316 research outputs found
A. G. Galanopoulos et E. Bacon, L'Atlantide. La vérité derrière la légende
No full textM. J. A. G. Galanopoulos et E. Bacon, L'Atlantide. La vérité derrière la légende. In: Bulletin de l'Association Guillaume Budé, n°2, juin 1970. p. 314
Angiodysplastic lesions as a cause of colonic bleeding in patients with chronic renal disease: Is there an association?
No full textGastrointestinal bleeding due to angiodysplastic lesions of the large bowel is a common problem among patients receiving hemodialysis and may sometimes be life-threatening. Several hypotheses have been advanced in order to explain the increased incidence of these lesions in this cohort of patients, including degenerative, metabolic, circulatory and other systemic factors. In terms of diagnosis, several advances have been made with sophisticated techniques, but endoscopy seems to be the most effective, having a dual role in diagnosis and treatment. Although most bleeds stop spontaneously, conservative treatment may not be enough. Endoscopic treatment, embolization with infusion of vasopressin, surgical resection of the bleeding intestinal segment and hormone administration may be useful therapeutic tools
Integration of carbon dioxide and hydrogen supply chains
No full textIn this work, the impact of Carbon Capture, Utilization, and Storage (CCUS) as a potential technology to reduce Germany's carbon dioxide (CO2) emissions is studied. Carbon dioxide is used as a raw material for methanol production in the global market. Carbon dioxide is captured from power plants and can be reacted to methanol with renewable hydrogen. The study shows that the integration of hydrogen- and carbon dioxide supply chains is only feasible if the electricity needed for renewable hydrogen can be delivered for free
Energy Efficient Spectrum Allocation and Mode Selection for D2D Communications in Heterogeneous Networks
No full textIn this paper, we consider a heterogeneous network consisting of both macro Base Station (MBS) and pico Base Stations (PBSs) in order to provide a spectrum allocation and mode selection in device-to-device (D2D) communications. A number of Component Carriers (CC) are considered available for allocation to the MBS and PBSs that are being utilized through carrier aggregation (CA) while mode selection decisions are made by each BS in order to balance between power consumption minimization and UE data rate requirements. A power minimization (energy-efficient) problem is formulated in order to provide a joint spectrum allocation and mode selection solution. This problem is solved using a state of the art optimization method known as proximal algorithm. First, a non-cooperative (centralized) solution is provided and second, a cooperative (distributed) employing distributed proximal algorithm is devised reducing the induced complexity. The cooperative solution is achieved by implementing distributed alternating direction method of multipliers (D-ADMM). Simulation results are carried out for all cases that reveal the energy efficient spectrum allocation and mode selection according under certain channels' conditions that can balance between achieving high data rate requirements and power minimization. Finally, useful insights are presented such as complexity, convergence, delay and actual implementation of such a solution for the future wireless networks. 2015 IEEE.Manuscript received September 15, 2019; revised January 13, 2020 and March 8, 2020; accepted March 16, 2020. Date of publication May 11, 2020; date of current version May 28, 2020. This work was supported in part by NPRP under Grant NPRP 6-1326-2-532 from the Qatar National Research Fund (a member of Qatar Foundation). The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Pierluigi SALVO ROSSI. (Corresponding author: Fotis Foukalas.) Apostolos Galanopoulos is with Trinity College Dublin, Dublin D02 PN40, Ireland (e-mail: [email protected]).Scopu
On the tectonic processes along the Hellenic Arc
No full textOn the grounds of existing geophysical data one might be allowed lo conclude t h a t the origin of t h e stress field in the Ionian center (Ceplialonia-Zante-Patras) at t h e northwestern margin of the Aegean microplate is r a t h e r shallow and in the southeastern center (Dodecanese-Crete) is surely under the crust. In the area occupied by the second center of higher earthquake activity t h e relief of the Moho-discontinuity is shallower and smoother in comparison to t h a t derived from g r a v i t y and seismic d a t a for t he area of t h e northwestern center. Another difference derived from the fault-plane solutions is t h a t the Ionian center is seated in a region of horizontal pressure; the second center in the southeastern Aegean Sea belongs to a