Land‐use dynamic discovery based on heterogeneous mobility sources

Nowadays, cities are the most relevant type of human settlement and their population has been endlessly growing for decades. At the same time, we are witnessing an explosion of digital data that capture many different aspects and details of city life. This allows detecting human mobility patterns in urban areas with more detail than ever before. In this context, based on the fusion of mobility data from different and heterogeneous sources, such as public transport, transport‐network connectivity and Online Social Networks, this study puts forward a novel approach to uncover the actual land use of a city. Unlike previous solutions, our work avoids a time‐invariant approach and it considers the temporal factor based on the assumption that urban areas are not used by citizens all the time in the same manner. We have tested our solution in two different cities showing high accuracy rates.     

Interactive curvilinear reformatting in native space

Curvilinear reformatting of 3D magnetic resonance imaging data has been recognized by the medical community as a helpful noninvasive tool for displaying the cerebral anatomy. It consists of automatically creating, with respect to a reference surface, a series of equidistant curvilinear slices at progressively deeper cuts. In comparison with planar slices, it allows more precise localization of lesions and identification of subtle structural abnormalities. However, current curvilinear reformatting tools either rely on the time-consuming manual delineation of guiding curves on 2D slices, or require costly automatic brain segmentation procedures. In addition, they extract the skin and skull, impeding a precise topographic correlation between the location of the brain lesion and skin surface. This impairs planning of craniotomy for neurosurgery, and of the appropriate implantation of electrodes for intracranial electroencephalography in presurgical evaluation. In this work, we present a novel approach based on direct manipulation of the visualized volume data. By using a 3D painting metaphor, the reference surface can be defined incrementally, according to the principle that the user interacts with what she/he sees. As a response, an animation of the reformatting process is displayed. The focus of this paper is a new volume tagging algorithm behind user interactions. It works at an interactive frame rate on current graphics hardware.     

HEAT TRANSFER IN PARTIALLY MISCIBLE TERNARY SYSTEMS

In the study of mass transfer between partially miscible liquids, temperature perturbations have been found to have an important effect in the generation of interfacial activity. Micro- and macro-generated interfacial convection usually occurs in combination with one another even in fairly simple heat or mass transfer events. These combinations are responsible for the enhancement of mass transfer rates. In an effort to acquire a better understanding of the heat transfer effects in ternary liquid-liquid systems, temperature difference profiles were measured when contacting two partially miscible phases. A vertical and a rotational transfer cell were designed to contact the partially miscible phases without inducing external disturbances. Five thermocouples were immersed in the bottom liquid phase at predetermined positions below the interface. In order to understand the influence of the convection generated, the vertical cell was designed to hinder convection in one phase, while the rotational cell permits convection in both phases. The experimental results showed larger temperature differences in the rotational cell after the contact of the phases. Also, systems which were initially unsaturated presented larger heat effects than those in which the partially miscible solvents were initially saturated. Several parameters indicating the importance of heat effects in the ternary systems studied are reported.     

On the robust control of stable minimum phase plants with large uncertainty in a time constant. A fractional-order control approach

This paper addresses the problem of designing controllers that are robust to a great uncertainty in a time constant of the plant. Plants must be represented by minimum phase rational transfer functions of an arbitrary order. The design specifications are: (1) a phase margin for the nominal plant, (2) a gain crossover frequency for the nominal plant, (3) zero steady state error to step commands, and (4) a constant phase margin for all the possible values of the time constant (T$T$): 0<T<∞$0<T<\infty$. We propose a theorem that defines the structure of the set of controllers that fulfil these specifications and show that it is necessary for these robust controllers to include a fractional-order PI$PI$ term. Examples are developed for both stable and unstable plants, and the results are compared with a standard PI$PI$ controller and a robust controller designed using the QFT$QFT$ methodology.     

Improving process models by mining mappings of low-level events to high-level activities

While it is possible to analyze the run-time behavior of a business process through process mining techniques, in practice there is often a gap between the low-level nature of the events recorded in an event log and the high-level of abstraction at which the process is modeled. This makes it difficult to understand the recorded behavior in terms of the high-level activities in the process model. Also, it makes it difficult to improve the model based on run-time data about the process. In this work we present an approach to mine mappings between the events in the log and the activities in the model. These mappings can be used to generate suggestions of how the process model can be extended in order to capture the behavior recorded in the event log. Using a real-world and publicly available event log, we show how the approach can improve the model in a stepwise manner, until it covers all the behavior recorded in the event log.     

The toughness of copolymers of polypropylene

A series of fracture mechanics tests of a set of random and impact copolymers of polypropylene, in which the ethylene content was varied, is described. The plane strain toughness is found to change from the homopolymer value, but thereafter to be independent of ethylene content. The yield stress of the impact copolymers decreases markedly with ethylene content, while that for random copolymers increases only slightly. This is reflected in toughness values in tension. A comparison with the behavior of other rubber-modified materials is made and it is concluded that crazing is an important mechanism in polypropylene and is perhaps more rate and temperature sensitive than in acrylonitrile-butadiene-styrene (ABS).     

