Input variable scaling for statistical modeling

Input variable scaling is one of the most important steps in statistical modeling. However, it has not been actively investigated, and autoscaling is mostly used. This paper proposes two input variable scaling methods for improving the accuracy of soft sensors. One method statistically derives the input variable scaling factors; the other one uses spectroscopic data of a material whose content is estimated by the soft sensor. The proposed methods can determine the scales of the input variables based on their importance in output estimation. Thus, it can reduce the negative effects of input variables which are not related to an output variable. The effectiveness of the proposed methods was confirmed through a numerical example and industrial applications to a pharmaceutical and a distillation processes. In the industrial applications, the proposed methods improved the estimation accuracy by up to 63% compared to conventional methods such as autoscaling with input variable selection.     

An efficient approach for the S‐shaped penalty function

Interval goal programming (IGP) with a marginal penalty function (PF) was first proposed by Charnes and Collomb in 1972, and further improved by Kvanli and other researchers. Recently, Lu and Chen proposed an efficient logarithmic method to formulate IGP with an S‐shaped PF. However, their method requires adding many binary variables when the problem size becomes large, which increases the computational burden in the solution process. This study proposes an efficient approach for the S‐shaped PF. The arbitrary PF frequently appears in the fields of business and industry. However, none of the previous approaches have addressed arbitrary PFs without adding binary variables. The proposed approach can be easily extended to formulate an arbitrary PF in which binary variables are no longer required, regardless of the number of break points. The proposed method can improve the efficiency of IGP for solving large size management and decision problems in considering PFs. In order to demonstrate the correctness, usefulness of the proposed model, illustrative examples are provided.     

变邻域量子烟花算法求解CVRP

针对带容量约束的车辆路径问题，提出一种融合量子进化算法和变邻域优化策略的变邻域量子烟花算法。该算法采用等分随机键与最大位置法结合的实数编码方式，通过量子旋转门和非门变异提高算法全局搜索能力，同时运用结合2-Opt的变邻域优化策略加强局部搜索能力。选取17个基准算例进行参数实验和对比实验，实验结果表明，相对于对比算法，所提出的算法具有较好的寻优能力和收敛速度。     

步长自适应的测量矩阵迭代优化方法

在压缩感知中，降低传感矩阵的列相干性可以提高重构精度。因为稀疏字典一般是固定的，所以目前主要通过优化测量矩阵来间接降低传感矩阵列相干性。提出一种改进的测量矩阵优化算法，使用梯度下降法更新测量矩阵并结合Barzilai-Borwen方法以及Armijo准则，使步长能够在迭代中自适应调整并保证算法收敛性。仿真实验表明，所提出的方法具有更快的收敛速度并且能够得到更优的测量矩阵。     

An efficient numerical scheme for solving fractional infinite-horizon optimal control problems

This paper presents an efficient numerical method to solve fractional infinite-horizon optimal control problems, where the dynamic control system depends on Caputo fractional derivatives. First, by a suitable change of variable, we transform the fractional infinite-horizon optimal control problem to a finite-horizon one. Then, with the help of an approximation, we replace the Caputo derivative to integer order derivative. According to the Pontryagin minimum principle (PMP) for optimal control problems and by constructing an error function, we define an unconstrained minimization problem. In the optimization problem, we use trial solutions for state, costate and control functions where these trial solutions are constructed by using two-layered perceptron neural network. Some numerical results are introduced to explain our main results.     

温拌LDPE改性沥青混合料性能研究

选择Sasobit和Evotherm 3G两种温拌剂对温拌LDPE沥青混合料制备工艺和性能进行研究。首先,比较变温等体积法和等黏温度法两种方法,并确定两种温拌混合料的拌和及击实温度。在此基础上,分别采用车辙试验、低温弯曲试验、中点加载弯曲试验以及冻融劈裂试验评价70#、LDPE、Sasobit-LDPE以及3G-LDPE四种沥青混合料的高温性能、低温性能、疲劳性能和水稳定性。结果表明,两种温拌技术均是可行的,Sasobit和3G温拌技术可使施工温度降低20℃和15℃。与热拌LDPE沥青混合料相比,Sasobit温拌沥青混合料具有更好的高温性能和水稳定性,在高应力比条件下抗疲劳性能更好,低温性能虽变差,但是优于70#沥青混合料;3G温拌沥青混合料的高温性能,低温性能以及水稳定性则与热拌LDPE沥青混合料各项性能较为接近,抗疲劳性能变差,但是优于70#沥青混合料。     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

