• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.1
• /
• pp.44-51
• /
• 1999

This paper proposes a new approach of plant fault diagnosis which is based on detecting the characteristic pattern signals and associating them with the corresponding faults. The new approach does not require analytic modeling of the target system but best reflects the expertise embedded in the experienced human operation by mimicking them in a systematic way. This paper intends to illustrate the feasibility of the proposed by developing the algorithms to detect and estimate the typical characteristic pattern signals, I. e., oscillatory patterns, and applying them to the diagnosis of various faults of a 500MW boiler control system including tube rupture, feed-water leak, and controller failure.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.455-458
• /
• 1997

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are no quantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by visual stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. Seven university students were participated in this study. The experiment was devised with eleven experimental conditions, which are control and ten different types of visual stimulation based on IAPS (International Affective Picture Systems). Wavelet transformation was employed to analyze the EEG signals. Most positive and negative emotional response were compared in pairs. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with positive and negative stimulus were found. This study could be extended to establish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.

• Proceedings of the KIEE Conference
• /
• 2005.07d
• /
• pp.2959-2961
• /
• 2005

This study presents a human sensibility evaluation algorithm based on the personality-group templates of EEGs. For this objective, 16-channel EEG signals of 10 adults are collected. After Preprocessing of EEG, various EEG Parameters are estimated and compared. The proposed algorithm uses LP coefficients, neural network and pre-/post-processing techniques. The results showed good performance in human sensibility evaluation.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.61-64
• /
• 2003

In this paper, we implement PAMD(Positive Answering Machine Detection) for discrimination human and ARS. We are used Grunt detection, Glitch Noise detection and Tone detection for PAMD. It distinguishes voice signals from ring-back tone and glitch noise respectively. And as a second step, it judges whether human responses or ARS responses after integrating pattern changes like initial response period, the number of voice data, each time of voice data period and glitch noise. The accuracy is about 9375 in ASR and about 98％ in Mobile phone.

• Journal of Biomedical Engineering Research
• /
• v.9 no.2
• /
• pp.149-152
• /
• 1988

From the analysis of proton NMR signals of human urine it is found that the signals corresponding to a phenolic compound of tyrosine are more frequently observed in cancer urine than in non-cancer urine. An effective reagent is obtained to detect the substance excreted in the urine and to find out a close connection with the result of the NMR analysis. An attempt is made to determine the reagent sensitivity and specificity for cancer diagnosis. The results of the attempt are respectively above 75% for both on an average.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1997.06a
• /
• pp.13-18
• /
• 1997

Each reproducing speech signal has each particular signal property, because of the processing of encoding and decoding for communications through various media. In this paper, we examine the correlation between speech signal quality and sensory pleasure for the sensory improvement of that signal. In experiments, we evaluate the quality of speech signals through various media by psychological auditory test and physical features of these signals.

• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.267-270
• /
• 2002

In this paper, a new watermarking method using an iterative scheme is proposed. The proposed method consists of two parts: watermark generation and its insertion. In the watermark generation, random signals with normalized distribution N(0,1) are produced and modified using an iterative scheme. In the watermark insertion, the resulting watermark signals are inserted into selected transform coefficients with various scaling parameters in order to achieve the invisibility and robustness against illegal attacks. The simulation results show that the proposed method has good performance for various attacks including image compression, filtering, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.10a
• /
• pp.265-270
• /
• 2001

Voice is one of the most efficient communication media and it includes several kinds of factors about speaker, context emotion and so on. Human emotion is expressed in the speech, the gesture, the physiological phenomena(the breath, the beating of the pulse, etc). In this paper, the method to have cognizance of emotion from anyone's voice signals is presented and simulated by using neuro-fuzzy model.

• Journal of Information Technology Applications and Management
• /
• v.12 no.4
• /
• pp.25-31
• /
• 2005

We know that the Hurst Exponent (HE) is a real number in [0, 1] which denotes randomness of time series. in this research, we suggest non-linear analysis of human biological signals through HE. The feasibility of human biological signals using inductive incitement provides Some diagnosis for active treatment. In our experiment, we measured the heartbeat through the MCG, 29 healthy and 34 abnormal subjects ostensibly. The raw data of acupuncture incitement are supported by opinions of gross examination and pathological diagnosis. The mean values of HE are 0.345, 0.755 and 0.805 for the periods of before, during and after acupuncture treatment, respectively in case of abnormal subjects. On the other hand, the mean values, 0.808, 0.797 and 0.785 are for normal cases, correspondingly. From this data, we show that HE is very significant in abnormal controls according to an acupuncture incitement, and the incitement effect is evidently extracted in abnormal subjects. But, in normal subjects, the incitement effect is meaningless.

• Journal of Biomedical Engineering Research
• /
• v.27 no.2
• /
• pp.59-63
• /
• 2006

Magnetocardiogram (MCG) topography is a useful diagnostic technique that employs multi-channel magnetocardiograms. Measurement of artifact-free MCG signals is essenctial to obtain MCG topography or map for a diagnosis of human heart. Principal component analysis (PCA) combined with an artificial neural network (ANN) is proposed to remove a pulse-type artifact in the MCG signals. The algorithm is composed of a PCA module which decomposes the obtained signal into its principal components, followed by an ANN module for the classification of the components automatically. In the experiments with volunteer subjects, 97% of the decisions that were made by the ANN were identical to those by the human experts. Using the proposed technique, the MCG topography was successfully obtained without the artifact.