The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied...The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied in many fields,including rehabilitation.However,the physiological representations of left and right lower limb movements are too close and activated deep in the cerebral cortex,making it difficult to distinguish their features.Therefore,classifying lower limbs motor imagery is more challenging.In this study,we propose a feature extraction method based on functional connectivity,which utilizes phase-locked values to construct a functional connectivity matrix as the features of the left and right legs,which can effectively avoid the problem of physiological representations of the left and right lower limbs being too close to each other during movement.In addition,considering the topology and the temporal characteristics of the electroencephalogram(EEG),we designed a temporal-spatial convolutional network(TSGCN)to capture the spatiotemporal information for classification.Experimental results show that the accuracy of the proposed method is higher than that of existing methods,achieving an average classification accuracy of 73.58%on the internal dataset.Finally,this study explains the network mechanism of left and right foot MI from the perspective of graph theoretic features and demonstrates the feasibility of decoding lower limb MI.展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
We investigate how dynamical behaviours of complex motor networks depend on the Newman-Watts small-world （NWSW） connections. Network elements are described by the permanent magnet synchronous motor （PMSM） with the...We investigate how dynamical behaviours of complex motor networks depend on the Newman-Watts small-world （NWSW） connections. Network elements are described by the permanent magnet synchronous motor （PMSM） with the values of parameters at which each individual PMSM is stable. It is found that with the increase of connection probability p, the motor in networks becomes periodic and falls into chaotic motion as p further increases. These phenomena imply that NWSW connections can induce and enhance chaos in motor networks. The possible mechanism behind the action of NWSW connections is addressed based on stability theory.展开更多
The intermittent connection（IC）of the field-bus in networked manufacturing systems is a common but hard troubleshooting network problem,which may result in system level failures or safety issues.However,there is no ...The intermittent connection（IC）of the field-bus in networked manufacturing systems is a common but hard troubleshooting network problem,which may result in system level failures or safety issues.However,there is no online IC location identification method available to detect and locate the position of the problem.To tackle this problem,a novel model based online fault location identification method for localized IC problem is proposed.First,the error event patterns are identified and classified according to different node sources in each error frame.Then generalized zero inflated Poisson process（GZIP）model for each node is established by using time stamped error event sequence.Finally,the location of the IC fault is determined by testing whether the parameters of the fitted stochastic model is statistically significant or not using the confident intervals of the estimated parameters.To illustrate the proposed method,case studies are conducted on a 3-node controller area network（CAN）test-bed,in which IC induced faults are imposed on a network drop cable using computer controlled on-off switches.The experimental results show the parameters of the GZIP model for the problematic node are statistically significant（larger than 0）,and the patterns of the confident intervals of the estimated parameters are directly linked to the problematic node,which agrees with the experimental setup.The proposed online IC location identification method can successfully identify the location of the drop cable on which IC faults occurs on the CAN network.展开更多
Patients with age-related hearing loss face hearing difficulties in daily life.The causes of age-related hearing loss are complex and include changes in peripheral hearing,central processing,and cognitive-related abil...Patients with age-related hearing loss face hearing difficulties in daily life.The causes of age-related hearing loss are complex and include changes in peripheral hearing,central processing,and cognitive-related abilities.Furthermore,the factors by which aging relates to hearing loss via changes in audito ry processing ability are still unclear.In this cross-sectional study,we evaluated 27 older adults(over 60 years old) with age-related hearing loss,21 older adults(over 60years old) with normal hearing,and 30 younger subjects(18-30 years old) with normal hearing.We used the outcome of the uppe r-threshold test,including the time-compressed thres h old and the speech recognition threshold in noisy conditions,as a behavioral indicator of auditory processing ability.We also used electroencephalogra p hy to identify presbycusis-related abnormalities in the brain while the participants were in a spontaneous resting state.The timecompressed threshold and speech recognition threshold data indicated significant diffe rences among the groups.In patients with age-related hearing loss,information masking(babble noise) had a greater effect than energy masking(speech-shaped noise) on processing difficulties.In terms of resting-state electroencephalography signals,we observed enhanced fro ntal lobe(Brodmann’s area,BA11) activation in the older adults with normal hearing compared with the younger participants with normal hearing,and greater activation in the parietal(BA7) and occipital(BA19) lobes in the individuals with age-related hearing loss compared with the younger adults.Our functional connection analysis suggested that compared with younger people,the older adults with normal hearing exhibited enhanced connections among networks,including the default mode network,sensorimotor network,cingulo-opercular network,occipital network,and frontoparietal network.These results suggest that both normal aging and the development of age-related hearing loss have a negative effect on advanced audito ry processing capabilities and that hearing loss accele rates the decline in speech comprehension,especially in speech competition situations.Older adults with normal hearing may have increased compensatory attentional resource recruitment represented by the to p-down active listening mechanism,while those with age-related hearing loss exhibit decompensation of network connections involving multisensory integration.展开更多
