• Korean Journal of Logic
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• v.12 no.1
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• pp.89-110
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• 2009

This paper investigates generalizations of weakening-free uninorm logics not assuming associativity of intensional conjunction (so called fusion) &, as non-associative fuzzy-relevance logics. First, the strong t-associative monoidal uninorm logic StAMUL and its schematic extensions are introduced as non-associative propositional fuzzy-relevance logics. (Non-associativity here means that, differently from classical logic, & is no longer associative.) Then the algebraic structures corresponding to the systems are defined, and algebraic completeness results for them are provided. Next, predicate calculi corresponding to the propositional systems introduced here are considered.

• Korean Journal of Logic
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• v.10 no.2
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• pp.125-146
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• 2007

This paper investigates the relevance system R-mingle (RM) as a a fuzzy-relevance logic. It shows that RM is fuzzy in Cintula's sense, i.e., RM is complete with respect to linearly ordered L-matrices (or L-algebras). More exactly, we first introduce RM and its weak versions wwRM and wRM. We next provide algebraic and matrix completeness results for them.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2785-2792
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• 2011

Such problems as delay, congestion, and crosstalk in the proxy system degrade not only QoS (Quality of Service) but responsiveness and reliability of the streaming media service. To solve this problem this paper proposed a FRTP (Fuzzy Relevance-based Transcoding Proxy) mechanism. The proposed FRTP mechanism analyzes fuzzy similarity for partitioned segment versions of media objects to create a FRTG (Fuzzy Relevance-based Transcoding Graph). Created FRTG determines the transcoding for partitioned media object segment versions. Determined transcoding improves DSR (Delay Saving Ratios), CHPR (Cache Hit Precision Ratio), and CHRR (Cache Hit Recall Ratio). The proposed mechanism is simulated to evaluate such performance parameters as DSR, CHPR, and CHRR. Simulation results shows that the proposed mechanism outperforms in DSR, CHPR and CHRR compared with the other existing mechanisms.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.89-96
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• 2000

Relevance feedback is a technique to learn the user's subjective perception of similarity between images, and has recently gained attention in Content Based Image Retrieval. Most relevance feedback methods assume that the individual features that are used in similarity judgments do not interact with each other. However, this assumption severely limits the types of similarity judgments that can be modeled In this paper, we explore a more sophisticated model for similarity judgments based on fuzzy measures and the Choquet Integral, and propose a suitable algorithm for relevance feedback, Experimental results show that the proposed method is preferable to traditional weighted- average techniques.

• Korean Journal of Logic
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• v.11 no.1
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• pp.131-156
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• 2008

This paper first investigates several uninorm logics (introduced by Metcalfe and Montagna in [8]) as fuzzy-relevance logics. We first show that the uninorm logic UL and its extensions IUL, UML, and IUML are fuzzy-relevant; fuzzy in Cintula's sense, i.e., the logic L is complete with respect to linearly ordered L-matrices; and relevant in the weak sense that ${\Phi}{\rightarrow}{\Psi}$ is a theorem only if either (i) $\Phi$ and $\Psi$ share a sentential variable or constant, or (ii) both $\sim\Phi$ and $\Psi$ are theorems. We next expand these systems to those with $\triangle$.

• Journal of Advanced Navigation Technology
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• v.14 no.4
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• pp.495-503
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• 2010

The clustering is an important mechanism thai provides information for mobile nodes efficiently and improves the processing capacity for routing and the allocation of bandwidth. This paper proposes a clustering scheme based on the fuzzy relevance degree to solve problems such as node distribution found in the dynamic property due to mobility and flat structure and to enhance the routing performance. The proposed scheme uses the fuzzy relevance degree, ${\alpha}$, to select the cluster head for clustering in FSV (Fuzzy State Viewing) structure. The fuzzy relevance ${\alpha}$ plays the role in CH selection that processes the clustering in FSV. The proposed clustering scheme is used to solve problems found in existing 1-hop and 2-hop clustering schemes. NS-2 simulator is used to verify the performance of the proposed scheme by simulation. In the simulation the proposed scheme is compared with schemes such as Lowest-ID, MOBIC, and SCA. The simulation result showed that the proposed scheme has better performance than the other existing compared schemes.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.238-240
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• 2002

If there is an Information Retrieval system which comprehends the semantic content of documents and knows the preference of users. the system can search the information better on the Internet, or improve the IR performance. Therefore we propose the IR model which combines semantic based indexing and fuzzy relevance model. In addition to the statistical approach, we chose the semantic approach in indexing, lexical chains, because we assume it would improve the performance of the index term extraction. Furthermore, we combined the semantic based indexing with the fuzzy model, which finds out the exact relevance of the user preference and index terms. The proposed system works as follows: First, the presented system indexes documents by the efficient index term extraction method using lexical chains. And then, if a user tends to retrieve the information from the indexed document collection, the extended IR model calculates and ranks the relevance of user query. user preference and index terms by some metrics. When we experimented each module, semantic based indexing and extended fuzzy model. it gave noticeable results. The combination of these modules is expected to improve the information retrieval performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.424-431
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• 2012

In information retrieval, search engine provide the rank of web page and the summary of the web page information to user. Snippet is a summaries information of representing web pages. Visiting the web page by the user is affected by the snippet. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy implication operator and relevance feedback. The proposed method uses relevance feedback to expand the use's query. The method uses the fuzzy implication operator between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.543-550
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• 2008

There exist many QoS problems such as delay and jitter for mobile streaming due to limited bandwidth. This paper proposed a transaction update method based on Fuzzy chunk to solve the problems. The proposed method updated a transaction, which is classified as a read or an update, using Fuzzy filtering. A chunk block is rearranged according to the fuzziness which is classified as better relevance for fuzziness greater than 0.8, relevance for fuzziness between 0.5 and 0.7, and less irrelevance for fuzziness less than 0.5. According to the simulation result for the rearranged chunk block, the proposed method has better performance than those of RBM(Randon Based method), DBM(Distance Based Method), and FBM(Frequency Based Method).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1684-1690
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• 2003

In this paper, we proposed a fuzzy controller for the evaluation of the quantization Parameters in the H.263 coder to optimize the subjective quality of each coded frame, keeping the transmission rate constant. We adopted the Mamdani method for fuzzification and the centroid method for defuzzification. The energy and entropy are correlated to features of the HVS in spatial domain, while motion vectors are used to estimate the temporal characteristics of the signal. And then, the fuzzy inputs adapted the variance and the entropy in spatial domain, and the motion vector in temporal domain. We induced the fuzzy membership function and decided the fuzzy relevance to be compatible in visual characteristics. And then, we designed FAM banks. The fuzzy technology has been applied to a practical video compression. This results is obtained an effective rate control technique, an optimum bit allocation and a high subjective quality using fuzzy quantization.