Miracle-dz/UniFAR-FTUs huggingface dataset:
Outdoor play decision-making by families, schools, and local government for children with disabilities

Introduction: Play is a right for all children and an essential childhood occupation. Yet, children with disabilities experience exclusion from outdoor play participation. How children’ skills interact with the environment in which they live, notably their family, school, and community, shapes their play choice. Aim: The aim of this study was to understand outdoor play decision-making at family, school, and local government levels for primary school-age children with disabilities. Method: A multiple-perspective case study allowed for comprehensive understanding of the phenomenon of outdoor play decision-making. Data collection included: interviews with five parents of children with disabilities, four teaching assistants, three special education teachers, one vice principal, four local government employees, and two employees of not-for-profit organizations within one culturally and linguistically diverse local government area; one week parent survey of their child’s play the day before; observations at school and community playgrounds; document review; and video-assisted recall with four school employees. Analysis was guided by cross-case analysis, interpretive description, and analytical deduction and involved first understanding individual perspectives, and then considering similarities and differences within and between stakeholder groups. Discussions are considered through the application of the capabilities approach. Findings: Families valued and planned for play within the context of their child’s interests and abilities and their family’s needs. Schools had low play expectations and considered the children’s presence on the playground sufficient. When considering playgrounds, local government focused on meeting minimal requirements and physical access rather than social inclusion. School and local government’s predominately-negative perception of children with disabilities and their families affected meaningful engagement. Conclusion: Children experienced greater play choice within their families than at school or in the community. Families should continue to value play as a means and ends, and plan for play based on their values and their child’s interests. To increase play choice and inclusion, the school needs to increase play expectations for children with disabilities and better support the play environment. Local government must increase meaningful engagement with families, and consider how to support the entire family’s playground inclusion. Finally, inclusive language should be modelled across ecocultural levels.
Supporting Children’s Learning of Probability Through Video Game Programming

Teaching programming and creating games have attracted much attention over the years, mostly the attention of curriculum developers and teachers. This study designed and developed a video game-based intervention, then investigated the effects of this intervention on middle school students’ learning of probability concepts. In the study, the students learned and used Scratch as a game programming tool. Initially, they received hands-on learning activities on how to use Scratch, and then developed video games based on scenarios authored by the researchers. The study collected quantitative as well as qualitative data using two different measurement tools: probability achievement test and student project assessment rubric, respectively. The data revealed that students were able to learn and use Scratch and develop probability-related and probability-based algorithms that generate random results successfully. The effect of Scratch intervention on students’ learning of probability was statistically significant. Findings were discussed in relation to similar studies reported in the literature. Finally, the study raised a set of further research questions in the Conclusion section.
A hierarchical compositional model for representation and sketching of high-resolution human images

This dissertation presents a composite template model, named And-Or graph for representing objects with large structural variabilities. Intuitively, an And-node represents a decomposition of certain graphical structures which expands to a set of Or-nodes with associated relations; an Or-node serves as a set of switch variable pointing to alternative And-nodes. A traversal from the root node of the And-Or graph, named the parse graph, produces a configuration of the terminal nodes (sub-templates) under (soft and hard) relations inherited from their ancestor nodes. The And-Or graph representation can generate a large set of constrained configurations with relatively small number of graph nodes, thus account for great structural variations. The And-Or graph model is tested on tasks as modeling and sketching human faces and clothes. A hierarchical-compositional model of human faces, as a three-layer And-Or graph is built. Faces are represented hierarchically: the first layer treats each face as a whole; the second layer refines the local facial parts jointly as a set of individual templates; the third layer further divides face into 16 zones and models detail facial features such as eye corners, marks or wrinkles. Transitions between the layers are realized by measuring the minimum description length (MDL) given the complexity of an input face image. Diverse face representations are formed by drawing from dictionaries of global faces, parts and skin detail features. A sketch captures the most informative part of a face in a much more concise and potentially robust representation. However, generating good facial sketches is extremely challenging because of the rich facial details and large structural variations, especially in the high-resolution images. The representing power of our generative model is demonstrated by reconstructing high-resolution face images and generating the cartoon facial sketches. Our model is useful for a wide variety of applications, including recognition, non-photorealistic rendering, super-resolution, and low-bit rate face coding. Cloth modeling and recognition is an important and challenging problem in both vision and graphics tasks, such as dressed human recognition and tracking, human sketch and portrait. We built a And-Or graph model to represent different clothes configurations, such as T-shirts, jackets, etc. In a supervised learning phase, we ask an artist to draw sketches on a set of dressed people, and we decompose the sketches into categories of cloth and body components: collars, shoulders, cuff, hands, pants, shoes, etc. Each component has a number of distinct sub-templates (sub-graphs). An algorithm which integrates the bottom-up proposals and the top-down information is proposed to infer the composite clothes template efficiently from the image.
Pengaruh Infeksi Kecacingan terhadap Kadar Hemoglobin pada Remaja Putri dengan Anemia

