8,389 research outputs found

    Bush-crickets with very special ears and songs – review of the East African Phaneropterinae genus Dioncomena Brunner von Wattenwyl, 1878, with notes on its biogeography and the description of new species

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    This study focuses on the genus Dioncomena and its acoustics, particularly the unique songs produced by male Dioncomena that consist of several distinct elements in a fixed sequence, culminating in a coda that typically elicits a response from a receptive female. We also examine the inflated pronotal lobes, which we term prebullae, that are prominently developed in some Dioncomena species but not in others. We discuss the role of prebullae in the context of acoustic communication in Dioncomena and other related Phaneropterini genera that have similar lateral pronotal lobes. We found that prebullae size is correlated with habitat distribution, with larger prebullae occurring in isolated species while aggregation-prone species have smaller or less pronounced prebullae. Using micro-computer tomography we show sexual dimorphism in the 3D geometry of the acoustic tracheae, being larger in the male. Interestingly, the tracheae are coupled by a septum, like in field crickets, which suggests potential cross talk. We define three groups of Dioncomena based on altitude preferences, ecology, color patterns, and songs: the jagoi-, tanneri-, and ornata-groups. We describe the songs of several species, including newly identified species such as D. flavoviridis sp. nov., D. magombera sp. nov., D. ngurumontana sp. nov., D. sanje sp. nov., D. tanneri, D. versicolor sp. nov., and D. zernyi. We also provide information on the nymphs, development time, and mating behavior of various species reared in the laboratory, shedding light on their phenology and adaptations to their habitats

    Multimodal spatio-temporal deep learning framework for 3D object detection in instrumented vehicles

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    This thesis presents the utilization of multiple modalities, such as image and lidar, to incorporate spatio-temporal information from sequence data into deep learning architectures for 3Dobject detection in instrumented vehicles. The race to autonomy in instrumented vehicles or self-driving cars has stimulated significant research in developing autonomous driver assistance systems (ADAS) technologies related explicitly to perception systems. Object detection plays a crucial role in perception systems by providing spatial information to its subsequent modules; hence, accurate detection is a significant task supporting autonomous driving. The advent of deep learning in computer vision applications and the availability of multiple sensing modalities such as 360° imaging, lidar, and radar have led to state-of-the-art 2D and 3Dobject detection architectures. Most current state-of-the-art 3D object detection frameworks consider single-frame reference. However, these methods do not utilize temporal information associated with the objects or scenes from the sequence data. Thus, the present research hypothesizes that multimodal temporal information can contribute to bridging the gap between 2D and 3D metric space by improving the accuracy of deep learning frameworks for 3D object estimations. The thesis presents understanding multimodal data representations and selecting hyper-parameters using public datasets such as KITTI and nuScenes with Frustum-ConvNet as a baseline architecture. Secondly, an attention mechanism was employed along with convolutional-LSTM to extract spatial-temporal information from sequence data to improve 3D estimations and to aid the architecture in focusing on salient lidar point cloud features. Finally, various fusion strategies are applied to fuse the modalities and temporal information into the architecture to assess its efficacy on performance and computational complexity. Overall, this thesis has established the importance and utility of multimodal systems for refined 3D object detection and proposed a complex pipeline incorporating spatial, temporal and attention mechanisms to improve specific, and general class accuracy demonstrated on key autonomous driving data sets

    Evolución composicional e isotópica durante el Ediacarense en la sección del margen activoperi-Gondwánico preservada en el Dominio de Obejo-Valsequillo (SW del Macizo Ibérico)

