• Title/Summary/Keyword: Web technologies

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Topic Modeling on Research Trends of Industry 4.0 Using Text Mining (텍스트 마이닝을 이용한 4차 산업 연구 동향 토픽 모델링)

  • Cho, Kyoung Won;Woo, Young Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.7
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    • pp.764-770
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    • 2019
  • In this research, text mining techniques were used to analyze the papers related to the "4th Industry". In order to analyze the papers, total of 685 papers were collected by searching with the keyword "4th industry" in Korea Journal Index(KCI) from 2016 to 2019. We used Python-based web scraping program to collect papers and use topic modeling techniques based on LDA algorithm implemented in R language for data analysis. As a result of perplexity analysis on the collected papers, nine topics were determined optimally and nine representative topics of the collected papers were extracted using the Gibbs sampling method. As a result, it was confirmed that artificial intelligence, big data, Internet of things(IoT), digital, network and so on have emerged as the major technologies, and it was confirmed that research has been conducted on the changes due to the major technologies in various fields related to the 4th industry such as industry, government, education field, and job.

Livestock Disease Forecasting and Smart Livestock Farm Integrated Control System based on Cloud Computing (클라우드 컴퓨팅기반 가축 질병 예찰 및 스마트 축사 통합 관제 시스템)

  • Jung, Ji-sung;Lee, Meong-hun;Park, Jong-kweon
    • Smart Media Journal
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    • v.8 no.3
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    • pp.88-94
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    • 2019
  • Livestock disease is a very important issue in the livestock industry because if livestock disease is not responded quickly enough, its damage can be devastating. To solve the issues involving the occurrence of livestock disease, it is necessary to diagnose in advance the status of livestock disease and develop systematic and scientific livestock feeding technologies. However, there is a lack of domestic studies on such technologies in Korea. This paper, therefore, proposes Livestock Disease Forecasting and Livestock Farm Integrated Control System using Cloud Computing to quickly manage livestock disease. The proposed system collects a variety of livestock data from wireless sensor networks and application. Moreover, it saves and manages the data with the use of the column-oriented database Hadoop HBase, a column-oriented database management system. This provides livestock disease forecasting and livestock farm integrated controlling service through MapReduce Model-based parallel data processing. Lastly, it also provides REST-based web service so that users can receive the service on various platforms, such as PCs or mobile devices.

An Analysis of Existing Studies on Parallel and Distributed Processing of the Rete Algorithm (Rete 알고리즘의 병렬 및 분산 처리에 관한 기존 연구 분석)

  • Kim, Jaehoon
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.7
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    • pp.31-45
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    • 2019
  • The core technologies for intelligent services today are deep learning, that is neural networks, and parallel and distributed processing technologies such as GPU parallel computing and big data. However, for intelligent services and knowledge sharing services through globally shared ontologies in the future, there is a technology that is better than the neural networks for representing and reasoning knowledge. It is a knowledge representation of IF-THEN in RIF or SWRL, which is the standard rule language of the Semantic Web, and can be inferred efficiently using the rete algorithm. However, when the number of rules processed by the rete algorithm running on a single computer is 100,000, its performance becomes very poor with several tens of minutes, and there is an obvious limitation. Therefore, in this paper, we analyze the past and current studies on parallel and distributed processing of rete algorithm, and examine what aspects should be considered to implement an efficient rete algorithm.

