Miracle-dz/UniFAR-FTUs huggingface dataset:
From Modern Teaching to Mathematics Achievement: The Mediating Role of Mathematics Attitude, Achievement Motivation, and Self-Efficacy

A modern teaching method influences both direct and indirect learning achievement through the student's nonacademic factors. The researcher has an intention to examine the influences of new teaching methodology on mathematics achievement towards mathematics attitude, achievement motivation, and self-efficacy of students as mediating variables (n teacher = 117, n student = 2,205). The Multilevel Structural Equation Modeling revealed that attitude towards mathematics is the most important factor in explaining the academic achievement of individual students. It could be explained the variance with achievement motivation and perceived self-efficacy of students by 60.50%. As for the modern teaching method, there was a positive effect on achievement both directly and indirectly through all three factors with statistical significance and explained conjointly about the variance of student achievement in each classroom by 99.00%. This finding suggests the importance and direction of teaching design that covers the development of relevant factors as proposed in discussions and implementations.
Reactive force field simulations of silicon clusters

ABSTRACT The fast and continuous growth of multidisciplinary approaches, consisting of the combination of various experimental techniques and computational methods tuned on purpose to depict and predict material properties and performance, is motivated by the need to design new superior devices for effective applications in a great variety of industrial sectors. This strategy not only produces excellent results but is also fundamental to drive the research towards innovative and cost-effective production systems. In this short review we outline the major steps of our theoretical modelling activity connected to the experimental gas-phase synthesis of silicon nanoparticles (SiNPs) in plasmas reactors, limiting the discussion to the long-scale simulations based on the classical reactive description (ReaxFF methodology) for reproducing the whole process, perturbations included. The huge computational workload at the quantum chemistry level, required to prepare the training data, calibrate the parameters and validate the procedure, is not reported for the sake of conciseness. The excellent agreement of the simulations results with the experimental data and the sound explanations of the observed phenomena suggest that the ReaxFF-based paradigm is a reliable approach capable of studying these types of materials on time and size scales corresponding to realistic scenarios. Major steps of the theoretical modelling activity connected to the experimental gas-phase synthesis of silicon nanoparticles (SiNPs) in plasmas reactors. Graphical abstract
A GPU Accelerated Text Classification Method in E-learning Environment Based on Semi-supervised NMF and SVM

With the beginning of revolution in education E-learning become increasingly popular. It is widespread among people while E-learning platform is used by more people to publish their own resources freely. As a result, a large number of document data need to be processed. Text classification is a key technology to this problem. In this paper, we propose a frame based on semi-supervised NMF and SVM for text classification. The method of semi-supervised NMF can work out a so called open set problem well. And we also proposed an accelerated version of the algorithm base on CUDA and GPU parallel architecture. These methods can work out the problems well. And finally we test the algorithms in the E-learning environment, than we give the conclusion according to the results.
Experiencias de los estudiantes de estomatología en el control de la conducta de niños. Análisis cualitativo

espanolIntroduccion. Uno de los factores que influyen en la atencion de los pacientes pediatricos, es la susceptibilidad de los ninos a desarrollar con facilidad miedos y temores ante una situacion desconocida y sobre todo cuando se trata de la practica odontologica. Objetivo del estudio es conocer las experiencias de los estudiantes de estomatologia en relacion al control de la conducta del paciente pediatrico. Metodologia. Para ello fue realizado un analisis cualitativo empleado un enfoque fenomenologico de tipo trascendental. Para lo cual se realizo la entrevista a todos los estudiantes que cumplieron los criterios de seleccion hasta obtener la saturacion de la informacion. El metodo de recoleccion de datos fue la entrevista recomendado por Marshall C 1, y la entrevista siguiendo el enfoque de Seidman I 2 que recomienda realizar tres entrevistas por separado a los participantes. Resultados. La informacion obtenida a traves de entrevistas y videos fue analizada a traves del programa informatico Atlas.Ti. Donde se obtiene como resultados la falta de confianza de los estudiantes al momento de atender pacientes pediatricos. Y como se va adquiriendo esta confianza al momento de realizar sus practicas pre profesionales orientadas por el docente. Conclusiones. Se concluye que el estudiante no adquiere las habilidades suficientes para lograr el control de la conducta del nino al momento de su atencion odontologica, a pesar de tener los conocimientos teoricos. Pero ello se va supliendo siempre y cuando el estudiante toma conciencia y pone en practica lo aprendido en la teoria. EnglishIntroduction. One of the factors that influence the care of pediatric patients is the susceptibility of children to easily develop fears and fears in an unknown situation and especially when it comes to dental practice. Objective of the study is to know the experiences of stomatology students in relation to the control of the behavior of the pediatric patient. Methodology. Far this, a qualitative analysis was carried out in a transcendental phenomenological approach. Why the interview was conducted to all students who met the selection criteria to obtain the saturation of the information. The method of data collection was approved by Marshall C 1, and the interview following the approach of Seidman I 2 that recommends conducting three separate interviews to participants. Results. The information obtained through interviews and videos was analyzed through the Atlas.Ti computer program. Where the lack of confidence of the students at the time of attending pediatric patients is obtained as results. And how this confidence is acquired at the moment of carrying out their pre-professional practices guided by the teacher. Conclusions. It is concluded that the student cannot acquire sufficient skills to achieve control of the child's behavior at the time of dental care, despite having the theoretical knowledge. But this can be provided as long as the student becomes aware and puts into practice what they have Iearned in theory.
Digital Image Forensics using Deep Learning