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    Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Geológicas, leída el 15-12-2022In the Iberian Massif, the Ossa-Morena Complex and its prolongation in the NW Iberia allochthonous complexes represent the outermost section of the North African margin of Gondwana. This margin hosted a long-lived magmatic arc active at least between c. 750 to 500 Ma. The activity of this arc can be traced by sedimentary sequences deposited along the margin and igneous rocks generated during the arc construction, as well as by deposits generated during its progressive dismantling. The dynamic evolution of the peri-Gondwanan North-African margin from the Late Ediacaran to the Early Cambrian resulted in a complex tectonic configuration involving units with continental affinity and others of oceanic/transitional nature. This PhD Thesis presents the results obtained from the study of this margin section preserved in SW Iberia and suggests a possible geodynamic and petrogenetic model based on its geochemical and isotopic evolution. This peri-Gondwanan arc section is probably one of the best well-preserved in the Variscan Orogen. The results also include the identification of previously undescribed tectonostratigraphic units, and the detailed description of a new ophiolitic unit, the Mérida Ophiolite.The methodology used includes a structural study of the units implied in this section, whole-rock and isotopic (Sr-Nd) geochemistry, and geochronology (U-Pb ) of implied rocks. The study of the Merida ophiolite further included Hf isotopes in the analyzed zircons. The results have been published in journals of impact in Earth Sciences. In this sense, this volume is presented as a compilation of publications following a chronological and thematic order...En el Macizo Ibérico, el Complejo de Ossa-Morena y su prolongación en los complejos alóctonos del NW de Iberia representan la sección más externa del margen norteafricano de Gondwana. Este margen albergó un arco magmático de larga duración activo al menos entre c. 750 y 500 Ma. La actividad de este arco puede ser rastreada por las secuencias sedimentarias depositadas a lo largo del margen y las rocas ígneas generadas durante la construcción del mismo, así como por los depósitos generados durante su progresivo desmantelamiento. La evolución dinámica del margen norteafricano peri-Gondwánico entre el Ediacárico terminal y el comienzo del Cámbrico, dio lugar a una compleja estructuración tectónica que involucra unidades con afinidad continental y otras de tipo oceánico/transicional. Esta Tesis Doctoral presenta los resultados obtenidos del estudio de la sección de este margen preservada en el SW de Iberia, y plantea un posible modelo geodinámico y petrogenético en base a su evolución geoquímica e isotópica. Se trata de una de las secciones de arco peri-Gondwánico mejor preservadas en el Orógeno Varisco. Los resultados también incluyen el reconocimiento de unidades tectonoestratigráficas no descritas hasta el momento, y la descripción detallada de una nueva unidad ofiolítica, la Ofiolita de Mérida...Fac. de Ciencias GeológicasTRUEunpu

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    Additively Manufactured Shape-changing RF Devices Enabled by Origami-inspired Structures

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    The work to be presented in this dissertation explores the possibility of implementing origami-inspired shape-changing structures into RF designs to enable continuous performance tunability as well as deployability. The research not only experimented novel structures that have unique mechanical behaviour, but also developed automated additive manufacturing (AM) fabrication process that pushes the boundary of realizable frequency from Sub-6 GHz to mm-wave. High-performance origami-inspired reconfigurable frequency selective surfaces (FSSs) and reflectarray antennas are realized for the first time at mm-wave frequencies via AM techniques. The research also investigated the idea of combining mechanical tuning and active tuning methods in a hybrid manner to realize the first truly conformal beam-forming phased array antenna that can be applied onto any arbitrary surface and can be re-calibrated with a 3D depth camera.Ph.D

    HR-NeuS: Recovering High-Frequency Surface Geometry via Neural Implicit Surfaces

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    Recent advances in neural implicit surfaces for multi-view 3D reconstruction primarily focus on improving large-scale surface reconstruction accuracy, but often produce over-smoothed geometries that lack fine surface details. To address this, we present High-Resolution NeuS (HR-NeuS), a novel neural implicit surface reconstruction method that recovers high-frequency surface geometry while maintaining large-scale reconstruction accuracy. We achieve this by utilizing (i) multi-resolution hash grid encoding rather than positional encoding at high frequencies, which boosts our model's expressiveness of local geometry details; (ii) a coarse-to-fine algorithmic framework that selectively applies surface regularization to coarse geometry without smoothing away fine details; (iii) a coarse-to-fine grid annealing strategy to train the network. We demonstrate through experiments on DTU and BlendedMVS datasets that our approach produces 3D geometries that are qualitatively more detailed and quantitatively of similar accuracy compared to previous approaches

    Multi-sensor Mapping in natural environment: Three-Dimensional Reconstruction and temporal alignment

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    The objective of this thesis is the adaptation and development of robotic techniques, suitable for geometric three dimensional reconstruction of natural environments, leading into the temporal alignment of natural outdoor surveys. The objective has been achieved by adapting the state-of-the-art in field robotics and computer vision, such as sensor fusion and visual \acrfull{SLAM}. Throughout this thesis, we combine data generated by cameras, lasers and an inertial measurement unit, in order to geometrically reconstruct the surrounding scene as well as to estimate the trajectory. By supporting cameras with laser depth information, we show that it is possible to stabilize the state-of-the-art in visual odometry, and recover scale for visual maps. We also show that factor graphs are powerful tools for sensor fusion, and can be used for a generalized approach involving multiple sensors. Using semantic knowledge, we constrain the \acrfull{ICP} in order to build keyframes as well as to align them both spatially and temporally. Hierarchical clustering of ICP-generated transformations is then used to both eliminate outliers and find alignment consensus, followed by an optimization scheme based on a factor graph that includes loop closure. Data was captured using a portable robotic sensor suite consisting of three cameras, three dimensional lidar, and an inertial navigation system. Throughout this thesis, data was captured in the natural environment using a wearable sensor suite, conceived in the first months of this thesis. The data was acquired in monthly intervals over 12 months, by revisiting the same trajectory between August 2020 and July 2021. Finally, it has been shown that it is possible to align monthly surveys, taken over a year using the conceived sensor suite, and to provide insightful metrics for change evaluation in natural environment.Ph.D