Hazelcast Vs. Ignite: Opportunities for Java Programmers

  • Maxim, Bartkov;Tetiana, Katkova;S., Kruglyk Vladyslav;G., Murtaziev Ernest;V., Kotova Olha
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.406-412
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    • 2022
  • Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

Study on the Application of Big Data Mining to Activate Physical Distribution Cooperation : Focusing AHP Technique (물류공동화 활성화를 위한 빅데이터 마이닝 적용 연구 : AHP 기법을 중심으로)

  • Young-Hyun Pak;Jae-Ho Lee;Kyeong-Woo Kim
    • Korea Trade Review
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    • v.46 no.5
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    • pp.65-81
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    • 2021
  • The technological development in the era of the 4th industrial revolution is changing the paradigm of various industries. Various technologies such as big data, cloud, artificial intelligence, virtual reality, and the Internet of Things are used, creating synergy effects with existing industries, creating radical development and value creation. Among them, the logistics sector has been greatly influenced by quantitative data from the past and has been continuously accumulating and managing data, so it is highly likely to be linked with big data analysis and has a high utilization effect. The modern advanced technology has developed together with the data mining technology to discover hidden patterns and new correlations in such big data, and through this, meaningful results are being derived. Therefore, data mining occupies an important part in big data analysis, and this study tried to analyze data mining techniques that can contribute to the logistics field and common logistics using these data mining technologies. Therefore, by using the AHP technique, it was attempted to derive priorities for each type of efficient data mining for logisticalization, and R program and R Studio were used as tools to analyze this. Criteria of AHP method set association analysis, cluster analysis, decision tree method, artificial neural network method, web mining, and opinion mining. For the alternatives, common transport and delivery, common logistics center, common logistics information system, and common logistics partnership were set as factors.

Mobile Ultra-Broadband, Super Internet-of-Things and Artificial Intelligence for 6G Visions

  • Hamza Ali Alshawabkeh
    • International Journal of Computer Science & Network Security
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    • v.23 no.12
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    • pp.235-245
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    • 2023
  • Smart applications based on the Network of Everything also known as Internet of Everything (IoE) are increasing popularity as network connectivity requires rise further. As a result, there will be a greater need for developing 6G technologies for wireless communications in order to overcome the primary limitations of visible 5G networks. Furthermore, implementing neural networks into 6G will bring remedies for the most complex optimizing networks challenges. Future 6G mobile phone networks must handle huge applications that require data and an increasing amount of users. With a ten-year time skyline from thought to the real world, it is presently time for pondering what 6th era (6G) remote correspondence will be just before 5G application. In this article, we talk about 6G dreams to clear the street for the headway of 6G and then some. We start with the conversation of imaginative 5G organizations and afterward underline the need of exploring 6G. Treating proceeding and impending remote organization improvement in a serious way, we expect 6G to contain three critical components: cell phones super broadband, very The Web of Things (or IoT and falsely clever (artificial intelligence). The 6G project is currently in its early phases, and people everywhere must envision and come up with its conceptualization, realization, implementation, and use cases. To that aim, this article presents an environment for Presented Distributed Artificial Intelligence as-a-Services (DAIaaS) supplying in IoE and 6G applications. The case histories and the DAIaaS architecture have been evaluated in terms of from end to end latency and bandwidth consumption, use of energy, and cost savings, with suggestion to improve efficiency.

Android Based Mobile Combination Login Application (안드로이드 기반 모바일 통합로그인 애플리케이션)

  • Lim, Jung-Gun;Choi, Chang-Suk;Park, Tae-Eun;Ki, Hyo-Sun;An, Beongku
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.3
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    • pp.151-156
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    • 2013
  • Android that was made by Google and Open Handset Alliance is the open source software toolkit for mobile phone. In a few years, Android will be used by millions of Android mobile phones and other mobile devices, and become the main platform for application developers. In this paper, the integrated login application based on Google's Android platform is developed. The main features of the mobile combination login application content based on Android are as follows. First, the application has more convenient login functionality than the functionality of general web browser as the web browser of the mobile-based applications(web browser style applications) as well as security features and faster screen(view) capability by reducing the amount of data transfer. Second, the application is so useful for management of ID and Password, and it can easily manage multiple ID information such as message, mail, profile. The results of performance evaluation of the developed application show the functionality that can login many kinds of portal sites simultaneously as well as the ability that can maintain login continuously. Currently, we are trying to develope a couple of the technologies that can insert multiple accounts into one ID and check all information on one screen.

