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	Author	Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Francesca Vidal; Zaida Sarrate
	Title	Noves perspectives en l estudi de la territorialitat cromosomica de cel·lules germinals masculines: estudis tridimensionals			Type	Journal
	Year	2017	Publication	Biologia de la Reproduccio	Abbreviated Journal	JBR
	Volume	15	Issue		Pages	73-78
	Keywords
	Abstract	In somatic cells, chromosomes occupy specific nuclear regions called chromosome territories which are involved in the maintenance and regulation of the genome. Preliminary data in male germ cells also suggest the importance of chromosome territoriality in cell functionality. Nevertheless, the specific characteristics of testicular tissue (presence of different cell types with different morphological characteristics, in different stages of development and with different ploidy) makes difficult to achieve conclusive results. In this study we have developed a methodology to approach the threedimensional study of all chromosome territories in male germ cells from C57BL/6J mice (Mus musculus). The method includes the following steps: i) Optimized cell fixation to obtain an optimal preservation of the three-dimensionality cell morphology, ii) Chromosome identification by FISH (Chromoprobe Multiprobe® OctoChrome™ Murine System; Cytocell) and confocal microscopy (TCS-SP5, Leica Microsystems), iii) Cell type identification by immunofluorescence iv) Image analysis using Matlab scripts, v) Numerical data extraction related to chromosome features, chromosome radial position and chromosome relative position. This methodology allows the unequivocally identification and the analysis of the chromosome territories of all spermatogenic stages. Results will provide information about the features that determine chromosomal position, preferred associations between chromosomes, and the relationship between chromosome positioning and genome regulation.
	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	978-84-697-3767-5	Medium
	Area		Expedition		Conference
	Notes	IAM; 600.096; 600.145			Approved	no
	Call Number	Admin @ si @ SBG2017c			Serial	2961
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	Author	Arnau Baro; Jialuo Chen; Alicia Fornes; Beata Megyesi
	Title	Towards a generic unsupervised method for transcription of encoded manuscripts			Type	Conference Article
	Year	2019	Publication	3rd International Conference on Digital Access to Textual Cultural Heritage	Abbreviated Journal
	Volume		Issue		Pages	73-78
	Keywords	A. Baró, J. Chen, A. Fornés, B. Megyesi.
	Abstract	Historical ciphers, a special type of manuscripts, contain encrypted information, important for the interpretation of our history. The first step towards decipherment is to transcribe the images, either manually or by automatic image processing techniques. Despite the improvements in handwritten text recognition (HTR) thanks to deep learning methodologies, the need of labelled data to train is an important limitation. Given that ciphers often use symbol sets across various alphabets and unique symbols without any transcription scheme available, these supervised HTR techniques are not suitable to transcribe ciphers. In this paper we propose an un-supervised method for transcribing encrypted manuscripts based on clustering and label propagation, which has been successfully applied to community detection in networks. We analyze the performance on ciphers with various symbol sets, and discuss the advantages and drawbacks compared to supervised HTR methods.
	Address	Brussels; May 2019
	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	DATeCH
	Notes	DAG; 600.097; 600.140; 600.121			Approved	no
	Call Number	Admin @ si @ BCF2019			Serial	3276
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	Author	Laura Igual; Agata Lapedriza; Ricard Borras
	Title	Robust Gait-Based Gender Classification using Depth Cameras			Type	Journal Article
	Year	2013	Publication	EURASIP Journal on Advances in Signal Processing	Abbreviated Journal	EURASIPJ
	Volume	37	Issue	1	Pages	72-80
	Keywords
	Abstract	This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section.
	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; OR;MV			Approved	no
	Call Number	Admin @ si @ ILB2013			Serial	2144
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	Author	Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva
	Title	Adaptable image cuts for motility inspection using WCE			Type	Journal Article
	Year	2013	Publication	Computerized Medical Imaging and Graphics	Abbreviated Journal	CMIG
	Volume	37	Issue	1	Pages	72-80
	Keywords
	Abstract	The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE.
	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; OR; 600.046; 605.203			Approved	no
	Call Number	Admin @ si @ DSM2012			Serial	2151
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	Author	Frederic Sampedro; Anna Domenech; Sergio Escalera; Ignasi Carrio
	Title	Computing quantitative indicators of structural renal damage in pediatric DMSA scans			Type	Journal Article
	Year	2017	Publication	Revista Española de Medicina Nuclear e Imagen Molecular	Abbreviated Journal	REMNIM
	Volume	36	Issue	2	Pages	72-77
	Keywords
	Abstract	OBJECTIVES: The proposal and implementation of a computational framework for the quantification of structural renal damage from 99mTc-dimercaptosuccinic acid (DMSA) scans. The aim of this work is to propose, implement, and validate a computational framework for the quantification of structural renal damage from DMSA scans and in an observer-independent manner. MATERIALS AND METHODS: From a set of 16 pediatric DMSA-positive scans and 16 matched controls and using both expert-guided and automatic approaches, a set of image-derived quantitative indicators was computed based on the relative size, intensity and histogram distribution of the lesion. A correlation analysis was conducted in order to investigate the association of these indicators with other clinical data of interest in this scenario, including C-reactive protein (CRP), white cell count, vesicoureteral reflux, fever, relative perfusion, and the presence of renal sequelae in a 6-month follow-up DMSA scan. RESULTS: A fully automatic lesion detection and segmentation system was able to successfully classify DMSA-positive from negative scans (AUC=0.92, sensitivity=81% and specificity=94%). The image-computed relative size of the lesion correlated with the presence of fever and CRP levels (p<0.05), and a measurement derived from the distribution histogram of the lesion obtained significant performance results in the detection of permanent renal damage (AUC=0.86, sensitivity=100% and specificity=75%). CONCLUSIONS: The proposal and implementation of a computational framework for the quantification of structural renal damage from DMSA scans showed a promising potential to complement visual diagnosis and non-imaging indicators.
