pinecone/core-2020-05-10-deduplication huggingface dataset:
Generalising Random Forest Parameter Optimisation to Include Stability
  and Cost

Random forests are among the most popular classification and regression
methods used in industrial applications. To be effective, the parameters of
random forests must be carefully tuned. This is usually done by choosing values
that minimize the prediction error on a held out dataset. We argue that error
reduction is only one of several metrics that must be considered when
optimizing random forest parameters for commercial applications. We propose a
novel metric that captures the stability of random forests predictions, which
we argue is key for scenarios that require successive predictions. We motivate
the need for multi-criteria optimization by showing that in practical
applications, simply choosing the parameters that lead to the lowest error can
introduce unnecessary costs and produce predictions that are not stable across
independent runs. To optimize this multi-criteria trade-off, we present a new
framework that efficiently finds a principled balance between these three
considerations using Bayesian optimisation. The pitfalls of optimising forest
parameters purely for error reduction are demonstrated using two publicly
available real world datasets. We show that our framework leads to parameter
settings that are markedly different from the values discovered by error
reduction metrics.Comment: To appear in ECML-PKDD 201
The Girgentana Goat Breed: A Zootechnical Overview on Genetics, Nutrition and Dairy Production Aspects

In recent years, there has been a great interest in recovering and preserving\ud
local livestock breeds. An interesting situation is represented by the\ud
Girgentana goat, an ancient local breed reared in Sicily. Over recent years, this\ud
breed has become almost extinct, in part as a consequence of the marked decrease\ud
in fresh goat milk consumption. On the basis of these considerations, several studies\ud
on its genetic structure and management aspects have been conducted in order to\ud
protect the Girgentana goat from the risk of extinction and recover its genetic and\ud
economic value. In this context, information on genetics, nutrition and dairy production\ud
aspects may have a crucial role in the improvement and management of the\ud
breed. Thus, this chapter describes some points of these applications through recent\ud
investigations on this goat breed
Spear operators between Banach spaces

The aim of this manuscript is to study \emph{spear operators}: bounded linear
operators $G$ between Banach spaces $X$ and $Y$ satisfying that for every other
bounded linear operator $T:X\longrightarrow Y$ there exists a modulus-one
scalar $\omega$ such that $$ \|G + \omega\,T\|=1+ \|T\|. $$ To this end, we
introduce two related properties, one weaker called the alternative Daugavet
property (if rank-one operators $T$ satisfy the requirements), and one stronger
called lushness, and we develop a complete theory about the relations between
these three properties. To do this, the concepts of spear vector and spear set
play an important role. Further, we provide with many examples among classical
spaces, being one of them the lushness of the Fourier transform on $L_1$. We
also study the relation of these properties with the Radon-Nikod\'ym property,
with Asplund spaces, with the duality, and we provide some stability results.
Further, we present some isometric and isomorphic consequences of these
properties as, for instance, that $\ell_1$ is contained in the dual of the
domain of every real operator with infinite rank and the alternative Daugavet
property, and that these three concepts behave badly with smoothness and
rotundity. Finally, we study Lipschitz spear operators (that is, those
Lipschitz operators satisfying the Lipschitz version of the equation above) and
prove that (linear) lush operators are Lipschitz spear operators.Comment: 114 pages, 9 chapter
Cut Finite Element Methods for Linear Elasticity Problems

We formulate a cut finite element method for linear elasticity based on
higher order elements on a fixed background mesh. Key to the method is a
stabilization term which provides control of the jumps in the derivatives of
the finite element functions across faces in the vicinity of the boundary. We
then develop the basic theoretical results including error estimates and
estimates of the condition number of the mass and stiffness matrices. We apply
the method to the standard displacement problem, the frequency response
problem, and the eigenvalue problem. We present several numerical examples
including studies of thin bending dominated structures relevant for engineering
applications. Finally, we develop a cut finite element method for fibre
reinforced materials where the fibres are modeled as a superposition of a truss
and a Euler-Bernoulli beam. The beam model leads to a fourth order problem
which we discretize using the restriction of the bulk finite element space to
the fibre together with a continuous/discontinuous finite element formulation.
Here the bulk material stabilizes the problem and it is not necessary to add
additional stabilization terms
Operational Research  IO2017, Valença, Portugal, June 28-30

