• Title/Summary/Keyword: Analysis Techniques

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A Study on Competitive Analysis Using Multidimensional Efficiency Analysis (다차원효율성분석을 활용한 경쟁분석에 관한 연구)

  • Yang, Dong-Heon;You, Yen-Yoo
    • The Journal of Society for e-Business Studies
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    • v.17 no.4
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    • pp.117-140
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    • 2012
  • This study focuses on the use of competitive analysis to identify the effective benchmarking target through consulting techniques to derive improvements. After developed using DEA(Date Envelopment Analysis) the relative efficiency analysis tool for competitor analysis to apply in consulting on-site or within the organization, this study compared the new techniques and the existing techniques. This study was carried out as follows. First, through a review of the literature, consulting competitive analysis techniques and methodologies relative efficiency analysis technique DEA for research scholars examined. Second, DEA-based competitive analysis, multidimensional efficiency analysis is presented. Third, The case study was conducted to determine the suitability and practicality of this analysis method for public company "A".

Analysis of Patents regarding Stabilization Technology for Steep Slope Hazards (급경사지재해 안정화기술에 대한 특허분석)

  • Song, Young-Suk;Kim, Jae-Gon
    • The Journal of Engineering Geology
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    • v.20 no.3
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    • pp.257-269
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    • 2010
  • We analyzed patent trends regarding stabilization technology for steep slope hazards, focusing on patents applied for and registered in Korea, the USA, Japan, and Europe. The technology was classified into four groups at the second classification step: prediction techniques, instrumentation techniques, countermeasure/reinforcement/mitigation techniques, and laboratory tests. A total of 2,134 patents were selected for the final effective analysis. As a result of portfolio analysis using the correlation between the number of patents and the applicant for each patent, the Korean and USA situations were classified as belonging to the developing period, and the Japanese and European situations were classified as belonging to the ebbing period. In particular, patent activity in Korea has been enlivened by government-led research. As a result of technology analysis at the second classification step, prediction techniques arising from Japan are evaluated as a competitive power technique, and laboratory tests arising from the USA are evaluated as a competitive power technique. However, prediction techniques and laboratory tests arising from Korea are evaluated as a blank technique. According to the prediction results regarding future research and developments, a new finite element analysis method and a numerical model should be established as part of prediction techniques, as well as sensors, and hazard prediction should be developed by integrating information and equipment using IT technology as part of instrumentation techniques. In addition, improvements to existing structures for erosion control and the development of new slope-reinforcement methods are required as part of countermeasure/reinforcement/mitigation techniques, and new laboratory apparatus and methods with an optimizing structure should be developed as part of laboratory tests.

A Technical Approach for Suggesting Research Directions in Telecommunications Policy

  • Oh, Junseok;Lee, Bong Gyou
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.12
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    • pp.4467-4488
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    • 2014
  • The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

A STUDY ON THE TECHNIQUES OF ESTIMATING THE PROBABILITY OF FAILURE

  • Lee, Yong-Kyun;Hwang, Dae-Sik
    • Journal of the Chungcheong Mathematical Society
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    • v.21 no.4
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    • pp.573-583
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    • 2008
  • In this paper, we introduce the techniques of estimating the probability of failure in reliability analysis. The basic idea of each technique is explained and drawbacks of these techniques are examined.

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Analysis of various statistical techniques used in the articles published during last 19 years in The Journal of Korean Acupuncture & Moxibusition Society (침구학회지 논문에 응용된 통계방식에 관한 연구 -1984 창간호부터 2002년 19권 6호까지 19년간-)

