To address the issues of unknown target size,blurred edges,background interference and low contrast in infrared small target detection,this paper proposes a method based on density peaks searching and weighted multi-f...To address the issues of unknown target size,blurred edges,background interference and low contrast in infrared small target detection,this paper proposes a method based on density peaks searching and weighted multi-feature local difference.Firstly,an improved high-boost filter is used for preprocessing to eliminate background clutter and high-brightness interference,thereby increasing the probability of capturing real targets in the density peak search.Secondly,a triple-layer window is used to extract features from the area surrounding candidate targets,addressing the uncertainty of small target sizes.By calculating multi-feature local differences between the triple-layer windows,the problems of blurred target edges and low contrast are resolved.To balance the contribution of different features,intra-class distance is used to calculate weights,achieving weighted fusion of multi-feature local differences to obtain the weighted multi-feature local differences of candidate targets.The real targets are then extracted using the interquartile range.Experiments on datasets such as SIRST and IRSTD-IK show that the proposed method is suitable for various complex types and demonstrates good robustness and detection performance.展开更多
Background:Epilepsy is a neurological disorder characterized by recurrent seizures due to hyperexcitable neuronal network activity.The manifestations vary widely,ranging from subtle sensory disturbances to profound al...Background:Epilepsy is a neurological disorder characterized by recurrent seizures due to hyperexcitable neuronal network activity.The manifestations vary widely,ranging from subtle sensory disturbances to profound alterations of consciousness,depending on which brain regions are affected and their underlying etiology.Exploring the biophysical mechanisms of epileptic seizures holds significant for predicting and controlling the disease.Methods:We analyzed 45 spontaneous seizures recorded from 24 patients with focal epilepsy,as well as stimulation-induced seizures from 2 additional patients.A second-order Butterworth low-pass filter isolated the slow-varying direct current(Sv DC)component(0.01-0.5 Hz),a frequency range often overlooked in electroencephalography(EEG).The energy ratio of the Sv DC component was calculated by dividing its total energy by the total signal energy during seizures and over a 1-hour period including the seizure,enabling comparison between ictal and interictal states.Results:The Sv DC component exhibited spatially dynamic changes during both ictal and interictal periods and showed a moderate correlation with high-frequency activity.Moreover,it accounted for a high energy proportion in both periods,with seizure data showing that 80.82%of leads had≥60%Sv DC energy.Notably,interictal Sv DC fluctuations were more pronounced in electrodes located within the epileptogenic zone,suggesting its potential as a marker for epileptogenic localization.Furthermore,the temporal variability of the Sv DC signal,reflected in its dispersion,demonstrates potential as an early indicator of seizure development.Conclusions:The Sv DC component may reflect local voltage differences likely linked to ion channel activity,potentially contributing to seizure initiation.Combined analysis of Sv DC with low-and high-frequency components offers a comprehensive framework for understanding epileptic networks and guiding diagnosis and therapy.展开更多
Change detection(CD)plays a crucial role in numerous fields,where both convolutional neural networks(CNNs)and Transformers have demonstrated exceptional performance in CD tasks.However,CNNs suffer from limited recepti...Change detection(CD)plays a crucial role in numerous fields,where both convolutional neural networks(CNNs)and Transformers have demonstrated exceptional performance in CD tasks.However,CNNs suffer from limited receptive fields,hindering their ability to capture global features,while Transformers are constrained by high computational complexity.Recently,Mamba architecture,which is based on state space models(SSMs),has shown powerful global modeling capabilities while achieving linear computational complexity.Although some researchers have incorporated Mamba into CD tasks,the existing Mamba⁃based remote sensing CD methods struggle to effectively perceive the inherent locality of changed regions when flattening and scanning remote sensing images,leading to limitations in extracting change features.To address these issues,we propose a novel Mamba⁃based CD method termed difference feature fusion Mamba model(DFFMamba)by mitigating the loss of feature locality caused by traditional Mamba⁃style scanning.Specifically,two distinct difference feature extraction modules are designed:Difference Mamba(DMamba)and local difference Mamba(LDMamba),where DMamba extracts difference features by calculating the difference in coefficient matrices between the state⁃space equations of the bi⁃temporal features.Building upon DMamba,LDMamba combines a locally adaptive state⁃space scanning(LASS)strategy to enhance feature locality so as to accurately extract difference features.Additionally,a fusion Mamba(FMamba)module is proposed,which employs a spatial⁃channel token modeling SSM(SCTMS)unit to integrate multi⁃dimensional spatio⁃temporal interactions of change features,thereby capturing their dependencies across both spatial and channel dimensions.To verify the effectiveness of the proposed DFFMamba,extensive experiments are conducted on three datasets of WHU⁃CD,LEVIR⁃CD,and CLCD.The results demonstrate that DFFMamba significantly outperforms state⁃of⁃the⁃art CD methods,achieving intersection over union(IoU)scores of 90.67%,85.04%,and 66.56%on the three datasets,respectively.展开更多
