• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2089-2090
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• 2006

본 논문은 기호 코딩 및 정보입자를 이용한 유전자 알고리즘의 전방향 퍼지 집합 기반 뉴럴네트워크 (Information Granules and Symbolic Encoding-based Fuzzy Set Polynomial Neural Networks ; IG and SE based FSPNN)의 모델 설계를 제안한다. 기존 퍼지 집합기반 다항식 뉴럴네트워크(FSPNN)의 구조 최적화를 위해 이진코딩을 사용하였다. 그러나 이진코딩에서 스트링의 길이가 길면 길수록 인접한 두 수 사이에 발생하는 급격한 비트 차이라는 해밍절벽이 발생하였다. 이에 제안된 모델에서는 해밍절벽의 문제를 해결하기 위해 기호코딩을 사용하였다. 제안된 모델은 각 입력에 대해 MFs의 개수 만큼 규칙을 생성하는 Fuzzy 집합기반 다항식 뉴럴네트워크(FSPNN)를 그대로 사용한다. 그리고 IG based gFSPNN의 평가을 위해 실험적 예제를 통하여 제안된 모델의 성능 및 근사화 능력의 우수함을 보인다.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.33 no.2
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• pp.148-152
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• 2000

To provide basic information on the integumentary system of the blenny, Pholis nebulosa, ultrastructures of epidermal and dermal layer were examined by means of the light and transmission electron microscope. The skin of the blenny consisted of epidermal and dermal layer. Epidermal layer consisted of supporting cell and unicellular gland. The supporting cells were classified into superficial cell, intermediated cell and basal cell, and the gland cells were classified into mucous secretory cell and club cell. The cytoplasm of supporting cells was divided into cortex and medullar part. In the cortex and medullar part, microfilaments and cell organelles were well developed, respectively. Superficial cell of epidermal layer was cuboidal and contained nucleus of horseshoe shape. Intermediated cell had a nucleus of irregular form and the electron density was higher than the other supporting cells, Basal cell was columnar, but nucleus was situated in the upper cytoplasm. Cell organelles of the basal cell were poor than the other supporting cells, but membrane interdigitations were well developed. The cytoplasm of mucous secretory cell had a well-developed ovoid secretory granules, which reacted to red with AB-PAS reaction. The club cell had a we31-developed round secretory granules and endoplasmic reticulum. figment cells were classified into two type. The one contained pigment granules of electron dense, and the other contained reflecting platelets. The cytoplasm of fibrocyte had n well developed rough endoplasmic reticulum.

• The Korean Journal of Malacology
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• v.28 no.4
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• pp.321-328
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• 2012

Light and transmission electron microscopy of Batillus cornutus hemocytes revealed differences that the morphological distinctions between blast-like cell, granulocytes and hyalinocytes. Base on the morphological characteristics of the cells, we identified the eight types of hemocytes and present a categorization of the hyalinocytes into six sub-categories. The hemocytes of B. cornutus were observed basophilic cell under the light microscopy. Blast-like cells had a spherical profile with a central nucleus filling almost the whole cell. Granulocytes were characterized by presenting variable numbers of granules. This cell had spherical shape with diameter 7 ${\mu}m$ and smooth endoplasmic reticula, granules, mitochondria, glycogen granules in the cytoplasm. Hyalinocytes were the most abundant cell type. Especially, hyalinocyte VI had iirregular an amoebal shape and observed autophagosome and heterophagosome in the cytoplasm. From these results, it is concluded that there are eight types of cells in the hemolymph of B. cornutus. Further studies are now needed to identify the role of these hemocytes in the enzymological and immunological response.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.53 no.1
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• pp.90-97
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• 2020

The purpose of this study was to provide basic information on sexual maturity and reproductive biology for the management of biological resources in abalone Haliotis discus hannai. The nucleus of the oogonium occupied about 42% of the cytoplasm, and had a distinctive basophilic chromatin. The cytoplasm of previtellogenic oocytes was homogeneous and the size of nuclear pores increased. Fine granular and vacuolar yolk granules were observed in the cytoplasm of the initial vitellogenic oocyte. In this stage, the egg stalk and jelly membrane began to develop. The nucleus of the active vitellogenic oocyte was located near the animal pole. Yolk granules were strongly acidophilic. Lampbrush chromosomes were observed in the nucleus and rough endoplasmic reticulum. Annulate lamellae developed in the cytoplasm. The shape of the ripe oocyte was rounded polygonal. The size of ripe oocytes was 202.9±21.40×142.1±18.82 ㎛ and the thickness of the jelly membrane was 10.1±1.52 ㎛. These results show that yolk accumulation in H. discus hannai is based on two methods: exogenous accumulation, through the egg stalk, and endogenous accumulation, through intracellular organelles. Management of biological resources will be necessary when oocytes predominate after the active vitellogenic stage.

