The advancement of wireless technology is increasing the demand for scarce spectrum. Cognitive radio ad hoc networks (CRAHNs) were proposed as a solution to spectrum scarcity which is also deployed in combat. However, military cognitive radio ad-hoc networks (MCRAHNs) are subject to destruction and frequent link breakages. The challenge with MCRAHNs routing is the timing-out of packets. This paper proposes the spectrum-aware transitive multi-cast on-demand distance vector (SAT-MAODV), optimised for throughput and delay. The relay nodes are selected based on zonal data and mobility. This is achieved through handshaking and sharing of location data. The nodes are expected to store location data of nodes encountered, which is used in routing and in determining the movement of the node. The mobility of military nodes is organised and structured, which simplifies routing. The SAT-MAODV was evaluated in network simulator 2 and the results show that the scheme is effective. Using SAT-MAODV instead of xWCETT, it reduced routing path and node relay delay by at least 65% and 13% respectively, and increased achievable throughput by 31%. It also improved the delivery ratio by 9% while reducing latency by 27% in comparison with MARSA. Categories · Networks ~ Network protocols, Network layer protocols, Routing protocols

ABSTRACT The electrical network is one of the least detected sources of electromagnetic interference, but it causes adverse effects on the medical equipment that is in its radius of action. The objective of this work is to analyze the effect of the magnetic field on the signal emitted by the Audix V equipment. A magnetic field generator, a gaussmeter, a signal simulator and an Audix equipment were transmitted. The research was carried out, following a methodology developed from different methods found in the literature. Screenshots of the signals emitted by the Audix V with visible influence on the parameters that characterize it were obtained by applying field values even below the 3.77 µT allowed by the IEC. It was concluded that there may be an error in the diagnosis due to the deformation caused by the electromagnetic field on the characteristics of the signal.

RESUMEN La red eléctrica es una de las fuentes de interferencia electromagnética menos detectadas, pero provoca efectos adversos sobre el equipo médico que se encuentre en su radio de acción. El objetivo de este trabajo es analizar el efecto del campo magnético sobre la señal emitida por el equipo Audix V. Se utilizó un generador de campo magnético, un gaussímetro, un simulador de señales y un equipo Audix. La investigación se llevó a cabo, siguiendo una metodología desarrollada a partir de diferentes métodos encontrados en la literatura. Se obtuvieron capturas de pantalla de las señales emitidas por el Audix V con influencia visible en los parámetros que lo caracterizan al aplicar valores de campo incluso por debajo de los 3,77 µT permitidos por la IEC. Se concluyó que puede haber error en el diagnóstico debido a la deformación que provoca el campo electromagnético sobre las características de la señal.

Abstract Working with Wireless Sensor Networks (WSN) in urban areas is a complicated task to perform, where various factors must be taken into account, due to the very nature of the environment. This is where analytical tools such as simulators play an important role for the success of networks. The objective of this work is to have a 3D virtual environment for WSN simulation that is reliable, scalable, modular and robust that allows certainty during network design. This paper presents the development of a 3D environment of the city of Torreón, using the discrete event simulator OMNeT++, with INET framework tools. The 3D simulation bed comprises a 1 km2 section of physical objects such as buildings and vegetation, the Torreón city map and elevation data from the Shuttle Radar Topography Mission (SRTM). Two comparative cases are presented between simulations and WSN data deployed in the city, obtaining the efficiency of the network and the Received Signal Strength Indicator (RSSI), at different distances between nodes. The first case study corresponds to the IEEE 802.15.4 standard at distances of 25, 50 and 100 m, and the second case to the Texas Instruments Legacy Long Range propetary mode at 90, 135 and 200 m. The results show an agreement of 92 % and 95 % on average respectively in received packets between simulated data and those collected with the WSN. As for the RSSI, it shows a behavior according to expectations, weakening at greater distances. The 3D simulation bed is a reliable tool to simulate networks with different levels of complexity and scale, it facilitates having visual references and allows understanding the behavior of the WSN to be designed, serving as support in the efforts for air quality monitoring that exist in the region.

