pinecone/core-2020-05-10-deduplication huggingface dataset:
Intelligence as inference or forcing Occam on the world

We propose to perform the optimization task of Universal Artificial Intelligence (UAI) through learning a reference machine on which good programs are short. Further, we also acknowledge that the choice of reference machine that the UAI objective is based on is arbitrary and, therefore, we learn a suitable machine for the environment we are in. This is based on viewing Occam’s razor as an imperative instead of as a proposition about the world. Since this principle cannot be true for all reference machines, we need to find a machine that makes the principle true. We both want good policies and the environment to have short implementations on the machine. Such a machine is learnt iteratively through a procedure that generalizes the principle underlying the Expectation-Maximization algorithm
Minimal-model-guided approaches to solving polynomial constraints and extensions

In this paper we present new methods for deciding the satisfiability of formulas involving integer polynomial constraints. In previous work we proposed to solve SMT(NIA) problems by reducing them to SMT(LIA): non-linear monomials are linearized by abstracting them with fresh variables and by performing case splitting on integer variables with finite domain. When variables do not have finite domains, artificial ones can be introduced by imposing a lower and an upper bound, and made iteratively larger until a solution is found (or the procedure times out). For the approach to be practical, unsatisfiable cores are used to guide which domains have to be relaxed (i.e., enlarged) from one iteration to the following one. However, it is not clear then how large they have to be made, which is critical. Here we propose to guide the domain relaxation step by analyzing minimal models produced by the SMT(LIA) solver. Namely, we consider two different cost functions: the number of violated artificial domain bounds, and the distance with respect to the artificial domains. We compare these approaches with other techniques on benchmarks coming from constraint-based program analysis and show the potential of the method. Finally, we describe how one of these minimal-model-guided techniques can be smoothly adapted to deal with the extension Max-SMT of SMT(NIA) and then applied to program termination proving.Peer ReviewedPostprint (author’s final draft
Susceptibility and Vulnerability to Landslides—Case Study: Basin of River Bengalas—City of Nova Friburgo—Brazil

Landslides have frequently occurred in last years, due to the disorderly grownth of the cities and the occupation of risk areas by the poor population, causing social, environmental and economic impacts. Urban areas in expansion move to geologically unstable areas and topographically inclined, such as the Basin of River Bengalas, located in the city of Nova Friburgo, mountainous region of the State of Rio de Janeiro, Brazil. This article aims to present the model developed and used to evaluate the susceptibility and vulnerability of the Basin of River Bengalas to landslides, which in January 2011, with the occurrence of heavy rains, caused landslides that impacted in the death of 429 people in city of Nova Friburgo. For the case study, several investigations have been made related to the areas of the basin, such as slope, soil conditions, lithology, land use and cover, vertical curvature, horizontal curvature, and precipitation data. With this study it was possible to understand how the natural and anthropics elements of the basin are related to the local dynamics of the disasters regarding to their interferences in the induction of landslides; evaluate the effectiveness of the guidelines of the Plano Diretor Participativo do Município de Nova Friburgo regarding the landslides; identify the susceptible and vulnerable basin areas to landslides and calculate the rates of susceptibility and vulnerability to landslides from new calculation model proposed
Role of Climate and Land Use Variations on the Occurrence of Damaging Hydrogeological Events in Apulia (Southern Italy)

The aim of this work is to present a methodology, based on the use of correlation, cross-correlation and trend analysis, which analyses monthly climatic data (rainfall, wet days, rainfall intensity, and temperature) from 1877 to 2008, in order to characterise the climate variations, particularly in terms of rainfall, and the effects on the occurrence trend of Damaging Hydrogeological Events (DHEs), floods and landslides. The proposed methodology consists of four phases. The first two phases concern the data collection and the creation of the climate and DHE databases, the third phase of work involves the analysis of data previously collected and the last part, not yet finished, is relative to the study of land use variations. This meth-odology was applied to a southern Italian region (Apulia) frequently hit by flood and landslide events. Despite the decreasing trend of rainfall and rainfall intensity and the increasing trend of temperatures and wet days, there is an increasing trend of DHE occurrence, which might related to the negative effect of anthropogenic activities in landslide-prone areas. The preliminary analysis on land use variations confirmed the increase of urban areas in the Apulia region from the 1959 to the 2006
A short history of engineering geology and geophysics at the British Geological Survey

Engineering geology in the British Geological Survey (BGS) began, in a formal sense, with the creation of the Engineering Geology Unit in 1967. Virtually since its inception, despite changing research priorities and economic drivers, the survey and research work carried out by BGS engineering geologists can be conveniently divided into four broad research areas: engineering geological mapping and urban geoscience, geotechnical properties of soils and rocks, engineering geophysics and geohazards. Since the late 1960s engineering geologists have undertaken innovative research initiatives and continue to play an important role in ensuring the delivery of BGS researc
A hybrid algorithm to improve the accuracy of support vector machines on skewed data-sets

