• 인터넷정보학회논문지
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• 제21권5호
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• pp.57-65
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• 2020

At present, the existing virus recognition systems usually use signature approach to detect malicious executable files, but these methods often fail to detect new and invisible malware. At the same time, some methods try to use more general features to detect malware, and achieve some success. Moreover, machine learning-based approaches are applied to detect malware, which depend on features extracted from malicious codes. However, the different distribution of features oftraining and testing datasets also impacts the effectiveness of the detection models. And the generation oflabeled datasets need to spend a significant amount time, which degrades the performance of the learning method. In this paper, we use transfer learning to detect new and previously unseen malware. We first extract the features of Portable Executable (PE) files, then combine transfer learning training model with KNN approachto detect the new and unseen malware. We also evaluate the detection performance of a classifier in terms of precision, recall, F1, and so on. The experimental results demonstrate that proposed method with high detection rates andcan be anticipated to carry out as well in the real-world environment.

• 공학교육연구
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• 제8권1호
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• pp.71-83
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• 2005

본 논문에서는 자바 언어를 학습하는데 있어 효율성을 증가시키기 위해 인터넷 기반 자율학습시스템이 제안되었다. 제안된 자율학습시스템은 JWP(Java Web Player)라고 불리며 Java Web Start 기술을 활용하여 웹상에서 실행이 가능한 자바 애플리케이션 프로그램이다. 또한 본 논문에서는 컴퓨터 언어를 학습하는데 있어 3가지 중요한 일련의 과정인 개념학습과정, 프로그래밍 실습과정, 그리고 학습 성취도 평가과정을 Java Web Start 기술을 이용하여 JWP에 통합하였다. 제안된 시스템은 학습과정을 교육공학적인 측면에서 멀티미디어 요소를 강화하였기 때문에 학습자가 흥미를 가지고 자발적으로 학습을 할 수 있도록 설계되었다. 더욱이 JWP 에는 효율적인 자바 언어 학습을 위해 학습내용에 대한 설명이 음성으로 출력되며, 이때 이와 관련된 이미지와 텍스트들이 동기화되어 동시에 화면에 표시된다. 더욱이 소스파일의 코딩, 에디팅, 실행 그리고 디버깅 등을 쉽게 할 수 있는 컴파일러가 삽입되어 있어 편리한 자바 언어 실습환경을 제공한다. 마지막으로 각 단원별 돌발퀴즈와 마무리 테스트를 통하여 학습자가 자신의 학습상황을 체크하여 반복학습을 할 수 있도록 유도하였다.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.258-266
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• 2024

E-learning systems have proliferated in recent years, particularly in the wake of the global COVID-19 pandemic. For kids, there isn't a specific online learning platform available, though. To do this, new conceptual models of training and learning software that are adapted to the abilities and preferences of end users must be created. Young pupils: those in kindergarten, preschool, and elementary school are unique subjects with little research history. From the standpoint of software technology, young students who have never had access to a computer system are regarded as specific users with high expectations for the functionality and interface of the software, social network connectivity, and instantaneous Internet communication. In this study, we suggested creating an electronic learning management system that is web-based and appropriate for primary school pupils. User-centered design is the fundamental technique that was applied in the development of the system that we are proposing. Test findings have demonstrated that students who are using the digital environment for the first time are studying more effectively thanks to the online learning management system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2012-2030
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• 2021

Named Entity Recognition (NER) is used to identify entity nouns in the corpus such as Location, Person and Organization, etc. NER is also an important basic of research in various natural language fields. The processing of Chinese NER has some unique difficulties, for example, there is no obvious segmentation boundary between each Chinese character in a Chinese sentence. The Chinese NER task is often combined with Chinese word segmentation, and so on. In response to these problems, we summarize the recognition methods of Chinese NER. In this review, we first introduce the sequence labeling system and evaluation metrics of NER. Then, we divide Chinese NER methods into rule-based methods, statistics-based machine learning methods and deep learning-based methods. Subsequently, we analyze in detail the model framework based on deep learning and the typical Chinese NER methods. Finally, we put forward the current challenges and future research directions of Chinese NER technology.

