• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.52-60
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• 2024

APT (Advanced Persistent Threat) attack is a dangerous, targeted attack form with clear targets. APT attack campaigns have huge consequences. Therefore, the problem of researching and developing the APT attack detection solution is very urgent and necessary nowadays. On the other hand, no matter how advanced the APT attack, it has clear processes and lifecycles. Taking advantage of this point, security experts recommend that could develop APT attack detection solutions for each of their life cycles and processes. In APT attacks, hackers often use phishing techniques to perform attacks and steal data. If this attack and phishing phase is detected, the entire APT attack campaign will be crash. Therefore, it is necessary to research and deploy technology and solutions that could detect early the APT attack when it is in the stages of attacking and stealing data. This paper proposes an APT attack detection framework based on the Network traffic analysis technique using open-source tools and deep learning models. This research focuses on analyzing Network traffic into different components, then finds ways to extract abnormal behaviors on those components, and finally uses deep learning algorithms to classify Network traffic based on the extracted abnormal behaviors. The abnormal behavior analysis process is presented in detail in section III.A of the paper. The APT attack detection method based on Network traffic is presented in section III.B of this paper. Finally, the experimental process of the proposal is performed in section IV of the paper.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.45-53
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• 2024

The maintenance of semiconductor equipment is crucial for the continuous growth of the semiconductor market. System management is imperative given the anticipated increase in the capacity and complexity of industrial equipment. Ensuring optimal operation of manufacturing processes is essential to maintaining a steady supply of numerous parts. Particularly, monitoring the status of substrate transfer robots, which play a central role in these processes, is crucial. Diagnosing failures of their major components is vital for preventive maintenance. Fault diagnosis methods can be broadly categorized into physics-based and data-driven approaches. This study focuses on data-driven fault diagnosis methods due to the limitations of physics-based approaches. We propose a methodology for data acquisition and preprocessing for robot fault diagnosis. Data is gathered from vibration sensors, and the data preprocessing method is applied to the vibration signals. Subsequently, the dataset is trained using Gradient Tree-based XGBoost machine learning classification algorithms. The effectiveness of the proposed model is validated through performance evaluation metrics, including accuracy, F1 score, and confusion matrix. The XGBoost classifiers achieve an accuracy of approximately 92.76% and an equivalent F1 score. ROC curves indicate exceptional performance in class discrimination, with 100% discrimination for the normal class and 98% discrimination for abnormal classes.

• Journal of Korean Home Economics Education Association
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• v.25 no.2
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• pp.79-101
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• 2013

This study examined how practical reasoning processes were reflected in the revised consumer education of technology & home economics textbooks in secondary schools. Twenty-four textbooks from secondary schools for 7th to 10th grades were analyzed. Areas of textbooks analyzed were introduction, body content, learning activity, and evaluation. Analysis criteria were extracted from the previous literature regarding contents and questions dealing with practical reasoning processes and revised by a researcher of this paper. The results and conclusions of this study are as follows. The results of the analysis of the practical reasoning processes showed that, across all grades, "contexts" was the most common element, and "alternatives and means" was the second most common elements. The elements of "consequences", "action and reflection" were less represented in the textbooks, with the exception of the learning activity part. The types of practical reasoning process reflected were classified either as the entire process of reasoning being reflected or some of the process being reflected, or included in the body content. Most of these were some of the process being reflected. Since there were a lot of concept-oriented statements rather than questions, more practical reasoning questions should be developed to increase the reasoning process. In addition, a need exists to develop a variety of ways to utilize the entire practical reasoning processes in the textbooks to help teachers apply the practical reasoning processes to their lessons.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.101-108
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• 2017

The study proposed a system that filters the data that is entered when analyzing big data such as SNS and BLOG. Personal information includes impersonal personal information, but there is also personal information that distinguishes it from personal information, such as religious institution, personal feelings, thoughts, or beliefs. Define these personally identifiable information as sensitive information. In order to prevent this, Article 23 of the Privacy Act has clauses on the collection and utilization of the information. The proposed system structure is divided into two stages, including Big Data Processing Processes and Sensitive Information Filtering Processes, and Big Data processing is analyzed and applied in Big Data collection in four stages. Big Data Processing Processes include data collection and storage, vocabulary analysis and parsing and semantics. Sensitive Information Filtering Processes includes sensitive information questionnaires, establishing sensitive information DB, qualifying information, filtering sensitive information, and reliability analysis. As a result, the number of Big Data performed in the experiment was carried out at 84.13%, until 7553 of 8978 was produced to create the Ontology Generation. There is considerable significan ce to the point that Performing a sensitive information cut phase was carried out by 98%.

