pinecone/core-2020-05-10-deduplication huggingface dataset:
Comparison of Local and Global Region Merging in the Topological Map

International audienceThe topological map is a model that represents 2D and 3D images subdivision. It aims to allow the use of topological and geometrical features of the subdivision in image processing operations. When handling regions in an image, one of the main operation is the region merging, for example in segmentation process. This paper presents two algorithms of region merging in 3D topological maps: one local which modifies locally the map around merged regions, and another one global which runs through all the elements of the map. We study their complexities and present experimental results to compare both approaches
Multilayer perceptron adaptive dynamic control of mobile robots : experimental validation

This paper presents experimental results acquired from the implementation of an adaptive control scheme for nonholonomic mobile robots, which was recently proposed by the same authors and tested only by simulations. The control system comprises a trajectory tracking kinematic controller, which generates the reference wheel velocities, and a cascade dynamic controller, which estimates the robot's uncertain nonlinear dynamic functions in real-time via a multilayer perceptron neural network. In this manner precise velocity tracking is attained, even in the presence of unknown and/or time-varying dynamics. The experimental mobile robot, designed and built for the purpose of this research, is also presented in this paper.peer-reviewe
Postural control on a quadruped robot using lateral tilt : a dynamical system approach

Autonomous adaptive locomotion over irregular terrain is one important
topic in robotics research. Postural control, meaning movement generation
for robot legs in order to attain balance, is a first step in this
direction. In this article, we focus on the essential issue of modeling the
interaction between the central nervous system and the peripheral information
in the locomotion context. This issue is crucial for autonomous
and adaptive control, and has received little attention so far. This modeling
is based on the concept of dynamical systems whose intrinsic robustness
against perturbations allows for an easy integration of sensory-motor
feedback and thus for closed-loop control. Herein, we focus on achieving
balance without locomotion.
The developed controller is modeled as discrete, sensory driven corrections
of the robot joint values in order to achieve balance. The robot
lateral tilt information modulates the generated trajectories thus achieving
balance. The system is demonstrated on a quadruped robot which
adjusts its posture until reducing the lateral tilt to a minimum
Learning relational options for inductive transfer in relational reinforcement learning

In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent usually has very little information. Therefore, when faced with complex problems that have a large state space, learning a good strategy might be infeasible or too slow to work in practice. One way to overcome this problem, is the use of guidance to supply the agent with traces of “reasonable policies”. However, in a lot of cases it will be hard for the user to supply such a policy. In this paper, we will investigate the use of transfer learning in Relational Reinforcement Learning. The goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. More specifically, we introduce an extension of the options framework to the relational setting and show how one can learn skills that can be transferred across similar, but different domains. We present experiments showing the possible benefits of using relational options for transfer learning.status: publishe
Simple Stochastic Games with Few Random Vertices are Easy to Solve

International audienceWe present a new algorithm for solving Simple Stochastic Games (SSGs). This algorithm is based on an exhaustive search of a special kind of positional optimal strategies, the f-strategies. The running time is , where and are respectively the number of vertices, random vertices and edges, and the maximum bit-length of a transition probability. Our algorithm improves existing algorithms for solving SSGs in three aspects. First, our algorithm performs well on SSGs with few random vertices, second it does not rely on linear or quadratic programming, third it applies to all SSGs, not only stopping SSGs
Robust Analysis of Timed Automata via Channel Machines

International audienceWhereas formal verification of timed systems has become a very active field of research, the idealised mathematical semantics of timed automata cannot be faithfully implemented. Several works have thus focused on a modified semantics of timed automata which ensures implementability, and robust model-checking algorithms for safety, and later LTL properties have been designed. Recently, a~new approach has been proposed, which reduces (standard) model-checking of timed automata to other verification problems on channel machines. Thanks to a new encoding of the modified semantics as a network of timed systems, we propose an original combination of both approaches, and prove that robust model-checking for coFlat-MTL, a large fragment of~MTL, is EXPSPACE-Complete
Compositional Methods for Information-Hiding

International audienceProtocols for information-hiding often use randomized primitives to obfuscate the link between the observables and the information to be protected. The degree of protection provided by a protocol can be expressed in terms of the probability of error associated to the inference of the secret information. We consider a probabilistic process calculus approach to the specification of such protocols, and we study how the operators affect the probability of error. In particular, we characterize constructs that have the property of not decreasing the degree of protection, and that can therefore be considered safe in the modular construction of protocols. As a case study, we apply these techniques to the Dining Cryptographers, and we are able to derive a generalization of Chaum's strong anonymity result
Epistemic constraints on autonomous symbolic representation in natural and artificial agents

