Miracle-dz/UniFAR-FTUs huggingface dataset:
NRC Publications Archive Archives des publications du CNRC

Databases and data warehouses contain an overwhelming volume of information that users must wade through in order to extract valuable and actionable knowledge to support the decision-making process. This contribution addresses the problem of automatically analyzing large multidimensional tables to get a concise representation of data, identify patterns and provide approximate answers to queries. Since data cubes are nothing but multi-way tables, we propose to analyze the potential of a probabilistic modeling technique, called non-negative multi-way array factorization, for approximating aggregate and multidimensional values. Using such a technique, we compute the set of components (clusters) that best ﬁt the initial data set and whose superposition approximates the original data. The generated components can then be exploited for approximately answering OLAP queries such as roll-up, slice and dice operations. The proposed modeling technique will then be compared against the log-linear modeling technique which has already been used in the literature for compression and out-lier detection in data cubes. Finally, three data sets will be used to discuss the potential beneﬁts of non-negative multi-way array factorization.
Joint Image-Text News Topic Detection and Tracking with And-Or Graph Representation

In this paper, we aim to develop a method for automatically detecting and tracking topics in broadcast news. We present a hierarchical And-Or graph (AOG) to jointly represent the latent structure of both texts and visuals. The AOG embeds a context sensitive grammar that can describe the hierarchical composition of news topics by semantic elements about people involved, related places and what happened, and model contextual relationships between elements in the hierarchy. We detect news topics through a cluster sampling process which groups stories about closely related events. Swendsen-Wang Cuts (SWC), an effective cluster sampling algorithm, is adopted for traversing the solution space and obtaining optimal clustering solutions by maximizing a Bayesian posterior probability. Topics are tracked to deal with the continuously updated news streams. We generate topic trajectories to show how topics emerge, evolve and disappear over time. The experimental results show that our method can explicitly describe the textual and visual data in news videos and produce meaningful topic trajectories. Our method achieves superior performance compared to state-of-the-art methods on both a public dataset Reuters-21578 and a self-collected dataset named UCLA Broadcast News Dataset.
Proving Model Transformations

Within the MDA context, model transformations (MT) play an important role as they ensure consistency and significant time savings. Several MT frameworks have been deployed and successfully used in practice. Like for any software, the development of MT programs is error prone. However there is limited support for verification and validation in current MDA technologies. This paper presents an approach to prove model transformations. Model transformations are firstly formalized in B. Then the B provers will be used to analyze and prove the correctness of transformation rules w.r. t. met models and transformation invariants. We also analyze and prove the consistency of transformation rules w.r. t. each other.
Unmanned helicopter waypoint trajectory tracking using model predictive control

A Model Predictive Control Based Trajectory Tracking (MPCTT) system for small unmanned helicopters is presented. A linear model predictive controller is used to take advantage of the fast algorithms available to solve convex optimization problems. The proposed MPCTT system is compared with a velocity tracking and a position tracking system implemented with classical PIDs from previous research work. Obtained simulation results demonstrate the superiority of the proposed MPCTT approach, generating a substantially less control effort in order to track waypoint trajectories. The unmanned helicopter used for the proposed MPCTT system is considered as a (linearized) linear state-space model obtained for hovering and slow motion; however, as shown, the MPCTT is robust enough to perform trajectory tracking under a cruise flight mode, too.
Dispersed Oil Disrupts Microbial Pathways in Pelagic Food Webs

Most of the studies of microbial processes in response to the Deepwater Horizon oil spill focused on the deep water plume, and not on the surface communities. The effects of the crude oil and the application of dispersants on the coastal microbial food web in the northern Gulf of Mexico have not been well characterized even though these regions support much of the fisheries production in the Gulf. A mesocosm experiment was carried out to determine how the microbial community off the coast of Alabama may have responded to the influx of surface oil and dispersants. While the addition of glucose or oil alone resulted in an increase in the biomass of ciliates, suggesting transfer of carbon to higher trophic levels was likely; a different effect was seen in the presence of dispersant. The addition of dispersant or dispersed oil resulted in an increase in the biomass of heterotrophic prokaryotes, but a significant inhibition of ciliates, suggesting a reduction in grazing and decrease in transfer of carbon to higher trophic levels. Similar patterns were observed in two separate experiments with different starting nutrient regimes and microbial communities suggesting that the addition of dispersant and dispersed oil to the northern Gulf of Mexico waters in 2010 may have reduced the flow of carbon to higher trophic levels, leading to a decrease in the production of zooplankton and fish on the Alabama shelf.
Exercise-cognition interaction : neuroscience perspectives