The normalized weighted capacity reliability index of a sub-domain interconnection large scale communication network is defined and a new algorithm to calculate the reliability index is proposed, The proposed algorith...The normalized weighted capacity reliability index of a sub-domain interconnection large scale communication network is defined and a new algorithm to calculate the reliability index is proposed, The proposed algorithm can be performed using logical or algebraic operation by means of computer-aided programming and the correctness of each key step is validated in detail. This paper takes the sub-domain interconnection symmetrical topologi- cal network for a typical example to calculate the network reliability index and verifies the correctness of the proposed algorithm us- ing the real measured statistical data. The real measured results are well in accordance with the results obtained by the proposed algorithm. The result shows that the proposed algorithm is a valid means to estimate the reliability index of a sub-domain intercon- nection large-scale communication network.展开更多
The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the externa...The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.展开更多
This study involves the development of an analytical model for understanding the behavior of the extended, stiffened end-plate moment connections with eight high strength bolts. Modeling of the connection as an assemb...This study involves the development of an analytical model for understanding the behavior of the extended, stiffened end-plate moment connections with eight high strength bolts. Modeling of the connection as an assemblage of finite elements (FE) used for load deformation analysis, with material, and contact nonlinearities are developed. Results from the FE mathematical model are verified with results from the ANSYS computer program as well as with the test results. Sensitivity and feasibility studies are carried out. Significant geometry and force related variables are introduced;and by varying the geometric variables of the connections within a practical range, a matrix of test cases is obtained. Maximum end-plate separation, maximum bending stresses in the end-plate, and the forces from the connection bolts for these test cases are obtained. From the FE analysis, a database is produced to collect results for the artificial neural network analysis. Finally, salient features of the optimized Artificial Neural Network (ANN) via Genetic Algorithm (GA) analysis are introduced and implemented with the aim of predicting the overall behavior of the connection.展开更多
BACKGROUND Group cognitive behavioral therapy(GCBT)is increasingly being used to treat obsessive-compulsive disorder(OCD)because of its high efficiency,economy,and interaction among group members.However,the changes i...BACKGROUND Group cognitive behavioral therapy(GCBT)is increasingly being used to treat obsessive-compulsive disorder(OCD)because of its high efficiency,economy,and interaction among group members.However,the changes in network functional connectivity(FC)in patients with OCD with GCBT remain unclear.AIM To investigate inter-and intra-network resting-state FC(rs-FC)abnormalities before and after GCBT in unmedicated patients with OCD and validate the efficacy of GCBT.METHODS Overall,33 individuals with OCD and 26 healthy controls underwent resting-state functional magnetic resonance imaging.The patients were rescanned 12 weeks after GCBT.Four cognition-related networks-default mode network(DMN),dorsal attention network(DAN),salience network(SAN),and frontoparietal network(FPN)-were selected to examine FC abnormalities within and between OCD networks before and after GCBT.Neuropsychological assessments including memory,executive function,speech,attention,and visuospatial ability were reassessed following GCBT.Pearson’s correlations were used to analyze the relationship between aberrant FC in cognition-related networks and altered neuropsychological assessments in patients.RESULTS Rs-FC within the DMN and DAN decreased significantly.Additionally,rs-FC between the DMN-DAN,DMNFPN,DMN-SAN,and DAN-SAN also decreased.Significant improvements were observed in cognitive functions,such as memory,executive function,attention,and visuospatial ability.Furthermore,reduced rs-FC within the DMN correlated with visuospatial ability and executive function;DAN positively correlated with Shape Trails Test(STT)-A test elapsed time;DMN-DAN negatively correlated with Rey-Osterrieth Complex Figure(Rey-O)mimicry time and the three elapsed times of the tower of Hanoi;DMN-SAN negatively correlated with Rey-O imitation time and positively correlated with STT-A test elapsed time;and DMN-FPN negatively correlated with Auditory Word Learning Test N1 and N4 scores.CONCLUSION Decreased rs-FC within the DMN and DAN,which correlated with executive function post-treatment,has potential as a neuroimaging marker to predict treatment response to GCBT in patients with OCD.展开更多
