• Journal of Digital Convergence
• /
• v.18 no.3
• /
• pp.99-110
• /
• 2020

This study deals with the relationship between entrepreneurship of corporate member and creativity at the organizational level by empirically analyzing the relationship between entrepreneurship, organizational learning orientation, individual creativity, and group creativity. In particular, the relationship between entrepreneurship and creativity focuses on analyzing the mediating effects of organizational learning orientation. Based on the literature research, the research model and hypothesis were established by explaining the relationship between entrepreneurship, individual and group creativity, and organizational learning orientation. 308 copies of the questionnaire were distributed and collected for manufacturing workers in Gyeongbuk, and empirical analysis was conducted through structural equations. As a result, it was confirmed that entrepreneurship has an influence on organizational learning orientation without directly affecting individual and group creativity. In addition, the effects of entrepreneurship on organizational learning orientation and organizational learning orientation on individual and group creativity were examined. These findings can provide Directions for organizational management from the cultural perspective by identifying the effects of entrepreneurship and organizational learning orientation at the organizational level.

• Journal of Convergence for Information Technology
• /
• v.11 no.6
• /
• pp.226-242
• /
• 2021

The purpose of this study was to examine the characteristics of Agile Culture, which is attracting attention as an organizational culture suitable for responding to changes in the recent corporate management environment, and to reveal the roles and relationships of leadership, Perceived Organizational Support(POS), and Agile Culture. The research was conducted on the employees of the National Agricultural Cooperative Federation and its subsidiaries, and SmartPLS 3.3.2 was mainly used for the research model test. As a result of the study, both Servant Leadership and Authentic Leadership had a positive effect on POS, and POS had a significant effect on all sub-dimensions of Agile Culture(Empowerment, Collective Intelligence and Continuous Learning). In addition, POS mediated the effects of the above two leaderships on Collective Intelligence and Empowerment, but there was no mediating effect in the relationship with Continuous Learning. These results suggest that leadership and Employees' perceptions of organizational support are important to build an Agile Culture.

• International journal of advanced smart convergence
• /
• v.10 no.1
• /
• pp.1-11
• /
• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

• Journal of the Semiconductor & Display Technology
• /
• v.22 no.3
• /
• pp.41-45
• /
• 2023

Currently, the method of loading items in the warehouse, the worker directly decides the loading location, and the most used method is to load the product at the location closest to the entrance. This can be effective when there is no difference in the required amount for goods, but when there is a difference in the required amount for goods, it is inefficient because items with a small required amount are loaded near the entrance and occupy the corresponding space for a long time. Therefore, in order to minimize the release time of goods, it is essential to select an appropriate location when loading goods. In this study, a method for determining the loading location by predicting the required amount of goods was studied to select the optimal loading location. Deep learning based bidirectional long-term memory networks (Bi-LSTM) was used to predict the required amount for goods. This study compares and analyzes the release time of goods in the conventional method of loading close to the entrance and in the loading method using the required amount for goods using the Bi-LSTM model.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.7
• /
• pp.11-18
• /
• 2023

In this paper, we evaluate deep learning time series forecasting models. Recent studies show that those models perform better than the traditional prediction model such as ARIMA. Among them, recurrent neural networks to store previous information in the hidden layer are one of the prediction models. In order to solve the gradient vanishing problem in the network, LSTM is used with small memory inside the recurrent neural network along with BI-LSTM in which the hidden layer is added in the reverse direction of the data flow. In this paper, we compared the performance of Informer by comparing with other models (LSTM, BI-LSTM, and Transformer) for real Nitrogen dioxide (NO2) data. In order to evaluate the accuracy of each method, mean square root error and mean absolute error between the real value and the predicted value were obtained. Consequently, Informer has improved prediction accuracy compared with other methods.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1329-1341
• /
• 2022

