Miracle-dz/UniFAR-FTUs huggingface dataset:
Principe local-global pour les zéro-cycles sur les surfaces réglées

Soient k un corps et X une k-variété projective, lisse et géométriquement intègre. Un zéro-cycle sur X est, rappelons-le, une combinaison linéaire à coefficients entiers de points fermés de X . On note k(P ) le corps résiduel en un point fermé P ∈ X . Le degré (sur k) d’un zéro-cycle ∑ nP P est l’entier ∑ P nP [k(P ) : k] ∈ Z. Le groupe de Chow CH0(X) des zéro-cycles sur X est le quotient du groupe Z0(X) des zéro-cycles par la relation d’équivalence rationnelle. L’application degré sur les zéro-cycles passe au quotient par l’équivalence rationnelle. On note A0(X) ⊂ CH0(X) le sousgroupe des classes de zéro-cycles de degré zéro et Br(X) = H ét(X, Gm) le groupe de Brauer de X . On note α(P ) ∈ Br(k(P )) l’évaluation en P d’un élément α ∈ Br(X) et (α, P ) = Coresk(P )/k(α(P )) ∈ Br(k). En envoyant le couple (α, ∑ P nP P ) sur ∑ P nP (α, P ) ∈ Br(k), on définit un accouplement Br(X) × Z0(X) → Br(k) qui passe au quotient par l’équivalence rationnelle et définit un accouplement biadditif Br(X)× CH0(X)→ Br(k). Supposons que k est un corps de nombres. Soit Ω l’ensemble de ses places. Soit kv le complété de k en v ∈ Ω. Notons Xv = X ×k kv. Le groupe de Brauer Br(kv) s’injecte dans Q/Z par l’invariant invv de la théorie du corps de classes local. Ceci définit pour chaque place v un accouplement biadditif Br(Xv)×CH0(Xv)→ Q/Z. Un élément de Br(X) s’annule sur CH0(Xv) pour presque toute place v. On a donc un accouplement biadditif Br(X)× ∏
MPC implementation in a PLC based on Nesterov's fast gradient method

This work presents a linear quadratic model predictive controller (MPC) implemented in an industrial programable logic controller (PLC). The control law is calculated by solving on-line the quadratic programming problem derived from the optimization control problem of MPC. Nesterov's fast gradient algorithm has been used to solve the corresponding linear quadratic MPC problems with input constraints. The predictive controller has been implemented in a Schneider Electric M340 using the standard structured language from the IEC 1131.1 norm. The memory and computational time requirements of the proposed implementation have been characterized through extensive simulations. In addition, the properties of the proposed controller have been experimentally demonstrated using a test-bed in which the MPC running in the M340 controls a model of a quadruple-tank process simulated in Matlab/Simulink through an OPC server.
Sentiment Analysis for Social Networks Using Machine Learning Techniques

The tremendous of the overall enormous net has conveyed a present day way of communicating the feelings of individuals. It's additionally a medium with a vast amount of data in which clients can see the assessment of different clients which can be ordered into exceptional entailment summons and are progressively more boom as a key component in decision making. This paper adds to the supposition assessment for customers assessment class that is utilized to analyze the records inside the type of the assortment of tweets wherein investigates are very unstructured and are both high fine or terrible, or somewhere in the middle of these . For this we first pre-prepared the dataset, after that extract the adjective from the dataset that has a couple of significance this is alluded to as capacity vector, at that point decided on the component vector posting and from that point accomplished device examining based write calculations particularly navie bayes, most entropy and svm along the edge of the semantic introduction based absolutely based on word net which extracts synonyms and similarity for the content characteristic. In the end, we measured the performance of the classifier in terms of considering, precision and accuracy.
Results of the French Evalda-Media evaluation campaign for literal understanding

The aim of the Media-Evalda project is to evaluate the understanding capabilities of dialog systems. This paper presents the Media protocol for speech understanding evaluation and describes the results of the June 2005 literal evaluation campaign. Five systems, both symbolic or corpus-based, participated to the evaluation which is based on a common semantic representation. Different scorings have been performed on the system results. The understanding error rate, for the Full scoring is, depending on the systems, from 29% to 41.3%. A diagnosis analysis of these results is proposed.
A QoE-based control system for bitrate adaption of wireless-accessed video stream

In this paper, we design and develop a Quality of Experience (QoE) based control system for bitrate adaption of wireless-accessed video stream. The system is designed to utilize the bandwidth resource better and improve user's viewing experience as much as possible. We set up a QoE prediction model based on classification decision tree with both objective and subjective factors taken into account, and design an algorithm for bitrate adaption of mobile video stream. The experimental result shows that the application of the QoE-based control system can significantly improve the QoE of mobile video.
Fingerprint classification using scale-invariant feature transform

