• Title/Summary/Keyword: Clustering Strategy

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A Study on Geotop Classification and Geodiversity in Mt. Jeombong Experimental Forest (점봉산 시험림 지역의 지오톱 분류와 지형다양성 연구)

  • Kim, Nam-Shin;Han, DongUk;Cha, Jin-Yeol;Kwon, Hye-Jin;Cho, Yong-Chan;Oh, Seung-Hwan;Yoo, Seung-Hwa;Yu, Dong-Su;Park, Yong-Su
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.18 no.6
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    • pp.179-190
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    • 2015
  • This study was carried out to suggest fundamental concepts and data ideas for biodiversity and confrontation strategy on global environmental changes by analyzing geomorphic milieu and geotop in Mt. Jeombong experimental forest. Elements of landform were classified as landform sets by scale. Scale for classification could be decide on four categories. We could classify landforms which scale zero is seven elements, scale one is twelve elements, scale two is fifteen elements, scale three is twenty nine elements. Especially mountain wetlands were classed as valley and channel types in Mt. Jeombong. Geotop by clustering methods could be four spatial units as 2, 3, 5, and 7 classes, and analyzed geodiversity as landform sets for explanation of vegetation distribution. Rate of rise of temperature was $0.031^{\circ}C$ per year, change ratio was increased $1.25^{\circ}C$, and also precipitation was increased 320mm during forty year(from year 1973 to year 2012). The result of this research can be affordable to provide information for forest management of mountainous areas.

Identification of Fuzzy Inference Systems Using a Multi-objective Space Search Algorithm and Information Granulation

  • Huang, Wei;Oh, Sung-Kwun;Ding, Lixin;Kim, Hyun-Ki;Joo, Su-Chong
    • Journal of Electrical Engineering and Technology
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    • v.6 no.6
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    • pp.853-866
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    • 2011
  • We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.

Early Detection of Lung Cancer Risk Using Data Mining

  • Ahmed, Kawsar;Abdullah-Al-Emran, Abdullah-Al-Emran;Jesmin, Tasnuba;Mukti, Roushney Fatima;Rahman, Md. Zamilur;Ahmed, Farzana
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.1
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    • pp.595-598
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    • 2013
  • Background: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of lung cancer prevention. However, this is a multi-layered problem. Therefore a lung cancer risk prediction system is here proposed which is easy, cost effective and time saving. Materials and Methods: Initially 400 cancer and non-cancer patients' data were collected from different diagnostic centres, pre-processed and clustered using a K-means clustering algorithm for identifying relevant and non-relevant data. Next significant frequent patterns are discovered using AprioriTid and a decision tree algorithm. Results: Finally using the significant pattern prediction tools for a lung cancer prediction system were developed. This lung cancer risk prediction system should prove helpful in detection of a person's predisposition for lung cancer. Conclusions: Most of people of Bangladesh do not even know they have lung cancer and the majority of cases are diagnosed at late stages when cure is impossible. Therefore early prediction of lung cancer should play a pivotal role in the diagnosis process and for an effective preventive strategy.

Innovation Cluster and Regional Development In Daejeon Regional (대전지역 혁신클러스터와 지역발전)

  • Ryu, Duk-Wi
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.2 no.3
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    • pp.103-122
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    • 2007
  • Innovation clusters developed or evolved around a specific region IS the key element of national innovation system and determine national competitiveness. Recognizing the importance of innovation clusters, Korean government has made "Daedeok Special R&D Zone" in 2005. This paper examines the success factors of famous Cluster in advanced countries and China, and proposes the strategy for regional development in Daejeon through boosting Daedeok Innovation Cluster. Although 30.5% of government R&D investment is being concentrated in Daedeok along with 10% of the country's doctorate degree holders, it is lack of increasing revenue by linking corporate R&D with a creative and challenging entrepreneur spirit. The core of the innovation cluster is the integration and mutual networking of the main participants. This paper suggests strategies for developing as a world class innovation cluster, global networking and clustering, venture ecosystem formation, commercialization the knowledge by interacting with market. It also explains the necessity of regional integration for cluster to cluster linkages in the East Asia Region.