Resumen Trabajar con Redes Inalámbricas de Sensores (RIS) en zonas urbanas es una tarea complicada, se deben tomar en cuenta diversos factores debido a la naturaleza propia del entorno. Es aquí en donde herramientas analíticas como los simuladores juegan un papel importante para el éxito de las redes. El objetivo de este trabajo es contar con un entorno virtual 3D para el simulado de RIS que sea confiable, escalable, modular y robusto que permita dar certidumbre durante el diseño de redes. En este trabajo se presenta el desarrollo de un entorno 3D de la ciudad de Torreón, haciendo uso del simulador de eventos discretos OMNeT++, con herramientas de INET framework. La cama de simulación 3D comprende una sección de 1 km2 de objetos físicos como edificaciones y vegetación, el mapa de la ciudad de Torreón y datos de elevación de la Misión Topográfica Shuttle Radar (SRTM, por sus siglas en ingles). Se presentan dos casos comparativos entre simulaciones y datos de RIS desplegadas en la ciudad, obteniendo la eficiencia de la red y el indicador de fuerza de la señal recibida (RSSI), a diferentes distancias entre nodos. El primer caso de estudio corresponde al estándar IEEE 802.15.4 en distancias de 25, 50 y 100 m, y el segundo caso al modo propietario de Texas Instruments Legacy Long Range a 90, 135 y 200 m. Los resultados muestran una coincidencia de 92 % y 95 % en promedio, respectivamente, en paquetes recibidos entre datos simulados y los recolectados con las RIS. En cuanto al RSSI se muestra un comportamiento acorde a lo esperado, debilitándose a mayores distancias. La cama de simulación 3D es una herramienta confiable para simular redes con diferentes niveles de complejidad y escala, facilita tener referencias visuales y permite entender el comportamiento de las RIS que se busquen diseñar, sirviendo de apoyo en los esfuerzos para el monitoreo de calidad de aire que existe en la región.

RESUMO Neste trabalho foi desenvolvido um modelo multiobjetivo para otimização da operação de sistemas de distribuição de água (SDAs), visando alcançar a eficiência hidroenergética considerando três objetivos: redução das perdas por vazamento; redução do custo de energia elétrica no bombeamento; e maximização da confiabilidade do sistema. O modelo de otimização foi concebido pela implementação de uma rotina computacional entre os algoritmos genéticos NSGAII e SPEA e o simulador hidráulico EPANET. O modelo foi aplicado a um SDA hipotético e demonstrou ser adequado para gerar um conjunto ótimo de regras operacionais. Dentre as soluções geradas pelos dois algoritmos, constatou-se que a diminuição do custo de energia elétrica no bombeamento não implicou, necessariamente, redução das perdas por vazamentos, ou seja, os dois objetivos podem ser conflitantes em SDAs caracterizados pela presença de reservatórios internos.

ABSTRACT In this work, a multi-objective model for operational optimization of water distribution systems has been developed in order to achieve hydro energy efficiency. Three objectives were considered: minimizing of leakage, minimizing of pumping energy costs, and maximizing system reliability. The optimization model was conceived by the implementation of a computational routine between a dyhraulic simulator (EPANET) and by genetic algorithms NSGAII and SPEA. The proposed model has been applied to the optimization of a hypothetical water distribution network to generate an optimal set of operational rules. Some solutions obtained by the two algorithms showed that a decrease in pumping energy costs did not necessarily imply in leakage reduction. This means that both objectives can be conflicting in water distribution systems with internal tanks.

In order to investigate the hot deformation behaviors of Invar36 alloy, isothermal compressive tests were conducted on a Gleeble 1500 thermo-mechanical simulator at the temperatures of 873, 948, 1023, 1098 and 1173 K and the strain rates of 0.01, 0.1, 1 and 10 s−1. The effects of strain, temperature and strain rate on flow stress were analyzed, and a dynamic recrystallization type softening characteristic with unimodal flow behavior is determined. An artificial neural network based on back-propagation algorithm was proposed to handle the complex deformation behavior characteristics. The ANN model was evaluated in terms of correlation coefficient and average absolute relative error. A comparative study was performed on ANN model and constitutive equation by regression method for Invar36 alloy. Finally, the ANN model was applied to the finite element simulation, and an experimental study on trial hot forming of a V-shaped part was conducted to demonstrate the precision of the finite element simulation based on predicted flow stress data by ANN model. The results have sufficiently showed that the well-trained ANN model with BP algorithm is able to deal with the complex flow behaviors of Invar36 alloy and has great application potentiality in hot deformation.

