Miracle-dz/UniFAR-FTUs huggingface dataset:
Introduction to Information Quality

This is a sound textbook for Information Technology and MIS undergraduate students, and MBA graduate students and all professionals looking to grasp a fundamental understanding of information quality. The authors performed an extensive literature search to determine the Fundamental Topics of Data Quality in Information Systems. They reviewed these topics via a survey of data quality experts at the International Conference on Information Quality held at MIT. The concept of data quality is assuming increased importance. Poor data quality affects operational, tactical and strategic decision-making, and yet error rates of up to 70%, with 30% typical are found in practice (Redman). Data that is deficient leads to misinformed people, who in turn make bad decisions. Poor quality data impedes activities such as re-engineering business processes and implementing business strategies. Poor data quality has contributed to major disasters in the federal government, NASA, Information Systems, Federal Bureau of Investigation, and most busineses. The diverse uses of data and the increased sharing of data that has arisen as a result of the widespread introduction of data warehouses have exacerbated deficiencies with the quality of data (Ballou). In addition, up to half the cost of creating a data warehouse is attributable to poor data quality. The management of data quality so as to ensure the quality of information products is examined in Wang. The purpose of this book is to alert our IT-MIS-Business professionals to the pervasiveness and criticality of data quality problems. The secondary agenda is to begin to arm the students with approaches and the commitment to overcome these problems. The current authors have a combined list of over 200 published papers on data and information quality.
Written Advising Strategies in Self-Directed Learning Modules and the Effect on Learning

Learners at Kanda University of International Studies in Japan have the opportunity to take optional, self-directed learning modules through the Self-Access Learning Centre (SALC). Participating students are assigned a learning advisor who works closely with them both in person and also through written communication on the learner’s work. The purpose of the modules is to facilitate the development of language learner autonomy and to provide individualised language learning opportunities. Comments provided to learners are intended to promote a deeper level of awareness of the language learning process and to focus on cognitive, metacognitive, social and affective factors. This paper summarises a two-year study where (1) written comments made to twenty-four learners by seven learning advisors were analysed over a one-semester period and (2) the learners’ reactions to the comments and effects that the comments had on actual cognitive and metacognitive development were investigated. I. Literature Review With an increased interest in supporting learners outside of class and in fostering learner autonomy and life-long learning skills comes the need for additional support mechanisms for independent language learners. If promoting autonomy is to be successful, then support for the development of cognitive and metacognitive growth outside scheduled class time needs to be available to learners. Cognitive awareness is the knowledge that a learner has about strategies
PGT - A path Generation Toolbox for MatLab (v0.1)

This users manual introduces the basic ideas of the PGT - Path Generation Toolbox for Matlab. The main features of the toolbox is to givethe user the possibility to 1) build paths in Cartesian (3DOF) space, 2) transform the Cartesian paths into jointspace. All the most important functions are explained and examples of how to use them are also included.
Author Profiling for English and Arabic Emails

This paper reports on some aspects of a research project aimed at automating the analysis of texts for the purpose of author profiling and identification. The Text Attribution Tool (TAT) was developed for the purpose of language-independent author profiling and has now been trained on two email corpora, English and Arabic. The complete analysis provides probabilities for the author’s basic demographic traits (gender, age, geographic origin, level of education and native language) as well as for five psychometric traits. The prototype system also provides a probability of a match with other texts, whether from known or unknown authors. A very important part of the project was the data collection and we give an overview of the collection process as well as a detailed description of the corpus of email data which was collected. We describe the overall TAT system and its components before outlining the ways in which the email data is processed and analysed. Because Arabic presents particular challenges for NLP, this paper also describes more specifically the text processing components developed to handle Arabic emails. Finally, we describe the Machine Learning setup used to produce classifiers for the different author traits and we present the experimental results, which are promising for most traits examined.
Implications of Learning Theories for Effective Technology Integration and Pre-service Teacher Training: A Critical Literature Review

This review will explore the influences of technology integration into pre-service teacher education programs from the constructivist and behaviorist perspectives for the ultimate aim of improving student learning and pre-service teacher training. A wide range of research is cited, including research articles, books, comparison studies, case studies, government records, dissertations and web sites. The study concludes that technology integration representing learning from technology (behaviorist perspective) is not the most effective way to improve learning although it helps learners to perform the lower level subskills automatically. On the other hand, constructivist-learning environments representing learning with technology, which encourages learners to actively process and organize information by making internal cognitive connections, can well provide the theoretical framework for the effective technology integration.
Web Image Retrieval using Prior Tags based on WordNet Semantic Information

