arXiv subjects

Haiyan Guo

Publications and source records attributed to Haiyan Guo.

18 recordsLinked to original sources

arXiv2026

Tight spectral conditions for the Hamiltonicity of $K_{1,r}$-free split graphs

The Hamiltonicity and related subjects of split graphs, and in particular $K_{1,r}$-free split graphs with $r\ge 3$ received much attention. Dai et al. [Discrete Math. 345 (2022) 112826] conjectured that every $(r-1)$-connected $K_{1,r}$-free split graph is Hamiltonian. They proved the case when $r=4$, and earlier Renjith and Sadagopan [Int. J. Found. Comput. Sci. 33 (2022) 1--32] proved the case when $r=3$. Recently, Liu, Song, Zhang and Lai [Discrete Math. 346 (2023) 113402] proved that a split graph is Hamiltonian if and only if it is fully cycle extendable. So for $r=3,4$ every $(r-1)$-connected $K_{1,r}$-free split graph is fully cycle extendable. We give tight spectral sufficient conditions for a $K_{1,r}$-free split graph to be Hamiltonian for $r=3,4$.

math.CO↗

arXiv2025

Temperature-driven polarization rotation and triclinic phase at morphotropic phase boundary of Pb(Mg1/3Nb2/3)O3-PbTiO3 crystals

Information about the crystal structures in the range of morphotropic phase boundary of ferroelectric perovskite solid solutions is important for understanding their intricate properties which result in wide opportunities for practical applications. However, for the (1-x)Pb(Mg1/3Nb2/3)O3-xPbTiO3 solid solution system this information is contradictory. Different composition-temperature phase diagrams have been reported for this system in literature based on the investigations of single crystals and ceramics using various experimental techniques. In this work we apply polarized light microscopy (PLM), X-ray diffraction (XRD) and dielectric spectroscopy to study the crystal structure and phase transitions in the 0.68Pb(Mg1/3Nb2/3)O3-0.32PbTiO3 single crystal. We confirm the monoclinic MB symmetry (space group Cm) of the room-temperature phase. According to PLM, it transforms with increasing temperature into a triclinic (Tr) phase rather than the previously reported monoclinic MC or tetragonal phase. XRD data are consistent with the presence of Tr phase. The Tr phase transforms to the monoclinic MC (Pm) phase and then to the cubic phase. Ergodic relaxor behavior is observed above the Curie temperature. The unit cell in the MC phase is pseudotetragonal with the lattice parameters a = b < c and small monoclinic angle. In the MB phase the direction of spontaneous polarization is temperature independent and close to the <111> pseudocubic direction. In the Tr and MC phases it changes with temperature so that near the Curie point it is close to [001] axis. No significant anomalies in the dielectric properties or changes in the domain structure are observed at the MB to Tr and Tr to MC phase transitions. The domain structure changes dramatically when the temperature varies within the Tr phase, causing a sharp change in birefringence.

cond-mat.mtrl-sci↗

arXiv2025

ILETIA: An AI-enhanced method for individualized trigger-oocyte pickup interval estimation of progestin-primed ovarian stimulation protocol

In vitro fertilization-embryo transfer (IVF-ET) stands as one of the most prevalent treatments for infertility. During an IVF-ET cycle, the time interval between trigger shot and oocyte pickup (OPU) is a pivotal period for follicular maturation, which determines mature oocytes yields and impacts the success of subsequent procedures. However, accurately predicting this interval is severely hindered by the variability of clinicians'experience that often leads to suboptimal oocyte retrieval rate. To address this challenge, we propose ILETIA, the first machine learning-based method that could predict the optimal trigger-OPU interval for patients receiving progestin-primed ovarian stimulation (PPOS) protocol. Specifically, ILETIA leverages a Transformer to learn representations from clinical tabular data, and then employs gradient-boosted trees for interval prediction. For model training and evaluating, we compiled a dataset PPOS-DS of nearly ten thousand patients receiving PPOS protocol, the largest such dataset to our knowledge. Experimental results demonstrate that our method achieves strong performance (AUROC = 0.889), outperforming both clinicians and other widely used computational models. Moreover, ILETIA also supports premature ovulation risk prediction in a specific OPU time (AUROC = 0.838). Collectively, by enabling more precise and individualized decisions, ILETIA has the potential to improve clinical outcomes and lay the foundation for future IVF-ET research.