Abstract: Drone racing is a popular sport where human pilots control their drones via radio frequency to fly at high speed through complex race tracks. The latter has motivated to pose the question: could an autonomous drone beat a human in a drone race. Thus, some works have dealt with the autonomous drone racing challenge; however, very few works have dealt with the case of a race when an opponent is present in the track. In this work, we present an initial approach to address the problem of autonomous navigation while considering the presence of an opponent in the race track. To address this problem, we present a compact Convolutional Neural Network that predicts flight commands from a set of camera images captured on the fly. This network has been trained by imitation; this is, the network learns from examples generated by a human pilot. It is important to highlight that there is no explicit gate detection or trajectory planning/tracking in our approach. We have carried out experiments in the Gazebo simulator in a race track where the autonomous drone will face an opponent on its way to the gate. Our results show that the network manages to pilot the drone to evade the opponent, and after the evasion, the drone gets on-track towards the gate.

ABSTRACT The condition of coincidence between analog and digital television services, as well as the global evolution of mobile services, define our country's need to make a more efficient use of the spectrum. In this sense, it is proposed the analysis of Single Frequency Network (SFN) as an alternative to the currently deployed in Havana Multifrequency Network (MFN). The proposed group of simulations is a first approaching to the advantages and limitations of this kind of broadcasting network at an early stage of its possible deployment. The used design strategy is based on the selection of delays for each transmitter in the network as a way to limit the cases of destructive self-interference. One of the objectives is to validate this strategy and the applicability of SFN under the evaluation conditions. The current coverage is maintained with a protection margin of 9 us for the theoretical guard interval of 74 us and 4 dB for the 15 dB of signal/interference (S/I) required for DTMB mode 6 demodulation. One of the main contributions of this research is the software of own creation Interference Simulator for SFN. It allows the analysis of interference in networks of multiple transmitters and it is based on the processing of the data provided by Radio Mobile about the co-channel interference between only two of the transmitters.

RESUMEN La actual condición de simultaneidad de los servicios de Televisión Analógica y Digital, así como la evolución y crecimiento del número de servicios móviles, definen la necesidad en nuestro país de estudiar nuevas vías para hacer un uso más eficiente del espectro radioeléctrico. En este sentido, en el presente trabajo, se propone el análisis de una red de frecuencia única (SFN) como alternativa a la red de múltiples frecuencias (MFN) actualmente desplegada en La Habana para la radiodifusión de TVD. El grupo de simulaciones propuesto constituye una primera aproximación a las bondades y limitaciones de este tipo de red de radiodifusión en una etapa inicial de su posible despliegue. La estrategia de diseño empleada se basa en la selección de los retardos para cada transmisor de la red, buscando limitar los casos de auto-interferencia destructiva. Se comprueba la validez de esta estrategia y la aplicabilidad de SFN en las condiciones de evaluación, pues se mantiene la cobertura actual con un margen de protección de 9 µs para el intervalo de guarda teórico de 74 µs y de 4 dB respecto a los 15 dB de señal/interferencia (S/I) necesarios para la demodulación en DTMB en modo 6. Como uno de los principales aportes se introduce el software de creación propia Simulador de Interferencias para SFN que permite el análisis de interferencias en redes de múltiples transmisores, basado en el procesamiento de los datos que aporta Radio Mobile sobre la interferencia co-canal entre solo dos de los transmisores.

Abstract: This paper aims to present the results obtained by comparing two reactive routing protocols: ad hoc on-demand distance vector and dynamic source routing protocol. This served to evaluate quality of service quality metrics in two wireless network topologies in a rural isolated electric microgrid. The network infrastructure was simulated using the Network Simulator 2. The quality of service metrics compared in this study includes the average delay, the throughput, the rate of successfully delivered packets, and the jitter in two network topologies: tree and mesh. The results showed that the reactive routing on-demand protocol presented better service quality indicators in both topologies. In conclusion, the routing protocol complies with the communication requirements for the operation of a rural isolated microgrid with low node density.

