The Potential for Student Performance Prediction in Small Cohorts with Minimal Available Attributes

The measurement of student performance during their progress through university study provides academic leadership with critical information on each student’s likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those “at risk” of failure/withdrawal. However, modern university environments, offering easy on-line availability of course material, may see reduced lecture/tutorial attendance, making such identification more challenging. Modern data mining and machine learning techniques provide increasingly accurate predictions of student examination assessment marks, although these approaches have focussed upon large student populations and wide ranges of data attributes per student. However, many university modules comprise relatively small student cohorts, with institutional protocols limiting the student attributes available for analysis. It appears that very little research attention has been devoted to this area of analysis and prediction. We describe an experiment conducted on a final-year university module student cohort of 23, where individual student data are limited to lecture/tutorial attendance, virtual learning environment accesses and intermediate assessments. We found potential for predicting individual student interim and final assessment marks in small student cohorts with very limited attributes and that these predictions could be useful to support module leaders in identifying students potentially “at risk.”.Peer reviewe

The Relationship of Alexithymia and Cognitive Failure with Spiritual Health in Male Students of Ardabil Payam-e Noor University

Background & Objectives: Students with a high spiritual health can adapt to the problems in their personal life. The purpose of this study was to investigate the relationship of alexithymia and cognitive failure with spiritual health in male students of Ardabil Payam-e Noor University. Methods: This descriptive-analytic study was performed on 268 male students of Ardabil Payam-e Noor University selected through multistage multi-cluster random sampling. Data collection tools included questionnaires of alexithymia (20 items), cognitive failure (25 items), and spiritual well-being (20 questions). Data were entered into SPSS version 23 and analyzed using inferential statistics tests, Pearson Correlation Coefficient and Multiple Regression tests. Results: There was no statistically significant relationship between demographic variables (age, educational level and field, occupation and marital status) and spiritual health among male students. However, alexithymia and cognitive failure showed significant statistical relationships with spiritual well-being. According to multiple regression results, alexithymia and cognitive failure have the potential for predicting spiritual well-being in male students (P <0.05). Conclusion: Considering the effect of alexithymia and cognitive failure on students’ spiritual health, it is recommended to help students to improve their spiritual health by overcoming alexithymia and cognitive failure. Key¬words: Affective Symptoms, Cognition, Health, Students Citation: Narimani M, Samadifard HR. The Relationship of Alexithymia and Cognitive Failure with Spiritual Health in Male Students of Ardabil Payam-e Noor University. Journal of Health Based Research 2017; 3(2): 163-173

On the design of timber bolted connections subjected to fire

Paper 121Current research at the University of Canterbury is investigating the application of Johansen’s yield equations to the prediction of the failure strength of bolted connections in fire conditions. A series of single bolted connections using steel side plates have been heated at constant temperature for several hours, then loaded to failure. The failure loads have been used to determine the embedment strength of the joints at various temperatures over a range of temperatures from ambient to 300°C. These temperature-dependent embedment strengths have also been used in the Johansen’s equations for wood-steel-wood and wood-wood-wood connections and compared with the results for single bolted connections tested over a range of constant temperatures. Comparisons have also been made with the results of several similar connections tested in fire conditions and show considerable promise for predicting failure of such joints

Materials for large length fibre-based ships. Characterization, selection, and numerical analysis

Fourth dissemination action for university students for increasing the interest in the use of fibre-reinforced polymers for large-length vessels design and shipbuilding in the future naval architects and marine engineers. This presentation was held at the School of Naval Architecture and Ocean Engineering (ETSINO) of the Technical University of&nbsp;Madrid on the 1st of October of 2019. In this presentation, the process of materials selection for marine applicactions and the numerical models for characterizing and predicting the fatigue and failure of such materials were introduced

Predictors of Angio access failure in end stage renal disease patients in Southern Egypt

Background: Hemodialysis (HD) seems to be the most often used Renal Replacement Therapy (RRT) modality worldwide, and it is the primary modality in the majority of instances with extended RRT. The ability to provide our patients with high-quality HD treatment while also increasing their chances of survival is heavily reliant on the functionality of the vascular access (VA). Despite the fact that it is a very necessary component of all clinical practise standards, it is the most expensive individual component of RRT.Objectives: This study was aimed at comparing between the group with Angio access failure and group without Angio access failure and predicting Angio access failure among end stage renal failure patients in Southern Egypt.Subjects and Methods: a prospective cohort study among 125 patients with end stage renal failure at Aswan University. The research comprised patients who had NCVA placement [intra-atrial catheter (IAC) and trans-lumbar catheter (TLC)] between January 1, 2020, and December 31, 2020.Results: The duration of previous RRT was significantly higher among the Angio access failure than the group without Angio access failure. In multivariate analysis using logistic regression, the age, duration of previous RRT, diabetes, IHD (ischemic heart disease), PVD (peripheral vascular disease) and CVD (cardiac vascular disease) were significantly direct predictors of the Angio access failure in the first one year.Conclusion: In conclusion the failure of Angio access was positively associated with age, previous RRT and other comorbidities

