To realize dynamic statistical publishing and protection of location-based data privacy,this paper proposes a differential privacy publishing algorithm based on adaptive sampling and grid clustering and adjustment.The...To realize dynamic statistical publishing and protection of location-based data privacy,this paper proposes a differential privacy publishing algorithm based on adaptive sampling and grid clustering and adjustment.The PID control strategy is combined with the difference in data variation to realize the dynamic adjustment of the data publishing intervals.The spatial-temporal correlations of the adjacent snapshots are utilized to design the grid clustering and adjustment algorithm,which facilitates saving the execution time of the publishing process.The budget distribution and budget absorption strategies are improved to form the sliding window-based differential privacy statistical publishing algorithm,which realizes continuous statistical publishing and privacy protection and improves the accuracy of published data.Experiments and analysis on large datasets of actual locations show that the privacy protection algorithm proposed in this paper is superior to other existing algorithms in terms of the accuracy of adaptive sampling time,the availability of published data,and the execution efficiency of data publishing methods.展开更多
Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems ca...Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems can be identified.This approach has been pioneered by Brunton et al.(2016,PNAS)with sparse identification of nonlinear dynamics.Complex systems,however,cannot be expected to benefit from such simple analytical descriptions.Yet,smoothness may be exploited by analytical local descriptions.In this paper,we identify a clusterwise polynomial dynamics from time-resolved snapshot data.The full state space is partitioned into clusters with a reduced-order polynomial description for each cluster and a global patching strategy.The resulting clusterwise modeling is entirely data-driven and requires no prior knowledge of the system dynamics.We illustrate the approach on the well-known chaotic Lorenz and Rössler systems,on the more challenging chaotic fluid flow dynamics of higher state-space dimensions,on a noisy electrocardiogram signal,and finally on the time evolution of the monthly sunspot number.Clusterwise modeling offers a powerful and interpretable paradigm for dynamical modeling.Nonlinear dynamics can be approximated by assembling many simple local models of different resolutions,opening new paths to understand and control intricate nonlinearities.展开更多
Deep reinforcement learning is broadly employed in the optimization of wireless video transmissions.Nevertheless,the instability of the deep reinforcement learning algorithm affects the further improvement of the vide...Deep reinforcement learning is broadly employed in the optimization of wireless video transmissions.Nevertheless,the instability of the deep reinforcement learning algorithm affects the further improvement of the video transmission quality.The federated learning method based on distributed data sets was used to reduce network costs and increase the learning efficiency of the deep learning network model.It solved too much data transfer costs and broke down the data silos.Intra-clustered dynamic federated deep reinforcement learning(IcD-FDRL)was constructed in clustered mobile edge-computing(CMEC)networks due to the promoted video transmission quality for the stability and efficiency of the DRL algorithm.Then,the IcD-FDRL algorithm was employed to CMEC networks’edge for intelligentedge video transmissions,which could satisfy the diversified needs of different users.The simulation analysis proved the effectiveness of IcD-FDRL in improving QoE,cache hit ratio,and training.展开更多
We investigate the interplay between the pseudogap state and d-wave superconductivity in the two-dimensional doped Hubbard model by employing an eight-site cluster dynamical mean-field theory method.By tuning electron...We investigate the interplay between the pseudogap state and d-wave superconductivity in the two-dimensional doped Hubbard model by employing an eight-site cluster dynamical mean-field theory method.By tuning electron hopping parameters,the strong-coupling pseudogap in the two-dimensional Hubbard model can be either enhanced or suppressed in the doped Mott insulator regime.We find that in underdoped cases,the closing of pseudogap leads to a significant enhancement of superconductivity,indicating competition between the two in the underdoped regime.In contrast,at large dopings,suppressing the pseudogap is accompanied by a concurrent decrease in the superconducting transition temperature Tc,which can be attributed to a reduction in antiferromagnetic correlations behind both the pseudogap and superconductivity.We elucidate this evolving relationship between pseudogap and superconductivity across different doping regimes.展开更多
