Assigning Refugees to Landlords in Sweden: Stable Maximum Matchings

This version: August 15, 2017 (original version: December 7, 2016)

Design principles for maximizing photovoltage in metal-oxide-protected water-splitting photoanodes

Metal oxide protection layers for photoanodes may enable the development of large-scale solar fuel and solar chemical synthesis, but the poor photovoltages often reported so far will severely limit their performance. Here we report a novel observation of photovoltage loss associated with a charge extraction barrier imposed by the protection layer, and, by eliminating it, achieve photovoltages as high as 630mV, the maximum reported so far for water-splitting silicon photoanodes. The loss mechanism is systematically probed in metal-insulator-semiconductor Schottky junction cells compared to buried junction p(+) n cells, revealing the need to maintain a characteristic hole density at the semiconductor/insulator interface. A leaky-capacitor model related to the dielectric properties of the protective oxide explains this loss, achieving excellent agreement with the data. From these findings, we formulate design principles for simultaneous optimization of built-in field, interface quality, and hole extraction to maximize the photovoltage of oxide-protected water-splitting anodes.

Engineering interfacial silicon dioxide for improved metal-insulator-semiconductor silicon photoanode water splitting performance

Silicon photoanodes protected by atomic layer deposited (ALD) TiO2 show promise as components of water splitting devices that may enable the large-scale production of solar fuels and chemicals. Minimizing the resistance of the oxide corrosion protection layer is essential for fabricating efficient devices with good fill factor. Recent literature reports have shown that the interfacial SiO2 layer, interposed between the protective ALD-TiO2 and the Si anode, acts as a tunnel oxide that limits hole conduction from the photoabsorbing substrate to the surface oxygen evolution catalyst. Herein, we report a significant reduction of bilayer resistance, achieved by forming stable, ultrathin (<1.3 nm) SiO2 layers, allowing fabrication of water splitting photoanodes with hole conductances near the maximum achievable with the given catalyst and Si substrate. Three methods for controlling the SiO2 interlayer thickness on the Si(100) surface for ALD-TiO2 protected anodes were employed: (1) TiO2 deposition directly on an HF-etched Si(100) surface, (2) TiO2 deposition after SiO2 atomic layer deposition on an HF-etched Si(100) surface, and (3) oxygen scavenging, post-TiO2 deposition to decompose the SiO2 layer using a Ti overlayer. Each of these methods provides a progressively superior means of reliably thinning the interfacial SiO2 layer, enabling the fabrication of efficient and stable water oxidation silicon anodes.

Assigning Refugees to Landlords in Sweden: Stable Maximum Matchings

The member states of the European Union received 1.2 million first time asylum applications in 2015 (a doubling compared to 2014). Even if asylum will be granted for many of the refugees that made the journey to Europe, several obstacles for successful integration remain. This paper focuses on one of these obstacles, namely the problem of finding housing for refugees once they have been granted asylum. In particular, the focus is restricted to the situation in Sweden during 2015–2016 and it is demonstrated that market design can play an important role in a partial solution to the problem. More specifically, because almost all accommodation options are exhausted in Sweden, the paper investigates a matching system, closely related to the system adopted by the European NGO “Refugees Welcome”, and proposes an easy-to-implement algorithm that finds a stable maximum matching. Such matching guarantees that housing is provided to a maximum number of refugees and that no refugee prefers some landlord to their current match when, at the same time, that specific landlord prefers that refugee to his current match.

A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.

The educational problem that MOOCs could solve: professional development for teachers of disadvantaged students

The demographics of massive open online course (MOOC) analytics show that the great majority of learners are highly qualified professionals, and not, as originally envisaged, the global community of disadvantaged learners who have no access to good higher education. MOOC pedagogy fits well with the combination of instruction and peer community learning found in most professional development. A UNESCO study therefore set out to test the efficacy of an experimental course for teachers who need but do not receive high-quality continuing professional development, as a way of exploiting what MOOCs can do indirectly to serve disadvantaged students. The course was based on case studies around the world of information and communication technology (ICT) in primary education and was carried out to contribute to the UNESCO “Education For All” goal. It used a co-learning approach to engage the primary teaching community in exploring ways of using ICT in primary education. Course analytics, forums and participant surveys demonstrated that it worked well. The paper concludes by arguing that this technology has the power to tackle the large-scale educational problem of developing the primary-level teachers needed to meet the goal of universal education.

