• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.58-67
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• 2024

In the era of the fourth industrial revolution, data plays a vital role in enhancing the productivity of industries. To advance digitalization in the construction industry, which suffers from a lack of available data, this study proposes a model that classifies construction site photos by work types. Unlike traditional image classification models that solely rely on visual data, the model in this study includes semantic analysis of construction work types. This is achieved by extracting the significance of relationships between objects and work types from the standard construction specification. These relationships are then used to enhance the classification process by correlating them with objects detected in photos. This model improves the interpretability and reliability of classification results, offering convenience to field operators in photo categorization tasks. Additionally, the model's practical utility has been validated through integration into a classification program. As a result, this study is expected to contribute to the digitalization of the construction industry.

• Journal of Digital Policy
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• v.3 no.1
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• pp.11-20
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• 2024

The intelligent information society is expected to drastically change our lives. The purpose of this content is to derive tasks in the field of media education for the elderly for the realization of digital inclusion in an intelligent information society. To this end, the vision, goals, strategies, and tasks of the intelligent information society were examined through the 6th National Informatization Basic Plan(2018~2022) and the 2022 Education Informatization White Paper(2022). In addition, the current status of the digital gap among the elderly classified as vulnerable groups was identified through the results of the 2022 Digital Information Gap Survey. In order to ease the digital information gap between the elderly in the intelligent information society, it is believed that the development of intelligent media education services using intelligent information technology, provision of media education services for the elderly through learning online service channels, and support for digital intelligent media education for the elderly are necessary.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.33-39
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• 2024

Inspecting cracks to determine a structure's condition is crucial for accurate safety diagnosis. However, visual crack inspection methods can be subjective and are dependent on field conditions, thereby resulting in low reliability. To address this issue, this study automates the detection of concrete cracks in image data using ResNet, FPN, and the Mask R-CNN components as the backbone, neck, and head of a convolutional neural network. The performance of the proposed model is analyzed using the intersection over the union (IoU). The experimental dataset contained 1,203 images divided into training (70%), validation (20%), and testing (10%) sets. The model achieved an IoU value of 95.83% for testing, and there were no cases where the crack was not detected. These findings demonstrate that the proposed model realized highly accurate detection of concrete cracks in image data.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.17-22
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• 2024

Recently, as the ICT field has been used in various environments, it has become possible to analyze pests by crops, use robots when harvesting crops, and predict by big data by utilizing ICT technologies in a sustainable agricultural environment. However, in a sustainable agricultural environment, efforts to solve resource depletion, agricultural population decline, poverty increase, and environmental destruction are constantly being demanded. This paper proposes an artificial intelligence-based big data processing analysis method to reduce the production cost and increase the efficiency of crops based on a sustainable agricultural environment. The proposed technique strengthens the security and reliability of data by processing big data of crops combined with AI, and enables better decision-making and business value extraction. It can lead to innovative changes in various industries and fields and promote the development of data-oriented business models. During the experiment, the proposed technique gave an accurate answer to only a small amount of data, and at a farm site where it is difficult to tag the correct answer one by one, the performance similar to that of learning with a large amount of correct answer data (with an error rate within 0.05) was found.

• Journal of the Korean Society of Earth Science Education
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• v.17 no.1
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• pp.1-19
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• 2024

This study is a design and development study that developed instructional strategies based on distributed cognitive theory for science classes using technology according to procedures that ensured reliability and validity. To develop instructional strategies, development study and validation study were conducted according to design and development research methodology procedures. In the development study, an initial instructional strategy was developed through prior literature review and prior expert review. In the validation study, the instructional strategy was validated using internal validation (expert validation, usability evaluation) and external validation (field application evaluation) methods, and the final instructional strategy was developed. The final instructional strategy consisted of 3 instructional principles, 9 instructional strategies, and 38 detailed guidelines. Through this study, the researcher suggested the suitability of instructional strategies for science classes using technology, the usefulness of blocks and teaching and learning processes, the possibility of using technology as a cognitive tool, the need for teachers' efforts to cultivate teaching capabilities using technology, and the needs lesson plan that takes into account conditions affecting the application of instructional strategies.

