PEPSI: Privacy-Enhanced Participatory Sensing Infrastructure.

Participatory Sensing combines the ubiquity of mobile phones with sensing capabilities of Wireless Sensor Networks. It targets pervasive collection of information, e.g., temperature, traffic conditions, or health-related data. As users produce measurements from their mobile devices, voluntary participation becomes essential. However, a number of privacy concerns -- due to the personal information conveyed by data reports -- hinder large-scale deployment of participatory sensing applications. Prior work on privacy protection, for participatory sensing, has often relayed on unrealistic assumptions and with no provably-secure guarantees. The goal of this project is to introduce PEPSI: a Privacy-Enhanced Participatory Sensing Infrastructure. We explore realistic architectural assumptions and a minimal set of (formal) privacy requirements, aiming at protecting privacy of both data producers and consumers. We design a solution that attains privacy guarantees with provable security at very low additional computational cost and almost no extra communication overhead.

Enhanced iron gettering by short, optimized low-temperature annealing after phosphorus emitter diffusion for industrial silicon solar cell processing

The introduction of a low-temperature (LT) tail after P emitter diffusion was shown to lead to considerable improvements in electron lifetime and solar cell performance by different researchers. So far, the drawback of the investigated extended gettering treatments has been the lack of knowledge about optimum annealing times and temperatures and the important increase in processing time. In this manuscript, we calculate optimum annealing temperatures of Fe-contaminated Si wafers for different annealing durations. Subsequently, it is shown theoretically and experimentally that a relatively short LT tail of 15 min can lead to a significant reduction of interstitial Fe and an increase in electron lifetime. Finally, we calculate the potential improvement of solar cell efficiency when such a short-tail extended P diffusion gettering is included in an industrial fabrication process.

Enhanced Exchange And Reduced Magnetization of Gd in an Fe/Gd/Fe Trilayer

The exchange interaction of Gd adjacent to Fe has been characterized by transport measurements on a double spin valve with a Fe/Gd/Fe trilayer as the middle layer. Our measurements show that the ferromagnetism of the Gd is enhanced by the presence of the Fe, and it remains ferromagnetic over its Curie temperature up to a thickness no smaller than 1 nm adjacent to the Fe. This thickness is more than double what has been reported before. Additionally, the saturation magnetization of the thin Gd layer sandwiched in Fe was found to be half of its bulk value. This reduced magnetization does not seem to be related to the proximity of Fe but rather to the incomplete saturation of Gd even for very high fields

Increased glutamine in leaves of poplar transgenic with pine GS1a caused greater anthranilate synthetase a-subunit (ASA1) transcript and protein abundances: an auxin-related mechanism for enhanced growth in GS transgenics?

The initial reaction in the pathway leading to the production of indole-3-acetic acid (IAA) in plants is the reaction between chorismate and glutamine to produce anthranilate, catalysed by the enzyme anthranilate synthase (ASA; EC 4.1.3.27). Compared with non-transgenic controls, leaves of transgenic poplar with ectopic expression of the pine cytosolic glutamine synthetase (GS1a; EC 6.3.1.2) produced significantly greater glutamine and significantly enhanced ASA a-subunit (ASA1) transcript and protein (approximately 130% and 120% higher than in the untransformed controls, respectively). Similarly, tobacco leaves fed with 30 mM glutamine and 2 mM chorismate showed enhanced ASA1 transcript and protein (175% and 90% higher than controls, respectively). Furthermore, free IAA was significantly elevated both in leaves of GS1a transgenic poplar and in tobacco leaves fed with 30 mM glutamine and 2 mM chorismate. These results indicated that enhanced cellular glutamine may account for the enhanced growth in GS transgenic poplars through the regulation of auxin biosynthesis

Polynomial approximation using particle swarm optimization of lineal enhanced neural networks with no hidden layers.

This paper presents some ideas about a new neural network architecture that can be compared to a Taylor analysis when dealing with patterns. Such architecture is based on lineal activation functions with an axo-axonic architecture. A biological axo-axonic connection between two neurons is defined as the weight in a connection in given by the output of another third neuron. This idea can be implemented in the so called Enhanced Neural Networks in which two Multilayer Perceptrons are used; the first one will output the weights that the second MLP uses to computed the desired output. This kind of neural network has universal approximation properties even with lineal activation functions. There exists a clear difference between cooperative and competitive strategies. The former ones are based on the swarm colonies, in which all individuals share its knowledge about the goal in order to pass such information to other individuals to get optimum solution. The latter ones are based on genetic models, that is, individuals can die and new individuals are created combining information of alive one; or are based on molecular/celular behaviour passing information from one structure to another. A swarm-based model is applied to obtain the Neural Network, training the net with a Particle Swarm algorithm.

