Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality Assurance in Teacher Education and Outcomes: A Study of 17 Countries

This study investigated the relationship between policies related to the recruitment, selection, preparation, and certification of new teachers and (a) the quality of future teachers as measured by their mathematics content and pedagogy content knowledge and (b) student achievement in mathematics at the national level. The study used data collected for the Teacher Education and Development Study in Mathematics, which compared the ways in which 17 countries prepared teachers of mathematics for the primary and secondary levels. A consistent positive association was found between the strength of a country’s quality assurance arrangements and future teachers’ knowledge of mathematics and mathematics pedagogy. Countries with strong policies for assuring the quality of new teachers were also found to be among the strongest performers on international tests of mathematics achievement.
Managing Probabilistic Data with MystiQ : The Can-Do , the Could-Do , and the Can ’ t-Do ?

MystiQ is a system that allows users to define a probabilistic database, then to evaluate SQL queries over this database. MystiQ is a middleware: the data itself is stored in a standard relational database system, and MystiQ is providing the probabilistic semantics. The advantage of a middleware over a reimplementation from scratch is that it can leverage the infrastructure of an existing database engine, e.g. indexes, query evaluation, query optimization, etc. Furthermore, MystiQ attempts to perform most of the probabilistic inference inside the relational database engine. MystiQ is currently available from mystiq.cs. washington.edu. The MystiQ system resulted from research on probabilistic databases at the University of Washington [8, 11, 10, 13, 23, 14]. Some of these research results have been fully incorporated in MystiQ, like the query evaluation techniques that allow it to evaluate SELECT-FROM-WHERE-GROUPBY queries over large probabilistic databases: this is what MystiQ can do. Other results are not implemented in the system, but they could either be implemented in some future version after only minor extensions, or can be used even today by a database administrator to perform certain data management tasks manually; an example are the techniques for representing materialized views over probabilistic data. This is what MystiQ could do. Finally, other research results require more work before they can be implemented in a system. For example, our evaluation techniques for queries with a HAVING clause applies only to safe queries; for another example, we currently don’t know of a good approach to extend safe queries and safe plans to queries with self-joins. This is what MystiQ can’t do. In this paper we give a gentle introduction into the MystiQ system, and describe the associated research that is used, or could be used, or is not yet ready to be used in MystiQ. Related Work Our research has focused primarily on SQL query evaluation and on views. Other groups have studied different aspects of probabilistic or incomplete databases. The Trio project [29, 7, 6, 15] focused on the study of lineage in incomplete databases. The MayBMS project has focused on representation problems, query language design, and query evaluation [3, 4, 2, 20]. Other
Religiosity and Family Values: Correlates of God-Image in a Protestant Sample

Religiosity is a multidimensional variable that can be measured in a number of ways, including religious behavior and conscious belief. Several studies have used measures of participants' images of God to operationalize the preconscious imagery that is theorized to be associated with the latter. A. Greeley, using General Social Survey (GSS) data, has examined the relationship between God-image and numerous social attitude variables. In a similar vein, the present study asks how measures of religiosity associate with progressive or traditional stances toward family life. Secondary analysis was performed on a dataset which included measures of God-image, religious behavior, family progressivism, and family traditionalism that were administered to a national sample of 523 Protestant Christians. The findings indicate that God-image and religious behavior are both significantly associated with the family values measures, and are relatively independent of each other. There is some question, however, as to the relative utility of each of the four God-image items. Implications for further research are discussed.
High-level Component Interfaces for Collaborative Development: A Proposal

Software development has rapidly moved toward collaborative development models where multiple partners collaborate in creating and evolving software intensive systems or components of sophisticated ubiquitous socio-technical-ecosystems. In this paper we extend the concept of software interface to a flexible high-level interface as means for accommodating change and localizing, controlling and managing the exchange of knowledge and functional, behavioral, quality, project and business related information between the partners and between the developed components.
Learning Feature Transformations to Recognize Faces Rotated in Depth

We present a method for recognizing objects (faces) on the basis of just one stored view, in spite of rotation in depth. The method is not based on the construction of a three-dimensional model for the object. Our recognition results represent a signi cant improvement over a previous system developed in our laboratory. We achieve this with the help of a simple assumption about the transformation of local feature vectors with rotation in depth. The parameters of this transformation are learned on training examples.
Effects of anthocyanin rich extracts on multiple biomarkers of colon cancer

