arXiv subjects

Lihong Zhang

Publications and source records attributed to Lihong Zhang.

10 recordsLinked to original sources

arXiv2026

A Curved Monopole Antenna for HF Radar with Enhanced Gain and Bandwidth

This paper presents the design and simulation of a new curved monopole antenna optimized for skywave HF radar applications, with a systematic investigation of the effects of curvature and fixed-section length on antenna performance. The proposed design achieves improved impedance matching, broader bandwidth, and enhanced realized gain compared to a conventional quarter-wavelength monopole at 15 MHz. Parametric analysis shows that fully bending the monopole degrades performance, whereas introducing a straight section and carefully optimizing the curvature enables a 18.5% gain increase and a 400 kHz bandwidth expansion. The single-element design is further extended to a 12-element linear array with 0.45λ spacing (where λ is the wavelength), demonstrating stable embedded-element behavior and improved low-to- moderate elevation gain for skywave over-the-horizon radar operation. At θ = 30°, the proposed array achieves 14.04 dBi compared to 13.11 dBi for the reference array, corresponding to 24% gain enhancement, which is significant in high-power HF radar systems. These results confirm that the proposed curved monopole antenna provides a compact, broadband, and scalable solution for next-generation HF radar arrays.

eess.SY↗

arXiv2025

Physics-Informed Neural Networks for Enhanced Interface Preservation in Lattice Boltzmann Multiphase Simulations

This paper presents an improved approach for preserving sharp interfaces in multiphase Lattice Boltzmann Method (LBM) simulations using Physics-Informed Neural Networks (PINNs). Interface diffusion is a common challenge in multiphase LBM, leading to reduced accuracy in simulating phenomena where interfacial dynamics are critical. We propose a coupled PINN-LBM framework that maintains interface sharpness while preserving the physical accuracy of the simulation. Our approach is validated through droplet simulations, with quantitative metrics measuring interface width, maximum gradient, phase separation, effective interface width, and interface energy. The enhanced visualization techniques employed in this work clearly demonstrate the superior performance of PINN-LBM over standard LBM for multiphase simulations, particularly in maintaining well-defined interfaces throughout the simulation. We provide a comprehensive analysis of the results, showcasing how the neural network integration effectively counteracts numerical diffusion, while maintaining physical consistency with the underlying fluid dynamics.

physics.flu-dyn↗

arXiv2025

Selective Attention Federated Learning: Improving Privacy and Efficiency for Clinical Text Classification

Federated Learning (FL) faces major challenges regarding communication overhead and model privacy when training large language models (LLMs), especially in healthcare applications. To address these, we introduce Selective Attention Federated Learning (SAFL), a novel approach that dynamically fine-tunes only those transformer layers identified as attention-critical. By employing attention patterns to determine layer importance, SAFL significantly reduces communication bandwidth and enhances differential privacy resilience. Evaluations on clinical NLP benchmarks (i2b2 Clinical Concept Extraction and MIMIC-III discharge summaries) demonstrate that SAFL achieves competitive performance with centralized models while substantially improving communication efficiency and privacy preservation.

cs.CL↗

arXiv2025

Federated Learning with Layer Skipping: Efficient Training of Large Language Models for Healthcare NLP

Federated learning (FL) enables collaborative model training across organizations without sharing raw data, addressing crucial privacy concerns in healthcare natural language processing (NLP). However, training large language models (LLMs) in federated settings faces significant challenges, including communication overhead and data heterogeneity. We propose Layer-Skipping Federated Learning, where only selected layers of a pre-trained LLM are fine-tuned across clients while others remain frozen. Applied to LLaMA 3.2-1B, our approach reduces communication costs by approximately 70% while maintaining performance within 2% of centralized training. We evaluate our method on clinical NER and classification tasks using i2b2 and MIMIC-III datasets. Our experiments demonstrate that Layer-Skipping FL outperforms competitive baselines, handles non-IID clinical data distributions effectively, and shows robustness when combined with differential privacy. This approach represents a practical solution for privacy-preserving collaborative learning in healthcare NLP.

cs.LG↗

arXiv2024

A Large-scale Investigation of Semantically Incompatible APIs behind Compatibility Issues in Android Apps

Application Programming Interface (API) incompatibility is a long-standing issue in Android application development. The rapid evolution of Android APIs results in a significant number of API additions, removals, and changes between adjacent versions. Unfortunately, this high frequency of alterations may lead to compatibility issues, often without adequate notification to developers regarding these changes. Although researchers have proposed some work on detecting compatibility issues caused by changes in API signatures, they often overlook compatibility issues stemming from sophisticated semantic changes. In response to this challenge, we conducted a large-scale discovery of incompatible APIs in the Android Open Source Project (AOSP) by leveraging static analysis and pre-trained Large Language Models (LLMs) across adjacent versions. We systematically formulate the problem and propose a unified framework to detect incompatible APIs, especially for semantic changes. It's worth highlighting that our approach achieves a 0.83 F1-score in identifying semantically incompatible APIs in the Android framework. Ultimately, our approach detects 5,481 incompatible APIs spanning from version 4 to version 33. We further demonstrate its effectiveness in supplementing the state-of-the-art methods in detecting a broader spectrum of compatibility issues (+92.3%) that have been previously overlooked.