This research is for early extraction and utilization of semantic information from the tags in tagged Web image retrieval. Generally, users attach a tag to a Web image with little thought of the order, up to over 100 ones. In this paper, we suggest a method of selecting prior tags based on their importance when tagged images are uploaded, and using them in image retrieval. Ideas came from the recognition of the important tags which give a better description of the image as the tags sharing more semantic information with other tags of the same image. This method includes calculation of relation scores between tags based on WordNet and multilevel search of tagged images with the scores. For evaluation, we compared the suggested method and other retrieval methods searching images with simple matching of tags to a given keyword. As the results, we found the superiority of our method in precision and recall rate.
Comparative Analysis of Connection and Disconnection in the Human Brain Using Diffusion MRI: New Methods and Applications

Dmagnetic resonance imaging (d) is a technique that can be used to examine the diffusion characteristics of water in the living brain. A recently developed application of this technique is “tractography”, in which information from brain images obtained using d is used to reconstruct the pathways which connect regions of the brain together. Proxy measures for the integrity, or coherence, of these pathways have also been defined using d-derived information. The “disconnection hypothesis” suggests that specific neurological impairments can arise from damage to these pathways as a consequence of the resulting interruption of information flow between relevant areas of cortex. The development of d and tractography have generated a considerable amount of renewed interest in the disconnectionist thesis, since they promise a means for testing the hypothesis in vivo in any number of pathological scenarios. However, in order to investigate the effects of pathology on particular pathways, it is necessary to be able to reliably locate them in three-dimensional d images. The aim of the work described in this thesis is to improve upon the robustness of existing methods for segmenting specific white matter “tracts” from image data, using tractography, and to demonstrate the utility of the novel methods for the comparative analysis of white matter integrity in groups of subjects. The thesis begins with an overview of probability theory, which will be a recurring theme throughout what follows, and its application to machine learning. After reviewing the principles of magnetic resonance in general, and d and tractography in particular, we then describe existing methods for segmenting particular tracts from group data, and introduce a novel approach. Our innovation is to use a reference tract to define the topological characteristics of the tract of interest, and then search a group of “candidate” tracts in the target brain volume for the best match to this reference. In order to assess how well two tracts match we define a heuristic but quantitative tract similarity measure. In later chapters we demonstrate that this method is capable of successfully segmenting tracts of interest in both young and old, healthy and unhealthy brains; and then describe a formalised version of the approach which uses machine learning methods to match tracts from different subjects. In this case the similarity between tracts is represented as a matching probability under an explicit model of topological variability between equivalent tracts in different brains. Finally, we examine the possibility of comparing the integrity of groups of white matter structures at a level more fine-grained than a whole tract.
Examining Application Components to Reveal Android Malware

Abstract : Smartphones are becoming ubiquitous in everyday life and malware is exploiting these devices. Therefore, a means to identify the threats of malicious applications is necessary. This paper presents a method to classify and analyze Android malware through application component analysis. The experiment parses select portions from Android packages to collect features using byte sequences and permissions of the application. Multiple machine learning algorithms classify the samples of malware based on these features. The experiment utilizes instance based learner, naive Bayes, decision trees, sequential minimal optimization, boosted naive Bayes, and boosted decision trees to identify the best components that reveal malware characteristics. The best case classifies malicious applications with an accuracy of 99.24% and an area under curve of 0.9890 utilizing boosted decision trees. This method does not require scanning the entire application and provides high true positive rates. This thesis investigates the components to provide malware classification.
Information integration in perceptual and value-based decisions

Research on the psychology and neuroscience of simple, evidence-based choices has led to an impressive progress in capturing the underlying mental processes as optimal mechanisms that make the fastest decision for a specified accuracy. The idea that decision-making is an optimal process stands in contrast with findings in more complex, motivation-based decisions, focussed on multiple goals with trade-offs. Here, a number of paradoxical and puzzling choice behaviours have been revealed, posing a serious challenge to the development of a unified theory of choice. These choice anomalies have been traditionally attributed to oddities at the representation of values and little is known about the role of the process under which information is integrated towards a decision. In a series of experiments, by controlling the temporal distribution of the decision-relevant information (i.e., sensory evidence or value), I demonstrate that the characteristics of this process cause many puzzling choice paradoxes, such as temporal, risk and framing biases, as well as preference reversal. In Chapter 3, I show that information integration is characterized by temporal biases (Experimental Studies 1-2, Computational Studies 1-3). In Chapter 4, I examine the way the integration process is affected by the immediate decision context (Experimental Studies 3-4, Computational Study 4), demonstrating that prior to integration, the momentary ranking of a sample modifies its magnitude. This principle is further scrutinized in Chapter 5, where a rank-dependent accumulation model is developed (Computational Study 5). The rank-dependent model is shown to underlie preference reversal in multi-attribute choice problems and to predict that choice is sensitive, not only to the mean strength of the information, but also to its variance, favouring riskier options (Computational Study 6). This prediction is further confirmed in Chapter 6, in a number of experiments (Experimental Studies 5-7) while the direction of risk preferences is found to be modulated by the cognitive perspective induced by the task framing (Experimental Study 8). I conclude that choice arises from a deliberative process which gathers samples of decision-relevant information, weighs them according to their salience and subsequently accumulates them. The salience of a sample is determined by i) its temporal order and ii) its local ranking in the decision context, while the direction of the weighting is controlled by the task framing. The implications of this simple, microprocess model are discussed with respect to choice optimality while directions for future research, towards the development of a unified theory of choice, are suggested.
Etude des systèmes dynamiques hybrides par représentation d'état discrète et automate hybride