We set out to address, in the form of a survey, the fundamental constraints upon self-updating representation in cognitive agents of natural and artificial origin. The foundational epistemic problem encountered by such agents is that of distinguishing errors of representation from inappropriateness of the representational framework. Resolving this conceptual difficulty involves ensuring the empirical falsifiability of both the representational hypotheses and the entities so represented, while at the same time retaining their epistemic distinguishability. We shall thus argue that perception-action frameworks provide an appropriate basis for the development of an empirically meaningful criterion for validating perceptual categories. In this scenario, hypotheses about the agent’s world are defined in terms of environmental affordances (characterised in terms of the agent’s active capabilities). Agents with the capability to hierarchically-abstract this framework to a level consonant with performing syntactic manipulations and making deductive conjectures are consequently able to form an implicitly symbolic representation of the environment within which new, higher-level, modes of environment manipulation are implied (e.g. tool-use). This abstraction process is inherently open-ended, admitting a wide-range of possible representational hypotheses — only the form of the lowest-level of the hierarchy need be constrained a priori (being the minimally sufficient condition necessary for retention of the ability to falsify high-level hypotheses). In biological agents capable of autonomous cognitive-updating, we argue that the grounding of such a priori ‘bootstrap’ representational hypotheses is ensured via the process of natural selection
Constructing a virtual Tower of Babel: a case study in cross-cultural collaboration across three continents

The collaboration project described in this paper revolves around the construction of a virtual Tower of Babel in a 3D Collaborative Virtual Environment (3D CVE). It involved students across three cooperating institutions, on three different continents in different time zones. It addresses the increasing need for students to engage in international collaboration, as much of today's Information and Communication Technology work demands it. This requires cross-cultural understandings with one's co-collaborators, yet there are few opportunities for this to occur in a pedagogical setting. Therefore, this paper discusses a pedagogically-oriented case study of the use of a 3D CVE as a multi-cultural classroom, describing and discussing different phases in the cross-cultural collaborative process
A conversation on the efficacies of the game engine to address notions of sacred space: the digital songlines project and transgressions of sacredness

The Digital Songlines (DSL) game engine is used as a vehicle for Indigenous Australian storytelling. Their storytelling is inextricably linked to the 'country' from which it emerges. The game engine provides a simulation of that country for embedding of the stories to be told. Much of the 'country' referred to is sacred. However, the fundamental underlying principles of threedimensional reproduction of space in a 3D computer game (3DCG) defines all spaces as mathematically equal - there is no place for notions of sacred spaces. This presents a dilemma for those cultures that do not subscribe to the scientific notions of ontological certainty underpinning such mathematically modelled space. In the case of the DSL game engine, notions of the sacredness of the country modelled has been made explicit in order to highlight its importance for its physical-world corollary. Hence, this paper discusses notions of sacredness and its place in the simulational spaces of the DSL's 3DCG engine. It presents a series of dilemmas for the inclusion of sacred places in simulational spaces. It does not attempt to resolve these dilemmas, but rather to bring them into sharp relief with examples drawn from the DSL project experience. In so doing, it presents a new way of thinking through the significance of this issue for Western and non-Western use of the 3DCG in cultural heritage applications
Efficient Algorithms for Node Disjoint Subgraph Homeomorphism
  Determination

Recently, great efforts have been dedicated to researches on the management
of large scale graph based data such as WWW, social networks, biological
networks. In the study of graph based data management, node disjoint subgraph
homeomorphism relation between graphs is more suitable than (sub)graph
isomorphism in many cases, especially in those cases that node skipping and
node mismatching are allowed. However, no efficient node disjoint subgraph
homeomorphism determination (ndSHD) algorithms have been available. In this
paper, we propose two computationally efficient ndSHD algorithms based on state
spaces searching with backtracking, which employ many heuristics to prune the
search spaces. Experimental results on synthetic data sets show that the
proposed algorithms are efficient, require relative little time in most of the
testing cases, can scale to large or dense graphs, and can accommodate to more
complex fuzzy matching cases.Comment: 15 pages, 11 figures, submitted to DASFAA 200
TwigBuffer: Avoiding Useless Intermediate Solutions Completely in Twig Joins

