Stability Analysis of Piecewise Affine Systems with Multi-model Model Predictive Control

Constrained model predictive control (MPC) is a widely used control strategy, which employs moving horizon-based on-line optimisation to compute the optimum path of the manipulated variables. Nonlinear MPC can utilize detailed models but it is computationally expensive; on the other hand linear MPC may not be adequate. Piecewise affine (PWA) models can describe the underlying nonlinear dynamics more accurately, therefore they can provide a viable trade-off through their use in multi-model linear MPC configurations, which avoid integer programming. However, such schemes may introduce uncertainty affecting the closed loop stability. In this work, we propose an input to output stability analysis for closed loop systems, consisting of PWA models, where an observer and multi-model linear MPC are applied together, under unstructured uncertainty. Integral quadratic constraints (IQCs) are employed to assess the robustness of MPC under uncertainty. We create a model pool, by performing linearisation on selected transient points. All the possible uncertainties and nonlinearities (including the controller) can be introduced in the framework, assuming that they admit the appropriate IQCs, whilst the dissipation inequality can provide necessary conditions incorporating IQCs. We demonstrate the existence of static multipliers, which can reduce the conservatism of the stability analysis significantly. The proposed methodology is demonstrated through two engineering case studies.Comment: 28 pages 9 figure

Automated Dynamic Resource Provisioning and Monitoring in Virtualized Large-Scale Datacenter

Infrastructure as a Service (IaaS) is a pay-as-you go based cloud provision model which on demand outsources the physical servers, guest virtual machine (VM) instances, storage resources, and networking connections. This article reports the design and development of our proposed innovative symbiotic simulation based system to support the automated management of IaaS-based distributed virtualized data enter. To make the ideas work in practice, we have implemented an Open Stack based open source cloud computing platform. A smart benchmarking application "Cloud Rapid Experimentation and Analysis Tool (aka CBTool)" is utilized to mark the resource allocation potential of our test cloud system. The real-time benchmarking metrics of cloud are fed to a distributed multi-agent based intelligence middleware layer. To optimally control the dynamic operation of prototype data enter, we predefine some custom policies for VM provisioning and application performance profiling within a versatile cloud modeling and simulation toolkit "CloudSim". Both tools for our prototypes' implementation can scale up to thousands of VMs, therefore, our devised mechanism is highly scalable and flexibly be interpolated at large-scale level. Autonomic characteristics of agents aid in streamlining symbiosis among the simulation system and IaaS cloud in a closed feedback control loop. The practical worth and applicability of the multiagent-based technology lies in the fact that this technique is inherently scalable hence can efficiently be implemented within the complex cloud computing environment. To demonstrate the efficacy of our approach, we have deployed an intelligible lightweight representative scenario in the context of monitoring and provisioning virtual machines within the test-bed. Experimental results indicate notable improvement in the resource provision profile of virtualized data enter on incorporating our proposed strategy

On the Use of Neural Text Generation for the Task of Optical Character Recognition

Optical Character Recognition (OCR), is extraction of textual data from scanned text documents to facilitate their indexing, searching, editing and to reduce storage space. Although OCR systems have improved significantly in recent years, they still suffer in situations where the OCR output does not match the text in the original document. Deep learning models have contributed positively to many problems but their full potential to many other problems are yet to be explored. In this paper we propose a post-processing approach based on the application deep learning to improve the accuracy of OCR system (minimizing the error rate).We report on the use of neural network language models to accomplish the task of correcting incorrectly predicted characters/words by OCR systems. We applied our approach to the IAM handwriting database. Our proposed approach delivers significant accuracy improvement of 20:41% in F-score, 10:86% in character level comparison using Levenshtein distance and 20:69% in document level comparison over previously reported context based OCR empirical results of IAM handwriting database

Sleep in Frontotemporal Dementia is Equally or Possibly More Disrupted, and at an Earlier Stage, When Compared to Sleep in Alzheimer's Disease

