Compressed sensing (CS) offers a framework for image acquisition, which has excellent potential in image sampling and compression applications due to the sub-Nyquist sampling rate and low complexity. In engineering practices, the resulting CS samples...
Block compressed sensing (BCS) is a promising technology for image sampling and compression for resource-constrained applications, but it needs to balance the sampling rate and quantization bit-depth for a bit-rate constraint. In this paper, we summa...
In Long Range Wide Area Network (LoRaWAN), the data rate of the devices can be adjusted to optimize the throughput by changing the spreading factor. However, the adaptive data rate has to be carefully utilized because the collision probability, which...
We investigate a portfolio optimization problem under the threat of a market crash, where the interest rate of the bond is modeled as a Vasicek process, which is correlated with the stock price process. We adopt a non-probabilistic worst-case approac...
The process of machine learning is to find parameters that minimize the cost function constructed by learning the data. This is called optimization and the parameters at that time are called the optimal parameters in neural networks. In the process o...
This paper proposes a three-step joint rate optimization method for intelligent reflecting surface (IRS)-assisted coal mine wireless communication systems. Different from terrestrial IRS-assisted communication scenarios, in coal mines, IRSs can be in...
Reconfigurable intelligent surfaces (RISs) hold promising technical prospects for 6G wireless communications to enhance system capacity, coverage and sum-rate. Unlike existing studies deploying only passive or active RISs, this paper adopts a novel h...
Tetrazolium salts provide an appealing candidate for 3D gel dosimeters as they exhibit a low intrinsic color, no signal diffusion and excellent chemical stability. However, a previously developed commercial product (the ClearView 3D Dosimeter) based...
The convergence rate of the augmented Lagrangian method (ALM) for solving the nonlinear semidefinite optimization problem is studied. Under the Jacobian uniqueness conditions, when a multiplier vector
Due to operational limitations in the industrial field, the operating variables of fluid catalytic cracking units (FCCU) are of multiple operating frequencies, which are CO combustion promoter amount, recycle slurry flow rate, combustion air flow rat...
With the rapid development of science and technology, the living habits of people have also changed from those in the past; the diet, living environment, various life pressures, etc., all overwhelm the body and mind, meaning that, nowadays, more peop...
As reliance on wind energy intensifies globally, optimizing the efficiency and reliability of wind turbines is becoming vital. This paper explores sophisticated maintenance strategies, crucial for enhancing the operational sustainability of wind turb...
To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the imp...
Exchange rate forecasting is a crucial but challenging task due to the uncertainty and fuzziness of the associated data caused by complex influence factors. However, most traditional forecasting methods ignore the ambiguity of the data itself. Thus,...
In this study, a Support Vector Regression (SVR) model was developed to predict the rate of penetration (ROP) during tunnel excavation, and its hyperparameters were optimized using Grid Search (GS), Random Search (RS), and Bayesian Optimization (BO)....
The vanadium flow batteries that employ the vanadium element as active couples for both half-cells, thus avoiding cross-contamination, are promising large-scale energy storage devices. In this work, the flow rate is optimized by incorporating the tem...
The Rate of Penetration (ROP), as a core indicator for evaluating drilling efficiency, holds significant importance for optimizing drilling parameter configurations, enhancing drilling efficiency, and reducing operational costs. To address the limita...
Accurate exchange rate forecasting is crucial for investment decisions, multinational corporations, and national policies. The nonlinear nature and volatility of the foreign exchange market hinder traditional forecasting methods in capturing exchange...
The global energy transition requires coal-fired power plants to transition from base-load sources to flexible regulation resources, necessitating a critical balance between rapid load adjustment capabilities and operational economic efficiency. To a...
Fish capture usually requires classification of fish species, and the cost of manual classification is relatively high. Recently, deep learning has been widely applied in the fishery field. Transfer learning was conducted on ResNet18, ShuffleNet, Eff...
The objective of the grinding process is to obtain a better surface finish (roughness, accuracy, etc.) or a high material removal rate of the workpiece. These grinding process response variables depend largely on both the grinding conditions and the...
We present a variable-rate learned image compression (LIC) model that integrates Transformer-based quantization–reconstruction (QR) offset prediction, entropy-guided hyper-latent quantization, and perceptually informed multi-objective optimizat...
Rate of penetration (ROP) prediction is essential for drilling efficiency, yet prevailing deep learning models employ millions of parameters and rely on surface-based pipelines constrained by low-bandwidth telemetry and round-trip delays measured in...
This study focuses on obtaining regression models for material removal rate and tool wear in rough honing processes. For this purpose, experimental tests were carried out according to a central composite design of experiments. Five different paramete...
Automatic speech recognition has advanced rapidly for high-resource languages, yet performance remains limited for low-resource languages such as Bangla, particularly in telehealth settings. Most systems rely on a standardized 16 kHz sampling rate, a...
