High-performance automatic target recognition through data-specificVLSI

Under the Mojave configurable computing project, we have developed a system for achieving high performance on an automatic target recognition (ATR) application through the use of configurable computing technology. The ATR system studied here involves real-time image acquisition from a synthetic aperture radar (SAR). SAR images exhibit statistical properties which can be used to improve system performance. In this paper, the Mojave configurable computing system uses field programmable gate arrays (FPGA's) to implement highly specialized circuits while retaining the flexibility of programmable components. A controller sequences through a set of specialized circuits in response to real-time events. Computer-aided design (CAD) tools have been developed to support the automatic generation of these specialized circuits. The resulting configurable computing system achieves a significant performance advantage over the existing solution, which is based on application specific integrated circuit (ASIC) technology     

Model-based monitoring of diamond turning process using cross entropy

This paper discusses the model-based monitoring as one of key steps toward building an inprocess diagnostic tool for the supervisory level control in diamond turning. In particular, estimation of surface profile from a nonlinear force model and model-based monitoring of tool chipping are demonstrated. Classification rule is based on the minimization of information-theoretic measure called the cross entropy. The experimental results indicate that monitoring strategy based on the minimum cross entropy guarantees the consistent and optimum classification results in the presence of varying cutting conditions. In addition, the cross entropy as a criterion for indicating the dynamic quality of machine-tool is explained.     

Normal-incidence InAs self-assembled quantum-dot infrared photodetectors with a high detectivity

An InAs/AlGaAs quantum-dot infrared photodetector based on bound-to-bound intraband transitions in undoped InAs quantum dots is reported. AlGaAs blocking layers were employed to achieve low dark current. The photoresponse peaked at 6.2 /spl mu/m. At 77 K and -0.7 V bias, the responsivity was 14 mA/W and the detectivity, D*, was 10/sup 10/ cm/spl middot/Hz/sup 1/2//W.     

The effect of topical corticosteroids on refractive outcome and corneal haze after photorefractive keratectomy

BACKGROUND: The effect of topical corticosteroids after excimer laser photorefractive keratectomy (PRK) remains a matter of some controversy. Refractive effects may be different according to the amount of myopia and timing of instillation. METHODS: Two groups of patients were studied: Study A consisted of 215 eyes (128 patients) with PRK (mean baseline myopia, -6.53 +/- 2.22 D) that received no corticosteroids (No Corticosteroid Group) unless significant regression or corneal haze appeared (Delayed Corticosteroid Group), and in Study B, we randomly assigned eyes to the Initial Corticosteroid Group (mean baseline myopia, -6.39 +/- 1.84 D) or the No/delayed Corticosteroid Group (mean baseline myopia -5.78 +/- 2.02 D). Clinical results after PRK for low-to-moderate and high myopia were compared. RESULTS: In the first group, 70.9% (73 eyes) of moderately myopic eyes (mean, -4.56 +/- 1.10 D) belonged to the No Corticosteroid Group that had a mean refraction of -5.39 +/- 1.77 D. Delayed Corticosteroid Group eyes were more myopic (mean, -7.52 +/- 2.10 D), and showed more severe haze than those in the No Corticosteroid Group. In study B, only in high myopes with more than -6.00 D (mean, -7.76 +/- 1.15 D) did refraction and corneal haze outcomes show significant difference between the Initial Corticosteroid Group and the No/delayed Corticosteroid Group. CONCLUSIONS: The effects of topical corticosteroids after PRK were less in moderate myopes compared to high myopes. Delayed instillation of corticosteroids did not reverse the regression or haze whereas initial instillation showed a beneficial effect on high myopes but not on moderate myopes.     

