Failure prediction plays an important role for many tasks such as optimal resource management in large-scale system. However, accurately failure number prediction of repairable large-scale long-running computing （RLL...Failure prediction plays an important role for many tasks such as optimal resource management in large-scale system. However, accurately failure number prediction of repairable large-scale long-running computing （RLLC） is a challenge because of the reparability and large-scale. To address the challenge, a general Bayesian serial revision prediction method based on Bootstrap approach and moving average approach is put forward, which can make an accurately prediction for the failure number. To demonstrate the performance gains of our method, extensive experiments on the data of Los Alamos National Laboratory （LANL） cluster is implemented, which is a typical RLLC system. And experimental results show that the prediction accuracy of our method is 80.2 %, and it is a greatly improvement with 4 % compared with some typical methods. Finally, the managerial implications of the models are discussed.展开更多
The efficient chiral Ru 3(CO) 12 systems were prepared in situ from Ru 3(CO) 12 and various chiral diimino-or diamino-diphosphine tetradentate ligands. The systems have been used for the asymmetric transfer hy...The efficient chiral Ru 3(CO) 12 systems were prepared in situ from Ru 3(CO) 12 and various chiral diimino-or diamino-diphosphine tetradentate ligands. The systems have been used for the asymmetric transfer hydrogenation of propiophenone in 2-propanol, leading to 1-phenyl-1-propanol in a 98% yield and 96% e.e. The IR study suggests that the carbonyl hydride anion [HRu 3(CO) 11]- most probably exists as a principal species under the reaction conditions. The high chiral efficiency may be due to the synergetic effect produced by the neighboring ruthenium atoms and a special chiral micro-environment involving the polydentate ligand and the Ru 3 framework.展开更多
The percolation fields constructed around the elements of a cluster system in the phase spaces of properties are studied.It is shown that such neighborhoods significantly increase the number of structure parameters of...The percolation fields constructed around the elements of a cluster system in the phase spaces of properties are studied.It is shown that such neighborhoods significantly increase the number of structure parameters of the system under study,expanding the possibilities of analytical description.To study the structure and properties of such systems in the proposed model,a three-dimensional continuum percolation problem with interacting elements is solved.The dependences of the structure and properties of clusters on the parameters of the generation processes of the cluster system are studied,and analytical dependences are obtained.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
An approach for web server cluster(WSC)reliability and degradation process analysis is proposed.The reliability process is modeled as a non-homogeneous Markov process(NHMH)composed of several non-homogeneous Poisson p...An approach for web server cluster(WSC)reliability and degradation process analysis is proposed.The reliability process is modeled as a non-homogeneous Markov process(NHMH)composed of several non-homogeneous Poisson processes(NHPPs).The arrival rate of each NHPP corresponds to the system software failure rate which is expressed using Cox s proportional hazards model(PHM)in terms of the cumulative and instantaneous load of the software.The cumulative load refers to software cumulative execution time,and the instantaneous load denotes the rate that the users requests arrive at a server.The result of reliability analysis is a time-varying reliability and degradation process over the WSC lifetime.Finally,the evaluation experiment shows the effectiveness of the proposed approach.展开更多
This work reports the structural feature and internal motion of one novel hyperbranching cluster system in dilution solution.The cluster system is composed of HB-PS_(300)-g-Pt BA_(45) hypergraft copolymer chains with ...This work reports the structural feature and internal motion of one novel hyperbranching cluster system in dilution solution.The cluster system is composed of HB-PS_(300)-g-Pt BA_(45) hypergraft copolymer chains with uniform subchain,high molar mass and low polydispersity(M_(w)=1.73×106 g/mol and<M_(w)/M_(n)>≈1.07),where HB-PS and Pt BA represent hyperbranched polystyrene core and poly(tert-butyl polyacrylate)graft,respectively.In the selective solvent of PS blocks(cyclohexane,T_(θ)=34.5℃),the aggregation kinetics and structural feature are found to be precisely tunable for assembled clusters by the aggregation temperature(11℃<T<17℃)and time(0 h<t<24 h).An interesting structural evolution kinetics is observed,namely,the fractal dimension(d_(f))of clusters is found to first increases and then decreases with t,eventually,it reaches a plateau value of d_(f)≈3.0,corresponds to a uniform spherical structure.By using dynamic light scattering(DLS)to monitor the number and strength of relaxation modes inΓ(q)withΓbeing the decay rate and q being the scattering vector,it is quantitatively revealed that the relaxation,intensity contribution and mode origin of internal motions of clusters are neither similar with previously reported cluster systems with high polydispersity,nor with the classical linear chain systems.In particular,in the broad range of 2.0<qR_(h)<6.0,we have observed that the reduced first cumulant[Γ^(*)=Γ(q)/(q^(3)k_(B)T/η_(0))]does not display an asymptotic behavior.Whereas,a better asymptotic behavior is observed by plottingΓ(q)/q^(4) versus qRh.For the first time,our observation provides direct evidence supporting that,for hyperbranching cluster system with low polydispersity and high local chain segment density,the hydrodynamic interaction is greatly weakened due to the enhanced hydrodynamic shielding effect.展开更多
