Fuel cell systems are regarded as a promising candidate in replacing the internal combustion engine as a renewable and emission free alternative in automotive applications. However, the operation of a fuel cell stack fulfilling transient power-demand...
Photovoltaic (PV) technology allows large-scale investments in a renewable power-generating system at a competitive levelized cost of electricity (LCOE) and with a low environmental impact. Large-scale PV installations operate in a highly competitive...
Machine-learning diagnostic systems are widely used to detect abnormal conditions in electrical equipment. Training robust and accurate diagnostic systems is challenging because only small databases of abnormal-condition data are available. However,...
In this work, a hybrid component Fault Detection and Diagnosis (FDD) approach for industrial sensor systems is established and analyzed, to provide a hybrid schema that combines the advantages and eliminates the drawbacks of both model-based and data...
This paper examines the transition of lithium-ion batteries from electric vehicles (EVs) to energy storage systems (ESSs), with a focus on diagnosing their state of health (SOH) to ensure efficient and safe repurposing. It compares direct methods, mo...
This study provides a general procedure to generate a direct expansion (DX) cooling coil system for a roof top unit (RTU), which is a typical heating ventilation and air-conditioning (HVAC) system for commercial buildings in the United States. Experi...
Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundan...
The condition-based maintenance of vibrating screens requires new methods of their elements’ diagnostics due to severe disturbances in measured signals from vibrators and falling pieces of material. The bolted joints of the sieving deck, when f...
Fault detection and isolation (FDI) in oil pipeline systems (OPS) is a very critical issue because faults in these systems such as leaks or equipment malfunctions may cause significant safety accidents and economic losses. These are the challenging f...
Since 2014, Formula 1 engines have been turbocharged spark-ignited engines. In this scenario, the maximum engine power available in full-load conditions can be achieved only by optimizing combustion phasing within the cycle, i.e., by advancing the ce...
This paper describes a methodology, developed by the authors, for condition monitoring and diagnostics of several critical components in the large-scale applications with machines. For industry, the main target of condition monitoring is to prevent t...
Monitoring the filtration efficiency of the diesel particulate filter (DPF), is a legislative requirement for minimizing particulate matter (PM) emissions from diesel engines of passenger cars and heavy-duty vehicles. To reach this target, on-board d...
Deep learning algorithms often struggle to accurately distinguish between healthy and anomalous states due to the scarcity of high-quality data in real-world applications. However, these data can be obtained through a physics-based simulation model....
Hydropower generation is one of the most prominent renewable sources of power. Run-of-river hydropower is like traditional hydropower but has significantly less environmental impact. Faults in industrial processes are a cause for large amounts of los...
Maintenance is crucial for aircraft engines because of the demanding conditions to which they are exposed during operation. A proper maintenance plan is essential for ensuring safe flights and prolonging the life of the engines. It also plays a major...
X-ray diagnostics are widely used to detect various diseases, such as bone fracture, pneumonia, or intracranial hemorrhage. This method is simple and accessible in most hospitals, but requires an expert who is sometimes unavailable. Today, some diagn...
The realm of medical imaging is a critical frontier in precision diagnostics, where the clarity of the image is paramount. Despite advancements in imaging technology, noise remains a pervasive challenge that can obscure crucial details and impede acc...
Laser-based methods are widely used techniques for thermonuclear plasma diagnostics, since they can probe the internal of the plasma, being contactless and non-invasive. The interferometer, the polarimeter and Thomson scattering are the most widespre...
The operation and maintenance (O&M) issues of offshore wind turbines (WTs) are more challenging because of the harsh operational environment and hard accessibility. As sudden component failures within WTs bring about durable downtimes and signifi...
Early detection is critical to reduce cancer deaths as treating early stage cancers is more likely to be successful. However, patients with early stage diseases are often asymptomatic and thus less likely to be diagnosed. Here, we utilized four micro...
The object of the research is the process of intelligent monitoring and diagnosis of animal health using IoT technology in the context of a digital farm. The problem lies in the absence of an integrated approach that can provide near-real-time assess...
Background: Antimicrobial drugs are used to treat bacterial diseases in livestock production systems, including bovine respiratory disease (BRD) in feedlot cattle. It is recommended that therapeutic antimicrobial use (AMU) in food animals be informed...
The SARS-CoV-2 pandemic has led to an urgent need for effective and rapid diagnostic tools. In the present study, we have evaluated the predictive diagnostic potential of nasal microbiota by analyzing microbial community structures at different taxon...
Background: Vascular anomalies (VAs), including hemangiomas and vascular malformations, present a significant diagnostic challenge due to their high prevalence, complex classification (nearly 100 subtypes), and visual mimicry. Current Multimodal Larg...
An important hurdle in medical diagnostics is the high-quality and interpretable classification of audio signals. In this study, we present an image-based representation of infant crying audio files to predict abnormal infant cries using a vision tra...
