• Journal of the HCI Society of Korea
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• v.13 no.3
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• pp.65-73
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• 2018

Game balance settings are crucial to game design. Game balancing must take into account a large amount of numerical values, configuration data, and the relationship between elements. Once released and served, a game - even for a balanced game - often requires calibration according to the game player's preference. To achieve sustainability, game balance needs adjustment while allowing for small changes. In fact, from the producers' standpoint, game balance issue is a critical success factor in game production. Therefore, they often invest much time and capital in game design. However, if such a costly game cannot provide players with an appropriate level of difficulty, the game is more likely to fail. On the contrary, if the game successfully identifies the game players' propensity and performs self-balancing to provide appropriate difficulty levels, this will significantly reduce the likelihood of game failure, while at the same time increasing the lifecycle of the game. Accordingly, if a novel technology for game balancing is developed using artificial intelligence (AI) that offers personalized, intelligent, and customized service to individual game players, it would bring significant changes to the game production system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1602-1608
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• 2019

In this study, we developed a "Zetton Children's Traffic Safety Education" application using mixed reality to help children experience a variety of traffic situations indirectly and to help them defend themselves from accidents. We analyze the types of high mortality child traffic accidents to set learning goal. And we developed the experience-oriented contents that players could acquire signal systems and traffic information naturally and funny in the course of playing scenarios according to designed various traffic situations. In order to verify the educational effectiveness of the developed application, children were given traffic safety education through after-school education activities. The result shows that the frequency of right answers to questions related to traffic safety awareness and learning objectives is increased.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.11-18
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• 2022

The use of multi-spectral cameras is essential for day and night pedestrian detection. In this paper, a color camera and a thermal imaging infrared camera were used to detect pedestrians near a crosswalk for 24 hours at an intersection with a high risk of traffic accidents. For pedestrian detection, the YOLOv5 object detector was used, and the detection performance was improved by using color images and thermal images at the same time. The proposed system showed a high performance of 0.940 mAP in the day/night multi-spectral (color and thermal image) pedestrian dataset obtained from the actual crosswalk site.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.45-53
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• 2020

In this paper, we describe a new method for acquiring calibration data using a user interaction process, which occurs continuously during web browsing in gaze estimation, and for performing calibration naturally while estimating the user's gaze. The proposed non-intrusive calibration is a tuning process over the pre-trained gaze estimation model to adapt to a new user using the obtained data. To achieve this, a generalized CNN model for estimating gaze is trained, then the non-intrusive calibration is employed to adapt quickly to new users through online learning. In experiments, the gaze estimation model is calibrated with a combination of various user interactions to compare the performance, and improved accuracy is achieved compared to existing methods.

• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.71-93
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• 2001

Commonly to design a database system. a conceptual database has to be designed and then it is transformed into a logical database schema prior to building a target database system. This paper proposes a method which transforms a Temporal Entity-Relationship Model(TERM) into a Temporal Object-Oriented Model(TOOM) to build an efficient database schema. I formalize the time concept in view of object versioning and specify the constraints required during transformation procedure. The proposed transformation method contributes to getting the logical temporal data from the conceptual temporal events Without any loss of semantics, Compared to other approaches of supporting various properties, this approach is more general and efficient because it is the semantically seamless transformation method by using the orthogonality of types of objects, semantics of relationships and constraints over roles.

• Journal of The Korean Association of Information Education
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• v.18 no.2
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• pp.357-370
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• 2014

The purpose of this research was to develop the tools needed to evaluate the effectiveness of using digital textbooks and smart education. We then developed the tools to evaluate the effectiveness of smart education and digital textbook utilization, which were an identification of 1) seven essential 21st century skills, definitions of each, and prerequisite abilities; 2) five 21st century teacher competencies, definitions of each, and prerequisite abilities; To develop the questionnaire, we conducted a literature review in this area, consulted experts, observed classes, interviewed members of focus groups, and met with policy makers from the Ministry of Education and KERIS. The student questionnaire(26 Questions developed) included; creativity and innovation, critical thinking and problem solving, communication, collaboration, ICT literacy, self-directed learning, and adaptability. The teacher questionnaire(24 questions developed) included; 21st Century Skills, ICT Literacy, Rapport building with learners, Instructional design, Evaluation and reflection. The tools we developed will be able to use for evaluating the effectiveness of smart education and digital textbooks.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.87-97
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• 2017

