This paper explores the overall picture regarding healthcare security systems through an extensive literature review. As the healthcare sector has now become digitalized, the security of healthcare systems and, by extension, the protection of patient...
To tackle the problems of sluggish convergence rates, low precision, and limited applicability to static settings, a fusion algorithm of the improved Gray Wolf Algorithm and the improved Dynamic Window Approach is proposed. With regard to the Gray Wo...
Effective path planning is crucial for autonomous mobile robots navigating complex environments. The “global–local” coupled path planning algorithm exhibits superior global planning capabilities and local adaptability. However, thes...
This paper addresses the unconstrained global minimization of continuously differentiable functions by introducing a novel global optimization framework based on the auxiliary function approach. First, a robust auxiliary function that remains unaffec...
To overcome the limitations of the sparrow search algorithm and the challenges of dynamic obstacle avoidance in mobile robots, an integrated method combining the enhanced sparrow search algorithm with the dynamic window approach is introduced. First,...
Social media platforms like Instagram have become a haven for online scams, employing various deceptive tactics to exploit unsuspecting users. This paper investigates advanced algorithmic approaches to combat this growing threat. We explore various m...
Path planning and formation control in leader–follower robotic systems are active areas of research, as both are highly relevant to the proper execution of the assigned task. In this work, a dual approach to the A* algorithm is applied to gener...
The study of path-planning algorithms is crucial for an electric logistics vehicle to reach its target point quickly and safely. In light of this, this work suggests a novel path-planning technique based on the improved A-star (A*) fusion dynamic win...
In response to the shortcomings of the traditional A-star algorithm, such as excessive node traversal, long search time, unsmooth path, close proximity to obstacles, and applicability only to static maps, a path planning method that integrates an ada...
In meal delivery robot path planning, enabling the robot to find an optimal path that avoids obstacles within its workspace is a crucial step. Usually, the traditional ant colony optimization (ACO) suffers from slow convergence and blind search behav...
Intelligent mobile robots play an important role in the green and efficient operation of warehouses and have a significant impact on the natural environment and the economy. Path planning technology is one of the key technologies to achieve intellige...
This paper examines a calculus-based approach to building model functions in a derivative-free algorithm. This calculus-based approach can be used when the objective function considered is defined via more than one blackbox. Two versions of a derivat...
The logistics demands of industries represented by e-commerce have experienced explosive growth in recent years. Vehicle path-planning plays a crucial role in optimization systems for logistics and distribution. A path-planning scheme suitable for an...
Disruptive technology, especially autonomous vehicles, is predicted to provide higher safety and reduce road traffic emissions. Lane detection and tracking are critical building blocks for developing autonomous or intelligent vehicles. This study pre...
To ensure the safety and energy efficiency of autonomous sampling operations for a deep-sea landing vehicle (DSLV), the Safety Energy-Dynamic Window Approach (SE-DWA) algorithm was proposed. The safety assessment sub-function formed from the warning...
To address the common limitations of conventional dual-layer path planning methods, such as slow global convergence, delayed local obstacle avoidance response, and insufficient inter-layer integration, this paper proposes an enhanced collaborative pl...
Circular Economy (CE) and circular cities are recognized as essential approaches for achieving sustainability and fostering sustainable urban development. Given the diverse definitions and principles, multidimensional complexities, and lack of a comp...
Unbalanced load condition is one of the major issues of all commercial, industrial and residential sectors. Unbalanced load means that, when different loads are distributed on a three-phase four-wire system, unequal currents pass through the three ph...
To maximize the advantages of being low-cost, highly mobile, and having a high flexibility, aerial recovery technology is important for unmanned aerial vehicle (UAV) swarms. In particular, the operation mode of “launch-recovery-relaunch”...
Background and Objectives: Metastatic spinal cord compression represents a substantial risk to patients, given its potential for spinal cord and/or nerve root compression, which can result in severe morbidity. This study aims to evaluate the effectiv...
This article addresses real-time local conflict resolution for a self-planning UAV operating in a three-dimensional dynamic environment with surrounding UAVs. To this end, we develop an SBA–DWA hybrid planning framework in which an improved sti...
Advances in wearable device and sensor technologies progressively shift respiratory monitoring from the clinical setting to real-world conditions. This rapidly developing field allows for more accurate diagnostics. However, reliable monitoring during...
Known as a multi-objective, large-scale, and complicated optimization problem, the multi-objective optimal power flow (MOOPF) problem tends to be introduced with many constraints. In this paper, compared with the frequently-used penalty function-base...
This paper examines the use of algorithms and non-algorithmic models in mathematics and science, especially in biology, during the past century by summarizing the gradual development of a conceptual rationale for non-algorithmic models in biology. Fi...
An inventory management problem is addressed for a make-to-order supply chain that has inventory holding and/or manufacturing locations at each node. The lead times between nodes and production capacity limits are heterogeneous across the network. Th...
