The entropy-weighting method (EWM) and variation coefficient method (VCM) are two typical diversity-based weighting methods, which are widely used in risk assessment and decision-making for natural hazards. However, for the attributes with a specific...
Accurate uncertainty estimation in unlabeled data represents a fundamental challenge in active learning. Traditional deep active learning approaches suffer from a critical limitation: uncertainty-based selection strategies tend to concentrate excessi...
Fixed-wing unmanned aerial vehicles, with their advantages of long endurance and substantial payload capacity, are poised to be a key platform for the future low-altitude economy. However, the challenge of achieving precise attitude tracking control...
Identifying noise sources in exceedance-triggered audio is essential for targeted source tracing and sustainable urban social noise governance. While accurate models require massive labeled data, the acoustic complexity, high redundancy, and imbalanc...
Supplier selection is an important decision-making link in bidding activity. When overall scores of several suppliers are similar, it is hard to obtain an accurate ranking of these suppliers. Applying the Diversity Factors Method (Diversity Factors M...
This study proposes super efficiency (SE) as an efficient analytical method for evaluating the performance of energy research projects. Because the SE method is based on data envelopment analysis (DEA), it is free from the difficulty of weighting out...
Optimisation-based methods are enormously used in the field of data classification. Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real worl...
The implementation of water diversion projects will exert different influences on upstream water offering areas and the downstream water receiving areas. In order to effectively promote the coordinated development of the two regions, a comprehensive...
To select a biomass crop type of the highest sustainability for the purpose of producing biofuel is recognized as a problem of the multi-criteria decision analysis (MCDA) type, as it comprises different conflicting criteria. To effectively address th...
In recent times, the issues of geodiversity assessment and mapping have been subject of great attention, and many evaluation methodologies, either quantitative or qualitative, have been developed. In this research, a first assessment of geodiversity...
Although the cost-reference particle filter (CRPF) has a good advantage in solving the state estimation problem with unknown noise statistical characteristics, its estimation accuracy is still affected by the lack of particle diversity and sensitivit...
26 April 2022
We aimed to understand adults’ self-weighing behaviors and explore significant predictors of body mass index (BMI) accuracy based on self-reported height and weight in a diverse sample of community-dwelling adults. Methods: In this cross-sectio...
Minimum dietary diversity for women of reproductive age (MDD-W) was validated as a population-level proxy of micronutrient adequacy, with indicator data collection proposed as either list-based or open recall. No study has assessed the validity of th...
The multi-attribute and group-decision problem in the selection of a construction diversion scheme for large hydropower projects often involves multi-decision subjects and schemes. Each scheme includes multiple attributes, and the attribute values an...
Motion-capture data provide high accuracy but are difficult to obtain, necessitating dataset augmentation. To our knowledge, no prior study has investigated few-shot generative models for motion-capture data that address both quality and diversity. W...
We propose a convolutional neural network (CNN) based method, namely phase diversity convolutional neural network (PD-CNN) for the speed acceleration of phase-diversity wavefront sensing. The PD-CNN has achieved a state-of-the-art result, with the in...
This research offers a solution to a highly recognized and controversial problem within the composite indicator literature: sub-indicators weighting. The research proposes a novel hybrid weighting method that maximizes the discriminating power of the...
In Global Navigation Satellite System (GNSS)-denied environments, navigation using signals of opportunity (SOP) from Low Earth Orbit (LEO) satellites is considered a feasible alternative. Compared with single-constellation systems, multiple-constella...
The flow analysis of the forebay of a lateral intake pumping station with asymmetrical operating pumps was carried out with a realizable k-ε turbulent model and SIMPLEC (Semi Implicit Method for Pressure Linked Equations Consistent) algorithm...
Background/Objectives: This study characterized genetic diversity in a Chongming white goat conservation population and identified loci associated with growth and body conformation. Methods: Whole-genome resequencing of 350 goats was used to assess g...
To assess a subject with multiple factors or attributes, a comprehensive evaluation index, or say a composite indicator, is often constructed to make a holistic judgement. The key problem is to assign weights to the factors. There are various weighti...
The Proportional Hazards Model (PHM) under a Condition-Based Maintenance (CBM) policy is used by asset-intensive industries to predict failure rate, reliability function, and maintenance decisions based on vital covariates data. Cox’s partial l...
Multi-objective combinatorial optimization problems (MOCOPs) are designed to identify solution sets that optimally balance multiple competing objectives. Addressing the challenges inherent in applying deep reinforcement learning (DRL) to solve MOCOPs...
Online auctions attract not only legitimate businesses trying to sell their products but also fraudsters wishing to commit fraudulent transactions. Consequently, fraudster detection is crucial to ensure the continued success of online auctions. This...
Fixed indicator weights cannot fully capture changes in governance priorities as wind–sand hazards intensify. Using the Xinjiang section of the G30 Lianhuo Expressway as a case study, this study classified wind–sand events into three scen...