The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are ...The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.展开更多
Conceptual clustering is mainly used for solving the deficiency and incompleteness of domain knowledge.Based on conceptual clustering technology and aiming at the institutional framework and characteristic of Web them...Conceptual clustering is mainly used for solving the deficiency and incompleteness of domain knowledge.Based on conceptual clustering technology and aiming at the institutional framework and characteristic of Web theme information,this paper proposes and implements dynamic conceptual clustering algorithm and merging algorithm for Web documents,and also analyses the super performance of the clustering algorithm in efficiency and clustering accuracy.展开更多
Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called ...Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called DCRCL (Dynamic Clustering Routing Considering Load). This algorithm is comprised of three phases including cluster head (CH) selection, cluster setup and inter-cluster routing. First, the CHs are selected based on residual energy and node load. Then the non-CH nodes choose a cluster by comparing the cost function of its neighbor CHs. At last, each CH communicates with base station by using multi-hop communication. The simulation results show that comparing with the existing one, the techniques life cycle and date volume of the network are increased by 30.7 percent and 29.8 percent respectively by using the proposed algorithm DCRCL.展开更多
Molecular dynamics （MD） simulation has become a powerful tool to investigate the structure- function relationship of proteins and other biological macromolecules at atomic resolution and biologically relevant timesc...Molecular dynamics （MD） simulation has become a powerful tool to investigate the structure- function relationship of proteins and other biological macromolecules at atomic resolution and biologically relevant timescales. MD simulations often produce massive datasets con- taining millions of snapshots describing proteins in motion. Therefore, clustering algorithms have been in high demand to be developed and applied to classify these MD snapshots and gain biological insights. There mainly exist two categories of clustering algorithms that aim to group protein conformations into clusters based on the similarity of their shape （geometric clustering） and kinetics （kinetic clustering）. In this paper, we review a series of frequently used clustering algorithms applied in MD simulations, including divisive algorithms, ag- glomerative algorithms （single-linkage, complete-linkage, average-linkage, centroid-linkage and ward-linkage）, center-based algorithms （K-Means, K-Medoids, K-Centers, and APM）, density-based algorithms （neighbor-based, DBSCAN, density-peaks, and Robust-DB）, and spectral-based algorithms （PCCA and PCCA＋）. In particular, differences between geomet- ric and kinetic clustering metrics will be discussed along with the performances of diflhrent clustering algorithms. We note that there does not exist a one-size-fits-all algorithm in the classification of MD datasets. For a specific application, the right choice of clustering algo- rithm should be based on the purpose of clustering, and the intrinsic properties of the MD conformational ensembles. Therefore, a main focus of our review is to describe the merits and limitations of each clustering algorithm. We expect that this review would be helpful to guide researchers to choose appropriate clustering algorithms for their own MD datasets.展开更多
Most of the existing security Mobicast routing protocols are not suitable for the monitoring applications with higher quality of service （QoS） requirement. A QoS dynamic clustering secure multicast scheme （QoS-DCSM...Most of the existing security Mobicast routing protocols are not suitable for the monitoring applications with higher quality of service （QoS） requirement. A QoS dynamic clustering secure multicast scheme （QoS-DCSMS） based on Mobicast and multi-level IxTESLA protocol for large-scale tracking sensornets is presented in this paper. The multicast clusters are dynamically formed according to the real-time status of nodes, and the cluster-head node is responsible for status review and certificating management of cluster nodes to ensure the most optimized QoS and security of multicast in this scheme. Another contribution of this paper is the optimal QoS security authentication algorithm, which analyzes the relationship between the QoS and the level Mofmulti-level oTESLA. Based on the analysis and simulation results, it shows that the influence to the network survival cycle （＇NSC） and real-time communication caused by energy consumption and latency in authentication is acceptable when the optimal QoS security authentication algorithm is satisfied.展开更多
