• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.231-233
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• 2018

Programming learning is difficult for learners, and there are many cases where students lose interest in programming or give up. In this situation, the resilience is the ability of learners to stand up and get resilient and gain confidence in learning. Also, depending on the programming language and tools, the learner may feel the cognitive burden and the learning motivation may be different. In this study, we compared and analyzed the differences of resilience among the students of the scratch course and the Python course of the liberal programming lecture. As a result of the study, the differences in resilience of Python lectures and scratch lectures were significant but not significant. Through this study, learning strategies based on programming languages and tools and learners' tendencies were established.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.50-64
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• 2016

Nowadays, smart meter (SM) technology is widely effectively used. In addition, power allocation (PA) and channel selection (CS) are considered problems with many proposed approaches. In this paper, we will suggest a specific scenario for an SM configuration system and show how to solve the optimization problem for transmission between SMs and the data concentrator unit (DCU), the center that collects the data from several SMs, via simulation. An efficient CS with PA scheme is proposed in the TV white space system, which uses the TV band spectrum. On the basic of the optimal configuration requirements, SMs can have a transmission schedule and channel selection to obtain the optimal efficiency of using spectrum resources when transmitting data to the DCU. The optimal goals discussed in this paper are the maximum capacity or maximum channel efficiency and the maximum allowable power of the SMs used to satisfy the quality of service without harm to another wireless system. In addition, minimization of the interference to the digital television system and other SMs is also important and needs to be considered when the solving coexistence scenario. Further, we propose a process that performs an interference analysis scheme by using the spectrum engineering advanced Monte Carlo analysis tool (SEAMCAT), which is an integrated software tool based on a Monte-Carlo simulation method. Briefly, the process is as follows: The optimization process implemented by genetic evolution optimization engines, i.e., a genetic algorithm, will calculate the best configuration for the SM system on the basis of the interference limitation for each SM by SEAMCAT in a specific configuration, which reaches the solution with the best defined optimal goal satisfaction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.1145-1148
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• 2005

In this paper, we introduce a probabilistic model based on Bayesian networks (BNs) for inferring human fatigue by integrating information from various visual cues and certain relevant contextual information. Visual parameters, typically characterizing the cognitive states of a person including parameters related to eyelid movement, gaze, head movement, and facial expression, serve as the sensory observations. But, an individual visual cue or contextual Information does not provide enough information to determine human fatigue. Therefore in this paper, a Bayesian network model was developed to fuse as many as possible contextual and visual cue information for monitoring human fatigue. At the experiment results, display the utility of the proposed BNs for predicting and modeling fatigue.

• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.120-133
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• 2000

Major obstruction of using formal methods for hybrid real-time systems in industry is the difficulty that engineers have in understanding and applying the quantitative methods in an abstract requirements phase. While formal methods technology in safety-critical systems can help increase confidence of software, difficulty and complexity in using them can cause another hazard. In order to overcome this obstruction, we propose a framework for qualitative requirements engineering of the hybrid real-time systems. It consists of a qualitative method for requirements specification, called QFM (Qualitative Formal Method), and a safety analysis method for the requirements based on a causality information, called CRSA (Causal Requirements Safety Analysis). QFM emphasizes the idea of a causal and qualitative reasoning in formal methods to reduce the cognitive burden of designers when specifying and validating the software requirements of hybrid safety systems. CRSA can evaluate the logical contribution of the software elements to the physical hazard of systems by utilizing the causality information that is kept during specification by QFM. Using the Shutdown System 2 of Wolsong nuclear power plants as a realistic example, we demonstrate the effectiveness of our approach.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.112-123
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• 2005

The latest E-commerce sites provide personalized services to maximize user satisfaction for Internet user The collaborative filtering is an algorithm for personalized item real-time recommendation. Various supplementary methods are provided for improving the accuracy of prediction and performance. It is important to consider these two things simultaneously to implement a useful recommendation system. However, established studies on collaborative filtering technique deal only with the matter of accuracy improvement and overlook the matter of performance. This study considers representative attribute-neighborhood, recommendation textile set, and similarity grouping that are expected to improve performance to the recommendation agent system. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommendation Agent System (FDRAS ).

