• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.83-105
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• 2019

This study aims to suggest an effective method for the automatic classification of keywords with similar patterns by calculating pattern similarity of temporal data. For this, large scale news on the Web were collected and time series data composed of 120 time segments were built. To make training data set for the performance test of the proposed model, 440 representative keywords were manually classified according to 8 types of trend. This study introduces a Dynamic Time Warping(DTW) method which have been commonly used in the field of time series analytics, and proposes an application model, MA-DTW based on a Moving Average(MA) method which gives a good explanation on a tendency of trend curve. As a result of the automatic classification by a k-Nearest Neighbor(kNN) algorithm, Euclidean Distance(ED) and DTW showed 48.2% and 66.6% of maximum micro-averaged F1 score respectively, whereas the proposed model represented 74.3% of the best micro-averaged F1 score. In all respect of the comprehensive experiments, the suggested model outperformed the methods of ED and DTW.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.163-170
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• 2017

Internet of things (IoT) is a new paradigm for collecting, processing and analyzing various contents in order to detect anomalies and to monitor particular patterns in a specific environment. The collected data can be used to discover new patterns and to offer new insights. IoT-enabled data mashup is a new technology to combine various types of information from multiple sources into a single web service. Mashup services create a new horizon for different applications. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations may utilize IoT - enabled data mashup service to merge different types of datasets from different IoT sensor networks in order to leverage their data analytics performance and the accuracy of the predictions. This paper presents an IoT - enabled data mashup service, where the multimedia data is collected from the various IoT platforms, then fed into an environmental cognition service which executes different image processing techniques such as noise removal, segmentation, and feature extraction, in order to detect interesting patterns in hazardous areas. The noise present in the captured images is eliminated with the help of a noise removal and background subtraction processes. Markov based approach was utilized to segment the possible regions of interest. The viable features within each region were extracted using a multiresolution wavelet transform, then fed into a discriminative classifier to extract various patterns. Experimental results have shown an accurate detection performance and adequate processing time for the proposed approach. We also provide a data mashup scenario for an IoT-enabled environmental hazard detection service and experimentation results.

• The Mathematical Education
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• v.40 no.1
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• pp.77-92
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• 2001

In this study, the number of theses conducted in 1990's for the master's degree in mathematics education was investigated in terms of their fields and themes. These theses were analysed as to how much they had been studied according to the field and whether they had conformed to the expectations and requirements for research in mathematics education under the current educational curriculum. Futhermore, this study aimed to discover advancing directions of research in mathematics education. The results are as follows: First, the rate of annual thesis presentations decreased as many as 3.82% in 1994 compared with the previous year, but the rate increased steadily in the other years showing an overall annual average increase of 8.41%. Second, in the geographical distribution of thesis presentations among local provinces, Seoul represented the highest frequency at 41.13% and Cheju Island the lowest at 1.68%. When the annual thesis presentations were analysed among regions, their number increased steadily in Seoul, but fluctuated in most other regions. Third, regarding study themes, theses on mathematics education formed 70.91% of the total while those focusing on pure mathematics formed 29.09%. Among the theses of mathematics education, most were based on teaching curriculums and the least were based on education assessment. Among the theses on teaching curriculum, teaching analytics formed the highest rate. Theses on education technology, such as computerizing and computing, have shown to be increasing annually and formed 8.95% of the total in 1999. The study also indicated that especially in the late 1990's, there have been many designed programs based on the Web, like JAVA and CGI, and studies on teaching and teaming methods using the internet.