ion par des systèmes événementiels Une autre approche de vérification de propriétés de systèmes hybrides consiste à calculer une abstraction purement discrète pour utiliser les méthodes et les outils de vérification des systèmes à événements discrets. L’idée est de construire une abstraction du modèle de départ, c’est-à-dire d’obtenir un automate qui modélise toutes les trajectoires autorisées par le modèle initial, afin de garantir que toute zone de l’espace d’état continu atteignable correspondra à une zone de l’espace discret. Ainsi, toutes les propriétés de sûreté prouvées sur le modèle discret seront garanties sur le modèle hybride de départ. Le problème pour obtenir un modèle purement discret d’un système hybride réside dans l’abstraction du modèle continu. L’approche la plus directe est présentée dans [PBVV96] et consiste à découper l’espace d’état continu en pavés rectangulaires, associés, chacun, à un état discret. La difficulté principale est alors de trouver un compromis entre la précision et le nombre d’états discrets par exemple en appliquant le concept de grille à des sous-espaces de l’espace d’état continu et en particulier aux surfaces de commutation du système hybride [CK98].
Neural networks—an overview

Abstract : This report provides an introduction to the field of neural networks, what they are, how they came about, how they work, how they are used, and their current status and potentialities. Neurons are brain cells. There are approximately ten billion (10 to the 10th power) brain cells of varying types in the human brain. These are interconnected by axons and dendrites, the axon being the output fiber of a neuron which branches off into dendrites which in turn connect to other neurons. The interconnectivity can be quite dense with one neuron receiving inputs from up to thousands of others. The action of the neuron is to generate an electrical pulse or pulse train if the summation of its inputs exceeds a threshold associated with a particular neuron. The collection is thus similar to a vast highly interconnected network of threshold elements. It is this network which constitutes the human thinking machine. This thinking machine has capabilities that, to date, have frustrated duplication by large scale digital computers. These capabilities are not in the area of esoteric high level mathematics but in what are generally considered simple normal processes, that is processes that could be performed even by children.
Advancing Systems Thinking in Evaluation

This article reviews four books published in 2010 and 2011 on the topic of systems thinking in evaluation: Developmental Evaluation: Applying Complexity Concepts to Enhance Innovation and Use by Michael Q. Patton; Purposeful Program Theory: Effective Use of Theories of Change and Logic Models by Sue Funnell and Patricia Rogers; Systems Concepts in Action: A Practitioner's Toolkit by Bob Williams and Richard Hummelbrunner, and Evaluation in the Face of Uncertainty: Anticipating Surprise and Responding to the Inevitable by Jonathan Morell. These books describe the interdisciplinary landscape of systems theories, encompassing general systems theory, systems dynamics, complexity theory, network theory, and learning systems, and how they can be used to improve evaluation practice. The books appeal to many different and sometimes overlapping audiences. Separately, they address specific information needs about how to incorporate systems concepts into different aspects of evaluation design, data collection, analysis, and reporting. Together, the books complement and reinforce each other, creating a cohesive picture of the state of the art of systems thinking by encouraging thinking about situational dynamics in an often complicated and complex world. The books’ authors also advance systems thinking in evaluation by inviting their readers to test out the books’ ideas and methods in their own evaluation work.
High-density Real-time Virtual Crowds via Unilaterally Incompressible Fluid Simulation

