• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.897-904
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• 2022

Sports video is a very critical information resource. High-precision extraction of effective segments in sports video can better assist coaches in analyzing the player's actions in the video, and enable users to more intuitively appreciate the player's hitting action. Aiming at the shortcomings of the current sports video clip extraction results, such as strong subjectivity, large workload and low efficiency, a classification method of sports video clips based on MobileNetV3 is proposed to save user time. Experiments evaluate the effectiveness of effective segment extraction. Among the extracted segments, the effective proportion is 97.0%, indicating that the effective segment extraction results are good, and it can lay the foundation for the construction of the subsequent badminton action metadata video dataset.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1131-1144
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• 2004

In this paper, we investigate a problem with an e-learning system for e-business environments and introduce the solving method of the problem. To be more accurate, existing Web-hosted and ASP (Application Service Provider)-oriented service model is difficult to cooperate and integrate among the different kinds of systems. So we have produced sharable and reusable learning object, they have extracted a principle from pedagogical designs for units of reuse. We call LIO (Learning Item Object). This modeling makes use of a constructing for XML Web Services. So to speak, units of reuse from pedagogical designs are test tutorial, resource, case example, simulation, problem, test, discovery and discussion and then map introduction, fact, try, quiz, test, link-more, tell-more LIO learning object. These typed LIOs are stored in metadata along with the information for a content location. Each one of LIOs is designed with components and exposed in an interface for XML Web services. These services are module applications, which are used a standard SOAP (Simple Object Access Protocol) and locate any computer over Internet and publish, find and bind to services. This guarantees the interoperation and integration of the different kinds of systems. As a result, the problem of e-learning systems for e-business environments was resolved and then the power of understanding about learning objects based on pedagogical design was increased for learner and instruction designers. And organizations of education hope for particular decreased costs in constructing e-learning systems.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.378-384
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• 2023

In this study, we explore social awareness, interest, and acceptance of generative AI, including chatGPT, which has revolutionized web search, 30 years after web search was released. For this purpose, we performed a machine learning-based topic modeling analysis based on Korean news big data collected from November 30, 2022, when chatGPT was released, to August 31, 2023. As a result of our research, we have identified seven topics related to chatGPT and generative AI; (1)growth of the high-performance hardware market, (2)service contents using generative AI, (3)technology development competition, (4)human resource development, (5)instructions for use, (6)revitalizing the domestic ecosystem, (7)expectations and concerns. We also explored monthly frequency changes in topics to explore social interest related to chatGPT and Generative AI. Based on our exploration results, we discussed the high social interest and issues regarding generative AI. We expect that the results of this study can be used as a precursor to research that analyzes and predicts the diffusion of innovation in generative AI.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.23-30
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• 2024

In this paper, we propose a deep learning-based personalized senior care service application. The proposed application uses Speech to Text technology to convert the user's speech into text and uses it as input to Autogen, an interactive multi-agent large-scale language model developed by Microsoft, for user convenience. Autogen uses data from previous conversations between the senior and ChatBot to understand the other user's intent and respond to the response, and then uses a back-end agent to create a wish list, a shared calendar, and a greeting message with the other user's voice through a deep learning model for voice cloning. Additionally, the application can perform home IoT services with SKT's AI speaker (NUGU). The proposed application is expected to contribute to future AI-based senior care technology.

• Journal of Industrial Technology
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• v.44 no.1
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• pp.17-23
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• 2024

K-means is a popular and efficient data clustering method which is one of the most important technique in data mining. K-means is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. Therefore, we need a robust K-means (RK-means) not only to reduce this possibility but also to increase the probability to search the global optimal clustering solution. The objective of this paper is to propose RK-means with best initial solution from good solutions with good central data for each cluster. The central data of each cluster is selected based on Roulette wheel probabilistic selection using sum of relative distance rate of each data. They have a problem in high density data because they deterministically select the central data for just one initial solution of K-medoid. Our proposed initial solution is the good starting point to find the robust solution by K-means with reducing the possibility being stuck in local optimal solutions. The performance of proposed RK-means data clustering is validated using machine learning repository datasets (Iris, Wine, Glass, Vowel, Cloud) comparing to original K-means by experiment and analysis. Our simulation shows that RK-means using probabilistically relative distance rate are better than K-means with random initialization. The minimum squared distance by RK-means with smaller deviation is lower than that by K-means with higher deviation. RK-means is competitive comparing to data clustering methods based on simulated annealing (SA) and hybrid K-means with SA (KSA & KSAK).

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.147-156
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• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.

• International Area Studies Review
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• v.14 no.3
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• pp.388-419
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• 2010

The aim of the study is to create a theoretical model and hypotheses on competitive advantages of exporting SMEs. For this we have proposed an integrated model in which learning competences and dynamic capabilities should have an influence on competitive advantages of the SMEs. This study have examined the influence of integrating and reconfigurating capability respectively. As a result, the learning competences had positive influences in dynamic capabilities and to the cost and service competitive advantage. To integrating capabilities had positive influences in competitive advantage. Besides, dynamic capabilities playing significant intermediate role only for the cost advantage through the analysis of intermediate effects of learning competence to the dynamic capabilities.

• Journal of Family Resource Management and Policy Review
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• v.16 no.1
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• pp.21-39
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• 2012

The purpose of this study is to propose the direction of environmental education for early childhood children based on the environment-friendly life style and to improve the possibility of application of it at home and kindergarten. This study reviewed reflectively the early studies on the concepts of ecocentrism, the emerging process of it, the importance of environmental education for early childhood children based on the ecocentrism, and the practice of these kinds of education at home and kindergarten. The main concepts connected to the environment-friendly life style based on ecocentrism, that is, 'preservation of nature', 'interdepentence', 'wholeness', 'equilibrium' are the foundations of environmental education for early childhood children. When these kinds of concepts are considered, the aims of environmental education for early childhood children should be focused on the life style that attaches great importance to the symbiosis of human being and nature. The educational contents and methods in harmony with ecocentrism are as follows: The educational methods should be connected to the education based on ordinariness, the learning through adults' model, the family-community-centered activities, and ways of thinking of the unity of knowledge and conduct. And educational contents should include all of the life styles in clothes, food, and shelter. And the educational methods also should be connected to the education through joint working of children and teacher, play-centered education, activities considering ages and individual variations, and education connected home. And educational contents should include many different kinds of activities of experiencing nature outside home and kindergarten.

• Journal of IKEEE
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• v.27 no.3
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• pp.213-219
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• 2023

According to statistics from the National Police Agency, smishing crimes using texts or messengers have increased dramatically since COVID-19. In addition, most of the cases of impersonation of public institutions reported to agency were related to vaccination and reward, and many methods were used to trick people into clicking on fake URLs (Uniform Resource Locators). When detecting them, URL-based detection methods cannot detect them properly if the information of the URL is hidden, and content-based detection methods are slow and use a lot of resources. In this paper, we propose a system for URL-based detection using transformer for regular URLs and content-based detection using XGBoost for shortened URLs through the process of determining shortened URLs using GRU(Gated Recurrent Units). The F1-Score of the proposed detection system was 94.86, and its average processing time was 5.4 seconds.

• Journal of Korean Society on Water Environment
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• v.35 no.5
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• pp.425-431
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• 2019

Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.