q-bio.QM↗

arXiv2024

A graph for which the second largest distance eigenvalue is less than $\frac{-3+\sqrt{5}}{2}$ is chordal

Let $G$ be a connected graph with vertex set $V(G)$. The distance, $d_G(u,v)$, between vertices $u$ and $v$ in $G$ is defined as the length of a shortest path between $u$ and $v$ in $G$. The distance matrix of $G$ is the matrix $D(G)=(d_G(u,v))_{u,v\in V(G)}$. The second largest distance eigenvalue of $G$ is the second largest one in the spectrum of $D(G)$. We show that any connected graph with the second largest distance eigenvalue less than $\frac{-3+\sqrt{5}}{2}$ is chordal, and characterize those bicyclic graphs and split graphs with the second largest distance eigenvalue less than $-\frac{1}{2}$.

math.CO↗

arXiv2024

Speaker Recognition Using Isomorphic Graph Attention Network Based Pooling on Self-Supervised Representation

The emergence of self-supervised representation (i.e., wav2vec 2.0) allows speaker-recognition approaches to process spoken signals through foundation models built on speech data. Nevertheless, effective fusion on the representation requires further investigating, due to the inclusion of fixed or sub-optimal temporal pooling strategies. Despite of improved strategies considering graph learning and graph attention factors, non-injective aggregation still exists in the approaches, which may influence the performance for speaker recognition. In this regard, we propose a speaker recognition approach using Isomorphic Graph ATtention network (IsoGAT) on self-supervised representation. The proposed approach contains three modules of representation learning, graph attention, and aggregation, jointly considering learning on the self-supervised representation and the IsoGAT. Then, we perform experiments for speaker recognition tasks on VoxCeleb1\&2 datasets, with the corresponding experimental results demonstrating the recognition performance for the proposed approach, compared with existing pooling approaches on the self-supervised representation.

cs.SD↗

arXiv2023

On the $α$-spectral radius of hypergraphs

For real $α\in [0,1)$ and a hypergraph $G$, the $α$-spectral radius of $G$ is the largest eigenvalue of the matrix $A_α(G)=αD(G)+(1-α)A(G)$, where $A(G)$ is the adjacency matrix of $G$, which is a symmetric matrix with zero diagonal such that for distinct vertices $u,v$ of $G$, the $(u,v)$-entry of $A(G)$ is exactly the number of edges containing both $u$ and $v$, and $D(G)$ is the diagonal matrix of row sums of $A(G)$. We study the $α$-spectral radius of a hypergraph that is uniform or not necessarily uniform. We propose some local grafting operations that increase or decrease the $α$-spectral radius of a hypergraph. We determine the unique hypergraphs with maximum $α$-spectral radius among $k$-uniform hypertrees, among $k$-uniform unicyclic hypergraphs, and among $k$-uniform hypergraphs with fixed number of pendant edges. We also determine the unique hypertrees with maximum $α$-spectral radius among hypertrees with given number of vertices and edges, the unique hypertrees with the first three largest (two smallest, respectively) $α$-spectral radii among hypertrees with given number of vertices, the unique hypertrees with minimum $α$-spectral radius among the hypertrees that are not $2$-uniform, the unique hypergraphs with the first two largest (smallest, respectively) $α$-spectral radii among unicyclic hypergraphs with given number of vertices, and the unique hypergraphs with maximum $α$-spectral radius among hypergraphs with fixed number of pendant edges.

cs.DM↗

arXiv2023

The Graph feature fusion technique for speaker recognition based on wav2vec2.0 framework

