• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.19-28
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• 2022

The study aimed to identify the impact of Applications of Internet of things on practice of knowledge management in organizations: the mediating role of employees' Engagement. A quantitative questionnaire survey is conducted. The study population consisted of all senior and middle administrations in small and medium enterprises in Jordan. The study sample consisted of (350) senior and middle administrations. The study sample was selected by random stratified method. The results revealed that There is an impact of Applications of Internet of things on the practice of knowledge management at (α ≤ 0.05) in the small and medium enterprises in Jordan. Furthermore, there is an impact of Applications of Internet of things on the employees' Engagement. The current study provided some important insights into an issue that requires further research. Understanding the applications of the Internet of Things and their impact on improving knowledge management is of paramount importance in raising the quality of products and improving the company's image, as shown in this research.

• Journal of Information Processing Systems
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• 제13권1호
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• pp.57-67
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• 2017

In this paper, Atanassov's intuitionistic fuzzy set theory is used to handle the uncertainty of students' knowledgeon domain concepts in an E-learning system. Their knowledge on these domain concepts has been collected from tests that were conducted during their learning phase. Atanassov's intuitionistic fuzzy user model is proposed to deal with vagueness in the user's knowledge description in domain concepts. The user model uses Atanassov's intuitionistic fuzzy sets for knowledge representation and linguistic rules for updating the user model. The scores obtained by each student were collected in this model and the decision about the students' knowledge acquisition for each concept whether completely learned, completely known, partially known or completely unknown were placed into the information table. Finally, it has been found that the proposed scheme is more appropriate than the fuzzy scheme.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.34-46
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• 2023

A growing number of large scale knowledge graphs raises several issues how knowledge graph data can be organized, discovered, and integrated efficiently. We present a novel semantic-based mashup platform for contents convergence which consists of acquisition, RDF storage, ontology learning, and mashup subsystems. This platform servers a basis for developing other more sophisticated applications required in the area of knowledge big data. Moreover, this paper proposes an entity matching method using graph convolutional network techniques as a preliminary work for automatic classification and discovery on knowledge big data. Using real DBP15K and SRPRS datasets, the performance of our method is compared with some existing entity matching methods. The experimental results show that the proposed method outperforms existing methods due to its ability to increase accuracy and reduce training time.

• 한국과학교육학회지
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• 제23권4호
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• pp.430-441
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• 2003

The purpose of this study was to investigate the effects of students' prior knowledge on scientific reasoning in solving a pendulum task with a computer simulation. Subjects were 60 Korean students: 27 fifth-grade students from an elementary school and 33 seventh grade students from a middle school located in a city with 300,000 people. This study adapted a pendulum task presented with a computer simulation on which subjects would use a pattern of multivariable causal inferences. The subjects were interviewed individually in a three-phase structured interview by the researcher and three assistants while he/she was investigating the pendulum task. This study showed that most students across grades focused heavily on demonstrating the primacy of their prior knowledge or their current hypothesis. In addition, students' theories that are part of one's prior knowledge have a significant impact on formulating, testing, and revising hypotheses. Therefore, this study supported the notion that students' prior knowledge had a strong effect on students' experimental intent and hypothesis evaluation.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.133-149
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• 2021

The purpose of this study is to explore the role of information systems in the implementation of knowledge management, at King Abdul-Aziz University (KAU) in Jeddah, by highlighting the importance of information systems and their implementation of the knowledge processes. The researcher used the case-study method to explore the importance of information systems in supporting the implementation of knowledge management at the university. Moreover, the study has used the questionnaire as a tool for collecting information and obtaining feedbacks from the administrators at the university, and a random sample was chosen to identify the study community. The study resulted that there is a statistical indication of the importance and degree of the use of electronic systems in the university by the administrators. The study sample members believe that the university is keen to provide information systems, where systems analyze data and convert them into knowledge information that benefits the senior management at the university. Members of the study sample emphasize the importance of electronic information systems at the university, which in turn saves time and effort in extracting information, reports, statistics and providing them easily to senior management. The study also concluded with some recommendations, such as emphasizing the importance of knowledge management as one of its top priorities, spreading the knowledge culture, instilling a vision of knowledge among individuals, and emphasizing the importance of information systems.