    CherryPicker: Semantic Skeletonization and Topological Reconstruction of Cherry Trees

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    In plant phenotyping, accurate trait extraction from 3D point clouds of trees is still an open problem. For automatic modeling and trait extraction of tree organs such as blossoms and fruits, the semantically segmented point cloud of a tree and the tree skeleton are necessary. Therefore, we present CherryPicker, an automatic pipeline that reconstructs photo-metric point clouds of trees, performs semantic segmentation and extracts their topological structure in form of a skeleton. Our system combines several state-of-the-art algorithms to enable automatic processing for further usage in 3D-plant phenotyping applications. Within this pipeline, we present a method to automatically estimate the scale factor of a monocular reconstruction to overcome scale ambiguity and obtain metrically correct point clouds. Furthermore, we propose a semantic skeletonization algorithm build up on Laplacian-based contraction. We also show by weighting different tree organs semantically, our approach can effectively remove artifacts induced by occlusion and structural size variations. CherryPicker obtains high-quality topology reconstructions of cherry trees with precise details.Comment: Accepted by CVPR 2023 Vision for Agriculture Worksho

    METROPOLITAN ENCHANTMENT AND DISENCHANTMENT. METROPOLITAN ANTHROPOLOGY FOR THE CONTEMPORARY LIVING MAP CONSTRUCTION

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    We can no longer interpret the contemporary metropolis as we did in the last century. The thought of civil economy regarding the contemporary Metropolis conflicts more or less radically with the merely acquisitive dimension of the behaviour of its citizens. What is needed is therefore a new capacity for imagining the economic-productive future of the city: hybrid social enterprises, economically sustainable, structured and capable of using technologies, could be a solution for producing value and distributing it fairly and inclusively. Metropolitan Urbanity is another issue to establish. Metropolis needs new spaces where inclusion can occur, and where a repository of the imagery can be recreated. What is the ontology behind the technique of metropolitan planning and management, its vision and its symbols? Competitiveness, speed, and meritocracy are political words, not technical ones. Metropolitan Urbanity is the characteristic of a polis that expresses itself in its public places. Today, however, public places are private ones that are destined for public use. The Common Good has always had a space of representation in the city, which was the public space. Today, the Green-Grey Infrastructure is the metropolitan city's monument that communicates a value for future generations and must therefore be recognised and imagined; it is the production of the metropolitan symbolic imagery, the new magic of the city

    Knowledge-based Modelling of Additive Manufacturing for Sustainability Performance Analysis and Decision Making