This proceedings book presents selected contributions from the XVIII Congress of APDIO (the Portuguese Association of Operational Research) held in Valença on June 28–30, 2017. Prepared by leading Portuguese and international researchers in the field of operations research, it covers a wide range of complex real-world applications of operations research methods using recent theoretical techniques, in order to narrow the gap between academic research and practical applications. Of particular interest are the applications of, nonlinear and mixed-integer programming, data envelopment analysis, clustering techniques, hybrid heuristics, supply chain management, and lot sizing and job scheduling problems. In most chapters, the problems, methods and methodologies described are complemented by supporting figures, tables and algorithms.
The XVIII Congress of APDIO marked the 18th installment of the regular biannual meetings of APDIO – the Portuguese Association of Operational Research. The meetings bring together researchers, scholars and practitioners, as well as MSc and PhD students, working in the field of operations research to present and discuss their latest works. The main theme of the latest meeting was Operational Research Pro Bono. Given the breadth of topics covered, the book offers a valuable resource for all researchers, students and practitioners interested in the latest trends in this field.info:eu-repo/semantics/publishedVersio
Banking risk as an epidemiological model: an optimal control approach

The process of contagiousness spread modelling is well-known in epidemiology.
However, the application of spread modelling to banking market is quite recent.
In this work, we present a system of ordinary differential equations,
simulating data from the largest European banks. Then, an optimal control
problem is formulated in order to study the impact of a possible measure of the
Central Bank in the economy. The proposed approach enables qualitative
specifications of contagion in banking obtainment and an adequate analysis and
prognosis within the financial sector development and macroeconomic as a whole.
We show that our model describes well the reality of the largest European
banks. Simulations were done using MATLAB and BOCOP optimal control solver, and
the main results are taken for three distinct scenarios.Comment: This is a preprint of a paper whose final and definite form is in
  'Operational Research', Springer Proceedings in Mathematics & Statistics,
  available at [http://www.springer.com/series/10533]. Paper Submitted
  23/March/17; Revised 29/May/17; Accepted 11/July/201
Scheduling of nonconforming devices: the case of a company in the automotive sector

This article presents a project developed in a company’s quality department aiming at scheduling the nonconforming devices analysis’ process. The company faced a problem of low compliance with pre-established time requests, resulting in large fines paid to its customers of the automotive sector. In order to overcome this problem, scheduling tools were developed and tested, with the goal of minimizing the number of tardy tasks in identical parallel machines. The simulation of different scheduling rules allowed confirmation that the current prioritization rule is not the most effective one. Preliminary simulations were carried out using Lekin software [18], showing that other criteria promote better results. The use of a newly developed algorithm, combining two different criteria, resulted in a reduction of tardy tasks, thus decreasing tardiness fines paid to customers. Despite the preliminary status of present results, it is possible to foresee some improvements in the analysis process performance, by using decision making support tools based on scheduling algorithms. This way, a significant improvement on the number of analysis which fulfills the defined pre-requirements will be achieved.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio
A penalty approach for solving nonsmooth and nonconvex MINLP problems

This paper presents a penalty approach for globally solving nonsmooth and nonconvex mixed-integer nonlinear programming (MINLP) problems. Both integrality constraints and general nonlinear constraints are handled separately by hyperbolic tangent penalty functions. Proximity from an iterate to a feasible promising solution is enforced by an oracle penalty term. The numerical experiments show that the proposed oracle-based penalty approach is effective in reaching the solutions of the MINLP problems and is competitive when compared with other strategies.FCT - Fundação para a Ciência e a Tecnologia.The authors would like to thank two anonymous referees for their valuable comments and suggestions to improve the paper. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e a Tecnologia within the projects UID/CEC/00319/2013 and UID/MAT/00013/ 2013.info:eu-repo/semantics/publishedVersio
Automated Adaptation and Assessment in Serious Games: a Portable Tool for Supporting Learning

We introduce the Adaptation and Assessment (TwoA) component, an open-source tool for serious games, capable of adjusting game difficulty to player skill level. Technically, TwoA is compliant with the RAGE (Horizon 2020) game component architecture, which offers seamless portability to a variety of popular game development platforms.
Conceptually, TwoA uses a modified version of the Computer Adaptive Practice algorithm. Our version offers two improvements over the original algorithm. First, the TwoA improves balancing of player's motivation and game challenge. Second, TwoA reduces the selection bias that may arise for items of similar difficulty by adopting a fuzzy selection rule. These improvements are validated using multi-agent simulations.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187.  This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains
Mapping Inventors’ Networks to Trace Knowledge Flows Among EU Regions

