When building a predictive model for predicting a clinical outcome using machine learning techniques, the model developers are often interested in ranking the features according to their predictive ability. A commonly used approach to obtain a robust...
Accurate detection and isolation of possible faults are indispensable for operating complex industrial processes more safely, effectively, and economically. In this paper, we propose a fault isolation method for steam boilers in thermal power plants...
Prioritising properties for early review in dense urban renewal areas is a spatial multi-criteria decision problem in which physical condition, accessibility, environmental quality, and hazard exposure must be weighed before formal appraisal. This st...
Understanding streamflow dynamics in watersheds affected by human activity and climate variability is important for sustainable water and environmental resource management. This study evaluates the vulnerability of Alabama watersheds to anthropogenic...
In this article, we propose a tree-structured method for either complete or partial rank data that incorporates covariate information into the analysis. We use conditional independence tests based on hierarchical log-linear models for three-way conti...
Background and Objectives: The issue of a missing variable precludes the external validation of many prognostic models. For example, the Liverpool score predicts the survival of patients undergoing surgical therapy for colorectal liver metastases, bu...
Mechanically recycled cotton is heterogeneous, and nep counts obtained from different analytical platforms may not be numerically interchangeable. This study provides a preliminary cross-platform comparison of five industrial batches selected in the...
Corn (Zea mays L.) yield productivity is driven by a multitude of factors, specifically genetics, environment, and management practices, along with their corresponding interactions. Despite continuous monitoring through proximal or remote sensors and...
The self-to-other model of empathy (SOME) states that a key reason for the empathic deficiency in autistic individuals is the imbalance of the self–other switch. The existing interventions of theory of mind contain training of self–other...
Two-phase sampling is an effective sampling approach that is useful in sample surveys when prior auxiliary information is not available. When two variables have an association, the ranks of the auxiliary variable are proportional to the study variabl...
Traditional DEA models can neither effectively handle fuzzy random variables nor achieve a complete ranking of decision-making units (DMUs). Based on the conventional fuzzy stochastic DEA model, this study introduces an exponential distribution exten...
Feature selection is a critical step in regression problems where a large number of continuous explanatory variables explain the same target through different dependency structures. Classical filters may remain sensitive to a single form of dependenc...
To estimate the finite population variance of the study variable, this paper proposes an improved class of efficient estimators using different transformations. When both the minimum and maximum values of the auxiliary variable are known and the rank...
This article suggests an improved class of efficient estimators that use various transformations to estimate the finite population variance of the study variable. These estimators are particularly helpful in situations where we know about the minimum...
A system of simultaneous multi-variable nonlinear equations can be solved by Newton’s method with local q-quadratic convergence if the Jacobian is analytically available. If this is not the case, then quasi-Newton methods with local q-superline...
Climate variabilities over the period of 80 years (1930–2010) are analyzed by the combined use of divergence measures and rank correlation. First, on the basis of a statistical linguistics procedure, the m-th order differences of the monthly me...
We develop an energy-stable variable-step BDF2-based scalar auxiliary variable (SAV) finite element scheme for a droplet thin-film coarsening model with a Lennard–Jones singular potential. The method uses continuous piecewise linear finite elem...
21 April 2020
The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients cho...
An efficient linearization method for solving a system of nonlinear equations was developed, showing good stability and convergence properties. It uses an unconventional and simple strategy to improve the performance of classic methods by a full-rank...
In real applications, obtained depth images are incomplete; therefore, depth image inpainting is studied here. A novel model that is characterised by both a low-rank structure and nonlocal self-similarity is proposed. As a double constraint, the low-...
Gaussian mixture model (GMM) has been one of the most representative models for hyperspectral unmixing while considering endmember variability. However, the GMM unmixing models only have proper smoothness and sparsity prior constraints on the abundan...
Selecting the relevant covariates in high-dimensional panel data remains a central challenge in applied econometrics. Conventional fixed effects and random effects models are not designed for systematic variable selection under model uncertainty. In...
Despite ample interest in the potential consequences of work engagement over the last two decades, the question of whether work engagement predicts proximal and more distal career-related outcomes has gained surprisingly little attention. Using Conse...
Cross-efficiency evaluation is an effective methodology for discriminating among a set of decision-making units (DMUs) through both self- and peer-evaluation methods. This evaluation technique is usually used for data envelopment analysis (DEA) model...
The sustainable third-party reverse logistics provider (3PRLP) selection, as the core of sustainable supply chain management, has become paramount in research nowadays. In the actual evaluation process, the decision makers may hesitate in a few lingu...
Fusing spatial observations from sensors with heterogeneous error characteristics is a persistent challenge in geostatistics. Classical kriging assumes a Gaussian likelihood for all observations, an assumption that fails when sensors exhibit one-side...