In dynamic scenarios,visual simultaneous localization and mapping(SLAM)algorithms often incorrectly incorporate dynamic points during camera pose computation,leading to reduced accuracy and robustness.This paper prese...In dynamic scenarios,visual simultaneous localization and mapping(SLAM)algorithms often incorrectly incorporate dynamic points during camera pose computation,leading to reduced accuracy and robustness.This paper presents a dynamic SLAM algorithm that leverages object detection and regional dynamic probability.Firstly,a parallel thread employs the YOLOX object detectionmodel to gather 2D semantic information and compensate for missed detections.Next,an improved K-means++clustering algorithm clusters bounding box regions,adaptively determining the threshold for extracting dynamic object contours as dynamic points change.This process divides the image into low dynamic,suspicious dynamic,and high dynamic regions.In the tracking thread,the dynamic point removal module assigns dynamic probability weights to the feature points in these regions.Combined with geometric methods,it detects and removes the dynamic points.The final evaluation on the public TUM RGB-D dataset shows that the proposed dynamic SLAM algorithm surpasses most existing SLAM algorithms,providing better pose estimation accuracy and robustness in dynamic environments.展开更多
The electronic structure for C 60 was semi empirically investigated by using MD (molecular dynamics) and MNDO (modified neglect of diatomic overlap) approach of quantum chemistry.Especially,taking both σ and ...The electronic structure for C 60 was semi empirically investigated by using MD (molecular dynamics) and MNDO (modified neglect of diatomic overlap) approach of quantum chemistry.Especially,taking both σ and π orbitals into account,one electron energy levels,those symmetries and π orbital occupancies as well as electron excitation energies for different select rules,cohesive energy,ionization energies and electronic affinity forces were calculated.The obtained molecular orbital ratio shows a wide separation of σ and π types,and near HOMO and LUMO levels there are π orbitals mainly.The calculated semi empirical calculation results are in good agreement with experimental and ab initio calculation data.展开更多
The research shows that projection pursuit cluster (PPC) model is able to form a suitable index for overcom-ing the difficulties in comprehensive evaluation, which can be used to analyze complex multivariate prob-lems...The research shows that projection pursuit cluster (PPC) model is able to form a suitable index for overcom-ing the difficulties in comprehensive evaluation, which can be used to analyze complex multivariate prob-lems. The PPC model is widely used in multifactor cluster and evaluation analysis, but there are a few prob-lems needed to be solved in practice, such as cutoff radius parameter calibration. In this study, a new model-projection pursuit dynamic cluster (PPDC) model-based on projection pursuit principle is developed and used in water resources carrying capacity evaluation in China for the first time. In the PPDC model, there are two improvements compared with the PPC model, 1) a new projection index is constructed based on dynamic cluster principle, which avoids the problem of parameter calibration in the PPC model success-fully;2) the cluster results can be outputted directly according to the PPDC model, but the cluster results can be got based on the scatter points of projected characteristic values or the re-analysis for projected character-istic values in the PPC model. The results show that the PPDC model is a very effective and powerful tool in multifactor data exploratory analysis. It is a new method for water resources carrying capacity evaluation. The PPDC model and its application to water resources carrying capacity evaluation are introduced in detail in this paper.展开更多
Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a s...Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member(CM) node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.展开更多