During the investigation of criminal activity when evidence is available, the issue at hand is determining the credibility of the video and ascertaining that the video is real. Today, one way to authenticate the footage is to identify the camera that was used to capture the image or video in question. While a very common way to do this is by using image meta-data, this data can easily be falsified by changing the video content or even splicing together content from two different cameras. Given the multitude of solutions proposed to this problem, it is yet to be sufficiently solved. The aim of our project is to build an algorithm that identifies which camera was used to capture an image using traces of information left intrinsically in the image, using filters, followed by a deep neural network on these filters. Solving this problem would have a big impact on the verification of evidence used in criminal and civil trials and even news reporting.
Strategy Formation in Complex Organizations: The Evolution of Strategic Issues in Hospitals

ABSTRACT This study investigates strategy formation in complex organizations by empirically tracking the evolution of strategic issues in hospitals. Given the utmost importance of successfully integrating strategic issues in the strategic agenda, this study focuses on how the structural and strategic contexts infuence strategic issues’ evolution. A case study is conducted in a German hospital group. Five evolution paths of strategic issues are identified, and a model of their evolution is developed. Overall, this study heeds the call to more holistically depict how strategic issues evolve. By discussing the empirically elaborated constraints and supports in the evolution of strategic issues, a better understanding of strategy formation in complex organizations is provided.
Web-based tool for the annotation of pathological variants on proteins: PMut 2017 update

Assessing the impact of amino acid mutations in human health is an important challenge in biomedical research. As sequencing technologies are more available, and more individual genomes become accessible, the number of identified variants has dramatically increased. PMut, released back in 2005 [1], has been one of the popular predictors in this field. PMut was a neural-network-based classifier using sequence data to provide a pathology score for point mutations in proteins. We now release a new, revised, and much more powerful version of PMut. It features PyMut prediction engine, a Python module that includes numerous machine learning capabilities aimed at the analysis of protein variant pathology annotation. We also release PMut2017 predictor, a full update of the PMut predictor based on the SwissVar [2] variation database. It achieves an accuracy of 82% and a Matthews Correlation Coefficient (MCC) of 0.62, and matches the most popular predictors’ performance. The engine is implemented in Python using MongoDB engine for data management. It has been adapted to run at the HPC level to cover large scale annotation projects.
Model-based Path Planning and Control for Autonomous Vehicles using Artificial Potential Fields

This report presents the results of the graduation thesis from the TU Delft, performed at the Integrated Vehicle Safety department of TNO. The goal of this graduation project is to develop a unified path planning and tracking method for autonomous vehicles in highway driving scenarios, by making use of Artificial Potential Fields (APFs). Most autonomous vehicles base their navigation control on first planning a path, which is then tracked by using a combination of feedback and feedforward control. The strength of using APFs is the possibility to integrate the path planning and tracking process. This concept has been extensively used in the field of robotics. The attractive and repulsive forces coming from the APF guide the robot towards the final goal while avoiding obstacles. This offers an intuitive way to represent the level of hazard experienced in the direct environment. However, considerably less research has been devoted to the application of APFs in the field of autonomous vehicles. Furthermore, the available research mostly treats the vehicle as a particle, thereby leaving out the more complicated vehicle dynamics. Therefore, this research is aimed at including the vehicle dynamics into the path-planning process such as to generate feasible and desirable paths. A Model Predictive Control (MPC) framework is proposed to fulfill this task. The adopted vehicle model is given by the linear bicycle model, which represents the vehicle dynamics sufficiently well for highway applications. The two main manoeuvers of lane keeping and lane changing are executed with the aid of two different APFs that were designed for these specific purposes, respectively. A second order Taylor approximation is used to incorporate the APFs into the quadratic MPC cost function. The Simulink model from TNO to simulate the controlled vehicle is modified by extending it to curved roads and by including the developed APF MPC algorithm. The resulting algorithm is capable of following curved highway lanes and overtaking slower vehicles at different velocities in the simulation environment. The results are compared with the previously developed path planner and lateral controller from TNO. In order to also deliver longitudinal control action, the model can be connected to the adaptive cruise control application of TNO. It is concluded that the suggested method potentially offers a powerful solution to the navigation control of autonomous vehicles. Real-life experiments have to be done in the future to validate the performance of the controller.
Theory of Mind, Emotion Knowledge, and School Engagement in Emerging Adolescents

