• Convergence Security Journal
• /
• v.22 no.3
• /
• pp.25-32
• /
• 2022

Recently, the image processing industry has been activated as deep learning-based technology is introduced in the image recognition and detection field. With the development of deep learning technology, learning model vulnerabilities for adversarial attacks continue to be reported. However, studies on countermeasures against poisoning attacks that inject malicious data during learning are insufficient. The conventional countermeasure against poisoning attacks has a limitation in that it is necessary to perform a separate detection and removal operation by examining the training data each time. Therefore, in this paper, we propose a technique for reducing the attack success rate by applying modifications to the training data and inference data without a separate detection and removal process for the poison data. The One-shot kill poison attack, a clean label poison attack proposed in previous studies, was used as an attack model. The attack performance was confirmed by dividing it into a general attacker and an intelligent attacker according to the attacker's attack strategy. According to the experimental results, when the proposed defense mechanism is applied, the attack success rate can be reduced by up to 65% compared to the conventional method.

• Journal of the Korean Society for Library and Information Science
• /
• v.57 no.2
• /
• pp.271-291
• /
• 2023

The purpose of this study is to analyze the current status and effects of open access conversion of journals from 7 societies that participated in the "Open Access Publication Declaration Academic Societies in the Field of Library and Information Science", and to identify problems and suggest improvement directions. To this end, the study analyzed the current status based on the elements presented in the "Roadmap for Open Access Publishing Conversion of the Library and Information Science Journals in Korea" and analyzed citation rates. The following problems were identified. First, some journals were not applying CCL or were unable to register it accurately with KJCI, and none of the 7 journals were registered with DOAJ. Second, the newly used journal platforms had not yet registered all previous issues after the conversion. Third, there was a tendency for the article processing charges to be partially increased, and there was also a tendency for editorial staff expenses to increase. Fourth, citation indexes after conversion were lower for both journals compared to the previous 4-5 years. This study proposes that joint publication of journals is necessary to solve practical problems jointly with societies while promoting economies of scale and suggests the need for further development of a roadmap.

• Journal of the Korean Society of Food Culture
• /
• v.22 no.6
• /
• pp.765-774
• /
• 2007

Aging rate of rural area in our country is relatively high compared to that of the urban area. Thus, the introduction of meal service for the elderly residing in the rural area is necessary for their better living quality. Food habit, health and the nutritive intake conditions during the busy farming season were surveyed and comparative analysis of dietary intake for the introduction of meal service in pavilion of the elderly living in Chungnam, Kangwon, Jeonnam and Kyungbuk was performed for basic reference data of meal service introduction to the pavilion of the elderly in rural area. In general subject, the male elderly had a significant difference in marital state and showed that 79.4% was married and 20% was separated by death(P<0.05). In allowance, there were no significant difference but most of them lived with less then three hundred thousand won and especially, female lived with less then one hundred thousand won. In health state, the female elderly showed significant difference on difficulty with every day activity but with small trouble although they had to prepare their own meal(P<0.05). The condition dental health conditions of the female elderly had a significant difference showing bad conditions in following order; Kangwon(48%)>Chungnam(38.1%)>Kyungbuk(22.9%)>Jeonnam(22.5%)(p<0.05). The female elderly showed a significant difference in usage of denture and number of the female elderly without using the denture were very high(p<0.05). In nutrition intake condition, amount of sodium was very high but intakes of fiber and calcium were relatively 1ow(P<0.05). Meal service introduction in the pavilion of the elderly is suggested for the improvement of the life quality of the elderly in rural area. When developing the menu for them, conditions such as shortage of the fiber and calcium in diets, the dental conditions should be considered.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.20 no.2
• /
• pp.73-87
• /
• 2018