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    Additiivista valmistusta on pidetty käyttökelpoisena monimutkaisissa geometrioissa, topologisesti optimoiduissa kappaleissa ja kappaleissa joita on muuten vaikea valmistaa perinteisillä valmistusprosesseilla. Eduista huolimatta, yksi additiivisen valmistuksen vallitsevista haasteista on ollut heikko kyky tuottaa toimivia osia kilpailukykyisillä tuotantomäärillä perinteisen valmistuksen kanssa. Mallintaminen ja simulointi ovat tehokkaita työkaluja, jotka voivat auttaa lyhentämään suunnittelun, rakentamisen ja testauksen sykliä mahdollistamalla erilaisten tuotesuunnitelmien ja prosessiskenaarioiden nopean analyysin. Perinteisten ja edistyneiden valmistusteknologioiden mahdollisuudet ja rajoitukset määrittelevät kuitenkin rajat uusille tuotekehityksille. Siksi on tärkeää, että suunnittelijoilla on käytettävissään menetelmät ja työkalut, joiden avulla he voivat mallintaa ja simuloida tuotteen suorituskykyä ja siihen liittyvän valmistusprosessin suorituskykyä, toimivien korkea arvoisten tuotteiden toteuttamiseksi. Motivaation tämän väitöstutkimuksen tekemiselle on, meneillään oleva kehitystyö uudenlaisen korkean lämpötilan suprajohtavan (high temperature superconducting (HTS)) magneettikokoonpanon kehittämisessä, joka toimii kryogeenisissä lämpötiloissa. Sen monimutkaisuus edellyttää monitieteisen asiantuntemuksen lähentymistä suunnittelun ja prototyyppien valmistuksen aikana. Tutkimus hyödyntää tietopohjaista mallinnusta valmistusprosessin analysoinnin ja päätöksenteon apuna HTS-magneettien mekaanisten komponenttien suunnittelussa. Tämän lisäksi, tutkimus etsii mahdollisuuksia additiivisen valmistuksen toteutettavuuteen HTS-magneettikokoonpanon tuotannossa. Kehitetty lähestymistapa käyttää fysikaalisiin kokeisiin perustuvaa tuote-prosessi-integroitua mallinnusta tuottamaan kvantitatiivista ja laadullista tietoa, joka määrittelee prosessi-rakenne-ominaisuus-suorituskyky-vuorovaikutuksia tietyille materiaali-prosessi-yhdistelmille. Tuloksina saadut vuorovaikutukset integroidaan kaaviopohjaiseen malliin, joka voi auttaa suunnittelutilan tutkimisessa ja täten auttaa varhaisessa suunnittelu- ja valmistuspäätöksenteossa. Tätä varten testikomponentit valmistetaan käyttämällä kahta metallin additiivista valmistus prosessia: lankakaarihitsaus additiivista valmistusta (wire arc additive manufacturing) ja selektiivistä lasersulatusta (selective laser melting). Rakenteellisissa sovelluksissa yleisesti käytetyistä metalliseoksista (ruostumaton teräs, pehmeä teräs, luja niukkaseosteinen teräs, alumiini ja kupariseokset) testataan niiden mekaaniset, lämpö- ja sähköiset ominaisuudet. Lisäksi tehdään metalliseosten mikrorakenteen karakterisointi, jotta voidaan ymmärtää paremmin valmistusprosessin parametrien vaikutusta materiaalin ominaisuuksiin. Integroitu mallinnustapa yhdistää kerätyn kokeellisen tiedon, olemassa olevat analyyttiset ja empiiriset vuorovaikutus suhteet, sekä muut tietopohjaiset mallit (esim. elementtimallit, koneoppimismallit) päätöksenteon tukijärjestelmän muodossa, joka mahdollistaa optimaalisen materiaalin, valmistustekniikan, prosessiparametrien ja muitten ohjausmuuttujien valinnan, lopullisen 3d-tulosteun komponentin halutun rakenteen, ominaisuuksien ja suorituskyvyn saavuttamiseksi. Valmistuspäätöksenteko tapahtuu todennäköisyysmallin, eli Bayesin verkkomallin toteuttamisen kautta, joka on vankka, modulaarinen ja sovellettavissa muihin valmistusjärjestelmiin ja tuotesuunnitelmiin. Väitöstyössä esitetyn mallin kyky parantaa additiivisien valmistusprosessien suorituskykyä ja laatua, täten edistää kestävän tuotannon tavoitteita.Additive manufacturing (AM) has been considered viable for complex geometries, topology optimized parts, and parts that are otherwise difficult to produce using conventional manufacturing processes. Despite the advantages, one of the prevalent challenges in AM has been the poor capability of producing functional parts at production volumes that are competitive with traditional manufacturing. Modelling and simulation are powerful tools that can help shorten the design-build-test cycle by enabling rapid analysis of various product designs and process scenarios. Nevertheless, the capabilities and limitations of traditional and advanced manufacturing technologies do define the bounds for new product development. Thus, it is important that the designers have access to methods and tools that enable them to model and simulate product performance and associated manufacturing process performance to realize functional high value products. The motivation for this dissertation research stems from ongoing development of a novel high temperature superconducting (HTS) magnet assembly, which operates in cryogenic environment. Its complexity requires the convergence of multidisciplinary expertise during design and prototyping. The research applies knowledge-based modelling to aid manufacturing process analysis and decision making in the design of mechanical components of the HTS magnet. Further, it explores the feasibility of using AM in the production of the HTS magnet assembly. The developed approach uses product-process integrated modelling based on physical experiments to generate quantitative and qualitative information that define process-structure-property-performance interactions for given material-process combinations. The resulting interactions are then integrated into a graph-based model that can aid in design space exploration to assist early design and manufacturing decision-making. To do so, test components are fabricated using two metal AM processes: wire and arc additive manufacturing and selective laser melting. Metal alloys (stainless steel, mild steel, high-strength low-alloyed steel, aluminium, and copper alloys) commonly used in structural applications are tested for their mechanical-, thermal-, and electrical properties. In addition, microstructural characterization of the alloys is performed to further understand the impact of manufacturing process parameters on material properties. The integrated modelling approach combines the collected experimental data, existing analytical and empirical relationships, and other data-driven models (e.g., finite element models, machine learning models) in the form of a decision support system that enables optimal selection of material, manufacturing technology, process parameters, and other control variables for attaining desired structure, property, and performance characteristics of the final printed component. The manufacturing decision making is performed through implementation of a probabilistic model i.e., a Bayesian network model, which is robust, modular, and can be adapted for other manufacturing systems and product designs. The ability of the model to improve throughput and quality of additive manufacturing processes will boost sustainable manufacturing goals
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