There has been a lot of interest in sufficient dimension reduction (SDR) methodologies, as well as nonlinear extensions in the statistics literature. The SDR methodology has previously been motivated by several considerations: (a) finding data-driven...
Analyzing the urban spatial structure of a city is a core topic within urban geographical information science that has the ability to assist urban planning, site selection, location recommendation, etc. Among previous studies, comprehending the funct...
Every finite-dimensional unitary representation of the N-extended world line supersymmetry without central charges may be obtained by a sequence of differential transformations from a direct sum of minimal Adinkras, simple supermultiplets that are id...
In recent years, heavy rainfall-induced flood incidents have occurred frequently in subway stations worldwide. Flooding in complex underground facilities, such as subway stations, can result in significant casualties and property damage. Therefore, i...
Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for...
Federated learning (FL) enables collaborative model training without centralizing raw data, yet practical deployments remain vulnerable to security threats such as Byzantine model poisoning, stealthy backdoor implantation, and integrity attacks that...
To interpret the nonlinear system identification of multi-degree-of-freedom vibrating structures with freeplay, an estimation procedure based on subspace method in time domain is developed in this paper. Two types of freeplay, namely, central freepla...
Finger vein recognition (FVR) has significant potential in biometrics due to its high accuracy and intrinsic liveness detection capabilities. However, the increasingly stringent privacy regulations have presented severe data security challenges for t...
With the steady improvement of advanced manufacturing processes and big data technologies, modern industrial systems have become large-scale. To enhance the sensitivity of fault detection (FD) and overcome the drawbacks of the centralized FD framewor...
Computing cross-partial derivatives using fewer model runs is relevant in modeling, such as stochastic approximation, derivative-based ANOVA, exploring complex models, and active subspaces. This paper introduces surrogates of all the cross-partial de...
Over the last decades, most agricultural land has been converted into residential colonies to accommodate the rapid population expansion. Population growth and urbanization result in negative consequences on the environment. Such land has experienced...
In this study, we develop quantum measurement theory for quantum systems described by C
In this paper, we propose a semi-implicit difference scheme for solving one-dimensional nonlinear space-fractional diffusion equations. The method is first-order accurate in time and second-order accurate in space. It uses a fractional central differ...
A number of pennate diatom genera typically have teratogenic deformations of their siliceous frustules due to the effects of environmental stress, such as high concentrations of heavy metals and low pH. However, the quantitative assessment of these d...
This manuscript proposes the possibility of concatenated signatures (instead of images) obtained from different integral transforms, such as Fourier, Mellin, and Hilbert, to classify skin lesions. Eight lesions were analyzed using some algorithms of...
With the continuous advancement of electromagnetic countermeasures, new types of interference signals (e.g., multi-polarization suppression interference) pose a significant threat to conventional Global Navigation Satellite System (GNSS) services, ev...
Due to its advantages of large transportation volume and low transportation cost, container shipping has become an important transportation mode in current international trade. The recovery of the shipping industry in 2021 and the signing of RCEP mak...
Residuals play a central role in linear regression, yet their geometry is often hidden by inverse- and pseudoinverse-based formulas. We develop a rank-aware framework for residual projection that makes the underlying orthogonality explicit. When the...
In 1933, Kolmogorov synthesized the basic concepts of probability that were in general use at the time into concepts and deductions from a simple set of axioms that said probability was a
Recently, a derivative-free optimization algorithm was proposed that utilizes a minimum Frobenius norm (MFN) Hessian update for estimating the second derivative information, which in turn is used for accelerating the search. The proposed update formu...
This paper addresses the challenge of segmenting consumer behavior in contexts characterized by both numerical regularities and semantic variability. Traditional models, such as RFM-based segmentation, capture the transactional dimension but neglect...
Mixed pixels remain a central obstacle to reliable endmember extraction from hyperspectral imagery. We present AMEE–PPI, a hybrid method that embeds the Pure Pixel Index (PPI) within morphological structuring elements and propagates spectral pu...
High-dimensional surrogate modeling with limited high-fidelity data poses a major challenge in uncertainty quantification. Classical supervised dimension reduction methods often fail in this setting due to insufficient accurate observations, while lo...
In this paper, we present a high resolution 3-D tomographic model of the upper mantle obtained from a large number of teleseismic travel time data from the ISC in the central Philippines. There are 2921 teleseismic events and 32,224 useful relative t...
Protein is one of the primary biochemical macromolecular regulators in the compartmental cellular structure, and the subcellular locations of proteins can therefore provide information on the function of subcellular structures and physiological envir...
The application of machine learning (ML) algorithms for processing remote sensing data is momentous, particularly for mapping hydrothermal alteration zones associated with porphyry copper deposits. The unsupervised Dirichlet Process (DP) and the supe...
Surface transient electromagnetic (TEM) data with large transmitter loops for deep mineral exploration are often complicated by the non-trivial coupling between extended sources and arbitrarily oriented geological targets. This case study reports a T...
Multi-dimensional classification (MDC), in which the training data are concurrently associated with numerous label variables across many dimensions, has garnered significant interest recently. Most of the current MDC methods are based on the framewor...
This paper surveys recent progress in our search for an appropriate internal space algebra for the standard model (SM) of particle physics. After a brief review of the existing approaches, we start with the Clifford algebras involving operators of le...
Federated learning enables collaborative model training without centralizing private data, yet its deployment on edge devices remains constrained by communication overhead, heterogeneous data distributions, and privacy leakage from shared model updat...