Miracle-dz/UniFAR-FTUs huggingface dataset:
Liderazgo y e-liderazgo en las historias de vida de líderes educativos a través del mundo

El liderazgo en los centros educativos ha de tener cada vez más en cuenta el papel de las nuevas tecnologías de la información y la comunicación, como medio para mejorar las organizaciones. En consecuencia, el objetivo de la presente investigación es analizar las historias de vida de 5 líderes educativos en 5 contextos diferentes: España, Guatemala, Chile, Kazajistán y Estados Unidos; y describir cómo las nuevas tecnologías se engarzan con sus prácticas de liderazgo. La metodología es cualitativa usando como instrumento entrevistas semiestructuradas recogidas entre 2012 y 2018 en los distintos entornos. Se ofrecen ejemplos de líderes, sus prácticas de liderazgo y, particularmente, el papel de los medios tecnológicos en su gestión del cambio. Los resultados revelan prácticas directivas similares y ajustadas a lo descrito previamente por la literatura académica, y muestran asimismo cómo liderazgo y tecnología se afectan mutuamente.Leadership in educational centers must increasingly consider the role of advanced information technologies to improve organizations. Consequently, the objective of this research is to analyze the life histories of 5 educational leaders in 5 different contexts: Spain, Guatemala, Chile, Kazakhstan and the United States; and describe how new technologies are linked with their leadership practices. The methodology is qualitative using as instrument semi-structured interviews collected between 2012 and 2018 in different environments. Examples of leaders, their leadership practices and, mainly, the role of technological media in their change management are offered. The results reveal similar management practices and adjusted to what was previously described by the academic literature, and also show how leadership and technology affect each other.
On supervised and unsupervised methodologies for mining of text data

The supervised and unsupervised methodologies of text mining using the plain text data of English language have been discussed. Some new supervised and unsupervised methodologies have been developed for effective mining of the text data after successfully overcoming some limitations of the existing techniques. The problems of unsupervised techniques of text mining, i.e., document clustering methods are addressed. A new similarity measure between documents has been designed to improve the accuracy of measuring the content similarity between documents. Further, a hierarchical document clustering technique is designed using this similarity measure. The main significance of the clustering algorithm is that the number of clusters can be automatically determined by varying a similarity threshold of the proposed similarity measure. The algorithm experimentally outperforms several other document clustering techniques, but it suffers from computational cost. Therefore another hybrid document clustering technique has been designed using the same similarity measure to overcome the computational burden of the proposed hierarchical algorithm, which performs better than the hierarchical one for most of the corpora. The limitations of nearest neighbor decision rule for text categorization are discussed. An efficient nearest neighbor decision rule is designed for qualitative improvement of text categorization. The significance of the proposed decision rule is that it does not categorize a document when a decision in not so certain. The method is showing better results than several other classifiers for text categorization. The decision rule is also implemented using the proposed similarity measure instead of traditional similarity measure, which performs better than the same using traditional similarity measure. The importance of dimensionality reduction for text categorization is also discussed. A supervised term selection technique has been presented to boost the performance of text categorization by removing redundant and unimportant terms. The empirical studies have shown that the proposed method has improved the quality of text categorization.
Enterprise User's Manual Version 2.2

This document is a user's manual for version 2.2 of the Enterprise parallel programming system. Enterprise is an interactive graphical programming environment for designing, coding, debugging, testing and executing programs in a distributed hardware environment. Enterprise code looks like familiar sequential code because the parallelism is expressed graphically and independently of the code. The system automatically inserts the code necessary to correctly handle communication and synchronization, allowing the rapid construction of distributed programs.
Improving Tools in Artificial Intelligence

The historical origin of the Artificial Intelligence (AI) is usually established in the Dartmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA), Norbert Wiener, Alan Mathison Turing, or Lofti Zadeh, for instance [12, 14]. Frequently AI requires Logic. But its Classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as Fuzzy Logic, Modal Logic, Non-Monotonic Logic and so on [1, 2]. Among the things that AI needs to represent are categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in AI can be classified in two general types [3, 5], search problems and representation problems. On this last "peak", there exist different ways to reach their summit. So, we have [4] Logics, Rules, Frames, Associative Nets, Scripts, and so on, many times connected among them. We attempt, in this paper, a panoramic vision of the scope of application of such representation methods in AI. The two more disputable questions of both modern philosophy of mind and AI will be perhaps the Turing Test and the Chinese Room Argument. To elucidate these very difficult questions, see our final note.
Las edades vulnerables: Infancia y vejez en la Antigüedad