<p><strong><em>Introduction:</em></strong><em> Anemia is one of the health problems in Indonesian. The government has launched anemia prevention programs, including for young women, but the prevalence of anemia is still high. Helminth infections can decrease hemoglobin (Hb) levels through gastrointestinal bleeding and decreased food intake. This study aimed to determine the effect of helminth infections on Hb levels in young women. </em></p><p><strong><em>Methods:</em></strong><em> This study was an observational analytic study with a case control approach. Research subject involved of 46 students of senior high school in Sukoharjo Regency and were divided into 26 young women with anemia and 20 young women without anemia. Helminth infection was determined using fecal examination. All collected data were analyzed by Chi square test and Independent sample t-test with p<0.05. </em></p><p><strong><em>Results:</em></strong><em> The mean of Hb levels in young women with anemia was 10.24±0.92g/dL and the mean of Hb levels in young women without anemia was 13.07±0.44g/dL. 7 young women suffered helminth infection, divided into 2 young women with anemia and 5 young women without anemia. However, there was not statistically significant relationship between helminth infection and anemia (p=0.11). The mean of Hb levels in young women with helminth infection were higher both those who suffered anemia (11.30± 0.56 g /dL) or not (13.08 ± 0.42g /dL) compared with Hb levels in young women without helminth infection (anemia 10.37±1.06g/dL; not anemia 11.34±1.52g/dL). </em></p><p><strong><em>Conclusion:</em></strong><em> Helminth infection was not related to the incidence of anemia in young women even though Hb levels in helminth infections were higher compared to Hb levels without helminth infections. </em></p><p><em><br /></em></p>
Learning on Riemannian manifolds for interpretation of visual environments

OF THE DISSERTATION Learning on Riemannian Manifolds for Interpretation of Visual Environments by Cuneyt Oncel Tuzel Dissertation Director: Peter Meer Classical machine learning techniques provide effective methods for analyzing data when the parameters of the underlying process lie in a Euclidean space. However, various parameter spaces commonly occurring in computer vision problems violate this assumption. We derive novel learning methods for parameter spaces having Riemannian manifold structure and present several practical applications for scene analysis. The mean shift algorithm on Lie groups is a generalization of the mean shift procedure which is also an unsupervised learning technique for vector spaces. The derived procedure can be used to cluster data points which form a matrix Lie group. We present an application of the new algorithm for multiple 3D rigid motion estimation problem from noisy point correspondences in the presence of outliers. The approach performs simultaneous estimation of all the motions and does not require prior specification of the number of motion groups. We present a novel geometric framework to learn a supervised classification model for data points lying on a connected Riemannian manifold. The structure of the classifier is an additive model, where the weak learners are trained on the tangent spaces of the manifold. The derived algorithm is applied to pedestrian detection problem which is known to be among the hardest examples of the detection tasks. We describe a regression model where the response parameters form a Lie group. The model is utilized for affine tracking problem where the motion is estimated as a
An exploration of U.S. adults’ information processing skills and political efficacy

As recent debates about the role of social media in election outcomes suggest, understanding the association between information processing skills and political efficacy in the U.S. is a significant inquiry for adult and continuing education. Data from the Programme for the International Assessment of Adult Competencies were used to explore relationships between U.S. participants’ information processing skills and political efficacy. Given the impact of certain demographic characteristics on political efficacy, the study also analyzed whether the relationship between information processing skills and self-reported political efficacy varied across levels of cultural engagement, formal educational attainment, or immigrant status. The results illustrate that higher levels of literacy, numeracy, and problem solving in technology-rich environments are associated with higher political efficacy for U.S. participants. Our research is framed in both cognitive and critical lenses, and we provide implications for practice in adult and continuing education settings.
Decision-making in communication aid recommendations in the UK: cultural and contextual influencers

