Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

Testing the GlaaS algorithm for dose measurements on low- and high-energy photon beams using an amorphous silicon portal imager

The GLAaS algorithm for pretreatment intensity modulation radiation therapy absolute dose verification based on the use of amorphous silicon detectors, as described in Nicolini et al. [G. Nicolini, A. Fogliata, E. Vanetti, A. Clivio, and L. Cozzi, Med. Phys. 33, 2839-2851 (2006)], was tested under a variety of experimental conditions to investigate its robustness, the possibility of using it in different clinics and its performance. GLAaS was therefore tested on a low-energy Varian Clinac (6 MV) equipped with an amorphous silicon Portal Vision PV-aS500 with electronic readout IAS2 and on a high-energy Clinac (6 and 15 MV) equipped with a PV-aS1000 and IAS3 electronics. Tests were performed for three calibration conditions: A: adding buildup on the top of the cassette such that SDD-SSD = d(max) and comparing measurements with corresponding doses computed at d(max), B: without adding any buildup on the top of the cassette and considering only the intrinsic water-equivalent thickness of the electronic portal imaging devices device (0.8 cm), and C: without adding any buildup on the top of the cassette but comparing measurements against doses computed at d(max). This procedure is similar to that usually applied when in vivo dosimetry is performed with solid state diodes without sufficient buildup material. Quantitatively, the gamma index (gamma), as described by Low et al. [D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, Med. Phys. 25, 656-660 (1998)], was assessed. The gamma index was computed for a distance to agreement (DTA) of 3 mm. The dose difference deltaD was considered as 2%, 3%, and 4%. As a measure of the quality of results, the fraction of field area with gamma larger than 1 (%FA) was scored. Results over a set of 50 test samples (including fields from head and neck, breast, prostate, anal canal, and brain cases) and from the long-term routine usage, demonstrated the robustness and stability of GLAaS. In general, the mean values of %FA remain below 3% for deltaD equal or larger than 3%, while they are slightly larger for deltaD = 2% with %FA in the range from 3% to 8%. Since its introduction in routine practice, 1453 fields have been verified with GLAaS at the authors' institute (6 MV beam). Using a DTA of 3 mm and a deltaD of 4% the authors obtained %FA = 0.9 +/- 1.1 for the entire data set while, stratifying according to the dose calculation algorithm, they observed: %FA = 0.7 +/- 0.9 for fields computed with the analytical anisotropic algorithm and %FA = 2.4 +/- 1.3 for pencil-beam based fields with a statistically significant difference between the two groups. If data are stratified according to field splitting, they observed %FA = 0.8 +/- 1.0 for split fields and 1.0 +/- 1.2 for nonsplit fields without any significant difference.

Energy Efficient Multimedia Communications in IEEE 802.11 Networks

During the last decade wireless mobile communications have progressively become part of the people’s daily lives, leading users to expect to be “alwaysbest-connected” to the Internet, regardless of their location or time of day. This is indeed motivated by the fact that wireless access networks are increasingly ubiquitous, through different types of service providers, together with an outburst of thoroughly portable devices, namely laptops, tablets, mobile phones, among others. The “anytime and anywhere” connectivity criterion raises new challenges regarding the devices’ battery lifetime management, as energy becomes the most noteworthy restriction of the end-users’ satisfaction. This wireless access context has also stimulated the development of novel multimedia applications with high network demands, although lacking in energy-aware design. Therefore, the relationship between energy consumption and the quality of the multimedia applications perceived by end-users should be carefully investigated. This dissertation addresses energy-efficient multimedia communications in the IEEE 802.11 standard, which is the most widely used wireless access technology. It advances the literature by proposing a unique empirical assessment methodology and new power-saving algorithms, always bearing in mind the end-users’ feedback and evaluating quality perception. The new EViTEQ framework proposed in this thesis, for measuring video transmission quality and energy consumption simultaneously, in an integrated way, reveals the importance of having an empirical and high-accuracy methodology to assess the trade-off between quality and energy consumption, raised by the new end-users’ requirements. Extensive evaluations conducted with the EViTEQ framework revealed its flexibility and capability to accurately report both video transmission quality and energy consumption, as well as to be employed in rigorous investigations of network interface energy consumption patterns, regardless of the wireless access technology. Following the need to enhance the trade-off between energy consumption and application quality, this thesis proposes the Optimized Power save Algorithm for continuous Media Applications (OPAMA). By using the end-users’ feedback to establish a proper trade-off between energy consumption and application performance, OPAMA aims at enhancing the energy efficiency of end-users’ devices accessing the network through IEEE 802.11. OPAMA performance has been thoroughly analyzed within different scenarios and application types, including a simulation study and a real deployment in an Android testbed. When compared with the most popular standard power-saving mechanisms defined in the IEEE 802.11 standard, the obtained results revealed OPAMA’s capability to enhance energy efficiency, while keeping end-users’ Quality of Experience within the defined bounds. Furthermore, OPAMA was optimized to enable superior energy savings in multiple station environments, resulting in a new proposal called Enhanced Power Saving Mechanism for Multiple station Environments (OPAMA-EPS4ME). The results of this thesis highlight the relevance of having a highly accurate methodology to assess energy consumption and application quality when aiming to optimize the trade-off between energy and quality. Additionally, the obtained results based both on simulation and testbed evaluations, show clear benefits from employing userdriven power-saving techniques, such as OPAMA, instead of IEEE 802.11 standard power-saving approaches.

