pinecone/core-2020-05-10-deduplication huggingface dataset:
Real-time lattice boltzmann shallow waters method for breaking wave simulations

We present a new approach for the simulation of surfacebased fluids based in a hybrid formulation of Lattice Boltzmann Method for Shallow Waters and particle systems. The modified LBM can handle arbitrary underlying terrain conditions and arbitrary fluid depth. It also introduces a novel method for tracking dry-wet regions and moving boundaries. Dynamic rigid bodies are also included in our simulations using a two-way coupling. Certain features of the simulation that the LBM can not handle because of its heightfield nature, as breaking waves, are detected and automatically turned into splash particles. Here we use a ballistic particle system, but our hybrid method can handle more complex systems as SPH. Both the LBM and particle systems are implemented in CUDA, although dynamic rigid bodies are simulated in CPU. We show the effectiveness of our method with various examples which achieve real-time on consumer-level hardware.Peer ReviewedPostprint (author's final draft
Xtru3D: Single-View 3D Object Reconstruction from Color and Depth Data

D object reconstruction from single image has been a noticeable research trend in recent years. The most common method is to rely on symmetries of real-life objects, but these are hard to compute in practice. However, a large class of everyday objects, especially when manufactured, can be generated by extruding a 2D shape through an extrusion axis. This paper proposes to exploit this property to acquire 3D object models using a single RGB+Depth image, such as those provided by available low-cost range cameras. It estimates the hidden parts by exploiting the geometrical properties of everyday objects, and both depth and color information are combined to refine the model of the object of interest. Experimental results on a set of 12 common objects are shown to demonstrate not only the effectiveness and simplicity of our approach, but also its applicability for tasks such as robotic grasping.The research leading to these results has been funded by the HANDLE European project (FP7/2007-2013) under grant agreement ICT 231640-http://www.handle-project.eu.Publicad
Data-aware picking for medical models

Medical doctors are often faced with the problem of selecting anchoring points in 3D space. These points are commonly used for measurement tasks, such as lengths of bones, or dimensions of pathological structures (e.g. tumours). Since previous research indicates that measurement tasks can be usually carried out more efficiently in VR environments than in desktop-based systems, we have concentrated on the development of selection tools for medical models. These models have a set of particularities such as the presence of semi-transparencies, and there is a lack of tools for measurement support for such models in VR environments. Our VR-based interaction technique uses the data to automatically generate candidate anchor points, and it is specially focused on the efficient selection of 3D points in datasets rendered using methods with semi-transparency such as Direct Volume Rendering. We will show that our method is effective, precise, and reduces the time and amount of movements required to set the anchor points as compared with other classical techniques based on clipping planes. We also provide a couple of improvements tailored to reduce the inherent imprecision of 3D devices due to hand vibration, and the flexibility in transfer function selection for anchor point definition.Peer ReviewedPostprint (author’s final draft
Enabling informed decision making through mobile technologies: A challenge for software engineering

The potential of mobile technologies is not fully exploited by current software services. One of the most influencing reasons for this problem is the lack of novel software engineering methods and tools that can master the complexity of mobile environments. Looking at a person in a smart environment, where mobile technologies and sensors are installed to support daily activities, it is observed that informed decision-making with the help of mobile technologies is beyond what users can expect from current software services. In this paper we present a motivating scenario to highlight the limitations of current decision support approaches. Based on this discussion we identify significant software engineering challenges, which currently hinder the realization of advanced decision support. In our research we have developed an initial version of a comprehensive framework that allows overcoming the challenges identified. It furthermore highlights which software engineering research lines may help to realize this vision.Peer ReviewedPostprint (author’s final draft
Assuring dependability of software reuse: An industrial standard

Whereas a software component may be perfectly suited to one application, it may prove to cause severe faults in other applications. The prestandard IEC/PAS 62814 (Dependability of Software Products Containing Reusable Components – Guidance for Functionality and Tests), which has recently been released, addresses the functionality, testing, and dependability of software components to be reused and products that contain software to be used in more than one application; that is, reused by the same or by another development organization, regardless of whether it belongs to the same or another legal entity than the one that has developed this software. This paper introduces into this pre-standard and give hints how to use it. The author, who chaired its realization that started in 2006, briefly summarizes the difficult process to bring the industrial partners with controversial interests to a consensus
Planet formation in Binaries

