Miracle-dz/UniFAR-FTUs huggingface dataset:
Vues matérialisées XML pour des entrepôts de données pair-à-pair

We consider the efficient, scalable management of XML documents in structured peer-to-peer networks based on distributed hash table (DHT) indices. We present an approach for exploiting materialized views deployed in the DHT network independently by the peers, to answer an interesting dialect of tree pattern queries. We provide algorithms for the distributed maintenance of the views and for view based query rewriting. We discuss view definition indexing strategies based on the DHT and compare their performance through a set of experiments on a completely deployed platform.
Analysis of Agriculture and Gross Domestic Product of Nigeria using First Difference Regression Model

The dwindling oil price in the international market reveals the fact that the Nigerian economy need to be diversified to develop the non-oil sector, of which agriculture is an example of the non-oil sector. It well reported in the literature that agriculture in Nigeria is a major sector of the economy, providing employment for about 70% of the population. This paper examines the relationship between agriculture and GDP in Nigeria using data from 1960 to 2014. Annual data for agriculture and GDP was extracted from CBN Statistical Bulletin. The ADF test revealed that agriculture and GDP variables are stationary at first difference. The evidence from bound testing and Johansen cointegration test revealed that agriculture and GDP variables are not cointegrated. Lastly, evidence from first difference revealed that 1% increase in the change of agriculture leads to about 90.86% increase in the change of GDP. This paper recommends that in this period of fall in oil price, investment that will grow the agricultural sector should be encouraged so as to enhance economic growth.
Correct-by-Design Human-Robot Collaboration through Supervisory Control of POMDP

by Xiaobin Zhang Human-Robot Collaboration (HRC) studies how to achieve e ective collaborations between human and robots to take advantage of the exibility from human and the autonomy from robots. Most of the existing work in HRC focused on the robot actuation design and low-level motion planning. However, many applications involving HRC, such as joint assembly manufacturing systems, need to achieve high-level tasks in a provably correct manner. In addition, many HRC applications are safety critical, such as advanced driver assistance systems and intelligent service robots. These applications motivate the requirements of HRC to have the performance guarantee to assure the task completion and safety of both human and robots. Hence, my Ph.D. research is motivated to build a correct-by-design HRC framework that enables a performance guaranteed HRC for the safety of human and robots and the completion of high-level tasks. For such a purpose, cross-disciplinary approaches combining methods from supervisory control theory, machine learning, and computational veri cation are pursued. In particular, three research thrusts are structured to emphasize the requirements on uncertainties modeling, high-level task completion, and safety guarantees in HRC. To model the uncertainties from human, robots and the environment, partially observable Markov decision process (POMDP) is used as the model for HRC. With the partial observability in POMDP, the collab-
Surface-micromachined silicon carbide structures and their application for microsystems

The first part of this thesis presents the design, fabrication and testing of silicon carbide (SiC)-based capacitive micromachined ultrasonic transducers (CMUT). The use of DC-sputtered amorphous SiC (a-SiC) as a structural layer allows the fabrication process to limit the temperature to a thermal budget of 200oC for 2 h, which is the lowest reported to date, making this technology ideally suited for above-IC integration. The high Young’s modulus of the deposited SiC film, along with its very low residual stress, result in high strength and resilient CMUT membranes. The placement of the suspended aluminum electrode directly at the bottom side of the membrane reduces the effective size of the electrostatic transduction gap, resulting in superior electro-mechanical coupling. Fabricated transducers are tested in air with both continuous-wave and pulsed signals, using a pitch-and-catch configuration. The transducer pair, composed of 110 µm-diameter membrane arrays, exhibits a resonant frequency of 1.75 MHz, a 3 dB-bandwidth of 0.15 MHz and a transmission gain of -38 dB. The CMUT prototypes showcase the versatility of low-temperature DC-sputtered SiC films applied in the field of microelectromechanical systems (MEMS). The second part of this thesis presents a low-cost and low temperature wafer-level packaging solution for MEMS devices. Heat-decomposable polymer poly(propylene carbonate) (PPC) is used as the sacrificial material to release the capping layer in a clean and fast manner. Free-standing caps made of a SiC films and as large as 450 µm in diameter are successfully fabricated. To demonstrate the validity of this technology, surface-micromachined Pirani vacuum gauges are fabricated as an example of MEMS devices and encapsulated. Capped Pirani gauges respond to pressure between 1 mtorr and 1 atm. The Pirani gauges are sealed with Parylene C films that exhibit near-hermetic properties and the initial sealing pressure for 300 µm-diameter cavities is characterized to be in the range of tens of torr. The developed silicon carbide-based encapsulation technology offers a practical solution to reduce cost in MEMS packaging therefore eliminating a large bottleneck for their commercialization. %%%%La premiere partie de cette these presente la conception, la fabrication et la qualification de transducteurs ultrasoniques micro-usines capacitifs (CMUT) a base de carbure de silicium (SiC). L'utilisation de SiC amorphe depose par pulverisation cathodique comme couche structurelle permet aux temperatures du procede de fabrication de se limiter a un budget thermique de 200˚C pendant 2 h, le plus faible rapporte a ce jour. Ainsi, la technologie est idealement adaptee pour integration directe sur circuits integres. Le module de Young eleve de la couche de SiC, ainsi que ses contraintes residuelles tres faibles, engendre des membranes CMUT tres solides et resistantes. Le posit ionnement de l'electrode d'aluminium directement sous la membrane suspendue permet de reduire la taille effective de l'espacement de transduction electrostatique,…
Human Capital, Gender and the Labor Market in Senegal