BACKGROUND Rumination is a critical psychological factor contributing to the relapse of major depressive episodes(MDEs)and a core residual symptom in remitted MDEs.Investigating its neural correlations is essential fo...BACKGROUND Rumination is a critical psychological factor contributing to the relapse of major depressive episodes(MDEs)and a core residual symptom in remitted MDEs.Investigating its neural correlations is essential for developing strategies to prevent MDE relapse.Despite its clinical importance,the brain network mechanisms underlying rumination in remitted MDE patients have yet to be fully elucidated.AIM To investigate the brain network mechanism underlying rumination in patients with remitted MDEs using functional magnetic resonance imaging(fMRI).METHODS We conducted an fMRI-based rumination-distraction task to induce rumination and distraction states in 51 patients with remitted MDEs.Functional connectivity(FC)was analyzed using the network-based statistic(NBS)approach,and eight topological metrics were calculated to compare the network topological properties between the two states.Correlation analyses were further performed to identify the relationships between individual rumination levels and the significantly altered brain network metrics.RESULTS The NBS analysis revealed that the altered FCs between the rumination and distraction states were located primarily in the frontoparietal,default mode,and cerebellar networks.No significant correlation was detected between these altered FCs and individual rumination levels.Among the eight topological metrics,the clustering coefficient,shortest path length,and local efficiency were significantly lower during rumination and positively correlated with individual rumination levels.In contrast,global efficiency was greater in the rumination state than in the distraction state and was negatively correlated with individual rumination levels.CONCLUSION Our work revealed the altered FC and topological properties during rumination in remitted MDE patients,offering valuable insights into the neural mechanisms of rumination from a brain network perspective.展开更多
Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities ...Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world （SW） connections. Network elements are described by two-dimensional map neurons （2DMNs） with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied.展开更多
BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explo...BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explore the potential characteristics of the brain network and functional connectivity(FC)of SA.METHODS Twenty-six SA individuals and 47 usual aging individuals were recruited from community-dwelling elderly,which were taken the magnetic resonance imaging scan and the global cognitive function assessment by Mini Mental State Examination(MMSE).The resting state-functional magnetic resonance imaging data were preprocessed by DPABISurf,and the brain functional network was conducted by DPABINet.The support vector machine model was constructed with altered functional connectivities to evaluate the identification value of SA.RESULTS The results found that the 6 inter-network FCs of 5 brain networks were significantly altered and related to MMSE performance.The FC of the right orbital part of the middle frontal gyrus and right angular gyrus was mostly increased and positively related to MMSE score,and the FC of the right supramarginal gyrus and right temporal pole:Middle temporal gyrus was the only one decreased and negatively related to MMSE score.All 17 significantly altered FCs of SA were taken into the support vector machine model,and the area under the curve was 0.895.CONCLUSION The identification of key brain networks and FC of SA could help us better understand the brain mechanism and further explore neuroimaging biomarkers of SA.展开更多
In recent years, deep convolutional neural networks have shown superior performance in image denoising. However, deep network structures often come with a large number of model parameters, leading to high training cos...In recent years, deep convolutional neural networks have shown superior performance in image denoising. However, deep network structures often come with a large number of model parameters, leading to high training costs and long inference times, limiting their practical application in denoising tasks. This paper proposes a new dual convolutional denoising network with skip connections(DECDNet), which achieves an ideal balance between denoising effect and network complexity. The proposed DECDNet consists of a noise estimation network, a multi-scale feature extraction network, a dual convolutional neural network, and dual attention mechanisms. The noise estimation network is used to estimate the noise level map, and the multi-scale feature extraction network is combined to improve the model's flexibility in obtaining image features. The dual convolutional neural network branch design includes convolution and dilated convolution interactive connections, with the lower branch consisting of dilated convolution layers, and both branches using skip connections. Experiments show that compared with other models, the proposed DECDNet achieves superior PSNR and SSIM values at all compared noise levels, especially at higher noise levels, showing robustness to images with higher noise levels. It also demonstrates better visual effects, maintaining a balance between denoising and detail preservation.展开更多
In this paper, the main schemes of connection admission control (CAC) in ATM networks are briefly discussed especially the principle of dynamic bandwidth allocation. Then the fair share of the bandwidth among differen...In this paper, the main schemes of connection admission control (CAC) in ATM networks are briefly discussed especially the principle of dynamic bandwidth allocation. Then the fair share of the bandwidth among different traffic sources is analyzed based on cooperative game model. A CAC scheme is proposed using the genetic algorithm (GA) to optimize the bandwidth-delay-product formed utilization function that ensures the fair share and accuracy of accepting/rejecting the incoming calls. Simulation results show that the proposed scheme ensures fairness of the shared bandwidth to different traffic sources.展开更多