Resumen: Este documento presenta los resultados obtenidos al comparar dos protocolos de encaminamiento reactivos: vector distancia bajo demanda ad hoc y el protocolo de fuente dinámica. Se evaluaron métricas de calidad de servicio en dos topologías de red inalámbricas en una microrred eléctrica rural aislada. La estructura de la red fue simulada en Network Simulator 2, comparando las métricas de calidad de servicio como lo son el retardo promedio, el caudal de datos, la tasa de paquetes entregados exitosamente y la variación del retardo para las topologías tipo de red: árbol y malla. Los resultados muestran que el protocolo de encaminamiento reactivo bajo demanda presentó mejores indicadores de calidad de servicio en ambas topologías. Se concluye que el protocolo de encaminamiento reactivo bajo demanda cumpliría con los requisitos de telecomunicaciones para la operación de una microrred rural aislada con baja densidad de nodos.

Resumen CHEMical KINetics SimuLATOR (Chemkinlator) es una interfaz gráfica para realizar simulaciones de mecanismos de reacción. La interfaz le permite al usuario ver y cambiar los parámetros de una red de reacciones en una única ventana. Chemkinlator puede realizar tres tipos de simulaciones cinéticas: Time Series, calcula la concentración de cada especie en un intervalo de tiempo del modelo estudiado; Bifurcation, es el resultado de ejecutar varias veces las simulaciones del modo Time Series, cambiando gradualmente diferentes constantes de velocidad; y Flow/ Temperature es una serie de tiempo en la que se tiene en cuenta el efecto del flujo considerando un Reactor de Flujo Continuo bien Agitado y el efecto de la temperatura sobre las constantes de velocidad según la ecuación de Arrhenius. En nuestro grupo de investigación, Chemkinlator ha sido la herramienta principal para verificar las predicciones hechas por los algoritmos que analizan el fenómeno de homochiralidad. Chemkinlator está escrito en C++14 y Qt, y usa la subrutina de Fortran DLSODE para resolver las ecuaciones diferenciales relacionadas con los mecanismos de reacción. Chemkinlator es software de código abierto bajo la licencia Apache 2.0 y se puede descargar libremente de https://gitlab.com/homochirality/chemkinlator.

Abstract CHEMicalKINetics SimuLATOR (Chemkinlator) is a Graphical User Interface for the simulation of reaction mechanisms. The interface allows the user to see and change the parameters of a reaction network within a single window. Chemkinlator comes with built-in support for three types of kinetic simulations: Time Series, which computes the concentration of all species in an interval of time for the defined model; Bifurcation diagrams, which are the result of running several Time Series simulations over gradually different kinetic rate constants; and Flow/Temperature time series, which takes into account the effect of flow in the Continuous-flow well-Stirred Tank Reactor, and the effect of temperature on the rates constants according to the Arrhenius equation. In our research group, Chemkinlator has been the primary tool used to test the predictions made by algorithms that analyze homochirality phenomena. Chemkinlator is written in C++14 and Qt, and it uses the Fortran subroutine DLSODE to solve the differential equations associated with the reaction networks. Chemkinlator is open source software under the Apache 2.0 license and can be downloaded freely from https://gitlab.com/homochirality/chemkinlator.

Resumo O CHEMical KINetics SimuLATOR (Chemkinlator) é uma interface gráfica para realizar simulações de mecanismos de reação. A interface permite ao usuário visualizar e alterar os parâmetros de uma rede de reação em uma única janela. O Chemkinlator pode realizar três tipos de simulações cinéticas: Time Series, calcula a concentração de cada espécie em um intervalo de tempo do modelo estudado; Bifurcation, é o resultado de executar várias vezes as simulações do modo Time Series, modificando gradualmente diferentes constantes de velocidade; e Flow/Temperature é uma serie de tempo que se considera o efeito do fluxo considerando um Reator de Fluxo Continuo bem Agitado e o efeito da temperatura sobre as constantes de velocidade pela equação de Arrhenius. No nosso grupo de investigação, o Chemkinlator tem sido a principal ferramenta para verificar as predições realizadas pelos algoritmos que analisam o fenómeno de homoquiralidade. O Chemkinlator está escrito em C++14 e Qt, e usa a sub-rotina de Fortran DLSODE para resolver as equações diferenciais relacionadas com os mecanismos de reação. O Chemkinlator é um software de código aberto baixo a licença Apache 2.0 e pode ser descarregado livremente em https://gitlab.com/homochirality/chemkinlator.

