The joint movement of pebbles in solving the ($$N^2-1$$)-puzzle suboptimally and its applications in rule-based cooperative path-finding

The present paper deals with the problem of solving the (\(n^2 - 1\))-puzzle and cooperative path-finding (CPF) problems sub-optimally by rule-based algorithms. To solve the puzzle, we need to rearrange \(n^2 - 1\) pebbles in the \(n \times n\)-sized square grid using one vacant position to achieve the goal configuration. An improvement to the existing polynomial-time algorithm is proposed and experimentally analyzed. The improved algorithm represents an attempt to move pebbles in a more efficient way compared to the original algorithm by grouping them into so-called snakes and moving them together as part of a snake formation. An experimental evaluation has shown that the snakeenhanced algorithm produces solutions which are 8–9 % shorter than the solutions generated by the original algorithm. Snake-like movement has also been integrated into the rule-based algorithms used in solving CPF problems sub-optimally, which is a closely related task. The task in CPF consists in moving a group of abstract robots on an undirected graph to specific vertices. The robots can move to unoccupied neighboring vertices; no more than one robot can be placed in each vertex. The (\(n^2 - 1\))-puzzle is a special case of CPF where the underlying graph is a 4-connected grid and only one vertex is vacant. Two major rule-based algorithms for solving CPF problems were included in our study—BIBOX and PUSH-and-SWAP (PUSH-and-ROTATE). The use of snakes in the BIBOX algorithm led to consistent efficiency gains of around 30 % for the (\(n^2 - 1\))-puzzle and up to 50 % in for CPF problems on biconnected graphs with various ear decompositions and multiple vacant vertices. For the PUSH-and-SWAP algorithm, the efficiency gain achieved from the use of snakes was around 5–8 %. However, the efficiency gain was unstable and hardly predictable for PUSH-and-SWAP.     

Test-retest reliability of Purdue Pegboard performance in thermoneutral and cold ambient conditions

In the cold, Purdue Pegboard (PP) performance declines. The purpose of this study was to determine if this cold-induced impairment is consistent across days (i.e. test-retest reliability) in 5°C. In thermoneutral air (25°C), 14 men were familiarised to the dominant hand (PPa) and bimanual (PPb) PP tasks. They then experienced two 90-min cold exposures (Day 1, Day 2) while wearing ～1 clo. Bare hands were maintained throughout. Performance on both tasks showed high reliability from day to day (intraclass correlations >0.700) in both thermoneutral and cold conditions. However for both tasks, room temperature performance did not predict performance in the cold (intraclass correlations <0.450). When screening applicants for manual labour in the cold, one must consider that room temperature dexterity does not correlate with dexterity in the cold. It is recommended that a 60-min period of cold exposure be employed to assess manual dexterity in these workers. STATEMENT OF RELEVANCE: This study shows that PP performance in room temperature does not predict performance in the cold but performance in the cold is consistent from day to day. When screening applicants for manual labour in the cold, it is recommended that dexterity tests be conducted in the same ambient conditions.     

A threshold insensitive method for locating the forest canopy top with waveform lidar

Lidars have the unique ability to make direct, physical measurements of forest height and vertical structure in much denser canopies than is possible with passive optical or short wavelength radars. However the literature reports a consistent underestimate of tree height when using physically based methods, necessitating empirical corrections. This bias is a result of overestimating the range to the canopy top due to background noise and failing to correctly identify the ground.This paper introduces a method, referred to as “noise tracking”, to avoid biases when determining the range to the canopy top. Simulated waveforms, created with Monte-Carlo ray tracing over geometrically explicit forest models, are used to test noise tracking against simple thresholding over a range of forest and system characteristics. It was found that noise tracking almost completely removed the bias in all situations except for very high noise levels and very low (< 10%) canopy covers. In all cases noise tracking gave lower errors than simple thresholding and had a lower sensitivity to the initial noise threshold.Finite laser pulses spread out the measured signal, potentially overriding the benefit of noise tracking. In the past laser pulse length has been corrected by adding half that length to the signal start range. This investigation suggests that this is not always appropriate for simple thresholding and that the results for noise tracking were more directly related to pulse length than for simple thresholding. That this effect has not been commented on before may be due to the possible confounding impacts of instrument and survey characteristics inherent in field data. This method should help improve the accuracy of waveform lidar measurements of forests, whether using airborne or spaceborne instruments.     

Colour and rotation invariant textural features based on Markov random fields

A visual appearance of natural materials significantly depends on acquisition circumstances, particularly illumination conditions and viewpoint position, whose variations cause difficulties in the analysis of real scenes. We address this issue with novel texture features, based on fast estimates of Markovian statistics, that are simultaneously rotation and illumination invariant. The proposed features are invariant to in-plane material rotation and illumination spectrum (colour invariance), they are robust to local intensity changes (cast shadows) and illumination direction. No knowledge of illumination conditions is required and recognition is possible from a single training image per material. The material recognition is tested on the currently most realistic visual representation - Bidirectional Texture Function (BTF), using CUReT and ALOT texture datasets with more than 250 natural materials. Our proposed features significantly outperform leading alternatives including Local Binary Patterns (LBP, LBP-HF) and texton MR8 methods.     

