Investigation into scalable energy and performance models for many-core systems

PhD ThesisIt is likely that many-core processor systems will continue to penetrate emerging embedded and high-performance applications. Scalable energy and performance models are two critical aspects that provide insights into the conflicting trade-offs between them with growing hardware and software complexity. Traditional performance models, such as Amdahl’s Law, Gustafson’s and Sun-Ni’s, have helped the research community and industry to better understand the system performance bounds with given processing resources, which is otherwise known as speedup. However, these models and their existing extensions have limited applicability for energy and/or performance-driven system optimization in practical systems. For instance, these are typically based on software characteristics, assuming ideal and homogeneous hardware platforms or limited forms of processor heterogeneity. In addition, the measurement of speedup and parallelization factors of an application running on a specific hardware platform require instrumenting the original software codes. Indeed, practical speedup and parallelizability models of application workloads running on modern heterogeneous hardware are critical for energy and performance models, as they can be used to inform design and control decisions with an aim to improve system throughput and energy efficiency. This thesis addresses the limitations by firstly developing novel and scalable speedup and energy consumption models based on a more general representation of heterogeneity, referred to as the normal form heterogeneity. A method is developed whereby standard performance counters found in modern many-core platforms can be used to derive speedup, and therefore the parallelizability of the software, without instrumenting applications. This extends the usability of the new models to scenarios where the parallelizability of software is unknown, leading to potentially Run-Time Management (RTM) speedup and/or energy efficiency optimization. The models and optimization methods presented in this thesis are validated through extensive experimentation, by running a number of different applications in wide-ranging concurrency scenarios on a number of different homogeneous and heterogeneous Multi/Many Core Processor (M/MCP) systems. These include homogeneous and heterogeneous architectures and viii range from existing off-the-shelf platforms to potential future system extensions. The practical use of these models and methods is demonstrated through real examples such as studying the effectiveness of the system load balancer. The models and methodologies proposed in this thesis provide guidance to a new opportunities for improving the energy efficiency of M/MCP systemsHigher Committee of Education Development (HCED) in Ira

Technical Report on Deploying a highly secured OpenStack Cloud Infrastructure using BradStack as a Case Study

Cloud computing has emerged as a popular paradigm and an attractive model for providing a reliable distributed computing model.it is increasing attracting huge attention both in academic research and industrial initiatives. Cloud deployments are paramount for institution and organizations of all scales. The availability of a flexible, free open source cloud platform designed with no propriety software and the ability of its integration with legacy systems and third-party applications are fundamental. Open stack is a free and opensource software released under the terms of Apache license with a fragmented and distributed architecture making it highly flexible. This project was initiated and aimed at designing a secured cloud infrastructure called BradStack, which is built on OpenStack in the Computing Laboratory at the University of Bradford. In this report, we present and discuss the steps required in deploying a secured BradStack Multi-node cloud infrastructure and conducting Penetration testing on OpenStack Services to validate the effectiveness of the security controls on the BradStack platform. This report serves as a practical guideline, focusing on security and practical infrastructure related issues. It also serves as a reference for institutions looking at the possibilities of implementing a secured cloud solution.Comment: 38 pages, 19 figures

Detection and segmentation the affected brain using ThingSpeak platform based on IoT cloud analysis

The world has accelerated around a new industrial revolution called the Internet of Things, as this technology is expected to enter all aspects of industrial life, commercial and civil applications. The Internet of Things stands for highly important applications in the world of medical applications, which is the access to linking all medical clinics in the world into a single network capable of analyzing patient data and presenting it to medical professionals anywhere in the world. One of the medical applications in the Internet of Things is the discovery of a healthy human brain. This work proposes a health care system based on medical image analysis processes in the programmable ThingSpeak platform using MATLAB built into the platform within the cloud. The analysis is done using the MATLAB program within the Windows operating system and then the analysis is performed within ThingSpeak platform. The analysis includes classification process by using SVM classifier linear kernel in which we achieved 99.4% classification rate as well as using RBF kernel, which achieved 98.6% classification accuracy in classifying infected brains from healthy ones and the work was supported by cross validation technology to ensure effective classification accuracy. The patient brain is segmented then the tumor segment is isolated, its area is calculated, and the tumor boundaries are found, based on the k-mean technique, to support the specialist doctor when performing the analysis process in the cloud environment. Through this work we achieved a match in the analysis processes within the local environment, and ThingSpeak platform environment by 100%, and in order to support our work, we have automated the analysis, visualization and data transfer processes within the cloud and MATLAB environment

Intelligent and secure real-time auto-stop car system using deep-learning models

In this study, we introduce an innovative auto-stop car system empowered by deep learning technology, specifically employing two Convolutional Neural Networks (CNNs) for face recognition and travel drowsiness detection. Implemented on a Raspberry Pi 4, our system is designed to cater exclusively to certified drivers, ensuring enhanced safety through intelligent features. The face recognition CNN model accurately identifies authorized drivers, employing deep learning techniques to verify their identity before granting access to vehicle functions. This first model demonstrates a remarkable accuracy rate of 99.1%, surpassing existing solutions in secure driver authentication. Simultaneously, our second CNN focuses on real-time detecting+ of driver drowsiness, monitoring eye movements, and utilizing a touch sensor on the steering wheel. Upon detecting signs of drowsiness, the system issues an immediate alert through a speaker, initiating an emergency park and sending a distress message via Global Positioning System (GPS). The successful implementation of our proposed system on the Raspberry Pi 4, integrated with a real-time monitoring camera, attains an impressive accuracy of 99.1% for both deep learning models. This performance surpasses current industry benchmarks, showcasing the efficacy and reliability of our solution. Our auto-stop car system advances user convenience and establishes unparalleled safety standards, marking a significant stride in autonomous vehicle technology

ASSOCIATION BETWEEN TOXOPLASMA GONDII INFECTION IN WOMEN AND THE PRESENCE OF CARDIOLIPIN AND PHOSPHOLIPID ANTIBODIES

IgG and IgM cardiolipin and phospholipid antibodies were measured, by an ELISA technique, in the sera of patients with toxoplasmosis. Immunological methods for autoantibodies had been applied by ELISA. Regarding Anti-cardiolipin it was revealed that 24.7% of toxoplasmosis cases versus 0% of control group showed significant positive result (P=0.0412) . Whereas, 12.5% of toxoplasmosis patients and 12% of healthy controls had anti-cardiolipin antibodies, with no significant differences (P=0.554) between these two groups

Does primary brachial plexus surgery alter palliative tendon transfer surgery outcomes in children with obstetric paralysis?

