123 research outputs found
Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion
No full textDataset Introduction
The advent of neural networks capable of learning salient features from variance in the radar data has expanded the breadth of radar applications, often as an alternative sensor or a complementary modality to camera vision. Gesture recognition for command control is the most commonly explored application. Nevertheless, more suitable benchmarking datasets are needed to assess and compare the merits of the different proposed solutions. Furthermore, most current publicly available radar datasets used in gesture recognition provide little diversity, do not provide access to raw ADC data, and are not significantly challenging. To address these shortcomings, we created and made available a new dataset that combines two synchronized modalities: radar and dynamic vision camera of 10 aircraft marshalling signals at several distances and angles, recorded from 13 people. Moreover, we propose a sparse encoding of the time domain (ADC) signals that achieve a dramatic data rate reduction (>76%) while retaining the efficacy of the downstream FFT processing (<2% accuracy loss on recognition tasks). Finally, we demonstrate early sensor fusion results based on compressed radar data encoding in range-Doppler maps with dynamic vision data. This approach achieves higher accuracy than either modality alone.
Dataset Structure
The dataset has a common directory structure which contains additional information about the captures.
dataset_dir///--/ofxRadar8Ghz_yyyy-mm-dd_HH-MM-SS.rad
Identifiers
stage [train, test].
room: [conference_room, foyer, open_space].
person: [0-9]. Note that 0 stands for no person, and 1 for an unlabeled, random person (only present in test).
gesture: ['none', 'emergency_stop', 'move_ahead', 'move_back_v1', 'move_back_v2', 'slow_down' 'start_engines', 'stop_engines', 'straight_ahead', 'turn_left', 'turn_right'].
distance: ['xxx', '100', '150', '200', '250', '300', '350', '400', '450'] (in cm). Note that xxx is used for none gestures when there is no person present in front of the radar (i.e. background samples), or when a person is walking infront of the radar with varying distances but performing no gesture.If you use this dataset, please also cite our accompanying paper:
@inproceedings{mueller2023aircraft, title={Aircraft Marshalling Signals Dataset of Radar and Event-Based Camera for Sensor Fusion}, author={M\"uller, Leon and Sifalakis, Manolis and Eissa, Sherif and Yousefzadeh, Amirreza and Detterer, Paul and Stuijk, Sander, and Corradi, Federico}, journal={IEEE Radar Conference, San Antonio, TX}, volume={}, number={1}, pages={1--15}, year={2023}, publisher={IEE}
Loose ends: almost one in five human genes still have unresolved coding status
No full textThe authors have accidently omitted one co-author. Part of the work described in this study was performed in the laboratory of Dr Manolis Kellis, Computer Science and Electrical Engineering Department, Massachusetts Institute of Technology, Cambridge, MA, USA and The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Dr Kellis’ name has been added to the authorship and the published article has been updated
Cognitive abstraction approach to sketch-based image retrieval
No full textThesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (leaves 151-157).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.As digital media become more popular, corporations and individuals gather an increasingly large number of digital images. As a collection grows to more than a few hundred images, the need for search becomes crucial. This thesis is addressing the problem of retrieving from a small database a particular image previously seen by the user. This thesis combines current findings in cognitive science with the knowledge of previous image retrieval systems to present a novel approach to content based image retrieval and indexing. We focus on algorithms which abstract away information from images in the same terms that a viewer abstracts information from an image. The focus in Imagina is on the matching of regions, instead of the matching of global measures. Multiple representations, focusing on shape and color, are used for every region. The matches of individual regions are combined using a saliency metric that accounts for differences in the distributions of metrics. Region matching along with configuration determines the overall match between a query and an image.by Manolis Kamvysselis and Ovidiu Marina.S.B.and M.Eng
OurOwnsKIN: The Development of 3D-Printed Footwear Inspired by Human Skin
No full textOurOwnsKIN 1 is a research project exploring the interplay between man, material, and machine to create innovative footwear design constructions inspired by human skin. The aim is to harness the capabilities of 3D printing in preparation for future biotechnologies
