pinecone/core-2020-05-10-deduplication huggingface dataset:
Efficient global minimization methods for variational problems in imaging and vision

Energy minimization has become one of the most important paradigms for formulating
image processing and computer vision problems in a mathematical language.
Energy minimization models have been developed in both the variational
and discrete optimization community during the last 20-30 years. Some models
have established themselves as fundamentally important and arise over a wide
range of applications.
One fundamental challenge is the optimization aspect. The most desirable
models are often the most difficult to handle from an optimization perspective.
Continuous optimization problems may be non-convex and contain many inferior
local minima. Discrete optimization problems may be NP-hard, which means
algorithms are unlikely to exist which can always compute exact solutions without
an unreasonable amount of effort.
This thesis contributes with efficient optimization methods which can compute
global or close to global solutions to important energy minimization models in
imaging and vision. New insights are given in both continuous and combinatorial
optimization, as well as a strengthening of the relationships between these fields.
One problem that is extensively studied is minimal perimeter partitioning
problems with several regions, which arise naturally in e.g. image segmentation
applications and is NP-hard in the discrete context. New methods are developed
that can often compute global solutions and otherwise very close approximations
to global solutions. Experiments show the new methods perform significantly
better than earlier variational approaches, like the level set method, and earlier
combinatorial optimization approaches. The new algorithms are significantly
faster than previous continuous optimization approaches.
In the discrete community, max-flow and min-cut (graph cuts) have gained
huge popularity because they can efficiently compute global solutions to certain
energy minimization models. It is shown that new types of problems can be solved
exactly by max-flow and min-cut. Furthermore, variational generalizations of
max-flow and min-cut are proposed which bring the global optimization property
to the continuous setting, while avoiding grid bias and metrication errors which
are major disadvantages of the discrete models. Convex optimization algorithms
are derived from the variational max-flow models, which are very efficient and
are more parallel friendly than traditional combinatorial algorithms
Multiplicative noise cleaning via a variational method involving curvelets coefficients

International audienceClassical ways to denoise images contaminated with multiplicative noise (e.g. speckle noise) are filtering, statistical (Bayesian) methods, variational methods and methods that convert the multiplicative noise into additive noise (using a logarithmic function) in order to apply a shrinkage estimation for the log-image data and transform back the result using an exponential function.We propose a new method that involves several stages: we apply a reasonable under-optimal hard-thresholding on the curvelet transform of the log-image; the latter is restored using a specialized hybrid variational method combining an ℓ1 data-fitting to the thresholded coefficients and a Total Variation regularization (TV) in the image domain; the restored image is an exponential of the obtained minimizer, weighted so that the mean of the original image is preserved. The minimization stage is realized using a properly adapted fast Douglas-Rachford splitting. The existence of a minimizer of our specialized criterion and the convergence of the minimization scheme are proved. The obtained numerical results outperform the main alternative methods
Highlight on a feature extracted at fine scales: the pointwise Lipschitz regularity

The aim of this paper is to study the robustness of the pointwise Lipschitz regularity in 2D, which is a measure of the local regularity of the intensity function associated to an image. This regularity can be efficiently computed  
by an approach based on fine scales. We assess its robustness when the image undergoes various transformations, especially geometric ones. The results we obtain show that the pointwise Lipschitz regularity is a suitable feature for applications in computer vision.status: publishe
Knowledge based information retrieval with an Adaptive Hypermedia System

This paper describes research on information retrieval with\ud
an adaptive hypermedia system (AHS) used during three higher education\ud
courses taught in a blended learning (BL) environment. The system\ud
generates different work plans for each student, according to their profile.\ud
Work plans are adapted by means of an algorithm. AHS enable course\ud
contents to be adapted to the learning needs of each student and structured\ud
in a way that leads to many different learning paths. The case\ud
study method was used in this research. The results suggest that the\ud
AHS has a positive impact on the learning process. Further research is\ud
needed to confirm these results.Peer ReviewedPostprint (published version
A genetic algorithm for the open shop problem with uncertain durations

Third International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2009 (3rd. 2009. Santiago de Compostela, Spain)We consider a variation of the open shop problem where task durations are allowed to be uncertain and where uncertainty is modelled using fuzzy numbers. We propose a genetic approach to minimise the expected makespan: we consider different possibilities for the genetic operators and analyse their performance, in order to obtain a competitive configuration. Finally, the performance of the proposed genetic algorithm is tested on several benchmark problems, modified so as to have fuzzy durations, compared with a greedy heuristic from the literatur
Prediction and inheritance of phenotypes

