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This brief addresses the gearshifting problem for Semi-Automated Manual Transmissions (S-AMT) in powered two-wheelers, a powertrain setup that allows fast and smooth gear shifts with minimal modifications to the traditional manual powertrain layout. We show that with a proper synchronization between the electronic clutch and engine torque, excellent gearshift performance can be obtained, but requires precise parameters calibration. We thus propose the use of a data-driven approach with Constrained Bayesian Optimization to optimize control parameters. The procedure's effectiveness is demonstrated on a real vehicle, assessing performance in terms of optimality, convergence rate, and repeatability., Comment: 8 pages, 9 figures

We present a coarse-to-fine neural deformation model to simultaneously recover the camera pose and the 4D reconstruction of an unknown object from multiple RGB sequences in the wild. To that end, our approach does not consider any pre-built 3D template nor 3D training data as well as controlled illumination conditions, and can sort out the problem in a self-supervised manner. Our model exploits canonical and image-variant spaces where both coarse and fine components are considered. We introduce a neural local quadratic model with spatio-temporal consistency to encode fine details that is combined with canonical embeddings in order to establish correspondences across sequences. We thoroughly validate the method on challenging scenarios with complex and real-world deformations, providing both quantitative and qualitative evaluations, an ablation study and a comparison with respect to competing approaches. Our project is available at https://github.com/smontode24/4DPV., Comment: 17th Asian Conference on Computer Vision (ACCV 2024)

An ordinary differential model is proposed to understand the role of egg quiescence on the efficacy of releasing the Wolbachia-carrying mosquito to suppress or diminish the wild mosquito population. The model has up to four steady states, which are: the persistence of the uninfected population and the extinction of the infected one, the persistence of the infected population and the extinction of the uninfected one, the extinction of both populations, and the persistence of both populations. Their stability is given by four thresholds; two are the fitness of infected and uninfected populations when isolated, and the other two are the relative fitness when they are competing. Bifurcation diagrams, phase space, and parameter space are shaped by the sex ratio that can be manipulated by the Wolbachia symbiont. A sensitive analysis indicates that the uninfected population always maximizes its fitness according to the environmental conditions throughout, changing the quiescence rate. Because Wolbachia-infected eggs do not survive quiescence or adults emerging from it are infertile, the risk of arbovirus transmission increases during or after environmental stress that triggers quiescence. This can jeopardize the use of Wolbachia-infected mosquito to control arbovirus transmissions in regions where quiescence occurs at a high rate., Comment: 32 pages, 4 figures, 3 tables and 3 appendices

We report experimental investigations of spin-to-charge current conversion and charge transfer dynamics (CT) at the interface of graphene/WS$_2$ van der Waals heterostructure. Pure spin current was produced by the spin precession in the microwave-driven ferromagnetic resonance of a permalloy film (Py-Ni$_{81}$Fe$_{19}$) and injected into the graphene/WS$_2$ heterostructure through the spin pumping process. The observed spin-to-charge current conversion in the heterostructure is attributed to inverse Rashba-Edelstein effect (IREE) at the graphene/WS$_2$ interface. Interfacial CT dynamics in this heterostructure was investigated based on the framework of core-hole-clock (CHC) approach. The results obtained from spin pumping and CHC studies show that the spin-to-charge current conversion and charge transfer process are more efficient in the graphene/WS$_2$ heterostructure compared to isolated WS2 and graphene films. The results show that the presence of WS$_2$ flakes improves the current conversion efficiency. These experimental results are corroborated by density functional theory (DFT) calculations, which reveal (i) Rashba spin-orbit splitting of graphene orbitals and (ii) electronic coupling between graphene and WS$_2$ orbitals. This study provides valuable insights for optimizing the design and performance of spintronic devices., Comment: 25 pages, 7 figures

Light field cameras and multi-camera arrays have emerged as promising solutions for accurately estimating depth by passively capturing light information. This is possible because the 3D information of a scene is embedded in the 4D light field geometry. Commonly, depth estimation methods extract this information relying on gradient information, heuristic-based optimisation models, or learning-based approaches. This paper focuses mainly on explicitly understanding and exploiting 4D geometrical cues for light field depth estimation. Thus, a novel method is proposed, based on a non-learning-based optimisation approach for depth estimation that explicitly considers surface normal accuracy and occlusion regions by utilising a fully explainable 4D geometric model of the light field. The 4D model performs depth/disparity estimation by determining the orientations and analysing the intersections of key 2D planes in 4D space, which are the images of 3D-space points in the 4D light field. Experimental results show that the proposed method outperforms both learning-based and non-learning-based state-of-the-art methods in terms of surface normal angle accuracy, achieving a Median Angle Error on planar surfaces, on average, 26.3\% lower than the state-of-the-art, and still being competitive with state-of-the-art methods in terms of Mean Squared Error $\vc{\times}$ 100 and Badpix 0.07.