Twig pattern matching plays a crucial role in XML data processing. TwigStack [2] is a holistic twig join algorithm that solves the problem in two steps: (1) finding potentially useful intermediate path solutions, (2) merging the intermediate solutions. The algorithm is optimal when the twig pattern has only //-edges, in the sense that no useless partial solutions are generated in the first step (thus expediting the second step and boosting the overall performance). However, when /-edges are present, a large set of useless partial solutions may be produced, which directly downgrades the overall performance. Recently, some improved versions of the algorithm (e.g., TwigStackList and iTwigJoin) have been proposed in an attempt to reduce the number of useless partial solutions when /-edges are involved. However, none of the algorithms can avoid useless partial solutions completely. In this paper, we propose a new algorithm, TwigBuffer, that is guaranteed to completely avoid the useless partial solutions. Our algorithm is based on a novel strategy to buffer and manipulate elements in stacks and lists. Experiments show that TwigBuffer significantly outperforms previous algorithms when arbitrary /-edges are present.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Metaheuristics for the Bi-objective Ring Star Problem

International audienceThe bi-objective ring star problem aims to locate a cycle through a subset of nodes of a graph while optimizing two types of cost. The first criterion is to minimize a ring cost, related to the length of the cycle, whereas the second one is to minimize an assignment cost, from non-visited nodes to visited ones. In spite of its natural multi-objective formulation, this problem has never been investigated in such a way. In this paper, three metaheuristics are designed to approximate the whole set of efficient solutions for the problem under consideration. Computational experiments are performed on well-known benchmark test instances, and the proposed methods are rigorously compared to each other using different performance metrics
Using a task-based approach in evaluating the usability of BoBIs in an e-book environment

This paper reports on a usability evaluation of BoBIs (Back-of-the-book Indexes) as searching and browsing tools in an e-book environment. This study employed a task-based approach and within-subject design. The retrieval performance of a BoBI was compared with a ToC and Full-Text Search tool in terms of their respective effectiveness and efficiency for finding information in e-books. The results demonstrated that a BoBI was significantly more efficient (faster) and useful compared to a ToC or Full-Text Search tool for finding information in an e-book environment
Improving Term Frequency Normalization for Multi-topical Documents, and
  Application to Language Modeling Approaches

Term frequency normalization is a serious issue since lengths of documents
are various. Generally, documents become long due to two different reasons -
verbosity and multi-topicality. First, verbosity means that the same topic is
repeatedly mentioned by terms related to the topic, so that term frequency is
more increased than the well-summarized one. Second, multi-topicality indicates
that a document has a broad discussion of multi-topics, rather than single
topic. Although these document characteristics should be differently handled,
all previous methods of term frequency normalization have ignored these
differences and have used a simplified length-driven approach which decreases
the term frequency by only the length of a document, causing an unreasonable
penalization. To attack this problem, we propose a novel TF normalization
method which is a type of partially-axiomatic approach. We first formulate two
formal constraints that the retrieval model should satisfy for documents having
verbose and multi-topicality characteristic, respectively. Then, we modify
language modeling approaches to better satisfy these two constraints, and
derive novel smoothing methods. Experimental results show that the proposed
method increases significantly the precision for keyword queries, and
substantially improves MAP (Mean Average Precision) for verbose queries.Comment: 8 pages, conference paper, published in ECIR '0
Finding the best picture: cross-media retrieval of content

We query the pictures of Yahoo! News for persons and objects by using the accompanying news captions as an indexing annotation. Our aim is to find these pictures on top of the answer list in which the sought persons or objects are most prominently present. We demonstrate that an appearance or content model based on syntactic, semantic and discourse analysis of the short news text is only useful for finding
the best picture of a person of object if the database contains photos each picturing many entities. In other circumstances a simpler bag-of-nouns representation has a good performance. The appearance models are tested in a probabilistic ranking function.status: publishe
An evaluation and analysis of incorporating term dependency for ad-hoc retrieval

Although many retrieval models incorporating term dependency have been developed, it is still unclear whether term dependency information can consistently enhance retrieval performance for different queries. We present a novel model that captures the main components of a topic and the relationship between those components and the power of term  dependency to improve retrieval performance. Experimental results demonstrate that the power of term dependency  strongly depends on the relationship between these components. Without relevance information, the model is still useful by predicting the components based on global  statistical information. We show the applicability of the model for adaptively incorporating term dependency for individual queries
Key sustainability issues and the spatial classification of sensitive regions in Europe

