• Title/Summary/Keyword: Learning Ally

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Analysis and Implications of Private-led Library Services for the Disabled in Major Advanced Countries (주요 선진국 민간주도형 도서관 장애인서비스 분석과 시사점)

  • Yoon, Hee-Yoon
    • Journal of Korean Library and Information Science Society
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    • v.53 no.2
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    • pp.1-23
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    • 2022
  • Access to knowledge and information is a universal human right. However, even after the Marrakesh Treaty was adopted on June 27, 2013, only 1-7% of standard printed materials are accessible to people with reading disabilities, including the visually impaired, and library services are very weak. As a result, the book famine of people with reading disabilities continues. This study, focusing on such severe access gaps and inequalities, analyzes Learning Ally and Bookshare in the US, the Royal National Institute of Blind People (RNIB) in the UK, Bibliothèque Numérique Francophone Accessible (BNFA) in France, and SAPIE in Japan, which are considered private organizations leading library services for the disabled in major developed countries. And based on the derived implications and the Marrakesh Treaty, a strategic plan was proposed to strengthen the services of the disabled in domestic libraries. It is urgent to enact the 'Act to Resolve Reading Barriers', amend the provisions related to the Copyright Act that restrict library services, strengthen the organizational capacity of the National Library for the Disabled, raise the service index for the disabled in library evaluation, and establish a library cooperation system centered on regional representative libraries and expand services, etc.

The Use of Phonetics in the Analysis of the Acquisition of Second Language Syntax

  • Fellbaum, Marie
    • Proceedings of the KSPS conference
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    • 1996.10a
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    • pp.430-431
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    • 1996
  • Among the scholars of second language (L2) acquisition who have used prosodic considerations in syntactic analyses, pausing and intonation contours have been used to define utterances in the speech of second language learners (e.g., Sato, 1990). In recent research on conversational analysis, it has been found that lexically marked causal clause combining in the discourse of native speakers can be distinguished as "intonational subordination" and "intonational coordination(Couper-Kuhlen, Elizabeth, forthcoming.)". This study uses Pienemann's Processability Theory (1995) for an analysis of the speech of native speakers of Japanese (L1) learning English. In order to accurately assess the psycholinguistic stages of syntactic development, it is shown that pitch, loudness, and timing must all be considered together with the syntactic analysis of interlanguage speech production. Twelve Japanese subjects participated in eight fifteen minute interviews, ninety-six dyads. The speech analyzed in this report is limited to the twelve subjects interacting with two different non-native speaker interviews for a total of twenty-four dyads. Within each of the interviews, four different tasks are analyzed to determine the stage of acquisition of English for each subject. Initially the speech is segmented according to intonation contour arid pauses. It is then classified accoding to specific syntactic units and further analysed for pitch, loudness and timing. Results indicate that the speech must be first claasified prosodic ally and lexically, prior to beginning syntactic analysis. This analysis stinguishes three interlanguage lexical categories: discourse markers, coordinator $s_ordinators, and transfer from Japanese. After these lexical categories have been determined, the psycholinguistic stages of syntactic development can be more accurately assessed.d.

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The Study on The Identification Model of Friend or Foe on Helicopter by using Binary Classification with CNN

  • Kim, Tae Wan;Kim, Jong Hwan;Moon, Ho Seok
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.3
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    • pp.33-42
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    • 2020
  • There has been difficulties in identifying objects by relying on the naked eye in various surveillance systems. There is a growing need for automated surveillance systems to replace soldiers in the field of military surveillance operations. Even though the object detection technology is developing rapidly in the civilian domain, but the research applied to the military is insufficient due to a lack of data and interest. Thus, in this paper, we applied one of deep learning algorithms, Convolutional Neural Network-based binary classification to develop an autonomous identification model of both friend and foe helicopters (AH-64, Mi-17) among the military weapon systems, and evaluated the model performance by considering accuracy, precision, recall and F-measure. As the result, the identification model demonstrates 97.8%, 97.3%, 98.5%, and 97.8 for accuracy, precision, recall and F-measure, respectively. In addition, we analyzed the feature map on convolution layers of the identification model in order to check which area of imagery is highly weighted. In general, rotary shaft of rotating wing, wheels, and air-intake on both of ally and foe helicopters played a major role in the performance of the identification model. This is the first study to attempt to classify images of helicopters among military weapons systems using CNN, and the model proposed in this study shows higher accuracy than the existing classification model for other weapons systems.