• Korean Journal of Cognitive Science
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• v.18 no.4
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• pp.399-415
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• 2007

Many objects are always present in a visual scene. Since the visual system has limited capacity to process multiple stimuli at a time, how to cope with this informational overload is one of the important problems to solve in visual perception. This study investigated the suppressive interactions among multiple stimuli when attention was directed to either one of the stimuli or all of them. The results indicate that suppressive interactions among multiple circles were reduced in V4 when subjects paid attention to one of the four locations, as compared to the unattended condition. However, suppressive interactions were not reduced when they paid attention to all four items as a set, in order to compute their mean size. These results suggest that whereas focused attention serves to later out irrelevant information, distributed attention provides an average representation of multiple stimuli.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1077-1094
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• 2016

Apache Spark is a fast and general-purpose cluster computing package. It provides a new abstraction named resilient distributed dataset, which is capable of support for fault tolerance while keeping data in memory. This type of abstraction results in a significant speedup compared to legacy large-scale data framework, MapReduce. In particular, Spark framework is suitable for iterative machine learning applications such as logistic regression and K-means clustering, and interactive data querying. Spark also supports high level libraries for various applications such as machine learning, streaming data processing, database querying and graph data mining thanks to its versatility. In this work, we introduce the concept and programming model of Spark as well as show some implementations of simple statistical computing applications. We also review the machine learning package MLlib, and the R language interface SparkR.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.117-127
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• 2011

The aim of this study was to examine the fate of tetracycline resistant bacteria (TRB) and tetracycline resistant genes (TRG) according to the spatial and operational wastewater treatment factors. As part of the effort, TRB and TRG of water samples at each unit processes of three different wastewater treatment plants (WWTPs) were analyzed over seven month study periods. With the data about different spatial and operating conditions of these WWTPs, TRB and TRGs, principal component analysis (PCA) was performed to find out any general correlation trend. Based on the statistic analysis results, the extent of TRB concentration in the activated sludge (TRBAS) is much related to the TRB concentration in primary clarifier effluent (TRBPE). Also, the study results indicated that the fate of TRB and TRG are significantly affected by the SRT variations.

• The KIPS Transactions:PartB
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• v.16B no.6
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• pp.497-502
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• 2009

In this paper, we introduce an automatic product feature extracting system that improves the efficiency of product review analysis. Our system consists of 2 parts: a review collection and correction part and a product feature extraction part. The former part collects reviews from internet shopping malls and revises spoken style or ungrammatical sentences. In the latter part, product features that mean items that can be used as evaluation criteria like 'size' and 'style' for a skirt are automatically extracted by utilizing term statistics in reviews and web documents on the Internet. We choose nouns in reviews as candidates for product features, and calculate degree of association between candidate nouns and products by combining inner association degree and outer association degree. Inner association degree is calculated from noun frequency in reviews and outer association degree is calculated from co-occurrence frequency of a candidate noun and a product name in web documents. In evaluation results, our extraction method showed an average recall of 90%, which is better than the results of previous approaches.

• Korean Chemical Engineering Research
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• v.48 no.5
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• pp.589-597
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• 2010

Strengthening the regulation standard of biological nutrient in wastewater treatment plant(WWTP), the necessity of repair of WWTP which is operated in conventional activated sludge process to advanced nutrient removal treatment is increased. However, in full-scale wastewater treatment system, it is not easy to fine the optimized operational condition of the advanced nutrient removal treatment through experiment due to the complex response of various influent conditions and operational conditions. Therefore, in this study, an upgrading design of conventional activated sludge process to advanced nutrient removal process using the modeling and simulation method based on activated sludge model(ASMs) is executed. And a design optimization of advanced treatment process using the response surface method(RSM) is carried out for statistical and systematic approach. In addition, for the operational optimization of full-scale WWTP, a correct analysis about kinetic variables of wastewater treatment is necessary. In this study, through partial least square(PLS) analysis which is one of the multivariable statistical analysis methods, a correlation between the kinetic variables of wastewater treatment system is comprehended, and the most effective variables to the advanced treatment operation result is deducted. Through this study, the methodology for upgrading design and operational optimization of advanced treatment process is provided, and an efficient repair of WWTP to advanced treatment can be expected reducing the design time and costs.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.427-434
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• 2018

