178 research outputs found
Correction: Guidelines for the prevention, detection and management of the renal complications of COVID-19 in Africa
No full textThe authors of the article ‘Guidelines for the prevention, detection and management of the renal complications of COVID-19 in Africa’ [1] wish to acknowledge the contribution of Professor Hussein El Fishawy. Our guidelines drew on various sources, including the Egyptian Ministry of Health guidelines, portions of which were adapted and reproduced with permission from the Egyptian Ministry of Health. Two of the authors of those guidelines, Professors Elsayed and Zaki, are also coauthors of our paper. Professor El Fishawy was the third author of the Egyptian guidelines and we would like to acknowledge his contribution to our review through this source, especially with respect to the treatment algorithms for patients with kidney transplants and those with acute kidney injury. Reference1. Elsayed HM, Wadee S, Zaki MS, Were AJO, Ashuntantang GE, Bamgboye EL, et al. Guidelines for the prevention, detection and management of the renal complications of COVID-19 in Africa. Afr J Nephrol. 2020; 23(1):109-126
Représentations littéraires du sacré dans le roman maghrébin de langue française
No full textThis interdisciplinary study explores how Driss Chraïbi’s L’Homme du Livre (1995), Assia Djebar’s Loin de Médine (1991), and Anissa Boumediène’s La fin d’un monde (1991) present accounts of particular historical moments in early Islam. This study explores the role of the imagination as well as freedom of invention when reconstructing historical events. It engages the novels through a study of the interplay between the literary text and the sources and traditions that impact and shape the text narrative. Gaining direct access to the original sources in Arabic serves to analyze how religious and early historical materials are considered in and reflected by the fictional texts. Because the sources tend to differ in both content and approach, this study examines their preoccupations in order to determine the criteria of selection applied by each novelist.Ph.D.Includes bibliographical referencesIncludes vitaby Hanan Elsaye
Intrathecal Drug Delivery Systems Survey: Trends in Utilization in Pain Practice [Corrigendum]
No full textAbd-Sayed A, Fiala K, Weisbein J, et al. J Pain Res. 2022;15:1305–1314.
The authors have advised there is an error in the author list on page 1305. The author name “Alaa Abd-Sayed” should read “Alaa Abd-Elsayed”.
The authors apologize for this error
Degradation modeling of ink fading and diffusion of printed images
No full textColor printing plays an important role in the modern society. It is known that the color of printed images degrades gradually due to the fading and diffusion of the inks. Color degradation leads to a distortion or loss of the original information in printed images. Therefore, it is desirable to understand how the color of printed images changes over time. In this dissertation, we present degradation models to predict the characteristics of the ink fading and diffusion of printed images.
We begin by modeling the ink degradation from a physics-based perspective. Color images are printed by projecting small ink dots on medium, usually paper. This technique is called halftone printing. Halftone printing of color images results in a variety of ink mixtures and subsequently their potential catalytic fading. For the most commonly used Cyan-Magenta-Yellow-Black (CMYK) ink set, sixteen possible ink mixtures are generated during printing. A state transition diagram is then proposed for the ink fading in this multi-ink printing scenario. The ink area coverage is used as the performance indicator. Assuming constant fading and diffusion rates, we develop an ink fading model based on the differential equations according to the state transition diagram and an autoregressive ink diffusion model by discretizing the two-dimensional diffusion equation. The two models are then integrated into a single degradation model.
Further examination of the developed degradation models reveals that the fading or diffusion rate is equivalent to the hazard rate in reliability engineering. It is known that the hazard rate of the exponential failure time distribution is constant. Hence, the developed degradation model with constant fading and diffusion rates is equivalent to the multistate Markov process model with exponential transition time distribution. By using non-exponential transition time distributions, the fading and diffusion rates become time-varying and a more general semi-Markov process degradation model is developed accordingly.
Moreover, stochastic process models are investigated to provide stochastic area coverage prediction for the ink degradation. We first model the ink fading using the Hull-White/Vasicek (HWV) stochastic process. The HWV ink fading model considers that the variance of the ink area coverage shrinks as it approaches zero. Besides, spatial convolution is used to model ink diffusion. The two models are integrated into a spatio-temporal stochastic degradation model for the ink fading and diffusion of printed images. The cases of recurrent and non-recurrent time-varying fading and diffusion rates are investigated.