region of paramount horizontal tension. In the western side of the Hellenic arc the high sediment supply rate, combined with a thickening of the E a r t h ' s crust along the Ionian zone, is interpreted as evidence t h a t accretion has occurred there until recently or may still be occurring locally; plate consumption, if any, is rather low. The existence, 011 t h e other hand, of two very deep subparallel trenches with little fill southeast of Crete (Pliny trench, Strabo trench), combined with a very high subcrustal activity in the southeastern margin of t h e Aegean Bubplate, suggest that the subduction rate at the northern boundary of the African plate must be relatively high; 110 p l a t e accretion is expected to occur there
Selective Edge Computing for Mobile Analytics
No full textAn increasing number of mobile applications rely on Machine Learning (ML) routines for analyzing data. Executing such tasks at the user devices saves the energy spent on transmitting and processing large data volumes at distant cloud-deployed servers. However, due to memory and computing limitations, the devices often cannot support the required resource-intensive routines and fail to accurately execute such tasks. In this work, we address the problem of edge-assisted analytics in resourceconstrained systems by proposing and evaluating a rigorous selective offloading framework. The devices execute their tasks locally and outsource them to cloudlet servers only when they predict a significant performance improvement. We consider the practical scenario where the offloading gains and resource costs are time-varying; and propose an online optimization algorithm that maximizes the service performance without requiring to know this information. Our approach relies on an approximate dual subgradient method combined with a primal-averaging scheme, and works under minimal assumptions about the system stochasticity. We fully implement the proposed algorithm in a wireless testbed and evaluate its performance using a state-of-theart image recognition application, finding significant performance gains and cost savings.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Embedded System
AutoML for video analytics with edge computing
No full textVideo analytics constitute a core component of many wireless services that require processing of voluminous data streams emanating from handheld devices. Multi-Access Edge Computing (MEC) is a promising solution for supporting such resource-hungry services, but there is a plethora of configuration parameters affecting their performance in an unknown and possibly time-varying fashion. To overcome this obstacle, we propose an Automated Machine Learning (AutoML) framework for jointly configuring the service and wireless network parameters, towards maximizing the analytics' accuracy subject to minimum frame rate constraints. Our experiments with a bespoke prototype reveal the volatile and system/data-dependent performance of the service, and motivate the development of a Bayesian online learning algorithm which optimizes on-the-fly the service performance. We prove that our solution is guaranteed to find a near-optimal configuration using safe exploration, i.e., without ever violating the set frame rate thresholds. We use our testbed to further evaluate this AutoML framework in a variety of scenarios, using real datasets.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Embedded System
Effective colonoscopy training techniques: strategies to improve patient outcomes
No full textIoannis S Papanikolaou,1 Pantelis S Karatzas,2 Lazaros T Varytimiadis,2 Athanasios Tsigaridas,2 Michail Galanopoulos,2 Nikos Viazis,2 Dimitrios G Karamanolis21Hepato-gastroenterology Unit, 2nd Department of Internal Medicine, Attikon University General Hospital, University of Athens, 2Gastroenterology Department, Evangelismos Hospital, Athens, GreeceAbstract: Colonoscopy has substantially evolved during the last 20 years and many different training techniques have been developed in order to improve the performance of endoscopists. The most known are mechanical simulators, virtual reality simulators, computer-simulating endoscopy, magnetic endoscopic imaging, and composite and explanted animal organ simulators. Current literature generally indicates that the use of simulators improves performance of endoscopists and enhances safety of patients, especially during the initial phase of training. Moreover, newer endoscopes and imaging techniques such as high-definition colonoscopes, chromocolonoscopy with dyes spraying, and third-eye retroscope have been incorporated in everyday practice, offering better visualization of the colon and detection of polyps. Despite the abundance of these different technological features, training devices are not widely used and no official guideline or specified training algorithm or technique for lower gastrointestinal endoscopy has been evolved. In this review, we present the most important training methods currently available and evaluate these using existing literature. We also try to propose a training algorithm for novice endoscopists.Keywords: endoscopy, colonoscopy, teaching techniques, simulator, endoscopists, colon, polyp