Enhanced Failure Detection Mechanism in MapReduce

The popularity of MapReduce programming model has increased interest in the research community for its improvement. Among the other directions, the point of fault tolerance, concretely the failure detection issue seems to be a crucial one, but that until now has not reached its satisfying level. Motivated by this, I decided to devote my main research during this period into having a prototype system architecture of MapReduce framework with a new failure detection service, containing both analytical (theoretical) and implementation part. I am confident that this work should lead the way for further contributions in detecting failures to any NoSQL App frameworks, and cloud storage systems in general.

TELMA: Technology enhanced learning environment for minimally invasive surgery

Background: Cognitive skills training for minimally invasive surgery has traditionally relied upon diverse tools, such as seminars or lectures. Web technologies for e-learning have been adopted to provide ubiquitous training and serve as structured repositories for the vast amount of laparoscopic video sources available. However, these technologies fail to offer such features as formative and summative evaluation, guided learning, or collaborative interaction between users. Methodology: The "TELMA" environment is presented as a new technology-enhanced learning platform that increases the user's experience using a four-pillared architecture: (1) an authoring tool for the creation of didactic contents; (2) a learning content and knowledge management system that incorporates a modular and scalable system to capture, catalogue, search, and retrieve multimedia content; (3) an evaluation module that provides learning feedback to users; and (4) a professional network for collaborative learning between users. Face validation of the environment and the authoring tool are presented. Results: Face validation of TELMA reveals the positive perception of surgeons regarding the implementation of TELMA and their willingness to use it as a cognitive skills training tool. Preliminary validation data also reflect the importance of providing an easy-to-use, functional authoring tool to create didactic content. Conclusion: The TELMA environment is currently installed and used at the Jesús Usón Minimally Invasive Surgery Centre and several other Spanish hospitals. Face validation results ascertain the acceptance and usefulness of this new minimally invasive surgery training environment.

Towards the development of poly (phenylene sulphide) based nanocomposites with enhanced mechanical, electrical and tribological properties

Novel poly(phenylene sulphide) (PPS) nanocomposites reinforced with an aminated derivative (PPS-NH2) covalently attached to acid-treated single-walled carbon nanotubes (SWCNTs) were prepared via simple melt-blending technique. Their morphology, viscoelastic behaviour, electrical conductivity, mechanical and tribological properties were investigated. Scanning electron microscopy revealed that the grafting process was effective in uniformly dispersing the SWCNTs within the matrix. The storage and loss moduli as a function of frequency increased with the SWCNT content, tending to a plateau in the low-frequency regime. The electrical conductivity of the nanocomposites was considerably enhanced in the range 0.1?0.5 wt% SWCNTs; electrical and rheological percolation thresholds occurred at similar nanotube concentrations. Mechanical tests demonstrated that with only 1.0 wt% SWCNTs the Young's modulus and tensile strength of the matrix improved by 51 and 37%, respectively, without decrement in toughness, ascribed to a very efficient load transfer. A moderate decrease in the friction coefficient and a 75% reduction in wear rate were found for the abovementioned nanotube loading, indicating that PPS-NH2-g-SWCNTs are good tribological additives for thermoplastic polymers. Based on the promising results obtained in this work, it is expected that these nanofillers will be used to develop high-performance thermoplastic/CNT nanocomposites for structural applications.

Towards materials with enhanced electro-mechanical response: CaCu3Ti4O12-polydimethylsiloxane composites

We describe a straightforward production pathway of polymer matrix composites with increased dielectric constant for dielectric elastomer actuators (DEAs). Up to date, the approach of using composites made of high dielectric constant ceramics and insulating polymers has not evidenced any improvement in the performance of DEA devices, mainly as a consequence of the ferroelectric nature of the employed ceramics. We propose here an unexplored alternative to these traditional fillers, introducing calcium copper titanate (CCTO) CaCu3Ti4O12, which has a giant dielectric constant making it very suitable for capacitive applications. All CCTO-polydimethylsiloxane (PDMS) composites developed display an improved electro-mechanical performance. The largest actuation improvement was achieved for the composite with 5.1 vol% of CCTO, having an increment in the actuation strain of about 100% together with a reduction of 25% in the electric field compared to the raw PDMS matrix.