Title of Thesis EFFECTS OF ANTHOCYANIN RICH EXTRACTS ON MULTIPLE BIOMARKERS OF COLON CANCER Geeta Lala Master of Science, 2005 Thesis directed by: Assistant Professor Bernadene A. Magnuson Department of Nutrition and Food Science The aim of this study was to investigate the chemoprotective activity of anthocyanin-rich extracts (AREs) from bilberry (Vaccinium myrtillus), chokeberry (Aronia meloncarpa) and grape (Vitis vinifera) by assessing multiple biomarkers of colon cancer in rats treated with a colon carcinogen, azoxymethane. Male F344 rats (n = 40) were fed AIN-93 diet (control) or AIN-93 diet supplemented with AREs for 14 weeks. Biomarkers evaluated included total aberrant crypt foci (ACF) that were reduced in ARE diet groups as compared to the control group. The number of large ACF and colonic cellular proliferation were decreased in rats fed bilberry and chokeberry ARE diets. Rats fed bilberry and grape ARE diets had lower COX-2 mRNA levels expression. Increased levels of fecal anthocyanins, fecal mass and moisture occurred in ARE-fed rats. Significant reduction of fecal bile acids was observed in ARE-fed rats. The results from this study suggest a protective role of AREs in colon carcinogenesis, and indicate multiple mechanisms of action are involved. EFFECTS OF ANTHOCYANIN RICH EXTRACTS ON MULTIPLE BIOMARKERS OF COLON CANCER
THE α METRIC VALUES FOR RANDOM AND FULLY ORGANIZED PROGRAMS

Software products are complex systems. Thereafter, the conventional engineering techniques for the measure of quality are not good enough. We advocate that, the methodologies suitable for the analysis of complex systems, namely “the theory of chaos”, can be used for the identification of the program organizations. In this paper we introduce a method to assess the complexity of source and object programs. We analyse how the new fractal software metric, called α, shows the presence of the semantic structure in programs and may quantify their complexity.
The R/evolution of civic engagement: an exploratory network analysis of the Facebook groups of occupy Chicago

ABSTRACT This study explores the role of social media as mediating structures for civic engagement. A network analysis of 2829 Facebook groups joined by 600 randomly sampled occupy Chicago (OC) participants shows that OC is embedded in diverse interconnected voluntary groups mediated by social media. The observed patterns of interconnection reveal a loosely connected, fragmented, and clustered structure. Such a structure may enable publics, as self-organized social groups shaped in networked flows of communication, to shift in and out of more established institutional structures and formal civic organizations to form ‘flexible network-domains’ at developing moments of mobilization. The study explains the empirical patterns of civic affiliation in the context of the broad historical structural changes and the specific characteristics of contemporary forms of mediated sociality.
P300 and Neuropsychological Assessment in Mild Cognitive Impairment and Alzheimer Dementia

Only a small proportion of individuals with Mild Cognitive Impairment (MCI) will convert to dementia. Methods currently available to identify risk for conversion do not combine enough sensitivity and specificity, which is even more problematic in low-educated populations. Current guidelines suggest the use of combined markers for dementia to enhance the prediction accuracy of assessment methods. The present study adhered to this proposal and investigated the sensitivity and specificity of the electrophysiological component P300 and standard neuropsychological tests to assess patients with Alzheimer’s disease (AD) and MCI recruited from a low-income country. The neuropsychological battery comprised tests of memory, attention, language, praxis, and executive functions. The P300 was recorded using a classical visual odd-ball paradigm. Three variables were found to achieve sensitivity and specificity values above 80% (Immediate and Delayed recall of word list – CERAD – and the latency of P300) for both MCI and AD. When they entered the model together (i.e., combined approach) the sensitivity for MCI increased to 96% and the specificity remained high (80%). Our preliminary findings suggest that the combined use of sensitive neuropsychological tasks and the analysis of the P300 may offer a very useful method for the preclinical assessment of AD, particularly in populations with low socioeconomic and educational levels. Our results provide a platform and justification to employ more resources to convert P300 and related parameters into a biological marker for AD.
A Review of Asynchronous Electroencephalogram-based Brain Computer Interface Systems

