• Title/Summary/Keyword: State identification

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Identifying Research Trends in Big data-driven Digital Transformation Using Text Mining (텍스트마이닝을 활용한 빅데이터 기반의 디지털 트랜스포메이션 연구동향 파악)

  • Minjun, Kim
    • Smart Media Journal
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    • v.11 no.10
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    • pp.54-64
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    • 2022
  • A big data-driven digital transformation is defined as a process that aims to innovate companies by triggering significant changes to their capabilities and designs through the use of big data and various technologies. For a successful big data-driven digital transformation, reviewing related literature, which enhances the understanding of research statuses and the identification of key research topics and relationships among key topics, is necessary. However, understanding and describing literature is challenging, considering its volume and variety. Establishing a common ground for central concepts is essential for science. To clarify key research topics on the big data-driven digital transformation, we carry out a comprehensive literature review by performing text mining of 439 articles. Text mining is applied to learn and identify specific topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview. A total of 10 key research topics and relationships among the topics are identified. This study contributes to clarifying a systematized view of dispersed studies on big data-driven digital transformation across multiple disciplines and encourages further academic discussions and industrial transformation.

A New Methodology for Advanced Gas Turbine Engine Simulation

  • M.S. Chae;Y.C. Shon;Lee, B.S.;J.S. Eom;Lee, J.H.;Kim, Y.R.;Lee, H.J.
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2004.03a
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    • pp.369-375
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    • 2004
  • Gas turbine engine simulation in terms of transient, steady state performance and operational characteristics is complex work at the various engineering functions of aero engine manufacturers. Especially, efficiency of control system design and development in terms of cost, development period and technical relevance implies controlling diverse simulation and identification activities. The previous engine simulation has been accomplished within a limited analysis area such as fan, compressor, combustor, turbine, controller, etc. and this has resulted in improper engine performance and control characteristics because of limited interaction between analysis areas. In this paper, we propose a new simulation methodology for gas turbine engine performance analysis as well as its digital controller to solve difficulties as mentioned above. The novel method has particularities of (ⅰ) resulting in the integrated control simulation using almost every component/module analysis, (ⅱ) providing automated math model generation process of engine itself, various engine subsystems and control compensators/regulators, (ⅲ) presenting total sophisticated output results and easy understandable graphic display for a final user. We call this simulation system GT3GS (Gas Turbine 3D Graphic Simulator). GT3GS was built on both software and hardware technology for total simulation capable of high calculation flexibility as well as interface with real engine controller. All components in the simulator were implemented using COTS (Commercial Off the Shelf) modules. In addition, described here includes GT3GS main features and future works for better gas turbine engine simulation.

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A DEVELOPMENT OF INTELLIGENT CONSTRUCTION LIFT-CAR TOOLKIT DEVICE FOR CONSTRUCTION VERTICAL LOGISTICS MANAGEMENT

  • Chang-Yeon Cho;Soon-Wook Kwon;Tae-Hong Shin;Sang-Yoon Chin;Yea-Sang Kim;Joo-Hyung Lee
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.242-249
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    • 2009
  • High-rise construction sites, especially those situated in spatially constrained urban areas, have difficulties in timely delivery of materials. Modern techniques such as Just-in-time delivery, and use of information technology such as Project Management Information System (PMIS), are targeted to improve the efficiency of the logistics. Such IT-driven management techniques can be further benefited from state-of-the-art devices such as Radio Frequency Identification (RFID) tags and Ubiquitous Sensor Networks (USN), which has resulted in notable achievements in automated logistics management at the construction sites. Based on those achievements, this research develops USN hardware toolkits for construction lifts, which aims to be automated the vertical material delivery by sensing the material information and routing it automatically to the right place. The gathered information from the sensors can also be used for monitoring the overall status. The developed system will be tested in the actual high-rise construction sites to assess the system's feasibility. The proposed system is being implemented using Zigbee communication modules and RFID sensor networks which will communicate with the intelligent palette system (previously developed by the authors). To support the system, a lift-mountable intelligent toolkit is under development. Its feasibility test will be conducted by applying the implemented system to a test bed and then analyzing efficiency of the system and the toolkit. The collected test data will be provided as a basis of autonomous vertical transport equipment development. From this research, efficient management of the material lift is expected with increased accuracy, as well as better management of overall construction schedule benefited from the system. Further research will be expected to develop a smart construction lift, which will eliminate the need for human supervision, thus enabling a real 'autonomous' operation of the system.

