• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.113-127
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• 2021

Topic modeling has been receiving much attention in academic disciplines in recent years. Topic modeling is one of the applications in machine learning and natural language processing. It is a statistical modeling procedure to discover topics in the collection of documents. Recently, there have been many attempts to find out topics in diverse fields of academic research. Although the first Department of Industrial Engineering (I.E.) was established in Hanyang university in 1958, Korean Institute of Industrial Engineers (KIIE) which is truly the most academic society was first founded to contribute to research for I.E. and promote industrial techniques in 1974. Korean Society of Industrial and Systems Engineering (KSIE) was established four years later. However, the research topics for KSIE journal have not been deeply examined up until now. Using topic modeling algorithms, we cautiously aim to detect the research topics of KSIE journal for the first half of the society history, from 1978 to 1999. We made use of titles and abstracts in research papers to find out topics in KSIE journal by conducting four algorithms, LSA, HDP, LDA, and LDA Mallet. Topic analysis results obtained by the algorithms were compared. We tried to show the whole procedure of topic analysis in detail for further practical use in future. We employed visualization techniques by using analysis result obtained from LDA. As a result of thorough analysis of topic modeling, eight major research topics were discovered including Production/Logistics/Inventory, Reliability, Quality, Probability/Statistics, Management Engineering/Industry, Engineering Economy, Human Factor/Safety/Computer/Information Technology, and Heuristics/Optimization.

• Journal of The Korean Association of Information Education
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• v.5 no.3
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• pp.321-328
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• 2001

Generally, a Learning Games made based on Off-line. But Today, Web based learning has been used for many educational system by aid of the development of internet technique. If Off-line learning game serviced by On-line learning game, can provide learner with interesting and growing learner's study will. In this paper, I design the Mathematical of Elementary school Roll playing game for learning based on On-line. This is matched the point of On-line game with the point of Learning. A Learner's mathematical technic will be improve by The Mathematical On-line Roll playing game for Elementary school student. A student's ability of self directed learning and solving problem is expended too.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3510-3516
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• 2010

In this paper to make young children to learn habits of the animals, crying, features, and English and Korean language, The system was developed to target the zoo various animals exist. If young child places a doll on the front of interesting animal, then young child can learn to look through the display connected to the model. The zoo is reducing the current appearance of the zoo, sensors that can recognize animals are attached to each cage. Attached to each sensor has a unique ID, If this approach recognizes a doll baby and will transmit a unique ID to the handler. Transmitted ID search the matched value sent from the database to retrieve the content and then the content is to be output through the output device. Also if the doll near the animal's room, young children find out animal sound and basic learning by multimedia effects. At the same time Korean, English, Mathematics are learned.

• Wind and Structures
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• v.26 no.5
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• pp.331-341
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• 2018

A numerical study on the flow over a square cylinder in the vicinity of a wall is conducted for different Couette-Poiseuille-based non-uniform flow with the non-dimensional pressure gradient P varying from 0 to 5. The non-dimensional gap ratio L (=$H^{\ast}/a^{\ast}$) is changed from 0.1 to 2, where $H^{\ast}$ is gap height between the cylinder and wall, and $a^{\ast}$ is the cylinder width. The governing equations are solved numerically through finite volume method based on SIMPLE algorithm on a staggered grid system. Both P and L have a substantial influence on the flow structure, time-mean drag coefficient ${\bar{C}}_D$, fluctuating (rms) lift coefficient ($C_L{^{\prime}}$), and Strouhal number St. The changes in P and L leads to four distinct flow regimes (I, II, III and IV). Following the flow structure change, the ${\bar{C}}_D$, $C_L{^{\prime}}$, and St all vary greatly with the change in L and/or P. The ${\bar{C}}_D$ and $C_L{^{\prime}}$ both grow with increasing P and/or L. The St increases with P for a given L, being less sensitive to L for a smaller P (< 2) and more sensitive to L for a larger P (> 2). A strong relationship is observed between the flow regimes and the values of ${\bar{C}}_D$, $C_L{^{\prime}}$ and St. An increase in P affects the pressure distribution more on the top surface than on bottom surface while an increase in L does the opposite.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1502-1522
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• 2019