The main objective of this article is to analyze the factors behind wage inequalities between men and women taking into account the qualification levels between these two groups. To achieve this goal, we used the standard Oaxaca model which allowed us to break down wages between these two groups to see the determinants of the gender pay gap. However, before decomposing, the determinants of salary were studied primarily through the Heckman selection model, for the entire population but also specifically for each sex. The main result is that men earn on average higher wages than women in all segments of the Senegalese labor market. An in-depth analysis of the factors behind these disparities was carried out. The results showed that there is a pay gap of 3.69% in the skilled segment and 5.41% in the non-skilled segment. The salary gap is therefore greater in the non-skilled segment. Keywords : Human capital ; gender ; labor market JEL Classification numbers : E24 ; J16 ; J40
Hybrid And Hierarchical Image Registration Techniques

A large number of image registration techniques have been developed for various types of sensors and applications, with the aim to improve the accuracy, computational complexity, generality, and robustness. They can be broadly classified into two categories: intensity-based and feature-based methods. The primary drawback of the intensity-based approaches is that it may fail unless the two images are misaligned by a moderate difference in scale, rotation, and translation. In addition, intensity-based methods lack the robustness in the presence of non-spatial distortions due to different imaging conditions between images. In this dissertation, the image registration is formulated as a two-stage hybrid approach combining both an initial matching and a final matching in a coarse-to-fine manner. In the proposed hybrid framework, the initial matching algorithm is applied at the coarsest scale of images, where the approximate transformation parameters could be first estimated. Subsequently, the robust gradient-based estimation algorithm is incorporated into the proposed hybrid approach using a multi-resolution scheme. Several novel and effective initial matching algorithms have been proposed for the first stage. The variations of the intensity characteristics between images may be large and nonuniform because of non-spatial distortions. Therefore, in order to effectively incorporate the gradient-based robust estimation into our proposed framework, one of the
Successful turnarounds in bankrupt firms? Assessing retrenchment in the most severe form of crisis

During economic downturns, firms file for bankruptcy in an effort to attempt a “turnaround. ” The objective of this study is to assess the effectiveness of retrenchment strategies in the context of bankruptcy, as the most severe form of crisis. We conducted a longitudinal analysis of a sample of 868 bankrupt Spanish firms during the period 2004–2017. The empirical results show that stakeholder support and deep cost retrenchment increase the likelihood of survival and performance recovery, while aggressive layoffs are detrimental for turning bankrupt firms around. Surprisingly, intense asset retrenchment had no significant effects on firm survival and also pushed performance downward. The findings suggest that retrenchment should not be regarded as a general remedy for firms suffering the most severe of crisis. Bankrupt firms should focus on restoring stakeholder relationships and reducing superfluous expenses, while making employees redundant or selling assets should be evaluated carefully when attempting a turnaround. JEL CLASSIFICATION M10; G33
The life scenarios of family who have autistic child at home

