Point cloud registration is a fundamental task in computer vision and graphics, which is widely used in 3D reconstruction, object tracking, and atlas reconstruction. Learning-based optimization and deep learning methods have been widely developed in...
With distributed generation (DG) being continuously connected into distribution networks, the stochastic and fluctuating nature of its power generation brings ever more problems than before, such as increasing operating costs and frequent voltage vio...
We consider a decision-making problem to evaluate absolute ratings of alternatives from the results of their pairwise comparisons according to two criteria, subject to constraints on the ratings. We formulate the problem as a bi-objective optimizatio...
We propose introducing fairness constraints to one of the most famous multi-criteria decision-making methods, the analytic hierarchy process (AHP). We offer a solution that guarantees consistency while respecting legally binding fairness constraints...
For order-of-addition experiments, the response is affected by the addition order of the experimental materials. Consequently, the main interest focuses on creating a predictive model and an optimal design for optimizing the response. Van Nostrand pr...
Software engineering occupies a prominent place in the theory and practice of simulation modeling, which necessitates scientific research in the field of methodological principles for forming software product quality. The problem of determining the o...
Since visible-light communication (VLC) has become an increasingly promising candidate for 6G, the field of underwater visible-light communication (UVLC) has also garnered significant attention. However, the impairments introduced by practical system...
Port state control (PSC) plays an important role in enhancing maritime safety and protecting the marine environment. Since the inspection resources are limited and the inspection process is costly and time-consuming, a critical issue for port states...
In a hydropower station, equipment needs maintenance to ensure safe, stable, and efficient operation. And the essence of equipment maintenance is a disassembly sequence planning problem. However, the complexity arises from the vast number of componen...
The generation of high-quality test cases remains challenging due to combinatorial explosion and difficulty balancing exploration-exploitation in complex parameter spaces. This paper presents a novel Hybrid Artificial Bee Colony (ABC) algorithm that...
This work presents a Bayesian statistical approach to the saliency map estimation problem. More specifically, we formalize the saliency map estimation issue in the fully automatic Markovian framework. The major and original contribution of the propos...
We consider the problem of evaluating preferences for criteria used by university students when selecting a hotel for accommodation during a professional development program in a foreign country. Input data for analysis come from a survey of 202 resp...
We study the generalization properties of stochastic optimization methods under adaptive data sampling schemes, focusing on the setting of pairwise learning, which is central to tasks like ranking, metric learning, and AUC maximization. Unlike pointw...
The search for efficient methods and procedures to optimize experimental designs is a vital process in field trials that is often challenged by computational bottlenecks. Most existing methods ignore the presence of some form of correlations in the d...
In network analysis, links depict the connections between each pair of network nodes. However, such pairwise connections fail to consider the interactions among more agents, which may be indirectly connected. Such non-pairwise or higher-order connect...
Feature selection is a basic and important step in real applications, such as face recognition and image segmentation. In this paper, we propose a new weakly supervised multi-view feature selection method by utilizing pairwise constraints, i.e., the...
The local independence assumption is crucial for the consistent estimation of item parameters in item response theory models. This article explores a pairwise likelihood estimation approach for the two-parameter logistic (2PL) model that treats the l...
Intelligent reflecting surface-assisted unmanned aerial vehicles (IRS-UAVs) have been widely applied in various communication scenarios. This paper addressed the uplink communication problem in wireless sensor networks (WSNs) by proposing a novel dou...
This study presents a systematic comparison of five crossover operators used in genetic algorithms (GA) for the Traveling Salesman Problem (TSP). Partially Mapped Crossover (PMX), Order Crossover (OX), Cycle Crossover (CX), Edge Recombination (ERX),...
Detecting single nucleotide polymorphisms’ (SNPs) interaction is one of the most popular approaches for explaining the missing heritability of common complex diseases in genome-wide association studies. Many methods have been proposed for SNP interac...
Absolute pose estimation from corrupted point correspondences is typically a problem of estimating parameters from outlier-contaminated data. Conventionally, for a fixed dimensionality d and the number of measurements N, a robust estimation problem c...
Pairwise comparison matrices play a prominent role in multiple-criteria decision-making, particularly in the analytic hierarchy process (AHP). Another form of preference modeling, called an incomplete pairwise comparison matrix, is considered when on...
The comparison of multiple (labeled) graphs with unrelated vertex sets is an important task in diverse areas of applications. Conceptually, it is often closely related to multiple sequence alignments since one aims to determine a correspondence, or m...
In this paper, a new multi-criteria problem solving method—the Full Consistency Method (FUCOM)—is proposed. The model implies the definition of two groups of constraints that need to satisfy the optimal values of weight coefficients. The...
This paper proposes a robust feature-based mosaicking method that can handle images obtained by lightweight unmanned aerial vehicles (UAVs). The imaging geometry of small UAVs can be characterized by unstable flight attitudes and low flight altitudes...