The three-dimensional single-bin-size bin packing problem: combining metaheuristic and machine learning approaches

The Three-Dimensional Single-Bin-Size Bin Packing Problem is one of the most studied problem in the Cutting & Packing category. From a strictly mathematical point of view, it consists of packing a finite set of strongly heterogeneous “small” boxes, called items, into a finite set of identical “large” rectangles, called bins, minimizing the unused volume and requiring that the items are packed without overlapping. The great interest is mainly due to the number of real-world applications in which it arises, such as pallet and container loading, cutting objects out of a piece of material and packaging design. Depending on these real-world applications, more objective functions and more practical constraints could be needed. After a brief discussion about the real-world applications of the problem and a exhaustive literature review, the design of a two-stage algorithm to solve the aforementioned problem is presented. The algorithm must be able to provide the spatial coordinates of the placed boxes vertices and also the optimal boxes input sequence, while guaranteeing geometric, stability, fragility constraints and a reduced computational time. Due to NP-hard complexity of this type of combinatorial problems, a fusion of metaheuristic and machine learning techniques is adopted. In particular, a hybrid genetic algorithm coupled with a feedforward neural network is used. In the first stage, a rich dataset is created starting from a set of real input instances provided by an industrial company and the feedforward neural network is trained on it. After its training, given a new input instance, the hybrid genetic algorithm is able to run using the neural network output as input parameter vector, providing as output the optimal solution. The effectiveness of the proposed works is confirmed via several experimental tests.

Mechanical design and hybrid control strategies for overconstrained cable-driven parallel robots

Cable-driven parallel robots offer significant advantages in terms of workspace dimensions and payload capability. They are attractive for many industrial tasks to be performed on a large scale, such as handling and manufacturing, without a substantial increase in costs and mechanical complexity with respect to a small-scale application. However, since cables can only sustain tensile stresses, cable tensions must be kept within positive limits during the end-effector motion. This problem can be managed by overconstraining the end-effector and controlling cable tensions. Tension control is typically achieved by mounting a load sensor on all cables, and using specific control algorithms to avoid cable slackness or breakage while the end-effector is controlled in a desired position. These algorithms require multiple cascade control loops and they can be complex and computationally demanding. To simplify the control of overconstrained cable-driven parallel robots, this Thesis proposes suitable mechanical design and hybrid control strategies. It is shown how a convenient design of the cable guidance system allows kinematic modeling to be simplified, without introducing geometric approximations. This guidance system employs swiveling pulleys equipped with position and tension sensors and provides a parallelogram arrangement of cables. Furthermore, a hybrid force/position control in the robot joint space is adopted. According to this strategy, a particular set of cables is chosen to be tension-controlled, whereas the other cables are length-controlled. The force-controlled cables are selected based on the computation of a novel index called force-distribution sensitivity to cable-tension errors. This index aims to evaluate the maximum expected cable-tension error in the length-controlled cables if a unit tension error is committed in the force-controlled cables. In practice, the computation of the force-distribution sensitivity allows determining which cables are best to be force-controlled, to ensure the lowest error in the overall force distribution when a hybrid force/position joint-space strategy is used.

Numerical modelling of rock masses interacting with dams: the case of Ridracoli

A three-dimensional Direct Finite Element procedure is here presented which takes into account most of the factors affecting the interaction problem of the dam-water-foundation system, whilst keeping the computational cost at a reasonable level by introducing some simplified hypotheses. A truncated domain is defined, and the dynamic behaviour of the system is treated as a wave-scattering problem where the presence of the dam perturbs an original free-field system. The rock foundation truncated boundaries are enclosed by a set of free-field one-dimensional and two-dimensional systems which transmit the effective forces to the main model and apply adsorbing viscous boundaries to ensure radiation damping. The water domain is treated as an added mass moving with the dam. A strategy is proposed to keep the viscous dampers at the boundaries unloaded during the initial phases of analysis, when the static loads are initialised, and thus avoid spurious displacements. A focus is given to the nonlinear behaviour of the rock foundation, with concentrated plasticity along the natural discontinuities of the rock mass, immersed in an otherwise linear elastic medium with Rayleigh damping. The entire procedure is implemented in the commercial software Abaqus®, whose base code is enriched with specific user subroutines when needed. All the extra coding is attached to the Thesis and tested against analytical results and simple examples. Possible rock wedge instabilities induced by intense ground motion, which are not easily investigated within a comprehensive model of the dam-water-foundation system, are treated separately with a simplified decoupled dynamic approach derived from the classical Newmark method, integrated with FE calculation of dam thrust on the wedges during the earthquake. Both the described approaches are applied to the case study of the Ridracoli arch-gravity dam (Italy) in order to investigate its seismic response to the Maximum Credible Earthquake (MCE) in a full reservoir condition.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part B)

