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Audio-visual keyword transformer for unconstrained sentence-level keyword spotting

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 142-152页

作者： Yidi Li Jiale Ren Yawei Wang Guoquan Wang Xia Li Hong Liu key laboratory of machine perception Peking UniversityShenzhen Graduate SchoolShenzhenChina College of Electronics and Information Engineering Sichuan UniversityChengduChina Department of Computer Science ETH ZurichZurichSwitzerland

As one of the most effective methods to improve the accuracy and robustness of speech tasks,the audio-visual fusion approach has recently been introduced into the field of keyword Spotting(KWS).However,existing audio-visual keyword spotting models are limited to detecting isolated words,while keyword spotting for unconstrained speech is still a challenging *** this end,an Audio-Visual keyword Transformer(AVKT)network is proposed to spot keywords in unconstrained video *** authors present a transformer classifier with learnable CLS tokens to extract distinctive keyword features from the variable-length audio and visual *** outputs of audio and visual branches are combined in a decision fusion *** humans can easily notice whether a keyword appears in a sentence or not,our AVKT network can detect whether a video clip with a spoken sentence contains a pre-specified ***,the position of the keyword is localised in the attention map without additional position ***-imental results on the LRS2-KWS dataset and our newly collected PKU-KWS dataset show that the accuracy of AVKT exceeded 99%in clean scenes and 85%in extremely noisy *** code is available at https://***/jialeren/AVKT.

关键词： artificial intelligence multimodal approaches natural language processing neural network speech processing

Conversion of a single-layer ANN to photonic SNN for pattern recognition

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Science China(Information Sciences) 2024年第1期67卷 261-270页

作者： Yanan HAN Shuiying XIANG Tianrui ZHANG Yahui ZHANG Xingxing GUO Yuechun SHI state key laboratory of Integrated Service Networks State Key Discipline Laboratory of Wide Bandgap Semiconductor TechnologyXidian University Yongjiang laboratory

This work presents a complete conversion scheme for photonic spiking neural networks(SNNs).We verified that the output of an artificial neural network(ANN) trained with the simulated optical activation function can be directly converted into the spike rate of a photonic spiking neuron *** reveal the feasibility of hardware implementation,we considered the effects of different bit precisions of data and weight,noise level,and bias current mismatch on the converted *** proposed scheme was evaluated using the Deterding vowel,IRIS,TIDIGITS,and MNIST datasets for pattern recognition,and achieved mean accuracies of 95.80%,98.67%,96.19%,and 92.33%,*** proposed scheme can convert an ANN into a photonic SNN with almost no precision loss,and the performance was comparable to that of an ANN trained with the rectified linear unit *** proposed scheme can enable the high-performance implementation of photonic SNNs.

关键词： photonic SNN conversion optical computing pattern recognition artificial neural network

Wall temperature effects on the stability of leeward vortices of a blunt inclined cone

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Acta Mechanica Sinica 2024年第7期40卷 29-42页

作者： Ligeng Zhang Bingbing Wan Siwei Dong Jianqiang Chen Xi Chen state key laboratory of Aerodynamics Mianyang 621000China

Streamwise vortex instability is one of the most potent mechanisms for the transition of the three-dimensional boundary *** using the global stability analysis methods,stability characteristics of the leeward vortex over a blunt cone with an angle of attack under a typical wind tunnel condition are studied and are compared to the case with a smaller wall temperature ratio(corresponding to a flight condition).The vortical structure features inward and outward vortices,similar to that in the flight *** the flight condition,the outward vortices appear stronger than the inward vortices,resulting in stronger outer-mode *** the inner mode is heavily stabilized compared to the flight condition,it can still radiate apparent *** acoustic sources are computed based on Lighthill's acoustic analogy,showing that the entropy term measuring the deviation from the isentropic relation is *** Mack second mode is shown to most likely trigger the transition in the flight condition,it is absent in the wind tunnel condition,and a shear-layer mode turns out to be the most dangerous ***,the instability frequencies and growth rates of the wind tunnel case are much smaller than those of the flight case,indicating that wall heating may stabilize the leeward vortices.

