The influence of Hf on the precipitation behavior of γ'phase and the subsequent tensile properties of a Ni-Cr-Mo alloy after long-term thermal exposure was investigated.The results reveal that the addition of Hf ...The influence of Hf on the precipitation behavior of γ'phase and the subsequent tensile properties of a Ni-Cr-Mo alloy after long-term thermal exposure was investigated.The results reveal that the addition of Hf increases the average diameter ofγ'phases after thermal exposure at 700℃ for 5000 h,which enhances the critical resolved shear stress required for dislocations to shear the γ'phases in the Ni-Cr-Mo alloy.Simultaneously,element Hf incorporated into the γ'phases increases the lattice mismatch between the γ'and γ phase,thereby strengthening the coherency strengthening effect.These two factors collectively contribute to the enhanced strength of the alloy.Thus,Hf alloying effectively improves the yield strength of the Ni-Cr-Mo alloy after thermal exposure at 700℃.展开更多
Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution an...The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution and short wavelength.Efficient and compact 193 nm DUV laser source thus becomes a hot research area.Currently,193 nm Ar F excimer gas laser is widely employed in DUV lithography systems and serves as the enabling technology for 7 and 5 nm semiconductor fabrication.展开更多
The high-frequency(HF) communication is one of essential communication methods for military and emergency application. However, the selection of communication frequency channel is always a difficult problem as the cro...The high-frequency(HF) communication is one of essential communication methods for military and emergency application. However, the selection of communication frequency channel is always a difficult problem as the crowded spectrum, the time-varying channels, and the malicious intelligent jamming. The existing frequency hopping, automatic link establishment and some new anti-jamming technologies can not completely solve the above problems. In this article, we adopt deep reinforcement learning to solve this intractable challenge. First, the combination of the spectrum state and the channel gain state is defined as the complex environmental state, and the Markov characteristic of defined state is analyzed and proved. Then, considering that the spectrum state and channel gain state are heterogeneous information, a new deep Q network(DQN) framework is designed, which contains multiple sub-networks to process different kinds of information. Finally, aiming to improve the learning speed and efficiency, the optimization targets of corresponding sub-networks are reasonably designed, and a heterogeneous information fusion deep reinforcement learning(HIF-DRL) algorithm is designed for the specific frequency selection. Simulation results show that the proposed algorithm performs well in channel prediction, jamming avoidance and frequency channel selection.展开更多
As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in effic...As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in efficient manner becomes one of the key challenges in HF communication. Spectrum prediction infers the future spectrum status from history spectrum data by exploring the inherent correlations and regularities. The investigation of HF electromagnetic environment data reveals the correlations and predictability of HF frequency band in both time and frequency domain. To solve this problem, we develop a Spectrum Prediction-based Frequency Band Pre-selection(SP-FBP) for HF communications. The pre-selection of HF frequency band mainly incorporated in prediction of HF spectrum occupancy and prediction of HF usable frequency, which provide the frequency band ranking of spectrum occupancy and alternative frequency for spectrum sensing, respectively. Performance evaluation via real-world HF spectrum data shows that SP-FBP significantly improves the efficiency of finding quality frequency in HF communications.展开更多
In this letter,a kind of associated synchronization algorithm which is suitable for HF(High Frequency) broadband OFDM(Orthogonal Frequency Division Multiplexing) system is presented based on describing and constructin...In this letter,a kind of associated synchronization algorithm which is suitable for HF(High Frequency) broadband OFDM(Orthogonal Frequency Division Multiplexing) system is presented based on describing and constructing the GMW(Gorden,Mills and Welch) sequence. The algorithm is based on the Schmidl and Minn's symbol timing principle,the constructed GMW sequence is trans-mitted and disposed,and the synchronization is adjudicated using the correlation of GMW sequence. The simulation result indicates that this algorithm has high performance synchronization ability under the low SNR(Signal to Noise Ratio) at two different kinds of channel models.展开更多
基金National Key Research and Development Program of China(2021YFB3704103)National Natural Science Foundation of China(51571191)。
文摘The influence of Hf on the precipitation behavior of γ'phase and the subsequent tensile properties of a Ni-Cr-Mo alloy after long-term thermal exposure was investigated.The results reveal that the addition of Hf increases the average diameter ofγ'phases after thermal exposure at 700℃ for 5000 h,which enhances the critical resolved shear stress required for dislocations to shear the γ'phases in the Ni-Cr-Mo alloy.Simultaneously,element Hf incorporated into the γ'phases increases the lattice mismatch between the γ'and γ phase,thereby strengthening the coherency strengthening effect.These two factors collectively contribute to the enhanced strength of the alloy.Thus,Hf alloying effectively improves the yield strength of the Ni-Cr-Mo alloy after thermal exposure at 700℃.
