Algorithms, Volume 14, Issue 7

Multi-actor multi-criteria analysis (MAMCA) was developed with a process involving the participation of various stakeholders. Stakeholders express various criteria as measures for the achievement of their respective goals. In general, the assessment...

Arabic text classification is a process to simultaneously categorize the different contextual Arabic contents into a proper category. In this paper, a novel deep learning Arabic text computer-aided recognition (ArCAR) is proposed to represent and rec...

Visual sentiment analysis has become more popular than textual ones in various domains for decision-making purposes. On account of this, we develop a visual sentiment analysis system, which can classify image expression. The system classifies images...

This paper presents a novel approach, using hybrid feature selection (HFS), machine learning (ML), and particle swarm optimization (PSO) to predict and optimize construction labor productivity (CLP). HFS selects factors that are most predictive of CL...

Plenoptic camera based system captures the light-field that can be exploited to estimate the 3D depth of the scene. This process generally consists of a significant number of recurrent operations, and thus requires high computation power. General pur...

This paper investigates the containment control problem of discrete-time first-order multi-agent system composed of multiple leaders and followers, and we propose a proportional-integral (PI) coordination control protocol. Assume that each follower h...

This paper proposes a hybridized simheuristic approach that couples a greedy randomized adaptive search procedure (GRASP), a Monte Carlo simulation, a Pareto archived evolution strategy (PAES), and an analytic hierarchy process (AHP), in order to sol...

The financial data supply chain is vital to the economy, especially for banks. It affects their customer service level, therefore, it is crucial to manage the scheduling of the financial data supply chain to elevate the efficiency of banking sectors’...

Deep learning methods are the de facto solutions to a multitude of medical image analysis tasks. Cardiac MRI segmentation is one such application, which, like many others, requires a large number of annotated data so that a trained network can genera...

The concentration of PM2.5 is an important index to measure the degree of air pollution. When it exceeds the standard value, it is considered to cause pollution and lower the air quality, which is harmful to human health and can cause a variety of di...

A variety of strategies are used to construct algorithms for solving equations. However, higher order derivatives are usually assumed to calculate the convergence order. More importantly, bounds on error and uniqueness regions for the solution are al...

Most research activities that utilize linear matrix inequality (LMI) techniques are based on the assumption that the separation principle of control and observer synthesis holds. This principle states that the combination of separately designed linea...

This work focuses on energy management for a system operated by multiple energy sources which include batteries, super capacitors, a hydrogen fuel cell, and a photovoltaic cell. The overall objective is to minimize the power consumption from all sour...

Congestion control is one of the key research topics in relation to the routing algorithms of wireless sensor networks (WSNs). In this paper, we propose a congestion-aware routing algorithm (CARA) for unlimited-lifetime wireless sensor networks by in...

Recently, cloud computing has begun to experience tremendous growth because government agencies and private organisations are migrating to the cloud environment. Hence, having a task scheduling strategy that is efficient is paramount for effectively...

Early diagnosis is crucial to prevent the development of a disease that may cause danger to human lives. COVID-19, which is a contagious disease that has mutated into several variants, has become a global pandemic that demands to be diagnosed as soon...

According to the requirements of point cloud simplification for T-profile steel plate welding in shipbuilding, the disadvantages of the existing simplification algorithms are analyzed. In this paper, a point cloud simplification method is proposed ba...

This paper studies the layout design of a robotic mobile fulfillment system with multiple workstations. This is a parts-to-picker storage system where robots hoist pods and bring them directly to the workstations for stationary pickers to retrieve re...

Incomplete Sparse Approximate Inverses (ISAI) has shown some advantages over sparse triangular solves on GPUs when it is used for the incomplete LU based preconditioner. In this paper, we extend the single GPU method for Block–ISAI to multiple GPUs a...

In the conventional k-means framework, seeding is the first step toward optimization before the objects are clustered. In random seeding, two main issues arise: the clustering results may be less than optimal and different clustering results may be o...

Financial and commercial data are mostly represented in decimal format. To avoid errors introduced when converting some decimal fractions to binary, these data are processed with decimal arithmetic. Most processors only have hardwired binary arithmet...

Wheeled mobile robots are widely implemented in the field environment where slipping and skidding may often occur. This paper presents a self-adaptive path tracking control framework based on a radial basis function (RBF) neural network to overcome s...

Object detection is a challenging computer vision task with numerous real-world applications. In recent years, the concept of the object relationship model has become helpful for object detection and has been verified and realized in deep learning. N...

This article aims to bring quantum computing to robotics. A quantum algorithm is developed to minimize the distance traveled in warehouses and distribution centers where order picking is applied. For this, a proof of concept is proposed through a Ras...

This article presents the possibilities in solving the Weighted Multi-Facility Location Problem and its related optimization tasks using a widely available office software—MS Excel with the Solver add-in. To verify the proposed technique, a set of be...

Recently, some researchers adopted the convolutional neural network (CNN) for time series classification (TSC) and have achieved better performance than most hand-crafted methods in the University of California, Riverside (UCR) archive. The secret to...

This paper presents an efficient coronavirus optimization algorithm (CVOA) to find the optimal values of the PID controller to track a preselected reference speed of a brushless DC (BLDC) motor under several types of disturbances. This work simulates...

A rising number of people use online reviews to choose if they want to use or buy a service or product. Therefore, approaches for identifying fake reviews are in high request. This paper proposes a hybrid rule-based fact-checking framework based on A...

Modeling traffic distribution and extracting optimal flows in multilayer networks is of the utmost importance to design efficient, multi-modal network infrastructures. Recent results based on optimal transport theory provide powerful and computationa...