We present metal abundance properties of 144 globular clusters associated with M81. These globulars represent the largest globular cluster sample in M81 till now. Our main results are： the distribution of metalliciti...We present metal abundance properties of 144 globular clusters associated with M81. These globulars represent the largest globular cluster sample in M81 till now. Our main results are： the distribution of metallicities is bimodal, with metallicity peaks at [Fe/H] -1.51 and -0.58, and the metal-poor globular clusters tend to be less spatially concentrated than the metal-rich ones; the metal-rich globular clusters in M81 do not demonstrate a centrally concentrated spatial distribution like the metalrich ones in M31 do; like our Galaxy and M31, the globular clusters in M81 have a small radial metallicity gradient. These results are consistent with those obtained from a small sample of M81 globular clusters. In addition, this paper shows that there is evidence that a strong rotation of the M81 globular cluster system around the minor axis exists, and that rotation is present in the metal-rich globular cluster subsample, but the metal-poor globular cluster subsample shows no evidence of rotation. The most significant difference between the rotation of the metal-rich and metal-poor globular clusters occurs at intermediate projected galactocentric radii. Our results confirm the conclusion of Schroder et al. that M81＇s metal-rich globular clusters at intermediate projected radii are associated with a thick disk of M81.展开更多
A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in vari...A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.展开更多
Absolute proper motions and radial velocities of 202 open clusters in the solar neighborhood, which can be used as tracers of the Galactic disk, are used to investigate the kinematics of the Galaxy in the solar vicini...Absolute proper motions and radial velocities of 202 open clusters in the solar neighborhood, which can be used as tracers of the Galactic disk, are used to investigate the kinematics of the Galaxy in the solar vicinity, including the mean heliocentric velocity components （u1, u2, u3） of the open cluster system, the characteristic velocity dispersions （σ1,σ2,σ3）, Oort constants （A, B） and the large-scale radial motion parameters （C, D） of the Galaxy. The results derived from the observational data of proper motions and radial velocities of a subgroup of 117 thin disk young open clusters by means of a maximum likelihood algorithm are： （u1,u2,u3） = （-16.1 ± 1.0,-7.9 ±1.4,-10.4±1.5） km·s^-1, （σ1,σ2,σ3） = （17.0±0.7, 12.2±0.9, 8.0±1.3） km·S^-1, （A, B） = （14.8±1.0, - 13.0±2.7） km·s^-1 kpc^-1, and （C, D） = （1.5 ± 0.7, -1.2 ±1.5） km·s^-1 kpc^-1. A discussion on the results and comparisons with what was obtained by other authors is given.展开更多
Shared nothing spatial database cluster system provides high availability since a replicated node can continue service even if any node in cluster system was crashed. However if the failed node wouldn’t be recovered ...Shared nothing spatial database cluster system provides high availability since a replicated node can continue service even if any node in cluster system was crashed. However if the failed node wouldn’t be recovered quickly, whole system performance will decrease since the other nodes must process the queries which the failed node may be processed. Therefore the recovery of cluster system is very important to provide the stable service. In most previous proposed techniques, external logs should be recorded in all nodes even if the failed node does not exist. So update transactions are processed slowly. Also recovery time of the failed node increases since a single storage for all database is used to record external logs in each node. Therefore we propose a parallel recovery method for recovering the failed node quickly.展开更多
For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Veh...For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.展开更多
Biomass is a renewable energy source helps reduce greenhouse gas emissions.However,combustion and reaction efficiency of biomass are significantly affected by their flow behavior.In this study,the flow characteristics...Biomass is a renewable energy source helps reduce greenhouse gas emissions.However,combustion and reaction efficiency of biomass are significantly affected by their flow behavior.In this study,the flow characteristics of wet elongated biomass particles in a lifting tube were experimentally investigated.Particle Tracking Velocimetry(PTV)was used to explore the particle area and velocity distribution under different gas-to-particle mass ratios(GPMR)and initial moisture contents(IMC).A homogeneity coefficient was also formulated to quantify the flow homogeneity of the particle population.The calculated range for the homogeneity coefficientαis 4.43-6.40,with smaller values indicating better flow homogeneity.Moreover,the factors affecting the fragmentation of larger particle clusters were analyzed with respect to the suspension process,the process of being carried out by the airflow,and the fragmentation process.The results indicated that the flow homogeneity of the particle population was better in the two sets of conditions when IMC was 28.7% and GPMR was 10 and when IMC was 32.5% and GPMR was 9.The homogeneity coefficient α was 4.43 and 4.79.In addition,the degree of fragmentation of larger particle clusters is mainly affected by the IMC.展开更多
