This paper studies interference in a data collection scenario in which multiple unmanned aerial vehicles (UAVs) are dispatched to wirelessly collect data from a set of distributed sensors. To improve the communication throughput and minimize the comp...
Determining the parameters of a manipulator for optimal performance is a challenging task. This is primarily due to possible conflicting objectives, various tasks that should be considered, and the highly non-linear behavior that is involved. This wo...
Demand for natural red colorants has increased due to regulatory and consumer pressure to replace synthetic additives; however, their industrial application remains limited by challenges related to production, stability, and safety. In this study, th...
This study presents a hierarchical multiscale homogenization framework to evaluate the thermo-mechanical performance of hybrid aluminum matrix composites (HAMCs) reinforced with Silicon Carbide (SiC) particles and Graphite (Gr) for lightweight automo...
This paper presents the design of an ultrabroadband solar absorber, developed using a metamaterial stack composed of only two materials, consisting of alternating layers of Cr and SiO2. Starting with a Cr layer as the substrate, multiple pairs of Cr...
In response to the issues of severe pitch oscillation and unstable roll attitude present in existing reinforcement learning-based aircraft cruise control methods during dynamic maneuvers, this paper proposes a precise control method for aircraft crui...
The shortest path problem (SPP) with constraints constitutes a fundamental yet computationally prohibitive NP-hard challenge in operations research and logistics. Traditional optimization algorithms, including both exact and approximate methods, ofte...
This article proposes an analytical methodology for the optimal design of a magnetorheological (MR) valve constrained in a specific volume. The analytical optimization method is to identify geometric dimensions of the MR valve, and to determine wheth...
Gaussian process-based Bayesian optimization (BO) is a sample-efficient sequential strategy for optimizing expensive black-box functions. The Gaussian process provides a probabilistic approximation of the unknown function, while an acquisition functi...
The Anatolian Caracal Optimization Algorithm (ACOA), a swarm-based optimization approach inspired by nature, approximately describes the characteristic hunting strategy of the Anatolian caracal, shaped by its superior auditory–visual perception...
A plant–controller co-design methodology is proposed in which the reference model dynamics are parameterized and incorporated directly into the optimization rather than prescribed a priori. Within an Explicit Model Following (EMF) architecture,...
In order to solve the problem of emergency decision-making with incomplete information and deal with the accident information in different time series at the scenes of major accidents, this paper proposes a method of sequential decision-making by uti...
Matrix gradient coils with up to 84 coil elements were recently introduced for magnetic resonance imaging. Ideally, each element is driven by a dedicated amplifier, which may be technically and financially infeasible. Instead, several elements can be...
Extensive research has been conducted to develop technologies that enable paratransit systems to operate autonomously, including advanced sensing technologies and associated software. However, there remains a gap in research addressing adaptive opera...
Microbial proteases are commonly produced by submerged (SmF) or solid-state fermentation (SSF), whose combination results in an unconventional method, called sequential fermentation (SF), which has already been used only to produce cellulolytic enzym...
Fuel cell hybrid vehicles offer significant potential in heavy-duty transportation due to their high efficiency, extended range, and zero emissions, making them a key enabler of sustainable transportation. To enhance the energy consumption economy an...
Vehicle-to-everything (V2X) information can support energy-efficient vehicle operation in signalized traffic. This paper presents a sequential hierarchical eco-driving strategy for fuel-cell hybrid electric vehicles (FCHEVs) traveling through multipl...
Resource Constraint Project Scheduling Problems with Discounted Cash Flows (RCPSPDC) focuses on maximizing the net present value by summing the discounted cash flows of project activities. An extension of this problem is the Payment at Event Occurren...
Accurate production forecasting of oil wells is of great significance for reservoir management, production optimization, and investment decisions. However, complex subsurface dynamics and sudden operational interventions frequently break the temporal...
Stevia is a natural source of high-intensity sweeteners, collectively known as steviol glycosides (SG), which are approximately 300 times sweeter than sucrose and widely used as sugar substitutes. This study examines the impact of five different red-...
Efficient management of medical diagnostic laboratories is critical for ensuring high-quality test results, optimal utilization of analytical resources, and continuity of services, particularly under conditions of increased and variable demand. This...
With agriculture being the second biggest contributor to greenhouse gas (GHG) emissions through the excessive use of fertilizers, machinery, and inefficient farming practices, global efforts to reduce emissions have been intensified, opting for smart...
To minimize the non-specific toxicity of drug combination during cancer therapy, we prepared a new system synthesized from bacteria to deliver the anticancer drugs cytosine arabinoside (Ara-C) and daunorubicin (DNR). In this study, we selected genipi...
Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented...
28 June 2016
The study reported here examined, as the research subject, surface soils in the Liuxin mining area of Xuzhou, and explored the heavy metal content and spectral data by establishing quantitative models with Multivariable Linear Regression (MLR), Gener...
