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A Study on the Factors of Well-aging through Big Data Analysis : Focusing on Newspaper Articles (빅데이터 분석을 활용한 웰에이징 요인에 관한 연구 : 신문기사를 중심으로)

  • Lee, Chong Hyung;Kang, Kyung Hee;Kim, Yong Ha;Lim, Hyo Nam;Ku, Jin Hee;Kim, Kwang Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.354-360
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    • 2021
  • People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.

Predicting Functional Outcomes of Patients With Stroke Using Machine Learning: A Systematic Review (머신러닝을 활용한 뇌졸중 환자의 기능적 결과 예측: 체계적 고찰)

  • Bae, Suyeong;Lee, Mi Jung;Nam, Sanghun;Hong, Ickpyo
    • Therapeutic Science for Rehabilitation
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    • v.11 no.4
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    • pp.23-39
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    • 2022
  • Objective : To summarize clinical and demographic variables and machine learning uses for predicting functional outcomes of patients with stroke. Methods : We searched PubMed, CINAHL and Web of Science to identify published articles from 2010 to 2021. The search terms were "machine learning OR data mining AND stroke AND function OR prediction OR/AND rehabilitation". Articles exclusively using brain imaging techniques, deep learning method and articles without available full text were excluded in this study. Results : Nine articles were selected for this study. Support vector machines (19.05%) and random forests (19.05%) were two most frequently used machine learning models. Five articles (55.56%) demonstrated that the impact of patient initial and/or discharge assessment scores such as modified ranking scale (mRS) or functional independence measure (FIM) on stroke patients' functional outcomes was higher than their clinical characteristics. Conclusions : This study showed that patient initial and/or discharge assessment scores such as mRS or FIM could influence their functional outcomes more than their clinical characteristics. Evaluating and reviewing initial and or discharge functional outcomes of patients with stroke might be required to develop the optimal therapeutic interventions to enhance functional outcomes of patients with stroke.

Influences of Smartphone Overuse on Health and Academic Impairment in Adolescents : Using Data from Korea Youth Risk Behavior Web-based Survey of 2017 (스마트폰 과사용이 청소년의 건강과 학업에 미치는 영향 : 2017년 청소년건강행태온라인조사 자료를 이용하여)

  • Moon, Jong-Hoon;Jeon, Min-Jae;Song, E-Seul
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.2
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    • pp.177-186
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    • 2019
  • The purpose of this study was to investigate the influences of the smartphone overuse on health and academic impairment in adolescents. This study used data from Korea youth risk behavior web-based survey of 2017. This survey was conducted on 64,991 adolescents(middle and high school students), and 62,276 (95.8%) responded. The researchers used frequency analysis, independent t test, chi-square test and Pearson correlation analysis using SPSS 22. As a result, the usage rate of adolescents's smartphone was 54,603 out of 62,276, which was 87.7%. The purpose of smartphone usage was messenger(1st rank, 27.3%), SNS(2nd rank, 18.7%) and game(3rd rank, 13.3%). The average daily use time of the smartphone was 206.68±194.73 minutes. Girl students showed significantly more use time of smartphones than boy students(p<.001). Students with more than 206 minutes of smartphone use had worse health and academic performance than students with less than 206 minutes(p<.001). Time of smart phone usage and academic ability showed a weak correlation(p<.001, r=.245). The present findings showed that the higher the smartphone usage, the lower the health level and academic ability, and the author discussed these results.

Detecting Weak Signals for Carbon Neutrality Technology using Text Mining of Web News (탄소중립 기술의 미래신호 탐색연구: 국내 뉴스 기사 텍스트데이터를 중심으로)