a,**Corresponding Author: Sandra Bosacki, Brock University, Niagara Region, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1, Canada. E-mail: Sandra.bosacki@brocku.ca bFlavia Moreira, Brock University, Canada. E-mail: flavia.moreira@brocku.ca cValentina Sitnik, Brock University, Canada. E-mail: valentina.sitnik@brocku.ca dKathleen Andrews, McGill University, Canada. E-mail: katherine.andrews@mail.mcgill. ca e Victoria Talwar, ? McGill University, Canada. E-mail: victoria.talwar@mcgillu.ca Abstract
Friends Classification of Ego Network Based on Combined Features

AbstractEgo networks consist of a user and his/her friends and depending on the number of friends a user has, makes them cumbersome to deal with. Social Networks allow users to manually categorize their “circle of friends”, but in today’s social networks due to the unlimited number of friends a user has, it is imperative to find a suitable method to automatically administrate these friends. Manually categorizing friends means that the user has to regularly check and update his circle of friends whenever the friends list grows. This may be time consuming for users and the results may not be accurate enough. In this paper, to solve this problem, we present a method, which combining user attributes, network structure and contact frequent three aspects. Efficiently using the profile of users, we first identify the relationship between them and then we attempt to solve the problem of community identification when a user’s profile is missing or inaccessible by use of ego network structural features. Lastly, to .
Household Food Security Status and Child Health Outcomes in Kenya

Interminable access to sufficient, nutritious, and safely prepared food is a human right. Attributed to insufficient food and nutrient intake, malnutrition is a major health burden in developing economies that has maimed socioeconomic development. In children, undernourishment impairs the functioning of the immune system, increases susceptibility to diseases, and undermines physical and cognitive development. In Kenya, there exists a paucity of empirical corroboration of the effect of household food security status (HFSS) on child health outcomes. Using data drawn from the 2014 Kenya Demographic and Health Survey, this paper focuses on analyzing the causal link between HFSS and child health outcomes and to provide evidencebased policy recommendations to promote child health outcomes. We employed three measures of HFSS: households that lacked food/enough money to purchase food, the Reduced Coping Strategy Index (CSI), and the Food Consumption Score (FCS). The child health production function was estimated using the two-stage residual inclusion (2SRI) technique to control for potential endogeneity. The results indicate that households that lacked food/enough money to purchase food were significantly associated with stunted, wasted, and underweight growth in children. Similarly, the Reduced CSI was a significant determinant of stunted and underweight growth in children. However, the effect was insignificant relative to wasted growth. The findings also indicate that FCS contributes significantly to improvements in child health outcomes. Our evidence has the potential to inform policies on the promotion of child health outcomes. We recommend implementation of programs such as social assistance, integration of nutrition and WASH, and capacity-building to promote women’s knowledge of health, nutrition, and better child-care practices.
Using mobile phones in support of student learning in secondary science inquiry classrooms

This paper reports on findings from a research project concerned with how electronic networking tools (e-networked tools), such as the Internet, online forums, and mobile technologies, can support authentic science inquiry in junior secondary classrooms. It focuses on three qualitative case studies involving science teachers from two high schools together with their Year 9 and Year 10 classes. The ways teachers and students view and take up the affordances of mobile phones to support authentic science inquiry are of interest. Data were collected from teacher reflections, student interviews, a student survey, classroom observations and student work. The findings highlight three key themes that illustrate the advantage of using mobile phones as part of the classroom culture to video record group practical investigations, support students’ developing abilities to think like a scientist, and enable the sharing of learning beyond the classroom. The findings have implications for practice and can contribute to a better understanding of the ways mobile devices can support and extend science inquiry in New Zealand secondary classrooms.
E-Book Collections in High School Libraries: Factors Influencing Circulation and Usage

When school librarians justify the purchase of electronic books (e-books) for their collections, they need to understand e-book usage patterns and whether or not e-books are meeting the recreational and informational needs of their students and teachers. Although a sizeable body of research is available examining the circulation and usage of e-books in academic and public libraries, there has yet to be a scientific study examining these variables in high school libraries. The purpose of this study was to gain a better understanding of high school e-book collections through the analysis of circulation data and interviews with school librarians. A Relative Use Factor analysis was conducted. Quantitative results revealed that e-book circulation represented a significantly low total circulation for most of the high school libraries examined. Analysis of the interviews revealed commonalities and differences between e-book collections. Findings suggested that purchasing practices and marketing strategies can have a considerable impact on the circulation and use of e-books in high school libraries.
MACHINE LEARNING CLASSIFICATION METHODS USED TO FILTER UNDESIRABLE MESSAGE FROM OSN USER WALLS

