Miracle-dz/UniFAR-FTUs huggingface dataset:
Domaines et fouille d'opinion : une étude des marqueurs multi-polaires au niveau du texte. (Domain Adaptation for Opinion Mining : A Study of Multi-polarity Words)

Cette these s’interesse a l’adaptation d’un classifieur statistique d’opinion au niveau du texte d’un domaine a un autre. Cependant, nous exprimons notre opinion differemment selon ce dont nous parlons. Un meme mot peut ne pas designer pas la meme chose ou bien ne pas avoir la meme connotation selon le theme de la discussion. Si ces mots ne sont pas detectes, ils induiront des erreurs de classification.Nous appelons donc marqueurs multi-polaires des mots ou bigrammes dont la presence indique une certaine polarite du texte entier, differente selon le domaine du texte. Cette these est consacrees a leur etude. Ces marqueurs sont detectes a l’aide d’un test du khi2 lorsque l’on dispose d’annotations au niveau du texte dans les deux domaines d’interet. Nous avons egalement propose une methode de detection semi-supervise. Nous utilisons une collections de mots pivots auto-epures afin d’assurer une polarite stable d’un domaine a un autre.Nous avons egalement verifie la pertinence linguistique des mots selectionnes en organisant une campagne d’annotation manuelle. Les mots ainsi valides comme multi-polaires peuvent etre des elements de contexte, des mots exprimant ou expliquant une opinion ou bien designant l’objet sur lequel l’opinion est portee. Notre etude en contexte a egalement mis en lumiere trois causes principale de changement de polarite : le changement de sens, le changement d’objet et le changement d’utilisation.Pour finir, nous avons etudie l’influence de la detection des marqueurs multi-polaires sur la classification de l’opinion au niveau du texte par des classifieurs automatiques dans trois cas distincts : adaptation d’un domaine source a un domaine cible, corpus multi-domaine, corpus en domaine ouvert. Les resultats de ces experiences montrent que plus le transfert initial est difficile, plus la prise en compte des marqueurs multi-polaires peut ameliorer la classification, allant jusqu’a plus cinq points d’exactitude.
Spatial Bounding of Self-Affine Iterated Function System Attractor Sets

An algorithm is presented which, given the parameters of an Iterated Function System (IFS) which uses affine maps, constructs a closed ball which completely contains the attractor set of the IFS. These bounding balls are almost always smaller than those computed by existing methods, and are sometimes much smaller. The algorithm is numerical in form, involving the optimisation of centre-point and radius relationships between the overall bounding ball and a set of smaller, contained balls which are derived by analysis of the contractivemaps of the IFS. The algorithm is well-behaved, in that although it converges toward an optimal ball which it only achieves in the limit, the process may still be stopped after any finite number of steps, with a guarantee that the sub-optimal ball which is returned will still bound the attractor.
Online Parameter-Estimation-Based Speed Control of PM AC Motor Drive in Flux-Weakening Region

This paper presents an online parameter-estimation-based high-speed control of an interior permanent-magnet synchronous motor (IPMSM) drive. The controller designed from standard linear d-q axis motor model with constant parameters will lead to an unsatisfactory prediction of the performance of an IPMSM owing to the magnetic saturation of this motor, particularly, at high-speed conditions. In this paper, an adaptive backstepping-based control technique has been developed for an IPMSM, wherein system parameter variations, as well as field control, will be taken into account at the design stage of the controller. The operating speed limit of the motor is expanded with the proposed parameter-estimation-based field control (PEFC). The complete drive is successfully implemented in real time for a laboratory 1-hp motor using digital signal processor board DS1102. The performance of the proposed drive is tested both in simulation and experiment at different operating conditions. A performance comparison of the proposed PEFC with the constant-parameter-based field control is also provided. The robustness of the controller for high-speed applications is evidenced by the results.
Role of brassinosteroids in alleviation of phenanthrene–cadmium co-contamination-induced photosynthetic inhibition and oxidative stress in tomato