• 인터넷정보학회논문지
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• 제8권6호
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• pp.127-133
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• 2007

u-러닝 환경은 수 없이 많은 단계를 거쳐 발전되어 왔으며, 현재에는 학습자의 학습 결과 분석과 양적인 사용, 질적인 평가 등을 통하여 정립되고 있다. 일반적으로 개선된 학습 효과와 학습자의 학습 결과분석을 위하여 대부분의 학습 시스템이 문항분석방법을 이용되고 있다. 그러나 오늘날 학습 시스템은 문항분석이론 대신에 문항반응이론을 사용하고 있다. 문항분석이론은 시험에 대한 각각의 가능한 응답에 대한 확률을 위해 명확한 모델을 제시한다. 따라서 본 연구에서는 문항반응이론을 이용한 경량 컴포넌트 기반의 u-러닝 시스템을 제시하고자 한다. u-러닝에 적용된 기기는 윈도우 모바일 5.0 환경의 PDA로 하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.1015-1029
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• 2021

Modern technology offers many ways to enhance teaching and learning that in turn promote the development of tools for educational activities both inside and outside the classroom. Many educational programs using the augmented reality (AR) technology are being widely used to provide supplementary learning materials for students. This paper describes the potential and challenges of using GeoGebra AR in mathematical studies, whereby students can view 3D geometric objects for a better understanding of their structure, and verifies the feasibility of its use based on experimental results. The GeoGebra software can be used to draw geometric objects, and 3D geometric objects can be viewed using AR software or AR applications on mobile phones or computer tablets. These could provide some of the required materials for mathematical education at high schools or universities. The use of the GeoGebra application for education in Laos will be particularly discussed in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.754-774
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• 2023

Wrestling is one of the popular events for modern sports. It is difficult to quantitatively describe a wrestling game between athletes. And deep learning can help wrestling training by human recognition techniques. Based on the characteristics of latest wrestling competition rules and human recognition technologies, a set of wrestling competition video analysis and retrieval system is proposed. This system uses a combination of literature method, observation method, interview method and mathematical statistics to conduct statistics, analysis, research and discussion on the application of technology. Combined the system application in targeted movement technology. A deep learning-based facial recognition psychological feature analysis method for the training and competition of classical wrestling after the implementation of the new rules is proposed. The experimental results of this paper showed that the proportion of natural emotions of male and female wrestlers was about 50%, indicating that the wrestler's mentality was relatively stable before the intense physical confrontation, and the test of the system also proved the stability of the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.1035-1048
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• 2023

The IEEE 802.11 WLAN adopts a random backoff algorithm for its collision avoidance mechanism, and it is well known that the contention-based algorithm may suffer from performance degradation especially in congested networks. In this paper, we design an efficient backoff algorithm that utilizes a reinforcement learning method to determine optimal values of backoffs. The mobile nodes share a common contention window (CW) in our scheme, and using a Q-learning algorithm, they can avoid collisions by finding and implicitly reserving their optimal time slot(s). In addition, we introduce Frame Size Control (FSC) algorithm to minimize the possible degradation of aggregate throughput when the number of nodes exceeds the CW size. Our simulation shows that the proposed backoff algorithm with FSC method outperforms the 802.11 protocol regardless of the traffic conditions, and an analytical modeling proves that our mechanism has a unique operating point that is fair and stable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.420-437
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• 2024

There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.141-148
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• 2023

As the direction of education in the fourth industry in the 21st century, convergence talent education that emphasizes the connection and convergence between core competency-based education and academia is emerging to foster creative talent. The purpose of this paper is to present the criteria for evaluating the competency of learning outcomes in order to develop a strategic model for innovation in engineering teaching-learning. In this paper, as a study to establish the direction of implementation of convergence talent education, a creative innovation teaching method support system was established to improve the quality of convergence talent education. Firstly, a plan to develop a teaching-learning model based on computing thinking. Secondly, it presented the development of a teaching-learning model based on linkage and convergence learning. Thirdly, we would like to present educational appropriateness and ease based on convergence learning in connection with curriculum improvement strategies based on computing thinking skills. Finally, we would like to present a strategic model development plan for innovation in engineering teaching-learning that applies the convergence talent education program.