14 papers · ranked by Valyu relevance
Nan Zhuang, Zhaogang Ren, Dongyao Yang, Xu Tian + 2 more
The gearbox is a critical component in modern industrial systems, directly determining the operational reliability of machinery. Therefore, effective fault diagnosis is essential to ensure its proper functioning. Modern diagnostic approaches often employ accelerometers to monitor vibration signals and apply data-driven…
Seewoo Li, Guemin Lee
The article proposes a new approach to estimating the latent distribution of item response theory (IRT) using kernel density estimation (KDE), particularly the solve-the-equation (STE) algorithm developed by Sheather and Jones (1991). As with existing methods, the KDE method aims to estimate the latent distribution of…
Parisa Shahnazari, Kaveh Kavousi, Hamid Reza Khorram Khorshid, Bahram Goliaei + 2 more
Integrating multiple omics modalities is a crucial strategy in cancer research, particularly in metabolomics, enabling early detection and detailed exploration of cancer biomarker signatures. This study evaluates five strategies for integrating metabolomics data from liquid chromatography-mass spectrometry, gas…
Shipeng Ren, Guoqing Yang, Deyin Yu, Anqi Wang + 3 more
Discovering meaningful feature (molecule) combinations to define simple, accurate, and easily interpretable decision rules for disease classification and prediction can improve the study of disease diagnosis and prognosis. However, the computational time complexity of constructing feature combinations for each feature…
Yi Ding, Ying Zhao, Yan Pei, Antonio Falcó
Kernel methods are widely applied across various domains; however, structural limitations of reproducing kernels in Hilbert spaces pose significant challenges. Many challenges inherent to Hilbert spaces can be effectively addressed within the framework of Banach spaces. In this work, we define the semi-inner product…
O. H. L. Preston, T. J. Rogers, K. Worden
This paper presents a detailed analysis of a process for recovering multi-degree-of-freedom Volterra kernels using neural network weights, addressing the fact that such Higher-order Frequency Response Functions (HFRFs) have not previously been directly recovered from data. A novel method is proposed for HFRF recovery…
Aravind R. Krishnan, Thomas Z. Li, Lucas W. Remedios, Michael E. Kim + 11 more
Kernel harmonization is an approach that mitigates systematic differences in quantitative measurements due to the variability of reconstruction kernels. The goal of kernel harmonization is to standardize the pixel noise in images reconstructed with different kernels to a common reference kernel, ensuring comparable and…
Jennie Martin, Michele Ceriotti, Graeme M. Day
Kernel and Generalized Convex Hull for Molecular Crystal Structure Prediction Authors: Jennie Martin, Michele Ceriotti, Graeme M. Day We adapted an existing approach to identifying stabilizable crystal structures from prediction setsthe Generalized Convex Hull (GCH)to improve its application to molecular crystal…
Chendi Han, Zhengshi Yang, Xiaowei Zhuang, Dietmar Cordes
Recent studies have extended nonlinear kernels to Kernel Canonical Correlation Analysis (KCCA), enabling more flexible modeling of complex relationships globally. Building on these developments, we propose three key enhancements to nonlinear KCCA. First, inspired by self-supervised learning in machine learning…
JungWoo Park, Minju Kang, Seungho Jeon, Seong Oun Hwang + 4 more
Fault localization (FL) is the task of identifying code locations responsible for bugs in software, and it is a prerequisite step in the bug-fixing process. FL in large-scale systems such as the Linux kernel involves three core challenges: First, the vast codebase fundamentally complicates fault search. Second, the…
Guiqin Liang, Jian Zhang, Dave Winkler
An accurate classification of material stability often requires fusing multiple features under uncertainty. Dempster-Shafer (D-S) theory is a powerful framework for multi-source information fusion under uncertainty. However, its effectiveness critically depends on the quality of basic probability assignments (BPAs)…
Sunil Kumar Prabhakar, Dong-Ok Won, Mahmoud Amouzadeh Tabrizi
To identify hypertension, Ballistocardiograph (BCG) signals can be primarily utilized. The BCG signal must be thoroughly understood and interpreted so that its application in the classification process could become clearer and more distinct. Various unhealthy habits such as excess consumption of alcohol and tobacco…
Jeffrey Wu, Gareth W. Peters, Alex Franks, Laleh Tafakori
This paper proposes a procedure for fitting a spatiotemporal model with an interpretable and parsimonious dependence structure to high-dimensional non-Gaussian data. A graph is estimated to represent spatial dependence, and a locally periodic kernel is estimated to represent temporal dependence. These two components…
Jiayi Bian, Jingjing Wu, M Ethan MacDonald, Lang Wu + 3 more
In genetic association studies, permutation tests serve as a cornerstone to estimate P-values. This is because researchers may design new test statistics without a known closed-form distribution, or the assumption of a well-established test may not hold. However, permutation tests require a vast number of permutations…