pinecone/core-2020-05-10-deduplication huggingface dataset:
Aspects that contribute to the success of personalized Web applications

Serie : Advances in intelligent systems and computing, ISSN 2194-5357, vol. 206Personalized applications exhibit features adjusted to the preferences or needs of users and can provide benefits related to customer relationship or related to the efficiency of organizational work. This article presents a conceptual model that can be viewed as a contribution to the body of knowledge of Information Systems and Technologies professionals with responsibilities in the adoption, and development of personalized Web applications. These contributions include: a conceptual model that combines and articulates aspects that contribute to the success and to the quality of personalized information system (this model combines design features, facets that contribute to the quality and metrics that can be used to evaluate the performance of organizational work supported by personalized information systems). This set of aspects combines a synthesis of information so far scattered in the literature with proposals and recommendations with empirical knowledge based on an empirical study
Standardization of processes applying CMMI best practices

Capability Maturity Model Integration (CMMI) is a set of practices that can be applied in companies in order to improve processes. The goal of this work was to understand the barriers in implementing CMMI and improve processes following the model. The study was conducted in a company in the North of Portugal, following three steps: (1) diagnosing the company (2) opinion gathering through questionnaires and (3) reimplementation of CMMI. The analysis of the questionnaires indicated that implementing CMMI is problematical due to bureaucracy and lack of detailed protocols. Based on the difficulties encountered we developed a detailed documentation with standard processes where the employer has a more prominent role in controlling the processes. The adapted CMMI was then re-introduced in the same company. Finally, linking perceptions and results from the reimplementation, we consider fundamental a good use of CMMI to ensure efficient production
Open source technologies involved in constructing a web-based football information system

The current information systems and match analysis software associated to professional football output a huge amount of statistics. Many football professionals are particularly interested in real time information about
the tactical plan occurring during the match, and the relations between that
information and what was prepared in the training sessions. It is fundamental to
have on the bench, and on-the-fly, the most relevant information each time they have to take a decision. In this paper, we present a set of open source technologies involved in building a multi-platform web based integrated football information system, supported in three main modules: user interfaces,
databases, and the tactical plan detection and classification. We show that the selected technologies are suitable for those modules, allowing field occurrences to trigger meaningful information
Leveraging knowledge from different communities using ontologies

The purpose of this paper is to provide research based understanding of leveraging knowledge and managing knowledge within and across several communities using the poverty domain as a case study. We hypothesize that leveraging knowledge with a good taxonomy and a good integration process are good approaches to organize and share knowledge. Problems appear when a group of people in different communities share data and collaborate using different perceptions, different concepts, different terms (terminologies), and different semantics to represent the same reality. In this paper we present an approach to solve this problem. We will generate a common set of terms based on the terms of several different storage devices, used by different communities, in order to make data retrieval independent of the different perceptions and terminologies used by those communities. We use ontologies to represent the particular knowledge of each community and discuss the use of mapping and integration techniques to find correspondences between the concepts used in those ontologies
Open source software documentation mining for quality assessment

Besides source code, the fundamental source of information about Open Source Software lies in documentation, and other non source code files, like README, INSTALL, or HowTo files, commonly available in the software ecosystem. These documents, written in natural language, provide valuable information during the software development stage, but also in future maintenance and evolution tasks. DMOSS is a toolkit designed to systematically assess the quality of non source code text found in software packages. The toolkit handles a package as an attribute tree, and performs several tree traverse algorithms through a set of plugins, specialized in retrieving specific metrics from text, gathering information about the software. These metrics are later used to infer knowledge about the software, and composed together to build reports that assess the quality of specific features of the software. This paper discusses the motivations for this work, continues with a description of the toolkit implementation and design goals. Follows an example of its usage to process a software package, and the produced report. Finally some final remarks and trends for future work are presented.Fundação para a Ciência e a Tecnologia (FCT
A multidimensional model for monitoring cloud services

The complexity of monitoring cloud environments and the lack of standards so far urge for a careful analysis, systematizing and understanding of key points involved when assessing the services provided. In this context, this paper proposes a layered model for Cloud Services monitoring, identifying the multiple dimensions of monitoring, while combining the perspectives of service providers and customers. This process involves the identification of relevant parameters and metrics for each monitoring dimension, focusing on monitoring of resources, quality of service, security and service contracts. Taking a stratified view of the problem, this study contributes to achieve a clearer and more efficient approach to cloud services monitoring.Fundação para a Ciência e a Tecnologia (FCT
Emerging organic contaminants in groundwater\ud