	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; no menciona			Approved	no
	Call Number	Admin @ si @ SDE2017			Serial	2842
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	Author	Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez
	Title	Exploiting Natural Language Generation in Scene Interpretation			Type	Book Chapter
	Year	2009	Publication	Human–Centric Interfaces for Ambient Intelligence	Abbreviated Journal
	Volume	4	Issue		Pages	71–93
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	Elsevier Science and Tech	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 @ FBR2009			Serial	1212
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	Author	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Depth of Valleys Accumulation Algorithm for Object Detection			Type	Conference Article
	Year	2011	Publication	14th Congrès Català en Intel·ligencia Artificial	Abbreviated Journal
	Volume	1	Issue	1	Pages	71-80
	Keywords	Object Recognition, Object Region Identification, Image Analysis, Image Processing
	Abstract	This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas.
	Address	Lleida
	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	978-1-60750-841-0	Medium
	Area	800	Expedition		Conference	CCIA
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011b			Serial	1699
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	Author	G. de Oliveira; Mariella Dimiccoli; Petia Radeva
	Title	Egocentric Image Retrieval With Deep Convolutional Neural Networks			Type	Conference Article
	Year	2016	Publication	19th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume		Issue		Pages	71-76
	Keywords
	Abstract
	Address	Barcelona; Spain; October 2016
	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	CCIA
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ODR2016			Serial	2790
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	Author	Anguelos Nicolaou; Sounak Dey; V.Christlein; A.Maier; Dimosthenis Karatzas
	Title	Non-deterministic Behavior of Ranking-based Metrics when Evaluating Embeddings			Type	Conference Article
	Year	2018	Publication	International Workshop on Reproducible Research in Pattern Recognition	Abbreviated Journal
	Volume	11455	Issue		Pages	71-82
	Keywords
	Abstract	Embedding data into vector spaces is a very popular strategy of pattern recognition methods. When distances between embeddings are quantized, performance metrics become ambiguous. In this paper, we present an analysis of the ambiguity quantized distances introduce and provide bounds on the effect. We demonstrate that it can have a measurable effect in empirical data in state-of-the-art systems. We also approach the phenomenon from a computer security perspective and demonstrate how someone being evaluated by a third party can exploit this ambiguity and greatly outperform a random predictor without even access to the input data. We also suggest a simple solution making the performance metrics, which rely on ranking, totally deterministic and impervious to such exploits.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; 600.121; 600.129			Approved	no
	Call Number	Admin @ si @ NDC2018			Serial	3178
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	Author	Carles Onielfa; Carles Casacuberta; Sergio Escalera
	Title	Influence in Social Networks Through Visual Analysis of Image Memes			Type	Conference Article
	Year	2022	Publication	Artificial Intelligence Research and Development	Abbreviated Journal
	Volume	356	Issue		Pages	71-80
	Keywords
	Abstract	Memes evolve and mutate through their diffusion in social media. They have the potential to propagate ideas and, by extension, products. Many studies have focused on memes, but none so far, to our knowledge, on the users that post them, their relationships, and the reach of their influence. In this article, we define a meme influence graph together with suitable metrics to visualize and quantify influence between users who post memes, and we also describe a process to implement our definitions using a new approach to meme detection based on text-to-image area ratio and contrast. After applying our method to a set of users of the social media platform Instagram, we conclude that our metrics add information to already existing user characteristics.
	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; no menciona			Approved	no
	Call Number	Admin @ si @ OCE2022			Serial	3799
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	Author	Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; J. Mauri; X. Carillo; T. Kovarnik; C. Wang; H. Chen; T. P. Exarchos; D. I. Fotiadis; F. Destrempes; G. Cloutier; Oriol Pujol; Marina Alberti; E. G. Mendizabal-Ruiz; M. Rivera; T. Aksoy; R. W. Downe; I. A. Kakadiaris
	Title	Standardized evaluation methodology and reference database for evaluating IVUS image segmentation			Type	Journal Article
	Year	2014	Publication	Computerized Medical Imaging and Graphics	Abbreviated Journal	CMIG
	Volume	38	Issue	2	Pages	70-90
	Keywords	IVUS (intravascular ultrasound); Evaluation framework; Algorithm comparison; Image segmentation
	Abstract	This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.
