Algorithms, Volume 17, Issue 7

Hybrid energy storage systems significantly impact the renewable energy sector due to their role in enhancing grid stability and managing its variability. However, implementing these systems requires advanced control strategies to ensure correct oper...

Decision making plays a pivotal role in shaping outcomes across various disciplines, such as medicine, economics, and business. This paper provides practitioners with guidance on implementing a decision tree designed to optimise treatment assignment...

The main contribution of this paper is to present a simple algorithm that theoretically and numerically assesses the switching angles of an inverter operated with the SPWM technique. This technique is the most widely used for eliminating harmonics in...

Public authorities and private companies have used video cameras as part of surveillance systems, and one of their objectives is the rapid detection of physically violent actions. This task is usually performed by human visual inspection, which is la...

The growth in the number of people suffering from eye diseases determines the relevance of research in the field of diagnosing retinal pathologies. Artificial intelligence models and algorithms based on measurements obtained via electrophysiological...

Reliability quantification of deep reinforcement learning (DRL)-based control is a significant challenge for the practical application of artificial intelligence (AI) in safety-critical systems. This study proposes a method for quantifying the reliab...

The crow search arithmetic optimization algorithm (CSAOA) method is introduced in this article as a novel hybrid optimization technique. This proposed strategy is a population-based metaheuristic method inspired by crows’ food-hiding techniques...

Academic evaluation is a process of assessing and measuring researchers, institutions, or disciplinary fields. Its goal is to evaluate their contributions and impact in the academic community, as well as to determine their reputation and status withi...

In this work, we systematize several implementations of the Gray code over an alphabet with $m\ge 2$ elements, which we present in C code so that they can be used directly after copying from the text. We consider two variants—reflected and modula...

In classical broadcast models, information is disseminated in synchronous rounds under the constant communication time model, wherein a node may only inform one of its neighbors in each time-unit—also known as the processor-bound model. These m...

Cervical cancer ranks among the leading causes of mortality in women worldwide, underscoring the critical need for early detection to ensure patient survival. While the Pap smear test is widely used, its effectiveness is hampered by the inherent subj...

Parking path optimization is the principal problem of automatic vertical parking (AVP); however, it is difficult to determine a collision avoiding, smooth, and accurate optimized parking path using traditional parking reference trajectory optimizatio...

Procedural Content Generation for video games (PCG) is widely used by today’s video game industry to create huge open worlds or enhance replayability. However, there is little scientific evidence that these systems produce high-quality content....

This article presents an in-depth analysis of three advanced strategies to tune fractional PID (FOPID) controllers for a nonlinear system of interconnected tanks, simulated using MATLAB. The study focuses on evaluating the performance characteristics...

Transportation asset management has historically overlooked equity considerations. However, recently, there has been a significant increase in concerns about this issue, leading to a range of research and practices aimed at achieving more equitable o...

A new two-step interior point method for solving linear programs is presented. The technique uses a convex combination of the auxiliary and central points to compute the search direction. To update the central point, we find the best value for step s...

In this paper, an algorithm is proposed to solve the non-convex optimization problem using sequential convex programming. An approximation method was used to solve the collision avoidance constraint. An iterative approach was utilized to estimate the...

A common and natural physiological response of the human body is cough, which tries to push air and other wastage thoroughly from the airways. Due to environmental factors, allergic responses, pollution or some diseases, cough occurs. A cough can be...

Unlike conventional CPU caches, non-datapath caches, such as host-side flash caches which are extensively used as storage caches, have distinct requirements. While every cache miss results in a cache update in a conventional cache, non-datapath cache...

In the era of inclusive education, students with attention deficits are integrated into the general classroom. To ensure a seamless transition of students’ focus towards the teacher’s instruction throughout the course and to align with th...

We investigate relationships between scheduling problems with the bottleneck objective functions (minimising makespan or maximal lateness) and problems of optimal colourings of the mixed graphs. The investigated scheduling problems have integer durat...

The development of a sparse-invariant depth completion model capable of handling varying levels of input depth sparsity is highly desirable in real-world applications. However, existing sparse-invariant models tend to degrade when the input depth poi...

A metaheuristic algorithm named the Crystal Structure Algorithm (CrSA), which is inspired by the symmetric arrangement of atoms, molecules, or ions in crystalline minerals, has been used for the accurate modeling of Mono Passivated Emitter and Rear C...

Dimension reduction is a technique used to transform data from a high-dimensional space into a lower-dimensional space, aiming to retain as much of the original information as possible. This approach is crucial in many disciplines like engineering, b...

