Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of Autonomy-based Systems: Tuning Emergent Cooperation

This paper presents our work, which relates to the general problem of adaptability for artificial entities. More particularly, our work tackles the problem of performance control in systems made up of adaptable entities. Control is discussed in the case of classical systems and revised through new definitions in the framework we are concerned with. In this context, reliability and efficiency (performances) are related to adaptability. We propose to focus more attention on the human-machine interaction in the design process, and to integrate techno-genesis of the software tools in the overall estimation of performances and in the approach of emergence. A model based on autonomy and focusing on the capabilities of interactions of an entity (with its environment as well as with other entities) is proposed. We report quantitative measurements (yielded by intensive experiments) that enable to understand the mechanisms that make a pool of operationally autonomous entities achieve a task of object regrouping. According to our theoretical apprehension of control and performance, these mechanisms are analyzed through statistical properties of the system, thus moving the focus from crude efficiency in terms of speed toward appropriate statistical properties reflecting non-deterministic but satisfactory behaviors. As a result, this application allows us to set-up experiments that exhibit the emergence of properties at a collective level and illustrate that cooperation at a collective level is not necessary incompatible with conflict situations at individual level. It also shows the powerness of an appropriate architecture of the software entities and their relationships aimed at increasing scalability, flexibility and robustness of the applications.
Object detection in urban environment

This paper deals with problems of surface moving object detection in urban environmental conditions in video sequences acquired in visible spectrum using various techniques. The objects feature is changed in dependence on time and space condition such as weather condition, urban environment, etc. In this article, we proposed a combined method for object detection in video sequences using three techniques that are a template matching technique, a threshold technique and a background subtraction. The video sequences were captured using Samsung HMX - F90 with a resolution 1280× 720. However, to test the algorithm, we have resized to the resolution 160×120. The designed algorithms were tested in program Matlab.
The Informational Advantage of Foreign Investors: An Empirical Study of the Swedish Bond Market

This paper uses daily capital flows to the Swedish bond market to analyse the relative information endowment of domestic and foreign investors. Using the standard framework of a noisy rational expectations equilibrium it is shown that foreign investors are, on average, better informed than domestic investors. The better information of foreign investors is related to pan-European factors, including ITL bond yields, future order flow, as well as pure Swedish factors.
Dimensionality Reduction for Data in Multiple Feature Representations

In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representations are typically high dimensional and assume diverse forms. Thus finding a way to transform them into a unified space of lower dimension generally facilitates the underlying tasks, such as object recognition or clustering. We describe an approach that incorporates multiple kernel learning with dimensionality reduction (MKL-DR). While the proposed framework is flexible in simultaneously tackling data in various feature representations, the formulation itself is general in that it is established upon graph embedding. It follows that any dimensionality reduction techniques explainable by graph embedding can be generalized by our method to consider data in multiple feature representations.
Oriented geodesic distance based non-local regularisation approach for optic flow estimation

Optical flow (OF) estimation needs spatial coherence regularisation, due to local image noise and the well-known aperture problem. More recently, OF local-region regularisation has been extended to larger or non-local region of regularisation to further deal with the aperture problem. After careful literature review, it has been determined that the criteria used for deciding the degree of motion coherence can be further improved. For this reason, we propose an oriented geodesic distance based motion regularisation scheme. The proposed approach is particular useful in reducing errors in estimating motions along object boundaries, and recovering motions for nearby objects with similar appearance. Experiment results, compared to leading-edge non-local regularisation schemes, have confirmed the superior performance of the proposed approach.
Autonomy Supportive Instruction as it relates to Students' Motivational Beliefs on an ePortfolio Project: The Moderating Role of Culturally Based Learning Preferences

This study investigated students’ perceptions of autonomy support from an instructor in relation to students’ motivational beliefs on an ePortfolio project. The motivational beliefs of interest included: Effort/Importance, felt Pressure/Tension, and Value/Usefulness. These relationships were further examined with particular focus on the potential moderating role of students’ culturally based learning preferences as outlined in Parrish and Linder-VanBerschot’s (2010) Cultural Dimensions of Learning Framework (CDLF). This study was quasi-experimental, survey-based research supported by self-reported data collected from a convenience sample of graduate and undergraduate students. Students enrolled in a variety of courses that assigned an ePortfolio assignment received an email invitation from their instructor and self-selected to participate. Based on the responses of 35 students, the findings from this research showed significant relationships between three culturally based learning preferences and the motivational belief of Value/Usefulness. A summary of findings, limitations, and implications for further research are discussed. Autonomy Supportive Instruction as it relates to Students’ Motivational Beliefs on an ePortfolio Project: The Moderating Role of Culturally Based Learning Preferences
An Efficient, One-Level, Primitive-Equation Spectral Model

