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Ranking Translation Word Selection Using a Bilingual Dictionary and WordNet

  • Kim, Kweon-Yang;Park, Se-Young
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.1
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    • pp.124-129
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    • 2006
  • This parer presents a method of ranking translation word selection for Korean verbs based on lexical knowledge contained in a bilingual Korean-English dictionary and WordNet that are easily obtainable knowledge resources. We focus on deciding which translation of the target word is the most appropriate using the measure of semantic relatedness through the 45 extended relations between possible translations of target word and some indicative clue words that play a role of predicate-arguments in source language text. In order to reduce the weight of application of possibly unwanted senses, we rank the possible word senses for each translation word by measuring semantic similarity between the translation word and its near synonyms. We report an average accuracy of $51\%$ with ten Korean ambiguous verbs. The evaluation suggests that our approach outperforms the default baseline performance and previous works.

A Study on Database of Region Statistic and Application (지역통계 데이타베이스 구축및 활용방안)

  • 이희춘;김승구
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.38
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    • pp.199-205
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    • 1996
  • The purpose of this study, therefore, was to construct the region statistical information to present methods of the data. The results of this paper are as follows: First, the construction of region statistical data is much in need of utilizing the server of regional information center, or the database to the server of public institutions, Second, there are some difficulties to receive the region statistical data because of only depending on the main source of KOSIS provided by national units from National Statistical Office. Third, as there is another problem which is text searching system served by KOSIS, GU system should be established for the user's satisfaction served by easier accessing screen. Fourth, there should be a standard software production to suit for the accessing software of the region statistical data.

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A Study on the Markup Scheme for Building the Corpora of Korean Culinary Manuscripts (한글 필사본 음식조리서 말뭉치 구축을 위한 마크업 방안 연구)

  • An, Ui-Jeong;Park, Jin-Yang;Nam, Gil-Im
    • Language and Information
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    • v.12 no.2
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    • pp.95-114
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    • 2008
  • This study aims at establishing a markup system for 17-19th century culinary manuscripts. To achieve this aim, we, in section 2, look into various theoretical considerations regarding encoding large-scale historical corpora. In section 3, we identify and analyze the characteristics of textual theme and structure of our source text. Section 4 proposes a markup scheme based on the XML standard for bibliographical and structural markups for the corpus as well as the grammatical annotations. We show that it is highly desirable to use XML-based markup system since it is extremely powerful and flexible in its expressiveness and scalable. The markup scheme we suggest is a modified and extended version of the TEI-P5 to accommodate the textual and linguistic characteristics of premodern Korean culinary manuscripts.

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Digital Watermarking Scheme Adopting Variable Spreading Sequence in Wireless Image Transmission (무선 이미지 전송에서 가변확산부호를 적용한 Digital Watermarking 기법)

  • 조복은;노재성;조성준
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.109-112
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    • 2002
  • In this paper, we propose the efficient digital watermarking scheme to transmit effectively the compressed medical image that embedded with watermarking data in mobile Internet access channel. The wireless channel error based on multiple access interference (MAI) is closely related to the length of spreading sequence in CDMA system. Also, the fixed length coded medical image with watermark bit stream can be classified by significance of source image. In the simulation, we compare the peak signal to noise ratio (PSNR) performance when the watermarked image with a simple symbol and when the watermarked image with a text file is transmitted using variable length of spreading sequences in case of limited length of spread sequence.

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Exceptionally stable green-synthesized gold nanoparticles for highly sensitive and selective colorimetric detection of trace metal ions and volatile aromatic compounds

  • Singh, Karanveer;Kukkar, Deepak;Singh, Ravinder;Kukkar, Preeti;Kim, Ki-Hyun
    • Journal of Industrial and Engineering Chemistry
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    • v.68
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    • pp.33-41
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    • 2018
  • The manuscript reports synthesis of exceptionally stable gold nanoparticles (GNPs) using Momordica charantia fruit extract. The synthesis approach was optimized by refining three experimental variables including source of the fruit extract (peel, seed, and seed coat), pH of the solution, and temperature of the reaction medium. As synthesized GNPs showed excellent stability against various thiolated compounds (e.g., thioglycolic acid, thiourea, ${\text\tiny{L}}-cystine$, 1-dodecanethiol, and cysteamine hydrochloride). Moreover, these nanoparticles showed distinctive colorimetric responses against $Cd^{2+}$ and thiophenol (TP) from their potential interferences. The limit of detection (LOD) values for $Cd^{2+}$ and TP were determined as 0.186 and $0.154{\mu}M$, respectively.