关键词： Instability of streamwise vortices Hypersonic boundary layer flow Spatial BiGlobal method PSE3D method

Control of defensive behavior by the nucleus of Darkschewitsch GABAergic neurons

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National Science Review 2024年第4期11卷 70-83页

作者： Huiying Zhao Jinrong Liu Yujin Shao Xiang Feng Binhan Zhao Li Sun Yijun Liu Linghui Zeng Xiao-ming Li Hongbin Yang Shumin Duan Yan-qin Yu Department of Neurology of Second Affiliated Hospital and School of Brain Science and Brain Medicine Zhejiang University School of Medicine Nanhu Brain-Computer Interface Institute Liangzhu laboratory MOE Frontier Science Center for Brain Science and Brain-Machine Integration State Key Laboratory of Brain-Machine Intelligence Zhejiang University NHC and CAMS key laboratory of Medical Neurobiology Zhejiang University key laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province School of Medicine Hangzhou City University

The nucleus of Darkschewitsch(ND), mainly composed of GABAergic neurons, is widely recognized as a component of the eye-movement controlling system. However, the functional contribution of ND GABAergic neurons(NDGABA) in animal behavior is largely unknown. Here, we show that NDGABA neurons were selectively activated by different types of fear stimuli, such as predator odor and foot *** and chemogenetic manipulations revealed that NDGABA neurons mediate freezing ***, using circuit-based optogenetic and neuroanatomical tracing methods, we identified an excitatory pathway from the lateral periaqueductal gray(l PAG) to the ND that induces freezing by exciting ND inhibitory outputs to the motor-related gigantocellular reticular nucleus, ventral part(Gi V). Together,these findings indicate the NDGABA population as a novel hub for controlling defensive response by relaying fearful information from the l PAG to Gi V, a mechanism critical for understanding how the freezing behavior is encoded in the mammalian brain.

关键词： nucleus of Darkschewitsch GABAergic population defensive behavior freezing neural circuitry

A Heuristic Radiomics Feature Selection Method Based on Frequency Iteration and Multi-Supervised Training Mode

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Computers, Materials & Continua 2024年第5期79卷 2277-2293页

作者： Zhigao Zeng Aoting Tang Shengqiu Yi Xinpan Yuan Yanhui Zhu School of Computer Hunan University of TechnologyZhuzhou412007China Hunan key laboratory of Intelligent Information perception and Processing Technology Zhuzhou412007China

Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for *** has received great attention due to its huge application prospects in recent *** can know that the number of features selected by the existing radiomics feature selectionmethods is basically about *** this paper,a heuristic feature selection method based on frequency iteration and multiple supervised training mode is *** on the combination between features,it decomposes all features layer by layer to select the optimal features for each layer,then fuses the optimal features to form a local optimal group layer by layer and iterates to the global optimal combination *** with the currentmethod with the best prediction performance in the three data sets,thismethod proposed in this paper can reduce the number of features fromabout ten to about three without losing classification accuracy and even significantly improving classification *** proposed method has better interpretability and generalization ability,which gives it great potential in the feature selection of radiomics.

关键词： Radiomics feature selection machine learning metaheuristic

Experimental and numerical demonstration of hierarchical time-delay reservoir computing based on cascaded VCSELs with feedback and multiple injections

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Science China(Information Sciences) 2024年第2期67卷 279-290页

作者： Xingxing GUO Shuiying XIANG Xingyu CAO Biling GU state key laboratory of Integrated Service Networks Xidian University state key Discipline laboratory of Wide Bandgap Semiconductor Technology School of MicroelectronicsXidian University

In this paper, we propose and demonstrate experimentally and numerically a hierarchical timedelay optical reservoir computing(RC) system based on cascaded vertical-cavity surface-emitting lasers(VCSELs) with feedback and multiple injections. The prediction performance characteristics of the hierarchical time-delay RC system based on cascaded VCSELs under different reservoir layers are ***, the prediction performance of the hierarchical time-delay RC system is first improved and saturates as the number of reservoir layers increases. Besides, the impacts of key factors on predicting the hierarchical time-delay RC system are also analyzed in detail experimentally and numerically. This proposed hierarchical time-delay RC system based on VCSELs is useful for the further development of RC systems and may be beneficial to improve the ability of RC systems to solve more complex problems.

