• The Journal of Korean Association of Computer Education
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• v.22 no.3
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• pp.79-87
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• 2019

This study examined the effect of e-learning contents with different dual-coding, media-richness, and cognitive-load degree on learning. To do so, after dividing summary and explanation presentation methods in e-learning contents according to information's quantity and kind, the effects on teaching presence and academic achievement were examined. The summary presentation method was produced as text type and text+illustration type and the explanation presentation method as audio type and audio+video type. The results of this study are as follows. First, in the summary method, the text+illustration type had significantly higher teaching presence than text type. Second, in the explanation method, the audio type was found to be significantly higher than the audio+video type. Third, the interaction between the summary method and explanation method was found to be significant in teaching presence and academic achievement.

• Biomedical Science Letters
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• v.24 no.4
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• pp.418-425
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• 2018

Amyloid brain positron emission tomography (PET) images are visually and subjectively analyzed by the physician with a lot of time and effort to determine the ${\beta}$-Amyloid ($A{\beta}$) deposition. We designed a convolutional neural network (CNN) model that predicts the $A{\beta}$-positive and $A{\beta}$-negative status. We performed 18F-florbetaben (FBB) brain PET on controls and patients (n=176) with mild cognitive impairment and Alzheimer's Disease (AD). We classified brain PET images visually as per the on the brain amyloid plaque load score. We designed the visual geometry group (VGG16) model for the visual assessment of slice-based samples. To evaluate only the gray matter and not the white matter, gray matter masking (GMM) was applied to the slice-based standard samples. All the performance metrics were higher with GMM than without GMM (accuracy 92.39 vs. 89.60, sensitivity 87.93 vs. 85.76, and specificity 98.94 vs. 95.32). For the patient-based standard, all the performance metrics were almost the same (accuracy 89.78 vs. 89.21), lower (sensitivity 93.97 vs. 99.14), and higher (specificity 81.67 vs. 70.00). The area under curve with the VGG16 model that observed the gray matter region only was slightly higher than the model that observed the whole brain for both slice-based and patient-based decision processes. Amyloid brain PET images can be appropriately analyzed using the CNN model for predicting the $A{\beta}$-positive and $A{\beta}$-negative status.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.70-82
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• 2022

At the current stage of a semi-autonomous vehicle, there are situations in which the vehicle has to request take-over control to the driver quickly. However, current self-driving cars use only simple messages and warning sounds to notify drivers when handing over control, so they do not adequately convey considerations of individual characteristics or explanations of various emergent situations. This study investigated how visual and auditory information and the efficacy of drivers in self-driving cars can improve efficient take-over requests between the car and the driver. We found that there were significant differences in driver's cognitive load, reliability, safety, usability, and usefulness according to the combination of three visual and auditory information provided in the experiment of the take-over request situation. The results of this study are expected to help design self-driving vehicles that can communicate more safely and efficiently with drivers in urgent control transition situations.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Asia Marketing Journal
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• v.17 no.4
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• pp.21-42
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• 2016

Purpose: Social influence has a decisive role in shaping a person's cognition and behavior. Chinese face consciousness, including moral component, is an important part of Chinese traditional culture, which influences people to implement moral behavior. With both eye-tracking technology and traditional questionnaire, this research aims to explore people's moral psychology and the psychological processing mechanisms of Chinese face consciousness, as well as the impact of Chinese face consciousness on the preference for the ecological product. Method and Data: 75 college and MBA students' eye movement data were collected when they read different kinds of moral materials, as well as data from the subsequent questionnaires. To test the hypothesis, ANOVA analysis and Heat Map analysis were performed. Besides, the PROCESS of bootstrap was used to test mediation effect. Findings: The results reveal that: 1. Compared to the moral-situation reading, when subjects read immoral situations, they need more processing time due to the moral dissonance and cognitive load. 2. Compared to the control condition, when threatened moral self is primed, subjects prefer to choose ecological product. 3. Protective face orientation is the mediator between threatened moral self and preference to ecological product. Key Contributions: First, this study broadens the use of eye-tracking technology in marketing and demonstrates a better understanding of the relationship between morality and consumer behavior in a more scientific way. Second, this study not only distinguishes the meanings between "protective face orientation" and "acquisitive face orientation", but also innovatively validates that when moral self is threatened, consumers tend to choose ecological product as moral compensation in order to protect their face. It can shed light on the promotion of ecological product in practical applications.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.61-75
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• 2023

This study aims to evaluate the usability of a banking app that is frequently used by the elderly. To this end, the usability PACMAD(People At the Center of Mobile Application Development) model that can be used in mobile was explained and the usability evaluation was empirically verified for the elderly over 60 years of age. For this study, descriptive statistics and variance analysis were conducted using SPSS 25.0 for 165 elderly people who had experience using banking apps. Looking at the analysis results of this study, efficiency, satisfaction, and effectiveness showed relatively high scores, and learnability, memorability, error, and cognitive load showed relatively low scores. In addition, in the verification of differences by age, it was confirmed that there were differences in all variables by age. These results suggest that the elderly's usability evaluation of banking apps and differences by age could be confirmed, but there is also a limitation that comparison with the general public is difficult because the age is limited to the elderly.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.171-186
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• 2018