• Journal of Computing Science and Engineering
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• 제10권4호
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• pp.128-136
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• 2016

It is impossible for any human being to analyze the more than 500 million tweets that are generated per day. Lexical ambiguities on Twitter make it difficult to retrieve the desired data and relevant topics. Most of the solutions for the word sense disambiguation problem rely on knowledge base systems. Unfortunately, it is expensive and time-consuming to manually create a knowledge base system, resulting in a knowledge acquisition bottleneck. To solve the knowledge-acquisition bottleneck, a topic signature is used to disambiguate words. In this paper, we evaluate the effectiveness of various features of newspapers on the topic signature extraction for word sense discrimination in tweets. Based on our results, topic signatures obtained from a snippet feature exhibit higher accuracy in discriminating company names than those from the article body. We conclude that topic signatures extracted from news articles improve the accuracy of word sense discrimination in the automated analysis of tweets.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (A)
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• pp.79-80
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• 2007

• 컴퓨터교육학회논문지
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• 제20권3호
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• pp.25-33
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• 2017

고등교육의 질 관리를 중요하게 생각한 국가들은 다양한 제도나 방법을 통해 교육의 질 강화를 진행하고 있다. 컴퓨터과학 분야에서도 고등교육의 질 관리를 위해 교육과정 표준을 구성하는 등 끊임없이 노력해 왔다. 컴퓨터과학 분야 교육과정 표준에서 언급한 지식영역의 우선순위를 파악해 보면, 내용체계 구성에 시사점을 줄 수 있을 것이다. 따라서 CS2013을 토대로 내용요소에 대한 Tier1, Tier2, Elective의 시수와 세부영역의 수를 중심으로 순위를 도출하였다. 분석결과, 가장 높은 우선순위를 지닌 지식영역으로는 Software Development Fundamentals이었다. 해당 지식영역은 CS2013에서 기초 요소이기 때문에 초급코스로 권장한다고 기술되기도 하였다. 도출되어진 영역별 우선순위가 향후 초중등 정보교육과정이나 고등 교양 정보교육과정, 교원양성기관의 정보교육과정 설정에 시사점을 줄 수 있을 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권5호
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• pp.1463-1478
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• 2012

Based on the theory of local-world network, the composition self-similarity (CSS) of network traffic is presented for the first time in this paper for the study of DoS detection. We propose the concept of composition distribution graph and design the relative operations. The $(R/S)^d$ algorithm is designed for calculating the Hurst parameter. Based on composition distribution graph and Kullback Leibler (KL) divergence, we propose the composition self-similarity anomaly detection (CSSD) method for the detection of DoS attacks. We evaluate the effectiveness of the proposed method. Compared to other entropy based anomaly detection methods, our method is more accurate and with higher sensitivity in the detection of DoS attacks.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.526-529
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• 2018

본 연구에서는 텍스트 네트워크분석을 활용하여 국방분야 연구의 핵심 주제어와 연구주제를 분석하고 이를 통해 전체 지식구조를 파악하고자 하였다. 이를 위해 2010년부터 2017년까지의 국방대학교 학위과정 논문을 대상으로 국방분야 연구현황을 진단하고 지식구조를 구성하였다. 8년간 누적된 논문 710건의 초록을 분석하여 총 6,883개의 단어를 추출한 후, 단어의 논문 등장 빈도수와 단어간 링크수를 파레토 법칙에 따라 상위 20%의 기준으로 총 270개의 단어로 추출하였고, 컴포넌트 분석을 통해 최종 170개의 핵심 주제어를 도출하였다. 이 핵심 주제어를 통해 중심성 분석과 응집구조를 분석하여, 국방분야에 대한 총 6개의 지식구조 그룹을 도출하였다.