pinecone/core-2020-05-10-deduplication huggingface dataset:
Operational semantics of aspects in business process management

Aspect orientation is an important approach to address complexity of cross-cutting concerns in Information Systems. This approach encapsulates these concerns separately and compose them to the main module when needed. Although there a different works which shows how this separation should be performed in process models, the composition of them is an open area. In this paper, we demonstrate the semantics of a service which enables this composition. The result can also be used as a blueprint to implement the service to support aspect orientation in Business Process Management area
Analysis of modular organisation of interaction networks based on asymptotic dynamics

International audienceThis paper investigates questions related to modularity in biological interaction networks. We develop a discrete theoretical framework based on the analysis of the asymptotic dynamics of biological interaction networks. More precisely, we exhibit formal conditions under which agents of interaction networks can be grouped into modules, forming a modular organisation. Our main result is that the conventional decomposition into strongly connected components fulfills the formal conditions of being a modular organisation. We also propose a modular and incremental algorithm for an efficient equilibria computation. Furthermore, we point out that our framework enables a finer analysis providing a decomposition in elementary modules, possibly smaller than strongly connected components
A simple model to control growth rate of synthetic E. coli during the exponential phase: model analysis and parameter estimation

International audienceWe develop and analyze a model of a minimal synthetic gene circuit, that describes part of the gene expression machinery in Escherichia coli, and enables the control of the growth rate of the cells during the exponential phase. This model is a piecewise non-linear system with two variables (the concentrations of two gene products) and an input (an inducer). We study the qualitative dynamics of the model and the bifurcation diagram with respect to the input. Moreover, an analytic expression of the growth rate during the exponential phase as function of the input is derived. A relevant problem is that of identi ability of the parameters of this expression supposing noisy measurements of exponential growth rate. We present such an identi ability study that we validate in silico with synthetic measurements
Learning path construction based on association link network.

Nowadays the Internet virtually serves as a library for people to quickly retrieve information (Web resources) on what they want to learn. Reusing Web resources to form learning resources offers a way for rapid construction of self-pace or even formal courses. This requires identifying suitable Web resources and organizing such resources into proper sequences for delivery. However, getting these done is challenging, as they need to determine a set of Web resources properties, including the relevance, importance and complexity of Web resources to students as well as the relationships among Web resources, which are not trivial to be done automatically. Particularly each student has different needs. To address the above problems, we present a learning path generation method based on the Association Link Network (ALN), which works out Web resources properties by exploiting the association among Web resources. Our experiments show that the proposed method can generate good quality learning paths and help improve student learning
Perceived support in e-collaborative learning: An exploratory study which make use of synchronous and asynchronous online-teaching approaches

Published version of a chapter in the book: Advances in Web-Based Learning - ICWL 2012. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-33642-3_2This study compares four different learning environments for e-collaborative learning in two European countries related to the dimension of student’s mutual support. The theoretical baseline is Vygotsky’s zone of proximal development (ZOPD) and the socio-genetic approach of Piaget. The analyzed data are based on questionnaires collected over the time period of an entire semester including four different courses at the master’s level. These courses applied different e-collaborative approaches including a variety of tools for supporting communication. It is assumed that these courses including communication tools e.g. virtual face-to-face meetings enhance the chances for better communication, and finally, for mutual support of students themselves. The objective is to investigate how the different environments have affected the students’ perception related to different e-collaborative learning platforms in the dimensions of social support, information exchange, and task support
BlueFix : using crowd-sourced feedback to support programming students in error diagnosis and repair.

Feedback is regarded as one of the most important influences on student learning and motivation. But standard compiler feedback is designed for experts - not novice programming students, who can find it difficult to interpret and understand. In this paper we present BlueFix, an online tool currently integrated into the BlueJ IDE which is designed to assist programming students with error diagnosis and repair. Unlike existing approaches, BlueFix proposes a feedback algorithm based upon frameworks combined from the HCI and Pedagogical domains, which can provide different students with dynamic levels of support based upon their compilation behaviour. An evaluation revealed that students' viewed our tool positively and that our methodology could identify appropriate fixes for uncompilable source code with a significantly higher rate of speed and precision over related techniques in the literature
Annotation tool for enhancing e-learning courses

