Miracle-dz/UniFAR-FTUs huggingface dataset:
The current state of teachers’ ICT use in classrooms in boys’ secondary schools in Saudi Arabia

The field of education has witnessed many changes and reforms in policy as well as numerous Information and Communication Technology (ICT) operational initiatives attempting to improve the process of teaching and learning. The interest of schools’ stakeholders in the potential advantages that ICT offers to the teaching and learning process has been rising (Kong et al., 2014). However, in Saudi Arabia, the ICT use by teachers for teaching and learning is still low, despite many ICT initiatives that the Ministry of Education (MOE) has introduced to improve education quality. Therefore, this study investigated teachers’ ICT use in classrooms in boys’ secondary schools in the city of Al-Rass in Saudi Arabia. This research aims to understand the current state of ICT in education in Saudi Arabia; and to understand how ICT is used by teachers in classroom for the process of teaching and learning; and to reveal any factors hindering ICT integration in the classroom. The Human Capital Theory (HCT) and Capabilities Approach (CA) were the basis of understanding why ICT is important in the educational process. The methodology adopted is an interpretivist qualitative approach using a triangulation method to analyse different methods and sources. Interviews were conducted at all levels of the education system: Five policy makers within the MOE; five secondary schools in Al-Rass city in Saudi Arabia were visited and interviews were conducted with five head teachers, 25 teachers who participated in 25 classroom observations and 25 student focus groups (100 students in total) who attended the classroom observations. The findings were analysed based on thematic analysis. The study’s findings using the triangulation method indicated that the government has paid huge attention to ICT for education development through relevant initiatives. However, the findings revealed the current situation of ICT is unsatisfactory and has not reflected the expectations and goals of the educational development initiatives. The findings revealed the absence of ICT policy, lack of teachers’ ICT use in the educational process, and internal and external barriers hindering the successful ICT integration in the process of teaching and learning. This included the absence of ICT policy, lack of professional development training, especially on how ICT can be used in relation to pedagogy and subject, and school management support, especially in terms of the teachers’ workload and ICT resource provision requests from authorities. The main implication the study concludes with is once ICT policy is well designed, all hindering factors could be addressed and as a result the integration of ICT into teaching and learning process could improve.
A Distributed Interactive Cube Exploration System

As the amount of data generated from web, mobile and social media increases rapidly, analytics using OLAP (Online Analytical Processing) data cubes is getting increasingly popular among organizations. In a typical scenario, this analysis is performed using BI tools to quickly get insights from the pre-materialized multi-dimensional aggregated data. We introduce DICE, a distributed interactive system that uses a novel session-oriented model for online data cube exploration, which is designed to provide the user with interactive sub-second latencies for specified accuracy levels. We provide a novel framework that combines three concepts: faceted exploration of data cubes, speculative execution of queries and query execution over sampled data. Our system uses a combination of intuitive frontend for faceted cube exploration and distributed query execution backend that guarantees interactive latencies. We catalog the challenges encountered in building such a system, we discuss design considerations, implementation details and optimizations of our system. Experiments demonstrate that cube exploration using DICE at billion-tuple scale is at least 33% faster than current approaches. As shown in our video demonstration, DICE allows the user to fluidly interact with billion-tuple datasets while maintaining sub-second interactive response times.
How a geographically distributed software team managed to negotiate successfully using chat technology

Negotiation is best accomplished in collocated settings, and negotiation in geographically distributed settings is prone to failure with a risk of conflicts. Investigating distributed software development, we were surprised to discover that a software development team, located in different parts of Brazil, was able to negotiate successfully and reach an agreement to change from ticket-oriented processes towards release-oriented processes for bug fixing activities using only chat technology. In this paper, we explore how the chat technology allowed the distributed software team (including both vendor and client team members) to successfully negotiate and reach agreement about adopting and implementing a new collaborative workflow in the governmental IT-project. Our research method is based upon an ethnographically informed empirical study of the software development involved in a Brazilian software company. Thus, the data collected shows that the chat technology provided a platform for the team to engage informally in important discussions across locations. The chat technology allowed participants to navigate both within and across diverse subgroups (collocated client-developers; distributed clientdeveloper, and distributed developers-developers), which supported successful subgroup dynamics avoiding the risk of conflicts emerging from faultlines.
ECONOMICS OF EDUCATION REVISITED – NEW INSIGHTS FROM IDENTITY AND BEHAVIORAL ECONOMICS

