Optimal neuronal tuning for finite stimulus spaces

The efficiency of neuronal encoding in sensory and motor systems has been proposed as a first principle governing response properties within the central nervous system. We present a continuation of a theoretical study presented by Zhang and Sejnowski, where the influence of neuronal tuning properties on encoding accuracy is analyzed using information theory. When a finite stimulus space is considered, we show that the encoding accuracy improves with narrow tuning for one- and two-dimensional stimuli. For three dimensions and higher, there is an optimal tuning width.     

Analytical solutions for sagittal plane waves in three-layer composites

The analytic dispersion equations for the symmetric and antisymmetric saggital plane plate modes of a three-layer composite system are presented. The composite consists of a solid isotropic plate sandwiched between two acoustically thin (<0.02 lambda) isotopic solid layers, where lambda is the acoustic wavelength. The thin layers are considered either as the mass loading or the chemical selective coating layers for the plate wave sensors. Explicit formulas which identify the contributions of the elasticity and inertia effects for the phase velocity and mass loading sensitivity of the lowest symmetric (S(0)) and antisymmetric (A(0)) mode for the case where the thickness of the composite plate is much less than lambda are obtained. The amounts by which the elasticity of the thin layer and the inertia decrease the mass loading sensitivity is found for both sensors. It is also found that the sensitivity of the A(0) mode significantly depends on the operating frequency but that of the S(0) mode does not. Specific examples are given for the case of a fused silica plate sandwiched by two thin lucite layers.     

Optical fiber sensor based on differential spectroscopic absorption

A material sensor based on differential spectroscopic absorption is proposed. The presence of a foreign material in a medium embodying the fiber sensor results in power attenuation at some particular wavelengths. This attenuation, which may be used for measuring the amount of the lossy material, is theoretically analyzed for the case of single-mode operation. A sensitivity analysis is carried out, and some design considerations are discussed.     

On Kalman filtering over fading wireless channels with controlled transmission powers

We study stochastic stability of centralized Kalman filtering for linear time-varying systems equipped with wireless sensors. Transmission is over fading channels where variable channel gains are counteracted by power control to alleviate the effects of packet drops. We establish sufficient conditions for the expected value of the Kalman filter covariance matrix to be exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing power control policies which minimize the total sensor power budget. In deriving the optimal power control laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.     

High-temperature and broadband immersion ultrasonic probes

Immersion ultrasonic probes for measurements and imaging at high temperature are presented. The probes consist of sol-gel-sprayed thick films as piezoelectric ultrasonic transducers (UTs) directly deposited onto steel buffer rods. They operate in pulse-echo mode at temperatures up to 500/spl deg/C. The operating ultrasonic frequency is between 5 MHz and 20 MHz, controlled by the film thickness. The ultrasonic thickness measurement of a steel plate with the probe fully immersed in molten zinc at 450/spl deg/C was demonstrated using ultrasonic plane waves. For imaging purposes, the probing end of the steel buffer rod was machined into a semispherical concave shape to form an ultrasonic lens and achieve high spatial resolution with focused ultrasound in liquids. Ultrasonic surface and subsurface imaging using a mechanical raster scan of the focused probe in silicone oil at 200/spl deg/C was also carried out. The importance of the signal-to-noise ratio (SNR) in the pulse-echo measurement is discussed.     

Assessing Positive and Negative Changes in the Aftermath of Adversity: Psychometric Evaluation of the Changes in Outlook Questionnaire.

The Changes in Outlook Questionnaire (CiOQ; S. Joseph, R. Williams, & W. Yule, 1993) is a 26-item self-report measure that was designed to assess positive and negative changes in the aftermath of adversity. This article had 3 aims: 1st, to investigate the factor structure of the CiOQ; 2nd, to test for internal consistency reliability and convergent and discriminant validity; and, 3rd, to investigate the association between positive and negative changes in outlook, posttraumatic stress, and psychological distress. Three studies are reported. Study 1 provides evidence that positive and negative changes are statistically separable and that the 2-factor model is a better fit than the 1-factor model. Studies 2 and 3 provide evidence for internal consistency reliability, convergent and discriminant validity of the CiOQ, and its associations with posttraumatic stress and psychological distress. In conclusion, the CiOQ has much promise for research on responses to stressful and traumatic events. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Microwave remote sensing of physically buried objects in the Negev Desert: implications for environmental research

We report remote detections of physically buried specularly reflecting objects using microwave radar at two sites: Ashalim and Tseelim in the northern region of the Negev Desert, Israel. These detections provide confirmation that microwave subsurface remote sensing is a genuine phenomenon. At Ashalim, a scatterometer operating in the P-band (441 MHz, 68 cm) was mounted on a cherry picker truck at a height of 8 m and used to detect two triangular aluminum mesh reflectors (forming a 1-m square area reflector) buried down to a depth of 8 cm in dry sand. At Tseelim, the same scatterometer was mounted on an airplane flying at an altitude of 70 m and used to detect 1-m square aluminum reflectors (each one submerged at a different location along the airplane flight path) buried down to a depth of 20 cm. The experimental results compare favorably with a theoretical model that incorporates radar absorption effects arising in the sandy subsurface layer and radar interference effects arising from phase differences between reflections from the surface and buried reflector. The theoretical modeling also predicts the detection of a subsurface reflector down to a depth of about 4.4 m. This experiment and the associated modeling approach is the first of a series of planned experiments, which we outline for the detection and the theoretical evaluation of buried reflectors using remote microwave and VHF radar. We identify potential subject areas for environmental research.     

Edge-preserving texture filtering for real-time rendering

Texture filtering is essential in enhancing the visual quality of real-time rendering. Conventional schemes do not consider the characteristics of texture content, thus the sharpness of edges in texture images cannot be retained. This paper proposes a novel texture-filtering algorithm, which consists of edge-preserving interpolation and edge-preserving MIP-map prefiltering. The memory bandwidth requirement is kept the same as in conventional schemes by dynamically adjusting the interpolation kernel. Hardware implementation is also provided to show the real-time processing capability. Published online: 28 January 2003     

Applying Plan Recognition Algorithms To Program Understanding

Program understanding is often viewed as the task of extracting plans and design goals from program source. As such, it is natural to try to apply standard AI plan recognition techniques to the program understanding problem. Yet program understanding researchers have quietly, but consistently, avoided the use of these plan recognition algorithms. This paper shows that treating program understanding as plan recognition is too simplistic and that traditional AI search algorithms for plan recognition are not suitable, as is, for program understanding. In particular, we show (1) that the program understanding task differs significantly from the typical general plan recognition task along several key dimensions, (2) that the program understanding task has particular properties that make it particularly amenable to constraint satisfaction techniques, and (3) that augmenting AI plan recognition algorithms with these techniques can lead to effective solutions for the program understanding problem.