Algorithms, Volume 17, Issue 6

Within the framework of sustainable supply chain management and logistics, this work tackles the complex challenge of optimizing inventory levels across varied storage facilities. It introduces a comprehensive many-objective optimization model design...

This study focuses on generating reliable signals from measured noisy signals through an enhanced sensor fusion method. The main contribution of this research is the development of a novel sensor fusion architecture that creates virtual sensors, impr...

The term Artificial Intelligence (AI) has come to be one of the most frequently expressed keywords around the globe [...]

A regular unranked tree folding consists of a regular unranked tree language and a folding operation that merges (i.e., folds) selected nodes of a tree to form a graph; the combination is a formal device for representing graph languages. If, in the p...

Precision agriculture involves the application of advanced technologies to improve agricultural productivity, efficiency, and profitability while minimizing waste and environmental impacts. Deep learning approaches enable automated decision-making fo...

GMRES is one of the most powerful and popular methods to solve linear systems in the Krylov subspace; we examine it from two viewpoints: to maximize the decreasing length of the residual vector, and to maintain the orthogonality of the consecutive re...

Modeling and simulation (M&S) serve as essential tools in various scientific and engineering domains, enabling the representation of complex systems and processes without the constraints of physical experimentation [...]

The recent advancement in wireless power transmission (WPT) has led to the development of wireless rechargeable sensor networks (WRSNs), since this technology provides a means to replenish sensor nodes wirelessly, offering a solution to the energy ch...

Three-dimensional reconstruction from point clouds is an important research topic in computer vision and computer graphics. However, the discrete nature, sparsity, and noise of the original point cloud contribute to the results of 3D surface generati...

Respiratory Inductance Plethysmography (RIP) is a non-invasive method for the measurement of respiratory rates and lung volumes. Accurate detection of respiratory rates and volumes is crucial for the diagnosis and monitoring of prognosis of lung dise...

With the rapid advancement of urban intelligence, there is an increasingly urgent demand for technological innovation in traffic management. License plate recognition technology can achieve high accuracy under ideal conditions but faces significant c...

Genomic selection (GS) is a groundbreaking statistical machine learning method for advancing plant and animal breeding. Nonetheless, its practical implementation remains challenging due to numerous factors affecting its predictive performance. This r...

This study introduces a novel algorithm tailored for the precise detection of lower outliers (i.e., data points at the lower tail) in univariate datasets, which is particularly suited for scenarios with a single cluster and similar data distribution....

A dominating set of a graph is a subset of vertices such that every vertex not in the subset has at least one neighbor within the subset. The corresponding optimization problem is known to be NP-hard. It is proved to be beneficial to separate the sol...

Breast tumor segmentation of ultrasound images provides valuable tumor information for early detection and diagnosis. However, speckle noise and blurred boundaries in breast ultrasound images present challenges for tumor segmentation, especially for...

Circular antenna arrays (CAAs) find extensive utility in a range of cutting-edge communication applications such as 5G networks, the Internet of Things (IoT), and advanced beamforming technologies. In the realm of antenna design, the side lobes level...

Currently, the problem of information overload, a term popularized by Alvin Toffler in his book Future Shock [...]

The introduction of machine learning in digital pathology has deeply impacted the field, especially with the advent of whole slide image (WSI) analysis. In this review, we tried to elucidate the role of machine learning algorithms in diagnostic preci...

Digital systems are nowadays ubiquitous and often comprise an extremely high level of complexity. Guaranteeing the correct behavior of such systems has become an ever more pressing need for manufacturers. The correctness of digital systems can be add...

The increasing growth in knowledge about the functioning of the nervous system of mammals and humans, as well as the significant neuromorphic technology developments in recent decades, has led to the emergence of a large number of brain–compute...

A Distributed Elevator Fault Diagnosis System (DEFDS) is developed to tackle frequent malfunctions stemming from the widespread distribution and aging of elevator systems. Due to the complexity of elevator fault data and the subtlety of fault charact...

With the global pursuit of renewable energy and carbon neutrality, hydrogen-based microgrids have also become an important area of research, as ensuring proper design and operation is essential to achieve optimal performance from hybrid systems. This...

Syntheticdata generation methods are used to transform the original data into privacy-compliant synthetic copies (twin data). With our proposed approach, synthetic data can be simulated in the same size as the input data or in any size, and in the ca...

The manuscript presents a novel non-gradient and non-iterative method for mapping two 3D objects by matching extrema. This innovative approach utilizes the amplification of extrema through the summation of dependent random values, accompanied by a co...

Antimicrobial resistance, particularly the emergence of resistant strains in fungal pathogens, has become a pressing global health concern. Antifungal peptides (AFPs) have shown great potential as a promising alternative therapeutic strategy due to t...