• The Journal of Information Technology
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• v.9 no.1
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• pp.21-32
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• 2006

Acrophobia is a symptom of feeling an abnormal fear of heights. Medications or cognitive-behavior methods have been mainly used to treat the acrophobia. In these days the virtua1 reality technology has been applied to treat such an anxiety disorders. In this thesis, an telemedicine assistant system for treatment of acrophobia using biomedical signals and virtual reality technique is proposed. I made two virtual reality simulations for treatment of acrophobia and telemedicine system for communication between doctor and patient using personal computer. A virtual environment provides patient with stimuli which arouses phobia, and exposition to such environment makes him have ability to overcome the fear. Recently, the patient can take diagnosis from a medical doctor in distance with the telemedicine system. Multimedia conference service, on-line questionary, signal transfer system are needed to configure such system. Virtual reality simulation system that composed of position sensor, head mount display, and audio system, is also included in this telemedicine system. I added virtual environment update system to this virtual reality telemedicine system for treatment of acrophobia. Former acrophobia treatment systems use only patient's score of the questionary to appraise. The new system developed in this thesis uses not only patient's score of the questionary but also biomedical signals such as HR, GSR amplitude, GSR RT to increase the objectivity and quantitativity. The experimental results show that HR and GSR amplitude are useful for decision of acrophobia. We will apply this system to the acrophobia patient in distance and be able to offer better medical treatment for mental illness in near future.

• Nuclear Engineering and Technology
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• v.21 no.1
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• pp.1-11
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• 1989

Numerous losses of decay heat removal capability have occurred at U during stutodwn while its significance to safety is needless to say. A study is carried out as an attempt to assess what could be done to lower the frequency of these events and to mitigate their consequences in the unlikely event that one occurs. The shutdown risk model is developed and analyzed using Event/Fault Tree for the typical pressurized water reactor. The human cognitive reliability (HCR) model, two-stage bayesian approach and staircase function model are used to estimate human reliability, initiating event frequency and offsite power non-recovery probability given loss of offsite power, respectively. The results of this study indicate that the risk of a Pm at shutdown is not much lower than the risk when the plant is operating. By examining the dominant accident sequences obtained, several design deficiencies are identified and it is found that some proposed changes lead to significant reduction in core damage frequency due to loss of cooling events.

• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.119-126
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• 2018

This study intended to exploratively testify human error causing factors for railway traffic controller, using AMOS structural equation model. Through literature survey, fatigue and stress as exogenous variable, errors in information process such as cognitive, memory, storage, and execution error as endogenous variable, and accident and incident(near-miss) as dependent variable were set up. Results based on AMOS using 201 railway traffic controllers' questionnaire showed that a clear causality loop like as 'stress ${\rightarrow}$ memory error ${\rightarrow}$ storage error ${\rightarrow}$ incident(near-miss) ${\rightarrow}$ accident' is formed. This result suggests that for the purpose of mitigation of traffic controller's accident, it is so necessary to reduce memory and execution error in the information processing process based on the effective management of stress, as the precedent of them.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.295-301
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• 2021

Individual mental fatigue not only reduces cognitive ability and work performance, but also becomes a major factor in large and small accidents occurring in daily life. In this paper, a CNN model for EEG-based mental fatigue discrimination was proposed. To this end, EEG in the resting state and task state were collected and applied to the proposed CNN model, and then the model performance was analyzed. All subjects who participated in the experiment were right-handed male students attending university, with and average age of 25.5 years. Spectral analysis was performed on the measured EEG in each state, and the performance of the CNN model was compared and analyzed using the raw EEG, absolute power, and relative power as input data of the CNN model. As a result, the relative power of the occipital lobe position in the alpha band showed the best performance. The model accuracy is 85.6% for training data, 78.5% for validation, and 95.7% for test data. The proposed model can be applied to the development of an automated system for mental fatigue detection.

• Journal of the Korea Safety Management & Science
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• v.23 no.2
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• pp.65-77
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• 2021

This paper conducted an empirical study to identify the causal relationship of factors affecting the purchase intention of automobiles from the customer's point of view. This study sets the purchase intention as a result variable and constructs a causal model with brand image, product attributes (exdogenous variable), and customer value (endogenous variable) as a cause that affects purchase intention. The results of this study are summarized as follows. First, the symbolic image of the brand was found to have a very significant effect on customer value (p=0.01), and the external attribute of the product also had a significant effect on customer value (p=0.1). Second, customer value was found to have a very significant effect on purchase intention (p=0.01), and the functional image of the brand also had a significant effect on purchase intention (p=0.1). Third, there is a strong positive (+) correlation between the functional image of the brand and the symbolic image of the brand, the intrinsic attribute of the product, and the external attribute of the product, and also between the symbolic image of the brand and the intrinsic attribute of the product and There was also a positive (+) correlation between extrinsic attributes. Therefore, in order to increase customer value, automobile manufacturing companies have a functional value of products from a customer-oriented perspective. It is judged that every effort should be made to maintain a lasting relationship by grasping the values of customers, which are social values, emotional values, situational values, and cognitive values.