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Author Pejman Rasti; Salma Samiei; Mary Agoyi; Sergio Escalera; Gholamreza Anbarjafari
Title Robust non-blind color video watermarking using QR decomposition and entropy analysis Type Journal Article
Year 2016 Publication Journal of Visual Communication and Image Representation Abbreviated Journal JVCIR
Volume 38 Issue Pages 838-847
Keywords Video watermarking; QR decomposition; Discrete Wavelet Transformation; Chirp Z-transform; Singular value decomposition; Orthogonal–triangular decomposition
Abstract Issues such as content identification, document and image security, audience measurement, ownership and copyright among others can be settled by the use of digital watermarking. Many recent video watermarking methods show drops in visual quality of the sequences. The present work addresses the aforementioned issue by introducing a robust and imperceptible non-blind color video frame watermarking algorithm. The method divides frames into moving and non-moving parts. The non-moving part of each color channel is processed separately using a block-based watermarking scheme. Blocks with an entropy lower than the average entropy of all blocks are subject to a further process for embedding the watermark image. Finally a watermarked frame is generated by adding moving parts to it. Several signal processing attacks are applied to each watermarked frame in order to perform experiments and are compared with some recent algorithms. Experimental results show that the proposed scheme is imperceptible and robust against common signal processing attacks.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB; Approved no
Call Number Admin @ si @RSA2016 Serial 2766
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Author Pedro Martins; Paulo Carvalho; Carlo Gatta
Title Context Aware Keypoint Extraction for Robust Image Representation Type Conference Article
Year 2012 Publication 23rd British Machine Vision Conference Abbreviated Journal
Volume Issue Pages 100.1 - 100.12
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Abstract
Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference BMVC
Notes MILAB Approved no
Call Number Admin @ si @ MCG2012a Serial 2140
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Author Pedro Martins; Paulo Carvalho; Carlo Gatta
Title Context-aware features and robust image representations Type Journal Article
Year 2014 Publication Journal of Visual Communication and Image Representation Abbreviated Journal JVCIR
Volume 25 Issue 2 Pages 339-348
Keywords
Abstract Local image features are often used to efficiently represent image content. The limited number of types of features that a local feature extractor responds to might be insufficient to provide a robust image representation. To overcome this limitation, we propose a context-aware feature extraction formulated under an information theoretic framework. The algorithm does not respond to a specific type of features; the idea is to retrieve complementary features which are relevant within the image context. We empirically validate the method by investigating the repeatability, the completeness, and the complementarity of context-aware features on standard benchmarks. In a comparison with strictly local features, we show that our context-aware features produce more robust image representations. Furthermore, we study the complementarity between strictly local features and context-aware ones to produce an even more robust representation.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes LAMP; 600.079;MILAB Approved no
Call Number Admin @ si @ MCG2014 Serial 2467
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Author Debora Gil; Jose Maria-Carazo; Roberto Marabini
Title On the nature of 2D crystal unbending Type Journal Article
Year 2006 Publication Journal of Structural Biology Abbreviated Journal
Volume 156 Issue 3 Pages 546-555
Keywords Electron microscopy
Abstract Crystal unbending, the process that aims to recover a perfect crystal from experimental data, is one of the more important steps in electron crystallography image processing. The unbending process involves three steps: estimation of the unit cell displacements from their ideal positions, extension of the deformation field to the whole image and transformation of the image in order to recover an ideal crystal. In this work, we present a systematic analysis of the second step oriented to address two issues. First, whether the unit cells remain undistorted and only the distance between them should be changed (rigid case) or should be modified with the same deformation suffered by the whole crystal (elastic case). Second, the performance of different extension algorithms (interpolation versus approximation) is explored. Our experiments show that there is no difference between elastic and rigid cases or among the extension algorithms. This implies that the deformation fields are constant over large areas. Furthermore, our results indicate that the main source of error is the transformation of the crystal image.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1047-8477 ISBN Medium
Area Expedition Conference
Notes IAM; Approved no
Call Number IAM @ iam @ GCM2006 Serial 1519
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Author Daniela Rato; Miguel Oliveira; Vitor Santos; Manuel Gomes; Angel Sappa
Title A sensor-to-pattern calibration framework for multi-modal industrial collaborative cells Type Journal Article
Year 2022 Publication Journal of Manufacturing Systems Abbreviated Journal JMANUFSYST
Volume 64 Issue Pages 497-507
Keywords Calibration; Collaborative cell; Multi-modal; Multi-sensor
Abstract Collaborative robotic industrial cells are workspaces where robots collaborate with human operators. In this context, safety is paramount, and for that a complete perception of the space where the collaborative robot is inserted is necessary. To ensure this, collaborative cells are equipped with a large set of sensors of multiple modalities, covering the entire work volume. However, the fusion of information from all these sensors requires an accurate extrinsic calibration. The calibration of such complex systems is challenging, due to the number of sensors and modalities, and also due to the small overlapping fields of view between the sensors, which are positioned to capture different viewpoints of the cell. This paper proposes a sensor to pattern methodology that can calibrate a complex system such as a collaborative cell in a single optimization procedure. Our methodology can tackle RGB and Depth cameras, as well as LiDARs. Results show that our methodology is able to accurately calibrate a collaborative cell containing three RGB cameras, a depth camera and three 3D LiDARs.
