1,695 Results Found

Despite extensive evidence reporting the numerous health benefits of physical activity, recent studies show that many people (60%) do not follow the recommendations to meet the accepted minimums of physical activity. Some of the main problems in toda...

This paper sheds light on the causes of school dropouts, a major challenge facing UPE attainment in public primary schools of Uganda. We offer microregional analysis of school dropout patterns in the Mpigi district, and show a number of distinct patt...

This paper is concerned with a networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta (SOD), sensor data are transmitted to the estimator node if...

Undergraduate dropout is a multidimensional phenomenon with implications for higher education, economic development, and social and cultural transformation, posing complex challenges for society as a whole. To address this, universities require effec...

This paper discusses the dissipative filtering problem for discrete-time nonlinear networked systems with dynamic quantization and data packet dropouts. The Takagi–Sugeno (T–S) fuzzy model is employed to approximate the considered nonline...

Tire–pavement interactions, like friction and rolling resistance, are significantly influenced by pavement macro-texture and micro-texture. Accurate texture measurement at the micro-texture level is vital to achieve the desired level of safety,...

Ride comfort and driving safety are highly vulnerable to the undesirable excessive vibrations caused by road surface irregularities and the imperfect in-vehicle network (IVN). The main contribution of this paper consists of proposing a near-optimal v...

This paper analyses the centralized fusion linear estimation problem in multi-sensor systems with multiple packet dropouts and correlated noises. Packet dropouts are modeled by independent Bernoulli distributed random variables. This problem is addre...

Background/Objectives: Adherence to active physiotherapy programs in children suffering from cancer is essential to enhance the improvement generated by the treatment. Therefore, the main aim of this review was to identify the factors influencing adh...

In this paper, the control problem is investigated for discrete time-varying delayed systems with stochastic uncertainty, external disturbance, and two-channel packet dropouts. Sliding mode functions with packet loss probabilities are proposed for th...

This paper investigates an optimal decision-making and optimization framework for networked systems operating under the coupled effects of stochastic transmission delays, packet dropouts, and input delays, which is a critical unresolved challenge in...

This paper focuses on the stability and sliding mode issues for the two-dimensional (2D) Fornasini-Marchesini (FMII) networked control system under packet dropouts. Firstly, the output-based 2D event-triggered strategy was constructed to alleviate in...

Against a backdrop of dominant deficit, victim-blaming and class/colourblind theories of unequal educational transitions and higher education outcomes, this article analyses thematically in-depth narrative interviews with Black working class “d...

This paper addresses the cooperative output tracking control problem for a class of leader-following linear heterogeneous networked multi-agent systems subject to random network delays and packet dropouts in the feedback and forward channels of each...

Child labour is a common financial coping strategy in poor households, especially in low-and middle-income countries with many children working under hazardous conditions. Little is known about the linkages between hazardous work conditions and psych...

Since a high dropout rate for university students is a significant risk to local communities and countries, a dropout prediction model using machine learning is an active research domain to prevent students from dropping out. However, it is challengi...

With the wide spread of massive open online courses ( MOOC ), millions of people have enrolled in many courses, but the dropout rate of most courses is more than 90%. Accurately predicting the dropout rate of MOOC is of great significance to prevent...

The core of dropout prediction lies in the selection of predictive models and feature tables. Machine learning models have been shown to predict student dropouts accurately. Because students may drop out of school in any semester, the student history...

A dropout early warning system enables schools to preemptively identify students who are at risk of dropping out of school, to promptly react to them, and eventually to help potential dropout students to continue their learning for a better future. H...

Overfitting remains a major difficulty in training deep neural networks, especially when attempting to achieve good generalization in complex classification tasks. Standard dropout is often employed to address this issue; however, its uniform random...

Sport dropout rates among children and youth are a concern for researchers and policy makers. The impact of relative age effects (RAEs) on dropout trends has not been adequately examined in female samples. The purpose of this study was to longitudina...

The purpose of this paper is to establish what sociodemographic and institutional factors cause students to drop out, become uncertain about their intentions to obtain a degree, or confidently advance towards the fulfilment of their ambitions. Our an...

The phenomenon of dropout is often found among customers of sports services. In this study we intend to evaluate the performance of machine learning algorithms in predicting dropout using available data about their historic use of facilities. The dat...

In a convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially. Except for randomly discarding regions or channels, many approache...

