Approximation of Pore Space with Ellipsoids: A Comparison of a Geometrical Method with a Statistical one

We work with tomographic images of pore space in soil. The images have large dimensions and so in order to speed-up biological simulations (as drainage or diffusion process in soil), we want to describe the pore space with a number of geometrical primitives significantly smaller than the number of voxels in pore space. In this paper, we use the curve skeleton of a volume to segment it into some regions. We describe the method to compute the curve skeleton and to segment it with a simple segment approximation. We approximate each obtained region with an ellipsoid. The set of final ellipsoids represents the geometry of pore space and will be used in future simulations. We compare this method …

Ontology-based state representations for intention recognition in human–robot collaborative environments

In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level state relationships that must be true for future actions to occur, a robot can use the detailed state information described in this paper to infer the probability of subsequent actions occurring. This would allow the robot to better help the …

Study of ambient light influence for three-dimensional scanners based on structured light

Ambient light in a scene can introduce errors into range data from most commercial three-dimensional range scanners, particularly scanners that are based on projected patterns and structured lighting. We study the effects of ambient light on a specific commercial scanner. We further present a method for characterizing the range accuracy as a function of ambient light distortions. After a brief review of related research, we first describe the capabilities of the scanner we used and define the experimental setup for our study. Then we present the results of the range characterization relative to ambient light. In these results, we note a systematic error source that appears to be an artifact…

A methodology for the semi-automatic generation of analytical models in manufacturing

International audience; Advanced analytics can enable manufacturing engineers to improve product quality and achieve equipment and resource efficiency gains using large amounts of data collected during manufacturing. Manufacturing engineers, however, often lack the expertise to apply advanced analytics, relying instead on frequent consultations with data scientists. Furthermore, collaborations between manufacturing engineers and data scientists have resulted in highly specialized applications that are not relevant to broader use cases. The manufacturing industry can benefit from the techniques applied in these collaborations if they can be generalized for a wide range of manufacturing probl…

PTNet: An efficient and green data center network

International audience; In recent years, data centers have witnessed an exponential growth for hosting hundreds of thousands of servers as well as to accommodating a very large demand for resources. To fulfill the required level of demand, some approaches tackled network aspects so to host a huge number of servers while others focused on delivering rapid services to the clients by minimizing the path length between any two servers. In general, network devices are often designed to achieve 1:1 oversubscription. Alternatively, in a realistic data center environment, the average utilization of a network could vary between 5% and 25%, and thus the energy consumed by idle devices is wasted. This…

Denoising 3D Models with Attributes using Soft Thresholding

International audience; Recent advances in scanning and acquisition technologies allow the construction of complex models from real world scenes. However, the data of those models are generally corrupted by measurement errors. This paper describes an efficient single pass algorithm for denoising irregular meshes of scanned 3D model surfaces. In this algorithm, the frequency content of the model is assessed by a multiresolution analysis that requires only 1-ring neighbourhood without any particular parameterization of the model faces. Denoising is achieved by applying the soft thresholding method to the detail coefficients given by the multiresolution analysis. Our method is suitable for irr…

Geometric constraint solving: The witness configuration method

Geometric constraint solving is a key issue in CAD, CAM and PLM. The systems of geometric constraints are today studied and decomposed with graph-based methods, before their numerical resolution. However, graph-based methods can detect only the simplest (called structural) dependences between constraints; they cannot detect subtle dependences due to theorems. To overcome these limitations, this paper proposes a new method: the system is studied (with linear algebra tools) at a witness configuration, which is intuitively similar to the unknown one, and easy to compute.

Gravitational weighted fuzzy c-means with application on multispectral image segmentation

This paper presents a novel clustering approach based on the classic Fuzzy c-means algorithm. The approach is inspired from the concept of interaction between objects in physics. Each data point is regarded as a particle. A specific weight is associated with each data particle depending on its interaction with other particles. This interaction is induced by attraction forces between pairs of particles and the escape velocity from other particles. Classification experiments using two data sets from UCI repository demonstrate the outperformance of the proposed approach over other clustering algorithms. In addition, results demonstrate the effectiveness of the proposed scheme for segmentation …

DEXML: A First Step Toward a UML Based Implementation Framework for PLCS

Data exchange specifications not only must be broad and general to achieve acceptance, but also must be customizable in a controlled and interoperable manner to be useful. The Product Life Cycle Support (PLCS) suite of data exchange specifications (known as DEXs) uses templates to enable controlled customizability without sacrificing breadth or interoperability. DEXs are business context-specific subsets of ISO 10303 Application Protocol (AP) 239, subject to additional constraints imposed by the templates. A PLCS template defines how AP239 entities and their attributes will be instantiated using an externally-defined controlled vocabulary defined in a Reference Data Library. Template instan…

A comparative study of best spectral bands selection systems for face recognition

Multispectral images (MI) have shown promising capabilities to solve problems resulting from high illumination variation in face recognition. However, the use of MI, with the huge number of captured spectral bands for each subject, is impractical unless a system for best spectral bands selection (BSBS) is used. In this work, first we give an up to date overview of the existing BSBS techniques proposed for face recognition. We aim to highlight the imporatnce of this component of MI based systems. The reviewed techniques are then experimented using the multispectral face database IRIS - M3 to compare their performances. To the best of our knowledge this is the first study that reviews and com…

Product lifecycle management support: a challenge in supporting product design and manufacturing in a networked economy

In this paper, we provide an overview of the changing design and manufacturing landscape in the 21st century that has come about because of IT and the changing global conditions. Based on this overview and a review of the current state of IT for PLM support in the design and manufacturing sector, we identify the areas of need for standards. A review of areas covered by standards leads us to the development of an initial typology of standards and a potential path for bringing convergence of these standards in support of PLM. We make a case throughout the paper that given the nature of the task we need to aspire to create open standards with wide participation. We conclude by arguing that the…

On the Impact of Wireless Communications on Controlling a Two-Dimensional Gantry System

Abstract Industrial wireless is essential to achieve the vision of future manufacturing systems which are highly dynamic and reconfigurable, and communicate large amounts of data. Main challenges of wireless deployment include the stochastic nature of the wireless channels and the harsh industrial transmission environment. In this work, a typical two-dimensional gantry system is controlled by a local controller which receives G-code commands wirelessly over a Wi-Fi network. The industrial wireless channel is replicated using a radio frequency (RF) channel emulator where various scenarios are considered and various wireless channel parameters are studied. The movement of the gantry system to…

New Geometric Constraint Solving Formulation: Application to the 3D Pentahedron

Geometric Constraint Solving Problems (GCSP) are nowadays routinely investigated in geometric modeling. The 3D Pentahedron problem is a GCSP defined by the lengths of its edges and the planarity of its quadrilateral faces, yielding to an under-constrained system of twelve equations in eighteen unknowns. In this work, we focus on solving the 3D Pentahedron problem in a more robust and efficient way, through a new formulation that reduces the underlying algebraic formulation to a well-constrained system of three equations in three unknowns, and avoids at the same time the use of placement rules that resolve the under-constrained original formulation. We show that geometric constraints can be …

A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics

We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.

