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See detailAn Evolutionary Algorithm to Optimise a Distributed UAV Swarm Formation System
Stolfi Rosso, Daniel UL; Danoy, Grégoire UL

in Applied Sciences (2022), 12(20),

In this article, we present a distributed robot 3D formation system optimally parameterised by a hybrid evolutionary algorithm (EA) in order to improve its efficiency and robustness. To achieve that, we ... [more ▼]

In this article, we present a distributed robot 3D formation system optimally parameterised by a hybrid evolutionary algorithm (EA) in order to improve its efficiency and robustness. To achieve that, we first describe the novel distributed formation algorithm3 (DFA3), the proposed EA, and the two crossover operators to be tested. The EA hyperparameterisation is performed by using the irace package and the evaluation of the three case studies featuring three, five, and ten unmanned aerial vehicles (UAVs) is performed through realistic simulations by using ARGoS and ten scenarios evaluated in parallel to improve the robustness of the configurations calculated. The optimisation results, reported with statistical significance, and the validation performed on 270 unseen scenarios show that the use of a metaheuristic is imperative for such a complex problem despite some overfitting observed under certain circumstances. All in all, the UAV swarm self-organised itself to achieve stable formations in 95% of the scenarios studied with a plus/minus ten percent tolerance. [less ▲]

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See detailLearning to Optimise a Swarm of UAVs
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

in Applied Sciences (2022), 12(19 9587),

The use of Unmanned Aerial Vehicles (UAVs) has shown a drastic increase in interest in the past few years. Current applications mainly depend on single UAV operations, which face critical limitations such ... [more ▼]

The use of Unmanned Aerial Vehicles (UAVs) has shown a drastic increase in interest in the past few years. Current applications mainly depend on single UAV operations, which face critical limitations such as mission range or resilience. Using several autonomous UAVs as a swarm is a promising approach to overcome these. However, designing an efficient swarm is a challenging task, since its global behaviour emerges solely from local decisions and interactions. These properties make classical multirobot design techniques not applicable, while evolutionary swarm robotics is typically limited to a single use case. This work, thus, proposes an automated swarming algorithm design approach, and more precisely, a generative hyper-heuristic relying on multi-objective reinforcement learning, that permits us to obtain not only efficient but also reusable swarming behaviours. Experimental results on a three-objective variant of the Coverage of a Connected UAV Swarm problem demonstrate that it not only permits one to generate swarming heuristics that outperform the state-of-the-art in terms of coverage by a swarm of UAVs but also provides high stability. Indeed, it is empirically demonstrated that the model trained on a certain class of instances generates heuristics and is capable of performing well on instances with a different size or swarm density. [less ▲]

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See detailEmpirical Perturbation Analysis of Two Adversarial Attacks: Black Box versus White Box
Chitic, Raluca; Topal, Ali Osman UL; Leprevost, Franck UL

in Applied Sciences (2022), 12(14), 7339

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See detailBead Geometry Prediction in Laser-Wire Additive Manufacturing Process Using Machine Learning: Case of Study
Mbodj, Natago Guilé UL; Abuabiah, Mohammad UL; Plapper, Peter UL et al

in Applied Sciences (2021), Volume 11(Issue 24),

In Laser Wire Additive Manufacturing (LWAM), the final geometry is produced using the layer-by-layer deposition (beads principle). To achieve good geometrical accuracy in the final product, proper ... [more ▼]

In Laser Wire Additive Manufacturing (LWAM), the final geometry is produced using the layer-by-layer deposition (beads principle). To achieve good geometrical accuracy in the final product, proper implementation of the bead geometry is essential. For this reason, the paper focuses on this process and proposes a layer geometry (width and height) prediction model to improve deposition accuracy. More specifically, a machine learning regression algorithm is applied on several experimental data to predict the bead geometry across layers. Furthermore, a neural network-based approach was used to study the influence of different deposition parameters, namely laser power, wire-feed rate and travel speed on bead geometry. To validate the effectiveness of the proposed approach, a test split validation strategy was applied to train and validate the machine learning models. The results show a particular evolutionary trend and confirm that the process parameters have a direct influence on the bead geometry, and so, too, on the final part. Several deposition parameters have been found to obtain an accurate prediction model with low errors and good layer deposition. Finally, this study indicates that the machine learning approach can efficiently be used to predict the bead geometry and could help later in designing a proper controller in the LWAM process. [less ▲]

