In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining ...In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining algorithm model is constructed. Firstly, according to the attribute, the collected data can be divided into the global data and the phase data, then the appropriate global variables are selected to mine the user’s electricity consumption patterns in the near future on the system clustering algorithm. Based on the theory of grey relational analysis, combing phase data with the power modes to analyze the potential characteristics of residential electricity consumption behaviors deeply that verify the ability of latest power mode to predict household electricity consumption situation in the coming few days and the effect of dominant phase variables on the peak load shifting. Finally, from the actual data of a certain family, the proposed data mining algorithm is testified that it can effectively explore the electricity consumption behavior habits and characteristics of the family.展开更多
This paper investigates the cluster consensus problem for second-order multi-agent systems by applying the pinning control method to a small collection of the agents. Consensus is attained independently for different ...This paper investigates the cluster consensus problem for second-order multi-agent systems by applying the pinning control method to a small collection of the agents. Consensus is attained independently for different agent clusters according to the community structure generated by the group partition of the underlying graph and sufficient conditions for both cluster and general consensus are obtained by using results from algebraic graph theory and the LaSalle Invariance Principle. Finally, some simple simulations are presented to illustrate the technique.展开更多
As data are growing rapidly in data centers,inline cluster deduplication technique has been widely used to improve storage efficiency and data reliability.However,there are some challenges faced by the cluster dedupli...As data are growing rapidly in data centers,inline cluster deduplication technique has been widely used to improve storage efficiency and data reliability.However,there are some challenges faced by the cluster deduplication system:the decreasing data deduplication rate with the increasing deduplication server nodes,high communication overhead for data routing,and load balance to improve the throughput of the system.In this paper,we propose a well-performed cluster deduplication system called AR-Dedupe.The experimental results of two real datasets demonstrate that AR-Dedupe can achieve a high data deduplication rate with a low communication overhead and keep the system load balancing well at the same time through a new data routing algorithm.In addition,we utilize application-aware mechanism to speed up the index of handprints in the routing server which has a 30%performance improvement.展开更多
The devastating complexity of decision making in severe dynamic competitive environment of the universe, has forced the wise managers to have relevant strategic plans for their firms. In this paper, a new approach by ...The devastating complexity of decision making in severe dynamic competitive environment of the universe, has forced the wise managers to have relevant strategic plans for their firms. In this paper, a new approach by utilizing Mahalanobis-Taguchi System (MTS) and clustering algorithm in formulating the strategy has been proposed. In this approach, first by performing environmental analysis all internal and external factors affecting organization will be listed. Then the long range goals will be identified by top managers. By applying MTS the main set of factors affecting goals will come out. By identifying main factors, the goal-factor matrix will be formed. At this stage, by using clustering algorithm the proper clusters containing goals and factors influencing them will be constructed. Finally, from the created clusters the appropriate strategies would be generated. The advantage of applying this method is its accuracy and ease of applications in the environment with plenty of goals and numerous factors with interactions among them.展开更多