Leakage of secret keys may be the most devastating problem in public key cryptosystems because it means that all security guarantees are missing. The forward security mechanism allows users to update secret keys frequently without updating public keys. Meanwhile, it ensures that an attacker is unable to derive a user's secret keys for any past time, even if it compromises the user's current secret key. Therefore, it offers an effective cryptographic approach to address the private key leakage problem. As an extension of the forward security mechanism in certificate-based public key cryptography, forward-secure certificate-based signature (FS-CBS) has many appealing merits, such as no key escrow, no secure channel and implicit authentication. Until now, there is only one FS-CBS scheme that does not employ the random oracles. Unfortunately, our cryptanalysis indicates that the scheme is subject to the security vulnerability due to the existential forgery attack from the malicious CA. Our attack demonstrates that a CA can destroy its existential unforgeability by implanting trapdoors in system parameters without knowing the target user's secret key. Therefore, it is fair to say that to design a FS-CBS scheme secure against malicious CAs without lying random oracles is still an unsolved issue. To address this problem, we put forward an enhanced FS-CBS scheme without random oracles. Our FS-CBS scheme not only fixes the security weakness in the original scheme, but also significantly optimizes the scheme efficiency. In the standard model, we formally prove its security under the complexity assumption of the square computational Diffie-Hellman problem. In addition, the comparison with the original FS-CBS scheme shows that our scheme offers stronger security guarantee and enjoys better performance.

• Journal of The Korean Association For Science Education
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• v.25 no.7
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• pp.746-753
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• 2005

In order to be efficient teachers should understand the current level of leaners through diagnostic evaluation. However, it is arduous to administer a diagnostic examination in every class because of various limitations. This study examined, the major issues arising from the development of a new science diagnostic evaluation system by incorporating the using knowledge state analysis method. The proposed evaluation system was based on the knowledge state analysis method. Knowledge state analysis is a method where by a distinguished collection of knowledge uses the theory of knowledge space. The theory of knowledge space is very advantageous when analyzing knowledge in strong hierarchies like mathematics and science. It helps teaching plan through methodically analyzing a hierarchy viewpoint for students' knowledge structure. The theory can also enhance objective validity as well as support a considerable amount of data fast by using the computer. In addition, student understanding is improved through individualistic feedback. In this study, an evaluation instrument was developed that measured student learning outcome, which is unattainable from the existing method. The instrument was administered to pre-service physics teachers, and the results of student evaluation was analyzed using the theory of knowledge space. Following this, a revised diagnostic evaluation system for facilitating student individualized learning was constructed.

• Journal of The Korean Association of Information Education
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• v.8 no.2
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• pp.155-164
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• 2004

In the field of number and operation of mathematics, a learner's learning deficit in one year can disturb or obstruct his or her learning in the following year, which is an obvious characteristic in math education. But the problem doesn't stop here. It may increase poor learning in the related math field or, in a serious case, cause mathematical learning incompetence. In the other hand, a teacher must guide a class of about 40 students and take charge of overburdensome routine; it's really impossible for him or her to secure individual teaching time for poor learners and to give lessons considering their individual poor learning elements. In order to solve these problems, this study has found out some poor learning elements from poor learners in teaching mathematical number and operation, offered learning fit for them, and allowed them to approach a learning system regardless of time and space. And it has embodied a web-based learning system for operation field underachiever in elementary school, applied it to the scene of education, and analyzed the results so that a teacher may manage their learning results by DB and guide poor learners systematically. As a consequence, the study could reduce a teacher's teaching overburden and at the same time, raise the learning accomplishments of poor learners.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.89-103
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• 2023

Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.