• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3386-3411
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• 2019

Secured and reliable routing is a crucial factor for improving the performance of Wireless Mesh Networks (WMN) since these networks are susceptible to many types of attacks. The existing assumption about the internal nodes in wireless mesh networks is that they cooperate well during the forwarding of packets all the time. However, it is not always true due to the presence of malicious and mistrustful nodes. Hence, it is essential to establish a secure, reliable and stable route between a source node and a destination node in WMN. In this paper, a trust based secure routing algorithm is proposed for enhancing security and reliability of WMN, which contains cross layer and subject logic based reliable reputation scheme with security tag model for providing effective secured routing. This model uses only the trusted nodes with the forwarding reliability of data transmission and it isolates the malicious nodes from the providing path. Moreover, every node in this model is assigned with a security tag that is used for efficient authentication. Thus, by combining authentication, trust and subject logic, the proposed approach is capable of choosing the trusted nodes effectively to participate in forwarding the packets of trustful peer nodes successfully. The simulation results obtained from this work show that the proposed routing protocol provides optimal network performance in terms of security and packet delivery ratio.

• Journal of National Security and Military Science
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• s.8
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• pp.271-309
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• 2010

The main theme of this study is about North Korea's contemporary military strategy which remained a blind spot in the 21st century. Indeed, Pyongyang's contemporary military strategy is evolved from the logic of War. On the basis of this logic, this study examined North Korea's contemporary military strategy with three analytical frameworks. The first is the discovery of Clausewitz's dictums and application of the Trinitarian analysis on the Korean cases. During the course of applying Clausewitzian main dictum--War as continuation of politics, the methodological analysis on war played a important role generalizing the pattern and matrix of North Korea's strategic thinking and military strategy. In particular, Clausewitz's Trinitarian framework on war -Government (reason), Army (chance), People (passion)- was a universal framework to scrutinize the North Korean missile and nuclear strategy. The second is about the matrix of North Korea's military strategy, The study suggested the genealogical feature of Pyongyang's military strategy. In principle, the dictum of 'Military-First Politics' 1S the combination of the political philosophy, Chuch'e (self-reliance) of Kim Il Sung and Kin Jong Il reflected in the military readiness. As a result this analysis was able to equate Clausewitz's dictums to explain Pyongyang's idea of the nature of war in that North Korea's military strategy is the central instrument of delivery to achieve political objectives. The third is about the theoretical encounter of 'Clausewitz's Wonderful Trinity' and 'Remarkable Trinity on North Korea's contemporary strategy'. On the basis, three elements are connected to one of three groups in society; the people, the military, and the government. In order to apply the Clausewitz's Trinitarian analysis into Kim Jong Il's 'Military-First' strategy, two case studies (Missile and Nuclear strategy) were examined. The finding of this study is that Clausewitzian dictum in the 19th century is still valid in the 21st century as it provided plausible theoretical framework to explain the North Korean contemporary military strategy with a reminder that the nature and logic of war are fixed in the socially constructed state.

• The Journal of Korean Philosophical History
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• no.52
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• pp.37-67
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• 2017

This article is to examine the characteristics of Habin Sin Hu-Dam's method of interpreting Zhouyi and to review its position in Zhouyi history of Joseon Dynasty. Especially, there has been drown attention to the connection both Habin and Tasan Cheong Yagyong. Habin is a philosopher who consistently interprets Zhouyi through the inner logic of it, not through Neo-confucian framework of it. The inner logic is yaobian theory, which is found through investigating the auguries in the old Books of Confucianism. It could be said that this discovery is the Habin's original one, although there may be historically connections between him and Seong-Ho School in the interpreting methodology about Zhouyi. However, at a future date this logic is found in Tasan. There are no connections between two philosophers, but it may be said that they arrive at the common method of interpreting Zhouyi through investigating the auguries in the old Books of Confucianism. We find that their common methods of interpreting Zhouyi do not keep to authoritative interpretation, but there is the passion of searching for Zhouyi the way as it is.

