pinecone/core-2020-05-10-deduplication huggingface dataset:
PolyLARVA : runtime verification with configurable resource-aware monitoring boundaries

Runtime verification techniques are increasingly being applied in industry as a lightweight formal approach to achieve added assurance of correctness at runtime. A key issue determining the adoption of these techniques is the\ud
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 overheads introduced by the runtime checks, affecting the performances of the\ud
 monitored systems. Despite advancements in the development of optimisation\ud
 techniques lowering these overheads, industrial settings such as online portals\ud
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 present new challenges, since they frequently involve the handling of high volume transaction throughputs and cannot afford substantial deterioration in the\ud
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 service they provide.\ud
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 One approach to reduce overheads is the deployment of the verification computation on auxiliary computing resources, creating a boundary between the system\ud
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 and the verification code. This limits the use of system resources with resource\ud
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 intensive verification being carried out on the remote-side. However, under particular scenarios this approach may still not be ideal, as it may induce significant communication overheads. In this paper, we propose a framework which\ud
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 enables fine-tuning of the tradeoff between processing, memory and communication monitoring overheads, through the use of a user-configurable monitoring\ud
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 boundary. This approach has been implemented in the second generation of the\ud
 LARVA runtime verification tool, polyLARVA.peer-reviewe
Schr\"{o}dinger Diffusion for Shape Analysis with Texture

In recent years, quantities derived from the heat equation have become
popular in shape processing and analysis of triangulated surfaces. Such
measures are often robust with respect to different kinds of perturbations,
including near-isometries, topological noise and partialities. Here, we propose
to exploit the semigroup of a Schr\"{o}dinger operator in order to deal with
texture data, while maintaining the desirable properties of the heat kernel. We
define a family of Schr\"{o}dinger diffusion distances analogous to the ones
associated to the heat kernels, and show that they are continuous under
perturbations of the data. As an application, we introduce a method for
retrieval of textured shapes through comparison of Schr\"{o}dinger diffusion
distance histograms with the earth's mover distance, and present some numerical
experiments showing superior performance compared to an analogous method that
ignores the texture.Comment: Extended version of NORDIA'12 paper. Includes one more figure and
  appendix with proo
Anchored deformable face ensemble alignment

At present, many approaches have been proposed for deformable face alignment with varying degrees of success. However, the common drawback to nearly all these approaches is the inaccurate landmark registrations. The registration errors which occur are predominantly heterogeneous (i.e. low error for some frames in a sequence and higher error for others). In this paper we propose an approach for simultaneously aligning an ensemble of deformable face images stemming from the same subject given noisy heterogeneous landmark estimates. We propose that these initial noisy landmark estimates can be used as an “anchor” in conjunction with known state-of-the-art objectives for unsupervised image ensemble alignment. Impressive alignment performance is obtained using well known deformable face fitting algorithms as “anchors
Uzawa Block Relaxation Methods for Color Image Restoration

International audienceIn this paper we propose to investigate the use of a vectorial total variation model with spatially varying regularization and data terms for color image denoising and restoration. We pay attention to two main minimization problems: the minimization of a weighted vectorial total variation term TVg , which acts as a regularization term, using the L2 norm as data term or the minimization of the vectorial total variation with a spatially varying L1g norm. The optimization process takes benefit of convex optimization tools by introducing an augmented Lagrangian formulation. This formulation leads us to simple and efficient algorithms based on Uzawa block relaxation schemes that are also robust towards the choice of the penalty parameter. In this paper, We propose to study more particularly the impact of spatially varying terms (total variation term or data terms) for color image restoration. A new weighted total variation term is proposed for old parchments restoration and we also compare the use of a weighted total variation term with a spatially varying data term for impulse noise removal in color images
A Knowledge-Based Approach to Augment Applications with Interaction Traces