Various researches on brain computer interfaces have been conducted for physical impaired to control an electronic assistive device using only their brainwaves or scientifically known as electroencephalogram (EEG). The problem of current EEG-based brain computer interface (BCI) system is its performance in accuracy and time response. There are two types of BCI; synchronous and asynchronous. Synchronous BCI is a cue based system which is restricted to a predefined time frame whereas an asynchronous BCI is a self paced system which operates independently of a cue stimulus. The main objective of this review study is to conduct a literature review on the effect of asynchronous design to the accuracy and time response of BCI systems. From the scope of EEG signal processing, research papers and conference proceedings had been collected and reviewed from abstract to conclusion. Results from five significant researches has been compiled and compared. The findings obtained in this study will be significant to researchers and engineers pursuing in EEG-based BCI system in biomedical and health science industry.
Comparison of complex-background subtraction algorithms using a fixed camera

In this paper we look at the problem which is the background subtraction algorithms when dealing with complex, or real-world, background, as background subtraction is a vital step for Computer Vision. We will be measuring the effectiveness of each background subtraction algorithm of handling a real-world scene and subtracting the unwanted background elements as well as the time taken to complete each data set. The data taken from this experiment can show that certain algorithms are suited to specific tasks and by joining them and we could successfully remove a complex background.
Working Paper Series 26 / 2007 Project webs and new modes of organising in the construction sector : insights from an in-depth comparative case study

There is a contemporary fascination with the way in which modern information and communication technologies (ICTs) may facilitate the emergence of innovative new forms of organising. In this paper we attempt to contribute to this debate by focusing on recent attempts to introduce Project Webs in the construction sector as a means of streamlining and improving the way projects are traditionally organised. We draw on in-depth, empirical evidence from interpretive studies of two high-profile construction projects, one based in Ireland and the other in the UK, to explore attempts to use such technologies to facilitate improved communication and collaboration between geographically-dislocated firms. Interestingly, the outcomes of the two projects contrasted radically with one another, with the technology enjoying significant success in one case while failing to make any significant impression at the other. While we point to a range of technological and management issues that contributed to such polarised outcomes, we argue that one of the most significant problems with the successful use of such technology concerns institutionalised practices and relationships within the sector. In particular, we draw attention to the importance of the broader social, political and economic structures that are manifested in the traditional working practices that prevail within the industry. In conclusion, we argue that, rather than conceptualising the introduction of such changes as primarily a technical problem, attention needs to be paid to the manner in which the outcomes are shaped by the specific socio-political context within which such practices are situated.
Epistemic Attitudes and Source Critique in Qualitative Research

In this essay, we explore and discuss current practices of source critique. In our empirical analysis of a sample of interview-based studies, we find that few studies show a careful and reflective stance toward their sources. In the majority of cases, we discern a tendency to either ignore basic issues of the trustworthiness of interview material or produce technical descriptions which seem to have no real effect on the actual assessment of the study’s sources. We suggest five epistemic attitudes which describe how scholars engage—or rather not engage—in source critique. To improve source critique, we suggest tactics of intra- and extrasource critique which seriously consider interactional dynamics behind and quality of interview content other than “truth” reporting, aiming to corroborate interview statements by carefully cross-checking interview material with observations and multiple sources.
Deforestation Induced Climate Change: Effects of Spatial Scale

Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scal land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we examine the effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is simulated over low latitude deforested areas. Mid latitude SAT response is mixed. In all simulations deforested areas tend to become drier and have lower SAT, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation cause an increase in soil carbon large enough to produce a net decrease of atmospheric CO2. Our results reveal the complex interactions between soil carbon dynamics and other climate subsystems in the energy partition responses to land cover change.
Content-Oriented Automatic Text Categorization with the Cognitive Situation Models

Text categorization is an important research field within text mining. The initial objective of text categorization is to recognize, understand and organize various volumes of texts or documents. The general procedures of categorization are treated as supervised learning, from which the similarity can be inferred from a collection of categorized texts for training purpose. Obviously, the typical approaches for categorization are restrained at single word level and not content-oriented. This paper introduces an innovative research work, a content-oriented automatic text categorization algorithm (CogCate), inspired with cognitive situation models, to simulate the human cognitive procedure in the text categorization task. CogCate is not limited with traditional statistics analysis at word level, but includes a process of lexical or semantics analysis, which secures the accuracy of categorization. The evaluation experiments have testified the precision of CogCate. Meanwhile, CogCate tremendously reduces the time and effort spent on training and corpus maintenance, and proves that text categorization can benefit from interdisciplinary research efforts.
Induction, Logic and Natural Language Processing

