• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.425-433
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• 2023

In this study, we developed a virtual artist play lesson model using gamification concepts and AI-generated art programs to foster creative thinking in freshman art majors. Targeting first-year students in the Digital Media Art Department at Sichuan Film & Television University in China, this course aims to alleviate fear of artistic creation and enhance problem-solving abilities. The educational model consists of four stages: persona creation, creative writing, text visualization, and virtual exhibitions. Through persona creation, students established their artist identities, and by introducing game-like elements into writing experiences, they discovered their latent creativity. Using AI-generated art programs for text visualization, students gained confidence in their creations, and in the virtual exhibitions, they were able to enhance their self-esteem as artists by appreciating and evaluating each other's works. This educational model offers a new approach to promoting creative thinking and problem-solving skills while increasing learner engagement and interest. Based on these research findings, we expect that by developing and implementing educational strategies that cultivate creative thinking, more students will grow their artistic capacities and creativity, benefiting not only art majors but also students from various fields.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.683-690
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• 2021

The purpose of this study is to identify research trends on artificial intelligence education. We analyzed 164 domestic journal papers related to AI education published since 2016. The criteria for papers analysis are number of publications by year, journal name, research topic, research type, data collection method, research subject, and subject. The main research areas and areas that require further research are reviewed. The method of the study was analyzed based on the topic and summary of the selected papers, but the text was checked if it was unclear. As a result of the study, research on 'artificial intelligence education' started in earnest after 2017, and has been rapidly increasing in recent years. As a result of the analysis, there were many studies on artificial intelligence education programs and content development, and artificial intelligence perception and image. As for the type of research, there were many quantitative studies, and the development research method was used a lot as a data collection method. In the study subjects, elementary school had a high proportion, and in subject, it was found that there were many practicial subject(technology) dealing with artificial intelligence contents.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.86-93
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• 2019

The population of domestic companion animals is estimated to be about 10 million now. In recent years, the domestic pet market has been launching a wide range of products and services for high quality, smart and well-being. As a result, the market size will increase from 900 billion won in 2012 to 2.3 trillion won in 2016, which has more than doubled in five years. The industry expects to reach 6 trillion won by 2020, expecting 3 trillion won this year. In particular, domestic dogs and cats market is estimated at 275.5 billion won, accounting for 19% of the domestic animal market and 1.425 billion won for the world market. However, despite the growing market for companion animals products, unfortunately the import dependence on related industrial goods is still high and the quality of service is very low. Unlike Europe and the United States, 90% of companion animals are housed in apartments, often causing problems in the health and safety of companions and companions. The purpose of this study is to develop a smart house for companion animals with environmental friendliness and AI function that can be won in competition with products of developed countries. The results of this study are expected to contribute to the creation of a new value - added base for the related industries through the strengthening of the competitiveness of the related SMEs and further the effect of employment increase and import substitution.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.519-526
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• 2019

Objective: We determined the risk factors limiting first service conception (FSC) rate in dairy cows and their economic impact. Methods: Data were collected from 790 lactations regarding cow parity, peri- and postpartum disorders, body condition score (BCS), reproductive performance, and expenses associated with reproductive management (treatment, culling, and others). Initially, we identified the risk factors limiting FSC rate in dairy cows. Various biological and environmental factors, such as herd, cow parity, BCS at 1 month postpartum and first artificial insemination (AI), resumption of cyclicity within 1 month of calving, year, AI season, insemination at detected estrus or timed AI, peri- and postpartum disorders, and calving to first AI interval, were evaluated. Next, we evaluated the economic impact of the success or failure of FSC by comparing the expense associated with reproductive management until conception between cows that did or did not conceive at their first service. Results: Cows with BCS <3.0 had a lower probability of conceiving at first insemination (odds ratio [OR] = 0.64, p<0.05) than cows with $BCS{\geq}3.0$. Cows inseminated during summer were less likely to conceive (OR = 0.44, p<0.001) than cows inseminated during spring. Cows with peri- or postpartum disorders were less likely to conceive (OR = 0.55, p<0.001) than cows without disorders. Survival curves generated using MedCalc showed an 81 day extension in the mean interval between calving and conception in cows that failed to conceive over those that did conceive at first insemination. Cows failing conceive required additional expenditure on reproductive treatment ($55.40) and other management ($567.00) than cows that conceived at first insemination. Conclusion: Lower BCS, hot weather at first insemination, and peri- and postpartum disorders are risk factors limiting FSC, which result in an economic loss of $622.40 per dairy cow.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.501-511
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• 2022

