• Journal of Internet of Things and Convergence
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• v.4 no.1
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• pp.31-36
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• 2018

In this paper, we developed a chatbot system using the Django framework using the KakaoTalk API so that college students can easily search for important information in their university. Unlike existing chatbot systems that provide only specific information, the chatbot developed in this research automatically provides search results for various types of user queries such as weather, YouTube, Naver real-time ranking search and language translation as well as important information within their own university. We developed a module using Apache, Python and Django in AWS Ubuntu server and developed a chatbot system that automatically responds to user queries by communicating with KakaoTalk server using KakaoTalk API and BeautifulSoup. The system developed in this study is expected to be applicable to the future university entrance information promotion and election promotion system.

• Journal of Engineering Education Research
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• v.24 no.5
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• pp.3-14
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• 2021

This study deals with the case of online-based project learning, which was designed for the purpose of university educational innovation and enhancing learners' competencies required by society, operated during the COVID-19 pandemic. The course was applied Python programming language, team-based project learning, and intensive course system, which is required by our society and companies in the era of the 4th industrial revolution. Also it was operated as a non-face-to-face online class, which would have been operated in an offline class if it had not been for Covid 19 pandemic, to explore the possibilities and educational effects of online learning. To do this, 32 university students participated in online-based project learning during 8 weeks, and then conducted a survey. The survey results were analyzed in terms of i) non-face-to-face online learning, ii) team-based project learning, and iii) application of the intensive course system. Results say that most of the learners were satisfied with the online learning, team-based project learning, and the intensive semester system applied in this course at a high level, and also they clearly presented the reasons. Thereby, it has been confirmed that the learners were already well aware of the pros and cons of each learning method. Based on these results, the implications were discussed.

• The Mathematical Education
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• v.58 no.2
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• pp.319-335
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• 2019

In this paper, we examine the effectiveness of calculation according to automation, which is one of Computational Thinking, by coding the conceptual process into Python language, focusing on the concept of divisibility in elementary school textbooks. The educational implications of these considerations are as follows. First, it is possible to make a field of learning that can revise the new mathematical concept through the opportunity to reinterpret the Conceptual Thinking learned in school mathematics from the perspective of Computational Thinking. Second, from the analysis of college students, it can be seen that many students do not have mathematical concepts in terms of efficiency of computation related to the divisibility. This phenomenon is a characteristic of the mathematics curriculum that emphasizes concepts. Therefore, it is necessary to study new mathematical concepts when considering the aspect of utilization. Third, all algorithms related to the concept of divisibility covered in elementary mathematics textbooks can be found to contain the notion of iteration in terms of automation, but little recursive activity can be found. Considering that recursive thinking is frequently used with repetitive thinking in terms of automation (in Computational Thinking), it is necessary to consider low level recursive activities at elementary school. Finally, it is necessary to think about mathematical Conceptual Thinking from the point of view of Computational Thinking, and conversely, to extract mathematical concepts from computer science's Computational Thinking.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.315-323
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• 2022

In this paper, we propose a python education program that applies computational thinking for non-majors and programming beginners. In this study, we focus on the basics of program logic, breaking away from the difficult grammar and memorization-oriented programming education. And by applying the problem-solving procedure of computational thinking, we propose an educational program that allows non-majors and programming beginners to learn programming easily. In this paper, an 8-week educational program was applied to middle school students with little text coding experience. and through a post-satisfaction survey, it was found that their confidence in programming increased, and they were able to apply computational thinking could be applied to life and other subjects. Although the importance of programming education is being emphasized, it is expected that it will be used as a useful educational program when composing program education for non-majors and beginners in programming for learners who still find it difficult to learn programming.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2322-2327
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• 2009

