The environmental issues we are currently facing require long-term prospective efforts for sustainable growth. Renewable energy sources seem to be one of the most practical and efficient alternatives in this regard. Understanding a nation’s pat...
Position-independent geometric errors crucially impact the accuracy of five-axis machine tools, yet their identification remains challenging due to computational complexities, inadequate measurement pose selection, and disturbances arising from therm...
Wireless edge systems increasingly rely on on-device learning for tasks such as user localization and misuser detection, but centralized training is often infeasible because of privacy and bandwidth constraints. In this work, we study communication-e...
Accurate short-term forecasting of residential electricity demand is increasingly important for smart distribution systems, particularly in the context of demand-side management and flexibility-oriented grid operation. In this study, a high-resolutio...
In this paper, a new hybrid prediction method is proposed for estimating remaining useful life, emissions, and performance parameters using experimental data obtained from a micro-turbojet engine. Experiments were conducted under various rotational s...
Modern distribution networks operate under increasingly demanding conditions, characterized by the integration of distributed energy resources, unbalanced three-phase operation, low measurement redundancy, variable topologies, and data uncertainty. I...
The complex jet-ground interactions of Short Take-off and Vertical Landing (STOVL) aircraft are critical to flight safety and performance, yet studying them with traditional full-scale wind tunnel tests is prohibitively expensive and time-consuming,...
Solar eclipses are astronomic phenomena in which the Earth’s moon transits between the planet and the Sun, projecting a shadow onto the planet’s surface. As solar power installed capacity increases, detailed studies of this region-wide phenomenon’s e...
This paper introduces an adaptive prescribed performance control (PPC) methodology designed to achieve appointed-time stabilization for morphing aircraft. The proposed approach ensures accurate attitude tracking despite challenges posed by time-varyi...
This study implements various, maximum overlap, discrete wavelet transform filters to model and forecast the time-dependent mortality index of the Lee-Carter model. The choice of appropriate wavelet filters is essential in effectively capturing the d...
Production-profile interpretation based on distributed temperature sensing (DTS) is an important method for the dynamic evaluation of hydraulically fractured horizontal gas wells. Because downhole temperature is jointly controlled by reservoir flow,...
Advancements in deep learning have revolutionized materials discovery by enabling predictive modeling of complex material properties. However, single-modal approaches often fail to capture the intricate interplay of compositional, structural, and mor...
Accurate neutron total cross-section prediction is difficult because of resonance complexity, sparse measurements, and isotope dependence. We present an ensemble-driven machine learning framework for EXFOR data over 10−3–103 MeV using nuc...
The optimization of coal chemical wastewater treatment networks (WTNs) faces a critical conflict between model fidelity and computational tractability. Rigorous models capture essential nonlinearities but hinder system-wide optimization, whereas simp...
With the rapid integration of distributed energy resources, achieving a balance between economic efficiency and environmental sustainability in multi-microgrid (MMG) systems is critical. However, existing studies typically treat microgrid operators a...
Land surface temperature (LST) is a crucial biophysical parameter related closely to the land–atmosphere interface. Satellite thermal infrared measurement provides an effective method to derive LST on regional and global scales, but it is very hard t...
The characterization of flow in subsurface porous media is associated with high uncertainty. To better quantify the uncertainty of groundwater systems, it is necessary to consider the model uncertainty. Multi-model uncertainty analysis can be perform...
Coherent sampling and ultra-pure signal sources are two major bottlenecks limiting the mass-production deployment of high-resolution dynamic testing of analog-to-digital converters (ADCs). The principal contribution of this study is the Multi-Amplitu...
The connectedness dynamics between large-, mid-, and small-cap stocks is investigated using the forecasted error variance decomposition (FEVD) spillover framework of Diebold and Yilmaz in the time-frequency domain. Total volatility spillover (i.e., c...
Due to industrialization, urbanization, and the need for sustainable water resources, the treatment of organic water has become a major environmental concern. Semiconductor photocatalysts degrade organic contaminants through a clean, energy-efficient...
In this study, we systematically evaluated “bottom-up” physiologically based oral absorption modeling, focusing on free weak base drugs. The gastrointestinal unified theoretical framework (the GUT framework) was employed as a simple and t...
This study proposes a type of Sliding Mode-based Proportional, Integral, and Derivative (SMPID) controllers to establish a model-free (treat dynamic plants as a whole uncertainty) sliding model control (MFSMC) platform for Bounded-Input and Bounded-O...
Poor classroom acoustic conditions can impair speech intelligibility, increase cognitive load, and reduce the quality of learning environments. Simulation-guided optimization provides a promising approach for improving building acoustic performance a...
The goal of the work is to enhance existing financial market forecasting frameworks by including an additional factor–in this example, a collection of carefully chosen tweets—into a long-short repetitive neural channel. In order to produc...
Autonomous driving systems (ADSs) increasingly rely on LiDAR sensors for perception. However, the resulting high-volume data places a strain on storage systems and network bandwidth and raises data-privacy concerns. We propose an IoT data engineering...
Computational science simulations produce huge volumes of data for scientific research organizations. Often, this data is shared by data centers distributed geographically for storage and analysis. Data corruption in the end-to-end route of data tran...
The International Space Station has become the platform for deploying hyperspectral sensors covering the solar reflective spectral range for earth observation. Intercalibration of hyperspectral sensors plays a crucial role in evaluating/improving rad...
In the context of drinking water safety assurance, water quality prediction faces challenges due to temporal fluctuations, seasonal cycles, and the impacts of sudden events. To address the issue of cumulative prediction bias caused by the simplistic...
An operational model for an area of the northeast Atlantic that encompasses all of Ireland’s territorial waters has been developed. The model is an implementation of the Regional Ocean Modelling System (ROMS) and uses operationally available at...
This study aims to analyse how translation experts from the German department of the European Commission’s Directorate-General for Translation (DGT) identify and correct different error categories in neural machine translated texts (NMT) and th...
Effective water quality monitoring is essential for protecting aquatic environments and supporting sustainable management of urban rivers. Accurate prediction and visualization of water quality parameters (WQPs) distributions across spatial, temporal...
The global navigation satellite system (GNSS) real-time kinematic (RTK) technique is used to achieve relative positioning centimeter levels among multiple agents on the move. A typical GNSS RTK estimates the relative positions of multiple rover recei...
In this paper, the stress–strength reliability of complex systems with diverse component types is investigated based on the theoretical framework of survival signatures. Assuming that both the strength and stress of components of the same type...
Total organic carbon (TOC) is a critical parameter for evaluating shale source rock quality and hydrocarbon generation potential. However, accurate TOC estimation from conventional well logs remains challenging, especially in data-limited geological...
Accurate determination of the optical absorption coefficient,
Utilizing underwater vehicles for hydropower infrastructure inspection is increasingly vital. However, these GNSS-denied and confined environments pose significant navigation challenges: Inertial Navigation Systems (INSs) suffer cumulative drift, Dop...
This paper presents a unified framework for trajectory tracking and static obstacle avoidance of differential-drive mobile robots. A nominal exact-decoupling controller achieves pure exponential longitudinal convergence and globally avoids angular si...
Air-borne particulate matter, PM2.5 (PM having a diameter of less than 2.5 micrometers), has aroused widespread concern and is a core indicator of severe air pollution in many cities globally. In our study, we present a validated framework to predict...
Many biometric systems based on physiological traits such as ones facial characteristics, iris, and fingerprint have been developed for authentication purposes. Such security systems, however, commonly suffer from impersonation attacks such as obfusc...
Overhead transmission conductors are flexible cable structures. Their initial equilibrium configuration is affected by self-weight, tension, boundary constraints, and material deformation, and is required for force analysis, sag calculation, and safe...
Accurate discretization of the orientation distribution function (ODF) is essential for reliable microstructural modeling of polycrystalline aggregates. This work proposes a novel texture discretization method that achieves high-fidelity ODF approxim...
In this study, a novel composite speed controller combining a sliding-mode speed controller with a disturbance observer is proposed for the vector-controlled synchronous reluctance motor (SynRM) drive system. The proposed composite speed controller e...
Filtering is one of the core post-processing steps for Airborne Laser Scanning (ALS) point clouds. A segmentation-based filtering (SBF) method is proposed herein. This method is composed of three key steps: point cloud segmentation, multiple echoes a...
This study analyzes daily bank stock returns and their dynamic connectedness for nine American banks between 18 March 2022 and 15 March 2023. It examines the interrelationships between bank stock returns and three economy-wide variables: market senti...
This study presents a novel composite thin film based on rhodamine B encapsulated into MOF-5 (Metal Organic Frameworks) as a fluorescence sensor for the real-time detection of the freshness of chilled pork. The composite film can adsorb and respond t...
Industrial microgrids are emerging as important providers of demand-side flexibility for active distribution networks. However, their participation in source–load coordination is hindered by complex production constraints, limited dispatch exec...
Accurate and computationally efficient prediction of radioactive plume dispersion is essential for rapid risk assessment and emergency response in the event of accidental atmospheric releases. This study presents a three-dimensional, mass-conservativ...
Total shrinkage, encompassing both drying and autogenous shrinkage components under standard drying conditions, is one of the most important factors affecting the long-term durability and serviceability of concrete structures. However, accurately pre...
Accurate prediction of effluent water quality is essential for the intelligent and sustainable operation of wastewater treatment plants (WWTPs). However, this task remains challenging due to the strong nonlinearity, long-term temporal dependencies, a...
With the gradual decline in conventional oil and gas production growth, unconventional natural gas has become a strategic alternative for hydrocarbon supply. Coal-rock gas (CRG) represents a deep unconventional gas resource with huge potential. Major...
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