In this paper an application of SIFT (scale-invariant feature transform) is presented. Even though the SIFT is a computer vision algorithm, its properties confirmed by the described algorithm allow for classification of the fingerprints. The described experiment was performed using FVC2004 fingerprints database. We obtained FRR (false rejection ratio) of about 15 % and FAR (false acceptance ratio) equal to 0 %. This result allows for application in the access control to restricted areas, i.e., if FAR has to be low. In general, SIFT can be considered as the first stage of classification of fingerprints in the database searching.
Simulation based bio engineering and science: From protein dynamics to DNA tile design

In this paper, we briefly summarize the history of elastic network model (ENM) as a useful atomistic modeling tool for biosystems. Various ENMs have been developed and mainly applied to the study on protein dynamics. Recently, its application area was extended to nano structure design and analysis. ENM based normal mode analysis and geometric interpolation method explain well not only the relationship between structure and function of proteins, but also the mechanism of self-assembly of DNA tiles in a solution. This computationally adequate and effective tool will play an important role in the area of “simulation based bio engineering and science”.
Quantitative Trait Loci for Interhemispheric Commissure Development and Social Behaviors in the BTBR T+ tf/J Mouse Model of Autism

Background Autism and Agenesis of the Corpus Callosum (AgCC) are interrelated behavioral and anatomic phenotypes whose genetic etiologies are incompletely understood. We used the BTBR T+ tf/J (BTBR) strain, exhibiting fully penetrant AgCC, a diminished hippocampal commissure, and abnormal behaviors that may have face validity to autism, to study the genetic basis of these disorders. Methods We generated 410 progeny from an F2 intercross between the BTBR and C57BL/6J strains. The progeny were phenotyped for social behaviors (as juveniles and adults) and commisural morphology, and genotyped using 458 markers. Quantitative trait loci (QTL) were identified using genome scans; significant loci were fine-mapped, and the BTBR genome was sequenced and analyzed to identify candidate genes. Results Six QTL meeting genome-wide significance for three autism-relevant behaviors in BTBR were identified on chromosomes 1, 3, 9, 10, 12, and X. Four novel QTL for commissural morphology on chromosomes 4, 6, and 12 were also identified. We identified a highly significant QTL (LOD score = 20.2) for callosal morphology on the distal end of chromosome 4. Conclusions We identified several QTL and candidate genes for both autism-relevant traits and commissural morphology in the BTBR mouse. Twenty-nine candidate genes were associated with synaptic activity, axon guidance, and neural development. This is consistent with a role for these processes in modulating white matter tract development and aspects of autism-relevant behaviors in the BTBR mouse. Our findings reveal candidate genes in a mouse model that will inform future human and preclinical studies of autism and AgCC.
A Multimodal System for Real-Time Action Instruction in Motor Skill Learning

We present a multimodal coaching system that supports online motor skill learning. In this domain, closed-loop interaction between the movements of the user and the action instructions by the system is an essential requirement. To achieve this, the actions of the user need to be measured and evaluated and the system must be able to give corrective instructions on the ongoing performance. Timely delivery of these instructions, particularly during execution of the motor skill by the user, is thus of the highest importance. Based on the results of an empirical study on motor skill coaching, we analyze the requirements for an interactive coaching system and present an architecture that combines motion analysis, dialogue management, and virtual human animation in a motion tracking and 3D virtual reality hardware setup. In a preliminary study we demonstrate that the current system is capable of delivering the closed-loop interaction that is required in the motor skill learning domain.
A comparison between divergence measures for network anomaly detection

This paper deals with the detection of flooding attacks which are the most common type of Denial of Service (DoS) attacks. We compare 2 divergence measures (Hellinger distance and Chi-square divergence) to analyze their detection accuracy. The performance of these statistical divergence measures are investigated in terms of true positive and false alarm ratio. A particular focus will be on how to use these measures over Sketch data structure, and which measure provides the best detection accuracy. We conduct performance analysis over publicly available real IP traces (MAWI) collected from the WIDE backbone network. Our experimental results show that Chi-square divergence outperforms Hellinger distance in network anomalies detection.
Compositional deadlock detection for rendezvous communication

Concurrent programming languages are growing in importance with the advent of multi-core systems. However, concurrent programs suffer from problems, such as data races and deadlock, absent from sequential programs. Unfortunately, traditional race and deadlock detection techniques fail on both large programs and small programs with complex behaviors. In this paper, we present a compositional deadlock detection technique for a concurrent language--SHIM--in which tasks run asynchronously and communicate using synchronous CSP-style rendezvous. Although SHIM guarantees the absence of data races, a SHIM program may still deadlock if the communication protocol is violated. Our previous work used NuSMV, a symbolic model checker, to detect deadlock in a SHIM program, but it did not scale well with the size of the problem. In this work, we take an incremental, divide-and-conquer approach to deadlock detection. In practice, we find our procedure is faster and uses less memory than the existing technique, especially on large programs, making our algorithm a practical part of the compilation chain.
Combining Chat and Task-Based Multimodal Dialogue for More Engaging HRI: A Scalable Method Using Reinforcement Learning