Artificial intelligence research in the stock market sector has been heavily geared towards stock price prediction rather than stock price manipulation. As online trading systems have increased the amount of high volu...Artificial intelligence research in the stock market sector has been heavily geared towards stock price prediction rather than stock price manipulation. As online trading systems have increased the amount of high volume and re-al-time data transactions, the stock market has increased vulnerability to at-tacks. This paper aims to detect these attacks based on normal trade behavior using an Artificial Immune System (AIS) approach combined with one of four clustering algorithms. The AIS approach is inspired by its proven ability to handle time-series data and its ability to detect abnormal behavior while only being trained on regular trade behavior. These two main points are essential as the models need to adapt over time to adjust to normal trade behavior as it evolves, and due to confidentiality and data restrictions, real-world manipula-tions are not available for training. This paper discovers a competitive alterna-tive to the leading approach and investigates the effects of combining AIS with clustering algorithms;Kernel Density Estimation, Self-Organized Maps, Densi-ty-Based Spatial Clustering of Applications with Noise and Spectral clustering. The best performing solution achieves leading performance using common clustering metrics, including Area Under the Curve, False Alarm Rate, False Negative Rate, and Computation Time.展开更多
The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchic...The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.展开更多
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
In wide area backup protection of electric power systems, the prerequisite of protection device's accurate, fast and reliable performance is its corresponding fault type and fault location can be discriminated qui...In wide area backup protection of electric power systems, the prerequisite of protection device's accurate, fast and reliable performance is its corresponding fault type and fault location can be discriminated quickly and defined exactly. In our study, global information will be introduced into the backup protection system. By analyzing and computing real-time PMU measurements, basing on cluster analysis theory, we are using mainly hierarchical cluster analysis to search after the statistical laws of electrical quantities' marked changes. Then we carry out fast and exact detection of fault components and fault sections, and finally accomplish fault isolation. The facts show that the fault detection of fault component (fault section) can be performed successfully by hierarchical cluster analysis and calculation. The results of hierarchical cluster analysis are accurate and reliable, and the dendrograms of hierarchical cluster analysis are in intuition.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
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
Inert gas-clustered systems (Xn, X = He, Ne, Ar and n = 2 - 20) were established in this study and their stability as a result of interparticulate interaction was examined. Ferric chloride and ferrous oxides were used...Inert gas-clustered systems (Xn, X = He, Ne, Ar and n = 2 - 20) were established in this study and their stability as a result of interparticulate interaction was examined. Ferric chloride and ferrous oxides were used as catalysts to promote reaction, and 5-nitro-1,2,4-triazol-3-one (NTO) was theoretically synthesized under an inert gas (X6)-clustered environment in this study. The raw material, urea, initially underwent chlorination using chlorine as the reagent, followed by amination, formylation and nitration. Reaction routes closely related to the experimental processes were successfully constructed, and the corresponding energy barriers were estimated for each elementary reaction. The findings revealed that the average errors in the B3LYP/6-31G(d, p)-calculated geometry and vibrational frequency of NTO in an Ne6 system relative to the observed values were 0.83% and 1.84%, respectively. The neon gas-clustered system achieved greater stabilization, which results from the difference in self-consistent field energy (ESCF), than the corresponding stabilization acquired in a helium- or argon-based system. Ferric chloride serves as a good catalyst to reduce the energy barrier of the chlorination reaction, and ferrous oxide is suitable for catalyzing the amination, formylation and nitration reactions, although nitric acid is the better agent for nitration. The catalytic Ne6-clustered reaction system is suggested to be a more feasible pathway for the synthesis of NTO.展开更多
In this paper, we explored a load-balancing algorithm in a cluster file system contains two levels of metadata-server, primary-level server quickly distributestasks to second-level servers depending on the closest loa...In this paper, we explored a load-balancing algorithm in a cluster file system contains two levels of metadata-server, primary-level server quickly distributestasks to second-level servers depending on the closest load-balancing information. At the same time, we explored a method which accurately reflect I/O traffic and storage of storage-node： computing the heat-value of file, according to which we realized a more logical storage allocation. According to the experiment result, we conclude that this new algorithm shortens the executing time of tasks and improves the system performance compared with other load algorithm.展开更多