Emerging organic contaminants (ECs) are compounds now being found in groundwater from agricultural, urban sources that were previously not detectable, or thought to be significant. ECs include pesticides and degradates, pharmaceuticals, industrial compounds, personal care products, fragrances, water treatment by-products, flame retardants and surfactants, as well as ‘life-style’ compounds such as caffeine and nicotine. ECs may have adverse effects on aquatic ecosystems and human health.  Frequently detected ECs include the anti-epileptic drug carbamazepine, the antibiotic sulfamethoxazole, the anti-inflammatories ibuprofen and diclofenac, and caffeine, as well as pesticide degradates. This means there will be challenges in the future in order to address these ECs and to minimise their impact on drinking water and ecosystems. In the coming decades, more ECs are likely to have environmental standards defined, and therefore a better understanding of environmental behaviour remains a priority
Multiple-cue-based visual object contour tracking with incremental learning

This paper proposes a visual object contour tracking algorithm using a multi-cue fusion particle filter. A novel contour evolution energy is proposed which integrates an incrementally learnt model of object appearance with a parametric snake model. This energy function is combined with a mixed cascade particle filter tracking algorithm which fuses multiple observation models for object contour tracking. Bending energy due to contour evolution is modelled using a thin plate spline (TPS). Multiple order graph matching is performed between contours in consecutive frames. Both of the above are taken as observation models for contour deformation; these models are fused efficiently using a mixed cascade sampling process. The dynamic model used in our tracking method is further improved by the use of optical flow. Experiments on real videos show that our approach provides high performance object contour tracking
Implementing QVT-R bidirectional model transformations using alloy

QVT Relations (QVT-R) is the standard language proposed by the OMG to specify bidirectional model transformations. Unfortunately, in part due to ambiguities and omissions in the original semantics, acceptance and development of effective tool support has been slow. Recently, the checking semantics of QVT-R has been clarified and formalized. In this paper we propose a QVT-R tool that complies to such semantics. Unlike any other existing tool, it also supports meta-models enriched with OCL constraints (thus avoiding returning ill-formed models), and proposes an alternative enforcement semantics that works according to the simple and predictable “principle of least change”. The implementation is based on an embedding of both QVT-R transformations and UML class diagrams (annotated with OCL) in Alloy, a lightweight formal specification language with support for automatic model finding via SAT solving.Fundação para a Ciência e a Tecnologi
Scale Filtered Euclidean Medial Axis

International audienceWe propose an Euclidean medial axis filtering method which generates subsets of Euclidean medial axis were filtering rate is controlled by one parameter. The method is inspired by Miklos', Giesen's and Pauly's scale axis method which preserves important features of an input object from shape understanding point of view even if they are at different scales. Our method overcomes the most important drawback of scale axis: scale axis is not, in general, a subset of Euclidean medial axis. It is even not necessarily a subset of the original shape. The method and its properties are presented in 2D space but it can be easily extended to any dimension. Experimental verification and comparison with a few previously introduced methods are also included
A Parallel Thinning Algorithm for Grayscale Images

International audienceGrayscale skeletonization offers an interesting alternative to traditional skeletonization following a binarization. It is well known that parallel algorithms for skeletonization outperform sequential ones in terms of quality of results, yet no general and well defined framework has been proposed until now for parallel grayscale thinning. We introduce in this paper a parallel thinning algorithm for grayscale images, and prove its topological soundness based on properties of the critical kernels framework. The algorithm and its proof, given here in the 2D case, are also valid in 3D. Some applications are sketched in conclusion
Computing Quantiles in Markov Reward Models

Probabilistic model checking mainly concentrates on techniques for reasoning about the probabilities of certain path properties or expected values of certain random variables. For the quantitative system analysis, however, there is also another type of interesting performance measure, namely quantiles. A typical quantile query takes as input a lower probability bound p and a reachability property. The task is then to compute the minimal reward bound r such that with probability at least p the target set will be reached before the accumulated reward exceeds r. Quantiles are well-known from mathematical statistics, but to the best of our knowledge they have not been addressed by the model checking community so far. \ud
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In this paper, we study the complexity of quantile queries for until properties in discrete-time finite-state Markov decision processes with non-negative rewards on states. We show that qualitative quantile queries can be evaluated in polynomial time and present an exponential algorithm for the evaluation of quantitative quantile queries. For the special case of Markov chains, we show that quantitative quantile queries can be evaluated in time polynomial in the size of the chain and the maximum reward
Tour Suggestion for Outdoor Activities

The present article introduces the outdoor activity tour suggestion problem (OATSP). This problem involves finding a closed path of maximal attractiveness in a transportation network graph, given a target path length and tolerance. Total path attractiveness is evaluated as the sum of the average arc attractiveness and the sum of the vertex prizes in the path. This problem definition takes its rise in the design of an interactive web application, which suggests closed paths for several outdoor activity routing modi, such as mountain biking. Both path length and starting point are specified by the user. The inclusion of POIs of some given types enrich the suggested outdoor activity experience.