Dropout is one of the most popular regularization methods in the scholarly domain for preventing a neural network model from overfitting in the training phase. Developing an effective dropout regularization technique that complies with the model arch...

The school-dropout problem is a serious issue that affects both a country’s education system and its economy, given the substantial investment in education made by national governments. One strategy for counteracting the problem at an early sta...

Adult learner dropout is adults’ withdrawal or stop-out from formal or non-formal educational programs before successful completion. For adult learners, withdrawal often manifests as stop-out or temporary disengagement rather than permanent att...

Background: Treatment dropout in substance use disorder (SUD) programs poses a significant challenge to achieving successful outcomes and leads to legal and financial issues. Socioeconomic factors have been identified as key contributors to treatment...

One of the problems regarding MOOCs (Massive Open Online Courses) is the high dropout rate. Although dropout periods have been studied, there is still a lack of understanding of how dropout differs for MOOCs with different levels of difficulty. A qua...

University dropout is a serious problem. It affects not only the individual who drops out but also the university and society. However, most previous studies have focused only on the subjective/individual level. University dropout is a very important...

Massive Open Online Courses (MOOCs) have gained widespread popularity for their potential to offer education to an unlimited global audience. However, they also face a critical challenge in the form of high dropout rates. This paper addresses the nee...

School dropout is a pressing social problem that stems from systemic inadequacies in the education system and socio-economic background. The aim of this study was to analyze how the travel time and financial difficulties impact school dropout in sate...

The undeniable computational power of artificial neural networks has granted the scientific community the ability to exploit the available data in ways previously inconceivable. However, deep neural networks require an overwhelming quantity of data i...

As test anxiety has evolved conceptually, identifying specific components contributing to educational success is essential. This study is the first to examine how different components of test anxiety are related to university dropout. Hungarian unive...

A neural network algorithm is a meta-heuristic algorithm inspired by an artificial neural network, which has a strong global search ability and can be used to solve global optimization problems. However, a neural network algorithm sometimes shows the...

The research on student dropout demonstrates that there is no consensus on its definition and scope. Although there is an expanding collection of research on the topic, student dropout remains a significant issue, characterized by numerous uncertaint...

In Portugal, the dropout rate of university courses is around 29%. Understanding the reasons behind such a high desertion rate can drastically improve the success of students and universities. This work applies existing data mining techniques to pred...

The phenomenon of student dropout in higher education presents significant challenges for students, higher education institutions, governments, and society. The present study focuses on the dropout rates within the engineering programmes at one schoo...

Education systems are working to reduce dropout risk, thereby reducing early leaving from education and training rates (ELET) for a more sustainable society. There is a wealth of research on the causes of dropout risk, but little that looks at it in...

Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes mus...

This paper presents the first systematic attempt to quantify higher education dropout rates in Slovenia and to examine their relationship with youth unemployment. Using annual data for the period 2011–2019, dropout rates were estimated based on...

Student dropout is a serious issue in that it not only affects the individual students who drop out but also has negative impacts on the former university, family, and society together. To resolve this, various attempts have been made to predict stud...

Background/Objectives: Convolutional Neural Networks (CNNs), while effective in tasks such as image classification and language processing, often experience overfitting and inefficient training due to static, structure-agnostic regularization techniq...

Dropout prediction is a problem that must be addressed in various organizations, as retaining customers is generally more profitable than attracting them. Existing approaches address the problem considering a dependent variable representing dropout o...

In recent years an increased drop-out rate in adolescents’ soccer participation has been observed. Given the potentially adverse consequences of drop-out from soccer, more information about risk factors for drop-out is warranted. In the current...

Massive Open Online Courses (MOOCs) are a relatively new educational model that provides free access to educational content regardless of location or time. Despite these benefits, MOOCs encounter significant challenges, such as low completion rates,...

Predicting student dropout from universities is an imperative but challenging task. Numerous data-driven approaches that utilize both student demographic information (e.g., gender, nationality, and high school graduation year) and academic informatio...

Background: Retention in treatment is crucial for the success of interventions targeting alcohol use disorder (AUD), which affects over 100 million people globally. Most previous studies have used classical statistical techniques to predict treatment...

College dropout represents a significant challenge for universities, and despite advances in machine learning technologies, predicting dropout remains a complex task. This literature review focuses on investigating the factors that influence college...

School dropout in higher education remains a significant global challenge with profound socioeconomic consequences. To address this complex issue, educational institutions increasingly rely on business intelligence (BI) and related predictive analyti...