While computational logic has become widely used for representing and reasoning with linguistic knowledge, the cross-fertilization between logic programming and machine learning has given rise to a new discipline known as inductive logic programming. Inspired by, and building on the achievements of logic programming within both natural language research and machine learning, we point out opportunities for induction of linguistic knowledge within logic (programming).
Performance evaluation of multilayer feed forward neural network for handwritten English Vowels Characters

This paper compares the performance of Gradient descent with momentum & adaptive backpropagation (TRAINGDX) and BFGS quasi-Newton backpropagation (TRAINBFG) of Backpropagation Algorithm in multilayer feed forward Neural Network for Handwritten English Characters of Vowels. This analysis is done with five samples of Handwritten English Characters of Vowels collected from five different people and stored as an image. After partition these scanned image into 4 portions, the densities of these images are determined by using MATLAB function. An input pattern will use these 4 densities of each character as an input for the two different Neural Network architectures. In our proposed work the Multilayer feed forward neural networks will train with two learning algorithms; those are the variant of Backpropagation learning algorithm namely Quasi-Newton backpropagation learning algorithm and Gradient descent with momentum and adaptive backpropagation learning algorithm for training set of the Handwritten English Characters of Vowels. The performance analysis of both Neural Network architectures is done for convergence and nonconvergence. Different observations have been considered for trends of error in the case of nonconvergence. From the observation of the result, it can be shown that in the performance of these above two learning algorithms with the training set of handwritten characters of Vowels, there is limitation of gradient descent learning algorithm for convergence due to the problem of local minima which is inherit problem of backpropagation learning algorithm.
The GESTYLE Language

GESTYLE is a new markup language to annotate text which has to be spoken by Embodied Conversational Agents (ECA), to prescribe the usage of hand-, headand facial gestures accompanying the speech in order to augment the communication. The annotation ranges from low level (e.g. perform a specific gesture) to high level (e.g. take turn in a conversation) instructions. On top of that, and central to GESTYLE is the notion of style which determines the gesture repertoire and the gesturing manner of the ECA. GESTYLE contains constructs to define and dynamically modify style. The low-level tags, prescribing specific gestures to be performed are generated automatically, based on the style definition and the high-level tags. By using GESTYLE, different aspects of gesturing of an ECA can be defined and tailored to the needs of different application situations or user groups.
Neurobiological Mechanism of Acupuncture for Relieving Visceral Pain of Gastrointestinal Origin

It is currently accepted that the neural transduction pathways of gastrointestinal (GI) visceral pain include the peripheral and central pathways. Existing research on the neurological mechanism of electroacupuncture (EA) in the treatment of GI visceral pain has primarily been concerned with the regulation of relevant transduction pathways. The generation of pain involves a series of processes, including energy transduction of stimulatory signals in the sensory nerve endings (signal transduction), subsequent conduction in primary afferent nerve fibers of dorsal root ganglia, and transmission to spinal dorsal horn neurons, the ascending transmission of sensory signals in the central nervous system, and the processing of sensory signals in the cerebral cortex. Numerous peripheral neurotransmitters, neuropeptides, and cytokines participate in the analgesic process of EA in visceral pain. Although EA has excellent efficacy in the treatment of GI visceral pain, the pathogenesis of the disease and the analgesic mechanism of the treatment have not been elucidated. In recent years, research has examined the pathogenesis of GI visceral pain and its influencing factors and has explored the neural transduction pathways of this disease.
An Intrusion Detection System Based on Hadoop

In this paper, considering that the serious network security situation we are facing and the problem of an increasing amount of data generated by the network, we proposed an Intrusion Detection System based on Hadoop, due to the lack of the traditional K-Means algorithm exists at we propose an improved K-Means algorithm, we analyze the performance of the K-Means algorithm and the improved K-Means algorithm with KDD '99 data sets by using the Intrusion Detection System based on Hadoop. The experimental results show that the Accuracy Rate can reach 0.96, the Detection Rate can reach 0.89, the False Alarm rate the minimum is only 0.018. Three intrusion detection performance indicators are better than the traditional K-Means algorithm.