One of the most popular forms of learning is through reading and for years we have used hard copy documents as the main material to learn. With the advent of the Internet and the fast development of new technologies, new tools have been developed to assist the learning process. However, reading is still the main learning method that is an individual activity. In this paper we propose a highlighting tool that enables the reading and learning process to become a collaborative and shared activity. In other words, the highlighting tool supports the so-called active-reading, a well-known and efficient means of learning. The highlighting tool brings to the digital environment the same metaphor of the traditional highlight marker and puts it in a social context. It enables users to emphasize certain portions of digital learning objects. Furthermore, it provides students, tutors, course coordinators and educational institutions new possibilities in the teaching and learning process. In this work we expose the first quantitative and qualitative results regarding the use of the highlight tool by over 750 students through 8 weeks of courses. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33642-3_6.EC/ECP 2008 EDU 428016CAPE
Bounds on Contention Management in Radio Networks

The local broadcast problem assumes that processes in a wireless network are provided messages, one by one, that must be delivered to their neighbors. In this paper, we prove tight bounds for this problem in two well-studied wireless network models: the classical model, in which links are reliable and collisions consistent, and the more recent dual graph model, which introduces unreliable edges. Our results prove that the Decay strategy, commonly used for local broadcast in the classical setting, is optimal. They also establish a separation between the two models, proving that the dual graph setting is strictly harder than the classical setting, with respect to this primitive
On Byzantine Broadcast in Loosely Connected Networks

We consider the problem of reliably broadcasting information in a multihop
asynchronous network that is subject to Byzantine failures. Most existing
approaches give conditions for perfect reliable broadcast (all correct nodes
deliver the authentic message and nothing else), but they require a highly
connected network. An approach giving only probabilistic guarantees (correct
nodes deliver the authentic message with high probability) was recently
proposed for loosely connected networks, such as grids and tori. Yet, the
proposed solution requires a specific initialization (that includes global
knowledge) of each node, which may be difficult or impossible to guarantee in
self-organizing networks - for instance, a wireless sensor network, especially
if they are prone to Byzantine failures. In this paper, we propose a new
protocol offering guarantees for loosely connected networks that does not
require such global knowledge dependent initialization. In more details, we
give a methodology to determine whether a set of nodes will always deliver the
authentic message, in any execution. Then, we give conditions for perfect
reliable broadcast in a torus network. Finally, we provide experimental
evaluation for our solution, and determine the number of randomly distributed
Byzantine failures than can be tolerated, for a given correct broadcast
probability.Comment: 1
Pessimistic Software Lock-Elision

Read-write locks are one of the most prevalent lock forms in concurrent applications because they allow read accesses to locked code to proceed in parallel. However, they do not offer any parallelism between reads and writes.
This paper introduces pessimistic lock-elision (PLE), a new approach for non-speculatively replacing read-write locks with pessimistic (i.e. non-aborting) software transactional code that allows read-write concurrency even for contended code and even if the code includes system calls. On systems with hardware transactional support, PLE will allow failed transactions, or ones that contain system calls, to preserve read-write concurrency.
Our PLE algorithm is based on a novel encounter-order design of a fully pessimistic STM system that in a variety of benchmarks spanning from counters to trees, even when up to 40% of calls are mutating the locked structure, provides up to 5 times the performance of a state-of-the-art read-write lock.National Science Foundation (U.S.) (Grant 1217921
Bounded-Contention Coding for Wireless Networks in the High SNR Regime

Efficient communication in wireless networks is typically challenged by the possibility of interference among several transmitting nodes. Much important research has been invested in decreasing the number of collisions in order to obtain faster algorithms for communication in such networks.
This paper proposes a novel approach for wireless communication, which embraces collisions rather than avoiding them, over an additive channel. It introduces a coding technique called Bounded-Contention Coding (BCC) that allows collisions to be successfully decoded by the receiving nodes into the original transmissions and whose complexity depends on a bound on the contention among the transmitters.
BCC enables deterministic local broadcast in a network with n nodes and at most a transmitters with information of ℓ bits each within O(alogn + aℓ) bits of communication with full-duplex radios, and O((alogn + aℓ)(logn)) bits, with high probability, with half-duplex radios. When combined with random linear network coding, BCC gives global broadcast within O((D + a + logn)(alogn + ℓ)) bits, with high probability. This also holds in dynamic networks that can change arbitrarily over time by a worst-case adversary. When no bound on the contention is given, it is shown how to probabilistically estimate it and obtain global broadcast that is adaptive to the true contention in the network.Simons Foundation (Postdoctoral Fellows Program)National Science Foundation (U.S.) (Award 0939370-CCF
A graph-based design framework for services