We introduce a new consensus pattern, named a successive lag cluster consensus(SLCC), which is a generalized pattern of successive lag consensus(SLC). By applying delay-dependent impulsive control, the SLCC of first-o...We introduce a new consensus pattern, named a successive lag cluster consensus(SLCC), which is a generalized pattern of successive lag consensus(SLC). By applying delay-dependent impulsive control, the SLCC of first-order and second-order multi-agent systems is discussed. Furthermore, based on graph theory and stability theory, some sufficient conditions for the stability of SLCC on multi-agent systems are obtained. Finally, several numerical examples are given to verify the correctness of our theoretical results.展开更多
Multiconfiguration quantum chemical calculation of geometry and electron properties of Fe2Si18 cluster indicates on the predictable change of spin states as a function of the excitation energy beginning from ground st...Multiconfiguration quantum chemical calculation of geometry and electron properties of Fe2Si18 cluster indicates on the predictable change of spin states as a function of the excitation energy beginning from ground state with the total spin S = 4. The charges on the two Fe atoms are quite different as well as the charge distribution on the surrounding Si atoms. Nevertheless the total dipole moment of the cluster is a monotonically decreasing function of the excitation energy and it reaches practically zero value in the first singlet state in which the cluster represents a new version of a quibit system.展开更多
On the basis of the first paper’s theoretical derivations and concrete instance calculations of the energies of the d orbitals for a low spin ( S =1/2) nd 5(t 2 5, 2T 2)(n =3, 4, 5) system, the ma...On the basis of the first paper’s theoretical derivations and concrete instance calculations of the energies of the d orbitals for a low spin ( S =1/2) nd 5(t 2 5, 2T 2)(n =3, 4, 5) system, the major results reported in this paper contain the following two respects: explicit relationships between the coefficients of the real and complex Kramers doublets have been derived by using two types of the expressions of the principal components of the g tensors in real and complex orbital representations obtained in the first paper; the use of these relationships of the real and complex orbital coefficients has carried out a series of mathematical demonstrations on the agreement of the real and complex orbital methods .展开更多
随着多变的分布式可再生能源的大规模接入,配电系统将逐步从单纯接受和分配电能的传统电力网络,转变为能量交换网络。近年来,我国智能配电网的建设步伐正在加快。在开展配电网现代化的其他方面工作之前,应该首先做好配电网体系结构设计...随着多变的分布式可再生能源的大规模接入,配电系统将逐步从单纯接受和分配电能的传统电力网络,转变为能量交换网络。近年来,我国智能配电网的建设步伐正在加快。在开展配电网现代化的其他方面工作之前,应该首先做好配电网体系结构设计,即配电网最顶层模型的设计。虽然所谓的总配电系统运营商(total distribution system operator,DSO)模型是最可取方案,但在实践中尚未得到重视。为此,该文在已经过科学论证的电网分层和集群体系结构的框架下对这一问题进行论述,揭示总DSO模式的科学性和其实施的重要意义,并指出由不同局部配电网内的部分分布式能源所集成的虚拟电厂模式的弊端。进而,阐释了与实施DSO模式相关的几个战略性问题,包括重新定义配电服务、开放电表市场、激励新型电力需求和分布式电源的增长,树立新的电网设计理念等,以期大幅降低电网现代化建设的巨额花费。展开更多
文摘In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining algorithm model is constructed. Firstly, according to the attribute, the collected data can be divided into the global data and the phase data, then the appropriate global variables are selected to mine the user’s electricity consumption patterns in the near future on the system clustering algorithm. Based on the theory of grey relational analysis, combing phase data with the power modes to analyze the potential characteristics of residential electricity consumption behaviors deeply that verify the ability of latest power mode to predict household electricity consumption situation in the coming few days and the effect of dominant phase variables on the peak load shifting. Finally, from the actual data of a certain family, the proposed data mining algorithm is testified that it can effectively explore the electricity consumption behavior habits and characteristics of the family.
基金Project supported by the National Natural Science Foundation of China (Grant No. 70571059)
文摘This paper investigates the cluster consensus problem for second-order multi-agent systems by applying the pinning control method to a small collection of the agents. Consensus is attained independently for different agent clusters according to the community structure generated by the group partition of the underlying graph and sufficient conditions for both cluster and general consensus are obtained by using results from algebraic graph theory and the LaSalle Invariance Principle. Finally, some simple simulations are presented to illustrate the technique.
