• Korean Journal of Family Social Work
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• no.61
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• pp.93-136
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• 2018

The purpose of this study is to find specific practice methods of single parents self-help groups in community welfare centers. A participatory action research was conducted to achieve the purpose. Six social workers and three researchers participated in the study who shared the problem of lack of specific practice methods even though a self-help group was useful for self-reliance and empowerment of low-income single-parents. Various activities such as reading articles, analysis of each self-help group, case studies, and learning facilitation methods were conducted during 10 meetings. At the same time, peer supervision proceeded at each meeting. The progress of each group was shared, the application of practice methods and plans were discussed, and applying discussed methods to group practice and reviewing the process and outcomes of the practice were repeated in the peer supervison. As a result, the following positive changes appeared: First, the goals and vision of each group became clearer. Second, initiative of the members was promoted. Third, intimacy, mutual cooperation, the attatchment to the group were strengthened. A qualitative analysis was also conducted on the content discussed. As a result, 17 practice methods were derived in four themes such as initiative/ empowerment, cohesion, leadership, and destandardization. Practice issues concerning single parents self-help groups in community welfare centers were discussed based on the results.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.193-205
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• 2021

The AI speaker market is growing steadily. However, the satisfaction of actual users is only 42%. Therefore, in this paper, we collected reviews on Amazon Echo Dot 3rd and 4th generation models to analyze what hinders the user experience through the topic changes and emotional changes of each generation of AI speakers. By using topic modeling analysis techniques, we found changes in topics and topics that make up reviews for each generation, and examined how user sentiment on topics changed according to generation through deep learning-based sentiment analysis. As a result of topic modeling, five topics were derived for each generation. In the case of the 3rd generation, the topic representing general features of the speaker acted as a positive factor for the product, while user convenience features acted as negative factor. Conversely, in the 4^th generation, general features were negatively, and convenience features were positively derived. This analysis is significant in that it can present analysis results that take into account not only lexical features but also contextual features of the entire sentence in terms of methodology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.65-70
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• 2019

The purpose of this study is to understand the college students' needs for software curriculum which based on surveys from educational satisfaction of the software lecture evaluation, as well as to find out the improvement plan by applying the text content analysis method. The research method used the text content analysis program to calculate the frequency of words occurrence, key words selection, co-occurrence frequency of key words, and analyzed the text center and network analysis by using the network analysis program. As a result of this research, the decent points of the software education network are mentioned with 'lecturer' is the most frequently occurrence after then with 'kindness', 'student', 'explanation', 'coding'. The network analysis of the shortage points has been the most mention of 'lecture', 'wish to', 'student', 'lecturer', 'assignment', 'coding', 'difficult', and 'announcement' which are mentioned together. The comprehensive network analysis of both good and shortage points has compared among key words, we can figure out difference among the key words: for example, 'group activity or task', 'assignment', 'difficulty on level of lecture', and 'thinking about lecturer'. Also, from this difference, we can provide that the lack of proper role of individual staff at group activities, difficult and excessive tasks, awareness of the difficulty and necessity of software education, lack of instructor's teaching method and feedback. Therefore, it is necessary to examine not only how the grouping of software education (activities) and giving assignments (or tasks), but also how carried out group activities and tasks and monitored about the contents of lectures, teaching methods, the ratio of practice and design thinking.

• Journal of Technology Innovation
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• v.27 no.1
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• pp.45-77
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• 2019

The balance between exploration for new possibility and exploitation for existing certainty is an important issue in strategy, innovation, R&D as well as organization learning. Among the convergence trends of technologies, many firms seek to have the wider technological knowledge assets and the deeper technology capabilities for the sustainable competitive advantage at the same time. While firms plan technology portfolio strategies, they should consider the attribute of the technology. Nanotechnology, a cutting-edge technology, is a general purpose technology, unlike conventional product-oriented technologies. This empirical study was focused on how multi-national firms' exploration and exploitation strategies for nanotechnology affect their innovative and financial performance. It uses multiple regression analysis on panel data. This result shows that the more diversified and specialized nanotechnology as platform technology is positively related to their innovative and financial performance, unlike the research results for product-oriented technologies. In addition, exploratory innovation is more effective to firm performance than exploitation. This implies how global firms can manage effectively platform technology strategies under the constraints of resources.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.177-186
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• 2020

Entrepreneurship education has been emphasized worldwide and the number of universities that open related subjects have been increasing. K University, located in Gyeonggi-do, was selected as one of the leading universities in entrepreneurship in 2014, and has continued to grow quantitatively by providing support and education related to entrepreneurship on and off campus. In addition, major issues in entrepreneurship education were derived by conducting written or face-to-face interviews and advisory meetings with instructors, field experts, and education demanders for environmental analysis. Based on this, three major tracks(venture start-up, entrepreneurship convergence, and social venture activation) were derived, and major competency and learning goals for each track were presented. On the other hand, in order for this study to be more effectively accepted, it is necessary to present the objectives of each track, the capabilities pursued, and the courses that help students' progress. Therefore, in the future research, it is necessary to design and present the goals for each track, the curriculum road map, and the detailed curriculum of the convergence major, and at the same time, research to match the appropriate teaching method for each newly opened subject will be required to increase educational effectiveness.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.229-242
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• 2021

The purpose of this study is an empirical case study that focuses on bring about changes in clients through narrative therapy using scaffolding. Through this, the purpose was to find the preferred values and hopes of the future among the stories that the client's has lived in. As the research method, we proceed through unstructured interview and loose structures in qualitative research. On this premise, the counselor did not diagnose or explain the 'decentralized but influential' attitudes and problem. And there was no order in the conversation, and I didn't decide in advance how to react to it before the client made any expressions. This study has the following significance on a practical and academic level: First of all, counseling through scaffolding further enrich the curiosity, temperament, and wishes of the client. Second, the scaffolding provides a concrete picture of the relationship between a counselor and a client in narrative therapy. Third, the scaffolding made in therapeutic dialogue presents a 'learning tasks'. Fourth, counseling through scaffolding has an active meaning that it can develop the higher mental function of clients in charge. Finally, we presented an application of narrative therapy in Vygotsky's theory through analysis of empirical cases. Based on this information, this study did not simply intend to position the client as a research object in narrative therapy. It is meaningful that they have identified the factors necessary to become the subject of narrative therapy and the role of the counselor in the process. In addition, this study has implications in that it contributed to the expansion and substantialization of the research scope of narrative therapy in that it utilized the concept of scaffolding, which has not received much attention in the domestic research.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.793-810
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• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.200-207
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• 2020

The purpose of the establishment of Fab Lab is to promote the sustainable development of local communities around the world. To this end, The Fab foundation are preparing a resource-circulating society that maintains a city's self-sufficiency rate of 50% or more by 2054. In developed countries, Fab Lab is not only a manufacturing space for startup support, but an open innovation space for learning and creation. In addition, in emerging countries, Fab Lab is playing a role as a digital production center to create and share appropriate new technologies by reflecting the needs of local communities. India has 70 Fab Labs, the largest emerging country, ahead of Russia's 48. India's Fab Lab is conducting a collaboration project through regular meetings held every six months. The subject of this study, Fab Lab Vigyan Ashram, is defined as a place to transfer the concept of digital lab to alternative schools in rural India. In this study, we looked at a case in which an alternative school for an agricultural community called Vigyan Ashram, the modern version of the Gurukula system, successfully combined with the digital fabrication called Fab Lab to become a new citizen-led making community of the 4th Industrial Revolution. Based on this, we explored the development model of the Indian Fab Lab that fits the local situation.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.