A fast method for the generation of heuristic solutions to the OATSP is presented. It is based on spatial filtering, the evaluation of triangles in a simplified search space and shortest path calculation. 
It generates valuable suggestions in the context of a web application. It is a promising method to generate candidate paths used by any local search algorithm, which further optimizes the solution.status: publishe
Preference Articulation by Means of the R2 Indicator

International audienceIn multi-objective optimization, set-based performance indicators have become the state of the art for assessing the quality of Pareto front approximations. As a consequence, they are also more and more used within the design of multi-objective optimization algorithms. The R2 and the Hypervolume (HV) indicator represent two popular examples. In order to understand the behavior and the approximations preferred by these indicators and algorithms, a comprehensive knowledge of the indicator's properties is required. Whereas this knowledge is available for the HV, we presented a first approach in this direction for the R2 indicator just recently. In this paper, we build upon this knowledge and enhance the considerations with respect to the integration of preferences into the R2 indicator. More specifically, we analyze the effect of the reference point, the domain of the weights, and the distribution of weight vectors on the optimization of μ solutions with respect to the R2 indicator. By means of theoretical findings and empirical evidence, we show the potentials of these three possibilities using the optimal distribution of μ solutions for exemplary setups
Force-based Cooperative Search Directions in Evolutionary Multi-objective Optimization

International audienceIn order to approximate the set of Pareto optimal solutions, several evolutionary multi-objective optimization (EMO) algorithms transfer the multi-objective problem into several independent single-objective ones by means of scalarizing functions. The choice of the scalarizing functions' underlying search directions, however, is typically problem-dependent and therefore difficult if no information about the problem characteristics are known before the search process. The goal of this paper is to present new ideas of how these search directions can be computed \emph{adaptively} during the search process in a \emph{cooperative} manner. Based on the idea of Newton's law of universal gravitation, solutions attract and repel each other \emph{in the objective space}. Several force-based EMO algorithms are proposed and compared experimentally on general bi-objective $\rho$MNK landscapes with different objective correlations. It turns out that the new approach is easy to implement, fast, and competitive with respect to a $(\mu+\lambda)$-SMS-EMOA variant, in particular if the objectives show strong positive or negative correlations
Visualising high-dimensional Pareto relationships in two-dimensional scatterplots

Copyright © 2013 Springer-Verlag Berlin Heidelberg. The final publication is available at link.springer.comBook title: Evolutionary Multi-Criterion Optimization7th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013), Sheffield, UK, March 19-22, 2013In this paper two novel methods for projecting high dimensional data into two dimensions for visualisation are introduced, which aim to limit the loss of dominance and Pareto shell relationships between solutions to multi-objective optimisation problems. It has already been shown that, in general, it is impossible to completely preserve the dominance relationship when mapping from a higher to a lower dimension – however, approaches that attempt this projection with minimal loss of dominance information are useful for a number of reasons. (1) They may represent the data to the user of a multi-objective optimisation problem in an intuitive fashion, (2) they may help provide insights into the relationships between solutions which are not immediately apparent through other visualisation methods, and (3) they may offer a useful visual medium for interactive optimisation. We are concerned here with examining (1) and (2), and developing relatively rapid methods to achieve visualisations, rather than generating an entirely new search/optimisation problem which has to be solved to achieve the visualisation– which may prove infeasible in an interactive environment for real time use. Results are presented on randomly generated data, and the search population of an optimiser as it progresses. Structural insights into the evolution of a set-based optimiser that can be derived from this visualisation are also discussed
Elasticity and Viscoelasticity of Open Cellular Material: Micromechanical Approach

