• Title/Summary/Keyword: Demand for Research Information

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Analysis of Donation Demand for Expansion of National Policy Information Collection: Focused on National Association for Policy Information (국가 정책정보 수집력 확대를 위한 기증수요 분석 - 국가정책정보협의회 회원기관을 중심으로 -)

  • Yoon, Hee-Yoon;Oh, Seon-Kyung;Kim, Sin-Young
    • Journal of the Korean Society for Library and Information Science
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    • v.52 no.4
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    • pp.5-26
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    • 2018
  • The National Library of Korea, Sejong is a subject branch of the National Library of Korea, which is centered on policy information for governments and related research institutes. Therefore the strategic orientation of the NLKS to establish the essential identity and to enhance it's capacity is to collect and preserve policy information both domestic and abroad. In order to strengthen the capacity of the NLKS as a national conservation center of policy information, we surveyed and analyzed the perception of the operation and policy information services of the National Association for Policy Information and intention of policy information bulk donations of the member institutions, which are the producers and consumers of policy information. And based on the results, we suggested ways to strengthen the policy collection ability of NLKS.

The Study on the Demand Investigation of the International Ship Instrument Distribution Center Construction (국제선용품 유통센터 건립 수요조사 연구)

  • Kang, Byung-Young;Kim, Chul-Min
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.8
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    • pp.2827-2834
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    • 2010
  • The purpose of this paper is as follow. The first is to investigate ship instrument supplier's and consumer's needs. The second is to study a feasibility of international ship instrument distribution center at Busan port. Therefore, the research scheme was experimented through a questionnaire survey answered by 878 companies. The results of this research indicate the necessity of ship instrument distribution center. The results of this study will be helpful for the success management of ship instrument distribution center.

A Study on the Integrated System of the Hotel Employment Management and the Determinants of the Employment (호텔종사원의 통합적 채용관리 시스템과 채용결정요인에 대한 연구 - 채용 전문가와 지원자 간의 차이분석 -)

  • Kim, U-Jin
    • Journal of Applied Tourism Food and Beverage Management and Research
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    • v.17 no.2
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    • pp.61-94
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    • 2006
  • This study analyzes the integrated system of the hotel employment management and the differences between the persons of employment concerning and the applicants about the importance of the determinants of the employment around the five-star hotels in Seoul. Firstly, the integrated strategies are presented by 3 stages such as recruiting, selection and placement. And then the 15 determinants of the employment are derived to analyze the perceptional differences between the persons of employment concerning and the applicants about the important determinants and to present the reasons and strategical implications. The results of this study indicates that the strategy to make him/her aware of sufficient information about the hotel and job through the proper balancing demand and supply and the industry-university cooperation program order to maintain and utilize the human resource to be aligned with the business performance of the hotel.

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A STUDY ON IDENTIFICATION OF URBAN CHARACTERISTIC USING SPATIAL ARRANGEMENT METHOD

  • Chou, Tien-Yin;Kuo, Ching-Yi
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.984-987
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    • 2003
  • In order to rapidly catch up urban region’s detailed land-use or land-cover information; this research used the post-classification algorithm (Spatial Reclassification Kernel: SPARK) to create a land-use map of Taichung City. We discussed the urban land-use classification model with the IKONOS images. The conclusions may be distinguished as follows:(a) Using the Maximum-Likelihood algorithm to classify seven broad land-cover categories. The overall accuracy in this stage achieves 92.72% and Kappa coefficient will be obtained 0.91; and (b) Using the SPARK method to classify images for detect the land-use, the overall accuracy achieves higher 89.64% and Kappa coefficient will be 0.86. To conclude, the research process in this study can fully and carefully describe local land-use pattern and assist the demand of land management and resources planning reference.

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A study on the development of a ship-handling simulation system based on actual maritime traffic conditions (실제 해상교통상황 기반 선박조종 시뮬레이션 시스템 개발에 관한 연구)

  • Eunkyu Lee;Jae-Seok Han;Kwang-Hyun Ko;Eunbi Park;Seong-Phil Ann
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.306-307
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    • 2022
  • Recently, in the process of developing, verifying, and upgrading the e-Navigation service and autonomous navigation system, there is an increasing demand for inter-working with a ship-handling simulator that can simulate actual maritime traffic conditions. In this paper, to develop a ship-handling simulation system based on actual maritime traffic conditions, a simulation server was built, received information on the actual maritime traffic conditions from the e-Navigation linkage system, and changed to information for operating the ship-handling simulator. In order to provide simulation images to users, 3D shape modeling for trade ports, coastal ports in Korea and major type of ship were performed. The developed system will be used for the advancement of e-Navigation service, development and verification of autonomous navigation systems, by enabling simultaneous processing of more than 10,000 ships and allowing users to simulate actual maritime traffic conditions in the desired area.

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Text Steganography Based on Ci-poetry Generation Using Markov Chain Model

  • Luo, Yubo;Huang, Yongfeng;Li, Fufang;Chang, Chinchen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.9
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    • pp.4568-4584
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    • 2016
  • Steganography based on text generation has become a hot research topic in recent years. However, current text-generation methods which generate texts of normal style have either semantic or syntactic flaws. Note that texts of special genre, such as poem, have much simpler language model, less grammar rules, and lower demand for naturalness. Motivated by this observation, in this paper, we propose a text steganography that utilizes Markov chain model to generate Ci-poetry, a classic Chinese poem style. Since all Ci poems have fixed tone patterns, the generation process is to select proper words based on a chosen tone pattern. Markov chain model can obtain a state transfer matrix which simulates the language model of Ci-poetry by learning from a given corpus. To begin with an initial word, we can hide secret message when we use the state transfer matrix to choose a next word, and iterating until the end of the whole Ci poem. Extensive experiments are conducted and both machine and human evaluation results show that our method can generate Ci-poetry with higher naturalness than former researches and achieve competitive embedding rate.