This paper reviews the economic literature on education along with the attempts to integrate sociological and psychological views of education into standard economic models. The analysis points to the key concepts from sociology and behavioral economics that are translated into inputs to economic models of education, in order to improve the understanding of the economists’ fundamental concern – resource allocation. By extending economic models that capture the relation between investing efforts and expected returns to education, insights from identity economics and behavioral economics shed light to the following question: when and under what circumstances are investments in education effective? Identity economics implies that educational efforts are not perfect determinants of the economic returns to education, taking into account that investments in education are determined by students’ social norms, ideals and identities. Behavioral economics focuses on behavioral biases that affect the individuals’ decisions on investing efforts in education and consequently, their long-term welfare. This novel framework contributes to education research by specifying policy interventions that could mitigate identified behavioral barriers that constrain decision making concerning educational pathways.
Artificial Intelligence Policy Innovations at the Canadian Federal Government

This article summarizes two initiatives for artificial intelligence (AI) underway in the Canadian public service: public consultation and collaboration in compiling an algorithmic impact assessment, and a symposium on AI and human rights held by Global Affairs Canada. The findings contextualize the national consultations on digital and data transformation and future steps for more inclusive AI governance in Canada.Cet article offre une synthèse de deux initiatives sur l’intelligence artificielle (IA) en cours dans la fonction publique canadienne : la consultation et collaboration du public dans la compilation d’une évaluation d’impact algorithmique et un symposium sur l’IA et les droits de la personne organisée par Affaires mondiales Canada. Les conclusions permettent de donner un contexte aux consultations nationales sur la transformation du numérique et des données et les mesures à prendre pour une gouvernance en intelligence artificielle plus inclusive au Canada.
The EU and U.S. approaches towards irregular immigration

The aim of this paper is to present and discuss the approaches of the European Union and the United States of America towards the phenomenon of irregular immigration after 2010. Our analysis is based on official documents and other works published by the EU and U.S. federal government as well as on the literature in this field. This study is a continuation of our comparative papers from 2016-2018 devoted to different aspects of complex migratory reality in the EU and U.S. as well as corresponding public policies. We conclude that the high concentration in recent years on securing the borders and strengthening the policy of their control is similar for both entities. However, the effectiveness of the U.S. in defining and implementing a single approach to irregular migration is possible to a greater degree than in the EU – an international organization grouping sovereign states having their own national interests.
Study of Key Technology of Distortion Correction Software for Fisheye Image

To meet the requirement of panoramic monitoring projects,a fisheye lens was used as the imaging unit of the image sensor for imaging.A new method was brought in estimating the circular area of the fisheye image.Sphere perspective projection and cylinder expanse model were used to solve the problem of distortion.At the same time,virtual PTZ control was realized.According to the test,the software has a strong robustness in kinds of monitoring situation,it can meet the requirement of full-field monitoring without blind zone totally.
Experimental Comparison between Four and Six Switch Inverters Fed FLC Based Speed Sensorless IM Drives at Very Low Speed

This paper introduces experimental comparison study between six and four switch inverter fed three phase induction motor drive system. The control strategy of the drive is based on speed sensoreless vector control using model reference adaptive system as a speed estimator. The adaptive mechanism of speed control loop depends on fuzzy logic control. Four switch inverter conFigureurations reduces the cost of the inverter, the switching losses, the complexity of the control algorithms, interface circuits, the computation of real-time implementation, volume-compactness and reliability of the drive system. The robustness of the proposed model reference adaptive system based on four switch three-phase inverter (FSTPI) fed induction motor drive is verified experimentally at different operating conditions. Experimental work is carried using digital signal processor (DSP1103) for a 1.1 kW motor. A performance comparison of the proposed FSTP inverter fed IM drive with a conventional six switch three-phase inverter (SSTP) inverter system is also made in terms of speed response. The results show that the proposed drive system provides a fast speed response and good disturbance rejection capability. The proposed FSTP inverter fed IM drive is found quite acceptable considering its performance, cost reduction and other advantages features. Full Text: PDF DOI: http://dx.doi. org/10.11591/ijpeds.v8. i1.pp130-146
Fast sparse recovery and coherence factor weighting in optoacoustic tomography