Cross-cutting environmental, social and economic changes may have harsh impacts on sensitive regions. To address sustainability issues by governmental policy measures properly, the geographical delineation of sensitive regions is essential. With reference to the European impact assessment guidelines from 2005, sensitive regions were identified by using environmental, social and economic data and by applying cluster analysis, United Nation Environmental Policy priorities and expert knowledge. On a regionalised ‘Nomenclature of Territorial Units for Statistics’ (NUTS) level and for pre-defined sensitive region types (post-industrial zones, mountains, coasts and islands) 31 % of the European area was identified as sensitive. However, the delineation mainly referred to social and economic issues since the regional data bases on environmental indicators are limited and do not allow the separation of medium-term vital classes of sensitive regions. Overall, the sensitive regions showed indicator values differing from the EU- 25 average.peer-reviewe
Relational sequence learning

Sequential behavior and sequence learning are essential to intelligence. Often the elements of sequences exhibit an internal structure that can elegantly be represented using relational atoms. Applying traditional sequential learning techniques to such relational sequences requires one either to ignore the internal structure or to live with a combinatorial explosion of the model complexity. This chapter briefly reviews relational sequence learning and describes several techniques tailored towards realizing this, such as local pattern mining techniques, (hidden) Markov models, conditional random fields, dynamic programming and reinforcement learning.status: publishe
Formal Approaches to Information-Hiding (Tutorial)

International audienceIn this survey paper we consider the class of protocols for information-hiding which use randomization to obfuscate the link between the observables and the information to be protected. We focus on the problem of formalizing the notion of information hiding, and verifying that a given protocol achieves the intended degree of protection. Without the pretense of being omni-comprehensive, we review the main approaches that have been explored in literature: possibilistic, probabilistic, information-theoretic, and statistical
Logical Networks: Towards Foundations for Programmable Overlay Networks and Overlay Computing Systems

International audienceWe propose and discuss foundations for programmable overlay networks and overlay computing systems. Such overlays are built over a large number of distributed computational individuals, virtually organized in colonies, and ruled by a leader (broker) who is elected or imposed by system administrators. Every individual asks the broker to log in the colony by declaring the resources that can be offered (with variable guarantees). Once logged in, an individual can ask the broker for other resources. Colonies can recursively be considered as evolved individuals who can log in an outermost colony governed by another (super)-broker. Communications and routing intra-colonies goes through a broker-2-broker PKI-based negotiation. Every broker routes intra- and inter- service requests by filtering its resource routing table, and then by forwarding the request first inside its colony, and second outside, via the proper super-broker (thus applying an endogenous-first-estrogen-last strategy). Theoretically, queries are formulæ in first-order logic equipped with a small program used to orchestrate and synchronize atomic formulæ. When the client individual receives notification of all (or part of) the requested resources, then the real resource exchange is performed di- rectly by the server(s) individuals, without any further mediation of the broker, in a pure peer-to-peer fashion. The proposed overlay promotes an intermittent participation in the colony, since peers can appear, disappear, and organize themselves dynamically. This implies that the routing process may lead to failures, because some individuals have quit, or are temporarily unavailable, or they were logged out manu militari by the broker due to their poor performance or greediness. We design, validate through simulation, and implement these foundations in a programmable overlay computer system, called Arigatoni
The conversation calculus: a model of service-oriented computation

We present a process-calculus model for expressing and analyzing service-based systems. Our approach addresses central features of the service-oriented computational model such as distribution, process delegation, communication and context sensitiveness, and loose coupling. Distinguishing aspects of our model are the notion of conversation context, the adoption of a context sensitive, message-passing-based communication, and of a simple yet expressive mechanism for handling exceptional behavior. We instantiate our model by extending a fragment of the π-calculus, illustrate its expressiveness by means of many examples, and study its basic behavioral theory; in particular, we establish that bisimilarity is a congruenc
Engineering Service Oriented Applications: From StPowla Processes to SRML Models

This is the author's final draft of the paper published as Lecture Notes in Computer Science, 2008, 4961, pp. 163-178. The original publication is available at www.springerlink.com. Doi: 10.1007/978-3-540-78743-3_13Service Oriented Computing is a paradigm for developing software systems as the composition of a number of services. Services are loosely coupled entities, can be dynamically published, discovered and invoked over a network. The engineering of such systems presents novel challenges, mostly due to the dynamicity and distributed nature of service-based applications. In this paper, we focus on the modelling of service orchestrations. We discuss the relationship between two languages developed under the Sensoria project: SRML as a high level modelling language for Service Oriented Architectures, and StPowla as a process-oriented orchestration approach that separates core business processes from system variability at the end-user’s level, where the focus is towards achieving business goals. We also extend the current status of StPowla to include workflow reconfigurations. A fundamental challenge of software engineering is to correctly align business goals with IT strategy, and as such we present an encoding of StPowla to SRML. This provides a formal framework for StPowla and also a separated view of policies representing system variability that is not present in SRML