Retrospective dosimetry: dose evaluation using unheated and heated quartz from a radioactive waste storage building

In the assessment of dose received from a nuclear accident, considerable attention has been paid to retrospective dosimetry using heated materials such as household ceramics and bricks. However, unheated materials such as mortar and concrete are more commonly found in industrial sites and particularly in nuclear installations. These materials contain natural dosemeters such as quartz, which usually is less sensitive than its heated counterpart. The potential of quartz extracted from mortar in a wall of a low-level radioactive-waste storage facility containing distributed sources of 60Co and 137Cs has been investigated. Dose-depth proliles based on small aliquots and single grains from the quartz extracted from the mortar samples are reported here. These are compared with results from heated quartz and polymineral fine grains extracted from an adjacent brick, and the integrated dose recorded by environmental TLDs.     

Object‐oriented design patterns for debugging heterogeneous languages and virtual machines

Debugging multi‐language software systems requires examining and executing these systems at multiple levels of abstraction. Embedded systems, for example, often comprise a mix of assembly language device drivers and C language control code. Embedded systems increasingly utilize Java to support dynamic loading and run‐time reconfiguration. The RTEEM (Research version of the Tcl Environment for Extensible Modeling) debugger employs three design patterns in solving the problems of multi‐language embedded system debugging. The Reflective virtual machine (VM) pattern models a language‐neutral virtual machine abstraction, with language‐specific interfaces extending this abstraction. Reflection allows a debugger to inspect and control a target VM. The Chain of Responsibility is a classic pattern used to arrange language‐specific debugger command interpreters in a delegation chain. All interpreters share a single command syntax, but each interpreter adapts commands to its language abstraction by interacting with its language‐specific VM view. Composite is another classic pattern, used to combine objects into tree structures. RTEEM employs it to aggregate VM debugger chains into a hierarchy that supports uniform command syntax for debugging threads, processes, multiprocessor systems, and compositions of these entities. This paper illustrates how combining two classic design patterns with the VM abstraction as a pattern results in an architecture that is powerful and flexible in adapting to the debugging needs of heterogeneous, distributed embedded systems. Copyright © 2004 John Wiley & Sons, Ltd.     

A neuromorphic depth-from-motion vision model with STDP adaptation

We propose a simplified depth-from-motion vision model based on leaky integrate-and-fire (LIF) neurons for edge detection and two-dimensional depth recovery. In the model, every LIF neuron is able to detect the irradiance edges passing through its receptive field in an optical flow field, and respond to the detection by firing a spike when the neuron's firing criterion is satisfied. If a neuron fires a spike, the time-of-travel of the spike-associated edge is transferred as the prediction information to the next synapse-linked neuron to determine its state. Correlations between input spikes and their timing thus encode depth in the visual field. The adaptation of synapses mediated by spike-timing-dependent plasticity is used to improve the algorithm's robustness against inaccuracy caused by spurious edge propagation. The algorithm is characterized on both artificial and real image sequences. The implementation of the algorithm in analog very large scale integrated (aVLSI) circuitry is also discussed.     

Parallel Assignments in Software Model Checking

In this paper we investigate how formal software verification systems can be improved by utilising parallel assignment in weakest precondition computations.We begin with an introduction to modern software verification systems. Specifically, we review the method in which software abstractions are built using counterexample-guided abstraction refinement (CEGAR). The classical NP-complete parallel assignment problem is first posed, and then an additional restriction is added to create a special case in which the problem is tractable with an O(n²) algorithm. The parallel assignment problem is then discussed in the context of weakest precondition computations. In this special situation where statements can be assumed to execute truly concurrently, we show that any sequence of simple assignment statements without function calls can be transformed into an equivalent parallel assignment block.Results of compressing assignment statements into a parallel form with this algorithm are presented for a wide variety of software applications. The proposed algorithms were implemented in the ComFoRT reasoning framework [J. Ivers and N. Sharygina. Overview of ComFoRT: A model checking reasoning framework. Technical Report CMU/SEI-2004-TN-018, Carnegie Mellon Software Engineering Institute, 2004] and used to measure the improvement in the verification of real software systems. This improvement in time proved to be significant for many classes of software.     

