We present a study on the single event transient （SET） induced by a pulsed laser in different silicon-germanium （SiGe） heterojunction bipolar transistors （HBTs） with the structure of local oxidation of silicon ...We present a study on the single event transient （SET） induced by a pulsed laser in different silicon-germanium （SiGe） heterojunction bipolar transistors （HBTs） with the structure of local oxidation of silicon （LOCOS） and deep trench isolation （DTI）. The experimental results are discussed in detail and it is demonstrated that a SiGe HBT with the structure of LOCOS is more sensitive than the DTI SiGe HBT in the SET. Because of the limitation of the DTI structure, the charge collection of diffusion in the DTI SiGe HBT is less than that of the LOCOS SiGe HBT. The SET sensitive area of the LOCOS SiGe HBT is located in the eollector-substrate （C/S） junction, while the sensitive area of the DTI SiGe HBT is located near to the collector electrodes.展开更多
Acoustic source localization(ASL)and sound event detection(SED)are two widely pursued independent research fields.In recent years,in order to achieve a more complete spatial and temporal representation of sound field,...Acoustic source localization(ASL)and sound event detection(SED)are two widely pursued independent research fields.In recent years,in order to achieve a more complete spatial and temporal representation of sound field,sound event localization and detection(SELD)has become a very active research topic.This paper presents a deep learning-based multioverlapping sound event localization and detection algorithm in three-dimensional space.Log-Mel spectrum and generalized cross-correlation spectrum are joined together in channel dimension as input features.These features are classified and regressed in parallel after training by a neural network to obtain sound recognition and localization results respectively.The channel attention mechanism is also introduced in the network to selectively enhance the features containing essential information and suppress the useless features.Finally,a thourough comparison confirms the efficiency and effectiveness of the proposed SELD algorithm.Field experiments show that the proposed algorithm is robust to reverberation and environment and can achieve higher recognition and localization accuracy compared with the baseline method.展开更多
The local seismicity observed by seismic network in siachen-nubra region during January 2010-December 2012 shows that the middle part of the crust (17 - 40 km) is aseismic. This aseismic layer (17 - 40 km) is sandwich...The local seismicity observed by seismic network in siachen-nubra region during January 2010-December 2012 shows that the middle part of the crust (17 - 40 km) is aseismic. This aseismic layer (17 - 40 km) is sandwiched between two seismically active layers and depicts a good spatial correlation with the observations of low resistivity reported from magnetotelluric studies for the same region. The local seismicity shows a trend along the Karakoram fault and clustering of events in Shyok Suture zone and Karakoram shear zone. The moment magnitude of these events lies between 1.3 and 4.3. Most of these events have been originated in upper crust.展开更多
A new method that is applicable to local seismic networks to estimate the azimuth and slowness of teleseismic signals is introduced in the paper. The method is based on the correlation between the arrival times and st...A new method that is applicable to local seismic networks to estimate the azimuth and slowness of teleseismic signals is introduced in the paper. The method is based on the correlation between the arrival times and station positions. The analyzed results indicate that the azimuth and slowness of teleseismic signals can be accurately estimated by the method. Average errors for azimuth and slowness measurements obtained by this method using data of Xian Digital Telemetry Seismic Network are 2.0?and 0.34 s/(?, respectively. The conclusions drawn from this study indicate that this method may be very useful to interpret teleseismic records of local seismic networks.展开更多
The method for rapidly, precisely and non-invasively localizing functional regions of the brain is a problem in neuromedicine research. Cortical electrostimulation is the optimal localization method during brain surge...The method for rapidly, precisely and non-invasively localizing functional regions of the brain is a problem in neuromedicine research. Cortical electrostimulation is the optimal localization method during brain surgery, with a degree of accuracy of approximately 5 mm. However, electrostimulation can damage the cerebral cortex, trigger epilepsy, and extend the operation time. Studies are required to determine whether cortical motor regions can be localized by wavelet analysis from electrocorticograms. In this study, based on wavelet analysis of electrocorticograms, a selection of algorithms for classification of the mu rhythm in the motor regions utilizing experimental data was verified. Results demonstrated that a characteristic quantity of energy ratio in the reconstructed signal was filtered in the d6 （7.81-15.62 Hz） band prior to and following motion events. A characteristic threshold was considered to be 40%. The accuracy of localization detection was 93%. The degree of accuracy was less than 5 mm. The present study avoided the problems of cerebral cortex injury and epilepsy onset, with an operation time of 60 seconds. Therefore, wavelet analysis on electrocorticogram is feasible for localizing cortical motor regions. Furthermore, this localization technique is accurate, safe and rapid.展开更多
