305 Results Found

Identification of the key environmental indicators (KEIs) from a large number of environmental variables is important for environmental management in tidal flat reclamation areas. In this study, a modified principal component analysis approach (MPCA)...

Data distillation is an emerging research area, attracting the attention of machine learning (ML) and big data scientists and experts. The main goal of a distillation approach is to generate a compact dataset that preserves the essential characterist...

This paper presents a computationally efficient haze removal and image enhancement methods. The major contribution of the proposed research is two-fold: (i) an accurate atmospheric light estimation using principal component analysis, and (ii) learnin...

In coastal saline–alkali regions, the intrusion of saline water exacerbates the nutrient depletion in the plow layer, posing a significant challenge to agricultural productivity. Given the limited understanding of soil fertility in these areas...

Classical time series methods are widely employed to analyze linear time series with a limited number of observations; however, their effectiveness relies on several strict assumptions. In contrast, artificial neural networks are particularly suitabl...

The effects of hesperidin and different casings on pH, moisture content, water-holding capacity, and total viable count (TVC) of sausages stored for 171 days were evaluated by principal component analysis (PCA) and discriminant analysis (DA). Sausage...

The quality changes of golden pompano fillets in air packaging (AP) and modified atmosphere packaging (MAP) with 30% CO2/70% N2, 50% CO2/50% N2, and 70% CO2/30% N2 were evaluated under superchilling (−3 °C). The results showed that the whit...

Multi-focus image fusion (MIF) uses fusion rules to combine two or more images of the same scene with various focus values into a fully focused image. An all-in-focus image refers to a fully focused image that is more informative and useful for visua...

This research aimed to investigate heat shock proteins in the tomato genome through the analysis of amino acids. The highest length among sequences was found in seq19 with 3534 base pairs. This seq19 was reported and contained a family of proteins kn...

In recent decades several methods have been developed to extract coastlines from remotely sensed images. In fact, this is one of the principal fields of remote sensing research that continues to receive attention, as testified by the thousands of sci...

This study aims to investigate the atmospheric conditions and human thermal comfort related to extreme heat in Rio de Janeiro during the first quarter of 2024. The dataset includes meteorological data from the A636-Jacarepaguá station of INMET...

The existing pansharpening methods applied to recently obtained satellite data can produce spectral distortion. Therefore, quality assessments should be performed to address this. However, quality assessment of the whole image may not be sufficient,...

This study investigated the internal stress distribution of unidirectional fiber-reinforced plastics (UD-FRP) at the micro level using principal component analysis (PCA). The composite material was simulated using a representative volume element mode...

Quartz crystal nanobalance (QCN) sensors are considered as powerful mass-sensitive sensors to determine materials in the sub-nanogram level. In this study, a singlepiezoelectric quartz crystal nanobalance modified with polystyrene was employed to det...

Recently, Jia et al. employed the index, modified remote sensing ecological index (MRSEI), to evaluate the ecological quality of the Qaidam Basin, China. The MRSEI made a modification to the previous remote sensing-based ecological index (RSEI), whic...

The detection of drowsiness while driving plays a vital role in ensuring road safety. Existing detection methods need to reduce external interference and sensor intrusiveness, and their algorithms must be modified to improve accuracy, stability, and...

In this study, the quality of sediment and surface water in two natural wetlands, Paca and Tragadero, in the central region of Peru was evaluated using pollution indices, including the geoaccumulation index, pollutant load index, modified pollution d...

In this article, the authors focus on the introduction of a hybrid method for risk-based fault detection (FD) using dynamic principal component analysis (DPCA) and failure method and effect analysis (FMEA) based Bayesian networks (BNs). The FD proble...

Semi-flexible pavement material (SFPM) combines the advantages and avoids the disadvantages of asphalt concrete flexible pavement and cement concrete rigid pavement. However, due to the problem of interfacial strength of composite materials, SFPM is...

Independent component analysis (ICA) is one of the most effective approaches in extracting independent signals from a global navigation satellite system (GNSS) regional station network. However, ICA requires the involved time series to be complete, t...

Studies on the geometry variation-related compressor uncertainty quantification (UQ) have often used dimension reduction methods, such as the principal component analysis (PCA), for the modeling of deviations. However, in the PCA method, the main eig...

Fava bean (Vicia faba L.) is a promising source of proteins that can be potentially used as nutritional and/or functional agents for industrial food applications. Fava ingredients are industrially produced, modified, and utilized for food application...

We live in the era of large data analysis, where processing vast datasets has become essential for uncovering valuable insights across various domains of our lives. Machine learning (ML) algorithms offer powerful tools for processing and analyzing th...

The objective of this work was to create an all-solid-state potentiometric bioelectronic tongue with an array of polymeric membrane-based sensors, which could then be used in the dairy sector. Membranes were modified with gold nanoparticles, and enzy...

Principal component analysis (PCA) has been widely used in metabolomics. However, it is not always possible to detect phenotype-associated principal component (PC) scores. Previously, we proposed a smoothed PCA for samples acquired with a time course...

