approaches how newly emerged game companies has implemented strategies for product diversification according to market growth cycle(beginninggrowing-mature) by empirical case study through evolutionary theory and resource based theory approach. At the beginning, online game companies had grown with different strategies(technology based, service based) by initial condition(genre, technological level, user attribute). After market growth, for product diversification, these companies carried out path-dependent alliance strategy(complementary, competitive) depending on resource base(technology capacity, service capacity based). As online game market getting mature, these companies has adapted flexibly in responding to market growth cycle by integrated strategy(naturally selected to mobilize every possible resource capability). By analyzing the alliance strategies pattern of online game companies in newly emerged game industry according to market growth cycle through combination of resource based theory and evolutionary theory, these results suggest that new industrial, theoretical, policy model is required.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.25-33
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• 2019

This paper presents a novel evolutionary framework for optimizing a bio-inspired fully dynamic neurocontroller for the maneuverable flapping flight of a simulated bird-sized ornithopter robot which takes advantage of the morphological computation and mechansensory feedback to improve flight stability. In order to cope with the difficulty of generating robust flapping flight and its maneuver, the wing of robot is modelled as a series of sub-plates joined by passive torsional springs, which implements the simplified version of feathers attached to the forearm skeleton. The neural controller is designed to have a bilaterally symmetric structure which consists of two fully connected neural network modules receiving mirrored sensory inputs from a series of flight navigation sensors as well as feather mechanosensors to let them participate in pattern generation. The synergy of wing compliance and its sensory reflexes gives a possibility that the robot can feel and exploit aerodynamic forces on its wings to potentially contribute to the agility and stability during flight. The evolved robot exhibited target-following flight maneuver using asymmetric wing movements as well as its tail, showing robustness to external aerodynamic disturbances.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.461-472
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• 2007

The emphasis in genome projects has Been moving towards the sequence analysis in order to extract biological "meaning"(e.g., evolutionary history of particular molecules or their functions) from the sequence. Especially. palindromic or direct repeats that appear in a sequence have a biophysical meaning and the problem is to recognize interesting patterns and configurations of words(strings of characters) over complementary alphabets. In this paper, we propose an algorithm to identify variable length palindromic pairs(longer than a threshold), where we can allow gaps(distance between words). The algorithm is called palindrome algorithm(PA) and has O(N) time complexity. A palindromic pair consists of a hairpin structure. By composing collected palindromic pairs we build n-pair palindromic patterns. In addition, we dot some of the longest pairs in a circle to represent the structure of a DNA sequence. We run the algorithm over several selected genomes and the results of E.coli K12 are presented. There existed very long palindromic pair patterns in the genomes, which hardly occur in a random sequence.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.466-471
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• 2006

IAn important problem of pattern recognition is to extract or select feature set, which is included in the pre-processing stage. In order to extract feature set, Principal component analysis has been usually used and SFS(Sequential Forward Selection) and SBS(Sequential Backward Selection) have been used as a feature selection method. This paper applies genetic algorithm which is a popular method for nonlinear optimization problem to the feature selection problem. So, we call it Genetic Algorithm Feature Selection(GAFS) and this algorithm is compared to other methods in the performance aspect.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.193-206
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• 2008

Medical diagnosis can be considered a classification task which classifies disease types from patient's condition data represented by a set of pre-defined attributes. This study proposes a hybrid genetic algorithm based classification method to develop classifiers for multidimensional pattern classification problems related with medical decision making. The classification problem can be solved by identifying separation boundaries which distinguish the various classes in the data pattern. The proposed method fits a finite number of regional agents to the data pattern by combining genetic algorithms and local adaptive operations. The local adaptive operations of an agent include expansion, avoidance and relocation, one of which is performed according to the agent's fitness value. The classifier system has been tested with well-known medical data sets from the UCI machine learning database, showing superior performance to other methods such as the nearest neighbor, decision tree, and neural networks.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.531-536
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• 2002

In this paper, we have applied Genetic Algorithms(GAs) to Intrusion Detection System(TDS), and then proposed and simulated the misuse detection model firstly. We have implemented with the KBD contest data, and tried to simulated in the same environment. In the experiment, the set of record is regarded as a chromosome, and GAs are used to produce the intrusion patterns. That is, the intrusion rules are generated. We have concentrated on the simulation and analysis of classification among the Data Mining techniques and then the intrusion patterns are produced. The generated rules are represented by intrusion data and classified between abnormal and normal users. The different rules are generated separately from three models "Time Based Traffic Model", "Host Based Traffic Model", and "Content Model". The proposed system has generated the update and adaptive rules automatically and continuously on the misuse detection method which is difficult to update the rule generation. The generated rules are experimented on 430M test data and almost 94.3% of detection rate is shown.3% of detection rate is shown.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1239-1243
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• 2010