基金the National High Technology Research and Development Program(863)of China(No.2013AA013201)the National Natural Science Foundation of China(Nos.61025009,61232003,61170288 and 61332003)
文摘As data are growing rapidly in data centers,inline cluster deduplication technique has been widely used to improve storage efficiency and data reliability.However,there are some challenges faced by the cluster deduplication system:the decreasing data deduplication rate with the increasing deduplication server nodes,high communication overhead for data routing,and load balance to improve the throughput of the system.In this paper,we propose a well-performed cluster deduplication system called AR-Dedupe.The experimental results of two real datasets demonstrate that AR-Dedupe can achieve a high data deduplication rate with a low communication overhead and keep the system load balancing well at the same time through a new data routing algorithm.In addition,we utilize application-aware mechanism to speed up the index of handprints in the routing server which has a 30%performance improvement.
文摘The devastating complexity of decision making in severe dynamic competitive environment of the universe, has forced the wise managers to have relevant strategic plans for their firms. In this paper, a new approach by utilizing Mahalanobis-Taguchi System (MTS) and clustering algorithm in formulating the strategy has been proposed. In this approach, first by performing environmental analysis all internal and external factors affecting organization will be listed. Then the long range goals will be identified by top managers. By applying MTS the main set of factors affecting goals will come out. By identifying main factors, the goal-factor matrix will be formed. At this stage, by using clustering algorithm the proper clusters containing goals and factors influencing them will be constructed. Finally, from the created clusters the appropriate strategies would be generated. The advantage of applying this method is its accuracy and ease of applications in the environment with plenty of goals and numerous factors with interactions among them.
文摘Artificial intelligence research in the stock market sector has been heavily geared towards stock price prediction rather than stock price manipulation. As online trading systems have increased the amount of high volume and re-al-time data transactions, the stock market has increased vulnerability to at-tacks. This paper aims to detect these attacks based on normal trade behavior using an Artificial Immune System (AIS) approach combined with one of four clustering algorithms. The AIS approach is inspired by its proven ability to handle time-series data and its ability to detect abnormal behavior while only being trained on regular trade behavior. These two main points are essential as the models need to adapt over time to adjust to normal trade behavior as it evolves, and due to confidentiality and data restrictions, real-world manipula-tions are not available for training. This paper discovers a competitive alterna-tive to the leading approach and investigates the effects of combining AIS with clustering algorithms;Kernel Density Estimation, Self-Organized Maps, Densi-ty-Based Spatial Clustering of Applications with Noise and Spectral clustering. The best performing solution achieves leading performance using common clustering metrics, including Area Under the Curve, False Alarm Rate, False Negative Rate, and Computation Time.
文摘The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.
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In wide area backup protection of electric power systems, the prerequisite of protection device's accurate, fast and reliable performance is its corresponding fault type and fault location can be discriminated quickly and defined exactly. In our study, global information will be introduced into the backup protection system. By analyzing and computing real-time PMU measurements, basing on cluster analysis theory, we are using mainly hierarchical cluster analysis to search after the statistical laws of electrical quantities' marked changes. Then we carry out fast and exact detection of fault components and fault sections, and finally accomplish fault isolation. The facts show that the fault detection of fault component (fault section) can be performed successfully by hierarchical cluster analysis and calculation. The results of hierarchical cluster analysis are accurate and reliable, and the dendrograms of hierarchical cluster analysis are in intuition.
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.
文摘Inert gas-clustered systems (Xn, X = He, Ne, Ar and n = 2 - 20) were established in this study and their stability as a result of interparticulate interaction was examined. Ferric chloride and ferrous oxides were used as catalysts to promote reaction, and 5-nitro-1,2,4-triazol-3-one (NTO) was theoretically synthesized under an inert gas (X6)-clustered environment in this study. The raw material, urea, initially underwent chlorination using chlorine as the reagent, followed by amination, formylation and nitration. Reaction routes closely related to the experimental processes were successfully constructed, and the corresponding energy barriers were estimated for each elementary reaction. The findings revealed that the average errors in the B3LYP/6-31G(d, p)-calculated geometry and vibrational frequency of NTO in an Ne6 system relative to the observed values were 0.83% and 1.84%, respectively. The neon gas-clustered system achieved greater stabilization, which results from the difference in self-consistent field energy (ESCF), than the corresponding stabilization acquired in a helium- or argon-based system. Ferric chloride serves as a good catalyst to reduce the energy barrier of the chlorination reaction, and ferrous oxide is suitable for catalyzing the amination, formylation and nitration reactions, although nitric acid is the better agent for nitration. The catalytic Ne6-clustered reaction system is suggested to be a more feasible pathway for the synthesis of NTO.