Inverse identification of buffeting and self-excited wind loads on the hardanger bridge from acceleration data
No full textThe traditional wind load assessment for long-span bridges rely on assumed models for the wind field and aerodynamic coefficients from wind tunnel tests, which usually introduces some uncertainties. It is therefore desired to develop tools that can utilize full-scale vibration response data from existing bridges in order to study the wind loading in detail for in-situ conditions. This paper presents a novel case study of inverse identification of dynamic wind loads on the 1310 m long Hardanger bridge, a suspension bridge equipped with a network of accelerometers. The identification method used is an extented Kalman-type filter for joint input, state, and parameter estimation. A system model considering the still-air modes in addition to a quasi-steady submodel for the self-excited forces of the bridge is presente. The coefficients for self-excited lift and pitching moment are considered unknown and are jointly estimated with the buffeting forces.Dynamics of StructuresOffshore Engineerin
Fluid structure interaction modelling on flapping wings
No full textFlapping wings display complex flows which can be used to generate large lift forces. Flexibility in wings is widely used by natural flyers to increase the aerodynamic performance. The influence of wing flexibility on the flow can be computed using numerical analysis with Fluid Structure Interaction (FSI). The influence of inertial, elastic and aerodynamic forces is quantified using a 2D wing. A sinusoidal flapping motion is imposed on the leading edge of the vertical wing. The inertial force on the wing dominates for high mass ratios and the wing deflection is rather independent of the flow. For a low mass ratio, the wing deformation scales with the increasing elasticity. The maximum lift and lowest drag were found for the wing with large flexibility and low mass so the passive deformation by aerodynamic forces creates a favourable shape for lift production. Flexible translating and revolving wings at an angle of attack of 45 degrees show that chordwise flexibility decreases both lift and drag, however the lift over drag ratio is increased. The flow around both wings forms a coherent structure with a Root Vortex (RV), Tip Vortex (TV), Leading Edge Vortex (LEV) and Trailing Edge Vortex (TEV). The LEV on the revolving wing is stable for approximately up to half the span because vorticity is transported outward in the vortex core. The flowfield and LEV breakdown are consistent with experimental data of the same wing. The translating wing builds up circulation but the LEV detaches quickly near the centre of the wing. Chordwise bending reduces the angle of attack which decreases the distance to the core of the shed LEVs.Aerodynamic
On the Combination of Random Matrix Theory With Measurements on a Single Structure
No full textAn approach is proposed for the evaluation of the probability density functions (PDFs) of the modal parameters for an ensemble of nominally identical structures when there is only access to a single structure and the dispersion parameter is known. The approach combines the Eigensystem realization algorithm on sets of dynamic data, with an explicit nonparametric probabilistic method. A single structure, either a mathematical model or a prototype, is used to obtain simulated data or measurements that are employed to build a discrete time state-space model description. The dispersion parameter is used to describe the uncertainty due to different sources such as the variability found in the population and the identification errors found in the noisy measurements from the experiments. With this approach, instead of propagating the uncertainties through the governing equations of the system, the distribution of the modal parameters of the whole ensemble is obtained by randomizing the matrices in the state-space model with an efficient procedure. The applicability of the approach is shown through the analysis of a two degrees-of-freedom mass-spring-damper system and a cantilever system. The results show that if the source of uncertainty is unknown and it is possible to specify an overall level of uncertainty, by having access to a single system's measurements, it is possible to evaluate the resulting PDFs on the modal parameters. It was also found that high values of the dispersion parameter may lead to nonphysical results such as negative damping ratios values.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Mechanics and Physics of Structure
Library collection development policies. Training Piloting Module n0: 8