Because connection number can express and process synthetic uncertainties caused by various uncertainties in the transmission network planning, a connection number model (CNM) was presented to compare the values of co...Because connection number can express and process synthetic uncertainties caused by various uncertainties in the transmission network planning, a connection number model (CNM) was presented to compare the values of connection number logically. This paper proposed a novel model for transmission network flexible planning with uncertainty. In the proposed planning model both certainty and uncertainty information were included, and the cost-benefit analysis method was used to evaluate the candidate schemes in the objective function. Its good adaptability and flexibility were illustrated through two examples.展开更多
Urban tourism is considered a complex system,and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism,so exploring the multiscale characteristics and...Urban tourism is considered a complex system,and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism,so exploring the multiscale characteristics and connection mechanisms of attraction networks is important for understanding the linkages between attractions and even the future destination planning.This paper uses geotagging data to compare the links between attractions in Beijing,China during four different periods:the pre-Olympic period(2004–2007),the Olympic Games and subsequent‘heat period’(2008–2013),the post-Olympic period(2014–2019),and the COVID-19(Corona Virus Disease 2019)pandemic period(2020–2021).The aim is to better understand the evolution and patterns of attraction networks at different scales in Beijing and to provide insights for tourism planning in the destination.The results show that the macro,meso-,and microscales network characteristics of attraction networks have inherent logical relationships that can explain the commonalities and differences in the development process of tourism networks.The macroscale attraction network degree Matthew effect is significant in the four different periods and exhibits a morphological monocentric structure,suggesting that new entrants are more likely to be associated with attractions that already have high value.The mesoscale links attractions according to the common purpose of tourists,and the results of the community segmentation of the attraction networks in the four different periods suggest that the functional polycentric structure describes their clustering effect,and the weak links between clusters result from attractions bound by incomplete information and distance,and the functional polycentric structure with a generally more efficient network of clusters.The pattern structure at the microscale reveals the topological transformation relationship of the regional collaboration pattern,and the attraction network structure in the four different periods has a very similar importance profile structure suggesting that the attraction network has the same construction rules and evolution mechanism,which aids in understanding the attraction network pattern at both macro and micro scales.Important approaches and practical implications for planners and managers are presented.展开更多
A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the informatio...A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the information of current TCP/ IP network connection information, including IDs of processes which established connections, establishing time, local address, local port, remote address, remote port, etc., from a physical memory on Windows Xflsta operating system. This method is reliable and efficient. It is verified on Windows Vista, Windows Vista SP1, Windows Vista SP2.展开更多
To understand the connectivity of cerebral cor-tex, especially the spatial and temporal pattern of movement, functional magnetic resonance imaging (fMRI) during subjects performing finger key presses was used to extra...To understand the connectivity of cerebral cor-tex, especially the spatial and temporal pattern of movement, functional magnetic resonance imaging (fMRI) during subjects performing finger key presses was used to extract functional networks and then investigated their character-istics. Motor cortex networks were constructed with activation areas obtained with statistical analysis as vertexes and correlation coefficients of fMRI time series as linking strength. The equivalent non-motor cortex networks were constructed with certain distance rules. The graphic and dynamical measures of motor cor-tex networks and non-motor cortex networks were calculated, which shows the motor cortex networks are more compact, having higher sta-tistical independence and integration than the non-motor cortex networks. It indicates the motor cortex networks are more appropriate for information diffusion.展开更多
The hybrid routing protocol has received more attention recently than the proactive and the reactive, especially for large-scale and highly dynamic connection,in mobile ad hoc network. A crucial reason is that zone-la...The hybrid routing protocol has received more attention recently than the proactive and the reactive, especially for large-scale and highly dynamic connection,in mobile ad hoc network. A crucial reason is that zone-layered is being utilized in the complex systems.A hybrid routing algorithm which is layered zone based on adjacency connection(LZBAC) is put forward under the background of a few members in network with steady position and link. The algorithm modifies storage structure of nodes and improves routing mechanism. The theoretical analysis and simulation testing testify that the algorithm costs shorter time of route finding and less delay than others.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
基金supported in part by the National Natural Science Foundation of China under Grant 62172368the Natural Science Foundation of Zhejiang Province under Grant LR22F020003.