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The first attempt of utilization of a wideband autonomous acoustic system and its general knowledge on analyzing the wideband acoustic data (광대역 자율 음향 시스템의 국내 최초 활용 시도와 광대역 음향 데이터 분석 방안)

  • KANG, Myounghee;CHO, Youn-Hyoung;LA, Hyoung sul;SON, Wuju;YUN, Hyeju;ADRIANUS, Aldwin;AN, Young-Su
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.58 no.2
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    • pp.130-140
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    • 2022
  • Recently, wideband acoustic technology has been introduced and started to be used in fisheries acoustic surveys in various waters worldwide. Wideband acoustic data provides high vertical resolution, high signal-to-noise ratio and continuous frequency characteristics over a wide frequency range for species identification. In this study, the main characteristics of wideband acoustic systems were elaborated, and a general methodology for wideband acoustic data analysis was presented using data collected in frequency modulation mode for the first time in Republic of Korea. In particular, this study described the data recording method using the mission planner of the wideband autonomous acoustic system, wideband acoustic data signal processing, calibration and the wideband frequency response graph. Since wideband acoustic systems are currently installed on many training and research vessels, it is expected that the results of this study can be used as basic knowledge for fisheries acoustic research using the state-of-the-art system.

Preparation and identification of U(IV) for the investigation of behaviors of uranium in a disposal repository (처분장에서 우라늄 거동 규명을 위한 U(IV)의 제조 및 확인)

  • Kim, Seung Soo;Kang, Kwang Chul;Kim, Jung Suck;Jung, Euo Chang;Baik, Min Hoon
    • Analytical Science and Technology
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    • v.21 no.2
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    • pp.143-147
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    • 2008
  • U(IV) ion, the valance state of uranium presumed at in a deep-depth disposal of a spent fuel, was prepared and separated from U(VI) ion. In order to prepare U(IV) ion, tests were performed by adding several reducing agents into a uranyl solution or by dissolution of uranium oxide in a mixed acid added with a reducing agent. The valance states of the uranium in the prepared solutions were identified by separating two ions with a Dowex AG 50W-X8 cation exchange resins and measuring the solutions using a laser-induced fluorescence spectroscopy. However, U(IV) and U(VI) were not separated by a Lichroprep Si60 exchange resin in the same separation condition of Pu(IV) and Pu(VI).

Identification of indirect effects in the two-condition within-subject mediation model and its implementation using SEM

  • Eujin Park;Changsoon Park
    • Communications for Statistical Applications and Methods
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    • v.30 no.6
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    • pp.631-652
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    • 2023
  • In the two-condition within-subject mediation design, pairs of variables such as mediator and outcome are observed under two treatment conditions. The main objective of the design is to investigate the indirect effects of the condition difference (sum) on the outcome difference (sum) through the mediator difference (sum) for comparison of two treatment conditions. The natural condition variables mean the original variables, while the rotated condition variables mean the difference and the sum of two natural variables. The outcome difference (sum) is expressed as a linear model regressed on two natural (rotated) mediators as a parallel two-mediator design in two condition approaches: the natural condition approach uses regressors as the natural condition variables, while the rotated condition approach uses regressors as the rotated condition variables. In each condition approach, the total indirect effect on the outcome difference (sum) can be expressed as the sum of two individual indirect effects: within- and cross-condition indirect effects. The total indirect effects on the outcome difference (sum) for both condition approaches are the same. The invariance of the total indirect effect makes it possible to analyze the nature of two pairs of individual indirect effects induced from the natural conditions and the rotated conditions. The two-condition within-subject design is extended to the addition of a between-subject moderator. Probing of the conditional indirect effects given the moderator values is implemented by plotting the bootstrap confidence intervals of indirect effects against the moderator values. The expected indirect effect with respect to the moderator is derived to provide the overall effect of moderator on the indirect effect. The model coefficients are estimated by the structural equation modeling approach and their statistical significance is tested using the bias-corrected bootstrap confidence intervals. All procedures are evaluated using function lavaan() of package {lavaan} in R.

Modeling and Trends of Road Transport Development in Eastern European Countries

  • Viktoriia Harkava;Olena Pylypenko;Oleksandr Haisha;Armen Aramyan;Volodymyr Kairov
    • International Journal of Computer Science & Network Security
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    • v.24 no.3
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    • pp.189-195
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    • 2024
  • Road transport occupies the largest share in domestic and international transport. It is of key importance for the development of the economy, forasmuch as it provides the livelihood of the population, the development of the national economy, the possibility of establishing foreign economic relations. The purpose of the research is as follows: analysis of the current state of functioning of the road transport sector in Eastern Europe and identification of key problems and trends in its development. Research methods: Methods of grouping, comparison and generalization, correlation analisys have been used to identify the dynamics of the main indicators of road transport in Eastern Europe. The method of correlation-regression analysis has been applied to determine the impact of increasing the length of roads on the turnover of the road freight transport and the number of employed population in this area. Results. It has been found that the increase in the employed population by 96% and increase in revenues from transportation and storage of goods, postal and courier services (turnover of the road freight transport - in the original language) in the field of road transport by 82% is explained by the change in transport infrastructure capacity by increasing length of highways. According to the correlation analysis, it has been revealed that there is a high direct dependence between the length of roads and increased revenues from transportation and storage of goods in the field of road transport, as well as between the length of roads and increasing employment in this area.