  • Jisong Jeong;Seungkook Roh
    • Journal of Industrial Convergence
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    • v.21 no.5
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    • pp.1-13
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    • 2023
  • Carbon neutrality is the concept of reducing greenhouse gases emitted by human activities and making actual emissions zero through removal of remaining gases. It is also called "Net-Zero" and "carbon zero". Korea has declared a "2050 Carbon Neutrality policy" to cope with the climate change crisis. Various carbon reduction legislative processes are underway. Since carbon neutrality requires changes in industrial technology, it is important to prepare a system for carbon zero. This paper aims to understand the status and trends of global carbon neutrality technology. Therefore, ROK's web platform "www.naver.com." was selected as the data collection scope. Korean online articles related to carbon neutrality were collected. Carbon neutrality technology trends were analyzed by future signal methodology and Word2Vec algorithm which is a neural network deep learning technology. As a result, technology advancement in the steel and petrochemical sectors, which are carbon over-release industries, was required. Investment feasibility in the electric vehicle sector and technology advancement were on the rise. It seems that the government's support for carbon neutrality and the creation of global technology infrastructure should be supported. In addition, it is urgent to cultivate human resources, and possible to confirm the need to prepare support policies for carbon neutrality.

A Bibliometric Study on Sustainable Development Goals (SDGs) Research Trends in Entrepreneurship (키워드 네트워크 분석을 활용한 창업분야 지속가능발전목표(SDGs) 연구동향 분석)

  • An, Seung Kwon;Choi, Min Jung
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.2
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    • pp.21-34
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    • 2023
  • The purpose of this study is to examine the extent of Sustainable Development Goals (SDGs)-related research in the field of entrepreneurship globally since the adoption of the SDGs at the UN General Assembly, and to compare international and domestic research trends in order to determine the direction of SDGs-related research in entrepreneurship in Korea. Utilizing three databases-Web of Science (WoS), KCI, and DBpia- SDGs-related studies in entrepreneurship were extracted by employing specific search terms. After data purification, a total of 356 studies abroad and 4 studies in Korea were used for analysis. After data purification, a total of 356 international studies and 4 Korean studies were analyzed. Due to the limited number of domestic studies, the research trends were examined by conducting frequency analysis and keyword network analysis on international studies alone. Frequency analysis revealed that SDGs research in entrepreneurship primarily focused on sustainability-related terms and was conducted in conjunction with business models, innovation, entrepreneurship education, and strategies. Furthermore, yearly frequency analysis demonstrated an expansion of topics to encompass research on entrepreneurship and SDGs policies, the roles and capabilities of female entrepreneurs in SDGs implementation, energy start-ups and SDGs, directions for implementing SDGs in business schools and SDGs education, indicators for SDGs implementation and evaluation, and technologies for sustainability. The keyword network analysis identified central topics such as business, sustainability, SDGs, innovation, entrepreneurship, business models, and education, with research areas extending to entrepreneurship ecosystems, change and strategy, ethics, and climate. This study holds significance in establishing a foundation for SDGs research in entrepreneurship, which is currently an underexplored area in Korea, by presenting emerging research trends related to SDGs in entrepreneurship.

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Development of Information Technology Infrastructures through Construction of Big Data Platform for Road Driving Environment Analysis (도로 주행환경 분석을 위한 빅데이터 플랫폼 구축 정보기술 인프라 개발)

  • Jung, In-taek;Chong, Kyu-soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.3
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    • pp.669-678
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    • 2018
  • This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

A Distributed SPARQL Query Processing Scheme Considering Data Locality and Query Execution Path (데이터 지역성 및 질의 수행 경로를 고려한 분산 SPARQL 질의 처리 기법)

  • Kim, Byounghoon;Kim, Daeyun;Ko, Geonsik;Noh, Yeonwoo;Lim, Jongtae;Bok, kyoungsoo;Lee, Byoungyup;Yoo, Jaesoo
    • KIISE Transactions on Computing Practices
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    • v.23 no.5
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    • pp.275-283
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    • 2017
  • A large amount of RDF data has been generated along with the increase of semantic web services. Various distributed storage and query processing schemes have been studied to efficiently use the massive amounts of RDF data. In this paper, we propose a distributed SPARQL query processing scheme that considers the data locality and query execution path of large RDF data. The proposed scheme considers the data locality and query execution path in order to reduce join and communication costs. In a distributed environment, when processing a SPARQL query, it is divided into several sub-queries according to the conditions of the WHERE clause by considering the data locality. The proposed scheme reduces data communication costs by grouping and processing the sub-queries through the index based on associated nodes. In addition, in order to reduce unnecessary joins and latency when processing the query, it creates an efficient query execution path considering data parsing cost, the amount of each node's data communication, and latency. It is shown through various performance evaluations that the proposed scheme outperforms the existing scheme.