• Journal of Microbiology and Biotechnology
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• v.29 no.4
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• pp.633-644
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• 2019

An advanced anaerobic expanded granular sludge bed (AnaEG) and an internal circulation (IC) reactor, which were adopted to treat starch processing wastewater (SPW) and ethanol processing wastewater (EPW), were comprehensively analyzed to determine the key factors that affected the granules and microbial communities in the bioreactors. The granule size of $900{\mu}m$ in the AnaEG reactor was smaller than that in the IC reactor, and the internal and external morphological structures of the granular sludge were also significantly different between the two types of reactors. The biodiversity, which was higher in the AnaEG reactor, was mainly affected by reactor type. However, the specific microbial community structure was determined by the type of wastewater. Furthermore, the dominant methanogens of EPW were mainly Methanosaeta and Methanobacterium, but only Methanosaeta was a major constituent in SPW. Compared with the IC reactor, characteristics common to the AnaEG reactor were smaller granules, higher biodiversity and larger proportion of unknown species. The comparison of characteristics between these two reactors not only aids in understanding the novel AnaEG reactor type, but also elucidates the effects of reactor type and wastewater type on the microbial community and sludge structure. This information would be helpful in the application of the novel AnaEG reactor.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.435-447
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• 2017

Associative and bidirectional associative memories are examples of associative structures studied intensively in the literature. The underlying idea is to realize associative mapping so that the recall processes (one-directional and bidirectional ones) are realized with minimal recall errors. Associative and fuzzy associative memories have been studied in numerous areas yielding efficient applications for image recall and enhancements and fuzzy controllers, which can be regarded as one-directional associative memories. In this study, we revisit and augment the concept of associative memories by offering some new design insights where the corresponding mappings are realized on the basis of a related collection of landmarks (prototypes) over which an associative mapping becomes spanned. In light of the bidirectional character of mappings, we have developed an augmentation of the existing fuzzy clustering (fuzzy c-means, FCM) in the form of a so-called collaborative fuzzy clustering. Here, an interaction in the formation of prototypes is optimized so that the bidirectional recall errors can be minimized. Furthermore, we generalized the mapping into its granular version in which numeric prototypes that are formed through the clustering process are made granular so that the quality of the recall can be quantified. We propose several scenarios in which the allocation of information granularity is aimed at the optimization of the characteristics of recalled results (information granules) that are quantified in terms of coverage and specificity. We also introduce various architectural augmentations of the associative structures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.131-146
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• 2021

Multimodal biometric-based recognition has been an active topic because of its higher convenience in recent years. Due to high user convenience of finger, finger-based personal identification has been widely used in practice. Hence, taking Finger-Print (FP), Finger-Vein (FV) and Finger-Knuckle-Print (FKP) as the ingredients of characteristic, their feature representation were helpful for improving the universality and reliability in identification. To usefully fuse the multimodal finger-features together, a new robust representation algorithm was proposed based on hierarchical model. Firstly, to obtain more robust features, the feature maps were obtained by Gabor magnitude feature coding and then described by Local Binary Pattern (LBP). Secondly, the LGBP-based feature maps were processed hierarchically in bottom-up mode by variable rectangle and circle granules, respectively. Finally, the intension of each granule was represented by Local-invariant Gray Features (LGFs) and called Hierarchical Local-Gabor-based Gray Invariant Features (HLGGIFs). Experiment results revealed that the proposed algorithm is capable of improving rotation variation of finger-pose, and achieving lower Equal Error Rate (EER) in our homemade database.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.1-19
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• 1998

In this Kdynote address, two types of information granules are considered : (ⅰ) one for set assignments of a concept descriptor and (ⅱ) the other for truthood assignment to the concept description verifier. The first is, the process which specifies the assignment of an object to a clump, a class, a group, etc., and hence defines the set membership with a relational constraint. the second is the assignment of the degree of truthood or the membership specification of the abstract concept of truthood which specifies the " veristic" constraint associated with the concept descriptor. The combination of these two distinct assignments let us generate four set and logic theories. This then leads to the concern of normal forms and their derivation from truth tables for each of these theories. In this regard, some of the fundamental issues arising in this context are discussed and certain preliminary answers are provided in order to highlight the consequences of these theories.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1815-1816
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• 2007

본 논문에서는 데이터의 특성을 이용한 정보 입자 기반 퍼지 뉴럴 네트워크의 연속적 최적화를 제안한다. 데이터들간의 거리를 중심으로 C-Means 클러스터링 알고리즘을 이용하여 멤버쉽 함수를 정의하고 각 중심의 후반부 중심값을 이용하여 후반부 학습에 적용한다. 구조/파라미터 동정에 있어서 실수 코딩 기반 유전자 알고리즘을 이용하여 입력변수의 수, 입력 변수의 선택, 멤버쉽함수의 수, 후반부 형태와 같은 시스템의 입력 구조와 전반부 멤버쉽함수의 정점 및 학습율과 모멘텀 계수와 같은 파라미터를 최적으로 동정한다. 또한, 구조 연산과 파라미터 연산의 연속적 동조 방법을 이용하여 퍼지 뉴럴 네트워크를 최적화한다. 제안된 퍼지 뉴럴 네트워크는 삼각형 멤버쉽 함수를 이용하며, 후반부 추론에는 간략, 선형, 변형된 2차식을 이용한다. 제안된 퍼지 뉴럴 네트워크는 표준 모델로서 널리 사용되는 수치적인 예를 통하여 평가한다.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).