Miracle-dz/UniFAR-FTUs huggingface dataset:
Patient-Centered Medical Homes and Hospital Value-Based Purchasing: Investigating Provider Responses to Incentives

13 Introduction . 14 Chapter 1 Concordance between provider and patient-reported characteristics of patient-centered medical homes . 15 Abstract . 15. 15 Introduction . 17 Conceptual framework . 18 Hypotheses. 21 Methods . 21 Data . 21 Statistical analysis. 27 Results . 30 Patient and provider perspective concordance . 31 Emergency department use and expenditures . 32 Discussion . 34 Limitations . 35 Conclusion . 36 Chapter 2 Hospital Value-Based Purchasing and Staff Budgeting Decisions . 46 Abstract . 46. 46 Introduction . 48 Conceptual framework . 50
Los programas de colonización y el Estado contrainsurgente en Guatemala

En el ensayo se examina el Patrimonio Agrario Colectivo, una forma de adjudicación y transferencia de tierras nacionales utilizada por el Estado guatemalteco entre 1962 y 1978. Esta forma de apropiación de la tierra y los bienes naturales permitió el asentamiento de comunidades indígenas en las zonas que las élites civiles y militares se proponían ocupar y explotar, en las que instalaban mano de obra barata, a la vez que se daba respuesta a la demanda de tierra de grupos campesinos. Ello permitió el establecimiento de comunidades indígenas en zonas de frontera agrícola conforme a sus estructuras ancestrales propias y normas de funcionamiento comunitario. Los Patrimonios Agrarios Colectivos en el periodo actual (2002-2018) son el objetivo del proceso moderno de despojo campesino y de apropiación privada de tierras por empresas agroindustriales para el establecimiento de plantaciones de palma africana, lo que erosiona la sobrevivencia de formas de organización comunitaria indígena en estas regiones.
Automatic Anisotropic Factor Based Improved Gaussian Filter for Edge Detection towards Multi–Label Image Classification

: Many dimensions of research work are carried out in the digital image processing. Multi-label image classification is one such thrust research paradigm in digital image processing. Edge detection plays a vital role in image segmentation for multi-label image classification. In our previous research paper noise removal is carried out. In this research work an improved Gaussian filter technique that makes use of automatic anisotropic factor is added up with the Gaussian filter is used. The automatic anisotropic factor aims to decrease the time taken for edge detection. Implementations are carried out using MATLAB. 40 images from four different datasets are used in the implementation. Time taken for edge detection is the performance metric taken. Simulation results prove that the improved Gaussian filter technique using automatic anisotropic factor decreases the time taken for edge detection.
A Comparative Review of Machine Learning for Arabic Named Entity Recognition

Arabic Named Entity Recognition (ANER) systems aim to identify and classify Arabic Named entities (NEs) within Arabic text. Other important tasks in Arabic Natural Language Processing (NLP) depends on ANER such as machine translation, question-answering, information extraction, etc. In general, ANER systems can be classified into three main approaches, namely, rule-based, machine-learning or hybrid systems. In this paper, we focus on research progress in machine-learning (ML) ANER and compare between linguistic resource, entity type, domain, method and performance. We also highlight the challenges when processing Arabic NEs through ML systems.
The Word Frequency Effect in English Second Language Students: An Eye Movement Monitoring Study

3 Literature Review.6 Methodology.17 Results.20 Discussion.22 Appendices.26 Appendix 1A.26 Appendix 1B.27 Appendix 1C.28 Appendix 2A.30 Appendix 2B.30 Appendix 2C.31 Appendix 2D.32 Appendix 2E.33 Appendix 2G.34 References.35
Human-Assisted Machine Information Exploitation: a crowdsourced investigation of information-based problem solving

The Human-Assisted Machine Information Exploitation (HAMIE) investigation utilizes large-scale online data collection for developing models of information-based problem solving (IBPS) behavior in a simulated time-critical operational environment. These types of environments are characteristic of intelligence workflow processes conducted during human-geo-political unrest situations when the ability to make the best decision at the right time ensures strategic overmatch. The project takes a systems approach to Human Information Interaction (HII) by harnessing the expertise of crowds to model the interaction of the information consumer and the information required to solve a problem at different levels of system restrictiveness and decisional guidance. The design variables derived from Decision Support Systems (DSS) research represent the experimental conditions in this online single-player against-the-clock game where the player, acting in the role of an intelligence analyst, is tasked with a Commander’s Critical Information Requirement (CCIR) in an information overload scenario. The player performs a sequence of three information processing tasks (annotation, relation identification, and link diagram formation) with the assistance of ‘HAMIE the robot’ who offers varying levels of information understanding dependent on question complexity. We provide preliminary results from a pilot study conducted with Amazon Mechanical Turk (AMT) participants on the Volunteer Science scientific research platform.
New evidence for learning-based accounts of gaze following: Testing a robotic prediction

