We examine how a linear (cyclic) sequence of six fundamental colors affects human color impression. In order to investigate the different effects of two spatial sequences, we consider a hexagonal diagram that is a projection of RGB color space from white to black. The hexagonal diagram corresponds roughly to the hue circle indicated by both hue and saturation in the HLS system. The projected route area indicates the magnitude of naturalness (as in rainbows) for color sequences. The minimum sequence is similar to the order of colors in rainbows, whereas the non-minimum sequence is completely different. Therefore, we proposed a human color impression model using the projected route area indicated by both hue and saturation. We clarified that subjects of nearly all ages have natural impressions when the route area is large and unnatural impressions when the route area is small, and compared the human color impression to the human color impression model.

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This paper relates the effects of the listening of wind band music to the changes of blood pressure and heart rate in daily living environment. Seven healthy peoples aged from 22 to 54 are invited as the experiment subjects, and five pieces of different-wind band music are employed as the test pieces. AH subjects are asked to listen to all test pieces individually, and their blood pressures and heart rates are recorded and analyzed. They are also asked to answer a questionnaire about which piece among the test pieces is impressive. The analysis results show that the trend of the blood pressure change and heart rate change for those subjects, whose answers are the same test piece, is similar, and the trend of the blood pressure change and heart rate change for those subjects, whose answers are not the same piece, is also similar. This fact shows that there exist some relationship between listening of a specific wind band piece and the trend of blood pressure change and heart rate change. Further, one subject is asked to listen to four extra sets of test pieces besides one mentioned above. The analysis results shows that the changes of blood pressure and heart rate during listening to the wind band music is smaller than the changes of blood pressure and heart rate in case of without listening to the music. The experiment data are analyzed by ANOVA (analysis of variance) method, and the results show the significant difference between the data with music listening and those without music listening. This fact also shows that there exist some relationship between listening of some specific wind band piece and the trend of blood pressure change and heart rate change. And further, when listening to the "poor performance" of wind band music, the coefficient of variation of heart rate is smaller than that when listening to the "skillful performance" of wind band music. This result shows that the effect of listening of wind band music apparently appears on changes of heart rate.

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This main objective of this paper is to develop a fuzzy classification model for epilepsy risk level analysis from EEG signals. The parametric values such as energy, variance and duration, co-variance, peaks, sharp and spike waves and events are derived in each epoch of two second duration in the EEG signal channels. Fuzzy techniques are applied to classify the risk level in each epoch for all the channels, the obtained risk level patterns are found to have low values of sensitivity, specificity Performance Index (PI) and Quality Value (QV). In order to increase the classification rate, a neural network Radial Basis Function (RBF) is used for optimization of fuzzy outputs. This network is trained and tested with 480 patterns extracted from three epochs of sixteen channel EEG signals often known epilepsy patients. Different architectures of RBF networks are compared based on the minimum Mean Square Error (MSE); the better network (16-16-1) is selected. The Quality Value is improved to 23.98 when compared to the value 6.25 achieved through fuzzy techniques.

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The wireless networking data processing at the Obafemi Awolowo University Teaching Hospital Complex (OA UTHC) is hereby presented for Hospital information management. It makes use of Client-Server architecture. Base station serves as the server while the mobile station serves as the clients. The access point into the network is through the Base station. The clients (mobile stations) are linked to the server through Radio Waves. As Medical Personnel move from ward to ward i.e. from one cell coverage to another, the drop in signal is not due to momentary fading but as the terminal is moving away from the base station. Frequency Hoping spread spectrum is employed for spread spectrum modulation. The Channel access method employed is Fixed Assignment Access Method and the channel management employed is Code Division Multiple Access to allow multi-user operation. The data in the network is secured through encryptions and cryptography.

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In this study, we measured pulse waves in dialysis patients, and analyzed dialysis-induced changes in pulse wave data. The data used were the mean blood pressure and quantitative pulse wave data such as maximum wave height, rising slope, and area of pulse waveform, before and after dialysis. The mean blood pressure was considerably correlated with the maximum wave height and area of pulse waves in dialysis patients. The mean blood pressure and the quantitative data of pulse waves were significantly decreased after dialysis. Moreover, the change of the maximum wave height was correlated with that of mean blood pressure before and after dialysis. Dialysis-induced changes of the pulse waveform pattern from the protuberant type (Bell type) to the flattened type (Flat type) were investigated by pulse wave pattern analysis. The analytical results suggest that quantitative data of pulse wave responses may be a noteworthy characteristic to represent changes before and after dialysis.

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Information Technology has recently been introduced to various social systems. Especially, important information for our living like a road map has been brought by Geographic Information Systems. Particularly, a 3-D road map is a strong concern of map-producing industries because of its visual understandability in car navigation. Although there are researches on the development of 3-D road maps, most of them employ aerial views obtained from an airplane or a satellite. They cannot offer an exact 3-D road map, since certain road information cannot be observed from above. This paper proposes a novel technique for creating a 3-D road map. It includes proposal of a vehicle that collects ground-view information of a road environment and a graphic system for producing a 3-D road map employing the collected information. The function of the proposed technique is to make a 3-D map by fitting measured data to a given 2-D map. In order to evaluate the proposed technique, we performed experiments at several cities in the world, and produced highly realistic 3-D graphical maps of the road environment. This confirms the availability of the proposed technique.

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To help us understand the details of pulsating blood flow through the post-stenotic dilatation artery we use the computational fluid dynamic techniques to gain the wall shear stress distributions and the streamline patterns. In the work, a mathematical model of the axially symmetric rigid artery containing the stenosis and the dilatation is introduced. The incompressible Navier-Stokes equations are solved numerically by using the finite difference method. The geometry and the flow conditions represent a real physiological situation as closely as possible.

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The objective of the present paper is a synthesis study of the Fast Fourier Transform (FFT) and the Wavelet Transform (WT) in analysing the first and the second heartbeat signals of the phonocardiagram (PCG). It is shown that the wavelet Transform provide a good time-frequency representation and enough features of the PCG signal that will help physician to obtain qualitative and quantitative measurements and consequently aid to diagnosis. Similarly, it is shown that the frequency content of such a signal can be determined by the FFT only without difficulties.

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This paper presents a novel algorithm for fuzzy segmentation of magnetic resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the radio-frequency coils or to problems associated with the acquisition sequences. The result is a slowly varying shading artifact over the image that can produce errors with conventional intensity based classification. The proposed algorithm is formulated by modifying the objective function of the standard fuzzy c-means (FCM) algorithm to compensate for such inhomogeneities and to allow the labeling of a pixel to be influenced by the labels in its immediate neighborhood. Clustering algorithms such as FCM that use calculus based optimization methods can be trapped by local extrema in the process of optimizing the clustering criterion. They are also very sensitive to initialization. The proposed algorithm uses GA to optimize the modified fuzzy (J_m) c-means function. The genetic algorithm approach is able to find the lowest known J_m value or a J_m associated with a partition very similar to that associated with the lowest J_m value. The performance of the algorithm is evaluated on a series of MR images of the brain.

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