Spurred by the discovery of numerous exoplanets in multiple systems, binaries
have become in recent years one of the main topics in planet formation
research. Numerous studies have investigated to what extent the presence of a
stellar companion can affect the planet formation process. Such studies have
implications that can reach beyond the sole context of binaries, as they allow
to test certain aspects of the planet formation scenario by submitting them to
extreme environments. We review here the current understanding on this complex
problem. We show in particular how each of the different stages of the
planet-formation process is affected differently by binary perturbations. We
focus especially on the intermediate stage of kilometre-sized planetesimal
accretion, which has proven to be the most sensitive to binarity and for which
the presence of some exoplanets observed in tight binaries is difficult to
explain by in-situ formation following the "standard" planet-formation
scenario. Some tentative solutions to this apparent paradox are presented. The
last part of our review presents a thorough description of the problem of
planet habitability, for which the binary environment creates a complex
situation because of the presence of two irradation sources of varying
distance.Comment: Review chapter to appear in "Planetary Exploration and Science:
  Recent Advances and Applications", eds. S. Jin, N. Haghighipour, W.-H. Ip,
  Springer (v2, numerous typos corrected
Automatically Adjusting Concurrency to the Level of Synchrony

International audienceThe state machine approach is a well-known technique for building distributed services requiring high performance and high availability, by replicating servers, and by coordinating client interactions with server replicas using consensus. Indulgent consensus algorithms exist for realistic eventually partially synchronous models, that never violate safety and guarantee liveness once the system becomes synchronous. Unavoidably, these algorithms may never terminate, even when no processor crashes, if the system never becomes synchronous. This paper proposes a mechanism similar to state machine replication, called RC-simulation, that can always make progress, even if the system is never synchronous. Using RC-simulation, the quality of the service will adjust to the current level of asynchrony of the network --- degrading when the system is very asynchronous, and improving when the system becomes more synchronous. RC-simulation generalizes the state machine approach in the following sense: when the system is asynchronous, the system behaves as if k+1 threads were running concurrently, where k is a function of the asynchrony. In order to illustrate how the RC-simulation can be used, we describe a long-lived renaming implementation. By reducing the concurrency down to the asynchrony of the system, RC-simulation enables to obtain a renaming quality that adapts linearly to the asynchrony
On Streaming and Communication Complexity of the Set Cover Problem

We develop the first streaming algorithm and the first two-party communication protocol that uses a constant number of passes/rounds and sublinear space/communication for logarithmic approximation to the classic Set Cover problem. Specifically, for n elements and m sets, our algorithm/protocol achieves a space bound of O(m ·n [superscript δ] log[superscript 2] n logm) using O(4[superscript 1/δ]) passes/rounds while achieving an approximation factor of O(4[superscript 1/δ]logn) in polynomial time (for δ = Ω(1/logn)). If we allow the algorithm/protocol to spend exponential time per pass/round, we achieve an approximation factor of O(4[superscript 1/δ]). Our approach uses randomization, which we show is necessary: no deterministic constant approximation is possible (even given exponential time) using o(m n) space. These results are some of the first on streaming algorithms and efficient two-party communication protocols for approximation algorithms. Moreover, we show that our algorithm can be applied to multi-party communication model.National Science Foundation (U.S.) (Grant CCF-1161626)National Science Foundation (U.S.) (Grant CCF-1065125)United States. Defense Advanced Research Projects Agency (United States. Air Force Office of Scientific Research Grant FA9550-12-1-0423)David & Lucile Packard FoundationSimons FoundationDanish National Research Foundation. Center for Massiave Data Algorithmics (MADALGO
Shape Reconstruction from Apparent Contours. Theory and Algorithms

Motivated by a variational model concerning the depth of the objects in a picture and the problem of hidden and illusory contours, this book investigates one of the central problems of computer vision: the  topological and algorithmic reconstruction of a smooth three dimensional scene starting from the visible part of an apparent contour.\ud
The authors focus their attention on the manipulation of apparent contours using a finite set of elementary moves, which correspond to diffeomorphic deformations of three dimensional scenes.\ud
A large part of the book is devoted to the  algorithmic part, with implementations, experiments, and computed examples. The book is intended also as a user's guide to the software code appcontour, written for the manipulation of apparent contours and their invariants. This book is addressed to theoretical and applied scientists working in the field of mathematical models of image segmentation
Assessing the kinect’s capabilities to perform a time-based clinical test for fall risk assessment in older people