The area of agriculture and fisheries business are expanding according to changes in the agriculture and fisheries environment. For the direction of long-term practical field training of department of Agriculture and Fisheries Business, which is a newly created department of Korea National College of Agriculture and Fisheries, production as well as other areas must be reviewed. The original long-term practical field training and the direction of selecting a long-term practical field training appropriate for the new department reviewed in this study are as follow. First, the original long-term practical field training can be summarized as single product-focused management, inadequate connection of production-processing-service areas, and individuality-focused management. However, a case management that sees new value creation as a basis of agricultural development can be summarized as diversification of value creation, horizontal integration, entrepreneurial management through corporate management, and leading management for regional revitalization through connecting local agricultural. Therefore, the direction of selecting the new department's long-term practical field training requires seeking of value creation management through horizontal integration, exploration of agricultural businessmen who have entrepreneurship needed to create added value in agriculture, and a way to connect to the original production-centered long-term practical field training.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.11
• /
• pp.493-504
• /
• 2023

The Republic of Korea is located far from the boundary of the earthquake plate, and the intra-plate earthquake occurring in these areas is generally small in size and less frequent than the interplate earthquake. Nevertheless, as a result of investigating and analyzing earthquakes that occurred on the Korean Peninsula between the past two years and 1904 and earthquakes that occurred after observing recent earthquakes on the Korean Peninsula, it was found that of a magnitude of 9. In this paper, the Korean Peninsula Historical Earthquake Record (2 years to 1904) published by the National Meteorological Research Institute is used to analyze the relationship between earthquakes on the Korean Peninsula and statistical self-similarity. In addition, the problem solved through this paper was the first to investigate the relationship between earthquake data occurring on the Korean Peninsula and statistical self-similarity. As a result of measuring the degree of self-similarity of earthquakes on the Korean Peninsula using three quantitative estimation methods, the self-similarity parameter H value (0.5 < H < 1) was found to be above 0.8 on average, indicating a high degree of self-similarity. And through graph visualization, it can be easily figured out in which region earthquakes occur most often, and it is expected that it can be used in the development of a prediction system that can predict damage in the event of an earthquake in the future and minimize damage to property and people, as well as in earthquake data analysis and modeling research. Based on the findings of this study, the self-similar process is expected to help understand the patterns and statistical characteristics of seismic activities, group and classify similar seismic events, and be used for prediction of seismic activities, seismic risk assessments, and seismic engineering.

• Communications of Mathematical Education
• /
• v.37 no.4
• /
• pp.717-736
• /
• 2023

The purpose of this study is to develop a statistical program using data and artificial intelligence prediction models and apply it to one class in the sixth grade of elementary school to see if it is effective in improving students' statistical literacy. Based on the analysis of problems in today's elementary school statistical education, a total of 15 sessions of the program was developed to encourage elementary students to experience the entire process of statistical problem solving and to make correct predictions by incorporating data, the core in the era of the Fourth Industrial Revolution into AI education. The biggest features of this program are the recognition of the importance of data, which are the key elements of artificial intelligence education, and the collection and analysis activities that take into account context using real-life data provided by public data platforms. In addition, since it consists of activities to predict the future based on data by using engineering tools such as entry and easy statistics, and creating an artificial intelligence prediction model, it is composed of a program focused on the ability to develop communication skills, information processing capabilities, and critical thinking skills. As a result of applying this program, not only did the program positively affect the statistical literacy of elementary school students, but we also observed students' interest, critical inquiry, and mathematical communication in the entire process of statistical problem solving.