VMC++ validation for photon beams in the energy range of 20-1000 keV

In high energy teletherapy, VMC++ is known to be a very accurate and efficient Monte Carlo (MC) code. In principle, the MC method is also a powerful dose calculation tool in other areas in radiation oncology, e.g., brachytherapy or orthovoltage radiotherapy. However, VMC++ is not validated for the low-energy range of such applications. This work aims in the validation of the VMC++ MC code for photon beams in the energy range between 20 and 1000 keV.

Dual-energy multidetector CT: how does it work, what can it tell us, and when can we use it in abdominopelvic imaging?

Dual-energy CT provides information about how substances behave at different energies, the ability to generate virtual unenhanced datasets, and improved detection of iodine-containing substances on low-energy images. Knowing how a substance behaves at two different energies can provide information about tissue composition beyond that obtainable with single-energy techniques. The term K edge refers to the spike in attenuation that occurs at energy levels just greater than that of the K-shell binding because of the increased photoelectric absorption at these energy levels. K-edge values vary for each element, and they increase as the atomic number increases. The energy dependence of the photoelectric effect and the variability of K edges form the basis of dual-energy techniques, which may be used to detect substances such as iodine, calcium, and uric acid crystals. The closer the energy level used in imaging is to the K edge of a substance such as iodine, the more the substance attenuates. In the abdomen and pelvis, dual-energy CT may be used in the liver to increase conspicuity of hypervascular lesions; in the kidneys, to distinguish hyperattenuating cysts from enhancing renal masses and to characterize renal stone composition; in the adrenal glands, to characterize adrenal nodules; and in the pancreas, to differentiate between normal and abnormal parenchyma.

Jet energy measurement with the ATLAS detector in proton-proton collisions at sqrt(s) = 7 TeV

The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of sqrt(s) = 7 TeV corresponding to an integrated luminosity of 38 inverse pb. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0.4 or R=0.6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pt > 20 GeV and pseudorapidities eta<4.5. The JES systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams. The JES uncertainty is less than 2.5% in the central calorimeter region (eta<0.8) for jets with 60 < pt < 800 GeV, and is maximally 14% for pt < 30 GeV in the most forward region 3.2 50 GeV after a dedicated correction for this effect. The JES is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pt, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pt jets recoiling against a high-pt jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, providing an improved jet energy resolution and a reduced flavour dependence of the jet response. The JES systematic uncertainty determined from a combination of in situ techniques are consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pt jets.

Determination of α_{s} from the QCD static energy

We compare lattice data for the short-distance part of the static energy in 21 flavor quantum chromodynamics (QCD) with perturbative calculations, up to next-to-next-to-next-to leading-logarithmic accuracy. We show that perturbation theory describes very well the lattice data at short distances, and exploit this fact to obtain a determination of the product of the lattice scale r0 with the QCD scale ΛMS. With the input of the value of r0, this provides a determination of the strong coupling αs at the typical distance scale of the lattice data. We obtain αs1.5  GeV0.3260.019, which provides a novel determination of αs with three-loop accuracy (including resummation of the leading ultrasoft logarithms), and constitutes one of the few low-energy determinations of αs available. When this value is evolved to the Z-mass scale MZ, it corresponds to αsMZ0.11560.00220.0021.

SLA-driven predictive orchestration for distributed cloud-based mobile services

We describe a system for performing SLA-driven management and orchestration of distributed infrastructures composed of services supporting mobile computing use cases. In particular, we focus on a Follow-Me Cloud scenario in which we consider mobile users accessing cloud-enable services. We combine a SLA-driven approach to infrastructure optimization, with forecast-based performance degradation preventive actions and pattern detection for supporting mobile cloud infrastructure management. We present our system's information model and architecture including the algorithmic support and the proposed scenarios for system evaluation.