The Choice Stepping Reaction Time (CSRT) task is time-based clinical test that has shown to reliably predict falls in older adults. Its current mode of delivery involves the use of a custom-made dance mat device. This mat is a measurement tool that can reliably obtain step data to discriminate between fallers and non-fallers. One of the pitfalls of this test is that the technology in use still imposes an obstacle on the degree of freedom to be able to perform adaptive exercises suitable for the elderly. In this paper, we describe a Kinect-based system that measures stepping performance through the use of a hybrid version of the CSRT task. This study focuses on assessing this system’s capabilities to reliably measure a time-based clinical test of fall risk. Results showed a favorable correspondence and agreement between the two systems, suggesting that this platform could be potentially useful in the clinical practice
Personas versus clones for player decision modelling

The current paper investigates how to model human play styles. Building on decision and persona theory we evolve game playing agents representing human decision making styles. Two methods are developed, applied, and compared: procedural personas, based on utilities designed with expert knowledge, and clones, trained to reproduce play traces. Additionally, two metrics for comparing agent and human decision making styles are proposed and compared. Results indicate that personas evolved from designer intuitions can capture human decision making styles equally well as clones evolved from human play traces.peer-reviewe
The Active Use of Online Presence, Movies and Gameplay to Improve Classroom Engagement

The online world is filled with rich interactive games, spaces, motion pictures and personas. Despite a rapid growth in online education, the tertiary classroom looks quite different to the entertaining online world it exists within. The design of mobile online resources, both official and unofficial, plays a key role in student engagement and learning. From the teachers perspective designing an online presence and in particular engaging online learning resources, is critical to the success of the learning environment. This project looked at the use of popular forms of online materials, including gameplay, movies and social media, and whether the application of entertainment centered tools enhanced the learning environment. The results of the 9 year, 984 participant study indicate that the increased and active use of the entertainment based tools had a significant positive effect in terms of student engagement and a significant positive effect on learning outcomes for international students.Arts, Education & Law Group, Queensland College of ArtFull Tex
An Effective Heuristic for Adaptive Importance Splitting in Statistical Model Checking

International audienceStatistical model checking avoids the intractable growth of states associated with numerical model checking by estimating the prob-ability of a property from simulations. Rare properties pose a challenge because the relative error of the estimate is unbounded. In [13] we de-scribe how importance splitting may be used with SMC to overcome this problem. The basic idea is to decompose a logical property into nested properties whose probabilities are easier to estimate. To improve perfor-mance it is desirable to decompose the property into many equi-probable levels, but logical decomposition alone may be too coarse. In this article we make use of the notion of a score function to improve the granularity of a logical property. We show that such a score function may take advantage of heuristics, so long as it also rigorously respects certain properties. To demonstrate our importance splitting approach we present an optimal adaptive importance splitting algorithm and an heuristic score function. We give experimental results that demonstrate a significant improvement in performance over alternative approaches
A Formalism for Stochastic Adaptive Systems

International audienceComplex systems such as systems of systems result from the combination of several components that are organized in a hierarchical manner. One of the main characteristics of those systems is their ability to adapt to new situations by modifying their architecture. Those sys-tems have recently been the subject of a series of works in the software engineering community. Most of those works do not consider quantitative features. The objective of this paper is to propose a modeling language for adaptive systems whose behaviors depend on stochastic features. Our language relies on an extension of stochastic transition systems equipped with (1) an adaptive operator that allows to reason about the probability that a system has to adapt its architecture over time, and (2) dynamic interactions between processes. As a second contribution, we propose a contract-based extension of probabilistic linear temporal logic suited to reason about assumptions and guarantees of such systems. Our work has been implemented in the Plasma-Lab tool developed at Inria. This tool allows us to define stochastic adaptive systems with an extension of the Prism language, and properties with patterns. In addition, Plasma-Lab offers a simulation-based model checking procedure to reason about finite executions of the system. First experiments on a large case study coming from an industrial driven European project give encouraging results
Modelling and Verifying an Evolving Distributed Control System Using an Event-Based Approach

