As lithium batteries are widely used in mobile electronic devices and electric vehicles, accurately assessing the Remaining Useful Life (RUL) of lithium-ion batteries is crucial to ensure the stable operation of the devices, improve energy efficiency...
Traditional power equipment defect-detection relies on manual verification, which places a high demand on the verifier’s experience, as well as a high workload and low efficiency, which can lead to false detection and missed detection. The Mask...
Dry gas seals are widely used in the petrochemical industry for shaft end sealing of compressors, pumps and other equipment involving flammable, explosive, toxic and harmful media. To address the challenge of accurately identifying the fault states o...
There are inevitable multiphase flow problems in the process of subsea oil-gas acquisition and transportation, of which the two-phase flow involving gas and liquid is given much attention. The performance of pipelines and equipment in subsea systems...
This paper proposes a new method of mixed gas identification based on a convolutional neural network for time series classification. In view of the superiority of convolutional neural networks in the field of computer vision, we applied the concept t...
As a critical supporting component in geotechnical engineering structures such as bridges, tunnels, and highways, the anchorage quality of bolts directly impacts their structural safety. The ultrasonic guided wave method is a popular method for the n...
Stargardt atrophy and geographic atrophy (GA) represent pivotal endpoints in FDA-approved clinical trials. Predicting atrophy progression is crucial for evaluating drug efficacy. Fundus autofluorescence (FAF), the standard 2D imaging modality in thes...
Liquefied petroleum gas (LPG), composed mainly of propane and butane, is widely used as an energy source in residential, commercial, and industrial sectors; however, its high flammability poses a critical risk in the event of accidental leaks. In Per...
In recent years, the application of Deep Neural Networks to gas recognition has been developing. The classification performance of the Deep Neural Network depends on the efficient representation of the input data samples. Therefore, a variety of filt...
The utilization of hydraulic fracturing technology is indispensable for unlocking the potential of tight oil and gas reservoirs. Understanding and accurately evaluating the impact of fracturing is pivotal in maximizing oil and gas production and opti...
It is difficult to detect and identify natural defects in welded components. To solve this problem, according to the Faraday magneto-optical (MO) effect, a nondestructive testing system for MO imaging, excited by an alternating magnetic field, is est...
Dissolved Gas Analysis (DGA) of transformer oil is a critical technique for transformer fault diagnosis that involves analyzing the concentration of gases to detect potential transformer faults in a timely manner. Given the issues of large model para...
This paper proposes a ResGA-Net algorithm for cloud top height (CTH) retrieval using FY-4A satellite data. The algorithm utilizes genetic algorithms for data selection and employs a residual module-based neural network for modeling. It takes the spec...
Integrating renewable energy sources (RES) into island microgrids is usually done to provide a cost-effective electricity supply. The integration process is carried out by scheduling generating unit operations with a unit commitment (UC) scheme to en...
As a new energy source, gas hydrates have attracted worldwide attention, but their exploration and development face enormous challenges. Thus, it has become increasingly crucial to identify hydrate distribution accurately. Electrical resistivity tomo...
The integrity of subsea oil and gas pipelines is essential for offshore safety and environmental protection. Conventional leak detection approaches, such as manual inspection and indirect sensing, are often costly, time-consuming, and prone to subjec...
The tight sandstone gas reservoirs in the LX area of the Ordos Basin are characterized by low porosity, poor permeability, and strong heterogeneity, which significantly complicate fluid type identification. Conventional methods based on petrophysical...
Interpreting chemical analysis results to identify ignitable liquid (IL) residues in fire debris samples is challenging, owing to the complex chemical composition of ILs and the diverse sample matrices. This work investigated a transfer learning appr...
Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and hu...
Nowadays, online examination (exam in short) platforms are becoming more popular, demanding strong security measures for digital learning environments. This includes addressing key challenges such as head pose detection and estimation, which are inte...
Corneal ulcer is one of the most devastating eye diseases causing permanent damage. There exist limited soft techniques available for detecting this disease. In recent years, deep neural networks (DNN) have significantly solved numerous classificatio...
Neuroendocrine neoplasms (NENs) are rare and heterogeneous tumors that require multidisciplinary discussion for optimal care. The theranostic approach (DOTA peptides labelled with 68Ga for diagnosis and with 90Y or 177Lu for therapy) plays a crucial...
The paper explores the impacts of changes in renewable energy sources (RES) financing in Poland on the profitability of coupled photovoltaic panels and heat pump systems. The profitability analysis is conducted with the use of Net Present Value calcu...
The water–gas shift (WGS) reaction (CO + H2O ↔ CO2 + H2) plays an important role in the hydrogen economy because it is an effective way to reduce the carbon release to net-zero CO2 emissions. The general goal of this research is to develop...
As urbanization continues to accelerate globally, energy demand in cities is reaching unprecedented levels, contributing to greenhouse gas emissions. In response, the concept of net-zero energy building (NZEB) is becoming a sustainable solution for u...
Electricity disparity in sub-Saharan Africa is a multi-dimensional challenge that has significant implications on the current socio-economic predicament of the region. Strategic implementation of demand response (DR) programs and renewable energy (RE...