Inks on the paper degrade, so does the paper. The degradation of paper condition may in turn affect the degradation of the inks. Therefore, the investigation of the degradation modeling of ink fading and ink diffusion with ink-paper interactions is needed. Two aspects of the ink-paper interactions are considered, i.e., the effect of paper aging such as depolymerization and yellowing, and the fiber orientation of the paper.
The degradation process of printed images usually takes a very long time. An accelerated degradation model and the optimal design of accelerated degradation test planning is developed for accurate degradation prediction of printed images. The effects of three constant environmental stresses: temperature, humidity, and illumination (intensity), are investigated, and experimental data are used to validate the proposed model. The results show strong agreements between the proposed ink fading and ink diffusion prediction model and the actual experimental data.Ph.D.Includes bibliographical reference
Reliability estimation of balanced systems with multi-dimensional distributed units
No full textBalanced systems with multi-dimensional distributed units are emerging in a diverse range of industries. This includes Unmanned Aerial Vehicles (UAV) with multi-level of rotary wings, Spherical Unmanned Vehicles (SUV), Spherical Phased Array Antenna (SPAA), etc. In this dissertation, we present the reliability estimation for such systems. In particular, we consider two configurations: 1) balanced systems with units distributed circularly on multi-level and 2) balanced systems with units distributed spherically.
First, balanced systems with units distributed circularly on multi-level are generalized as (k₁, k₂)-out-of-(n, m) pairs: G balanced systems. We consider two scenarios: 1) all units perform the same function and 2) adjacent pairs perform complementary functions. For both scenarios, unbalanced system is considered as failed. When units fail and cause the system imbalance, we explore two approaches to rebalance the system: 1) forcing down units on other locations and 2) resuming units that are previously forced down (if any). When units in a system perform the same function, operational states are defined as balanced states with at least k₁ operating pairs and each operating pair has at least k₂ units on each side. The system reliability is obtained by enumerating all of the operational states and summing the probabilities of those states. For (k₁, k₂)-out-of-(n, m) pairs: G balanced systems with adjacent pairs performing complementary functions, in addition to maintaining system balance, the adjacent operating pairs are required to perform complementary functions. Thus, if a pair fails, one of the adjacent pairs is forced down. Similarly, the system reliability is obtained by enumerating all of the operational states. It becomes computational expensive when the number of units in each pair and/or the number of pairs are large. In that case, efficient algorithms are developed to obtain the reliability for such systems.
The balanced system with units distributed spherically is generalized as a spherical k-n-i: G balanced system. We consider two balancing requirements: 1) rotational balance is maintained so that the system is not rotating w.r.t. roll, yaw and pitch axes and 2) symmetrical balance is essential in improving the systems’ stability. We present mathematical approaches to determine the balance status of a system. Similarly, the unbalanced system is rebalanced by 1) forcing down units on other locations and 2) resuming previously forced-down units. The system reliability is obtained by the enumeration of operational states and calculation of operational states’ probabilities. We develop an efficient algorithm for reliability estimation when the number of units in the system is large.
Degradation models are developed for the (k₁, k₂)-out-of-(n, m) pairs: G balanced systems to further investigate the system reliability when degradation data are available. The degradation processes of units in the system are either stationary (inverse Gaussian process) or non-stationary (improved inverse Gaussian process). We propose a degradation balance mechanism in which the ‘most’ degraded units are forced down temporarily during the degradation process so that the system is less possible to fail due to imbalance. A closed-form lower bound reliability is presented when the balance mechanism is not applied. When it is applied, reliability is obtained by Monte Carlo simulation.