A closed-form approximate maximum likelihood（AML） algorithm for estimating the position and velocity of a moving source is proposed by utilizing the time difference of arrival（TDOA） and frequency difference of arr...A closed-form approximate maximum likelihood（AML） algorithm for estimating the position and velocity of a moving source is proposed by utilizing the time difference of arrival（TDOA） and frequency difference of arrival（FDOA） measurements of a signal received at a number of receivers.The maximum likelihood（ML） technique is a powerful tool to solve this problem.But a direct approach that uses the ML estimator to solve the localization problem is exhaustive search in the solution space,and it is very computationally expensive,and prohibits real-time processing.On the basis of ML function,a closed-form approximate solution to the ML equations can be obtained,which can allow real-time implementation as well as global convergence.Simulation results show that the proposed estimator achieves better performance than the two-step weighted least squares（WLS） approach,which makes it possible to attain the Cramér-Rao lower bound（CRLB） at a sufficiently high noise level before the threshold effect occurs.展开更多
Objective:To screen phytochemicals in ethanolic leaf extracts of Phyllanthus amarus collected from three different geographical zones in Nigeria and evaluate their effects on larva and adult of Anopheles gambiae.Metho...Objective:To screen phytochemicals in ethanolic leaf extracts of Phyllanthus amarus collected from three different geographical zones in Nigeria and evaluate their effects on larva and adult of Anopheles gambiae.Methods:The sample extracts of Phyllanthus amarus prepared with ethanol solvent were tested against Anopheles gambiae at two important developmental stages of its life cycle using slightly modified WHO protocols.Results:Alkaloids,saponins,tannins,flavonoids,glycosides,phenols,and terpenes were detected in each extract.Among these samples,the extract from northwest exhibited the highest larvicidal activity(LC50=263.02 ppm),followed by southeast and southwest extracts(LC50=288.40 and 295.12 ppm,respectively after 48 h),while the extract from southwest exhibited the highest adulticidal activity(LC50=275.42 ppm),followed by northwest and southeast extract(LC50=301.99 and 316.22 ppm,respectively after 24 h).A 50%larva mortality was almost attained at 600 ppm after 48 h duration of exposure to the northwest extract.Conclusions:The tested samples possess strong larvicidal and adulticidal property against Anopheles gambiae which depends on their chemical composition and localities of collection.Further studies are needed to explore the insecticidal activity against a wider range of mosquito species,and to identify active ingredient(s)of the extract responsible for such activity.展开更多
The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute th...The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.展开更多
By considering higher order approximation to the interaural phase difference, a more general localization equation for stereo sound image with interchannel phase difference is derived. At very low frequency or low int...By considering higher order approximation to the interaural phase difference, a more general localization equation for stereo sound image with interchannel phase difference is derived. At very low frequency or low interchannel phase difference, the equation can be simplified to Makita theory. In general, image position is obviously affected by frequency.It is shown that image position varying with freqllency is the main reason for image width broadening in stereo reproduction with interchannel phase difference. And an extra interaural sound level difference caused by interchannel phase difference is the main reason for image naturalness degrading. In practice, it is necessary to reduce the interchannel phase difference,at least, to less than 60°.展开更多
The aluminum alloy structure impact localization system by using fiber Bragg grating （FBG） sensors and impact localization algorithm was investigated. A four-FBG sensing network was established. And the power intens...The aluminum alloy structure impact localization system by using fiber Bragg grating （FBG） sensors and impact localization algorithm was investigated. A four-FBG sensing network was established. And the power intensity demodulation method was initialized employing the narrow-band tunable laser. The wavelet transform was used to weaken the impact signal noise. And the impact signal time difference was extracted to build the time difference localization algorithm. At last, a fiber Bragg grating impact localization system was established and experimentally verified. The experimental results showed that in the aluminum alloy plate with the 500mm＊500mm＊2mm test area, the maximum and average impact abscissa localization errors were 11 mm and 6.25mm, and the maximum and average impact ordinate localization errors were 9 mm and 4.25 mm, respectively. The fiber Bragg grating sensors and demodulation system are feasible to realize the aviation aluminum alloy material structure impact localization. The research results provide a reliable method for the aluminum alloy material structure impact localization.展开更多
We continue our investigations on pointwise multipliers for Besov spaces of dominating mixed smoothness. This time we study the algebra property of the classes S_(p,q)~rB(R^d) with respect to pointwise multiplication....We continue our investigations on pointwise multipliers for Besov spaces of dominating mixed smoothness. This time we study the algebra property of the classes S_(p,q)~rB(R^d) with respect to pointwise multiplication. In addition, if p≤q, we are able to describe the space of all pointwise multipliers for S_(p,q)~rB(R^d).展开更多