• Journal of Technologic Dentistry
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• v.46 no.2
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• pp.36-41
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• 2024

Purpose: This study aimed to generate virtual mandibular left first molar teeth using deep convolutional generative adversarial networks (DCGANs) and analyze their matching accuracy with actual tooth morphology to propose a new paradigm for using medical data. Methods: Occlusal surface images of the mandibular left first molar scanned using a dental model scanner were analyzed using DCGANs. Overall, 100 training sets comprising 50 original and 50 background-removed images were created, thus generating 1,000 virtual teeth. These virtual teeth were classified based on the number of cusps and occlusal surface ratio, and subsequently, were analyzed for consistency by expert dental technicians over three rounds of examination. Statistical analysis was conducted using IBM SPSS Statistics ver. 23.0 (IBM), including intraclass correlation coefficient for intrarater reliability, one-way ANOVA, and Tukey's post-hoc analysis. Results: Virtual mandibular left first molars exhibited high consistency in the occlusal surface ratio but varied in other criteria. Moreover, consistency was the highest in the occlusal buccal lingual criteria at 91.9%, whereas discrepancies were observed most in the occusal buccal cusp criteria at 85.5%. Significant differences were observed among all groups (p<0.05). Conclusion: Based on the classification of the virtually generated left mandibular first molar according to several criteria, DCGANs can generate virtual data highly similar to real data. Thus, subsequent research in the dental field, including the development of improved neural network structures, is necessary.

• Journal of The Korean Association For Science Education
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• v.32 no.1
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• pp.15-29
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• 2012

The purpose of this study was to investigate the educational factors on career choice of science-gifted students to science and technology bound universities and the difference of perception in regards to group factors. In addition, this study aimed to examine the effects of science-gifted education and critical events in relation to career choice to science and technology bound universities. For the study, 104 university freshmen, 75 males and 29 females, were sampled from UNIST (Ulsan National Institute of Science and Technology), that many science high school graduates entered this year. The survey was conducted with questionnaires to do with the perceptions concerning career choice and educational factors that cause them to choose such career directions. The educational factors on career choice to science and technology bound universities were classified as 3 main categories such as educational environment factor (teaching-learning factor), human factor, attitude towards science factor and the subcategories within each category. The research findings are as follows: First, the factors were closely connected with each other and 'the project centered classes' were highly interrelated with other educational environment factors such as 'the experiment activity and environment for the activity' and 'influence of teachers (professors).' Second, the female students and graduates of the science high school were more positively influenced by the educational environment and human factors on their decision for career than male students and graduates of the general high school. Third, this research found that historical scientific knowledge, perception of scientists' social status and job applications in the science field gave less influence rather than other factors on their decision for career. As a result of examining critical events for science-gifted education in relation to career choice to science and technology bound universities, numerous students mentioned that the extracurricular science activities such as science camps and field trips gave significant effects on students' career choices to science and engineering fields.

• Journal of Science Education
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• v.34 no.2
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• pp.405-420
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• 2010

The purpose of this study was to contrive the specific teaching plans based on the frame of 2007 revised science curriculum for applying open-inquiry lesson in real education situation and to research the effects of open-inquiry lesson on the student's science-related attitude, science process skill, and to investigate instructing teachers' cognition about open-inquiry. For this study, two fifth grade classes were chosen, one class was the experimental group, who were taught by open-inquiry based lesson, and another was the comparative group, who were taught by traditional method based lesson. The findings of this study were as follows: After open-inquiry lesson, the experimental group students came to enjoy open-inquiry learning and had the positive thought about it. After open-inquiry lesson, the experimental group marked higher mean score than the comparative group in science-related attitude's field but didn't showed the meaningful difference. On the other hand, in science process skill's field, the experimental group showed the significant higher improvement than the comparative one, especially in the subordinate area of basic science process skill. Finally, teachers who instructed students open-inquiry lesson thought open-inquiry lesson is the self-directed problem solving learning which raise the student's science process skill and interest. And the teachers thought the obstacles to instruct open-inquiry lesson are the lack of the student's cognition about open-inquiry and the insufficient circumstance for open-inquiry lesson. Therefore the teachers argued that the prerequisite for settling open-inquiry lesson successfully is to develope open-inquiry lesson curricula and teaching materials.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.