• International Commerce and Information Review
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• v.13 no.3
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• pp.229-248
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• 2011

The increasing complexity of business and social settings bas lead to innovation becoming a strategic imperative. The need for innovation in the quest for competitive advantage also means that firms must be dynamic and flexible. This is often achieved through collaborative arrangements such as strategic alliances or strategic network Many organizations form alliances by leveraging their resources to gain access to the partner's skills and capabilities; ultimately to enhance innovation and performance. We demonstrate empirically that the "chain of innovation" is central to the process of innovation in global alliances. This chain comprises the creativity and learning processes and knowledge stock in alliances. Our empirical analysis is based on a survey of alliances that resulted in 114 responses. For management, this research bas significant potential in guiding attention to the chain of innovation, to better manage the overall process of innovation in alliances. Our work shows that more effective creativity and learning processes and a greater knowledge stock lead to a more effective alliance innovation process. Managers therefore, need to concentrate on creating environments wherein the processes of creativity and learning are fostered, increasing the alliance knowledge stock and in turn, increasing innovative output via an effective innovation process.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.125-137
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• 2023

This study analyzed the types of knowledge building discourse and knowledge building processes in small group learning using augmented reality. Eight 8th grade students took classes using augmented reality in solubility, boiling and melting points. These classes were carried out twice and all the classes were videotaped and recorded. Every student participated in a semi-structured interview. In the types of knowledge building discourse, the proportion of knowledge sharing and knowledge construction was similar. Beneath the knowledge sharing, the proportion of introductory level discussion was higher than identifying key elements of augmented reality. Recalling existing knowledge rarely appeared. Under the knowledge construction, the proportion of advanced level discussion was the highest and the proportion of sharing and critiquing ideas at a different level and efforts to rise above current levels of explanation was similar. The introductory level discussion and identifying key elements of augmented reality were developed into efforts to rise above current levels of explanation and sharing and critiquing ideas at a different level. Visualized results of knowledge building processes showed all the students' graph drew an upward curve, though cumulative number of impact value was different by each student. As a result of the study, effective ways of improving small group learning using augmented reality are discussed.

• Korean Educational Research Journal
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• v.41 no.1
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• pp.59-79
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• 2020

Men learning has no fixed route. In other words, any route can be taken, which can also be seen in the structure of other "complex systems" discussed in modern society. It can also be examined through Yang's long-standing classic, The Book of Changes Men learning itself started from informal learning to become today's formal learning. As we look at the stages of human civilization's progress, we can quickly discover these stages of development. The issue of human beings has always been a topic of discussion, and these discussions are ongoing. Men learn through language and tools, technology and culture, and through philosophy, art, and religion to deal with their complex and diverse mental world. Through these various activities, learning is accomplished. This is not limited to the physical processes of one generation learning through inheriting knowledge; men's learning, a kind of mental process, has extended our life. This is why there is no other reason that men's minds and learning are always developing. This study is about how to learn in a complex and diversified modern society and to find out how to coexist with the principles of the "complex system" and The Book of Changes.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.2
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• pp.510-525
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• 2013

The purpose of this study is to investigate adult learners' experience by studying Humanities & General Education and get to know types and characteristics by classifying their learning experiences. This study uses grounded theory method which is suitable to investigate subjective experiences. In this study, data is collected from 13 adult learners by using Focus Group Interview(FGI) who participate in learning experience of Humanities & General Education of D university in Busan region. The data is categorized by open coding, axial coding and selective coding based on data analysis method of grounded theory and analysis processes. This study provides several outcomes as follows: 113 concepts, 38 subcategories and 16 upper categories are derived through the process of abbreviation and categorization of learning experience of Humanities & General Education. In a process of learning experience, this study shows interrelationship in a frame of paradigm and derives results of a process of abbreviation and categorization casual condition, contextual condition, phenomenon and interaction(help/obstruction factor). Tree types of learning experiences and characteristics are drawn as follows: 1) "Self-realization" is the type who participate in Humanities & General Education with desire of learning and they want to find identity and plan detailed future. 2) "The pursuit of happiness" has less desire on learning than "self-realization" and they are types who participate in Humanities & General Education because of someone else's help and suggestion. 3) "Local community" is the type who participate in Humanities & General Education because they feel necessity of social role and they expect local development based on their interest in local community. Several conclusions and suggestions are provided for further studies.

• Korean Medical Education Review
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• v.22 no.2
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• pp.67-76
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• 2020

The structures and processes of medical education have changed little since the publication of Flexner's report, which stressed the scientific orientation of medical education and the curricular structure of 2 years of formal knowledge education and 2 years of clinical experience. However, the previous perspectives on medical education are facing challenges, and these call for new pedagogy and theories on which to base medical education practice. Considering that social dimensions of learning have been emphasized in practice, perspectives that integrate these aspects are needed. Among the various learning theories, social cognitive theory refers to the theoretical framework which contends that learning occurs within interactions with others and environments. From a social cognitive standpoint, learning through observation is a critical component in human functioning. Indeed, observational learning has particular significance in medical education in that it provides the context for which the importance and meaning of role models can be understood. In addition, as theoretical constructs such as self-efficacy and outcome expectations allow us to establish an effective learning environment, exploring the concepts of the theory could be beneficial to medical education practice. In this context, the present review article aims to provide a glimpse of the fundamental assumptions and theoretical concepts of social cognitive theory and discusses the implications the theory has on teaching and learning. Further, a review of previous studies could help explain how the theory has informed medical education practice. Finally, the author will conclude with the implications and limitations of applying social cognitive theory in medical education.