Sparsity-aware narrowband interference mitigation and subcarriers selection in OFDM-based cognitive radio networks

In this paper, the performance of an orthogonal frequency division multiplexing overlay cognitive radio network with subcarrier selection schemes is investigated. We propose three subcarrier selection techniques that reduce the level of interference at the primary base station based on collected channel state information from the different network nodes. Approximated outage probability expressions are also derived and verified by simulations for the different studied techniques. In addition, we propose and investigate a new approach for asynchronous narrowband interference (NBI) estimation and mitigation in cognitive radio networks. The proposed approach does not require prior knowledge of …

Dupin cyclide blends between non-natural quadrics of revolution and concrete shape modeling applications

Abstract In this work, we focus on the blending of two quadrics of revolution by two patches of Dupin cyclides. We propose an algorithm for the blending of non-natural quadrics of revolution by decomposing the blending operation into two complementary sub-blendings, each of which is a Dupin cyclide-based blending between one of the two quadrics and a circular cylinder, thus enabling the direct computation of the two Dupin cyclide patches and offering better flexibility for shape composition. Our approach uses rational quadric Bezier curves to model the relevant arcs of the principal circles of Dupin cyclides. It is quite general and we have successfully used it for the blending of several n…

Relay selection in FDD amplify-and-forward cooperative networks

In this paper, the problems of relay selection and distributed beamforming are investigated for bi-directional dual-hop amplify-and-forward frequency-division duplex cooperative wireless networks. When using individual per-relay maximum transmission power constraint, it has been proven that the relay selection and beamforming optimization problem becomes NP hard and requires exhaustive search to find the optimal solution. Therefore, we propose a computationally affordable sub-optimal multiple relay selection and beamforming optimization scheme based on the l1 norm squared relaxation. The proposed scheme performs the selection for the two transmission directions, simultaneously, while aiming…

A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living

This research aims to describe pattern recognition models for detecting behavioural and health-related changes in a patient who is monitored continuously in an assisted living environment. The early anticipation of anomalies can improve the rate of disease prevention. Here we present different learning techniques for predicting abnormalities and behavioural trends in various user contexts. In this paper we described a Hidden Markov Model based approach for detecting abnormalities in daily activities, a process of identifying irregularity in routine behaviours from statistical histories and an exponential smoothing technique to predict future changes in various vital signs. The outcomes of t…

Optimizing Query Perturbations to Enhance Shape Retrieval

3D Shape retrieval algorithms use shape descriptors to identify shapes in a database that are the most similar to a given key shape, called the query. Many shape descriptors are known but none is perfect. Therefore, the common approach in building 3D Shape retrieval tools is to combine several descriptors with some fusion rule. This article proposes an orthogonal approach. The query is improved with a Genetic Algorithm. The latter makes evolve a population of perturbed copies of the query, called clones. The best clone is the closest to its closest shapes in the database, for a given shape descriptor. Experimental results show that improving the query also improves the precision and complet…

Nonlinear systems solver in floating-point arithmetic using LP reduction

This paper presents a new solver for systems of nonlinear equations. Such systems occur in Geometric Constraint Solving, e.g., when dimensioning parts in CAD-CAM, or when computing the topology of sets defined by nonlinear inequalities. The paper does not consider the problem of decomposing the system and assembling solutions of subsystems. It focuses on the numerical resolution of well-constrained systems. Instead of computing an exponential number of coefficients in the tensorial Bernstein basis, we resort to linear programming for computing range bounds of system equations or domain reductions of system variables. Linear programming is performed on a so called Bernstein polytope: though,…

Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte …

Digital Heritage Enrichment through Artificial Intelligence and SemanticWeb Technologies

Art and culture represent substantial ways to transfer the history of humans across civilizations and epochs. Preserving artwork and cultural objects is thus important and the focus of multiple institutions and governments around the world. Digital preservation in cultural heritage represents a cost-effective and reliable long-term preservation and several challenges related to its effectiveness and its reliability have arisen such as metadata enrichment, digital curation, link discoveries, etc. Through this paper, we discuss these challenges and present innovative ways that leverage recent endeavors in artificial intelligence and semantic web technologies to enrich cultural data. Our contr…

Supershape Recovery from 3D Data Sets

In this paper, we apply supershapes and R-functions to surface recovery from 3D data sets. Individual supershapes are separately recovered from a segmented mesh. R-functions are used to perform Boolean operations between the reconstructed parts to obtain a single implicit equation of the reconstructed object that is used to define a global error reconstruction function. We present surface recovery results ranging from single synthetic data to real complex objects involving the composition of several supershapes and holes.

Evaluating State-Based Intention Recognition Algorithms against Human Performance

In this paper, we describe a novel intention recognition approach based on the representation of state information in a cooperative human-robot environment. We compare the output of the intention recognition algorithms to those of an experiment involving humans attempting to recognize the same intentions in a manufacturing kitting domain. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. Based upon a set of predefined high-level states relationships that must be true for future actions to occur, a robot can use the approaches described in this paper to infer the likelihood of subsequent actions occurring. This wo…

Data structures and algorithms for topological analysis

International audience; One of the steps of geometric modeling is to know the topology and/or the geometry of the objects considered. This paper presents different data structures and algorithms used in this study. We are particularly interested by algebraic structures, eg homotopy and homology groups, the Betti numbers, the Euler characteristic, or the Morse-Smale complex. We have to be able to compute these data structures, and for (homotopy and homology) groups, we also want to compute their generators. We are also interested in algorithms CIA and HIA presented in the thesis of Nicolas DELANOUE, which respectively compute the connected components and the homotopy type of a set defined by…

Surface Reconstruction Based on a Descriptive Approach

The design of complex surfaces is generally hard to achieve. A natural method consists in the subdivision of the global surface into basic surface elements. The different elements are independently designed and then assembled together to represent the final surface. This method requires a classification and a formal description of the basic elements. This chapter presents a general framework for surface description, based on a constructive tree approach. In this tree the leaves are surface primitives and the nodes are constructive operators.

Fuzzy Distributed Genetic Approaches for Image Segmentation

This paper presents a new image segmentation algorithm (called FDGA-Seg) based on a combination of fuzzy logic, multiagent systems and genetic algorithms. We propose to use a fuzzy representation of the image site labels by introducing some imprecision in the gray tones values. The distributivity of FDGA-Seg comes from the fact that it is designed around a MultiAgent System (MAS) working with two different architectures based on the master-slave and island models. A rich set of experimental segmentation results given by FDGA-Seg is discussed and compared to the ICM results in the last section.