关键词： vertical-cavity surface-emitting laser reservoir computing neuromorphic photonics time-delay system information processing

A credible traffic prediction method based on self-supervised causal discovery

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Science China(Information Sciences) 2024年第5期67卷 244-258页

作者： Dan WANG Yingjie LIU Bin SONG state key laboratory of Integrated Services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(QoS) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(SSTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. Experimental results demonstrate the effectiveness of the SSTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised

Uncertain knowledge graph embedding:an effective method combining multi-relation and multi-path

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Frontiers of Computer Science 2024年第3期18卷 73-89页

作者： Qi LIU Qinghua ZHANG Fan ZHAO Guoyin WANG key laboratory of Tourism Multisource Data perception and Decision Ministry of Culture and TourismChongqing University of Posts and TelecommunicationsChongqing 400065China Chongqing key laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Chongqing key laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing 400065China

Uncertain Knowledge Graphs(UKGs)are used to characterize the inherent uncertainty of knowledge and have a richer semantic structure than deterministic knowledge *** research on the embedding of UKG has only recently begun,Uncertain Knowledge Graph Embedding(UKGE)model has a certain effect on solving this ***,there are still unresolved *** the one hand,when reasoning the confidence of unseen relation facts,the introduced probabilistic soft logic cannot be used to combine multi-path and multi-step global information,leading to information *** the other hand,the existing UKG embedding model can only model symmetric relation facts,but the embedding problem of asymmetric relation facts has not be *** address the above issues,a Multiplex Uncertain Knowledge Graph Embedding(MUKGE)model is proposed in this ***,to combine multiple information and achieve more accurate results in confidence reasoning,the Uncertain ResourceRank(URR)reasoning algorithm is ***,the asymmetry in the UKG is *** embed asymmetric relation facts of UKG,a multi-relation embedding model is ***,experiments are carried out on different datasets via 4 tasks to verify the effectiveness of *** results of experiments demonstrate that MUKGE can obtain better overall performance than the baselines,and it helps advance the research on UKG embedding.

关键词： knowledge representation uncertain knowledge graph multi-relation embedding uncertain reasoning

Micelle-directed self-assembly of single-crystal-like mesoporous stoichiometric oxides for high-performance lithium storage

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National Science Review 2024年第4期11卷 195-205页

作者： Yanhua Wan Changyao Wang Xingmiao Zhang Yang Yin Mengmeng Liu Bing Ma Linlin Duan Yuzhu Ma Wei Zhang Changlin Zheng Dongliang Chao Fei Wang Yongyao Xia Wei Li Department of Chemistry Laboratory of Advanced Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials State Key Laboratory of Molecular Engineering of Polymers College of Chemistry and Materials ScienceFudan University state key laboratory of Surface Physics and Department of Physics Fudan University

Due to their uncontrollable assembly and crystallization process,the synthesis of mesoporous metal oxide single crystals remains a formidable ***,we report the synthesis of single-crystal-like mesoporous Li2TiSiO5by using soft micelles as *** key lies in the atomic-scale self-assembly and step-crystallization processes,which ensure the formation of single-crystal-like mesoporous Li2TiSiO5microparticles via an oriented attachment growth mechanism under the confinement of an in-situ formed carbon *** mesoporous Li2TiSiO5anode achieves a superior rate capability(148 mAh g-1at5.0 A g-1) and outstanding long-term cycling stability(138 mAh g-1after 3000 cycles at 2.0 A g-1) for lithium storage as a result of the ultrafast Li+diffusion caused by penetrating mesochannels and nanosized crystal frameworks（5-10 nm）.In comparison,bulk Li2TiSiO5exhibits poor rate capability and cycle performance due to micron-scale diffusion *** method is very simple and reproducible,heralding a new way of designing and synthesizing mesoporous single crystals with controllable frameworks and chemical functionalities.

关键词： mesoporous materials micelles single-crystal-like Li2TiSiO5 lithium-ion batteries