1. History of Research into the Acute Exercise-Cognition Interaction2. History of Research into the Chronic Exercise-Cognition Interaction3. Animal Models of the Exercise-Brain Interaction4. Beyond the Catecholamines Hypothesis for an Acute Exercise-Cognition Interaction: A Neurochemical Perspective5. Acute Exercise and Event-Related Potential: Current Status and Future Prospective6. Acute Exercise and Cognition: Effects of Cerebral Oxygenation and Blood Flow7. Reticular Activation Hypofrontality Theory8. The Evidence for a Neurochemical Rationale for a Chronic Exercise-Cognition Interaction9. The Chronic Exercise-Cognition Interaction: fMRI Research10. The Chronic Exercise-Cognition Interaction: EEG Research11. Effects of Fitness on the Exercise-Cognition Interaction12. `"Cogito ergo sum" or "ambulo ergo sum"? New Perspectives in Developmental Exercise and Cognition Research13. Acute Exercise and Cognition in Children and Adolescents: The Roles of Testosterone and Cortisol14. The Chronic Exercise-Cognition Interaction in the Elderly15. The Chronic Exercise-Cognition Interaction and Parkinson's Disease16. The Chronic Exercise-Cognition Interaction and Dementia and Alzheimer's Disease17. The Chronic Exercise-Cognition Interaction and Diabetes18. The Chronic Exercise-Cognition Interaction and Attention Deficit Hyperactivity Disorder19. The Chronic Exercise-Cognition Interaction and Breast Cancer Survivors20. The Chronic Exercise-Cognition Interaction and Cardiovascular Risk Factors21. The Chronic Exercise-Cognition Effect in Overweight and Obese Children22. Exercise-Cognition Interaction: State of the Art and Future Research
Absent Autonomy: Relational Competence and Gendered Paths to Faculty Self-Determination in the Promotion and Tenure Process

This research examines ways in which men and women university faculty sought self-determination in the promotion and tenure (P&T) process. Self-Determination Theory (SDT; Deci & Ryan, 2012) research tends to view autonomy as the central factor in self-determination, taking priority over other psychological needs of relatedness and competence. The P&T process occurs within a context that inherently limits autonomy, providing a unique opportunity to examine experiences of relatedness and competence when autonomy is constrained. We used a qualitative research strategy with a matched case study design to explore how individuals experience the constructs of SDT (i.e., autonomy, competence, and relatedness) within the P&T process. Our project focuses on faculty in science, technology, engineering, and mathematics (STEM) departments undergoing P&T review at one university. Women faculty in STEM were compared with men faculty at the same rank and in similar departments concurrently going through P&T review. Findings showed that men reported experiencing self-determination via informational competence whereas women approached self-determination through relational competence. Creating a level playing field for faculty navigating the P&T process requires being attuned to different paths to self-determination, fostering relationships between faculty, and clarifying policies and procedures.
Privacy preserving in big data sets through multiple shuffle

Big data privacy-preserving has attracted increasing attention of researchers in recent years. But existing models are so complicated and time-consuming that they are not easy to implement. In this paper, we propose a more feasible and efficient model for big data sets privacy-preserving using shuffling multiple attributes(M-Shuffle) to achieve a tradeoff between data utility and privacy. Our strategy is firstly categorize all the records into some groups using K-means algorithm according to the sensitive attributes. Then we choose the columns to be shuffled using entropy. At last we introduce the random shuffle algorithm to our model to break the correlation among the columns of big data sets. Experiments on real-world datasets show that our framework achieves excellent data utility and efficiency while satisfying privacy-preserving.
A psychoacoustic model with Partial Spectral Flatness Measure for tonality estimation

Psychoacoustic studies show that the strength of masking is, among others, dependent on the tonality of the masker: the effect of noise maskers is stronger than that of tone maskers. Recently, a Partial Spectral Flatness Measure (PSFM) was introduced for tonality estimation in a psychoacoustic model for perceptual audio coding. The model consists of an Infinite Impulse Response (IIR) filterbank which considers the spreading effect of individual local maskers in simultaneous masking. An optimized (with respect to audio quality and computational efficiency) PSFM is now compared to a similar psychoacoustic model with prediction based tonality estimation in medium (48 kbit/s) and low (32 kbit/s) bit rate conditions (mono) via subjective quality tests. 15 expert listeners participated in the subjective tests. The results are depicted and discussed. Additionally, we conducted the subjective tests with 15 non-expert consumers whose results are also shown and compared to those of the experts.
Towards massive spatial data validation with SpatialHadoop

