• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.280-288
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• 2022

This study examined the diagnostics of abnormalities and faults of equipment, whose rotational speed changes even during regular operation. The purpose of this study was to suggest a procedure that can properly apply machine learning to the time series data, comprising non-stationary characteristics as the rotational speed changes. Anomaly and fault diagnosis was performed using machine learning: k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Random Forest. To compare the diagnostic accuracy, an autoencoder was used for anomaly detection and a convolution based Conv1D was additionally used for fault diagnosis. Feature vectors comprising statistical and frequency attributes were extracted, and normalization & dimensional reduction were applied to the extracted feature vectors. Changes in the diagnostic accuracy of machine learning according to feature selection, normalization, and dimensional reduction are explained. The hyperparameter optimization process and the layered structure are also described for each algorithm. Finally, results show that machine learning can accurately diagnose the failure of a variable-rotation machine under the appropriate feature treatment, although the convolution algorithms have been widely applied to the considered problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.121-127
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• 2022

Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the useer along with the mirror function. This paper went beyond the form of dealing with smart mirrors only stand alone device the provide information to users, and constructed a network in which smart mirrors are connected, and proposed and implemented a CoMirror system that allows users to talk and share information with other smart mirror users. The CoMirror system has a structure in which several CoMirror clients are connected on one CoMirror server. The CoMirror client consists of Raspberry Pi, a mirror film, a touch pad, a display device, an web camera, etc. The server has functions such as face learning and recognition, user management, a relay role for exchanging messages between clients, and setting up for video call. Users can communicate with other CoMirror users via the server, such as text, image, and audio messages, as well as 1:1 video call.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.360-366
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• 2022

This paper presents a AI model structure for restoring Korean traditional palace photographs, which remain only black-and-white photographs, to color photographs using Pix2Pix, one of the adversarial generative neural network techniques. Pix2Pix consists of a combination of a synthetic image generator model and a discriminator model that determines whether a synthetic image is real or fake. This paper deals with an artificial intelligence model by adjusting a receptive field of the discriminator, and analyzes the results by considering the characteristics of the ancient palace photograph. The receptive field of Pix2Pix, which is used to restore black-and-white photographs, was commonly used in a fixed size, but a fixed size of receptive field is not suitable for a photograph which consisting with various change in an image. This paper observed the result of changing the size of the existing fixed a receptive field to identify the proper size of the discriminator that could reflect the characteristics of ancient palaces. In this experiment, the receptive field of the discriminator was adjusted based on the prepared ancient palace photos. This paper measure a loss of the model according to the change in a receptive field of the discriminator and check the results of restored photos using a well trained AI model from experiments.

• Journal of Family Resource Management and Policy Review
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• v.26 no.2
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• pp.53-70
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• 2022

This study aimed to develop a scale to measure the family strength of single-parent families. We analyzed the everyday life and demands of single-parent families using the theory of family strength to draw 78 items that encompass family basis, relationships, roles, social networks and family culture. Using a sample of 286 single-parent families through an online survey platform, we examined the factor structure of the items and selected 48 items based on the results of the factor analysis. Reliability, criterion and construct validity were also examined. The final scale comprised of five domains ; basis, parents' role, work-life balance, social network, lifestyle and household management. This scale can be used as an assessment measure of the family strength of single-parent families for consulting, case management and suggesting various programs in the field. This merit will help enhance the quality of programing for single-parent families at the Healthy Family Support Center and the development of family strength scales for various types of families.

• Clean Technology
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• v.28 no.4
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• pp.278-284
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• 2022

This study presents an excellent planar heater based on low-dimensional composites. By optimizing the ratio of 1D carbon nanotubes (CNT) and 2D MXene (Ti₃C₂T_X), it is possible to create a planar heater that has superior electrical conductivity and high heat generation characteristics. Low-dimensional composites were prepared by mixing CNT paste and MXene solution with eco-friendly waterborne polyurethane (WPU). In order to find the optimal mixing ratio for the MXene-CNT-WPU composites, samples with MXene to CNT weight ratios of 3:1, 1:1, 1:3, 1:7, and 1:14 were investigated. In addition to these different weight ratios, 5 wt% WPU was equally applied to each sample. It was confirmed that the higher the weight ratio of CNT, the lower the sheet resistance and the higher the heating temperature. In particular, when the MXene-CNT-WPU planar heater was fabricated by mixing MXene and CNT at a weight ratio of 1:7 and 1:14, the heating temperature was higher than the heating temperature of a CNT-WPU planar heater. These characteristics are due to the optimized mixture of the 1D materials (CNT) and the 2D materials (MXene) causing the formation of a flat surface and a dense network structure. The low-dimensional composites manufactured with the optimized mixing ratios found in this study are expected to be applied in flexible electronic devices.