In the search for functional relationships between genotypes and phenotypes, there are two possible  ndings. A phenotype may be heritable when it depends on a reduced set of genetic markers. Or it may be predictable from a wide genomic description. The distinction between these two kinds of functional relationships is very important since the computational tools used to  nd them are quite di erent. In this paper we present a general framework to deal with phenotypes and genotypes, and we study the case of the height of barley plants: a predictable phenotype whose heritability is quite reduce
On the Values of Reducibility Candidates

The straightforward elimination of union types is known to break subject reduction, and for some extensions of the lambda-calculus, to break strong normalization as well. Similarly, the straightforward elim- ination of implicit existential types breaks subject reduction. We propose elimination rules for union types and implicit existential quantification which use a form call-by-value issued from Girard's re- ducibility candidates. We show that these rules remedy the above men- tioned difficulties, for strong normalization and, for the existential quan- tification, for subject reduction as well. Moreover, for extensions of the lambda-calculus based on intuitionistic logic, we show that the obtained existential quantification is equivalent to its usual impredicative encoding w.r.t. provability in realizability models built from reducibility candidates and biorthogonals
A Fuzzy inference expert system to support the decision of deploying a military naval unit to a mission

Naval military units are complex systems required to operate in  xed time frames in o shore tasks where maintenance operations are drastically limited. A failure during a mission is a critical event that can drastically in\ud
uence the mission success. The decision of switching a unit to a mission hence requires complex judgments involving information about the health status of machineries and the environmental conditions. The present procedure aims to support the decision about\ud
switching a unit to a mission considering the vagueness and uncertainty of information by means of fuzzy theory and emulates the decision process of a human expert by means of a rule-based inference engine. A numerical application is presented to prove the e ectiveness of the approach
Mechanism of Fruit Ripening - Chapter 16

The fruit ripening process has been viewed over the last decades as being\ud
successively of physiological, biochemical, and molecular nature. Fruit ripening\ud
is accompanied by a number of biochemical events, including changes in color,\ud
sugar, acidity, texture, and aroma volatiles that are crucial for the sensory quality\ud
(Fig. 16.1). At the late stages of ripening, some senescence-related physiological\ud
changes occur that lead to membrane deterioration and cell death. In that regard,\ud
fruit ripening can thus be considered as the first step of a programmed cell death\ud
process. All biochemical and physiological changes that take place during fruit\ud
ripening are driven by the coordinated expression of fruit ripening-related genes.\ud
These genes encode enzymes that participate directly in biochemical and physiological\ud
changes. They also encode regulatory proteins that participate in the signaling\ud
pathways, and in the transcriptional machinery that regulate gene expression\ud
and set in motion the ripening developmental progra
FIA : an open foresic integration architecture for composing digital evidence

The analysis and value of digital evidence in an investigation has been the domain of discourse in the digital forensic community for several years. While many works have considered different approaches to model digital evidence, a comprehensive understanding of the process of merging different evidence items recovered during a forensic analysis is still a distant dream. With the advent of modern technologies, pro-active measures are integral to keeping abreast of all forms of cyber crimes and attacks. This paper motivates the need to formalize the process of analyzing digital evidence from multiple sources simultaneously. In this paper, we present the forensic integration architecture (FIA) which provides a framework for abstracting the evidence source and storage format information from digital evidence and explores the concept of integrating evidence information from multiple sources. The FIA architecture identifies evidence information from multiple sources that enables an investigator to build theories to reconstruct the past. FIA is hierarchically composed of multiple layers and adopts a technology independent approach. FIA is also open and extensible making it simple to adapt to technological changes. We present a case study using a hypothetical car theft case to demonstrate the concepts and illustrate the value it brings into the field
Architecture for Hybrid Robotic Behavior

Software architectures for agent technology and robots have  been polarized between reactive architectures and architectures based on  planning and reasoning. Although hybrid architectures have been shown  to offer benefits from both, these seem complicated to integrate. In this  paper we integrate the reactive nature of finite state machines and the  reasoning capabilities of non-monotonic logics to produce intelligent autonomous  robots. In particular, we demonstrate this with a robotic poker  player. The robotic player integrates vision, sound recognition, motion  control and the reasoning to perform competitively as a player in a complex  game with incomplete information.Griffith Sciences, School of Information and Communication TechnologyFull Tex
The Bias Variance Trade-Off in Bootstrapped Error Correcting Output Code Ensembles