基金supported by the National Natural Science Foundation of China (No.52205548)。
文摘To address the issues of unknown target size,blurred edges,background interference and low contrast in infrared small target detection,this paper proposes a method based on density peaks searching and weighted multi-feature local difference.Firstly,an improved high-boost filter is used for preprocessing to eliminate background clutter and high-brightness interference,thereby increasing the probability of capturing real targets in the density peak search.Secondly,a triple-layer window is used to extract features from the area surrounding candidate targets,addressing the uncertainty of small target sizes.By calculating multi-feature local differences between the triple-layer windows,the problems of blurred target edges and low contrast are resolved.To balance the contribution of different features,intra-class distance is used to calculate weights,achieving weighted fusion of multi-feature local differences to obtain the weighted multi-feature local differences of candidate targets.The real targets are then extracted using the interquartile range.Experiments on datasets such as SIRST and IRSTD-IK show that the proposed method is suitable for various complex types and demonstrates good robustness and detection performance.
基金supported by the National Natural Science Foundation of China(82271494)the STI2030-Major Project(2021ZD0201605)the National Natural Science Foundation of China Major Project(62293552).
文摘Background:Epilepsy is a neurological disorder characterized by recurrent seizures due to hyperexcitable neuronal network activity.The manifestations vary widely,ranging from subtle sensory disturbances to profound alterations of consciousness,depending on which brain regions are affected and their underlying etiology.Exploring the biophysical mechanisms of epileptic seizures holds significant for predicting and controlling the disease.Methods:We analyzed 45 spontaneous seizures recorded from 24 patients with focal epilepsy,as well as stimulation-induced seizures from 2 additional patients.A second-order Butterworth low-pass filter isolated the slow-varying direct current(Sv DC)component(0.01-0.5 Hz),a frequency range often overlooked in electroencephalography(EEG).The energy ratio of the Sv DC component was calculated by dividing its total energy by the total signal energy during seizures and over a 1-hour period including the seizure,enabling comparison between ictal and interictal states.Results:The Sv DC component exhibited spatially dynamic changes during both ictal and interictal periods and showed a moderate correlation with high-frequency activity.Moreover,it accounted for a high energy proportion in both periods,with seizure data showing that 80.82%of leads had≥60%Sv DC energy.Notably,interictal Sv DC fluctuations were more pronounced in electrodes located within the epileptogenic zone,suggesting its potential as a marker for epileptogenic localization.Furthermore,the temporal variability of the Sv DC signal,reflected in its dispersion,demonstrates potential as an early indicator of seizure development.Conclusions:The Sv DC component may reflect local voltage differences likely linked to ion channel activity,potentially contributing to seizure initiation.Combined analysis of Sv DC with low-and high-frequency components offers a comprehensive framework for understanding epileptic networks and guiding diagnosis and therapy.
基金supported by the National Natural Science Foundation of China(Nos.42371449,41801386).
文摘Change detection(CD)plays a crucial role in numerous fields,where both convolutional neural networks(CNNs)and Transformers have demonstrated exceptional performance in CD tasks.However,CNNs suffer from limited receptive fields,hindering their ability to capture global features,while Transformers are constrained by high computational complexity.Recently,Mamba architecture,which is based on state space models(SSMs),has shown powerful global modeling capabilities while achieving linear computational complexity.Although some researchers have incorporated Mamba into CD tasks,the existing Mamba⁃based remote sensing CD methods struggle to effectively perceive the inherent locality of changed regions when flattening and scanning remote sensing images,leading to limitations in extracting change features.To address these issues,we propose a novel Mamba⁃based CD method termed difference feature fusion Mamba model(DFFMamba)by mitigating the loss of feature locality caused by traditional Mamba⁃style scanning.Specifically,two distinct difference feature extraction modules are designed:Difference Mamba(DMamba)and local difference Mamba(LDMamba),where DMamba extracts difference features by calculating the difference in coefficient matrices between the state⁃space equations of the bi⁃temporal features.Building upon DMamba,LDMamba combines a locally adaptive state⁃space scanning(LASS)strategy to enhance feature locality so as to accurately extract difference features.Additionally,a fusion Mamba(FMamba)module is proposed,which employs a spatial⁃channel token modeling SSM(SCTMS)unit to integrate multi⁃dimensional spatio⁃temporal interactions of change features,thereby capturing their dependencies across both spatial and channel dimensions.To verify the effectiveness of the proposed DFFMamba,extensive experiments are conducted on three datasets of WHU⁃CD,LEVIR⁃CD,and CLCD.The results demonstrate that DFFMamba significantly outperforms state⁃of⁃the⁃art CD methods,achieving intersection over union(IoU)scores of 90.67%,85.04%,and 66.56%on the three datasets,respectively.