Economic clusters have been a central focus of current urban and regional research, policies and practices. However, a methodology to identify and analyze policy-relevant economic cluster dynamics is still not well de...Economic clusters have been a central focus of current urban and regional research, policies and practices. However, a methodology to identify and analyze policy-relevant economic cluster dynamics is still not well developed. Based on input-output(I-O) data of 1987, 1992, 1997, 2002 and 2007 of Beijing, this article presents an adapted principle component analysis for identifying the evolution of local economic cluster patterns. This research addresses the changes of economic interaction of industries with complementary and common activities over time. The identified clusters provide an insight into the reality of economic development in a diversifying urban economy: the increasing importance of services and the growing interaction between service and manufacturing industries. Our method therefore provides the analysts with a better understanding of the emergence, disappearance and development of economic clusters citywide. The results could be used to assist monitoring urban economic development and designing more practical urban economic strategies.展开更多
The sintering process of nanometer size gold clusters is investigated by using molecular dynamics simulation in the frame of embedded atomistic method. Several molecular dynamics simulation techniques are used to obse...The sintering process of nanometer size gold clusters is investigated by using molecular dynamics simulation in the frame of embedded atomistic method. Several molecular dynamics simulation techniques are used to observe and describe the evolution of the sintering process. The energy distribution for single cluster is examined and the snapshots of sintering process of two clusters are recorded. The evolution of sintering is also described by plotting the mass center changes with time for each cluster. The variations of kinetic and potential energy during the process of sintering are monitored and measured to analyze the dominant mechanisms of sintering from the energy point of view.展开更多
The influence of water on protein conformation was investigated by simulating the molecular dynamics of a model protein lysozyme in different water systems.The lysozyme-water system with TIP3P water model and lysozyme...The influence of water on protein conformation was investigated by simulating the molecular dynamics of a model protein lysozyme in different water systems.The lysozyme-water system with TIP3P water model and lysozyme-water cluster system with six-ring water model were evaluated.In addition,the radial distribution function of solvent around lysozyme was calculated.It is found that the distribution of water molecules around lysozyme is similar to that of water clusters.The analyses of dihedral angles and disulfide bonds of lysozyme show that the conformation of lysozyme is severely damaged in the lysozyme-water cluster system compared with that in the lysozyme-water system.This difference can be attributed to the formation of larger number of intermolecular hydrogen bonds between lysozyme and water cluster.It is in agreement with the analysis that water clusters can change the degree of denaturation in the process of heat denaturation of lysozyme.展开更多
The effects of the diameters of single-walled carbon nanotubes （SWCNTs） （7.83A to 27.40A） and temperature （20 K-45 K） on the equilibrium structure of an argon cluster are systematically studied by molecular dyna...The effects of the diameters of single-walled carbon nanotubes （SWCNTs） （7.83A to 27.40A） and temperature （20 K-45 K） on the equilibrium structure of an argon cluster are systematically studied by molecular dynamics simulation with consideration of the SWCNTs to be fixed. Since the diameters of SWCNTs with different chiralities increase when temperature is fixed at 20 K, the equilibrium structures of the argon cluster transform from monoatomic chains to helical and then to multishell coaxial cylinders. Chirality has almost no noticeable influence on these cylindrosymmetric structures. The effects of temperature and a non-equilibrium sudden heating process on the structures of argon clusters in SWCNTs are also studied by molecular dynamics simulation.展开更多
The accumulation of He on a W surface during keV-He ion irradiation has been simulated using cluster dynamics modeling. This is based mainly on rate theory and improved by involving different types of objects, adoptin...The accumulation of He on a W surface during keV-He ion irradiation has been simulated using cluster dynamics modeling. This is based mainly on rate theory and improved by involving different types of objects, adopting up-to-date parameters and complex reaction processes, as well as considering the diffusion process along with depth. These new features make the simulated results compare very well with the experimental ones. The accumulation and diffusion processes are analyzed, and the depth and size dependence of the He concentrations contributed by different types of He clusters is also discussed. The exploration of the trapping and diffusion effects of the He atoms is helpful in understanding the evolution of the damages in the near-surface of plasma-facing materials under He ion irradiation.展开更多
基金supported by National Nature Science Foundation of China(No.62361036)Nature Science Foundation of Gansu Province(No.22JR5RA279).
文摘To realize dynamic statistical publishing and protection of location-based data privacy,this paper proposes a differential privacy publishing algorithm based on adaptive sampling and grid clustering and adjustment.The PID control strategy is combined with the difference in data variation to realize the dynamic adjustment of the data publishing intervals.The spatial-temporal correlations of the adjacent snapshots are utilized to design the grid clustering and adjustment algorithm,which facilitates saving the execution time of the publishing process.The budget distribution and budget absorption strategies are improved to form the sliding window-based differential privacy statistical publishing algorithm,which realizes continuous statistical publishing and privacy protection and improves the accuracy of published data.Experiments and analysis on large datasets of actual locations show that the privacy protection algorithm proposed in this paper is superior to other existing algorithms in terms of the accuracy of adaptive sampling time,the availability of published data,and the execution efficiency of data publishing methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.12172109,12202121,and 12302293)the China Postdoctoral Science Foundation(Grant Nos.2023M730866 and 2023T160166)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515011492)the Shenzhen Science and Technology Program(Grant Nos.JCYJ20220531095605012,KJZD20230923115210021,and 29853MKCJ202300205).
文摘Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems can be identified.This approach has been pioneered by Brunton et al.(2016,PNAS)with sparse identification of nonlinear dynamics.Complex systems,however,cannot be expected to benefit from such simple analytical descriptions.Yet,smoothness may be exploited by analytical local descriptions.In this paper,we identify a clusterwise polynomial dynamics from time-resolved snapshot data.The full state space is partitioned into clusters with a reduced-order polynomial description for each cluster and a global patching strategy.The resulting clusterwise modeling is entirely data-driven and requires no prior knowledge of the system dynamics.We illustrate the approach on the well-known chaotic Lorenz and Rössler systems,on the more challenging chaotic fluid flow dynamics of higher state-space dimensions,on a noisy electrocardiogram signal,and finally on the time evolution of the monthly sunspot number.Clusterwise modeling offers a powerful and interpretable paradigm for dynamical modeling.Nonlinear dynamics can be approximated by assembling many simple local models of different resolutions,opening new paths to understand and control intricate nonlinearities.
基金supported by the Start-up Project of Doctoral Research in Jiangxi University of Water Resources and Electric Power(No.2024kyqd062)the Key Project of Science and Technology Research of Jiangxi Provincial Education Department(No.GJJ180251)the National Natural Science Foundation of China(No.61961021).
文摘Deep reinforcement learning is broadly employed in the optimization of wireless video transmissions.Nevertheless,the instability of the deep reinforcement learning algorithm affects the further improvement of the video transmission quality.The federated learning method based on distributed data sets was used to reduce network costs and increase the learning efficiency of the deep learning network model.It solved too much data transfer costs and broke down the data silos.Intra-clustered dynamic federated deep reinforcement learning(IcD-FDRL)was constructed in clustered mobile edge-computing(CMEC)networks due to the promoted video transmission quality for the stability and efficiency of the DRL algorithm.Then,the IcD-FDRL algorithm was employed to CMEC networks’edge for intelligentedge video transmissions,which could satisfy the diversified needs of different users.The simulation analysis proved the effectiveness of IcD-FDRL in improving QoE,cache hit ratio,and training.
基金supported by the National Natural Science Foundation of China(Grant Nos.12274472,12494594,12494591,and 92165204)National Key Research and Development Program of China(Grant No.2022YFA1402802)+2 种基金Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices(Grant No.2022B1212010008)Guangdong Fundamental Research Center for Magnetoelectric Physics(Grant No.2024B0303390001)Guangdong Provincial Quantum Science Strategic Initiative(Grant No.GDZX2401010)。
文摘We investigate the interplay between the pseudogap state and d-wave superconductivity in the two-dimensional doped Hubbard model by employing an eight-site cluster dynamical mean-field theory method.By tuning electron hopping parameters,the strong-coupling pseudogap in the two-dimensional Hubbard model can be either enhanced or suppressed in the doped Mott insulator regime.We find that in underdoped cases,the closing of pseudogap leads to a significant enhancement of superconductivity,indicating competition between the two in the underdoped regime.In contrast,at large dopings,suppressing the pseudogap is accompanied by a concurrent decrease in the superconducting transition temperature Tc,which can be attributed to a reduction in antiferromagnetic correlations behind both the pseudogap and superconductivity.We elucidate this evolving relationship between pseudogap and superconductivity across different doping regimes.