En esta publicacion se afrontan dos periodos de la vida concretos: la infancia y la vejez. Seran tratados en distintas sociedades de la Antiguedad: Mesopotamia, Grecia y Roma, extendiendose la reflexion hasta el siglo VII. Conceptos como vulnerabilidad, dependencia y alteridad aparecen en los distintos capitulos, en los que el periodo infantil y la senectud se combinan tambien con la posicion economica, el estatus juridico y el genero. Surge asi una contribucion que nos permite ahondar mas alla de la etapa adulta en la que hombres y mujeres disfrutaban de plenas facultades. Edades, en cuya descripcion y comentarios reconoceremos algunos aspectos que definen nuestro presente, pero que en otros casos son reflejo particular de las construcciones socioculturales que caracterizaron nuestro pasado.
Design and development of a new portable test setup to study friction and wear

In this paper, a novel portable sliding friction and wear test rig is introduced. Unlike other laboratory-based test setups, this setup can be used for both indoor and outdoor experiments. There is also no limitation on the size and type of the substrate surface that can be used for the friction and wear test in contrast to typical test rigs, which have some limitations for the size and type of substrate surface. A small six-wheel ground robot is developed to drag the sample on an arbitrary surface for a desired distance and velocity. A ground robot is an unmanned ground vehicle, capable of driving on the ground without humans on board. The speed of this robot can be measured and controlled precisely. The nominal normal load is adjusted using dead weights placed on the sample holder and the friction force is measured using a load cell. An adjustable sample holder was also designed and built to hold different-size specimens. The results of styrene–butadiene rubber block sliding on an asphalt track are presented to validate the test setup and illustrate the potential of the system for friction and wear testing. In addition, the effect of sliding velocity on the friction and wear is studied, and the correlation between the wear rate and the friction coefficient is investigated. These experimental results can be used to estimate the friction and life span of a tire tread compound on the real asphalt road. Finally, the formation of abrasion pattern observed on the rubber surface sliding on an asphalt track is discussed, which provides an insight into the understanding of dominant wear mechanism of tire tread compound on typical asphalt surfaces.
Aquisição de estruturas clivadas no português europeu: produção espontânea e induzida

This paper focuses on the acquisition of cleft sentences by monolingual Portuguese children. Leaning on the analysis of longitudinal data from the spontaneous production of six children from 1;2 to 4;6 and on the results of an elicited production task carried out with 3-6 year old children, it argues in favour of the hypothesis that computational complexity determines the order of emergence and the development of cleft structures in the child speech.
Discriminant feature extraction and selection for person-independent facial expression recognition

Automatic facial expression recognition has attracted significant research attention since the 1990s due to its potential applications in human computer interaction. Although facial expression recognition seems easy and straight forward to us, it is a challenging task for computers. Due to the subtlety and variability of human facial expressions, existing methods based on 2D images/videos have limitations such as sensitivity to changes in recording conditions, and inability to represent easily-confused expressions etc. Moreover, the human face is neither convex nor rigid, which means that some of the deformations are hard to record by single-view 2D images/videos. In order to represent facial expressions sufficiently, 3D data based methods for expression analysis have recently gained popularity due to the availability of low cost 3D recording devices. An ideal facial expression recognition system should be fully automatic, person-independent, and able to work with all types of facial expressions. Existing research has focused on addressing individual aspects but a system that fulfills all these requirements is yet to be developed. This thesis investigates the facial expression recognition problem with emphasis on: (1) full automation, from landmark detection to expression classification, (2) discriminative feature extraction to represent facial expressions, such as colour spaces, facial components, and descriptors; (3) disambiguation of easily-confused expressions by designing novel classifiers. Firstly, the useful colour spaces for facial expression recognition are investigated in this thesis. Especially, the Uncorrelated Colour Space (UCS) and the Discriminant Colour Space (DCS) are derived for expression recognition and their performance is compared against the standard RGB colour space and grayscale colour spaces typically used, on the Oulu-CASIA NIR&VIS facial expression database and the CurtinFaces database. For feature extraction on grayscale images, two categories are mainly investigated: geometric features and appearance-based features. This thesis proposes a combination of these two feature types as a better representation for facial expression recognition. In order to disambiguate the misclassification between easily-confused expressions, such as anger and sadness, a two-tiered hierarchical classification is proposed and different sets of features are fed to support vector machine (SVM) classifiers in each tier. Our results show that the six prototypic expressions are not mutually exclusive, and that our hierarchical classification can reduce major confusions between anger and sadness. Next, this thesis proposes a fully automatic 3D static facial expression recognition method. Unlike the majority of existing works which rely on manually annotated landmarks to
Federated Access Management for Collaborative Environments