Algorithmic complexity is a foundational notion in theoretical computer science, but its incomputability has led to two families of practical estimators: compression-based and program-execution-based (e.g., the Coding Theorem Method, CTM). Despite wi...
This study leveraged the millimeter wireless access in vehicular environments (mmWAVE) communication technology to reflect the maneuvering characteristics of small fishing vessels and constructed a collision prevention algorithm that can be applied r...
This paper proposes a distributed algorithm for games with shared coupling constraints based on the variational approach and the proximal-point algorithm. The paper demonstrates the effectiveness of the proximal-point algorithm in distributed computi...
The assessment of time irreversibility, i.e., of the lack of invariance of the statistical properties of a system under the operation of time reversal, is a topic steadily gaining attention within the research community. Irreversible dynamics have be...
This paper introduces a novel formulation of the clustering problem, namely, the minimum sum-of-squares clustering of infinitely tall data (MSSC-ITD), and presents HPClust, an innovative set of hybrid parallel approaches for its effective solution. B...
The A* algorithm is widely used in path planning for Automated Guided Vehicles (AGVs), but the path it generates is prone to collision with random obstacles. To address this issue, this paper proposes a hybrid path planning algorithm integrating the...
This paper describes the algorithm for optimal distribution network reconfiguration using the combination of a heuristic approach and genetic algorithms. Although similar approaches have been developed so far, they usually had issues with poor conver...
Aiming at the shortcomings of the traditional sparrow search algorithm (SSA) in path planning, such as its high time-consumption, long path length, it being easy to collide with static obstacles and its inability to avoid dynamic obstacles, this pape...
A full understanding of the patterns, trends, and strategies for long-term ecosystem changes helps decision-makers evaluate the effectiveness of ecological restoration projects. This study identified the ecological restoration approaches on planted f...
Bat algorithm has disadvantages of slow convergence rate, low convergence precision and weak stability. In this paper, we designed an improved bat algorithm with a logarithmic decreasing strategy and Cauchy disturbance. In order to meet the requireme...
Accurate damage identification is of great significance to maintain timely and prevent structural failure. To accurately and quickly identify the structural damage, a novel two-stage approach based on convolutional neural networks (CNN) and an improv...
The advancement of mobile robot technology has made path planning a necessary condition for autonomous navigation, but traditional algorithms have issues with efficiency and reliability in dynamic and unstructured environments. This study proposes a...
Many physical and biological phenomena are characterized by time asymmetry, and are referred to as irreversible. Time-reversal symmetry breaking is in fact the hallmark of systems operating away from equilibrium and reflects the power dissipated by d...
The nurse scheduling problem (NSP) is an NP-Hard combinatorial optimization scheduling problem that allocates a set of shifts to the group of nurses concerning the schedule period subject to the constraints. The objective of the NSP is to create a sc...
The A* algorithm is widely used in mobile robot path planning; however, it faces challenges such as unsmooth planned paths, redundant nodes, and extensive search areas. This paper proposes a hybrid algorithm combining an improved A* algorithm with th...
Predictive iron bioavailability (FeBio) methods aimed at evaluating the association between diet and body iron have been proposed, but few studies explored their validity and practical usefulness in epidemiological studies. In this cross-sectional st...
The use of distribution-based data representation to handle large-scale scientific datasets is a promising approach. Distribution-based approaches often transform a scientific dataset into many distributions, each of which is calculated from a small...
In mobile robot path planning, the conventional A* algorithm often suffers from redundant node expansion and excessive turning points, whereas the Dynamic Window Approach (DWA) is prone to local optima and deviations from the global path in dynamic e...
In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at market prices like any other commodity. As a result, the deregulation...
This paper presents an integrated approach for the estimation of the parameters of a mixture model in the context of data clustering. The method is designed to estimate the unknown number of clusters from observed data. For this, we marginalize out t...
Traditional object tracking technology usually regards the target as a point source object. However, this approximation is no longer appropriate for tracking extended objects such as large targets and closely spaced group objects. Bayesian extended o...
Prediction problems in timed datasets related to human activities are especially difficult to solve, because of the specific characteristics and the scarce number of predictive (input) variables available to tackle these problems. In this paper, we t...
In this paper, we propose an innovative approach for the path planning of Uninhabited Aerial Vehicles (UAVs) that combines an advanced Genetic Algorithm (GA) for optimising missions in advance and a geometrically based obstacle avoidance algorithm (Q...
The minimum error entropy principle (MEE) is an alternative of the classical least squares for its robustness to non-Gaussian noise. This paper studies the gradient descent algorithm for MEE with a semi-supervised approach and distributed method, and...
19 July 2022
In recent years, smart and ecological urbanism and transformations into the new models of city making have become a global mainstream. These are models of the smart city, the eco-city, and the eco-megacity. The article proposes a conceptual approach...
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