空气弹簧液压悬置动特性及隔振特性研究

研究了具有可变刚度阻尼的发动机空气弹簧液压悬置的动特性和隔振特性。针对影响发动机空气弹簧液压悬置动特性的关键参数上液室等效体积刚度,采用理论和试验方法研究了上液室等效体积刚度的等效值,基于该等效值建立了空气弹簧液压悬置的理论模型,对空气腔开闭两种工况进行了空气弹簧液压悬置动特性的仿真和试验研究。搭建了发动机空气弹簧液压悬置系统试验台架,研究了台架各种激励频率下的空气弹簧液压悬置的隔振特性。结果表明:本研究采用的上液室等效体积刚度进行空气弹簧进行建模是正确、可行的,提高了空气弹簧建模效率和准确性;空气弹簧液压悬置在空气腔开启和关闭两种状态下,峰值动刚度增大幅值达78.5%,峰值阻尼角增大幅值达250%。台架试验表明:当台架激励频率小于25Hz时,悬置采用大刚度大阻尼;当台架激励频率大于等于25 Hz时,悬置采用小刚度小阻尼;悬置隔振率提升明显,不同频率下提升幅值达10%～67%。     

Simultaneous synthesis of a heat exchanger network with multiple utilities using utility substages

Heat exchanger network synthesis (HENS) has progressed by using mathematical programming-based simultaneous methodology. Although various considerations such as non-isothermal mixing and bypass streams are applied to consider real world alternatives in modeling phase, many challenges are faced because of its properties within non-convex mixed-integer nonlinear programming (MINLP). We propose a modified superstructure, which contains a utility substage for use in considering multiple utilities in a simultaneous MINLP model. To improve model size and convergence, fixed utility locations according to temperature and series connections between utilities are suggested. The numbers of constraints, discrete, and continuous variables show that overall model size decreases compared with previous research. Thus, it is possible to expand the feasible search area for reaching the nearest global solution. The model's effectiveness and applications are exemplified by several literature problems, where it is used to deduce a network superior to that of any other reported methodology.     

Spray coating process variable and property analysis of UV-curable polyurethane acrylate coating on polycarbonate substrate

A series of spray coating experiments were conducted on an UV-curable, polyurethane-modified, acrylate-based coating formulation with the aim to control defects, coating thickness, and thickness variation. Statistical approaches including design of experiment, residual examination, analysis of variance, and t-test were used in designing the experiments and analyzing data. Viscosity of formulation, atomizing pressure, liquid feeding pressure, distance between nozzle and substrate, and travel speed of substrate were the process variables studied. The ranges of process variables that gave defect-free coating were identified and used in the subsequent experiments to determine process variables and interactions that had significant contribution to the changes in coating thickness and thickness variation. All process variables studied were found to have contribution to the change in coating thickness, but they showed no significant contribution to the variation of coating thickness. No interaction displayed significant contribution. Confirmation tests performed on extra samples prepared with varying coating thicknesses indicated a good agreement with the experimental results. Additional samples were tested for total transmittance, transmission haze, adhesion, surface roughness, hardness, scratch hardness, abrasion resistance, and durability to attack of car wash chemicals. Spray coated samples showed slight improvement in the total transmittance over the uncoated samples, while maintaining the transmission haze and exhibiting rougher surfaces. Only samples with thin coatings were found to possess sufficient adhesion to the substrate. These thin coatings gave improved hardness, scratch hardness, and durability to car wash attack to the level comparable to commercial coated polycarbonate headlamp lenses, whilst giving better abrasion resistance.