Miracle-dz/UniFAR-FTUs huggingface dataset:
DEVELOPMENT AND EFFECT OF MULTIMEDIA LEARNING ARITHMETIC TO IMPROVE ELEMENTARY STUDENTS’ MATHEMATICAL ABILITIES

The second phase of this research is develop and measure multimedia learning arithmetic to improve elementary students' mathematical abilities based on the results of the first phase of the study. Multimedia learning arithmetic made, conducted using 10 indicators that is communicative, creative, simple, unity, the depiction of objects in the form of a representative image, the selection of the appropriate color, typography, layout, moving visual elements, and navigation. Barriers in developing multimedia learning arithmetic is collective bargaining entire team to create and measure multimedia is in the process of realizing a multimedia representative; find professionals who are willing to make a multimedia learning arithmetic representative; practical power of multimedia learning arithmetic makers who understand the character of elementary school students in learning arithmetic. Nevertheless multimedia learning arithmetic can improve elementary students' mathematical ability, and better than the learning outcomes of students who are learning without the use of multimedia learning arithmetic. Keywords: Multimedia, Arithmetic
Nature-Inspired Metaheuristic Algorithms

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.
Facets and outcomes of healthcare service innovation: a study of catholic service providers in Northern Portugal

The aim of this study was to promote a better understanding of the factors influencing innovation in the provision of health services by branches of the Catholic church's 'Sacred House of Mercy' (Santa Casa de Misericordia) operating in Portugal, and to determine the effects of innovation on the performance of individual staff and the local organisations as a whole. The chosen method for data collection was the questionnaire survey. The unit of analysis is constituted by the staff of Misericordias in the North of Portugal that provide health services. To evaluate the relationship between innovation and performance, recourse was made to a structural equation model and AMOS 20 software. The results of the study suggest that the Misericordias analysed display innovative behaviour that contributes positively to individual employee satisfaction, team spirit and overall organisational performance. The study provided a better understanding of the factors that influence innovation in this type of not-for-profit organisations.
Explicit Vocabulary Instruction in an English Content-Area Course with University Student Teachers: When Comprehensible Input Needs to Be Comprehended.

This action research study explores explicit vocabulary instruction in an L2 (English) content-area course with a group of university student teachers. The study reviews several positions on the treatment of vocabulary in L2 contexts. The researcher takes up the teaching of explicit vocabulary through class activities and the students’ completion of vocabulary entries in a Word Study notebook. The data collection procedures included the teacher´s lesson plans, the students´ Word Study entries, and their opinions on both their vocabulary learning and their notebook completion through a final interview. Research findings reveal that the Word Study notebook did contribute to students’ learning since they had a grasp of the vocabulary used in the class in terms of participating in the instructional conversations led by the professor and doing the class activities.
The Aesthetics and Affects of Cuteness

Cuteness is a powerful affective register whose social proliferation since the turn of the millennium has been striking. The essays in The Aesthetics and Affects of Cuteness (forthcoming, Routledge, 2017) variously draw connections between cuteness and the social, political, economic, and technological conditions of the early 21st century. While the work of writers such as Daniel Harris, Lori Merish, Christine Yano, and Sianne Ngai has helped to increase our understanding of the aesthetic impact of cuteness by highlighting the power imbalance between the spectator and the cute object, the forms and functions of cuteness still need further explication, particularly as cute regimes proliferate shared affective responses through an increasing variety of media platforms and real-world events and situations. The Aesthetics and Affects of Cuteness aims to consolidate existing studies of cuteness and to extend the scope of scholarship in this realm with a particular view toward globally encompassing representational and cultural developments. Tracing how vectors of age, gender, ethnicity, sexuality, nationality, and species shape (and are shaped through) cuteness, this book also addresses a range of vehicles for the expression and consumption of cuteness including local and globalizing developments in fashion, performance art, (sub)cultures, toys, games, social media, internet memes, television, movies, stand-up comedy, YouTube videos, and mobile apps, as a means of further understanding this ubiquitous aesthetic and the affects that inform it.
Developing a framework for best practice in sustainable virtual campuses