Transient stability assessment(TSA)based on artificial intelligence typically has two distinct model management approaches:a unified management approach for all faulted lines and a separate management approach for eac...Transient stability assessment(TSA)based on artificial intelligence typically has two distinct model management approaches:a unified management approach for all faulted lines and a separate management approach for each faulted line.To address the shortcomings of the aforementioned approaches,namely accuracy,training time,and model management complexity,a multi-model management approach for power system TSA based on multi-moment feature clustering has been proposed.First,the steady-state and transient features present under fault conditions were obtained through a transient simulation of line faults.The input sample set was then constructed using the aforementioned multi-moment electrical features and the embedded faulty line numbers.Subsequently,K-means clustering was conducted on each line based on the similarity of their electrical features,employing t-SNE dimensionality reduction.The PSO-CNN model was trained separately for each cluster to generate several independent TSA models.Finally,a model effectiveness evaluation system consisting of five metrics was established,and the effect of the sample imbalance ratio on the model effectiveness was investigated.The model effectiveness was evaluated using the IEEE 39-bus system algorithm.The results showed that the multi-model management strategy based on multi-moment feature clustering can effectively combine the two advantages of superior evaluation performance and streamlined model management by fully extracting system features.Moreover,this approach allows for more flexible adjustments to line topology changes.展开更多
Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their preferences.These systems analyze users...Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their preferences.These systems analyze users’emotional responses,listening habits,and personal preferences to provide personalized suggestions.A significant challenge they face is the“cold start”problem,where new users have no past interactions to guide recommendations.To improve user experience,these systems aimto effectively recommendmusic even to such users by considering their listening behavior and music popularity.This paper introduces a novel music recommendation system that combines order clustering and a convolutional neural network,utilizing user comments and rankings as input.Initially,the system organizes users into clusters based on semantic similarity,followed by the utilization of their rating similarities as input for the convolutional neural network.This network then predicts ratings for unreviewed music by users.Additionally,the system analyses user music listening behaviour and music popularity.Music popularity can help to address cold start users as well.Finally,the proposed method recommends unreviewed music based on predicted high rankings and popularity,taking into account each user’s music listening habits.The proposed method combines predicted high rankings and popularity by first selecting popular unreviewedmusic that themodel predicts to have the highest ratings for each user.Among these,the most popular tracks are prioritized,defined by metrics such as frequency of listening across users.The number of recommended tracks is aligned with each user’s typical listening rate.The experimental findings demonstrate that the new method outperformed other classification techniques and prior recommendation systems,yielding a mean absolute error(MAE)rate and rootmean square error(RMSE)rate of approximately 0.0017,a hit rate of 82.45%,an average normalized discounted cumulative gain(nDCG)of 82.3%,and a prediction accuracy of new ratings at 99.388%.展开更多
With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing hig...With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing higher requirements on the accuracy and efficiency of the power system state estimation to address the challenge of balancing computational efficiency and estimation accuracy in traditional coupled transmission and distribution state estimation methods,this paper proposes a collaborative state estimation method based on distribution systems state clustering and load model parameter identification.To resolve the scalability issue of coupled transmission and distribution power systems,clustering is first carried out based on the distribution system states.As the data and models of the transmission system and distribution systems are not shared.For the transmission system,equating the power transmitted from the transmission system to the distribution system is the same as equating the distribution system.Further,the power transmitted from the transmission system to different types of distribution systems is equivalent to different polynomial equivalent load models.Then,a parameter identification method is proposed to obtain the parameters of the equivalent load model.Finally,a transmission and distribution collaborative state estimation model is constructed based on the equivalent load model.The results of the numerical analysis show that compared with the traditional master-slave splitting method,the proposed method significantly enhances computational efficiency while maintaining high estimation accuracy.展开更多
The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficie...The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficiency of process optimization or monitoring studies.However,the distillation process is highly nonlinear and has multiple uncertainty perturbation intervals,which brings challenges to accurate data-driven modelling of distillation processes.This paper proposes a systematic data-driven modelling framework to solve these problems.Firstly,data segment variance was introduced into the K-means algorithm to form K-means data interval(KMDI)clustering in order to cluster the data into perturbed and steady state intervals for steady-state data extraction.Secondly,maximal information coefficient(MIC)was employed to calculate the nonlinear correlation between variables for removing redundant features.Finally,extreme gradient boosting(XGBoost)was integrated as the basic learner into adaptive boosting(AdaBoost)with the error threshold(ET)set to improve weights update strategy to construct the new integrated learning algorithm,XGBoost-AdaBoost-ET.The superiority of the proposed framework is verified by applying this data-driven modelling framework to a real industrial process of propylene distillation.展开更多