Concept detection scores for the MED16train dataset (TRECVID MED task)
No full text<p>We provide concept detection scores for the MED16train dataset which is used at the TRECVID Multimedia Event Detection (MED) task [1]. First, each video is decoded into a set of keyframes at fixed temporal intervals (2 keyframes per second). Then, we calculated concept detection scores for the two following concept sets: i) 487 sport-related concepts from YouTube Sports-1M Dataset[1] and ii) 345 TRECVID SIN concepts [3]. The scores have been generated as follows:<br>
1) For the 487 concepts for the Sports-1M Dataset, a Googlenet network [4] originally trained on 5055 ImageNet concepts was fine-tuned, following the extension strategy of [2] with one extension layer of dimension 128.<br>
2) For the 345 TRECVID SIN concepts, a pre-trained Googlenet network [4] on 5055 ImageNet concepts was fine-tuned on these concepts, again following the extension strategy of [2] with one extension layer of dimension 1024. </p>
<p>After unpacking the compressed file two different folders can be found, namely "Prob_sports_MED16train" and "Prob_SIN_MED16train", one for each concept set. We provide one file for every video of the MED16train dataset for each concept set. Each file consists of N columns (where N = 345 for TRECVID SIN and N = 487 for Sports-1M Dataset) and M rows (where M is the number of extracted keyframes for the corresponding video). Each column corresponds to a different concept, with all concept scores being in the range [0,1]. The higher the score the more likely that the corresponding concept appears in the keyframe. Two additional files are provided; files "sports_487_Classes.txt" and "SIN_345_Classes.txt" indicate the order of the concepts that is used in the concept score files.</p>
<p>[1] A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar and L. Fei-Fei, "Large-scale video classification with convolutional neural networks", In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, pp. 1725-1732, 2014.<br>
[2] N. Pittaras, F. Markatopoulou, V. Mezaris and I. Patras, "Comparison of Fine-tuning and Extension Strategies for Deep Convolutional Neural Networks", Proc. 23rd Int. Conf. on MultiMedia Modeling (MMM'17), Reykjavik, Iceland, Springer LNCS vol. 10132, pp. 102-114, Jan. 2017.<br>
[3] G. Awad, C. Snoek, A. Smeaton, and G. Quénot, "TRECVid semantic indexing of video: a 6-year retrospective", ITE Transactions on Media Technology and Applications, 4 (3). pp. 187-208, 2016.<br>
[4] C. Szegedy, Wei Liu, Yangqing Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke and A. Rabinovich, "Going deeper with convolutions", In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1-9, 2015.</p>Linked publications: (1) N. Pittaras, F. Markatopoulou, V. Mezaris, I. Patras, "Comparison of Fine-tuning and Extension Strategies for Deep Convolutional Neural Networks", Proc. 23rd Int. Conf. on MultiMedia Modeling (MMM'17), Reykjavik, Iceland, Jan. 2017 (2) F. Markatopoulou, A. Moumtzidou, D. Galanopoulos, T. Mironidis, V. Kaltsa, A. Ioannidou, S. Symeonidis, K. Avgerinakis, S. Andreadis, I. Gialampoukidis, S. Vrochidis, A. Briassouli, V. Mezaris, I. Kompatsiaris, I. Patras, "ITI-CERTH participation to TRECVID 2016", In TRECVID 2016 Workshop, Gaithersburg, MD, USA, 2016
Health indicators for diagnostics and prognostics of composite aerospace structures
No full textIn order to reduce aircraft downtimes Condition-Based-Maintenance (CBM) is a topic gaining increased popularity in recent years. However, to apply such maintenance policies reliable health monitoring techniques should be implemented. Two state of the art monitoring techniques, namely Fiber Bragg Gratings (FBG) and Acoustic Emission (AE) are used to monitor the fatigue behavior of single stiffened composite panels (SSCPs) subjected to variable amplitude compression-compression (C-C) fatigue. Advanced features, called Health indicators (HIs) are extracted from the raw sensor data to monitor the degradation behavior. It is crucial to have robust and reliable HIs that capture the degradation of the structures. This work focuses on providing capable HIs for monitoring degradation of composite structures.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Structural Integrity & Composite
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