Gaze following is an early-emerging skill in infancy argued to be fundamental to joint attention and later language. However, how gaze following emerges has been a topic of great debate. The most widely-accepted developmental theories suggest that infants are able to gaze follow only by understanding shared attention. Another group of theories suggests that infants may learn to follow gaze based on low-level social reinforcement. Nagai et al. [Advanced Robotics, 20, 10 (2006)] successfully taught a robot to gaze follow purely through social reinforcement, and found that the robot learned to follow gaze in the horizontal plane before it learned to follow gaze in the vertical plane. In the current study, we tested whether 12-month-old infants were also better at gaze following in the horizontal than the vertical plane. This prediction does not follow from the predominant developmental theories, which have no reason to assume differences between infants' ability to follow gaze in the two planes. We found that infants had higher accuracy when following gaze in the horizontal than the vertical plane ($p = .01$). These results confirm a core prediction of the robot model, suggesting that children may also learn to gaze follow through reinforcement learning. This study was pre-registered, and all data, code, and materials are openly available on the Open Science Framework (https://osf.io/fqp8z/).
Audiovisual Narrative, Ontology and Terrorism: Communicative Paradoxes in the Islamic State Videos

This article analyzes the processes of significance and overall impact of audiovisual material generated by the self-proclaimed Islamic State. It is undoubtedly an object of contemporary and first-order study, insofar as a large part of the geopolitical crisis in the Near East, as well as the migration flows to Europe, now hang from the warlike actions of the terrorist forces that emerged from the so-called Arab Spring. Our starting hypothesis is that the communication technique of the Islamic State is not just a wild evolution of the communicative processes themselves in post-modern societies, but it is profoundly paradoxical and inconsistent as far as its meaning processes are concerned. To analyze this material, we will use a hybrid composite methodology, first through a political ontology, where the relations between spectacle, atrocity, terrorism and political control are traced, including references to the existence of the obscenity law as an ideological basis for generating messages. Then, we will briefly review some of the audiovisual narrative resources that generate meaning in these pieces.
Cyberbullying of teachers

This chapter discusses cyberbullying of teachers. The deteriorating status of teachers is shown with the consequences of more student violence towards teachers. With the increase in technology use and subsequent ability to abuse teachers, students and parents can now also cyberbully teachers. An Australian study of the prevalence of cyberbullying of teacher is presented. There is some evidence of the prevalence and impact of cyberbullying of adults in the workplace, however, there are few studies that have examined cyberbullying of teachers by students and parents. We do not know how teachers are affected by cyberbullying in these instances, in terms of wellbeing and ability to work, but also the impact on teachers’ social media involvement. This chapter examines the frequency and impact of cyberbullying on secondary school teachers in Australia when students and parents were the perpetrators. Additionally, the study looked at whether the threat of cyberbullying led to changes in social media involvement. A 16-item survey was conducted online using Key Survey with advertisements posted in Australian Education Union Newsletters and later through Facebook. Completed surveys were returned by 129 teachers with 24% (31) indicating they had been cyberbullied by students or parents in their role as a secondary school teacher. The survey included a definition of cyberbullying and asked about participants’ experience of cyberbullying by parents and students (including ex-students) and the impact this had on their wellbeing and ability to work. Teachers who were cyberbullied were more concerned about future cyberbullying than those who had not been cyberbullied. The most common medium for cyberbullying was Facebook followed by phone, email and the Rate My Teacher website. Those who were bullied by both parents and students showed a greater negative impact on wellbeing and ability to work, than those who were bullied by students only. Participants who were cyberbullied reported a greater impact on their involvement in social media than those who were not cyberbullied. Implications for education and training on cyberbullying for teachers and schools are discussed.
Business-to-Consumer eCommerce Adoption in Nicaragua