AIM:To evaluate long-term visual field(VF)prediction using K-means clustering in patients with primary open angle glaucoma(POAG).METHODS:Patients who underwent 24-2 VF tests≥10 were included in this study.Using 52 to...AIM:To evaluate long-term visual field(VF)prediction using K-means clustering in patients with primary open angle glaucoma(POAG).METHODS:Patients who underwent 24-2 VF tests≥10 were included in this study.Using 52 total deviation values(TDVs)from the first 10 VF tests of the training dataset,VF points were clustered into several regions using the hierarchical ordered partitioning and collapsing hybrid(HOPACH)and K-means clustering.Based on the clustering results,a linear regression analysis was applied to each clustered region of the testing dataset to predict the TDVs of the 10th VF test.Three to nine VF tests were used to predict the 10th VF test,and the prediction errors(root mean square error,RMSE)of each clustering method and pointwise linear regression(PLR)were compared.RESULTS:The training group consisted of 228 patients(mean age,54.20±14.38y;123 males and 105 females),and the testing group included 81 patients(mean age,54.88±15.22y;43 males and 38 females).All subjects were diagnosed with POAG.Fifty-two VF points were clustered into 11 and nine regions using HOPACH and K-means clustering,respectively.K-means clustering had a lower prediction error than PLR when n=1:3 and 1:4(both P≤0.003).The prediction errors of K-means clustering were lower than those of HOPACH in all sections(n=1:4 to 1:9;all P≤0.011),except for n=1:3(P=0.680).PLR outperformed K-means clustering only when n=1:8 and 1:9(both P≤0.020).CONCLUSION:K-means clustering can predict longterm VF test results more accurately in patients with POAG with limited VF data.展开更多
In the cloud age, heterogeneous application modes on large-scale infrastructures bring about the chal- lenges on resource utilization and manageability to data cen- ters. Many resource and runtime management systems a...In the cloud age, heterogeneous application modes on large-scale infrastructures bring about the chal- lenges on resource utilization and manageability to data cen- ters. Many resource and runtime management systems are developed or evolved to address these challenges and rele- vant problems from different perspectives. This paper tries to identify the main motivations, key concerns, common fea- tures, and representative solutions of such systems through a survey and analysis. A typical kind of these systems is gener- alized as the consolidated cluster system, whose design goal is identified as reducing the overall costs under the quality of service premise. A survey on this kind of systems is given, and the critical issues concerned by such systems are sum- marized as resource consolidation and runtime coordination. These two issues are analyzed and classified according to the design styles and external characteristics abstracted from the surveyed work. Five representative consolidated cluster systems from both academia and industry are illustrated and compared in detail based on the analysis and classifications. We hope this survey and analysis to be conducive to both de- sign implementation and technology selection of this kind of systems, in response to the constantly emerging challenges on infrastructure and application management in data centers.展开更多
We demonstrate fast time-division color etectroholography using a multiple-graphics-processing-unit （GPU） cluster system with a spatial light modulator and a controller to switch the color of the reconstructing ligh...We demonstrate fast time-division color etectroholography using a multiple-graphics-processing-unit （GPU） cluster system with a spatial light modulator and a controller to switch the color of the reconstructing light. The controller comprises a universal serial bus module to drive the liquid crystal optical shutters. By using the controller, the computer-generated hologram （CGH） display node of the multiple-GPU cluster system synchronizes the display of the CGH with the color switching of the reconstructing light. Fast time-division color electroholography at 20 fps is realized for a three-dimensional object comprising 21,000 points per color when 13 GPUs are used in a multiple-GPU cluster system.展开更多
Due to depletion interactions, a few of colloidal spheres will be packed into cluster or clusters, even a phase transition may take place if the volume fraction of system is large enough. In a binary colloidal system,...Due to depletion interactions, a few of colloidal spheres will be packed into cluster or clusters, even a phase transition may take place if the volume fraction of system is large enough. In a binary colloidal system, if the mole fraction of one component is very small, then it can be taken as the impurity of the other component. In this work, the effect of impurity on critical conditions of colloidal cluster nucleation was studied by Carnahan-Starling state equation and the principle of entropy maximum. The results show that, even the mole fraction of small-spheres is very small, the critical volume fraction is obvious smaller than that of one component system, so the influence on critical volume fraction from impurity is very huge and cannot be ignored. In addition, it is also found that, the larger the volume fraction of the system is, the larger cluster density can be packed, however, the critical size of nucleating cluster is almost independent of the density of the cluster.展开更多
基金supported by the National Natural Science Foundationof China (60701006 60804054 71071158)
文摘Failure prediction plays an important role for many tasks such as optimal resource management in large-scale system. However, accurately failure number prediction of repairable large-scale long-running computing （RLLC） is a challenge because of the reparability and large-scale. To address the challenge, a general Bayesian serial revision prediction method based on Bootstrap approach and moving average approach is put forward, which can make an accurately prediction for the failure number. To demonstrate the performance gains of our method, extensive experiments on the data of Los Alamos National Laboratory （LANL） cluster is implemented, which is a typical RLLC system. And experimental results show that the prediction accuracy of our method is 80.2 %, and it is a greatly improvement with 4 % compared with some typical methods. Finally, the managerial implications of the models are discussed.
