• Title/Summary/Keyword: Keyword-Based Approach

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Analytical Approach to the Literature of Cupping Therapy

  • Koran, Serhat;Irban, Arzu
    • Journal of the Korean Society of Physical Medicine
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    • v.16 no.3
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    • pp.1-14
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    • 2021
  • PURPOSE: This study aims to reveal the prevalence, therapeutic efficacy and undesirable side effects of cupping therapy all over the world from past to present. METHODS: This meta-analysis is based on the data obtained by scanning the keyword "cupping therapy" from the Pub-Med system, which is an international database. The date range has been set as 1950-2019. Local databases were not included. Cupping therapy studies combined with other complementary therapies such as acupuncture, moxa and hirudotherapy are also included in the meta-analysis. RESULTS: A total of 381 scientific studies were found on cupping therapy. Of these studies 127 wererandomized controlled trials (RCSs). Cupping treatment has been found effective in studies of painful conditions such as herpes zoster pain, fibromyalgia, back pain, neck pain, headache and acute injury pain. In addition, the effectiveness of cupping therapy was found to be high in studies related to bone / muscular system diseases such as osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, gout, carpal tunnel syndrome, cervical spondylosis. In addition, cupping treatment is also promising in studies on skin diseases, neurological diseases, respiratory system diseases and cardiovascular system diseases. CONCLUSION: Recently, there has been an increase in the number of RCSs related to cupping therapy. The vast majority of this increase has been made in European and American countries rather than in Far Eastern countries. Studies on cupping therapy, which have been and will be carried out in the future, will provide evidence-based indication of whether cupping therapy is effective. and it will allow more patients to benefit from this treatment, which has a very low rate of side effects and complications.

A Review of the Application of Constructed Wetlands as Stormwater Treatment Systems

  • Reyes, Nash Jett;Geronimo, Franz Kevin;Guerra, Heidi;Jeon, Minsu;Kim, Lee-Hyung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.162-162
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    • 2022
  • Stormwater management is an essential component of land-use planning and development. Due to the additional challenges posed by climate change and urbanization, various stormwater management schemes have been developed to limit flood damages and ease water quality concerns. Nature-based solutions (NBS) are increasingly used as cost-effective measures to manage stormwater runoff from various land uses. Specifically, constructed wetlands were already considered as socially acceptable green stormwater infrastructures that are widely used in different countries. There is a large collection of published literature regarding the effectiveness or efficiency of constructed wetlands in treating stormwater runoff; however, metadata analyses using bibliographic information are very limited or seldomly explored. This study was conducted to determine the trends of publication regarding stormwater treatment wetlands using a bibliometric analysis approach. Moreover, the research productivity of various countries, authors, and institutions were also identified in the study. The Web of Science (WoS) database was utilized to retrieve bibliographic information. The keywords ("constructed wetland*" OR "treatment wetland*" OR "engineered wetland*" OR "artificial wetland*") AND ("stormwater*" or "storm water*") were used to retrieve pertinent information on stormwater treatment wetlands-related publication from 1990 up to 2021. The network map of keyword co-occurrence map was generated through the VOSviewer software and the contingency matrices were obtained using the Cortext platform (www.cortext.net). The results obtained from this inquiry revealed the areas of research that have been adequately explored by past studies. Furthermore, the extensive collection of published scientific literature enabled the identification of existing knowledge gaps in the field of stormwater treatment wetlands.

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Anatomy of Sentiment Analysis of Tweets Using Machine Learning Approach

  • Misbah Iram;Saif Ur Rehman;Shafaq Shahid;Sayeda Ambreen Mehmood
    • International Journal of Computer Science & Network Security
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    • v.23 no.10
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    • pp.97-106
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    • 2023
  • Sentiment analysis using social network platforms such as Twitter has achieved tremendous results. Twitter is an online social networking site that contains a rich amount of data. The platform is known as an information channel corresponding to different sites and categories. Tweets are most often publicly accessible with very few limitations and security options available. Twitter also has powerful tools to enhance the utility of Twitter and a powerful search system to make publicly accessible the recently posted tweets by keyword. As popular social media, Twitter has the potential for interconnectivity of information, reviews, updates, and all of which is important to engage the targeted population. In this work, numerous methods that perform a classification of tweet sentiment in Twitter is discussed. There has been a lot of work in the field of sentiment analysis of Twitter data. This study provides a comprehensive analysis of the most standard and widely applicable techniques for opinion mining that are based on machine learning and lexicon-based along with their metrics. The proposed work is helpful to analyze the information in the tweets where opinions are highly unstructured, heterogeneous, and polarized positive, negative or neutral. In order to validate the performance of the proposed framework, an extensive series of experiments has been performed on the real world twitter dataset that alter to show the effectiveness of the proposed framework. This research effort also highlighted the recent challenges in the field of sentiment analysis along with the future scope of the proposed work.

