arXiv subjects

Teng Gao

Publications and source records attributed to Teng Gao.

8 recordsLinked to original sources

arXiv2026

Intelligence Delivery Network: Toward an Internet Architecture for the AI Age

The rapid emergence of AI-powered applications is reshaping the role of the Internet. Users increasingly rely on the network to obtain intelligence services derived from large foundation models, rather than merely to reach remote endpoints or retrieve specific content. Today's dominant deployment paradigm for AI services remains cloud-centric, where user requests are transmitted to remote data centers for centralized inference. Although operationally convenient, this paradigm suffers from latency and jitter, heavy wide-area traffic, limited utilization of distributed heterogeneous compute resources, and growing privacy and governance concerns. In this paper, we propose the Intelligence Delivery Network (IDN), an Internet architecture that treats AI capabilities as deliverable network services. The key idea is to position, select, reuse, and verify intelligence across cloud, regional, edge, and local environments according to demand locality, resource availability, and policy constraints. We present the system assumptions of IDN, define its core architectural mechanisms, and discuss how capability abstraction, compute resource integration, demand-driven deployment, service routing, state-aware caching, and trust management can jointly support distributed AI services. We believe that IDN provides a practical path toward an Internet architecture for the AI age, making AI capabilities more accessible, efficient, trustworthy, and responsive to diverse application needs.

cs.NI↗

arXiv2022

6G Network AI Architecture for Everyone-Centric Customized Services

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions.

cs.NI↗

arXiv2021

Attention-Guided Generative Adversarial Network for Whisper to Normal Speech Conversion

Whispered speech is a special way of pronunciation without using vocal cord vibration. A whispered speech does not contain a fundamental frequency, and its energy is about 20dB lower than that of a normal speech. Converting a whispered speech into a normal speech can improve speech quality and intelligibility. In this paper, a novel attention-guided generative adversarial network model incorporating an autoencoder, a Siamese neural network, and an identity mapping loss function for whisper to normal speech conversion (AGAN-W2SC) is proposed. The proposed method avoids the challenge of estimating the fundamental frequency of the normal voiced speech converted from a whispered speech. Specifically, the proposed model is more amendable to practical applications because it does not need to align speech features for training. Experimental results demonstrate that the proposed AGAN-W2SC can obtain improved speech quality and intelligibility compared with dynamic-time-warping-based methods.

cs.SD↗

arXiv2021

CycleGAN with Dual Adversarial Loss for Bone-Conducted Speech Enhancement

Compared with air-conducted speech, bone-conducted speech has the unique advantage of shielding background noise. Enhancement of bone-conducted speech helps to improve its quality and intelligibility. In this paper, a novel CycleGAN with dual adversarial loss (CycleGAN-DAL) is proposed for bone-conducted speech enhancement. The proposed method uses an adversarial loss and a cycle-consistent loss simultaneously to learn forward and cyclic mapping, in which the adversarial loss is replaced with the classification adversarial loss and the defect adversarial loss to consolidate the forward mapping. Compared with conventional baseline methods, it can learn feature mapping between bone-conducted speech and target speech without additional air-conducted speech assistance. Moreover, the proposed method also avoids the oversmooth problem which is occurred commonly in conventional statistical based models. Experimental results show that the proposed method outperforms baseline methods such as CycleGAN, GMM, and BLSTM. Keywords: Bone-conducted speech enhancement, dual adversarial loss, Parallel CycleGAN, high frequency speech reconstruction