Abstract High-tech communication aids are one form of augmentative and alternative communication (AAC) intervention offered to children following an assessment process to identify the most appropriate system based on their needs. Professional recommendations are likely to include consideration of child characteristics and communication aid attributes. Recommendations may be influenced by contextual factors related to the cultural work practices and service context of professionals involved, as well as by contextual factors from the child’s life including their family environment and wider settings. The aim of this study was to explore the influence of cultural and contextual factors on the real-time decision-making processes of specialized AAC professionals in the UK. A total of six teams were recruited to the study. Each team carried out an assessment appointment related to a communication aid recommendation for a child and family. Following the appointment, each team participated in a focus group examining their decision-making processes during the preceding assessment. Inductive coding was used to analyse the transcribed data, and three organizing themes emerged relating to the global theme of Cultural and Contextual Influencers on communication aid decision-making. An explanatory model was developed to illustrate the funnelling effect that contextual factors may have on decision-making, which can substantially alter the nature and timing of a communication aid recommendation. Implications for clinical practice and future research are discussed.
The Methodological Divide of Sociology: Evidence from Two Decades of Journal Publications

Past research indicates that Sociology is a low-consensus discipline, where different schools of thought have distinct expectations about suitable scientific practices. This division of Sociology into different subfields is to a large extent related to methodology and choices between qualitative or quantitative research methods. Relying on theoretical constructs of the academic prestige economy, boundary demarcation and taste for research, we examine the methodological divide in generalist Sociology journals. Using automated text analysis for 8737 abstracts of articles published between 1995 and 2017, we discover evidence of this divide, but also of an entanglement between methodological choices and different research topics. Moreover, our results suggest a marginally increasing time trend for the publication of quantitative research in generalist journals. We discuss how this consolidation of methodological practices could enforce the entrenchment of different schools of thought, which ultimately reduces the potential for innovative and effective sociological research.
Multi-area Thévenin equivalent based power flow techniques

This thesis explores the possibility of applying the existing Multi-Area Thevenin Equivalent (MATE) algorithm to the power flow problem. Various theoretical considerations/difficulties of handling link connections in power flow are discussed. The current equation power flow program is examined in hopes of aiding link decoupling by taking advantage of the current equation’s inherent symmetrical links. However, implementation and testing of the current equation program indicated contrary results to recently published material on current equation programs. In an attempt to make MATE viable for power flow, one of MATE’s bottlenecks was examined, the link matrix. It was found that the problem could be alleviated by using a multi-level approach. This approach would allow link computation to be distributed across the subsystems and levels. An existing multi-level MATE algorithm has already been proposed but was implemented for only two levels. This thesis proposes a massively parallel algorithm for a general number of levels. The distribution of the link matrix allows for mass parallelization of the system matrix into very small subsystems. A flop analysis of the proposed multi-level MATE algorithm reveals that the majority of the computation is spent performing independent small matrix multiplication operations. Upon inspection of the strengths of the proposed multi-level MATE algorithm, it appears that the algorithm would benefit from a parallel computing platform such as modern GPUs. Today’s GPUs contain hundreds to thousands of scalar processors providing approximately an order of magnitude in computational power over multi-core CPUs. This has garnered the GPU much attention in many scientific disciplines. To test the feasibility of the MATE’s algorithm on the GPU, the algorithm’s most common operation, small matrix multiplication, was implemented. The test case was arranged to simulate the conditions of a 15,000 node system being factorized. The routine is meant to serve as the algorithm’s BLAS since linear algebra libraries on the GPU are not meant to handle very small matrices. The routine was found to successfully achieve a decent portion of the GPU’s peak flops.
Improved side impact protection - a search for systems modeling priorities

