Wind energy is a variable energy source with a growing presence in many electrical networks across the world. Wind-speed prediction has become an important tool for many agents involved in energy markets. In this paper, an approach to this problem is...
A data-driven indirect approach for predicting the response of existing structures induced by excavation is hereby proposed based on making full use of monitoring data during excavation, which can predict the deformation history of the research objec...
This paper proposes an RG hyperparameter optimization approach, based on a sequential use of random search (R) and grid search (G), for improving the blood glucose level prediction of boosting ensemble learning models. An indirect prediction of blood...
The management of product quality is a crucial process in factory manufacturing. However, this approach still has some limitations, e.g., depending on the expertise of the engineer in evaluating products and being time consuming. Various approaches u...
Obtaining Radar Cross Section (RCS) data, one of the essential parameters for aircraft design, generally takes a lot of time and cost. Measurement time and accuracy of measurement results may be affected depending on the RCS measurement method and en...
Annual river discharge is a critical variable for water resources planning and management. Tree rings are widely used to reconstruct annual discharge, but errors can be large when tree growth fails to respond commensurately to hydrologically importan...
The present study was designed to examine the direct and indirect contributions of parenting daily hassles and approaches to children’s externalizing and internalizing behavior problems during the COVID-19 pandemic. The sample for this study wa...
Accurately estimating and forecasting evapotranspiration is one of the most important tasks to strengthen water resource management, especially in desert areas such as La Yarada, Tacna, Peru, a region located at the head of the Atacama Desert. In thi...
This paper presents the results of a study on data preprocessing and modeling for predicting corrosion in water pipelines of a steel industrial plant. The use case is a cooling circuit consisting of both direct and indirect cooling. In the direct coo...
The demand for personalized medicine in radiotherapy has been met by a surge of mechanistic models offering predictions of the biological effect of ionizing radiation under consideration of a growing number of parameters. We present an extension of o...
The remove–compute–restore (RCR) approach is widely used in local quasi-geoid modeling. However, the classical RCR approach usually does not take into account the noise of the satellite-only global gravity field model (GGM), which may lea...
Model predictive control has become a tremendously popular control method for power converters, notably a modular multilevel converter, owing to the ability to control various objectives at once with a particular cost function and prominent dynamic p...
Experimental data from viscosity measurements of 124 glassy slags were used to drive and develop machine learning models that could be used for direct or indirect viscosity prediction. Samples were categorized according to the content of chemical com...
Traditional maize (Zea mays L.) breeding approaches use directly measured phenotypic performance to make decisions for the next generation of crosses. Indirect assessment of cultivar performance can be utilized using various methods such as genomic p...
Grading is a decisive step in the successful distribution of mangoes to customers according to their preferences for the maturity index. A non-destructive method using near-infrared spectroscopy has historically been used to predict the maturity of f...
Storm surge disasters result in severe casualties and economic losses. Accurate prediction of storm surge water level is crucial for disaster assessment, early warning, and effective disaster management. Machine learning methods are relatively more e...
The number of fault samples for the new nuclear valve is commonly rare; thus, the machine learning algorithm is not suitable for the fault prediction of this kind of equipment. In order to overcome this difficulty, this paper proposes a novel method...
Monitoring of changes in forest biomass requires accurate transfer functions between remote sensing-derived changes in canopy height (ΔH) and the actual changes in aboveground biomass (ΔAGB). Different approaches can be used to accomplish...
The paper describes an approach for indirect data-based assessment and use of user preferences in an unobtrusive sensor-based coaching system with the aim of improving coaching effectiveness. The preference assessments are used to adapt the reasoning...
Airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) have both been demonstrated as reliable sources of information on forest stand inventory attributes. The increasing availability of both datasets provides a means for improving sta...
The increasing traffic on roads poses a significant challenge to the structural integrity of bridges and viaducts. Indirect structural monitoring offers a cost-effective and efficient solution for monitoring multiple infrastructures. The presented wo...
The traditional method of related commodity discovery mainly focuses on direct co-occurrence association of commodities and ignores their indirect connection. Link prediction can estimate the likelihood of links between nodes and predict the existent...
Background: Vaccine hesitancy, associated with medical mistrust, confidence, complacency and knowledge of vaccines, presents an obstacle to the campaign against the coronavirus disease 2019 (COVID-19). The relationship between vaccine hesitancy and c...
Forest fuel loads and structural characteristics strongly affect fire behavior, regulating the rate of spread, fireline intensity, and flame length. Accurate fuel characterization, including disaggregation of the fuel load by size classes, is therefo...
The standard of living has significantly risen along with ongoing economic progress, but CO2 emissions have also been rising. The reduction in CO2 resulting from the daily activities of residents has become a crucial priority for every province. A re...