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A Task Offloading Approach using Classification and Particle Swarm Optimization (분류와 Particle Swarm Optimization을 이용한 태스크 오프로딩 방법)

  • Mateo, John Cristopher A.;Lee, Jaewan
    • Journal of Internet Computing and Services
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    • v.18 no.1
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    • pp.1-9
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    • 2017
  • Innovations from current researches on cloud computing such as applying bio-inspired computing techniques have brought new level solutions in offloading mechanisms. With the growing trend of mobile devices, mobile cloud computing can also benefit from applying bio-inspired techniques. Energy-efficient offloading mechanisms on mobile cloud systems are needed to reduce the total energy consumption but previous works did not consider energy consumption in the decision-making of task distribution. This paper proposes the Particle Swarm Optimization (PSO) as an offloading strategy of cloudlet to data centers where each task is represented as a particle during the process. The collected tasks are classified using K-means clustering on the cloudlet before applying PSO in order to minimize the number of particles and to locate the best data center for a specific task, instead of considering all tasks during the PSO process. Simulation results show that the proposed PSO excels in choosing data centers with respect to energy consumption, while it has accumulated a little more processing time compared to the other approaches.

A Study on the Customer Segmentation and Performance by Medical Service Experience : Focusing on the Relational Benefits (의료서비스 경험에 의한 고객세분화와 성과에 관한 연구: 병원-고객 간의 관계혜택을 중심으로)

  • Park, Gwijeong
    • Journal of the Korea Convergence Society
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    • v.9 no.9
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    • pp.371-378
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    • 2018
  • The purpose of this study is to classify the customers according to the characteristics of the relational benefits and to compare the performances of the sub-groups. As a result of the research, the group type according to the relational benefits was subdivided into 3 groups, and each group was named emotional relational group, continuous relational group and intermittent relational group considering customer characteristics. First, the emotional relational group is the group that emphasizes the empathy and assurance between the service provider and the customer, and the continuous relational group is the group with the highest social, confidence and economic benefits. The intermittent relational group was simply a transaction-oriented group. This implies that a differentiated customer management strategy is needed for each relational benefit group based on customer experience in medical services.

Impact of Difference in Korean Wave Awareness among Chinese Women on Quality Perception and Purchasing Behavior of Korean Cosmetic Products (중국여성의 한류 인지도 차이가 한국 화장품에 대한 품질인식과 구매행동에 미치는 영향)

  • Lee, Jeong-Suk
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.10
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    • pp.5097-5104
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    • 2013
  • To derive implication for marketing strategy for Korean cosmetic products in China, an analysis was conducted on the difference in quality perception and purchase behavior between two groups of Chinese women classified by their awareness of Korean Wave. Analytical methods including k-means clustering method, independent samples t-test, factor analysis were applied on the survey results of Chinese women residing in Guangzhou city. The positive impact of Korean Wave on quality perception and brand image is much stronger for higher awareness group, compared against for lower awareness group, that leads to higher product satisfaction and willingness to recommend purchases. Thus, marketing strategies need to be adjusted based on the difference in customers awareness of Korean Wave. However, the low price is the primary inducement for purchases for both groups, increased efforts to enhance brand image and product quality as premium products is strongly required, together with the utilization of Koran Wave.

Nano Technology Trend Analysis Using Google Trend and Data Mining Method for Nano-Informatics (나노 인포매틱스 기반 구축을 위한 구글 트렌드와 데이터 마이닝 기법을 활용한 나노 기술 트렌드 분석)

  • Shin, Minsoo;Park, Min-Gyu;Bae, Seong-Hun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.237-245
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    • 2017
  • Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

Core Managing Points in a Wine Training Program Deduced by Loyalty (와인교육프로그램 수강생의 충성도 군집별 교육프로그램의 중점관리점 도출)