In recent years, global supply chains have increasingly suffered from reliability issues due to various external and difficult to-manage events. The following paper aims to build an integrated approach for the design of a Supply Chain under the risk of disruption and demand fluctuation. The study is divided in two parts: a mathematical optimization model, to identify the optimal design and assignments customer-facility, and a discrete-events simulation of the resulting network. The first one describes a model in which plant location decisions are influenced by variables such as distance to customers, investments needed to open plants and centralization phenomena that help contain the risk of demand variability (Risk Pooling). The entire model has been built with a proactive approach to manage the risk of disruptions assigning to each customer two types of open facilities: one that will serve it under normal conditions and a back-up facility, which comes into operation when the main facility has failed. The study is conducted on a relatively small number of instances due to the computational complexity, a matheuristic approach can be found in part A of the paper to evaluate the problem with a larger set of players. Once the network is built, a discrete events Supply Chain simulation (SCS) has been implemented to analyze the stock flow within the facilities warehouses, the actual impact of disruptions and the role of the back-up facilities which suffer a great stress on their inventory due to a large increase in demand caused by the disruptions. Therefore, simulation follows a reactive approach, in which customers are redistributed among facilities according to the interruptions that may occur in the system and to the assignments deriving from the design model. Lastly, the most important results of the study will be reported, analyzing the role of lead time in a reactive approach for the occurrence of disruptions and comparing the two models in terms of costs.

An Integrated Framework To Improve The Concept Of Resource Specialisation.

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.

Biased Random-key Genetic Algorithms For The Winner Determination Problem In Combinatorial Auctions.

Abstract In this paper, we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer-linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.

Metamorfose planar via métodos Level Set e Particle Level Set para a reconstrução de superfícies tridimensionais

Evolving interfaces were initially focused on solutions to scientific problems in Fluid Dynamics. With the advent of the more robust modeling provided by Level Set method, their original boundaries of applicability were extended. Specifically to the Geometric Modeling area, works published until then, relating Level Set to tridimensional surface reconstruction, centered themselves on reconstruction from a data cloud dispersed in space; the approach based on parallel planar slices transversal to the object to be reconstructed is still incipient. Based on this fact, the present work proposes to analyse the feasibility of Level Set to tridimensional reconstruction, offering a methodology that simultaneously integrates the proved efficient ideas already published about such approximation and the proposals to process the inherent limitations of the method not satisfactorily treated yet, in particular the excessive smoothing of fine characteristics of contours evolving under Level Set. In relation to this, the application of the variant Particle Level Set is suggested as a solution, for its intrinsic proved capability to preserve mass of dynamic fronts. At the end, synthetic and real data sets are used to evaluate the presented tridimensional surface reconstruction methodology qualitatively.

Metamorfose planar via métodos Level Set e Particle Level Set para a reconstrução de superfícies tridimensionais

Evolving interfaces were initially focused on solutions to scientific problems in Fluid Dynamics. With the advent of the more robust modeling provided by Level Set method, their original boundaries of applicability were extended. Specifically to the Geometric Modeling area, works published until then, relating Level Set to tridimensional surface reconstruction, centered themselves on reconstruction from a data cloud dispersed in space; the approach based on parallel planar slices transversal to the object to be reconstructed is still incipient. Based on this fact, the present work proposes to analyse the feasibility of Level Set to tridimensional reconstruction, offering a methodology that simultaneously integrates the proved efficient ideas already published about such approximation and the proposals to process the inherent limitations of the method not satisfactorily treated yet, in particular the excessive smoothing of fine characteristics of contours evolving under Level Set. In relation to this, the application of the variant Particle Level Set is suggested as a solution, for its intrinsic proved capability to preserve mass of dynamic fronts. At the end, synthetic and real data sets are used to evaluate the presented tridimensional surface reconstruction methodology qualitatively.

Respostas agudas de parâmetros biomecânicos à utilização de diferentes tamanhos de palmar no nado crawl

Universidade Estadual de Campinas . Faculdade de Educação Física