• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• Journal of The Korean Association For Science Education
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• v.27 no.9
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• pp.818-831
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• 2007

Recognizing the importance of abductive inquiry in Earth science, some theoretical approaches that deploy abduction have been researched. And, it is necessary that the abductive inquiry in a geological field excursion as a vivid locale of Earth science inquiry should be researched. We developed a geological field trip based on the abductive learning model, and investigated students' abductive inference, thinking strategies used in those inferences, and the impact of a teacher's pedagogical intervention on students' abductive inference. Results showed that students, during the field excursion, could accomplish abductive inference about rock identification, process of different rock generation, joints generation in metamorpa?ic rocks, and terrains at the field trip area. They also used various thinking strategies in finding appropriate rules to construe the facts observed at outcrops. This means that it is significant for the enhancement of abductive reasoning skills that students experience such inquiries as scientists do. In addition, a teacher's pedagogical interventions didn't ensure the content of students' inference while they helped students perform abductive reasoning and guided their use of specific thinking strategies. Students had found reasoning rules to explain the 01: served facts from their wrong prior knowledge. Therefore, during a geological field excursion, teachers need to provide students with proper background knowledge and information in order that students can reason rues for persuasive abductive inference, and construe the geological features of the field trip area by the establishment of appropriate hypotheses.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.67-74
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• 2024

In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method's accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.

• Archives of design research
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• v.19 no.1 s.63
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• pp.15-26
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• 2006

As the interest and use of computer have been increased among elderly users according to the entry to the aging society, the issue of universal design for computer usability was brought forward. Especially, it is widely recognized that universal UI(User Interlace) design on MS windows is important. The objective of this study is to conceptualize Universal GUI design on MS windows which can be used more easily and intuitively by novice users such as elderly and housewives. Especially, the solution for Universal GUI design on MS windows was developed by reflecting elderly users' needs because elderly users is the group with more difficulties than other user groups in learning and using MS windows. First, elderly user's needs was collected by participant observation as a teaching assistant in computer dass for elderly people for 4 weeks. Secondly, the experimental test and in-depth interview was implemented to find difficulties factors and needs in addition to participant observation. Based on the findings, the new GUI design solution was suggested. The design solution consists of ideas in several categories such as setting default, simplification of function for easy conceptual model making, customization of function and working environment, and intuitive GUI in interaction process. The new MS windows GUI design can be accessed by novice mode when user login in window XP. This study has the significance in finding elderly users detailed needs through in-depth and long term participant observation. However, the usability of the suggested prototype needs to be verified to various user groups besides elderly users in the future.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.3
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• pp.157-180
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• 2012

The purposes of this study are to design and apply an experienced-based reading program using picture books for the struggling readers to improve their reading ability; and to analyze and verify how this program influences their self-esteem. The final objects of this study are 53 struggling readers who are 1-4th graders in 8 elementary schools. For this, the specific goals are set up as follows: First, an experience-based reading program using ADDIE teaching design model and Kolb's experience learning cycle are planned and developed to improve reading abilities and self-esteem of the struggling readers. Second, it also aimed to clarify how the experience-based reading program using picture books influence the struggling readers' self-esteem in affective ones. As a result, this experience-based reading program using picture books is effective on improving the struggling readers' self-esteem, generally. Although the degree of improvement is different from each of the subordinate factors, the overall scores of self-esteem are raised. This study suggests that an experience-based reading program using picture books is appropriate for improving the affective characteristics of the struggling readers. And it is also needed to produce a research manual to get the same test condition that prescribes the methods of pre-test and post-test.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.623-637
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• 2016

This study examined the importance of social capital in facilitating older adults' learning and adaptation of information technology as well as alleviating depressive symptoms. At two senior community centers in South Korea, 144 adults aged 60 and older were recruited to participate in 12 week-long technology classes to learn computers, smart phone, and internet skills. At the baseline interviews were conducted to assess their health status, depression, and online social relationships. Online and offline social capital (bonding vs. bridging) was assessed (Williams, 2006). Four-step Hierarchical Linear Regression analysis was conducted to examine the effects of online social relationship on depression. Findings suggested that depressive symptoms were associated with being widowed, being unemployed, and perceiving poor health status. Adding social capital variables in the final step, older adults who perceived less stressors, greater level of subjective health and high online bonding capitals had less depressive symptoms. Only online social bonding was significant in alleviating depression. This final model explained 48% of the variance. Computer/Internet training for older adults need to consider the significant role bonding social capital can play. The findings of this pilot study provided a preliminary base of knowledge about acceptable community-based interventions for older adults.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.113-122
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• 2018

The purpose of this study is to investigate the effects of the educational context variables on students' science achievement and interest in TIMSS 2015. TIMSS 2015 science data and questionnaire results were used to fit the Hierarchical Linear Model (HLM) in this study. According to the results, books at home, parents' level of education, and students' views on science lessons have significant influence on science achievement of above-high level 4th-grade students, and books at home on below-intermediate level 4th-grade students. Books at home, students' views on science lessons, and school composition by student economic background have significant influence on science achievement of above-high level 8th-grade students, and books at home and students' views on science lessons on science achievement of below-Intermediate level 8th-grade students. In all grade levels, books at home, and students' views on science lessons have significant influence on science achievement and interest. Discussed in the conclusion are ways to improve science teaching and learning including offering systematic reading programs for all students, reinforcement of student-participation in science classes, connecting science hands-on activities with science concepts for below-Intermediate level elementary students, and so on.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.99-110
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• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

• Smart Media Journal
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• v.5 no.2
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• pp.15-23
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• 2016

In this paper we propose the depth-poselets using body-part-poses and also propose the method to recognize the gesture. Since the gestures are composed of sequential poses, in order to recognize a gesture, it should emphasize to obtain the time series pose. Because of distortion and high degree of freedom, it is difficult to recognize pose correctly. So, in this paper we used partial pose for obtaining a feature of the pose correctly without full-body-pose. In this paper, we define the 16 gestures, a depth image using a learning image was generated based on the defined gestures. The depth poselets that were proposed in this paper consists of principal three-dimensional coordinates of the depth image and its depth image of the body part. In the training process after receiving the input defined gesture by using a depth camera in order to train the gesture, the depth poselets were generated by obtaining 3D joint coordinates. And part-gesture HMM were constructed using the depth poselets. In the testing process after receiving the input test image by using a depth camera in order to test, it extracts foreground and extracts the body part of the input image by comparing depth poselets. And we check part gestures for recognizing gesture by using result of applying HMM. We can recognize the gestures efficiently by using HMM, and the recognition rates could be confirmed about 89%.