• Science of Emotion and Sensibility
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• v.6 no.3
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• pp.55-62
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• 2003

Patients with schizophrenia have thinking disorders such as delusion or hallucination, because they have a deficit in the ability which to systematize and integrate information. therefore, they cannot integrate or systematize visual, auditory and tactile stimuli. In this study, we suggest a virtual reality system for the assessment of cognitive ability of schizophrenia patients, based on the brain multimodal integration model. The virtual reality system provides multimodal stimuli, such as visual and auditory stimuli, to the patient, and can evaluate the patient's multimodal integration and working memory integration abilities by making the patient interpret and react to multimodal stimuli, which must be remembered for a given period of time. the clinical study showed that the virtual reality program developed is comparable to those of the WCST and the SPM.

• The Journal of Korean Association of Computer Education
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• v.4 no.1
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• pp.43-52
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• 2001

The aim of this paper is to develop a network-based collaborative learning system based on cooperative learning, computer simulation, role playing, and web-based instruction, which is called NetClass. It is an educational system of hybrid-type, and supports three learning modes as a distributed network, a stand-alone system, or a web browser. To accomplish the purpose of this paper, we have studied on the following topics. First, we selected appropriate learning contents among dilemmas on information ethics. Second, a Collaborative Dilemma-solving Learning Model (CDLM) was designed, and this model means systematic procedures that leaners can notice others' feeling and thinking and predict the results of his actions by introducing interactions among learners on computer networks. Third, Collaborative Learning System Model based on standard architecture of an educational system was proposed. Fourth, we developed many components such as network components, database components, and interface components.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.189-196
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• 2020

In this paper, we propose a study on the purchasing intent of the new e-commerce consumer, the coronavirus may once again drive the structural change of China's economy, and the new online marketing model will be noticed during the epidemic. Through 438 questionnaires collected on the Internet, frequency analysis, element analysis, reliability analysis and structural equation analysis were performed using SPSS V22.0 and AMOS V22.0 methods. Study the validation of hypotheses in the model to reveal the reasons why consumers in the new e-business are exposed. The results show that e-commerce features of Internet celebrities and individual characteristics of Internet celebrities can only enhance consumers' satisfaction. Quasi social relationships only increase consumer satisfaction without generating the will to purchase directly. Consumer satisfaction is the core foundation that dominates long-term consumption. E-commerce should focus on the ability of online celebrities to sell their expertise and the adaptability of value and product characteristics when conducting online celebrity marketing.

• Journal of Digital Contents Society
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• v.7 no.1
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• pp.47-52
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• 2006

This paper proposes an algorithm for human sensibility evaluation using 4-channel EEG signals of the prefrontal and the parietal lobes. The algorithm uses an artificial neural network and the multiple templates. The linear prediction coefficients are used as the feature parameters of human sensibility. Comfortableness and temperature/humidity are evaluated. Many conventional researches have emphasized that a wave of left prefrontal lobe is activated in case of positive sensibility and that of right prefrontal lobe is activated in case of negative sensibility. So the power ratio of n wave is obtained from for computation and the results are compared. The results of the comfortableness evaluation for temperature and humidity showed that the outputs of the proposed algorithm coincided with corresponding sensibilities depending on the task of the temperature and the humidity. The conventional method using a wave is hardly related with comfortableness. And it is also observed that the uncomfortable state due to the high temperature and humidity can be easily changed to the comfortable state by small drop of the temperature and the humidity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.213-218
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• 2013

One of the most popular approaches to parameter adaptation in hidden Markov model (HMM) based systems is the maximum likelihood linear regression (MLLR) technique. In our previous study, we proposed factored MLLR (FMLLR) where each MLLR parameter is defined as a function of a control vector. We presented a method to train the FMLLR parameters based on a general framework of the expectation-maximization (EM) algorithm. Using the proposed algorithm, supplementary information which cannot be included in the models is effectively reflected in the adaptation process. In this paper, we apply the FMLLR algorithm to a pitch sequence as well as spectrum parameters. In a series of experiments on artificial generation of expressive speech, we evaluate the performance of the FMLLR technique and also compare with other approaches to parameter adaptation in HMM-based speech synthesis.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.421-434
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• 2005

Abstract Based onthe characteristics of Carlin-type gold deposit in Nevada district, a potential in Korea is evaluated to the Yemi area where is structurally controlled by folds and trust fault. The fault of high angles are combined with a more permeable rocks such as the Yemi breccia and laminated silty limestone. The pattern of enrichment factors for Tl, Sb, As, Ag, Pb, Zn, Cu, Mo and W of limestones in the southern area are geochemically similar with those reported from the Carlin-type Bold deposit. Moreover, the oxygen and carbon isotopes show a hydrothermal alteration is widely developed in this area. According to the result of geophysical interpretation, stable isotope, alteration mineralogy, geochemical study, and geological structure, this mineralized zone may be extended to the M direction, so a detailed systematic exploration is required to identify this alteration zone.

• Archives of design research
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• v.17 no.3
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• pp.245-254
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• 2004

In Accordance with the change of design paradigm, the design process has changed into user-centered workflow from designer-centered workflow. Since the purpose of the past research methods is quantitative analysis or the understanding of the present situation, it doesn't fit in practical design that expressed the user's needs. Therefore, the real data about what they see and how they feel will be useful for the user-centered design. This paper's objective is to analyze eye-movement recordings and pupil size of user for mobile interface design. For this objective, it was experimented on that the user's eyegaze data of using a mobile phone by the Eyegaze Interface System, and analyzed three levels of user's task performance. The results provided evaluation of new developed and old existing interface design of mobile phone by the experiment of eye-movement recordings and pupil size. The benefit of results is compliment of the limitation of current usability test through visual characteristics of design and qualitative data of user.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.5
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• pp.1-9
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• 2021

Children's drawings are widely used in the diagnosis of children's psychology as a means of expressing inner feelings. This paper proposes a children's drawings-based object detection algorithm applicable to children's psychology analysis. First, the sketch area from the picture was extracted and the data labeling process was also performed. Then, we trained and evaluated a Faster R-CNN based object detection model using the labeled datasets. Based on the detection results, information about the drawing's area, position, or color histogram is calculated to analyze primitive information about the drawings quickly and easily. The results of this paper show that Artificial Intelligence-based object detection algorithms were helpful in terms of psychological analysis using children's drawings.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.23-29
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• 2019

In this paper, the mood of images was classified into eight categories through a deep convolutional neural network and video was automatically generated using proper background music. Based on the collected image data, the classification model is learned using a multilayer perceptron (MLP). Using the MLP, a video is generated by using multi-class classification to predict image mood to be used for video generation, and by matching pre-classified music. As a result of 10-fold cross-validation and result of experiments on actual images, each 72.4% of accuracy and 64% of confusion matrix accuracy was achieved. In the case of misclassification, by classifying video into a similar mood, it was confirmed that the music from the video had no great mismatch with images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.1-7
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• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.