Cellular materials are characterized by remarkable mechanical properties with light weight. Such materials are used in various applications mainly in energy absorption. Their microstructure are described by two ma- jor families : open and close cell foams. This paper deals with the prediction of the macroscopic behavior of open cell foams in elasticity and viscoelasticity as function of their microstructure. Firstly, we use a micromechanical model based on Cosserat homogenization framework. Secondly, Finite Element (FE) computations are performed on a unit cell subjected to periodic boundary conditions. The results are confronted to various models developped in litter- ature. Finaly, the linear viscoelastic behavior is deduced from elastic results by taking advantage of correspondence principle
Curbing resource consumption using team-based feedback : paper printing in a longitudinal case study

This paper details a team-based feedback approach for reducing resource consumption. The approach uses paper printing within office environments as a case study. It communicates the print usage of each participant’s team rather than the participant’s individual print usage. Feedback is provided weekly via emails and contains normative information, along with eco-metrics and team-based comparative statistics. The approach was empirically evaluated to study the effectiveness of the feedback method. The experiment comprised of 16 people belonging to 4 teams with data on their print usage gathered over 58 weeks, using the first 30-35 weeks as a baseline. The study showed a significant reduction in individual printing with an average of 28%. The experiment confirms the underlying hypothesis that participants are persuaded to reduce their print usage in order to improve the overall printing behaviour of their teams. The research provides clear pathways for future research to qualitatively investigate our findings
Social Stairs: taking the Piano Staircase towards long-term behavioral change

Abstract. This paper addresses the development of Social Stairs, an intelli-gent musical staircase to change peoples behavior in the long-term to take the stairs in favor of the elevator. Through designing with the Experiential Design Landscape (EDL) method, a design opportunity was found that social engage-ment encouraged people to take the stairs at work in favor of the elevator. To encourage this social behavior, people who involved each other and worked to-gether whilst using the Social Stairs were treated with more diverse orchestral chimes that echoed up the stairwell. In this paper we reflect on the differences between the persuasive system of the well-known Piano Staircase and the So-cial Stairs. We report on the deployment of the Social Stairs for a period of three weeks in the public space within the university community and identify opportunities for triggering intrinsic motivation, social engagement and how to keep people involved in the long-term
A customisable dashboard display for environmental performance visualisations

We conducted an exploratory study of a mobile energy monitoring tool: The Dashboard. Our point of departure from prior work was the emphasis of end-user customisation and social sharing. Applying extensive feedback, we deployed the Dashboard in real-world conditions to socially linked research participants for a period of five weeks. Participants were encouraged to devise, construct, place, and view various data feeds. The aim of our study was to test the assumption that participants, having control over their Dashboard configuration, would engage, and remain engaged, with their energy feedback throughout the trial.\ud
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Our research points to a set of design issues surrounding the adoption and continued use of such tools. A novel finding of our study is the impact of social links between participants and their continued engagement with the Dashboard. Our results also illustrate the emergence of energy-voyeurism, a form of social energy monitoring by peers
Particulate Fillers in Thermoplastics

The characteristics of particulate filled thermoplastics are determined by four factors: component properties, composition, structure and interfacial interactions. The most important filler characteristics are particle size, size distribution, specific surface area and particle shape, while the main matrix property is stiffness. Segregation, aggregation and the orientation of anisotropic particles determine structure. Interfacial interactions lead to the formation of a stiff interphase considerably influencing properties. Interactions are changed by surface modification, which must be always system specific and selected according to its goal. Under the effect of external load inhomogeneous stress distribution develops around heterogeneities, which initiate local micromechanical deformation processes determining the macroscopic properties of the composites
Generating map sketches for strategy games

How can a human and an algorithm productively collaborate on generating game content? In this paper, we try to answer this question in the context of\ud
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generating balanced and interesting low-resolution sketches for game levels. We\ud
introduce six important criteria for successful strategy game maps, and present\ud
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map sketches optimized for one or more of these criteria via a constrained evolutionary algorithm. The sketch-based map representation and the computationally\ud
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lightweight evaluation methods are geared towards the integration of the evolutionary algorithm within a mixed-initiative tool, allowing for the co-creation of\ud
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game content by a human and an artificial designer.peer-reviewe
Identifying Market Price Levels Using Differential Evolution

Evolutionary data mining is used in this paper to investigate the concept of support and resistance levels in financial markets. Specifically, Differential Evolution is used to learn support/resistance levels from price data. The presence of these levels is then tested in out-of-sample data. Our results from a set of experiments covering five years worth of daily data across nine different US markets show that there is statistical evidence for price levels in certain markets, and that Differential Evolution can uncover them