Systems Modeling evaluates the fleetwide crashworthiness of a vehicle design across the full range of potential impact speeds, angles, collision partners, occupant seating locations, and occupant restraints. Although this approach provides a more thorough assessment of crash protection than provided by a single crash test or simulation, the development of a complete Systems Model requires exhaustive simulation of every potential crash mode – a computationally prohibitive approach. This paper presents a methodology in which real world highway accident data is used to systematically develop Systems Modeling strategies that fully expose the tradeoffs between computational expense and model fidelity as measured by Harm. Using Australian side impact accident data, the paper illustrates the methodology by developing two computationally efficient strategies for developing a Systems Model for the evaluation and optimization of Side Impact protection.
Embracing Corporate Social Responsibility in Malaysia - Towards Sustaining Value Creation

This paper aims to review the existing research on Corporate Social Responsibility (CSR) that has been undertaken in Malaysia in order to revisit and understand the current practices and disclosures of Malaysian companies and to suggest viable future directions in regards to CSR in Malaysia. This paper is primarily discursive and conceptual. The first part of the paper reviews existing research on CSR in Malaysia with a view to establishing a general overview of the current state of CSR in Malaysia. This review facilitates the identification of key dimensions which influence the management of CSR activities in Malaysia. The second part of the paper pinpoints key areas of CSR that can potentially be managed by Malaysian companies in order to place Malaysia in the fore-front in the field of CSR and to be at par with other developed nations. The third part of the paper highlights on the seven papers that have been included in the special issue and briefly describes how each one contributes to the field of research in the areas of governance, accountability and value creation.Keywords: Corporate social responsibility, governance, accountability
Factor-Based Allocation: Is There a Superior Strategy?

Factor-based allocation embraces the idea of factors, as opposed to asset classes, as the ultimate building blocks of an investment portfolio. Our study contributes to the literature by addressing the question whether there is a superior way of combining factors in a portfolio. We provide a comprehensive comparison of factor-based allocation strategies within a multiple testing framework. Factor-based allocation is profitable, even when applying the necessary multiple testing corrections. Investment portfolios can be efficiently diversified using factor-based allocation since we find robust economic performance over various market states. Ultimately, we provide guidance for investors on the best method to choose when constructing factor-based portfolios. A naive equal-weighted factor portfolio, albeit simple and costless, cannot be outperformed by more sophisticated allocation strategies.
Impacts of dynamic managerial capability and international opportunity identification on firm performance

Purpose This paper aims to investigate the antecedents and outcomes of international opportunity identification (IOI) in export-manufacturing firms. The fundamental question addressed in this research is: How does dynamic managerial capability (DMC) of entrepreneurs contribute to IOI and success of the firms? Design/methodology/approach The research model was tested through structural equation modeling among the readymade garment manufacturing firms in the least developed country, Bangladesh. A survey was conducted with a random sampling approach and responses were collected from 390 firms. Findings The salient findings are: DMC has direct and indirect impacts through IOI on financial and non-financial performance; IOI mediates the relationship between managerial social capital and non-financial performance and between managerial cognition and non-financial performance; IOI has a negative relationship with the financial performance of the firms; and scope of accelerated internationalization positively moderates the relationship between IOI and financial performance of firms. Originality/value This paper notably shows that DMC of export-manufacturing entrepreneurs leads to the identification of the right kind of opportunities, which, in turn, generate better performance. It is advantageous for this type of firm to operate a business in multiple countries.
Individual Fitness App Use: The Role of Goal Orientations and Motivational Affordances

Lacking physical activity is an ongoing problem in our society and fitness apps are positioned to address this issue. They aim to induce motivation towards physical activity by providing different motivational features that build upon self-quantification, gamification, and social network capabilities. Little is known, however, whether, how, and why users with differing motivation-relevant goals employ these motivational features differently. Drawing upon Motivational Affordances, the Choice of Situation model, and Achievement Goal Theory, this paper investigates how users’ goal orientations (i.e., mastery and performance goals) account for different ways of using fitness apps. Empirical validation with 417 fitness app users reveals distinct patterns between individual goals and the use of fitness apps for self-monitoring, exercise guidance, rewards, and social comparison. This paper contributes to the literature on individualized fitness app use, theoretically extends the concept of motivational affordances with individual differences and aids practice in tailoring fitness app features.