11th International Coral Reef Symposium Proceedings

A defining theme of the 11th International Coral Reef Symposium was that the news for coral reef ecosystems are far from encouraging. Climate change happens now much faster than in an ice-age transition, and coral reefs continue to suffer fever-high temperatures as well as sour ocean conditions. Corals may be falling behind, and there appears to be no special silver bullet remedy. Nevertheless, there are hopeful signs that we should not despair. Reef ecosystems respond vigorously to protective measures and alleviation of stress. For concerned scientists, managers, conservationists, stakeholders, students, and citizens, there is a great role to play in continuing to report on the extreme threat that climate change represents to earth’s natural systems. Urgent action is needed to reduce CO2 emissions. In the interim, we can and must buy time for coral reefs through increased protection from sewage, sediment, pollutants, overfishing, development, and other stressors, all of which we know can damage coral health. The time to act is now. The canary in the coral-coal mine is dead, but we still have time to save the miners. We need effective management rooted in solid interdisciplinary science and coupled with stakeholder buy in, working at local, regional, and international scales alongside global efforts to give reefs a chance.https://nsuworks.nova.edu/occ_icrs/1000/thumbnail.jp

A study on the Probabilistic Interval-based Event Calculus

Η Αναγνώριση Σύνθετων Γεγονότων είναι το πεδίο εκείνο της Τεχνητής Νοημοσύνης το οποίο αποσκοπεί στο σχεδιασμό και την κατασκευή συστημάτων τα οποία επεξεργάζονται γρήγορα μεγάλες και πιθανώς ετερογενείς ροές δεδομένων και τα οποία είναι σε θέση να αναγνωρίζουν εγκαίρως μη τετριμμένα και ενδιαφέροντα συμβάντα, βάσει κατάλληλων ορισμών που προέρχονται από ειδικούς. Σκοπός ενός τέτοιου συστήματος είναι η αυτοματοποιημένη εποπτεία πολύπλοκων και απαιτητικών καταστάσεων και η υποβοήθηση της λήψης αποφάσεων από τον άνθρωπο. Η αβεβαιότητα και ο θόρυβος είναι έννοιες που υπεισέρχονται φυσικά σε τέτοιες ροές δεδομένων και συνεπώς, καθίσταται απαραίτητη η χρήση της Θεωρίας Πιθανοτήτων για την αντιμετώπισή τους. Η πιθανοτική Αναγνώριση Σύνθετων Γεγονότων μπορεί να πραγματοποιηθεί σε επίπεδο χρονικής στιγμής ή σε επίπεδο χρονικού διαστήματος. Η παρούσα εργασία εστιάζει στον PIEC, έναν σύγχρονο αλγόριθμο για την Αναγνώριση Σύνθετων Γεγονότων με τη χρήση πιθανοτικών, μέγιστων διαστημάτων. Αρχικά παρουσιάζουμε τον αλγόριθμο και τον ερευνούμε ενδελεχώς. Μελετούμε την ορθότητά του μέσα από μια σειρά μαθηματικών αποδείξεων περί της ευρωστίας (soundness) και της πληρότητάς του (completeness). Κατόπιν, παραθέτουμε εκτενή πειραματική αποτίμηση του υπό μελέτη αλγορίθμου και σύγκρισή του με συστήματα πιθανοτικής Αναγνώρισης Γεγονότων σε επίπεδο χρονικών σημείων. Τα αποτελέσματά μας δείχνουν ότι ο PIEC επιδεικνύει σταθερά καλύτερη Ανάκληση (Recall), παρουσιάζοντας, ωστόσο κάποιες απώλειες σε Ακρίβεια (Precision) σε ορισμένες περιπτώσεις. Για τον λόγο αυτόν, εμβαθύνουμε και εξετάζουμε συγκεκριμένες περιπτώσεις στις οποίες ο PIEC αποδίδει καλύτερα, καθώς και άλλες στις οποίες παράγει αποτελέσματα υποδεέστερα των παραδοσιακών μεθόδων σημειακής αναγνώρισης, σε μια προσπάθεια να εντοπίσουμε και να διατυπώσουμε τις δυνατότητες αλλά και τις αδυναμίες του αλγορίθμου. Τέλος, θέτουμε τις γενικές κατευθυντήριες γραμμές για περαιτέρω έρευνα στο εν λόγω ζήτημα, τμήματα της οποίας βρίσκονται ήδη σε εξέλιξη.Complex Event Recognition is the subdivision of Artificial Intelligence that aims to design and construct systems that quickly process large and often heterogeneous streams of data and timely deduce – based on definitions set by domain experts – the occurrence of non-trivial and interesting incidents. The purpose of such systems is to provide useful insights into involved and demanding situations that would otherwise be difficult to monitor, and to assist decision making. Uncertainty and noise are inherent in such data streams and therefore, Probability Theory becomes necessary in order to deal with them. The probabilistic recognition of Complex Events can be done in a timepoint-based or an interval-based manner. This thesis focuses on PIEC, a state-of-the-art probabilistic, interval-based Complex Event Recognition algorithm. We present the algorithm and examine it in detail. We study its correctness through a series of mathematical proofs of its soundness and completeness. Afterwards, we provide thorough experimental evaluation and comparison to point-based probabilistic Event Recognition methods. Our evaluation shows that PIEC consistently displays better Recall measures, often at the expense of a generally worse Precision. We then focus on cases where PIEC performs significantly better and cases where it falls short, in an effort to detect and state its main strengths and weaknesses. We also set the general directions for further research on the topic, parts of which are already in progress

Architectures and Standards for Spatial Data Infrastructures and Digital Government: European Union Location Framework Guidelines

This document provides an overview of the architecture(s) and standards for Spatial Data Infrastructures (SDI) and Digital Government. The document describes the different viewpoints according to the Reference Model for Open and Distributed Processing (RM-ODP) which is often used in both the SDI and e-Government worlds: the enterprise viewpoint, the engineering viewpoint, the information viewpoint, the computational viewpoint and the technological viewpoint. The document not only describes these viewpoints with regard to SDI and e-Government implementations, but also how the architecture(s) and standards of SDI and e-Government relate. It indicates which standards and tools can be used and provides examples of implementations in different areas, such as process modelling, metadata, data and services. In addition, the annex provides an overview of the most commonly used standards and technologies for SDI and e-Government.JRC.B.6-Digital Econom

Performance Analysis For Wireless G (IEEE 802.11 G) And Wireless N (IEEE 802.11 N) In Outdoor Environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. the comparison consider on coverage area (mobility), through put and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g

Performance analysis for wireless G (IEEE 802.11G) and wireless N (IEEE 802.11N) in outdoor environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. The comparison consider on coverage area (mobility), throughput and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g