E-MIS validity applied to TELMA enhanced learning environment

Enhanced learning environments are arising with great success within the field of cognitive skills training in minimally invasive surgery (MIS) because they provides multiple benefits since they avoid time, spatial and cost constraints. TELMA [1,2] is a new technology enhanced learning platform that promotes collaborative and ubiquitous training of surgeons. This platform is based on four main modules: an authoring tool, a learning content and knowledge management system, an evaluation module and a professional network. TELMA has been designed and developed focused on the user; therefore it is necessary to carry out a user validation as final stage of the development. For this purpose, e-MIS validity [3] has been defined. This validation includes usability, contents and functionality validities both for the development and production stages of any e-Learning web platform. Using e-MIS validity, the e-Learning is fully validated since it includes subjective and objective metrics. The purpose of this study is to specify and apply a set of objective and subjective metrics using e-MIS validity to test usability, contents and functionality of TELMA environment within the development stage.

Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd–EOB–DTPA-enhanced MRI

Accurate detection of liver lesions is of great importance in hepatic surgery planning. Recent studies have shown that the detection rate of liver lesions is significantly higher in gadoxetic acid-enhanced magnetic resonance imaging (Gd–EOB–DTPA-enhanced MRI) than in contrast-enhanced portal-phase computed tomography (CT); however, the latter remains essential because of its high specificity, good performance in estimating liver volumes and better vessel visibility. To characterize liver lesions using both the above image modalities, we propose a multimodal nonrigid registration framework using organ-focused mutual information (OF-MI). This proposal tries to improve mutual information (MI) based registration by adding spatial information, benefiting from the availability of expert liver segmentation in clinical protocols. The incorporation of an additional information channel containing liver segmentation information was studied. A dataset of real clinical images and simulated images was used in the validation process. A Gd–EOB–DTPA-enhanced MRI simulation framework is presented. To evaluate results, warping index errors were calculated for the simulated data, and landmark-based and surface-based errors were calculated for the real data. An improvement of the registration accuracy for OF-MI as compared with MI was found for both simulated and real datasets. Statistical significance of the difference was tested and confirmed in the simulated dataset (p < 0.01).

Enhanced recommendations for e-learning authoring tools based on a proactive context-aware recommender

Authoring tools are powerful systems in the area of e-Learning that make easier for teachers to create new learning objects by reusing or editing existing educational resources coming from learning repositories or content providers. However, due to the overwhelming number of resources these tools can access, sometimes it is difficult for teachers to find the most suitable resources taking into account their needs in terms of content (e.g. topic) or pedagogical aspects (e.g. target level associated to their students). Recommender systems can take an important role trying to mitigate this problem. In this paper we propose a new model to generate proactive context-aware recommendations on resources during the creation process of a new learning object that a teacher carries out by using an authoring tool. The common use cases covered by the model for having recommendations in online authoring tools and details about the recommender model itself are presented.

Self-organized colloidal quantum dots and metal nanoparticles for plasmon-enhanced intermediate-band solar cells

A colloidal deposition technique is presented to construct long-range ordered hybrid arrays of self-assembled quantum dots and metal nanoparticles. Quantum dots are promising for novel opto-electronic devices but, in most cases, their optical transitions of interest lack sufficient light absorption to provide a significant impact in their implementation. A potential solution is to couple the dots with localized plasmons in metal nanoparticles. The extreme confinement of light in the near-field produced by the nanoparticles can potentially boost the absorption in the quantum dots by up to two orders of magnitude. In this work, light extinction measurements are employed to probe the plasmon resonance of spherical gold nanoparticles in lead sulfide colloidal quantum dots and amorphous silicon thin-films. Mie theory computations are used to analyze the experimental results and determine the absorption enhancement that can be generated by the highly intense near-field produced in the vicinity of the gold nanoparticles at their surface plasmon resonance. The results presented here are of interest for the development of plasmon-enhanced colloidal nanostructured photovoltaic materials, such as colloidal quantum dot intermediate-band solar cells.

AMELIE: Authoring Multimedia-Enhanced Learning Interactive Environment for medical contents

This paper presents the AMELIE Authoring Tool for medical e-learning applications. The tool allows for the creation of enhanced-video based didactic contents, and can be adjusted to any number of platforms and applications. Validation provides preliminary good results on its acceptance and usefulness.

AMELIE: Authoring Multimedia-Enhanced Learning Interactive Environment for e-Health Contents

This paper presents the AMELIE Authoring Tool for e-health applications. AMELIE provides the means for creating video-based contents with a focus on e-learning and telerehabilitation processes. The main core of AMELIE lies in the efficient exploitation of raw multimedia resources, which may be already available at clinical centers or recorded ad hoc for learning purposes by health professionals. Three real use cases scenarios involving different target users are presented: (1) cognitive skills? training of surgeons in minimally invasive surgery (medical professionals), (2) training of informal carers for elderly home assistance and (3) cognitive rehabilitation of patients with acquired brain injury. Preliminary validation in the field of surgery hints at the potential of AMELIE; and its versatility in different medical applications is patent from the use cases described. Regardless, new validation studies are planned in the three main application areas identified in this work.