基金supported by the National Natural Science Foundation of China(6153302061309014)the Natural Science Foundation Project of CQ CSTC(cstc2017jcyj AX0408)
文摘The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.
基金Suppurted by the Vatonnd“863”Prograan of Chia(2002AAI1010,2003AA0010321)
文摘Conceptual clustering is mainly used for solving the deficiency and incompleteness of domain knowledge.Based on conceptual clustering technology and aiming at the institutional framework and characteristic of Web theme information,this paper proposes and implements dynamic conceptual clustering algorithm and merging algorithm for Web documents,and also analyses the super performance of the clustering algorithm in efficiency and clustering accuracy.
文摘Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called DCRCL (Dynamic Clustering Routing Considering Load). This algorithm is comprised of three phases including cluster head (CH) selection, cluster setup and inter-cluster routing. First, the CHs are selected based on residual energy and node load. Then the non-CH nodes choose a cluster by comparing the cost function of its neighbor CHs. At last, each CH communicates with base station by using multi-hop communication. The simulation results show that comparing with the existing one, the techniques life cycle and date volume of the network are increased by 30.7 percent and 29.8 percent respectively by using the proposed algorithm DCRCL.
基金supported by Shenzhen Science and Technology Innovation Committee(JCYJ20170413173837121)the Hong Kong Research Grant Council(HKUST C6009-15G,14203915,16302214,16304215,16318816,and AoE/P-705/16)+2 种基金King Abdullah University of Science and Technology(KAUST) Office of Sponsored Research(OSR)(OSR-2016-CRG5-3007)Guangzhou Science Technology and Innovation Commission(201704030116)Innovation and Technology Commission(ITCPD/17-9and ITC-CNERC14SC01)
文摘Molecular dynamics （MD） simulation has become a powerful tool to investigate the structure- function relationship of proteins and other biological macromolecules at atomic resolution and biologically relevant timescales. MD simulations often produce massive datasets con- taining millions of snapshots describing proteins in motion. Therefore, clustering algorithms have been in high demand to be developed and applied to classify these MD snapshots and gain biological insights. There mainly exist two categories of clustering algorithms that aim to group protein conformations into clusters based on the similarity of their shape （geometric clustering） and kinetics （kinetic clustering）. In this paper, we review a series of frequently used clustering algorithms applied in MD simulations, including divisive algorithms, ag- glomerative algorithms （single-linkage, complete-linkage, average-linkage, centroid-linkage and ward-linkage）, center-based algorithms （K-Means, K-Medoids, K-Centers, and APM）, density-based algorithms （neighbor-based, DBSCAN, density-peaks, and Robust-DB）, and spectral-based algorithms （PCCA and PCCA＋）. In particular, differences between geomet- ric and kinetic clustering metrics will be discussed along with the performances of diflhrent clustering algorithms. We note that there does not exist a one-size-fits-all algorithm in the classification of MD datasets. For a specific application, the right choice of clustering algo- rithm should be based on the purpose of clustering, and the intrinsic properties of the MD conformational ensembles. Therefore, a main focus of our review is to describe the merits and limitations of each clustering algorithm. We expect that this review would be helpful to guide researchers to choose appropriate clustering algorithms for their own MD datasets.
基金Supported by the National Natural Science Foundation of China （No. 60903157）
文摘Most of the existing security Mobicast routing protocols are not suitable for the monitoring applications with higher quality of service （QoS） requirement. A QoS dynamic clustering secure multicast scheme （QoS-DCSMS） based on Mobicast and multi-level IxTESLA protocol for large-scale tracking sensornets is presented in this paper. The multicast clusters are dynamically formed according to the real-time status of nodes, and the cluster-head node is responsible for status review and certificating management of cluster nodes to ensure the most optimized QoS and security of multicast in this scheme. Another contribution of this paper is the optimal QoS security authentication algorithm, which analyzes the relationship between the QoS and the level Mofmulti-level oTESLA. Based on the analysis and simulation results, it shows that the influence to the network survival cycle （＇NSC） and real-time communication caused by energy consumption and latency in authentication is acceptable when the optimal QoS security authentication algorithm is satisfied.