Electronic commerce has changed the landscape of business reality, enabling conduits that create opportunities for the ones capable of overcoming their challenges. The causes affecting the adoption have been well documented in many regions of the world. However, there are few studies in Latin America and especially in Central America. Therefore, this research aims to describe the factors that facilitate and inhibit Business-to-Consumer eCommerce adoption in Nicaragua. For this purpose, a literature review on eCommerce adoption in developing countries was carried out to find the possible factors that might affect the adoption based on the entrepreneurial characteristics (innovativeness, knowledge, and perceived behavioral control), the communication of the innovation (innovation decision, communication channels, homophily in communication networks, message about the innovation, and the personal proximity network in the information exchange), the characteristics of the innovation (relative advantage, compatibility, complexity, observability, and purchasing costs), and the socioeconomic context (market eReadiness, transport logistics, logistic services, financial institutions eReadiness, telecommunication eReadiness, legal framework, and government commitment) besides a series of control variables considered and supported by the “Diffusion of Innovation Theory” by Rogers (2003). A questionnaire was developed based on prior empirical studies and tested through a pilot test prior to its application. The research comprises a descriptive approach, presenting secondary data about the country and industry related to eCommerce adoption in Nicaragua, and primary data obtained through the quantitative survey which tests the theoretical concepts from eCommerce adoption in this context. The survey had the participation of 315 managers from micro, small, medium, and large companies from all sectors in Nicaragua. The eCommerce status: connected eCommerce, static eCommerce, interactive eCommerce, transactive eCommerce, and integrated eCommerce were empirically investigated, using the survey to determine the characteristics of non-adopters that correspond to the categories of connected and static adopters from interactive, transactive, and integrated according to the eCommerce literature. A descriptive statistics and logistic regression was used to analyze the data and research hypotheses. The analysis demonstrates the technology, communication, managerial characteristics, and contextual factors that may affect eCommerce. Three hypotheses were confirmed: re-
The Emerge of the social strike - A new opportunity for labour?

In recent years a new emergent form of collective action – the social strike – has been discussed in social movement networks. So far, the concept of social strike has only surfaced briefly in previous research and this article aims to deepen the understanding of the concept and why it is emerging in our historical moment. In order to do this the article looks at a social movement network called Transnational Social Strike Platform (TSS). In the analysis both movement texts produced by TSS was used as well as ethnographic material collected at an assembly meeting in London. According to my analysis it is hard to define the social strike as a distinct form of collective action. Instead, the emergence of the concept of social strike should be located at the historical impasse of late capitalism. I suggest that the concept of social strike offers an imaginary solution to the disappearance of the working class as a political subject and reflects the eclipse of organised labour. The social strike uses the symbolic dimensions of the strike as a symbol of resistance but detaches the strike from its material base in waged labour. In this process, the strike becomes a multivocal symbol that can be invoked by actors in order to give symbolic support and discursive legitimisation to their struggles. As the symbolic dimensions of the strike gets increasingly detached from its material anchor in waged labour the value of using the strike as a symbol of resistance may erode as it no longer can deliver the concrete material effects of collective work stoppage that historically has given the strike its pivotal role in labour struggles.
Mind The Gap! A study of some pitfalls preventing peak performance in polyhedral compilation using a polyhedral antidote

The polyhedral model is a wonderful but imperfect world. While many advanced and fully automatic program analysis and optimization techniques have been developed thanks to its accuracy and expressiveness, these techniques may fail in producing efficient codes in some circumstances. Recently, this has been identified more clearly through the proposition of a new programming structure called xfor (multifor). This structure eases the manual application of optimizing transformations on loop nests for expert programmers and allows to generate executable codes that may be significantly faster than those generated automatically using well-established polyhedral strategies. In this paper, we highlight five main gaps regarding these strategies and discuss some ideas on how to bridge them.
A New method to Design Accurate Images with Tree Structural Transformations

Image recognition and segmentation techniques are playing key role in the field of image processing. Present researchers are working on the design concepts of accurate image processing. This paper explains the method for designing of accurate image processing with the help of the principle called automatic construction of tree structural image transformation and graphics processing unit as a hardware unit. Genetic algorithms are also used to obtain fast image processing on graphic processors.
Efficient distributed algorithms suited for uncertain context

Distributed systems become increasingly wide and complex, while their usage extends to various domains (e.g., communication, home automation, monitoring, cloud computing). Thus, distributed systems are executed in diverse contexts. In this thesis, we focus on uncertain contexts, i.e., the context is not completely known a priori or is unsettled. More precisely, we consider two main kinds of uncertainty: processes that are not completely identified and the presence of faults. The absence of identification is frequent in large networks composed of massively produced and deployed devices. In addition, anonymity is often required for security and privacy. Similarly, large networks are exposed to faults (e.g, process crashes, wireless connection drop), but the service must remain available.This thesis is composed of four main contributions. First, we study the leader election problem in unidirectional rings of homonym processes, i.e., processes are identified but their ID is not necessarily unique. Then, we propose a silent self-stabilizing leader election algorithm for arbitrary connected network. This is the first algorithm under such conditions that stabilizes in a polynomial number of steps. The third contribution is a new stabilizing property designed for dynamic networks that ensures fast and gradual convergences after topological changes. We illustrate this property with a clock synchronizing algorithm. Finally, we consider the issue of concurrency in resource allocation problems. In particular, we study the level of concurrency that can be achieved in a wide class of resource allocation problem, i.e., the local resource allocation.
System Centralnej Informacji o Postępowaniach Sądowych i Egzekucyjnych – zarys koncepcji