Over the past few years, has been shown that generalization power of Support Vector Machines (SVM) falls dramatically on imbalanced data-sets. In this paper, we propose a new method to improve accuracy of SVM on imbalanced data-sets. To get this outcome, firstly, we used undersampling and SVM to obtain the initial SVs and a sketch of the hyperplane. These support vectors help to generate new artificial instances, which will take part as the initial population of a genetic algorithm. The genetic algorithm improves the population in artificial instances from one generation to another and eliminates instances that produce noise in the hyperplane. Finally, the generated and evolved data were included in the original data-set for minimizing the imbalance and improving the generalization ability of the SVM on skewed data-sets
A Novel 2-Stage Combining Classifier Model with Stacking and Genetic Algorithm based Feature Selection

This paper introduces a novel 2-stage classification system with stacking and genetic algorithm (GA) based feature selection. Specifically, Level1 data is first generated by stacking on the original data (called Level0 data) with base classifiers. Level1data is then classified by a second classifier (denoted by C) with feature selection using GA. The advantage of applying GA on Level1 data is that it has lower dimension and is more uniformity than Level0 data. We conduct experiments on both 18 UCI data files and CLEF2009 medical image database to demonstrate superior performance of our model in comparison with several popular combining algorithms.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Combining Multi Classifiers based on A Genetic Algorithm: A Gaussian Mixture Model framework

Combining outputs from different classifiers to achieve high accuracy in classification task is one of the most active research areas in ensemble method. Although many state-of-art approaches have been introduced, no one method performs the best on all data sources. With the aim of introducing an effective classification model, we propose a Gaussian Mixture Model (GMM) based method that combines outputs of base classifiers (called meta-data or Level1 data) resulted from Stacking Algorithm. We further apply Genetic Algorithm (GA) to that data as a feature selection strategy to explore an optimal subset of Level1 data in which our GMM-based approach can achieve high accuracy. Experiments on 21 UCI Machine Learning Repository data files and CLEF2009 medical image database demonstrate the advantage of our framework compared with other well-known combining algorithms such as Decision Template, Multiple Response Linear Regression (MLR), SCANN and fixed combining rules as well as GMM-based approaches on original data.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Transitional justice in times of 'exponential change': constructing normative frameworks fit for purpose - the importance of general international law

In the attempt to reformulate transitional justice to include broader rule of law approaches, there are substantial challenges in ensuring institutional, normative, and policy coherence. Though the rhetoric of the UN policy ‘pillars’ of human rights, development, and peace and security is uncontroversial and commendable, achieving it through tangential legal regimes is problematic. With at least three forms of incoherence at work: within a regime, between legal regimes, and between regimes and the UN’s policy goals, ensuring effective responses requires resort to tools of general international law. The chapter comes to three conclusions: first, that as achieving transitional justice requires reliance upon divergent areas of international law, general issues of normative ordering and fragmentation must be confronted. Secondly, normative incoherence can be mitigated through a range of general techniques, including the development of unified substantive (‘primary’) rules across regimes – using the principle of prevention here as the example – and recourse to treaty interpretation as a secondary tool to maximise rule-linkage. Thirdly, there are a number of meta-, or overriding, principles which might assist with developing an overarching coherence, including the concept of sustainable development and various principles of human rights. Thus, transitional justice as both a policy and legal objective should not eschew, and indeed benefits from, precepts and techniques of the general legal order
Kinematic design of a reconfigurable deployable canopy

A reconfigurable and deployable mechanism is proposed for a canopy which can also be used as a tent or a semi-open structure. The proposed single degree-of-freedom mechanism has four as-sembly modes. The conditions for deployment and reconfiguration of the mechanism are derived. These conditions impose three equality and two inequality constraints on the 11 design parameters of the mechanism. A virtual model of the mechanism is constructed in Excel for design and simulation purposes. A computational case study is presented
Function generation synthesis with a 2-DoF overconstrained double-spherical 7R mechanism using the method of decomposition and least squares approximation

