An energy-efficient cloud system with novel dynamic resource allocation methods

The Journal of Supercomputing - In the last decade, cloud computing has brought enormous changes to people’s lives. Cloud computing gives a client-driven computational model. In this case,...     

An end-to-end denoising autoencoder-based deep neural network approach for fault diagnosis of analog circuit

Analog Integrated Circuits and Signal Processing - Fault diagnosis of analog circuit is critical to improve safety and reliability in electrical systems and reduce losses. Traditional fault...     

High-rate capability of carbon-coated micron-sized hexagonal TT-Nb2O5 composites for lithium-ion battery

With excellent specific capacity, superior cycle stability, safety and strong practical, Nb₂O₅ has been considered as one of the prospective anode materials for lithium-ion batteries (LIBs). However, current study suggests that Nb₂O₅ electrode materials for LIBs still face the vital issues of low electrical conductivity and poor rate performance. Therefore, carbon-coated TT-Nb₂O₅ materials are designed and synthesized through solid state method in this work, which present high specific capacity (228 mA h g^?1 at 0.2C), satisfactory rate properties (107 mA h g^?1 at 20 C). The outstanding electrochemical property can not only give the credit to the pseudocapacitance effect of TT-Nb₂O₅, but also attribute to introduction of carbon. The homogeneous carbon-coated materials enhance the electrical conductivity, increase the electron transmission speed and alleviate particle crushing. This research not only offers a new method for preparing excellent electrode materials, but also provides a kind of excellent anode material with prospective application for LIBs.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Software assurance practices for mobile applications

Mobile software applications have to cope with a particular environment that involves small size, limited resources, high autonomy requirements, competitive business models and many other challenges. To provide development guidelines that respond to these needs, several practices have been introduced; however, it is not clear how these guidelines may contribute to solve the issues present in the mobile domain. Furthermore, the rapid evolution of the mobile ecosystem challenges many of the premises upon which the proposed practices were designed. In this paper, we present a survey of the literature on software assurance practices for mobile applications, with the objective of describing them and assessing their contribution and success. We identified, organized and reviewed a body of research that spans in three levels: software development processes, software product assurance practices, and software implementation practices. By carrying out this literature survey, we reviewed the different approaches that researchers on Software Engineering have provided to address the needs that raise in the mobile software development arena. Moreover, we review the evolution of these practices, identifying how the constant changes and modernization of the mobile execution environment has impacted the methods proposed in the literature. Finally, we introduced discussion on the application of these practices in a real productive setting, opening an area for further research that may determine if practitioners have followed the proposed assurance paradigms.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

Se doped nickel-molybdenum bimetal sulfide with enhanced electrochemical activity for hydrogen evolution reaction

In this work, we synthesized Se doped MoS₂@Ni₃S₂ with nanosheets coated nanorods structure supported on Ni foam (MoNiSeS). Firstly, MoS₂@Ni₃S₂ (MoNiS) nanorods was synthesized by hydrothermal method. After selenization treatment, MoSe₂ successfully formed on the edge of MoS₂ nanosheets and particle Ni₃S₂ transformed into NiSe, in which MoSe₂ and NiSe acted as new phase in MoNiSeS. The obtained MoNiSeS only needs a low overpotential of 68 mV to reach the current density of 10 mA cm^?2, and has a low Tafel plots of 72.77 mV dec^?1 and good electrochemical durability, whose electrochemical activity is much better than that of MoNiS and NiSeS, implying the introduction of Mo and Se is beneficial to improve the electrocatalytic performance of NiS for HER. In addition, the proper amount of Mo source, which has an effect on the morphology of product, has also been investigated. For MoNiSeS, the typical nanosheets coated nanarods expose more active sites and the synergic effects is good to the improvement of the catalytic activity. Meanwhile, WNiSeS has also been prepared using the same method and the corresponding results show that the electrochemical activity of WNiSeS is much better than that of NiSeS, proving the universality of this strategy.