A Comparative Bibliometric Analysis of Substance Use Disorder Research in Social Science, Natural Science and Technology, and Multidisciplinary Field (사회과학, 자연과학기술 및 융복합 분야의 약물중독 연구에 대한 계량서지학적 비교 분석 연구)

  • Nam, Dongin;Park, Ji-Hong
    • Journal of the Korean Society for information Management
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    • v.39 no.2
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    • pp.203-232
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    • 2022
  • Drug addiction or substance use disorder is continuously observed worldwide for its risks and prevalence. In this context, numerous studies have been conducted regarding this issue. However, bibliometric analysis related to drug addiction is insufficient. In particular, it is difficult to find research that utilizes a macro-level bibliographic approach that comprehensively reflects various characteristics related to drug addiction. In this study, to reflect the multidimensional features of drug addiction, research trends in drug addiction in social science, natural science, and multidisciplinary studies were compared and analyzed. This study collected drug addiction research articles from 2002 to 2021 by searching from the Web of Science, and classified academic disciplines based on SCI(E) and SSCI information. Author keyword co-occurrence analysis was also conducted, which provided confirmation that natural science mainly studied psychoactive substances and the reward system in the brain, while drug addiction studies reflecting demographic characteristics were conducted in the domain of social science. In the multidisciplinary field, all of the above topics were covered. Author co-citation analysis was also employed, which showed that there are superstars (i.e., authors who receive a rigorous amount of citation) in the field of natural science, while in the social science domain, authors were highly cited not only at the individual level but also at the institutional level.

An SAO-based Text Mining Approach for Technology Roadmapping Using Patent Information (기술로드맵핑을 위한 특허정보의 SAO기반 텍스트 마이닝 접근 방법)

  • Choi, Sung-Chul;Kim, Hong-Bin;Yoon, Jang-Hyeok
    • Journal of Technology Innovation
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    • v.20 no.1
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    • pp.199-234
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    • 2012
  • Technology roadmaps (TRMs) are considered to be the essential tool for strategic technology planning and management. Recently, rapidly evolving technological trends and severe technological competition are making TRM more important than ever before. That is because TRM plays a role of "map" that align organizational objectives with their relevant technologies. However, constructing and managing TRMs are costly and time-consuming because they rely on the qualitative and intuitive knowledge of human experts. Therefore, enhancing the productivity of developing TRMs is one of the major concerns in technology planning. In this regard, this paper proposes a technology roadmapping approach based on function of which concept includes objectives, structures and effects of a technology and which are represented as Subject-Action-Object structures extractable by exploiting natural language processing of patent text. We expect that the proposed method will broaden experts' technological horizons in the technology planning process and will help to construct TRMs efficiently with the reduced time and costs.

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Semantic Image Retrieval Using Color Distribution and Similarity Measurement in WordNet (컬러 분포와 WordNet상의 유사도 측정을 이용한 의미적 이미지 검색)

  • Choi, Jun-Ho;Cho, Mi-Young;Kim, Pan-Koo
    • The KIPS Transactions:PartB
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    • v.11B no.4
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    • pp.509-516
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    • 2004
  • Semantic interpretation of image is incomplete without some mechanism for understanding semantic content that is not directly visible. For this reason, human assisted content-annotation through natural language is an attachment of textual description to image. However, keyword-based retrieval is in the level of syntactic pattern matching. In other words, dissimilarity computation among terms is usually done by using string matching not concept matching. In this paper, we propose a method for computerized semantic similarity calculation In WordNet space. We consider the edge, depth, link type and density as well as existence of common ancestors. Also, we have introduced method that applied similarity measurement on semantic image retrieval. To combine wi#h the low level features, we use the spatial color distribution model. When tested on a image set of Microsoft's 'Design Gallery Line', proposed method outperforms other approach.

