Diseño de un mini acueducto por gravedad en los barrios San Agustín, Gaspar García Laviana y Guadalupe del casco urbano del municipio de Dipilto, departamento de Nueva Segovia

Presenta el diseño de un sistema de abastecimiento de agua potable para los barrios San Agustín, Gaspar García Laviana y Guadalupe del casco urbano del municipio de Dipilto, departamento de Nueva Segovia, del tipo mini-acueducto por gravedad (MAG).Se realiza un análisis hidráulico de las principales redes a diseñar mediante el uso del software EPANET

The Americanization of the Child Soldier Narrative

In less than a decade, the child soldier narrative has changed form and audience, relocating from post-colonial African fiction to North American autobiographical memoir, a change I will refer to as “Americanization.” 1 The shift reveals much about the modern social construct of “childhood,” the requirements of translation and genre blending, and the reading horizons of audience. This essay tracks the change, using as pivotal texts Ken Saro-Wiwa’s Sozaboy (1985), Amadou Kourouma’s Allah n’est pas obligé (2000) (Allah is not Obliged, 2006), China Keitetsi’s Child Soldier: Fighting for my Life (2002) and Uzodinma Iweala’s Beasts of No Nation (2005), arriving finally at Ishmael Beah’s sensational best-seller A Long Way Gone (2007)

Segmentation of Kidneys Deformed by Nephroblastoma using Case-Based Reasoning

International audienceImage segmentation is a hot topic in image processing re- search. Most of the time, segmentation is not fully automated, and a user is required to guide the process in order to obtain correct results. Yet, even with programs, it is a time-consuming process. In a medical context, segmentation can provide a lot of information to surgeons, but since this task is manual, it is rarely executed because of time. Artificial Intelligence (AI) is a powerful approach to create viable solutions for fully automated treatments. In this paper, we define a case-based rea- soning (CBR) that can enhance region-growing segmentation of kidneys deformed by nephroblastoma. The main problem with region-growing methods is that a user needs to place the seeds in the image manually. Automated methods exist but they are not ecient every time and they often give an over-segmentation. That is why we have designed an adap- tation phase which can modify the coordinates of seeds recovered during the retrieval phase. We compared our CBR approach with manual re- gion growing and Convolutional Neural Networking (CNN) to segment kidneys and tumours of CT-scans. Our CBR system succeeded in per- forming the best segmentation for the kidney