Embedding, evolution, and validation of model-driven spreadsheets

This paper proposes and validates a model-driven software engineering technique for spreadsheets. The technique that we envision builds on the embedding of spreadsheet models under a widely used spreadsheet system. This means that we enable the creation and evolution of spreadsheet models under a spreadsheet system. More precisely, we embed ClassSheets, a visual language with a syntax similar to the one offered by common spreadsheets, that was created with the aim of specifying spreadsheets. Our embedding allows models and their conforming instances to be developed under the same environment. In practice, this convenient environment enhances evolution steps at the model level while the corresponding instance is automatically co-evolved.Finally,wehave designed and conducted an empirical study with human users in order to assess our technique in production environments. The results of this study are promising and suggest that productivity gains are realizable under our model-driven spreadsheet development setting.

Review of robotic technology for keyhole transcranial stereotactic neurosurgery

The research of stereotactic apparatus to guide surgical devices began in 1908, yet a major part of today's stereotactic neurosurgeries still rely on stereotactic frames developed almost half a century ago. Robots excel at handling spatial information, and are, thus, obvious candidates in the guidance of instrumentation along precisely planned trajectories. In this review, we introduce the concept of stereotaxy and describe a standard stereotactic neurosurgery. Neurosurgeons' expectations and demands regarding the role of robots as assistive tools are also addressed. We list the most successful robotic systems developed specifically for or capable of executing stereotactic neurosurgery. A critical review is presented for each robotic system, emphasizing the differences between them and detailing positive features and drawbacks. An analysis of the listed robotic system features is also undertaken, in the context of robotic application in stereotactic neurosurgery. Finally, we discuss the current perspective, and future directions of a robotic technology in this field. All robotic systems follow a very similar and structured workflow despite the technical differences that set them apart. No system unequivocally stands out as an absolute best. The trend of technological progress is pointing toward the development of miniaturized cost-effective solutions with more intuitive interfaces.

ADSNARK: Nearly practical and privacy-preserving proofs on authenticated data

We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., the third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source — even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland’13), ADSNARK achieves up to 25× improvement in proof-computation time and a 20× reduction in prover storage space.

Three-phase three-level current-source converter for EVs fast battery charging systems

This paper presents a three-phase three-level fast battery charger for electric vehicles (EVs) based in a current-source converter (CSC). Compared with the traditional voltage-source converters used for fast battery chargers, the CSC can be seen as a natural buck-type converter, i.e., the output voltage can assume a wide range of values, which varies between zero and the maximum instantaneous value of the power grid phase-to-phase voltage. Moreover, using the CSC it is not necessary to use a dc-dc back-end converter in the battery side, and it is also possible to control the grid current in order to obtain a sinusoidal waveform, and in phase with the power grid voltage (unitary power factor). Along the paper is described in detail the proposed CSC for EVs fast battery charging systems: the circuit topology, the power control theory, the current control strategy and the grid synchronization algorithm. Several simulation results of the EV fast battery charger operating with a maximum power of 50 kW are presented.

An integrated system for human action recognition from video using hidden Markov model

In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.

Wi-Fi fingerprinting in the real world – RTLS@UM at the EvAAL competition

Research and development around indoor positioning and navigation is capturing the attention of an increasing number of research groups and labs around the world. Among the several techniques being proposed for indoor positioning, solutions based on Wi-Fi fingerprinting are the most popular since they exploit existing WLAN infrastructures to support software-only positioning, tracking and navigation applications. Despite the enormous research efforts in this domain, and despite the existence of some commercial products based on Wi-Fi fingerprinting, it is still difficult to compare the performance, in the real world, of the several existing solutions. The EvAAL competition, hosted by the IPIN 2015 conference, contributed to fill this gap. This paper describes the experience of the RTLS@UM team in participating in track 3 of that competition.

Where@UM - Dependable organic radio maps

In the past decade, the research community has been dedicating considerable effort into indoor positioning systems based on Wi-Fi fingerprinting techniques, mainly due to their capability to exploit existing infrastructures. Crowdsourcing approaches, also known as organic, have been proposed recently to address the problem of creating and maintaining the corresponding radio maps. In these organic systems, the users of the system build the radio map themselves while using it to estimate their own position/location. However, most of these collaborative methods, proposed by several authors, assume that all the users are honest and committed to contribute to a good quality radio map. In this paper we assess the quality of a radio map built collaboratively and propose a method to classify the credibility of individual contributions and the reputation of individual users. Experimental results are presented for an organic indoor location system that has been used by more than one hundred users over a period of around 12 months.

On the impact of overlapping access points in detecting node encounters

Data traces, consisting of logs about the use of mobile and wireless networks, have been used to study the statistics of encounters between mobile nodes, in an attempt to predict the performance of opportunistic networks. Understanding the role and potential of mobile devices as relaying nodes in message dissemination and delivery depends on the knowledge about patterns and number of encounters among nodes. Data traces about the use of WiFi networks are widely available and can be used to extract large datasets of encounters between nodes. However, these logs only capture indirect encounters between nodes, and the resulting encounters datasets might not realistically represent the spatial and temporal behaviour of nodes. This paper addresses the impact of overlapping between the coverage areas of different Access Points of WiFi networks in extracting encounters datasets from the usage logs. Simulation and real-world experimental results show that indirect encounter traces extracted directly from these logs strongly underestimate the opportunities for direct node-to- node message exchange in opportunistic networks.