Access control has been historically recognized as an effective technique for ensuring that computer systems preserve important security properties. Recently, attributebased access control (ABAC) has emerged as a new paradigm to provide access mediation by leveraging the concept of attributes: observable properties that become relevant under a certain security context and are exhibited by the entities normally involved in the mediation process, namely, end-users and protected resources. Also recently, independently-run organizations from the private and public sectors have recognized the benefits of engaging in multi-disciplinary research collaborations that involve sharing sensitive proprietary resources such as scientific data, networking capabilities and computation time and have recognized ABAC as the paradigm that suits their needs for restricting the way such resources are to be shared with each other. In such a setting, a robust yet flexible access mediation scheme is crucial to guarantee participants are granted access to such resources in a safe and secure manner. However, no consensus exists either in the literature with respect to a formal model that clearly defines the way the components depicted in ABAC should interact with each other, so that the rigorous study of security properties to be effectively pursued. This dissertation proposes an approach tailored to provide a well-defined and formal definition of ABAC, including a description on how attributes exhibited by different independent organizations are to be leveraged for mediating access to shared resources, by allowing for collaborating parties to engage in federations for the specification, discovery, evaluation and communication of attributes, policies, and access mediation decisions. In addition, a software assurance framework is introduced to support the correct construction of enforcement mechanisms implementing our approach by leveraging validation and verification techniques based on software assertions, namely, design by contract (DBC) and behavioral interface spec-
Problems of teaching and learning the basics of programming Problemas de ensino e aprendizagem dos fundamentos de programação

Among the scenarios related to computer science, learning activities associated with computer programming have been recognized with a high degree of difficulty, according to the information revealed in this review article. With this situation, which apparently is quite common at the global level, the causes of this problem are related to certain characteristics that happen inside the classroom. Certain cognitive skills are relevant at the time of learning the basics of programming, such as the ability of abstraction, a good logical-mathematical aptitude and ability to solve algorithmic order problems. In addition, motivators are necessary when faced with the issues associated with programming fundamentals in practice settings. The content of this review involves experiences in different areas of the planet, whose interest aims to uncover the origins of the problem. Finally, a reflection is made in the search for possible solutions, and where the performance space is opened to a new orientation based on the core of the Essence of Semat.
Expresii watercolor

We present Expresii, a software tool that gives digital artists the serendipity of painting with water-based media like never before. Our watercolor simulation is based on Computational Fluid Dynamics to give true fluidity. We devised a novel hybrid-vector-raster rendering method to allow large output at 12k+ resolution. Our expressive virtual brush can capture stroke rhythm as if wielding a real brush to give organic variations. Finally, we also make use of G-Sensor in today's tablet computer for surface tilting and stylus pressure for variation in color loading to make the painting experience closer to real life.
II. Current developments in the design and production of three- dimensional curved objects - Computational geometry

The accurate representation of shape which is essential to engineering design and manufacture conventionally has been achieved by two-dimensional drafting but new computer-based methods are being developed. The mathematical representation, manipulation, analysis and synthesis of shape information in a computer is termed computational geometry. A mathematical representation must take into account not only the capabilities and limitations of computer hardware and software but also those of a mathematically unsophisticated user. A distinction is drawn between the fitting of a mathematical representation to a predesigned object and the design of an object ab initio or by modification of an existing mathematical model. Conventional curve and surface fitting techniques have been found to be unsuitable. Several methods of representation which are intended to overcome these problems are discussed.
Coh-Metrix Measures Text Characteristics at Multiple Levels of Language and Discourse

Coh-Metrix analyzes texts on multiple measures of language and discourse that are aligned with multilevel theoretical frameworks of comprehension. Dozens of measures funnel into five major factors that systematically vary as a function of types of texts (e.g., narrative vs. informational) and grade level: narrativity, syntactic simplicity, word concreteness, referential cohesion, and deep (causal) cohesion. Texts are automatically scaled on these five factors with Coh-Metrix-TEA (Text Easability Assessor). This article reviews how these five factors account for text variations and reports analyses that augment Coh-Metrix in two ways. First, there is a composite measure called formality, which increases with low narrativity, syntactic complexity, word abstractness, and high cohesion. Second, the words are analyzed with Linguistic Inquiry and Word Count, an automated system that measures words in texts on dozens of psychological attributes. One next step in automated text analyses is a topics analysis that scales the difficulty of conceptual topics.
A Sea-Sky Line Detection Aided GNSS/INS Integration Method for Unmanned Surface Vehicle Navigation