Abstract A one-level, global, spectral model using the primitive equations is formulated in terms of a concise form of the prognostic equations for vorticity and divergence. The model integration incorporates a grid transform technique to evaluate nonlinear terms; the computational efficiency of the model is found to be far superior to that of an equivalent model based on the traditional interaction coefficients. The transform model, in integrations of 116 days, satisfies principles of conservation of energy, angular momentum, and square potential vorticity to a high degree.
Data association for a hybrid metric map representation

This paper presents an approach to solve the data association problem for a hybrid metric map representation. The hybrid metric map representation uses Voronoi diagram to partition the global map space into a series of local subregions, and then a local dense map is built in each subregion. Finally the global feature map and the local maps make up of the hybrid metric map, which can represent all the observed environment. In the proposed map representation, there exists an important property that global feature map and local maps have clear one-to-one correspondence. Benefited from this property, an identifying rule of the data association based on compatibility testing is proposed. The identifying rule can efficiently reject the wrong data association hypothesis in the application of dense environment. Two experiments validated the efficiency of data association approach and also demonstrated the feasibility of the hybrid metric map presentation.
Familial Factors and Substance Abuse : Implications for Prevention

Several decades of research have revealed that the etiology of drug abuse comprises a complex network of interactive social, biologic, and genetic factors, which exhibits different levels of salience across development. There are several excellent summaries of the extensive literature on risk factors for drug use (Brook et al. 1990; Clayton 1992; Dembo et al. 1985; Hawkins et al. 1992; Kumpfer 1989; Swaim 1991), but far less is known about the risk and protective factors for drug abuse or dependence. Risk factors for drug abuse generally fall into three major domains: the individual, the family, and the social environment, which includes peer, school, neighborhood, and the broader cultural background. This chapter focuses on the role of familial factors in the etiology of substance abuse.
3 Département de Sciences Biologiques,

Farach, Kannan and Warnow (1995) defined Problem MCA (matrix completion to additive) and proved it to be NP-complete: given a partial dissimilarity d on a finite set X, does there exist a tree metric extending d to all pairs of elements of X. We use a previously described simple method of phylogenetic reconstruction, and its extension to partial dissimilarities, to characterize some classes of polynomial instances of MCA and of a related problem. We point out that these problems admit many other polynomial instances. We focus particularly on two classes of generalized cycles, together with the corresponding maximal acyclic graphs (2-trees and 2dtrees). Résumé. Farach, Kannan et Warnow (1995) ont posé le problème MCA (matrix completion to additive) suivant et ont démontré sa NP-complétude : étant donné une dissimilarité d partielle sur un ensemble fini X, est-il possible de l'étendre en une distance d'arbre définie sur toutes les paires d'éléments de X. Nous utilisons une méthode simple de reconstruction phylogénétique, précédemment décrite, et son extension aux dissimilarités partielles pour caractériser des classes d'instances polynomiales de MCA et d'un problème voisin. Nous montrons qu'en fait beaucoup d'autres instances sont aussi polynomiales. L'outil principal est constitué par deux classes de cycles généralisés, avec les graphes acycliques maximaux (2-arbres et 2d-arbres) correspondants.
Visualizing Topics and Social Networks within a Health Newsgroup CS 598

Introduction The goal of this project was to develop a visualization that would simultaneously overlay topics extracted from a newsgroup with social networking information. The motivation of this work is to determine if social networking information can be used as a method to evaluate the quality of topic extraction from a newsgroup. This work is also motivated by the questions: can hierarchical clustering and summarization of newsgroup messages lead to insights about the formation and sustainability of social networks? How can individual analysis be combined to inform another analysis? Ideally, a synergistic effect would be discovered, leading to insights about the community as a whole.
Pitch characteristics of bone conducted speech

This paper investigates the pitch characteristics of bone conducted speech. Pitch determination of speech signal can not attain the expected level of accuracy in adverse conditions. Bone conducted speech is robust to ambient noise and it has regular harmonic structure in the lower spectral region. These two properties make it very suitable for pitch tracking. Few works have been reported in the literature on bone conducted speech to facilitate detection and removal of unwanted signal from the simultaneously recorded air conducted speech. In this paper, we show that bone conducted speech can also be used for robust pitch determination even in highly noisy environment that can be very useful in many practical speech communication applications like speech enhancement, speech/speaker recognition, and so on.
Alternative-based thresholding: a simulation study