Comparative Reliability Evaluation on Semantic Service Platforms (시맨틱 서비스 플랫폼상에서의 신뢰성 비교 평가)

  • Jung, Han-Min;Lee, Mi-Kyoung;You, Beom-Jong;Kim, Do-Wan
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.1
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    • pp.105-109
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    • 2010
  • While numerous information services are provided on the Web as a core infrastructure of information society, semantic services using the Semantic Web technologies still stay deployed number and application range. This situation would be mainly originated from the failure of securing reliability to the user. Thus, this paper introduces an evaluation method for measuring reliabilities of the semantic services comparatively. To measure the reliability of the compared systems, the observer assesses 'precision in task performance' as a quantitative analysis and 'reliability of expectation-result' as a qualitative analysis described by the test persons. On the other hand, the test person should rate the functional reliability and reliability of the served information on the vector graph by himself with a scale from 0 to 5. Experimental results show that assessment by the observer is very similar to rating value by test persons, and that the accuracy of the served information has a close effect on the functional reliability. Through this paper, we can verify the essential factors for evaluating the reliability of semantic service systems. These are functional reliability and reliability of served information resulting from function execution. In particular, it has been proven that the reliability of the semantic information services largely influences the "Quality in Use" and therefore determines the major factors of the semantic service reliability.

Construction of Internet Public Library Asia (아시아 인터넷 공공 도서관(Internet Public Library Asia) 구축에 관한 연구)

  • 이원숙;일본명;일본명;일본명;일본명
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.13 no.2
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    • pp.59-73
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    • 2002
  • Libraries, not only research libraries but also public libraries, have been fundamentally affected by the immense spread of the Internet and the World Wide Web. Many public libraries have their Web pages, through which they are providing their new and conventional services. There are also web sites which provide library-like services. This paper shows an experimental project named Internet Public Library Asia, which provides information in multiple languages of information resources published in Chinese, Japanese and Korean languages. This paper firstly overviews how traditional public libraries have been affected by the Internet. Then, it describes a few aspects from the viewpoint of crucial library function on the Internet and also from the viewpoint of Asian resources and users. This paper secondly proposes a model to serve information about valuable resources published in multiple Asian languages, and then shows the metadata schema and a few software tools developed for IPL-Asia The name of IPL is borrowed from Internet Public Library based at University of Michigan, since it is, in part, a collaborative activity with the IPL in Michigan. The metadata schema is defined based both on Dublin Core and IEEE LOM and adapted for parallel description in the four languages, i. e. , Chinese, Japanese, Korean and English. The software tools provide functions to support collaboration among people engaged in development of metadata database and metadata editing. These tools have been developed based on the XML technologies.

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Analysis and Modeling of Traffic at Ntopia Subscriber Network of Korea Telecom (KT의 Ntopia가입자 망 트래픽 분석 및 모델링)

  • 주성돈;이채우
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.41 no.5
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    • pp.37-45
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    • 2004
  • As Internet technologies are mature, many new applications that are different characteristics are emerging. Recently we see wide use of P2P(Peer to Peer) applications of which traffic shows different statistical characteristics compared with traditional application such as web(HTTP) and FTP(File Transfer Protocol). In this paper, we measured subscriber network of KT(Korea Telecom) to analyze P2P traffic characteristics. We show flow characteristics of measured traffic. We also estimate Hurst parameter of P2P traffic and compare self-similarity with web traffic. Analysis results indicate that P2P traffic is much bustier than web traffic and makes both upstream traffic and downstream traffic be symmetric. To predict parameters related QoS such as packet loss and delays we model P2P traffic using two self-similar traffic models and predict both loss probability and mm delay then compare their accuracies. With simulation we show that the self-similar traffic models we derive predict the performance of P2P traffic accurately and thus when we design a network or evaluate its performance, we can use the P2P traffic model as reference input traffic.