Computational Design approaches facilitate the generation of typographic design, but evaluating these designs remains a challenging task. In this paper, we propose a set of heuristic metrics for typographic design evaluation, focusing on their legibility, which assesses the text visibility, aesthetics, which evaluates the visual quality of the design, and semantic features, which estimate how effectively the design conveys the content semantics. We experiment with a constrained evolutionary approach for generating typographic posters, incorporating the proposed evaluation metrics with varied setups, and treating the legibility metrics as constraints. We also integrate emotion recognition to identify text semantics automatically and analyse the performance of the approach and the visual characteristics outputs., Comment: Paper accepted be presented in the 13th International Conference Artificial Intelligence in Music, Sound, Art and Design -- EvoMUSART 2024, Held as Part of EvoStar 2024, Aberystwyth, Wales, United Kingdom, April 3\textendash{}5, 2024

This paper proposes a generative approach for the automatic typesetting of books in desktop publishing. The presented system consists in a computer script that operates inside a widely used design software tool and implements a generative process based on several typographic rules, styles and principles which have been identified in the literature. The performance of the proposed system is tested through an experiment which included the evaluation of its outputs with people. The results reveal the ability of the system to consistently create varied book designs from the same input content as well as visually coherent book designs with different contents while complying with fundamental typographic principles., Comment: 26 pages, 5 figures. Revised version published at Visual Informatics, 7(2), pp. 1\textendash{}12

The hybridization process has recently touched also the world of agricultural vehicles. Within this context, we develop an Energy Management Strategy (EMS) aiming at optimizing fuel consumption, while maintaining the battery state of charge. A typical feature of agricultural machines is that their internal combustion engine is speed controlled, tracking the reference requested by the driver. In view of avoiding any modification on this original control loop, an add-on EMS strategy is proposed. In particular, we employ a multi-objective Model Predictive Control (MPC), taking into account the fuel consumption minimization and the speed tracking requirement, including the engine speed controller in the predictive model. The proposed MPC is tested in an experimentally-validated simulation environment, representative of an orchard vineyard tractor., Comment: Accepted for publication on IEEE Transactions on Vehicular Technology

The rapid spread of Lithium-ions batteries (LiBs) for electric vehicles calls for the development of accurate physical models for Battery Management Systems (BMSs). In this work, the electrochemical Single Particle Model (SPM) for a high-power LiFePO4 cell is experimentally identified through a set of non-invasive tests (based on voltage-current measurements only). The SPM is identified through a two-step procedure in which the equilibrium potentials and the kinetics parameters are characterized sequentially. The proposed identification procedure is specifically tuned for LiFePO4 chemistry, which is particularly challenging to model due to the non-linearity of its open circuit voltage (OCV) characteristic. The identified SPM is compared with a second-order Equivalent Circuit Model (ECM) with State of Charge dependency. Models performance is compared on dynamic current profiles. They exhibit similar performance when discharge currents peak up to 1C (RMSE between simulation and measures smaller than 20 mV) while, increasing the discharge peaks up to 3C, ECM's performance significantly deteriorates while SPM maintains acceptable RMSE (< 50 mV)., Comment: Accepted for publication at the IFAC World Congress 2023

Combining the advantages of standard bicycles and electrified vehicles, electric bikes (e-Bikes) are promising vehicles to reduce emission and traffic. The current literature on e-Bikes ranges from works on the energy management to the vehicle control to properly govern the human-vehicle interaction. This last point is fundamental in chain-less series bikes, where the link between the human and the vehicle behavior is only given by a control law. In this work, we address this problem in a series-parallel bike. In particular, we provide an extension of the virtual-chain concept, born for series bikes, and then we improve it developing a virtual-bike framework. Experimental results are used to validate the effectiveness of the solutions, when the cyclist is actually riding the bike., Comment: Accepted for publication at the IFAC World Congress 2023

We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case study illustrates that even with relatively few sMolBoxes, it is possible to express complex analyses tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods., Comment: 10 pages, 9 figures, IEEE VIS, TVCG

Computational approaches are beginning to be used to design dynamic visual identities fuelled by data and generative processes. In this work, we explore these computational approaches in order to generate a visual identity that creates bespoke letterings and images. We achieve this developing a generative design system that automatically assembles black and white visual modules. This system generates designs performing two main methods: (i) Assisted generation; and (ii) Automatic generation. Assisted generation method produces outputs wherein the placement of modules is determined by a configuration file previous defined. On the other hand, the Automatic generation method produces outputs wherein the modules are assembled to depict an input image. This system speeds up the process of design and deployment of one visual identity design as well as it generates outputs visual coherent among them. In this paper, we compressively describe this system and its achievements., Comment: Paper presented in 10th Typography Meeting "Borders", 22--23 Oct. 2019, Matosinhos, Portugal

We present ESSYS* Sharing #UC, an audiovisual installation artwork that reflects upon the emotional context related to the university and the city of Coimbra, based on the data shared about them on Twitter. The installation was presented in an urban art gallery of C\'irculo de Artes Pl\'asticas de Coimbra during the summer and autumn of 2021. In the installation space, one may see a collection of typographic posters displaying the tweets and listening to an ever-changing ambient sound. The present audiovisuals are created by an autonomous computational creative approach, which employs a neural classifier to recognize the emotional context of a tweet and uses this resulting data as feedstock for the audiovisual generation. The installation's space is designed to promote an approach and blend between the online and physical perceptions of the same location. We applied multiple experiments with the proposed approach to evaluate the capability and performance. Also, we conduct interview-based evaluation sessions to understand how the installation elements, especially poster designs, are experienced by people regarding diversity, expressiveness and possible employment in other commercial and social scenarios., Comment: Paper to be published in 2022 IEEE VIS Arts Program (VISAP 2022). For the associated supplementary materials, see https://cdv.dei.uc.pt/essys_sharing_uc/