In fMRI research, researchers often aim to investigate activation in specific functional regions of interest (fROIs). Current statistical methods tend to localize fROIs inconsistently, only avoiding the detection of false activation. Avoiding to miss true activation is however equally important in this context. We discuss a new procedure (Durnez et al., 2013) that complements classical testing with evidence against activation and evaluate the technique for defining fROIs using simulated data.
A FALLBACK DISK ACCRETION INVOLVED FORMATION CHANNEL TO PSR J1903+0327

The discovery of the eccentric binary and millisecond pulsar J1903+03273 has raised interesting questions about the formation mechanisms of this peculiar system. Here we present a born-fast scenario for PSR J1903+03273. We assume that during the supernova (SN) explosion that produced the pulsar, a fallback disk was formed around and accreted onto the newborn neutron star. Mass accretion could accelerate the neutron star's spin to milliseconds, and decrease its magnetic field to ∼108–109 G, provided that there was sufficient mass (∼0.1 M☉) in the fallback disk. The neutron star became a millisecond pulsar after mass accretion terminated. In the meanwhile the binary orbit has kept to be eccentric (due to the SN explosion) for ∼109 yr. We have performed population synthesis calculations of the evolutions of neutron stars with a fallback disk, and found that there might be tens to hundreds of PSR J1903+03273 like systems in the Galaxy. This scenario also suggests that some fraction of isolated millisecond pulsars in the Galactic disk could be formed through the same channel.
Heuristics for Robust Allocation of Resources to Parallel Applications with Uncertain Execution Times in Heterogeneous Systems with Uncertain Availability

The scheduling of moldable parallel applications to clusters of processors is challenging, where the number of processors on which a moldable application executes is decided by the scheduler. When the application execution times are stochastic in nature, and the availability of the resources is uncertain, this becomes an even greater challenge. A model is presented for the stochastic execution times of moldable parallel applications that are assigned to heterogeneous parallel resources, incorporating the change in execution times when applications are mapped to different numbers of processors. To account for the uncertainties in both application execution times and resource availability, a robustness model that combines the two sources of uncertainties is proposed. Using this robustness model, three novel iterative-greedy heuristics are developed to allocate heterogeneous resources to batches of parallel applications to maximize the probability of completing by a designated time, called the makespan goal. To verify the performance of the proposed heuristics, a simulation study is conducted using different batch and system sizes. To showcase the benefit of using the proposed iterative-greedy heuristics, their performance is studied against two comparison heuristics. The five heuristics are evaluated against the upper bound on robustness.
A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

This paper reviews the most relevant works that have investigated robustness in power grids using Complex Networks (CN) concepts. In this broad field there are two different approaches. The first one is based solely on topological concepts, and uses metrics such as mean path length, clustering coefficient, efficiency and betweenness centrality, among many others. The second, hybrid approach consists of introducing (into the CN framework) some concepts from Electrical Engineering (EE) in the effort of enhancing the topological approach, and uses novel, more efficient electrical metrics such as electrical betweenness, net-ability, and others. There is however a controversy about whether these approaches are able to provide insights into all aspects of real power grids. The CN community argues that the topological approach does not aim to focus on the detailed operation, but to discover the unexpected emergence of collective behavior, while part of the EE community asserts that this leads to an excessive simplification. Beyond this open debate it seems to be no predominant structure (scale-free, small-world) in high-voltage transmission power grids, the vast majority of power grids studied so far. Most of them have in common that they are vulnerable to targeted attacks on the most connected nodes and robust to random failure. In this respect there are only a few works that propose strategies to improve robustness such as intentional islanding, restricted link addition, microgrids and Energies 2015, 8 9212 smart grids, for which novel studies suggest that small-world networks seem to be the best topology.
Novel Gene Expression Profile of Women with Intrinsic Skin Youthfulness by Whole Transcriptome Sequencing