Spatial data usually encapsulate semantic characterization of features which carry out important meaning and relations among objects, such as the containment between the extension of a region and of its constituent parts. The GeoUML methodology allows one to bring the gap between the definition of spatial integrity constraints at conceptual level and the realization of validation procedures. In particular, it automatically generates SQL validation queries starting from a conceptual specification and using predefined SQL templates. These queries can be used to check data contained into spatial relational databases, such as PostGIS. However, the quality requirements and the amount of available data are considerably growing making unfeasible the execution of these validation procedures. The use of the map-reduce paradigm can be effectively applied in such context since the same test can be performed in parallel on different data chunks and then partial results can be combined together to obtain the final set of violating objects. Pigeon is a data-flow language defined on top of Spatial Hadoop which provides spatial data types and functions. The aim of this paper is to explore the possibility to extend the GeoUML methodology by automatically producing Pigeon validation procedures starting from a set of predefined Pigeon macros. These scripts can be used in a map-reduce environment in order to make feasible the validation of large datasets.
A framework for the Virtual Heterogeneous Associative Machine

The authors give an overview of the Heterogeneous Associative Computing paradigm (HAsC) for heterogeneous computing, being developed at Kent State University. They then discuss the concept of the Virtual Heterogeneous Associative Machine (VHAM) which is an augmented view of the virtual machine concept as it applies to HAsC. The VHAM instruction set is then outlined along with the meta-commands used to maintain the instructions. Last the VHAM Administrator is introduced and discussed as that portion of HAsC which maintains the VHAM and facilitates the associative principles applied in HAsC. <<ETX>>
Nonparametric Relational Learning for Social Network Analysis

Social networks usually involve rich collections of objects, which are jointly linked into complex relational networks. Social network analysis has gained in importance due to the growing availability of data on novel social networks, e.g. citation networks, Web 2.0 social networks like facebook, and the hyperlinked internet. Recently, the inflnite hidden relational model (IHRM) has been developed for the analysis of complex relational domains. The IHRM extends the expressiveness of a relational model by introducing for each object an inflnite-dimensional hidden variable as part of a Dirichlet process mixture model. In this paper we discuss how the IHRM can be used to model and analyze social networks. In such an IHRM-based social network model, each edge is associated with a random variable (RV) and the probabilistic dependencies between these RVs are specifled by the model based on the relational structure. The hidden variables, one for each object, are able to transport information such that non-local probabilistic dependencies can be obtained. The IHRM provides efiective relationship prediction and cluster analysis for social networks. The experimental analysis is performed on two social network applications. The flrst application is an analysis of the cooperative efiect in a recommendation framework where both user properties and item properties are taken into account. The experimental results demonstrate that the IHRM provides good prediction accuracy for user preference on movies and gives interpretable clusters of users and items. In the second experiment we apply the IHRM to Sampson’s monastery data, and obtain a grouping of the actors that agrees with results from previous publications. As an additional contribution of this paper, we present a new mean fleld approximation to inference in the IHRM.
ORLANDO LAWRENCE NATIONAL LABORATORY ERNEST BERKELEY Branes and N ~ 2 Theories in Two Dimensions

Type IIA brane configurations are used to construct N = 2 supersymmetric gauge theories in two dimensions. Using localization of chiral multiplets in ten-dimensional spacetime, supersymmetric non-linear sigma models with target space such as Cpn 1 and the Grassmann manifolds are studied in detail. The quantum properties of these models are realized in M theory by taking the strong Type IIA coupling limit. The brane picture implies an equivalence between the parameter space of N = 2 supersymmetric theories in two dimensions and the moduli space of vacua of N = 2 supersymmetric gauge theories in four dimensions. Effects like level-rank duality are interpreted in the brane picture as continuation past infinite coupling. The BPS solitons of the cpn-l model are identified as topological excitations of a membrane and their masses are computed. This provides the brane realization of higher rank tensor representations of the flavor group.
Electro-Tactile Display with Localized High-Speed Switching

The electro-tactile display with localized high-speed switching is a novel type of electro-tactile display based on H-Bridge circuit that uses only one electrical source at a time. By using this display electrical stimulations can easily be presented and measured simultaneously. In this paper, other new methods for electrical stimulation, including scan-type ectrical stimulation and dipole electrical stimulation, are introduced.
Fast Search of Sequences of Multiple Moving Objects

In this paper, we propose a technique to captures the features of a moving object at sampled instances. These features of every sampled instance are mapped from the high-dimensional feature space into a point in low-dimensional distance space. Thus, each moving object, is represented by a sequence of points that is considered the time-varying feature trajectory of the object in the low-dimensional space. Each of these sequences is represented by a minimum bounding box (MBB) to reduce further reduce the storage requirements of an index structure. The proposed technique indexes a sequence by the MBBs of its objects using a spatial access method (SAM), such as an R-tree to speed up the search. The proposed technique does not result in any false dismissal, but might contain a few false alarms, which are remove by a two-step refinement process.
P.M. assisted synchronous reluctance drive for minimal hybrid application