By performing experiments on publicly available multi-class datasets we examine the effect of bootstrapping on the bias/variance behaviour of error-correcting output code ensembles. We present evidence to show that the general trend is for bootstrapping to reduce variance but to slightly increase bias error. This generally leads to an improvement in the lowest attainable ensemble error, however this is not always the case and bootstrapping appears to be most useful on datasets where the non-bootstrapped ensemble classifier is prone to overfitting
Security analysis of standard authentication and key agreement protocols utilising timestamps

We propose a generic modelling technique that can be used to extend existing frameworks for theoretical security analysis in order to capture the use of timestamps. We apply this technique to two of the most popular models adopted in literature (Bellare-Rogaway and Canetti-Krawczyk). We analyse previous results obtained using these models in light of the proposed extensions, and demonstrate their application to a new class of protocols. In the timed CK model we concentrate on modular design and analysis of protocols, and propose a more efficient timed authenticator relying on timestamps. The structure of this new authenticator implies that an authentication mechanism standardised in ISO-9798 is secure. Finally, we use our timed extension to the BR model to establish the security of an efficient ISO protocol for key transport and unilateral entity authentication
Reducing Key Length of the McEliece Cryptosystem

International audienceThe McEliece cryptosystem is one of the oldest public-key cryptosystem ever designated. It is also the first public-key cryptosystem based on linear error-correcting codes. The main advantage of the McEliece cryptosystem is to have a very fast encryption and decryption functions but suffers from a major drawback. It requires a very large public key which makes it very difficult to use in many practical situations. In this paper we propose a new general way to reduce the public key size through quasi-cyclic codes. Our construction introduces a new method of hiding the structure of the secret generator matrix by first choosing a subfield subcode of a quasi-cyclic code that is defined over a large alphabet and then by randomly shortening the chosen subcode. The security of our variant is related to the hardness of decoding a random quasi-cyclic code. We introduce a new decisional problem that is associated to the decoding of an arbitrary quasi-cyclic code. We prove that it is an NP-complete problem. Starting from subfield subcodes of quasi-cyclic generalized Reed-Solomon codes, we propose a system with several size of parameters from 6,000 to 11,000 bits with a security ranging from 2 80 to 2 107 . Implementations of our proposal show that we can encrypt at a speed of 120 Mbits/s (or one octet for 120 cycles). Hence our new proposal represents the most competitive public-key cryptosystem
Fault prediction in aircraft engines using Self-Organizing Maps

Communication présentée au 7th International Workshop WSOM 09, St Augustine, Floride, USA, June 2009Aircraft engines are designed to be used during several tens of years. Their maintenance is a challenging and costly task, for obvious security reasons. The goal is to ensure a proper operation of the engines, in all conditions, with a zero probability of failure, while taking into account aging. The fact that the same engine is sometimes used on several aircrafts has to be taken into account too. The maintenance can be improved if an efficient procedure for the prediction of failures is implemented. The primary source of information on the health of the engines comes from measurement during flights. Several variables such as the core speed, the oil pressure and quantity, the fan speed, etc. are measured, together with environmental variables such as the outside temperature, altitude, aircraft speed, etc. In this paper, we describe the design of a procedure aiming at visualizing successive data measured on aircraft engines. The data are multi-dimensional measurements on the engines, which are projected on a self-organizing map in order to allow us to follow the trajectories of these data over time. The trajectories consist in a succession of points on the map, each of them corresponding to the two-dimensional projection of the multi-dimensional vector of engine measurements. Analyzing the trajectories aims at visualizing any deviation from a normal behavior, making it possible to anticipate an operation failure
Career-Path Analysis Using Optimal Matching and Self-Organizing Maps

This paper is devoted to the analysis of career paths and employability. The state-of-the-art on this topic is rather poor in methodologies. Some authors propose distances well adapted to the data, but are limiting their analysis to hierarchical clustering. Other authors apply sophisticated methods, but only after paying the price of transforming the categorical data into continuous, via a factorial analysis. The latter approach has an important drawback since it makes a linear assumption on the data. We propose a new methodology, inspired from biology and adapted to career paths, combining optimal matching and self-organizing maps. A complete study on real-life data will illustrate our proposal
Pattern-based model-to-model transformation: Handling attribute conditions