Successful track-to-track association (TTTA) in a multisensor and multitarget scenario is predicated on a reasonable likelihood function to evaluate the similarity of asynchronous mono tracks. To deal with the lack of synchronous data and prior knowl...
Sensor-based human activity recognition (HAR) has attracted interest both in academic and applied fields, and can be utilized in health-related areas, fitness, sports training, etc. With a view to improving the performance of sensor-based HAR and opt...
This work develops a deep-learning-based cooperative localization technique for high localization accuracy and real-time operation in vehicular networks. In cooperative localization, the noisy observation of the pairwise distance and the angle betwee...
The best–worst method (BWM) has recently demonstrated its applicability in addressing various decision-making problems in a practical setting. The traditional BWM method is based on deterministic information gathered from experts as pairwise co...
Multiway spatial join plays an important role in GIS (Geographic Information Systems) and their applications. With the increase in spatial data volumes, the performance of multiway spatial join has encountered a computation bottleneck in the context...
The ear recognition task is known as predicting whether two ear images belong to the same person or not. More recently, most ear recognition methods have started based on deep learning features that can achieve a good accuracy, but it requires more r...
Learning to Rank (L2R) methods that utilize machine learning techniques to solve the ranking problems have been widely studied in the field of information retrieval. Existing methods usually concatenate query and document features as training input,...
The Analytic Hierarchy Process (AHP) multicriteria method can be cognitively demanding for large-scale decision problems due to the requirement for the decision maker to make pairwise evaluations of all alternatives. To address this issue, this paper...
This study examined the prevalence and clustering patterns of pro-environmental behaviors that are conducive to socially and environmentally sustainable living among Canadians. Cross-sectional data from the 2015 Households and the Environment Survey...
In this paper, we generalize the construction of locally repairable codes (LRCs) by leveraging pairwise balanced designs (PBDs) and balanced incomplete block designs (BIBDs) to construct codes with nonuniform locality or nonuniform availability. Our...
This paper proposes a technique to estimate the minimal quantity of orthogonal channel resources required for ad hoc and sensor network connectivity. Simultaneously, the resource allocation to each specific line is conducted by grouping lines into co...
28 January 2023
Introduction: Numerous tools exist to detect potentially inappropriate medication (PIM) and potential prescribing omissions (PPO) in older people, but it remains unclear which tools may be most relevant in which setting. Objectives: This cross sectio...
Terpolymer raspberry vesicles contain domains of different chemical affinities. They are potential candidates as multi-compartment cargo carriers. Their efficacy depends on their stability and load capacity. Using a model star terpolymer system in an...
Changes of mind can become less likely the longer an agent has adopted a given opinion state. This resilience or inertia to change has been called “aging”. We perform a comparative study of the effects of aging on the critical behavior of...
In this paper, a globally optimal algorithm based on a maximum feasible subsystem framework is proposed for robust pairwise registration of point cloud data. Registration is formulated as a branch-and-bound problem with mixed-integer linear programmi...
This study investigated the integration of detection and communication techniques. First, the fractional-order Fourier transform (FRFT) is introduced, and the golden section method, parabolic interpolation, and Brent method are applied to search for...
Clustering algorithms for multi-database mining (MDM) rely on computing (n2−n)/2 pairwise similarities between n multiple databases to generate and evaluate m∈[1,(n2−n)/2] candidate clusterings in order to select the ideal partitioning that optimizes...
The real-time diagnostic monitoring of self-priming centrifugal pumps is essential to ensure their safe operation. Nevertheless, owing to the intricate structure and complex operational conditions inherent in such pumps, existing fault diagnosis meth...
It is a challenging problem to efficiently interpret the large volumes of remotely sensed image data being collected in the current age of remote sensing “big data”. Although human visual interpretation can yield accurate annotation of remote sensing...
Adsorption cooling technologies driven by low-grade thermal or solar power are used as an energy-efficient alternative to conventional refrigeration and air conditioning systems. Explicit understanding of the adsorption cycles requires precise determ...
This paper presents a developed method for fuzzy multiple-criteria optimization of the rolled-steel heat treatment processes in the modern metallurgical plant. At the first stage of the study, by means of passive industrial experiments or a mathemati...
The registration of bridge point cloud data (PCD) is an important preprocessing step for tasks such as bridge modeling, deformation detection, and bridge health monitoring. However, most existing research on bridge PCD registration only focused on pa...
In this paper, data consistency in the three-option Davidson model is investigated. Starting out with the usual consistency definition in pairwise matrices-based methods, we examine its consequences. We formulate an equivalent statement based on the...
The efficient coding hypothesis states that neural response should maximize its information about the external input. Theoretical studies focus on optimal response in single neuron and population code in networks with weak pairwise interactions. Howe...
In the Minimum Description Length (MDL) principle, learning from the data is equivalent to an optimal coding problem. We show that the codes that achieve optimal compression in MDL are critical in a very precise sense. First, when they are taken as g...
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