• Korean Journal of Cognitive Science
• /
• v.15 no.4
• /
• pp.15-20
• /
• 2004

To develop a cognitive system with the flexibility and breadth of human, it's very important to construct a large scale knowledge base which include commonsense knowledge as well as expert knowledge. Efficient knowledge representation and reasoning techniques will play a key role for this. This paper introduce a cognitive system which is based on Cyc knowledge base and augmented with our work on qualitative and spatial representation and reasoning. Our system has been implemented and tested on various examples.

• Korean Journal of Cognitive Science
• /
• v.7 no.4
• /
• pp.203-216
• /
• 1996

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.05a
• /
• pp.247-250
• /
• 2003

Due to the increasing use of very large databases, mining useful information and implicit knowledge from databases is evolving. However, most conventional data mining algorithms identify the relationship among features using binary values (TRUE/FALSE or 0/1) and find simple If-THEN rules at a single concept level. Therefore, implicit knowledge and causal relationships among features are commonly seen in real-world database and applications. In this paper, we thus introduce the mechanism of mining fuzzy association rules and constructing causal knowledge base form database. Acausal knowledge base construction algorithm based on Fuzzy Cognitive Map(FCM) and Srikant and Agrawal's association rule extraction method were proposed for extracting implicit causal knowledge from database. Fuzzy association rules are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. It integrates fuzzy set concept and causal knowledge-based data mining technologies to achieve this purpose. The proposed mechanism consists of three phases: First, adaptation of the fuzzy membership function to the database. Second, extraction of the fuzzy association rules using fuzzy input values. Third, building the causal knowledge base. A credit example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstration the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.14 no.5
• /
• pp.833-841
• /
• 2011

In this paper, we propose uncoordinated dynamic frequency(channel) allocation schemes based on cognitive radio in mobile cellular networks(MCNs). Under the assumptions that mobile base stations are equipped with cognitive radio(CR) function and they construct uncoordinated network, the proposed scheme enables the MCNs by suppression of successive channel switching and management of channel allocation in a dynamic and distributed manner. The proposed scheme is composed of two phase processes. In the first phase, highly orthogonal sequences are generated and assigned to mobile base stations. In the second phase, each mobile base station is allocated a channel according to the pre-assigned orthogonal sequences. Simulation results show that the number of successive spectrum switching is reduced significantly compared with the random switching scheme.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.315-320
• /
• 1997

Rule minimization technique adapted from rough set theory was applied to remove redundant knowledge which is not necessary to make a knowledge base. New algorithm to diagnose fault using Improved Fuzzy Cognitive Maps(I-FCMs), and Fuzzy Associative Memory(FAM) is proposed. I-FCM[22] is superior to gathering knowledge from many experts and descries dynamic behaviors of systems very well. I-FCM is not only a knowledge base, but also a inference engine. FAM has learning capability like neural network[12]. Rule minimization and composition of I-FCM and FAM make it possible to construct compact knowledge base and breaks the border between inference engine and knowledge base.

• Journal of the Korean School Mathematics Society
• /
• v.17 no.2
• /
• pp.167-191
• /
• 2014

In this study, we investigate the term-sets of 'base' or 'bottom': 'the bottom side of a polygon' and 'the base side (of a geometrical figure)'. And we study the concept of 'the base area' in the solid figures and the formula of 'the bottom dimensions'. We start from the 6th grade math problem: 'Find the bottom dimension of the rectangular.' The primary answer is that it does not use the term('the bottom dimensions') in the elementary mathematics. However, in the middle school mathematics, 'the base area' is used as means of 'the area of one bottom side', which is not explained anywhere from the elementary mathematics to middle school mathematics. In addition, the base is defined and 'the surface area' and 'the side area' is taught in the elementary mathematics, so we naturally think of 'the base area'. Therefore we first investigate the term-sets of 'base' or 'bottom' which has two elements: 'the bottom side of a polygon' and 'the base side (of a geometrical figure)'. Next we discuss 'the base area' through curriculum and textbooks, dictionary definitions and so on. In addition, we survey pre-service teachers and teachers about the solid figures and analyse the understanding of 'the base side' and 'the base area' comparatively. In particular, we compare the changes and the tendency of correct answers from the first question to the last question. As a result, we verify 'the cognitive gap' between the elementary mathematics and the middle school mathematics, we suggest the teaching of 'the base area' and succession subjects to teach figure domain in the elementary mathematics.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.4
• /
• pp.613-631
• /
• 2013

Cognitive radio (CR) is proposed as a key solution to improve spectral efficiency and overcome the spectrum scarcity. Spectrum sensing is an important task in each CR system with the aim of identifying the spectrum holes and using them for secondary user's (SU) communications. Several conventional methods for spectrum sensing have been proposed such as energy detection, matched filter detection, etc. However, the main limitation of these classical methods is that the CR network is not able to communicate with its own base station during the spectrum sensing period and thus a fraction of the available primary frame cannot be exploited for data transmission. The other limitation in conventional methods is that the SU data frames should be synchronized with the primary network data frames. To overcome the above limitations, here, we propose a spectrum sensing technique based on blind source separation (BSS) that does not need time synchronization between the primary network and the CR. Moreover, by using the proposed technique, the SU can maintain its transmission with the base station even during spectrum sensing and thus higher rates are achieved by the CR network. Simulation results indicate that the proposed method outperforms the accuracy of conventional BSS-based spectrum sensing techniques.

• Korean Journal of Cognitive Science
• /
• v.16 no.3
• /
• pp.213-224
• /
• 2005

To develop a cognitive system with the flexibility and breadth of human reasoning, it's very important to construct a large scale knowledge base which includes commonsense knowledge as well as expert knowledge. This paper introduces a cognitive system which provides a commonsense reasoning for everyday physical phenomena using qualitative reasoning. It is difficult to apply previous qualitative reasoning to commonsense reasoning since it provides reasoning based on abstract concepts which are apart from everyday real world concepts. Our research provides commonsense reasoning based on sketches and real world concepts by integrating qualitative reasoning and general large scale Cyc knowledge base. Our system has been implemented and tested on various examples.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.10
• /
• pp.1236-1239
• /
• 2016

In this paper, we propose a new incentive mechanism for hybrid access in cognitive femtocell networks. The purpose of the proposed incentive mechanism is to guarantee the QoS of macro user equipments (MUEs) and to increase femtocell capacity. MUEs channel condition report triggers bidding procedure by neighbor femtocell base stations (FBS). Macro base station (MBS) can offer some subchannels as rewards to encourage FBSs to reliably support its MUEs. Simulation results validate the effectiveness of our proposed scheme.

• Cross-Cultural Studies
• /
• v.19
• /
• pp.295-311
• /
• 2010

The concept of frame in semantics has implications for our understanding of such problematic terms as "meaning" and "concept". It is conventional to say that a particular word corresponds to a particular "concept" and to assume that concepts are essentially identical across speakers. In contrast, the notion of frame accepts that the frame for a particular word can vary across speakers as a function of their particular life experience. To say, instead of thinking in terms of words as expressing "concepts", we should think of them as tools, like frames, that cause listeners to activate certain areas of their knowledge base, with different areas activated to different degrees in different contexts of use. This notion is Fillmore's most crucial contribution to current cognitive linguistic theories, and his frame semantics is built on such a notion. This paper discusses the basic assumptions and goals of frame semantics, and examines the notion of frame and illustrates various framing words of English and Korean under such a notion.