Destroying the marine environment and marine ecosystem and causing marine accidents, marine debris is generated every year, and among them, submerged marine debris is difficult to identify and collect because it is on the seabed. Therefore, deep-learning-based semantic segmentation was experimented on waste fish nets and waste ropes using underwater images to identify efficient collection and distribution. For segmentation, a high-resolution network (HRNet), a state-of-the-art deep learning technique, was used, and the performance of each optimizer was compared. In the segmentation result fish net, F1 score=(86.46%, 86.20%, 85.29%), IoU=(76.15%, 75.74%, 74.36%), For the rope F1 score=(80.49%, 80.48%, 77.86%), IoU=(67.35%, 67.33%, 63.75%) in the order of adaptive moment estimation (Adam), Momentum, and stochastic gradient descent (SGD). Adam's results were the highest in both fish net and rope. Through the research results, the evaluation of segmentation performance for each optimizer and the possibility of segmentation of marine debris in the latest deep learning technique were confirmed. Accordingly, it is judged that by applying the latest deep learning technique to the identification of submerged marine debris through underwater images, it will be helpful in estimating the distribution of marine sedimentation debris through more accurate and efficient identification than identification through the naked eye.

• Journal of Christian Education in Korea
• /
• v.74
• /
• pp.273-294
• /
• 2023

The purpose of this study is to use K-MOOC, which has limitations in utilization because it is centered on theory delivery, to derive tasks to activate the teaching methods of instructors, and to implement the derived tasks using the metaverse platform. to develop a prototype. According to the purpose of the study, the study was conducted as follows. First, from October 4 to November 15, 2022, a Delphi survey was conducted on 21 experts with experience of consulting, research, class development, and operation related to the K-MOOC project. Second, in order to realize the tasks in the teaching method field derived from the Delphi survey, matching with the teaching method class model elements to result of Delphi survey was applied was carried out. Finally, based on the results of expert Delphi and the elements of the class model applicable to the metaverse platform, a teaching method was developed. Through the process of the study, a total of 16 detailed items were derived for the teaching method-related tasks for the activation of K-MOOC: support strategic tasks, teaching method competency, aspect of class design, evaluation and sharing of learning outcomes. By applying the metaverse, the teaching model elements for K-MOOC revitalization were derived from four categories: self-directed repetition, individualized problem solving, practice opportunity expansion, and immediate feedback, and matched with the first 16 detailed items. A four-step teaching model was completed: course attendance (step 1), mission analysis by individual level (step 2), sharing of mission solutions (step 3), and mission evaluation and feedback (step 4). Through the results of this study, the possibility of using the metaverse as a teaching practice platform was confirmed even in terms of the introduction and development of specialized techniques.

• The Journal of the Korea Contents Association
• /
• v.17 no.6
• /
• pp.22-31
• /
• 2017

This study has begun with the perception that proper measuring system is required to grow community business in equilibrium and to grope for some developmental directions of it. First, for effective performance evaluation of community business, the study developed a performance evaluation model based on balanced score cards, and to apply validity analysis and analytic hierarchy process (AHP) by classifying. Second, the relative importance of the second indicator for each of the first aspects shows that participation of local residents and in the aspect of person interested, satisfaction of inner education in the aspect of learning and growth, shortening of work process in the aspect of inner process, and sales per head in the aspect of substantiality were high in relative importance. Third, in the result of calculation of overall weight for each aspect, participation of local residents, a business connection to the community, sales per head were ranked in the upper group. Thus, it's now necessary to have management support through fostering intermediate support organizations in community business which has been bureaucratic, and improvement of product and service through connection with outside consulting agencies and strategic alliance with the leading businesses is required.

• Journal of Digital Convergence
• /
• v.15 no.1
• /
• pp.53-60
• /
• 2017

The time of digital era and the increasing complexity of the management environment have raised uncertainties about the future. Companies have made steady investments in education as a way to prepare for the future. In this study, design and development methodology based on web - based management simulation games (manufacturing, distribution, finance) which author participated in development was presented. The development methodology presented in this study can be roughly divided into business simulation game design methodology and business simulation game development methodology. Since there is no existing research methodology for development methodology, development model is presented based on empirical based on development case. In this paper, we propose an overall content development methodology and propose a detailed methodology of the content.

• Journal of Digital Convergence
• /
• v.17 no.2
• /
• pp.177-185
• /
• 2019

The purpose of this study is to investigate the causes of career problems, which are the biggest problems of Korean university students, and to solve them by using case studies of domestic and global universities, I would like to suggest a career advisor system model for college students. It is most important to collect advice and learning data to solve the career problems of college students by utilizing information technology such as data analysis and AI. Research has not been actively pursued because the university has very limited internal data to advise on career problems. In this paper, we study the data types and methods of college students' career advice, and propose a career advisor counseling system for college students.