• 한국물환경학회지
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• 제22권2호
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• pp.300-307
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• 2006

The combined SHARON (Single reactor system for High ammonium Removal Over Nitrite)-ANAMMOX (Anaerobic ammonium oxidation) reactor were operated in mesophilic condition ($35^{\circ}C$). In this study, microbial granulation and characteristics of SHARON and ANAMMOX sludges were investigated using settling test, Scanning Electron Microscopy (SEM) and Fluorescence In Situ Hybridization (FISH). In SHARON reactor, Aerobic granulation with diameter of 1.5~2.5 mm was accomplished but aerobic granulation was weaker than anaerobic granular sludge. Initial seed sludge of ANAMMOX reactor was used as attached media for biofilm growth. ANAMMOX sludge was more compact and rounder rather than seed sludge. Though ANAMMOX sludge has high activity, it has lower settling ability than the seed granule. The color of ANAMMOX sludge was changed from dark to redish brown granular with diameter of 1~2 mm. In FISH of ANAMMOX sludge, high fraction of Candidatus B. stuttgartiensis which paid great role of nitrogen conversion was detected. Also, FISH results reveals that ANAMMOX bacteria inhabit at inner parts near surface, having advantages in utilization of substrates and protection from oxygen inhibition.

• 한국융합학회논문지
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• 제12권1호
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• pp.185-191
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• 2021

과립 분말 야금법은 기존 분말 야금법보다 치밀도가 높은 소결 부품을 얻을 수 있는 제조 기술이다. 하지만 추가 과립화 공정에 따른 생산 비용 증가가 상당하다는 단점이 있다. 과립 분말 야금법의 생산성 향상을 위해서는 과립 분말 제조 시 높은 회수율이 보장되어야 한다. 본 논문에서는 분체 동역학 전산 해석법인 이산요소법을 이용하여 과립 분말의 수율에 영향을 미치는 과립화 공정의 특성에 대해 살펴보았다. 분무 과립 공정 중 과립화 분말의 비산, 충돌 및 소착 현상을 시뮬레이션함으로써 분무 건조기의 운전 조건에 따른 과립화 분말의 파손 및 회수 가능 여부를 예측하였다. 본 논문의 가상 공정 시뮬레이션 융합 연구 결과는 실제 금속 분말의 분무 과립화 공정의 생산성 향상에 이바지할 것으로 기대한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.340-342
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• 2004

In this paper, we introduce a new category of fuzzy inference systems baled on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects(data, in particular) drawn together by the criteria of proximity, similarity, or functionality. Granulation of information with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.343-345
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• 2004

We propose a new category of fuzzy set-based fuzzy inference systems based on data granulation related to fuzzy space division for each variables. Data granules are viewed as linked collections of objects(data, in particular) drawn together by the criteria of proximity, similarity, or functionality. Granulation of data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. Numerical example is included to evaluate the performance of the proposed model.

• 한국세라믹학회지
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• 제25권4호
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• pp.357-363
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• 1988

Ccompaction and sintering behavior of highly pure PSZ powders were investigated by laying the stress on the granulation processes. The particle size of coprecipitated PSZ powder was so fine that the agglomeration was severely formed during drying and calcing step and by this agglomeration differential sinering was occurred. The methanol dispersion of precipitates was the good method of avoiding severe agglomeration formed during drying process because of small surface tension than water. But perfect deagglomeraton was not possible due to high surface area of powders. So homogenization by granulation was needed, and among the method spray granulation was the most desirable to obtain homogeneous compacts and subsequent flaw-free ceramics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.1865_1866
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• 2009

본 연구에서는 복잡하고 비선형 시스템의 모델을 동정하기 위해 Information Granulation에 기반한 퍼지추론 시스템의 새로운 범주를 소개한다. Information Granulation은 근접성, 유사성 EH는 기능성 등에 인하여 서로 결합되는 대상(특히, 데이터)의 연결된 모임으로 간주된다. HCM클러스터링에 의한 Information Granulation은 퍼지 규칙의 전반부 및 후반부에서 사용되는 멤버쉽 함수의 초기 정점과 다항식함수의 초기 값과 같은 퍼지 모델의 초기 파라미터를 결정하는데 도움을 준다. 그리고 초기 파라미터는 PSO 알고리즘과 최소자승법에 의해 효과적으로 동조된다. 제안된 모델은 Box와 jenkins가 사용한 가스로 공정[6]을 모델링하여 기존 퍼지 모델링 방법과 비교 평가한다.

• Journal of Korean Neurosurgical Society
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• 제43권1호
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• pp.48-50
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• 2008

We experienced a case of giant arachnoid granulation misdiagnosed as dural sinus thrombosis. A 66-year-old woman presented with a one month history of progressive occipital headache. Computed tomography angiography and cerebral angiography showed a round filling defect at the transverse sinus which was speculated as a transverse sinus thrombosis. Anticoagulation therapy was performed to prevent worsening of thrombosis for 2 weeks and then a Gadolinium-enhanced magnetic resonance imaging scan was performed. The filling defect lesion at the transverse sinus revealed a non-enhancing granule with central linear enhancement, which was compatible with giant arachnoid granulation. We checked the intrasinus pressure difference across the lesion the through the dural sinus in order to exclude the lesion as the cause of headache. Normal venous pressure with no significant differential pressure across the lesion was noted. Headache was treated with medical therapy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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• pp.253-258
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• 2005

In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality. To identify the structure of fuzzy rules we use genetic algorithms (GAs). Granulation of information with the aid of Hard C-Means (HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method (LSM). The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• Archives of Pharmacal Research
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• 제2권1호
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• pp.17-24
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• 1979

A first systematic approach on new and simple preparation method of spherical granules in the system using organic granulating solution was carried out. Mixer granulation required narrow range of moisture content but gentle action of tumbling in the mixer and capilary forces were adequate to compact the porous mass and also were highly effective to produce granules close to sphere. Where the granules by massing and screening provided the more open structure, its pore distribution lied between 71 and 16 .mu.m by above 50% and on the contrary, that of the mixer granulated granules showed only below 25%. Increase in retention time in the mixer decreased the intragranular porosity of granules produced, and in comparison with granular particles produced by conventional wet granulation, those from the mixer granulation had the advantages of flow properties, packing characteristics and definite spherocity. They also had extremely low friability resulting in few fines.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권2호
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• pp.45-51
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• 2006

In this paper, we propose a new architecture of Information Granulation based genetically optimized Self-Organizing Fuzzy Polynomial Neural Networks (IG_gSOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially information granulation and genetic algorithms. The proposed IG_gSOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). To evaluate the performance of the IG_gSOFPNN, the model is experimented with using two time series data(gas furnace process and NOx process data).