Multi-Label Classification for Corporate Review Text: A Local Grammar Approach (머신러닝 기반의 기업 리뷰 다중 분류: 부분 문법 적용을 중심으로)

  • HyeYeon Baek;Young Kyun Chang
    • Information Systems Review
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    • v.25 no.3
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    • pp.27-41
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    • 2023
  • Unlike the previous works focusing on the state-of-the-art methodologies to improve the performance of machine learning models, this study improves the 'quality' of training data used in machine learning. We propose a method to enhance the quality of training data through the processing of 'local grammar,' frequently used in corpus analysis. We collected a vast amount of unstructured corporate review text data posted by employees working in the top 100 companies in Korea. After improving the data quality using the local grammar process, we confirmed that the classification model with local grammar outperformed the model without it in terms of classification performance. We defined five factors of work engagement as classification categories, and analyzed how the pattern of reviews changed before and after the COVID-19 pandemic. Through this study, we provide evidence that shows the value of the local grammar-based automatic identification and classification of employee experiences, and offer some clues for significant organizational cultural phenomena.

State-of-the-Art in Cyber Situational Awareness: A Comprehensive Review and Analysis

  • Kookjin Kim;Jaepil Youn;Hansung Kim;Dongil Shin;Dongkyoo Shin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.5
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    • pp.1273-1300
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    • 2024
  • In the complex virtual environment of cyberspace, comprised of digital and communication networks, ensuring the security of information is being recognized as an ongoing challenge. The importance of 'Cyber Situation Awareness (CSA)' is being emphasized in response to this. CSA is understood as a vital capability to identify, understand, and respond to various cyber threats and is positioned at the heart of cyber security strategies from a defensive perspective. Critical industries such as finance, healthcare, manufacturing, telecommunications, transportation, and energy can be subjected to not just economic and societal losses from cyber threats but, in severe cases, national losses. Consequently, the importance of CSA is being accentuated and research activities are being vigorously undertaken. A systematic five-step approach to CSA is introduced against this backdrop, and a deep analysis of recent research trends, techniques, challenges, and future directions since 2019 is provided. The approach encompasses current situation and identification awareness, the impact of attacks and vulnerability assessment, the evolution of situations and tracking of actor behaviors, root cause and forensic analysis, and future scenarios and threat predictions. Through this survey, readers will be deepened in their understanding of the fundamental importance and practical applications of CSA, and their insights into research and applications in this field will be enhanced. This survey is expected to serve as a useful guide and reference for researchers and experts particularly interested in CSA research and applications.

Development of a sequence-characterized amplified region (SCAR) marker for female off-season flowering detection in date palm (Phoenix dactylifera L.)

  • Lalita Kethirun;Puangpaka Umpunjun;Ngarmnij Chuenboonngarm;Unchera Viboonjun
    • Journal of Plant Biotechnology
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    • v.50
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    • pp.190-199
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    • 2023
  • Date palm (Phoenix dactylifera L.: Arecaceae) is a dioecious species where only female trees bear fruits. In their natural state, date palms produce dates once a year. However, in Thailand, some trees were observed to produce dates during the off-season, despite no variations in morphology. The availability of such off-season fruits can significantly increase their market value. Interestingly, most female off-season date palms investigated in this study were obtained through micropropagation. Hence, there is an urgent need for genetic markers to distinguish female offseason flowering plantlets within tissue culture systems. In this study, we aimed to develop random amplification of polymorphic DNA-sequence characterized amplified region (RAPD-SCAR) markers for the identification of female off-season flowering date palms cultivated in Thailand. A total of 160 random decamer primers were employed to screen for specific RAPD markers in off-season flowering male and female populations. Out of these, only one primer, OPN-02, generated distinct genomic DNA patterns in female off-season flowering (FOFdp) individuals compared to female seasonal flowering genotypes. Based on the RAPD-specific sequence, specific SCAR primers denoted as FOFdpF and FOFdpR were developed. These SCAR primers amplified a single 517-bp DNA fragment, predominantly found in off-season flowering populations, with an accuracy rate of 60%. These findings underscore the potential of SCAR marker technology for tracking offseason flowering in date palms. Notably, a BLAST analysis revealed a substantial similarity between the SCAR marker sequence and the transcript variant mRNA from Phoenix dactylifera encoding the SET DOMAIN GROUP 40 protein. In Arabidopsis, this protein is involved in the epigenetic regulation of flowering time. The genetic potential of the off-season flowering traits warrants further elucidation.