• Geophysics and Geophysical Exploration
• /
• v.26 no.4
• /
• pp.211-228
• /
• 2023

Ground-penetrating radar (GPR) surveys are commonly used to monitor embankments, which is a nondestructive geophysical method. The results of GPR surveys can be complex, depending on the situation, and data processing and interpretation are subject to expert experiences, potentially resulting in false detection. Additionally, this process is time-intensive. Consequently, various studies have been undertaken to detect cavities in GPR survey data using deep learning methods. Deep-learning-based approaches require abundant data for training, but GPR field survey data are often scarce due to cost and other factors constaining field studies. Therefore, in this study, a deep- learning-based model was developed for embankment GPR survey cavity detection using data augmentation strategies. A dataset was constructed by collecting survey data over several years from the same embankment. A you look only once (YOLO) model, commonly used in computer vision for object detection, was employed for this purpose. By comparing and analyzing various strategies, the optimal data augmentation approach was determined. After initial model development, a stepwise process was employed, including box clustering, transfer learning, self-ensemble, and model ensemble techniques, to enhance the final model performance. The model performance was evaluated, with the results demonstrating its effectiveness in detecting cavities in embankment GPR survey data.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.6
• /
• pp.841-849
• /
• 2023

Construction projects have risks due to various factors such as construction delays and construction accidents. Based on these construction risks, the method of calculating the construction period of the construction project is mainly made by subjective judgment that relies on supervisor experience. In addition, unreasonable shortening construction to meet construction project schedules delayed by construction delays and construction disasters causes negative consequences such as poor construction, and economic losses are caused by the absence of infrastructure due to delayed schedules. Data-based scientific approaches and statistical analysis are needed to solve the risks of such construction projects. Data collected in actual construction projects is stored in unstructured text, so to apply data-based risks, data pre-processing involves a lot of manpower and cost, so basic data through a data classification model using text mining is required. Therefore, in this study, a document-based data generation classification model for risk management was developed through a data classification model based on SVM (Support Vector Machine) by collecting construction project documents and utilizing text mining. Through quantitative analysis through future research results, it is expected that risk management will be possible by being used as efficient and objective basic data for construction project process management.

• Journal of Korean Elementary Science Education
• /
• v.43 no.1
• /
• pp.185-200
• /
• 2024

This study explored the changes in the elementary science teaching expertise of teachers who participated in an in-school professional learning community for elementary science instructional research. Six elementary school teachers from grades 4, 5, and 6 at an 18-class S elementary school in a medium-sized city in Chungcheongbuk-do conducted collaborative instructional research on elementary science lessons as part of an in-school professional learning community, which was held 26 times over 7 months in 2020. During the professional learning community, video and audio recordings of the activities, research lessons, course materials, and professional learning community reflection activities were collected for analysis. The collected data were analyzed using qualitative research methods; data processing, reading, note-taking, description, classification, interpretation, reporting, and visualization; and the instructional professionalism elements were extracted based on the instructional professionalism framework. In the early professional learning community activity stages, the participating teachers first discussed their teaching perspectives, their experiences, and their goals for teaching science, which resulted in a selection of research questions. The teachers then collaboratively designed and implemented research lessons for each grade level, after which lesson reflections were conducted. The teachers' abilities to engage in qualitative reflection on the research questions improved after each reflection iteration. It was found that this professional learning community collaborative lesson study experience positively contributed to teaching expertise development. Based on the study findings, the implications for using professional learning communities to improve elementary teachers' science teaching expertise are given.

• Smart Media Journal
• /
• v.13 no.2
• /
• pp.32-43
• /
• 2024

Game agents which are behavioral agent for game playing are a crucial component of game satisfaction. However it takes a lot of time and effort to create game agents for various game levels, environments, and players. In addition, when the game environment changes such as adding contents or updating characters, new game agents need to be developed and the development difficulty gradually increases. And it is important to have a game agent that can be customized for different levels of players. This is because a game agent that can play games of various levels is more useful and can increase the satisfaction of more players than a high-level game agent. In this paper, we propose a method for learning and controlling the level of play of game agents that can be rapidly developed and fine-tuned for various game environments and changes. At this time, reinforcement learning applies a policy-based distributed reinforcement learning method IMPALA for flexible processing and fast learning of various behavioral structures. Once reinforcement learning is complete, we choose actions by sampling based on Softmax-Temperature method. From this result, we show that the game agent's play level decreases as the Temperature value increases. This shows that it is possible to easily control the play level.