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See detailOcular Biometrics Recognition by Analyzing Human Exploration during Video Observations
Cazzato, Dario; Carcagni, Pierluigi; Cimarelli, Claudio UL et al

in Applied Sciences (2020), 10(13), 4548

Soft biometrics provide information about the individual but without the distinctiveness and permanence able to discriminate between any two individuals. Since the gaze represents one of the most ... [more ▼]

Soft biometrics provide information about the individual but without the distinctiveness and permanence able to discriminate between any two individuals. Since the gaze represents one of the most investigated human traits, works evaluating the feasibility of considering it as a possible additional soft biometric trait have been recently appeared in the literature. Unfortunately, there is a lack of systematic studies on clinically approved stimuli to provide evidence of the correlation between exploratory paths and individual identities in “natural” scenarios (without calibration, imposed constraints, wearable tools). To overcome these drawbacks, this paper analyzes gaze patterns by using a computer vision based pipeline in order to prove the correlation between visual exploration and user identity. This correlation is robustly computed in a free exploration scenario, not biased by wearable devices nor constrained to a prior personalized calibration. Provided stimuli have been designed by clinical experts and then they allow better analysis of human exploration behaviors. In addition, the paper introduces a novel public dataset that provides, for the first time, images framing the faces of the involved subjects instead of only their gaze tracks. [less ▲]

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See detailEffect of Red Blood Cell Aging In Vivo on Their Aggregation Properties In Vitro: Measurements with Laser Tweezers
Ermolinskiy, Petr; Lugovtsov, Andrei; Yaya, Francois et al

in Applied Sciences (2020), 10(21), 7581-10

Red blood cell (RBC) aggregation highly influences hemorheology and blood microcirculation in the human body. The aggregation properties of RBCs can vary due to numerous factors, including RBC age. The ... [more ▼]

Red blood cell (RBC) aggregation highly influences hemorheology and blood microcirculation in the human body. The aggregation properties of RBCs can vary due to numerous factors, including RBC age. The aim of this work was to estimate in vitro the differences in the RBC aggregation properties of different RBC age populations in single-cell experiments using laser tweezers. RBCs from five healthy volunteers were separated into four subpopulations by Percoll density gradient centrifugation. Each subpopulation of the RBC was separately resuspended in autologous plasma or dextran 70 kDa (50 mg/mL). The aggregation force between the single cells was measured with holographic laser tweezers. The obtained data demonstrated an enhancement of RBC aggregation force in doublets with age: the older the cells, the higher the aggregation force. The obtained data revealed the differences between the aggregation and aggregability of RBC in dependence of the RBC in vivo age. [less ▲]

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See detailHarnessing the Full Potential of Industrial Demand-Side Flexibility : an End-to-End Approach Connecting Machines with Markets through Service-Oriented IT Platforms
Roesch, Martin; Bauer, Dennis; Haupt, Leon et al

in Applied Sciences (2019), 9(18),

The growing share of renewable energy generation based on fluctuatingwind and solar energy sources is increasingly challenging in terms of power grid stability. Industrial demand-side response presents a ... [more ▼]

The growing share of renewable energy generation based on fluctuatingwind and solar energy sources is increasingly challenging in terms of power grid stability. Industrial demand-side response presents a promising way to balance energy supply and consumption. For this, energy demand is flexibly adapted based on external incentives. Thus, companies can economically benefit and at the same time contribute to reducing greenhouse gas emissions. However, there are currently some major obstacles that impede industrial companies fromtaking part in the energymarkets. A broad specification analysis systematically dismantles the existing barriers. On this foundation, a new end-to-end ecosystem of an energy synchronization platform is introduced. It consists of a business-individual company-side platform, where suitable services for energy-oriented manufacturing are offered. In addition, one market-side platform is established as a mediating service broker, which connects the companies to, e.g., third party service providers, energy suppliers, aggregators, and energy markets. The ecosystems aim at preventing vendor lock-in and providing a flexible solution, relying on open standards and offering an integrated solution through an end-to-end energy flexibility data model. In this article, the resulting functionalities are discussed and the remaining deficits outlined. [less ▲]

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