While much is known about genes that promote aging, little is known about genes that protect against or prevent aging, particularly in human skin. The main objective of this study was to perform an unbiased, whole transcriptome search for genes that associate with intrinsic skin youthfulness. To accomplish this, healthy women (n = 122) of European descent, ages 18–89 years with Fitzpatrick skin type I/II were examined for facial skin aging parameters and clinical covariates, including smoking and ultraviolet exposure. Skin youthfulness was defined as the top 10% of individuals whose assessed skin aging features were most discrepant with their chronological ages. Skin biopsies from sun-protected inner arm were subjected to 3’-end sequencing for expression quantification, with results verified by quantitative reverse transcriptase-polymerase chain reaction. Unbiased clustering revealed gene expression signatures characteristic of older women with skin youthfulness (n = 12) compared to older women without skin youthfulness (n = 33), after accounting for gene expression changes associated with chronological age alone. Gene set analysis was performed using Genomica open-access software. This study identified a novel set of candidate skin youthfulness genes demonstrating differences between SY and non-SY group, including pleckstrin homology like domain family A member 1 (PHLDA1) (p = 2.4x10-5), a follicle stem cell marker, and hyaluronan synthase 2-anti-sense 1 (HAS2-AS1) (p = 0.00105), a non-coding RNA that is part of the hyaluronan synthesis pathway. We show that immunologic gene sets are the most significantly altered in skin youthfulness (with the most significant gene set p = 2.4x10-5), suggesting the immune system plays an important role in skin youthfulness, a finding that has not previously been recognized. These results are a valuable resource from which multiple future studies may be undertaken to better understand the mechanisms that promote skin youthfulness in humans.
Beyond global differences between monolingual and bilingual children on the nonword repetition task: retention skills for phonemes’ identity and serial order

This study compared NRT-performance in monolingual Dutch and bilingual Turkish–Dutch third-graders using a Dutch Nonword Repetition Task (NRT). Several novel response analyses at the phoneme level were applied to further understand the earlier reported overall accuracy differences in NRT-performance between bilinguals and monolinguals. Analyses in which the retention of phonemes and the retention of their serial order were disentangled revealed that monolinguals outperform bilinguals with respect to the retention of the phonemes themselves. However, both groups did not differ in their retention of the serial order of correctly recalled phonemes. Furthermore, this study confirms that expressive vocabulary skills do affect overall NRT-performance. The results are discussed in light of current short-term memory (STM) models and the role of long-term phonological knowledge in NRT tasks.
Machine Translation for Multilingual Summary Content Evaluation

The multilingual summarization pilot task at TAC'11 opened a lot of problems we are facing when we try to evaluate summary quality in different languages. The additional language dimension greatly increases annotation costs. For the TAC pilot task English articles were first translated to other 6 languages, model summaries were written and submitted system summaries were evaluated. We start with the discussion whether ROUGE can produce system rankings similar to those received from manual summary scoring by measuring their correlation. We study then three ways of projecting summaries to a different language: projection through sentence alignment in the case of parallel corpora, simple summary translation and summarizing machine translated articles. Building such summaries gives opportunity to run additional experiments and reinforce the evaluation. Later, we investigate whether an evaluation based on machine translated models can perform close to an evaluation based on original models.
CASA - A Contract-based Adaptive Software Architecture Framework

Traditionally, applications are developed with an implicit reliance on the stability of their execution environment and available resources, while little or no support is provided for the runtime adaptation of application behavior in case of any instability encountered. But such an approach proves futile for more dynamic environments, such as those encountered in self-organized mobile networks, wherein any form of reliance on the runtime computing environment of an application would be highly optimistic. The Contract-based Adaptive Software Architecture (CASA) framework, described in this paper, addresses the need to equip an application with the ability to dynamically adapt itself in response to changes in its execution environment. This implies that an application is able to meet its functional and/or non-functional commitments even when its runtime computing environment changes. The framework builds on the idea of specifying resource requirements and adaptation behavior of applications in application contracts.
Towards A Universal Tool For NLP Resource Acquisition

This paper describes an approach to developing a universal tool for eliciting, from a non-expert human user, knowledge about any language L. The purpose of this elicitation is rapid development of NLP systems. The approach is described on the example of the syntax module of the Boas knowledge elicitation system for a quick ramp up of a standard transfer-based machine translation system from L into English. The preparation of knowledge for the MT system is carried out into two stages; the acquisition of descriptive knowledge about L and using the descriptive knowledge to derive operational knowledge for the system. Boas guides the acquisition process using data-driven, expectation-driven and goal-driven methodologies.
Layered Multicast Rate Control using Lagrangian Relaxation and Dynamic Programming

In this paper, we address the rate control problem for layered multicast sessions, with the objective of solving a generalized throughput/fairness objective. Our approach is based on a combination of lagrangian relaxation and dynamic programming. Unlike previously proposed dual-based approaches, the algorithm presented in this paper scales well as the number of multicast groups in the network increases. Moreover, unlike all existing approaches, our approach takes into account the discreteness of the receiver rates that is inherent to layered multicasting. We show analytically that our algorithm converges and yields rates that are approximately optimal. Simulations carried out in an asynchronous network environment demonstrate that our algorithm exhibits good convergence speed and minimal rate fluctuations. Keywords—Mathematical programming/optimization, Control theory.