In this paper, we describe the PS³ load distribution scheme. A target service is a transaction service consisting of multiple processes that communicate with each other. A target system consists of workstations connected by a LAN. PS³ determines the process allocation by estimating response times and throughputs. It allows us to set an upper limit of a response time, and to set lower and upper limits for the throughput of each service. PS³ tries to find a process allocation that provides the minimum response time under conditions set by the user in advance. We measured the response times and throughputs and compared the values with the estimated ones. The results show that PS³ provides an appropriate process allocation, and that calculated results agree well with the measured ones.

For cluster systems consisting of multiple nodes and shared servers which consist of an on-line and a backup server, we propose a hot-standby scheme of shared servers. In this scheme for shared servers, the shared servers have user data and control data. The on-line shared server sends only the control data to the backup server when it receives an update command. When the on-line shared server fails, the backup shared server reconstructs the shared data by using the latest control data sent from the on-line server and the user data sent from each node. We evaluated the system recovery time and the performance overhead for the hot-standby scheme. This enables the system recovery time to be shortened to 30 seconds and the performance overhead to be reduced to 2%.

A. Chatterjee et al. proposed tests with linearity property for gate delay faults to determine, at a required clock speed, whether a circuit under test is a marginal chip or not. The latest transition time at the primary output is changed linearly with the size of the gate delay fault when the proposed test is applied to the circuit under test. To authors' knowledge, no reports on an algorithmic method for generating tests with linearity property have been presented before. In this paper, we propose a method for generating tests with linearity property for gate delay faults. The proposed method introduces a new extended timed calculus to calculate the size of a given gate delay fault that can be propagated to the primary output. The method has been applied to ISCAS benchmark circuits under the unit delay model.

A method to recognize planar objects undergoing affine transformation is proposed in this paper. The method is based upon wavelet multiscale features and Hopfield neural networks. The feature vector consists of the multiscale wavelet transformed extremal evolution. The evolution contains the information of the contour primitives in a multiscale manner, which can be used to discriminate dominant points, hence a good initial state of the Hopfield network can be obtained. Such good initiation enables the network to converge more efficiently. A wavelet normalization scheme was applied to make our method scale invariant and to reduce the distortion resulting from normalizing the object contours. The Hopfield neural network was employed as a global processing mechanism for feature matching and made our method suitable to recognize planar objects whose shape distortion arising from an affine transformation. The Hopfield network was improved to guarantee unique and more stable matching results. A new matching evaluation scheme, which is computationally efficient, was proposed to evaluate the goodness of matching. Two sets of images, noiseless and noisy industrial tools, undergoing affine transformation were used to test the performance of the proposed method. Experimental results showed that our method is not only effective and robust under affine transformation but also can limit the effect of noises.

In this paper, an effective method of system modeling and dynamic scheduling to improve operation and control for the Back-End process of semiconductor manufacturing is developed by using Colored Timed Petri-Nets (CTPNs). The simulator of a CTPNs model was utilized to generate a new heuristic scheduling method with genetic algorithm(GA) which enables us to obtain the optimal values of the weighted delay time and standard deviation of lead time.

The glottal closure instants (GCIs) obtained from the wavelet analysis of speech signal are investigated in comparison with those obtained from the EGG signal. Experimental results have shown that about 96% of GCIs with wavelet transformed speech signal is located within 0.5 ms with respect to the GCIs with EGG signal.

A new feature parameter based on a discrete wavelet transform is proposed for word boundary detection of isolated utterances. The sum of standard deviation of wavelet coefficients in the third coarse and weighted first detailed scale is defined as a new feature parameter for endpoint detection. Experimental results demonstrate the superiority of the proposed feature to the conventional ones in capturing word boundaries even in noisy speech.