Objective: A global-local processing task was adapted to be used in an event- related potential paradigm in order to examine the effects of positive emotion on
为了解决事件行人重识别领域(event-based person ReID)中事件流噪声问题和类间不平衡问题,提出了一种基于时空协同滤波的事件行人重识别方法(SCF-Net)。该方法包含时空协同滤波器和局部代理稀疏性学习模块两个部分。时空协同滤波器通...为了解决事件行人重识别领域(event-based person ReID)中事件流噪声问题和类间不平衡问题,提出了一种基于时空协同滤波的事件行人重识别方法(SCF-Net)。该方法包含时空协同滤波器和局部代理稀疏性学习模块两个部分。时空协同滤波器通过利用真实事件之间的时空协同特性来区分真实事件和噪声事件,并滤除噪声事件,以消除事件流中噪声的影响。局部代理稀疏性学习模块考虑了行人特征之间的差异性,通过将行人实例特征映射到局部代理域,并强制各代理互相远离,在特征空间中得到了清晰的类别边界。在Event-ReID数据集上的实验表明,与目前先进的事件行人重识别方法相比,SCF-Net方法取得了较大的性能提升,mAP指标提升了6.9%,Rank-1指标提升了4.4%。展开更多
Conventional shot-gather migration uses a cross-correlation imaging condition proposed by Clarebout （1971）, which cannot preserve imaging amplitudes. The deconvolution imaging condition can improve the imaging ampli...Conventional shot-gather migration uses a cross-correlation imaging condition proposed by Clarebout （1971）, which cannot preserve imaging amplitudes. The deconvolution imaging condition can improve the imaging amplitude and compensate for illumination. However, the deconvolution imaging condition introduces instability issues. The least-squares imaging condition first computes the sum of the cross-correlation of the forward and backward wavefields over all frequencies and sources, and then divides the result by the total energy of the forward wavefield. Therefore, the least-squares imaging condition is more stable than the classic imaging condition. However, the least-squares imaging condition cannot provide accurate results in areas where the illumination is very poor and unbalanced. To stabilize the least-squares imaging condition and balance the imaging amplitude, we propose a novel imaging condition with structure constraints that is based on the least-squares imaging condition. Our novel imaging condition uses a plane wave construction that constrains the imaging result to be smooth along geological structure boundaries in the inversion frame. The proposed imaging condition improves the stability of the imaging condition and balances the imaging amplitude. The proposed condition is applied to two examples, the horizontal layered model and the Sigsbee 2A model. These tests show that, in comparison to the damped least-squares imaging condition, the stabilized least-squares imaging condition with structure constraints improves illumination stability and balance, makes events more consecutive, adjusts the amplitude of the depth layers where the illumination is poor and unbalanced, suppresses imaging artifacts, and is conducive to amplitude preserving imaging of deep layers.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 61274106
文摘We present a study on the single event transient （SET） induced by a pulsed laser in different silicon-germanium （SiGe） heterojunction bipolar transistors （HBTs） with the structure of local oxidation of silicon （LOCOS） and deep trench isolation （DTI）. The experimental results are discussed in detail and it is demonstrated that a SiGe HBT with the structure of LOCOS is more sensitive than the DTI SiGe HBT in the SET. Because of the limitation of the DTI structure, the charge collection of diffusion in the DTI SiGe HBT is less than that of the LOCOS SiGe HBT. The SET sensitive area of the LOCOS SiGe HBT is located in the eollector-substrate （C/S） junction, while the sensitive area of the DTI SiGe HBT is located near to the collector electrodes.
基金supported by the National Natural Science Foundation of China(61877067)the Foundation of Science and Technology on Near-Surface Detection Laboratory(TCGZ2019A002,TCGZ2021C003,6142414200511)the Natural Science Basic Research Program of Shaanxi(2021JZ-19)。
文摘Acoustic source localization(ASL)and sound event detection(SED)are two widely pursued independent research fields.In recent years,in order to achieve a more complete spatial and temporal representation of sound field,sound event localization and detection(SELD)has become a very active research topic.This paper presents a deep learning-based multioverlapping sound event localization and detection algorithm in three-dimensional space.Log-Mel spectrum and generalized cross-correlation spectrum are joined together in channel dimension as input features.These features are classified and regressed in parallel after training by a neural network to obtain sound recognition and localization results respectively.The channel attention mechanism is also introduced in the network to selectively enhance the features containing essential information and suppress the useless features.Finally,a thourough comparison confirms the efficiency and effectiveness of the proposed SELD algorithm.Field experiments show that the proposed algorithm is robust to reverberation and environment and can achieve higher recognition and localization accuracy compared with the baseline method.
