High Sensitivity,Wearable, Piezoresistive Pressure Sensors Based on Irregular Microhump Structures and Its Applications in Body Motion Sensing

A pressure sensor based on irregular microhump patterns has been proposed and developed. The devices show high sensitivity and broad operating pressure regime while comparing with regular micropattern devices. Finite element analysis (FEA) is utilized to confirm the sensing mechanism and predict the performance of the pressure sensor based on the microhump structures. Silicon carbide sandpaper is employed as the mold to develop polydimethylsiloxane (PDMS) microhump patterns with various sizes. The active layer of the piezoresistive pressure sensor is developed by spin coating PEDOT:PSS on top of the patterned PDMS. The devices show an averaged sensitivity as high as 851 kPa^?1, broad operating pressure range (20 kPa), low operating power (100 nW), and fast response speed (6.7 kHz). Owing to their flexible properties, the devices are applied to human body motion sensing and radial artery pulse. These flexible high sensitivity devices show great potential in the next generation of smart sensors for robotics, real‐time health monitoring, and biomedical applications.     

MINING SURPRISING PATTERNS AND THEIR EXPLANATIONS IN CLINICAL DATA

□ We present a new technique for interactively mining patterns and generating explanations by harnessing the expertise of domain experts. Key to the approach is the distinction between what is unexpected from the perspective of the computational data mining process and what is surprising to the domain experts and interesting relative to their needs. We demonstrate the potential of the approach for discovering patterns and generating rich explanations in a clinical domain. Discovering interesting facts in clinical data is a grand challenge, because medical practitioners and clinicians generally have exceptional knowledge in the problem domain in which they work, however, this knowledge is typically difficult to isolate computationally. To identify the desired surprising patterns, we formally record user knowledge and use that knowledge to filter and constrain the output from an objective data mining technique, with the user making the final judgement about whether a rule is surprising. Specifically, we introduce an unexpectedness algorithm based on association rule mining and Bayesian Networks and a ?-explanations technique for explanation generation to identify unexpected patterns. An implemented prototype is successfully demonstrated using a large clinical database recording incidence, prevalance, and outcome of dialysis and kidney transplant patients.     

3D Scene Reconstruction from Multiple Spherical Stereo Pairs

We propose a 3D environment modelling method using multiple pairs of high-resolution spherical images. Spherical images of a scene are captured using a rotating line scan camera. Reconstruction is based on stereo image pairs with a vertical displacement between camera views. A 3D mesh model for each pair of spherical images is reconstructed by stereo matching. For accurate surface reconstruction, we propose a PDE-based disparity estimation method which produces continuous depth fields with sharp depth discontinuities even in occluded and highly textured regions. A full environment model is constructed by fusion of partial reconstruction from spherical stereo pairs at multiple widely spaced locations. To avoid camera calibration steps for all camera locations, we calculate 3D rigid transforms between capture points using feature matching and register all meshes into a unified coordinate system. Finally a complete 3D model of the environment is generated by selecting the most reliable observations among overlapped surface measurements considering surface visibility, orientation and distance from the camera. We analyse the characteristics and behaviour of errors for spherical stereo imaging. Performance of the proposed algorithm is evaluated against ground-truth from the Middlebury stereo test bed and LIDAR scans. Results are also compared with conventional structure-from-motion algorithms. The final composite model is rendered from a wide range of viewpoints with high quality textures.     

On the lower bound of monitor solutions of maximally permissive supervisors for a subclass α-S3PR of flexible manufacturing systems

Recently, a novel and computationally efficient method – based on a vector covering approach – to design optimal control places and an iteration approach that computes the reachability graph to obtain a maximally permissive liveness enforcing supervisor for FMS (flexible manufacturing systems) have been reported. However, it is unclear as to the relationship between the structure of the net and the minimal number of monitors required. This paper develops a theory to show that the minimal number of monitors required cannot be less than that of basic siphons in α-S³PR (systems of simple sequential processes with resources). This confirms that two of the three controlled systems by Chen et al. are of a minimal monitor configuration since they belong to α-S³PR and their number in each example equals that of basic siphons.     

GLL parse-tree generation

Backtracking techniques which are often used to extend recursive descent (RD) parsers can have explosive run-times and cannot deal with grammars with left recursion. GLL parsers are fully general, worst-case cubic parsers which have the recursive descent-like property that they are easy to write and to use for grammar debugging. They have the direct relationship with the grammar that an RD parser has. In this paper we give an algorithm for generating GLL parsers which build an SPPF representation of the derivations of the input, complementing our existing GLL recognition algorithm, and we show that such parsers and recognisers are worst-case cubic.     

Structure of weakly 2-dependent siphons

Deadlocks arising from insufficiently marked siphons in flexible manufacturing systems can be controlled by adding monitors to each siphon – too many for large systems. Li and Zhou add monitors to elementary siphons only while controlling the rest of (called dependent) siphons by adjusting control depth variables of elementary siphons. Only a linear number of monitors are required. The control of weakly dependent siphons (WDSs) is rather conservative since only positive terms were considered. The structure for strongly dependent siphons (SDSs) has been studied earlier. Based on this structure, the optimal sequence of adding monitors has been discovered earlier. Better controllability has been discovered to achieve faster and more permissive control. The results have been extended earlier to S³PGR² (systems of simple sequential processes with general resource requirements). This paper explores the structures for WDSs, which, as found in this paper, involve elementary resource circuits interconnecting at more than (for SDSs, exactly) one resource place. This saves the time to compute compound siphons, their complementary sets and T-characteristic vectors. Also it allows us (1) to improve the controllability of WDSs and control siphons and (2) to avoid the time to find independent vectors for elementary siphons. We propose a sufficient and necessary test for adjusting control depth variables in S³PR (systems of simple sequential processes with resources) to avoid the sufficient-only time-consuming linear integer programming test (LIP) (Nondeterministic Polynomial (NP) time complete problem) required previously for some cases.     

Design of an integrated UWB antenna with dual band notch characteristics

A miniaturized couple-line-fed planar ultra-wideband (UWB) antenna is proposed, which has a dual band-notched characteristic as well as two integrated monopoles. Narrowband notches are generated at frequencies of 3.5 GHz and 5.5 GHz using independently controlled bent resonators, whereas the monopoles are designed for radiation at 900 MHz and 2.4 GHz. The proposed design is simulated with full wave solvers and verified with measurements. A good agreement is observed between the simulations and measurements for the antenna's return loss, gain and radiation pattern performances.     

Critical superparamagnetic/single-domain grain sizes in interacting magnetite particles: implications for magnetosome crystals

Magnetotactic bacteria contain chains of magnetically interacting crystals (magnetosome crystals), which they use for navigation (magnetotaxis). To improve magnetotaxis efficiency, the magnetosome crystals (usually magnetite or greigite in composition) should be magnetically stable single-domain (SSD) particles. Smaller single-domain particles become magnetically unstable owing to thermal fluctuations and are termed superparamagnetic (SP). Previous calculations for the SSD/SP threshold size or blocking volume did not include the contribution of magnetic interactions. In this study, the blocking volume has been calculated as a function of grain elongation and separation for chains of identical magnetite grains. The inclusion of magnetic interactions was found to decrease the blocking volume, thereby increasing the range of SSD behaviour. Combining the results with previously published calculations for the SSD to multidomain threshold size in chains of magnetite reveals that interactions significantly increase the SSD range. We argue that chains of interacting magnetosome crystals found in magnetotactic bacteria have used this effect to improve magnetotaxis.