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Mobile Cloud Networking: Virtualisation of Cellular Networks

Virtualisation of cellular networks can be seen as a way to significantly reduce the complexity of processes, required nowadays to provide reliable cellular networks. The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN) is a EU FP7 Large-scale Integrating Project (IP) funded by the European Commission that is focusing on cloud computing concepts to achieve virtualisation of cellular networks. It aims at the development of a fully cloud-based mobile communication and application platform, or more specifically, it aims to investigate, implement and evaluate the technological foundations for the mobile communication system of Long Term Evolution (LTE), based on Mobile Network plus Decentralized Computing plus Smart Storage offered as one atomic service: On-Demand, Elastic and Pay-As-You-Go. This paper provides a brief overview of the MCN project and discusses the challenges that need to be solved.

The Integration of Electricity from Renewable Energy Sources in the European Union Electricity Market – The case for “Smart Grids”

The power sector is to play a central role in a low carbon economy. In all the decarbonisation scenarios of the European Union renewable energy sources (RES) will be a crucial part of the solution. Current grids constitute however major bottlenecks for the future expansion of RES. Recognising the need for a modernisation of its grids, the European Union has called for the creation of a "smart supergrid" interconnecting European grids at the continental level and making them "intelligent" through the addition of information and communication technology (ICT). To implement its agenda the EU has taken a leading role in coordinating research efforts and creating a common legislative framework for the necessary modernisation of Europe’s grids. This paper intends to give both an overview and a critical appraisal of the measures taken so far by the European Union to "transform" the grids into the backbone of a decarbonised electricity system. It suggests that if competition is to play a significant role in the deployment of smart grids, the current regulatory paradigm will have to be fundamentally reassessed

Jet energy measurement with the ATLAS detector in proton-proton collisions at sqrt(s) = 7 TeV

The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of sqrt(s) = 7 TeV corresponding to an integrated luminosity of 38 inverse pb. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0.4 or R=0.6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pt > 20 GeV and pseudorapidities eta<4.5. The JES systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams. The JES uncertainty is less than 2.5% in the central calorimeter region (eta<0.8) for jets with 60 < pt < 800 GeV, and is maximally 14% for pt < 30 GeV in the most forward region 3.2 50 GeV after a dedicated correction for this effect. The JES is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pt, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pt jets recoiling against a high-pt jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, providing an improved jet energy resolution and a reduced flavour dependence of the jet response. The JES systematic uncertainty determined from a combination of in situ techniques are consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pt jets.

Green Wireless-Energy Efficiency in Wireless Networks

Wireless networks have become more and more popular because of ease of installation, ease of access, and support of smart terminals and gadgets on the move. In the overall life cycle of providing green wireless technology, from production to operation and, finally, removal, this chapter focuses on the operation phase and summarizes insights in energy consumption of major technologies. The chapter also focuses on the edge of the network, comprising network access points (APs) and mobile user devices. It discusses particularities of most important wireless networking technologies: wireless access networks including 3G/LTE and wireless mesh networks (WMNs); wireless sensor networks (WSNs); and ad-hoc and opportunistic networks. Concerning energy efficiency, the chapter discusses challenges in access, wireless sensor, and ad-hoc and opportunistic networks.

Network Store: Exploring Slicing in Future 5G Networks

In this paper, we present a revolutionary vision of 5G networks, in which SDN programs wireless network functions, and where Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties are provided with NFV-ready Network Store. The proposed Network Store serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enable 5G application use-cases. Currently existing application stores, such as Apple's App Store for iOS applications, Google's Play Store for Android, or Ubuntu's Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the cloud as the application store is currently to a software platform.

SCAD: Sensor Context-aware Adaptive Duty-cycled Beaconless Opportunistic Routing for WSNs

Low quality of wireless links leads to perpetual transmission failures in lossy wireless environments. To mitigate this problem, opportunistic routing (OR) has been proposed to improve the throughput of wireless multihop ad-hoc networks by taking advantage of the broadcast nature of wireless channels. However, OR can not be directly applied to wireless sensor networks (WSNs) due to some intrinsic design features of WSNs. In this paper, we present a new OR solution for WSNs with suitable adaptations to their characteristics. Our protocol, called SCAD-Sensor Context-aware Adaptive Duty-cycled beaconless opportunistic routing protocol is a cross-layer routing approach and it selects packet forwarders based on multiple sensor context information. To reach a balance between performance and energy-efficiency, SCAD adapts the duty-cycles of sensors according to real-time traffic loads and energy drain rates. We compare SCAD against other protocols through extensive simulations. Evaluation results show that SCAD outperforms other protocols in highly dynamic scenarios.