From the reliability study of the both configurations, it is observed that the reliability of a balanced system with multi-dimensional distributed units depends not only on the system’s total number of units and the least number of operating units, but also on the system configurations and balance requirements. Systems with more units do not necessarily provide a higher reliability since they are more likely to fail due to imbalance. Thus, optimal system design is key to maximize the system reliability which is investigated through numerical examples in this dissertation.Ph.D.Includes bibliographical reference
Quantifying secondary particle dose contributions in proton therapy
No full textIn order to create radiotherapy treatment plans for cancer patients, dose calculations need to be done as quickly as possible to get accurate results. However, current dose calculation algorithms take too much time to be deployed effectively. The current in house algorithm of the Medical Physics and Technology Section at the TU Delft, attempts to solve this problem by utilising a deterministic algorithm that has a significant time advantage over Monte Carlo algorithms. However, this comes with the cost of inaccuracy, one of which is that it assumesall dose is deposited locally along the beam path. This is inaccurate as secondary particles created from non-elastic nuclear interactions can deposit their dose far from the beam path due to retaining significant kinetic energy. This thesis attempts to reduce this inaccuracy by mapping and quantifying the secondary particles to assess their contribution in non-local dose deposition. And analysing the relevant particle’s energy and angle distributions to gain insight into the development of the particle's characteristics with depth. Thereafter the relevantparticle’s are then utilised as a source to emulate their production in a primary proton beam at different depths to obtain the relevant 3D dose distributions. The analysis concluded that secondary protons are the most relevant secondary particle as they contribute to 88% of the secondary dose and have a significant range to deposit their dose non locally. By utilising the secondary protons as a source, it was found that the relative error between the integrated depth dose (IDD) of the scored protons and the IDD obtained directly from Monte Carlo simulations is equal to 5.1% in the z-direction and 3.4% in the x and y-direction. The absolute difference was found to be 1.54 × 10−5 Gy which is equal to 0.096% of the total dose and 2.75% of the dose contributed by all secondary particles. The results show that the methodology can produce accurate 3D dose matrices for secondary protons at different depths, which can then be used to improve the accuracy of the in house algorithm by adding the precalculated 3D dose matrices to the algorithmApplied Physic
The Impact of Low-Power Design Methodology on Digital Libraries
No full textIn recent years, exciting new low-power design methods have been introduced, such as: multiple supply voltages, body bias techniques and power shut-off. In order to use these low power design methods, strict requirements for both libraries and tools are needed. An additional challenge is the introduction of more accurate characterization models for newer technologies (current source models like ECSM and CCS). This has made the task of library checking a serious issue that needs to be automated. The main part of this thesis presents a checker tool that is used to verify the consistency of the different library formats (views) in standard cell libraries. The layout consistency checker in our tool checks the consistency of the layout of pins between GDSII and LEF library views; we devised a new algorithm,Grid Formation and Centre Inclusion, for this checker. The tool also verifies the pin consistency and availability of cells across other library formats, such as: Verilog and Liberty. The tool was tested using different technology libraries (such as 90nm and 40nm), provided by different vendors (such as GLOBALFOUNDRIES); multiple interfacing errors were caught using our library checker tool. A second part at the end of the thesis shows experiments with some of the low-power design techniques used during the design of a digital block, using -for implementation- standard cells from one of the libraries that have been checked with the library checker tool. Benefits of using these techniques are evaluated and trade-offs are discussed. Power-Shut Off (PSO) design technique proved to be the most effective in reducing power consumption, with power savings that reached 20%.Circuits and SystemsElectrical Engineering, Mathematics and Computer Scienc
Anomaly detection and process diagnostic in three-dimensional surface topography
No full textThe recent development of optical measuring instruments has increased the use of surface topographic data for monitoring the quality of the engineered surface. Monitoring topographic variations in the surface is crucial for quality engineers since the change in the surface finish is closely related to the performance of products in use. However, several challenging issues such as the existence of spatial autocorrelation within the surface, and changes of topographic features such as position and shape of peaks and valleys across defect-free surfaces make it difficult to monitor variations in the surface. In addition, existing monitoring approaches fail to detect local changes in the surface. Moreover, surface inspection becomes more difficult when the surface contains local defects that are often concealed due to the high-dimensional data structure of the surface image.
This dissertation presents efficient anomaly detection approaches for monitoring topographic variations in the three-dimensional (3D) surface. We first propose a residual-based surface segmentation approach to effectively identify local surface changes. We obtain residuals from the surface through a fitted surface prediction model, which characterizes the generic behavior of defect-free surfaces. Then, the proposed approach binarizes the surface based on local residual properties and identifies the defective areas where residuals are spatially autocorrelated. By considering both deviated residuals and neighboring residuals, which have similar values from local regions, the approach effectively captures residual patterns in the defective areas, which are concealed due to the high-dimensional surface data structure. Then, a spatial randomness-based monitoring statistic is introduced to evaluate binarized surfaces in order to detect surface anomalies.