Heavy metal pollution often occurs together with organic contaminants. Brassinosteroids (BRs) induce plant tolerance to several abiotic stresses, including phenanthrene (PHE) and cadmium (Cd) stress. However, the role of BRs in PHE+Cd co-contamination-induced stress amelioration is unknown. Here, the interactive effects of PHE, Cd, and 24-epibrassinolide (EBR; a biologically active BR) were investigated in tomato plants. The application of Cd (100 µM) alone was more phytotoxic than PHE applied alone (100 µM); however, their combined application resulted in slightly improved photosynthetic activity and pigment content compared with Cd alone after a 40 d exposure. Accumulation of reactive oxygen species and membrane lipid peroxidation were induced by PHE and/or Cd; however, the differences in effect were insignificant between Cd and PHE+Cd. The foliar application of EBR (0.1 µM) to PHE- and/or Cd-stressed plants alleviated photosynthetic inhibition and oxidative stress by causing enhancement of the activity of the enzymes and related transcript levels of the antioxidant system, secondary metabolism, and the xenobiotic detoxification system. Additionally, PHE and/or Cd residues were significantly decreased in both the leaves and roots after application of EBR, more specifically in PHE+Cd-stressed plants when treated with EBR, indicating a possible improvement in detoxification of these pollutants. The findings thus suggest a potential interaction of EBR and PHE for Cd stress alleviation. These results advocate a positive role for EBR in reducing pollutant residues for food safety and also strengthening phytoremediation.
Comparative evaluation of 15 kV SiC MOSFET and 15 kV SiC IGBT for medium voltage converter under same dv/dt conditions

The 15 kV SiC MOSFET and 15 kV SiC IGBT are two state-of-the-art high voltage SiC devices. These high voltage SiC devices enable simple two level converters for medium voltage source converter compared to the complex three level and multilevel topologies with Silicon devices. This paper presents the detailed experimental results for the characterization of 15 kV SiC MOSFET module at 10 kV and 12 kV DC bus for two different configuration of device under test. This paper also presents the switching loss comparison of 15 kV SiC MOSFET with 15 kV SiC IGBT for the same dv/dt. Based on loss data obtained from experiments, this paper finally reports the switching frequency limits of 15 kV SiC MOSFET for 10 kV DC bus, 3-Phase two level converter and Bi-directional DC-DC phase leg converter with 10 kV output voltage and comparative evaluation of 15 kV SiC MOSFET and 15 kV SiC IGBT for the same dv/dt in a unidirectional DC-DC boost hard switching converter for 10 kV output voltage.
Hospital Structure and Expenditure

differential decline of the two rates. Despite the sense of conservative alarm and, even, an appc. :rc;i~ increase in the social hostility directed at unmarried mothers, this may be the case. Some B7iclfare support, albeit meagre, does now exist and some increase in tolerance may have taken place at some levels. Community opinion is not monolithic. It could well be argued, however, that the role of single mother is still sufficiently stigmatised and unpleasant as to predispose many women (especially those who are younger and have fewer economic resources) to choose marriage in preference, if marriage is in fact a real option for them. Given the dis-
Haemoglobin C and S Role in Acquired Immunity against Plasmodium falciparum Malaria

A recently proposed mechanism of protection for haemoglobin C (HbC; β6Glu→Lys) links an abnormal display of PfEMP1, an antigen involved in malaria pathogenesis, on the surface of HbC infected erythrocytes together with the observation of reduced cytoadhesion of parasitized erythrocytes and impaired rosetting in vitro. We investigated the impact of this hypothesis on the development of acquired immunity against Plasmodium falciparum variant surface antigens (VSA) encoding PfEMP1 in HbC in comparison with HbA and HbS carriers of Burkina Faso. We measured: i) total IgG against a single VSA, A4U, and against a panel of VSA from severe malaria cases in human sera from urban and rural areas of Burkina Faso of different haemoglobin genotypes (CC, AC, AS, SC, SS); ii) total IgG against recombinant proteins of P. falciparum asexual sporozoite, blood stage antigens, and parasite schizont extract; iii) total IgG against tetanus toxoid. Results showed that the reported abnormal cell-surface display of PfEMP1 on HbC infected erythrocytes observed in vitro is not associated to lower anti- PfEMP1 response in vivo. Higher immune response against the VSA panel and malaria antigens were observed in all adaptive genotypes containing at least one allelic variant HbC or HbS in the low transmission urban area whereas no differences were detected in the high transmission rural area. In both contexts the response against tetanus toxoid was not influenced by the β-globin genotype. These findings suggest that both HbC and HbS affect the early development of naturally acquired immunity against malaria. The enhanced immune reactivity in both HbC and HbS carriers supports the hypothesis that the protection against malaria of these adaptive genotypes might be at least partially mediated by acquired immunity against malaria.
A Secure Attribute-Based Keyword Search Scheme Against Keyword Guessing And Chosen Keyword Attack

—To provide the privacy of the users who receive some computing services from the cloud, the users must encrypt their documents before outsourcing them to the cloud. Computation on outsourced encrypted data in the cloud rises some complexity to the system especially in the case when an entity would like to find some documents related to a special keyword. Searchable encryption is a tool for data owners to encrypt their data in a searchable manner. Generally, there exist two kinds of searchable encryption, namely symmetric (secret key) and asymmetric (public key) ones. Most of the public key searchable encryption schemes are vulnerable to the keyword guessing attack (KGA). In this paper, we propose an attribute-based keyword search scheme which is proved to be secure against KGA. Also, we formally prove that the proposed scheme is secure against another attack, namely the chosen keyword attack (CKA) in the random oracle model.
A Biresolution Spectral Framework for Product Quantization