The automotive industry has recently adopted multicore processors and microcontrollers to meet the requirements of new features, such as autonomous driving, and comply with the latest safety standards. However, inter-core communication poses a challe...

Cloud service providers deliver computing services on demand using the Infrastructure as a Service (IaaS) model. In a cloud data center, several virtual machines (VMs) can be hosted on a single physical machine (PM) with the help of virtualization. T...

Differential privacy, a cornerstone of privacy-preserving techniques, plays an indispensable role in ensuring the secure handling and sharing of sensitive data analysis across domains such as in census, healthcare, and social networks. Histograms, se...

Recent advancements in text-to-speech (TTS) models have aimed to streamline the two-stage process into a single-stage training approach. However, many single-stage models still lag behind in audio quality, particularly when handling Kurdish text and...

In a landscape where interest in prime sieving has waned and practitioners are few, we are still hoping for a domain renaissance, fueled by a resurgence of interest and a fresh wave of innovation. Building upon years of extensive research and experim...

A revolutionary concept of Multi-controller Software-Defined Networking (MC-SDN) is a promising structure for pursuing an evolving complex and expansive large-scale modern network environment. Despite the rich operational flexibility of MC-SDN, it is...

In traditional finance, option prices are typically calculated using crisp sets of variables. However, as reported in the literature novel, these parameters possess a degree of fuzziness or uncertainty. This allows participants to estimate option pri...

This research aims to apply Artificial Intelligence (AI) methods, specifically Artificial Immune Systems (AIS), to design an optimal control strategy for a multivariable control plant. Two specific industrial control approaches are investigated: I-PD...

The ability to automatically generate code, i.e., program synthesis, is one of the most important applications of artificial intelligence (AI). Currently, two AI techniques are leading the way: large language models (LLMs) and genetic programming (GP...

Facial expressions are often considered the primary indicators of emotions. However, it is challenging to detect genuine emotions because they can be controlled. Many studies on emotion recognition have been conducted actively in recent years. In thi...

This work introduces an unsupervised framework for video anomaly detection, leveraging a hybrid deep learning model that combines a vision transformer (ViT) with a convolutional spatiotemporal relationship (STR) attention block. The proposed model ad...

Transfer learning has gained significant traction in natural language processing due to the emergence of state-of-the-art pre-trained language models (PLMs). Unlike traditional word embedding methods such as TF-IDF and Word2Vec, PLMs are context-depe...

Unmanned aerial vehicles (UAVs, drones) are not just a technological achievement based on modern ideas of artificial intelligence; they also provide a sustainable solution for green technologies in logistics, transport, and material handling. In part...

L-tryptophan is an essential amino acid widely used in the pharmaceutical and feed industries. Enhancing its production in microorganisms necessitates activating and inactivating specific genes to direct more resources toward its synthesis. In this s...

Accurate brain extraction is crucial for the validity of MRI analyses, particularly in the context of traumatic brain injury (TBI), where conventional automated methods frequently fall short. This study investigates the interplay between intensity no...

This study presents a comprehensive analysis of utilizing TensorFlow Lite on mobile phones for the on-edge medical diagnosis of lung diseases. This paper focuses on the technical deployment of various deep learning architectures to classify nine resp...

This study briefly describes the concept of guided training of deep neural networks (DNNs) to learn physically reasonable solutions. The proposed method does not need the gradients of the physical equations, although the conventional physics-informed...

As a crucial task in natural language processing, table question answering has garnered significant attention from both the academic and industrial communities. It enables intelligent querying and question answering over structured data by translatin...

This research presents a novel algorithmic implementation to improve the analysis of visually controlled interception and accompanying motor action through the computational application of harmonic ratios and stimulation invariants. Unlike traditiona...

Object detection in unmanned aerial vehicle (UAV) scenes is a challenging task due to the varying scales and complexities of targets. To address this, we propose a novel object detection model, AFE-YOLOv8, which integrates three innovative modules: t...

Technological advancements have improved solar energy generation and reduced the cost of installing photovoltaic (PV) systems. However, challenges such as low energy-conversion efficiency and the unpredictability of electricity generation due to shad...

In this paper, we describe the supervised dynamic correlated topic model (sDCTM) for classifying categorical time series. This model extends the correlated topic model used for analyzing textual documents to a supervised framework that features dynam...

The paper outlines a methodology for validating the accuracy of a control system’s runtime implementation. The runtime takes the form of a virtual machine executing portable code compliant with IEC 61131-3 standards. A formal model, comprising...

Current stomach disease detection and diagnosis is challenged by data complexity and high dimensionality and requires effective deep learning algorithms to improve diagnostic accuracy. To address this challenge, in this paper, an improved strategy ba...