In this paper, a fuzzy inference system for sleep staging was developed. Nine input variables including temporal and spectrum analyses of the EEG, EOG, and EMG signals were extracted and normalization was applied to these variables to reduce the effect of individual variability. A fuzzy inference system contains fourteen fuzzy rules was designed to classify the 30-s sleep epochs as five sleep stages. Finally, a smoothing process was applied to the scoring results for fine-tuning. The average accuracy of the proposed method applied to 16 all-night polysomnography (PSG) recordings compared with the manual scorings can reach 87 %. This method can integrate with various PSG systems for sleep monitoring in clinical or homecare applications.

Two incremental algorithms for drawing circles using short line segments are proposed in this paper. The proposed algorithms can draw manypoints at one time. They use only addition, subtraction, and shift operations except in the initialization of the algorithm. Using this simplified approach we can greatly increase the speed of drawing circles, relative to other conventional algorithms.

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This paper proposes an optimal efficiency of fuel cell/battery hybrid power management system. The research evaluated the characteristics of fuel cell and battery to predict the efficiency and state of charge. The optimization hybrid power management controls the percentage of each power according to the demand power and efficiency. The simulation results show the proposed strategy achieves the goal of promoting the efficiency of hybrid power management.