文摘The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied in many fields,including rehabilitation.However,the physiological representations of left and right lower limb movements are too close and activated deep in the cerebral cortex,making it difficult to distinguish their features.Therefore,classifying lower limbs motor imagery is more challenging.In this study,we propose a feature extraction method based on functional connectivity,which utilizes phase-locked values to construct a functional connectivity matrix as the features of the left and right legs,which can effectively avoid the problem of physiological representations of the left and right lower limbs being too close to each other during movement.In addition,considering the topology and the temporal characteristics of the electroencephalogram(EEG),we designed a temporal-spatial convolutional network(TSGCN)to capture the spatiotemporal information for classification.Experimental results show that the accuracy of the proposed method is higher than that of existing methods,achieving an average classification accuracy of 73.58%on the internal dataset.Finally,this study explains the network mechanism of left and right foot MI from the perspective of graph theoretic features and demonstrates the feasibility of decoding lower limb MI.
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
基金Project supported by the Key Program of the National Natural Science Foundation of China (Grant No. 50937001)the National Natural Science Foundation of China (Grant Nos. 10862001 and 10947011)the Construction of Key Laboratories in Universities of Guangxi,China (Grant No. 200912)
文摘We investigate how dynamical behaviours of complex motor networks depend on the Newman-Watts small-world （NWSW） connections. Network elements are described by the permanent magnet synchronous motor （PMSM） with the values of parameters at which each individual PMSM is stable. It is found that with the increase of connection probability p, the motor in networks becomes periodic and falls into chaotic motion as p further increases. These phenomena imply that NWSW connections can induce and enhance chaos in motor networks. The possible mechanism behind the action of NWSW connections is addressed based on stability theory.
基金Supported by National Natural Science Foundation of China(Grant No51005205)Science Fund for Creative Research Groups of Nationa Natural Science Foundation of China(Grant No.51221004)+1 种基金Nationa Basic Research Program of China(973 Program,Grant No.2013CB035405)Open Foundation of State Key Laboratory of Automotive Safety and Energy,Tsinghua University,China(Grant No.KF13011)
文摘The intermittent connection（IC）of the field-bus in networked manufacturing systems is a common but hard troubleshooting network problem,which may result in system level failures or safety issues.However,there is no online IC location identification method available to detect and locate the position of the problem.To tackle this problem,a novel model based online fault location identification method for localized IC problem is proposed.First,the error event patterns are identified and classified according to different node sources in each error frame.Then generalized zero inflated Poisson process（GZIP）model for each node is established by using time stamped error event sequence.Finally,the location of the IC fault is determined by testing whether the parameters of the fitted stochastic model is statistically significant or not using the confident intervals of the estimated parameters.To illustrate the proposed method,case studies are conducted on a 3-node controller area network（CAN）test-bed,in which IC induced faults are imposed on a network drop cable using computer controlled on-off switches.The experimental results show the parameters of the GZIP model for the problematic node are statistically significant（larger than 0）,and the patterns of the confident intervals of the estimated parameters are directly linked to the problematic node,which agrees with the experimental setup.The proposed online IC location identification method can successfully identify the location of the drop cable on which IC faults occurs on the CAN network.
基金supported by the National Natural Science Foundation of China,Nos.82171138 (to YQZ),82071 062 (to YXC)the Natural Science Foundation of Guangdong Province,No.2021A1515012038 (to YXC)+1 种基金the Fundamental Research Funds for the Central Universities,No.20ykpy91 (to YXC)the Sun Yat-Sen Clinical Research Cultivating Program,No.SYS-Q-201903 (to YXC)。
文摘Patients with age-related hearing loss face hearing difficulties in daily life.The causes of age-related hearing loss are complex and include changes in peripheral hearing,central processing,and cognitive-related abilities.Furthermore,the factors by which aging relates to hearing loss via changes in audito ry processing ability are still unclear.In this cross-sectional study,we evaluated 27 older adults(over 60 years old) with age-related hearing loss,21 older adults(over 60years old) with normal hearing,and 30 younger subjects(18-30 years old) with normal hearing.We used the outcome of the uppe r-threshold test,including the time-compressed thres h old and the speech recognition threshold in noisy conditions,as a behavioral indicator of auditory processing ability.We also used electroencephalogra p hy to identify presbycusis-related abnormalities in the brain while the participants were in a spontaneous resting state.The timecompressed threshold and speech recognition threshold data indicated significant diffe rences among the groups.In patients with age-related hearing loss,information masking(babble noise) had a greater effect than energy masking(speech-shaped noise) on processing difficulties.In terms of resting-state electroencephalography signals,we observed enhanced fro ntal lobe(Brodmann’s area,BA11) activation in the older adults with normal hearing compared with the younger participants with normal hearing,and greater activation in the parietal(BA7) and occipital(BA19) lobes in the individuals with age-related hearing loss compared with the younger adults.Our functional connection analysis suggested that compared with younger people,the older adults with normal hearing exhibited enhanced connections among networks,including the default mode network,sensorimotor network,cingulo-opercular network,occipital network,and frontoparietal network.These results suggest that both normal aging and the development of age-related hearing loss have a negative effect on advanced audito ry processing capabilities and that hearing loss accele rates the decline in speech comprehension,especially in speech competition situations.Older adults with normal hearing may have increased compensatory attentional resource recruitment represented by the to p-down active listening mechanism,while those with age-related hearing loss exhibit decompensation of network connections involving multisensory integration.
