For the connection request procedure in mobile communication systems, a previous study had shown that the 3-channel systems provide the haighest maximum of stable per channel throughput. In this paper, we propose and study a new algorithm, called the Parallel Collision Resolution Algorithm, which can be implemented in a Q-channel connection request environment, where Q3. For the implementation, the channels are arranged in R groups, where R is a positive integer. The collision resolution scheme distributes the collided messages over all the groups so that throughput and delay measures can be improved. At any point in time, there can be a maximum of R collision resolution schemes operational irrespective of the channel or the group number over which collisions occurred. The performance measures are estimated by computer simulation. Under the new algorithm, almost the same level of the perchannel stable throughput measure of a 3-channel network can be achieved in networks for which Q3. This feature allows freedom to the network designer to employ a higher number of connection request channels without forfeiting high channel utilization rates. When Q is an integral multiple of 3, the maximum stable per channel throughput level achieved can be the same as that achieved by the 3 channel system, if the grouping of channels is such that each group consists of 3 channels. When Q is not an integral multiple of 3, the intuitive strategy of organizing the channels in such a way that Q/3 groups consist of 3 channels each and one group consists of (Q mod 3) channels, may result in much degraded performance. It is found that, if the channels are so organised that no group is composed of (Q mod 3) channels, the performance levels can be substantially enhanced. Also, under the new algorithm, the delay measure is significantly improved, particularly in schemes like the mobile satellite systems with high propagation delays. We conclude that the new scheme presents a promising collision resolution methodology for connection request procedures.

A new cleaning solution (FPM; HF-H2O2-H2O) was investigated in order to remove effectively metallic impurities on the silicon wafer surface. The removability of metallic impurities on the wafer surface and the concentrations of metallic impurities adsorbed on the wafer surface from each contaminated cleaning solution were compared between FPM and conventional cleaning solutions, such as HPM (HCl-H2O2-H2O), SPM (H2SO4-H2O2), DHF (HF-H2O) and APM (NH4OH-H2O2-H2O). This new cleaning solution had higher removability of metallic impurities than conventional ones. Adsorption of some kinds of metallic impurities onto the wafer surface was a serious problem for conventional cleaning solutions. This problem was solved by the use of FPM. FPM was important not only as a cleaning solution for metallic impurities, but also as an etchant. Furthemore, this new cleaning solution made possible to construct a simple cleaning system, because the concentrations of HF and H2O2 are good to be less than 1% for each, and it can be used at room temperature.

In this paper, subband image coding with symmetric biorthogonal wavelet filters is studied. In order to implement the symmetric biorthogonal wavelet basis, we use the Laplacian Pyramid Model (LPM) and the trigonometric polynomial solution method. These symmetric biorthogonal wavelet basis are used to form filters in each subband. Also coefficients of the filter are optimized with respect to the coding efficiency. From this optimization, we show that the values of a in the LPM generating kernel have the best coding efficiency in the range of 0.7 to 0.75. We also present an optimal bit allocation method based on considerations of the reconstruction filter characteristics. The step size of each subband uniform quantizer is determined by using this bit allocation method. The coding efficiency of the symmetric biorthogonal wavelet filter is compared with those of other filters: QMF, SSKF and Orthonormal wavelet filter. Simulation results demonstrate that the symmetric biorthogonal wavelet filter is useful as a basic means for image analysis/synthesis filters and can give better coding efficiency than other filters.

For the development of a practical device simulation, it is necessary to solve the large sparse linear equations with a high speed computation of direct solution method. The use of parallel computation methods to solve the linear equations can reduce the CPU time greatly. The Multi Step Diakoptics (MSD) algorithm, is proposed as one of these parallel computation methods with direct solution, which is based on Diakoptics, that is, a tearing-based parallel computation method for sparse linear equations. We have applied the MSD algorithm to device simulation. This letter describes the partition and connection schedules in the MSD algorithm. The evaluation of this algorithm is done using a massively parallel computer with distributed memory (AP1000).