Sparse recovery algorithms have shown great potential to reconstruct images with limited view datasets in optoacoustic tomography, with a disadvantage of being computational expensive. In this paper, we improve the fast convergent Split Augmented Lagrangian Shrinkage Algorithm (SALSA) method based on least square QR (LSQR) formulation for performing accelerated reconstructions. Further, coherence factor is calculated to weight the final reconstruction result, which can further reduce artifacts arising in limited-view scenarios and acoustically heterogeneous mediums. Several phantom and biological experiments indicate that the accelerated SALSA method with coherence factor (ASALSA-CF) can provide improved reconstructions and much faster convergence compared to existing sparse recovery methods.
Notes on the increasing use of urban nesting and roosting sites in Kenya: a nesting site for Yellow-billed Storks Mycteria ibis and Pink-backed Pelicans Pelecanus rufescens in Naivasha

Introduction Historically, birds have been known to thrive in urban areas and close to human habitation where various species seem at home, feeding and nesting calmly without feeling threatened by the presence of man. Some species have even acquired names that relate to these sites. Common examples of urban nesters include the House Sparrow Passer domesticus and Little Swift Apus affinis. Many members of the pigeon family have long used buildings for nesting, and various weaver and sparrow species such as the Village Weaver Ploceus cucullatus and the Kenya Rufous Sparrow Passer rufocinctus nest close to human residences. Some species have actually taken to nesting inside the roof gutters of houses.
Automatic Tagging of Audio: The State-of-the-Art

Recently there has been a great deal of attention paid to the automatic prediction of tags for music and audio in general. Social tags are user­generated keywords associated with some resource on the Web. In the case of music, social tags have become an important component of ``Web 2.0'' recommender systems. There have been many attempts at automatically applying tags to audio for different purposes: database management, music recommendation, improved human­computer interfaces, estimating similarity among songs, and so on. Many published results show that this problem can be tackled using machine learning techniques, however, no method so far has been proven to be particularly suited to the task. First, it seems that no one has yet found an appropriate algorithm to solve this challenge. But second, the task definition itself is problematic. In an effort to better understand the task and also to help new researchers bring their insights to bear on this problem, this chapter provides a review of the state­of­the­art methods for addressing automatic tagging of audio. It is divided in the following sections: goal, framework, audio representation, labeled data, classification, evaluation, and future directions. Such a division helps understand the commonalities and strengths of the different methods that have been proposed.
Scientific Discourse on YouTube: Motivations for Citing Research in Comments

YouTube is a valuable source of user‐generated content on a wide range of topics, and it encourages user participation through the use of a comment system. Video content is increasingly addressing scientific topics, and there is evidence that both academics and consumers use video descriptions and video comments to refer to academic research and scientific publications. Because commenting is a discursive behavior, this study will provide insights on why individuals post links to research publications in comments. For this, a qualitative content analysis and iterative coding approach were applied. Furthermore, the reasons for mentioning academic publications in comments were contrasted with the reasons for citing in scholarly works and with reasons for commenting on YouTube. We discovered that the primary motives for sharing research links were (1) providing more insights into the topic and (2) challenging information offered by other commentators.
Political communication in Social Networks Election campaigns and Digital Data Analysis: A Bibliographic Review

The outcomes of a bibliographic review on political communication, in particular electoral communication in social networks, are presented here. The electoral campaigning are a crucial test to verify the transformations of the media system and of the forms and uses of the linguistic acts by dominant actors in public sphere – candidates, parties, journalists and Gatekeepers. The aim is to reconstruct the first elements of an analytical model on the transformations of the political public sphere, with which to systematize the results of the main empirical research carried out in recent years, in particular those conducted with a promising methodology: Digital Trace Data Analysis.
Critical Civic Education for Young Children

Conventional civic educational efforts in the lower grades often frame young children as “future” citizens who need to learn nationalistic patriotism, obedience to rules and laws, and trust in civic institutions to operate fairly toward all members of the community. In this paper we present a framework of “critical civic education” at the early childhood level that positions children as already civic beings with identities and experiences that inform their ideas about what problems matter and how they can be solved. We ask educators to help young children develop (a) a general understanding of current injustices (along with root causes) within their communities, (b) the ability to articulate and reflect on their own conception of an ideal society that advances human flourishing, and (c) strategies to advance their ideas. Through three vignettes we offer examples of how early childhood education can engage in this type of critical civic education.
Students' Perceptions of Using a Course Management System to Supplement Traditional Advising