Despite the significant investment and growth both in Europe and globally in the development of virtual universities and virtual campuses over the last decade, there have been a number of high-profile projects and initiatives that failed to achieve their intended goals. If such failures are to be avoided in the future, then it is vital that a better understanding of best practice within virtual universities and virtual campuses is achieved. This paper reports on the work of a European Commission Education Audiovisual & Culture Executive Agency (EACEA) co-financed project 'Promoting Best Practice in Virtual Campuses' (PBP-VC), which is aimed at providing a deeper understanding of the key issues and success factors underlying the implementation of virtual campuses. The paper will outline a tentative model of the issues underpinning best practice in virtual campuses which covers areas that include organisational, pedagogical, technological, student/user, financial and consolidation issues derived from an investigation into virtual campus projects and initiatives within Europe. The project is working towards developing a practical framework to help guide the process of creating best practice in virtual campuses, as well as raising awareness of issues and approaches to creating sustainable virtual campuses.
Electronic books: a review and evaluation

This paper discusses the genesis of e‐books and derives a comprehensive definition from various definitions reported for them. It lists the various types of e‐books with their characteristics and the major players in the market. It also highlights the pros and cons of e‐books, and compares select e‐book reader hardware and software with their specifications, requirements and characteristics. The impact of e‐books on the publishing industry, on libraries and librarians, and digital rights management is discussed. The author concludes that e‐books are rapidly becoming a viable alternative and provide growing advantages over the traditional medium.
Previous Experience and the Learning of Computer Programming: The Computer Helps Those Who Help Themselves

Recent developments in mathematics education indicate that previous experience is the best predictor of high school math achievement scores. Given this information we hypothesized that previous experience with computers would serve as a predictor of performance in college computer science courses. Also of interest was the possible interaction of gender, prior computing experience and computer science course performance. To examine these issues, we designed and administered a questionnaire to students across two semesters of the first year Pascal programming course at the university level. Roughly one-quarter of the students enrolled across the two semesters were female. Results show that males have more prior experience, especially in advanced computer science topics, than females, and that much of this prior experience is gained outside of school through “hacking” and unguided exploration. Amount of prior computing experience was found to predict course performance for males. For females very little prior experience was reported and this limited amount of experience was not predictive of course performance. The question of why women have so little prior experience with computers and are so sparsely represented in computer science courses is addressed.
Who will win Wimbledon? The recognition heuristic in predicting sports events

Goldstein and Gigerenzer (2002) described the recognition heuristic as a fast, frugal, and effective decision strategy. However, most studies concerning the recognition heuristic have been conducted in static domains, that is, in domains where it could plausibly be argued that relevant variables stay relatively constant. Yet the question is whether the heuristic would also work in dynamic environments where the quality of the actors rises and falls, such as in sports. We tested performance of the recognition heuristic in a dynamic environment and used it to predict the outcomes of tennis matches in Wimbledon 2003. Recognition data of amateur tennis players and laypeople was used to build recognition rankings. These rankings correlated with official rankings and led to at least as good predictions. Simulations of individual choices showed high recognition validities of both amateurs (0.73) and laypeople (0.67). In a second study the recognition heuristic correctly predicted 90% of actual individual choices. Overall, the recognition heuristic may be effectively generalized to dynamic environments. Copyright © 2006 John Wiley & Sons, Ltd.
EFL Learners' Use of Print and Online Dictionaries in L1 and L2 Writing Processes

The study aims to obtain a profile of users in previous instruction learners have received with regard to solving vocabulary gap problems in Korean (L1) and English (L2) writing, to gain knowledge on the type and form of dictionaries, and the dictionary use strategies that are being used in writing Korean (L1) and English (L2) compositions. Data was collected through questionnaires and semi-structured interviews from 54 students in three English composition classes at a university. The analysis of the data revealed that the students have hardly received instruction for solving lexical gap problems and dictionary use in writing of L1 and L2. With regard to the type and form of dictionaries used in writing L1 and L2, the print monolingual dictionary and the Internet (online) bilingual dictionary was most popularly used where Korean-English bilingual dictionary is most frequently utilized in L2 writing. The results imply that easy access of the Internet (online) bilingual dictionaries contributes to its popular use in L2 writing. The dictionary use strategies that students employed to reduce their vocabulary gap knowledge differed significantly between L1 and L2, favoring L2. The results suggest that writing tasks in L2 entail learners to solve lexical gap problems and that there is need to devise classroom tasks for productive use of dictionaries.
Parallelization of design and simulation: virtual machine tools in real product development