Catalytic combustion of trichloroethene over Ru/Al2O3: Reaction mechanism and kinetic study

The performance of 0.5% Ru/Al₂O₃ for the deep oxidation of trichloroethene (1000–2500 ppmV, WHSV = 55 h⁻¹) in air was studied in this work. Experiments were carried out both at dry and wet (20,000 ppmV of H₂O) conditions. Catalytic performance was studied in terms of activity and selectivity for the different reaction products (CO₂, HCl, Cl₂, C₂Cl₄, CCl₄ and CHCl₃). Both the activity and the selectivity for total combustion are higher than other catalysts suggested in the literature for this process (especially Pd and Pt).The main organic by-products are CCl₄ and CHCl₃, whereas in all the other catalysts tested in the literature, tetrachloroethene is the main organic by-product. This fact suggests that the mechanism of the combustion reaction, involving a double-bond scission, is essentially specific for this catalyst.Kinetic data was fit to a pseudo-first order kinetic expression, providing fairly good fit.     

Effect of the addition of Cr and Nb on the microstructure and electrochemical corrosion of heat-treatable Al-Zn-Mg alloys

The effect of the addition of Cr and Nb on the microstructure and the electrochemical corrosion of the weldable, high-strength and stress corrosion cracking (SCC) resistant Al-5%Zn–1.67%Mg–0.23%Cu alloy (H) has been studied. Combined additions of the alloying elements, J (with Nb), L (with Cr) and O (with Cr and Nb) and different heat treatments, ST (cold-rolled), A (annealed), F (quenched), B (quenched and aged) and C (quenched in two steps and aged), to obtain different microstructures and hardness have been performed. To correlate the electrochemical corrosion with the microstructure of the specimens, corrosion potential (E _cor) measurements in different chloride solutions were performed and optical microscopy, SEM, TEM and EDX were applied. In chloride solutions containing dissolved O₂ or H₂O₂, the present alloys were polarized up to the pitting attack. It was shown that theE _cor measurements were very sensitive to the alloy composition and heat treatment, increasing in the order H < J < L < O < Al (for a given heat treatment) and F < A ST < B < C (for a given alloy). The MgZn₂ precipitates of the annealed (A) and cold-rolled (ST) specimens were dissolved in chloride solutions containing oxidizing agents and pitting attack was shown to develop in the cavities where the precipitates were present. In the specimens B and C, the compositions of the precipitate free zones was found to be equal to that of the matrix solid solution and preferential intergranular attack was not evident, this being in agreement with their SCC resistance. The addition of Cr and Nb increased the pitting corrosion resistance. The effects of Cr and Nb were additive, that of Cr being predominant, either, in theE _cor shift or in the increase in the pitting corrosion resistance.     

Learning to rank academic experts in the DBLP dataset

Expert finding is an information retrieval task that is concerned with the search for the most knowledgeable people with respect to a specific topic, and the search is based on documents that describe people's activities. The task involves taking a user query as input and returning a list of people who are sorted by their level of expertise with respect to the user query. Despite recent interest in the area, the current state‐of‐the‐art techniques lack in principled approaches for optimally combining different sources of evidence. This article proposes two frameworks for combining multiple estimators of expertise. These estimators are derived from textual contents, from graph‐structure of the citation patterns for the community of experts and from profile information about the experts. More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combining all of the estimators of expertise. Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state‐of‐the‐art data fusion techniques were also explored for the rank aggregation framework. Experiments that were performed on a dataset of academic publications from the Computer Science domain attest the adequacy of the proposed approaches.     

Modelling and analysis of non-cooperative peer-assisted VoD streaming in managed networks

The growing popularity of the Video on Demand service in the Internet Protocol Television environments and the demand for increased quality of the offered videos are becoming a serious threat for the service providers because the high amounts of video traffic are causing congestion in the delivery networks. One of the most acceptable approaches to solve this issue is the peer-assisted streaming, where the peers participate in the streaming process in order to alleviate the load on the streaming servers and in the core of the network. Although the reliability of the Peer-to-Peer service is considerably improved in the managed networks because of the control that the operators have over the clients’ Set-Top Boxes, the failures of the peers still cannot be completely eliminated. The operator can take advantage of the streaming and storage resources of the clients and use them for peer-assisted streaming only while they are watching a video, but not after they finish the streaming session because they may turn off their receiving devices until the next session. In this chapter, we address the issue of the failures of the peers in such environments and their influence on the traffic requested from the servers for providing uninterrupted video experience. For that purpose, we propose a precise mathematical tool for modelling a peer-assisted system for Video on Demand streaming in managed networks with non-cooperative peers, which may decide not to share their resources while they are not active. This tool calculates the performance of the system taking into consideration large variety of system parameters, including the failure probability and the time the peers spend until they decide to turn on the STB and join the network. As the results from the simulations verify the correctness of the mathematical model, we use it to analyse how the failures of the peers are affecting the system’s performance for different system parameters.