• Title/Summary/Keyword: Bigdata Convergence

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An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research

  • Sungchul Kim;Sungman Cho;Kyungjin Cho;Jiyeon Seo;Yujin Nam;Jooyoung Park;Kyuri Kim;Daeun Kim;Jeongeun Hwang;Jihye Yun;Miso Jang;Hyunna Lee;Namkug Kim
    • Korean Journal of Radiology
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    • v.22 no.12
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    • pp.2073-2081
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    • 2021
  • Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.

A Study on Implementation of Fraud Detection System (FDS) Applying BigData Platform (빅데이터 기술을 활용한 이상금융거래 탐지시스템 구축 연구)

  • Kang, Jae-Goo;Lee, Ji-Yean;You, Yen-Yoo
    • Journal of the Korea Convergence Society
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    • v.8 no.4
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    • pp.19-24
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    • 2017
  • The growing number of electronic financial transactions (e-banking) has entailed the rapid increase in security threats such as extortion and falsification of financial transaction data. Against such background, rigid security and countermeasures to hedge against such problems have risen as urgent tasks. Thus, this study aims to implement an improved case model by applying the Fraud Detection System (hereinafter, FDS) in a financial corporation 'A' using big data technique (e.g. the function to collect/store various types of typical/atypical financial transaction event data in real time regarding the external intrusion, outflow of internal data, and fraud financial transactions). As a result, There was reduction effect in terms of previous scenario detection target by minimizing false alarm via advanced scenario analysis. And further suggest the future direction of the enhanced FDS.

A Study of improving reliability on prediction model by analyzing method Big data (빅데이터 분석방법을 이용한 예측모형의 신뢰도 향상에 관한 연구)

  • Song, Min-Gu;Kim, Sun-Bae
    • Journal of Digital Convergence
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    • v.11 no.6
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    • pp.103-112
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    • 2013
  • Traditional method of establishing prediction model is usually using formal data stored in Data Base. However, nowadays advent of "smart" era brought by ground-breaking development of communication system makes informal data to dominate overall data, such 80% in total. Therefore, conventional method using formal data as establishing predicting model would be untrustworthy means in present. In other words, it is indispensible to make prediction model credible including informal data(SNS, image, video) and semi-formal data(log data). In this study, we increase credibility of predicting model adapting Bigdata method and comparing reliability of conventional measurement to real-data.

Blockchain based SDN multicontroller framework for Secure Sat_IoT networks (안전한 위성-IoT 네트워크를 위한 블록체인 기반 SDN 분산 컨트롤러 구현)

  • June Beom Park;Jong Sou Park
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.141-148
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    • 2023
  • Recent advancements in the integration of satellite technology and the Internet of Things (IoT) have led to the development of a sophisticated network ecosystem, capable of generating and utilizing vast amounts of big data across various sectors. However, this integrated network faces significant security challenges, primarily due to constraints like limited latency, low power requirements, and the incorporation of diverse heterogeneous devices. Addressing these security concerns, this paper explores the construction of a satellite-IoT network through the application of Software Defined Networking (SDN). While SDN offers numerous benefits, it also inherits certain inherent security vulnerabilities. To mitigate these issues, we propose a novel approach that incorporates blockchain technology within the SDN framework. This blockchain-based SDN environment enhances security through a distributed controller system, which also facilitates the authentication of IoT terminals and nodes. Our paper details the implementation plan for this system and discusses its validation through a series of tests. Looking forward, we aim to expand our research to include the convergence of artificial intelligence with satellite-IoT devices, exploring new avenues for leveraging the potential of big data in this context.

Risk Factors Identification and Priority Analysis of Bigdata Project (빅데이터 프로젝트의 위험요인 식별과 우선순위 분석)

  • Kim, Seung-Hee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.2
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    • pp.25-40
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    • 2019
  • Many companies are executing big data analysis and utilization projects to legitimize the development of new business areas or conversion of management or technical strategies. In Korea and abroad, however, such projects are failing because they are not completed within specified deadlines, which is not unrelated to the current situation in which the knowledge base for big data project risk management from an engineering perspective is grossly lacking. As such, the current study analyzes the risk factors of big data implementation and utilization projects, in addition to finding risk factors that are highly important. To achieve this end, the study extracts project risk factors via literature review, after which they are grouped using affinity methodology and sifted through expert surveys. The deduced risk factors are structuralize using factor analysis to develop a table that categorizes various types of big data project risk factors. The current study is significant that in it provides a basis for developing basic control indicators related to risk identification, risk assessment, and risk analysis. The findings from the study contribute greatly to the success of big data projects, by providing theoretical basis regarding efficient big data project risk management.

