Investigation of a Rotating Shaft with a Novel Integrated Wireless Accelerometer

Rotating shafts are the most critical components of rotating machines such as motors, pumps, engines and turbines. Due to their heavy workloads, defects are more likely to develop during operation. There are many techniques used to monitor shaft defects by analysing the vibration of the shaft as well as the instantaneous angular speed (IAS) of the shaft. The signals are measured either using non-contact techniques such as laser-based measurement or indirect measurement such as the vibration on bearing housings. The advancement in low cost and low power Micro Electro Mechanical Systems (MEMS) make it possible to develop an integrated wireless sensor mounted on rotating shafts directly. This can make the fault diagnosis of rotating shafts more effective as it is likely to capture more details of shaft dynamics. This paper presents a novel integrated wireless accelerometer mounted directly on a rotating shaft and demonstrates that it can effectively monitor different degree of misalignments occurring commonly in a shaft system

Superior memory efficiency of quantum devices for the simulation of continuous-time stochastic processes

Continuous-time stochastic processes pervade everyday experience, and the simulation of models of these processes is of great utility. Classical models of systems operating in continuous-time must typically track an unbounded amount of information about past behaviour, even for relatively simple models, enforcing limits on precision due to the finite memory of the machine. However, quantum machines can require less information about the past than even their optimal classical counterparts to simulate the future of discrete-time processes, and we demonstrate that this advantage extends to the continuous-time regime. Moreover, we show that this reduction in the memory requirement can be unboundedly large, allowing for arbitrary precision even with a finite quantum memory. We provide a systematic method for finding superior quantum constructions, and a protocol for analogue simulation of continuous-time renewal processes with a quantum machine.Comment: 13 pages, 8 figures, title changed from original versio

CNV and nervous system diseases - what's new?

Several new genomic disorders caused by copy number variation (CNV) of genes whose dosage is critical for the physiological function of the nervous system have been recently identified. Dup(7)(q11.23) patients carry duplications of the genomic region deleted in Williams-Beuren syndrome, they are characterized by prominent speech delay. The phenotypes of Potocki-Lupski syndrome and MECP2 duplication syndrome were neuropsychologically examined in detail, which revealed autism as an endophenotype and a prominent behavioral feature of these disorders. Tandem duplication of LMNB1 was reported to cause adult-onset autosomal dominant leukodystrophy. PAFAH1B1/LIS1 and YWHAE, which were deleted in isolated lissencephaly (PAFAH1B1/LIS1 alone) and Miller-Dieker syndrome (both genes), were found to be duplicated in patients with developmental delay. Finally, two novel microdeletion syndromes affecting 17q21.31 and 15q13.3, as well as their reciprocal duplications, were also identified. In this review, we provide an overview of the phenotypic manifestation of these syndromes and the rearrangements causing them. Copyright (C) 2009 S. Karger AG, Base

Glassy Dynamics in a Frustrated Spin System: Role of Defects

In an effort to understand the glass transition, the kinetics of a spin model with frustration but no quenched randomness has been analyzed. The phenomenology of the spin model is remarkably similiar to that of structural glasses. Analysis of the model suggests that defects play a major role in dictating the dynamics as the glass transition is approached.Comment: 9 pages, 5 figures, accepted in J. Phys.: Condensed Matter, proceedings of the Trieste workshop on "Unifying Concepts in Glass Physics

Active repositioning of storage units in Robotic Mobile Fulfillment Systems

In our work we focus on Robotic Mobile Fulfillment Systems in e-commerce distribution centers. These systems were designed to increase pick rates by employing mobile robots bringing movable storage units (so-called pods) to pick and replenishment stations as needed, and back to the storage area afterwards. One advantage of this approach is that repositioning of inventory can be done continuously, even during pick and replenishment operations. This is primarily accomplished by bringing a pod to a storage location different than the one it was fetched from, a process we call passive pod repositioning. Additionally, this can be done by explicitly bringing a pod from one storage location to another, a process we call active pod repositioning. In this work we introduce first mechanisms for the latter technique and conduct a simulation-based experiment to give first insights of their effect

Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation

Recently, X-ray imaging dose from computed tomography (CT) or cone beam CT (CBCT) scans has become a serious concern. Patient-specific imaging dose calculation has been proposed for the purpose of dose management. While Monte Carlo (MC) dose calculation can be quite accurate for this purpose, it suffers from low computational efficiency. In response to this problem, we have successfully developed a MC dose calculation package, gCTD, on GPU architecture under the NVIDIA CUDA platform for fast and accurate estimation of the x-ray imaging dose received by a patient during a CT or CBCT scan. Techniques have been developed particularly for the GPU architecture to achieve high computational efficiency. Dose calculations using CBCT scanning geometry in a homogeneous water phantom and a heterogeneous Zubal head phantom have shown good agreement between gCTD and EGSnrc, indicating the accuracy of our code. In terms of improved efficiency, it is found that gCTD attains a speed-up of ~400 times in the homogeneous water phantom and ~76.6 times in the Zubal phantom compared to EGSnrc. As for absolute computation time, imaging dose calculation for the Zubal phantom can be accomplished in ~17 sec with the average relative standard deviation of 0.4%. Though our gCTD code has been developed and tested in the context of CBCT scans, with simple modification of geometry it can be used for assessing imaging dose in CT scans as well.Comment: 18 pages, 7 figures, and 1 tabl