This paper examined how consumers' attitude toward the telecommunication expense was affected by news reports through the experiment. Participants were randomly assigned to one of four group (control group, high-expense-claimed-media group, low-expense-claimed-media group, and both-exposed-media group), and asked to indicate credibility & neutrality toward media report, similarity between media report, and their own thought, their attitude toward the telecommunication expense. The result of ANOVA showed that the high-expense-claimed-media was perceived more credible and neutral than the low-expense-claimed-media. ANCOVA was conducted to eliminate the impact of similarity between media report and their own thought on the evaluation of credibility & neutrality toward media report, and the result showed that there was no difference. Also, participants evaluated the telecommunication service so expensive, regardless of what kind of media reports they were exposed. We found that consumers' prior belief, which telecommunication service was expensive, might interrupt consumers' learning process for new information from media. To resolve the social pressure about mobile service rate-cutting, it is necessary to investigate how to dampen consumers' stereotype about the telecommunication expense. The future research using the framing effect could be considerable.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.177-186
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• 2021

The 2015 revised curriculum is structured around the core competencies of the 21st century, this is in line with the world's flow of education, such as OECD Education 2030. A future practical leading model was studied to provide a variety of creative teaching and learning experiences to elementary and Secondary students using intelligent information technology to cultivate core competencies such as ICT and computing thinking. In order for this practical model to stably settle the school field, the training was planned and operated to strengthen the creative convergence education capacity required by the teachers at the unit school through various types of the training. In particular, a nationwide administrators training program was operated for three years, reflecting the new curriculum, teaching and learning methods, and evaluation that can lead to future convergence talent training. In this paper, the perception of creative convergence education was investigated and analyzed considering the influence that administrators may have on the school field. Based on this, through the three-year operation results of the training, it was intended to establish a new training method for stable access to future creative convergence education under the post-corona era's social issues.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.619-630
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• 2022

The concrete mix design and compressive strength evaluation are used as basic data for the durability of sustainable structures. However, the recent diversification of mixing factors has created difficulties in calculating the correct mixing factor or setting the reference value concrete mixing design. The purpose of this study is to design a predictive model of bidirectional analysis that calculates the mixing elements of ternary concrete using deep learning, one of the artificial intelligence techniques. For the DNN-based predictive model for calculating the concrete mixing factor, performance evaluation and comparison were performed using a total of 8 models with the number of layers and the number of hidden neurons as variables. The combination calculation result was output. As a result of the model's performance evaluation, an average error rate of about 1.423% for the concrete compressive strength factor was achieved. and an average MAPE error of 8.22% for the prediction of the ternary concrete mixing factor was satisfied. Through comparing the performance evaluation for each structure of the DNN model, the DNN5L-2048 model showed the highest performance for all compounding factors. Using the learned DNN model, the prediction of the ternary concrete formulation table with the required compressive strength of 30 and 50 MPa was carried out. The verification process through the expansion of the data set for learning and a comparison between the actual concrete mix table and the DNN model output concrete mix table is necessary.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.147-154
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• 2012

The higher thinking skills, such as creativity and problem-solving about a given problem, are difficult to assess and diagnose. For an accurate diagnosis of these higher thinking abilities, we need to fully observe learner's problem-solving process or learner's individual reports. However, in an online learning or virtual class environments, evaluation of learner's problem-solving process becomes more difficult to diagnose. The best way to solve this problem is through reporting by tracking learner's actions when he tries to solve a problem. In this study, we developed a module which can evaluate and diagnose student's problem-solving ability by tracking actions in MS-Office suite, which is used by students to solve a given problem. This module performs based on the learner's job history through user tracking. To evaluate the effectiveness of this diagnostic module, we conducted satisfaction survey from students who were preparing the actual MOS exams. As a result, eighty-one (81) of the participants were positive on the effectiveness of the learning system with the use of this module.