Development of Design Loads for Transmission Line Structures Subjected to Downbursts Using Aero-elastic Testing and Numerical Modeling

The failure of transmission line structures due to severe High Intensity Wind (HIW) events is one of the major problems facing the electrical utility companies in various places around the globe including Canada. An extensive research program focusing on this problem started about fifteen years ago at The University of Western Ontario (UWO). In this Thesis, two major milestones are achieved leading to the advancement of the knowledge in this field. The first milestone is conducting, for the first time, a test on an aero-elastic model of a multi-span transmission system under reduced–scale simulated downbursts. The first objective of the experimental program is to assess the dynamic response of the conductors and the towers resulting from the transient nature of both the mean and the fluctuating components of downbursts. The second objective is to use the experimental results to validate a numerical model previously developed in-house at UWO for the analysis of transmission line structures under downbursts. The second milestone achieved in this Thesis is the development, for the first time, of a set of load cases that simulates the critical effects of downbursts on transmission line structures taking into account the variation in the location and size of the wind events. A load case that is particular for downbursts results in a velocity profile on the line that is non uniform and unequal along the conductor spans adjacent to the opposite sides of a tower. This leads to unequal tensions in the two spans adjacent to the tower and the difference in tensions leads to a force transmitted to the tower along the longitudinal direction of the line. This force is believed to be the cause of the failure of many towers. A procedure that is simple enough for application and for estimation such a force is developed in this study. Finally, through conducting an extensive parametric study for a number of transmission line systems, a comprehensive and simple procedure for estimating critical downburst loads on both the tower and the conductors is developed and presented in a simplified manner for possible implementation in the codes of practice

Sparse Coral Classification Using Deep Convolutional Neural Networks

Autonomous repair of deep-sea coral reefs is a recent proposed idea to support the oceans ecosystem in which is vital for commercial fishing, tourism and other species. This idea can be operated through using many small autonomous underwater vehicles (AUVs) and swarm intelligence techniques to locate and replace chunks of coral which have been broken off, thus enabling re-growth and maintaining the habitat. The aim of this project is developing machine vision algorithms to enable an underwater robot to locate a coral reef and a chunk of coral on the seabed and prompt the robot to pick it up. Although there is no literature on this particular problem, related work on fish counting may give some insight into the problem. The technical challenges are principally due to the potential lack of clarity of the water and platform stabilization as well as spurious artifacts (rocks, fish, and crabs). We present an efficient sparse classification for coral species using supervised deep learning method called Convolutional Neural Networks (CNNs). We compute Weber Local Descriptor (WLD), Phase Congruency (PC), and Zero Component Analysis (ZCA) Whitening to extract shape and texture feature descriptors, which are employed to be supplementary channels (feature-based maps) besides basic spatial color channels (spatial-based maps) of coral input image, we also experiment state-of-art preprocessing underwater algorithms for image enhancement and color normalization and color conversion adjustment. Our proposed coral classification method is developed under MATLAB platform, and evaluated by two different coral datasets (University of California San Diego's Moorea Labeled Corals, and Heriot-Watt University's Atlantic Deep Sea).Comment: Thesis Submitted for the Degree of MSc Erasmus Mundus in Vision and Robotics (VIBOT 2014

Automatic Classification of Bright Retinal Lesions via Deep Network Features

The diabetic retinopathy is timely diagonalized through color eye fundus images by experienced ophthalmologists, in order to recognize potential retinal features and identify early-blindness cases. In this paper, it is proposed to extract deep features from the last fully-connected layer of, four different, pre-trained convolutional neural networks. These features are then feeded into a non-linear classifier to discriminate three-class diabetic cases, i.e., normal, exudates, and drusen. Averaged across 1113 color retinal images collected from six publicly available annotated datasets, the deep features approach perform better than the classical bag-of-words approach. The proposed approaches have an average accuracy between 91.23% and 92.00% with more than 13% improvement over the traditional state of art methods.Comment: Preprint submitted to Journal of Medical Imaging | SPIE (Tue, Jul 28, 2017

The effect of Touch Math multi-sensory program on teaching basic computation skills to young children identified as at risk for the acquisition of computation skills