Address
Corporate Author Thesis
Publisher Science Direct Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ ROS2022 Serial 3750
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Author Iban Berganzo-Besga; Hector A. Orengo; Felipe Lumbreras; Paloma Aliende; Monica N. Ramsey
Title Automated detection and classification of multi-cell Phytoliths using Deep Learning-Based Algorithms Type Journal Article
Year 2022 Publication Journal of Archaeological Science Abbreviated Journal JArchSci
Volume 148 Issue Pages 105654
Keywords
Abstract This paper presents an algorithm for automated detection and classification of multi-cell phytoliths, one of the major components of many archaeological and paleoenvironmental deposits. This identification, based on phytolith wave pattern, is made using a pretrained VGG19 deep learning model. This approach has been tested in three key phytolith genera for the study of agricultural origins in Near East archaeology: Avena, Hordeum and Triticum. Also, this classification has been validated at species-level using Triticum boeoticum and dicoccoides images. Due to the diversity of microscopes, cameras and chemical treatments that can influence images of phytolith slides, three types of data augmentation techniques have been implemented: rotation of the images at 45-degree angles, random colour and brightness jittering, and random blur/sharpen. The implemented workflow has resulted in an overall accuracy of 93.68% for phytolith genera, improving previous attempts. The algorithm has also demonstrated its potential to automatize the classification of phytoliths species with an overall accuracy of 100%. The open code and platforms employed to develop the algorithm assure the method's accessibility, reproducibility and reusability.
Address December 2022
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MSIAU; MACO; 600.167 Approved no
Call Number Admin @ si @ BOL2022 Serial 3753
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Author Neus Salvatella; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; H. Tizon; Xavier Carrillo; J. Mauri; Petia Radeva
Title Radial Artery Volume Changes After Administration Of Two Different Intra-arterial Drug Regimens. Assessment by Intravascular Ultrasound Type Journal Article
Year 2010 Publication Journal of the American College of Cardiology Abbreviated Journal JACC
Volume 56 Issue 13s1 Pages B119
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Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ SFC2010b Serial 1364
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Author Miguel Oliveira; Victor Santos; Angel Sappa
Title Multimodal Inverse Perspective Mapping Type Journal Article
Year 2015 Publication Information Fusion Abbreviated Journal IF
Volume 24 Issue Pages 108–121
Keywords Inverse perspective mapping; Multimodal sensor fusion; Intelligent vehicles
Abstract Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.055; 600.076 Approved no
Call Number Admin @ si @ OSS2015c Serial 2532
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Author Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez
Title Chromatic shadow detection and tracking for moving foreground segmentation Type Journal Article
Year 2015 Publication Image and Vision Computing Abbreviated Journal IMAVIS
Volume 41 Issue Pages 42-53
Keywords Detecting moving objects; Chromatic shadow detection; Temporal local gradient; Spatial and Temporal brightness and angle distortions; Shadow tracking
Abstract Advanced segmentation techniques in the surveillance domain deal with shadows to avoid distortions when detecting moving objects. Most approaches for shadow detection are still typically restricted to penumbra shadows and cannot cope well with umbra shadows. Consequently, umbra shadow regions are usually detected as part of moving objects, thus a ecting the performance of the nal detection. In this paper we address the detection of both penumbra and umbra shadow regions. First, a novel bottom-up approach is presented based on gradient and colour models, which successfully discriminates between chromatic moving cast shadow regions and those regions detected as moving objects. In essence, those regions corresponding to potential shadows are detected based on edge partitioning and colour statistics. Subsequently (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for each potential shadow region for detecting the umbra shadow regions. Our second contribution re nes even further the segmentation results: a tracking-based top-down approach increases the performance of our bottom-up chromatic shadow detection algorithm by properly correcting non-detected shadows.