基金National High-tech Research and Development Program of China (2010AA7010422,2011AA7014061)
文摘A closed-form approximate maximum likelihood（AML） algorithm for estimating the position and velocity of a moving source is proposed by utilizing the time difference of arrival（TDOA） and frequency difference of arrival（FDOA） measurements of a signal received at a number of receivers.The maximum likelihood（ML） technique is a powerful tool to solve this problem.But a direct approach that uses the ML estimator to solve the localization problem is exhaustive search in the solution space,and it is very computationally expensive,and prohibits real-time processing.On the basis of ML function,a closed-form approximate solution to the ML equations can be obtained,which can allow real-time implementation as well as global convergence.Simulation results show that the proposed estimator achieves better performance than the two-step weighted least squares（WLS） approach,which makes it possible to attain the Cramér-Rao lower bound（CRLB） at a sufficiently high noise level before the threshold effect occurs.
文摘Objective:To screen phytochemicals in ethanolic leaf extracts of Phyllanthus amarus collected from three different geographical zones in Nigeria and evaluate their effects on larva and adult of Anopheles gambiae.Methods:The sample extracts of Phyllanthus amarus prepared with ethanol solvent were tested against Anopheles gambiae at two important developmental stages of its life cycle using slightly modified WHO protocols.Results:Alkaloids,saponins,tannins,flavonoids,glycosides,phenols,and terpenes were detected in each extract.Among these samples,the extract from northwest exhibited the highest larvicidal activity(LC50=263.02 ppm),followed by southeast and southwest extracts(LC50=288.40 and 295.12 ppm,respectively after 48 h),while the extract from southwest exhibited the highest adulticidal activity(LC50=275.42 ppm),followed by northwest and southeast extract(LC50=301.99 and 316.22 ppm,respectively after 24 h).A 50%larva mortality was almost attained at 600 ppm after 48 h duration of exposure to the northwest extract.Conclusions:The tested samples possess strong larvicidal and adulticidal property against Anopheles gambiae which depends on their chemical composition and localities of collection.Further studies are needed to explore the insecticidal activity against a wider range of mosquito species,and to identify active ingredient(s)of the extract responsible for such activity.
基金supported by the National Natural Science Foundation of China(61101173)
文摘The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.
文摘By considering higher order approximation to the interaural phase difference, a more general localization equation for stereo sound image with interchannel phase difference is derived. At very low frequency or low interchannel phase difference, the equation can be simplified to Makita theory. In general, image position is obviously affected by frequency.It is shown that image position varying with freqllency is the main reason for image width broadening in stereo reproduction with interchannel phase difference. And an extra interaural sound level difference caused by interchannel phase difference is the main reason for image naturalness degrading. In practice, it is necessary to reduce the interchannel phase difference,at least, to less than 60°.
文摘The aluminum alloy structure impact localization system by using fiber Bragg grating （FBG） sensors and impact localization algorithm was investigated. A four-FBG sensing network was established. And the power intensity demodulation method was initialized employing the narrow-band tunable laser. The wavelet transform was used to weaken the impact signal noise. And the impact signal time difference was extracted to build the time difference localization algorithm. At last, a fiber Bragg grating impact localization system was established and experimentally verified. The experimental results showed that in the aluminum alloy plate with the 500mm＊500mm＊2mm test area, the maximum and average impact abscissa localization errors were 11 mm and 6.25mm, and the maximum and average impact ordinate localization errors were 9 mm and 4.25 mm, respectively. The fiber Bragg grating sensors and demodulation system are feasible to realize the aviation aluminum alloy material structure impact localization. The research results provide a reliable method for the aluminum alloy material structure impact localization.
文摘We continue our investigations on pointwise multipliers for Besov spaces of dominating mixed smoothness. This time we study the algebra property of the classes S_(p,q)~rB(R^d) with respect to pointwise multiplication. In addition, if p≤q, we are able to describe the space of all pointwise multipliers for S_(p,q)~rB(R^d).