We develop the first system to combine task-based and chatbot-style dialogue in a multimodal system for Human-Robot Interaction. We show that Reinforcement Learning is beneficial for training dialogue management (DM) in such systems -- providing a scalable method for training from data and/or simulated users. We first train in simulation, and evaluate the benefits of a combined chat/task policy over systems which can only perform chat or task-based conversation. In a real user evaluation, we then show that a trained combined chat/task multimodal dialogue policy results in longer dialogue interactions than a rule-based approach, suggesting that the learned dialogue policy provides a more engaging mixture of chat and task interaction than a rule-based DM method.
A semi-analytic dynamical friction model for cored galaxies

We present a dynamical friction model based on Chandrasekhar’s formula that reproduces the fast inspiral and stalling experienced by satellites orbiting galaxies with a large constant density core. We show that the fast inspiral phase does not owe to resonance. Rather, it owes to the background velocity distribution function for the constant density core being dissimilar from the usually-assumed Maxwellian distribution. Using the correct background velocity distribution function and the semi-analytic model from Petts, Gualandris & Read (2015), we are able to correctly reproduce the infall rate in both cored and cusped potentials. However, in the case of large cores, our model is no longer able to correctly capture core-stalling. We show that this stalling owes to the tidal radius of the satellite approaching the size of the core. By switching off dynamical friction when rt(r) = r (where rt is the tidal radius at the satellite’s position) we arrive at a model which reproduces the N-body results remarkably well. Since the tidal radius can be very large for constant density background distributions, our model recovers the result that stalling can occur for Ms/Menc 1, where Ms and Menc are the mass of the satellite and the enclosed galaxy mass, respectively. Finally, we include the contribution to dynamical friction that comes from stars moving faster than the satellite. This next-to-leading order effect becomes the dominant driver of inspiral near the core region, prior to stalling.
Research laboratory for power Electronic generator systems in wind turbines comprising converters, generators, interaction and grid interaction

Power generated from wind is actually a very great and a very fast growing renewable source of the world energy consumption. Optimizing performance and costs is an important issue for wind turbine generators. A laboratory for comprehensive research on the four types of power electronic generator systems for wind turbine generators and for their grid integration is presented. It consists of drives in a downscaled power range, special developed devices for generating test conditions and for measurement as well as of numerical simulations. The laboratory is presented and research including measurements are shown.
CREST-a current estimator for CMOS circuits

CREST is a pattern-independent current estimation approach developed to support electromigration analysis tools. It uses the powerful, original concept of probabilistic simulation to generate accurate estimates of the expected current waveforms efficiently. The original implementation of CREST is extended to circuits containing pass transistors, reconvergent fanout, and feedback, and heuristics to simulate circuits with large reconvergent fanout or feedback blocks efficiently are provided. The results of using CREST on several real circuits are presented. <<ETX>>
Fault localization prioritization: Comparing information-theoretic and coverage-based approaches

Test case prioritization techniques seek to maximize early fault detection. Fault localization seeks to use test cases already executed to help find the fault location. There is a natural interplay between the two techniques; once a fault is detected, we often switch focus to fault fixing, for which localization may be a first step. In this article we introduce the Fault Localization Prioritization (FLP) problem, which combines prioritization and localization. We evaluate three techniques: a novel FLP technique based on information theory, FLINT (Fault Localization using INformation Theory), that we introduce in this article, a standard Test Case Prioritization (TCP) technique, and a “test similarity technique” used in previous work. Our evaluation uses five different releases of four software systems. The results indicate that FLP and TCP can statistically significantly reduce fault localization costs for 73% and 76% of cases, respectively, and that FLINT significantly outperforms similarity-based localization techniques in 52% of the cases considered in the study.
Efficient Stereo with Accurate 3-D Boundaries

This paper presents methods for recovering accurate binocular disparity estimates in the vicinity of 3D surface discontinuities. Of particular concern are methods that impact coarse-to-fine, block matching as it forms the basis of the fastest and resource efficient disparity estimation procedures. Two advances are put forth. First, a novel approach to coarse-to-fine processing is presented that adapts match window support across scale to ameliorate corruption of disparity estimates near 3D boundaries. Second, a novel formulation of half-occlusion cues within the coarse-to-fine, block matching framework is described to inhibit false matches that can arise in regions near occlusions. Empirical results show that incorporation of these advances in coarse-to-fine, block matching reduces disparity errors by more than a factor of two, while performing little extra computation.
Techniques for efficient in-memory checkpointing