Now a days Social networking on social media websites involves the use of the internet to connect users with their friends, family and associates. The most well-known social media sites are Facebook, twitter, Instagram and LinkedIn. These sites allowed sharing photos, videos, and information, the main drawback of this On-line Social Networks (OSNs) is the lack of privacy for the users own private walls. This project represents system enforcing content-based message filtering consider as a key service for On-line Social Networks (OSNs). Our system provides ability to OSN users to possess a straight control on the messages denoted on their walls. Up to now, OSNs offer very little support to stop undesirable messages on user private walls, there is no content-based preferences are supported and so it's impossible to stop undesirable messages, like political or vulgar ones, regardless of the user who posts them. One basic issue during this system is blocking of user for lifetime. we tend to overcome this drawback by using proposed System; during this paper we tend to proposed a system that performs blocking of undesirable message user and additionally sends back a notification to it who has send undesirable message on users wall using threshold frequency worth. To filter messages we tend to proposed an increased filtering system by using machine learning based categorization techniques.
Real-time haze removal by GPU acceleration based on dark channel prior algorithm

Dark channel prior haze removal algorithm is very simple and effective for single image haze removal, but it’s somehow limited by color distortion in gray areas and expenditure of time. Firstly, aiming at solving color distortions, we propose a modified dark channel prior haze removal algorithm. We correct the transmission of the gray areas by introducing the correction parameter, and the transmission is unchanged when the areas meet the law of dark channel prior. Secondly, to realize real-time haze removal for video surveillance, we use GPU to parallel accelerate and optimize the new algorithm on Compute Unified Device Architecture platform released by NVIDIA. Experiments show that the modified algorithm works effectively in gray areas. At the same time, the processing speed of images with a resolution of 640x480 can reach 37 frames per second after GPU acceleration and can also obtain the real-time haze removal result.
SOCIAL MEDIA RECRUITMENT: INTEGRATING OF SOCIAL MEDIA INTO THE RECRUITMENT STRATEGY OF AN INTERNATIONAL SME Case Company: Globuzzer

Tran, Anh Type of publication Bachelor’s thesis Published Spring 2019 Number of pages 72 pages, 5 pages of appendices Title of publication Social Media Recruitment: The Integration of Social Media into Recruitment Strategy of an International SME Case Company: Globuzzer Name of Degree Bachelor of Business Administration Abstract Within the explosion of technology and the internet, the recruitment strategy has been dramatically changing over the past 20 years. Since 2010, recruitment has changed to another game when social media and the internet are more popularly adopted. Social networking sites allow recruiters to head-hunt more easily during hiring process. Observing the optimistic shift that social media brings to the recruitment process, the author decided to write this thesis to adopt social media into recruitment and develop an effective recruitment strategy for the case company. The research mainly employs an inductive approach and uses both qualitative and quantitative research methods at different stages of the study. The theoretical and empirical parts are evenly discussed throughout the whole content. Regarding the theory section, it provides the reader with the basic knowledge of recruitment and social media in recruitment strategy. Regarding the empirical part, qualitative data was collected from the owner of the case company while the data of potential candidates was analyzed by adopting the quantitative method. The author conducted an interview by discussing with the owner via email and a survey online to gather data from candidates. All in all, the findings of the research revealed that the case company should combine social media into their recruitment strategy which helps them reach a larger pool of targeted audience. To integrate social media into recruitment strategy, the company should choose the right social channels for recruiting to attract talented candidates for the company in the future. Finally, the author pointed out some suggestions for other researchers to conduct further research in the future.
130-MH , 16-BIT FOUR-CHANNEL DIGITIZER

The PAD (Phase and Amplitude Detector) was designed to digitize high-speed analog input data with large dynamic range. Because of its high speed and high resolution processing capability, it has been useful to applications beyond measuring phase and amplitude of RF signals and klystron beam voltages. These applications include beamposition monitors, bunch-length monitors, and beamcharge monitors. For each channel, the 16-bit digitized signal is clocked into a 64k sample FIFO. Commercial FIFOs are available that store up to 256k samples in the same package. The data are then read from the FIFO into the Arcturus Coldfire uCDIMM. A CPLD is used to handle triggering, resetting the FIFO, interfacing the processor to the 4 FIFOs, and interrupting the processor. The processor runs RTEMS version 4.7 and EPICS 3.14. 8.2. There is an optional add-on available that attaches to the QSPI port on the PAD for reading 8 slow, 24-bit analog signals.