Abstract The Flying Ad-hoc Network (FANET) networks have often operated in regions that are difficult to reach and have no fixed infrastructure. The use of devices such as Unmanned Aerial Vehicles (UAV) enable aerial networks to be created that are extremely fast, although there are no specific routing protocols for this type of network that can make communication more efficient among these devices. For this reason, this paper sets out a specific routing protocol for FANET networks that is designed for the discovery of routes among UAV devices. Evidence of the benefits of this strategy has been obtained through simulation by the Network Simulator version 2.

RESUMO Objetivo: Propor um modelo preliminar de inteligência artificial, baseado em redes neurais artificiais, para previsão do risco de infecção hospitalar em unidades de cuidado intensivo. Métodos: Foi usada uma rede neural artificial, que utiliza aprendizagem supervisionada. A geração dos conjuntos de dados baseia-se em dados derivados do sistema Japanese Nosocomial Infection Surveillance . Estudamos como o Java Neural Network Simulator aprende a categorizar esses pacientes para prever o respectivo risco de infecção hospitalar. As simulações são realizadas com diferentes algoritmos de aprendizagem por retropropagação e diversos grupos de parâmetros, comparando-se os resultados com base na soma dos erros quadráticos e erros médios por padrão. Resultados: O algoritmo de retropropagação com momentum mostrou desempenho superior ao do algoritmo de retropropagação. O desempenho foi melhor com os valores de parâmetros do arquivo xor. README em comparação aos parâmetros default . Não houve falhas na categorização de pacientes quanto ao respectivo risco de infecção hospitalar. Conclusão: Embora esse modelo se baseie em um conjunto de dados sintéticos, o excelente desempenho observado com um pequeno número de padrões sugere que o uso de números maiores de variáveis e camadas de rede para analisar volumes maiores de dados pode criar redes neurais artificiais poderosas, possivelmente capazes de prever com precisão o risco de infecção hospitalar em unidades de cuidado intensivo. O uso de um banco de dados real durante as simulações torna possível a realização da capacidade preditiva desse modelo.

ABSTRACT Objective: To propose a preliminary artificial intelligence model, based on artificial neural networks, for predicting the risk of nosocomial infection at intensive care units. Methods: An artificial neural network is designed that employs supervised learning. The generation of the datasets was based on data derived from the Japanese Nosocomial Infection Surveillance system. It is studied how the Java Neural Network Simulator learns to categorize these patients to predict their risk of nosocomial infection. The simulations are performed with several backpropagation learning algorithms and with several groups of parameters, comparing their results through the sum of the squared errors and mean errors per pattern. Results: The backpropagation with momentum algorithm showed better performance than the backpropagation algorithm. The performance improved with the xor. README file parameter values compared to the default parameters. There were no failures in the categorization of the patients into their risk of nosocomial infection. Conclusion: While this model is still based on a synthetic dataset, the excellent performance observed with a small number of patterns suggests that using higher numbers of variables and network layers to analyze larger volumes of data can create powerful artificial neural networks, potentially capable of precisely anticipating nosocomial infection at intensive care units. Using a real database during the simulations has the potential to realize the predictive ability of this model.

Abstract: This paper presents a novel modelling framework for a component-based architecture that allows validating control strategies for urban traffic networks integrating intelligent traffic control based on cyber-physical transport systems, specifically using V2X (vehicle-to-vehicle) technology. The architecture named ITSiE (Integrated tools in a Simulated Environment), is constituted of three components that work in a cooperative way via a middleware, allowing to analyze the traffic behavior in a simulated environment for a defined urban area (selected network streets) and evaluate the impact of using intelligent transport strategies based in V2X. The first component named CiudadelaSIM executes the simulation and communicate in real time with the other components; the second component named SCPV (Road Proposal Capture System (by its meaning in Spanish), is used to define the simulated scenario (traffic lights, traffic policies, information objects) and the third component is a Control Speed System (SpeCo) which allow defining the intelligent strategy, through the capture of multiple techniques and methods to control the speed of the vehicles in a segment with particular features.

