With increasingly serious environmental problems caused by the improvement in people’s living standards, the number of cars has increased sharply in recent years, which directly leads to the continuous increase in the concentration of NO2 in th...
NO2 is a toxic gas mainly generated by combustion processes, such as vehicle emissions and industrial activities. It is a key contributor to smog, acid rain, ground-level ozone, and particulate matter, all of which pose serious risks to human health...
Metal–organic frameworks (MOFs) have broad application prospects in the development of efficient, sensitive and single select gas sensors. However, in order to construct a chemical resistance gas sensor based on MOFs, the problem of poor conduc...
Thin films are being used more and more in gas sensing applications, relying on their high surface area to volume ratio. In this study, ZnO thin film was produced through a thermal aerosol spraying and chemical vapor deposition (spray-CVD) process at...
This study explores the surface chemistry and electrical responses of ultra-high-sensitivity SnO2 MEMS arrays to enable a novel sequential detection methodology for detecting nitrogen dioxide (NO2) and ethanol (C2H5OH) as a route to achieve selective...
Owing to high electrical conductivity, layered structure, and abundant surface functional groups, transition metal carbides/nitrides (MXenes) have received enormous interest in the field of gas sensors at room temperature. In this work, we synthesize...
Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a mu...
Recently, gene selection has played an important role in cancer diagnosis and classification. In this study, it was studied to select high descriptive genes for use in cancer diagnosis in order to develop a classification analysis for cancer diagnosi...
Effective gene feature selection is critical for enhancing the interpretability and accuracy of genetic data analysis, particularly in the realm of disease prediction and precision medicine. Most evolutionary feature selection algorithms tend to beco...
This article proposes a dual-band, frequency- and polarization-selective surface. Multiple resonant modes are introduced using the U-shaped resonator with a ground via to achieve dual-band responses and polarization selectivity. Two symmetrically gro...
A unique line of Holstein cattle has been maintained without selection in Minnesota since 1964. After many generations, unselected cattle produce less milk, but have better reproductive performance and health traits when compared with contemporary co...
Resource utilization strategies of avian migrants are a major concern for conservation and management. Understanding seasonal habitat selection by migratory birds helps us explain the ongoing continental declines of migratory bird populations. Our ob...
A computational explanation of how visual attention, interpretation of visual stimuli, and eye movements combine to produce visual behavior, seems elusive. Here, we focus on one component: how selection is accomplished for the next fixation. The popu...
The aim of this paper is to review up-to-date recent results in the field of star selection principles, a rapidly growing area of topology, and to present a few new results.
Genomic selection (GS) is an efficient method to improve genetically economic traits. Feature selection is an important method for GS based on whole-genome sequencing (WGS) data. We investigated the prediction performance of GS of milk production tra...
Feature selection metrics are commonly used in the machine learning pipeline to rank and select features before creating a predictive model. While many different metrics have been proposed for feature selection, final models are often evaluated by ac...
In organic synthesis, it is important to control the selectivity target product with high purity and reduce the cost of energy and equipment for separation. This study investigated supported gold catalysts on biochar-modified titanate-based nanofiber...
In this paper, a highly selective quad-band frequency selective surface (FSS) with ultra-wideband rejection is presented. The proposed FSS structure was developed by cascading five metallic layers by three thin dielectric substrates. The five metalli...
Feather pecking (FP) is a longstanding serious problem in commercial flocks of laying hens. It is a highly polygenic trait and the genetic background is still not completely understood. In order to find genomic regions influencing FP, selection signa...
In the shipping network optimization, the feeder liner companies not only need to decrease the operation cost by comprehensively optimizing the route, schedule, and fleet but also try to increase the operation income by attracting more shippers, with...
A genetic algorithm (GA) contains a number of genetic operators that can be tweaked to improve the performance of specific implementations. Parent selection, crossover, and mutation are examples of these operators. One of the most important operation...
V0.5/Pt/TiO2 tandem catalysts exhibit both an outstanding low-temperature NH3 conversion rate and high N2 selectivity in NH3-SCO reactions, but the mechanism of high N2 selectivity remains unclear. In this work, Vx/Pt/TiO2 tandem catalysts were synth...
The prediction of genetic gain from artificial selection in a trait is important in plant and animal breeding. Lush’s classical breeder’s equation (BE) is widely used for this purpose, although it is also applied to predicting evolution u...
This research focuses on the manufacturing of a glass interposer that has gone through glass via (TGV) connection holes. Glass has unique properties that make it suitable for 3D integrated circuit (IC) interposers, which include low permittivity, hig...
Machine learning algorithms are often used to model and predict animal habitat selection—the relationships between animal occurrences and habitat characteristics. For broadly distributed species, habitat selection often varies among populations and r...