In order to establish a general design methodology for water-based electromagnetic metamaterial absorber microstructures, a topology optimization method for water-based metamaterial absorber microstructures design was proposed in this paper. Accordin...
The current journal paper proposes an end-to-end analysis for the numerical implementation of a two-degrees-of-freedom (2DOF) control structure, starting from the sampling rate selection mechanism via a quasi-optimal manner, along with the estimation...
High shares of wind and solar power make generation outputs strongly random. Traditional stochastic optimal power flow (SOPF) also lacks power–carbon coordination. Low-carbon constraints are often disconnected from operational scheduling. To ad...
Achieving ubiquitous coverage in 6G networks presents significant challenges due to the limitations of high-frequency signals and the need for extensive infrastructure, and providing seamless connectivity in remote and rural areas remains a challenge...
Considering the excellent environmental properties and heating capability under wide running conditions of the natural fluid CO2, the transcritical CO2 heat pump system has widely been used in the application of water heaters, commercial heating and...
Addressing the issues of low positioning accuracy and poor robustness in shaft-rate magnetic fields, this study introduces the Improved Exponential Triangular Optimization Algorithm (IETO). By incorporating adaptive attenuation factors, dynamic popul...
The increasing proliferation of Internet-of-things (IoT) networks in a given space requires exploring various communication solutions (e.g., cooperative relaying, non-orthogonal multiple access, spectrum sharing) jointly to increase the performance o...
This paper addresses the challenge of optimally controlling silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) to minimize switching losses while simultaneously reducing overshoots and voltage slew rates. A digitally c...
Objective: Microwave hyperthermia is a clinically validated adjunctive therapy in oncology, employing antenna applicators to selectively raise tumor tissue temperature to 40–44 °C. For deep-seated tumors, especially those in anatomically co...
Based on the theory of finite-time thermodynamics (FTT), the effects of three design parameters, that is, inlet temperature, inlet pressure, and inlet total mole flow rate, of a tubular plug-flow sulfuric acid decomposition reactor on the total entro...
Electrochemical machining (ECM) is a preferred advanced machining process for machining Monel 400 alloys. During the machining, the toxic nickel hydroxides in the sludge are formed. Therefore, it becomes necessary to determine the optimum ECM process...
Objective: Microwave hyperthermia is a clinically proven cancer treatment used in combination with conventional therapies to enhance the overall treatment outcome. It consists in selectively increasing the temperature of tumor cells to 40–44 &d...
Rate-distortion optimization (RDO) plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC). Among all the possible coding modes, it aim...
Wireless powered communication networks (WPCNs) provide a sustainable solution for energy-constrained IoT devices by enabling wireless energy transfer (WET) in the downlink and wireless information transmission (WIT) in the uplink. However, their per...
In this work, the dry turning of Inconel 601 alloy in a dry environment with PVD-coated cutting inserts was studied. Turning was performed at various cutting speeds, feeds, insert shapes, corner radii, rake angles, and approach angles. After machinin...
With the increasing renewable penetration in electrical grids, high power ramp rates can lead to grid instability. Power ramp-rate control (PRRC) requirements are being implemented in an increasing number of countries, with penalties for non-complian...
The prediction of production decline rate in the development of offshore high water-cut reservoirs predominantly relies on the traditional Arps decline curves. However, the solution process is complex, and the interpretation efficiency is low, making...
This paper introduces a novel convolutional neural network (CNN) architecture tailored for state of charge (SoC) estimation in battery management systems (BMS), accompanied by an advanced optimization technique to enhance training efficiency. The pro...
Ultrasonic vibration-assisted grinding using cubic boron nitride (CBN) wheels has emerged as an effective approach for improving surface integrity and machining efficiency in hard-to-machine materials. However, achieving a desirable balance between s...
Since occupants spend most of their time indoors, an energy-saving and comfortable indoor environment are particularly important. The differences in the metabolic rate of occupants make them have different requirements for their thermal environment....
Complex mechanical parts such as a blisk of aero-engines are commonly used in aerospace industry. These parts are complex in shape and their rough machining are conducted in 4-axis machine tools with end mills. The end mills are fully engaged into th...
Accurate and stable prediction of icing thickness on transmission lines is of great significance for ensuring the safe operation of the power grid. In order to improve the accuracy and stability of icing prediction, an innovative prediction model bas...
Tribological properties are important to evaluate the in-service conditions of machine elements, especially those which work as tandem parts. Considering their wide range of application areas, metal matrix composites (MMCs) serve as one of the most s...
Due to the simplicity and convenience of PPG signal acquisition, the detection of the respiration rate based on the PPG signal is more suitable for dynamic monitoring than the impedance spirometry method, but it is challenging to achieve accurate pre...
Accurate prediction of the internal corrosion rate is crucial for the safety management and maintenance planning of oil and gas pipelines. However, this task is challenging due to the complex, multi-factor nature of corrosion and the scarcity of avai...
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