文摘The normalized weighted capacity reliability index of a sub-domain interconnection large scale communication network is defined and a new algorithm to calculate the reliability index is proposed, The proposed algorithm can be performed using logical or algebraic operation by means of computer-aided programming and the correctness of each key step is validated in detail. This paper takes the sub-domain interconnection symmetrical topologi- cal network for a typical example to calculate the network reliability index and verifies the correctness of the proposed algorithm us- ing the real measured statistical data. The real measured results are well in accordance with the results obtained by the proposed algorithm. The result shows that the proposed algorithm is a valid means to estimate the reliability index of a sub-domain intercon- nection large-scale communication network.
基金National Natural Science Foundation of China,No.42371222,No.41971167Fundamental Scientific Research Funds of Central China Normal University,No.CCNU24ZZ120,No.CCNU22JC026。
文摘The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.
文摘This study involves the development of an analytical model for understanding the behavior of the extended, stiffened end-plate moment connections with eight high strength bolts. Modeling of the connection as an assemblage of finite elements (FE) used for load deformation analysis, with material, and contact nonlinearities are developed. Results from the FE mathematical model are verified with results from the ANSYS computer program as well as with the test results. Sensitivity and feasibility studies are carried out. Significant geometry and force related variables are introduced;and by varying the geometric variables of the connections within a practical range, a matrix of test cases is obtained. Maximum end-plate separation, maximum bending stresses in the end-plate, and the forces from the connection bolts for these test cases are obtained. From the FE analysis, a database is produced to collect results for the artificial neural network analysis. Finally, salient features of the optimized Artificial Neural Network (ANN) via Genetic Algorithm (GA) analysis are introduced and implemented with the aim of predicting the overall behavior of the connection.
基金Supported by the Pharmaceutical Science and Technology Project of Zhejiang Province,No.2023RC266the Natural Science Foundation of Ningbo,No.202003N4266.
文摘BACKGROUND Group cognitive behavioral therapy(GCBT)is increasingly being used to treat obsessive-compulsive disorder(OCD)because of its high efficiency,economy,and interaction among group members.However,the changes in network functional connectivity(FC)in patients with OCD with GCBT remain unclear.AIM To investigate inter-and intra-network resting-state FC(rs-FC)abnormalities before and after GCBT in unmedicated patients with OCD and validate the efficacy of GCBT.METHODS Overall,33 individuals with OCD and 26 healthy controls underwent resting-state functional magnetic resonance imaging.The patients were rescanned 12 weeks after GCBT.Four cognition-related networks-default mode network(DMN),dorsal attention network(DAN),salience network(SAN),and frontoparietal network(FPN)-were selected to examine FC abnormalities within and between OCD networks before and after GCBT.Neuropsychological assessments including memory,executive function,speech,attention,and visuospatial ability were reassessed following GCBT.Pearson’s correlations were used to analyze the relationship between aberrant FC in cognition-related networks and altered neuropsychological assessments in patients.RESULTS Rs-FC within the DMN and DAN decreased significantly.Additionally,rs-FC between the DMN-DAN,DMNFPN,DMN-SAN,and DAN-SAN also decreased.Significant improvements were observed in cognitive functions,such as memory,executive function,attention,and visuospatial ability.Furthermore,reduced rs-FC within the DMN correlated with visuospatial ability and executive function;DAN positively correlated with Shape Trails Test(STT)-A test elapsed time;DMN-DAN negatively correlated with Rey-Osterrieth Complex Figure(Rey-O)mimicry time and the three elapsed times of the tower of Hanoi;DMN-SAN negatively correlated with Rey-O imitation time and positively correlated with STT-A test elapsed time;and DMN-FPN negatively correlated with Auditory Word Learning Test N1 and N4 scores.CONCLUSION Decreased rs-FC within the DMN and DAN,which correlated with executive function post-treatment,has potential as a neuroimaging marker to predict treatment response to GCBT in patients with OCD.
基金the National Key Research and Development Program of China,No.2021ZD0202000the National Natural Science Foundation of China,No.82101612 and No.82471570+1 种基金the Natural Science Foundation of Hunan Province,China,No.2022JJ40692the Science and Technology Innovation Program of Hunan Province,No.2021RC2040 and No.2024RC3056.
文摘BACKGROUND Rumination is a critical psychological factor contributing to the relapse of major depressive episodes(MDEs)and a core residual symptom in remitted MDEs.Investigating its neural correlations is essential for developing strategies to prevent MDE relapse.Despite its clinical importance,the brain network mechanisms underlying rumination in remitted MDE patients have yet to be fully elucidated.AIM To investigate the brain network mechanism underlying rumination in patients with remitted MDEs using functional magnetic resonance imaging(fMRI).METHODS We conducted an fMRI-based rumination-distraction task to induce rumination and distraction states in 51 patients with remitted MDEs.Functional connectivity(FC)was analyzed using the network-based statistic(NBS)approach,and eight topological metrics were calculated to compare the network topological properties between the two states.Correlation analyses were further performed to identify the relationships between individual rumination levels and the significantly altered brain network metrics.RESULTS The NBS analysis revealed that the altered FCs between the rumination and distraction states were located primarily in the frontoparietal,default mode,and cerebellar networks.No significant correlation was detected between these altered FCs and individual rumination levels.Among the eight topological metrics,the clustering coefficient,shortest path length,and local efficiency were significantly lower during rumination and positively correlated with individual rumination levels.In contrast,global efficiency was greater in the rumination state than in the distraction state and was negatively correlated with individual rumination levels.CONCLUSION Our work revealed the altered FC and topological properties during rumination in remitted MDE patients,offering valuable insights into the neural mechanisms of rumination from a brain network perspective.
基金Project supported by the Key Program of National Natural Science Foundation of China (Grant No. 50937001),the National Natural Science Foundation of China (Grant Nos. 50877028, 10947011 and 10862001)the High Technology Research and Development Program of China (Grant No. 2007AA05Z229)+1 种基金the Science Foundation of Guangdong Province, China (Grant No. 8251064101000014)the Construction of Key Laboratories in Universities of Guangxi Province, China (Grant No. 200912)
文摘Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world （SW） connections. Network elements are described by two-dimensional map neurons （2DMNs） with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied.
基金Supported by the Wuxi Municipal Health Commission Major Project,No.Z202107。
文摘BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explore the potential characteristics of the brain network and functional connectivity(FC)of SA.METHODS Twenty-six SA individuals and 47 usual aging individuals were recruited from community-dwelling elderly,which were taken the magnetic resonance imaging scan and the global cognitive function assessment by Mini Mental State Examination(MMSE).The resting state-functional magnetic resonance imaging data were preprocessed by DPABISurf,and the brain functional network was conducted by DPABINet.The support vector machine model was constructed with altered functional connectivities to evaluate the identification value of SA.RESULTS The results found that the 6 inter-network FCs of 5 brain networks were significantly altered and related to MMSE performance.The FC of the right orbital part of the middle frontal gyrus and right angular gyrus was mostly increased and positively related to MMSE score,and the FC of the right supramarginal gyrus and right temporal pole:Middle temporal gyrus was the only one decreased and negatively related to MMSE score.All 17 significantly altered FCs of SA were taken into the support vector machine model,and the area under the curve was 0.895.CONCLUSION The identification of key brain networks and FC of SA could help us better understand the brain mechanism and further explore neuroimaging biomarkers of SA.
基金funded by National Nature Science Foundation of China,grant number 61302188。
文摘In recent years, deep convolutional neural networks have shown superior performance in image denoising. However, deep network structures often come with a large number of model parameters, leading to high training costs and long inference times, limiting their practical application in denoising tasks. This paper proposes a new dual convolutional denoising network with skip connections(DECDNet), which achieves an ideal balance between denoising effect and network complexity. The proposed DECDNet consists of a noise estimation network, a multi-scale feature extraction network, a dual convolutional neural network, and dual attention mechanisms. The noise estimation network is used to estimate the noise level map, and the multi-scale feature extraction network is combined to improve the model's flexibility in obtaining image features. The dual convolutional neural network branch design includes convolution and dilated convolution interactive connections, with the lower branch consisting of dilated convolution layers, and both branches using skip connections. Experiments show that compared with other models, the proposed DECDNet achieves superior PSNR and SSIM values at all compared noise levels, especially at higher noise levels, showing robustness to images with higher noise levels. It also demonstrates better visual effects, maintaining a balance between denoising and detail preservation.