This study addresses the approximate function generation synthesis with an overconstrained two degrees-of-freedom double spherical 7R mechanism using least squares approximation with equal spacing of the design points on the input domain. The 7R mechanism is a constructed by combining a spherical 5R mechanism with a spherical 4R mechanism with distant centers and a common moving link and then removing the common link. This construction allows the analysis and synthesis of the re-sulting single-loop mechanism by decomposing it into fictitious 5R and 4R loops. The two inputs to the mechanism are provided in the 5R loop and the output is in the 4R loop. The fictitious output of the 5R loop is an input to the 4R loop this intermediate variable is used to also decompose the function to be generated. This decomposition provides the designer extra freedom in synthesis and enables de-creasing the error of approximation. A case study is presented at the end of the study where the 7R de-sign is compared with an equivalent spherical 5R mechanism; hence the advantage of the 7R mecha-nism is demonstrated
On the experimental intradiscal pressure measurement techniques : a review

Series : Mechanisms and machine science, ISSN 2211-0984, vol. 24The intradiscal pressure has been essential for prevent the spinal complaints by forming a basis for clinical advice to promote the correct sitting postures. As a consequence, it is evident the need of an accurate method for measure the intradiscal pressure, to better understand the disc response to hydorstatic pressure fluctuations. Numerous reviews regarding disc mechanics are available, including intradiscal pressure benchmarks; however, an analysis on the techniques of intradiscal pressure measurement is needed. Therefore, this review will remain focused on the methodologies adopted for measure the intradiscal pressure in several conditions: for different daily activities, under external loads and for values where occurs annulus fibrosus disruption. The importance of the intradiscal pressure on disc function will be discussed as well as the some guidelines for design new measurement techniques will be defined
An advanced 3D multi-body system model for the human lumbar spine

Series : Mechanisms and machine science, ISSN 2211-0984, vol. 24A novel 3D multi-body system model of the human lumbar spine is presented, allowing the dynamic study of the all set but also to access mechanical demands, characteristics and performance under work of the individual intervertebral discs. An advanced FEM analysis was used for the most precise characterization of the disc 6DOF mechanical behavior, in order to build up a tool capable of predicting and assist in the design of disc recovery strategies – namely in the development of replace-ment materials for the degenerated disc nucleus – as well as in the analysis of variations in the me-chanical properties (disorders) at disc level or kinematic structure (e.g. interbody fusion, pedicle fixa-tion, etc.), and its influence in the overall spine dynamics and at motion segments individual level. Preliminary results of the model, at different levels of its development, are presented
Biomechanical experimental data curation : an example for main lumbar spine ligaments characterization for a MBS spine model

Series : Mechanisms and machine science, ISSN 2211-0984, vol. 24This work overviews an extensive analysis in the context of mechanical characterization of human biomaterials, carried out over a broad set of published experimental data. Focused on main lumbar spine ligaments, several test procedures are exhaustively analyzed, in order to identify possible causes for divergences that have been found in some results. Moreover, guidelines are proposed for da-ta filtering and selection. The main objective of the task was to retrieve trustworthy inputs to a hybrid Finite Element Analysis / Multibody System dynamic simulation model of the human intervertebral disc, which can be used on the prediction of nucleus prosthetics working performance
On generalized dual Euler angles

This paper first explores the generalization of Euler angles to the case in which the rotation axes are not necessarily members of an orthonormal triad, and presents a concise solution to their computation that relies on the calculation of standard Euler angles. Then, this generalization is taken one step further by introducing translations, that is, by defining generalized Euler angles about screw axes using a variation of the principle of transference that avoids the use of dual numbers. As an example, the obtained formulation is applied to solve the inverse kinematics of a 3C manipulator.Peer ReviewedPostprint (author’s final draft
Machine and mechanism design at UMinho: research-teaching interaction

Publicado em: "New trends in mechanism and machine science: from fundamentals to industrial applications. ISBN 978-3-319-09410-6. Series: Mechanisms and machine science, vol. 24, ISSN 2211-0984"The Multiweave project involved the design of a prototype machine with several mecha-nisms, namely gear trains and various conjugate cams with oscillating roller followers. For this design phase the research team integrated postgraduate student work. In order to evaluate the quality of the manufactured cam profiles as well as the accuracy of the follower’s displacement, an experimental work has been designed. This study, which was carried out within a final year Mechanical Engineering student’s group project, was of great importance in the development of the prototype machine to pro-duce multidirectional woven fabrics, which was the main objective of the Multiweave project. The whole set-up is presented with the experimental details and the results are analysed and discussed. This measurement system is based on a laser triangulation sensor Micro-Epsilon ILD 1302-50 to measure with no contact and high resolution. The obtained results were compared with the expected theoretical values and it could be concluded that, in general, the experimental results adjust very well to the theo-retical ones. However it was possible to conclude about the existence of some differences due to clear-ances in joints, geometric differences in the kinematic chain and manufacturing defects on the follower in terms of irregularities and surface roughness as well as some manufacturing imperfections of the cam surface
Ground plane detection using an rgb-d sensor