Second, we investigate unique surfaces that exhibit multiple in-control modes. Due to the complexities of modern industrial processes, surfaces of final products under the normal manufacturing process may have multiple modes, such that the surface consists of different topographic features from one in-control mode to another. In this case, existing monitoring approaches based on the single mode surface cannot characterize normal surfaces with multiple modes, and result in poor detection performance. To overcome this limitation, a new approach for monitoring variations in multimode surface topography is presented. We propose a multimode surface prediction model, which characterizes the generic behavior of normal surfaces with multiple in-control modes. Moreover, we present a mode-specific surface monitoring approach that identifies topographic variations on the surfaces based on the similarity between probability density function (PDF) of residuals from observed and normal surfaces obtained through the multimode surface prediction model. A novel probabilistic distance measure (PDM) is introduced to effectively measure the similarity between a single residual PDF and a set of residual PDFs under the same mode.
We then propose a novel approach for monitoring local topographic variations in the presence of multimode surface topography. We present a multimode surface binarization model that characterizes distinct topographic features of surfaces under different in-control modes and better identifies the local variations in the surface data. In order to systematically evaluate the deviations between the observed and defect-free surfaces with multiple in-control modes, we introduce a novel PDM that effectively compares spatial randomness between two binarized surfaces.
Lastly, we present a new approach for monitoring and diagnosing local topographic variations on the surface topography. Once the observed surface is considered as an anomaly, identifying the shape, location, or size of the defective area is essential for diagnosing the root cause of the abnormal surface. Thus we develop a variable selection-based fault detection and diagnostic approach that selects potentially defective areas on the surface by considering the spatial structure of the surface and residual information. Suspicious areas are then employed to detect anomalies and further utilized to identify defect size, location, and shape for fault diagnosis purposes.
The proposed surface monitoring approaches in this dissertation are efficient and effective in monitoring spatial patterns in topographic data. The proposed monitoring approach investigated in Chapter 3 is superior to existing surface monitoring approaches regardless of the defect size and the number of defects. In the presence of multimode in-control surfaces, the mode-specific surface monitoring approach developed in Chapter 4 outperforms existing single mode and multimode-based approaches in detecting global topographic variations. Moreover, local topographic variations in the presence of multimode surface topography are effectively captured by the proposed approach introduced in Chapter 5. Finally, the proposed approach presented in Chapter 6 identifies fault diagnostic information such as fault size and location, and it is sensitive to detecting local variations on the surface. The effectiveness of the proposed approaches is demonstrated through extensive numerical simulation studies and real-life applications of paper surface monitoring.Ph.D.Includes bibliographical reference
Analysis of process control baseline data using data mining
No full textThere are two phases in multivariate statistical process control (MSPC). In phase I, we model baseline data off-line to characterize the process. Baseline data is a collection of observations describing successful manufacturing. In phase II, we compare on-line observations to these models to determine whether the process is in control. This dissertation addresses four questions to improve phase I analysis: (1) How many operational modes are in baseline data? (2) In a large historical dataset collected over a long time period, which periods are the baseline? (3) In profile baseline data, are there outlier profiles? (4) When should the phase I model be updated?
Each operational mode appears as a cluster in baseline data. To address the first question, we propose a new method to determine the number of clusters with all of the following critical features: it determines if there is only one cluster, the most common case; it identifies convex or non-convex clusters; and it is insensitive to user-specified parameters. No existing method has them all. Simulations show that the proposed method works well.
We propose a new method to address the second question, where historical data may be collected during both baseline and unsuccessful periods. The identified baseline periods are reasonably long, and have the best product quality with a stable distribution. Through simulated and real datasets, the proposed method shows its robustness to various distributions, in contrast to the existing change point identification method that is very sensitive to the distribution.
We address the third question in the context of complex profiles. We treat complex profiles as high-dimension vectors. We apply the control chart to identify outliers. Applied to simulated and real datasets, it demonstrates better performance on complex profiles than the existing nonlinear regression method.
We address the fourth question by testing whether the correlation matrix changes from the baseline. The correlation matrix describes relationships among variables. We propose a new method to diagnose the responsible variables when the change is indicated.
We also discuss the future work of applying MSPC and data mining technologies on data from a brain neural system.Ph.D.Includes bibliographical references (p. 118-122)
Aggregation enhanced excimer emission (AEEE) with efficient blue emission based on pyrene dendrimers
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