A key component of multi-criteria decision analysis is the estimation of criteria weights, reflecting the preference strength of different stakeholder groups related to different objectives. One common method is the Analytic Hierarchy Process (AHP)....

Consider a collection of entities moving continuously with bounded speed, but otherwise unpredictably, in some low-dimensional space. Two such entities encroach upon one another at a fixed time if their separation is less than some specified threshol...

Analyzing crowdfunding data has been the focus of many research efforts, where analysts typically explore this data to identify the main factors and characteristics of the lending process as well as to discover unique patterns and anomalies in loan d...

First-order algorithms have long dominated the training of deep neural networks, excelling in tasks like image classification and natural language processing. Now there is a compelling opportunity to explore alternatives that could outperform current...

This paper presents various machine learning methods with different text features that are explored and evaluated to determine the authorship of the texts in the example of the Azerbaijani language. We consider techniques like artificial neural netwo...

A fitness landscape analysis of the loss surfaces produced by product unit neural networks is performed in order to gain a better understanding of the impact of product units on the characteristics of the loss surfaces. The loss surface characteristi...

The kinematics of the human hand exhibit complex and diverse characteristics unique to each individual. Various techniques such as vision-based, ultrasonic-based, and data-glove-based approaches have been employed to analyze human hand movements. How...

With the rapid development of computer technology, communication technology, and control technology, cyber-physical systems (CPSs) have been widely used and developed. However, there are massive information interactions in CPSs, which lead to an incr...

Facial emotion recognition (FER) is crucial across psychology, neuroscience, computer vision, and machine learning due to the diversified and subjective nature of emotions, varying considerably across individuals, cultures, and contexts. This study e...

We study an online distribution problem in which a producer has to send a load from an origin to a destination. At each time period before the deadline, they ask for transportation price quotes and have to decide to either accept or not accept the mi...

The adequacy and efficacy of simple and hybrid machine learning and Computational Intelligence algorithms were evaluated for the classification of potential prostate cancer patients in two distinct categories, the high- and the low-risk group for PCa...

Spike sorting, an indispensable process in the analysis of neural biosignals, aims to segregate individual action potentials from mixed recordings. This study delves into a comprehensive investigation of diverse unsupervised classification algorithms...

Price prediction tools play a significant role in small investors’ behavior. As such, this study aims to propose a method to more effectively predict stock prices in North America. Chiefly, the study addresses crucial questions related to the r...

This paper introduces an innovative method for load frequency control (LFC) in multi-area interconnected power systems vulnerable to denial-of-service (DoS) attacks. The system is modeled as a switching system with two subsystems, and an adaptive con...

Limited understanding exists regarding the methodologies behind designing interfaces for low-income contexts, despite acknowledging their potential value. The ERSA (Engineering design Research meta-model based Systematic Analysis) process, defined as...

Customer churn is a significant concern, and the telecommunications industry has the largest annual churn rate of any major industry at over 30%. This study examines the use of ensemble learning models to analyze and forecast customer churn in the te...

This paper proposes a heuristic approach for managing complex construction projects. The tool incorporates Primavera P6 EPPM and Synchro 4D, enabling proactive clash detection and resolution of spatial conflicts during concurrent tasks. Additionally,...

One of the most essential components of human life is sleep. One of the first steps in spotting abnormalities connected to sleep is classifying sleep stages. Based on the kind and frequency of signals obtained during a polysomnography test, sleep pha...

This paper presents a novel approach to automated music mixing, focusing on the optimization of loudness control in multi-track recordings. By taking into consideration the complexity and artistic nature of traditional mixing processes, we introduce...

This study delves into the realm of Explainable Artificial Intelligence (XAI) frameworks, aiming to empower researchers and practitioners with a deeper understanding of these tools. We establish a comprehensive knowledge base by classifying and analy...

The simultaneous estimation of multiple quantiles is a crucial statistical task that enables a thorough understanding of data distribution for robust analysis and decision-making. In this study, we adopt a Bayesian approach to tackle this critical ta...

This paper presents an approach to community detection in complex networks by simultaneously incorporating a connectivity-based metric and Max-Min Modularity. By leveraging the connectivity-based metric and employing a heuristic algorithm, we develop...

The Industrial Metaverse provides unparalleled prospects for increasing productivity and efficiency across multiple sectors. As wireless sensor networks play an important role in data collection and transmission within this ecosystem, preserving cont...

Breathing pattern assessment holds critical importance in clinical practice for detecting respiratory dysfunctions and their impact on health and wellbeing. This systematic literature review investigates the efficacy of inertial sensors in assessing...

A major area of application of multiobjective path problems and resolution algorithms is telecommunication network routing design, taking into account the extremely rapid technological and service evolutions. The need for explicit consideration of he...