With the fast development of unmanned systems technology and artificial intelligence, Unmanned Surface Vehicle (USV) following unmanned aerial vehicle and unmanned vehicle is becoming more and more popular in military and civilian applications, such as hydrographic survey, maritime search and rescue, coastal water environment monitoring, 3D mapping and enemy reconnaissance. One of the core technologies of the USV is the precise and autonomous navigation system, which is essential for the USV accomplishing a variety of missions without human interventions. Usually, Global Navigation Satellite Systems (GNSS) is integrated with Inertial Navigation System (INS) or other embedded sensors to obtain more accurate position, attitude, speed, heading, etc. To meet the high performance requirements for USV navigation, a sea-sky line detection aided GNSS/INS integration method is proposed in this paper. The proposed method uses sea-sky line as an aid to GNSS/INS integration for USV navigation, which uses the different system to compensate the drawbacks of each source. First, a novel image-based sea-sky line detection method is presented. Then, the detected sea-sky line is applied into a geometric model to determine the roll and pitch angle of the USV. Finally, the difference equation of the SSL is integrated into the GNSS/INS hybridization architecture to improve the performance of the navigation system. Experimental results demonstrate the effectiveness of our proposed algorithm over the existing GNSS/INS integration method in the navigation parameters estimation, which can be applied for USVs with a camera system available on board.
Visual perspective taking as investigated by fast periodic visual stimulation (FPVS)

Visual perspective taking (VPT) corresponds to our ability to see the world from another person's perspective. We investigated VPT using fast periodic visual stimulation (FPVS) approach while measuring electroencephalography (EEG). This thesis had two main objectives, the first was to extend the FPVS approach to study high-level socio-cognitive functions in the human brain. The second objective was to investigate the cognitive basis of mind-reading, and discriminate whether implicit VPT involves perspective taking mechanisms (mentalizing hypothesis) or only spatial cuing mechanisms (submentalizing hypothesis). Our findings lead to support another theoretical framework, the continuum scale theory which consider that submentalizing and implicit mentalizing are not dichotomous processes but reflect a continuum of processing of increased depth. Overall,this thesis provides a promising new approach for exploring the neural basis in human social cognition and their inter-individual differe.
A Model of Continuous Improvement of Data Quality in Modelling and Simulation

Accurate, reliable and adaptive data form the foundation stone of large-scale simulation system and data quality becomes one of the most important measures weighing the reliability of simulation system. This paper firstly establishes an index system of data quality evaluation for large-scale simulation system which uses the six-grade scale method to mark and calculate weights of indexes, then draws out the curve between investments and quality index values by Pearl forecasting model, and lastly gets the optimized outlay distribution based on GA upon the condition of fixed total investment, realizing the continuous improvement of data quality and helping to the promotion of reliability for large-scale simulation system.
Evaluation of Sonographic Detected Fatty Livers: Comparison of Multi Parametric MRI with ARFI Elastography; An Initial Experience

Background: Even as ultrasound based elastography detects changes in liver stiffness with good accuracy newer emerging tools using magnetic resonance imaging(MRI) are being evaluated to have a global assessment of Non alcoholic fatty liver disease(NAFLD). This study was designed to compare the role Multiparametric MRI (mpMRI) and ultrasound elastography in the assessment of fatty liver detected on sonogram. Study: 50 consecutive non alcoholic patients with no prior history of chronic liver disease with fatty liver on sonogram had shear wave elastography using acoustic radiation force impulse (SW-ARFI) imaging followed by Mp MRI. The median liver stiffness was assessed on ARFI while liver fat content, iron content along with Mean T1 value of liver determined on MpMRI. The results of both modalities were statistically analyzed. Original Research Article Kapur et al.; JAMMR, 23(10): 1-14, 2017; Article no.JAMMR. 36343 2 Results: Out of 50 patients examined with echogenic fatty livers, 30 were males and 20 females with mean age of 42 years. The median liver stiffness on ARFI was 1.37 m/s while median T1 on Mp MRI was 653.8 msec. MpMRI showed a sensitivity and specificity of 100%, 91% in detection of liver inflammation with AUC of 1.0 with ARFI. Statistically significant linear relationship was seen between liver iron content and liver fat content in all groups with T1 maps. 3 patients had abnormal high liver iron content with normal liver fat content but had echogenic fatty liver appearance on ultrasound. Conclusion: Mp MRI detects changes in liver stiffness based on T1 estimation of liver parenchyma with high sensitivity and specificity with results comparable with SWI-ARFI. It has advantage over ARFI being more robust and also estimates liver fat and iron content and can be used a single shot test for comprehensive evaluation of echogenic livers.