Photograph - Ann and William Sanderson

A framed copy of 2 photographed sketches. Each photograph is 18 cm x 13 cm. Ann and William Sanderson are displayed in this frame.

Photograph - Ann Sophia Sanderson

Photograph of a sketch, 13 cm x 10 cm, of Ann Sophia Sanderson. The photographer was G.F. Maitland of St. Catharines.

Indenture between William and Ann Waters and William B. Winterbottom

Indenture of mortgage with dower between William and Ann Waters of Niagara to William B. Winterbottom of Niagara regarding the easterly half of Lot no. 265 in Niagara. This was recorded in the Register of Forms of Niagara on April 13, 1850, Book A, folios 207-208 - instrument no. 2093, April 1, 1850.

Indenture between Johnson T. Butler, Ann Jane Butler and Henry Rogers

Indenture of bargain and sale between Johnson T. Butler and his wife Ann Jane Butler, both of the Township of Niagara to Henry Rogers of the Township of Niagara regarding part of Lot no. 113 in the Township of Niagara - instrument no. 14467 [it is listed as 14467 and 14466 on different parts of the document], April 13, 1864.

Invitation to the Funeral of Ann Elizabeth Woodruff

Invitation to the funeral of Ann Elizabeth Woodruff, daughter of the late Richard N. Woodruff. The funeral was to be held on Oct. 17, 1871 at her residence in St. Davids, Oct. 16, 1871.

Indenture of bargain and sale between James and Ann Jane Butler of the Town of Niagara to Joseph Augustus Woodruff of the Town of Niagara

Indenture of bargain and sale between James and Ann Jane Butler of the Town of Niagara to Joseph Augustus Woodruff of the Town of Niagara for 50 acres composed of the west half of Lot no. 169 in the Township of Niagara – instrument no. 3309. This was recorded in the Niagara Township Register on Aug. 14, 1851, Book A, Folio 219, Aug. 12, 1851.

Indenture of quit claim between John and Nancy Ann Kerlin of the Township of Grantham to Joseph Augustus Woodruff of the Town of Niagara

Indenture of quit claim between John and Nancy Ann Kerlin of the Township of Grantham to Joseph Augustus Woodruff of the Town of Niagara for 100 acres in the west half of Lot no. 29 in the 2nd Concession in the Township of Nissouri, Middlesex, April 29, 1853.

Indenture of quit claim between John and Deborah Ann McNeilly of the Town of Niagara and Joseph Augustus Woodruff of the Town of Niagara

Indenture of quit claim between John and Deborah Ann McNeilly of the Town of Niagara and Joseph Augustus Woodruff of the Town of Niagara regarding 4 acres on the west side of King Street in Niagara, Dec. 4, 1853.

Marriage Bond between Joseph Bridgeman of Grimsby and Calinda Ann Lounsberry of Grimsby

Marriage Bond between Joseph Bridgeman of Grimsby and Calinda Ann Lounsberry of Grimsby signed by Palmer Buckbee of Grimsby and Robert F. Nelles of Grimsby, July [?] 6, 1837.

The west coast of México, from the boundary line between the United States and México to Cape Corrientes, including the gulf of California

UANL

Planification en contexte mégaévénementiel et reconversion urbaine : le cas du Green Point Urban Park à Cape Town en Afrique du Sud


Depuis les années 2000, nous observons de plus en plus de pays en développement (PED) hôtes de mégaévénements. En accueillant un mégaévénement en leur sol, les PED espèrent améliorer leur cadre urbain et attirer des investissements étrangers. Ceci étant dit, les retards en termes d’infrastructures et d’équipements que connaissent ces pays et les stricts cadres normatifs imposés par des organismes internationaux comme la FIFA, nous amènent à questionner la possibilité d’intégrer les aménagements mégaévénementiels, à leur contexte local. En ce sens, le processus de planification, dans lequel les cadres normatifs externes et locaux sont négociés, peut être vu comme un moment charnière ayant une incidence sur le potentiel de reconversion. Dans le cadre de ce mémoire, nous avons entamé une réflexion à ce sujet en examinant le processus de planification d’un aménagement mégaévénementiel, le Green Point Urban Park (GPUP) à Cape Town, et son incidence sur son potentiel de reconversion. Plus précisément, nous allons, en premier lieu, décrire le processus de planification du site, nous allons par la suite évaluer son potentiel de reconversion, puis nous allons faire ressortir des liens entre le processus de planification et le potentiel de reconversion des aménagements mégaévénementiels. En somme, notre travail met en évidence une relation entre, d’une part, la prépondérance du cadre normatif imposé par l’organisme international et la dynamique du système d’acteurs au moment de la planification du GPUP et, d’autre part, la difficile reconversion de ce dernier après la Coupe du monde de 2010.

Investigations On The Development Of An Ann Model & Visual Manipulation Approach For 2-D Dft Computation In Image Processing

This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned

Learning disability prediction tool using ANN and ANFIS

Learning Disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 15 % of children enrolled in schools. The prediction of LD is a vital and intricate job. The aim of this paper is to design an effective and powerful tool, using the two intelligent methods viz., Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System, for measuring the percentage of LD that affected in school-age children. In this study, we are proposing some soft computing methods in data preprocessing for improving the accuracy of the tool as well as the classifier. The data preprocessing is performed through Principal Component Analysis for attribute reduction and closest fit algorithm is used for imputing missing values. The main idea in developing the LD prediction tool is not only to predict the LD present in children but also to measure its percentage along with its class like low or minor or major. The system is implemented in Mathworks Software MatLab 7.10. The results obtained from this study have illustrated that the designed prediction system or tool is capable of measuring the LD effectively