pinecone/core-2020-05-10-deduplication huggingface dataset:
Channel coding for joint colour and depth segmentation

Segmentation is an important preprocessing step in many applications.\ud
Compared to colour segmentation, fusion of colour and depth\ud
greatly improves the segmentation result. Such a fusion is easy to do by\ud
stacking measurements in di erent value dimensions, but there are better\ud
ways. In this paper we perform fusion using the channel representation,\ud
and demonstrate how a state-of-the-art segmentation algorithm can be\ud
modi ed to use channel values as inputs. We evaluate segmentation results\ud
on data collected using the Microsoft Kinect peripheral for Xbox\ud
360, using the superparamagnetic clustering algorithm. Our experiments\ud
show that depth gradients are more useful than depth values for segmentation,\ud
and that channel coding both colour and depth gradients makes\ud
tuned parameter settings generalise better to novel images.Peer ReviewedPostprint (updated version
Indoor Calibration using Segment Chains

International audienceIn this paper, we present a new method for line segments matching for indoor reconstruction. Instead of matching individual seg- ments via a descriptor like most methods do, we match segment chains that have a distinctive topology using a dynamic programing formulation. Our method relies solely on the geometric layout of the segment chain and not on photometric or color profiles. Our tests showed that the presented method is robust and manages to produce calibration information even under a drastic change of viewpoint
Single channel music sound separation based on spectrogram decomposition and note classification

Separating multiple music sources from a single channel mixture is a challenging problem. We present a new approach to this problem based on non-negative matrix factorization (NMF) and note classification, assuming that the instruments used to play the sound signals are known a priori. The spectrogram of the mixture signal is first decomposed into building components (musical notes) using an NMF algorithm. The Mel frequency cepstrum coefficients (MFCCs) of both the decomposed components and the signals in the training dataset are extracted. The mean squared errors (MSEs) between the MFCC feature space of the decomposed music component and those of the training signals are used as the similarity measures for the decomposed music notes. The notes are then labelled to the corresponding type of instruments by the K nearest neighbors (K-NN) classification algorithm based on the MSEs. Finally, the source signals are reconstructed from the classified notes and the weighting matrices obtained from the NMF algorithm. Simulations are provided to show the performance of the proposed system. © 2011 Springer-Verlag Berlin Heidelberg
Moving towards adaptive search in digital libraries

Search applications have become very popular over the last two decades, one of the main drivers being the advent of the Web. Nevertheless, searching on the Web is very different to searching on smaller, often more structured collections such as digital libraries, local Web sites, and intranets. One way of helping the searcher locating the right information for a specific information need in such a collection is by providing well-structured domain knowledge to assist query modification and navigation. There are two main challenges which we will both address in this chapter: acquiring the domain knowledge and adapting it automatically to the specific interests of the user community. We will outline how in digital libraries a domain model can automatically be acquired using search engine query logs and how it can be continuously updated using methods resembling ant colony behaviour. © 2011 Springer-Verlag
Filtering of FTLE for Visualizing Spatial Separation in Unsteady 3D Flow

In many cases, feature detection for flow visualization is structured
in two phases: first candidate identification, and then filtering.
With this paper, we propose to use the directional information contained
in the finite-time Lyapunov exponents (FTLE) computation,
in order to filter the FTLE field. In this way we focus on those
separation structures that delineate flow compartments which develop
into different spatial locations, as compared to those that
separate parallel flows of different speed. We provide a discussion
of the underlying theory and our related considerations. We derive
a new filtering scheme and demonstrate its effect in the context of
several selected fluid flow cases, especially in comparison with unfiltered
FTLE visualization. Since previous work has provided insight
with respect to the studied flow patterns, we are able to provide a discussion of the resulting visible separation structures
Prometheus Framework for Fuzzy Information Retrieval in Semantic Spaces

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data (such as location data, ontology-backed search queries, in- and outdoor conditions) the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion
The Proposal of the System That Recommends e-Learning Courses Matching the Learning Styles of the Learners

In providing e-learning, it is desirable to build an environment that is suitable to the student’s learning style. In this study, using the questionnaire to measure the student’s preferences for asynchronous learning and the use of ICT in learning that has been develoed by authors, the relationship between the learning preferences of a student that have been measured before and after the course and his or her adaptability to the course is explored. The result of multiple regression analyses, excluding the changes in learning preferences that may occur duirng the course, shows that a student’s learning adaptability can be estimated to some extent based on his/her learning preference measured before the course starts. Based on this result, we propose a system to recommend e-learning courses that are suitable to a student before the student takes the courses
Exploring synergetic effects of dimensionality reduction and resampling tools on hyperspectral imagery data classification

