This study discusses the properties and decompositions of the traveltime sensitivity kernels in elastic isotopic and transversely isotropic media. Analytical solutions in homogeneous isotropic elastic media are derived and help better understand thei...
We derived gravimetric mass change products, i.e., gridded and basin-averaged mass changes, for the Antarctic Ice Sheet (AIS) from time-variable gravity-field solutions acquired by the Gravity Recovery and Climate Experiment (GRACE) mission and its s...
As a nonlinear similarity measure defined in the reproducing kernel Hilbert space (RKHS), the correntropic loss (C-Loss) has been widely applied in robust learning and signal processing. However, the highly non-convex nature of C-Loss results in perf...
Recently, inspired by correntropy, kernel risk-sensitive loss (KRSL) has emerged as a novel nonlinear similarity measure defined in kernel space, which achieves a better computing performance. After applying the KRSL to adaptive filtering, the corres...
The maximum complex correntropy criterion (MCCC) has been extended to complex domain for dealing with complex-valued data in the presence of impulsive noise. Compared with the correntropy based loss, a kernel risk-sensitive loss (KRSL) defined in ker...
Randomized response models aim to protect respondent privacy when sampling sensitive variables but consequently compromise estimator efficiency. We propose a new sampling method, titled joint scrambling, which preserves all true responses while prote...
The constrained recursive maximum correntropy criterion (CRMCC) combats the non-Gaussian noise effectively. However, the performance surface of maximum correntropy criterion (MCC) is highly non-convex, resulting in low accuracy. Inspired by the smoot...
Safety design is a critical concern for energetic materials, with sensitivities and performance parameters becoming increasingly important as energy density rises. However, obtaining experimental data for these properties is costly and risky. Althoug...
Distributed estimation over sensor networks has attracted much attention due to its various applications. The mean-square error (MSE) criterion is one of the most popular cost functions used in distributed estimation, which achieves its optimality on...
In this paper we review and discuss the seismic method based on the analysis of seismic coda waves used in the last 10 years by the present authors and/or their co-workers, to produce separate images of intrinsic- and scattering attenuation in zones...
The structure learning of a Bayesian network (BN) is a crucial process that aims to unravel the complex dependencies relationships among variables using a given dataset. This paper proposes a new BN structure learning method for data with continuous...
Drought stress is a major factor that contributes to disease susceptibility and yield loss in agricultural crops. To identify drought responsive proteins and explore metabolic pathways involved in maize tolerance to drought stress, two maize lines (B...
Development of landscape connectivity and spatial population models is challenging, given the uncertainty of parameters and the sensitivity of models to factors and their interactions over time. Using spatially and temporally explicit simulations, we...
This study examined the gel behavior of naturally-occurring palmyra palm kernel (PPK). Due to the presence of polysaccharide in PPK hydrogels, they exhibit excellent swelling behavior in response to pH. Chemotherapeutic drug 5-fluorouracil (5-FU) was...
In recent years, outliers caused by manual operation errors and equipment acquisition failures often occur, bringing challenges to big data analysis. In view of the difficulties in identifying and correcting outliers of multi-source data, an intellig...
Accurate air conditioning (AC) load prediction under extreme weather conditions is critical for power grid stability and energy management. While tree-based ensemble methods such as XGBoost, LightGBM, and Gradient Boosting have become the dominant pa...
Quantile-oriented sensitivity analysis (QOSA) requires repeated evaluation of conditional quantiles over many conditioning states. A four-moment Hermite model yields closed-form quantiles, but its published two-branch form has a local admissibility g...
Marine velocity-model building using full-waveform inversion (FWI) is strongly affected by acquisition geometry because different surveys sample different parts of the wavefield. In this study, we investigate a sequential OBS (ocean-bottom seismomete...
Stuck pipe incidents are one of the contributors to non-productive time (NPT), where they can result in a higher well cost. This research investigates the feasibility of applying machine learning to predict events of stuck pipes during drilling opera...
This cross-sectional, hypothesis-generating analysis examined six blood metal and volatile organic compound (VOC) biomarkers in relation to self-reported lifetime cancer history among 136 adults whose longest-held job was in construction in the 2009&...
It is considered that a part of the inner core surface where iron in the fluid outer core is precipitated may have melted and formed a mushy region, but its position is not well understood seismologically. We recently analyzed seismic waveforms obser...
Coconut kernel fiber (CKF) is a by-product of coconut oil processing; it is rich in protein and serves as a potential source of bioactive peptides. In this study, from the enzymatic hydrolysis products of CKF (CKFH), a low-molecular-weight CKFH compo...
The intrinsic heterogeneity property of concrete causes strong multiple scatterings during wave propagation, forming coda wave that follows very complex trajectories. As a superposition of multiply scattered waves, coda wave shows great sensitivity t...
Can a replicase be found in the vast sequence space by random drift? We partially answer this question through a proof-of-concept study of the times of occurrence (hitting times) of some critical events in the origins of life for low-dimensional RNA...