To do so, a combination of motion lters in a data association framework exploits the temporal consistency between objects and shadows to increase
the shadow detection rate. Experimental results exceed current state-of-the-
art in shadow accuracy for multiple well-known surveillance image databases which contain di erent shadowed materials and illumination conditions.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ISE; 600.078; 600.063 Approved no
Call Number Admin @ si @ HHM2015 Serial 2703
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Author Noha Elfiky; Jordi Gonzalez; Xavier Roca
Title Compact and Adaptive Spatial Pyramids for Scene Recognition Type Journal Article
Year 2012 Publication Image and Vision Computing Abbreviated Journal IMAVIS
Volume 30 Issue 8 Pages 492–500
Keywords
Abstract Most successful approaches on scenerecognition tend to efficiently combine global image features with spatial local appearance and shape cues. On the other hand, less attention has been devoted for studying spatial texture features within scenes. Our method is based on the insight that scenes can be seen as a composition of micro-texture patterns. This paper analyzes the role of texture along with its spatial layout for scenerecognition. However, one main drawback of the resulting spatial representation is its huge dimensionality. Hence, we propose a technique that addresses this problem by presenting a compactSpatialPyramid (SP) representation. The basis of our compact representation, namely, CompactAdaptiveSpatialPyramid (CASP) consists of a two-stages compression strategy. This strategy is based on the Agglomerative Information Bottleneck (AIB) theory for (i) compressing the least informative SP features, and, (ii) automatically learning the most appropriate shape for each category. Our method exceeds the state-of-the-art results on several challenging scenerecognition data sets.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ EGR2012 Serial 2004
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Author Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez
Title An Iterative Multiresolution Scheme for SFM with Missing Data: single and multiple object scenes Type Journal Article
Year 2010 Publication Image and Vision Computing Abbreviated Journal IMAVIS
Volume 28 Issue 1 Pages 164-176
Keywords
Abstract Most of the techniques proposed for tackling the Structure from Motion problem (SFM) cannot deal with high percentages of missing data in the matrix of trajectories. Furthermore, an additional problem should be faced up when working with multiple object scenes: the rank of the matrix of trajectories should be estimated. This paper presents an iterative multiresolution scheme for SFM with missing data to be used in both the single and multiple object cases. The proposed scheme aims at recovering missing entries in the original input matrix. The objective is to improve the results by applying a factorization technique to the partially or totally filled in matrix instead of to the original input one. Experimental results obtained with synthetic and real data sequences, containing single and multiple objects, are presented to show the viability of the proposed approach.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0262-8856 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ JSL2010 Serial 1278
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Author Jordi Gonzalez; Dani Rowe; Javier Varona; Xavier Roca
Title Understanding Dynamic Scenes based on Human Sequence Evaluation Type Journal Article
Year 2009 Publication Image and Vision Computing Abbreviated Journal IMAVIS
Volume 27 Issue 10 Pages 1433–1444
Keywords Image Sequence Evaluation; High-level processing of monitored scenes; Segmentation and tracking in complex scenes; Event recognition in dynamic scenes; Human motion understanding; Human behaviour interpretation; Natural-language text generation; Realistic demonstrators
Abstract In this paper, a Cognitive Vision System (CVS) is presented, which explains the human behaviour of monitored scenes using natural-language texts. This cognitive analysis of human movements recorded in image sequences is here referred to as Human Sequence Evaluation (HSE) which defines a set of transformation modules involved in the automatic generation of semantic descriptions from pixel values. In essence, the trajectories of human agents are obtained to generate textual interpretations of their motion, and also to infer the conceptual relationships of each agent w.r.t. its environment. For this purpose, a human behaviour model based on Situation Graph Trees (SGTs) is considered, which permits both bottom-up (hypothesis generation) and top-down (hypothesis refinement) analysis of dynamic scenes. The resulting system prototype interprets different kinds of behaviour and reports textual descriptions in multiple languages.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ GRV2009 Serial 1211
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Author Oriol Pujol; Debora Gil; Petia Radeva
Title Fundamentals of Stop and Go active models Type Journal Article
Year 2005 Publication Image and Vision Computing Abbreviated Journal
Volume 23 Issue 8 Pages 681-691
Keywords Deformable models; Geodesic snakes; Region-based segmentation
Abstract An efficient snake formulation should conform to the idea of picking the smoothest curve among all the shapes approximating an object of interest. In current geodesic snakes, the regularizing curvature also affects the convergence stage, hindering the latter at concave regions. In the present work, we make use of characteristic functions to define a novel geodesic formulation that decouples regularity and convergence. This term decoupling endows the snake with higher adaptability to non-convex shapes. Convergence is ensured by splitting the definition of the external force into an attractive vector field and a repulsive one. In our paper, we propose to use likelihood maps as approximation of characteristic functions of object appearance. The better efficiency and accuracy of our decoupled scheme are illustrated in the particular case of feature space-based segmentation.