Uncertainty of power system operation increases due to complexity and facilities diversification in the power system. Therefore the importance of SCADA(Supervisory Control and Data Acquisition) system which obtain and manage the actual data in real-time is very important. Accordingly in the studies of power system analysis, the efforts to include real-time power system analysis in simulation and applications are made in many ways. The real-time communication characteristics of SCADA system is considered so as to develop the power system analysis program that matches actual system conditions. The observation and management of SCADA system is realized by Intouch which is mainly used for factory automation and PSS/E(Power System Simulator for Engineers) provides real time system data. SQL DB and Python language is used for real-time communication between the softwares. It is very comfortable to use the various functions in Intouch WindowMaker.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.590-600
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• 2009

In the simulation of underwater vehicles such as a submarine or a torpedo, various type of simulations like an engineering level simulation for predicting the performance precisely and an engagement level simulation for examining the effectiveness of a certain tactic is required. For this reason, a tactics manager which can change the behavior of a simulation model according to external tactics is needed. In this study the tactics manager supporting a script language and engine which can represent various tactics and can help users define external input tactics for the tactic manager easily is suggested. Python and Lua which are representative among script languages have been compared and analyzed from the viewpoint of a tactic manage, and the tactic manger using the script engines of those script languages was implemented. To demonstrate the effectiveness of the tactic manager, a target motion analysis simulation of the warfare between a submarine and a surface ship.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.11-20
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• 2015

This paper describes design and implementation experience of SAS-G2S slotmachine accounting protocol middleware system that converts the legacy binary format SAS (Slot Accounting System) protocol with servers with recent standards G2S protocol. The paper examines the difference of two protocols such as link control, message format, and parameters. The converter architecture uses bridge and connector patterns and implemented in C++ and Python mixed language on Linux environment. The prototype system uses a 1GMHz-512MB linux machine and has passed Korean official protocol compatibility and performance test in 2015.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.239-250
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• 2022

This study examined the level of capital structure and its determinants of publicly traded companies in Malaysia before and after the COVID-19 pandemic. The data for this study was examined using Python Programming Language and time-series financial data from 2,784 quarterly observations in 2019 and 2020. The maximum debt is larger before the COVID-19 period, according to the findings. During the COVID-19 period, short-term debts and total debts have both decreased slightly. However, long-term debts have increased marginally. As a result, this research demonstrates that the capital structure has changed slightly during the COVID-19 period. The findings imply that independent of the capital structure proxies, tangibility, liquidity, and business size had an impact on capital structure in both periods. It was found that profitability had a significant impact on total debts both before and after the COVID-19 crisis. While higher-profit enterprises appear to have lesser short-term debts before the COVID-19 periods, they are also more likely to have lower long-term debts during the COVID-19 periods. Even though growing companies tend to have higher short-term debts and thus total debts during those periods, longterm debts are unaffected by potential growth.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.79-84
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• 2023

Apache Spark, which provides the fastest processing speed among recent distributed and parallel processing technologies, provides real-time functions and machine learning functions. Although official documentation guides for these functions are provided, a method for fusion of functions to predict a specific value in real time is not provided. Therefore, in this paper, we conducted a study to predict the value of data in real time by fusion of these functions. The overall configuration is collected by downloading stock price data provided by the Python programming language. And it creates a model of regression analysis through the machine learning function, and predicts the adjusted closing price among the stock price data in real time by fusing the real-time streaming function with the machine learning function.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.132-138
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• 2022

Due to the impacts of the current pandemic COVID-19 and the continuation of studying online. There is an urgent need for an effective and efficient education platform to help with the continuity of studying online. Therefore, the question bank system (QB) is introduced. The QB system is designed as a website to create a single platform used by faculty members in universities to generate questions and store them in a bank of questions. In addition to allowing them to add two types of questions, to help the lecturer create exams and present the results of the students to them. For the implementation, two languages were combined which are PHP and Python to generate questions by using Artificial Intelligence (AI). These questions are stored in a single database, and then these questions could be viewed and included in exams smoothly and without complexity. This paper aims to help the faculty members to reduce time and efforts by using the Question Bank System by using AI and Natural Language Processing (NLP) to extract and generate questions from given text. In addition to the tools used to create this function such as NLTK and TextBlob.