Microgimbal torsion beam design using open, thin-walled crosssections

A thin-film micromolding process enabled the construction of microtorsional springs with unique cross-sectional designs by combining high-aspect-ratio beams with horizontal surface features. Cross sections such as T-bars, pi sections, and channels were utilized in creating torsional springs with low torsional stiffnesses and high in- and out-of-plane bending stiffnesses. Experimental modal analysis was used to determine torsional stiffnesses as low as 0.13 μN·m/deg with T-bar springs 45 μm tall, 50 μm wide, and 100 μm long. Springs of the same outer dimensions but with solid rectangular cross sections were calculated to have torsional stiffnesses of at least two orders of magnitude greater. Several microgimbals were constructed using the thin-film micromolding process with various torsional spring designs. Modal analysis was used to experimentally determine pitch and roll natural frequencies. Torsional stiffness models for open, thin-walled sections that included warping effects were developed and used to analytically predict the torsional natural frequencies of tested spring designs to within 20%     

High-aspect-ratio, molded microstructures with electrical isolation and embedded interconnects

 A thin film molding process was developed to enable the fabrication of monolithic micromechanical structures with built-in electrical isolation and embedded interconnects. High-aspect-ratio composite structures were created from undoped polysilicon, low stress nitride and doped polysilicon, in a dual micromolding process. These monolithic electro-mechanical microstructures are more resistant to thermal effects and misalignment errors compared to microsystems assembled from discrete elements. In addition, the microstructures are molded in a re-usable mold providing an economical advantage. A gimballed electrostatic microactuator was successfully fabricated using this process. Electrical isolation was achieved with a combination of low stress nitride and undoped polycrystalline silicon. Various isolation geometries were investigated. Current leakages of less than 1 nA at 30 V were measured for isolation structures 40 μm long and 80 μm tall. Received: 13 November 2000/Accepted: 16 November 2000     

The Shopping Jacket: Wearable computing for the consumer

As part of the Bristol Wearable Computing Initiative, we are exploring location-sensing systems suitable for use with wearable computing. In this paper we present our findings, and in particular a wearable application — the ‘Shopping Jacket’ — which relies on a minimal infrastructure to be effective. We use two positioning devices, ‘pingers’ and GPS. The pinger is used to signal the presence of a shop, and to indicate the type of shop and its website. The GPS is used to disambiguate which branch of a high street chain is being passed. The wearable uses this information to determine whether the wearer needs to be alerted that they are passing an interesting shop, or to direct the wearer around a shopping mall. The Shopping Jacket integrates a wearable CardPC, GPS and pinger receivers, a near-field radio link, hand-held display, GSM data telephone and a speech interface into a conventional sports blazer.     

Progressively weighted affine adaptive correlation matching for quasi-dense 3D reconstruction

Correlation matching has been widely accepted as a rudimentary similarity measure to obtain dense 3D reconstruction from a stereo pair. In particular, given a large overlapping area between images with minimal scale differences, the correlation results followed by a geometrically constrained global optimisation delivers adequately dense and accurate reconstruction results. In order to achieve greater reliability, however, correlation matching should correctly account for the geometrical distortion introduced by the different viewing angles of the stereo or multi-view sensors. Conventional adaptive least squares correlation (ALSC) matching addresses this by modifying the shape of a matching window iteratively, assuming that the distortion can be approximated by an affine transform. Nevertheless, since an image captured from different viewing angle is often not practically identical due to scene occlusions, the matching confidence normally deteriorates. Subsequently, it affects the density of the reconstruction results from ALSC-based stereo region growing algorithms. To address this, we propose an advanced ALSC matching method that can progressively update matching weight for each pixel in an aggregating window using a relaxation labelling technique. The experimental results show that the proposed method can improve matching performance, which consequently enhances the quality of stereo reconstruction. Also, the results demonstrate its ability to refine a scale invariant conjugate point pair to an affine and scale invariant point pair.     

Synthesis and characterization of ET(P)S-4 and ET(P)S-10

Phosphorus containing ET(P)S-4 and ET(P)S-10 were synthesized from gels of composition xNa₂O–0.6KF–0.2TiO₂–(1.28 − 4y)xHCl–yP₂O₅–1.49SiO₂–39.5H₂O at 190 °C for 3 days. The XRD patterns are almost identical to the corresponding ETS samples. The presence of phosphorus in the initial gel influences the kinetic parameters of the crystallization process, the morphology and the size of the crystals. The ³¹P-NMR of the samples show that part of the phosphorus is attached at the siliceous surface as dihydrogenophosphate SiOPO(OH)₂ groups and cannot be introduced in a tetrahedral or octahedral framework position.