云环境下安全密文区间检索方案的新设计

针对目前密文区间检索多次断言存在信息泄露等问题,有单断言的密文区间检索方案(SRQSAE方案),并证明方案在唯密文攻击下的隐私安全性。对SRQSAE方案的安全性进行了分析,分析结果表明SRQSAE方案并不能隐藏搜索关键字的大小关系排序。通过在每次生成搜索索引或陷门消息时引入不同随机数的方法,提出了单断言的密文区间检索新方案。新方案对搜索关键字、区间的大小关系提供了很好的隐私保护;而且新方案在安全性提高的同时,并不以损失效率为代价。     

Extended vertical lists for temporal pattern mining from multivariate time series

In this paper, the problem of mining complex temporal patterns in the context of multivariate time series is considered. A new method called the Fast Temporal Pattern Mining with Extended Vertical Lists is introduced. The method is based on an extension of the level‐wise property, which requires a more complex pattern to start at positions within a record where all of the subpatterns of the pattern start. The approach is built around a novel data structure called the Extended Vertical List that tracks positions of the first state of the pattern inside records and links them to appropriate positions of a specific subpattern of the pattern called the prefix. Extensive computational results indicate that the new method performs significantly faster than the previous version of the algorithm for Temporal Pattern Mining; however, the increase in speed comes at the expense of increased memory usage.     

A new interval diagnosis method: Application to the spacecraft rendezvous phase of the Mars sample return mission

This paper presents a new optimized interval principal component analysis applied to detect and isolate actuators faults of an autonomous spacecraft involved in the rendezvous phase of the Mars sample return mission. Based on the exploitation of various arithmetic and interval analysis properties, the new interval model is built by solving the interval eigenpairs problem via a resolution of a parametric linear programming problem. The detection and isolation phases are performed by extending the classic methods to interval-valued data. The proposed method is applied to detect and isolate actuators faults that can occur on the spacecraft's thrusters. Based on data provided by a “high fidelity” industrial simulator developed by Thales Alenia Space, the obtained results proved the effectiveness of the proposed interval fault diagnosis method on detecting and isolating thrusters' faults.     

Fatigue crack initiation and crystallographic growth in 316L stainless steel

A mesoscale model of fatigue crack formation and stress–strain behavior in crystalline alloys entitled Sistaninia–Niffenegger Fatigue (SNF) model is applied to AISI 316L austenitic stainless steel. An inelastic hysteresis energy criterion in conjunction with continuum damage modeling provides a strong tool for studying the behavior of the austenitic steel under cyclic loading. The model predictions are validated against fatigue experimental data. The results show that this microstructural-based modeling approach is capable for predicting the behavior of the steel even under complex loading conditions. It can reproduce and help to understand well known fatigue experimental facts, e.g. the effect of grain size and initial defects, by considering the anisotropic behavior of crystalline materials at the level of the microstructure.     

An optimization decision support approach for risk analysis of carbon emission trading in electric power systems

Concerns over dramatic increasing electricity demand, exacerbating power shortage and changing climatic condition are emerging associated with municipal electric power systems (EPS). In this study, a risk-explicit mixed-integer full-infinite programming (RMFP) approach is developed for planning carbon emission trading (CET) in EPS. RMFP-CET has advantages in risk reflection and policy analysis, particularly when the input parameters are provided as crisp and functional intervals as well as probabilistic distributions. The developed method is applied to a real case study of CET planning of EPS in Beijing. Various electricity policies are incorporated within the modeling formulation for enhancing the RMFP-CET's capability. The results indicate that reasonable solutions have been generated, which are useful for making decisions of electricity production and supply as well as gaining insight into the tradeoffs among electricity supply risk, system cost, and CO₂ mitigation strategy.     

An inventory model with truncated exponential replenishment intervals and special sale offer

In this study, we develop an inventory model with stochastic replenishment intervals and special sale offer from a supplier. The replenishment interval is assumed to obey a truncated exponential distribution and shortage is partially backordered. Our goal in this research is to maximize the total profit of cost savings due to special sale offer from supplier. A closed-form solution of the model and its convexity condition is developed. A numerical example with real world data is provided to illustrate the theory.     