Minimizing risk using prediction uncertainty in neural networkestimation fusion and its application to papermaking

The paper presents Bayesian information fusion theory in the context of neural-network model combination. It shows how confidence measures can be combined with individual model estimates to minimize risk through the fusion process. The theory is illustrated through application to the real task of quality prediction in the papermaking industry. Prediction uncertainty estimates are calculated using approximate Bayesian learning. These are incorporated into model combination as confidence measures. Cost functions in the fusion center are used to control the influence of the confidence measures and improve the performance of the resultant committee.     

A rotating ball inlet for on-line MALDI mass spectrometry

The rotating ball inlet (ROBIN) is presented in a new design for on-line matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). This method uses a capillary to deliver a matrix and analyte solution to the surface of a rotating ball upon which MALDI is carried out. The ball is in contact with a polymer gasket surrounding the capillary. Sample adhering to the surface of the ball is dragged past the gasket into the vacuum of the mass spectrometer where it is irradiated by a pulsed UV laser, and the resulting ions are mass-separated in a linear time-of-flight mass spectrometer. The mechanical sample introduction prevents clogging of the vacuum interface by matrix crystals or frozen solvent. Preliminary results from flow injection analysis (FIA) suggest that the new interface does not introduce a significant peak-tailing or memory effect. The system is capable of 20-30 h of continuous operation with a flow rate of 2 microL/min before cleaning of the ball is needed. With the prototype inlet, concentration detection limits are at the low micromolar level.     

Adaptive optical array receivers for detection of surface acoustic waves

Adaptive interferometric detection systems based on two-wave mixing in photorefractive crystals have been configured as distributed optical receivers. The spatial distribution of the detection laser power on the sample surface is controlled by use of phase gratings and amplitude masks. The responses of point, line, array, and chirped optical receivers to propagating surface acoustic waves (SAW's) are discussed theoretically and demonstrated experimentally. It is shown that by use of different object beam footprints it is possible to configure adaptive holographic SAW receivers that are either broadband or narrow band and that are preferentially sensitive to SAW's propagating in given directions. The receivers also allow for the distribution of laser power over the sample, eliminating the excessive heating or surface damage that can occur in some materials when high power, point-focused, detection lasers are used.     

Using Real-Time Stereo Vision for Mobile Robot Navigation

This paper describes a working vision-based mobile robot that navigates and autonomously explores its environment while building occupancy grid maps of the environment. We present a method for reducing stereo vision disparity images to two-dimensional map information. Stereo vision has several attributes that set it apart from other sensors more commonly used for occupancy grid mapping. We discuss these attributes, the errors that some of them create, and how to overcome them. We reduce errors by segmenting disparity images based on continuous disparity surfaces to reject spikes caused by stereo mismatches. Stereo vision processing and map updates are done at 5 Hz and the robot moves at speeds of 300 cm/s.     

The influence of goat genotype on the production of Capretto and Chevon carcasses. 3. Dissected carcass composition

The dissected composition from left sides of the carcasses obtained from 50 buck kids from five goat genotypes (10 kids/genotype), Boer x Angora (BA), Boer x Saanen (BS), Feral x Feral (FF), Saanen x Angora (SA) and Saanen x Feral (SF), was compared at two age groups. The muscle content of various primal cuts varied between 53 and 73% for Capretto and Chevon groups, with minor differences between genotypes. SA kids had significantly higher separable carcass fat compared to BS and SF for the Capretto group, while Chevon carcasses from BA and SF deposited more carcass fat than FF. The bone content (19–21%) of the carcass side did not differ significantly between genotypes for the Chevon group. The dissected carcass components (muscle, fat and bone) were significantly correlated with those components of most of the individual cuts. The percentage carcass muscle and fat increased and bone content decreased significantly with age.