Service-oriented systems rely on software applications that offer services through the orchestration of activities performed by external services procured on the fly when they are needed. This paper presents an overview of a graph-based framework developed around the notions of service and activity module for supporting the design of service-oriented systems in a way that is independent of execution languages and deployment platforms. The framework supports both behaviour and quality-of-service constraints for the discovery, ranking and selection of external services. Service instantiation and binding are captured as algebraic operations on configuration graphs. © 2012 Springer-Verlag
Towards the specification and verification of modal properties for structured systems

System specification formalisms should come with suitable property specification languages and effective verification tools. We sketch a framework for the verification of quantified temporal properties of systems with dynamically evolving structure. We consider visual specification formalisms like graph transformation systems (GTS) where program states are modelled as graphs, and the program\ud
behavior is specified by graph transformation rules. The state space of a GTS can be represented as a graph transition system (GTrS), i.e. a transition system with states and transitions labelled, respectively, with a graph, and with a partial morphism representing the evolution of state components. Unfortunately, GTrSs are prohibitively large or infinite even for simple systems, making verification intractable and hence calling for appropriate abstraction techniques
Exploiting over- and under-approximations for infinite-state counterpart models

Software systems with dynamic topology are often infini-testate. Paradigmatic examples are those modeled as graph transformation systems (GTSs) with rewrite rules that allow an unbounded creation of items. For such systems, verification can become intractable, thus calling for the development of approximation techniques that may ease\ud
the verification at the cost of losing in preciseness and completeness. Both over- and under-approximations have been considered in the literature, respectively offering more and less behaviors than the original system. At the same time, properties of the system may be either preserved or\ud
reflected by a given approximation. In this paper we propose a general notion of approximation that captures some of the existing approaches for GTSs. Formulae are specified by a generic quantified modal logic, one that also generalizes many specification logics adopted in the literature for GTSs. We also propose a type system to denote part of the formulae as either reflected or preserved, together with a technique that exploits\ud
under- and over-approximations to reason about typed as well as untyped formula
Bottom-up meta-modelling: An interactive approach

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33666-9_2Proceedings of 15th International Conference, MODELS 2012, Innsbruck, Austria, September 30–October 5, 2012The intensive use of models in Model-Driven Engineering (MDE) raises the need to develop meta-models with different aims, like the construction of textual and visual modelling languages and the specification of source and target ends of model-to-model transformations. While domain experts have the knowledge about the concepts of the domain, they usually lack the skills to build meta-models. These should be tailored according to their future usage and specific implementation platform, which demands knowledge available only to engineers with great expertise in MDE platforms. These issues hinder a wider adoption of MDE both by domain experts and software engineers.
In order to alleviate this situation we propose an interactive, iterative approach to meta-model construction enabling the specification of model fragments by domain experts, with the possibility of using informal drawing tools like Dia. These fragments can be annotated with hints about the intention or needs for certain elements. A meta-model is automatically induced, which can be refactored in an interactive way, and then compiled into an implementation meta-model using profiles and patterns for different platforms and purposes.This work was funded by the Spanish Ministry of Economy and Competitivity (project “Go Lite” TIN2011-24139) and the R&D programme of the Madrid Region (project “e-Madrid” S2009/TIC-1650
An Exploratory Study of Forces and Frictions affecting Large-Scale
  Model-Driven Development

In this paper, we investigate model-driven engineering, reporting on an
exploratory case-study conducted at a large automotive company. The study
consisted of interviews with 20 engineers and managers working in different
roles. We found that, in the context of a large organization, contextual forces
dominate the cognitive issues of using model-driven technology. The four forces
we identified that are likely independent of the particular abstractions chosen
as the basis of software development are the need for diffing in software
product lines, the needs for problem-specific languages and types, the need for
live modeling in exploratory activities, and the need for point-to-point
traceability between artifacts. We also identified triggers of accidental
complexity, which we refer to as points of friction introduced by languages and
tools. Examples of the friction points identified are insufficient support for
model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe
V1-inspired features induce a weighted margin in SVMs

