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Understanding the merging behavior patterns at freeway on-ramps is important for assistanting the decisions of autonomous driving. This study develops a primitive-based framework to identify the driving patterns during merging processes and…

Signal Processing · Electrical Eng. & Systems 2021-08-03 Yue Zhang , Yajie Zou , Lingtao Wuand Wanbing Han

Motivation: The abundance of gene flow in the Tree of Life challenges the notion that evolution can be represented with a fully bifurcating process, as this process cannot capture important biological realities like hybridization,…

Populations and Evolution · Quantitative Biology 2023-11-10 Zhaoxing Wu , Claudia Solis-Lemus

Background: In the marine environment, where there are few absolute physical barriers, contemporary contact between previously isolated species can occur across great distances, and in some cases, may be inter-oceanic. [..] in the minke…

Adaptation to local environments often occurs through natural selection acting on a large number of loci, each having a weak phenotypic effect. One way to detect these loci is to identify genetic polymorphisms that exhibit high correlation…

Populations and Evolution · Quantitative Biology 2015-03-20 Eric Frichot , Sean Schoville , Guillaume Bouchard , Olivier François

Rice disease classification is a critical task in agricultural research, and in this study, we rigorously evaluate the impact of integrating feature extraction methodologies within pre-trained convolutional neural networks (CNNs). Initial…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Md. Shohanur Islam Sobuj , Md. Imran Hossen , Md. Foysal Mahmud , Mahbub Ul Islam Khan

A physics-informed machine learning framework based on holomorphic neural networks is introduced for detecting cracks in two-dimensional solids from strain or displacement data. Crack detection is formulated as an inverse problem in which…

Computational Engineering, Finance, and Science · Computer Science 2026-03-16 Jonas Hund , Nicolas Cuenca , Tito Andriollo

High-throughput pheno-, geno-, and envirotyping allows characterization of plant genotypes and the trials they are evaluated in, producing different types of data. These different data modalities can be integrated into statistical or…

Biological organisms exhibit diverse strategies for adapting to varying environments. For example, a population of organisms may express the same phenotype in all environments (`unvarying strategy'), or follow environmental cues and express…

Populations and Evolution · Quantitative Biology 2022-06-08 BingKan Xue , Pablo Sartori , Stanislas Leibler

The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is…

Machine Learning · Computer Science 2023-07-31 Anabia Sohail , Bibi Ayisha , Irfan Hameed , Muhammad Mohsin Zafar , Hani Alquhayz , Asifullah Khan

Heterogeneity is a hallmark of complex diseases. Regression-based heterogeneity analysis, which is directly concerned with outcome-feature relationships, has led to a deeper understanding of disease biology. Such an analysis identifies the…

Methodology · Statistics 2022-11-29 Ziye Luo , Xinyue Yao , Yifan Sun , Xinyan Fan

Antimicrobial Resistance (AMR) is a rapidly escalating global health crisis. While genomic sequencing enables rapid prediction of resistance phenotypes, current computational methods have limitations. Standard machine learning models treat…

Machine Learning · Computer Science 2025-09-30 Md. Saiful Bari Siddiqui , Nowshin Tarannum

The discovery of disease biomarkers from gene expression data has been greatly advanced by feature selection (FS) methods, especially using ensemble FS (EFS) strategies with perturbation at the data level (i.e., homogeneous, Hom-EFS) or…

Machine Learning · Computer Science 2021-08-03 Felipe Colombelli , Thayne Woycinck Kowalski , Mariana Recamonde-Mendoza

Recent studies have consistently inferred high rates of adaptive molecular evolution between Drosophila species. At the same time, the Drosophila genome evolves under different rates of recombination, which results in partial genetic…

Populations and Evolution · Quantitative Biology 2014-09-09 Stephan Schiffels , Michael Lässig , Ville Mustonen

Assessing the health status (HS) of system/component has long been a challenging task in the prognostic and health management (PHM) study. Differed from other regression based prognostic task such as predicting the remaining useful life,…

Signal Processing · Electrical Eng. & Systems 2022-04-12 Zekun Wu , Kaiwei Wu

The hidden Markov model (HMM) provides a powerful framework for inference in time-varying environments, where the underlying state evolves according to a Markov chain. To address the optimal filtering problem in general dynamic settings, we…

Systems and Control · Electrical Eng. & Systems 2025-06-10 Dongyan Sui , Haotian Pu , Siyang Leng , Stefan Vlaski

Significant phylogenetic codivergence between plant or animal hosts ($H$) and their symbionts or parasites ($P$) indicate the importance of their interactions on evolutionary time scales. However, valid and realistic methods to test for…

Populations and Evolution · Quantitative Biology 2008-08-28 Chris L. Schardl , Kelly D. Craven , Adam Lindstrom , Skyler Speakman , Arnold Stromberg , Ruriko Yoshida

Profile hidden Markov models (pHMMs) are widely employed in various bioinformatics applications to identify similarities between biological sequences, such as DNA or protein sequences. In pHMMs, sequences are represented as graph…

The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome…

Quantitative Methods · Quantitative Biology 2015-01-06 Peng Yang , Xiaoquan Su , Le Ou-Yang , Hon-Nian Chua , Xiao-Li Li , Kang Ning

Fully Homomorphic Encryption (FHE) allows for computation directly on encrypted data and enables privacy-preserving neural inference in the cloud. Prior work has focused on models with dense inputs (e.g., CNNs), with less attention given to…

Cryptography and Security · Computer Science 2026-02-23 Karthik Garimella , Austin Ebel , Gabrielle De Micheli , Brandon Reagen

Insider threat detection assumes that an adaptive insider leaves behavioral residue distinguishing them from legitimate users. We test this assumption against an LLM-driven adaptive insider in a controlled multi-agent simulator. Our…

Cryptography and Security · Computer Science 2026-05-11 Vickson Ferrel