Abstract The goal of this paper is to characterize and compare different network simulators, to establish the most appropriate network simulation tool, based on user needs. A series of useful parameters in network simulation for each analyzed tool, such as the type of use, the type of license required, the learning curve, the operative system required, the type of graphic results, the technologies in level 2 and 3 available, and type of network traffic allowed to simulate are defined. This information was summarized in a matrix that links each simulator and the relevant characteristics. The table allows any user to choose a network simulator, considering its context and the simulator goal. The most relevant factors for selecting a simulation tool is the learning curve and the type of license.

Resumen El objetivo de este artículo es caracterizar y comparar diferentes herramientas de simulación de red, entregando pautas para realizar una selección apropiada de acuerdo a las necesidades de cada usuario o proyecto. Se definieron una serie de características que debe cumplir una herramienta de simulación, entre las cuales se destacan: el tipo de uso dado a la herramienta, la licencia requerida, curva de aprendizaje requerida, plataforma o sistema operativo que requiere para funcionar, resultados gráficos que entregan, que tecnologías de nivel 2 y 3 soportan, y que tipo de tráfico permite modelar. Los resultados obtenidos después de caracterizar cada herramienta de simulación se presentan en una tabla comparativa que permite al lector elegir la herramienta de simulación según sus necesidades. Los factores más influyentes en la selección de una herramienta de simulación son la curva de aprendizaje y el tipo de licencia.

The Time-Slotted Channel Hopping (TSCH) mode for medium access control (MAC) included in the standard IEEE 802.15.4 has been designed as the multichannel MAC protocol for Low-power and lossy networks (LLNs), a key component of the Internet of Things (IoT). Its flexibility makes the TSCH mode a very promising candidate for the future of the MAC layer in LLNs. As such, its performance under different conditions must be assessed, so that accurate guidelines for its application can be drawn. In this paper, we present an experimental evaluation of the protocol based on simulations on ContikiOS Java Simulator (COOJA). The experimental setup is based on the 6TiSCH architecture for LLNs. Results show that TSCH performs better under conditions of medium traffic load than under low or high traffic load

El modo Salto de Canal por Ranuras de Tiempo (TSCH1) para control de acceso al medio (MAC) en el estándar IEEE 802.15.4 ha sido designado como el protocolo MAC estándar para redes de baja potencia con pérdidas (LLN), un componente clave en la denominada Internet de las Cosas (IoT). Su flexibilidad hace del modo TSCH un candidato promisorio para el futuro de la capa MAC en LLN. Por tanto, es indispensable evaluar su desempeño bajo diferentes condiciones de carga de tráfico con el fin de trazar guías para su empleo y configuración en diferentes aplicaciones de IoT. En este artículo, se presenta una evaluación experimental del desempeño de TSCH basada en simulaciones en el simulador en Java de ContikiOS (COOJA). La evaluación se realiza utilizando diferentes valores de carga de tráfico en una configuración típica de LLN; y el desempeño del protocolo es evaluado en términos de razón de entrega de paquetes (PDR), demora extremo a extremo y consumo de energía. Los resultados muestran que TSCH se desempeña mejor en condiciones de tráfico medias que con baja y alta carga de tráfico

Abstract Simulation tools are essential for validating any research idea before it is being implemented. This is very essential for all the researchers irrespective of the field of research. Simulators provide a way for analysing the design. There are many simulation tools available for the network researchers. Network Simulators are used to test the performance of existing or new algorithms and protocols.Some of the simulation tools in networking include OPNET (optimized Network Engineering Tool), NS-2 (Network Simulator version 2), OMNET++ (Objective Modular NETwork Testbed in C++), GloMoSim (Global Mobile Information System Simulator), QualNet, NetSim (Network Simulator), JiST/SWANS (Java in Simulation Time/ Scalable Wireless Network Simulator), J-Sim (Java-based simulation) and NS-3 (Network Simulator Version 3). Simulation tools may be open source or commercial. In this paper, both the open source and commercial simulators are discussed. This survey reveals that for simulating large networks, simulators like OPNET, GloMoSim, QualNet, NetSim, JiST/SWANs and NS-3 can be used. For small network simulation NS-2 and J-Sim can be preferred. Open source simulators are poor in documentation. Commercial simulators have good documentation. Based on the requirements of the research, a proper simulation tool can be selected.