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02408-5_7Proceedings of Second International Conference, ICMT 2009, Zurich, Switzerland, June 29-30, 2009Pattern-based model-to-model transformation is a new approach for specifying transformations in a declarative, relational and formal style. The language relies on patterns describing allowed or forbidden relations between two models, which are compiled into operational mechanisms to perform forward and backward transformations.
In this paper, we extend the approach for handling attribute conditions expressed in some suitable logic, adapt the operational mechanisms based on graph transformation to relax attribute handling by constraint solving, and discuss heuristics for the compilation of patterns into rules.Work supported by the Spanish Ministry of Science and Innovation,
projects METEORIC (TIN2008-02081),MODUWEB (TIN2006-09678)
and FORMALISM (TIN2007-66523).Moreover, part of this work was done during
a sabbatical leave of the third author at TU Berlin, with financial support from
the Ministerio de Ciencia e Innovaci´on (grant ref. PR2008-0185). We thank the
referees for their useful comment
Towards model round-trip engineering : an abductive approach

Providing support for reversible transformations as a basis for round-trip engineering is a significant challenge in model transformation research. While there are a number of current approaches, they require the underlying transformation to exhibit an injective behaviour when reversing changes. This however, does not serve all practical transformations well. In this paper, we present a novel approach to round-trip engineering that does not place restrictions on the nature of the underlying transformation. Based on abductive logic programming, it allows us to compute a set of legitimate source changes that equate to a given change to the target model. Encouraging results are derived from an initial prototype that supports most concepts of the Tefkat transformation language \u
Average-case analysis of perfect sorting by reversals

International audienceA sequence of reversals that takes a signed permutation to the identity is perfect if at no step a common interval is broken. Determining a parsimonious perfect sequence of reversals that sorts a signed permutation is NP-hard. Here we show that, despite this worst-case analysis, with probability one, sorting can be done in polynomial time. Further, we find asymptotic expressions for the average length and number of reversals in commuting permutations, an interesting sub-class of signed permutations
A Type System for Usage of Software Components

The aim of this article is to support component-based software engineering by modelling exclusive and inclusive usage of software components. Truong and Bezem describe in several papers abstract languages for component software with the aim to find bounds of the number of instances of components. Their language includes primitives for
instantiating and deleting instances of components and operators for sequential, alternative and parallel composition and a scope mechanism.
The language is here supplemented with the primitives use, lock and
free. The main contribution is a type system which guarantees the safety
of usage, in the following way: When a well-typed program executes a
subexpression use[x] or lock[x], it is guaranteed that an instance of x
is available
A New Elimination Rule for the Calculus of Inductive Constructions

Published in the post-proceedings of TYPES but actually not presented orally to the conferenceInternational audienceIn Type Theory, definition by dependently-typed case analysis can be expressed by means of a set of equations — the semantic approach — or by an explicit pattern-matching construction — the syntactic approach. We aim at putting together the best of both approaches by extending the pattern-matching construction found in the Coq proof assistant in order to obtain the expressivity and flexibility of equation-based case analysis while remaining in a syntax-based setting, thus making dependently-typed programming more tractable in the Coq system. We provide a new rule that permits the omission of impossible cases, handles the propagation of inversion constraints, and allows to derive Streicher's K axiom. We show that subject reduction holds, and sketch a proof of relative consistency
Designing data warehouses for geographic OLAP querying by using MDA

Data aggregation in Geographic Information Systems (GIS) is a desirable feature, spatial data are integrated in OLAP engines for this purpose. However, the development and operation of those systems is still a complex task due to methodologies followed. There are some ad hoc solutions that deal only with isolated aspects and do not provide developer and analyst with an intuitive, integrated and standard framework for designing all relevant parts. To overcome these problems, we have defined a model driven approach to accomplish Geographic Data Warehouse (GDW) development. Then, we have defined a data model required to implement and query spatial data. Its modeling is defined and implemented by using an extension of UML metamodel and it is also formalized by using OCL language. In addition, the proposal has been verified against a example scenario with sample data sets. For this purpose, we have accomplished a developing tool based on Eclipse platform and MDA standard. The great advantage of this solution is that developers can directly include spatial data at conceptual level, while decision makers can also conceptually make geographic queries without being aware of logical details.This work has been partially supported by the ESPIA project (TIN2007-67078) from the Spanish Ministry of Education and Science and by the QUASIMODO project (PAC08-0157-0668) from the Castilla-La Mancha Ministry of Education and Science (Spain). Octavio Glorio is funded by the University of Alicante under the 11th Latin American grant program
Visualization of complex biological systems: An immune response model using OpenGL

In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment