The purpose of this paper is to define a reference framework for introducing eLearning practices in mainly face-to-face higher education institutions. We suggest a suitable adoption and management of associated infrastructures and processes, in order...
Education has changed dramatically due to the severe global pandemic COVID-19, with the phenomenal growth of e-learning, whereby teaching is undertaken remotely and on digital platforms. E-learning is revolutionizing education systems, as it remains...
The COVID-19 pandemic affected educational institutions in an unrivaled way around the globe and forced them to switch from conventional classroom learning mode to e-learning mode within a short time period. Neither instructors nor students had ample...
Learning analysis provides a new opportunity for the development of online education, and has received extensive attention from scholars at home and abroad. How to use data and models to predict learners’ academic success or failure and give te...
In recent years, with the flourishing of the catering economy and the trends in computer technology, restaurant operators have increasingly relied on employees with computational and information skills. Breaking through the traditional teaching metho...
This research analyses the impact of COVID-19 on the Spanish university system during the period of home lockdown put in place by the government of Spain between 15 March and 21 June 2020. This period did not involve a change to online teaching. Inst...
Open science refers to all things open in research and scholarly communication: from publications and research data to code, models and methods as well as quality evaluation based on open peer review. However, getting started with implementing open s...
The recent growth of learning technologies has catalyzed the surge in investments in e-learning systems across higher education to revolutionize pedagogical practices. Thus, the implementation of 3D virtual learning tools has become an indispensable,...
Since the advent of modern technology, various e-learning initiatives have been implemented in schools. Although such initiatives have enhanced English as a second language (ESL) teachers’ technological knowledge, these teachers continue to struggle...
Knowledge payment is a new type of E-learning that has developed in the era of social media. With the influence of the COVID-19 epidemic, the knowledge payment market is developing rapidly. Exploring the influencing factors of users’ continuanc...
The global navigation satellite system (GNSS) position time series provides essential data for geodynamic and geophysical studies. Interpolation of the GNSS position time series is necessary because missing data will produce inaccurate conclusions ma...
Water scarcity is a global problem. Deficit irrigation (DI) reduces evapotranspiration, improving water efficiency in agriculture. Reference evapotranspiration
Accurate traffic prediction is pivotal when constructing intelligent cities to enhance urban mobility and to efficiently manage traffic flows. Traditional deep learning-based traffic prediction models primarily focus on capturing spatial and temporal...
Purpose: E-waste management (EWM) refers to the operation management of discarded electronic devices, a challenge exacerbated due to overindulgent urbanization. The main purpose of this paper is to amalgamate production engineering, statistical metho...
There is relatively little research on deep learning for anomaly detection within the field of deep learning. Existing deep anomaly detection methods focus on the learning of feature reconstruction, but such methods mainly learn new feature represent...
The Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM) is a widely utilized product for geological, climatic, oceanic, and ecological applications. However, the accuracy of the SRTM DEM is constrained by topography and vegetation....
Confusing low-molecular-weight hyaluronic acid (LMWHA) from acid degradation and enzymatic hydrolysis (named LMWHA–A and LMWHA–E, respectively) will lead to health hazards and commercial risks. The purpose of this work is to analyze the s...
Objective: Phase transfer entropy (
27 April 2026
Antimicrobial resistance in Escherichia coli (E. coli) is a major public health concern globally, driven by increased resistance to commonly used antimicrobial agents such as β-lactams and fluoroquinolones. The main goal of our research is to de...
Prediction of gas chromatographic retention indices based on compound structure is an important task for analytical chemistry. The predicted retention indices can be used as a reference in a mass spectrometry library search despite the fact that thei...
The data presented in this article comprise an educational dataset collected from the student information system (SIS), the learning management system (LMS) called Moodle, and video interactions from the mobile application called “eDify.”...
Wisconsin card-sorting tasks provide unique opportunities to study cognitive flexibility and its limitations, which express themselves behaviorally as perseverative errors (PE). PE refer to those behavioral errors on Wisconsin card-sorting tasks that...
This paper proposes a learning-based adaptive imputation method (LAI) for imputing missing power data in an energy system. This method estimates the missing power data by using the pattern that appears in the collected data. Here, in order to capture...
Machine-learning techniques, properly combined with data structures, have resulted in Learned Static Indexes, innovative and powerful tools that speed up Binary Searches with the use of additional space with respect to the table being searched into....
Non-invasive Glucose Measurement (NGM) technology makes great sense for the blood glucose management of patients with hyperglycemia or hypoglycemia. Individual Discrepancies (IDs), e.g., skin thickness and color, not only block the development of NGM...
This paper presents the construction of a new objective method for estimation of visual perceiving quality. The proposal provides an assessment of image quality without the need for a reference image or a specific distortion assumption. Two main proc...
