• Title/Summary/Keyword: Corpus Analysis Tools

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Development of Windows forensic tool for verifying a set of data (윈도우 포렌식 도구의 검증용 데이터 세트의 개발)

  • Kim, Min-Seo;Lee, Sang-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.6
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    • pp.1421-1433
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    • 2015
  • For an accurate analysis through the forensic of digital devices and computer, it is a very important validation of the reliability of digital forensic tools. To verify the reliability of the tool, it is necessary to research and development of the data set to be input to the tool. In many-used Windows operating system of the computer, there is a Window forensic artifacts associated with time and system behavior. In this paper, we developed a set of data in the Windows operating system to be able to analyze all of the two Windows artifacts and we conducted a test with published digital forensic tools. Therefore, the developed data set presents the use of the following method. First, artefacts education for growing ability can be analyzed acts standards. Secondly, the purpose of tool tests for verifying the reliability of digital forensics. Lastly, recyclability for new artifact analysis.

Unveiling the synergistic nexus: AI-driven coding integration in mathematics education for enhanced computational thinking and problem-solving

  • Ipek Saralar-Aras;Yasemin Cicek Schoenberg
    • The Mathematical Education
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    • v.63 no.2
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    • pp.233-254
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    • 2024
  • This paper delves into the symbiotic integration of coding and mathematics education, aimed at cultivating computational thinking and enriching mathematical problem-solving proficiencies. We have identified a corpus of scholarly articles (n=38) disseminated within the preceding two decades, subsequently culling a portion thereof, ultimately engendering a contemplative analysis of the extant remnants. In a swiftly evolving society driven by the Fourth Industrial Revolution and the ascendancy of Artificial Intelligence (AI), understanding the synergy between these domains has become paramount. Mathematics education stands at the crossroads of this transformation, witnessing a profound influence of AI. This paper explores the evolving landscape of mathematical cognition propelled by AI, accentuating how AI empowers advanced analytical and problem-solving capabilities, particularly in the realm of big data-driven scenarios. Given this shifting paradigm, it becomes imperative to investigate and assess AI's impact on mathematics education, a pivotal endeavor in forging an education system aligned with the future. The symbiosis of AI and human cognition doesn't merely amplify AI-centric thinking but also fosters personalized cognitive processes by facilitating interaction with AI and encouraging critical contemplation of AI's algorithmic underpinnings. This necessitates a broader conception of educational tools, encompassing AI as a catalyst for mathematical cognition, transcending conventional linguistic and symbolic instruments.

Korean Noun Extractor using Occurrence Patterns of Nouns and Post-noun Morpheme Sequences (한국어 명사 출현 특성과 후절어를 이용한 명사추출기)

  • Park, Yong-Hyun;Hwang, Jae-Won;Ko, Young-Joong
    • Journal of KIISE:Software and Applications
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    • v.37 no.12
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    • pp.919-927
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    • 2010
  • Since the performance of mobile devices is recently improved, the requirement of information retrieval is increased in the mobile devices as well as PCs. If a mobile device with small memory uses a tradition language analysis tool to extract nouns from korean texts, it will impose a burden of analysing language. As a result, the need for the language analysis tools adequate to the mobile devices is increasing. Therefore, this paper proposes a new method for noun extraction using post-noun morpheme sequences and noun patterns from a large corpus. The proposed noun extractor has only the dictionary capacity of 146KB and its performance shows 0.86 $F_1$-measure; the capacity of noun dictionary corresponds to only the 4% capacity of the existing noun extractor with a POS tagger. In addition, it easily extract nouns for unknown word because its dependence for noun dictionaries is low.