The present paper addresses the problem of the classification of hyperspectral images with multiple imbalanced classes and very high dimensionality. Class imbalance is handled by resampling the data set, whereas PCA and a supervised filter are applied to reduce the number of spectral bands. This is a preliminary study that pursues to investigate the benefits of combining several techniques to tackle the imbalance and the high dimensionality problems, and also to evaluate the order of application that leads to the best classification performance. Experimental results demonstrate the significance of using together these two preprocessing tools to improve the performance of hyperspectral imagery classification. Although it seems that the most effective order corresponds to first a resampling strategy and then a feature (or extraction) selection algorithm, this is a question that still needs a much more thorough investigation in the futureThis work has partially been supported by the Spanish Ministry of Education and Science under grants CSD2007–00018, AYA2008–05965–0596 and TIN2009–14205, the Fundació Caixa Castelló–Bancaixa under grant P1–1B2009–04, and the Generalitat Valenciana under grant PROMETEO/2010/02
Walking Rover Trafﬁcability - Presenting a Comprehensive Analysis and Prediction Tool

Although walking rovers perform well in rocky terrain, their performance over sands and other deformable materials has not been well studied. A better understanding of walking rover terramechanics will be essential if they are to be actually deployed on a space mission. This paper presents a comprehensive walking rover terramechanics model incorporating slip and sinkage dependencies. In addition to quantifying the leg / soil forces, the superior trafficability potential of a walking rover in deformable terrain is demonstrated, and a control approach is described which can reduce the risk inherent in traversing soils with unknown physical parameters. This work enhances the state of the art of legged rover trafficability and highlights some potential benefits from deploying micro-legged rovers for future surface exploration missions
Enhancing self-similar patterns by asymmetric artificial potential functions in partially connected swarms

The control of mobile robotic agents is required to be highly reliable. Artificial potential function (APF) methods have previously been assessed in the literature for providing stable and verifiable control, whilst maintaining a high degree of nonlinearity. Further, these methods can, in theory, be characterised by a full analytic treatment. Many examples are available in the literature of the employment of these methods for controlling large ensembles of agents that evolve into minimum energy configurations corresponding in many cases to regular lattices [1-2]. Although regular lattices can present naturally centric symmetry and self-similarity characteristics, more complex formations can also be achieved by several other means. In [3] the equilibrium configuration undergoes bifurcation by changing a parameter belonging to the part of artificial potential that couples the agents to the reference frame. In this work it is shown how the formation shape produced can be controlled in two further ways, resulting in more articulated patterns. Specifically the control applied is to alter the symmetry of interactions amongst agents, and/or by selectively rewiring interagent connections. In the first case, the network of connections remains the same, and may be fully connected
The interaction between vortices and a biomimetic flexible fin

The fluid-structure interaction of flexible bodies in steady and unsteady flow is a key area of interest for the development of underwater vehicles. In the design of marine vehicles the flow can often be seen as an obstacle to overcome, whilst in nature a fish interacts with the flow and is capable of achieving a high level of efficiency. Therefore by understanding how fish - or flexible bodies - interact with the flow we may be able to achieve a better level of co-operation between our vehicles and their environment, potentially attaining a better efficiency in design
Can the Arrow of Time be understood from Quantum Cosmology?

I address the question whether the origin of the observed arrow of time can
be derived from quantum cosmology. After a general discussion of entropy in
cosmology and some numerical estimates, I give a brief introduction into
quantum geometrodynamics and argue that this may provide a sufficient framework
for studying this question. I then show that a natural boundary condition of
low initial entropy can be imposed on the universal wave function. The arrow of
time is then correlated with the size of the Universe and emerges from an
increasing amount of decoherence due to entanglement with unobserved degrees of
freedom. Remarks are also made concerning the arrow of time in multiverse
pictures and scenarios motivated by dark energy.Comment: 14 pages, to appear in "The Arrow of Time", ed. by L.
  Mersini-Houghton and R. Vaa
Energy Games in Multiweighted Automata

