• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.427-436
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• 2023

Je Baek-seok, who is well versed in poetry, calligraphy, painting, and sculpture, has established himself as the most outstanding painter and pavilion in the history of modern and contemporary Chinese art. During the Ming and Qing Dynasties, the art of the pavilion was developed greatly during the enlightenment period, with the emergence of many masters of the pavilion, including Jeonggyeong, Hwanghwangseokyeo, Oyangji, Jo Ji-gyeom, Hwang Mok-bo, and Oh Chang-seok. Je Baek-seok formed an original ritual under this social background. Je Baek-seok's tactics were formed by imitating works from the Hanwi period, and he harmonized Jin Kwon, Sopan, and Janggunin while using the penmanship of the Cheonbal Shinchambi based on the "Sasam Gongsanbi." In addition, by boldly using the Danipdo method, it is possible to use the human face as much as possible while fully exhibiting the artistry of calligraphy and adding to the atmosphere of gold stone. This paper mainly analyzed and reviewed the process of Je Baek-seok's transcription transformation and humanities practice from two aspects. First, it is planned to summarize the process of Je Baek-seok's transformation into a Jeonseo. Second, Je Baek-seok's humanities practice was analyzed. This paper will further understand Je Baek-seok's humanistic ideas and practical search by clarifying the originality of Je Baek-seok's engraving art with examples of Je Baek-seok's works, and it is believed that this will provide future scholars with learning paths and rich experiences.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.1-21
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• 2023

This study specifically reviewed the performance of the ranking schemes as an efficient feature selection method for text classification. Until now, feature ranking schemes are mostly based on document frequency, and relatively few cases have used the term frequency. Therefore, the performance of single ranking metrics using term frequency and document frequency individually was examined as a feature selection method for text classification, and then the performance of combination ranking schemes using both was reviewed. Specifically, a classification experiment was conducted in an environment using two data sets (Reuters-21578, 20NG) and five classifiers (SVM, NB, ROC, TRA, RNN), and to secure the reliability of the results, 5-Fold cross-validation and t-test were applied. As a result, as a single ranking scheme, the document frequency-based single ranking metric (chi) showed good performance overall. In addition, it was found that there was no significant difference between the highest-performance single ranking and the combination ranking schemes. Therefore, in an environment where sufficient learning documents can be secured in text classification, it is more efficient to use a single ranking metric (chi) based on document frequency as a feature selection method.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.17-33
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• 2023

This study examined inservice elementary teachers' thoughts on the development of educational apps by preservice elementary teachers and implications for TPACK education for preservice elementary teachers. A case study was conducted in which preservice elementary teachers developed a science education app, and the three teachers were surveyed for their thoughts regarding this. The results regarding the characteristics of the developed app by preservice teachers were as follows. First, "inquiry" had the highest value among educational goals intended by the preservice teachers. In addition, the scores for tool-type apps and apps in which interaction between learners and instructors occurs were relatively high. Second, most of the preservice teachers developed apps to meet curriculum goals, but their apps showed low-level characteristics in terms of the constructive and cooperative dimensions. The results of the analysis of the thinking of elementary school teachers regarding the education development apps are as follows. First, elementary school teachers assigned the lowest scores to the effectiveness of the apps, and to this problem, the achievement standard with respect to the curriculum and the evaluation and modification activities fir the apps were proposed. Second, the teachers indicated that it would be appropriate to provide the experience of making apps to directly improve the TPACK of preservice teachers. Third, the respondents thought that preservice teachers should develop block coding literacy to create apps using App Inventor. Fourth, the teachers considered it necessary to emphasize simulated instructions, as well as the experience of collecting and handling data through apps to improve preservice teachers' TPACK app development for educational use.

• Korean Journal of Social Welfare
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• v.69 no.4
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• pp.177-202
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• 2017

We usually expect that children in residential care are not able to have excellent academic achievement, even though their school achievement in adolescence is crucial as a part of whole lifespan development. The purpose of this study is to carefully understand characteristics and experiences of only a few academically talented children in residential care and to find out the practical suggestion to support the academic performance of children in residential care. For this purpose, we had interviewed eight children in depth and analyzed the data using a qualitative case study method. As a result, we found a total of 21 subcategories and 5 categories. The categories included that 'always being faithful despite being not fast', 'believing myself when I face limitations', 'conflict in high support and high expectation', 'sometimes refusing to support on me, but I am leaning on my mind', 'relieving anxiety by studying'. In conclusion, we found that the central theme of 'running to change prejudice into hope' were found through the cases with excellent academic achievement. Based on the results, we suggested the guidelines to consider when developing and providing the academic support services for children in residential care.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.435-452
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• 2023

This study experimented with automatic classification of subject headings using BERT-based transfer learning model, and analyzed its performance. This study analyzed the classification performance according to the main class of KDC classification and the category type of subject headings. Six datasets were constructed from Korean national bibliographies based on the frequency of the assignments of subject headings, and titles were used as classification features. As a result, classification performance showed values of 0.6059 and 0.5626 on the micro F1 and macro F1 score, respectively, in the dataset (1,539,076 records) containing 3,506 subject headings. In addition, classification performance by the main class of KDC classification showed good performance in the class General works, Natural science, Technology and Language, and low performance in Religion and Arts. As for the performance by the category type of the subject headings, the categories of plant, legal name and product name showed high performance, whereas national treasure/treasure category showed low performance. In a large dataset, the ratio of subject headings that cannot be assigned increases, resulting in a decrease in final performance, and improvement is needed to increase classification performance for low-frequency subject headings.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• 한국노년학
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• v.25 no.2
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• pp.171-193
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• 2005

Nowadays, the employment policies for older people is requested to become the new form in the change of information, globalization, and aging. It is discussed, simultaneously, about an age integrated society as the full time jobs' continuation and social jobs after the full time jobs. The discussion of jobs' continuation include from institutional system to age integrated society. Social jobs include from public labor to social wages. jobs' continuation passes over stabilization, regarding it as ideal society. social jobs are interpreted it as residual welfare, excluding the meaning of social solidarity. In fact, most of the debates is overwhelmed by the logic of economy. And so they pass over the quality of life of individuals. Therefore, this study critics the employment policies for older people in the present situation and states a direction improving the quality of life older people.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.53-66
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• 2023

Recently, there has been a significant interest in the development of autonomous driving simulation environment based on digital twin. In the development of such digital twin-based simulation environment, many researches has been conducted not only performance and functionality validation of autonomous driving, but also generation of virtual training data for deep learning. However, such digital twin-based autonomous driving simulation system has the problem of requiring a significant amount of time and cost for the system development and the data construction. Therefore, in this research, we aim to propose a method for rapidly designing and implementing a digital twin-based autonomous driving simulation system, using only the existing 3D models and high-definition map. Specifically, we propose a method for integrating 3D model of FBX and NGII HD Map for the Busan EDC area into CARLA, and a method for adding and modifying CARLA functions. The results of this research show that it is possible to rapidly design and implement the simulation system at a low cost by using the existing 3D models and NGII HD map. Also, the results show that our system can support various functions such as simulation scenario configuration, user-defined driving, and real-time simulation of traffic light states. We expect that usability of the system will be significantly improved when it is applied to broader geographical area in the future.