To the on-site nursing staff or field management in prehospital emergency care, it seems baffling to conduct more targeted checklist tests for a specific disease. To address this problem, we proposed a decision support method for prehospital emergenc...
In this paper, we propose and compare new methodologies for ranking the importance of variables in productive processes via an adaptation of OneClass Support Vector Machines. In particular, we adapt two methodologies inspired by the machine learning...
In order to test within-group homogeneity for numerical or ordinal variable groupings, we have introduced a family of discrete probability distributions, related to the Gini mean difference, that we now study in a deeper way. A member of such a famil...
Flexible Manufacturing Systems (FMSs) provide a competitive edge in the ever-evolving manufacturing landscape, offering the agility to swiftly adapt to changing customer demands and product lifecycles. Nevertheless, the complex and interconnected nat...
With the gradual decline in conventional oil and gas production growth, unconventional natural gas has become a strategic alternative for hydrocarbon supply. Coal-rock gas (CRG) represents a deep unconventional gas resource with huge potential. Major...
The concept of ranked sparsity, originally introduced in the context of penalized regression, arises in modeling applications when an expected disparity exists in the quality of information between different feature sets. Its presence can cause tradi...
A long-standing challenge for the structural health monitoring (SHM) community is the masking effect of environmental variability, typically addressed by orthogonal projection (OP)-based data normalization to isolate the influence of environmental va...
This article presents a new set of estimators designed to estimate the finite population variance of a study variable in two-phase sampling. These estimators utilize the information about extreme values and ranks of an auxiliary variable. Through a f...
Drought remains a phenomenal disaster of critical concerns in West Africa, particularly within the Niger River Basin, due to its insidious, multifaceted, and long-lasting nature. Its continuous severe impacts on communities, combined with the limitat...
Contemporary biological assemblage composition and biodiversity are often shaped by a range of natural environmental factors, human disturbances, and their interactions. It is critical to disentangle the effects of individual natural variables and hu...
The problem of extracting bearing weak fault features under variable-speed conditions with strong background noise interference remains challenging due to the limitations of existing feature extraction methods. These methods, especially those that re...
The design optimization of electromechanical linear actuators (EMLAs) is challenged by coupled tribological, thermal, and dynamic effects. Such interactions can violate the additivity assumptions of compact orthogonal designs. Factor ranking may beco...
Wind power forecasting techniques have received substantial attention recently due to the increasing penetration of wind energy in national power systems. While the initial focus has been on point forecasts, the need to quantify forecast uncertainty...
Susceptibility mapping represents a modern tool to support forest protection plans and to address fuel management. With the present work, we continue with a research framework developed in a pioneristic study at the local scale for Liguria (Italy) an...
This study tackles interobserver variability with respect to specialty training in manual segmentation of non-small cell lung cancer (NSCLC). Four readers included for segmentation are: a data scientist (BY), a medical student (LS), a radiology train...
Previous studies have demonstrated that individuals with internet gaming disorder (IGD) display abnormal autonomic activities at rest and during gameplay. Here, we examined whether and how in-game autonomic activity is modulated by human characterist...
In high-dimensional gene expression data analysis, the accuracy and reliability of cancer classification and selection of important genes play a very crucial role. To identify these important genes and predict future outcomes (tumor vs. non-tumor), v...
This study introduces a non-parametric methodology for estimating expected frequencies of defaults and other credit events. The methodology allows for an independent estimation of a credit-quality variable, referred to as a default rank variable. In...
Feature screening is an important and challenging topic in current class-imbalance learning. Most of the existing feature screening algorithms in class-imbalance learning are based on filtering techniques. However, the variable rankings obtained by v...
The concept of sustainability has become more important, especially as a result of the depletion of energy resources and increasing environmental concerns. UI GreenMetric ranks universities based on sustainability, environmental, and energy concerns,...
This paper proposes the use of a goal programming model for the objective ranking of universities. This methodology has been successfully used in other areas to analyze the performance of firms by focusing on two opposite approaches: (a) one favourin...
The aim of this study is to analyse the variables related to knowledge (Talent Management and Training) as a source of human capital in the companies listed in the ranking of the most attractive organisations within the Spanish labour market, publish...
A critical determinant of infectivity and virulence of the most infectious and or lethal variants of concern (VOCs): Wild Type, Delta and Omicron is related to the binding interactions between the receptor-binding domain of the spike and its host rec...
The digital economy, driven by innovative technologies and artificial intelligence (AI), is transforming economic systems and increasing the demand for accurate assessments of digital competitiveness. This study addresses the inconsistencies in count...
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