Arthroscopic reduction and fixation of bony avulsion of the posterior cruciate ligament of the tibia

Bony avulsion fractures of the posterior cruciate ligament of the tibia have commonly been treated by open reduction and internal fixation using the posterior approach. However, this approach, using the prone position, makes it difficult to investigate and treat other combined injuries of the knee joint. We report a case of posterior cruciate ligament avulsion of the tibia that was arthroscopically reduced and firmly fixed with two cannulated screws. The posterior sag was absent after the operation and the result was excellent. By arthroscopy, we got rigid fixation of the avulsed fragment for early rehabilitation, and detection of a concomitant injury was also possible.     

Recording of volume hologram using a beam pattern from taperedoptical fiber

A photorefractive volume hologram was recorded and probed using light diffracted from a tapered optical fiber as a reference beam. A single-mode fiber (SMF) was chemically etched and tapered to give a complicated beam pattern, and it is shown that the tapered optical fiber can be utilized to increase the storage density of the volume hologram. Spatial selectivity of the volume hologram with this method was increased by two times compared to the normal SMF referencing, which is due to the fact that the complicated beam pattern has little correlation with its shifted version     

Measurements and correlation of effect of cosolvents on the solubilities of complex molecules in supercritical carbon dioxide

A new transparent microscale circulation-type high pressure equilibrium cell with on-line sampling was devised. With this apparatus, experimental solubility of molecularly complex species such as steroids (cholesterol, stigmasterol and ergosterol) and fatty acids (palmitic acid and stearic acid) in supercritical carbon dioxide(sc-C0₂) were measured. Also, to find an appropriate substance for enhancing both the polarity and the solubility power of the SC-CO₂ solvent, we arbitrarily selected three polar substances such as acetone, methanol and water and the effect of these cosolvents on the solubility of solutes in SC-CO₂ are examined. The supercritical phase equilibrium data of solute-cosolvent-sc-CO₂ systems were quantitatively correlated using a new equation of state based on the lattice fluid theory incorporated with the concept of multibody interaction. We found that the addition of tracer amount of acetone or methanol to SC-CO₂ enhances the solubility of all solutes about thirty to sixty times when compared with the case of pure sc-CO₂ However, for the case of cosolvent water, no further enhancement of the solubility of solutes was realized. Also, the versatile fittability of the equation of state proposed in this work was demonstrated with the newly measured ternary supercritical equilibrium data.     

Selection of network and learning parameters for an adaptive neural robotic control scheme

This paper presents the results of a study in the design of a neural network based adaptive robotic control scheme. The neural network used here is a two hidden layer feedforward network and the learning scheme is the well-known backpropagation algorithm. The neural network essentially provides the inverse of the plant and acts in conjunction with a standard PD controller in the feedback loop. The objective of the controller is to accurately control the end position of a single link manipulator in the presence of large payload variations, variations in the link length and also variations in the damping constant. Based on results of this study, guidelines are presented in selecting the number of neurons in the hidden layers and also the parameters for the learning scheme used for training the network. Results also indicate that increasing the number of neurons in the hidden layer will improve the convergence speed of learning scheme up to a certain limit beyond which the addition of neurons will cause oscillations and instability. Guidelines for selecting the proper learning rate, momentum and fast backpropagation constant that ensure stability and convergence are presented. Also, a relationship between the r.m.s. error and the number of iterations used in training the neural network is established.     

Area- and time-specific marginal capacity costs of electricity distribution

Marginal costs of electricity vary by time and location. In the past, researchers attributed the variations to factors related to electricity generation and transmission. These authors, however, have not analyzed possible variations in marginal distribution capacity costs (MDCC). The objectives of this paper are:

1. (i) to show that large MDCC variations are due to the dispersion in distribution capital expenditures by time and space,

2. (ii) to propose a method for quantifying the area- and time-specific MDCC in the presence of lumpy investments, and

3. (iii) to compare our MDCC estimates to those commonly used in the electric utility industry.

Our proposed method and its results were adopted by the California Public Utilities Commission (CPUC) in 1992 for Pacific Gas and Electric Company (PG&E), the largest privately owned electric utility in the U.S.