International audienceEnergy games have recently attracted a lot of attention. These are games played on finite weighted automata and concern the existence of infinite runs subject to boundary constraints on the accumulated weight, allowing e.g. only for behaviours where a resource is always available (nonnegative accumulated weight), yet does not exceed a given maximum capacity. We extend energy games to a multiweighted and parameterized setting, allowing us to model systems with multiple quantitative aspects. We present reductions between Petri nets and multiweighted automata and among different types of multiweighted automata and identify new complexity and (un)decidability results for both one and two-player games. We also investigate the tractability of an extension of multiweighted energy games in the setting of timed automata
CBR with Commonsense Reasoning and Structure Mapping: An Application to Mediation

Mediation is an important method in dispute resolution. We implement a case based reasoning approach to mediation integrating analogical and commonsense reasoning components that allow an artificial mediation agent to satisfy requirements expected from a human mediator, in particular: utilizing experience with cases in different domains; and structurally transforming the set of issues for a better solution. We utilize a case structure based on ontologies reflecting the perceptions of the parties in dispute. The analogical reasoning component, employing the Structure Mapping Theory from psychology, provides a flexibility to respond innovatively in unusual circumstances, in contrast with conventional approaches confined into specialized problem domains. We aim to build a mediation case base incorporating real world instances ranging from interpersonal or intergroup disputes to international conflicts.This work was supported by a JAE-Predoc fellowship\ud
from CSIC, and the research grants: 2009-SGR-1434 from the Generalitat de\ud
Catalunya, CSD2007-0022 from MICINN, and Next-CBR TIN2009-13692-C03-\ud
01 from MICINN.Peer reviewe
Discovery and integration of Web 2.0 content into geospatial information infrastructures: a use case in wild fire monitoring

Efficient environment monitoring has become a major concern for society to guarantee sustainable development. For instance, forest fire detection and analysis is important to provide early warning systems and identify impact. In this environmental context, availability of up-to-date information is very important for reducing damages caused. Environmental applications are deployed on top of GeospatialInformation Infrastructures (GIIs) to manage information pertaining to our environment. Suchinfrastructures are traditionally top-down infrastructures that do not consider user participation. This provokes a bottleneck in content publication and therefore a lack of content availability. On the contrary mainstream IT systems and in particular the emerging Web 2.0 Services allow active user participation that is becoming a massive source of dynamic geospatial resources. In this paper, we present a webservice, that implements a standard interface, offers a unique entry point for spatial data discovery, both in GII services and web 2.0 services. We introduce a prototype as proof of concept in a forest fire scenario, where we illustrate how to leverage scientific data and web 2.0 conten
The Role of the Emerging Countries in the G20: Agenda-setter, Veto Player or Spectator?  Bruges Regional Integration & Global Governance Paper 2/2011

In 2008, the G20 convened for the first time at leaders’ level, making emerging countries such as China, India and Brazil permanent members of an informal gathering at the highest political level. The aim of this paper is to refine previous assessments on the role of these emerging countries in the new G20. We first analyse the preferences of the United States and European members as a proxy for G8 positions and then juxtapose them with the preferences of China, India and Brazil as representatives of the emerging countries within the G20. We find that the latter share in particular the concern for more voice in global economic governance but – due to often heterogeneous preferences – do not generally act as a bloc. Moreover, by comparing their preferences with G20 outcomes, the paper investigates to what extent the emerging countries have agenda-setting or veto power, or whether they are taking a back-seat role among the G20 countries. We show that they are not mere spectators but have a certain agenda-setting power, especially when they are able to forge coalitions or hold the presidency
An analysis of ranking principles and retrieval strategies

The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP’s limitations. All alternatives deviate from the PRP by incorporating dependencies. This results in a re-ranking that promotes or demotes documents depending upon their relationship with the documents that have been already ranked. In this paper, we compare and contrast the behaviour of state-of-the-art ranking strategies and principles. To do so, we tease out analytical relationships between the ranking approaches and we investigate the document kinematics to visualise the effects of the different approaches on document ranking
Towards a better understanding of the relationship between probabilistic models in IR

Probability of relevance (PR) models are generally assumed to implement the Probability Ranking Principle (PRP) of IR, and recent publications claim that PR models and language models are similar. However, a careful analysis reveals two gaps in the chain of reasoning behind this statement. First, the PRP considers the relevance of particular documents, whereas PR models consider the relevance of any query-document pair. Second, unlike PR models, language models consider draws of terms and documents. We bridge the first gap by showing how the probability measure of PR models can be used to define the probabilistic model of the PRP. Furthermore, we argue that given the differences between PR models and language models, the second gap cannot be bridged at the probabilistic model level. We instead define a new PR model based on logistic regression, which has a similar score function to the one of the query likelihood model. The performance of both models is strongly correlated, hence providing a bridge for the second gap at the functional and ranking level. Understanding language models in relation with logistic regression models opens ample new research directions which we propose as future work
A query-basis approach to parametrizing novelty-biased cumulative gain