  • Lee, Seung-deok
    • Journal of Acupuncture Research
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    • v.20 no.1
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    • pp.144-158
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    • 2003
  • This study was carried out to investigate what kinds of statistical techniques have been used to analyze data from oriental medicine research, For study, 551 original articles which used statistical techniques in their data analysis were selected form the articles published in The journal of Korean Acupuncture & Moxibustion Society(JKAMS) between 1984 to 2002. among them, 122 articles used descriptive statistics while 429 articles used inferential statistics for data analysis. For that 429 articles, t-test (189 articles), analysis fo variance (111 articles), chi-square test (14 articles), correlation (10 articles), regression analysis (4 articles), factor analysis(5 articles), or nonparametric test (23 articles) were chose to analyze the data. Nonparametric approach has substantial power in case data do not meet the assumption of normality. This method is not only easy to use ut also provides measures of the statistical variation of nominal and ordinal scale. This study shows that more and more recent papers use nonparametric test compared to the old articles. nine different statistical software or packages (SAS, SPSS, Statview, Minitab, Sigma plot, ISP, Graphpad prism, Excel, Access) have been used in the articles published JKMAS. High level statistical techniques such as SAS, SPSS, and Statview are user friendly and used most for acupuncture and Moxibustion research. Including tables and plots in an article facilitates understanding family process data from a descriptive standpoint, minimized erroneous statistical conclusions, and clarifies theoretically important relationships among variables. Table and plots have been used 500 and 233 articles, respectively. A computer procedure is proposed and illustrated with statistical packages using SAS, SPSS, Statview and ISP.

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Multiple-Case Studies of Hand-on Breast Massage Techniques used by Breastfeeding Experts (산후 유방 마사지 손기술에 대한 다중사례분석)

  • Park, Hyunsoon;Cho, Insook;Kim, Min-Kyeong
    • Women's Health Nursing
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    • v.23 no.3
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    • pp.155-165
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    • 2017
  • Purpose: The aim of this study was to understand the hand-on breast massage techniques used by well-known experts in breastfeeding clinics. Methods: A qualitative multiple-case design was applied that involved a feasibility test. Four experts sampling qualitative data collected by observing participants and in individual interviews were analyzed by content analysis, linking data to the propositions, and cross-case pattern matching. This study explored differences within and between cases, and the possibilities of replicating findings across cases. Thirty-nine postpartum women participated voluntarily in the feasibility test, which investigated the usability of four massage techniques. Results: The four techniques showed considerable similarities in terms of the application of stimulation to the breast base and increased flexibility of the wired flexible body, which was the core mechanism underlying the techniques. The breast management strategies were consistent with existing practice guidelines with the exception of using cold cabbage to control engorgement pain. There was insufficient scientific evidence for supporting the massage techniques used by the experts. All of the techniques showed 100% education completeness, but application rates were higher for self-control-oriented techniques. Conclusion: The massage techniques applied by experts in breastfeeding were based on hypotheses and self-control techniques are feasible to apply in practice.

Is Text Mining on Trade Claim Studies Applicable? Focused on Chinese Cases of Arbitration and Litigation Applying the CISG

  • Yu, Cheon;Choi, DongOh;Hwang, Yun-Seop
    • Journal of Korea Trade
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    • v.24 no.8
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    • pp.171-188
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    • 2020
  • Purpose - This is an exploratory study that aims to apply text mining techniques, which computationally extracts words from the large-scale text data, to legal documents to quantify trade claim contents and enables statistical analysis. Design/methodology - This is designed to verify the validity of the application of text mining techniques as a quantitative methodology for trade claim studies, that have relied mainly on a qualitative approach. The subjects are 81 cases of arbitration and court judgments from China published on the website of the UNCITRAL where the CISG was applied. Validation is performed by comparing the manually analyzed result with the automatically analyzed result. The manual analysis result is the cluster analysis wherein the researcher reads and codes the case. The automatic analysis result is an analysis applying text mining techniques to the result of the cluster analysis. Topic modeling and semantic network analysis are applied for the statistical approach. Findings - Results show that the results of cluster analysis and text mining results are consistent with each other and the internal validity is confirmed. And the degree centrality of words that play a key role in the topic is high as the between centrality of words that are useful for grasping the topic and the eigenvector centrality of the important words in the topic is high. This indicates that text mining techniques can be applied to research on content analysis of trade claims for statistical analysis. Originality/value - Firstly, the validity of the text mining technique in the study of trade claim cases is confirmed. Prior studies on trade claims have relied on traditional approach. Secondly, this study has an originality in that it is an attempt to quantitatively study the trade claim cases, whereas prior trade claim cases were mainly studied via qualitative methods. Lastly, this study shows that the use of the text mining can lower the barrier for acquiring information from a large amount of digitalized text.