• Annals of Clinical Neurophysiology
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• v.22 no.2
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• pp.92-103
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• 2020

Background: The purpose of this study was to identify the top-100 cited articles on genetic generalized epilepsy (GGE) published in journals that have made key contributions to the field of epilepsy. Methods: We searched the Web of Science website produced by Clarivate Analytics for articles on GGE, and sorted them according to the number of citations to identify the top-100 cited articles. We then manually reviewed the contents of the top-100 cited articles, which were designated as "citation classics". Results: The top-100 cited articles were published in 27 journals, with the largest proportion appearing in Epilepsia (19 articles). The articles originated from institutions in 17 countries, with 31 articles from the USA. The institution associated with the largest numbers of articles in the field of GGE was the University of Melbourne, Australia (9 articles). Panayiotopoulos C. P. was the first author of three articles, and was listed most frequently in the GGE citation classics. The publication years were concentrated in the 2000s, when 56 articles were published. The most-common study topics were genetics (35 articles) and neuroimaging (17 articles). Conclusions: This study has identified the top-100 cited articles on GGE. These citation classics represent the landmark articles on GGE, and they provide useful insights into international research leaders and the research trends in the field.

• Journal of Information Science Theory and Practice
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• v.6 no.4
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• pp.6-16
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• 2018

This article shows an approach to the study of two fundamental aspects of the prepublication of scientific manuscripts in specialized repositories (arXiv). The first refers to the size of the interaction of "standard papers" in journals appearing in the Web of Science (WoS)-now Clarivate Analytics-and "non-standard papers" (manuscripts appearing in arXiv). Specifically, we analyze the citations found in the WoS to articles in arXiv. The second aspect is how publication in arXiv affects the citation count of authors. The question is whether or not prepublishing in arXiv benefits authors from the point of view of increasing their citations, or rather produces a dispersion, which would diminish the relevance of their publications in evaluation processes. Data have been collected from arXiv, the websites of the journals, Google Scholar, and WoS following a specific ad hoc procedure. The number of citations in journal articles published in WoS to preprints in arXiv is not large. We show that citation counts from regular papers and preprints using different sources (arXiv, the journal's website, WoS) give completely different results. This suggests a rather scattered picture of citations that could distort the citation count of a given article against the author's interest. However, the number of WoS references to arXiv preprints is small, minimizing this potential negative effect.

• Restorative Dentistry and Endodontics
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• v.48 no.3
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• pp.27.1-27.11
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• 2023

Objectives: Advancements in nanotechnology have led to the widespread usage of nanoparticles in the endodontic field. This bibliometric study aimed to determine and analyze the top 100 most-cited articles about nanoparticles in endodontics from 2000 to 2022. Materials and Methods: A detailed electronic search was conducted on the "Clarivate Analytics Web of Science, All Databases" to receive the most-cited articles related to the topic. Articles were ranked in descending order based on their citation counts, and the first 100 were selected for bibliometric analysis. Parameters such as citation density, publication year, journal, country, institution, author, study design, study field, evidence level, and keywords were analyzed. Results: The top 100 most-cited articles received 4,698 citations (16-271) with 970.21 (1.91-181) citation density in total. Among decades, citations were significantly higher in 2011-2022 (p < 0.001). Journal of Endodontics had the largest number of publications. Canada and the University of Toronto made the highest contribution as country and institution, respectively. Anil Kishen was the 1 who participated in the largest number of articles. The majority of the articles were designed in vitro. The main study field was "antibacterial effect." Among keywords, "nanoparticles" followed by "Enterococcus faecalis" were used more frequently. Conclusions: Developments in nanotechnology had an impact on the increasing number of studies in recent years. This bibliometric study provides a comprehensive view of nanoparticle advances and trends using citation analysis.

• The Journal of Bigdata
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• v.8 no.2
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• pp.83-95
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• 2023

Big data analytics and AI play a critical role in the development of smart plants. This study presents a big data platform for plant data and an 'AutoML platform' for AI-based plant O&M(Operation and Maintenance). The big data platform collects, processes and stores large volumes of data generated in plants using Hadoop, Spark, and Kafka. The AutoML platform is a machine learning automation system aimed at constructing predictive models for equipment prognostics and process optimization in plants. The developed platforms configures a data pipeline considering compatibility with existing plant OISs(Operation Information Systems) and employs a web-based GUI to enhance both accessibility and convenience for users. Also, it has functions to load user-customizable modules into data processing and learning algorithms, which increases process flexibility. This paper demonstrates the operation of the platforms for a specific process of an oil company in Korea and presents an example of an effective data utilization platform for smart plants.

