• Food Science and Preservation
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• v.30 no.5
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• pp.758-769
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• 2023

The main aim of this study was to determine python fat's several physicochemical properties, including dimensions, color, structure, acid value (AV), saponification value (SV), density, and recovery efficiency. The optimum yield obtained was approximately 80.40% at 180℃ for 60 min with an AV of 0.3366 and SV of 179.56 mg KOH/g. Fatty acids, comprising oleic acid (72.462%), palmitic acid (26.243%), linolenic acid (0.835%), and myristic acid (0.459%), were identified using gas chromatography-mass spectrometry (GC-MS). The python fat had a very weak antioxidant capacity and almost no antibacterial ability with gram-positive (Staphylococcus aureus - ATCC 25923 and Bacillus cereus - ATCC 10876) and gram-negative (Escherichia coli - ATCC 25922 and Salmonella enterica - ATCC 35664) bacteria (used the paper disc diffusion method for antibiotic susceptibility testing). Moreover, python fat is considered to be very resistant to high temperatures.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.310-322
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• 2023

Although the network environment is gradually improving, the virtual nature of the network is still the same fact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studied by using Python technology. Specifically, the 2019 "Ethiopian air crash" event was taken as the research subject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June 20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayes classifier. The Weibo network public opinion user identity graph model under the "Ethiopian air crash" on June 20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easily influenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinion users have an influence on other types of public opinion users. That is to say, in the network public opinion space of the "Ethiopian air crash," media public opinion users play an important role in the dissemination of network public opinion information. This research can lay a foundation for the classification and identification of user identity information types under different public opinion life cycles. Future research can start from the supervision of public opinion and the type of user identity to improve the scientific management and control of user information dissemination through Weibo network public opinion.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.117-129
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• 2020

The purpose of this paper is to explore ways to assess computational thinking from a formative perspective and to design a process for assessing programming learning using Python. Therefore, this study explored the computational thinking domain and analyzed research related to assessment design. Also, this study identified the areas of Python programming learning that beginners learn and the areas of computational thinking ability that can be obtained through Python learning. Through this, we designed an assessment method that provides feedback by analyzing syntax corresponding to computational thinking ability. Besides, self-assessment is possible through reflective thinking by using the flow-chart and pseudo-code to express ideas, and peer feedback is designed through code sharing and communication using community.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.4
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• pp.306-311
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• 2020

This paper deals with how to improve the performance of Python language with various libraries when developing a model using big data. The Python language uses the Pandas library for processing spreadsheet-format data such as Excel. In processing data, Python operates on an in-memory basis. There is no performance issue when processing small scale of data. However, performance issues occur when processing large scale of data. Therefore, this paper introduces a method for distributed processing of execution tasks in a single cluster and multiple clusters by using a Dask library that can be used with Pandas when processing data. The experiment compares the speed of processing a simple exponential model using only Pandas on the same specification hardware and the speed of processing using a dask together. This paper presents a method to develop a model by distributing a large scale of data by CPU cores in terms of performance while maintaining that python's advantage of using various libraries is easy.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.247-253
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• 2021

There are various programming errors that occur in the course of programming practice for beginners in computer programming. At this time, since it is difficult for learners to recognize errors by themselves, they correct program errors through the instructor's feedback. However, as students learn programming techniques in an online learning environment due to the COVID-19 pandemic, there is a limit to interaction between the students and the instructor in comparison with offline classes, so it is necessary for learners to develop their own ability to solve programming errors by themselves. Therefore, in this study, error cases in online programming classes using the Python language are analyzed and an online programming education method that can improve learners' ability to correct programming errors is proposed based on the analysis results.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.181-188
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• 2024

With the development of precision facility technology, the importance of four-axis CNC precision processing technology is increasing. However, due to complex shape processing, it is difficult to operate the system. This paper compared precision control and efficiency by manufacturing a four-axis control structure to solve this problem and implementing Bresenham's Line Algorithm and Runspeed Algorithm without using commercial programs. When Runspeed was applied, there was an error improvement of about 12.03% and curvature accuracy improvement compared to Bresenham. It was confirmed that precise processing was possible to a three-dimensional structure by driving a rotary shaft A motor.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.439-441
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• 2023

National park is one of the important types of protected area management systems established by IUCN and a management model for effective conservation and sustainable use of natural and cultural heritage in countries around the world, and it assumes important roles in conservation, scientific research, education, recreation and driving community development. This study takes Liaohe National Park in China, a typical representative of global coastal wetlands, as a case study, and uses python technology to collect travelogues and reviews of visitors from Mafengwo.com, Ctrip.com, Go.com, Meituan.com and Dianping.com as a source, and the text spans from 2015 to 2022. The results show that wildlife resources, natural landscape with river and sea, wetland ecology and fishing and hunting culture of northern China are fully reflected in the perceptions of visitors to Liaohe National Park. However, there is still much room for improvement in terms of supporting services and facilities, public education and tourists' experience and participation in Liaohe National Park. In this paper, we use python data visualization technology to study the public perception of wetland wildlife as the theme, and grasp the satisfaction, spatial distribution, activity content and emotional tendency of the public in the process of wetland wildlife as the theme, so as to better promote the Liaohe National Park to better carry out the public experience while strictly adhering to ecological protection, and to provide the Liaohe National Park with a better opportunity to This will provide scientific basis for the Liaohe National Park to play a better role in ecological civilization construction and education of ecological civilization awareness.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.140-143
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• 2019

The Internet has been expanded constantly and greatly such that we are having vast number of web pages with dynamic changes. Especially, the fast development of wireless communication technology and the wide spread of various smart devices enable information being created at speed and changed anywhere, anytime. In this situation, web crawling, also known as web scraping, which is an organized, automated computer system for systematically navigating web pages residing on the web and for automatically searching and indexing information, has been inevitably used broadly in many fields today. This paper aims to implement a prototype web crawler with Python and to improve the execution speed using threads on multicore CPU. The results of the implementation confirmed the operation with crawling reference web sites and the performance improvement by evaluating the execution speed on the different thread configurations on multicore CPU.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.229-231
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• 2021

In this paper, we describe a hardware design of the SIMECK block cipher algorithm that can be implemented in lightweight hardware with appropriate security strength. To achieve fast encryption and decryption operations, it was designed using two-step method that reduces the number of operation rounds. The designed SIMECK cryptographic core was implemented in Arty S7-50 FPGA device and its hardware operation was verified with a GUI using Python.