No full textThe author reports about the training on Pilot Module No. 8 ,,Library Collection Development Policy" for the library staff. Training took place at the USARB Scientific Library within the framework of ERASMUS+ LNSS Project "Library Network Support Services: Modernizing Libraries in Armenia, Moldova and Belarus through Library Staff Development and Reforming Library Services". The training was attended by European partner universities, Angela Repanovici, PhD, professor, University "Transilvania", Brasov, Romania, and Dr. Manolis Koukourakis, Director of the Library of the University of Crete
Multiple Photovoltaic Battery Integrated Modules: How interconnecting PBIMs to form a grid can improve performance
No full textResidential PV energy is already evolving to a major factor in the energy transition. However, conventional solar home systems pose various disadvantages concerning modularity, flexibility and ease of installation. The Photovoltaic Battery Integrated Module (PBIM) is an alternative approach towards integrating all the components of a solar home system into one device, in an attempt to tackle such challenges. Together with the possibility to interconnect several PBIMs to constitute a small grid, new challenges appear particularly related to the way in which the general power flow is decided. This project evaluates how forming a PBIMG grid can help mitigate the effect of mismatches between the various PBIMs during operation. It is expected that due to differences in PV generation and battery state of charge levels, the individual PBIMs should coordinate with other PBIMs to operate optimally. Although research has been made in the context of individual PBIM modules, forming a grid of multiple modules could provide feasible and scalable solutions for both on- and off- grid applications. All the advantages of the PBIM (scalability, modularity, ease of installation etc.) could potentially be scaled up to a microgrid level as to form an independent power source. The scope of this project is to evaluate how the formation of such a grid can improve system performance by performing a comparative energy and economic analysis between interconnected and non-interconnected PBIMs. The case studies simulated include: a) independent vs interconnected PBIMs powering an offgrid household in Costa Rica b) multiple grid-connected household powered by PBIM grids versus an interconnected neighborhood, powered by a bigger PBIM grid in Costa Rica and the Netherlands The results indicate that PBIM grid shows superior performance than multiple non-interconnected PBIMs, as smaller systems can achieve comparable performances when interconnected by reducing both battery degradation and the need to exchange power with the main grid, leading to considerable financial gains.Electrical Engineering | Sustainable Energy Technolog
Face recognition using traditional machine learning algorithms and deep neural networks with application to face verification
No full textBiometrics authentication has been very useful and necessary nowadays due to the great developments in technology and the transaction of huge amounts of sensitive data on a daily basis. Traditionally, access to some data or service is achieved by means of some documents or a password. However, these methods are not very convenient. Alternatively, typical biometric systems can be employed that use fingerprint, iris, voice, face recognition or a combination of them. This project focuses on the task of face recognition from still images and investigates how different algorithms for face verification perform under various adverse conditions modelled by blur, salt-and-pepper noise and changes in illumination. Conventional pattern recognition algorithms are first presented. Pixel intensities, Gabor features, Local Binary Patterns (LBP) and 2D-DCT coefficients are considered as features while for classification the nearest neighbor (NNC), nearest mean (NMC), SVM classifiers, and Likelihood Ratio Tests (LRT) with Gaussian Mixture Models (GMM) are examined. Out of all these methods, Gabor features combined with the linear SVM classifier are shown to produce best results across all degradations giving an average Equal Error Rate (EER) of 0:97% using the ORL face dataset. Then, emphasis is placed on deep learning and Convolutional Neural Networks (CNN). Specically, VGG-Face with triplet loss training for face verification is suggested. VGG-Face achieves an average EER of 2:63% when both test images of a query image pair are drawn from the same degradation conditions and an average EER of 3:80% when only one image in the given pair is degraded and the other one is derived from the clean ORL dataset. We also experimented with the extracted VGG-Face features and NNC, linear SVM and Gaussian SVM and it is seen that a linear SVM gives an average EER of 1:10% by macro-averaging the Detection Error Tradeoff (DET) curves.Face recognition using traditional machine learning algorithms and deep neural networks with application to face verificationElectrical Engineering | Circuits and System
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