Application of geomatics for determining the coverage for current land use from satellite images and comparison with the shape land use. Case study: municipaly Tibaná (Boyaca)

El proyecto en primer lugar está orientado a determinar el uso actual del suelo utilizando como insumos una imagen Rapideye, mediante la técnica de clasificación supervisada, utilizando los usos y coberturas del primer nivel de sistema de clasificación del CIAF, para el municipio de Tibana Departamento de Boyacá. El segundo objetivo del proyecto es realizar la comparación entre los resultados obtenidos y la cobertura de uso del suelo del municipio de TibanaThe project first is aimed at determining the current land use using as input one RapidEye image using the technique of supervised classification using the uses and covers the first level of classification system CIAF to the town Tibana Department of Boyacá. The second objective is the comparison between the results obtained and the land use coverage Township Tiban

Banach's fixed point theorem for partial metric spaces

In 1994, S.G. Matthews introduced the notion of a par- tial metric space and obtained, among other results, a Banach contraction mapping for these spaces. Later on, S.J. O’Neill gen- eralized Matthews’ notion of partial metric, in order to establish connections between these structures and the topological aspects of domain theory. Here, we obtain a Banach fixed point theorem for complete partial metric spaces in the sense of O’Neill. Thus, Matthews’ fixed point theorem follows as special case of our result

Análisis asintótico de relaciones de recurrencia en complejidad algorítmica mediante la teoría de ecuaciones en diferencia

[spa] La teoría de ecuaciones en diferencias permite modelas satisfactoriamente múltiples procesos que surgen de modo natural en diversas áreas de las ciencias aplicadas. En concreto, las ecuaciones en diferencias resultan de gran utilidad en Ciencias de la Computación. El objetivo del presente artículo es introducir a los estudiantes de las titulaciones de Grado en Matemáticas y Grado en Ingeniería Informática, así como a los futuros investigadores que se forman cursando el título de Máster en Tecnologías de la Información, en las técnicas de resolución de un tipo en particular de ecuaciones en diferencias, las denominadas ecuaciones en diferencias finitas lineales, y mostrar su aplicabilidad al análisis de complejidad algorítmica

Contributions of biomechanical modeling and machine learning to the automatic registration of Multiparametric Magnetic Resonance and Transrectal Echography for prostate brachytherapy

El cáncer de próstata (CaP) es el primer cáncer por incidencia en hombres en países occidentales, y el tercero en mortalidad. Tras detectar en sangre una elevación del Antígeno Prostático Específico (PSA) o tras tacto rectal sospechoso se realiza una Resonancia Magnética (RM) de la próstata, que los radiólogos analizan para localizar las regiones sospechosas. A continuación, estas se biopsian, es decir, se toman muestras vivas que posteriormente serán analizadas histopatológicamente para confirmar la presencia de cáncer y establecer su grado de agresividad. Durante la biopsia se emplea típicamente Ultrasonidos (US) para el guiado y la localización de las lesiones. Sin embargo, estas no son directamente visibles en US, y el urólogo necesita usar software de fusión que realice un registro RM-US que transfiera la localizaciones marcadas en MR al US. Esto es fundamental para asegurar que las muestras tomadas provienen verdaderamente de la zona sospechosa. En este trabajo se compendian cinco publicaciones que emplean diversos algoritmos de Inteligencia Artificial (IA) para analizar las imágenes de próstata (RM y US) y con ello mejorar la eficiencia y precisión en el diagnóstico, biopsia y tratamiento del CaP: 1. Segmentación automática de próstata en RM y US: Segmentar la próstata consiste en delimitar o marcar la próstata en una imagen médica, separándola del resto de órganos o estructuras. Automatizar por completo esta tarea, que es previa a todo análisis posterior, permite ahorrar un tiempo significativo a radiólogos y urólogos, mejorando también la precisión y repetibilidad. 2. Mejora de la resolución de segmentación: Se presenta una metodología para mejorar la resolución de las segmentaciones anteriores. 3. Detección y clasificación automática de lesiones en RM: Se entrena un modelo basado en IA para detectar las lesiones como lo haría un radiólogo, asignándoles también una estimación del riesgo. Se logra mejorar la precisión diagnóstica, dando lugar a un sistema totalmente automático que podría implantarse para segunda opinión clínica o como criterio para priorización. 4. Simulación del comportamiento biomecánico en tiempo real: Se propone acelerar la simulación del comportamiento biomecánico de órganos blandos mediante el uso de IA. 5. Registro automático RM-US: El registro permite localizar en US las lesiones marcadas en RM. Una alta precisión en esta tarea es esencial para la corrección de la biopsia y/o del tratamiento focal del paciente (como braquiterapia de alta tasa). Se plantea el uso de la IA para resolver el problema de registro en tiempo casi real, utilizando modelos biomecánicos subyacentes.Prostate cancer (PCa) is the most common malignancy in western males, and third by mortality. After detecting elevated Prostate Specific Antigen (PSA) blood levels or after a suspicious rectal examination, a Magnetic Resonance (MR) image of the prostate is acquired and assessed by radiologists to locate suspicious regions. These are then biopsied, i.e. living tissue samples are collected and analyzed histopathologically to confirm the presence of cancer and establish its degree of aggressiveness. During the biopsy procedure, Ultrasound (US) is typically used for guidance and lesion localization. However, lesions are not directly visible in US, and the urologist needs to use fusion software to performs MR-US registration, so that the MR-marked locations can be transferred to the US image. This is essential to ensure that the collected samples truly come from the suspicious area. This work compiles five publications employing several Artificial Intelligence (AI) algorithms to analyze prostate images (MR and US) and thereby improve the efficiency and accuracy in diagnosis, biopsy and treatment of PCa: 1. Automatic prostate segmentation in MR and US: Prostate segmentation consists in delimiting or marking the prostate in a medical image, separating it from the rest of the organs or structures. Automating this task fully, which is required for any subsequent analysis, saves significant time for radiologists and urologists, while also improving accuracy and repeatability. 2. Segmentation resolution enhancement: A methodology for improving the resolution of the previously obtained segmentations is presented. 3. Automatic detection and classification of MR lesions: An AI model is trained to detect lesions as a radiologist would and to estimate their risk. The model achieves improved diagnostic accuracy, resulting in a fully automatic system that could be used as a second clinical opinion or as a criterion for patient prioritization. 4. Simulation of biomechanical behavior in real time: It is proposed to accelerate the simulation of biomechanical behavior of soft organs using AI. 5. Automatic MR-US registration: Registration allows localization of MR-marked lesions on US. High accuracy in this task is essential for the correctness of the biopsy and/or focal treatment procedures (such as high-rate brachytherapy). Here, AI is used to solve the registration problem in near-real time, while exploiting underlying biomechanically-compatible models