Gas-phase chemistry has been identified as a major computational bottleneck in both the forward and adjoint modes of chemical transport models (CTMs). Although previous studies have demonstrated the potential of deep learning models to simulate and a...
Accurate segmentation in medical imaging is essential for disease diagnosis and monitoring, particularly in lung imaging using proton and hyperpolarized gas MRI. However, image degradation due to noise and artifacts—especially in hyperpolarized...
This paper presents a demand response (DR) framework that intertwines thermodynamic building models with a genetic algorithm (GA)-based optimization method. The framework optimizes heating/cooling schedules of end-users inside a business park microgr...
CNNs and other deep learners are now state-of-the-art in medical imaging research. However, the small sample size of many medical data sets dampens performance and results in overfitting. In some medical areas, it is simply too labor-intensive and ex...
Expansion of modern power systems due to increasing energy demands face the challenges of grid reinforcement cost, size and complexity, transmission losses, and environmental factors. Placement of renewable energy sources (RES) based generation syste...
This study explored the performance and reliability of three predictive models—extreme gradient boosting (XGB), convolutional neural network (CNN), and residual neural network (ResNet)—for determining the moisture content in Porphyra yezo...
This paper proposes an improved human-body-segmentation algorithm with attention-based feature fusion and a refined corner-based feature-point design with sub-pixel stereo matching for the anthropometric system. In the human-body-segmentation algorit...
Girth weld defects in long-distance oil and gas pipelines are one of the main causes of pipeline leakage failure and serious accidents. Magnetic flux leakage (MFL) is one of the most widely used inline inspection methods for long-distance pipelines....
Several areas of Earth that are rich in oil and natural gas also have huge deposits of salt below the surface. Because of this connection, knowing precise locations of large salt deposits is extremely important to companies involved in oil and gas ex...
In 2023, the UAE adapted its National Energy Strategy to accommodate several new goals, including doubling renewable energy (RE) capacity to 14 GW by 2030. This development further highlights the significance of transitioning towards RE sources. This...
There is a strong global demand for oil and gas resources, and forecasts indicate robust growth in oil demand in the coming years. Meeting this demand necessitates the exploitation of unconventional resources and enhancing the recovery of existing oi...
In this study, cargo boil-off gas (BOG) re-liquefaction systems for ammonia-fueled liquefied carbon dioxide (LCO2) carriers were analyzed. These systems use cold energy from ammonia to reliquefy the CO2 BOG. In this study, a system that can completel...
Memristor crossbars offer promising low-power and parallel processing capabilities, making them efficient for implementing convolutional neural networks (CNNs) in terms of delay time, area, etc. However, mapping large CNN models like ResNet-18, ResNe...
As oil and gas exploration and development advance into deep and ultra-deep areas, kick accidents are becoming more frequent during drilling operations, posing a serious threat to construction safety. Traditional kick monitoring methods are limited i...
The combined cooling, heating, and power (CCHP) microgrid system is good for energy gradient utility. At the same time, it can promote the renewable energy (RE) consumption and abate environmental pollution. In a CCHP microgrid system, the electrical...
Early detection of breast lesions and distinguishing between malignant and benign lesions are critical for breast cancer (BC) prognosis. Breast ultrasonography (BU) is an important radiological imaging modality for the diagnosis of BC. This study pro...
The use of liquefied natural gas (LNG) in the transportation sector is increasing, and boil-off gas (BOG) management systems are considered viable options to increase economic efficiency and reduce greenhouse gas emissions at LNG refueling stations....
Butanol is currently produced on an industrial scale, primarily from fossil-based raw materials. An alternative method involves gas fermentation. To improve the efficiency of microbial processes, one promising approach is electrofermentation, which i...
Gas leaks threaten ecological and social safety. Non-contact infrared imaging enables large-scale, real-time measurements; however, in complex environments, weak signals from small leaks can hinder reliable detection. This study proposes a novel auto...
Current mass balances of C, N, and P were estimated using a model (Fluxin = Fluxout + ΔFlux) from Gamak Bay, Korea, in August 2017, where eutrophication and reducing conditions are prevalent. To examine the current fluxes of particulate organic...
For high-precision navigation, obtaining and maintaining high-precision point-of-interest (POI) data on the road network is crucial. In urban areas with complex terrains, the accuracy of traditional road network POI acquisition methods often falls sh...
Enhancing the efficiency of windows is important for improving the energy efficiency of buildings. The Korean government has performed numerous building renovation projects to reduce greenhouse gas emissions and mitigate energy poverty. To reduce the...
Background/Objectives: Attenuation correction (AC) is essential for achieving quantitatively accurate PET imaging. In 68Ga-PSMA PET, however, artifacts such as respiratory motion, halo effects, and truncation errors in CT-based AC (CT-AC) images comp...
The research focuses on the analysis of seismic data, specifically targeting the detection, edge segmentation, and classification of seismic images. These processes are fundamental in image processing and are crucial in understanding the stratigraphi...
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