International audienceEvolving distributed systems are made of several physical devices distributed through a network and a set of functionalities or ap-plications hosted by the physical devices. The configuration of the phys-ical components may be modified through the time, hence the continu-ous evolving of the whole system. This should affect neither the hosted software components nor the global functionning of the whole system. The components of the systems are software components or physical components but their abstract models are considered with the aim of modelling and reasoning. We show that an event-based approach can be benefically used to model and verify this kind of evolving control sys-tems. The proposed approach is first presented, then the CCTV case study is introduced and modelled. The resulting model is structured as a B abstract machine. The functional properties of the case study are captured, modelled and proved. The refinement technique of Event-B is used to introduce and prove some properties
Static Inference of Transmission Data Sizes\ud
in Distributed Systems

We present a static analysis to infer the amount of data that a distributed system may ransmit. The different locations of a distributed system communicate and coordinate their actions by posting tasks among them. A task is posted by building a message with the task name and the data on which such task has to be executed. When the task completes, the result can be retrieved by means of another message from which the result of the computation can be obtained. Thus, the transmission data size of a distributed system mainly depends on the amount of messages posted among the locations of the system, and the sizes of the data transferred in the messages. Our static analysis has two main parts: (1) we over-approximate the sizes of the data at the program points where tasks are spawned and where the results are received, and (2) we over-approximate the total number of messages. Knowledge of the transmission data sizes is essential, among other things, to predict the bandwidth required to achieve a certain response time, or conversely, to estimate the response time for a given bandwidth. A prototype implementation in the SACO system demonstrates the accuracy and feasibility of the proposed analysis
Statistical Abstraction Boosts Design and Test Efficiency of Evolving Critical Systems

International audienceMonte Carlo simulations may be used to efficiently estimate critical properties of complex evolving systems but are nevertheless computationally intensive. Hence, when only part of a system is new or modified it seems wasteful to re-simulate the parts that have not changed. It also seems unnecessary to perform many simulations of parts of a system whose behaviour does not vary significantly. To increase the efficiency of designing and testing complex evolving systems we present simulation techniques to allow such a system to be verified against behaviourpreserving statistical abstractions of its environment. We propose a frequency domain metric to judge the a priori performance of an abstraction and provide an a posteriori indicator to aid construction of abstractions optimised for critical properties
Domain Specific Languages for Managing Feature Models: Advances and Challenges

International audienceManaging multiple and complex feature models is a tedious and error-prone activity in software product line engineering. Despite many advances in formal methods and analysis techniques, the supporting tools and APIs are not easily usable together, nor unified. In this paper, we report on the development and evolution of the Familiar Domain-Specific Language (DSL). Its toolset is dedicated to the large scale management of feature models through a good support for separating concerns, composing feature models and scripting manipulations. We overview various applications of Familiar and discuss both advantages and identified drawbacks. We then devise salient challenges to improve such DSL support in the near future
Domain-Specific Code Generator Modeling: A Case Study for Multi-faceted Concurrent Systems

International audienceIn this paper we discuss an elaborate case study utilizing the domain-specific development of code generators within the Cinco meta tooling suite. Cinco is a framework that allows for the automatic generation of a wide range of graphical modeling tools from an abstract high-level specification. The presented case study makes use of Cinco to rapidly construct custom graphical interfaces for multi-faceted, concur-rent systems, comprising non-functional properties like time, probability, data, and costs. The point of this approach is to provide user commu-nities and their favorite tools with graphical interfaces tailored to their specific needs. This will be illustrated by generating graphical interfaces for timed automata (TA), probabilistic timed automata (PTA), Markov decision processes (MDP) and simple labeled transition systems (LTS). The main contribution of the presented work, however, is the metamodel-based domain-specific construction of the corresponding code generators for the verification tools Uppaal, Spin, PLASMA-lab, and Prism
(1)-D Shallow Water Models for Dam Break Flash Floods with Different Junction and Bend Treatments

<Book Title> AsiaSim 2014Recently-developed Finite Element/Volume Methods for the cross-sectionally averaged 1-D shallow water equations in open channel networks are applied to idealized and real cases of dam break flash floods for their examination on robustness and versatility. The major differences among the schemes are the treatments of junctions and bends in the momentum equation as the internal boundary conditions. The computational results show robustness of the schemes. The results also show critical influences of the internal boundary conditions on the water surface profiles and flood arrival times, indicating that a necessary ingredient for their successful prediction is evaluation of the momentum flux with appropriately considering the channel configurations