In 2021, ransomware attacks became popular, and the number is rapidly increasing every year. Since PowerShell is used as the primary ransomware technique, the need for PowerShell-based malware detection is ever increasing. However, the existing detection techniques have limits in that they cannot detect obfuscated scripts or require a long processing time for deobfuscation. This paper proposes a simple and fast deobfuscation method and a deep learning-based classification model that can detect PowerShell-based malware. Our technique is composed of Word2Vec and a convolutional neural network to learn the meaning of a script extracting important features. We tested the proposed model using 1400 malicious codes and 8600 normal scripts provided by the AI-based PowerShell malicious script detection track of the 2021 Cybersecurity AI/Big Data Utilization Contest. Our method achieved 5.04 times faster deobfuscation than the existing methods with a perfect success rate and high detection performance with FPR of 0.01 and TPR of 0.965.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.137-142
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• 2022

Every year, the number of wild animals appearing in human settlements increases, resulting in increased damage to property and human life. In particular, the damage is more severe when wild animals appear on highways or farmhouses. To solve this problem, ecological pathways and guide fences are being installed on highways. In addition, in order to solve the problem in farms, horn repelling using sensors, installing a net, and repelling by smell of excrement are being used. However, these methods are expensive and their effectiveness is not high. In this paper, we used YOLO (You Only Look Once), an AI-based image analysis method, to analyze harmful animals in real time to reduce malfunctions, and high-brightness LEDs and ultrasonic frequency speakers were used as extermination devices. The speaker outputs an audible frequency that only animals can hear, increasing the efficiency to only exterminate wild animals. The proposed system is designed using a general-purpose board so that it can be installed economically, and the detection performance is higher than that of the devices using the existing sensor.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.69-76
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• 2021

The purpose of this study is to identify research trends on artificial intelligence education. We analyzed 164 domestic journal papers related to AI education published since 2016. The criteria for thesis analysis are number of publications by year, journal name, research topic, research type, data collection method, research subject, and subject. The main research areas and areas that require further research are reviewed. The method of the study was analyzed based on the topic and summary of the selected thesis, but the text was checked if it was unclear. As a result of the study, research on 'artificial intelligence education' started in earnest after 2017, and has been rapidly increasing in recent years. As a result of the analysis, there were many studies on artificial intelligence education programs and content development, and artificial intelligence perception and image. As for the type of research, there were many quantitative studies, and the development research method was used a lot as a data collection method. In the study subjects, elementary school had a high proportion, and in subject, it was found that there were many practicial subject(technology) dealing with artificial intelligence contents.

• Human Ecology Research
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• v.61 no.1
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• pp.15-28
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• 2023

The aim of this study was to develop, implement, and evaluate the use of Artificial Intelligence in the prevention of violence among middle-school students. The sample for this study consisted of 20 first-year middle-school students who participated in theme selection activities in a free semester program as part of their home economics studies. The data for the study consisted of nine class observation logs, four group activity outputs, 30 class results, an online survey, and in-depth interviews with three students. A program called "R.U.OK" was developed by setting problematic situation for school violence prevention linked to the contents of the Home Economics Education(HEE) curriculum. After the program was implemented, the survey on the students' class satisfaction content elements, with AI-based learning activities and PBL and interest, displayed high points, with an average of 4.0 or higher. Our qualitative analysis produced four significant results. First, students' concerns about school violence had increased and they showed a change in attitude, having more empathy with friends and more interest in their surroundings. Second, digital and AI literacy had improved, and students' interest in digital media learning had increased. Third, there had been an improvement in problem-solving ability in terms of being able to think more critically and independently. Fourth, the results also demonstrated that there had been a positive effect on self-direction and an improved capacity for teamwork. This study was significant in demonstrating the effectiveness of a program for the prevention of school violence based on the use of digital technology in the educational environment.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.661-672
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• 2022

After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.1922-1929
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• 2020

Objective: The present study aimed to survey seasonal changes in reproductive performance of local cows receiving artificial insemination (AI) in the Pursat province of Cambodia, a tropical country, to investigate if ambient conditions affect the reproductive performance of cows as to better understand the major problems regarding cattle production. Methods: The number of cows receiving AI, resultant number of calving, and calving rate were analyzed for those receiving the first AI from 2016 to 2017. The year was divided into three seasons: cool/dry (from November to February), hot/dry (from March to June), and wet (from July to October), based on the maximal temperature and rainfall in Pursat, to analyze the relationship between ambient conditions and the reproductive performance of cows. Body condition scores (BCS) and feeding schemes were also analyzed in these seasons. Results: The number of cows receiving AI was significantly higher in the cool/dry season than the wet season. The number of calving and calving rate were significantly higher in cows receiving AI in the cool/dry season compared with the hot/dry and wet seasons. The cows showed higher BCSs in the cool/dry season compared to the hot/dry and wet seasons probably due to the seasonal changes in the feeding schemes: these cows grazed on wild grasses in the cool/dry season but fed with a limited amount of grasses and straw in the hot/dry and wet seasons. Conclusion: The present study suggests that the low number of cows receiving AI, low number of calving, and low calving rate could be mainly due to poor body condition as a result of the poor feeding schemes during the hot/dry and wet seasons. The improvement of body condition by the refinement of feeding schemes may contribute to an increase in the reproductive performance in cows during the hot/dry and wet seasons in Cambodia.