Accurate estimation of sparse underwater acoustic channels is challenging because of multipath delay spread, correlated inputs, and impulsive non-Gaussian noise. Existing KRSL-based algorithms still suffer from limited convergence speed and tracking...
When determining subgroups with heterogeneous treatment effects in cancer clinical trials, the threshold of a variable that defines subgroups is often pre-determined by physicians based on their experience, and the optimality of the threshold is not...
Reverse time migration (RTM) exploits time-reversal symmetry and adjoint duality to focus wavefields and reconstruct subsurface reflectivity, but large surveys remain limited by the cost of forward and backward propagation. We present a Graphics Proc...
This paper presents Nyström minimum kernel risk-sensitive loss (NysMKRSL) based control of a three-phase four-wire grid-tied dual-stage PV-hybrid energy storage system, under varying conditions such as irradiation variation, unbalanced load, and abno...
Cleaning loss is an important parameter to judge the performance of a corn combine harvester. At present, there exists the phenomenon that corn cleaning loss rate detection devices have a long signal processing time and low recognition accuracy. To s...
The growing number of security threats has prompted the use of a variety of security techniques. The most common security tools for identifying and tracking intruders across diverse network domains are intrusion detection systems. Machine Learning cl...
Maize kernels were treated using two varieties of drying methodologies, namely combined hot air- and vacuum-drying (HAVD) and natural drying (ND). We performed frequency sweep tests, modified Cole–Cole (MCC) analysis, and frequency–temper...
Memory-dependent evolution equations replace the time derivative of the state by a convolution with a memory kernel
This study evaluates ultra-low-dose computed tomography (ULDCT) protocols concerning the detectability of pulmonary nodules. The influence of tube current settings, kernels, strength levels of third-generation iterative reconstruction algorithms, and...
Sensors based on interferometric systems have been studied due to their wide range of advantages, such as high sensitivity. For these types of sensors, traditional methods, which generally depend on the linear sensitivity of one variable, have been u...
Early detection of pancreatic cancer is difficult, and thus many cases of pancreatic cancer are diagnosed late. When pancreatic cancer is detected, the cancer is usually well developed. Machine learning is an approach that is part of artificial intel...
Precise distinguishing of maize blends and the evaluation of kernel losses enhances the accurate measurement of harvest loss. To address the low accuracy and poor anti-interference ability of traditional maize kernel detection methods under complex c...
Deep learning methods have achieved remarkable success in remote sensing object detection. Existing object detection methods focus on integrating convolutional neural networks (CNNs) and Transformer networks to explore local and global representation...
The maximum correntropy criterion (MCC), as an effective method for dealing with anomalous measurement noise, is widely applied in the design of filters. However, its performance largely depends on the proper setting of the kernel bandwidth, and curr...
The primary objective of the study was to compare a spiral breast computed tomography system (SBCT) to digital breast tomosynthesis (DBT) for the detection of microcalcifications (MCs) in breast specimens. The secondary objective was to compare vario...
Depending on the temperature regime used during roasting, the biochemical and sensory characteristics of macadamia nuts can change. ‘A4′ and ‘Beaumont’ were used as model cultivars to examine how roasting temperatures affected...
The pectic polysaccharides extracted from flaxseed (Linum usitatissiumum L.) mucilage and kernel were characterized as rhamnogalacturonan-I (RG-I). In this study, the conformational characteristics of RG-I fractions from flaxseed mucilage and kernel...
Due to the discreteness, sparsity, multidimensionality, and incompleteness of geotechnical investigation data, traditional methods cannot reasonably predict complex stratigraphic profiles, thus hindering the three-dimensional (3D) reconstruction of g...
Handcrafted radiomics features (HRFs) are quantitative features extracted from medical images to decode biological information to improve clinical decision making. Despite the potential of the field, limitations have been identified. The most importa...
Maize kernel growth is sensitive to heat stress, which is predicted to result in yield loss. However, the response of maize to short-term heat stress during different kernel-growth stages is still not clear. A 3-year field experiment, included two he...
The heterogeneity of grain quality can lead to limited predictability of qualitative and quantitative characteristics of the wheat yield, especially with an increase in the importance of drought and salinity caused by climate change. This study was u...
Maturation and signaling in tumor-associated macrophages are distributed over time rather than concentrated at a single instant. We replace the discrete maturation lag in a tumor–macrophage model with weak and strong gamma memory kernels. Becau...
Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to develop various algorithms for both drowsiness and stress recognition. In contrast to...
Uncertainty estimation is critical for deploying large language models (LLMs) in safety-sensitive and decision-critical applications. Recent approaches estimate semantic uncertainty by clustering multiple sampled responses into equivalence classes an...
Solar dimming due to global climate change is becoming increasingly more common in some agricultural areas. Such low-light stress inhibits maize ear number, kernel number per unit area (KN), and kernel weight (KW) as vital yield components. However,...
Synthetic aperture radar (SAR) target discrimination is an important stage that distinguishes targets from clutters in the radar automatic target recognition field. However, in complex SAR scenes, the performance of some traditional discriminators wi...
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