Interaction paradigms versus age-related user profiles: an evaluation on content selection

Novel input modalities such as touch, tangibles or gestures try to exploit human's innate skills rather than imposing new learning processes. However, despite the recent boom of different natural interaction paradigms, it hasn't been systematically evaluated how these interfaces influence a user's performance or whether each interface could be more or less appropriate when it comes to: 1) different age groups; and 2) different basic operations, as data selection, insertion or manipulation. This work presents the first step of an exploratory evaluation about whether or not the users' performance is indeed influenced by the different interfaces. The key point is to understand how different interaction paradigms affect specific target-audiences (children, adults and older adults) when dealing with a selection task. 60 participants took part in this study to assess how different interfaces may influence the interaction of specific groups of users with regard to their age. Four input modalities were used to perform a selection task and the methodology was based on usability testing (speed, accuracy and user preference). The study suggests a statistically significant difference between mean selection times for each group of users, and also raises new issues regarding the “old” mouse input versus the “new” input modalities.

Using relational algebra on the specification of real world ETL processes

Modeling Extract-Transform-Load (ETL) processes of a Data Warehousing System has always been a challenge. The heterogeneity of the sources, the quality of the data obtained and the conciliation process are some of the issues that must be addressed in the design phase of this critical component. Commercial ETL tools often provide proprietary diagrammatic components and modeling languages that are not standard, thus not providing the ideal separation between a modeling platform and an execution platform. This separation in conjunction with the use of standard notations and languages is critical in a system that tends to evolve through time and which cannot be undermined by a normally expensive tool that becomes an unsatisfactory component. In this paper we demonstrate the application of Relational Algebra as a modeling language of an ETL system as an effort to standardize operations and provide a basis for uncommon ETL execution platforms.

Análise da estrutura de mercado de Resíduos de Equipamentos Elétricos e Eletrónicos: REEE em Portugal

Dissertação de mestrado em Economia Industrial e de Empresa

Gd2O3: Eu Nanoparticle-Based Poly(vinylidene fluoride) Composites for Indirect X-ray Detection

Polymer based scintillator composites have been fabricated by combining poly(vinylidene fluoride) (PVDF) and Gd2O3:Eu nanoparticles (50nm). PVDF has been used since it is a flexible and stable binder matrix and highly resistance to thermal and light deterioration. Gd2O3:Eu has been selected as scintillator material due to its wide band gap, high density and suitable visible light yield. The structural, mechanical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. The introduction of Gd2O3:Eu nanoparticles into the PVDF matrix does not influence the morphology of the polymer or the degree of crystallinity. On the other hand, an increase of the Young´s modulus with respect to PVDF matrix is observed for filler contents of 0.1-0.75 wt.%. The introduction of Gd2O3:Eu into the PVDF matrix increases dielectric constant and DC electrical conductivity as well as the visible light yield in the nanocomposite, being this increase dependent upon Gd2O3:Eu content and X-ray input power. In this way, Gd2O3:Eu/PVDF composites shows suitable characteristics to be used as X-ray radiation transducers, in particular for large area applications.

OnBoard reconfigurable battery charger for electric vehicles with traction-to-auxiliary mode

This paper proposes a single-phase reconfigurable battery charger for Electric Vehicle (EV) that operates in three different modes: Grid-to-Vehicle (G2V) mode, in which the traction batteries are charged from the power grid; Vehicle-to-Grid (V2G) mode, in which the traction batteries deliver part of the stored energy back to the power grid; and in Traction-to-Auxiliary (T2A) mode, in which the auxiliary battery is charged from the traction batteries. When connected to the power grid, the battery charger works with sinusoidal current in the AC side, for both G2V and V2G modes, and also regulates the reactive power. When the EV is disconnected from the power grid, the control algorithms are modified and the full-bridge AC-DC bidirectional converter works as a full-bridge isolated DC-DC converter that is used to charge the auxiliary battery of the EV, avoiding the use of an additional charger to accomplish this task. To assess the behavior of the proposed reconfigurable battery charger under different operation scenarios, a 3.6 kW laboratory prototype has been developed and experimental results are presented.

An interactive web-based tool for breast reduction surgery simulation

In this work, we present a 3D web-based interactive tool for numerical modeling and simulation approach to breast reduction surgery simulation, to assist surgeons in planning all aspects related to breast reduction surgery before the actual procedure takes place, thereby avoiding unnecessary risks. In particular, it allows the modeling of the initial breast geometry, the definition of all aspects related to the surgery and the visualization of the post-surgery breast shape in a realistic environment.

Titanium oxide adhesion layer for high temperature annealed Si/Si3N4/TiOx/Pt/LiCoO2 battery structures

This work describes the influence of a high annealing temperature of about 700C on the Si(substrate)/Si3N4/TiOx/Pt/LiCoO2 multilayer system for the fabrication of all-solid-state lithium ion thin film microbatteries. Such microbatteries typically utilize lithium cobalt oxide (LiCoO2) as cathode material with a platinum (Pt) current collector. Silicon nitride (Si3N4) is used to act as a barrier against Li diffusion into the substrate. For a good adherence between Si3N4 and Pt, commonly titanium (Ti) is used as intermediate layer. However, to achieve crystalline LiCoO2 the multilayer system has to be annealed at high temperature. This post-treatment initiates Ti diffusion into the Pt-collector and an oxidation to TiOx, leading to volume expansion and adhesion failures. To solve this adhesion problem, we introduce titanium oxide (TiOx) as an adhesion layer, avoiding the diffusion during the annealing process. LiCoO2, Pt and Si3N4 layers were deposited by magnetron sputtering and the TiOx layer by thermal oxidation of Ti layers deposited by e-beam technique. Asdeposited and annealed multilayer systems using various TiOx layer thicknesses were studied by scanning electron microscopy (SEM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) and x-ray photoelectron spectroscopy (XPS). The results revealed that an annealing process at temperature of 700C leads to different interactions of Ti atoms between the layers, for various TiOx layer thicknesses (25–45 nm).