International audienceThis paper presents a trace-based framework for assisting personalization and enrichment of end-user experience in an application. We propose a modular ontology-based architecture, to provide semantics for interaction traces, observed elements and their associated objects, and we extend existing inference services, with a declarative and generic approach, in order to reason with those interaction traces. We present the architecture of our framework and its reasoning levels, provide a proof of concept on a medical Web application, and emphasize that different kinds of actors can benefit from the supported inferences
Hierarchical Late Fusion for Concept Detection in Videos

Oral session 1: WS21 - Workshop on Information Fusion in Computer Vision for Concept RecognitionInternational audienceWe deal with the issue of combining dozens of classifiers into a better one, for concept detection in videos. We compare three fusion approaches that share a common structure: they all start with a classifier clustering stage, continue with an intra-cluster fusion and end with an inter-cluster fusion. The main difference between them comes from the first stage. The first approach relies on a priori knowledge about the internals of each classifier (low-level descriptors and classification algorithm) to group the set of available classifiers by similarity. The second and third approaches obtain classifier similarity measures directly from their output and group them using agglomerative clustering for the second approach and community detection for the third one
Unsupervised classemes

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33885-4_41Proceedings of Information Fusion in Computer Vision for Concept Recognition at the ECCV 2012In this paper we present a new model of semantic features that, unlike previously presented methods, does not rely on the presence of a labeled training data base, as the creation of the feature extraction function is done in an unsupervised manner.

We test these features on an unsupervised classification (clustering) task, and show that they outperform primitive (low-level) features, and that have performance comparable to that of supervised semantic features, which are much more expensive to determine relying on the presence of a labeled training set to train the feature extraction function
Exploring failures at the team level in offshore-outsourced software development projects

Offshore-outsourced software development (OOSD) projects involvemultifaceted risks throughout the project execution, as they are handed over tothird-party organizations and thus are exposed to more risks than in domesticoutsourcing or captive offshoring. We concentrate on failed OOSD projects inthis paper and analyze the unique aspects of such projects at the team level thatlead to failures. Using the grounded theory approach, we conducted semistructuredinterviews with 19 project managers involved in OOSD projectfailures from the vendor and client sides, who are based in India or Switzerland.We developed a set of propositions regarding multiple teams in the OOSDproject context to explain failures. Integration of inter-organizational offshoreand onshore teams from the vendor and client sides was found to beindispensable in avoiding project failures. Six categories of unique aspects thatlead to OOSD project failures were identified and discussed in this exploratorywork
Kinect enabled Monte Carlo localisation for a robotic wheelchair

Proximity sensors and 2D vision methods have shown to work robustly in particle filter-based Monte Carlo Localisation (MCL). It would be interesting however to examine whether modern 3D vision sensors would be equally efficient for localising a robotic wheelchair with MCL. In this work, we introduce a visual Region Locator Descriptor, acquired from a 3D map using the Kinect sensor to conduct localisation. The descriptor segments the Kinect's depth map into a grid of 36 regions, where the depth of each column-cell is being used as a distance range for the measurement model of a particle filter. The experimental work concentrated on a comparison of three different localization cases. (a) an odometry model without MCL, (b) with MCL and sonar sensors only, (c) with MCL and the Kinect sensor only. The comparative study demonstrated the efficiency of a modern 3D depth sensor, such as the Kinect, which can be used reliably for wheelchair localisation. © 2013 Springer-Verlag
Timed trajectory generation combined with an Extended Kalman Filter for a vision-based autonomous mobile robot