Impact of Word Embedding Methods on Performance of Sentiment Analysis with Machine Learning Techniques

  • Park, Hoyeon;Kim, Kyoung-jae
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.8
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    • pp.181-188
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    • 2020
  • In this study, we propose a comparative study to confirm the impact of various word embedding techniques on the performance of sentiment analysis. Sentiment analysis is one of opinion mining techniques to identify and extract subjective information from text using natural language processing and can be used to classify the sentiment of product reviews or comments. Since sentiment can be classified as either positive or negative, it can be considered one of the general classification problems. For sentiment analysis, the text must be converted into a language that can be recognized by a computer. Therefore, text such as a word or document is transformed into a vector in natural language processing called word embedding. Various techniques, such as Bag of Words, TF-IDF, and Word2Vec are used as word embedding techniques. Until now, there have not been many studies on word embedding techniques suitable for emotional analysis. In this study, among various word embedding techniques, Bag of Words, TF-IDF, and Word2Vec are used to compare and analyze the performance of movie review sentiment analysis. The research data set for this study is the IMDB data set, which is widely used in text mining. As a result, it was found that the performance of TF-IDF and Bag of Words was superior to that of Word2Vec and TF-IDF performed better than Bag of Words, but the difference was not very significant.

Application of Machine Learning Techniques for the Classification of Source Code Vulnerability (소스코드 취약성 분류를 위한 기계학습 기법의 적용)

  • Lee, Won-Kyung;Lee, Min-Ju;Seo, DongSu
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.4
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    • pp.735-743
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    • 2020
  • Secure coding is a technique that detects malicious attack or unexpected errors to make software systems resilient against such circumstances. In many cases secure coding relies on static analysis tools to find vulnerable patterns and contaminated data in advance. However, secure coding has the disadvantage of being dependent on rule-sets, and accurate diagnosis is difficult as the complexity of static analysis tools increases. In order to support secure coding, we apply machine learning techniques, such as DNN, CNN and RNN to investigate into finding major weakness patterns shown in secure development coding guides and present machine learning models and experimental results. We believe that machine learning techniques can support detecting security weakness along with static analysis techniques.

An Analysis on Key Factors of Mobile Fitness Application by Using Text Mining Techniques : User Experience Perspective (텍스트마이닝 기법을 이용한 모바일 피트니스 애플리케이션 주요 요인 분석 : 사용자 경험 관점)

  • Lee, So-Hyun;Kim, Jinsol;Yoon, Sang-Hyeak;Kim, Hee-Woong
    • Journal of Information Technology Services
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    • v.19 no.3
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    • pp.117-137
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    • 2020
  • The development of information technology leads to changes in various industries. In particular, the health care industry is more influenced so that it is focused on. With the widening of the health care market, the market of smart device based personal health care also draws attention. Since a variety of fitness applications for smartphone based exercise were introduced, more interest has been in the health care industry. But although an amount of use of mobile fitness applications increase, it fails to lead to a sustained use. It is necessary to find and understand what matters for mobile fitness application users. Therefore, this study analyze the reviews of mobile fitness application users, to draw key factors, and thereby to propose detailed strategies for promoting mobile fitness applications. We utilize text mining techniques - LDA topic modeling, term frequency analysis, and keyword extraction - to draw and analyze the issues related to mobile fitness applications. In particular, the key factors drawn by text mining techniques are explained through the concept of user experience. This study is academically meaningful in the point that the key factors of mobile fitness applications are drawn by the user experience based text mining techniques, and practically this study proposes detailed strategies for promoting mobile fitness applications in the health care area.