Product quantization (PQ) (and its variants) has been effectively used to encode high-dimensional data into compact codes for many problems in vision. In principle, PQ decomposes the given data into a number of lower-dimensional subspaces where the quantization proceeds independently for each subspace. While the original PQ approach does not explicitly optimize for these subspaces, later proposals have argued that the performance tends to benefit significantly if such subspaces are chosen in an optimal manner. Despite such consensus, existing approaches in the literature diverge in terms of which specific properties of these subspaces are desirable and how one should proceed to solve/optimize them. Nonetheless, despite the empirical support, there is less clarity regarding the theoretical properties that underlie these experimental benefits for quantization problems in general. In this paper, we study the quantization problem in the setting where subspaces are orthogonal and show that this problem is intricately related to a specific type of spectral decomposition of the data. This insight not only opens the door to a rich body of work in spectral analysis, but also leads to distinct computational benefits. Our resultant biresolution spectral formulation captures both the subspace projection error as well as the quantization error within the same framework. After a reformulation, the core steps of our algorithm involve a simple eigen decomposition step, which can be solved efficiently. We show that our method performs very favorably against a number of state of the art methods on standard data sets.
Feedback for a simulation practice on communication skills in pharmacy education: A pilot study

Although simulation practice with standard patients became popular in curriculums since years of various countries, it hasn’t been used in the education of pharmacists and pharmacy technicians in Turkey yet. In this study, it is aimed to conduct a pilot study with standard patients on students in the simulation laboratory for the first time and get feedback of them. This study was conducted with 22 pharmacy technicians, four pharmacy students and four standard patients in 15-16 December 2015. Six scenarios were used. After the study, video recordings of the "student-standard patient interaction" were watched with the students to improve the simulation laboratory and the practices planned to be. The physical properties of the place, the use of body language, issues related to the needs and feelings during practice for the development of training programs has come to fore during the feedback of the students. It is useful to generalize this pilot study in terms of both student groups for starting their profession with communication skills and achieving the golden standards in education.
An Introduction to Deep Learning

The deep learning paradigm tackles problems on which shallow architectures (e.g. SVM) are affected by the curse of dimensionality. As part of a two-stage learning scheme involving multiple layers of non-linear processing a set of statistically robust features is automatically extracted from the data. The present tutorial introducing the ESANN deep learning special session details the state-of-the-art models and summarizes the current understanding of this learning approach which is a reference for many difficult classification tasks.
DeepMVS: Learning Multi-view Stereopsis –Supplementary Material–

In this supplementary document, we present additional implementation details and results to complement the main paper. We first describe in detail the formulation for applying DenseCRF to disparity refinement. We then present additional experimental results, including evaluation using scale-invariant errors, results on DeMoN’s testing dataset, and the effect of input image resolutions. Finally, we show additional qualitative comparisons with conventional MVS algorithms.
Variability in the summer season hydrological cycle over the Atlantic‐Europe region 1979–2007

Variability in aspects of the hydrological cycle over the Europe‐Atlantic region during the summer season is analysed for the period 1979–2007, using observational estimates, reanalyses and climate model simulations. Warming and moistening trends are evident in observations and models although decadal changes in water vapour are not well represented by reanalyses, including the new European Centre for Medium Range Weather Forecasts (ECMWF) Interim reanalysis. Over the north Atlantic and northern Europe, observed water vapour trends are close to that expected from the temperature trends and Clausius–Clapeyron equation (7% K−1), larger than the model simulations. Precipitation over Europe is dominated by large‐scale dynamics with positive phases of the North Atlantic Oscillation coinciding with drier conditions over north Europe and wetter conditions over the Mediterranean region. Evaporation trends over Europe are positive in reanalyses and models, especially for the Mediterranean region (1–3% per decade in reanalyses and climate models). Over the north Atlantic, declining precipitation combined with increased moisture contributed to an apparent rise in water vapour residence time. Maximum precipitation minus evaporation over the north Atlantic occurred during summer 1991, declining thereafter. Copyright © 2010 Royal Meteorological Society
Developing Communication Strategy for Multi-Agent Systems with Incremental Fuzzy Model