Novelty-biased cumulative gain (α-NDCG) has become the de facto measure within the information retrieval (IR) community for evaluating retrieval systems in the context of sub-topic retrieval. Setting the incorrect value of parameter α in α-NDCG prevents the measure from behaving as desired in particular circumstances. In fact, when α is set according to common practice (i.e. α = 0.5), the measure favours systems that promote redundant relevant sub-topics rather than provide novel relevant ones. Recognising this characteristic of the measure is important because it affects the comparison and the ranking of retrieval systems. We propose an approach to overcome this problem by defining a safe threshold for the value of α on a query basis. Moreover, we study its impact on system rankings through a comprehensive simulation
On the use of complex numbers in quantum models for information retrieval

Quantum-inspired models have recently attracted increasing attention in Information Retrieval. An intriguing characteristic of the mathematical framework of quantum theory is the presence of complex numbers. However, it is unclear what such numbers could or would actually represent or mean in Information Retrieval. The goal of this paper is to discuss the role of complex numbers within the context of Information Retrieval. First, we introduce how complex numbers are used in quantum probability theory. Then, we examine van Rijsbergen’s proposal of evoking complex valued representations of informations objects. We empirically show that such a representation is unlikely to be effective in practice (confuting its usefulness in Information Retrieval). We then explore alternative proposals which may be more successful at realising the power of complex numbers
Predicting the performance of recommender systems: An information theoretic approach

Proceedings of Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011.The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-23318-0_5Performance prediction is an appealing problem in Recommender Systems, as it enables an array of strategies for deciding when to deliver or hold back recommendations based on their foreseen accuracy. The problem, however, has been barely addressed explicitly in the area. In this paper, we propose adaptations of query clarity techniques from ad-hoc Information Retrieval to define performance predictors in the context of Recommender Systems, which we refer to as user clarity. Our experiments show positive results with different user clarity models in terms of the correlation with single recommender’s performance. Empiric results show significant dependency between this correlation and the recommendation method at hand, as well as competitive results in terms of average correlation.This work was supported by the Spanish Ministry of Science and
Innovation (TIN2008-06566-C04-02), University Autónoma de Madrid and the Community
of Madrid (CCG10-UAM/TIC-5877
Issues on conflict resolution in collaborative networks

12th IFIP Working Conference on VIRTUAL ENTERPRISES, 17 - 19 October 2011 - São Paulo, BrazilConflicts are frequent in virtually every scenario involving complex interactions. Collaborative Networks, in which there is a compromise between skills, competencies and resources, are not an exception. Moreover, these conflicts can be different in nature, ranging from cultural or relational conflicts to conflicts of interests. Although conflicts are common in these virtual settings, very few tools exist to settle them. Therefore, parties involved in conflict resolution generally have to resort to traditional approaches, which delay the process and waste the advantages of these Virtual Organizations. In this paper we present a structured model of a contract for a Collaborative Network. Based on this model, we developed an information system which is able to build conflict scenarios and determine the possible and probable outcomes. We combine this development with the UMCourt platform, which comprises a rich negotiation and mediation tool, to build a conflict resolution framework in the context of Collaborative Networks.The work described in this paper was developed under the TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), a research project supported by FCT (Science & Technology Foundation), Portugal
Modelling virtual organisations: Structure and reconfigurations

Organisations have to adapt rapidly to survive in today’s diverse and rapidly changing environments. The idea of virtual organisations emerged as an answer. There is a strong need to understand virtual organisations (VOs) in a formal way: changes can have side effects and hence one might wish to understand precisely what consequences a change might have. The Virtual Organisation Modelling Language (VOML) consists of sub-languages to model different aspects of VOs such as their structure or operational models: VO-S deals with structural aspects while VO-R addresses reconfigurations. The concepts are exemplified through a travel booking VO that needs to cope with extra demands imposed by a large event such as the Olympic games.Peer-reviewedPost-printAdaptation and Value Creating Collaborative Networks 12th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2011, São Paulo, Brazil, October 17-19, 2011