Soil texture, defined by the proportions of sand, silt, and clay particles in the soil, is one of the most essential physical properties of soil. High-resolution soil texture data can provide critical parameter support for soil hydrological modeling,...
Agriculture accounts for a large percentage of nitrous oxide (N2O) emissions, mainly due to the misapplication of nitrogen-based fertilizers, leading to an increase in the greenhouse gas (GHG) footprint. These emissions are of a direct nature, releas...
20 August 2021
The COVID-19 lockdown increased the day-to-day challenges faced by parents, and thereby may have increased parental burnout risk. Therefore, identifying parental burnout protection factors is essential. This study aimed to assess the protective role...
25 February 2020
An emerging body of literature has implied that perceived social support is known as an upstream element of cognitive health. Various dimensions of perceived social support may have divergent influence on physical and cognitive health in later life....
To control a bioprocess, the determination of the current state is necessary. Most state variables require substantial effort and time to measure or sometimes are not measurable at all, and a direct measurement is not always an option. Instead, an in...
Afforestation is one of the most effective processes for removing carbon dioxide from the atmosphere and combating global warming. Landsat data and machine learning approaches can be used to map afforestation (i) indirectly, by constructing two maps...
This study tested the potential of parametric and nonparametric regression modeling utilizing multispectral data from two different unoccupied aerial vehicles (UAVs) as a tool for the prediction of and indirect selection of grain yield (GY) in barley...
The 1960s was an exciting era for atmospheric predictability research: a finite predictability of the atmosphere was uncovered using Lorenz’s models and the well-acknowledged predictability limit of two weeks was estimated using a general circu...
Most research on factors related to physical child abuse risk rely heavily on direct self-report measures, which is a methodological strategy susceptible to participant response distortions. Such methodological reliance obfuscates the interpretations...
This study investigates how topic-specific expression by women delivery riders on digital platforms predicts their community engagement, emphasizing the mediating role of self-disclosure and the moderating influence of cognitive and emotional languag...
Airborne laser scanner (ALS) data are used to map a range of forest inventory attributes at operational scales. However, when wall-to-wall ALS coverage is cost prohibitive or logistically challenging, alternative approaches are needed for forest mapp...
Potatoes, as the world’s fourth-largest staple crop, are vital for global food security. Efficient methods for assessing yield and quality are essential for policy-making and optimizing production. Traditional yield assessment techniques remain...
In response to the need for multiple complete bearing degradation datasets in traditional deep learning networks to predict the impact on individual bearings, a novel deep learning-based rolling bearing remaining life prediction method is proposed in...
Reinforced-concrete shear walls stand as the primary construction method for urban residential structures in northern China. In alignment with national carbon neutrality goals for residential construction, this study developed a set of prediction mod...
The adoption of Interior Permanent Magnet Synchronous Motor (IPMSM) in Battery Electric Vehicle (BEV) and Plug-in Hybrid Electric Vehicle (PHEV) drives the need for innovative approaches to improve control performance and power conversion efficiency....
This study examined the impact of fear and anxiety on the intent to take the first COVID-19 booster vaccine. The objective of this study is to provide guidance for messaging campaigns of public health practitioners. A survey approach provided insight...
Smart data selection can quickly sieve valuable information from initial data. Doing so improves the efficiency of analyzing situations to aid in better decision-making. Past methods have mostly been based on expert experience, which may be subjectiv...
In the field of agriculture, measuring the leaf area is crucial for the management of crops. Various techniques exist for this measurement, ranging from direct to indirect approaches and destructive to non-destructive techniques. The non-destructive...
Accurate determination of soil-water characteristic curve (SWCC) is of immense importance for understanding the mechanical behavior of unsaturated soils. Due to the difficulty and long duration of experimental procedures, it is of great significance...
The indirect tensile strength of two geomaterials treated with variable cement contents, degrees of compaction and water contents were tested after several curing times. A statistical review through an analysis of variance allows for identifying the...
Background: Scientific evidence and everyday experience show that sleep disturbances and self-regulation as a proxy of stress reactivity are linked. Particular personality traits such as neuroticism, internalizing and externalizing problems are also...
This paper presents a comprehensive analysis comparing the implementation of electric and diesel buses for public transport services in the low-density area of the City of Jastrebarsko in Croatia. It utilizes a multidimensional approach and incorpora...
in the prediction of quantiles of daily Standard&Poor’s 500 (S&P 500) returns we consider how to use high-frequency 5-minute data. We examine methods that incorporate the high frequency information either indirectly, through combining forecas...
The radiosensitivity of biological systems is strongly affected by the system oxygenation. On the nanoscopic scale and molecular level, this effect is considered to be strongly related to the indirect damage of radiation. Even though particle track r...
Mesoscale eddies play a critical role in sea navigation and route planning, yet traditional prediction methods have often overlooked their spatial relationships, relying on indirect approaches to capture their distribution across extensive maps. To a...
of 6