Image representations derived from simplified models of the primary visual cortex (V1), such as HOG and SIFT, elicit good performance in a myriad of visual classification tasks including object recognition/detection, pedestrian detection and facial expression classification. A central question in the vision, learning and neuroscience communities regards why these architectures perform so well. In this paper, we offer a unique perspective to this question by subsuming the role of V1-inspired features directly within a linear support vector machine (SVM). We demonstrate that a specific class of such features in conjunction with a linear SVM can be reinterpreted as inducing a weighted margin on the Kronecker basis expansion of an image. This new viewpoint on the role of V1-inspired features allows us to answer fundamental questions on the uniqueness and redundancies of these features, and offer substantial improvements in terms of computational and storage efficiency
Shapecollage: Occlusion-Aware, Example-Based Shape Interpretation

This paper presents an example-based method to interpret a 3D shape from a single image depicting that shape. A major difficulty in applying an example-based approach to shape interpretation is the combinatorial explosion of shape possibilities that occur at occluding contours. Our key technical contribution is a new shape patch representation and corresponding pairwise compatibility terms that allow for flexible matching of overlapping patches, avoiding the combinatorial explosion by allowing patches to explain only the parts of the image they best fit. We infer the best set of localized shape patches over a graph of keypoints at multiple scales to produce a discontinuous shape representation we term a shape collage. To reconstruct a smooth result, we fit a surface to the collage using the predicted confidence of each shape patch. We demonstrate the method on shapes depicted in line drawing, diffuse and glossy shading, and textured styles.National Science Foundation (U.S.) (Grant 1111415)United States. Office of Naval Research (Grant N00014-09-1-1051)National Institutes of Health (U.S.) (Grant R01-EY019262
Augmented attributes representations

We propose a new learning method to infer a mid-level feature representation that combines the advantage of semantic attribute representations with the higher expressive power of non-semantic features. The idea lies in augmenting an existing attribute-based representation with additional dimensions for which an autoencoder model is coupled with a large-margin principle. This construction allows a smooth transition between the zero-shot regime with no training example, the unsupervised regime with training examples but without class labels, and the supervised regime with training examples and with class labels. The resulting optimization problem can be solved efficiently, because several of the necessity steps have closed-form solutions. Through extensive experiments we show that the augmented representation achieves better results in terms of object categorization accuracy than the semantic representation alone
Elastic shape matching of parameterized surfaces using square root normal fields.

In this paper we define a new methodology for shape analysis of parameterized surfaces, where the main issues are: (1) choice of metric for shape comparisons and (2) invariance to reparameterization. We begin by defining a general elastic metric on the space of parameterized surfaces. The main advantages of this metric are twofold. First, it provides a natural interpretation of elastic shape deformations that are being quantified. Second, this metric is invariant under the action of the reparameterization group. We also introduce a novel representation of surfaces termed square root normal fields or SRNFs. This representation is convenient for shape analysis because, under this representation, a reduced version of the general elastic metric becomes the simple \ensuremathL2\ensuremathL2 metric. Thus, this transformation greatly simplifies the implementation of our framework. We validate our approach using multiple shape analysis examples for quadrilateral and spherical surfaces. We also compare the current results with those of Kurtek et al. [1]. We show that the proposed method results in more natural shape matchings, and furthermore, has some theoretical advantages over previous methods
Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras
Divergence-Free Motion Estimation

International audienceThis paper describes an innovative approach to estimate motion from image observations of divergence-free flows. Unlike most state-of-the-art methods, which only minimize the divergence of the motion field, our approach utilizes the vorticity-velocity formalism in order to construct a motion field in the subspace of divergence free functions. A 4DVAR-like image assimilation method is used to generate an estimate of the vorticity field given image observations. Given that vorticity estimate, the motion is obtained solving the Poisson equation. Results are illustrated on synthetic image observations and compared to those obtained with state-of-the-art methods, in order to quantify the improvements brought by the presented approach. The method is then applied to ocean satellite data to demonstrate its performance on the real images