• The Mathematical Education
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• v.41 no.3
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• pp.329-339
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• 2002

This study analyzes the epistemological meaning of‘social construction’in mathematical instruction. The perspective that consider the cognition of mathematical concept as a social construction is explained by a cyclic scheme of an academic context and a school context. Both of the contexts require a public procedure, social conversation. However, there is a considerable difference that in the academic context it is Lakatos' ‘logic of mathematical discovery’In the school context, it is Vygotsky's‘instructional and learning interaction’. In the situation of mathematics education, the‘society’which has an influence on learner's cognition does not only mean‘collective members’, but‘form of life’which is constituted by the activity with purposes, language, discourse, etc. Teachers have to play a central role that guide and coordinate the educational process involving interactions with learners in this context. We can get useful suggestions to mathematics education through this consideration of the social contexts and levels to form didactical situations of mathematics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.119-124
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• 2004

Real data as web log file tend to be incomplete. But we have to find useful knowledge from these for optimal decision. In web log data, many useful things which are hyperlink information and web usages of connected users may be found. The size of web data is too huge to use for effective knowledge discovery. To make matters worse, they are very sparse. We overcome this sparse problem using Markov Chain Monte Carlo method as multiple imputations. This missing value imputation changes spare web data to complete. Our study may be a useful tool for discovering knowledge from data set with sparseness. The more sparseness of data in increased, the better performance of MCMC imputation is good. We verified our work by experiments using UCI machine learning repository data.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.894-897
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• 2014

The speed of processes and the extremely large amount of data to be used in Intelligence Transportations System (ITS) cannot be handling by humans without considerable automation. However, it is difficult to develop software with conventional fixed algorithms (hard-wired logic on decision making level) for effectively manipulate dynamically evolving real time transportation environment. This situation can be resolved by applying methods of artificial intelligence and data mining that provide flexibility and learning capability. This paper presents a brief introduction of data mining and artificial intelligence (AI) applications in Intelligence Transportation System (ITS), analyzing the prospects of enhancing the capabilities by means of knowledge discovery and accumulating intelligence to support in decision making.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.6
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• pp.199-212
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• 2014

Recently, there are increasing to the interest in the organizational innovation DNA as the innovation origin and these interest mainly were approached through the case analysis of global innovative companies. The purpose of study is to investigate the applicability under the CEO of SMEs settings as global companies' cases. The research focused on the impact of innovator's DNA on innovative strategy by the empirical study that analyzed from 110 firm's data in Daegu and Gyeongbuk region. The results of empirical study, innovator's DNA has positive effects on the overall innovative strategy, especially the effects of discovery DNA are stronger than operational DNA. Included to the discovery DNA effects, operational DNA bring about negative on the product differentiation, though it has positive on the market differentiation. In terms of components of innovator's DNA, the questioning and association have strong impacts on the overall innovative strategy, and analyzing has positive on market differentiation, but specific task implementation has negative on the product differentiation. The results suggest that the logic of global innovation case is possible to the SME's CEO and need to learning efforts to promote discovery DNA for successful innovation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.223-226
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• 2007

지식 발견 (knowledge discovery)의 관점에서, 단기간 동안 취득된 데이터 패턴을 학습하고자 하는 경우 데이터에 비일관적인(inconsistent) 패턴이 포함되어 있다면 확률적 퍼지 룰(probabilistic fuzzy rule) 기반의 지식 표현 방법 및 적절한 학습 알고리즘을 이용하여 효과적으로 다룰 수 있다. 하지만 장기간 동안 지속적으로 얻어진 데이터 패턴을 다루고자 하는 경우, 데이터가 시변(time-varying) 특성을 가지고 있으면 기존에 추출된 지식을 변화된 데이터에 활용하기 어렵게 된다. 때문에 이러한 데이터를 다루는 학습 시스템에는 패턴의 변화에 맞추어 갈 수 있는 지속적인 적응력(adaptivity)이 요구된다. 본 논문에서는 이러한 적응성의 측면을 고려하여 평생 학습(life-long learning)의 관점 에 서 확률적 퍼지 룰 기반의 학습 시스템에 적용될 수 있는 두 가지 형태의 적응 방법에 대해서 설명하도록 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.390-395
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• 2004

A semiconductor manufacturing process is the complicate and dynamic process, and consists of many sub-processes. An etching process is the most important process in the semiconductor fabrication. In this paper, the decision support system based upon data mining and knowledge discovery is an important factor to improve the productivity and yield. The proposed decision support system consists of a neural network model and an inference system based on fuzzy logic Firstly, the product results are predicted by the neural network model constructed by the product patterns that represent the quality of the etching process. And the product patters are classified by expert's knowledge. Finally, the product conditions are estimated by the fuzzy inference system using the rules extracted from the classified patterns. Prediction of product qualities can be linked to each input and process variables. We employ data mining and intelligent techniques to find the best condition of the etching process. The proposed decision support system is efficient and easy to be implemented for the process management based upon expert's knowledge.