Living with autism is not easy for the autistic children themselves and their family members. Especially the family members who are also the main caregivers. This ethnographic study aimed to describe the ways of life of families who have children with autism at home. Data were collected through participant observations, focus group discussions and in-depth interviews. There were 20 families as key informants taken by purposive sampling who consist of mothers, grandmothers, and siblings. The data were analyzed by thematic analysis. There were four family life scenarios of family living with autistism including: 1) basic self care activity, 2) locking doors to protect the autistic children, 3) woman act as a main caregiver, 4) risk of child abuse, and 5) supporting from spouse and other family members. Main caregivers risk psychological, physical and social problems. Nurses should provide counseling to the main caregiver by deep listening to their concerns and teaching them how to manage stress. In addition, caregivers need supports from the family member particularly the husband.
A matter of choice—professionals’ views on the incorporation of practical work with intimate partner violence into Swedish personal social services

During the last decades, efforts have been made to increase local support provided to victims of intimate partner violence (IPV) in Sweden. As with other social problems, responsibility to address IPV falls on the municipal personal social services. The present article draws upon data obtained via structured telephone interviews with designated personal social services staff members from a sample of 99 municipalities, focusing on aspects of potential progress in social work with IPV. The results show that successful incorporation of IPV into personal social services largely seems to depend upon the commitment and dedication of individual actors within the organisations. Furthermore, the data indicate that competence in this field depends on personal inclination, with attention to IPV appearing as ‘a matter of choice’. The results are analysed using neo-institutional theory as well as concepts related to social movement studies, with focus on individual agency in organisational change and the potential relevance of IPV as an issue related to gender inequality to gender inequality. The analysis suggests that while IPV social work may challenge institutionalised practises within social services, change may go both ways with IPV being reframed to fit within the established framework of social services.
Grab ‘em by the masculinity: changes in gendered beliefs and sexism following the 2016 US presidential election

ABSTRACT Due in part to Hillary Clinton’s historic candidacy, gender was a salient dimension of the 2016 US presidential election. In particular, the purported masculinity and femininity of each candidate was on display, discussed extensively in the media, and may have had an impact on citizens’ own gendered beliefs and behaviors. In a longitudinal study of 618 adults (women and men, Democrats and Republicans), we explored changes in gendered self concept and sexism from before to shortly after the election. Male Republicans increased in their conformity to masculine norms following the election, whereas male Democrats decreased in gender collective self-esteem and benevolent sexism and increased in willingness to intervene in everyday benevolent sexist situations. Few meaningful changes emerged for women of either political party. We suggest that the election of a hostilely sexist male leader deepened already held ideological positions and associated behaviors, at least for men.
Multitask assessment of roads and vehicles network (MARVN)

Vehicle detection in wide area motion imagery (WAMI) has drawn increasing attention from the computer vision research community in recent decades. In this paper, we present a new architecture for vehicle detection on road using multi-task network, which is able to detect and segment vehicles, estimate their pose, and meanwhile yield road isolation for a given region. The multi-task network consists of three components: 1) vehicle detection, 2) vehicle and road segmentation, and 3) detection screening. Segmentation and detection components share the same backbone network and are trained jointly in an end-to-end way. Unlike background subtraction or frame differencing based methods, the proposed Multitask Assessment of Roads and Vehicles Network (MARVN) method can detect vehicles which are slowing down, stopped, and/or partially occluded in a single image. In addition, the method can eliminate the detections which are located at outside road using yielded road segmentation so as to decrease the false positive rate. As few WAMI datasets have road mask and vehicles bounding box anotations, we extract 512 frames from WPAFB 2009 dataset and carefully refine the original annotations. The resulting dataset is thus named as WAMI512. We extensively compare the proposed method with state-of-the-art methods on WAMI512 dataset, and demonstrate superior performance in terms of efficiency and accuracy.
New contributions on the determinants of International Tourism Demand: Weather, Travel Diseases and Income