A Study on the Global Competitiveness and Way of Coexistence of Korean ICT Industries

  • Chang, Young-Hyun
    • International journal of advanced smart convergence
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    • v.4 no.2
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    • pp.124-130
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    • 2015
  • Infinite competition on ICT industries is starting again. The basis of competence over global dominance will be human resource, a global ecosystem for products and national agenda for science and technology, etc.. This paper presents the six solution for the Global Competitiveness and Coexistence of Korean ICT Industries. Korea should nurture the brand of "World Best Korean ICT Forever" to secure technical competency of ICT related fields in global market. All ICT technologies should be aligned to global standard and market demand from beginning and the ecosystem around product needs to be established. System framework for utilizing the resource of core SW experts must be established. Through global partnership with China as manufacturing base for Korea-developed products, technical competency can be maintained including product planning. Security measure for technical assets is mandatory. Finally, core technology that will drive the future of ICT industries in Korea should be regarded as core subjects.

A Study on the Calculation and Provision of Accruals-Quality by Big Data Real-Time Predictive Analysis Program

  • Shin, YeounOuk
    • International journal of advanced smart convergence
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    • v.8 no.3
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    • pp.193-200
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    • 2019
  • Accruals-Quality(AQ) is an important proxy for evaluating the quality of accounting information disclosures. High-quality accounting information will provide high predictability and precision in the disclosure of earnings and will increase the response to stock prices. And high Accruals-Quality, such as mitigating heterogeneity in accounting information interpretation, provides information usefulness in capital markets. The purpose of this study is to suggest how AQ, which represents the quality of accounting information disclosure, is transformed into digitized data in real-time in combination with IT information technology and provided to financial analyst's information environment in real-time. And AQ is a framework for predictive analysis through big data log analysis system. This real-time information from AQ will help financial analysts to increase their activity and reduce information asymmetry. In addition, AQ, which is provided in real time through IT information technology, can be used as an important basis for decision-making by users of capital market information, and is expected to contribute in providing companies with incentives to voluntarily improve the quality of accounting information disclosure.

The Study on the Improvement Plan of Bicycle Rental Center in Seoul by Big data Analysis (빅데이터 분석을 통한 서울시 자전거 대여소 개선방안 연구)

  • Kang, Sang-Min;Kang, Tae-Gu
    • Journal of Industrial Convergence
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    • v.15 no.1
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    • pp.33-42
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    • 2017
  • The purpose of this study is to identify the current situation of bicycle rental center in Seoul through big data analysis and to find ways to improve it. For this purpose, we analyzed the open data set provided by the Seoul Metropolitan Government and the typical data which is the citizen opinion of the customer center of the Seoul City bicycle. As the result, it was found that it is better to install a bicycle rental shop in Gangdong-gu, Seoul.

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The Trends of Next Generation Cyber Security (차세대 사이버 보안 동향)

  • Lee, Daesung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.11
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    • pp.1478-1481
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    • 2019
  • As core technologies(IoT, 5G, Cloud, Bigdata, AI etc) leading the Fourth Industrial Revolution promote smart convergence across the national socio-economic infrastructure, the threat of new forms of cyber attacks is increasing and the possibility of massive damage is also increasing. Reflecting this trend, cyber security is expanding from simple information protection to CPS(Cyber Physical System) protection that combines safety and security that implements hyper-connectivity and ultra-reliability. This study introduces the recent evolution of cyber attacks and looks at the next generation cyber security technologies based on the conceptual changes of cyber security technologies such as SOAR(Security Orchestration, Automation and Response) and Zero Trust.

Education Improvement Plan Related to Data Analysis & Processing in the ICT Field for the Era of Hyperconnectivity & Superintelligence

  • LEE, Seung-Woo;LEE, Sangwon
    • International Journal of Advanced Culture Technology
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    • v.9 no.4
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    • pp.102-109
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    • 2021
  • Since the 4th Industrial Revolution is implemented based on superintelligence, new insights must be provided through convergence studies with other fields to find optimal solutions to create new ideas. In this paper, we intende to present improvement measures for probability and statistical education, which is an athlete's subject on data analysis and processing in the ICT(Information & Communication Technologies) field in the era of superintelligence of the 4th industrial revolution. This paper aims to strengthen competitiveness through early development and commercialization of new technologies by presenting probabilities and statistical curriculums that require linkage in the ICT field. Second, it is necessary to present an educational system diagram linking probabilities and statistics in the ICT field to prepare a mid- to long-term response strategy for ICT education in response to innovative changes. Third, through a survey, we intend to present an effective educational operation plan linking probability and statistics to ICT major subjects by analyzing the perception of probability, statistical importance, and utilization of majors in this field.