文摘The local seismicity observed by seismic network in siachen-nubra region during January 2010-December 2012 shows that the middle part of the crust (17 - 40 km) is aseismic. This aseismic layer (17 - 40 km) is sandwiched between two seismically active layers and depicts a good spatial correlation with the observations of low resistivity reported from magnetotelluric studies for the same region. The local seismicity shows a trend along the Karakoram fault and clustering of events in Shyok Suture zone and Karakoram shear zone. The moment magnitude of these events lies between 1.3 and 4.3. Most of these events have been originated in upper crust.
基金Foundation of Verification Researches for Arm Control Technology
文摘A new method that is applicable to local seismic networks to estimate the azimuth and slowness of teleseismic signals is introduced in the paper. The method is based on the correlation between the arrival times and station positions. The analyzed results indicate that the azimuth and slowness of teleseismic signals can be accurately estimated by the method. Average errors for azimuth and slowness measurements obtained by this method using data of Xian Digital Telemetry Seismic Network are 2.0?and 0.34 s/(?, respectively. The conclusions drawn from this study indicate that this method may be very useful to interpret teleseismic records of local seismic networks.
文摘The method for rapidly, precisely and non-invasively localizing functional regions of the brain is a problem in neuromedicine research. Cortical electrostimulation is the optimal localization method during brain surgery, with a degree of accuracy of approximately 5 mm. However, electrostimulation can damage the cerebral cortex, trigger epilepsy, and extend the operation time. Studies are required to determine whether cortical motor regions can be localized by wavelet analysis from electrocorticograms. In this study, based on wavelet analysis of electrocorticograms, a selection of algorithms for classification of the mu rhythm in the motor regions utilizing experimental data was verified. Results demonstrated that a characteristic quantity of energy ratio in the reconstructed signal was filtered in the d6 （7.81-15.62 Hz） band prior to and following motion events. A characteristic threshold was considered to be 40%. The accuracy of localization detection was 93%. The degree of accuracy was less than 5 mm. The present study avoided the problems of cerebral cortex injury and epilepsy onset, with an operation time of 60 seconds. Therefore, wavelet analysis on electrocorticogram is feasible for localizing cortical motor regions. Furthermore, this localization technique is accurate, safe and rapid.
文摘Objective: A global-local processing task was adapted to be used in an event- related potential paradigm in order to examine the effects of positive emotion on
文摘为了解决事件行人重识别领域(event-based person ReID)中事件流噪声问题和类间不平衡问题,提出了一种基于时空协同滤波的事件行人重识别方法(SCF-Net)。该方法包含时空协同滤波器和局部代理稀疏性学习模块两个部分。时空协同滤波器通过利用真实事件之间的时空协同特性来区分真实事件和噪声事件,并滤除噪声事件,以消除事件流中噪声的影响。局部代理稀疏性学习模块考虑了行人特征之间的差异性,通过将行人实例特征映射到局部代理域,并强制各代理互相远离,在特征空间中得到了清晰的类别边界。在Event-ReID数据集上的实验表明,与目前先进的事件行人重识别方法相比,SCF-Net方法取得了较大的性能提升,mAP指标提升了6.9%,Rank-1指标提升了4.4%。
基金financially supported by Important National Science and Technology Specific Projects of China(Grant No. 2011ZX05023-005-005)
文摘Conventional shot-gather migration uses a cross-correlation imaging condition proposed by Clarebout （1971）, which cannot preserve imaging amplitudes. The deconvolution imaging condition can improve the imaging amplitude and compensate for illumination. However, the deconvolution imaging condition introduces instability issues. The least-squares imaging condition first computes the sum of the cross-correlation of the forward and backward wavefields over all frequencies and sources, and then divides the result by the total energy of the forward wavefield. Therefore, the least-squares imaging condition is more stable than the classic imaging condition. However, the least-squares imaging condition cannot provide accurate results in areas where the illumination is very poor and unbalanced. To stabilize the least-squares imaging condition and balance the imaging amplitude, we propose a novel imaging condition with structure constraints that is based on the least-squares imaging condition. Our novel imaging condition uses a plane wave construction that constrains the imaging result to be smooth along geological structure boundaries in the inversion frame. The proposed imaging condition improves the stability of the imaging condition and balances the imaging amplitude. The proposed condition is applied to two examples, the horizontal layered model and the Sigsbee 2A model. These tests show that, in comparison to the damped least-squares imaging condition, the stabilized least-squares imaging condition with structure constraints improves illumination stability and balance, makes events more consecutive, adjusts the amplitude of the depth layers where the illumination is poor and unbalanced, suppresses imaging artifacts, and is conducive to amplitude preserving imaging of deep layers.