Checkpointing is a pivotal technique in system research, with applications ranging from crash recovery to replay debugging. In this paper, we evaluate a number of in-memory checkpointing techniques and compare their properties. We also present a new compiler-based checkpointing scheme which improves state-of-the-art performance and memory guarantees in the general case. Our solution relies on a shadow state to efficiently store incremental in-memory checkpoints, at the cost of a smaller user-addressable virtual address space. Contrary to common belief, our results show that in-memory checkpointing can be implemented efficiently with moderate impact on production systems.
Building blocks of development [robot learning]

This article provides a brief introduction to hierarchical discriminant regression and lobe component analysis, two algorithms usable in components of the mental architecture of an AMD system. The processes that guide the development of the "mind" of an autonomously-learning robot must be given within the developmental program. This is what must drive the learning of the robot's eventual behaviors and skills, which emerges in response to the robot's interactions with the environment. A biologically sophisticated version of a developmental program, where behaviors and skills autonomously emerge in the robot with a human level of complexity, has not yet been written. But there has been progress in creating developmental "building blocks. " These are designed to be used in components of the developmental program. These algorithms must be specially designed to handle many of the difficult constraints of AMD. In this article, we introduce two such algorithms, briefly outline their purpose and key features, and describe how to use sample versions available on the El lab's Web site
Modeling scenarios for the performance prediction of distributed real-time embedded systems

Autonomous defence systems are typically characterized by hard constraints on space, weight and power. These constraints have a strong impact on the non-functional properties and especially performance of the final system. System execution modelling tools permit early prediction of the performance of model driven systems; however they are intended for one shot analysis, not for repeatable, interactive use. In this paper we propose a Domain Specific Language for describing scenarios to repeatedly test a system execution model within a Synthetic Environment. We exemplify it by describing and executing a scenario involving an UAV and a CMS.
The Crucial Role of Alcohol Dehydrogenase Adh3 in Kluyveromyces marxianus Mitochondrial Metabolism

The function of mitochondrial Adh3 in the thermotolerant yeast Kluyveromyces marxianus was investigated. An ADH3-disrupted mutant exhibited growth retardation on non-fermentable carbon sources, except for ethanol, and this was suppressed by supplementation with antioxidants. Detailed analysis of the phenotype revealed that the mutant showed an increase in the activity of NADH dehydrogenase, sensitivity to H2O2, and accumulation of reactive oxygen species (ROS), and that these carbon sources increased the activity of succinate dehydrogenase. The increase in both activities may reflect enhanced expression of both dehydrogenases by elevation of their substrate levels. The ROS level became low when antioxidants were added. These findings suggest that the ADH3 mutation and such carbon sources cause an elevation of the substrate level of the respiratory chain and eventually of the ROS level via increased expression of primary dehydrogenases, which in turn causes cell growth retardation. Adh3 might thus play a crucial role in the control of the NADH/NAD+ balance in mitochondria.
DVFS-Aware Consolidation for Energy-Efficient Clouds

Nowadays, data centers consume about 2% of the worldwide energy production, originating more than 43 million tons of CO2 per year. Cloud providers need to implement an energy-efficient management of physical resources in order to meet the growing demand for their services and ensure minimal costs. From the application-framework viewpoint, Cloud workloads present additional restrictions as 24/7 availability, and SLA constraints among others. Also, workload variation impacts on the performance of two of the main strategies for energy-efficiency in Cloud data centers: Dynamic Voltage and Frequency Scaling (DVFS) and Consolidation. Our work proposes two contributions: 1) a DVFS policy that takes into account the trade-offs between energy consumption and performance degradation; 2) a novel consolidation algorithm that is aware of the frequency that would be necessary when allocating a Cloud workload in order to maintain QoS. Our results demonstrate that including DVFS awareness in workload management provides substantial energy savings of up to 39.14% for scenarios under dynamic workload conditions.
A Rational Krylov Method Based on Hermite Interpolation for Nonlinear Eigenvalue Problems

This paper proposes a new rational Krylov method for solving the nonlinear eigenvalue problem: $A(\lambda)x = 0$. The method approximates $A(\lambda)$ by Hermite interpolation where the degree of the interpolating polynomial and the interpolation points are not fixed in advance. It uses a companion-type reformulation to obtain a linear generalized eigenvalue problem (GEP). To this GEP we apply a rational Krylov method that preserves the structure. The companion form grows in each iteration and the interpolation points are dynamically chosen. Each iteration requires a linear system solve with $A(\sigma)$, where $\sigma$ is the last interpolation point. The method is illustrated by small- and large-scale numerical examples. In particular, we illustrate that the method is fully dynamic and can be used as a global search method as well as a local refinement method. In the last case, we compare the method to Newton's method and illustrate that we can achieve an even faster convergence rate.