The Bernstein Basis and its applications in solving geometric constraint systems

International audience; This article reviews the properties of Tensorial Bernstein Basis (TBB) and its usage, with interval analysis, for solving systems of nonlinear, univariate or multivariate equations resulting from geometric constraints. TBB are routinely used in computerized geometry for geometric modelling in CAD-CAM, or in computer graphics. They provide sharp enclosures of polynomials and their derivatives. They are used to reduce domains while preserving roots of polynomial systems, to prove that domains do not contain roots, and to make existence and uniqueness tests. They are compatible with standard preconditioning methods and fit linear program- ming techniques. However, curre…

Robustness and Randomness

The study of robustness problems for computational geometry algorithms is a topic that has been subject to intensive research efforts from both computer science and mathematics communities. Robustness problems are caused by the lack of precision in computations involving floating-point instead of real numbers. This paper reviews methods dealing with robustness and inaccuracy problems. It discusses approaches based on exact arithmetic, interval arithmetic and probabilistic methods. The paper investigates the possibility to use randomness at certain levels of reasoning to make geometric constructions more robust.

A survey on data center network topologies

Data centers are the infrastructures that support the cloud computing services. So, their topologies have an important role on controlling the performance of these services. Designing an efficient topology with a high scalability and a good network performance is one of the most important challenges in data centers. This paper surveys recent research advances linked to data center network topologies. We review some representative topologies and discuss their proprieties in details. We compare them in terms of average path length, network fault tolerance, scalability and connection pattern techniques. Springer Nature Switzerland AG 2018. Acknowledgment. This publication was made possible by …

Wireless Interference Estimation Using Machine Learning in a Robotic Force-Seeking Scenario

Cyber-physical systems are systems governed by the laws of physics that are tightly controlled by computer-based algorithms and network-based sensing and actuation. Wireless communication technology is envisioned to play a primary role in conducting the information flows within such systems. A practical industrial wireless use case involving a robot manipulator control system, an integrated wireless force-torque sensor, and a remote vision-based observer is constructed and the performance of the cyber-physical system is examined. By using readings from the remote observer, an estimation system is developed using machine learning regression techniques. We demonstrate the practicality of comb…

Towards a Hierarchical Multitask Classification Framework for Cultural Heritage

Digital technologies such as 3D imaging, data analytics and computer vision opened the door to a large set of applications in cultural heritage. Digital acquisition of a cultural assets takes nowadays a couple of seconds thanks to the achievements in 2D and 3D acquisition technologies. However, enriching these cultural assets with labels and relevant metadata is still not fully automatized especially due to their nature and specificities. With the recent publication of several cultural heritage datasets, many researchers are tackling the challenge of effectively classifying and annotating digital heritage. The challenges that are often addressed are related to visual recognition and image c…

A Cost-Effective 3D Acquisition and Visualization Framework for Cultural Heritage

Museums and cultural institutions, in general, are in a constant challenge of adding more value to their collections. The attractiveness of assets is practically tightly related to their value obeying the offer and demand law. New digital visualization technologies are found to give more excitements, especially to the younger generation as it is proven by multiple studies. Nowadays, museums around the world are currently trying to promote their collections through new multimedia and digital technologies such as 3D modeling, virtual reality (VR), augmented reality (AR), and serious games. However, the difficulty and the resources required to implement such technologies present a real challen…

Dynamic best spectral bands selection for face recognition

In this paper, face recognition in uncontrolled illumination conditions is investigated. A twofold contribution is proposed. First, three state-of-art algorithms, namely Multiblock Local Binary Pattern (MBLBP), Histogram of Gabor Phase Patterns (HGPP) and Local Gabor Binary Pattern Histogram Sequence (LGBPHS) are evaluated upon the IRIS-M3 face database to study their robustness against a high illumination variation conditions. Second, we propose to use visible multispectral images, provided by the same face database, to enhance the performance of the three mentioned algorithms. To reduce the high data dimensionality introduced by the use of multispectral images, we have designed a system t…

Digitization and preservation of cultural heritage: The CEPROQHA approach

The humanity has always learned from the previous experiences for many reasons. The national heritage proves to be a great way to discover a nation's history. As a result, these priceless cultural items have a special attention. However, Since the wide adoption of new digital technologies, documenting, storing, and exhibiting cultural heritage assets became more affordable and reliable. These digital records are then used in several applications. Researchers saw the opportunity to use digital heritage recordings for long-term preservation. In this paper, we present the research progress in cultural heritage digital processing and preservation, highlighting the most impactful advances. Addit…

Message from SIT Track Chairs

A Virtual Milling Machine Model to Generate Machine-Monitoring Data for Predictive Analytics

Real data from manufacturing processes are essential to create useful insights for decision-making. However, acquiring real manufacturing data can be expensive and time consuming. To address this issue, we implement a virtual milling machine model to generate machine monitoring data from process plans. MTConnect is used to report the monitoring data. This paper presents (1) the characteristics and specification of milling machine tools, (2) the architecture for implementing the virtual milling machine model, and (3) the integration with a simulation environment for extending to a virtual shop floor model. This paper also includes a case study to explain how to use the virtual milling machin…

A Multiresolution Approach Based on MRF and Bak–Sneppen Models for Image Segmentation

The two major Markov Random Fields (MRF) based algorithms for image segmentation are the Simulated Annealing (SA) and Iterated Conditional Modes (ICM). In practice, compared to the SA, the ICM provides reasonable segmentation and shows robust behavior in most of the cases. However, the ICM strongly depends on the initialization phase. In this paper, we combine Bak-Sneppen model and Markov Random Fields to define a new image segmentation approach. We introduce a multiresolution technique in order to speed up the segmentation process and to improve the restoration process. Image pixels are viewed as lattice species of Bak-Sneppen model. The a-posteriori probability corresponds to a local fitn…

Witness computation for solving geometric constraint systems

International audience; In geometric constraint solving, the constraints are represented with an equation system F(U, X) = 0, where X denotes the unknowns and U denotes a set of parameters. The target solution for X is noted XT. A witness is a couple (U_W, X_W) such that F(U_W, X_W) = 0. The witness is not the target solution, but they share the same combinatorial features, even when the witness and the target lie on two distinct connected components of the solution set of F(U, X) = 0. Thus a witness enables the qualitative study of the system: the detection of over- and under-constrained systems, the decomposition into irreducible subsystems, the computation of subsystems boundaries. This …

Conversion of Dupin Cyclide Patches into Rational Biquadratic Bézier Form

This paper uses the symmetry properties of circles and Bernstein polynomials to establish a series of interesting barycentric properties of rational biquadratic Bezier patches. A robust algorithm is presented, based on these properties, for the conversion of Dupin cyclide patches into Bezier form. A set of conversion examples illustrates the use of this algorithm.

Higher Education Internationalization: The Erasmus-Mundus network added value

International audience; Higher education internationalization can play a major role in developing universities and students' capacities and their opportunities broadly throughout the world. Irrespective of contextual differences within and between countries, nearly all higher education institutions worldwide are engaged in international activities and are seeking to expand them. Engaging with the world is now considered part of the definition of quality in education and research. However, with the current crisis, possible tensions and counter reactions to the development of the internationalization can occur, such as an imminent resistance to a supposed denationalizing effect of internation…

Genetic algorithms for 3d reconstruction with supershapes

Supershape model is a recent primitive that represents numerous 3D shapes with several symmetry axes. The main interest of this model is its capability to reconstruct more complex shape than superquadric model with only one implicit equation. In this paper we propose a genetic algorithms to re-construct a point cloud using those primitives. We used the pseudo-Euclidean distance to introduce a threshold to handle real data imperfection and speed up the process. Simulations using our proposed fitness functions and a fitness function based on inside-outside function show that our fitness function based on the pseudo-Euclidean distance performs better.

PTNet: A parameterizable data center network

This paper presents PTNet, a new data center topology that is specifically designed to offer a high and parameterized scalability with just one layer architecture. Furthermore, despite its high scalability, PTNet grants a reduced latency and a high performance in terms of capacity and fault tolerance. Consequently, compared to widely known data center networks, our new topology shows better capacity, robustness, cost-effectiveness and less power consumption. Conducted experiments and theoretical analyses illustrate the performance of the novel system. 2016 IEEE. Scopus

Integrating Variability Management in Data Center Networks

International audience; Data centers have an important role in supporting cloud computing services (i.e. checking social media, sending emails, video conferencing,..). Hence, data centers topologies design became more important and must be able to respond to ever changing service requirements and application demands. An ultimate challenge in this research is the design of data center network that interconnects the massive number of servers, and provides efficient and fault-tolerant routing algorithm. Several topologies such as DCell, FlatNet and ScalNet have been proposed. However, these topologies generally seek to improve the scalability without taking into consideration the energy usage …

Rational supershapes for surface reconstruction

Simple representation of complex 3D data sets is a fundamental problem in computer vision. From a quality control perspective, it is crucial to use efficient and simple techniques do define a reference model for further recognition or comparison tasks. In this paper, we focus on reverse engineering 3D data sets by recovering rational supershapes to build an implicit function to represent mechanical parts. We derive existing techniques for superquadrics recovery to the supershapes and we adapt the concepts introduced for the ratioquadrics to introduce the rational supershapes. The main advantage of rational supershapes over standard supershapes is that the radius is now expressed as a ration…

Multiresolution Analysis for Irregular Meshes

International audience; The concept of multiresolution analysis applied to irregular meshes has become more and more important. Previous contributions proposed a variety of methods using simplification and/or subdivision algorithms to build a mesh pyramid. In this paper, we propose a multiresolution analysis framework for irregular meshes with attributes. Our framework is based on simplification and subdivision algorithms to build a mesh pyramid. We introduce a surface relaxation operator that allows to build a non-uniform subdivision for a low computational cost. Furthermore, we generalize the relaxationoperator to attributes such as color, texture, temperature, etc. The attribute analysis…

3D Reconstruction of rough terrain for USARSim using a height-map method

In this paper, a process for a simplified reconstruction of rough terrains from point clouds acquired using laser scanners is presented. The main idea of this work is to build height-maps which are level gray-scale images representing the ground elevation. These height-maps are generated from step-fields which can be represented by a set of side-by-side pillars. Although height-maps are a practical means for rough terrain reconstruction, it is not possible to represent two different elevations for a given location with one height-map. This is an important drawback as terrain point clouds can show different zones representing surfaces above other surfaces.In this paper, a methodology to crea…

Multiresolution Analysis for Meshes with Appearance Attributes

International audience; We present a new multiresolution analysis framework for irregular meshes with attributes based on the lifting scheme. We introduce a surface prediction operator to compute the detail coefficients for the geometry and the attributes of the model. Attribute analysis gives appearance information to complete the geometrical analysis of the model. A set of experimental results are given to show the efficiency of our framework. We present two applications to adaptive visual-ization and denoising.

Computation of Yvon-Villarceau circles on Dupin cyclides and construction of circular edge right triangles on tori and Dupin cyclides

Ring Dupin cyclides are non-spherical algebraic surfaces of degree four that can be defined as the image by inversion of a ring torus. They are interesting in geometric modeling because: (1) they have several families of circles embedded on them: parallel, meridian, and Yvon-Villarceau circles, and (2) they are characterized by one parametric equation and two equivalent implicit ones, allowing for better flexibility and easiness of use by adopting one representation or the other, according to the best suitability for a particular application. These facts motivate the construction of circular edge triangles lying on Dupin cyclides and exhibiting the aforementioned properties. Our first contr…

NIR and Visible Image Fusion for Improving Face Recognition at Long Distance

Face recognition performance achieves high accuracy in close proximity. However, great challenges still exist in recognizing human face at long distance. In fact, the rapidly increasing need for long range surveillance requires a passage from close-up distances to long distances which affects strongly the human face image quality and causes degradation in recognition accuracy. To address this problem, we propose in this paper, a multispectral pixel level fusion approach to improve the performance of automatic face recognition at long distance. The main objective of the proposed approach is to formulate a method to enhance the face image quality as well as the face recognition rate. First, v…

Intention recognition in manufacturing applications

In this article, we present a novel approach to intention recognition, based on the recognition and representation of state information in a cooperative human-robot environment. States are represented by a combination of spatial relations along with cardinal direction information. The output of the Intention Recognition Algorithms will allow a robot to help a human perform a perceived operation or, minimally, not cause an unsafe situation to occur. We compare the results of the Intention Recognition Algorithms to those of an experiment involving human subjects attempting to recognize the same intentions in a manufacturing kitting domain. In almost every case, results show that the Intention…

OntoSTEP: Enriching product model data using ontologies

The representation and management of product lifecycle information is critical to any manufacturing organization. Different modeling languages are used at different lifecycle stages, for example STEP's EXPRESS may be used at a detailed design stage, while UML may be used for initial design stages. It is necessary to consolidate product information created using these different languages to build a coherent knowledge base. In this paper, we present an approach to enable the translation of STEP schema and its instances to Ontology Web Language (OWL). This gives a model-which we call OntoSTEP-that can easily be integrated with any OWL ontologies to create a semantically rich model. As an examp…

Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics

To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This pape…

Extending CSG with projections: Towards formally certified geometric modeling

We extend traditional Constructive Solid Geometry (CSG) trees to support the projection operator. Existing algorithms in the literature prove various topological properties of CSG sets. Our extension readily allows these algorithms to work on a greater variety of sets, in particular parametric sets, which are extensively used in CAD/CAM systems. Constructive Solid Geometry allows for algebraic representation which makes it easy for certification tools to apply. A geometric primitive may be defined in terms of a characteristic function, which can be seen as the zero-set of a corresponding system along with inequality constraints. To handle projections, we exploit the Disjunctive Normal Form,…

Trademarks recognition based on local regions similarities

This paper deals with content based image retrieval. We propose a logo recognition algorithm based on local regions, where the trademark (or logo) image is segmented by the clustering of points of interest obtained by Harris corners detector. The minimum rectangle surrounding each cluster is detected forming the regions of interest. Global features such as Hu moments and histograms of each local region are combined to find similar logos in the database. Similarity is measured based on the integrated minimum average distance of the individual components. The results obtained demonstrate tolerance to logos distortions such as rotation, occlusion and noise.

Study and Evaluation of Pre-trained CNN Networks for Cultural Heritage Image Classification

The classification of digital images is an essential task during the restoration and preservation of cultural heritage (CH). In computer vision, cultural heritage classification relies on the classification of asset images regarding a certain task such as type, artist, genre, style identification, etc. CH classification is challenging as various CH asset images have similar colors, textures, and shapes. In this chapter, the aim is to study and evaluate the use of pre-trained deep convolutional neural networks such as VGG16, VGG-19, ResNet50, and Inception-V3 for cultural heritage images classification using transfer learning techniques. The main idea is to start with CNN models previously t…

OPTIMIZATIONS FOR TENSORIAL BERNSTEIN–BASED SOLVERS BY USING POLYHEDRAL BOUNDS

The tensorial Bernstein basis for multivariate polynomials in n variables has a number 3n of functions for degree 2. Consequently, computing the representation of a multivariate polynomial in the tensorial Bernstein basis is an exponential time algorithm, which makes tensorial Bernstein-based solvers impractical for systems with more than n = 6 or 7 variables. This article describes a polytope (Bernstein polytope) with a number of faces, which allows to bound a sparse, multivariate polynomial expressed in the canonical basis by solving several linear programming problems. We compare the performance of a subdivision solver using domain reductions by linear programming with a solver using a c…

Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks

Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. …

Digitization and Preservation of Cultural Heritage Products

Cultural heritage encompasses various aspects of a nation's history. Cultural heritage artifacts are considered as priceless items that need special care. Since the wide adoption of new digital technologies, documenting and storing cultural heritage assets became more affordable and reliable. These records are then used in several applications. Researchers saw the opportunity to use digital heritage recordings for long-term preservation. They are considering cultural heritage artifacts as products, and the history behind them as a product lifecycle. In this paper, we present the research progress in cultural heritage digital processing and preservation, highlighting the most impactful advan…

MESH COMPARISON USING ATTRIBUTE DEVIATION METRIC

We propose a mesh comparison method using a new attribute deviation metric. The considered meshes contain geometrical and appearance attributes (material color, texture, temperature, etc.). The proposed deviation metric computes local differences between the attributes of two meshes. A mesh comparison assessment can be done easily and quickly using this metric. The techniques proposed are applicable in a number of ways, e.g. 3D matching and registration, and the example described in the paper is the simplification of a surface by iteratively reducing its complexity according to an error metric. The results are presented showing the success of the algorithm through comparisons with other me…

Conversion d'un carreau de Bézier rationnel biquadratique en un carreau de cyclide de Dupin quartique

Dupin cyclides were introduced in 1822 by the French mathematician C-P. Dupin. They are algebraic surfaces of degree 3 or 4. The set of geometric properties of these surfaces has encouraged an increasing interest in using them for geometric modeling. A couple of algorithmes is already developed to convert a Dupin cyclide patch into a rational biquadratic Bezier patch. In this paper, we consider the inverse problem: we investigate the conditions of convertibility of a Bezier patch into a Dupin cyclide one, and we present a conversion algorithm to compute the parameters of a Dupin cyclide with the boundary of the patch that corresponds to the given Bezier patch.

Chaotic multiagent system approach for MRF-based image segmentation

In this paper, we propose a new chaotic approach for image segmentation based on multiagent system (MAS). We consider a set of segmentation agents organized around a coordinator agent. Each segmentation agent performs iterated conditional modes (ICM) starting from its own initial image created using a chaotic mapping. The coordinator agent diversifies the initial images using a crossover and a chaotic mutation operators. The efficiency of our chaotic MAS approach is shown through some experimental results.

Ontology-based state representation for intention recognition in cooperative human-robot environments

In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level states relationships that must be true for future actions to occur, a robot can use the detailed state information presented in this paper to infer the probability of subsequent actions occurring. This would enable the robot to better help th…

Efficient techniques for energy saving in data center networks

Data centers are constructed with a huge number of network devices to support the expanding cloud based services. These devices are used to achieve the highest performance in case of full utilization of the network. However, the peak capacity of the network is rarely reached. Consequently, many devices are set into idle state and cause a huge energy waste leading to a non-proportionality between the network load and the energy consumed. In this paper, we propose a new approach to improve the efficiency of data centers in terms of energy consumption. Our approach exploits the correlation in time of the inter-node communication traffic and some topological features to maximize energy saving w…

Modelling Complex Volume Shape Using Ellipsoid: Application to Pore Space Representation

Natural shapes have complex volume forms that are usually difficult to model using simple analytical equations. The complexity of the representation is due to the heterogeneity of the physical environment and the variety of phenomena involved. In this study we consider the representation of the porous media. Thanks to the technological advances in Computed Topography scanners, the acquisition of images of complex shapes becomes possible. However, and unfortunately, the image data is not directly usable for simulation purposes. In this paper, we investigate the modeling of such shapes using a piece wise approximation of image data by ellipsoids. We propose to use a split-merge strategy and a…

A literature review of sensor ontologies for manufacturing applications

The purpose of this paper is to review existing sensor and sensor network ontologies to understand whether they can be reused as a basis for a manufacturing perception sensor ontology, or if the existing ontologies hold lessons for the development of a new ontology. We develop an initial set of requirements that should apply to a manufacturing perception sensor ontology. These initial requirements are used in reviewing selected existing sensor ontologies. Additionally, we present our developed sensor ontology thus far that incorporates a refined list of requirements. This paper describes 1) extending and refining the requirements; 2) proposing hierarchical structures for verifying the purpo…

Optimization on ports activation towards energy efficient data center networks

Nowadays, Internet of thing including network support (i.e. checking social media, sending emails, video conferencing) requires smart and efficient data centers to support these services. Hence, data centers become more important and must be able to respond to ever changing service requirements and application demands. However, data centers are classified as one of the largest consumers of energy in the world. Existing topologies such as ScalNet improves the data center scalability while leading to enormous amounts of energy consumption. In this paper, we present a new energy efficient algorithm for ScalNet called Green ScalNet. The proposed topology strikes a compromise between maximizing …

G1-Blend between a Differentiable Superquadric of Revolution and a Plane or a Sphere Using Dupin Cyclides

In this article, we present a method to perform G1-continuous blends between a differentiable superquadric of revolution and a plane or a sphere using Dupin cyclides. These blends are patches delimited by four lines of curvature. They allow to avoid parameterization problems that may occur when parametric surfaces are used. Rational quadratic Bezier curves are used to approximate the principal circles of the Dupin cyclide blends and thus a complex 3D problem is now reduced to a simpler 2D problem. We present the necessary conditions to be satisfied to create the blending patches and illustrate our approach by a number of superellipsoid/plane and superellipsoid/sphere blending examples.

An Ontology Architecture for Standards Integration and Conformance in Manufacturing

Standards reflect consensus on the semantics of terms. When used to communicate, whether between people or software systems, standards ensure the communication is correct. Different standards have different semantics for the same terms and express common concepts using different terms and in different ways. Communication between software systems based on different standards is sometimes difficult to achieve. Standards integration concerns the explicit representation of the overlapping sets of concepts in standards and the differences in their semantics to ensure that these standards are used consistently together. This in turn enables software that is based on integrated standards to intero…

Numerical decomposition of geometric constraints

Geometric constraint solving is a key issue in CAD/CAM. Since Owen's seminal paper, solvers typically use graph based decomposition methods. However, these methods become difficult to implement in 3D and are misled by geometric theorems. We extend the Numerical Probabilistic Method (NPM), well known in rigidity theory, to more general kinds of constraints and show that NPM can also decompose a system into rigid subsystems. Classical NPM studies the structure of the Jacobian at a random (or generic) configuration. The variant we are proposing does not consider a random configuration, but a configuration similar to the unknown one. Similar means the configuration fulfills the same set of inci…

Product Lifecycle Management and the Industry of the Future

INTERVAL-BASED TRACING OF STRANGE ATTRACTORS

The method described here relies on interval arithmetic and graph theory to compute guaranteed coverings of strange attractors like Hénon attractor. It copes with infinite intervals, using either a geometric method or a new directed projective interval arithmetic.

Multilinear sparse decomposition for best spectral bands selection

Optimal spectral bands selection is a primordial step in multispectral images based systems for face recognition. In this context, we select the best spectral bands using a multilinear sparse decomposition based approach. Multispectral images of 35 subjects presenting 25 different lengths from 480nm to 720nm and three lighting conditions: fluorescent, Halogen and Sun light are groupped in a 3-mode face tensor T of size 35x25x2 . T is then decomposed using 3-mode SVD where three mode matrices for subjects, spectral bands and illuminations are sparsely determined. The 25x25 spectral bands mode matrix defines a sparse vector for each spectral band. Spectral bands having the sparse vectors with…

On the Complexity of the Bernstein Combinatorial Problem

International audience

Solving the pentahedron problem

Nowadays, all geometric modelers provide some tools for specifying geometric constraints. The 3D pentahedron problem is an example of a 3D Geometric Constraint Solving Problem (GCSP), composed of six vertices, nine edges, five faces (two triangles and three quadrilaterals), and defined by the lengths of its edges and the planarity of its quadrilateral faces. This problem seems to be the simplest non-trivial problem, as the methods used to solve the Stewart platform or octahedron problem fail to solve it. The naive algebraic formulation of the pentahedron yields an under-constrained system of twelve equations in eighteen unknowns. Even if the use of placement rules transforms the pentahedron…

Vector anisotropic filter for multispectral image denoising

In this paper, we propose an approach to extend the application of anisotropic Gaussian filtering for multi- spectral image denoising. We study the case of images corrupted with additive Gaussian noise and use sparse matrix transform for noise covariance matrix estimation. Specifically we show that if an image has a low local variability, we can make the assumption that in the noisy image, the local variability originates from the noise variance only. We apply the proposed approach for the denoising of multispectral images corrupted by noise and compare the proposed method with some existing methods. Results demonstrate an improvement in the denoising performance.

Achieving energy efficiency in data centers with a performance-guaranteed power aware routing

Nowadays, data centers are designed to offer the highest performance in case of high traffic load and peak utilisation of the network. However, in a realistic data center environment, the peak capacity of the network is rarely reached and the average utilisation of devices varies between 5% and 25% which results into a huge loss of energy since most of the time links and servers are idle or under-utilized. The high impact of this wasted power on environmental effects, energy needs and electricity costs raised the concerns to seek for an efficient solution to make data centers more power effective while keeping the desired quality of service. In this paper, we propose a power-aware routing a…

Dupin Cyclide Blends Between Quadric Surfaces for Shape Modeling

We introduce a novel method to define Dupin cyclide blends between quadric primitives. Dupin cyclides are nonspherical algebraic surfaces discovered by French mathematician Pierre-Charles Dupin at the beginning of the 19th century. As a Dupin cyclide can be fully characterized by its principal circles, we have focussed our study on how to determine principal circles tangent to both quadrics being blended. This ensures that the Dupin cyclide we are constructing constitutes aG 1 blend. We use the Rational Quadratic Bezier Curve (RQBC) representation of circular arcs to model the principal circles, so the construction of each circle is reduced to the determination of the three control points o…

A Graph Database Approach to Wireless IIoT Workcell Performance Evaluation

The workcell is considered a main building block of various industrial settings. Hence, it is examined as a primary testing environment for studying wireless communication techniques in factory automation processes. A new testbed was recently designed and developed to facilitate such studies in workcells by replicating various data flows in an emulated production environment. In this paper, an approach to storing and analyzing network performance data from a manufacturing factory workcell is introduced. A robotic testbed was constructed using two collaborative grade robot arms, machine emulators, and wireless communication devices. A graph database approach was implemented to capture networ…

A Sparsity-Aware Approach for NBI Estimation and Mitigation in Large Cognitive Radio Networks

Underlay cognitive networks should follow strict interference thresholds to operate in parallel with primary networks. This constraint limits their transmission power and eventually the coverage area. Therefore, in this paper, we first design a new approach for asynchronous narrow-band interference (NBI) estimation and mitigation in orthogonal frequency-division multiplexing cognitive radio networks that does not require prior knowledge of the NBI characteristics. Our proposed approach allows the primary user to exploit the sparsity of the secondary users' interference signal to recover it and cancel it based on sparse signal recovery theory. We also propose two subcarrier selection schemes…

SIT: Track on Signal Image Technology

A Neural Network Meta-Model and its Application for Manufacturing

International audience; Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to increase a manufacturer's competitive advantage through improved sustainability, productivity, and flexibility of their operations. Manufacturers, as well as other industries, have successfully applied a promising statistical learning technique, called neural networks (NNs), to extract meaningful information from large data sets, so called big data. However, the application of NN to manufacturing problems remains limited because it involves the specialized skills of a data scientist. This paper introduces an appr…

LaCoDa: Layered connected topology for massive data centers

One of the fundamental challenges of existing data centers is to design a network that interconnects massive number of servers, and therefore providing an efficient and fault-tolerant routing service to upper-layer applications. Several solutions have been proposed (e.g. FatTree, DCell and BCube), however they either scale too fast (i.e., double exponentially) or too slow. This paper proposes a new data center topology, called LaCoDa, that combines the advantages of previous topologies while avoiding their limitations. LaCoDa uses a small node degree that matches physical restriction for servers, and it also interconnects a large number of servers while reducing the wiring complexity and wi…

Detecting All Dependences in Systems of Geometric Constraints Using the Witness Method

In geometric constraints solving, the detection of dependences and the decomposition of the system into smaller subsystems are two important steps that characterize any solving process, but nowadays solvers, which are graph-based in most of the cases, fail to detect dependences due to geometric theorems and to decompose such systems. In this paper, we discuss why detecting all dependences between constraints is a hard problem and propose to use the witness method published recently to detect both structural and non structural dependences.We study various examples of constraints systems and show the promising results of the witness method in subtle dependences detection and systems decomposi…

MULTIRESOLUTION ANALYSIS FOR IRREGULAR MESHES WITH APPEARANCE ATTRIBUTES

We present a new multiresolution analysis framework based on the lifting scheme for irregular meshes with attributes. We introduce a surface prediction opera- tor to compute the detail coefficients for the geometry and the attributes of the model. Attribute analysis gives appearance information to complete the geomet- rical analysis of the model.We present an application to adaptive visualization and some experimental results to show the efficiency of our framework.

A Model for Capturing Product Assembly Information

The important issue of mechanical assemblies has been a subject of intense research over the past several years. Most electromechanical products are assemblies of several components, for various technical as well as economic reasons. This paper provides an object-oriented definition of an assembly model called the Open Assembly Model (OAM) and defines an extension to the NIST Core Product Model (NIST-CPM). The assembly model represents the function, form, and behavior of the assembly and defines both a system level conceptual model and associated hierarchical relationships. The model provides a way for tolerance representation and propagation, kinematics representation, and engineering anal…

A survey of wireless data center networks

Data centers are becoming more and more popular for a wide variety of applications. However, the efficiency of data centers are restricted by many issues like cabling and maintenance problems in addition to performance problems like oversubscription. Wireless technology was proposed as it has the capability and the flexibility to offer feasible approaches to solve some of these problems. In this paper, we conduct a deep investigation about wireless data center networks, describe some works that enhance the performance of the network, then give some remarks and critiques. 2015 IEEE. Scopus

Solution isolation strategies for the Bernstein polytopes-based solver

The Bernstein polytopes-based solver is a new method developed to solve systems of nonlinear equations, which often occur in Geometric Constraint Solving Problems. The principle of this solver is to linearize nonlinear monomials and then to solve the resulting linear programming problems, through linear programming. However, without any strategy for the isolation of the many solutions of multiple-solution systems, this solver is slow in practice. To overcome this problem, we propose in this work, a study of several strategies for solution isolation, through the split of solution boxes into several subboxes, according to three main steps answering the questions: when, where, and how to perfo…

Adaptative Network Topology for Data Centers

Data centers have an important role in supporting cloud computing services (such as email, social networking, web search, etc.) enterprise computing needs, and infrastructure-based services. Data center networking is a research topic that aims at improving the overall performances of the data centers. It is a topic of high interest and importance for both academia and industry. Several architectures such as FatTree, FiConn, DCel, BCube, and SprintNet have been proposed. However, these topologies try to improve the scalability without any concerns about energy that data centers use and the network infrastructure cost, which are critical parameters that impact the performances of data centers…

Smart Manufacturing Testbed for the Advancement of Wireless Adoption in the Factory

Wireless communication is a key enabling technology central to the advancement of the goals of the Industry 4.0 smart manufacturing concept. Researchers at the National Institute of Standards and Technology are constructing a testbed to aid in the adoption of wireless technology within the factory workcell and other harsh industrial radio environments. In this paper the authors present a new industrial wireless testbed design that motivates academic research and is relevant to the needs of industry. The testbed is designed to serve as both a demonstration and research platform for the wireless workcell. The work leverages lessons learned from past testbed incarnations that included a dual r…

Modified total variation regularization using fuzzy complement for image denoising

In this paper, we propose a denoising algorithm based on the Total Variation (TV) model. Specifically, we associate to the regularization term of the Rodin-Osher-Fatimi (ROF) functional a small weight whenever denoising is performed in edge and texture regions, which means less regularization and more details preservation. On the other hand, a large weight is associated if the region being filtered is smooth which means noise will be well suppressed. The weight computation is inspired from the fuzzy edge complement. Experiments on well-known images and comparison with state of the art denoising algorithms demonstrate that the proposed method not only presents good denoising performance but …

Toward a Reference Architecture for Archival Systems

Long-term preservation of product data is imperative for many organizations. A product data archive should be designed to ensure information accessibility and understanding over time. Approaches such as the Open Archival Information System (OAIS) Reference Model and the Audit and Certification of Trustworthy Digital Repositories (ACTDR) provide a framework for conceptually describing and evaluating archives. These approaches are generic and do not focus on particular contexts or content types. Enterprise architecture provides a way to describe systems in their potentially complex environments.

A Graph Based Algorithm For Intersection Of Subdivision Surfaces

Computing surface intersections is a fundamental problem in geometric modeling. Any boolean operation can be seen as an intersection calculation followed by a selection of the parts necessary for building the surface of the resulting object. A robust and efficient algorithm to compute intersection on subdivision surfaces (surfaces generated by the Loop scheme) is proposed here. This algorithm relies on the concept of a bipartite graph which allows the reduction of the number of faces intersection tests. Intersection computations are accelerated by the use of the bipartite graph and the neighborhood of intersecting faces at a given level of subdivision to deduce intersecting faces at the fol…

Interrogating witnesses for geometric constraint solving

International audience; Classically, geometric constraint solvers use graph-based methods to decompose systems of geometric constraints. These methods have intrinsic limitations, which the witness method overcomes; a witness is a solution of a variant of the system. This paper details the computation of a basis of the vector space of free infinitesimal motions of a typical witness, and explains how to use this basis to interrogate the witness for dependence detection. The paper shows that the witness method detects all kinds of dependences: structural dependences already detectable by graph-based methods, but also non-structural dependences, due to known or unknown geometric theorems, which…

Boolean operations with implicit and parametric representation of primitives using R-functions

We present a new and efficient algorithm to accurately polygonize an implicit surface generated by multiple Boolean operations with globally deformed primitives. Our algorithm is special in the sense that it can be applied to objects with both an implicit and a parametric representation, such as superquadrics, supershapes, and Dupin cyclides. The input is a constructive solid geometry tree (CSG tree) that contains the Boolean operations, the parameters of the primitives, and the global deformations. At each node of the CSG tree, the implicit formulations of the subtrees are used to quickly determine the parts to be transmitted to the parent node, while the primitives' parametric definition …

