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A computer curriculum guideline for Taiwan junior high schools was announced in 1994 and will be nationally implemented in 1998. Due to the specific educational system in Taiwan, the guideline will affect computer textbook writing, computer teaching and learning, computer teachers" professional development, and computer education researches. This paper is to introduce the guideline, discuss its impacts, and describe issues. We believe that a mandatory curriculum guideline or standard is necessary for providing computer concepts and skills to all our next generations. A solid computer education research base should be established to provide usable and promising perspectives and strategies for computer education practices.

This paper presents an evolution-based hierarchical feature fusion system that selects the dominant features among multiple feature vectors for ultrasonic liver tissue characterization. After extracting the spatial gray-level dependence matrices, multiresolution fractal feature vectors and multiresolution energy feature vectors, the system utilizes evolution-based algorithms to select features. In each feature space, features are selected independently to compile a feature subset. As the features of different feature vectors contain complementary information, a feature fusion process is used to combine the subsets generated from different vectors. Features are then selected from the fused feature vector to form a fused feature subset. The selected features are used to classify ultrasonic images of liver tissue into three classes: hepatoma, cirrhosis, and normal liver. Experiment results show that the classification accuracy of the fused feature subset is superior to that derived by using individual feature subsets. Moreover, the findings demonstrate that the proposed algorithm is capable of selecting discriminative features among multiple feature vectors to facilitate the early detection of hepatoma and cirrhosis via ultrasonic liver imaging.

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