• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.35-43
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• 2023

This study tried to find out the applicability and effectiveness of the AI-based adaptive learning system in university classes by operating an AI-based adaptive learning system on a pilot basis. To this end, an AI-based adaptive learning system was applied to analyze the operation results of 42 learners who participated in basic mathematics classes, and a survey and in-depth interviews were conducted with students and professors. As a result of the study, the use of an AI-based customized learning system improved students' academic achievement. Both instructors and learners seem to contribute to improving learning performance in basic concept learning, and through this, the AI-based adaptive learning system is expected to be an effective way to enhance self-directed learning and strengthen knowledge through concept learning. It is expected to be used as basic data related to the introduction and application of basic science subjects for AI-based adaptive learning systems. In the future, we suggest a strategy study on how to use the analyzed data and to verify the effect of linking the learning process and analyzed data provided to students in AI-based customized learning to face-to-face classes.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.439-449
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• 2023

This paper deals with a resource efficient artificial intelligence (AI) service architecture for multi-channel video streams. As an AI service, we consider the object detection model, which is the most representative for video applications. Since most object detection models are basically designed for a single channel video stream, the utilization of the additional resource for multi-channel video stream processing is inevitable. Therefore, we propose a resource efficient AI service framework, which can be associated with various AI service models. Our framework is designed based on the modular architecture, which consists of adaptive frame control (AFC) Manager, multiplexer (MUX), adaptive channel selector (ACS), and YOLO interface units. In order to run only a single YOLO process without regard to the number of channels, we propose a novel approach efficiently dealing with multi-channel input streams. Through the experiment, it is shown that the framework is capable of performing object detection service with minimum resource utilization even in the circumstance of multi-channel streams. In addition, each service can be guaranteed within a deadline.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.151-159
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• 2018

This study focused on appreciative inquiry(AI) of salespeople who have to respond to various types of emotions according to the desires of individual customers at service contact points and the effect of emotional labor on adaptive selling behavior and customer satisfaction. Dyadic questionnaires were administerd to 115 automobile salespeople and 2 customers who received service from each salesperson, and the collected data was analyzed by using structural equation modeling. The results showed that AI had positive influences on deep acting and surface acting. Only deep acting was found to have positive relationship with adaptive selling behavior, but not to surface acting. Adaptive selling behavior had a positive effect on customer satisfaction. This study will contribute to identifying the need for AI access for salespersons and for activating adaptive selling behavior through emotional labor related to AI practice.

• Journal of The Korean Association of Information Education
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• v.26 no.4
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• pp.249-263
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• 2022

The purpose of this study is to investigate the effects of assessment by adopting adaptive learning in higher education that are rarely examined in previous studies. In particular, this study applied research questions: 1) How does technical perception, perceived contents and features, and perceived integration of the AI-based adaptive system with lecture affect overall satisfaction, overall effectiveness, overall usefulness, overall motivation for the study, and intention to use it with other classes? 2) How do overall satisfaction, overall effectiveness, overall usefulness, motivation for the class, and intention to use affect loyalty on the AI-based adaptive system? This study conducted online surveys after the completion of the classes adopted AI-based adaptive learning system, ALEKS. This study applied ANOVA, regression, and factor analyses. The results of this study found that perceived integration of the AI-based adaptive learning system with the lectures on overall satisfaction, effectiveness, motivation, and intention to use for other classes showed significant with higher effect size. The results of this study provides implication that the AI-based learning system help improve learning outcomes in graduate level studies. The results provide policy and managerial implications that the AI-based adaptive learning system should improve better customer relationships in higher education.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.107-120
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• 2023

In this study, we investigate the changes and realities of the content production process focusing on Image generation AI revolutions such as Stable Diffusion, Midjourney, and DELL-E, and examine the current status of related department operations at universities and Find out the status of the current curriculum. Through this, we suggest the need to produce AI-adaptive content talent through re-establishing the capabilities of content-related departments in art universities and quickly introducing curriculum. This is because it can be input into the efficient AI content development system currently being applied in industrial fields, and it is necessary to cultivate talent who can perform managerial and technical roles using various AI systems in the future. In conclusion, we will prepare cornerstone research to establish the university's status as a source of talent that can lead the content industry beyond the AI content production era, and focus on convergence capabilities and experience with the goal of producing convergence talent to cultivate AI adaptive content talent, suggests the direction of curriculum application for value creation.