Since the 1980s, Mexico has undergone profound economic and political transformations grounded in neoliberalism, reflected in the opening of the agri-food sector. As a result, imports of powdered milk increased, consolidating a corporate agri-food re...

This paper aims to improve the predictability of extreme droughts in China by identifying their relationship with atmospheric teleconnection patterns (ATPs). Firstly, a core drought region (CDR) is defined based on historical drought analysis to inve...

In this paper, we propose a new scheme for probabilistic power flow in networks with renewable power generation by making use of a data clustering technique. The proposed clustering technique is based on the combination of Principal Component Analysi...

In order to guide consumers in their purchase of a new fragrance, one approach is to visualize the spectrum of men’s or women’s fragrances on a two-dimensional plot. One of such sensory maps available is the Hexagon of Fragrance Families....

Starch in its pure form can be used as a functional component of numerous food products; however, much better results both in terms of technological and economical aspects are obtained with the use of modified starches. The aim of the work was to est...

The proposed study explores the consistency of the geometrical character of surfaces under scaling, rotation and translation. In addition to its mathematical significance, it also exhibits advantages over image processing and economic applications. I...

Hazelnut skin is a by-product produced from hazelnut processing. It can be used as a nutritional supplement due to its high nutrient values. The purpose of this study was to evaluate the dough properties of refined flour (RF) with the addition of haz...

Management education holds promise for addressing deficiencies in interuniversity science, technology, engineering, and mathematics (STEM), as well as sustainability curricula. Accordingly, we designed, developed, implemented, and longitudinally eval...

Different strategies have been used to degrade the molecular structure of lignins in natural fibers. Both chemical and biological processes can obtain different types of lignins for industrial use. In this study, a variation of the spectral intensity...

A taste sensor with global selectivity can be used to discriminate taste of foods and provide evaluations. Interfaces that could interact with broad food ingredients are beneficial for data collection. Here, we prepared electrochemically reduced grap...

This paper reports the use of nanoparticles (NPs)-modified voltammetric sensors for the rapid determination of glycerol in the presence of ethanol and methanol, which are used in the transesterification reaction of biodiesel production. Two different...

In this paper we present several expert systems that predict the class identity of the modeled compounds, based on a preprocessed spectral database. The expert systems were built using Artificial Neural Networks (ANN) and are designed to predict if a...

The excessive use of power semiconductor devices in a grid utility increases the malfunction of the control system, produces power quality disturbances (PQDs) and reduces the electrical component life. The present work proposes a novel algorithm base...

The low-frequency sea level variability in the South China Sea (SCS) is examined using high-resolution regional ocean model simulations that span the last six decades. The analysis reveals interdecadal oscillations with a periodicity of 12–13 y...

In this work, a new colorimetric sensor based on mesoporous silica nanosphere-modified color-sensitive materials was established for application in monitoring the total volatile basic nitrogen (TVB-N) of oysters. Firstly, mesoporous silica nanosphere...

Huntington’s disease (HD) is an autosomal dominant, incurable neurodegenerative disease caused by mutation in the huntingtin gene (HTT). HTT mutation leads to protein misfolding and aggregation, which affect cells’ functions and structural features....

Properly measuring the complexity of time series is an important issue. The permutation entropy (PE) is a widely used as an effective complexity measurement algorithm, but it is not suitable for the complexity description of multi-dimensional data. I...

A total of 83 third trimester pregnant women were recruited to examine the role of pre-pregnancy versus late-pregnancy physical activity on maternal insulin resistance. Principal component analysis plots demonstrated a distinction between the high an...

We address the sensitive detection and discrimination of gases impacting the environment, such as CH4, NH3, SO2, and CO, using a sensor array and aided by principal component analysis (PCA). A 32-element chemiresistive sensor array consisting of nine...

Direct sequence spread spectrum (DSSS) signals are now widely used in air and underwater acoustic communications. A receiver which does not know the pseudo-random (PN) sequence cannot demodulate the DSSS signal. In this paper, firstly, the principle...

Accurate forecasting of annual runoff time series is of great significance for water resources planning and management. However, considering that the number of forecasting factors is numerous, a single forecasting model has certain limitations and a...

Hydroxyurea, an oral medication with important clinical benefits in the treatment of sickle cell anemia, can be accurately determined in plasma with a transition metal dichalcogenide-based electrochemical sensor. We used a two-dimensional molybdenum...

Several online principal component analysis (PCA) methodologies exist for data arriving sequentially that focus only on compression risk minimization. Recent work in this realm revolves around minimizing the cost-compression risk, which takes into ac...

Avocado cultivation is displacing traditional coffee production in Veracruz, Mexico. This change modifies the floristic composition and agronomic management (AM), both of which are affected by socioeconomic factors and generate variation in edaphic c...

Cadmium presence in soil is considered a significant threat to human health. Biochar is recognized as an effective method to immobilize Cd ions in different soils. However, obtaining effective and viable biochar to remove elevated Cd from postmining...