26 November 2021
Social media platforms have become accessible resources for health data analysis. However, the advanced computational techniques involved in big data text mining and analysis are challenging for public health data analysts to apply. This study propos...
Fine aerosols with a diameter of less than 2.5 microns (PM2.5) have a significant negative impact on human health. However, their measurement devices or instruments are usually expensive and complicated operations are required, so a simple and effect...
Drought stress and nutrient status are highly important for plant growth and productivity. Two field experiments were conducted during two consecutive seasons (2017–2018 and 2018–2019) at El-Molak, Abo-Hammad, Sharkia, Egypt. This work was conducted...
The objectives of this study were: (1) to identify factors influencing the performance of dairy cows in an automated milking system (AMS); (2) to construct a synthetic robotic adaptability index (RAI) of cows’ adaptation to the AMS; (3) to eval...
Automatic irrigation scheduling systems are highly demanded in the agricultural sector due to their ability to both save water and manage deficit irrigation strategies. Elaborating a functional and efficient automatic irrigation system is a very comp...
Background: The purpose of this study was to assess the volume of the pulmonary nodules and masses on serial chest X-rays (CXRs) from deep-learning-based automatic detection algorithm (DLAD)-based parameters. Methods: In a retrospective single-instit...
In this study, methods for predicting energy demand on hourly consumption data are established for realizing an energy management system for buildings. The methods consist of an energy prediction algorithm that automatically separates the datasets to...
Background: There is a lack of automatic real-time monitoring of airborne pollens in China and no validation study has been performed. Methods: Two-year continuous automatic real-time pollen monitoring (n = 437) was completed in 2023 (3 April–3...
Measuring weight during cattle growth is essential for determining their status and adjusting the feed amount. Cattle must be weighed on a scale, which is laborious and stressful and could hinder growth. Therefore, automatically predicting cattle wei...
Air pollution is one of the most challenging and complex problems of our time. This research presents the prediction of air pollutant values based on using an R program with linear regression. The research sample consists of obtained values of air po...
For remanufacturing to be more economically attractive, there is a need to develop automatic disassembly and automated visual detection methods. Screw removal is a common step in end-of-life product disassembly for remanufacturing. This paper present...
Circular data arise in a wide range of scientific fields, including meteorology, medicine, biology, and neuroscience, yet existing regression methods for such data are largely restricted to parametric generalized linear models or tree-based methods t...
Ridge regression is one of the most popular shrinkage estimation methods for linear models. Ridge regression effectively estimates regression coefficients in the presence of high-dimensional regressors. Recently, a generalized ridge estimator was sug...
In this paper, we analyzed the data of the 17 body sizing measurement parameters of 300 adult male participants who were Shaanxi adult male aged 20?0, which were collected by using the 3D automatic measurement, 3D interactive measurement and manual m...
This research is the first attempt to create machine learning (ML) algorithmic systems that would be able to automatically trade precious metals. The algorithm uses three forecast methodologies: linear regression (LR), Darvas boxes (DB), and Bollinge...
A new simple airborne method based on wide optics camera is developed for leaf area index (LAI) estimation in coniferous forests. The measurements are carried out in winter, when the forest floor is completely snow covered and thus acts as a light ba...
The stochastic structural plane of a rock mass is the key factor controlling the stability of rock mass. Obtaining the distribution of stochastic structural planes within a rock mass is crucial for analyzing rock mass stability and supporting rock sl...
The aim of this study was to find an efficient method to determine features that characterize octave illusion data. Specifically, this study compared the efficiency of several automatic feature selection methods for automatic feature extraction of th...
This paper aims to monitor the ambient level of particulate matter less than 2.5
The purpose of this study was to investigate the accuracy of the airway volume measurement by a Regression Neural Network-based deep-learning model. A set of manually outlined airway data was set to build the algorithm for fully automatic segmentatio...
The aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020–2024). A description of ML methods (linear and logistic regression, classification and regression trees, chi-squa...
Reliable and continuous operation of the equipment is expected in the wastewater treatment plant, as any perturbations can lead to environmental pollution and the need to pay penalties. Optimization and minimization of operating costs of the pump sta...
This paper gives a comprehensive overview of the state-of-the-art machine learning methods that can be used for estimating self-compacting rubberized concrete (SCRC) compressive strength, including multilayered perceptron artificial neural network (M...
In this study, new approaches are proposed over a range of conditions with unknown loading time to determine the initial conditions and identify the explicit model parameters of successive weighing system in the early part of the transient response....
Identifying the patients who are likely to be non-responders to a certain treatment may allow clinicians to provide alternative strategies and avoid frustration and unrealistic expectations for the patients and their families. A retrospective study o...
