• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.65-74
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• 2022

In natural language processing, commonly used words such as prepositions are referred to as stop-words; they have no inherent meaning and are therefore ignored in indexing and retrieval tasks. The removal of stop-words from Arabic text has a significant impact in terms of reducing the size of a cor- pus text, which leads to an improvement in the effectiveness and performance of Arabic-language processing systems. This study investigated the effectiveness of applying a stop-word lists elimination with normalization as a preprocessing step. The idea was to merge statistical method with the linguistic method to attain the best efficacy, and comparing the effects of this two-pronged approach in reducing corpus size for Ara- bic natural language processing systems. Three stop-word lists were considered: an Arabic Text Lookup Stop-list, Frequency- based Stop-list using Zipf's law, and Combined Stop-list. An experiment was conducted using a selected file from the Arabic Newswire data set. In the experiment, the size of the cor- pus was compared after removing the words contained in each list. The results showed that the best reduction in size was achieved by using the Combined Stop-list with normalization, with a word count reduction of 452930 and a compression rate of 30%.

• 한국수학교육학회지시리즈A:수학교육
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• 제63권2호
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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.

• 컴퓨터교육학회논문지
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• 제7권4호
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• pp.103-110
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• 2004

최근 학교 교육에서 학습자 중심의 ICT교육에 대한 중요성이 강조됨에 따라 앞으로의 교육은 이미 정해진 틀에 학습자를 맞추기보다는 학습자의 개인적 자질을 존중하는 방향으로 나아가야 한다. 이러한 관점은 Gardner의 다중지능이론에 논리적 근거를 두고 있다. 이런 맥락에서 초등학교에서 이루어지고 있는 ICT소양교육도 다중지능을 바탕으로 개개인 학생의 능력과 소질을 잘 판단하여 적합한 교육과정과 교수 방법을 적용할 필요가 있다. 이에 대한 기초자료를 제공하기 위해 본 연구에서는 ICT소양교육의 학업성취도와 다중지능의 상관관계를 살펴보았고, ICT소양교육의 학업성취 우수아와 부진아를 대상으로 어떤 지능이 ICT소양교육의 성취도를 결정하는 요인인지 알아보았다. 그 결과 논리수학지능이 ICT소양교육의 학업성취도와 유의미한 상관이 있었고, 논리수학지능과 언어지능이 ICT소양교육의 학업성적의 우열 결정에 크게 작용하는 요인으로 나타났다.

• 한국콘텐츠학회논문지
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• 제17권4호
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• pp.606-620
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• 2017

본 연구의 목적은 아동의 놀이 양식 및 선호를 측정할 수 있는 아동 놀이성향 척도(CPDS)를 개발하고 타당화하는 것으로, 만 5-7세 아동(월령 범위 51~106개월)의 부모 437명을 대상으로 설문을 진행했다. 이를 위해, 먼저 선행 연구 및 다중지능이론과 관련 척도를 검토하여 예비문항을 개발하였다. 전문가를 통해 문항의 적절성 및 타당성을 확인받은 뒤, 문항들은 탐색적 요인 분석을 거쳐 최종적으로 6요인의 27문항으로 확정되었다. 6요인은 각각 주도성, 언어성, 탐구성, 예술성, 운동성, 감수성이다. 본 척도의 공인타당도는 CPDS의 각 요인과 유아용/초등용 다중 지능 체크리스트의 하위 요인 및 총점간의 관계를 통해 산출하였으며, CPDS 각 요인의 신뢰도 범위는 .53~.79이다. 본 척도는 아동의 발달적 강점을 강화하고, 약점은 보완하여 아동 발달을 지원하는데 필요한 정보를 제공할 수 있을 것으로 기대하며, 향후 아동의 놀이 콘텐츠 제공과 놀이방법 등을 적절하게 지도하는데 기여할 수 있다.