The purpose of this paper was to investigate the effect of Touch Math multi-sensory program on   teaching basic computation skills to young children identified as at risk for the acquisition of computation skills. The children selected for the present study were all kindergarteners from two public kindergarten schools, located at Nasr city, Cairo. 40 children from both schools were included. Of the children who participated in the study (N= 40), 72% were male and 28% were female. Mean age was 5.3 years. A quasi-experimental, two-groups pretest-posttest design was employed, where the same dependent variables (addition skills and subtraction skills) were measured in the two groups of children before (pretest) and after (posttest) a treatment was administered. Using two-way ANOVA, the author analyzed the data from the pre- and post-test.  The data were analyzed using the Statistical Package for the Social Sciences (SPSS) 18.0. The results of the two-way ANOVA and t- test showed that there were differences in post- test mean scores between experimental and control   groups in addition and subtraction skills. In favor of the experimental group, which indicated the effectiveness of Touch Math multi-sensory program. Implications for practice, recommendations for future research and conclusion were included

Impact of Removable Partial Denture Type on Patient Satisfaction and Abutment Survival Rate-RCT

BACKGROUND: Patient’s satisfaction and the preservation of abutments is the most important outcomes that the clinician seeks during fabrication of any dental treatment, especially when it is concerned with removable prosthodontic rehabilitation. AIM: The present study evaluates three different Removable Partial Denture (RPD) types restoring mandibular class II modification I edentulous cases with regards to patient’s satisfaction and abutments survival. METHODS: Forty-two partially edentulous patients were divided into three groups (Group I rehabilitated with Vitallium RPD, Group II rehabilitated with Vitallium RPD where the modification area restored with the surveyed bridge, Group III rehabilitated with Thermopress RPD). The patients were followed up for twenty-four months. Using a questionnaire, prosthodontic maintenance required was documented at the delivery and after 3 months. RESULTS: There was a significant difference regarding patient satisfaction for group III (P-value <0.05) while for groups I and II there was a non-significant difference (P-value >0.05). Regarding the survival rate, there was a non-significant difference between the three groups (P-value >0.05) at the end of twenty-four months of follow up. CONCLUSION: Patient satisfaction and abutment survival were better with Thermopress RPD than conventional Vitallium RPD or Vitallium RPD with a surveyed bridge restoring the modification area. Although a non-statistically significant difference was found in the survival rate of abutments between groups, a clinically important result was revealed as no abutments failures were reported in the Thermopress group

The Ligand Substitution Reactions of Hydrophobic Vitamin B12 Derivatives. Reaction of Cobyric Acid Heptapropyl Ester with Heterocyclic N-donor Ligands

The hydrophobic cobyrinic acid heptapropyl ester corrinoids XCbs-Pr (axial ligand X=CN–, SO32–, CH3– and CH3CH2–) have been prepared from vitamin B12 by hydrolysis of the amide side chains and their conversion to propyl esters. Both the position of the γ-band and the general shape of the UV-visible spectra of these complexes show significant solvent dependence as the polarity of the solvent is varied. The equilibrium constants, K, for the reaction of five-membered heterocyclic nitrogenous bases (the azoles imidazole, pyrazole and 1,2,4-triazole) with displacement of coordinated H2O in aquacyanocobyrinic acid heptapropyl ester, and coordination by the predominantly five-coordinate complexes sulphitocobyrinic acid heptapropyl ester, ethylcobyrinic acid heptapropyl ester and methylcobyrinic acid heptapropyl ester, have been determined spectrophotometrically at 25 °C in water, methanol, acetonitrile, ethyl acetate and toluene. Values of K are dependent on the identity of the trans ligand (X=CN–>SO3 2–> CH3 – > CH3CH2 –); they increase with the basicity of the azole (pyrazole < 1,2,4-triazole < imidazole); and they increase as the solvent polarity increases (toluene<ethyl acetate< acetonitrile< methanol< H2O). Molecular mechanics calculations suggest that these effects are largely electronic in origin.Keywords: Hydrophobic vitamin B12, cobalt corrinoids, equilibrium constants, solvent polarity, trans influencePDF and Supplementry file attache

Data analysis for image transmitted using Discrete Wavelet Transform and Vector Quantization compression

In this paper we are going to study the effect of channel noise in image compressed with vector quantization and discrete wavelet transform. The objective of this study is to analyze and understand the way that the noise attack transmitted data by doing lot of tests like dividing the indices in different levels according to discrete wavelet transform and dividing  each level in frames of bits. The collected information well helps us to propose solutions to make the received image more resistible to the channel noise also to benefit from the good representation obtained by using vector quantization and discrete wavelet transform

Interleaved reception method for restored vector quantization image

The transmission of image compression by vector quantization produce wrong blocks in received image which are completely different to the original one that makes the restoration process too hard because we don’t have any information about the original blocks. As a solution of this problem we try to keep the maximum of pixels that form the original block by building new blocks. Our proposition is based on decomposition and interleaving. For the simulation we use a binary symmetric channel with different BER and in the restoration process we use simple median filter just to check the efficiency of proposed approach