Ground plane detection is essential for successful navigation of vision based mobile robots. We introduce a very simple but robust ground plane detection method based on depth information obtained using anRGB-Depth sensor. We present two different variations of the method: the simplest one is robust in setups where the sensor pitch angle is fixed and has no roll, whereas the second one can handle changes in pitch and roll angles. Our comparisons show that our approach performs better than the vertical disparity approach. It produces accurate ground plane-obstacle segmentation for difficult scenes, which include many obstacles, different floor surfaces, stairs, and narrow corridors.Publisher's VersionAuthor Post Prin
On the equivalence of modes of convergence for log-concave measures

An important theme in recent work in asymptotic geometric analysis is that
many classical implications between different types of geometric or functional
inequalities can be reversed in the presence of convexity assumptions. In this
note, we explore the extent to which different notions of distance between
probability measures are comparable for log-concave distributions. Our results
imply that weak convergence of isotropic log-concave distributions is
equivalent to convergence in total variation, and is further equivalent to
convergence in relative entropy when the limit measure is Gaussian.Comment: v3: Minor tweak in exposition. To appear in GAFA seminar note
Bounding the norm of a log-concave vector via thin-shell estimates

Chaining techniques show that if X is an isotropic log-concave random vector
in R^n and Gamma is a standard Gaussian vector then E |X| < C n^{1/4} E |Gamma|
for any norm |*|, where C is a universal constant. Using a completely different
argument we establish a similar inequality relying on the thin-shell constant
sigma_n = sup ((var|X|^){1/2} ; X isotropic and log-concave on R^n).
  In particular, we show that if the thin-shell conjecture sigma_n = O(1)
holds, then n^{1/4} can be replaced by log (n) in the inequality.
  As a consequence, we obtain certain bounds for the mean-width, the dual
mean-width and the isotropic constant of an isotropic convex body.
  In particular, we give an alternative proof of the fact that a positive
answer to the thin-shell conjecture implies a positive answer to the slicing
problem, up to a logarithmic factor.Comment: preliminary version, 13 page
Analysing the M&A Preparedness Building Approach

One of the complex and dynamic changes on the organisation level is Mergers and Acquisitions (M&As). M&As have been practiced since several decades for growth and expansion purposes. Recent developments in the frequency of M&As has drawn attention from researchers resulting in findings that more than half of the deals fails to achieve the aimed synergies. Solution to this problem could be to build preparedness to allow organisations to prepare for future or announced mergers in a way that enable faster pre-merger planning and smoother post-merger integration (PMI).  In this article we will analyse M&A Preparedness building using a retrospective case study to a) demonstrate that the success of such strategic changes depends on several essential and largely overlooked factors, and b) outline a possible approach of building preparedness for M&As.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Using the Alliance Form for Operation and Maintenance of Privatized Infrastructures

A significant number of privatizations utilized to operate and maintain critical networked infrastructures have failed to meet contractual expectations and the expectations of the community. The author carried out empirical research ex-ploring four urban water systems. This research revealed that of the four forms of privatization the alliance form was particularly suited to the stewardship of an ur-ban water system. The question then is whether these findings from urban water can be generalised to O&M of infrastructure generally. The answer is increasingly important as governments seek financial sustainability through reapplying the contestability strategy and outsource and privatise further services and activities. This paper first examines the issues encountered with O & M privatisations. Second the findings as to the stewardship achieved by the four case study water systems are unpacked with particular focus upon the alliance form. Third the key variables which were found to have distinct causal links to the stewardship-like behaviour of the private participants in the Alliance case study are described. Fourth the variables which may be crucial to the successful application of the alliance form to the broader range of infrastructures are separated out. Fifth this paper then sets the path for research into these crucial features of the alliance form
Making optimal and justifiable asset maintenance decisions

Maintenance decisions for large-scale asset systems are often beyond an asset manager's capacity to handle. The presence of a number of possibly conflicting decision criteria, the large number of possible maintenance policies, and the reality of budget constraints often produce complex problems, where the underlying trade-offs are not apparent to the asset manager. This paper presents the decision support tool "JOB" (Justification and Optimisation of Budgets), which has been designed to help asset managers of large systems assess, select, interpret and optimise the effects of their maintenance policies in the presence of limited budgets. This decision support capability is realized through an efficient, scalable backtracking- based algorithm for the optimisation of maintenance policies, while enabling the user to view a number of solutions near this optimum and explore tradeoffs with other decision criteria. To assist the asset manager in selecting between various policies, JOB also provides the capability of Multiple Criteria Decision Making. In this paper, the JOB tool is presented and its applicability for the maintenance of a complex power plant system