Pre-trained wav2vec2.0 model has been proved its effectiveness for speaker recognition. However, current feature processing methods are focusing on classical pooling on the output features of the pre-trained wav2vec2.0 model, such as mean pooling, max pooling etc. That methods take the features as the independent and irrelevant units, ignoring the inter-relationship among all the features, and do not take the features as an overall representation of a speaker. Gated Recurrent Unit (GRU), as a feature fusion method, can also be considered as a complicated pooling technique, mainly focuses on the temporal information, which may show poor performance in some situations that the main information is not on the temporal dimension. In this paper, we investigate the graph neural network (GNN) as a backend processing module based on wav2vec2.0 framework to provide a solution for the mentioned matters. The GNN takes all the output features as the graph signal data and extracts the related graph structure information of features for speaker recognition. Specifically, we first give a simple proof that the GNN feature fusion method can outperform than the mean, max, random pooling methods and so on theoretically. Then, we model the output features of wav2vec2.0 as the vertices of a graph, and construct the graph adjacency matrix by graph attention network (GAT). Finally, we follow the message passing neural network (MPNN) to design our message function, vertex update function and readout function to transform the speaker features into the graph features. The experiments show our performance can provide a relative improvement compared to the baseline methods. Code is available at xxx.

eess.AS↗

arXiv2022

Joint Reconfigurable Intelligent Surface Location and Passive Beamforming Optimization for Maximizing the Secrecy-Rate

The physical layer security (PLS) is investigated for reconfigurable intelligent surface (RIS) assisted wireless networks, where a source transmits its confidential information to a legitimate destination with the aid of a single small RIS in the presence of a malicious eavesdropper. A new joint RIS location and passive beamforming (J-LPB) optimization scheme is proposed for the sake of maximizing the secrecy rate under the RIS location constraint and the constraint that the modulus of the reflecting coefficient at each RIS's unit is not larger than 1. Specifically, we analyze the optimal location of the RIS, and conclude that the product involving the source-RIS distance and the RIS-destination distance should be minimized. Since the product minimization problem is nonconvex, we then propose a two-tier optimization algorithm for solving it. Based on the near-optimal RIS 3D location obtained, we further formulate the passive beamforming optimization problem, and then propose to apply the Charnes-Cooper transformation along with the sequential rank-one constraint relaxation (SROCR) algorithm to solve it. Our numerical results show that the secrecy rate of the proposed J-LPB optimization scheme is higher than that of the benchmarks. Explicitly, we use the following benchmarks: the near-source-based RIS location and passive beamforming (NSB-LPB) optimization scheme, the near-destination-based RIS location and passive beamforming (NDB-LPB) optimization scheme, and the random RIS location and passive beamforming (R-LPB) optimization scheme. Finally, the benefits of our J-LPB scheme are further increased with the number of RIS units.

cs.IT↗

arXiv2022

Universal Graph Filter Design based on Butterworth, Chebyshev and Elliptic Functions

Graph filters are crucial tools in processing the spectrum of graph signals. In this paper, we propose to design universal IIR graph filters with low computational complexity by using three kinds of functions, which are Butterworth, Chebyshev, and Elliptic functions, respectively. Specifically, inspired by the classical analog filter design method, we first derive the zeros and poles of graph frequency responses. With these zeros and poles, we construct the conjugate graph filters to design the Butterworth high pass graph filter, Chebyshev high pass graph filter, and Elliptic high pass graph filter, respectively. On this basis, we further propose to construct a desired graph filter of low pass, band pass, and band stop by mapping the parameters of the desired graph filter to those of the equivalent high pass graph filter. Furthermore, we propose to set the graph filter order given the maximum passband attenuation and the minimum stopband attenuation. Our numerical results show that the proposed graph filter design methods realize the desired frequency response more accurately than the autoregressive moving average (ARMA) graph filter design method, the linear least-squares fitting (LLS) based graph filter design method, and the Chebyshev FIR polynomial graph filter design method.