Recently, the Seoul government implemented 'Free Public Transportation' policy and 'Citizen Participatory Alternative-Day-No-Driving' system as 'Emergency Fine Dust Reduction Measures'. In this paper, after identifying the effectiveness of the two traffic policies, suggestions for direction of future fine dust policy were made. The effect of traffic on the fine dust was analyzed by regression analysis and the responses to the two traffic policies and petitions were analyzed using text mining. Our experimental results show that the responses to the policy were mostly negative, and the influence of the domestic factors was considerable unlike expectation of citizens. Moreover, the result made us possible to know people's specific needs on fine dust reduction policy. Finally, based on the result, the suggestions for fine dust reduction policy direction were provided.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1045-1046
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• 2009

본 논문에서는 이산 이벤트 시뮬레이터인 SMPL을 이용하여 노변 네트워크에서의 데이터 처리에 따르는 데이터 캐쉬 성능분석기를 구현한다. 구현된 성능분석기는 SMPL의 요청 도착과 서비스 사건 처리를 기본 골격으로 하여 실제 차량의 궤적 데이터에 기반한 데이터 요청 생성부와 큐잉 정책과 캐쉬 정책을 선택할 수 있는 정책 처리부 등으로 구성된다. 이 분석기는 서비스율, 해당 정책, 캐쉬의 크기 등의 수행인자를 설정하여 이에 따르는 큐 길이의 분포, 캐쉬의 히트율, 요청 처리시간의 분포 등을 측정할 수 있도록 한다. 추정된 성능 요소를 기반으로 노변 네트워크에 기반한 차량 텔레매틱스 시스템에서 RSU(RoadSide Unit)의 배치, 성능 요구사항 분석, 새로운 큐잉 정책과 캐쉬 정책의 설계 등 다양한 응용이 가능하다.

• International Area Studies Review
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• v.13 no.3
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• pp.413-438
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• 2009

Tourism is an attractive field of industry to many countries due to its strong potentials in increasing employment rates as well as improving the national image. The positive effect of the tourism on the national economy and globalization has been recognized in Korea. A multilateral effort has been made in order to develop its tourist industry. Therefore, it is necessary to analyze the patterns of tourism demand in Korea. The present study analyzes and demonstrates the effects of a nation's characteristics on tourism demand. The study model was based on factors that affected tourism demand, especially emphasizing on the economic size, distance, national income, and language differences from the mother country. In particular, this study highlights the effects of economic relations between the countries and their exchange rate on tourism demand. In summary, this thesis demonstrates that actual national and international panel data enhance the credibility of the research and precisely determine factors that have a direct influence on tourism demand. A corresponding strategy of development and products are required as most tourists show the preference in advanced nations.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.313-319
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• 1997

한국어 의존 파싱에서는 불필요한 의존관계의 과다한 생성과 이에 따른 다수의 구문분석 결과 생성에 대처하는 연구가 필요하다. 본 논문에서는 한국어 의존 파싱 과정에서 생기는 불 필요한 의존관계에 따른 다수의 후보 의존 트리들에 대하여 통계/의미 정보를 활용하여 최적 트리를 결정하는 구문 분석 방법을 제안한다. 본 논문의 구문 분석에서 사용하는 통계/의미 정보는 구문구조부착 말뭉치(Tree Tagged Corpus)를 이용하여 구축한 술어 하위범주화 정보 사전에서 얻었으며, 이러한 정보를 활용한 구문 분석은 한국어 구문 분석의 모호성 해소에 적용되어 한국어 구문 분석의 정확도를 높인다.

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.47-53
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• 2003

본 논문은 정제된 대용량 말뭉치로부터 얻은 음절 n-gram과 어절 통계를 이용한 한국어 자동 띄어쓰기 시스템을 제안한다. 한 문장 내에서 최적의 띄어쓰기 위치는 Viterbi 알고리즘에 의해 결정된다. 통계 기반 연구에 고유한 문제인 데이터 부족 문제, 학습 말뭉치 의존 문제를 개선하기 위하여 말뭉치를 확장하고 실험을 통해 얻은 매개변수를 사용하고 최장 일치 Viable Prefix를 찾아 어절 목록에 추가한다. 본 연구에 사용된 학습 말뭉치는 33,641,511어절로 구성되어 있으며 구어와 문어를 두루 포함한다.