cs.SE↗

arXiv2024

Confidence interval estimation of mixed oil length with conditional diffusion model

Accurately estimating the mixed oil length plays a big role in the economic benefit for oil pipeline network. While various proposed methods have tried to predict the mixed oil length, they often exhibit an extremely high probability (around 50\%) of underestimating it. This is attributed to their failure to consider the statistical variability inherent in the estimated length of mixed oil. To address such issues, we propose to use the conditional diffusion model to learn the distribution of the mixed oil length given pipeline features. Subsequently, we design a confidence interval estimation for the length of the mixed oil based on the pseudo-samples generated by the learned diffusion model. To our knowledge, we are the first to present an estimation scheme for confidence interval of the oil-mixing length that considers statistical variability, thereby reducing the possibility of underestimating it. When employing the upper bound of the interval as a reference for excluding the mixed oil, the probability of underestimation can be as minimal as 5\%, a substantial reduction compared to 50\%. Furthermore, utilizing the mean of the generated pseudo samples as the estimator for the mixed oil length enhances prediction accuracy by at least 10\% compared to commonly used methods.

stat.AP↗

arXiv2022

Combining Topic Modeling with Grounded Theory: Case Studies of Project Collaboration

This paper proposes an Artificial Intelligence (AI) Grounded Theory for management studies. We argue that this novel and rigorous approach that embeds topic modelling will lead to the latent knowledge to be found. We illustrate this abductive method using 51 case studies of collaborative innovation published by Project Management Institute (PMI). Initial results are presented and discussed that include 40 topics, 6 categories, 4 of which are core categories, and two new theories of project collaboration.

cs.HC↗

arXiv2020

Properties of Berwald scalar curvature

In this short paper, we prove that a Finsler manifold with vanishing Berwald scalar curvature has zero $\mathbf{E}$-curvature. As a consequence, Landsberg manifolds with vanishing Berwald scalar curvature are Berwald manifolds. This improves a previous result in \cite{Li}. For $(α,β)$-metrics on manifold of dimension greater than 2, if the mean Landsberg curvature and the Berwald scalar curvature both vanish, the Berwald curvature also vanishes.

math.DG↗

arXiv2016

Decreased aneurysmal subarachnoid hemorrhage incidence rate in elderly population than in middle aged population: a retrospective analysis of 8,144 cases in Mainland China

Purpose: Rupture of an intracranial aneurysm is the most common cause of subarachnoid haemorrhage (SAH), which is a life-threatening acute cerebrovascular event that typically affects working-age people. This study aims to investigate the aneurysmal SAH incidence rate in elderly population than in middle aged population in China. Materials and methods: Aneurysmal SAH cases were collected retrospectively from the archives of 21 hospitals in Mainland China. All the cases collected were from September 2016 and backward consecutively for a period of time up to 8 years. SAH was initially diagnosed by brain computed tomography, and CT angiography (CTA) or digital subtraction angiography (DSA) was followed and SAH was confirmed to be due to cerebral aneurysm. When for cases multiple bleeding occurred, the age of the first SAH was used in this study. The toltal incidence from all hospital at each age were summed together for females and males; then adjusted by the total population number at each age for females and males. The total population data was from the 2010 population census of the People's Republic of China. Results: In total there were 8,144 cases, with 4,861 females and 3,283 males. Our analysis shows for both females and males the relative aneurysmal SAH rate started to decrease after around 65 years old. The males the relative aneurysmal SAH rate might have started to decrease after around 55 years old. Conclusion: In contrast to previous reports, our data demonstrated a decreased aneurysmal subarachnoid hemorrhage incidence rate in elderly population than in middle aged population. Our data therefore support the hypothesis that aneurysms do not grow progressively once they form but probably either rupture or stabilize and that very elderly patients are at a reduced risk of rupture compared with atients who are younger with the same-sized aneurysms.

q-bio.TO↗

arXiv2012

On 3-Lie algebras with abelian ideals and subalgebras

In this paper, we study the maximal dimension $α(L)$ of abelian subalgebras and the maximal dimension $β(L)$ of abelian ideals of m-dimensional 3-Lie algebras $L$ over an algebraically closed field. We show that these dimensions do not coincide if the field is of characteristic zero, even for nilpotent 3-Lie algebras. We then prove that 3-Lie algebras with $β(L) = m-2$ are 2-step solvable (see definition in Section 2). Furthermore, we give a precise description of these 3-Lie algebras with one or two dimensional derived algebras. In addition, we provide a classification of 3-Lie algebras with $α(L)=\dim L-2$. We also obtain the classification of 3-Lie algebras with $α(L)=\dim L-1$ and with their derived algebras of one dimension.

math-ph↗