Background: Conversely to other neurodegenerative diseases (i.e., Alzheimer's disease, AD), sleep in frontotemporal dementia (FTD) has not been studied adequately. Although some evidence exists that sleep-wake disturbances occur in FTD, very little is known regarding sleep macrostructure and/or primary sleep disorders. Objective: To investigate these issues in this population and compare them to similar issues in AD and in healthy elderly (HE). Methods: Twelve drug-naïve behavioral-variant FTD (bvFTD) patients (7 men/5 women) of mean age 62.5 ± 8.6 years were compared to seventeen drug-naïve AD patients (9 men/8 women) of mean age 69.0 ± 9.9 years and twenty drug-naïve HE (12 men/8 women) of mean age 70.2 ± 12.5 years. All participants were fully assessed clinically, through a sleep questionnaire, an interview, and video-polysomnography recordings. Results: The two patient groups were comparably cognitively impaired. However, compared to FTD patients, the AD patients had a statistically significant longer disease duration. Overall, the sleep profile was better preserved in HE. Sleep complaints did not differ considerably between the two patient groups. Sleep parameters and sleep macrostructure were better preserved in AD compared to FTD patients, regardless of primary sleep disorders, which occurred equally in the two groups. Conclusions: With respect to AD, FTD patients had several sleep parameters similarly or even more affected by neurodegeneration, but in a much shorter time span. The findings probably indicate a centrally originating sleep deregulation. Since in FTD patients sleep disturbances may be obvious from an early stage of their disease, and possibly earlier than in AD patients, physicians and caregivers should be alert for the early detection and treatment of these symptoms

Fate of the Aortic Arch Following Surgery on Aortic Root and Ascending Aorta in Bicuspid Aortic Valve.

BACKGROUND: Recent guidelines support more aggressive surgery for aneurysms of the ascending aorta and root in patients with bicuspid aortic valve. However, the fate of the arch after surgery of the root and ascending aorta is unknown. We set out to assess outcomes following root and ascending aortic surgery and subsequent growth of the arch. METHODS: Between 2005 and 2016, 536 consecutive patients underwent surgery for aneurysm of the root and ascending aorta. 168 had bicuspid aortic valve. Patients with dissection were excluded. Arch diameter was measured before and after surgery, at six months and then annually. RESULTS: Of 168 patients, 127 (75.6%) had aortic root replacement and 41 (24.4%) had ascending replacement. Mean age was 57±12.8 years, 82.7% were males and five operations were performed during pregnancy. There was one (0.6%) hospital death. One (0.6%) patient had a stroke and one (0.6%) had re-sternotomy for bleeding. Median ICU and hospital stays were 1 and 6 days respectively. Follow-up was complete for 94% at a median of 5.9 years (1-139 months). Aortic arch diameter was 2.9 cm preoperatively and 3.0 cm at follow-up. There was 97% freedom from reoperation and none of the patients required surgery on the arch. CONCLUSIONS: Prophylactic arch replacement during aortic root and ascending aortic surgery in patients with bicuspid aortic valve is not supported. Our data does not support long term surveillance of the rest of the aorta in this population

Biofabrication of customized bone grafts by combination of additive manufacturing and bioreactor knowhow

This study reports on an original concept of additive manufacturing for the fabrication of tissue engineered constructs (TEC), offering the possibility of concomitantly manufacturing a customized scaffold and a bioreactor chamber to any size and shape. As a proof of concept towards the development of anatomically relevant TECs, this concept was utilized for the design and fabrication of a highly porous sheep tibia scaffold around which a bioreactor chamber of similar shape was simultaneously built. The morphology of the bioreactor/scaffold device was investigated by micro-computed tomography and scanning electron microscopy confirming the porous architecture of the sheep tibiae as opposed to the non-porous nature of the bioreactor chamber. Additionally, this study demonstrates that both the shape, as well as the inner architecture of the device can significantly impact the perfusion of fluid within the scaffold architecture. Indeed, fluid flow modelling revealed that this was of significant importance for controlling the nutrition flow pattern within the scaffold and the bioreactor chamber, avoiding the formation of stagnant flow regions detrimental for in vitro tissue development. The bioreactor/scaffold device was dynamically seeded with human primary osteoblasts and cultured under bi-directional perfusion for two and six weeks. Primary human osteoblasts were observed homogenously distributed throughout the scaffold, and were viable for the six week culture period. This work demonstrates a novel application for additive manufacturing in the development of scaffolds and bioreactors. Given the intrinsic flexibility of the additive manufacturing technology platform developed, more complex culture systems can be fabricated which would contribute to the advances in customized and patient-specific tissue engineering strategies for a wide range of applications.This work was supported by the NHMRC, the Australian Research Council and Hans Fischer Senior Fellowship, IAS-TUM. Pedro Costa acknowledges the Portuguese Foundation for Science and Technology for his PhD grant (SFRH/BD/62452/2009)