A novel Temperature–Humidity–Time defrosting control method based on a frosting map for air-source heat pumps

To improve the defrosting accuracy and the energy efficiency of the air-source heat pump (ASHP) under frosting and defrosting conditions, a novel Temperature–Humidity–Time (T–H–T) defrosting control method, based on a frosting map for the ASHP unit, is proposed in this paper. A field test was conducted for two heating seasons, to verify the feasibility and applicability of the T–H–T method. The advantages of the T–H–T method, compared to the conventional Temperature–Time (T–T) defrosting control method, are presented. In total, eight cases are shown in this paper. Cases 1 to 4 were chosen to reveal the T–H–T performance under different frosting conditions. It was found that no matter what kind of frosting conditions, defrosting was always initiated in a similar situation: ∼90% of the outdoor coil surface was covered by frost; the temperature difference between the compressor suction and discharge increased by ∼20%; and the heating capacity decreased by ∼30%. These results indicate that the T–H–T method can make an accurate decision under different frosting conditions. Cases 5a, 5b and Cases 6a, 6b were two groups of cases to compare the advantages of the T–H–T method against the conventional T–T method. Cases 5a and 5b were chosen for the non-frosting condition. It was found that the T–T method initiated the defrosting operation 31 times within 24 h. However, none of the defrosting operations was conducted for the T–H–T method. Cases 6a and 6b were chosen to compare these two methods under consecutive and variable frosting conditions. For the T–T method, 63% of the defrosting processes were found to be executed under conditions where defrosting was not necessary. However, for the T–H–T method, all the defrosting controls were found to be accurate and reasonable. These results indicated that the novel T–H–T method is suitable for the defrosting control of the ASHP, and has a more competitive performance than the conventional T–T method.     

One-way ANOVA based on interval information

This paper deals with extending the one-way analysis of variance (ANOVA) to the case where the observed data are represented by closed intervals rather than real numbers. In this approach, first a notion of interval random variable is introduced. Especially, a normal distribution with interval parameters is introduced to investigate hypotheses about the equality of interval means or test the homogeneity of interval variances assumption. Moreover, the least significant difference (LSD method) for investigating multiple comparison of interval means is developed when the null hypothesis about the equality of means is rejected. Then, at a given interval significance level, an index is applied to compare the interval test statistic and the related interval critical value as a criterion to accept or reject the null interval hypothesis of interest. Finally, the method of decision-making leads to some degrees to accept or reject the interval hypotheses. An applied example will be used to show the performance of this method.     

Methods for uncertainty propagation in life cycle assessment

Life cycle assessment (LCA) calculates the environmental impact of a product over its entire life cycle. Uncertainty analysis is an important aspect in LCA, and is usually performed using Monte Carlo sampling. In this study, Monte Carlo sampling, Latin hypercube sampling, quasi Monte Carlo sampling, analytical uncertainty propagation and fuzzy interval arithmetic were compared based on e.g. convergence rate and output statistics. Each method was tested on three LCA case studies, which differed in size and behaviour. Uncertainty propagation in LCA using a sampling method leads to more (directly) usable information compared to fuzzy interval arithmetic or analytical uncertainty propagation. Latin hypercube and quasi Monte Carlo sampling provide more accuracy in determining the sample mean than Monte Carlo sampling and can even converge faster than Monte Carlo sampling for some of the case studies discussed in this paper.     

Optimal water resource planning under fixed budget by interval-parameter credibility constrained programming

In this study, an interval credibility constrained programming (ICCP) was developed through introducing the concept of intervals into credibility constrained programming framework. Interval credibility levels can help decision makers to reflect uncertainties of preferences. By ICCP, a water resource planning model with fixed fuzzy budget was developed for supporting the planning of agriculture development and environmental protection. Surface and ground water were planned for regional irrigation in wet and normal seasons. For the interval credibility preference, best and worst cases were analysed. The tradeoff between the budget and the benefit were studied by sensitive analysis. The results showed that the current water resource budget is reasonable.