Currently, the use of industrial seawater reverse osmosis desalination (ISROD) plants has increased in popularity in light of the growing global demand for freshwater. In ISROD plants, any fault in the components of their control systems can lead to...
Artificial intelligence (AI) has been increasingly applied to condition-based maintenance (CBM), a knowledge-based method taking advantage of human expertise and other system knowledge that can serve as an alternative in cases in which machine learni...
Aerosols exhaled from the lungs have distinctive patterns that can be linked to the abnormalities of the lungs. Yet, due to their intricate nature, it is highly challenging to analyze and distinguish these aerosol patterns. Small airway diseases pose...
Variation in gaze behavior due to age is currently a considerable challenge in building reliable eye-tracking systems for Autism Spectrum Disorder (ASD) diagnosis. However, existing strategies often focus on static gaze representation or dataset-base...
Deep knowledge tracing (KT) models estimate students’ evolving skill mastery from sequences of question–response events and predict whether the next response will be correct. They are often compared using AUC, a score of how well predicti...
Photovoltaic systems are a core component of eco-friendly energy technologies and are now widely utilized across the world for power generation. However, solar modules that are continuously exposed to the external environment experience gradual perfo...
In this study, we developed a leakage-free time-series machine learning framework to improve the accuracy of short-term (10 min ahead) wind speed forecasting. The measurements were obtained from real operational data collected at the Bandırma/Ba...
Background: Dengue fever remains a major global health problem, and early diagnosis is challenging where confirmatory testing is limited. Machine-learning studies using routine hematological data have focused mainly on discrimination, whereas calibra...
This work focuses on the evaluation of third-order simplified spherical harmonics (SP3) model-based image reconstruction with respect to its clinical utility to diagnose rheumatoid arthritis (RA). The existing clinical data of 219 fingers was reconst...
This paper presents a hybrid finite element method (FEM)–analytical model of a three-phase squirrel cage induction motor solved using parallel processing for reducing the simulation time. The growing development in artificial intelligence (AI)...
COVID-19 has shaken the entire world economy and affected millions of people in a brief period. COVID-19 has numerous overlapping symptoms with other upper respiratory conditions, making it hard for diagnosticians to diagnose correctly. Several mathe...
Background/Objectives: Establishing drowning as the cause of death remains one of the most challenging tasks in forensic pathology, particularly when classical autopsy findings are absent, nonspecific, or compromised by decomposition. Molecular bioma...
Operation and maintenance costs are a major contributor to the Levelized Cost of Energy for electricity produced by offshore wind and can be significantly reduced if existing corrective actions are performed as efficiently as possible and if future c...
During the process of disease diagnosis, overdiagnosis can lead to potential health loss and unnecessary anxiety for patients as well as increased medical costs, while underdiagnosis can result in patients not being treated on time. To deal with thes...
Forest fires have devastating effects on extensive forest areas, compromising vital ecological services such as air purification, water conservation, and recreational opportunities, thus posing a significant socioeconomic threat. Furthermore, the ris...
Background: Knowledge of the anatomy of pulmonary arteries is essential in many invasive procedures concerning pulmonary circulation. In the diagnosis and treatment of chronic thromboembolic pulmonary hypertension (CTEPH), two-dimensional (2D) pulmon...
We have read the article titled “Accuracy of New Deep Learning Model-Based Segmentation and Key-Point Multi-Detection Method for Ultrasonographic Developmental Dysplasia of the Hip (DDH) Screening” by Lee et al. [...]
In recent years, infectious disease diagnosis has increasingly turned to host-centered approaches as a complement to pathogen-directed ones. The former, however, typically requires the interpretation of complex multiple biomarker datasets to arrive a...
Aero-engines are faced with severe challenges of availability and reliability in the increasing operation, and traditional gas path filtering diagnostic methods have limitations restricted by various factors such as strong nonlinearity of the system...
Background: The increasing utilization of diagnostic imaging has raised concerns regarding imaging overuse, unnecessary radiation exposure, and downstream diagnostic cascades. Because primary care physicians serve as the first point of contact for mo...
Dry-type air-core reactors (DARs) often have inter-turn short circuit (ITSC) faults. However, traditional fault detection methods for DARs generally demonstrate poor timeliness and low sensitivity, and few methods combine intelligent algorithms for o...
This study compared the diagnostic performance of different ultrasound-based models in discriminating between benign and malignant ovarian masses in a Filipino population. This was a prospective cohort study in women with findings of an ovarian mass...
Making complex medical decisions is becoming an increasingly challenging task due to the growing amount of available evidence to consider and the higher demand for personalized treatment and patient care. IT systems for the provision of clinical deci...
The fuel system, which aims to provide sufficient fuel to the engine to maintain thrust and power, is one of the most critical systems in the aircraft. However, possible degradation modes, such as leakage and blockage, can lead to component failure,...
In this article, a description is presented of simulation investigations concerning the quality of regeneration effects of a technical object in an intelligent system with an artificial neural network. All repairable technical objects used are subjec...
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