<p>Abstract</p> <p>Background</p> <p>The surgical management of obstetrical brachial plexus palsy can generally be divided into two groups; early reconstructions in which the plexus or affected nerves are addressed and late or palliative reconstructions in which the residual deformities are addressed. Tendon transfers are the mainstay of palliative surgery. Occasionally, surgeons are required to utilise already denervated and subsequently reinnervated muscles as motors. This study aimed to compare the outcomes of tendon transfers for residual shoulder dysfunction in patients who had undergone early nerve surgery to the outcomes in patients who had not.</p> <p>Methods</p> <p>A total of 91 patients with obstetric paralysis-related shoulder abduction and external rotation deficits who underwent a modified Hoffer transfer of the latissimus dorsi/teres major to the greater tubercle of the humerus tendon between 2002 and 2009 were retrospectively analysed. The patients who had undergone neural surgery during infancy were compared to those who had not in terms of their preoperative and postoperative shoulder abduction and external rotation active ranges of motion.</p> <p>Results</p> <p>In the early surgery groups, only the postoperative external rotation angles showed statistically significant differences (25 degrees and 75 degrees for total and upper type palsies, respectively). Within the palliative surgery-only groups, there were no significant differences between the preoperative and postoperative abduction and external rotation angles. The significant differences between the early surgery groups and the palliative surgery groups with total palsy during the preoperative period diminished postoperatively (p < 0.05 and p > 0.05, respectively) for abduction but not for external rotation. Within the upper type palsy groups, there were no significant differences between the preoperative and postoperative abduction and external rotation angles.</p> <p>Conclusions</p> <p>In this study, it was found that in patients with total paralysis, satisfactory shoulder abduction values can be achieved with tendon transfers regardless of a previous history of neural surgery even if the preoperative values differ.</p

Saudi-KAU Coupled Global Climate Model: Description and Performance

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Postoperative outcomes in oesophagectomy with trainee involvement

BACKGROUND: The complexity of oesophageal surgery and the significant risk of morbidity necessitates that oesophagectomy is predominantly performed by a consultant surgeon, or a senior trainee under their supervision. The aim of this study was to determine the impact of trainee involvement in oesophagectomy on postoperative outcomes in an international multicentre setting. METHODS: Data from the multicentre Oesophago-Gastric Anastomosis Study Group (OGAA) cohort study were analysed, which comprised prospectively collected data from patients undergoing oesophagectomy for oesophageal cancer between April 2018 and December 2018. Procedures were grouped by the level of trainee involvement, and univariable and multivariable analyses were performed to compare patient outcomes across groups. RESULTS: Of 2232 oesophagectomies from 137 centres in 41 countries, trainees were involved in 29.1 per cent of them (n = 650), performing only the abdominal phase in 230, only the chest and/or neck phases in 130, and all phases in 315 procedures. For procedures with a chest anastomosis, those with trainee involvement had similar 90-day mortality, complication and reoperation rates to consultant-performed oesophagectomies (P = 0.451, P = 0.318, and P = 0.382, respectively), while anastomotic leak rates were significantly lower in the trainee groups (P = 0.030). Procedures with a neck anastomosis had equivalent complication, anastomotic leak, and reoperation rates (P = 0.150, P = 0.430, and P = 0.632, respectively) in trainee-involved versus consultant-performed oesophagectomies, with significantly lower 90-day mortality in the trainee groups (P = 0.005). CONCLUSION: Trainee involvement was not found to be associated with significantly inferior postoperative outcomes for selected patients undergoing oesophagectomy. The results support continued supervised trainee involvement in oesophageal cancer surgery

A novel bioactive glass/graphene oxide composite coating for a polyether ether ketone-based dental implant.

Polyether ether ketone (PEEK) is a biocompatible material that lacks antimicrobial activity and bioactivity; therefore, is not appropriate for use as a dental implant. To overcome these deficiencies, a novel composite coating of bioactive glass and graphene oxide was prepared. PEEK discs were polished, cleaned, and the surface treated with sulfuric acid for 15 min. The composite coating consisted of bioactive glass produced by the sol-gel route and doped with 0.75 wt% graphene oxide. X-ray diffraction, Fourier transform infrared spectroscopy, and scanning electron microscopy-energy dispersive spectroscopy analyses were employed to characterize the composite coating, and the coating adhesion strength quantified using a pull-off test. Cytotoxicity was assessed using osteoblast-like cells and gingival fibroblasts. The wettability of the coated and non-coated samples was determined by optical contact angle assessment, and bioactivity was assessed by immersion in simulated body fluid. The results revealed that the bioactive glass/graphene oxide composite coating, approximately 7 μm thick, was transparent, homogenous with few microcracks and microporosities, but adhered strongly and was not cytotoxic to either osteoblast-like cells or gingival fibroblasts. The wettability of the PEEK sample was increased to <20° after coating with the composite, and apatite formation was detectable after 14 days of immersion in simulated body fluid