A Semantic-Based Feature Expansion Approach for Improving the Effectiveness of Text Categorization by Using WordNet (문서범주화 성능 향상을 위한 의미기반 자질확장에 관한 연구)

  • Chung, Eun-Kyung
    • Journal of the Korean Society for information Management
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    • v.26 no.3
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    • pp.261-278
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    • 2009
  • Identifying optimal feature sets in Text Categorization(TC) is crucial in terms of improving the effectiveness. In this study, experiments on feature expansion were conducted using author provided keyword sets and article titles from typical scientific journal articles. The tool used for expanding feature sets is WordNet, a lexical database for English words. Given a data set and a lexical tool, this study presented that feature expansion with synonymous relationship was significantly effective on improving the results of TC. The experiment results pointed out that when expanding feature sets with synonyms using on classifier names, the effectiveness of TC was considerably improved regardless of word sense disambiguation.

A Study on the Secure Database Controlled Under Cloud Environment (클라우드 환경하에서의 안전한 데이터베이스 구축에 관한 연구)

  • Kim, SungYong;Kim, Ji-Hong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.23 no.6
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    • pp.1259-1266
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    • 2013
  • Nowadays, the databases are getting larger and larger. As the company has difficulty in managing the database, they want to outsource the database to the cloud system. In this case the database security is more important because their database is managed by the cloud service provider. Among database security techniques, the encryption method is a well-certified and established technology for protecting sensitive data. However, once encrypted, the data can no longer be easily queried. The performance of the database depends on how to encrypt the sensitive data, and on the approach for searching, and the retrieval efficiency that is implemented. In this paper we propose the new suitable mechanism to encrypt the database and lookup process on the encrypted database under control of the cloud service provider. This database encryption algorithm uses the bloom filter with the variable keyword based index. Finally, we demonstrate that the proposed algorithm should be useful for database encryption related research and application activities.

The Development of a Trial Curriculum Classification and Coding System Using Group Technology

  • Lee, Sung-Youl;Yu, Hwa-Young;Ahn, Jung-A;Park, Ga-Eun;Choi, Woo-Seok
    • Journal of Engineering Education Research
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    • v.17 no.4
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    • pp.43-47
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    • 2014
  • The rapid development of science & technology and the globalization of society have accelerated the fractionation and specialization of academic disciplines. Accordingly, Korean colleges and universities are continually dropping antiquated courses to make room for new courses that better meet societal demands. With emphasis placed on providing students with a broader range of choices in terms of course selection, compulsory courses have given way to elective courses. On average, 4 year institutions of higher learning in Korea currently offer somewhere in the neighborhood of 1,000 different courses yearly. The classification of an ever growing list of courses offered and the practical use of such data would not be possible without the aid of computers. For example, if we were able to show the pre/post requisite relationship among various courses as well as the commonalities in substance among courses, such data generated regarding the interrelationship of different courses would undoubtedly greatly benefit the students, as well as the professors, during course registration. Furthermore, the GT system's relatively simple approach to course classification and coding will obviate the need for the development of a more complicated keyword based search engine, and hopefully contribute to the standardization of the course coding scheme in the future..Therefore, as a sample case project, this study will use GT to classify and code all courses offered at the College of Engineering of K University, thereby developing a system that will facilitate the scanning of relevant courses.

The Review on the Study of Bee Venom in the Journals of Korean Medicine (국내 봉독 관련 연구에 대한 고찰)

  • Han, Chang-Hyun;Lee, Yong-Seok;Kwon, Oh-Min;Lee, Young-Joon
    • Korean Journal of Acupuncture
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    • v.30 no.1
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    • pp.27-36
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    • 2013
  • Objectives : The focus of the analysis was laid on changes in research pertaining to bee venom in regards to time progression. Methods : We collected 365 articles on Bee venom study result from OASIS system using the Keyword 'bee venom, apitoxin, apitherapy, bee sting'. We figured out number and percentage of theses according to year, study method, journal, subject. Results : Bee venom papers published in the journal of korean medicine from 1976. The classification of papers associated with bee venom, clinical studies outnumbered the other study types by a ratio of 1.3 to 1, followed by 138 for experimental papers, and 22 for literature studies. Proportion of Experimental Papers Classified According to the Theme, 16 for pain-killing, 14 papers concentrated on apoptosis anticancer, 13 for anti inflammatory, 11 for arthritis, and other disorders were followed. Type analysis of papers associated with bee venom in clinical trials, lumbar disorders comprised 38 out of 205 papers, 35 papers concentrated on upper limb disorders, 34 papers concentrated on systemic disease, followed by the effect on body. Conclusions : Bee venom is a treatment method based on the unique theory of Korean traditional medicine. Its effort and academical approach on bee venom are expected to receive positive evaluation through numerous research works.