Techniques for effective and efficient fire detection from social media images

Social media could provide valuable information to support decision making in crisis management, such as in accidents, explosions and fires. However, much of the data from social media are images, which are uploaded in a rate that makes it impossible for human beings to analyze them. Despite the many works on image analysis, there are no fire detection studies on social media. To fill this gap, we propose the use and evaluation of a broad set of content-based image retrieval and classification techniques for fire detection. Our main contributions are: (i) the development of the Fast-Fire Detection method (FFDnR), which combines feature extractor and evaluation functions to support instance-based learning, (ii) the construction of an annotated set of images with ground-truth depicting fire occurrences -- the FlickrFire dataset, and (iii) the evaluation of 36 efficient image descriptors for fire detection. Using real data from Flickr, our results showed that FFDnR was able to achieve a precision for fire detection comparable to that of human annotators. Therefore, our work shall provide a solid basis for further developments on monitoring images from social media.Comment: 12 pages, Proceedings of the International Conference on Enterprise Information Systems. Specifically: Marcos Bedo, Gustavo Blanco, Willian Oliveira, Mirela Cazzolato, Alceu Costa, Jose Rodrigues, Agma Traina, Caetano Traina, 2015, Techniques for effective and efficient fire detection from social media images, ICEIS, 34-4

ARCHANGEL: Tamper-proofing Video Archives using Temporal Content Hashes on the Blockchain

We present ARCHANGEL; a novel distributed ledger based system for assuring the long-term integrity of digital video archives. First, we describe a novel deep network architecture for computing compact temporal content hashes (TCHs) from audio-visual streams with durations of minutes or hours. Our TCHs are sensitive to accidental or malicious content modification (tampering) but invariant to the codec used to encode the video. This is necessary due to the curatorial requirement for archives to format shift video over time to ensure future accessibility. Second, we describe how the TCHs (and the models used to derive them) are secured via a proof-of-authority blockchain distributed across multiple independent archives. We report on the efficacy of ARCHANGEL within the context of a trial deployment in which the national government archives of the United Kingdom, Estonia and Norway participated.Comment: Accepted to CVPR Blockchain Workshop 201

40 Gbps Access for Metro networks: Implications in terms of Sustainability and Innovation from an LCA Perspective

In this work, the implications of new technologies, more specifically the new optical FTTH technologies, are studied both from the functional and non-functional perspectives. In particular, some direct impacts are listed in the form of abandoning non-functional technologies, such as micro-registration, which would be implicitly required for having a functioning operation before arrival the new high-bandwidth access technologies. It is shown that such abandonment of non-functional best practices, which are mainly at the management level of ICT, immediately results in additional consumption and environmental footprint, and also there is a chance that some other new innovations might be 'missed.' Therefore, unconstrained deployment of these access technologies is not aligned with a possible sustainable ICT picture, except if they are regulated. An approach to pricing the best practices, including both functional and non-functional technologies, is proposed in order to develop a regulation and policy framework for a sustainable broadband access.Comment: 10 pages, 6 Tables, 1 Figure. Accepted to be presented at the ICT4S'15 Conferenc

Energy-efficient acceleration of MPEG-4 compression tools

We propose novel hardware accelerator architectures for the most computationally demanding algorithms of the MPEG-4 video compression standard-motion estimation, binary motion estimation (for shape coding), and the forward/inverse discrete cosine transforms (incorporating shape adaptive modes). These accelerators have been designed using general low-energy design philosophies at the algorithmic/architectural abstraction levels. The themes of these philosophies are avoiding waste and trading area/performance for power and energy gains. Each core has been synthesised targeting TSMC 0.09 μm TCBN90LP technology, and the experimental results presented in this paper show that the proposed cores improve upon the prior art

QoE-Based Low-Delay Live Streaming Using Throughput Predictions

Recently, HTTP-based adaptive streaming has become the de facto standard for video streaming over the Internet. It allows clients to dynamically adapt media characteristics to network conditions in order to ensure a high quality of experience, that is, minimize playback interruptions, while maximizing video quality at a reasonable level of quality changes. In the case of live streaming, this task becomes particularly challenging due to the latency constraints. The challenge further increases if a client uses a wireless network, where the throughput is subject to considerable fluctuations. Consequently, live streams often exhibit latencies of up to 30 seconds. In the present work, we introduce an adaptation algorithm for HTTP-based live streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is designed to operate with a transport latency of few seconds. To reach this goal, LOLYPOP leverages TCP throughput predictions on multiple time scales, from 1 to 10 seconds, along with an estimate of the prediction error distribution. In addition to satisfying the latency constraint, the algorithm heuristically maximizes the quality of experience by maximizing the average video quality as a function of the number of skipped segments and quality transitions. In order to select an efficient prediction method, we studied the performance of several time series prediction methods in IEEE 802.11 wireless access networks. We evaluated LOLYPOP under a large set of experimental conditions limiting the transport latency to 3 seconds, against a state-of-the-art adaptation algorithm from the literature, called FESTIVE. We observed that the average video quality is by up to a factor of 3 higher than with FESTIVE. We also observed that LOLYPOP is able to reach a broader region in the quality of experience space, and thus it is better adjustable to the user profile or service provider requirements.Comment: Technical Report TKN-16-001, Telecommunication Networks Group, Technische Universitaet Berlin. This TR updated TR TKN-15-00

Gold nanorods as molecular contrast agents in photoacoustic imaging: the promises and the caveats\ud

Rod-shaped gold nanoparticles exhibit intense and narrow absorption peaks for light in the far-red and near-infrared wavelength regions, owing to the excitation of longitudinal plasmons. Light absorption is followed predominantly by non radiative de-excitation, and the released heat and subsequent temperature rise cause strong photoacoustic (optoacoustic) signals to be produced. This feature combined with the relative inertness of gold, and its favorable surface chemistry, which permits affinity biomolecule coupling, has seen gold nanorods (AuNR) attracting much attention as contrast agents and molecular probes for photoacoustic imaging. In this article we provide an short overview of the current status of the use of AuNR in molecular imaging using photoacoustics. We further examine the state of the art in various chemical, physical and biochemical phenomena that have implications for the future photoacoustic applications of these particles. We cover the route through fine-tuning of AuNR synthetic procedures, toxicity reduction by appropriate coatings, in vitro cellular interactions of AuNRs, attachment of targeting antibodies, in vivo fate of the particles and the effects of certain light interactions with the AuN