eess.SP↗

arXiv2022

Optimal Fractional Fourier Filtering in Time-vertex Graphs signal processing

Graph signal processing (GSP) is an effective tool in dealing with data residing in irregular domains. In GSP, the optimal graph filter is one of the essential techniques, owing to its ability to recover the original signal from the distorted and noisy version. However, most current research focuses on static graph signals and ordinary space/time or frequency domains. The time-varying graph signals have a strong ability to capture the features of real-world data, and fractional domains can provide a more suitable space to separate the signal and noise. In this paper, the optimal time-vertex graph filter and its Wiener-Hopf equation are developed, using the product graph framework. Furthermore, the optimal time-vertex graph filter in fractional domains is also developed, using the graph fractional Laplacian operator and graph fractional Fourier transform. Numerical simulations on real-world datasets will demonstrate the superiority of the optimal time-vertex graph filter in fractional domains over the optimal time-vertex graph filter in ordinary domains and the optimal static graph filter in fractional domains.

eess.SP↗

arXiv2020

On extremal leaf status and internal status of trees

For a vertex $u$ of a tree $T$, the leaf (internal, respectively) status of $u$ is the sum of the distances from $u$ to all leaves (internal vertices, respectively) of $T$. The minimum (maximum, respectively) leaf status of a tree $T$ is the minimum (maximum, respectively) leaf statuses of all vertices of $T$. The minimum (maximum, respectively) internal status of a tree $T$ is the minimum (maximum, respectively) internal statuses of all vertices of $T$. We give the smallest and largest values for the minimum leaf status, maximum leaf status, minimum internal status, and maximum internal status of a tree and characterize the extremal cases. We also discuss these parameters of a tree with given diameter or maximum degree.

cs.DM↗

arXiv2020

An Iterative Graph Spectral Subtraction Method for Speech Enhancement

In this paper, we investigate the application of graph signal processing (GSP) theory in speech enhancement. We first propose a set of shift operators to construct graph speech signals, and then analyze their spectrum in the graph Fourier domain. By leveraging the differences between the spectrum of graph speech and graph noise signals, we further propose the graph spectral subtraction (GSS) method to suppress the noise interference in noisy speech. Moreover, based on GSS, we propose the iterative graph spectral subtraction (IGSS) method to further improve the speech enhancement performance. Our experimental results show that the proposed operators are suitable for graph speech signals, and the proposed methods outperform the traditional basic spectral subtraction (BSS) method and iterative basic spectral subtraction (IBSS) method in terms of both signal-to-noise ratios (SNR) and mean Perceptual Evaluation of Speech Quality (PESQ).

eess.AS↗

arXiv2019

Minimum status, matching and domination of graphs

The minimum status of a graph is the minimum of statuses of all vertices of this graph. We give a sharp upper bound for the minimum status of a connected graph with fixed order and matching number (domination number, respectively), and characterize the unique trees achieving the bound. We also determine the unique tree such that its minimum status is as small as possible when order and matching number (domination number, respectively) are fixed.

cs.DM↗

arXiv2018

Security-Reliability Tradeoff for Distributed Antenna Systems in Heterogeneous Cellular Networks

In this paper, we investigate physical-layer security for a spectrum-sharing heterogeneous cellular network comprised of a macro cell and a small cell, where a passive eavesdropper is assumed to tap the transmissions of both the macro cell and small cell. In the macro cell, a macro base station (MBS) equipped with multiple distributed antennas sends its confidential information to a macro user (MU) through an opportunistic transmit antenna. Meanwhile, in the small cell, a small base station (SBS) transmits to a small user (SU) over the same spectrum used by MBS. We propose an interference-canceled opportunistic antenna selection (IC-OAS) scheme to enhance physical-layer security for the heterogeneous network. To be specific, when MBS sends its confidential message to MU through an opportunistic distributed antenna, a special signal is artificially designed and emitted at MBS to ensure that the received interference at MU from SBS is canceled out. For comparison, the conventional interference-limited opportunistic antenna selection (IL-OAS) is considered as a benchmark. We characterize the security-reliability tradeoff (SRT) for the proposed IC-OAS and conventional IL-OAS schemes in terms of deriving their closed-form expressions of intercept probability and outage probability. Numerical results show that compared with the conventional IL-OAS, the proposed IC-OAS scheme not only brings SRT benefits to the macro cell, but also has the potential of improving the SRT of small cell by increasing the number of distributed antennas. Additionally, by jointly taking into account the macro cell and small cell, an overall SRT of the proposed IC-OAS scheme is shown to be significantly better than that of the conventional IL-OAS approach in terms of a sum intercept probability versus sum outage probability.