基金Supported by the National Natural Science Foundation of China(No.2 0 0 730 34,2 0 3730 5 6,2 0 1710 37),Fujian Provinceand Technology Comm ission(No.2 0 0 2 F0 16 ) and Xiamen Science and Technology Com mission(No.35 0 2 Z2 0 0 2 10 4 4 )
文摘The efficient chiral Ru 3(CO) 12 systems were prepared in situ from Ru 3(CO) 12 and various chiral diimino-or diamino-diphosphine tetradentate ligands. The systems have been used for the asymmetric transfer hydrogenation of propiophenone in 2-propanol, leading to 1-phenyl-1-propanol in a 98% yield and 96% e.e. The IR study suggests that the carbonyl hydride anion [HRu 3(CO) 11]- most probably exists as a principal species under the reaction conditions. The high chiral efficiency may be due to the synergetic effect produced by the neighboring ruthenium atoms and a special chiral micro-environment involving the polydentate ligand and the Ru 3 framework.
文摘The percolation fields constructed around the elements of a cluster system in the phase spaces of properties are studied.It is shown that such neighborhoods significantly increase the number of structure parameters of the system under study,expanding the possibilities of analytical description.To study the structure and properties of such systems in the proposed model,a three-dimensional continuum percolation problem with interacting elements is solved.The dependences of the structure and properties of clusters on the parameters of the generation processes of the cluster system are studied,and analytical dependences are obtained.
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The National Natural Science Foundation of China(No.61402333,61402242)the National Science Foundation of Tianjin(No.15JCQNJC00400)
文摘An approach for web server cluster(WSC)reliability and degradation process analysis is proposed.The reliability process is modeled as a non-homogeneous Markov process(NHMH)composed of several non-homogeneous Poisson processes(NHPPs).The arrival rate of each NHPP corresponds to the system software failure rate which is expressed using Cox s proportional hazards model(PHM)in terms of the cumulative and instantaneous load of the software.The cumulative load refers to software cumulative execution time,and the instantaneous load denotes the rate that the users requests arrive at a server.The result of reliability analysis is a time-varying reliability and degradation process over the WSC lifetime.Finally,the evaluation experiment shows the effectiveness of the proposed approach.
基金financially supported by the National Natural Science Foundation of China(No.21973088)Shenzhen Science and Technology Program(Nos.RCYX20210706092101012 and ZDSYS20210623100800001)。
文摘This work reports the structural feature and internal motion of one novel hyperbranching cluster system in dilution solution.The cluster system is composed of HB-PS_(300)-g-Pt BA_(45) hypergraft copolymer chains with uniform subchain,high molar mass and low polydispersity(M_(w)=1.73×106 g/mol and<M_(w)/M_(n)>≈1.07),where HB-PS and Pt BA represent hyperbranched polystyrene core and poly(tert-butyl polyacrylate)graft,respectively.In the selective solvent of PS blocks(cyclohexane,T_(θ)=34.5℃),the aggregation kinetics and structural feature are found to be precisely tunable for assembled clusters by the aggregation temperature(11℃<T<17℃)and time(0 h<t<24 h).An interesting structural evolution kinetics is observed,namely,the fractal dimension(d_(f))of clusters is found to first increases and then decreases with t,eventually,it reaches a plateau value of d_(f)≈3.0,corresponds to a uniform spherical structure.By using dynamic light scattering(DLS)to monitor the number and strength of relaxation modes inΓ(q)withΓbeing the decay rate and q being the scattering vector,it is quantitatively revealed that the relaxation,intensity contribution and mode origin of internal motions of clusters are neither similar with previously reported cluster systems with high polydispersity,nor with the classical linear chain systems.In particular,in the broad range of 2.0<qR_(h)<6.0,we have observed that the reduced first cumulant[Γ^(*)=Γ(q)/(q^(3)k_(B)T/η_(0))]does not display an asymptotic behavior.Whereas,a better asymptotic behavior is observed by plottingΓ(q)/q^(4) versus qRh.For the first time,our observation provides direct evidence supporting that,for hyperbranching cluster system with low polydispersity and high local chain segment density,the hydrodynamic interaction is greatly weakened due to the enhanced hydrodynamic shielding effect.