The web environment is evolving rapidly. Testing in the web based software is an essential process to improve stability and productivity. Testing of complex web contents and ill(user interface) is most important thing. Implemented test cases are efficient when they are automated and reusable. But, most of the testing automation tools are focused on technical accessibility and functions still. A collaboration of the persons concerned and reusability of implemented test case are ignored. In this paper we propose an efficient way to design automated test case in web environment, and to share and pattern automated test cases we introduce testing framework called NTAF(NHN Test Automation Framework.). The NTAF is based on open source framework. It provides integrated testing environment that web testing cane be automated and managed continuously.

• Proceedings of the Technology Innovation Conference
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• 2009.02a
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• pp.89-122
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• 2009

기술혁신 시스템이 추격형에서 선도형으로의 변환과정에 대해서는 일부 개념적 모형이나 탐색적 연구가 개념적으로만 제시되었을 뿐 체계적이고 구체적으로 연구가 부족하다. 한국이나 대만 등 동아시아 국가들의 선진국 기술추격과 탈추격형 혁신시스템으로 진화에 대한 국제적인 관심과 연구가 크게 증가하고 있지만, 대부분의 기존 연구들은 거시적인 관점에서 국가 차원의 제도 및 정책, 산학연의 연구역량과 협력체계, 외국기술의 도입 및 활용 등을 기술추격의 성공요인으로 들고 있을 뿐, 미시적인 관점에서 탈추격형 기술개발 성과의 사업화 추진 전략과 방법, 지원정책에 대한 구체적인 대안을 제시하지는 못하였다(Lee & Lim, 2001; Hobday et al., 2004; Kim, 1997). 추격형에서 선도형으로의 변환과정에 초점을 맞추어 특히 그 중요성이 대두되고 있는 사용자들의 혁신 과정에서의 역할에 대해 사례연구를 통해 규명하고자 한다. 선도적 혁신에서 제품 및 공정상에서 사용자혁신의 패턴을 밝혀내면, 이를 위한 제도적 인프라를 구축할 수 있다. 궁극적으로 선도적 혁신을 위한 기술혁신시스템에서 사용자로서의 기업과 선도사용자인 고객의 역할이 중요해지고 있음을 반영하고, 이를 바탕으로 기술혁신정책의 패러다임 전환을 위한 시사점을 개진하고자 한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.492-499
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• 2016

Null pattern synthesis method using the Quantum-inspired Evolutionary Algorithm(QEA) is described in this study. A $12{\times}12$ planar array antenna is considered and each element of the array antenna is controlled by 6-bit phase shifter. The maximum number of iteration of 500 is used in simulation and the rotation angle for updating Q-bit individuals is determined to make the individual converge to the best solution and is summarized in a look-up table. In this study we showed that QEA can satisfactorily synthesize the null pattern using smaller number of individuals compared with the conventional Genetic Algorithm.

• Annual Conference of KIPS
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• 2017.11a
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• pp.118-120
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• 2017

모바일 이동통신망의 Core 노드들은 2G CDMA, 3G WCDMA, 4G LTE 교환기를 비롯하여 IMS 및 다양한 부가장비들로 이루어져 있다. 최근 5G로 진화하는 과정에는 NFV(Network Function Virtualization)가 그 중심에 서 있다. NFV 환경에서는 기존 통신 노드와 다르게 범용서버 및 범용 운영체제가 주축이 되어, 일반 IT 툴로도 통신망 내부 노드의 로그분석이 용이해 졌다. 또한 다양하고 복잡한 Core 네트워크에서 빅데이터로 발생하는 로그 또한 머신러닝으로 분석이 가능하며, 운용에 활용할 수 있다. 따라서 본 연구에서는 vDPI, vMMSGW OS 로그를 대상으로 분석하였으며, 잠재되어 있는 문제점들을 확인할 수 있었다. 또한 어플리케이션의 비정형화 된 로그에서도 비정상적인 패턴들을 발견하여 대용량 트래픽이 발생하며 SLA가 유난히 높은 통신환경에서도 비지도 머신러닝 분석이 유용함을 확인하였다.