Analysis of oceanaut operating performance using an integrated Bayesian network aided by the fuzzy logic theory

Because the oceanaut plays a significant role in safety and capability during manned deep-diving scientific tasks, preventing oceanaut performance decline is of paramount importance. However, the factors responsible for oceanaut performance are almost entirely unexplored. To address the preceding issues, a quantitative method of fuzzy integrated Bayesian network (FIBN) was modeled within the limits of oceanaut operating procedures. To quantify the probabilities of the influencing factors, the probability of each node in the FIBN was calculated using integrated expert judgement, fuzzy logic theory, and Bayesian network. By considering a total of 28 factors related to oceanaut performance in the “Jiaolong” manned submersible, this study found that difficult sampling, long sampling times, cabin equipment failure, oceanaut physical decline, and declining decision-making ability are important factors that affect oceanaut performance. The FIBN proposed in our study fused the qualitative and quantitative methods and can be developed into a versatile tool for analysis of comprehensive systems that contain both static and dynamic factors.Relevance to industryThe results provide a powerful basis for the design of manned submersible and assignment of tasks to oceanauts, while the fuzzy integrated Bayesian network (FIBN) method proposed can be effectively applied to various quantitative assessment fields which direct researchers to deal with analysis problems of complex systems.     

A fuzzy hierarchical reinforcement learning based scheduling method for semiconductor wafer manufacturing systems

Scheduling semiconductor wafer manufacturing systems has been viewed as one of the most challenging optimization problems owing to the complicated constraints, and dynamic system environment. This paper proposes a fuzzy hierarchical reinforcement learning (FHRL) approach to schedule a SWFS, which controls the cycle time (CT) of each wafer lot to improve on-time delivery by adjusting the priority of each wafer lot. To cope with the layer correlation and wafer correlation of CT due to the re-entrant process constraint, a hierarchical model is presented with a recurrent reinforcement learning (RL) unit in each layer to control the corresponding sub-CT of each integrated circuit layer. In each RL unit, a fuzzy reward calculator is designed to reduce the impact of uncertainty of expected finishing time caused by the rematching of a lot to a delivery batch. The results demonstrate that the mean deviation (MD) between the actual and expected completion time of wafer lots under the scheduling of the FHRL approach is only about 30 % of the compared methods in the whole SWFS.     

Water table fluctuation with a random initial condition

The nonlinear Boussinesq equation is used to understand water table fluctuations in various ditch drainage problems. An approximate solution of this equation with a random initial condition and deterministic boundary conditions, recharge rate and aquifer parameters has been developed to predict a transient water table in a ditch-drainage system. The effects of uncertainty in the initial condition on the water table are illustrated with the help of a synthetic example. These results would find applications in ditch-drainage design.Notation A / tanh t - a lower value of the random variable representing the initial water table height at the mid point - a+b Upper value of the random variable representing the initial water table height at the midpoint - B tanh t - C 4/ - h variable water table height - h mean of the variable water table height - h _m variable water table height at the mid point - h _m mean of the variable water table height at the mid point - K hydraulic conductivity - L half spacing between the ditches - m ₀ initial water table height at the mid point - N Uniform rate of recharge - S specific yield - t time of observation - x distance measured from the ditch boundary - (4/SL)(NK)^1/2 - (L/4)(N/K)^1/2 - dummy integral variable     

REVERSED RESIDUALS IN AUTOREGRESSIVE TIME SERIES ANALYSIS

Abstract. Both linear and non-linear time series can have directional features which can be used to enhance the modelling and investigation of linear or non-linear autoregressive statistical models. For this purpose, reversed p th-order residuals are introduced. Cross-correlations of residuals and squared reversed residuals allow extensions of current model identification ideas. Quadratic types of partial autocorrelation functions are introduced to assess dependence associated with non-linear models which nevertheless have linear autoregressive correlation structures. The use of these residuals and their cross-correlation functions is exemplified empirically on some deseasonalized river flow data for which a first-order autoregressive model is a satisfactory second-order fit. Parallel theoretical computations are undertaken for the non-linear first-order random coefficient autoregressive model and comparisons are made. While the data are shown to be strongly non-linear, their correlational signatures are found to be convincingly different from those of a first-order autoregressive model with random coefficients.     