In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enh...
Renewable energy communities are emerging as key players in the sustainable energy transition, yet there is a lack of systematic approaches for evaluating the digital tools that support their development and operation. This study proposes a comprehen...
Creating an effective deep learning technique for accurately diagnosing leak signals across diverse environments is crucial for integrating artificial intelligence (AI) into the power plant industry. We propose an automatic weight redistribution ense...
Complex decision-making often involves numerous alternatives and diverse criteria, making it difficult to set clear priorities under resource constraints. This study proposes a two-layer hierarchical decision model that structures the process into se...
The limited availability of in-situ images of the lunar surface significantly hinders the performance improvement of intelligent algorithms, such as scientific target point-of-interest recognition. To address the low diversity of images generated by...
Particle filters have been widely used in dim and small target tracking, which plays a significant role in navigation applications. However, their characteristics, such as difficulty of expressing features for dim and small targets and lack of partic...
Background/Objectives: This study investigated how phase-specific dietary strategies and weight regulation influence gut microbiota composition and diversity in competitive weightlifters. Particular emphasis was placed on integrating energy intake, m...
We propose a hybrid intelligent methodology for forecasting outcomes in complex human-centered systems characterized by uncertainty and reliance on expert knowledge. The framework integrates fuzzy cognitive maps (FCMs), a novel Least-Influence Method...
Homologous sequence alignments contain important information about the constraints that shape protein family evolution. Correlated changes between different residues, for instance, can be highly predictive of physical contacts within three-dimensiona...
The use of non-destructive commercial near-infrared (NIR) spectroscopy to estimate Brix% was verified using all samples of cherry tomato ‘TY Chika’, currant tomato ‘Microbeads’, and the M&S or market-purchased and suppleme...
The knapsack problem is a typical bi-objective combinatorial optimization issue, wherein maximizing the value of the packed items is achieved concurrently with minimizing the weight of the load. Due to the conflicting objectives of the knapsack probl...
Typical in silico models for ecotoxicology focus on a few endpoints, but there is a need to increase the diversity of these models. This study proposes models using the NOEC for the harlequin fly (Chironomus riparius) and EC50 for swollen duckweed (L...
Indoor positioning based on the received signal strength (RSS) of the WiFi signal has become the most popular solution for indoor localization. In order to realize the rapid deployment of indoor localization systems, solutions based on crowdsourcing...
11 February 2023
Background: The present study aimed to evaluate microbial diversity, taxonomic profiles, and fecal short chain fatty acid (SCFA) in female patients with fibromyalgia syndrome (FMS). Methods: Forty participants (19 patients with FMS and 21 controls) w...
Domain adaptation-based models for fault classification under variable working conditions have become a research focus in recent years. Previous domain adaptation approaches generally assume identical label spaces in the source and target domains, ho...
Decomposition-based evolutionary algorithms are popular with solving multi-objective optimization problems. It uses weight vectors and aggregate functions to keep the convergence and diversity. However, it is hard to balance diversity and convergence...
Over the past decade, significant advancements have been made in low-light image enhancement (LLIE) methods due to the robust capabilities of deep learning in non-linear mapping, feature extraction, and representation. However, the pursuit of a unive...
Background: Obesity is a major global public health issue with no fully satisfactory solutions. Most nutritional interventions rely on caloric restriction, with varying degrees of success. Very low-calorie ketogenic diets (VLCKD) have demonstrated ra...
Background and Aim: Underweight young adult women are vulnerable to health risks such as menstrual disorders and vitamin deficiencies. Because few seek medical care for low body weight, the underlying causes remain unclear. This study aimed to examin...
In the field of ensemble learning, bagging and stacking are two widely used ensemble strategies. Bagging enhances model robustness through repeated sampling and weighted averaging of homogeneous classifiers, while stacking improves classification per...
Objectives: The aim of this study is to assess the influence of diabetes mellitus on the microbial flora involved in root canal infections through a comparative analysis with that of systemically healthy individuals. Methods: A total of 39 participan...
This paper addresses the problem of target localization in a distributed waveform diverse array radar system, exploiting the technique of sparse reconstruction. At the configuration stage, the distributed radar system consists of two individual Frequ...
In response to the limited available information during the initial stages of coal spontaneous combustion and the influence of decision makers’ risk preferences on decision-making, this paper proposes an emergency decision-making method for coa...
Compared with single-input multiple-output (SIMO) radar, colocated multiple-input multiple-output (MIMO) radar can detect moving targets better by adopting waveform diversity. When the colocated MIMO radar transmits a set of orthogonal waveforms, the...
The genetic diversity of cultured species (e.g., plants and fish) has decreased as intensive agriculture and aquaculture have increased in recent decades. Maintaining genetic diversity in agriculture is a significant concern. To test whether aquacult...
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