A machine tool is a mechatronic system, whose complexity and precision requirements, necessary to the current strategic and technologic diﬀerentiation in the global market, are becoming increasingly challenging. The design of machine tool structures is subject to the usual conﬂicts present in product development: high productivity and eﬃciency require shorter machining times, leading to the construction of lightweight axes, in order to achieve higher accelerations. On the other hand, the increasing requirements regarding surface quality and precision necessitate high static and dynamic stiﬀness, leading inevitably to larger masses. The combination of a multitude of contradicting conditions requires detailed design criteria, whose reliability is adapted to the complexity of modern multi-axis machine tools, in order to reduce the number of real prototypes before the series production. The precept of the right ﬁrst time has become indispensable in the reality of Swiss small and medium-sized enterprises, because production is often characterized by small series, in order to oﬀer customized solutions to the client. These aspects have led to the increasing interest of the machine tool industry for simulation. The systematic integration of detailed virtual studies of the structural dynamic behavior into the design process aims at simultaneously improving the product quality and shortening the time to market launch. To achieve this, there is a need for tools and guidelines embedded into the development concept, without impinging on existing procedures.
Full solution for the storage of correlated memories in an autoassociative memory

We complement our previous work [arxiv: 0707.0565] with the full (non diluted) solution describing the stable states of an attractor network that stores correlated patterns of activity. The new solution provides a good fit of simulations of a network storing the feature norms of McRae and colleagues [McRae et al, 2005], experimentally obtained combinations of features representing concepts in semantic memory. We discuss three ways to improve the storage capacity of the network: adding uninformative neurons, removing informative neurons and introducing popularity-modulated hebbian learning. We show that if the strength of synapses is modulated by an exponential decay of the popularity of the pre-synaptic neuron, any distribution of patterns can be stored and retrieved with approximately an optimal storage capacity - i.e, C ~ I.p, the minimum number of connections per neuron needed to sustain the retrieval of a pattern is proportional to the information content of the pattern multiplied by the number of patterns stored in the network.
Distributed Resource Allocation in Wireless Networks

The full connectivity offered by the nature of wireless communication poses a vast number of benefits and challenges to the designers of future generation wireless networks. One of the main challenges being faced is dealing with the unresolvable interference at the receivers. It is widely recognized that the heart of this challenge lies in the design of resource allocation schemes which provide the best trade-off between efficiency and complexity Exploration of this trade-off requires appropriate choices of performance metrics and mathematical models. In this regard, the thesis is concerned with certain technical and mathematical aspects of resource allocation in wireless networks. We specifically argue that an efficient resource allocation in wireless networks needs to take into account the following parameters: (i) rate of environment changes, (ii) traffic model, and (iii) amount of information available at transmitters. As mathematical tools for our investigation, we use optimization theory and game theory. We are especially interested in distributed resource allocation in networks with slow fading channels and with partial channel side information at the transmitters. Transmitters with partial channel side information have exact information of their own channel as well as statistical knowledge of other channels. In such a context, the system is inherently impaired by a nonzero outage probability. We propose low complexity distributed algorithms for joint rate and power allocation, aiming at maximizing the individual throughput, defined as the successfully-received-information rate, under a power constraint.
Exploring the effects of Lamarckian and Baldwinian learning in evolving recurrent neural networks

A drawback of using genetic algorithms (GAs) to train recurrent neural networks is that it takes a large number of generations to evolve the networks into an optimal solution. In order to reduce the number of generations taken, the Lamarckian learning mechanism and the Baldwinian learning mechanism are embedded into a cellular GA. This paper investigates the effects of these two learning mechanisms on the convergence performance of the cellular GA. The criteria that make learning useful to GAs are also discussed. The results show that the Lamarckian mechanism is able to assist the cellular GA, while the Baldwinian mechanism fails to do so. In addition to reducing the number of generations taken, we have found that it is also possible to reduce the time taken by embedding learning into the cellular GA in an appropriate manner.
Online Georeferencing for Libraries: The British Library Implementation of Georeferencer for Spatial Metadata Enhancement and Public Engagement