Purpose: To develop and test an innovative semi-automatic method for quantifying the three-dimensional morphology of the peripapillary retinal pigment epithelium-basement membrane (ppRPE/BM) layer, with application to lumbar puncture (LP) patients. M...
Pig weighing is an essential procedure for monitoring growth and animal health; however, conventional methods are often labor-intensive, costly, and potentially stressful. In this context, this study proposes a non-invasive approach for estimating th...
Facial nerve palsy induces a weakness or loss of facial expression through damage of the facial nerve. A quantitative and reliable assessment system for facial nerve palsy is required for both patients and clinicians. In this study, we propose a rapi...
The development of multimodal media compensates for the lack of information expression in a single modality and thus gradually becomes the main carrier of sentiment. In this situation, automatic assessment for sentiment information in multimodal cont...
We developed two models for real-time monitoring and forecasting of the evolution of the COVID-19 pandemic: a non-linear regression model and an error correction model. Our strategy allows us to detect pandemic peaks and make short- and long-term for...
This study examines the influence of roundabout geometric design on motorcyclists’ risky behaviours in mixed-traffic environments, where motorcycles form a dominant traffic component. While conventional safety analyses often emphasise the perfo...
The temporal dynamics of forest-associated insects are closely associated with climatic variability, and identifying their temporal patterns and climatic associations is important for understanding insect population dynamics. In this study, automatic...
Buildings represent a significant portion of global energy consumption. Ventilation units are complex components, often customized for the specific building, responsible for a large part of energy consumption. Their faults impact buildings’ ene...
Current technologies based on inertial measurement units (IMUs) are considered valid and reliable tools for monitoring barbell velocity in strength training. However, the extracted outcomes are often limited to a few velocity metrics, such as mean or...
All non-foot-mounted inertial localization systems have a common challenge: the need for calibrating the parameters of the step length model. The calibration of the parameters of a step length model is key for an accurate estimation of the pedestrian...
This study aimed to develop a warning system platform for coffee rust incidence fifteen days in advance, as well as validating and regionalizing multiple linear regression models based on meteorological variables. The models developed by Pinto were v...
In existing models with an unknown link function, the issue of predictors containing both multiple functional data and multiple scalar data has not been studied. To fill this gap, we propose a generalized partially functional linear model, which not...
It is of the utmost importance to accurately estimate different ships’ weights during their design stages. Additionally, lightship displacement (LD) data are not always easily accessible to shipping stakeholders, while other ships’ dimens...
Multi-temporal images acquired at high spatial and temporal resolution are an important tool for detecting change and analyzing trends, especially in agricultural applications. However, to insure a reliable use of this kind of data, a rigorous radiom...
Lifting is one of the most potentially harmful activities for work-related musculoskeletal disorders (WMSDs), due to exposure to biomechanical risk. Risk assessment for work activities that involve lifting loads can be performed through the NIOSH (Na...
With more machine learning methods being involved in social and environmental research activities, we are addressing the role of available information for model training in model performance. We tested the abilities of several machine learning models...
In the field of autofocus for optical systems, although passive focusing methods are widely used due to their cost-effectiveness, fixed focusing windows and evaluation functions in certain scenarios can still lead to focusing failures. Additionally,...
From the perspective of functional symmetry design, this study constructed a functionally complementary framework between “prediction” and “explanation” in the field of risk early warning. To address the semantic gap between p...
It is necessary to optimize clustering processing of communication big data numerical attribute feature information in order to improve the ability of numerical attribute mining of communication big data, and thus a big data clustering algorithm base...
Change-point regression models are often used to develop building energy baselines that can be used to predict energy use and determine energy savings during a given performance period. However, the reliability of building energy baselines can depend...
This study evaluated the accuracy of a sensor-based device (AfiCollar) to automatically monitor and record grazing and rumination behaviours of grazing dairy cows on a real-time basis. Multiparous spring-calved dairy cows (n = 48) wearing the AfiColl...
Predicting groundwater availability is important to water sustainability and drought mitigation. Machine-learning tools have the potential to improve groundwater prediction, thus enabling resource planners to: (1) anticipate water quality in unsample...
In this paper, we investigate several variable selection procedures to give an overview of the existing literature for practitioners. “Let the data speak for themselves” has become the motto of many applied researchers since the number of...
This paper addresses the multi-sensor fusion target tracking problem based on maximum mixture correntropy in non-Gaussian noise environments exclusively using Doppler measurements. As Doppler measurements are non-linear, a statistical linear regressi...
Nowadays, image analysis has a relevant role in most scientific and research areas. This process is used to extract and understand information from images to obtain a model, knowledge, and rules in the decision process. In the case of biological area...
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