sformalizować oraz umożliwić jej wprowadzenie. Słowa system Summary: This article aims to present the process concept of the Central Information about Court Proceedings and Enforcement Proceedings (CIPSE), whose task should be to collect information on the ongoing court proceedings and enforcement proceedings and then the provision of appropriate information collections dedicated to the recipients. The concept assumes the current data synchronization and data preparation for further processing. The article will also present the concept of the architecture of the system, which would allow to automate and improve the current use of information about court proceedings and enforcement proceedings. As proposed in the article the concept of CIPSE is not rendering the legal rules, the authors of the article indicate the directions and outline changes to legislation that would formalize and allow its introduction.
Analyse de similarité de trajectoires d'objets mobiles suivant le même itinéraire

More and more mobile objects are now equipped with sensors allowing real time monitoring of their movements which can be stored in spatio-temporal databases. Nowadays, data mining on a huge quantity of stored positions allows to analyse the behaviour of those mobile objects. From results of statistical analysis on sets of trajectories, spatio-temporal patterns can be defined (main routes and spatio-temporal channels). Using these patterns, unusual situations can be detected in real time. Furthermore, mobile object behaviour can be defined by comparing a trajectory with a main route. In this article, this technique is applied to ship movements in an open maritime area in order to detect unusual behaviours such as being ahead of schedule or delayed, veering to the left or to the right of the main route.
Introduction to Deep Learning for Natural Language Processing (Tutorial at DeepLearning2017 summer school in Bilbao)

In this talk, I start with a brief introduction to the history of deep learning and its application to natural language processing (NLP) tasks. Then I describes in detail the deep learning technologies that are recently developed for three areas of NLP tasks. First is a series of deep learning models to model semantic similarities between texts and images, the task that is fundamental to a wide range of applications, such as Web search ranking, recommendation, image captioning and machine translation. Second is a set of neural models developed for machine reading comprehension and question answering. Third is the use of deep learning for various of dialogue agents, including task-completion bots and social chat bots.
Employer preferences and political alignments during the Eurocrisis: Evidence from the Portuguese case

Abstract This paper strives to shed light on the interaction between business groups and the main governing parties after the onset of the economic crisis through a “thick narrative” approach. By focusing on the Portuguese case, the study aims to examine the preferences of the employer confederations during the distinct phases of the economic crisis and to analyze the political alignments established with different party governments. This contribution confirms the fragmentation of business interests on the one hand and tensions between the right-wing government and the main employer confederations on the other. While a pragmatic approach to party politics seems to be the predominant trend, historical and institutional legacies are still important factors when considering the actions and inner tensions of these organizations.
Entity display priority in a distributed geographic information system

The present invention describes a system for ranking geospatial entities. In one embodiment, the system includes an entity ranking module and an interface for entering ranking data for a plurality of geospatial entities. This module uses a ranking mechanism to generate position ranks for geospatial entities based on ranking data. Store the ranked object data generated by the object ranking module in the database. The entity ranking module may be configured to evaluate a plurality of various attributes to determine a total score for the geospatial entity. The entity ranking module may be configured to organize the ranked entity data into placemark layers. Geospatial objects, distributed geospatial information systems, entity ranking modules, placemarks
Does Money Growth Granger-Cause Inflation in the Euro Area? Evidence from Out-of-Sample Forecasts Using Bayesian VARs

We use a mean-adjusted Bayesian VAR model as an out-of-sample forecasting tool to test whether money growth Granger-causes inflation in the euro area. Based on data from 1970 to 2006 and forecasting horizons of up to 12 quarters, there is surprisingly strong evidence that including money improves forecasting accuracy. The results are very robust with regard to alternative treatments of priors and sample periods. That said, there is also reason not to overemphasize the role of money. The predictive power of money growth for inflation is substantially lower in more recent sample periods compared to the 1970s and 1980s. This cautions against using money-based inflation models anchored in very long samples for policy advice.
SENTIMENT ANALYSIS OF TWEETS

— Social media analytics is an influential means for uncovering human sentiment across countless online sources. The analytics facilitate to various fields to identify sentiment and identify trend and inclination of people. Sentiment analysis method involved observation and monitoring different public sentiment and qualitatively exploring the underlying content. In proposed method twitter data get scrutinized for the sentiment analysis. This is implementing polarity classification over Tweet offered on multiple keys to monitor the feelings/emotions of general public towards bring up issues. These posts are classified as positive, negative or neutral. The project focuses on addressing polarity classification for topic featured in tweet by linking semantic association between the features and polarity words.