Aggregation Pattern Transitions by Slightly Varying the Attractive/Repulsive Function

Among collective behaviors of biological swarms and flocks, the attractive/repulsive (A/R) functional links between particles play an important role. By slightly changing the cutoff distance of the A/R function, a drastic transition between two distinct aggregation patterns is observed. More precisely, a large cutoff distance yields a liquid-like aggregation pattern where the particle density decreases monotonously from the inside to the outwards within each aggregated cluster. Conversely, a small cutoff distance produces a crystal-like aggregation pattern where the distance between each pair of neighboring particles remains constant. Significantly, there is an obvious spinodal in the variance curve of the inter-particle distances along the increasing cutoff distances, implying a legible transition pattern between the liquid-like and crystal-like aggregations. This work bridges the aggregation phenomena of physical particles and swarming of organisms in nature upon revealing some common mechanism behind them by slightly varying their inter-individual attractive/repulsive functions, and may find its potential engineering applications, for example, in the formation design of multi-robot systems and unmanned aerial vehicles (UAVs)

Resilience Model for Teams of Autonomous Unmanned Aerial Vehicles (UAV) Executing Surveillance Missions

Teams of low-cost Unmanned Aerial Vehicles (UAVs) have gained acceptance as an alternative for cooperatively searching and surveilling terrains. These UAVs are assembled with low-reliability components, so unit failures are possible. Losing UAVs to failures decreases the team\u27s coverage efficiency and impacts communication, given that UAVs are also communication nodes. Such is the case of a Flying Ad Hoc Network (FANET), where the failure of a communication node may isolate segments of the network covering several nodes. The main goal of this study is to develop a resilience model that would allow us to analyze the effects of individual UAV failures on the team\u27s performance to improve the team\u27s resilience. The proposed solution models and simulates the UAV team using Agent-Based Modeling and Simulation. UAVs are modeled as autonomous agents, and the searched terrain as a two-dimensional M x N grid. Communication between agents permits having the exact data on the transit and occupation of all cells in real time. Such communication allows the UAV agents to estimate the best alternatives to move within the grid and know the exact number of all agents\u27 visits to the cells. Each UAV is simulated as a hobbyist, fixed-wing airplane equipped with a generic set of actuators and a generic controller. Individual UAV failures are simulated following reliability Fault Trees. Each affected UAV is disabled and eliminated from the pool of active units. After each unit failure, the system generates a new topology. It produces a set of minimum-distance trees for each node (UAV) in the grid. The new trees will thus depict the rearrangement links as required after a node failure or if changes occur in the topology due to node movement. The model should generate parameters such as the number and location of compromised nodes, performance before and after the failure, and the estimated time of restitution needed to model the team\u27s resilience. The study addresses three research goals: identifying appropriate tools for modeling UAV scenarios, developing a model for assessing UAVs team resilience that overcomes previous studies\u27 limitations, and testing the model through multiple simulations. The study fills a gap in the literature as previous studies focus on system communication disruptions (i.e., node failures) without considering UAV unit reliability. This consideration becomes critical as using small, low-cost units prone to failure becomes widespread

A collective intelligence framework for in silico representations of biomolecules and their activities.

The novel framework proposed in this thesis offers great potential for modelling the multi scale adaptive dynamics from molecules to cell at the physiological timescale. Most approaches for modelling biological phenomena focus on studies based on a specific instance of life, where specific biological problems are analysed. Mechanistic models based on universal principles will facilitate in developing general models for wider application in systems biology. The aim of the thesis is to investigate best approaches in representing biological complexity from molecules to cells and developing computational approaches to bring abstract theories to practical use by: (i) Identifying the major biomolecular self organising mechanism. (ii) Using a bottom-up integrative approach to model the internal organisation of the biological cell. (iii) Develop a Collective Intelligence based cell modelling and simulation environment to conduct analysis studies. This thesis argues that a system theoretic approach based on Collective Intelligence where the concepts of self organisation and emergence underlie the approach is ideal to represent the multi scale and multi objective nature of the biological cell from the bottom up. This thesis proposes a Collective Intelligence based cell modelling and simulation environment to conduct analysis studies on the collective behaviour of biomolecules

Anales del XIII Congreso Argentino de Ciencias de la Computación (CACIC)

Contenido: Arquitecturas de computadoras Sistemas embebidos Arquitecturas orientadas a servicios (SOA) Redes de comunicaciones Redes heterogéneas Redes de Avanzada Redes inalámbricas Redes móviles Redes activas Administración y monitoreo de redes y servicios Calidad de Servicio (QoS, SLAs) Seguridad informática y autenticación, privacidad Infraestructura para firma digital y certificados digitales Análisis y detección de vulnerabilidades Sistemas operativos Sistemas P2P Middleware Infraestructura para grid Servicios de integración (Web Services o .Net)Red de Universidades con Carreras en Informática (RedUNCI

Anales del XIII Congreso Argentino de Ciencias de la Computación (CACIC)

Contenido: Arquitecturas de computadoras Sistemas embebidos Arquitecturas orientadas a servicios (SOA) Redes de comunicaciones Redes heterogéneas Redes de Avanzada Redes inalámbricas Redes móviles Redes activas Administración y monitoreo de redes y servicios Calidad de Servicio (QoS, SLAs) Seguridad informática y autenticación, privacidad Infraestructura para firma digital y certificados digitales Análisis y detección de vulnerabilidades Sistemas operativos Sistemas P2P Middleware Infraestructura para grid Servicios de integración (Web Services o .Net)Red de Universidades con Carreras en Informática (RedUNCI