基金supported by the National Natural Science Foundation of China (Grant Nos. 10873016, 10633020, 10803007,11003021, 11173016 and 11073032)the National Basic Research Program of China (973 Program, 2007CB815403)
文摘We present metal abundance properties of 144 globular clusters associated with M81. These globulars represent the largest globular cluster sample in M81 till now. Our main results are： the distribution of metallicities is bimodal, with metallicity peaks at [Fe/H] -1.51 and -0.58, and the metal-poor globular clusters tend to be less spatially concentrated than the metal-rich ones; the metal-rich globular clusters in M81 do not demonstrate a centrally concentrated spatial distribution like the metalrich ones in M31 do; like our Galaxy and M31, the globular clusters in M81 have a small radial metallicity gradient. These results are consistent with those obtained from a small sample of M81 globular clusters. In addition, this paper shows that there is evidence that a strong rotation of the M81 globular cluster system around the minor axis exists, and that rotation is present in the metal-rich globular cluster subsample, but the metal-poor globular cluster subsample shows no evidence of rotation. The most significant difference between the rotation of the metal-rich and metal-poor globular clusters occurs at intermediate projected galactocentric radii. Our results confirm the conclusion of Schroder et al. that M81＇s metal-rich globular clusters at intermediate projected radii are associated with a thick disk of M81.
文摘A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.
基金Supported by the National Natural Science Foundation of China.
文摘Absolute proper motions and radial velocities of 202 open clusters in the solar neighborhood, which can be used as tracers of the Galactic disk, are used to investigate the kinematics of the Galaxy in the solar vicinity, including the mean heliocentric velocity components （u1, u2, u3） of the open cluster system, the characteristic velocity dispersions （σ1,σ2,σ3）, Oort constants （A, B） and the large-scale radial motion parameters （C, D） of the Galaxy. The results derived from the observational data of proper motions and radial velocities of a subgroup of 117 thin disk young open clusters by means of a maximum likelihood algorithm are： （u1,u2,u3） = （-16.1 ± 1.0,-7.9 ±1.4,-10.4±1.5） km·s^-1, （σ1,σ2,σ3） = （17.0±0.7, 12.2±0.9, 8.0±1.3） km·S^-1, （A, B） = （14.8±1.0, - 13.0±2.7） km·s^-1 kpc^-1, and （C, D） = （1.5 ± 0.7, -1.2 ±1.5） km·s^-1 kpc^-1. A discussion on the results and comparisons with what was obtained by other authors is given.
基金This work is supported by University IT Research Center Project
文摘Shared nothing spatial database cluster system provides high availability since a replicated node can continue service even if any node in cluster system was crashed. However if the failed node wouldn’t be recovered quickly, whole system performance will decrease since the other nodes must process the queries which the failed node may be processed. Therefore the recovery of cluster system is very important to provide the stable service. In most previous proposed techniques, external logs should be recorded in all nodes even if the failed node does not exist. So update transactions are processed slowly. Also recovery time of the failed node increases since a single storage for all database is used to record external logs in each node. Therefore we propose a parallel recovery method for recovering the failed node quickly.
基金supported by the National Natural Science Foundation of China(No.62271399)the National Key Research and Development Program of China(No.2022YFB1807102)。
文摘For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.
基金thefinancial support of the National Natural Science Foundation of China(grant No.51906092)Postgraduate Research&Practice Innovation Program of Jiangsu Province(grant No.SJCX23_2219).
文摘Biomass is a renewable energy source helps reduce greenhouse gas emissions.However,combustion and reaction efficiency of biomass are significantly affected by their flow behavior.In this study,the flow characteristics of wet elongated biomass particles in a lifting tube were experimentally investigated.Particle Tracking Velocimetry(PTV)was used to explore the particle area and velocity distribution under different gas-to-particle mass ratios(GPMR)and initial moisture contents(IMC).A homogeneity coefficient was also formulated to quantify the flow homogeneity of the particle population.The calculated range for the homogeneity coefficientαis 4.43-6.40,with smaller values indicating better flow homogeneity.Moreover,the factors affecting the fragmentation of larger particle clusters were analyzed with respect to the suspension process,the process of being carried out by the airflow,and the fragmentation process.The results indicated that the flow homogeneity of the particle population was better in the two sets of conditions when IMC was 28.7% and GPMR was 10 and when IMC was 32.5% and GPMR was 9.The homogeneity coefficient α was 4.43 and 4.79.In addition,the degree of fragmentation of larger particle clusters is mainly affected by the IMC.