This paper deals with the design realization and full control of a PM assisted synchronous reluctance machine (PMASR) for minimal hybrid electric vehicle. The work is based on a European Research Project that involved seven partners from five different countries (including universities, motor producers and car makers) and that defined the specification for both a PMASR prototype and a switched reluctance prototype. The adopted motor design approach is illustrated in the paper together with the observer-based control strategy. Experimental results are given, from the prototype drive.
Resistive Bridging Fault Simulation of Industrial Circuits

We report the successful application of a resistive bridging fault (RBF) simulator to industrial benchmark circuits. Despite the slowdown due to the consideration of the sophisticated RBF model, the run times of the simulator were within an order of magnitude of the run times for pattern-parallel complete-circuit stuck-at fault simulation. Industrial-size circuits, including a multi-million-gates design, could be simulated in reasonable time despite a significantly higher number of faults to be simulated compared with stuck-at fault simulation.
Optical tomography: forward and inverse problems

This is a review of recent mathematical and computational advances in optical tomography. We discuss the physical foundations of forward models for light propagation on microscopic, mesoscopic and macroscopic scales. We also consider direct and numerical approaches to the inverse problems that arise at each of these scales. Finally, we outline future directions and open problems in the field.
Painting in situ: the benefits of live mural painting for residents on two secure long-term care dementia units

Abstract Quality of life in long-term care is a growing concern for clinicians and social scientists. Attention is turning increasingly to the impact of the institutional environment on residents’ experience of themselves and others. In an effort to improve residents’ experience, distraction and illusion murals are being created to disguise exit doors and decrease exit-seeking behaviour. Most research focuses on the effect on exit-seeking behaviour once murals are complete. This paper will discuss benefits for residents in terms of sustained attention and aesthetic awareness, memory and gender identity and community-building that were realized during the painting in situ.
Modeling landscapes with ridges and rivers: bottom up approach

We present a new fractal based method of generating realistic models of natural landscapes. In this paper, we describe a three-steps method that produces a terrain mesh using ridge lines and rivers drainage network. As opposed to previous methods that compute water erosion for a given terrain model --- Digital Elevation Map ---, our terrain mesh is generated constrained by a precomputed set of ridge lines and rivers network. A skeleton of a ridges and rivers network is computed and stored in a Digital Elevation Map (D.E.M.) as initial values. Then, the elevations data set is enriched using a novel interpolation method based on a Midpoint Displacement's Inverse process. Finally, a midpoint displacement subdivision is applied to interpolate the remaining elevation coordinates. The resulting terrain meshes lead to naturalistic landscape models and our method seems to be very promising. Images produced by our model are presented.
A formal model of Diffie-Hellman using CSP and rank functions

Formal analysis techniques have proved successful in findin g flaws in security protocols. Such techniques typically assume the prese nce of perfect encryption, an assumption that is clearly not true in practice. Whe n w aim to prove the correctness of a protocol, we must be more careful in assu ming bounds on the capabilities of the intruder: a real intruder can, and wi ll, exploit properties of the underlying cryptosystem. The Diffie-Hellman key agre em nt scheme exhibits a rich set of algebraic properties, and this report su ggests how the existing CSP approach can be extended to incorporate these propertie s in a rank function verification. The utility of the approach is established by p erforming an analysis of a key agreement protocol from the CLIQUES suite.
Researcher Profiling for Researcher Analysis Service

This study examines a method of generating comprehensive profiling information for a researcher analysis service. In addition to basic and performance-based information about researchers necessary to generate profiling information, we introduce researcher performance index models for researcher analysis service. The models can that measure qualitative and quantitative performance, researcher influence, and growth potential, which are necessary to analyze the skills of a researcher from multiple perspectives. We measure the qualitative performance index of researchers by using the citation index of the papers they have published. The quantitative performance index can be measured based on a researcher’s published papers. The Influence index measures the social influence of researchers according to their academic work. The growth potential index measures the speed at which a researcher improves research performance. We expect to develop a researcher analysis service that can evaluate a researcher’s performance and enhance his or her research abilities.
Architectures for Federation of Process-Centered Environments

We describe two models for federating process centered environments homogeneous federation where the interoperability is among distinct process models enacted by di erent copies of the same system and heterogeneous federation with interoperability among distinct process enact ment systems We identify the requirements and possible architectures for each model The bulk of the paper presents the speci c architecture and infrastructure for homogeneous federation we realized in the Oz system We brie y consider how Oz might be integrated into a heterogeneous federation to serve as one of its interoperating PCEs