From Dupin cyclides to scaled cyclides

Dupin cyclides are algebraic surfaces introduced for the first time in 1822 by the French mathematician Pierre-Charles Dupin. They have a low algebraic degree and have been proposed as a solution to a variety of geometric modeling problems. The circular curvature line’s property facilitates the construction of the cyclide (or the portion of a cyclide) that blends two circular quadric primitives. In this context of blending, the only drawback of cyclides is that they are not suitable for the blending of elliptic quadric primitives. This problem requires the use of non circular curvature blending surfaces. In this paper, we present another formulation of cyclides: Scaled cyclides. A scaled cy…

Mobile manipulator performance measurement towards manufacturing assembly tasks

Mobile manipulator performance measurement research is relatively minimal as compared to that of robot arms. Measurement methods, such as optical tracking systems, are useful for measuring the performance of mobile manipulators, although at a much higher relative cost as compared to artifacts. The concept of using test artifacts demonstrates to potential manufacturers and users of mobile manipulator systems that relatively low cost performance measurement methods exist. This paper discusses the concept of reconfigurable mobile manipulator artifacts that were designed and built. An artifact was then used through experimentation to measure the performance of a mobile manipulator to demonstrat…

A Guaranteed performance of a green data center based on the contribution of vital nodes

International audience; In order to satisfy the need for the critical computing resources, many data center architectures proposed to house a huge number of network devices. These devices are used to achieve the highest performance in case of full utilization of the network. However, the peak capacity of the network is rarely reached. Consequently, many devices are set into idle state and cause a huge energy waste leading to a non-proportionality between the network load and the energy consumed. In this paper, we propose a power-aware routing algorithm that saves energy consumption with a negligible trade-off on the performance of the network. The idea is to keep active only the source and …

MRF Model-Based Approach for Image Segmentation Using a Chaotic MultiAgent System

In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is s…

Studies on the Effectiveness of Multispectral Images for Face Recognition: Comparative Studies and New Approaches

In this paper, we investigate face recognition in unconstrained illumination conditions. A twofold contribution is proposed: First, three state of the art algorithms, namely Multiblock Local Binary Pattern (MBLBP), Histogram of Gabor Phase Patterns (HGPP) and Local Gabor Binary Pattern Histogram Sequence (LGBPHS) are challenged against the IRIS-M3 multispectral face data base to evaluate their robustness against high illumination variation. Second, we propose to enhance the Performance of the three mentioned algorithms, which has been drastically decreased because of the non-monotonic illumination variation that distinguishes the IRIS-M3 face database. Instead of the usual braod band images…

Generic attribute deviation metric for assessing mesh simplification algorithm quality

International audience; This paper describes an efficient method to compare two triangular meshes. Meshes considered here contain geometric features as well as other surface attributes such as material colors, texture, temperature, radiation, etc. Two deviation measurements are presented to assess the differences between two meshes. The first measurement, called geometric deviation, returns geometric differences. The second measurement , called attribute deviation, returns attribute differences regardless of the attribute type. In this paper we present an application of this method to the Mesh Simplification Algorithm (MSA) quality assessment according to the appearance attributes. This ass…

Multispectral image denoising with optimized vector non-local mean filter

Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …

Deep Learning and Cultural Heritage: The CEPROQHA Project Case Study

Cultural heritage takes an important part of the history of humankind as it is one of the most powerful tools for the transfer and preservation of moral identity. As a result, these cultural assets are considered highly valuable and sometimes priceless. Digital technologies provided multiple tools that address challenges related to the promotion and information access in the cultural context. However, the large data collections of cultural information have more potential to add value and address current challenges in this context with the recent progress in artificial intelligence (AI) with deep learning and data mining tools. Through the present paper, we investigate several approaches tha…

Towards a Reference Architecture for Archival Systems: Use Case With Product Data

Long-term preservation of product data is imperative for many organizations. A product data archive should be designed to ensure information accessibility and understanding over time. Approaches, such as the Open Archival Information System Reference Model (OAIS RM) and the Audit and Certification of Trustworthy Digital Repositories (ACTDR), provide a framework for conceptually describing and evaluating archives. These approaches are generic and do not focus on particular contexts or content types such as product data. Moreover, these approaches offer no guidance on how to formally and comprehensively describe archival systems. Such descriptions should include the business activities that a…

Fuzzy-logic-based approach for identifying objects of interest in the PRIDE framework

On-road autonomous vehicle navigation requires real-time motion planning in the presence of static and moving objects. Based on sensed data of the environment and the current traffic situation, an autonomous vehicle has to plan a path by predicting the future location of objects of interest. In this context, an object of interest is a moving or stationary object in the environment that has a reasonable probability of intersecting the path of the autonomous vehicle within a predetermined time frame. This paper investigates the identification of objects of interest within the PRIDE (PRediction In Dynamic Environments) framework. PRIDE is a multi-resolutional, hierarchical framework that predi…

Performance evaluation of robotic knowledge representation (PERK)

In this paper, we explore some ways in which symbolic knowledge representations have been evaluated in the past and provide some thoughts on what should be considered when applying and evaluating these types of knowledge representations for real-time robotics applications. The emphasis of this paper is that the robotic applications require real-time access to information, which has not been one of the aspects measured in traditional symbolic representation evaluation approaches.

A proposed mapping method for aligning machine execution data to numerical control code

The visions of the digital thread and smart manufacturing have boosted the potential of relating downstream data to upstream decisions in design. However, to date, the tools and methods to robustly map across the related data representations is significantly lacking. In response, we propose a mapping technique for standard manufacturing data representations. Specifically, we focus on relating controller data from machining tools in the form of MTConnect, an emerging standard that defines the vocabulary and semantics as well as communications protocols for execution data, and G-Code, the most widely used standard for numerical control (NC) instructions. We evaluate the efficacy of our mappin…

An Energy Saving Mechanism Based on Vacation Queuing Theory in Data Center Networks

To satisfy the growing need for computing resources, data centers consume a huge amount of power which raises serious concerns regarding the scale of the energy consumption and wastage. One of the important reasons for such energy wastage relates to the redundancies. Redundancies are defined as the backup routing paths and unneeded active ports implemented for the sake of load balancing and fault tolerance. The energy loss may also be caused by the random nature of incoming packets forcing nodes to stay powered on all the times to await for incoming tasks. This paper proposes a re-architecturing of network devices to address energy wastage issue by consolidating the traffic arriving from di…

Construction of 3D Triangles on Dupin Cyclides

This paper considers the conversion of the parametric Bézier surfaces, classically used in CAD-CAM, into patched of a class of non-spherical degree 4 algebraic surfaces called Dupin cyclides, and the definition of 3D triangle with circular edges on Dupin cyclides. Dupin cyclides was discovered by the French mathematician Pierre-Charles Dupin at the beginning of the 19th century. A Dupin cyclide has one parametric equation, two implicit equations, and a set of circular lines of curvature. The authors use the properties of these surfaces to prove that three families of circles (meridian arcs, parallel arcs, and Villarceau circles) can be computed on every Dupin cyclide. A geometric algorithm …