Full configuration interaction (FCI) can provide an exact molecular ground-state energy within a given basis set and serve as benchmark for approximate methods in quantum chemical calculations, including the emerging variational eigensolver. However, its exponential computational memory requirements easily exceed capability of single server limit applicability to large molecules. In this paper, we present distributed FCI implementation employing hybrid parallelization scheme with...

Journal Article A delay fractioning approach to robust sliding mode control for discrete-time stochastic systems with randomly occurring non-linearities Get access Jun Hu, Hu Space Control and Inertial Technology Research Center, Harbin Institute of Technology, 150001, People's Republic China Search other works by this author on: Oxford Academic Google Scholar Zidong Wang, Wang * Department Information Systems Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, UK *Corresponding...

Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the problem of sample imbalance and there is no study investigate impact on identifying genes. In addition, it not clear which method more suitable for unbalanced data.Based random sampling, evaluation models are Using models, performances six famous compared data. The experimental results indicate that has a great influence...

The increase in the amount of manufacturing information available means that big data can be collected and, with appropriate deep analysis, could great value to manufacturers. However, most small manufacturers cannot afford overhead a professional analytics team. To address this problem, paper generic system, Generic Manufacturing Data Analytics system (GMDA), is proposed. This perform tasks and users easily carry out analysis even if they have no prior knowledge or experience analytics....

Tasks allocation plays an important role in resource-limited sensor networks. However, existing methods separate energy saving and QoS (Quality-of- Service)-guarantee into two issues, consequently, the scheduling length could be very long which violating user's deadline requirement or might waste lots of energy. This paper discusses problem allocating a set real-time tasks with dependencies onto heterogeneous network. In order to find optimal that minimize overall consumption while meeting...

In this paper, we deal with the problem of rule-based entity resolution on imprecise temporal data. Entity (ER) is widely explored in research community, but data, especially without available timestamps, has not been studied well yet. Because elapsing time, records referring to same observed different time periods may be different. Besides traditional similarity-based ER approaches, by carefully exploring several data quality rules, e.g., matching dependency and currency, much information...

In real world, social networks are large scale, noisy and evolutionary. Communities inherent characteristics of human interaction in networks. Tracking evolutionary communities dynamic has become an increasingly important research topic. Several classic incremental clustering algorithms have been proposed. But they all face a problem controlling the balance between running time quality. this paper, we propose fast community evolution tracking (FICET) framework to discover track slowly highly...

Data quality issues have attracted widespread attention due to the negative impacts of dirty data on mining and machine learning results. The relationship between accuracy results could be applied selection appropriate algorithm with consideration determination share clean. However, rare research has focused exploring such relationship. Motivated by this, this paper conducts an experimental comparison for effects missing, inconsistent conflicting classification clustering algorithms. Based...

In wireless sensor networks, missing data is inevitable due to the inherent characteristic of and it causes many difficulties in various applications. To solve problem, best way estimate as accurately possible. this paper, for changing smoothly, a temporal correlation based estimation algorithm proposed, which adopts cubic spline interpolation model capture trend varying. Next, non-smoothly, spatial multiple regression describe among neighbor nodes. Based on these two algorithms, an adaptive...

Anomaly detection plays a significant role in helping gas turbines run reliably and economically. Considering the collective anomalous data both sensitivity robustness of anomaly model, sequential symbolic method is proposed applied to turbine fuel system. A structural Finite State Machine used evaluate posterior probabilities observing sequences most probable state they may locate. Hence an estimation-based model decoding-based are identify anomalies two different ways. Experimental results...