• 아시아태평양코퍼스연구
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• 제1권1호
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• pp.95-125
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• 2020

This paper aims to inform people how to support each other on social media. It alludes to an architecture for social media discourse and proposes a novel theory of support in social media discourse. It makes a methodological contribution. It combines predominately artificial intelligence with corpus linguistics analysis. It is on a large-scale dataset of anonymised diabetes-related user's posts from the Facebook platform. Log-likelihood and precision measures help with validation. A multi-method approach with Discourse Analysis helps in understanding any potential patterns. People living with Diabetes are found to employ sophisticated high-frequency patterns of device-enabled categories of purpose and content. It is with, for example, linguistic forms of Advice with stance-taking and targets such as Diabetes amongst other interactional ways. There can be uncertainty and variation of effect displayed when sharing information for support. The implications of the new theory aim at healthcare communicators, corpus linguists and with preliminary work for AI support-bots. These bots may be programmed to utilise the language patterns to support people who need them automatically.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.302-305
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• 1996

In this paper, an optimal identification method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzz-neural networks(FNNs) and parameters of membership function are tuned using genetic algorithm(GAs). For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activated sludge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The show that the proposed method can produce the intelligence model w th higher accuracy than other works achieved previously.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1264-1272
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• 1993

The software for unmanned control of three row typed rice combine has been developed using fuzzy logic. Three fuzzy variables were used : operating status of combine, steering, and speed. Eleven fuzzy rules were constructed and the eleven linguistic variables were used for the fuzzy rules. Six sensors were use of to get input values and sensor input values were quantified into 11 levels. The fuzzy output was infered with fuzzy inferrence which uses the correlation product encoding , and it must have been defuzzified by the method of center of gravity to use it for the control. The result of performance test using graphic simulation showed that the intelligently unmanned control of a rice combine was possible using fuzzy logic control.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.157-162
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• 2022

Cerebral palsy is one of the most serious forms of disorders of the psychophysical development of children, which manifests itself in disturbances of motor functions, which are often combined with speech disorders, other complications of the formation of higher mental functions, and often with a decrease in intelligence. The article will discuss the speech disorder in children with cerebral palsy. Emphasis is placed on some important aspects, which should bear in mind, investigating the problem of specifics of speech development of children with cerebral palsy. In particular at the heart of speech disorders in the cerebral palsy is not only damage to certain structures of the brain, but also the later formation or underdevelopment of those parts of the cerebral cortex, which are of major importance in linguistic and mental activity. This is an ontogenetically young region of the cerebral cortex, which is most rapidly developing after birth (premotor, frontal, temmono-temporal). It is important to take into account, that children with cerebral palsy have disturbances of phonemic perception. Often, children do not distinguish between hearing sounds, cannot repeat component rows, allocate sounds in words. At dysarthria, there are violations of pronunciation of vowel and consonant sounds, tempo of speech, modulation of voice, breathing, phonation, as well as asynchronous breathing, alignment and articulation. As a result, we identified the main features and specifics of the speech development of children with cerebral palsy and described the conditions necessary for the full development of language. Language disturbances in children's cerebral palsy depend on the localization and severity of brain damage. Great importance in the mechanism of speech disorders has a pathology that limits the ability of movement and knowledge of the world.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.72-74
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• 2022

국가과학기술지식정보서비스(이하 NTIS)에서는 국가R&D과제정보를 제공하고 있다. 과제정보는 '과제명', '과제수행기관', '연구책임자명' 등의 메타정보와 '연구목표', '연구내용', '기대효과'와 같은 과제를 설명하는 텍스트들로 구성되어있다. 과제정보 100만건을 대상으로 검색한 결과목록에서 '연구목표' 나 '연구내용' 등을 모두 확인하여 원하는 과제정보를 찾기 위해서는 많은 시간이 필요하다는 문제가 있다. 이러한 문제점을 해소하기 위해, 본 논문에서는 국가R&D 과제정보 내에서 장문의 텍스트로 구성된 부분을 요약하는 과제정보 요약 시스템을 제안하고자 한다. 한국어의 언어학적 특징을 분석하여 전처리기를 구축하고 전처리된 텍스트 정보를 처리하기 위한 자연어 처리 기술 기반 과제정보 요약 모델을 개발하였다. 이를 통해 장문으로 구성된 과제정보를 압축 및 요약된 형태로 제공하여, 이용자들이 요약정보만으로도 전반적인 내용을 쉽고 빠르게 유추하는 데 도움이 될 것이다.