Design of Splunk Platform based Big Data Analysis System for Objectionable Information Detection (Splunk 플랫폼을 활용한 유해 정보 탐지를 위한 빅데이터 분석 시스템 설계)

  • Lee, Hyeop-Geon;Kim, Young-Woon;Kim, Ki-Young;Choi, Jong-Seok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.1
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    • pp.76-81
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    • 2018
  • The Internet of Things (IoT), which is emerging as a future economic growth engine, has been actively introduced in areas close to our daily lives. However, there are still IoT security threats that need to be resolved. In particular, with the spread of smart homes and smart cities, an explosive amount of closed-circuit televisions (CCTVs) have been installed. The Internet protocol (IP) information and even port numbers assigned to CCTVs are open to the public via search engines of web portals or on social media platforms, such as Facebook and Twitter; even with simple tools these pieces of information can be easily hacked. For this reason, a big-data analytics system is needed, capable of supporting quick responses against data, that can potentially contain risk factors to security or illegal websites that may cause social problems, by assisting in analyzing data collected by search engines and social media platforms, frequently utilized by Internet users, as well as data on illegal websites.

An XML Structure Translation System using Schema Structure Data Mapping (스키마 구조 데이타 매핑을 이용한 XML 구조변환 시스템)

  • 송종철;김창수;정회경
    • Journal of KIISE:Computing Practices and Letters
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    • v.10 no.5
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    • pp.406-418
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    • 2004
  • Last days, various kinds of applications and system were individually introduced into specific groups or enterprises by different objective without considering interoperability among those. However, the environment for data processing is changing rapidly in these days. And now the necessity is growing to integrate and couple applications and system in the process dimension for more flexible and quicker data processing on these application programs and system. When integrating these application programs or system, an integration based on XML is recommended as it is one of good methods which will the additional cost and satisfy the requirements of the integration. This is because the XML is not only device-independent data type which can be used any platform, but also it uses XSLT, the document conversion standard established by W3C, which allows easy data conversion from one to another type on occasion of demands. This paper studies a design and implementation of system to convert XML structure. This system shows the structure of source- side providing data and destination-side processing data with using XML schema that defines structural information of a XML document. And this system defines the structure relationship of desired form as mapping structural information and data. This system creates the XSLT document that defines conversion rule between two structures based information which is defined. The XSLT document which is created as described above will convert data to be appropriate to the structure of the destination- side. By implementing this system, it is able to apply a document into various kinds of structure without considering specific system or platform and it is able to construct XSLT document to which meaning of desired form can be given. This paper aims to offer a process conversion between documents and to improve interoperability and scalability, so that we can contribute to build XML document processing environment

A Study of Integrating ASP Databases with Customer Databases (ASP 용의 데이터베이스와 고객 데이터베이스 연동에 관한 연구)

  • Kim, Ho-Yoon;Lee, Jae-Won
    • The KIPS Transactions:PartD
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    • v.11D no.5
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    • pp.1063-1072
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    • 2004
  • In the ASP(Application Service Provider) business, applications using database sometimes require some data from clients' databases. These days such data are extracted from client database using manual database operations as an EXCEL file and the ASP, once receiving this file, transfers it into the application's database using manual database operations. This paper describes how to deal with data transmitting between the client database and ASP database on the web without using database manual operations for data extraction and insertion. We propose a framework which enables to transmit client data in a systematical way, to match different attribute names of each database for sharing same attribute values, and to avoid exposing information about the network path of client database to the ASP. This approach consists of two steps of data processing. The first is extracting data from client database as XML format by using a downloaded client program from ASP site, the second is uploading and storing the XML file into the ASP database. The implemented prototype system shows the suggested data integration paradigm is valid and ASP business needing integration of client database can be activated using it.