• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.215-222
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• 2021

As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.428-433
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• 2003

In this study, we composed algorithm of DIAL(Differential Absorption Lidar). we investigated the absorption spectrum of $O_3$, S $O_2$ and N $O_2$ dependent on wavelengths using data base UV-Bank and determine the optimized wavelength model. Here, the selected optimal wavelengths are 292.00(λ$_{on}$ ), 295.20(λ$_{off}$) for $O_3$, 299.38(λ$_{on}$ ), 300.05(λ$_{off}$) for S $O_2$ and 448.00(λ$_{on}$ ), 449.85(λ$_{off}$) for N $O_2$. In particular, we established the supposed model of DIAL and simulated the error of measuring distance using the selected optimal wavelength. In the model-I with telescope of 300 mm diameter, laser energy of 3 mJ and transmission of 10000 shots, maximum distances are 4 km for $O_3$ measurement and 5 km for S $O_2$ and N $O_2$ measurements. Also, in the model-II with telescope of 600 mm diameter, laser energy of 30 mJ and transmission of 10000 shots, maximum distances are 13 km for S $O_2$ and N $O_2$ measurements.ments.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.195-201
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• 2014

In this study, face recognition system was designed based on polynomial Radial Basis Function Neural Networks(pRBFNNs) pattern classifier using 2-directional 2-dimensional principal component analysis algorithm. Existing one dimensional PCA leads to the reduction of dimension of image expressed by the multiplication of rows and columns. However $(2D)^2PCA$(2-Directional 2-Dimensional Principal Components Analysis) is conducted to reduce dimension to each row and column of image. and then the proposed intelligent pattern classifier evaluates performance using reduced images. The proposed pRBFNNs consist of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with the aid of fuzzy c-means clustering. In the conclusion part of rules. the connection weight of RBFNNs is represented as the linear type of polynomial. The essential design parameters (including the number of inputs and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. Using Yale and AT&T dataset widely used in face recognition, the recognition rate is obtained and evaluated. Additionally IC&CI Lab dataset is experimented with for performance evaluation.