  • Lee, In-Soon;Lee, Hae-Young;Kim, Hye-Young
    • Journal of the Korean Society of Food Culture
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    • v.28 no.4
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    • pp.371-385
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    • 2013
  • This study aimed to classify attendants of a wine training institute according to loyalty for wine training service program and to deduce the core managing points in a wine training program by IPA (Importance-Performance Analysis). Self-administered questionnaires were collected from 192 trainees and statistical data analysis completed using SPSS ver. 18.0. As a result of clustering analysis based on trainee loyalty from both attitude and behavioral perspectives, four classification groups were identified: a "genuine" loyalty group, a "latent" loyalty group, a "mendacious" loyalty group, and a "low" loyalty group. For the genuine loyalty group, the importance of total service quality was 4.32 on average whereas the performance was measured as 4.22; thus there was little difference between importance to quality and performance. However, for the other three groups, especially the low loyalty group, there were significant wide gaps between importance to quality and performance. According to IPA, different service quality items were posted on the 'Focus here' quadrant (a domain with high service quality importance but low performance) by group, while the other three quadrants had several common items regardless of the group. Finally, the core quality managing points were different depending on the level of trainee loyalty. Therefore, it is necessary to plan and conduct a wine training program that reflects the characteristics and needs of its students, which will lead to a differentiated management strategy according to the level of loyalty.

논제 부정 Access에 대한 Firewall의 과제와 대책

  • 변성준;서정석;최원석
    • Proceedings of the Korea Database Society Conference
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    • 2000.11a
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    • pp.227-238
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    • 2000
  • Firewall은 다양한 부정Access의 방지책으로서 확실히 유효한 수단이지만 이 Firewall은 사용자로부터 지시된 설정을 충실히 실행하는 것으로 설정 오류, 소프트웨어의 정지, 허가된 룰을 악용한 침입 등 반드시 사용자가 바라는 작용을 무조건적 상태에서 보증해 주는 것은 아니다. 따라서 사용자는 도입 후 에도 운용시에 Access log를 감시하고 본래의 Security Policy에 반하는 행위를 매일 매일 체크하지 않으면 안될 상황에 처해 있다. 본 연구는 이러한 부정Access에 대한 이와 같은 Firewall의 현상에 대한 과제 중에서 "부정Access를 어떻게 하면 일찍, 정확히 체크할 수 있는가\ulcorner"라는 주제를 선택하여 Firewall의 한계와 그 대응책을 실제로 부정Access를 시험해 보는 것으로 검증하기로 하였다. 실험결과에서 (1)Port Scan이나 전자메일 폭탄(서비스정지공격)등은 Firewall로 방지하는 것은 불가능하거나 혹은 Checking이 곤란하다. (2)공격마다 로그 수집을 했음에도 관계없이 Firewall의 로그는 번잡하므로 단시간에 사태의 발견이 대단히 곤란하다고 하는 Firewall의 한계를 인식하였다. 그리고 그 대책으로서 우리는 체크 툴의 유효성에 착안하여 조사한 결과, 결국 무엇이 부정Access인가에 대해서는 어디까지나 이용하는 측이 판단하여 Firewall 상에 설정하지 않으면 안되지만 체크 툴은 이 부정Access 정보를 데이터베이스로서 갖고 있음으로써 '무엇이 부정Access인가'를 이용자 대신에 판단하고 툴에 따라서는 설정을 자동적으로 변경하여 부정 Access의 저지율을 향상시킨다. 이처럼 체크 툴은 Firewall의 수비능력을 보강하는 위치에 있다고 생각할 수 있다.다. 4 장에서는 3장에서 제기한 각각의 문제점에 대해 RAD 의 관점에 비추어 e-business 시스템의 단기개발을 실현하기 위한 고려사항이나 조건 해결책을 제안한다. 본 논문이 지금부터 e-business 를 시작하려고 하는 분, e-business 시스템의 개발을 시작하려고 하는 분께 단기간의 e-business 실현을 위한 하나의 지침이 된다면 다행이겠다.formable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.uage ("Association of research for algorithm of calculating machine (1992)"). As a result, conventional NN and CNN were available for interpolation of sampling data. Moreover, when nonlinear intensity is not so large under the field condition of small slope, interpolation performance of CNN was a little not so better than NN. However, when nonlinear intensity is large under the field condition of large slope, interpolation performance of CNN was relatively better than NN.콩과 자연 콩이 성분 분석에서 차이를

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