• Journal of The Korean Association For Science Education
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• v.42 no.2
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• pp.265-275
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• 2022

In this study, focusing on science education in the future society, we explored students' key competencies to be cultivated for the future society, and the role and PCK expertise necessary for science teachers, who are the main agents of competency-based education to nurture these key competencies. A survey conducted among earth science teachers across the country results in 105 valid responses being obtained. The research results are discussed in terms of students' key competencies to be nurtured for the future society, the role and the expertise of science teachers required for competency-based education, and the structural relationship between the teacher role and teacher expertise. We also conducted network analysis to examine the relationship between student competency and teacher expertise, and the structure between the teacher's role and expertise. Main results include that communication and collaboration skills are the most important for students in the future society as core competencies. For science teachers, providing opportunities for collaboration-oriented activities are deemed as the most important. Regarding the structural relationship between the teacher's role and the teacher's expertise, there is a clear relationship with roles such as providing opportunities for collaboration-oriented activities and utilizing various materials and contents in relation to the expertise related to the science teaching practice. Based on the results, ways to promote student's agency based on raising teachers' awareness of the student's competencies, the inter-relatedness of the teacher's role and the teacher's expertise, and the totality of teachers' expertise were suggested.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.224-236
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• 2022

This study tests the hypotheses that city slogan reduces the retrieval of city memory unrelated to the slogan from the long term memory and that some variables moderate this effect, using the experimental method. The theoretical basis for the hypotheses is from the structure of the long term memory and the principle of memory retrieval discussed in ANM(Associative Network Model). For the test of hypotheses, the study adopted 4 experimental groups (2(slogan relevance: high or low) * 2(slogan concreteness: high or low)) and 1 control group. Each experimental group was exposed to one slogan corresponding to its condition while the control group was not. Then, the recall score was compared among experimental and control groups. One hundred and seventy-four undergraduate students belonging to the college of the authors participated in the study. The sample group was between 18 and 27 years of age, with an average of 22.4 years, and 54 percent comprised males. Results showed that city slogan had a negative effect on the retrieval of city memory unrelated to the slogan in most experimental conditions. This effect was more evident when the slogan had high relevance or high concreteness. But the main effect did not appear when the slogan had low relevance and low concreteness.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.903-911
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• 2022

Groundwater, one of the resources for supplying water, fluctuates in water level due to various natural factors. Recently, research has been conducted to predict fluctuations in groundwater levels using Artificial Neural Network (ANN). Previously, among operators in ANN, Gradient Descent (GD)-based Optimizers were used as Optimizer that affect learning. GD-based Optimizers have disadvantages of initial correlation dependence and absence of solution comparison and storage structure. This study developed Gradient Descent combined with Harmony Search (GDHS), a new Optimizer that combined GD and Harmony Search (HS) to improve the shortcomings of GD-based Optimizers. To evaluate the performance of GDHS, groundwater level at Icheon Yullhyeon observation station were learned and predicted using Multi Layer Perceptron (MLP). Mean Squared Error (MSE) and Mean Absolute Error (MAE) were used to compare the performance of MLP using GD and GDHS. Comparing the learning results, GDHS had lower maximum, minimum, average and Standard Deviation (SD) of MSE than GD. Comparing the prediction results, GDHS was evaluated to have a lower error in all of the evaluation index than GD.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.337-342
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• 2021

The purpose of this study is to analyze the environment and strategic behaviors of cultural contents companies with a focus on Iconix, and to derive strategic recommendations for Iconix to pursue in order to create a sustainable competitive advantage. As a result of the analysis, Iconix is a vertically integrated development-business system from content planning to business in line with their mission to develop into an all-weather entertainment content provider that can confidently compete with the major players in the US and Europe that are already leading the global market. It is building a strong global business network covering both domestic and overseas markets in stages, taking a high-level global strategy. However, depending on Pororo's success or due to various problems within the organizational structure, it is facing limitations. Therefore, if the various strategic suggestions presented in this study are implemented based on the One Source Multi Channel/Multi Use strategy that can maximize the added value of contents through the participation and business linkage of leading companies in each sector of the entertainment industry, the total entertainment will be stabilized. It will establish itself as a leader in the contents industry.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.119-131
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• 2021

With the boom of platform businesses, digital transformation has become the most important topic for businesses. Digital transformation has now become the most urgent strategy for survival, from a strategy considered as an option to choose in the past. Many companies are desperately seeking the ways to be digitally transformed. Even though there have been many studies on digital transformation, most of them are on strategic and conceptual model levels based on simple case analyses. In this study, we analyze the benefits of data integration and network effects from it, based on platform business model at the core of digital transformation. The change based on platform can be categorized into the internal one for the integration of data and better decision making, and the external one for the expansion of the businesses and better prediction of consumer behaviors through the integration of external data sets by the platform business model based enterprises. While the progress for digital transformation is not mature enough yet, financial industry is one of the most promising industries for the change and realization of the aim of it with its relatively much more advanced IT infrastructure. Many companies are making various efforts for the integration of external data, and if the good results can be accomplished, financial industry will contribute to the advancement of digital transformation in other industries as well. For "My Data" project by Korean government, we suggest the data structure and transaction of data (of Korea) should be advanced and established more quickly.