基金the National Natural Science Foundation of China(No.62063006)to the Guangxi Natural Science Foundation under Grant(Nos.2023GXNSFAA026025,AA24010001)+3 种基金to the Innovation Fund of Chinese Universities Industry-University-Research(ID:2023RY018)to the Special Guangxi Industry and Information Technology Department,Textile and Pharmaceutical Division(ID:2021 No.231)to the Special Research Project of Hechi University(ID:2021GCC028)to the Key Laboratory of AI and Information Processing,Education Department of Guangxi Zhuang Autonomous Region(Hechi University),No.2024GXZDSY009。
文摘In dynamic scenarios,visual simultaneous localization and mapping(SLAM)algorithms often incorrectly incorporate dynamic points during camera pose computation,leading to reduced accuracy and robustness.This paper presents a dynamic SLAM algorithm that leverages object detection and regional dynamic probability.Firstly,a parallel thread employs the YOLOX object detectionmodel to gather 2D semantic information and compensate for missed detections.Next,an improved K-means++clustering algorithm clusters bounding box regions,adaptively determining the threshold for extracting dynamic object contours as dynamic points change.This process divides the image into low dynamic,suspicious dynamic,and high dynamic regions.In the tracking thread,the dynamic point removal module assigns dynamic probability weights to the feature points in these regions.Combined with geometric methods,it detects and removes the dynamic points.The final evaluation on the public TUM RGB-D dataset shows that the proposed dynamic SLAM algorithm surpasses most existing SLAM algorithms,providing better pose estimation accuracy and robustness in dynamic environments.
文摘The electronic structure for C 60 was semi empirically investigated by using MD (molecular dynamics) and MNDO (modified neglect of diatomic overlap) approach of quantum chemistry.Especially,taking both σ and π orbitals into account,one electron energy levels,those symmetries and π orbital occupancies as well as electron excitation energies for different select rules,cohesive energy,ionization energies and electronic affinity forces were calculated.The obtained molecular orbital ratio shows a wide separation of σ and π types,and near HOMO and LUMO levels there are π orbitals mainly.The calculated semi empirical calculation results are in good agreement with experimental and ab initio calculation data.
文摘The research shows that projection pursuit cluster (PPC) model is able to form a suitable index for overcom-ing the difficulties in comprehensive evaluation, which can be used to analyze complex multivariate prob-lems. The PPC model is widely used in multifactor cluster and evaluation analysis, but there are a few prob-lems needed to be solved in practice, such as cutoff radius parameter calibration. In this study, a new model-projection pursuit dynamic cluster (PPDC) model-based on projection pursuit principle is developed and used in water resources carrying capacity evaluation in China for the first time. In the PPDC model, there are two improvements compared with the PPC model, 1) a new projection index is constructed based on dynamic cluster principle, which avoids the problem of parameter calibration in the PPC model success-fully;2) the cluster results can be outputted directly according to the PPDC model, but the cluster results can be got based on the scatter points of projected characteristic values or the re-analysis for projected character-istic values in the PPC model. The results show that the PPDC model is a very effective and powerful tool in multifactor data exploratory analysis. It is a new method for water resources carrying capacity evaluation. The PPDC model and its application to water resources carrying capacity evaluation are introduced in detail in this paper.
基金Projects(90820302,60805027)supported by the National Natural Science Foundation of ChinaProject(200805330005)supported by the Research Fund for the Doctoral Program of Higher Education,ChinaProject(2009FJ4030)supported by Academician Foundation of Hunan Province,China
文摘Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member(CM) node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.