The British Library partnered with Klokan Technologies to customise the Georeferencer application for crowdsourcing of spatial metadata capture for two of its most important collections of historic mapping of Britain. This effort built upon previous work in online georeferencing and developments in metadata uses with geographical interfaces in libraries. The authors describe the project and the customised, new release of Georeferencer, with the results and benefits such a project may yield for both cartographic researchers and holding institutions.
The Role of Information Architecture in Designing a Third-Generation Library Web Site

Library Web sites have evolved over the past decade, from simple pages with a few links to complex sites that provide direct access to hundreds of different resources. In many cases, this evolution occurs with little overall planning, often resulting in Web sites that are hard to manage and difficult for users to navigate. This article outlines the process of using Information Architecture (IA) to redesign a third-generation library Web site from the ground up. The result was a much more usable and cohesive library Web site that meets the needs of a broad range of users.
The syntax of serial verbs

This monograph is about the chains of verbs commonly found in Creole Languages, West African languages, in particular the Kwa sub-group of Niger-Congo, Chinese and certain other languages and have acquired the name of 'serial verbs' in the literature. As a case study, the serial constructions of Sranan, a creole language of Surinam with an English lexical base, are examined in detail.
Sequential analysis and observational methods for the behavioral sciences

1. Introduction to observational methods 2. Coding schemes and observational measurement 3. Recording observational data 4. Representing observational data 5. Observer agreement and Cohen's kappa 6. Kappas for point-by-point agreement 7. The intraclass correlation coefficient (ICC) for summary measures 8. Summary statistics for individual codes 9. Cell and summary statistics for contingency tables 10. Preparing for sequential and other analyses 11. Time-window and log-linear sequential analysis 12. Recurrence analysis and permutation tests.
Semi-supervised learning with graphs

In traditional machine learning approaches to classification, one uses only a labeled set to train the classifier. Labeled instances however are often difficult, expensive, or time consuming to obtain, as they require the efforts of experienced human annotators. Meanwhile unlabeled data may be relatively easy to collect, but there has been few ways to use them. Semi-supervised learning addresses this problem by using large amount of unlabeled data, together with the labeled data, to build better classifiers. Because semi-supervised learning requires less human effort and gives higher accuracy, it is of great interest both in theory and in practice. We present a series of novel semi-supervised learning approaches arising from a graph representation, where labeled and unlabeled instances are represented as vertices, and edges encode the similarity between instances. They address the following questions: How to use unlabeled data? (label propagation); What is the probabilistic interpretation? (Gaussian fields and harmonic functions); What if we can choose labeled data? (active learning); How to construct good graphs? (hyperparameter learning); How to work with kernel machines like SVM? (graph kernels); How to handle complex data like sequences? (kernel conditional random fields); How to handle scalability and induction? (harmonic mixtures). An extensive literature review is included at the end.
Deep Web Database Selection with Classification and Rich Features

The Web has been rapidly deepened by many searchable databases online, where data are hidden behind query interfaces. There may be hundreds or thousands of Web databases providing data of relevance to a specific domain on the Web. In the face of these large-scale Web databases, the core problem is to select the most appropriate ones to a users query. While this problem has received more attentions recently, current approaches still have the simplified and empirical limitations. In this paper, we propose a Web database selection approach based on classification. We cast Web database selection as a classification problem and combine multiple kinds of features which are about the query and Web databases. We use the classification model to obtain the relevancy of every individual Web database for a user query and select top-K ones to provide the query results. Experiments show that our approach yields high performance.
Hollow Revetment Elements

Als Schutzelemente fur geneigte Kustenschutzbauwerke werden patentierte Hohlformkorper vorgeschlagen. Durch die boschungsparallel gebildete Hohlstruktur wird die Wechselwirkung zwischen der am Bauwerk partiell stehenden Welle und der Waschbewegung auf der Boschung im Sinne geringerer Wellenbelastung gunstig beeinflusst. Durch die Verwendung von Hohldeckwerken konnen Kustenschutzbauwerke niedriger und mit steilerer seeseitiger Neigung ausgefuhrt werden. Die partielle Reflexion wird masgeblich durch die zwischen einfallender und reflektierter Welle auftretende Phasendifferenz bestimmt. Zudem wird eine selektive Reflexion definiert.