• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.119-128
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• 2020

Object detection is an important field of computer vision and is applied to applications such as security, autonomous driving, and face recognition. Recently, as the application of artificial intelligence technology including deep learning has been applied in various fields, it has become a more powerful tool that can learn meaningful high-level, deeper features, solving difficult problems that have not been solved. Therefore, deep learning techniques are also being studied in the field of object detection, and algorithms with excellent performance are being introduced. In this paper, a deep learning-based object detection algorithm used to detect multiple objects in an image is investigated, and future development directions are presented.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.190-195
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• 2021

Currently, one of the fields leading the 4th industrial revolution is the image recognition field of artificial intelligence, which is showing good results in many fields. In this paper, using is a YOLO V2 model, which is one of the image recognition models, we intend to classify and select into three types according to the characteristics of fruits. To this end, it was designed to proceed the number of iterations of learning 9000 counts based on 640 mandarin image data of 3 classes. For model evaluation, normal, rotten, and unripe mandarin oranges were used based on images. We as a result of the experiment, the accuracy of the learning model was different depending on the number of learning. Normal mandarin oranges showed the highest at 60.5% in 9000 repetition learning, and unripe mandarin oranges also showed the highest at 61.8% in 9000 repetition learning. Lastly, rotten tangerines showed the highest accuracy at 86.0% in 7000 iterations. It will be very helpful if the results of this study are used for fruit farms in rural areas where labor is scarce.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.274-281
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• 2021

In the field of artificial intelligence education, discussions on the direction of artificial intelligence education are actively underway, and it is necessary to establish a foundation for future information education. It is necessary to design a creative convergence teaching-learning and evaluation method. Although AI experience coding education has been applied, the evaluation stage is insufficient. In this paper, we propose an evaluation system that can verify the validity of the proposed education model to find a way to supplement the existing learning module. The core components of this proposed system are Assessment-Factor, Self-Diagnosis, Item Bank, and Evaluation Result modules, which are designed to enable system access according to the roles of administrator, instructors and learners. This system enables individualized learning through online and offline connection.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.412-419
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• 2022

The amount of digital text data is growing exponentially, and many machine learning solutions are being used to monitor and manage this data. Artificial intelligence and machine learning are used in many areas of our daily lives, but the underlying processes and concepts are not easy for most people to understand. At a time when many experts are needed to run a machine learning solution, no-code machine learning tools are a good solution. No-code machine learning tools is a platform that enables machine learning functions to be performed without engineers or developers. The latest No-Code machine learning tools run in your browser, so you don't need to install any additional software, and the simple GUI interface makes them easy to use. Using these platforms can save you a lot of money and time because there is less skill and less code to write. No-Code machine learning tools make it easy to understand artificial intelligence and machine learning. In this paper, we examine No-Code machine learning tools and compare their features.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.56-61
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• 2023

The present study explored a comprehensive investigation of university professors' perspectives on the implementation of ChatGPT - an artificial intelligence-powered language model - in their teaching practices. A diverse group of 30 university professors responded to a questionnaire about the level of their interest in implementing the tool, willingness to apply it, and concerns they have regarding the intervention of ChatGPT in higher education setting. The results showed that the participants are highly interested in employing the tool into their teaching practice, and find that the students are likely to benefit from using ChatGPT in classroom settings. On the other hand, they displayed concerns regarding high depandency on data, privacy-related issues, lack of supports required, and technical contraints. In today's fast-paced society, educators are urged to mindfully apply this inevitable generative AI means with thoughtfulness and ethical considerations to and for their learners. Relevant topics are discussed to successfully intervene AI tools in teaching practices in higher education.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.249-253
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• 2024

The ultimate purpose of this study is as follows: The current primary concern in the defense sector revolves around how to strategically utilize Fourth Industrial Revolution technologies in combat. The Fourth Industrial Revolution denotes a shift towards an environment where automation and connectivity are maximized, driven by technologies such as artificial intelligence. Coined by Klaus Schwab in the 2015 Davos Forum, this term highlights the significant role of machine learning and artificial intelligence. Particularly, the military application of Fourth Industrial Revolution technologies is expected to be actively researched and implemented. Combat involves military actions between units, typically conducted as part of a larger war, with units striving to achieve one or more objectives. The concept of combat refers to the fundamental ideas of how units should engage with the enemy, both presently and in future scenarios, to achieve assigned objectives.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.128-133
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• 2024