Human crowds experience limited individual freedom of motion and tend to exhibit aggregate behavior at high densities. This observation can be exploited in simulations by representing virtual crowds as both distinct agents and continua. We introduce a global planning algorithm suitable for navigating large virtual crowds of agents. These crowds are in turn modeled as unilaterally incompressible fluids to effectively simulate large-scale behavior. The algorithm is ultimately tested on certain specific scenarios with the intention of detecting common emergent behaviors, to finally draw conclusions on its ability to simulate real-life situations.
Kant or Cant: The Myth of the Democratic Peace

I T h e theory of the “Democratic Peace” raises important theoretical issues:’ the contention that democratic states behave differently toward each other than toward nondemocracies cuts to the heart of the international relations theory debate about the relative salience of second-image (domestic politics) and of thirdimage (systemic structure) explanations of international political outcomes. Democratic peace theory has also come to have a real-world importance as well: Policymakers who have embraced democratic peace theory see a crucial link between America’s security and the spread of democracy, which is viewed as the antidote that will prevent future wars. Indeed some democratic peace theorists, notably Bruce Russett, believe that in an international system comprising a critical mass of democratic states, ”It may be possible in part to supersede the ‘realist’ principles (anarchy, the security dilemma of states) that have dominated practice to the exclusion of ’liberal’ or ’idealist’ ones since at least the seventeenth century. ”2 Because of its theoretical claims and
Encyclopedia of Trauma: An Interdisciplinary Guide

encyclopedia of trauma: an interdisciplinary guide encyclopedia of trauma an interdisciplinary guide haow encyclopedia of trauma an interdisciplinary guide wcbk encyclopedia of trauma an interdisciplinary guide the encyclopedia of psychological trauma cofp encyclopedia of trauma: an interdisciplinary guide the encyclopedia of psychological trauma ztrd the encyclopedia of psychological trauma jlip trauma, dissociation and ptsd research group 2015-2016 summer 2013 impact child trauma home book the encyclopedia of psychological trauma usoforal summer 2013 conversations about historical trauma: part two cv eugenia l.weiss 2015 university of southern california the vtt navaa benjamin b. keyes page 1 regent weiss curriculum vitae 32013 university of southern curriculum vita the college of psychology at nsu category title isbn publisher pub date coaching understood sl gilkey, cv 2015 tamuk vicarious trauma, compassion fatigue and burnout in editor charles r. figley tulane university list of references & bibiography brieftherapyconference interdisciplinary handbook of trauma and culture ebook postscripts tulane school of social work curriculum vitae marva l. lewis april 2015 i. contact shifting the paradigm 2015 assembled answers liz additions generac power systems manual quafe autostart hdr manual avexfx healing daysa guide for kids who have experienced trauma people v gathings hsandc a windows dos study guide vrsell siberian keepers upsky free ebooks encyclopedia of the vatican and papacy loved by the cowboy angfit
TangiPaint: Interactive Tangible Media

TangiPaint: Interactive Tangible Media Anthony M. Blatner Supervising Professors: Dr. James Ferwerda, Dr. Reynold Bailey Currently, there is a wide disconnection between the real and virtual worlds in computer graphics. Art created with textured paints on canvases have visual effects which naturally supplement simple color. Real paint exhibits shadows and highlights, which change in response to viewing and lighting directions. The colors interact with this environment and can produce very noticeable effects. Additionally, the traditional means of human-computer interaction using a keyboard and mouse is unnatural and inefficient—gestures and actions are not performed on the objects themselves. These visual effects and natural interactions are missing from digital media in the virtual world. The absence of these visual characteristics disconnects users from their content. Our research looks into simulating these missing pieces and reconnecting users. TangiPaint is an interactive, tangible application for creating and exploring digital media. It gives the experience of working with real materials, such as oil paints and textured canvases, on a digital display. TangiPaint implements natural gestures and allows users to directly interact with their work. The Tangible Display technology allows users to tilt and reorient the device and screen to see the subtle gloss, shadow, and impasto lighting effects of the simulated surface. To simulate realistic lighting effects we use a Ward BRDF illumination model. This model is implemented as an OpenGL shader program. Our system tracks the texture and relief of a piece of art by saving topographical information. We implement height fields, normal vectors, and parameter
Judgement and Decision Making in Dynamic Tasks

Abstract : This research note presents a theory of task conditions on the grounds that such a theory is a prerequisite for studying dynamic decision making. The principal features of the theory are: a) a task-cognition inducement principle, b) a distinction drawn between surface and depth characteristics of tasks, and c) a task continuum index. Also presented is a theory of cognition in dynamic tasks, the main features of which are a cognitive continuum index set in parallel with the continuum index, and a description of the role of pattern seeking and functional-relation seeking in dynamic tasks. The practical consequences for both designers and operators are indicated.