Module-based WebGIS platform for spatial information sharing system (공간정보 공유체계를 위한 모듈기반 WebGIS 플랫폼 연구)

  • Shin, Jeong-Seog;Choi, Yeong-Rak
    • Journal of Korea Multimedia Society
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    • v.25 no.11
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    • pp.1557-1563
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    • 2022
  • Currently Spatial Data is collected and processed in various methods, and its usability is very high. However, the existing Spatial Data analysis Software usually requires professional knowledge in the collection, refinement, and application of spatial Date, making it difficult to access and apply it. Therefore, this study established a new WebGIS platform with improved accessibility and usability to solve these problems. This platform supports various services such as master map sharing, spatial data generation, automatic coordinate system conversion, WMS issuance, grid generation, and grid analysis. These services increase operational convenience, such as simplifying repetitive tasks and automatically expressing text files. While it is believed that non-experts can easily and conveniently because of them to simplify and express the results. In addition, it is judged to have high accuracy and reliability compared to the analysis results using the existing Open Source-based GIS software.

Voice-based Device Control Using oneM2M IoT Platforms

  • Jeong, Isu;Yun, Jaeseok
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.3
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    • pp.151-157
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    • 2019
  • In this paper, we present a prototype system for controlling IoT home appliances via voice-based commands. A voice command has been widely deployed as one of unobtrusive user interfaces for applications in a variety of IoT domains. However, interoperability between diverse IoT systems is limited by several dominant companies providing voice assistants like Amazon Alexa or Google Now due to their proprietary systems. A global IoT standard, oneM2M has been proposed to mitigate the lack of interoperability between IoT systems. In this paper, we deployed oneM2M-based platforms for a voice record device like a wrist band and LED control device like a home appliance. We developed all the components for recording voices and controlling IoT devices, and demonstrate the feasibility of our proposed method based on oneM2M platforms and Google STT (Speech-to-Text) API for controlling home appliances by showing a user scenario for turning the LED device on and off via voice commands.

POI Recommendation Method Based on Multi-Source Information Fusion Using Deep Learning in Location-Based Social Networks

  • Sun, Liqiang
    • Journal of Information Processing Systems
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    • v.17 no.2
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    • pp.352-368
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    • 2021
  • Sign-in point of interest (POI) are extremely sparse in location-based social networks, hindering recommendation systems from capturing users' deep-level preferences. To solve this problem, we propose a content-aware POI recommendation algorithm based on a convolutional neural network. First, using convolutional neural networks to process comment text information, we model location POI and user latent factors. Subsequently, the objective function is constructed by fusing users' geographical information and obtaining the emotional category information. In addition, the objective function comprises matrix decomposition and maximisation of the probability objective function. Finally, we solve the objective function efficiently. The prediction rate and F1 value on the Instagram-NewYork dataset are 78.32% and 76.37%, respectively, and those on the Instagram-Chicago dataset are 85.16% and 83.29%, respectively. Comparative experiments show that the proposed method can obtain a higher precision rate than several other newer recommended methods.

ON NONLINEAR ELLIPTIC EQUATIONS WITH SINGULAR LOWER ORDER TERM

  • Marah, Amine;Redwane, Hicham
    • Bulletin of the Korean Mathematical Society
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    • v.58 no.2
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    • pp.385-401
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    • 2021
  • We prove existence and regularity results of solutions for a class of nonlinear singular elliptic problems like $$\{-div\((a(x)+{\mid}u{\mid}^q){\nabla}u\)=\frac{f}{{\mid}u{\mid}^{\gamma}}{\text{ in }}{\Omega},\\{u=0\;on\;{\partial}{\Omega},$$ where Ω is a bounded open subset of ℝℕ(N ≥ 2), a(x) is a measurable nonnegative function, q, �� > 0 and the source f is a nonnegative (not identicaly zero) function belonging to Lm(Ω) for some m ≥ 1. Our results will depend on the summability of f and on the values of q, �� > 0.

Explaining the Translation Error Factors of Machine Translation Services Using Self-Attention Visualization (Self-Attention 시각화를 사용한 기계번역 서비스의 번역 오류 요인 설명)

  • Zhang, Chenglong;Ahn, Hyunchul
    • Journal of Information Technology Services
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    • v.21 no.2
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    • pp.85-95
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    • 2022
  • This study analyzed the translation error factors of machine translation services such as Naver Papago and Google Translate through Self-Attention path visualization. Self-Attention is a key method of the Transformer and BERT NLP models and recently widely used in machine translation. We propose a method to explain translation error factors of machine translation algorithms by comparison the Self-Attention paths between ST(source text) and ST'(transformed ST) of which meaning is not changed, but the translation output is more accurate. Through this method, it is possible to gain explainability to analyze a machine translation algorithm's inside process, which is invisible like a black box. In our experiment, it was possible to explore the factors that caused translation errors by analyzing the difference in key word's attention path. The study used the XLM-RoBERTa multilingual NLP model provided by exBERT for Self-Attention visualization, and it was applied to two examples of Korean-Chinese and Korean-English translations.