The Impact of COVID-19 on Earnings Management in the Distribution and Service Industries

  • RYU, Haeyoung;CHAE, Soo-Joon
    • Journal of Distribution Science
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    • v.20 no.4
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    • pp.95-100
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    • 2022
  • Purpose: This study aimed to investigate whether distribution and service companies maintained their accounting information quality and provided reliable information despite the economic changes occurring after the outbreak of the COVID-19 pandemic in Korea. The distribution industry has enjoyed increased demand as many companies expanded their untact distribution channels, including to online sales. However, as the pandemic drags on, their future prospects remain uncertain. Research design, data, and methodology: In this study, we define 2018-2019 as the "pre COVID-19 period" and 2020 as the "post COVID-19 period." An empirical analysis was performed using a regression model that includes POST, the independent variable, indicating the post COVID-19 period, and discretionary accruals(DA), a proxy for earnings management, as a dependent variable. Results: The analysis shows that the coefficient of POST is significantly positive (+) for the dependent variable DA. This finding suggests that distribution and service companies engaged in more earnings management during the post COVID-19 period than during the pre COVID-19 period, indicating their awareness of the uncertainty of future business performance as the pandemic persists. An additional analysis confirmed that smaller companies with fewer stakeholders and higher information asymmetry tend to engage more in earnings management than larger companies.

Expanded Exit-Pupil Holographic Head-Mounted Display With High-Speed Digital Micromirror Device

  • Kim, Mugeon;Lim, Sungjin;Choi, Geunseop;Kim, Youngmin;Kim, Hwi;Hahn, Joonku
    • ETRI Journal
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    • v.40 no.3
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    • pp.366-375
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    • 2018
  • Recently, techniques involving head-mounted displays (HMDs) have attracted much attention from academia and industry owing to the increased demand for virtual reality and augmented reality applications. Because HMDs are positioned near to users' eyes, it is important to solve the accommodation-vergence conflict problem to prevent dizziness. Therefore, holography is considered ideal for implementing HMDs. However, within the Nyquist region, the accommodation effect is limited by the space-bandwidth-product of the signal, which is determined by the sampling number of spatial light modulators. In addition, information about the angular spectrum is duplicated over the Fourier domain, and it is necessary to filter out the redundancy. The size of the exit-pupil of the HMD is limited by the Nyquist sampling theory. We newly propose a holographic HMD with an expanded exit-pupil over the Nyquist region by using the time-multiplexing method, and the accommodation effect is enhanced. We realize time-multiplexing by synchronizing a high-speed digital micromirror device and a liquid-crystal shutter array. We also demonstrate the accommodation effect experimentally.

A Feedback Clue Model for Dynamically Updating e-book Content from User Feedback (전자책에서 동적 사용자 피드백의 편집을 위한 피드백 클루 모델의 제안)

  • Choi, Ja-Ryoung;Hwang, JungSoo;Sin, Eun-Joo;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.313-321
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    • 2017
  • The emergence of E-book have allowed readers to interact with other readers and to actively participate (e.g. social reading). Furthermore, there is a growing demand in writer's community to take the advantage of the feedback from their readers to update the content of E-book. To do that, they require the service that utilizes the user feedback while creating or updating the e-book content. This study aims to let authors collect and to apply the reader's feedback on E-book content. However, in order to apply the user feedback, users first need to explicitly type the feedback, and even if they do, authors need to develop the software to automatically analyze and to apply the user feedback. This makes difficult for authors without programming background to produce E-book with automatic content adaptation. In this paper, we propose Feedback Clue Model to generate, analyze and apply the user feedback into E-book content. Based on this model, we develop the block editor which allows easy implementation of E-book that can be dynamically updated.

Sentiment Analysis on 'HelloTalk' App Reviews Using NRC Emotion Lexicon and GoEmotions Dataset

  • Simay Akar;Yang Sok Kim;Mi Jin Noh
    • Smart Media Journal
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    • v.13 no.6
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    • pp.35-43
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    • 2024
  • During the post-pandemic period, the interest in foreign language learning surged, leading to increased usage of language-learning apps. With the rising demand for these apps, analyzing app reviews becomes essential, as they provide valuable insights into user experiences and suggestions for improvement. This research focuses on extracting insights into users' opinions, sentiments, and overall satisfaction from reviews of HelloTalk, one of the most renowned language-learning apps. We employed topic modeling and emotion analysis approaches to analyze reviews collected from the Google Play Store. Several experiments were conducted to evaluate the performance of sentiment classification models with different settings. In addition, we identified dominant emotions and topics within the app reviews using feature importance analysis. The experimental results show that the Random Forest model with topics and emotions outperforms other approaches in accuracy, recall, and F1 score. The findings reveal that topics emphasizing language learning and community interactions, as well as the use of language learning tools and the learning experience, are prominent. Moreover, the emotions of 'admiration' and 'annoyance' emerge as significant factors across all models. This research highlights that incorporating emotion scores into the model and utilizing a broader range of emotion labels enhances model performance.