EnglishIn the last two decades, there have been significant researches that focus on association between climate change and tourism. However, researchers also have shown how income is more important variable than temperature, for international tourism demand. This thesis deeply analyzes three of these topics that include both short-term and long-term prospective. This thesis, not only, evaluated climate change effect on tourist flow, but also consider travel related diseases impact on international tourism demand. Moreover, most significant variable, income has been explored separately, with some new insights. The analysis includes both time series and panel data, with multiple statistical techniques including ARIMAX and Gravity model. The studies result will contribute significantly by overcoming current limitations and enhanced information for policy making. catalaEn les ultimes dues decades, s'han dut a terme multiples investigacions que han centrat la seva atencio en les interrelacions entre el canvi climatic i el turisme. Amb tot, els investigadors han mostrat com la renda acaba sent el mes important que la temperatura a l’hora de determinar la demanda turistica internacional. Aquesta tesi analitza amb profunditat tres temes que inclouen tant prospectiva a curt termini com a llarg termini. Aquesta tesi persegueix aixi, en primer lloc, avaluar l'efecte del canvi climatic sobre el flux turistic de manera directe a traves de l’analisi de les condicions meteorologiques sobre l’interes turistic d’un desti, en segon lloc, considerar l'impacte de les malalties relacionades amb els viatges sobre la demanda turistica internacional i, en tercer lloc, aprofundir en la variable mes significativa en el models de demanda, la renda, per millorar les prediccions a llarg termini. L'analisi es du a terme amb l’estudi de les series temporals i amb dades del panell, amb diverses tecniques estadistiques, incloent ARIMAX i els models gravitacionals. Els resultats dels estudis s’esperi que contribueixen significativament al coneixement de l’area i permetin una formulacio de politiques mes acurada.
Strategic Message Convergence in Communicating Biosecurity: The Case of the 2013 Porcine Epidemic Diarrhea Virus

Inconsistent, unclear, and inaccurate messages can dissuade audiences from engaging in appropriate crisis response behaviors. Thus, message convergence is both a priority and a persistent challenge for crisis communicators. In 2013, the Porcine Epidemic Diarrhea virus (PEDv) caused substantial losses in the U.S. swine industry. This study examines interview responses by spokespersons from multiple swine agency experts and university extension agents through the lens of message convergence theory. Results extend previous research regarding what to communicate by revealing how to communicate effectively. Ultimately, this analysis explains how, when existing convergent messages are no longer accurate, practitioners must sometimes foster their own divergence to put forward a more accurate message (in this case, for effectively improving biosecurity).
Component Pin Recognition Using Algorithms Based on Machine Learning

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.
Regulatory quality in the European Union and the United Kingdom: Old Questions and New Finding

This paper examines the quality of impact assessments in the European Commission and the United Kingdom for the period 2005-2010. We coded 477 impact assessments for the UK and 251 for the European Commission, using a detailed scorecard - adjusted to reduce the bias evidenced by previous usages of this instrument. The findings suggest that impact assessment is not merely a perfunctory activity in the European Union and the UK. Quality has improved steadily over the years, arguably as a result of learning and regulatory oversight. The UK and the European Commission are strikingly similar on a number of impact assessment dimensions (such as economic analysis and identification of costs and benefits). The impact assessments of the European Commission seem to pay more attention to social and environmental aspects, however. The conclusions reflect on the implications of our findings for current policy discussions on regulatory quality and the role of regulatory oversight bodies.
Modelling of PV module and its application for partial shading analysis – part I: model and parameter estimation of PV module

Under partially shaded conditions (PSC), a photovoltaic (PV) array gets more complex characteristics. Yet, it is very difficult and utterly necessary for PV system designers to understand and predict them. Other than the prevailing methodology of solving a set of non-linear equations, the proposed methodology focus on three key points of short circuit (0, I sc ), MPP( V mp , I mp ), and open circuit ( V oc , 0), and splits its V – I curve into three regions, which are replaced by three asymptote lines. From this new viewpoint, this study presents a novel Psim-based piece-wise linear macro-model and its circuit parameter values can be determined based on the three key points. Parameter estimation method is then developed to calculate the values of three key points under arbitrary irradiance and temperature by using only the datasheet under the standard test condition. The new model can be used to predict PV module characteristics for various operating conditions and understand the behaviours of a long PV string and a large-scale PV array under any PSC patterns on Psim platform. Compared with the published other models, the new model have merits of short running time, relative high accurateness, and reliable unique solution, avoiding the computational complexity and convergence issues. The accurateness of new model and formulas is experimentally validated and the computational error can meet the requirement of routine engineering analysis and design. Therefore, the new model and formulas will provide a powerful tool for one to learn the behaviour of a large-scale PV array in a complex scenario and optimise entire PV power plant, which involves DC/DC converter for MPPT and DC/AC inverter.