基金supported by the Science and Technology Project of SGCC(5100-202199558A-0-5-ZN).
文摘Transient stability assessment(TSA)based on artificial intelligence typically has two distinct model management approaches:a unified management approach for all faulted lines and a separate management approach for each faulted line.To address the shortcomings of the aforementioned approaches,namely accuracy,training time,and model management complexity,a multi-model management approach for power system TSA based on multi-moment feature clustering has been proposed.First,the steady-state and transient features present under fault conditions were obtained through a transient simulation of line faults.The input sample set was then constructed using the aforementioned multi-moment electrical features and the embedded faulty line numbers.Subsequently,K-means clustering was conducted on each line based on the similarity of their electrical features,employing t-SNE dimensionality reduction.The PSO-CNN model was trained separately for each cluster to generate several independent TSA models.Finally,a model effectiveness evaluation system consisting of five metrics was established,and the effect of the sample imbalance ratio on the model effectiveness was investigated.The model effectiveness was evaluated using the IEEE 39-bus system algorithm.The results showed that the multi-model management strategy based on multi-moment feature clustering can effectively combine the two advantages of superior evaluation performance and streamlined model management by fully extracting system features.Moreover,this approach allows for more flexible adjustments to line topology changes.
基金funded by the National Nature Sciences Foundation of China with Grant No.42250410321。
文摘Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their preferences.These systems analyze users’emotional responses,listening habits,and personal preferences to provide personalized suggestions.A significant challenge they face is the“cold start”problem,where new users have no past interactions to guide recommendations.To improve user experience,these systems aimto effectively recommendmusic even to such users by considering their listening behavior and music popularity.This paper introduces a novel music recommendation system that combines order clustering and a convolutional neural network,utilizing user comments and rankings as input.Initially,the system organizes users into clusters based on semantic similarity,followed by the utilization of their rating similarities as input for the convolutional neural network.This network then predicts ratings for unreviewed music by users.Additionally,the system analyses user music listening behaviour and music popularity.Music popularity can help to address cold start users as well.Finally,the proposed method recommends unreviewed music based on predicted high rankings and popularity,taking into account each user’s music listening habits.The proposed method combines predicted high rankings and popularity by first selecting popular unreviewedmusic that themodel predicts to have the highest ratings for each user.Among these,the most popular tracks are prioritized,defined by metrics such as frequency of listening across users.The number of recommended tracks is aligned with each user’s typical listening rate.The experimental findings demonstrate that the new method outperformed other classification techniques and prior recommendation systems,yielding a mean absolute error(MAE)rate and rootmean square error(RMSE)rate of approximately 0.0017,a hit rate of 82.45%,an average normalized discounted cumulative gain(nDCG)of 82.3%,and a prediction accuracy of new ratings at 99.388%.
基金State Grid Jiangsu Electric Power Co.,Ltd.Technology Project(J2023121).
文摘With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing higher requirements on the accuracy and efficiency of the power system state estimation to address the challenge of balancing computational efficiency and estimation accuracy in traditional coupled transmission and distribution state estimation methods,this paper proposes a collaborative state estimation method based on distribution systems state clustering and load model parameter identification.To resolve the scalability issue of coupled transmission and distribution power systems,clustering is first carried out based on the distribution system states.As the data and models of the transmission system and distribution systems are not shared.For the transmission system,equating the power transmitted from the transmission system to the distribution system is the same as equating the distribution system.Further,the power transmitted from the transmission system to different types of distribution systems is equivalent to different polynomial equivalent load models.Then,a parameter identification method is proposed to obtain the parameters of the equivalent load model.Finally,a transmission and distribution collaborative state estimation model is constructed based on the equivalent load model.The results of the numerical analysis show that compared with the traditional master-slave splitting method,the proposed method significantly enhances computational efficiency while maintaining high estimation accuracy.
基金supported by the National Key Research and Development Program of China(2023YFB3307801)the National Natural Science Foundation of China(62394343,62373155,62073142)+3 种基金Major Science and Technology Project of Xinjiang(No.2022A01006-4)the Programme of Introducing Talents of Discipline to Universities(the 111 Project)under Grant B17017the Fundamental Research Funds for the Central Universities,Science Foundation of China University of Petroleum,Beijing(No.2462024YJRC011)the Open Research Project of the State Key Laboratory of Industrial Control Technology,China(Grant No.ICT2024B70).