cs.SD↗

arXiv2016

Effect of Wigner energy on the symmetry energy coefficient in nuclei

The nuclear symmetry energy coefficient (including the coefficient $a_{\rm sym}^{(4)}$ of $I^{4}$ term) of finite nuclei is extracted by using the differences of available experimental binding energies of isobaric nuclei. It is found that the extracted symmetry energy coefficient $a^{*}_{\rm sym}(A,I)$ decreases with increasing of isospin asymmetry $I$, which is mainly caused by Wigner correction, since $e^{*}_{\rm sym}$ is the summation of the traditional symmetry energy $e_{\rm sym}$ and the Wigner energy $e_{\rm W}$. We obtain the optimal values $J=30.25\pm0.10$ MeV, $a_{\rm ss}=56.18\pm1.25$ MeV, $a_{\rm sym}^{(4)}=8.33\pm1.21$ MeV and the Wigner parameter $x=2.38\pm0.12$ through the polynomial fit to 2240 measured binding energies for nuclei with $20 \leq A \leq 261$ with an rms deviation of 23.42 keV. We also find that the volume symmetry coefficient $J\simeq 30$ MeV is insensitive to the value $x$, whereas the surface symmetry coefficient $a_{\rm ss}$ and the coefficient $a_{\rm sym}^{(4)}$ are very sensitive to the value of $x$ in the range $1\leq x\leq 4$. The contribution of $a_{\rm sym}^{(4)}$ term increases rapidly with increasing of isospin asymmetry $I$. For very neutron-rich nuclei, the contribution of $a_{\rm sym}^{(4)}$ term will play an important role.

nucl-th↗

arXiv2015

Wafer-scale CVD Growth of Monolayer Hexagonal Boron Nitride with Large Domain Size by Cu Foil Enclosure Approach

Chemical vapor deposition synthesis of large domain hexagonal boron nitride (h-BN) with uniform thickness on Cu foils is of great challenge, originating from the extremely high nucleation densities and the reverse hydrogen etching competition reaction. We report herein the successful growth of wafer-scale high-quality h-BN monolayer film with the largest single crystalline domain sizes up to 72 micrometer in edge length using a folded Cu enclosure approach. The highly-confined growth space with this facile and unique approach enables the drastic decrease of nucleation centers together with the effective suppression of hydrogen etching reaction. It is revealed, for the first time, that the orientations of as-grown h-BN monolayers are strongly correlated with the crystalline facets of growth substrates, with the Cu (111) being the best substrate for growing high-quality single crystalline h-BN monolayer, consistent with the density functional theory calculations. The present study offers a practical pathway for growing high-quality h-BN films and deepens the fundamental understanding of h-BN growth process.

cond-mat.mtrl-sci↗

arXiv2014

Quasi-freestanding monolayer heterostructure of graphene and hexagonal boron nitride on Ir(111) with a chiral boundary

Monolayer lateral heterostructure of graphene and hexagonal boron nitride (h-BNC) has attracted a growing attention mainly due to its tunable band-gap character and unique physical properties at interface. Hereby, we reported the first-time synthesis of a nearly freestanding h-BNC hybrid on a weakly coupled substrate of Ir (111), where graphene and h-BN possessing different surface heights and corrugations formed a perfect monolayer hybrid. With the aid of scanning tunneling microscopy/spectroscopy (STM/STS), we demonstrated that h-BN can patch alongside the boundary of pre-deposited graphene domains and vice versa to form a seamless monolayer hybrid, with the realization of predominant zigzag type chiral boundaries at the interface. Density-functional theory calculations and STM/STS measurements aided us to reveal that this interface between graphene and h-BN were atomically sharp in aspects of the chemical bonding as well as the local electronic property from both theoretical and experimental points of view.

physics.chem-ph↗

arXiv2014

Directly grown monolayer MoS2 on Au foils as efficient hydrogen evolution catalysts

Synthesis of monolayer MoS2 is essential for fulfilling the potential of MoS2 in catalysis, optoelectronics and valleytronics, etc. Herein, we report for the first time the scalable growth of high quality, domain size tunable (edge length from ~ 200 nm to 50 μm), strictly monolayer MoS2 on commercially available Au foils, via a low pressure chemical vapor deposition method. The nanosized triangular MoS2 flakes on Au foils was proved to be an excellent electrocatalyst for hydrogen evolution reaction (HER), featured by a rather low Tafel slope (61 mV/decade) and a supreme exchange current density (38.1 μA/cm2). The abundant active edge sites and the excellent electron coupling between MoS2 and Au foils account for the extraordinary HER activity. Our work presents a sound proof that strictly monolayer MoS2 assembled on a well selected electrode can manifest comparable or even superior HER property than that of nanoparticles or few-layer MoS2 electrocatalyst.

cond-mat.mtrl-sci↗