• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.10
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• pp.983-994
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• 2014

In this paper, we analyze the telecom services and their socio-economic effect of using open spectrum, which is to access sharing spectrum. For this, we suggest a concept and a classification of open spectrum as spectrum access model and make a survey for analyzing the socio-economic effect of spectrum, 2,605 MHz which is candidated for sharing between 2.9~5.925 Hz in Korea. From survey results, we propose Mobile Telecommunications Assist Service and WiFi as the most effective services and Smart Car Service and M2M, IoT, and RFID/USN Service as the effective services to open spectrum.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.239-246
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• 2023

In this paper, we propose an open-loop algorithm to classify speech and music signals using the spectral flux parameters and Mel Frequency Cepstral Coefficients(MFCC) parameters for the audio coder. To increase responsiveness, the MFCC was used as a short-term feature parameter and spectral fluxes were used as a long-term feature parameters to improve accuracy. The overall voice/music signal classification decision is made by combining the short-term classification method and the long-term classification method. The Gaussian Mixed Model (GMM) was used for pattern recognition and the optimal GMM parameters were extracted using the Expectation Maximization (EM) algorithm. The proposed long-term and short-term combined speech/music signal classification method showed an average classification error rate of 1.5% on various audio sound sources, and improved the classification error rate by 0.9% compared to the short-term single classification method and 0.6% compared to the long-term single classification method. The proposed speech/music signal classification method was able to improve the classification error rate performance by 9.1% in percussion music signals with attacks and 5.8% in voice signals compared to the Unified Speech Audio Coding (USAC) audio classification method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.1-8
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• 2014

This paper proposes an emotion classifier from EEG signals based on Bayes' theorem and a machine learning using a perceptron convergence algorithm. The emotions are represented on the valence and arousal dimensions. The fast Fourier transform spectrum analysis is used to extract features from the EEG signals. To verify the proposed method, we use an open database for emotion analysis using physiological signal (DEAP) and compare it with C-SVC which is one of the support vector machines. An emotion is defined as two-level class and three-level class in both valence and arousal dimensions. For the two-level class case, the accuracy of the valence and arousal estimation is 67% and 66%, respectively. For the three-level class case, the accuracy is 53% and 51%, respectively. Compared with the best case of the C-SVC, the proposed classifier gave 4% and 8% more accurate estimations of valence and arousal for the two-level class. In estimation of three-level class, the proposed method showed a similar performance to the best case of the C-SVC.

• Wind and Structures
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• v.19 no.3
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• pp.295-320
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• 2014

Starting from an overview on the research on thunderstorms in the last forty years, this paper provides a general discussion on some emerging issues and new frameworks for wind loading on structures in mixed climates. Omitting for sake of simplicity tropical cyclones and tornadoes, three main aspects are pointed out. The first concerns the separation and classification of different intense wind events into extra-tropical depressions, thunderstorms and gust fronts, with the aim of improving the interpretation of the phenomena of engineering interest, the probabilistic analysis of the maximum wind velocity, the determination of the wind-induced response and the safety format for structures. The second deals with the use of the response spectrum technique, not only as a potentially efficient tool for calculating the structural response to thunderstorms, but also as a mean for revisiting the whole wind-excited response in a more general and comprehensive framework. The third involves the statistical analysis of extreme wind velocities in mixed climates, pointing out some shortcomings of the approaches currently used for evaluating wind loading on structures and depicting a new scenario for a more rational scheme aiming to pursue structural safety. The paper is set in the spirit of mostly simplified analyses and mainly qualitative remarks, in order to capture the conceptual aspects of the problems dealt with and put on the table ideas open to discussion and further developments.