基金Supported by the Industrialized Foundation ofHebei Province(020501) the Natural Science Foundation of HebeiUniversity(2005Q04)
文摘In this paper, we explored a load-balancing algorithm in a cluster file system contains two levels of metadata-server, primary-level server quickly distributestasks to second-level servers depending on the closest load-balancing information. At the same time, we explored a method which accurately reflect I/O traffic and storage of storage-node： computing the heat-value of file, according to which we realized a more logical storage allocation. According to the experiment result, we conclude that this new algorithm shortens the executing time of tasks and improves the system performance compared with other load algorithm.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61663006 and 11661026)the Guangxi Natural Science Foundation Program,China(Grant No.2015GXNSFBB139002)+1 种基金the Guangxi Key Laboratory of Cryptography and Information Security,China(Grant No.GCIS201612)the Innovation of GUET Graduate Education,China(Grant No.2018YJCX57)
文摘We introduce a new consensus pattern, named a successive lag cluster consensus(SLCC), which is a generalized pattern of successive lag consensus(SLC). By applying delay-dependent impulsive control, the SLCC of first-order and second-order multi-agent systems is discussed. Furthermore, based on graph theory and stability theory, some sufficient conditions for the stability of SLCC on multi-agent systems are obtained. Finally, several numerical examples are given to verify the correctness of our theoretical results.
文摘Multiconfiguration quantum chemical calculation of geometry and electron properties of Fe2Si18 cluster indicates on the predictable change of spin states as a function of the excitation energy beginning from ground state with the total spin S = 4. The charges on the two Fe atoms are quite different as well as the charge distribution on the surrounding Si atoms. Nevertheless the total dipole moment of the cluster is a monotonically decreasing function of the excitation energy and it reaches practically zero value in the first singlet state in which the cluster represents a new version of a quibit system.
文摘On the basis of the first paper’s theoretical derivations and concrete instance calculations of the energies of the d orbitals for a low spin ( S =1/2) nd 5(t 2 5, 2T 2)(n =3, 4, 5) system, the major results reported in this paper contain the following two respects: explicit relationships between the coefficients of the real and complex Kramers doublets have been derived by using two types of the expressions of the principal components of the g tensors in real and complex orbital representations obtained in the first paper; the use of these relationships of the real and complex orbital coefficients has carried out a series of mathematical demonstrations on the agreement of the real and complex orbital methods .
文摘随着多变的分布式可再生能源的大规模接入,配电系统将逐步从单纯接受和分配电能的传统电力网络,转变为能量交换网络。近年来,我国智能配电网的建设步伐正在加快。在开展配电网现代化的其他方面工作之前,应该首先做好配电网体系结构设计,即配电网最顶层模型的设计。虽然所谓的总配电系统运营商(total distribution system operator,DSO)模型是最可取方案,但在实践中尚未得到重视。为此,该文在已经过科学论证的电网分层和集群体系结构的框架下对这一问题进行论述,揭示总DSO模式的科学性和其实施的重要意义,并指出由不同局部配电网内的部分分布式能源所集成的虚拟电厂模式的弊端。进而,阐释了与实施DSO模式相关的几个战略性问题,包括重新定义配电服务、开放电表市场、激励新型电力需求和分布式电源的增长,树立新的电网设计理念等,以期大幅降低电网现代化建设的巨额花费。