文摘The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficiency of process optimization or monitoring studies.However,the distillation process is highly nonlinear and has multiple uncertainty perturbation intervals,which brings challenges to accurate data-driven modelling of distillation processes.This paper proposes a systematic data-driven modelling framework to solve these problems.Firstly,data segment variance was introduced into the K-means algorithm to form K-means data interval(KMDI)clustering in order to cluster the data into perturbed and steady state intervals for steady-state data extraction.Secondly,maximal information coefficient(MIC)was employed to calculate the nonlinear correlation between variables for removing redundant features.Finally,extreme gradient boosting(XGBoost)was integrated as the basic learner into adaptive boosting(AdaBoost)with the error threshold(ET)set to improve weights update strategy to construct the new integrated learning algorithm,XGBoost-AdaBoost-ET.The superiority of the proposed framework is verified by applying this data-driven modelling framework to a real industrial process of propylene distillation.
基金Supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),the Ministry of Health&Welfare,Republic of Korea(No.RS-2020-KH088726)the Patient-Centered Clinical Research Coordinating Center(PACEN),the Ministry of Health and Welfare,Republic of Korea(No.HC19C0276)the National Research Foundation of Korea(NRF),the Korea Government(MSIT)(No.RS-2023-00247504).
文摘AIM:To evaluate long-term visual field(VF)prediction using K-means clustering in patients with primary open angle glaucoma(POAG).METHODS:Patients who underwent 24-2 VF tests≥10 were included in this study.Using 52 total deviation values(TDVs)from the first 10 VF tests of the training dataset,VF points were clustered into several regions using the hierarchical ordered partitioning and collapsing hybrid(HOPACH)and K-means clustering.Based on the clustering results,a linear regression analysis was applied to each clustered region of the testing dataset to predict the TDVs of the 10th VF test.Three to nine VF tests were used to predict the 10th VF test,and the prediction errors(root mean square error,RMSE)of each clustering method and pointwise linear regression(PLR)were compared.RESULTS:The training group consisted of 228 patients(mean age,54.20±14.38y;123 males and 105 females),and the testing group included 81 patients(mean age,54.88±15.22y;43 males and 38 females).All subjects were diagnosed with POAG.Fifty-two VF points were clustered into 11 and nine regions using HOPACH and K-means clustering,respectively.K-means clustering had a lower prediction error than PLR when n=1:3 and 1:4(both P≤0.003).The prediction errors of K-means clustering were lower than those of HOPACH in all sections(n=1:4 to 1:9;all P≤0.011),except for n=1:3(P=0.680).PLR outperformed K-means clustering only when n=1:8 and 1:9(both P≤0.020).CONCLUSION:K-means clustering can predict longterm VF test results more accurately in patients with POAG with limited VF data.
文摘In the cloud age, heterogeneous application modes on large-scale infrastructures bring about the chal- lenges on resource utilization and manageability to data cen- ters. Many resource and runtime management systems are developed or evolved to address these challenges and rele- vant problems from different perspectives. This paper tries to identify the main motivations, key concerns, common fea- tures, and representative solutions of such systems through a survey and analysis. A typical kind of these systems is gener- alized as the consolidated cluster system, whose design goal is identified as reducing the overall costs under the quality of service premise. A survey on this kind of systems is given, and the critical issues concerned by such systems are sum- marized as resource consolidation and runtime coordination. These two issues are analyzed and classified according to the design styles and external characteristics abstracted from the surveyed work. Five representative consolidated cluster systems from both academia and industry are illustrated and compared in detail based on the analysis and classifications. We hope this survey and analysis to be conducive to both de- sign implementation and technology selection of this kind of systems, in response to the constantly emerging challenges on infrastructure and application management in data centers.
基金partially supported by the Japan Society for the Promotion of Science through a Grant-in-Aid for Scientific Research(C)under Grant No.15K00153
文摘We demonstrate fast time-division color etectroholography using a multiple-graphics-processing-unit （GPU） cluster system with a spatial light modulator and a controller to switch the color of the reconstructing light. The controller comprises a universal serial bus module to drive the liquid crystal optical shutters. By using the controller, the computer-generated hologram （CGH） display node of the multiple-GPU cluster system synchronizes the display of the CGH with the color switching of the reconstructing light. Fast time-division color electroholography at 20 fps is realized for a three-dimensional object comprising 21,000 points per color when 13 GPUs are used in a multiple-GPU cluster system.
文摘Due to depletion interactions, a few of colloidal spheres will be packed into cluster or clusters, even a phase transition may take place if the volume fraction of system is large enough. In a binary colloidal system, if the mole fraction of one component is very small, then it can be taken as the impurity of the other component. In this work, the effect of impurity on critical conditions of colloidal cluster nucleation was studied by Carnahan-Starling state equation and the principle of entropy maximum. The results show that, even the mole fraction of small-spheres is very small, the critical volume fraction is obvious smaller than that of one component system, so the influence on critical volume fraction from impurity is very huge and cannot be ignored. In addition, it is also found that, the larger the volume fraction of the system is, the larger cluster density can be packed, however, the critical size of nucleating cluster is almost independent of the density of the cluster.
