http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
이경미,조영민 한국냄새환경학회 2011 실내환경 및 냄새 학회지 Vol.10 No.1
The present study investigated the emission characteristics of odorous elements from a local livestock waste treatment plant. Target materials were sampled twice from each place including the boundaries of the plant, exhaust of a fan from utility-pipe conduit and bio-filter bio-filter chamber. Among the sulfur compounds, methyl mercaptan was 3.0 ppb at the boundary Ⅰ, 2.2 ppb at the fan exhaust, and 4,723.3 ppb at the outlet of bio-filter scrubber. In particular, one of main odor control facilities; bio-filter scrubber has released a large volume of methyl mercaptan. It also removes 76.8% of ammonia and 26.5% of trimethylamine. 본 연구는 축산폐수 및 분뇨처리장에서 발생하는 악취물질의 배출특성을 파악하고자 하였다. 측정 지점은 처리장 주변의 경계지점과 지하공동구의 환기팬, 그리고 탈취 시스템인 바이오필터 챔버 전, 후단부로 선정하였다. 황화합물 계열의 악취 물질 중 메틸머캅탄의 농도는 경계지역 Ⅰ에서 3.0 ppb, 환기팬은 2.2 ppb 그리고 바이오필터 후단에서는 4,723.3 ppb로 측정되었다. 악취농도지수를 통한 기여도 분석 결과 바이오필터 후단에서는 메틸머캅탄의 기여도가 가장 높은 것으로 나타났다. 또한 바이오필터의 처리 효율은 암모니아의 경우 76.8%, 트리메틸아민은 26.5%로 나타났다.
Medoid Determination in Deterministic Annealing-based Pairwise Clustering
이경미,이건명 한국지능시스템학회 2011 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.11 No.3
The deterministic annealing-based clustering algorithm is an EM-based algorithm which behaves like simulated annealing method, yet less sensitive to the initialization of parameters. Pairwise clustering is a kind of clustering technique to perform clustering with inter-entity distance information but not enforcing to have detailed attribute information. The pairwise deterministic annealing-based clustering algorithm repeatedly alternates the steps of estimation of mean-fields and the update of membership degrees of data objects to clusters until termination condition holds. Lacking of attribute value information, pairwise clustering algorithms do not explicitly determine the centroids or medoids of clusters in the course of clustering process or at the end of the process. This paper proposes a method to identify the medoids as the centers of formed clusters for the pairwise deterministic annealing-based clustering algorithm. Experimental results show that the proposed method locate meaningful medoids.
Fuzzy Technique-based Identification of Close and Distant Clusters in Clustering
이경미,이건명 한국지능시스템학회 2011 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.11 No.3
Due to advances in hardware performance, user-friendly interfaces are becoming one of the major concerns in information systems. Linguistic conversation is a very natural way of human communications. Fuzzy techniques have been employed to liaison the discrepancy between the qualitative linguistic terms and quantitative computerized data. This paper deals with linguistic queries using clustering results on data sets, which are intended to retrieve the close clusters or distant clusters from the clustering results. In order to support such queries, a fuzzy technique-based method is proposed. The method introduces distance membership functions, namely, close and distant membership functions which transform the metric distance between two objects into the degree of closeness or farness, respectively. In order to measure the degree of closeness or farness between two clusters, both cluster closeness measure and cluster farness measure which incorporate distance membership function and cluster memberships are considered. For the flexibility of clustering, fuzzy clusters are assumed to be formed. This allows us to linguistically query close or distant clusters by constructing fuzzy relation based on the measures.