Series : Advances in intelligent systems and computing, vol. 193, ISSN 2194-5357Planning collision-free trajectories requires the combination of generation and modulation techniques. This is especially important if temporal stabilization of the generated trajectories is considered. Temporal stabilization means to conform to the planned movement time, in spite of environmental conditions or perturbations. This timing problem has not been addressed in most current robotic systems, and it is critical in several robotic tasks such as sequentially structured actions or human-robot interaction. This work focuses on generating trajectories for a mobile robot, whose goal is to reach a target within a constant time, independently of the world complexity. Trajectories are generated by nonlinear dynamical systems. Herein, we extend our previous work by including an Extended Kalman Filter (EKF) to estimate the target location relative to the robot. A simulated hospital environment and a Pioneer 3-AT robot are used to demonstrate the robustness and reliability of the proposed approach in cluttered, dynamic and uncontrolled scenarios. Multiple experiments confirm that the inclusion of the EKF preserves the timing properties of the overall architecture.Work supported by the Portuguese Science Foundation (grant PTDC/EEA-CRO/100655/2008), and by project FCT PEst-OE/EEI/LA0009/2011. Jorge B. Silva is supported by PhD Grant SFRH/BD/68805/2010, granted by the Portuguese Science Foundation
Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robots ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMPbased platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation faul
Feedback Control of Traffic Signal Network of Less Traffic Sensors by Help of Machine Learning

doi: 10.1007/978-3-642-33932-5_81As a way of resolving vehicle congestion, there is a feedback control approach which models a traffic network as a discrete dynamical system and derives feedback gain for controlling green light times of each junction. Since the input is the sensory observed traffic flow of each link, and since the state equation models both the topology and the parameters of the network, it is effective for adaptive control of a wide area traffic in real-time. One of the essential factors in a state equation is the vehicles’ turning ratio at each junction. However, in a normal traffic sensor layout, it is impossible to directly measure this value in real-time, and values from traffic census are used. This paper is to propose a method that predicts this value in real-time through machine learning and gives more appropriate feedback control. Out idea is to find the turning ratio through probabilistic search by Reinforcement Learning referring to the degree of improvement of the entire traffic flow. At this moment we have finished formulation of the scheme and the verification for the performance by a traffic simulator is on the way
A web-based filtering engine for understanding event specifications in large conceptual schemas

A complete conceptual schema must include all relevant general static and dynamic aspects of an information system. Event types
describe a nonempty set of allowed changes in the population of entity or relationship types in the domain of the conceptual schema. The conceptual schemas of many real-world information systems that include
the speci cation of event types are too large to be easily managed or understood. There are many information system development activities in which people need to understand the eff ect of a set of events. We
present an information  filtering tool in which a user focuses on one or more event types of interest for her task at hand, and the tool automatically  filters the schema in order to obtain a reduced conceptual schema
that illustrates all the elements affected by the given events.Peer ReviewedPreprin
Requirement-driven creation and deployment of multidimensional and ETL designs

We present our tool for assisting designers in the error-prone and time-consuming tasks carried out at the early stages of a data warehousing project. Our tool semi-automatically produces multidimensional (MD) and ETL conceptual designs from a given set of business requirements (like SLAs) and data source descriptions. Subsequently, our tool translates both the MD and ETL conceptual designs  produced  into  physical  designs, so they can be further  deployed on a DBMS and an ETL engine. In this paper, we describe the system architecture and present our demonstration proposal by means of an example.Peer ReviewedPostprint (author's final draft
Specialization in i* strategic rationale diagrams

ER 2012 Best Student Paper AwardThe specialization relationship is offered by the  i* modeling language through the  is-a construct defined over actors (a subactor  is-a superactor). Although the overall meaning of this construct is highly intuitive, its semantics when it comes to the fine-grained level of strategic rationale (SR) diagrams is not defined, hampering seriously its appropriate use. In this paper \ud
we provide a formal definition of the specialization relationship at the level of \ud
i* SR diagrams. We root our proposal over existing work in conceptual modeling in general, and object-orientation in particular. Also, we use the results of a survey conducted in the  i* community that provides some hints about what i* modelers expect from specialization. As a consequence of this twofold analysis, we identify, define and specify two specialization operations, \ud
extension and refinement, that can be applied over SR diagrams. Correctness conditions for them are also clearly stated. The result of our work is a formal proposal of specialization for i* that allows its use in a well-defined mannerPeer ReviewedAward-winningPostprint (author’s final draft
Understanding constraint expressions in large conceptual schemas by automatic filtering