Recent literature on technological changes has highlighted the role of knowledge recombination in innovation. Evidence suggests that the production of scientific and technological knowledge is becoming an increasingly collective phenomenon. Thus, in rapidly developing industries, it is almost inevitable to develop inter-organizational collaborations to identify new opportunities for new technologies.\ud
\ud
The aim of this chapter was to explore the innovative activities and networks in European regions (EU 27 plus Norway and Switzerland) from 1980 to 2010. Specifically, we analysed the most innovative sectors: environmental (green), biotechnology (biotech), laser and optic technology and nanotechnology (nanotech). This longitudinal study relies on European Patent Office (EPO) patents and inventors’ data by year and region, as provided by OECD-Regpat database. Our main findings emphasize the rise of co-inventions in intra-regional and inter-regional inventive networks, the concentration of innovations in central regions and peripheral regions’ reliance on external knowledge flows to compensate for their technological weaknesses
Generating cost-aware covering arrays for free

Software systems generally have a large number of configurable options interacting with each other. Such systems are more likely to be prone to errors, crashes, and faulty executions that are usually caused by option interactions. To avoid such errors, testing all possible configurations during the development phase is usually not feasible, since the number of all possible configurations is exponential in the order of number of options. A t-way covering array (CA) is a 2-dimensional combinatorial object that helps to efficiently cover all t-length option interactions of the system under test. Generating a CA with a small number of configurations is important to shorten the testing phase. However, the testing cost (e.g. the testing time) may differ from one configuration to another. Currently, most sequential tools can generate optimum CAs in terms of number of configurations, but they are not cost-aware, i.e., they cannot handle the varying costs of configurations. In this work, we implement a parallel, cost-aware CA-generation tool based on a sequential tool, Jenny, to generate lower-cost CAs faster. Experimental results show that our cost-aware CA construction approach can generate 32% and 21% lower cost CAs on average for t = 2 and t = 3, respectively, compared to state-of-the-art CA-generation tools. Moreover, the cost-awareness comes for free, i.e., we speed up our algorithm by leveraging parallel computation. The cost models and cost reduction techniques we propose could also be adapted for other existing CA generation tools
Networked Markets and Relational Contracts

Empirical studies of commercial relationships between firms reveal that (i) suppliers encounter situations in which they can gain in the short run by acting opportunistically for example, delivering a lower quality than promised after being paid; and (ii) good conduct is sustained not exclusively by formal contracts but through informal relationships and the expectation of future business. In such relationships, the need to offer each supplier a large enough share of future business to deter cheating limits the number of supply relationships each buyer can sustain. The market thus becomes networked, with trade restricted to durable relationships. We propose and analyze a simple dynamic model to examine the structure of such overlapping relational contracts in equilibrium. Due to exogenous stochastic shocks, suppliers are not always able to make good on their promises even if they wish to, and so links are constantly dissolving and new ones are forming to take their place. This induces a Markov process on networks. We study how the stationary distribution over networks depends on the parameters most importantly, the value of trade and the probability of shocks. When the rate at which shocks hit increases, as might happen during an economic downturn, maintaining incentive compatibility with suppliers requires promising each more future business and this necessitates maintaining fewer relationships with suppliers. This results in a destruction of social capital, and even if the rate of shocks later returns to its former level, it can take considerable time for social capital to be rebuilt because of search frictions. This creates a novel way for shocks to be persistent. It also suggests new connections between the theory of relational contracting, on the one hand, and the macroeconomic analysis of recessions, on the other
Computing Approximate Pure Nash Equilibria in Shapley Value Weighted
  Congestion Games

We study the computation of approximate pure Nash equilibria in Shapley value
(SV) weighted congestion games, introduced in [19]. This class of games
considers weighted congestion games in which Shapley values are used as an
alternative (to proportional shares) for distributing the total cost of each
resource among its users. We focus on the interesting subclass of such games
with polynomial resource cost functions and present an algorithm that computes
approximate pure Nash equilibria with a polynomial number of strategy updates.
Since computing a single strategy update is hard, we apply sampling techniques
which allow us to achieve polynomial running time. The algorithm builds on the
algorithmic ideas of [7], however, to the best of our knowledge, this is the
first algorithmic result on computation of approximate equilibria using other
than proportional shares as player costs in this setting. We present a novel
relation that approximates the Shapley value of a player by her proportional
share and vice versa. As side results, we upper bound the approximate price of
anarchy of such games and significantly improve the best known factor for
computing approximate pure Nash equilibria in weighted congestion games of [7].Comment: The final publication is available at Springer via
  http://dx.doi.org/10.1007/978-3-319-71924-5_1
Towards Implementing Gamification in MOOCs

