The purposes of this study were to determine whether brain growth spurts occur in normal pupils and to determine whether there was a uniform difference in head circumference between boys and girls. Subjects were 3,062 normal elementary pupils, grades one through six, from one suburban school district. Fiberglass measuring tapes were used to measure pupils' head circumference. The hypotheses of the study predicted that the relationship between head circumference and age would be linear. Further, it was predicted that the differences in head circumference between boys and girls would be uniform over seven specified ages. The first hypothesis was tested using a test for linear trend and deviation from linear trend using the General Linear Models procedure. The results indicated that there was a significant linear trend between head circumference and age. The test for deviation from the linear trend was not significant. This would suggest that any deviation from a straight line observed in the data can be attributed to chance. It was concluded that since there was no significant deviation from linear trend, it would suggest a continuous growth of the brain for the ages included in this study. A two-way analysis of variance was used to test the second hypothesis. The results indicated that the male mean head circumference was significantly larger than that of the female in all age groups. As the interaction of sex and age groups was tested, there was no interaction between sex and age groups. It was concluded that since the interaction between sex and age groups was not significant, there is no indication of differences in the rates of brain growth between boys and girls.

The LeanScreenTM app uses photographs and touchscreen technology of an iPad or iPhone to estimate body composition using the Department of Defense (DoD) prediction equations that use cirumference measurements of the neck, abdomen, waist, and hips. The purpose of this study was to determine the validity and reliability of the LeanScreenTM app in 148 weight-stable adults (82 men, 66 women) who were normal weight, overweight, or obese as defined by body mass index. The percent body fat (%BF) of each subject was estimated during one visit using dual-energy x-ray absorptiometery (DXA) as the criterion measure, and three field methods: the LeanScreenTM app, manually measured circumferences, and an OMRON bioelectical impedance (BIA) device. The %BF of each subject was determined once using DXA. Each of two administrators assessed the %BF of each subject twice using the LeanScreenTM app, manually measured circumferences, and the OMRON BIA device. When using the LeanScreenTM app, administrators assessed body composition using photographs they had taken and the photographs taken by the other administrator. Validity was established by comparing estimates of %BF from the LeanScreenTM app, manually measured circumferences, and the OMRON BIA device to %BF values obtained from DXA. Inter- and intrarater reliability was determined using mutliple measurements taken by each of two administrators. The three field methods were compared to DXA using mixed model ANOVA and Bland-Altman analyses. Analysis of the data revealed that the LeanScreenTM app, manually measured circumferences, and the OMRON BIA device significantly underestimated (p < 0.05) the %BF determined by DXA by an average of -3.26 ± 3.57 %BF, -4.82 ± 3.45 %BF, and -8.45 ± 3.48 %BF, respectively. Limits of agreement (LOA) for the LeanScreenTM app (6.99 %BF), manually measured circumferences (6.76 %BF), and the OMRON BIA device (6.82 %BF) were large. Slopes of the line-of-best-fit through the data in the Bland-Altman plots indicate that bias of %BF estimates using the LeanScreenTM app (slope = 0.06; p = 0.008) and the OMRON BIA device (slope = 0.15; p < 0.0001) increased as %BF increased. For each method of assessment, minimal variance could be attributed to different administrators peforming the assessment and each administrator performing multiple assessments. All inter- and intrarater reliability coefficients of the LeanScreenTM app, manually measured circumferences, and OMRON BIA estimates of %BF exceeded 0.99. The results of this study indicate that all three field methods of body composition assessments were highly reliable, however, these field measures are not recommended for use in the assessments of %BF due to a significant bias and large limits of agreements.

Orientador: Prof. Dr. Rovílson Mafalda. / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia e Gestão da Inovação, 2018. / Nas últimas décadas, o problema da navegação autônoma tem sido o principal foco da robótica móvel. Este problema consiste em gerar trajetórias para guiar o deslocamento do robô num determinado ambiente a partir de informações provenientes de sistemas de sensores externos e/ou de informações constantes no mapa do ambiente. A partir destes pode saber sua localização e movimentar-se para quaisquer pontos do ambiente de trabalho de maneira segura, evitando colisões e regiões onde não há espaço suficiente para sua travessia. O planejamento de trajetórias é parte fundamental para o deslocamento de robôs móveis. A elaboração de um plano para movimentação autônoma é uma tarefa complexa. O planejamento de caminhos está relacionado ao planejamento geométrico da movimentação do robô no ambiente. Já o planejamento de trajetória é responsável por baseado no planejamento de caminhos, atuar sobre a movimentação dinâmica do robô [1]. A forma como o ambiente é mapeado no sistema é determinante na sua precisão e desempenho. Dentro deste contexto, neste trabalho é proposto um método para planejamento de caminhos para robôs móveis, considerando um ambiente interno, estruturado e estático, onde o ambiente e os obstáculos, entre os quais estes se movem, estão modelados como um Diagrama de Voronói para Circunferências. Algoritmos com a finalidade de encontrar o caminho de menor distância entre os caminhos disponíveis no mapa do ambiente discretizado de acordo com a modelagem acima são estudados e avaliados. Esta pesquisa também envolve estudos sobre problemas de tangências entre circunferências, estudos sobre a representação matemática do Diagrama de Voronoi e estudos sobre otimização de caminhos sobre estes Diagramas. / Over the last decades, researches in mobile robotics has focused on autonomous navigation problem. This problem consists on generating trajectories to guide the movement of a robot from a start point to an end point in a determined local. It is based on data from external sensor systems and /or information of the environment map. From this information, the robot is able to know its location and to move to another point in the working environment in a safe path, avoiding collisions and regions where there is not enough space for crossing. Trajectory planning is a fundamental part for movement of mobile robots. To elaborate a path planning for autonomous displacement is a complex task. Path planning relates to the geometric planning of robot movement in the environment. Already the trajectory planning is responsible for, based on path planning, to act on a dynamic movement of the robot. The approach applied to model an environment is determinant over accuracy and performance of a trajectory system. Within this context, in this work it is proposed a method to plan routes for mobile robots, where the environment map is model as a Voronói Diagram for Circumferences. Searching algorithms with the purpose of finding the shortest routes between the paths available in the map are studied and analyzed. This research also involves studies on circumferential tangency problems, studies on the mathematical representation of the Voronoi Diagram, and studies on path optimization on these Diagrams.