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金supported by the National Natural Science Foundation of China(Grant Nos.62450006,62304217,62274157,62127807,62234011,62034008,62074142,62074140)Tianshan Innovation Team Program(Grant No.2022TSYCTD0005)+1 种基金Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0880000)Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant Nos.2023124,Y2023032)。
文摘The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution and short wavelength.Efficient and compact 193 nm DUV laser source thus becomes a hot research area.Currently,193 nm Ar F excimer gas laser is widely employed in DUV lithography systems and serves as the enabling technology for 7 and 5 nm semiconductor fabrication.
基金supported by Guangxi key Laboratory Fund of Embedded Technology and Intelligent System under Grant No. 2018B-1the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province under Grant No. BK20160034+1 种基金the National Natural Science Foundation of China under Grant No. 61771488, No. 61671473 and No. 61631020in part by the Open Research Foundation of Science and Technology on Communication Networks Laboratory
文摘The high-frequency(HF) communication is one of essential communication methods for military and emergency application. However, the selection of communication frequency channel is always a difficult problem as the crowded spectrum, the time-varying channels, and the malicious intelligent jamming. The existing frequency hopping, automatic link establishment and some new anti-jamming technologies can not completely solve the above problems. In this article, we adopt deep reinforcement learning to solve this intractable challenge. First, the combination of the spectrum state and the channel gain state is defined as the complex environmental state, and the Markov characteristic of defined state is analyzed and proved. Then, considering that the spectrum state and channel gain state are heterogeneous information, a new deep Q network(DQN) framework is designed, which contains multiple sub-networks to process different kinds of information. Finally, aiming to improve the learning speed and efficiency, the optimization targets of corresponding sub-networks are reasonably designed, and a heterogeneous information fusion deep reinforcement learning(HIF-DRL) algorithm is designed for the specific frequency selection. Simulation results show that the proposed algorithm performs well in channel prediction, jamming avoidance and frequency channel selection.
基金the Project of National Natural Science Foundation of China (Grant No. 61471395, No. 61301161, and No. 61501510)partly supported by Natural Science Foundation of Jiangsu Province (Grant No. BK20161125 and No. BK20150717)
文摘As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in efficient manner becomes one of the key challenges in HF communication. Spectrum prediction infers the future spectrum status from history spectrum data by exploring the inherent correlations and regularities. The investigation of HF electromagnetic environment data reveals the correlations and predictability of HF frequency band in both time and frequency domain. To solve this problem, we develop a Spectrum Prediction-based Frequency Band Pre-selection(SP-FBP) for HF communications. The pre-selection of HF frequency band mainly incorporated in prediction of HF spectrum occupancy and prediction of HF usable frequency, which provide the frequency band ranking of spectrum occupancy and alternative frequency for spectrum sensing, respectively. Performance evaluation via real-world HF spectrum data shows that SP-FBP significantly improves the efficiency of finding quality frequency in HF communications.
文摘In this letter,a kind of associated synchronization algorithm which is suitable for HF(High Frequency) broadband OFDM(Orthogonal Frequency Division Multiplexing) system is presented based on describing and constructing the GMW(Gorden,Mills and Welch) sequence. The algorithm is based on the Schmidl and Minn's symbol timing principle,the constructed GMW sequence is trans-mitted and disposed,and the synchronization is adjudicated using the correlation of GMW sequence. The simulation result indicates that this algorithm has high performance synchronization ability under the low SNR(Signal to Noise Ratio) at two different kinds of channel models.