基金National Science Foundation of China,Grant No.69682010
文摘In this paper, the main schemes of connection admission control (CAC) in ATM networks are briefly discussed especially the principle of dynamic bandwidth allocation. Then the fair share of the bandwidth among different traffic sources is analyzed based on cooperative game model. A CAC scheme is proposed using the genetic algorithm (GA) to optimize the bandwidth-delay-product formed utilization function that ensures the fair share and accuracy of accepting/rejecting the incoming calls. Simulation results show that the proposed scheme ensures fairness of the shared bandwidth to different traffic sources.
基金the National Natural Science Founda-tion of China (No. 50177017)the Shanghai Key Scienceand Technology Research Program (No. 041612012)
文摘Because connection number can express and process synthetic uncertainties caused by various uncertainties in the transmission network planning, a connection number model (CNM) was presented to compare the values of connection number logically. This paper proposed a novel model for transmission network flexible planning with uncertainty. In the proposed planning model both certainty and uncertainty information were included, and the cost-benefit analysis method was used to evaluate the candidate schemes in the objective function. Its good adaptability and flexibility were illustrated through two examples.
基金Under the auspices of the National Natural Science Foundation of China(No.41971202)the National Natural Science Foundation of China(No.42201181)the Fundamental research funding targets for central universities(No.2412022QD002)。
文摘Urban tourism is considered a complex system,and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism,so exploring the multiscale characteristics and connection mechanisms of attraction networks is important for understanding the linkages between attractions and even the future destination planning.This paper uses geotagging data to compare the links between attractions in Beijing,China during four different periods:the pre-Olympic period(2004–2007),the Olympic Games and subsequent‘heat period’(2008–2013),the post-Olympic period(2014–2019),and the COVID-19(Corona Virus Disease 2019)pandemic period(2020–2021).The aim is to better understand the evolution and patterns of attraction networks at different scales in Beijing and to provide insights for tourism planning in the destination.The results show that the macro,meso-,and microscales network characteristics of attraction networks have inherent logical relationships that can explain the commonalities and differences in the development process of tourism networks.The macroscale attraction network degree Matthew effect is significant in the four different periods and exhibits a morphological monocentric structure,suggesting that new entrants are more likely to be associated with attractions that already have high value.The mesoscale links attractions according to the common purpose of tourists,and the results of the community segmentation of the attraction networks in the four different periods suggest that the functional polycentric structure describes their clustering effect,and the weak links between clusters result from attractions bound by incomplete information and distance,and the functional polycentric structure with a generally more efficient network of clusters.The pattern structure at the microscale reveals the topological transformation relationship of the regional collaboration pattern,and the attraction network structure in the four different periods has a very similar importance profile structure suggesting that the attraction network has the same construction rules and evolution mechanism,which aids in understanding the attraction network pattern at both macro and micro scales.Important approaches and practical implications for planners and managers are presented.
基金This work is supported by the National Natural Science Foundation of China （61070163） and Shandong Natural Science Foundation （Y2008G35）.
文摘A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the information of current TCP/ IP network connection information, including IDs of processes which established connections, establishing time, local address, local port, remote address, remote port, etc., from a physical memory on Windows Xflsta operating system. This method is reliable and efficient. It is verified on Windows Vista, Windows Vista SP1, Windows Vista SP2.
文摘To understand the connectivity of cerebral cor-tex, especially the spatial and temporal pattern of movement, functional magnetic resonance imaging (fMRI) during subjects performing finger key presses was used to extract functional networks and then investigated their character-istics. Motor cortex networks were constructed with activation areas obtained with statistical analysis as vertexes and correlation coefficients of fMRI time series as linking strength. The equivalent non-motor cortex networks were constructed with certain distance rules. The graphic and dynamical measures of motor cor-tex networks and non-motor cortex networks were calculated, which shows the motor cortex networks are more compact, having higher sta-tistical independence and integration than the non-motor cortex networks. It indicates the motor cortex networks are more appropriate for information diffusion.
基金This work was supported in part by Research fund from Educational Committee of China (No104086)
文摘The hybrid routing protocol has received more attention recently than the proactive and the reactive, especially for large-scale and highly dynamic connection,in mobile ad hoc network. A crucial reason is that zone-layered is being utilized in the complex systems.A hybrid routing algorithm which is layered zone based on adjacency connection(LZBAC) is put forward under the background of a few members in network with steady position and link. The algorithm modifies storage structure of nodes and improves routing mechanism. The theoretical analysis and simulation testing testify that the algorithm costs shorter time of route finding and less delay than others.