Gamification is well known as a design strategy used to generate a change in users’ behaviour, such as motivation. However, while in recent years interest in it has been growing, empirical evidence on the effects that the application of game elements can generate on users’ behaviour is still lacking.
We present the results of a study as a step towards designing gamification with better understanding of the possible effects that each game element could generate on end users. By involving three groups of experts: game designers, learning scientists and specialists in technology-enhanced learning (TEL), we assessed a selected number of 21 game design patterns in relation to the effects these could generate on learning performance, goal achievement and engagement of learners if implemented in a Massive Online Open Course
(MOOC). Based on quantitative and qualitative data collected, 9 game elements have been selected to be further investigated
gMOOCs – Flow and Persuasion to Gamify MOOCs

Gamification has gained great interest recently in several fields.
However, while the literature reports that a gamification design relying on
external motivation only can lead users to cognitive dissonance, most
gamification approaches use points, badges and leaderboards as dominant game
elements. We present our developed testable predictions with the aim of
investigating additional motivational theories (flow and persuasion) to argue for
a deeper integration of gamification and the learning content at hand. Relying
on expert selected game elements, we consequently derive design
considerations to create gMOOCs, gamified massive online open courses,
designed according to the principles of flow and persuasion. Our findings are
the basis of our experiment and a contribution to the development of a new
theoretical design for gamificatio
Neurons as an Information-theoretic Engine

We show that dynamical gain modulation of neurons' stimulus response is
described as an information-theoretic cycle that generates entropy associated
with the stimulus-related activity from entropy produced by the modulation. To
articulate this theory, we describe stimulus-evoked activity of a neural
population based on the maximum entropy principle with constraints on two types
of overlapping activities, one that is controlled by stimulus conditions and
the other, termed internal activity, that is regulated internally in an
organism. We demonstrate that modulation of the internal activity realises gain
control of stimulus response, and controls stimulus information. A cycle of
neural dynamics is then introduced to model information processing by the
neurons during which the stimulus information is dynamically enhanced by the
internal gain-modulation mechanism. Based on the conservation law for entropy
production, we demonstrate that the cycle generates entropy ascribed to the
stimulus-related activity using entropy supplied by the internal mechanism,
analogously to a heat engine that produces work from heat. We provide an
efficient cycle that achieves the highest entropic efficiency to retain the
stimulus information. The theory allows us to quantify efficiency of the
internal computation and its theoretical limit.Comment: 16 pages, 4 figures; corrected four typos in the original submissio
Science for Loss and Damage. Findings and Propositions

The debate on “Loss and Damage” (L&D) has gained traction over the last few years. Supported by growing scientific evidence of anthropogenic climate change amplifying frequency, intensity and duration of climate-related hazards as well as observed increases in climate-related impacts and risks in many regions, the “Warsaw International Mechanism for Loss and Damage” was established in 2013 and further supported through the Paris Agreement in 2015. Despite advances, the debate currently is broad, diffuse and somewhat confusing, while concepts, methods and tools, as well as directions for policy remain vague and often contested. This book, a joint effort of the Loss and Damage Network—a partnership effort by scientists and practitioners from around the globe—provides evidence-based insight into the L&D discourse by highlighting state-of-the-art research conducted across multiple disciplines, by showcasing applications in practice and by providing insight into policy contexts and salient policy options. This introductory chapter summarises key findings of the twenty-two book chapters in terms of five propositions. These propositions, each building on relevant findings linked to forward-looking suggestions for research, policy and practice, reflect the architecture of the book, whose sections proceed from setting the stage to critical issues, followed by a section on methods and tools, to chapters that provide geographic perspectives, and finally to a section that identifies potential policy options. The propositions comprise (1) Risk management can be an effective entry point for aligning perspectives and debates, if framed comprehensively, coupled with climate justice considerations and linked to established risk management and adaptation practice; (2) Attribution science is advancing rapidly and fundamental to informing actions to minimise, avert, and address losses and damages; (3) Climate change research, in addition to identifying physical/hard limits to adaptation, needs to more systematically examine soft limits to adaptation, for which we find some evidence across several geographies globally; (4) Climate risk insurance mechanisms can serve the prevention and cure aspects emphasised in the L&D debate but solidarity and accountability aspects need further attention, for which we find tentative indication in applications around the world; (5) Policy deliberations may need to overcome the perception that L&D constitutes a win-lose negotiation “game” by developing a more inclusive narrative that highlights collective ambition for tackling risks, mutual benefits and the role of transformation