Numerical tools for the design of fibre-based ships of large lengths

First dissemination action for university students at the School of Naval and Ocean Engineering (ETSINO) of Cartagena University (UPCT) with the intention of increasing the interest of the students and future engineers and naval architects in the use of composite materials for the design and shipbuilding of large-length vessels. In this presentation, the numerical models developed for predicting the fatigue and failure of composite materials were showed. Besides, the new numerical tools to design and anayze fiber-based ships of large length were introduced, specifically a coupled seakeeping-FEA tool, a new graphical user interface (GUI) for materials definition, hull girder analysis and collapse assesemt

The Predictive Significance of Pre-college data with reference to College Success

Intelligence tests have been used extensively by colleges and universities as a basis for predicting success or failure in college since the world war. Due to this fact it was decided to make a survey of what is being done in this country with reference to admission to colleges and to determine the predictive value of intelligence tests, high school marks, and college marks of students who enter the University of Tennesee. In consderation of what has been done, and because of the indefiniteness of the work done along this line in the past it was decided to make a further study of the specific situation in the University of Tennessee. The pre-college data used in this study consists of intelligence quotients, high school marks, and English placement grades

Three-dimensional multifractal analysis of trabecular bone under clinical computed tomography

Purpose: An adequate understanding of bone structural properties is critical for predicting fragility conditions caused by diseases such as osteoporosis, and in gauging the success of fracture prevention treatments. In this work we aim to develop multiresolution image analysis techniques to extrapolate high-resolution images predictive power to images taken in clinical conditions. Methods: We performed multifractal analysis (MFA) on a set of 17 ex vivo human vertebrae clinical CT scans. The vertebræ failure loads (FFailure) were experimentally measured. We combined bone mineral density (BMD) with different multifractal dimensions, and BMD with multiresolution statistics (e.g., skewness, kurtosis) of MFA curves, to obtain linear models to predict FFailure. Furthermore we obtained short- and long-term precisions from simulated in vivo scans, using a clinical CT scanner. Ground-truth data - high-resolution images - were obtained with a High-Resolution Peripheral Quantitative Computed Tomography (HRpQCT) scanner. Results: At the same level of detail, BMD combined with traditional multifractal descriptors (Lipschitz-Hölder exponents), and BMD with monofractal features showed similar prediction powers in predicting FFailure (87%, adj. R2). However, at different levels of details, the prediction power of BMD with multifractal features raises to 92% (adj. R2) of FFailure. Our main finding is that a simpler but slightly less accurate model, combining BMD and the skewness of the resulting multifractal curves, predicts 90% (adj. R2) of FFailure. Conclusions: Compared to monofractal and standard bone measures, multifractal analysis captured key insights in the conditions leading to FFailure. Instead of raw multifractal descriptors, the statistics of multifractal curves can be used in several other contexts, facilitating further research.Fil: Baravalle, Rodrigo Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Thomsen, Felix Sebastian Leo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur; ArgentinaFil: Delrieux, Claudio Augusto. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lu, Yongtao. Dalian University of Technology; ChinaFil: Gómez, Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Stošić, Borko. Universidade Federal Rural Pernambuco; BrasilFil: Stošić, Tatijana. Universidade Federal Rural Pernambuco; Brasi

Towards the Grade’s Prediction. A Study of Different Machine Learning Approaches to Predict Grades from Student Interaction Data

There is currently an open problem within the field of Artificial Intelligence applied to the educational field, which is the prediction of students’ grades. This problem aims to predict early school failure and dropout, and to determine the well-founded analysis of student performance for the improvement of educational quality. This document deals the problem of predicting grades of UNIR university master’s degree students in the on-line mode, proposing a working model and comparing different technologies to determine which one fits best with the available data set. In order to make the predictions, the dataset was submitted to a cleaning and analysis phases, being prepared for the use of Machine Learning algorithms, such as Naive Bayes, Decision Tree, Random Forest and Neural Networks. A comparison is made that addresses a double prediction on a homogeneous set of input data, predicting the final grade per subject and the final master’s degree grade. The results were obtained demonstrate that the use of these techniques makes possible the grade predictions. The data gives some figures in which we can see how Artificial Intelligence is able to predict situations with an accuracy above 96%

Bending Tests of Hat Sections with Multiple Longitudinal Stiffeners

This paper is the first in a series of articles that report findings of the authors investigation into the behavior of cold formed steel hat sections in bending with multiple intermediate longitudinal stiffeners. Presented in this paper is the test program that was carried out at the University of Waterloo as part of a two year research program. It is known that sections with multiple intermediate stiffeners can fail either in a local sub-element buckling mode, or alternatively, can experience an overall plate buckling mode of failure. Although both failure modes were examined, the main objective was to develop a consistently accurate and practical method of predicting the ultimate bending strength of sections which failed in overall plate buckling. Recent testing carried out by previous researchers indicates that the bending resistance of multiple stiffened cold formed steel members which fail in overall plate buckling is too conservatively predicted by the current Canadian design standard (S136-94). These researchers have also shown that the American design specification (AlSI 96) is unconservative for the same sections. Data from 18 previous test specimens were compiled and supplemented with 94 additional tests carried out at the University of Waterloo, encompassing a range of section dimensions and material properties. All test specimens were simply supported and subjected to uniformly distributed loading. The Waterloo test program consisted of hat sections that failed primarily in overall plate buckling and in a few cases also in local sub-element buckling of the compression flange. Only six of the 112 specimens were observed to have failed in local sub-element buckling, while the remainder experienced overall plate buckling at failure