Academic Articles & Research Papers

Identifying private pumping wells in a land subsidence area in Taiwan using deep learning technology and street view images

Study region: The Choushui River Fan, Taiwan. Study focus: Groundwater overdraft has led to not only groundwater depletion but also environmental disasters, such as subsidence and seawater intrusion in the Choushui River Alluvial Fan, Taiwa...

A 2D and 3D segmentation-based microstructure study on the role of brittle phases in diffusion brazed AISI 304L/NiCrSiFeMoB joints

Nickel-based filler metals are frequently used in high temperature vacuum diffusion brazing for austenitic stainless-steel joints when components are subjected to high static or dynamic loads, corrosive environments and elevated temperature...

An introduction to deep learning

Deep learning allows automatically learning multiple levels of representations of the underlying distribution of the data to be modeled. In this work, a specific implementation called stacked denoising autoencoders is explored. We contribut...

Research on Strategies and Technologies for Resource Management and Control of Heterogeneous Network of High and Low Orbit Satellites

With the vigorous development of space communication technology and the continuous advancement of space-integrated-ground information network, satellite communication networks resource management and control is becoming more and more comple...

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning SystemResearch in context

Summary: Background: Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it...

Deep Learning in Mammography

OBJECTIVES: The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an independent, dual-center mam...

Diagnostic utility of body fat distribution parameters in distinguishing osteosarcopenia from osteoporosis or sarcopenia alone in postmenopausal women: a retrospective cross-sectional study.

Research Progress on Distributed Fiber Optic Event Recognition Methods Under Data Constraints

Due to the dynamic monitoring capability, Distributed Acoustic Sensing (DAS) has been widely deployed in various industrial scenarios. Deep learning greatly boosts the event detection accuracy of fiber sensing systems. Nevertheless, practic...

Intelligent Distribution-Network Fault Handling via Cross-Modal Semantic Fusion and Knowledge-Graph Reasoning

Power distribution network fault handling imposes stringent requirements on both response timeliness and decision reliability. The high penetration of distributed renewable generation, the widespread deployment of power-electronic devices, ...

Machine learning insight in quality control and maintenance management of drilling mud pumps

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

The distribution of antibiotic resistance and virulence factor genes in the sediment of Inexpressible Island, East Antarctica.

Performance Analysis and Optimization of Terahertz Metamaterial Absorbers Using Machine Learning-Based Inverse Modeling

We present a tunable broadband terahertz (THz) metamaterial absorber with a structurally simple, single-layered vanadium dioxide (VO2) elliptical ring resonator. This design achieves a wide, near-perfect absorption band (3.5–5 THz) w...

Randomized iterative trajectory reweighting for steady-state distributions without discretization error.

Bayesian machine learning-based method for prediction of slope failure time

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomen...

Cybersecurity in Smart Grids: Detecting False Data Injection Attacks Utilizing Supervised Machine Learning Techniques

By integrating advanced technologies and data-driven systems in smart grids, there has been a significant revolution in the energy distribution sector, bringing a new era of efficiency and sustainability. Nevertheless, with this advancement...

Machine learning in pain research

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain?

In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images i...

Source apportionment and stochastic evaluation of soil contamination and human health risks of potentially toxic elements in Nangodi, northern Ghana

Abstract Artisanal and Small-Scale Mining (ASM) is a critical driver of soil contamination in West Africa, yet quantifying the relative contributions of natural and anthropogenic sources remains a major challenge. This study presents an int...

High temperature Nb-Si alloys using data science: optimization of fracture toughness and high-temperature strength

Abstract High temperature Nb-Si based alloys face a critical challenge: achieving adequate room-temperature fracture toughness ( > 18 MPa·m1/2) for processing while maintaining high-temperature strength, properties that typically compete wi...

Revealing the dynamic evolution of interfacial water during Mg anodic dissolution

Though magnesium alloys possess attractive mechanical properties, their applications are severely limited by galvanic corrosion, due to the rapid anodic dissolution and anomalous hydrogen evolution. In this work, well-tempered metadynamics ...