	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; LAMP; HuPBA; 600.046; 600.063; 600.079			Approved	no
	Call Number	Admin @ si @ BGC2013			Serial	2314
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	Author	Ariel Amato
	Title	Moving cast shadow detection			Type	Journal Article
	Year	2014	Publication	Electronic letters on computer vision and image analysis	Abbreviated Journal	ELCVIA
	Volume	13	Issue	2	Pages	70-71
	Keywords
	Abstract	Motion perception is an amazing innate ability of the creatures on the planet. This adroitness entails a functional advantage that enables species to compete better in the wild. The motion perception ability is usually employed at different levels, allowing from the simplest interaction with the ’physis’ up to the most transcendental survival tasks. Among the five classical perception system , vision is the most widely used in the motion perception field. Millions years of evolution have led to a highly specialized visual system in humans, which is characterized by a tremendous accuracy as well as an extraordinary robustness. Although humans and an immense diversity of species can distinguish moving object with a seeming simplicity, it has proven to be a difficult and non trivial problem from a computational perspective. In the field of Computer Vision, the detection of moving objects is a challenging and fundamental research area. This can be referred to as the ’origin’ of vast and numerous vision-based research sub-areas. Nevertheless, from the bottom to the top of this hierarchical analysis, the foundations still relies on when and where motion has occurred in an image. Pixels corresponding to moving objects in image sequences can be identified by measuring changes in their values. However, a pixel’s value (representing a combination of color and brightness) could also vary due to other factors such as: variation in scene illumination, camera noise and nonlinear sensor responses among others. The challenge lies in detecting if the changes in pixels’ value are caused by a genuine object movement or not. An additional challenging aspect in motion detection is represented by moving cast shadows. The paradox arises because a moving object and its cast shadow share similar motion patterns. However, a moving cast shadow is not a moving object. In fact, a shadow represents a photometric illumination effect caused by the relative position of the object with respect to the light sources. Shadow detection methods are mainly divided in two domains depending on the application field. One normally consists of static images where shadows are casted by static objects, whereas the second one is referred to image sequences where shadows are casted by moving objects. For the first case, shadows can provide additional geometric and semantic cues about shape and position of its casting object as well as the localization of the light source. Although the previous information can be extracted from static images as well as video sequences, the main focus in the second area is usually change detection, scene matching or surveillance. In this context, a shadow can severely affect with the analysis and interpretation of the scene. The work done in the thesis is focused on the second case, thus it addresses the problem of detection and removal of moving cast shadows in video sequences in order to enhance the detection of moving object.
	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 @ Ama2014			Serial	2870
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	Author	Mikhail Mozerov; Ariel Amato; Xavier Roca
	Title	Occlusion Handling in Trinocular Stereo using Composite Disparity Space Image			Type	Conference Article
	Year	2009	Publication	19th International Conference on Computer Graphics and Vision	Abbreviated Journal
	Volume		Issue		Pages	69–73
	Keywords
	Abstract	In this paper we propose a method that smartly improves occlusion handling in stereo matching using trinocular stereo. The main idea is based on the assumption that any occluded region in a matched stereo pair (middle-left images) in general is not occluded in the opposite matched pair (middle-right images). Then two disparity space images (DSI) can be merged in one composite DSI. The proposed integration differs from the known approach that uses a cumulative cost. A dense disparity map is obtained with a global optimization algorithm using the proposed composite DSI. The experimental results are evaluated on the Middlebury data set, showing high performance of the proposed algorithm especially in the occluded regions. One of the top positions in the rank of the Middlebury website confirms the performance of our method to be competitive with the best stereo matching.
	Address	Moscow (Russia)
	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	978-5-317-02975-3	Medium
	Area		Expedition		Conference	GRAPHICON
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ MAR2009b			Serial	1207
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	Author	Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil
	Title	Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging			Type	Book Chapter
	Year	2015	Publication	Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015	Abbreviated Journal
	Volume	9534	Issue		Pages	69-79
	Keywords
	Abstract	Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm.
	Address	Munich; Germany; January 2015
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-319-28711-9	Medium
	Area		Expedition		Conference	STACOM
	Notes	ADAS; IAM; 600.075; 600.076; 600.060; 601.145			Approved	no
	Call Number	Admin @ si @ KHM2015			Serial	2734
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	Author	Aura Hernandez-Sabate; Debora Gil; Petia Radeva
	Title	On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging			Type	Conference Article
	Year	2005	Publication	Proceeding of the 2005 conference on Artificial Intelligence Research and Development	Abbreviated Journal
	Volume		Issue		Pages	67-74
	Keywords	classification; vessel border modelling; IVUS
	Abstract	IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication	Amsterdam, The Netherlands	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	IAM;MILAB			Approved	no
	Call Number	IAM @ iam @ HGR2005c			Serial	1549
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