基金Under the auspices of National Natural Science Foundation of China(No.41371008)
文摘Economic clusters have been a central focus of current urban and regional research, policies and practices. However, a methodology to identify and analyze policy-relevant economic cluster dynamics is still not well developed. Based on input-output(I-O) data of 1987, 1992, 1997, 2002 and 2007 of Beijing, this article presents an adapted principle component analysis for identifying the evolution of local economic cluster patterns. This research addresses the changes of economic interaction of industries with complementary and common activities over time. The identified clusters provide an insight into the reality of economic development in a diversifying urban economy: the increasing importance of services and the growing interaction between service and manufacturing industries. Our method therefore provides the analysts with a better understanding of the emergence, disappearance and development of economic clusters citywide. The results could be used to assist monitoring urban economic development and designing more practical urban economic strategies.
文摘The sintering process of nanometer size gold clusters is investigated by using molecular dynamics simulation in the frame of embedded atomistic method. Several molecular dynamics simulation techniques are used to observe and describe the evolution of the sintering process. The energy distribution for single cluster is examined and the snapshots of sintering process of two clusters are recorded. The evolution of sintering is also described by plotting the mass center changes with time for each cluster. The variations of kinetic and potential energy during the process of sintering are monitored and measured to analyze the dominant mechanisms of sintering from the energy point of view.
基金Supported by National Natural Science Foundation of China (No. 20676094)
文摘The influence of water on protein conformation was investigated by simulating the molecular dynamics of a model protein lysozyme in different water systems.The lysozyme-water system with TIP3P water model and lysozyme-water cluster system with six-ring water model were evaluated.In addition,the radial distribution function of solvent around lysozyme was calculated.It is found that the distribution of water molecules around lysozyme is similar to that of water clusters.The analyses of dihedral angles and disulfide bonds of lysozyme show that the conformation of lysozyme is severely damaged in the lysozyme-water cluster system compared with that in the lysozyme-water system.This difference can be attributed to the formation of larger number of intermolecular hydrogen bonds between lysozyme and water cluster.It is in agreement with the analysis that water clusters can change the degree of denaturation in the process of heat denaturation of lysozyme.
基金Project supported by the National Natural Science Foundation of China(Grant No.11072242)
文摘The effects of the diameters of single-walled carbon nanotubes （SWCNTs） （7.83A to 27.40A） and temperature （20 K-45 K） on the equilibrium structure of an argon cluster are systematically studied by molecular dynamics simulation with consideration of the SWCNTs to be fixed. Since the diameters of SWCNTs with different chiralities increase when temperature is fixed at 20 K, the equilibrium structures of the argon cluster transform from monoatomic chains to helical and then to multishell coaxial cylinders. Chirality has almost no noticeable influence on these cylindrosymmetric structures. The effects of temperature and a non-equilibrium sudden heating process on the structures of argon clusters in SWCNTs are also studied by molecular dynamics simulation.
基金supported by the Special Funds for Major State Basic Research Project of China(973)(Nos.2007CB925004 and 2008CB717802)the Knowledge Innovation Program of the Chinese Academy of Sciences(No.KJCX2-YW-N35)+2 种基金National Natural Science Foundation of China(No.11005124)the China Postdoctoral Science Foundation Funded Project(No.20100470863)Director Grants of CASHIPS.Part of the calculations were performed in the Center for Computational Science of CASHIPS
文摘The accumulation of He on a W surface during keV-He ion irradiation has been simulated using cluster dynamics modeling. This is based mainly on rate theory and improved by involving different types of objects, adopting up-to-date parameters and complex reaction processes, as well as considering the diffusion process along with depth. These new features make the simulated results compare very well with the experimental ones. The accumulation and diffusion processes are analyzed, and the depth and size dependence of the He concentrations contributed by different types of He clusters is also discussed. The exploration of the trapping and diffusion effects of the He atoms is helpful in understanding the evolution of the damages in the near-surface of plasma-facing materials under He ion irradiation.