As an important branch of machine learning, recommendation algorithms have attracted the attention of many experts and scholars. The current recommendation algorithms all more or less have problems such as cold start and single recommended items. In...
The crystalline state of matter serves as a reference point in the context of studies of properties of a variety of chemical compounds. This is due to the fact that prepared crystalline solids of practically useful materials (inorganic or organic) ma...
This paper provides new field-based evidence on loss aversion and short-run learning using high-frequency performance data from professional golf. Leveraging over 100,000 putts recorded during the 2020 Korea Professional Golfers’ Association (K...
Federated Learning (FL) is emerging as an encouraging paradigm for AI model training in healthcare that enables collaboration among institutions without revealing sensitive information. The lack of transparency in federated models makes their deploym...
The increasing availability of Synthetic Aperture Radar (SAR) images facilitates the generation of rich Differential Interferometric SAR (DInSAR) data. Temporal analysis of DInSAR products, and in particular deformation Time Series (TS), enables adva...
Unsupervised change detection (UCD) is a key technique in Earth observation, aiming to identify and quantify surface changes over time by analyzing multi-temporal remote sensing images without manual annotations. Unlike supervised approaches that rel...
The study on which the article is based investigates which learning strategies multilingual pupils use when using a multimedia and multilingual media offer in geography lessons and how these influence their subject-related learning success. By way of...
Location-based Augmented Reality (AR) refers to educational mobile applications where a layer of digital content overlays the users’ physical environment when the users reach specific geographical locations. Unlike marker-based AR, which relies...
Entity alignment helps discover and link entities from different knowledge graphs (KGs) that refer to the same real-world entity, making it a critical technique for KG fusion. Most entity alignment methods are based on knowledge representation learni...
Overfitting is an important problem in machine learning. Several algorithms, such as the extreme learning machine (ELM), suffer from this issue when facing high-dimensional sparse data, e.g., in text classification. One common issue is that the exten...
Identifying important factors (e.g., features and prediction models) for forest aboveground biomass (AGB) estimation can provide a vital reference for accurate AGB estimation. This study proposed a novel feature of the canopy height distribution (CHD...
Thoracic diseases refer to disorders that affect the lungs, heart, and other parts of the rib cage, such as pneumonia, novel coronavirus disease (COVID-19), tuberculosis, cardiomegaly, and fracture. Millions of people die every year from thoracic dis...
Machine learning techniques have been increasingly used in flood management worldwide to enhance the effectiveness of traditional methods for flood susceptibility mapping. Although these models have achieved higher accuracy than traditional ones, the...
Fiber-reinforced polymer (FRP) is widely used in the field of structural engineering, for example, as a confining material for concrete. The ultimate conditions (i.e., compressive strength and ultimate axial strain) are key factors that need to be co...
Evapotranspiration is often expressed in terms of reference crop evapotranspiration (
Deep learning models have an intrinsic privacy issue as they memorize parts of their training data, creating a privacy leakage. Membership inference attacks (MIAs) exploit this to obtain confidential information about the data used for training, aimi...
Visual odometry (VO) refers to incremental estimation of the motion state of an agent (e.g., vehicle and robot) by using image information, and is a key component of modern localization and navigation systems. Addressing the monocular VO problem, thi...
Modern computational models in supervised machine learning are often highly parameterized universal approximators. As such, the value of the parameters is unimportant, and only the out of sample performance is considered. On the other hand much of th...
Power lithium battery is an important core component of electric vehicles (EV), which provides the main power and energy for EV. In order to improve the estimation accuracy of the state of charge (SOC) of the electric vehicle battery (E-cell), the ex...
China’s Chang’e lunar exploration project obtains digital orthophoto image (DOM) and digital elevation model (DEM) data covering the whole Moon, which are critical to lunar research. The DOM data have three resolutions (i.e., 7, 20 and 50 m), while t...
Fatty acid abundance is a key parameter for evaluating the quality of edible oils. This study developed a rapid and non-destructive method for predicting palmitic acid content in edible oils by combining visible-near-infrared (Vis-NIR) reflectance sp...
A total of 2932 publications in the field of ozone pollution were obtained from the Web of Science and briefly reviewed using a bibliometric analysis and WOS-based citation reports. CiteSpace 5.7.R3 (64 bit) was used to perform a visualization of kno...
In this study, an inquiry-based sequence was designed, developed and implemented using facets of flipped classroom and aspects of inquiry learning using the ADDIE model. The sequence intends to promote the students’ scientific literacy. The aim...
This study examines information recovery under structured partial observation in multi-informant questionnaire systems. Rather than predicting an external ground truth, we evaluate the recoverability of an operational full-information decision rulewh...
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