Painting, as an artistic creation with aesthetic characteristics, is inseparable from "shape". "Modeling" is a subjective way of expressing objects, and "black shape" is not only a way of expression, but also a way of composition. "Black shape" is a way of expressing the overall picture of the creator, and "black shape" extracted from the pattern analysis of black and white gray structure is a powerful means to deeply explore the emotions and thoughts of the painter. How to create the expression of subjective intention in the creation of artificial figure painting and to explore the beauty of picture form and the presentation of formal language in multiple dimensions is always sought by painters. Tang Dynasty political stability, economic and cultural development of unprecedented prosperity, "Toujian Diu" as a representative painting of Tang Dynasty, the figure is plump and realistic, colorful but elegant. It not only represents the aesthetic taste of the Tang Dynasty, but also reflects the overall style of the Tang Dynasty's artificial figure painting. The aim of this paper is to explore the value of "black shape" in "Toughen Diagram" and analyze its multi-component form in depth.

• Journal of Korean Academy of Nursing
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• v.31 no.4
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• pp.692-702
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• 2001

Purpose: To extend the understanding on climacteric symptoms, and to improve women's health and the quality of life by providing the basic data relating to the climacteric symptoms of natural menopausal women and artificial menopausal women. Method: The subjects of this study were 149 women selected conviniently (89 natural menopausal women and 60 total hystrectomy women) who have visited the climacteric clinic of G. hospital in Inchon, the MENSI questionnaire which was developed by Sarrel (1995)was modified considering Korean culture for the measuring tool of this study with 20 items of question(Cronbach's$\alpha$ =.76), duration of data collection with the questionnaire was 5 months from Sept. 1, 2000 to Jan. 30, 2001. Result: Artificial meanopausal women showed statistically significant higher menopausal symptoms than the natural menopausal women in the most of the items, and psychiatric and urogenital symtoms of artificial menopausal women were significantly higher than those of the natural menopausal women. Conclusion: Nursing intervention for psychological support upon artificial menopausal women and their spouses is recommended more than natural menpause women.

• The Korean Journal of Mycology
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• v.35 no.2
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• pp.76-80
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• 2007

This study was carried out to obtain basic data on mycelial growth characteristics for an artificial cultivation of Grifola frondosa. Ten strains of G. frondosa were collected from Korea, China and Japan and investigated its optimal culture condition. Among four kinds of mushroom culture media, PDA medium was selected as the suitable culture medium. The optimal conditions for the mycelial growth of G. frondosa in PDA medium were $25^{\circ}C$ and $4{\sim}5$ of pH, respectively. The carbon and nitrogen sources for the optimum mycelial growth were fructose and peptone, respectively, and the highest mycelial growth was observed when the C/N ratio was $10{\sim}20$.

• Journal of Microbiology and Biotechnology
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• v.8 no.5
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• pp.523-530
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• 1998

Rapid and quantitative analysis of physiological change and clavulanic acid production was studied by the combination of pyrolysis mass spectrometry (PyMS) and artificial neural network (ANN) in Streptomyces clavuligerus. Firstly, the continuous culture studies were carried out to get the physiological background and PyMS samples. Clavulanic acid production was inversely related to growth rate: Mycelium growth and $q_{cal}$ were optimum at 0.1 $h^{-1}\; and \;0.025 h^{-1}$ respectively. Changes in specific nutrient uptake rates ($q_{gly}$ and $q_{amn}$) also affected clavulanic acid production since clavulanic acid production appeared to be stimulated by the limitation of carbon and nitrogen. Fermentation broth containing mycelium taken from continuous cultures was analyzed by PyMS, and the PyMS spectra were analyzed with multivariate statistics. PCCV plots revealed that samples harvested under the same culture condition were clustered together but samples from different culture conditions formed separate clusters. To deconvolute the pyrolysis mass spectra so as to obtain quantitative information on the concentration of clavulanic acid, ANN was trained on Py MS data using a radial basis function classifier. The results showed that the physiological stages with different growth rate were successfully differentiated and it was possible to monitor the clavulanic acid production precisely and rapidly.