Communication can guarantee the coordinated behavior in the multi-agent systems. However, in many realworld problems, communication may not be available at every time because of limited bandwidth, noisy environment or communication cost. In this paper, we introduce an algorithm to develop a communication strategy for cooperative multi-agent systems in which the communication is limited. This method employs a fuzzy model to estimate the benefit of communication for each possible situation. This specifies minimal communication that is necessary for successful joint behavior. An incremental method is also presented to create and tune our fuzzy model that reduces the high computational complexity of the multi-agent systems. We use several standard benchmark problems to assess the performance of our proposed method. Experimental results show that the generated communication strategy can improve the performance as well as full-communication strategy, while the agents utilize little communication. Keywords—Multi-agent systems; decentralized partially observable Markov decision process; communication; planning under uncertainty; fuzzy inference systems
Baseline Desensitizing in Translation Averaging

Many existing translation averaging algorithms are either sensitive to disparate camera baselines and have to rely on extensive preprocessing to improve the observed Epipolar Geometry graph, or if they are robust against disparate camera baselines, require complicated optimization to minimize the highly nonlinear angular error objective. In this paper, we carefully design a simple yet effective bilinear objective function, introducing a variable to perform the requisite normalization. The objective function enjoys the baseline-insensitive property of the angular error and yet is amenable to simple and efficient optimization by block coordinate descent, with good empirical performance. A rotation-assisted Iterative Reweighted Least Squares scheme is further put forth to help deal with outliers. We also contribute towards a better understanding of the behavior of two recent convex algorithms, LUD [20] and Shapefit/kick [9], clarifying the underlying subtle difference that leads to the performance gap. Finally, we demonstrate that our algorithm achieves overall superior accuracies in benchmark dataset compared to state-of-the-art methods, and is also several times faster.
Generative Adversarial Networks for Depth Map Estimation from RGB Video

Depth cues are essential to achieving high-level scene understanding, and in particular to determining geometric relations between objects. The ability to reason about depth information in scene analysis tasks can often result in improved decision-making capabilities. Unfortunately, depth-capable sensors are not as ubiquitous as traditional RGB cameras, which limits the availability of depth-related cues. In this work, we investigate data-driven approaches for depth estimation from images or videos captured with monocular cameras. We propose three different approaches and demonstrate their efficacy through extensive experimental validation. The proposed methods rely on processing of (i) a single 3-channel RGB image frame, (ii) a sequence of RGB frames, and (iii) a single RGB frame plus the optical flow field computed between the frame and a neighboring frame in the video stream, and map the respective inputs to an estimated depth map representation. In contrast to existing literature, the input-output mapping is not directly regressed; rather, it is learned through adversarial techniques that leverage conditional generative adversarial networks (cGANs).
A Subjective Evaluation of Attitudes towards E-health

E-health, the provision of healthcare services via the Internet, has the potential to address the limited capacity of the healthcare system and thereby improve health outcomes. While there is considerable development of e-health services in practice, research in this important area often lags practice and takes a restricted view of user needs. The study presented in this paper undertakes a holistic evaluation of perceptions of e-health services and tools by addressing the activities of diverse stakeholders from healthcare practitioners to the general public. The research uses Q-methodology to explore the opportunities, challenges, barriers, and potential benefits of e-health to guide the development of a holistic e-health strategy that targets all stakeholders. Q methodology is a research design that provides a foundation for the systematic study of subjectivity and so is appropriate as a way of fostering deep understandings of e- health phenomena from different user perspectives . A three factor solution was selected for the interpretation of the data. Our finding suggests that government authorities and healthcare providers should be aware of the existence of health literacy issue as well as other issues among diverse users of the health system. The design of universal (ubiquitous) online health systems must accommodate users with different skills, knowledge, age, gender, and disabilities.
Research on Recognition Method of Driving Fatigue State Based on Sample Entropy and Kernel Principal Component Analysis

In view of the nonlinear characteristics of electroencephalography (EEG) signals collected in the driving fatigue state recognition research and the issue that the recognition accuracy of the driving fatigue state recognition method based on EEG is still unsatisfactory, this paper proposes a driving fatigue recognition method based on sample entropy (SE) and kernel principal component analysis (KPCA), which combines the advantage of the high recognition accuracy of sample entropy and the advantages of KPCA in dimensionality reduction for nonlinear principal components and the strong non-linear processing capability. By using support vector machine (SVM) classifier, the proposed method (called SE_KPCA) is tested on the EEG data, and compared with those based on fuzzy entropy (FE), combination entropy (CE), three kinds of entropies including SE, FE and CE that merged with KPCA. Experiment results show that the method is effective.
Rate Distortion Function of Gaussian Asymptotically WSS Vector Processes

In this paper, we obtain an integral formula for the rate distortion function (RDF) of any Gaussian asymptotically wide sense stationary (AWSS) vector process. Applying this result, we also obtain an integral formula for the RDF of Gaussian moving average (MA) vector processes and of Gaussian autoregressive MA (ARMA) AWSS vector processes.