用模糊规划证明期望放出体的合理性

文章采用模糊规划的方法证明了期望放出体在放矿中的合理性,从而使放矿这个复杂的过程能方便地采用数学手段来处理。同时说明了如何在崩落法矿山利用期望体来解决实际生产中的放矿问题。     

An alignment-free fingerprint bio-cryptosystem based on modified Voronoi neighbor structures

Bio-cryptography is an emerging security technology which combines cryptography with biometrics. A good bio-cryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in bio-cryptosystem design. However, fingerprint uncertainty caused by distortion and rotation during the image capturing process makes it difficult to achieve a high recognition rate in most bio-cryptographic systems. Moreover, most existing bio-cryptosystems rely on the accurate detection of singular points for fingerprint image pre-alignment, which is very hard to achieve, and the image rotation transformation during the alignment process can cause significant singular point deviation and minutiae changes. In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignment-free bio-cryptosystem based on fixed-length bit-string representations extracted from modified VNSs, which are rotation- and translation-invariant and distortion robust. The proposed alignment-free bio-cryptosystem is able to provide strong security while achieving good recognition performance. Experimental results in comparison with most existing alignment-free bio-cryptosystems using the publicly-available databases show the validity of the proposed scheme.     

Prediction of liquid film mass transfer coefficients in packed columns using liquid holdup

A unique characteristic linear dimension (d), defined as the cube root of the specific liquid holdup (h_sp) in the packed column, was used to correlate successfully the liquid film mass transfer coefficient k_La for gas absorption-desorption for sparingly soluble gases in liquids below loading. To produce this simple, dimensionless correlation, k_La data reported in literature were used, covering a wide range of physical properties of liquids, packings and operating conditions. This new approach showed operating holdup as an important factor in gas liquid mass transfer.     

一种改进的VI CFAR检测器

为得到不同杂波背景下的良好检测性能,给出了一种改进的VI CFAR检测器.该检测器主要利用均值类可变性指示（MLVI）CFAR检测器和有序统计类可变性指示（OSVI）CFAR检测器的各自优点以及VI CFAR的以背景均匀程度自动选择不同检测器思想.理论分析和仿真结果表明：该检测器在均匀背景下性能基本与MLVI CFAR重合;多目标背景下具有较强的抗多目标能力;杂波边缘背景下有较好的虚警概率控制能力且运算量小,是一种稳健的检测器.     

储罐地震易损性数值仿真分析

为了研究储罐的抗震性能,忽略储罐罐壁的质量,将储罐中的液体质量简化为三质点体系模型,地基土由两个弹簧和两个阻尼器模拟.考虑罐体的平动和转动,建立了在水平地震激励下储罐的动力方程;给出了随机变量的概率模型和基于易损性理论的失效概率计算方法.通过对大庆某油库2×104 m3和5×104m3两种大型储罐进行数值仿真方法的地震易损性分析.结果表明:随着地震烈度的增大,储罐的易损性逐渐增大;5×104 m3储罐的抗震性能要好于2×104 m3储罐;2×104 m3和5×104 m3储罐的主要失效模式分别是抗失稳和抗提离.由此可见从多个失效模式对储罐进行地震易损性研究比从单一失效模式进行易损性研究更加科学.     

基于模糊层次分析法的应用性技术成果评价

针对现有应用性技术成果的评价指标体系,建立了相应的模糊层次分析法数学模型,此模型可克服传统层次分析法判断矩阵构造主观性强和一致性不易检验等缺点,为应用性技术成果的等级评价提供了一种简便合理的科学评价方法.