Shallow Water Bathymetry Mapping from UAV Imagery based on Machine Learning

The determination of accurate bathymetric information is a key element for near offshore activities, hydrological studies such as coastal engineering applications, sedimentary processes, hydrographic surveying as well as archaeological mapping and biological research. UAV imagery processed with Structure from Motion (SfM) and Multi View Stereo (MVS) techniques can provide a low-cost alternative to established shallow seabed mapping techniques offering as well the important visual information. Nevertheless, water refraction poses significant challenges on depth determination. Till now, this problem has been addressed through customized image-based refraction correction algorithms or by modifying the collinearity equation. In this paper, in order to overcome the water refraction errors, we employ machine learning tools that are able to learn the systematic underestimation of the estimated depths. In the proposed approach, based on known depth observations from bathymetric LiDAR surveys, an SVR model was developed able to estimate more accurately the real depths of point clouds derived from SfM-MVS procedures. Experimental results over two test sites along with the performed quantitative validation indicated the high potential of the developed approach.Comment: 8 pages, 9 figure

Cognitive spatial-motor processes--6. Visuomotor memory scanning

Summary. Fourteen human subjects performed in a modified Sternberg memory-scanning task. First, they made a series of 2 6 movements in different directions from a central point towards peripheral lights on a planar working surface ("list trials"). Then, after a warning signal, one of the previous list stimuli, except the last, was presented again ("test trial"). Subjects were instructed to move in the direction of the stimulus which was presented next in sequence in the list. The mean reaction time (RT) in the test trials increased as a linear function of the number of movements, S, in the list: Mean RT (ms)=105+205.8S (2<S<6). This finding suggests that the task involves memory scanning of visuomotor list items

ART – BASED TRAINING METHODS FOR EMPOWERING ADULTS IN THE DIGITAL ERA

Since the dawn of humanity, dancing has been central to life occasions, for celebration, mourning, entertaining or even communicating. Still, it remains a vital practice around the world. With the development of technology, many efforts have been made to adapt specific choreographies and dancing rituals to the modern era, via digital platforms. However, these sequences cannot be construed as realistic when they are viewed through computers, because the actual expressions are lost in the translation. A lot of attempts have been made to provide a solution to this issue, but the most successful are the motion capturing devices and equipment. In this research, we focus on the recording of choreographies, which represent important social concepts, using a Microsoft Kinect sensor as a motion capturing device. Microsoft Kinect is chosen because it is a low-cost device that can deliver adequate results. The outcome of the research is a “handbook” in virtual reality environment, which can be used as an educational tool by anyone. The project aims at being a response to the global need of today’s world for creation of inclusive environments, where socially aware people can peacefully co – exist. The digital handbook can enhance the skills and competences of adult trainers in arts and culture and every participant gets in touch with sensitive concepts and develops social awareness. Inspiration for the project is drawn via social and humanistic values stemming from philosophical, sociological and psychological texts and it is innovative not only for its content but also for the way this is developed

ACCURATE 3D SCANNING OF DAMAGED ANCIENT GREEK INSCRIPTIONS FOR REVEALING WEATHERED LETTERS

In this paper two non-invasive non-destructive alternative techniques to the traditional and invasive technique of squeezes are presented alongside with specialized developed processing methods, aiming to help the epigraphists to reveal and analyse weathered letters in ancient Greek inscriptions carved in masonry or marble. The resulting 3D model would serve as a detailed basis for the epigraphists to try to decipher the inscription. The data were collected by using a Structured Light scanner. The creation of the final accurate three dimensional model is a complicated procedure requiring large computation cost and human effort. It includes the collection of geometric data in limited space and time, the creation of the surface, the noise filtering and the merging of individual surfaces. The use of structured light scanners is time consuming and requires costly hardware and software. Therefore an alternative methodology for collecting 3D data of the inscriptions was also implemented for reasons of comparison. Hence, image sequences from varying distances were collected using a calibrated DSLR camera aiming to reconstruct the 3D scene through SfM techniques in order to evaluate the efficiency and the level of precision and detail of the obtained reconstructed inscriptions. Problems in the acquisition processes as well as difficulties in the alignment step and mesh optimization are also encountered. A meta-processing framework is proposed and analysed. Finally, the results of processing and analysis and the different 3D models are critically inspected and then evaluated by a specialist in terms of accuracy, quality and detail of the model and the capability of revealing damaged and ”hidden” letters

SHALLOW WATER BATHYMETRY MAPPING FROM UAV IMAGERY BASED ON MACHINE LEARNING

The determination of accurate bathymetric information is a key element for near offshore activities, hydrological studies such as coastal engineering applications, sedimentary processes, hydrographic surveying as well as archaeological mapping and biological research. UAV imagery processed with Structure from Motion (SfM) and Multi View Stereo (MVS) techniques can provide a low-cost alternative to established shallow seabed mapping techniques offering as well the important visual information. Nevertheless, water refraction poses significant challenges on depth determination. Till now, this problem has been addressed through customized image-based refraction correction algorithms or by modifying the collinearity equation. In this paper, in order to overcome the water refraction errors, we employ machine learning tools that are able to learn the systematic underestimation of the estimated depths. In the proposed approach, based on known depth observations from bathymetric LiDAR surveys, an SVR model was developed able to estimate more accurately the real depths of point clouds derived from SfM-MVS procedures. Experimental results over two test sites along with the performed quantitative validation indicated the high potential of the developed approach

