arXiv subjects

Wang Jing

Publications and source records attributed to Wang Jing.

6 recordsLinked to original sources

arXiv2025

A Novel Brain-Computer Interface Architecture: The Brain-Muscle-Hand Interface for replicating the motor pathway

Myoelectric interfaces enable intuitive and natural control by decoding residual muscle activity, providing an effective pathway for motor restoration in individuals with preserved musculature. However, in patients with severe muscular atrophy or high-level spinal cord injury, the absence of reliable muscle activity renders myoelectric control infeasible. In such cases, motor brain-computer interfaces (BCIs) offer an alternative route. However, conventional brain-computer interface systems rely mainly on noisy cortical signals and classification-based decoding algorithms, which often result in low signal fidelity, limited controllability, and unstable real-time performance. Inspired by the motor pathway--an evolutionarily optimized system that filters, integrates, and transmits motor commands from the brain to the muscles--this study proposes the Brain-Muscle-Hand Interface (BMHI). BMHI decodes cortical EEG signals to reconstruct muscle-level EMG activity, functionally substituting for the muscles and enabling regression-based, continuous, and natural control via a myoelectric interface. To validate this architecture, we performed offline verification, comparative analysis, and online control experiments. Results demonstrate that: (1) the BMHI achieves a prediction accuracy of 0.79; (2) compared with conventional end-to-end brain-hand interfaces, it reduces training time by approximately eighteenfold while improving decoding accuracy; and (3) in online operation, the BMHI enables stable and efficient manipulation of both a virtual hand and a robotic arm. Compared with conventional BCIs, the BMHI, by replicating the motor pathway, enables continuous, stable, and naturally intuitive control.

q-bio.NC↗

arXiv2021

The crossing number of the generalized Petersen graph $P(3k,k)$ in the projective plane

The crossing number of a graph $G$ in a surface $Σ$, denoted by $cr_Σ(G)$, is the minimum number of pairwise intersections of edges in a drawing of $G$ in $Σ$. Let $k$ be an integer satisfying $k\geq 3$, the generalized Petersen graph $P(3k,k)$ is the graph with vertex set $V(P(3k,k))=\{u_i, v_i| i=1,2,\cdots,3k\}$ and edge set $E(P(3k,k))=\{u_iu_{i+1}, u_iv_i, v_iv_{k+i}| i=1,2,\cdots,3k\},$ the subscripts are read modulo $3k.$ This paper investigates the crossing number of $P(3k,k)$ in the projective plane. We determine the exact value of $cr_{N_1}(P(3k,k))$ is $k-2$ when $3\le k\le 7,$ moreover, for $k\ge 8,$ we get that $k-2\le cr_{N_1}(P(3k,k))\le k-1.$

math.CO↗

arXiv2021

The generalized 3-connectivity of the folded hypercube $FQ_n$

The generalized $k$-connectivity of a graph $G$, denoted by $κ_k(G)$, is a generalization of the traditional connectivity. It is well known that the generalized $k$-connectivity is an important indicator for measuring the fault tolerance and reliability of interconnection networks. The $n$-dimensional folded hypercube $FQ_n$ is obtained from the $n$-dimensional hypercube $Q_n$ by adding an edge between any pair of vertices with complementary addresses. In this paper, we show that $κ_3(FQ_n)=n$ for $n\ge 2$, that is, for any three vertices in $FQ_n$, there exist $n$ internally disjoint trees connecting them.

math.CO↗

arXiv2019

Do We Need Neural Models to Explain Human Judgments of Acceptability?

Native speakers can judge whether a sentence is an acceptable instance of their language. Acceptability provides a means of evaluating whether computational language models are processing language in a human-like manner. We test the ability of computational language models, simple language features, and word embeddings to predict native English speakers judgments of acceptability on English-language essays written by non-native speakers. We find that much of the sentence acceptability variance can be captured by a combination of features including misspellings, word order, and word similarity (Pearson's r = 0.494). While predictive neural models fit acceptability judgments well (r = 0.527), we find that a 4-gram model with statistical smoothing is just as good (r = 0.528). Thanks to incorporating a count of misspellings, our 4-gram model surpasses both the previous unsupervised state-of-the art (Lau et al., 2015; r = 0.472), and the average non-expert native speaker (r = 0.46). Our results demonstrate that acceptability is well captured by n-gram statistics and simple language features.

cs.CL↗

arXiv2014

Online Group Feature Selection

Online feature selection with dynamic features has become an active research area in recent years. However, in some real-world applications such as image analysis and email spam filtering, features may arrive by groups. Existing online feature selection methods evaluate features individually, while existing group feature selection methods cannot handle online processing. Motivated by this, we formulate the online group feature selection problem, and propose a novel selection approach for this problem. Our proposed approach consists of two stages: online intra-group selection and online inter-group selection. In the intra-group selection, we use spectral analysis to select discriminative features in each group when it arrives. In the inter-group selection, we use Lasso to select a globally optimal subset of features. This 2-stage procedure continues until there are no more features to come or some predefined stopping conditions are met. Extensive experiments conducted on benchmark and real-world data sets demonstrate that our proposed approach outperforms other state-of-the-art online feature selection methods.

cs.CV↗

arXiv2013

Multi- Physics analysis of the RFQ for the Injector Scheme II of CADS Driver Linac

A 162.5 MHz, 2.1 MeV Radio Frequency Quadruples (RFQ) structure is being designed for the Injector Scheme II of China Accelerator Driver System (CADS) driver linac. The RFQ will operate at continuous wave (CW) mode as required. For the CW normal conducting machine, the heat management will be one of the most important issues, since the temperature fluctuation may cause cavity deformation and leading to the resonant frequency shift. Therefor a detailed multi-physics analysis is necessary to ensure that the cavity can be stably worked at the required power level. The multi-physics analysis process includes RF Electromagnetic analysis, Thermal analysis, Mechnical analysis, and this process will be iterated for several cycles until the satisfied solution can be found. As one of the widely accepted measures, the cooling water system is used for frequency fine tunning, so the tunning capability of the cooling water system is also studied at different conditions. The results indicate that with the cooling water system, both the temperature rise and the frequency shift can be controlled in an acceptable level.

physics.acc-ph↗