cs.IT↗

arXiv2018

Uniform hypergraphs with the first two smallest spectral radii

The spectral radius of a uniform hypergraph $G$ is the the maximum modulus of the eigenvalues of the adjacency tensor of $G$. For $k\ge 2$, among connected $k$-uniform hypergraphs with $m\ge 1$ edges, we show that the $k$-uniform loose path with $m$ edges is the unique one with minimum spectral radius, and we also determine the unique ones with second minimum spectral radius when $m\ge 2$.

math.SP↗

arXiv2018

On the $α$-spectral radius of graphs

For $0\le α\le 1$, Nikiforov proposed to study the spectral properties of the family of matrices $A_α(G)=αD(G)+(1-α)A(G)$ of a graph $G$, where $D(G)$ is the degree diagonal matrix and $A(G)$ is the adjacency matrix. The $α$-spectral radius of $G$ is the largest eigenvalue of $A_α(G)$. We give upper bounds for $α$-spectral radius for unicyclic graphs $G$ with maximum degree $Δ\ge 2$, connected irregular graphs with given maximum degree and and some other graph parameters, and graphs with given domination number, respectively. We determine the unique tree with second maximum $α$-spectral radius among trees, and the unique tree with maximum $α$-spectral radius among trees with given diameter. For a graph with two pendant paths at a vertex or at two adjacent vertex, we prove results concerning the behavior of the $α$-spectral radius under relocation of a pendant edge in a pendant path. We also determine the unique graphs such that the difference between the maximum degree and the $α$-spectral radius is maximum among trees, unicyclic graphs and non-bipartite graphs, respectively.

math.CO↗

arXiv2017

Power-Constrained Secrecy Rate Maximization for Joint Relay and Jammer Selection Assisted Wireless Networks

In this paper, we examine the physical layer security for cooperative wireless networks with multiple intermediate nodes, where the decode-and-forward (DF) protocol is considered. We propose a new joint relay and jammer selection (JRJS) scheme for protecting wireless communications against eavesdropping, where an intermediate node is selected as the relay for the sake of forwarding the source signal to the destination and meanwhile, the remaining intermediate nodes are employed to act as friendly jammers which broadcast the artificial noise for disturbing the eavesdropper. We further investigate the power allocation among the source, relay and friendly jammers for maximizing the secrecy rate of proposed JRJS scheme and derive a closed-form sub-optimal solution. Specificially, all the intermediate nodes which successfully decode the source signal are considered as relay candidates. For each candidate, we derive the sub-optimal closed-form power allocation solution and obtain the secrecy rate result of the corresponding JRJS scheme. Then, the candidate which is capable of achieving the highest secrecy rate is selected as the relay. Two assumptions about the channel state information (CSI), namely the full CSI (FCSI) and partial CSI (PCSI), are considered. Simulation results show that the proposed JRJS scheme outperforms the conventional pure relay selection, pure jamming and GSVD based beamforming schemes in terms of secrecy rate. Additionally, the proposed FCSI based power allocation (FCSI-PA) and PCSI based power allocation (PCSI-PA) schemes both achieve higher secrecy rates than the equal power allocation (EPA) scheme.

cs.IT↗

arXiv2008

Direct Measurement of Piezoelectric Response around Ferroelectric Domain Walls in Crystals with Engineered Domain Configuration

We report the first investigation of the piezoelectric response on a nanoscale in the poled ferroelectric crystals with engineered configuration of domains. Piezoresponse force microscopy of tetragonal 0.63PMN-0.37PT relaxor-based ferroelectric crystals reviled that the d33 piezoelectric coefficient is significantly reduced within the distance of about 1 um from the uncharged engineered domain wall. This finding is essential for understanding the mechanisms of the giant piezoresponse in relaxor-based crystals and for designing new piezoelectric materials.

cond-mat.mtrl-sci↗