HEAVY METALS IN URBAN PARK SOILS FROM ATHENS, GREECE

Η αστική γεωχημεία είναιένας επιστημονικός κλάδος ο οποίος αναπτύσσεταιτα τελευταία χρόνια κυρίως λόγω των περιβαλλοντικών επιπτώσεων που προκύπτουν από την αστικοποίηση. Η παρούσα εργασία έχει ως στόχο τον προσδιορισμό των συγκεντρώσεων δυνητικά επιβλαβών στοιχείων (PHEs) των επιφανειακών (0-10 cm) εδαφών προερχόμενων από αλσύλια της Αθήνας. Η δειγματοληψία υπαίθρου πραγματοποιήθηκε σε 20 αλσύλια της Αττικής και κάλυψε συνολική έκταση περίπου 200km2 . Αναλύθηκαν 20 εδαφικά δείγματα κοκκομετρίας Mn >Ni≈ Cu≈ Zn> Cr. Τα δεδομένα της έρευνας υποδεικνύουν ότι το έδαφος των αλσυλίων μπορεί να είναι ένας σημαντικός ταμιευτήρας των ανθρωπογενών στοιχείων στο αστικό έδαφοςUrban geochemistry is a scientific discipline which is growing in the recent years mainly because of the environmental impact caused by urbanization. The present study aims to determine the concentrations of potentially harmful elements (PHEs) on surface soils (0-10cm) in Athens parks. Soil sampling was carried out in public park areas within the Athens urban area. Twenty surface soil (0-10cm) samples were collected and the Mn >Ni≈ Cu≈ Zn> Cr. The data indicate that park areas seem to be important sinks of anthropogenic elements in urban soils

Mesoscale modeling of combined aerosol and photo-oxidant processes in the Eastern Mediterranean

International audienceParticulate matter and photo-oxidant processes in the Eastern Mediterranean have been studied using the UAM-AERO mesoscale air quality model in conjunction with the NILU-CTM regional model. Meteorological data were obtained from the RAMS prognostic meteorological model. The modeling domain includes the eastern Mediterranean area between the Greek mainland and the island of Crete. The modeling system is applied to study the atmospheric processes in three periods, i.e. 13?16 July 2000, 26?30 July 2000 and 7?14 January 2001. The spatial and temporal distributions of both gaseous and particulate matter pollutants have been extensively studied together with the identification of major emission sources in the area. The modeling results were compared with field data obtained in the same period. The objective of the current modeling work was mainly to apply the UAM-AERO mesoscale model in the eastern Mediterranean in order to assess the performed field campaigns and determine that the applied mesoscale model is fit for this purpose. Comparison of the modeling results with measured data was performed for a number of gaseous and aerosol species. The UAM-AERO model underestimates the PM10 measured concentrations during summer and winter campaigns. Discrepancies between modeled and measured data are attributed to unresolved particulate matter emissions. Particulate matter in the area is mainly composed by sulphate, sea salt and crustal materials, and with significant amounts of nitrate, ammonium and organics. During winter the particulate matter and oxidant concentrations were lower than the summer values

Attentive Learning of Sequential Handwriting Movements: A Neural Network Model

Defense Advanced research Projects Agency and the Office of Naval Research (N00014-95-1-0409, N00014-92-J-1309); National Science Foundation (IRI-97-20333); National Institutes of Health (I-R29-DC02952-01)

A somatic mutation in the thyrotropin receptor gene in a patient with an autonomous nodule within a multinodular goiter

ABSTRACT Thyrotropin (TSH) is the prime regulator of thyroid cell growth and function and acts through the thyrotropin receptor (TSHR) located on the surface membrane of thyrocytes. Somatic heterozygous mutations that cause TSHR activation in the absence of TSH have been found in toxic adenomas and in hot nodules of multinodular goiters. Clinically and histologically heterogeneous nodules can share common gain-of-function mutations. Mutation prevalence varies greatly and is inversely related to iodine intake of the population. We report a Greek patient presenting with subclinical hyperthyroidism due to a fast-growing autonomous hyperplastic nodule in a long-standing multinodular goiter. Direct DNA sequencing showed that the hot nodule harbored a somatic heterozygous activating TSHR mutation: substitution of glutamine for leucine in the third transmembrane helix. This mutation (L512Q) was recently described in two solitary toxic adenomas. This report expands the spectrum of mutations shared by dissimilar hot nodules, supporting a common mechanism for nonautoimmune thyroid autonomy. The identification of the L512Q substitution demonstrates that gainof-function TSHR mutations are encountered in Greece, although iodine deficiency has been significantly corrected over the last three decades