Few universities have adapted their course management systems to serve as an advising tool. The purpose of this qualitative study was to use focus group interviews to explore undergraduate students’ experiences and perceptions of using Canvas, a course management system, to supplement face-to-face advising in the College of Agriculture and Applied Sciences at Utah State University. Forty students representing all college academic departments participated in eight focus groups. Most participants indicated they were unaware of Canvas’s advising features, thinking the tool was primarily used to send announcements and respond to students’ e-mails. Participants enjoyed receiving announcements about club activities, internships, and important deadlines for their academic program. The majority of participants requested that the college’s student services center provide more explanation on how to use Canvas as an advising tool, including details about the existing resources and how to access them. Participants also requested more resources, including scheduling advisor meetings online, a discussion board, and a student forum. These findings offer information for how academic advisors or faculty advisors could use their university’s or college’s existing course management system to interact with students and help them make more informed advising decisions.
Research of Text Categorization Based on Improved Maximum Entropy Algorithm

This paper discussed the problems in text categorization accuracy.In traditional text classification algorithm,different feature words have the same affecte on classification result,and classification accuracy is lower,causing the increase algorithm time complexity.Because the maximum entropy model can integrated various relevant or irrelevant probability knowledge observed,the processing of many issues can achieve better results.In order to solve the above problems,this paper proposed an improved maximum entropy text classification,which fully combines c-mean and maximum entropy algorithm advantages.The algorithm firstly takes shannon entropy as maximum entropy model of the objective function,simplifies classifier expression form,and then uses c-mean algorithm to classify the optimal feature.The simulation results show that the proposed method can quickly get the optimal classification feature subsets,greatly improve text classification accuracy,compared with the traditional text classification.
A Lightweight Mobile TV Recommender Towards a One-Click-to-Watch Experience

In this paper we present a novel program recommender for DVB-H based Mobile TV systems. It addresses the restriction of low processing resources on the client devices and is fully compliant to the OMA BCAST 1 standard. There is no learning phase included and hence users can instantly start using the system. Based on the proposed, highly scalable architecture design we implemented a prototype application that employs a powerful, though minimal, mobile user interface.
A Transmission in ISI Channel

In order to improve the transmission performance in intersymbol interference(ISI) channel,high rate lower-order modulation transmission with ISI was studied and the error rate performance of lower-order modulation and higher-order modulation with the same message rate and band width was compared.High rate lowerorder modulation transmission with ISI makes full use of the potential anti-jam capability of the system and the threshold signal to noise ratio is greatly decreased by more than 10? dB.Simulation results show that with the same message rate and band width,lower-order modulation transmission,interfered by ISI and employing sequence detection,obtains greater performance gain than higher-order modulation,which is not influenced by ISI and detected symbol by symbol.
How do Information Technology Resources Facilitate Relational and Contractual Governance in Green Supply Chain Management?

Although a plethora of studies demonstrate that information technology (IT) has a positive influence on integration, collaboration and coordination side of green supply chain management, our knowledge about the influence of IT resources on governance side remains limited, especially the relational and contractual governance, two of the fundamental governances in green supply chain management. Based on the transaction and agency cost perspective and literature of information systems and B2B governance, this study investigates how IT resources affect the effects of relational and contractual governance. The results show that IT resources could improve the relational governance (i.e., joint-actions) and contractual governance (explicit and contingent contract clauses designing), and thus, effectively mitigate partner’s opportunism. Finally, the theoretical contribution and implications for managers are also given in the end.
An Automatic Road Network Extraction from Satellite Images Using Modified SOFM Approach

Objective : The objective of this study is an Automatic Extraction of road networks from very high resolution satellite images. It is an important research area in remote sensing field. Methods/Analysis : We present fully automatic road extraction from high resolution satellite images using modified self organizing map. Firstly, it focuses a road detection using self organizing map algorithm. At the end, the T-Cluster method is used to improve the segmentation in road networks. Findings : Experimental results show the significant accuracy (90%) and efficiency of proposed approach. Application/Improvement : The modified T-SOM technique provides the resources for readily creating, maintaining and updating the road transportation databases used in vehicle tracking and traffic management.