In this study, prior to the launch of compact advanced satellite 500 (CAS500-4), which is an agriculture and forestry satellite, nine major tree species were classified using multi-temporally integrated imageries based on a random forest model using...
The high-precision laser micromachining of thermally sensitive PMMA polymers is severely limited by thermal accumulation, which deteriorates the surface quality of micro-hole arrays. Current laser drilling path optimization strategies predominantly p...
Distributed hydrokinetic systems produce sequential operational telemetry that can support predictive condition monitoring and power-control optimization. This study combines short-horizon prediction of exact-zero-power onset with field-informed eval...
This paper presents an approach for event recognition in sequential images using human body part features and their surrounding context. Key body points were approximated to track and monitor their presence in complex scenarios. Various feature descr...
Selecting a subset of samples to label from a large pool of unlabeled data points, such that a sufficiently accurate classifier is obtained using a reasonably small training set is a challenging, yet critical problem. Challenging, since solving this...
During pandemics, such as COVID-19, supplies of vaccines can be insufficient for meeting all needs, particularly when vaccines first become available. Our study develops a dynamic methodology for vaccine allocation, segmented by region, age, and time...
Emerging actuators with various soft materials and a traveling wave motion are frequently discussed. Various configurations have been proposed and their resulting performances investigated, but it remains challenging to realize large strokes. This st...
Corrosion and conductor breaks in grounding grids can compromise the safe dissipation of substation fault currents. To diagnose these faults using only a limited number of accessible nodes, this study groups frequencies and selects reference-port imp...
Financial fraud is still one of the most important threats to the financial industry, causing enormous economic losses and mounting difficulties for conventional fraud detection systems. The systems tend to face challenges in dealing with the rising...
The aim of this study was to develop trajectory planning that would allow an autonomous racing car to be driven as close as possible to what a driver would do, defining the most appropriate inputs for the current scenario. The search for the optimal...
Accurate prediction of air quality is crucial for assessing the state of the atmospheric environment, especially considering the nonlinearity, volatility, and abrupt changes in air quality data. This paper introduces an air quality index (AQI) predic...
High-g accelerometers are in high demand across sectors such as aerospace, defense, and industrial inspection. This paper presents a MEMS accelerometer based on graphene piezoresistors, designed for precise acceleration measurement under sudden impac...
This review examines the integration of sensor data into probabilistic bridge reliability analysis, covering the workflow from sensor selection and data acquisition through preprocessing, computational Bayesian inference and reliability index β...
It would be very beneficial to determine in advance whether a student is likely to succeed or fail within a particular learning area, and it is hypothesized that this can be accomplished by examining student patterns based on the data generated befor...
Microgrids can deploy traditional and/or renewable power sources to support remote sites. Utilizing renewable power sources requires more complicated control strategies to achieve acceptable power quality and maintain grid stability. In this research...
In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL), for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Proj...
This paper deals with the Dual-Function Radar and Communication (DFRC) signal design for a Multiple-Input–Multiple-Output (MIMO) system, considering the presence of signal-dependent clutter. A modulation methodology called Spectral Position Ind...
Wind power producers face severe financial risks from intermittent generation and volatile prices. In this paper, we develop a multivariate scenario-based optimization framework that integrates heavy-tailed Laplace forecast-error path generation, pri...
In this paper, a novel soft computing technique is designed to analyze the mathematical model of the steady thin film flow of Johnson–Segalman fluid on the surface of an infinitely long vertical cylinder used in the drainage system by using art...
Stealth malware is a representative tool of advanced persistent threat (APT) attacks, which poses an increased threat to cyber-physical systems (CPS) today. Due to the use of stealthy and evasive techniques, stealth malwares usually render convention...
Widespread release of cyanide from industrial activities represents a significant environmental challenge due to its acute toxicity and adverse effects on biological systems. In response to this concern, this study focused on the production of rhodan...
Supercritical carbon dioxide (CO2) is a promising working fluid for advanced power cycles. However, under high heat flux and low mass flux, its heat transfer performance can deteriorate severely, posing significant risks to system safety and efficien...
Sparse spikes deconvolution is one of the oldest inverse problems, which is a stylized version of recovery in seismic imaging. The goal of sparse spike deconvolution is to recover an approximation of a given noisy measurement
The N-Queens problem is a fundamental challenge in combinatorial optimization, commonly used as a benchmark for assessing the efficiency of algorithms. Traditional algorithms, such as Backtracking with Forward Checking (BFC), constraint satisfaction...
Background/Objective: Autonomous vehicles (AVs) require control algorithms capable of handling complex and dynamic environments while satisfying multiple conflicting objectives such as safety, comfort, energy efficiency, and trajectory accuracy. Mode...
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