This paper develops a new approach to band subset selection (BSS) for hyperspectral image classification (HSIC) which selects multiple bands simultaneously as a band subset, referred to as simultaneous multiple band selection (SMMBS), rather than one...
Hyperspectral sensing, measuring reflectance over visible to shortwave infrared wavelengths, has enabled the classification and mapping of vegetation at a range of taxonomic scales, often down to the species level. Classification with hyperspectral m...
A compact high-selective band-pass frequency selective surface (FSS) with the unit cell less than λ/7 is presented. For the simulation of the structure, the multilevel Green’s function interpolation method (MLGFIM) using Floquet theory i...
Natural selection is commonly seen not just as an explanation for adaptive evolution, but as the inevitable consequence of “heritable variation in fitness among individuals”. Although it remains embedded in biological concepts, such a formalisation m...
Bi-directional selection for increased and decreased 56-day body weights (BW56) has been applied to two lines of White Plymouth Rock chickens—the Virginia high (HWS) and low (LWS) body weight lines. Correlated responses have been observed, incl...
Feature selection (FS) has attracted the attention of many researchers in the last few years due to the increasing sizes of datasets, which contain hundreds or thousands of columns (features). Typically, not all columns represent relevant values. Con...
This study proposes an alternate data extraction method that combines three well-known feature selection methods for handling large and problematic datasets: the correlation-based feature selection (CFS), best first search (BFS), and dominance-based...
The objective of this paper is to pursue an intuitive idea: for a consumer who represents an “unfavorable” health risk but an “excellent risk” as a driver, a multi-peril policy could be associated with a reduced selection effo...
Compared to multi-spectral imagery, hyperspectral imagery has very high spectral resolution with abundant spectral information. In underwater target detection, hyperspectral technology can be advantageous in the sense of a poor underwater imaging env...
In the field of geomatics, artificial intelligence (AI) and especially machine learning (ML) are rapidly transforming the field of geomatics with respect to collecting, managing, and analyzing spatial data. Feature selection as a building block in ML...
Band selection is an important step in the dimensionality reduction processing of hyperspectral images and is highly important for eliminating redundant spectral information and reducing computational costs. In recent years, band selection methods ba...
When mutational pressure is weak, the generative process of protein evolution involves explicit probabilities of mutations of different types coupled to their conditional probabilities of fixation dependent on selection. Establishing this mechanistic...
Sustainability assessments can play an important role in decision making. This role starts with selecting appropriate methods for a given situation. We observed that scientists, consultants, and decision-makers often do not systematically perform a...
Reproductive performance is an important trait in poultry production. Traditional methods of improving reproductive traits can only use recorded information from females, making it difficult to effectively assess the reproductive potential of males....
Model selection and model averaging are popular approaches for handling modeling uncertainties. The existing literature offers a unified framework for variable selection via penalized likelihood and the tuning parameter selection is vital for consist...
26 August 2014
The estrogen receptors (ERs) are a group of versatile receptors. They regulate an enormity of processes starting in early life and continuing through sexual reproduction, development, and end of life. This review provides a background and structural...
This paper presents an approach to band selection fusion (BSF) which fuses bands produced by a set of different band selection (BS) methods for a given number of bands to be selected, nBS. Since each BS method has its own merit in finding the desired...
Nodulin 26-like intrinsic proteins (NIPs) of the plant aquaporin family majorly facilitate the transport of physiologically relevant solutes. The present study intended to investigate how substrate selectivity in grapevine NIPs is influenced by the a...
In recent times, with the advancement in technology and revolution in digital information, networks generate massive amounts of data. Due to the massive and rapid transmission of data, keeping up with security requirements is becoming more challengin...
The No Free Lunch Theorem tells us that no algorithm can beat other algorithms on all types of problems. The algorithm selection structure is proposed to select the most suitable algorithm from a set of algorithms for an unknown optimization problem....
This paper proposes a feature selection (FS) approach, namely, correlation and fitness value-based feature selection (CFFS). CFFS is an improvement feature selection approach of correlation-based feature selection (CFS) for the common failure cases o...
Design of low-density SNP chips provides an opportunity for wide application of genomic selection at lower cost. A novel strategy referred to as the “block-free” method is proposed in this study to select a subset of SNPs from a high-dens...
We introduce a novel Bayesian approach for feature (variable) selection using Gaussian process regression, which is crucial for enhancing interpretability and model regularization. Our method employs nearest neighbor Gaussian processes as scalable ap...
Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). To evaluate FSAs effectively, co...
As a cellular network of the fifth generation (5G) is commercialized, mobile devices and data throughput have rapidly increased. According to the spatial density for communication increases, the nodes of cell are overloaded. Therefore, the heterogene...
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