Prueba de habilidades prácticas CCNA2.

En el desarrollo de este trabajo, se dará solución a un problema planteado como parte de un examen final da habilidades prácticas en el curso CCNA 2; el escenario del problema consiste en: Una empresa de Tecnología posee tres sucursales distribuidas en las ciudades de Bogotá, Medellín y Bucaramanga, en donde el estudiante será el administrador de la red, el cual deberá configurar e interconectar entre sí cada uno de los dispositivos que forman parte del escenario, acorde con los lineamientos establecidos para el direccionamiento IP, protocolos de enrutamiento y demás aspectos que forman parte de la topología de red.In the development of this work, a problem will be solved as part a final exam gives practical skills in the CCNA 2 course; the stage of Problem is: A Technology company has three branches distributed in the cities of Bogotá, Medellín and Bucaramanga, where the student will be the network administrator, who must configure and interconnect each other the devices that are part of the scenario, according to the guidelines established for IP addressing, routing protocols and others aspects that are part of the network topology

Internet congestion control: From stochastic to dynamical models

Since its inception, control of data congestion on the Internet has been based on stochas tic models. One of the first such models was Random Early Detection. Later, this model was reformulated as a dynamical system, with the average queue sizes at a router’s buffer being the states. Recently, the dynamical model has been generalized to improve global stability. In this paper we review the original stochastic model and both nonlin ear models of Random Early Detection with a two-fold objective: (i) illustrate how a random model can be “smoothed out” to a deterministic one through data aggregation and (ii) how this translation can shed light into complex processes such as the Internet data traffic. Furthermore, this paper contains new materials concerning the occurrence of chaos, bifurcation diagrams, Lyapunov exponents and global stability robustness with respect to control parameters. The results reviewed and reported here are expected to help design an active queue management algorithm in real conditions, that is, when sys tem parameters such as the number of users and the round-trip time of the data packets change over time. The topic also illustrates the much-needed synergy of a theoretical approach, practical intuition and numerical simulations in engineerin

Design and Expression of Specific Hybrid Lantibiotics Active Against Pathogenic Clostridium spp.

Clostridium difficile has been reported as the most common cause of nosocomial diarrhea (antibiotic-associated diarrhea), resulting in significant morbidity and mortality in hospitalized patients. The resistance of the clostridia' spores to antibiotics and their side effects on the gut microbiota are two factors related to the emergence of infection and its relapses. Lantibiotics provide an innovative alternative for cell growth inhibition due to their dual mechanism of action (membrane pore-forming and cell wall synthesis inhibition) and low resistance rate. Based on the fact that bacteriocins are usually active against bacteria closely related to the producer strains, a new dual approach combining genome mining and synthetic biology was performed, by designing new lantibiotics with high activity and specificity toward Clostridium. We first attempted the heterologous expression of putative lantibiotics identified following Clostridium genome mining. Subsequently, we designed new hybrid lantibiotics combining the start or end of the putative clostridial peptides and the start or end parts of nisin. The designed peptides were cloned and expressed using the nisin biosynthetic machinery in Lactococcus lactis. From the 20 initial peptides, only 1 fulfilled the requirements established in this work to be considered as a good candidate: high heterologous production level and high specificity/activity against clostridial species. The high specificity and activity observed for the peptide AMV10 makes it an interesting candidate as an alternative to traditional antibiotics in the treatment of C. difficile infections, avoiding side effects and protecting the normal gut microbiota