• Genomics & Informatics
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• v.16 no.4
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• pp.28.1-28.6
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• 2018

Due to the increasing interest in synonymous codons, several codon bias-related terms were introduced. As one measure of them, the tRNA adaptation index (tAI) was invented about a decade ago. The tAI is a measure of translational efficiency for a gene and is calculated based on the abundance of intracellular tRNA and the binding strength between a codon and a tRNA. The index has been widely used in various fields of molecular evolution, genetics, and pharmacology. Afterwards, an improved version of the index, named specific tRNA adaptation index (stAI), was developed by adapting tRNA copy numbers in species. Although a subsequently developed webserver (stAIcalc) provided tools that calculated stAI values, it was not available to access pre-calculated values. In addition to about 100 species in stAIcalc, we calculated stAI values for whole coding sequences in 148 species. To enable easy access to this index, we constructed a novel web database, named STADIUM (Species-specific tRNA adaptive index compendium). STADIUM provides not only the stAI value of each gene but also statistics based on pathway-based classification. The database is expected to help researchers who have interests in codon optimality and the role of synonymous codons. STADIUM is freely available at http://stadium.pmrc.re.kr.

• Journal of Korea Game Society
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• v.5 no.4
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• pp.23-32
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• 2005

This paper introduces environment analysis way to improve the game AI. The way of environment analysis can provide game user the more reality than generally used AI patterns. This paper suggests the way to make die NPC patterns variously. To realize this theory we designed the organization of NPC server newly, and also accomplished the experiment of NPC server simulation test to get the performance applied in real situation.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.129-140
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• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.

• Journal of the Korean housing association
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• v.22 no.3
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• pp.113-122
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• 2011

This study aimed to develop AI- (Artificial Intelligence) based thermal control logics and test their performance for identifying the optimal thermal control method in buildings. For this objective, a conventional Two-Position On/Off logic and two AI-based variable logics, which applied ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System), have developed. Performance of each logic was tested in a typical two-story residential building in U.S.A. using the computer simulation incorporating MATLAB and IBPT (International Building Physics Toolbox). In the analysis of the test results, AI-based control logic presented the advanced thermal comfort with stability compared to the conventional logic while they did not show significant energy saving effects. In conclusion, the predictive and adaptive AI-based control logics have a potential to maintain interior air temperature more comfortably, and the findings in this study could be a solid foundation for identifying the optimal thermal control method in buildings.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.844-847
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• 2003

Display devices are becoming increasingly important as an interface between humans and machines in the growing information society. In display devices, PDP (Plasma Display Panel) has many advantages in that it has wide screen, wide viewing angle and is light weight, thin. In PDP driving method, if the brightness of input image is high, applying the fixed sustain pulse to the PDP panel will raise the PDP power consumption and may damages the PDP panel. To overcome these problems, the Plasma AI driving method was introduced by the Matshushita co. in Japan. The Plasma AI driving module calculates the peak value and average value of 1 frame image and adjusts the gradation and sustain pulses for 1 frame sustain. In this paper, the proposed PDP driving module is based on the Plasma AI driving module. The proposed driving module calculates peak value and average value, and the brightness distribution of 1 frame image. Using brightness distribution, the proposed driving module divides 1 frame input image into 15 image patterns. For each image pattern, minimum sustain pulses and sub-frames are used for the brightness of 1 frame image and the sustain weight for 64, 128, 192 gradation is proposed. Therefore, the sustain power consumption can be reduced.