SOMA Network Model Based on Native Visibility Graph

In this article, we want to propose a new model of the network for analyzing the evolution algorithms.We focus on the graph called native visibility graph. We show how we can get a time series from the run ofthe self-organizing migrating algorithm and how we can convert these series into a network. At the end of thearticle, we focus on some basic network properties and we propose how can we use these properties for laterinvestigation. All experiments run on well-known CEC 2016 benchmarks

Design, Testing and Evaluation of Robotic Mechanisms and Systems for Environmental Monitoring and Interaction

Unmanned Aerial Vehicles (UAVs) have significantly lowered the cost of remote aerial data collection. The next generation of UAVs, however, will transform the way that scientists and practitioners interact with the environment. In this thesis, we address the challenges of flying low over water to collect water samples and temperature data. We also develop a system that allows UAVs to ignite prescribed fires. Specifically, this thesis contributes a new peristaltic pump designed for use on a UAV for collecting water samples from up to 3m depth and capable of pumping over 6m above the water. Next, temperature sensors and their deployment on UAVs, which have successfully created a 3D thermal structure map of a lake, contributes to mobile sensors. A sub-surface sampler, the “Waterbug” which can sample from 10m deep and vary buoyancy for longer in-situ analysis contributes to robotics and mobile sensors. Finally, we designed and built an Unmanned Aerial System for Fire Fighting (UAS-FF), which successfully ignited over 150 acres of prescribed fire during two field tests and is the first autonomous robot system for this application. Advisers: Carrick Detweiler and Carl Nelso

Multiscale Modelling Of Platelet Aggregation

During clotting under flow, platelets bind and activate on collagen and release autocrinic factors such ADP and thromboxane, while tissue factor (TF) on the damaged wall leads to localized thrombin generation. Toward patient-specific simulation of thrombosis, a multiscale approach was developed to account for: platelet signaling (neural network trained by pairwise agonist scanning, PAS-NN), platelet positions (lattice kinetic Monte Carlo, LKMC), wall-generated thrombin and platelet-released ADP/thromboxane convection-diffusion (PDE), and flow over a growing clot (lattice Boltzmann). LKMC included shear-driven platelet aggregate restructuring. The PDEs for thrombin, ADP, and thromboxane were solved by finite element method using cell activation-driven adaptive triangular meshing. At all times, intracellular calcium was known for each platelet by PAS-NN in response to its unique exposure to local collagen, ADP, thromboxane, and thrombin. The model accurately predicted clot morphology and growth with time on collagen/TF surface as compared to microfluidic blood perfusion experiments. The model also predicted the complete occlusion of the blood channel under pressure relief settings. Prior to occlusion, intrathrombus concentrations reached 50 nM thrombin, ~1 μM thromboxane, and ~10 μM ADP, while the wall shear rate on the rough clot peaked at ~1000-2000 sec-1. Additionally, clotting on TF/collagen was accurately simulated for modulators of platelet cyclooxygenase-1, P2Y1, and IP-receptor. The model was then extended to a rectangular channel with symmetric Gaussian obstacles representative of a coronary artery with severe stenosis. The upgraded stenosis model was able to predict platelet deposition dynamics at the post-stenotic segment corresponding to development of artery thrombosis prior to severe myocardial infarction. The presence of stenosis conditions alters the hemodynamics of normal hemostasis, showing a different thrombus growth mechanism. The model was able to recreate the platelet aggregation process under the complex recirculating flow features and make reasonable prediction on the clot morphology with flow separation. The model also detected recirculating transport dynamics for diffusible species in response to vortex features, posing interesting questions on the interplay between biological signaling and prevailing hemodynamics. In future work, the model will be extended to clot growth with a patient cardio-vasculature under pulsatile flow conditions

An overview on structural health monitoring: From the current state-of-the-art to new bio-inspired sensing paradigms

In the last decades, the field of structural health monitoring (SHM) has grown exponentially. Yet, several technical constraints persist, which are preventing full realization of its potential. To upgrade current state-of-the-art technologies, researchers have started to look at nature’s creations giving rise to a new field called ‘biomimetics’, which operates across the border between living and non-living systems. The highly optimised and time-tested performance of biological assemblies keeps on inspiring the development of bio-inspired artificial counterparts that can potentially outperform conventional systems. After a critical appraisal on the current status of SHM, this paper presents a review of selected works related to neural, cochlea and immune-inspired algorithms implemented in the field of SHM, including a brief survey of the advancements of bio-inspired sensor technology for the purpose of SHM. In parallel to this engineering progress, a more in-depth understanding of the most suitable biological patterns to be transferred into multimodal SHM systems is fundamental to foster new scientific breakthroughs. Hence, grounded in the dissection of three selected human biological systems, a framework for new bio-inspired sensing paradigms aimed at guiding the identification of tailored attributes to transplant from nature to SHM is outlined.info:eu-repo/semantics/acceptedVersio

Optimal Control of Hybrid Systems and Renewable Energies

This book is a collection of papers covering various aspects of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). In particular, attention is focused both on the optimal control of new technologies and on their integration in buildings, microgrids, and energy markets. The examples presented in this book are among the most promising technologies for satisfying an increasing share of thermal and electrical demands with renewable sources: from solar cooling plants to offshore wind generation; hybrid plants, combining traditional and renewable sources, are also considered, as well as traditional and innovative storage systems. Innovative solutions for transportation systems are also explored for both railway infrastructures and advanced light rail vehicles. The optimization and control of new solutions for the power network are addressed in detail: specifically, special attention is paid to microgrids as new paradigms for distribution networks, but also in other applications (e.g., shipboards). Finally, optimization and simulation models within SCADA and energy management systems are considered. This book is intended for engineers, researchers, and practitioners that work in the field of energy, smart grid, renewable resources, and their optimization and control

Autonomous Aerial Water Sampling

Obtaining spatially separated, high frequency water samples from rivers and lakes is critical to enhance our understanding and effective management of fresh water resources. In this thesis we present an aerial water sampler and verify the system in field experiments. The aerial water sampler has the potential to vastly increase the speed and range at which scientists obtain water samples while reducing cost and effort. The water sampling system includes: 1) a mechanism to capture three 20 ml samples per mission; 2) sensors and algorithms for safe navigation and altitude approximation over water; and 3) software components that integrate and analyze sensor data, control the vehicle, and drive the sampling mechanism. In this thesis we validate the system in the lab, characterize key sensors, and present results of outdoor experiments. We compare water samples from local lakes obtained by our system to samples obtained by traditional sampling techniques. We find that nearly all water properties are consistent between the two techniques. These experiments show that despite the challenges associated with flying precisely over water, it is possible to quickly obtain water samples with an Unmanned Aerial Vehicle (UAV). Advisers: Carrick Detweiler and Matthew B. Dwye