Human understanding of constraint expressions (also called schema rules) in large conceptual schemas is very di cult. This is due to the fact that the elements (entity types, attributes, relationship types) involved in an expression are de ned in di fferent places in the schema, which may be very distant from each other and embedded in an intricate web of irrelevant elements. The problem is insignifi cant when the
conceptual schema is small, but very signi cant when it is large. In this paper we describe a novel method that, given a set of constraint expressions and a large conceptual schema, automatically  filters the conceptual schema, obtaining a smaller one that contains the elements of interest for
the understanding of the expressions. We also show the application of the method to the important case of understanding the specication of event types, whose constraint expressions consists of a set of pre and postconditions. We have evaluated the method by means of its application to a set of large conceptual schemas. The results show that the method is eff ective and e cient. We deal with conceptual schemas in UML/OCL,
but the method can be adapted to other languages.Peer ReviewedPreprin
Runtime Verification: The Application Perspective

International audienceIn the past decade, Runtime Verification (RV) has gained much focus, from both the research community and practitioners. RV combines a set of theories, techniques and tools aiming towards efficient analysis of systems' executions and guaranteeing their correctness using monitoring techniques. Major challenges in RV include characterizing and formally expressing requirements that can be monitored, offering intuitive and concise specification formalisms, and monitoring specifications efficiently for functional and non-functional behavior. In spite of the major strides made in recent years, much effort is still needed to make RV an attractive and viable methodology for industrial use and to apply it to wider application domains, such as security, bio-health, power micro-grids. This special issue of STTT proposes extended versions of four papers that have been selected from the Runtime Verification track at ISoLA 2012 [10]
Runtime Verification of Biological Systems

International audienceComplex computational systems are ubiquitous and their study increasingly important. Given the ease with which it is possible to construct large systems with heterogeneous technology, there is strong motivation to provide automated means to verify their safety, efficiency and reliability. In another context, biological systems are supreme examples of complex systems for which there are no design specifications. In both cases it is usually difficult to reason at the level of the description of the systems and much more convenient to investigate properties of their executions. To demonstrate runtime verification of complex systems we apply statistical model checking techniques to a model of robust biological oscillations taken from the literature. The model demonstrates some of the mechanisms used by biological systems to maintain reliable performance in the face of inherent stochasticity and is therefore instructive. To perform our investigation we use two recently developed SMC platforms: that incorporated in Uppaal and Plasma. Uppaalsmc offers a generic modeling language based on stochastic hybrid automata, while Plasma aims at domain specific support with the facility to accept biological models represented in chemical syntax
On the (in)security of IDEA in various hashing modes

In this article, we study the security of the IDEA block cipher when it is used in various simple-length or double-length hashing modes. Even though this cipher is still considered as secure, we show that one should avoid its use as internal primitive for block cipher based hashing. In particular, we are able to generate instantaneously free-start collisions for most modes, and even semi-free-start collisions, pseudo-preimages or hash collisions in practical complexity. This work shows a practical example of the gap that exists between secret-key and known or chosen-key security for block ciphers. Moreover, we also settle the 20-year-old standing open question concerning the security of the Abreast-DM and Tandem-DM double-length compression functions, originally invented to be instantiated with IDEA. Our attacks have been verified experimentally and work even for strengthened versions of IDEA with any number of rounds
Evaluation of Microsimulated Traffic Light Optimisation Using V2I Technology

Within the research project KOLINE a cooperative system for urban road transport is developed. Its traffic related goals are to reduce travel time and fuel consumption as well as noise and pollutant emissions. The herein described evaluation shall determine whether, to which extent and how economically the KOLINE system is able to address these goals. Three differently comprehensive quantifying evaluation procedures are applied to the outputs of a microscopic traffic simulation. Thus not only the ranking of all scenarios, but also comparisons between these procedures become possible