• Safety and Health at Work
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• v.15 no.3
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• pp.245-254
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• 2024

Background: In recent years, the rise of workplace racial discrimination and microaggressions has decreased the efficiency and productivity of organizations and institutions, and realization of organizational goals globally. Accordingly, it was decided to conduct a systematic review and meta-analysis in the present study with the aim of investigating the prevalence of microaggression and racial discrimination in the workplace. Methods: The PubMed, Scopus, Web of Science, ScienceDirect and Google Scholar databases were systematically searched for studies that had reported the effects of work stress among managers. The search did include a lower time limit and was conducted in June 2023. The heterogeneity of the studies was investigated using the I² index, and accordingly random effects method was adopted for meta-analysis. Data analysis was conducted with the Comprehensive Meta-Analysis (v.2) software. Results: In the review of seven studies with a sample size of 2998 people, the overall prevalence of microaggression and racial discrimination in the workplace was found to be 73.6% and 18.8%, respectively. Publication bias within the selected studies was examined with the Egger's test, which indicated the absence of publication bias for the pooled prevalence of workplace microaggression (p: 0.264) and for the pooled prevalence of workplace racial discrimination (p: 0.061). Conclusion: The results obtained from this report indicate the high impact of micro-aggression and racial discrimination in the workplace. Considering the negative effects of such behaviours, the findings from this study will be helpful to managers and health policymakers.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.141-174
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• 2021

In this study, by examining the actual usage data of the university library website before and after COVID-19 outbreak, the usage behavior of users was analyzed, and the data before and after the virus outbreak was compared, so that university libraries can provide more efficient information services in a pandemic situation. We would like to suggest ways to improve it. In this study, the user traffic made on the website of University C was 'using Google Analytics', from January 2018 to December 2018 before the oneself of the COVID-19 virus and from January 2020 to 2020 after the outbreak of the virus. A comparative analysis was conducted until December. Web traffic variables were analyzed by classifying them into three characteristics: 'User information', 'Path', and 'Site behavior' based on metrics such as session, user, number of pageviews, number of pages per session time, and bounce rate. To summarize the study results, first, when compared with data from January 1 to January 20 before the oneself of COVID-19, users, new visitors, and sessions all increased compared to the previous year, and the number of sessions per user, number of pageviews, and number of pages per session, which showed an upward trend before the virus outbreak in 2020, increased significantly. Second, as social distancing was upgraded to the second stage, there was also a change in the use of university library websites. In 2020 and 2018, when the number os students was the lowest, the number of page views increased by 100,000 more in 2020 compared to 2018, and the number of pages per session also recorded10.46, which was about 2 more pages compared to 2018. The bounce rate also recorded 14.38 in 2018 and 2019, but decreased by 1 percentage point to 13.05 in 2020, which led to more active use of the website at a time when social distancing was raised.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.163-170
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• 2020

With the development of information and communication technologies, the growing volume of data is increasing exponentially, raising interest in big data. As technologies related to big data have developed, big data is being collected, stored, processed, analyzed, and utilized in many fields. Big data analytics in the health care sector, in particular, is receiving much attention because they can also have a huge social and economic impact. It is predicted that it will be able to use Big Data technology to analyze patients' diagnostic data and reduce the amount of money that is spent on simple hospital care. Therefore, in this thesis, patient data is analyzed to present to patients who are unable to go to the hospital or caregivers who do not have medical expertise with close care guidelines. First, the collected patient data is stored in HDFS and the data is processed and classified using R, a big data processing and analysis tool, in the Hadoop environment. Visualize to a web server using R Shiny, which is used to implement various functions of R on the web.