Calculating WCET Estimates from Timed Traces

© The Author(s) 2015. This article is published with open access at Springerlink.comReal-time systems engineers face a daunting duty: They must ensure that each task in their system can always meet its deadline. To analyse schedulability they must know the worst-case execution time (WCET) of each task. However, determining exact WCETs is practically infeasible in cost-constrained industrial settings involving real-life code and COTS hardware. Static analysis tools that could yield sufficiently tight WCET bounds are often unavailable. As a result, interest in portable analysis approaches like measurement-based timing analysis (MBTA) is growing. We present an approach based on integer linear programming (ILP) for calculating a WCET estimate from a given database of timed execution traces. Unlike previous work, our method specifically aims at reducing overestimation, by means of an automatic classification of code executions into scenarios with differing worst-case behaviour. To ease the integration into existing analysis tool chains, our method is based on the implicit path enumeration technique (IPET). It can thus reuse flow facts from other analysis tools and produces ILP problems that can be solved by off-the-shelf solvers.Peer reviewe

SOLUS: An innovative multimodal imaging system to improve breast cancer diagnosis through diffuse optics and ultrasounds

To improve non-invasively the specificity in the diagnosis of breast cancer after a positive screening mammography or doubt/suspicious ultrasound examination, the SOLUS project developed a multimodal imaging system that combines: B-mode ultrasound (US) scans (to assess morphology), Color Doppler (to visualize vascularization), shear-wave elastography (to measure stiffness), and time domain multi-wavelength diffuse optical tomography (to estimate tissue composition in terms of oxy- and deoxy-hemoglobin, lipid, water, and collagen concentrations). The multimodal probe arranges 8 innovative photonic modules (optodes) around the US transducer, providing capability for optical tomographic reconstruction. For more accurate estimate of lesion composition, US-assessed morphological priors can be used to guide the optical reconstructions. Each optode comprises: i) 8 picosecond pulsed laser diodes with different wavelengths, covering a wide spectral range (635-1064 nm) for good probing of the different tissue constituents; ii) a large-area (variable, up to 8.6 mm2) fast-gated digital Silicon Photomultiplier; iii) the acquisition electronics to record the distribution of time-of-flight of the re-emitted photons. The optode is the basic element of the optical part of the system, but is also a stand-alone, ultra-compact (about 4 cm3) device for time domain multi-wavelength diffuse optics, with potential application in various fields

SOLUS: a novel multimodal approach to ultrasound and diffuse optics imaging of breast cancer

A multimodal instrument for breast imaging was developed, combining ultrasound (morphology), shear wave elastography (stiffness), and time domain multiwavelength diffuse optical tomography (blood, water, lipid, collagen) to improve the non-invasive diagnosis of breast cancer

Dynamic Power Management for Reactive Stream Processing on the SCC Tiled Architecture

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Dynamic voltage and frequency scaling} (DVFS) is a means to adjust the computing capacity and power consumption of computing systems to the application demands. DVFS is generally useful to provide a compromise between computing demands and power consumption, especially in the areas of resource-constrained computing systems. Many modern processors support some form of DVFS. In this article we focus on the development of an execution framework that provides light-weight DVFS support for reactive stream-processing systems (RSPS). RSPS are a common form of embedded control systems, operating in direct response to inputs from their environment. At the execution framework we focus on support for many-core scheduling for parallel execution of concurrent programs. We provide a DVFS strategy for RSPS that is simple and lightweight, to be used for dynamic adaptation of the power consumption at runtime. The simplicity of the DVFS strategy became possible by sole focus on the application domain of RSPS. The presented DVFS strategy does not require specific assumptions about the message arrival rate or the underlying scheduling method. While DVFS is a very active field, in contrast to most existing research, our approach works also for platforms like many-core processors, where the power settings typically cannot be controlled individually for each computational unit. We also support dynamic scheduling with variable workload. While many research results are provided with simulators, in our approach we present a parallel execution framework with experiments conducted on real hardware, using the SCC many-core processor. The results of our experimental evaluation confirm that our simple DVFS strategy provides potential for significant energy saving on RSPS.Peer reviewe

Strategic research agenda for biomedical imaging

This Strategic Research Agenda identifies current challenges and needs in healthcare, illustrates how biomedical imaging and derived data can help to address these, and aims to stimulate dedicated research funding efforts. Medicine is currently moving towards a more tailored, patient-centric approach by providing personalised solutions for the individual patient. Innovation in biomedical imaging plays a key role in this process as it addresses the current needs for individualised prevention, treatment, therapy response monitoring, and image-guided surgery. The use of non-invasive biomarkers facilitates better therapy prediction and monitoring, leading to improved patient outcomes. Innovative diagnostic imaging technologies provide information about disease characteristics which, coupled with biological, genetic and -omics data, will contribute to an individualised diagnosis and therapy approach. In the emerging field of theranostics, imaging tools together with therapeutic agents enable the selection of best treatments and allow tailored therapeutic interventions. For prenatal monitoring, the use of innovative imaging technologies can ensure an early detection of malfunctions or disease. The application of biomedical imaging for diagnosis and management of lifestyle-induced diseases will help to avoid disease development through lifestyle changes. Artificial intelligence and machine learning in imaging will facilitate the improvement of image interpretation and lead to better disease prediction and therapy planning. As biomedical imaging technologies and analysis of existing imaging data provide solutions to current challenges and needs in healthcare, appropriate funding for dedicated research is needed to implement the innovative approaches for the wellbeing of citizens and patients

NEW CAVE-DWELLING SPECIES OF THE GENUS REMYELLA JEANNEL (LEPTODIRINI, LEIODIDAE, COLEOPTERA) FROM SERBIA

Abstract — The new leiodid beetle species, Remyella raskae n. sp. and Remyella javorensis n. sp. (both from caves in Southwest Serbia, region of Sandžak), are described and diagnosed. Adult genitalia and other taxonomically important characters are illustrated. The new species studied are clearly distinct from their closest congeners. The new forms are of Tertiary or even Pre-Tertiary age and originated during the Alpine Orogeny, which affected vast areas of the Balkan Peninsula, including the Dinarides, their terra typica. The new species represent endemic relicts inhabiting Southwest Serbia. Thorough analysis indicates that the new Remyella taxa originated in the proto-Balkan region; their present distributions correspond to at least a part of their primordial ranges (and habitats)

SOLUS project: Bringing innovation into breast cancer diagnosis and in the time-domain diffuse optical field

To improve the specificity of breast cancer diagnosis SOLUS combines ultrasound, shear-wave elastography and time-domain diffuse optical tomography in a multimodal imaging system. An innovative compact device for time-domain multi-wavelength diffuse optics was also developed

SOLUS: A novel multimodal approach to ultrasound and diffuse optics imaging of breast cancer

A multimodal instrument for breast imaging was developed, combining ultrasound (morphology), shear wave elastography (stiffness), and time domain multiwavelength diffuse optical tomography (blood, water, lipid, collagen) to improve the non-invasive diagnosis of breast cancer

SOLUS: A novel multimodal approach to diffuse optics and ultrasound imaging of breast cancer

A multimodal instrument for breast imaging was developed, combining ultrasound (morphology), shear wave elastography (stiffness), and time domain multiwavelength diffuse optical tomography (blood, water, lipid, collagen) to improve the non-invasive diagnosis of breast cancer