Ann Levine Wolff Scrapbook

Ann (Anna Eva) Levine was born on November 12, 1890 to William and Sarah Ida Levine, and died on April 3, 1890. This scrapbook contains family memories, photographs, and an exam book in holograph for a history class in 1936 at Colby College.

Determination of the photoinduced birefringence and of the refractive index by Brewster method of epoxy resin doped with CdS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Anderson localization and Brewster anomalies in photonic disordered quasiperiodic lattices

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Steel bars identification in reinforced concrete structures by using ANN and magnetic fields

This work proposes a methodology for non destructive testing (NDT) of reinforced concrete structures, using superficial magnetic fields and artificial neural networks, in order to identify the size and position of steel bars, embedded into the concrete. For the purposes of this paper, magnetic induction curves were obtained by using a finite element program. Perceptron Multilayered (PML) ANNs, with Levemberg-Marquardt training algorithm were used. The results presented very good agreement with the expect ones, encouraging the development of real systems based upon the proposed methodology.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling

In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

Niobium Effects on the Recrystallization Behavior on a Full Austenitic 15Cr-15Ni Stainless Steel Investigated Using Adaptive Neural Networks (ANN)

A new series of austenitic stainless steels-Nb stabilized, without Mo additions, non-susceptible to delta ferrite formation and devoid of intemetallic phases (sigma and chi), without deformation induced martensite is being developed, aiming at high temperature applications as well as for corrosive environments. The base steel composition is a 15Cr-15Ni with normal additions of Nb of 0.5, 1.0 and 2 wt%. Mechanical properties, oxidation and corrosion resistance already have been invetigated in previous papers. In this paper, the effects of Nb on the SFE, strain hardening and recrystallization resistance are evaluated with the help of Adaptive Neural Networks (ANN).

Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.

Wom(b)anism: Reading Relationships Between the Community and the Womb in Sankofa, The Women of Brewster Place, and Corregidora

This project attempts to contribute to the various discourses within the black womanist tradition. In 1983, Alice Walker published her landmark collection of essays entitled In Search of Our Mother Gardens: Womanist Prose. At the outset of the volume, Walker defines the core concept of womanism. After a poetic four-part definition of the term womanist, Walker concludes by stating, 'womanist is to feminist as purple to lavender' (Phillips 19). Although this analogy is critically engaged, the scholarly discourse that emerged in response to Walker's proposition shapes the intellectual inner workings of this project. Certain established concepts (such as ancestral mediation or the laying on of hands) work in conjunction with my own concepts of 'wom(b)anism' and 'the communal womb' to frame the interpretive discussions throughout these pages. Wom(b)anism and the communal womb both emerge from the black feminist and womanist traditions, especially via the role of ancestral mediation but also within the contested discourses on womanism itself. I apply the two concepts (wom(b)anism and the communal womb) to my readings of Haile Gerima's Sankofa, Gloria Naylor's The Women of Brewster Place, and Gayl Jones' Corregidora. The relationship between the community and women's wombs across each of these texts construct a narrative that features ancestral mediation (or intervention), various acts of violence committed against women's bodies, and the complicated circumstances through which women heal themselves andtheir communities.