On the design of multiple key hashing files for concurrent orthogonal range retrieval between two disks

This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.

A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system.     

Electrical and optical feedback in an InGaAs/InP light-amplifyingoptical switch (LAOS)

A circuit model for optical and electrical feedback has been developed to investigate the cause of negative differential resistance (NDR) switching in a series connected heterojunction phototransistor (HPT) light-emitting diode (LED) device. The model considers optical feedback from the light generated in the LED, electrical feedback from the holes thermally emitted over the LED cladding layer, nonlinear gain of the HPT, the Early effect, and leakage resistance. The analysis shows that either electrical or optical feedback can be the dominant cause for the NDR, depending upon their relative strengths. The NDR observed in the devices was caused primarily by electrical feedback since the optical feedback is weak. For low input power, avalanche breakdown appears to initiate the NDR in the devices although avalanching alone cannot cause NDR     

An integrated air-gap-capacitor pressure sensor and digital readoutwith sub-100 attofarad resolution

The fabrication and characterization of an integrated air-gap-capacitor pressure sensor are presented. The capacitor fabrication process uses standard IC processing to create NMOS circuits, and an added polysilicon layer to create poly-to-n⁺ capacitors with a 0.6-μm-thick dielectric using deposited oxide. Subsequent processing is used to produce deformable, parallel-plate, air-gap capacitors on the front side alongside MOS circuits. Sensor chips are fabricated using 100-μm×100-μm, 100-fF air-gap capacitors with on-chip circuitry. The sensor chip is a part of a capacitive measurement system that uses a charge-redistribution sense technique to achieve very high capacitance resolution. The behavior of the pressure sensor chips was studied as a function of applied pressure in the 0-240-kPa (0-35-psi) range. Measurements indicate a sensitivity of 0.93 mV/kPa (6.40 mV/psi) with a deflection of 10 nm/kPa (70 nm/psi) at 0-69 kPa (0-10 psi). Standard deviations indicate a static pressure resolution of 0.54 kPa (0.078 psi), which translates to 30 attofarads at a sampling frequency of 11 kHz     

Structural properties of 0.65Pb(Mg1/3Nb2/3)O3–0.35PbTiO3 relaxor ferroelectric thin films on SrRuO3 conducting oxides

Coating of 0.65Pb(Mg_1/3Nb_2/3)O₃–0.35PbTiO₃ (PMN–PT) relaxor ferroelectrics by a sol–gel method is followed by growth of epitaxial SrRuO₃ (SRO) metallic oxide electrodes on SrTiO₃ (STO) single-crystal substrate by pulsed laser deposition. High-quality PMN–PT films on SRO with preferred growth orientation were successfully fabricated by controlling the operation parameters. Structural properties of relaxor ferroelectric PMN–PT thin films on SRO/STO substrates have been studied by X-ray diffraction (XRD), transmission electron microscopy (TEM) and atomic force microscopy (AFM). In-plane and out-of-plane alignments of the heterostructure are confirmed and the structural twinning of the materials are also revealed.     

Study on Contamination Control for Yield Enhancement in the Manufacturing Line of Cellular Phone Modules

Practical studies on the method of contamination control for yield enhancement in the cellular phone modules production line were carried out. A contamination control method was proposed, consisting of data collection, data analysis, improvement action, verification, and implementation of control. The partition check method and the composition analysis for data collection and data analysis were respectively used in the cellular phone modules manufacturing process, and these methods were evaluated by the variation of yield loss before and after implementing the actions for improvement. In the partition check method, the critical process step was selected, and yield loss reduction through improvement actions was observed, whereas in the composition analysis, critical sources were selected, and yield loss reduction through improvement actions was investigated. From the results, it is concluded that the partition check and the composition analysis are effective solutions for contamination control in cleanroom production lines.     

Application of artificial neural networks to the analysis of two‐dimensional fluorescence spectra in recombinant E coli fermentation processes

A two‐dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E coli for the production of 5‐aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyzed using artificial neural networks, ie self‐organizing map (SOM) and feedforward backpropagation neural network (BPNN). The SOM‐based classification of the whole spectral data has made it possible to qualitatively associate some process parameters with the normalized weights and variances, and to select some useful combinations of excitation and emission wavelengths. Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process's performance, eg forecasting the process's performance. Copyright © 2005 Society of Chemical Industry