Recent research has shown that elementary school students can experience epistemic affect -emotions and feelings experienced within epistemic practices, such as the enjoyment of having a wonderful idea or uncomfortable feeling of at a cognitive dissonance- during modeling process. This study explores how an introverted elementary student could participate in the modeling process by constructing an epistemic affect. Based on the theory of constructed emotion, we analyzed one elementary student's constructed epistemic affect using data resources such as emotion diaries, video recordings, and post interviews. We selected one introverted student (a fifth grader), showing peripheral and full participation during modeling. Specifically, we explored which emotions were constructed when she participated in modeling peripherally -and which epistemic affect was constructed when she participated fully- during the construction, evaluation, and revision processes. The research results showed, first, that the introverted elementary student came to participate in the model construction process by constructing the epistemic affect called aha. Second, the results showed that she came to participate in the model revision process by constructing the epistemic affect called feeling that the reasoning was wrong when confronting the rebuttals of the other student. Finally, she came to participate in the model evaluation process by constructing the epistemic affect called dislike of another student's idea. Through our exploration of the constructed epistemic affect of the introverted elementary student, we deduced that it is important to help each student to construct an epistemic affect that facilitates his or her participation in modeling. Also, we discussed that it is important to understand the impact of the emotional load that can occur for each student, depending on the constructed past, present, and future emotions.

• Journal of The Korean Association For Science Education
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• v.33 no.7
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• pp.1471-1485
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• 2013

The purpose of this study was to develop a HAM (Heuristic Attention Model) by analyzing the difference between eye movements according to the science achievement of elementary school students on discrimination task. Science achievement was graded by the results of the Korea national achievement test conducted in 2012 for a random sampling of classes. As an assessment tool to check discrimination task, two discrimination measure problems from TSPS (Test of Science Process Skill, developed in 1994) which were suitable for an eye tracking system were adopted. The subjects of this study were 20 students from the sixth grade who agreed to participate in the research. SMI was used to collect EMD (eye movement data). Experiment 3.2 and BeGaze 3.2 programs were used to plan experiments and analyze EMD. As a result, eye movements of participants in discrimination tasks varied greatly in counts and duration of fixation, first fixation duration, and dwell time, according to students' science achievement and difficulty of the problems. By the analysis of EMD, strategies of the students' problem-solving could be found. During problem solving, subjects' eye movements were affected by visual attention; bottom-up attention, top-down attention and convert attention, and aflunter attention. In conclusion, HAM was developed, and it is believed to help in the development of a science learning program for underachievers.

• Fire Science and Engineering
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• v.17 no.4
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• pp.20-27
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• 2003

Hazard Analysis is one of the basic tasks to ensure the safety of chemical plants. However, it is an arduous, tedious, time-consuming work and requires multidisciplinary knowledge and demands considerable cognitive load from the analysts. To overcome these problems, there have been attempts to automate this work by utilizing computer technology, particularly in the area of knowledge-based technique. There is two methods in the risk assessment of Chemical plant; quantitative and qualitative risk assessment. Both of them have been applied respectively, but if the integrated method of quantitative and qualitative risk assessments is used, all of the advantage of two methods can be applied. It is difficult to carry out integrated risk management of chemical plant. Therefore, automated integration system of risk management is necessary. We developed S/W Automated System for Hazard Screening & Analysis(ASCA) and applied to practical plant. By applying ASCA to case study, we can get the information about relative ranks of equipments, variable deviation, and consequence of potential accident. In this study, we applied ASCA to the H.T.U(Hydrotreating Unit) of the process to produce aromatic material. We could know relative ranks of equipments, variable deviation of malfunction in storage tank, D-101, and consequence of potential accident using ASCA. If integrated risk management in the chemical plant is applied, we can develop the emergency plan and prevent the accident.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.47-56
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• 2012

The purpose of this study is to test the effect of pedagogical agent realism and expertise on persona effect. There were two perspectives of the pedagogical agents' social interaction. Self-identification hypothesis argues that complexity of agent image is better to increase social interaction. Subjective identification insists that simplified image is more helpful to facilitate social interaction. However, from the cognitive load theory perspective, learners' expertise can be a major factor to determine persona effect. Sixty-eight college students (male=19 and female=49) participated. The independent variables were the degree of realism of pedagogical agent (detailed vs. simplified image) and the expertise (high prior knowledge group vs. low prior knowledge group). The dependant variables were comprehension test and the agent persona instrument (API). There was no significant difference in comprehension test score; however, there were significant interaction effect on the most constructs of API: 1) facilitating of learning, 2) credible, and 3) human-like. The follow-up analysis of simple main effect revealed that high expertise group showed significantly higher perception of the three construct with high realism of pedagogical agent. The results of study show that learners' expertise plays a key role of perception of persona effect.