Address
Corporate Author Thesis
Publisher Butterworth-Heinemann Place of Publication Newton, MA, USA Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0262-8856 ISBN Medium
Area Expedition Conference
Notes IAM;MILAB;HuPBA Approved no
Call Number IAM @ iam @ PGR2005 Serial 1629
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Author T. Widemann; Xavier Otazu
Title Titanias radius and an upper limit on its atmosphere from the September 8, 2001 stellar occultation Type Journal Article
Year 2009 Publication International Journal of Solar System Studies Abbreviated Journal
Volume 199 Issue 2 Pages 458–476
Keywords Occultations; Uranus, satellites; Satellites, shapes; Satellites, dynamics; Ices; Satellites, atmospheres
Abstract On September 8, 2001 around 2 h UT, the largest uranian moon, Titania, occulted Hipparcos star 106829 (alias SAO 164538, a V=7.2, K0 III star). This was the first-ever observed occultation by this satellite, a rare event as Titania subtends only 0.11 arcsec on the sky. The star's unusual brightness allowed many observers, both amateurs or professionals, to monitor this unique event, providing fifty-seven occultations chords over three continents, all reported here. Selecting the best 27 occultation chords, and assuming a circular limb, we derive Titania's radius: View the MathML source (1-σ error bar). This implies a density of View the MathML source using the value View the MathML source derived by Taylor [Taylor, D.B., 1998. Astron. Astrophys. 330, 362–374]. We do not detect any significant difference between equatorial and polar radii, in the limit View the MathML source, in agreement with Voyager limb image retrieval during the 1986 flyby. Titania's offset with respect to the DE405 + URA027 (based on GUST86 theory) ephemeris is derived: ΔαTcos(δT)=−108±13 mas and ΔδT=−62±7 mas (ICRF J2000.0 system). Most of this offset is attributable to a Uranus' barycentric offset with respect to DE405, that we estimate to be: View the MathML source and ΔδU=−85±25 mas at the moment of occultation. This offset is confirmed by another Titania stellar occultation observed on August 1st, 2003, which provides an offset of ΔαTcos(δT)=−127±20 mas and ΔδT=−97±13 mas for the satellite. The combined ingress and egress data do not show any significant hint for atmospheric refraction, allowing us to set surface pressure limits at the level of 10–20 nbar. More specifically, we find an upper limit of 13 nbar (1-σ level) at 70 K and 17 nbar at 80 K, for a putative isothermal CO2 atmosphere. We also provide an upper limit of 8 nbar for a possible CH4 atmosphere, and 22 nbar for pure N2, again at the 1-σ level. We finally constrain the stellar size using the time-resolved star disappearance and reappearance at ingress and egress. We find an angular diameter of 0.54±0.03 mas (corresponding to View the MathML source projected at Titania). With a distance of 170±25 parsecs, this corresponds to a radius of 9.8±0.2 solar radii for HIP 106829, typical of a K0 III giant.
Address
Corporate Author Thesis
Publisher ELSEVIER Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0019-1035 ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ Wid2009 Serial 1052
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Author Joan Marc Llargues Asensio; Juan Peralta; Raul Arrabales; Manuel Gonzalez Bedia; Paulo Cortez; Antonio Lopez
Title Artificial Intelligence Approaches for the Generation and Assessment of Believable Human-Like Behaviour in Virtual Characters Type Journal Article
Year 2014 Publication Expert Systems With Applications Abbreviated Journal EXSY
Volume 41 Issue 16 Pages 7281–7290
Keywords Turing test; Human-like behaviour; Believability; Non-player characters; Cognitive architectures; Genetic algorithm; Artificial neural networks
Abstract Having artificial agents to autonomously produce human-like behaviour is one of the most ambitious original goals of Artificial Intelligence (AI) and remains an open problem nowadays. The imitation game originally proposed by Turing constitute a very effective method to prove the indistinguishability of an artificial agent. The behaviour of an agent is said to be indistinguishable from that of a human when observers (the so-called judges in the Turing test) cannot tell apart humans and non-human agents. Different environments, testing protocols, scopes and problem domains can be established to develop limited versions or variants of the original Turing test. In this paper we use a specific version of the Turing test, based on the international BotPrize competition, built in a First-Person Shooter video game, where both human players and non-player characters interact in complex virtual environments. Based on our past experience both in the BotPrize competition and other robotics and computer game AI applications we have developed three new more advanced controllers for believable agents: two based on a combination of the CERA–CRANIUM and SOAR cognitive architectures and other based on ADANN, a system for the automatic evolution and adaptation of artificial neural networks. These two new agents have been put to the test jointly with CCBot3, the winner of BotPrize 2010 competition (Arrabales et al., 2012), and have showed a significant improvement in the humanness ratio. Additionally, we have confronted all these bots to both First-person believability assessment (BotPrize original judging protocol) and Third-person believability assessment, demonstrating that the active involvement of the judge has a great impact in the recognition of human-like behaviour.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.055; 600.057; 600.076 Approved no
Call Number Admin @ si @ LPA2014 Serial 2500
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