Solving quadratic convex bilevel programming problems using a smoothing method

In this paper, we present a smoothing sequential quadratic programming to compute a solution of a quadratic convex bilevel programming problem. We use the Karush-Kuhn-Tucker optimality conditions of the lower level problem to obtain a nonsmooth optimization problem known to be a mathematical program with equilibrium constraints; the complementary conditions of the lower level problem are then appended to the upper level objective function with a classical penalty. These complementarity conditions are not relaxed from the constraints and they are reformulated as a system of smooth equations by mean of semismooth equations using Fisher-Burmeister functional. Then, using a quadratic sequential programming method, we solve a series of smooth, regular problems that progressively approximate the nonsmooth problem. Some preliminary computational results are reported, showing that our approach is efficient.     

Bayesian Variable Selection via Particle Stochastic Search

We focus on Bayesian variable selection in regression models. One challenge is to search the huge model space adequately, while identifying high posterior probability regions. In the past decades, the main focus has been on the use of Markov chain Monte Carlo (MCMC) algorithms for these purposes. In this article, we propose a new computational approach based on sequential Monte Carlo (SMC), which we refer to as particle stochastic search (PSS). We illustrate PSS through applications to linear regression and probit models.     

Efficient space-filling and non-collapsing sequential design strategies for simulation-based modeling

Simulated computer experiments have become a viable cost-effective alternative for controlled real-life experiments. However, the simulation of complex systems with multiple input and output parameters can be a very time-consuming process. Many of these high-fidelity simulators need minutes, hours or even days to perform one simulation. The goal of global surrogate modeling is to create an approximation model that mimics the original simulator, based on a limited number of expensive simulations, but can be evaluated much faster. The set of simulations performed to create this model is called the experimental design. Traditionally, one-shot designs such as the Latin hypercube and factorial design are used, and all simulations are performed before the first model is built. In order to reduce the number of simulations needed to achieve the desired accuracy, sequential design methods can be employed. These methods generate the samples for the experimental design one by one, without knowing the total number of samples in advance. In this paper, the authors perform an extensive study of new and state-of-the-art space-filling sequential design methods. It is shown that the new sequential methods proposed in this paper produce results comparable to the best one-shot experimental designs available right now.     

A sequential perspective on searching for static targets

We present a sequential approach to detect static targets with imperfect sensors, which range from tower-mounted cameras to satellites. The scenario is operationally relevant to many military, homeland security, search and rescue, environmental engineering, counter-narcotics, and law enforcement applications. The idea is to stop the search as soon as there is enough probabilistic evidence about the targets’ locations, given an operator-prescribed error tolerance, knowledge of the sensors’ parameters, and a sequence of detection signals from the sensors. By stopping the search as soon as possible, we promote efficiency by freeing up sensors and operators to perform other tasks. The model we develop has the added benefits of decreasing operator workload and providing negative information as a search progresses.     

Simultaneous Determination of 1,4‐Benzodiazepines and Tricyclic Antidepressants in Saliva after Sequential SPE Elution by the Same HPLC Conditions

A new method has been described to determine both benzodiazepines (six) and tricyclic antidepressants (four) simultaneously in saliva by HPLC with a UV detector set at 240 nm using cholchicine as the internal standard. A careful specific sequential solid‐phase elution was optimized and performed to elute benzodiazepines using a mixture of methanol‐acetonitrile (1:1 v/v) followed by the elution of tricyclic antidepressants with methanol. Separation of the compounds was performed on a Kromasil column (250 × 4 mm, 5 μm) by a gradient eluents consisting of 0.05 M CH₃COONH₄‐acetonitrile‐methanol (55:15:30 v/v/v). The results were linear for both benzodiazepines and tricyclic antidepressants up to 20 ng μL^‐1 with the correlation coefficients greater than 0.998. The sensitivity limits, LOD and LOQ were 0.08‐0.34 ng μL^‐1 and 0.28‐1.13 ng μL^‐1, respectively. The method is simple, fast and reliable with good specificity and sensitivity, will be suitable for use in a clinical setting, where there is a concomitant use of 1,4‐benzodiazepines and tricyclic antidepressants.     

微量原位水质总碱度在线检测新方法研究

为实现原位水质总碱度快速准确检测的需求,融合顺序注射分析（sequential injection analysis, SIA）与连续光谱检测法,设计了一种小型微量原位水质总碱度在线快速检测仪,系统主要通过设计滴定池将SIA和连续光谱检测法应用于总碱度自动化滴定检测流程,并对连续光谱检测法判断滴定临界值的新方法进行实验研究。基于国标总碱度检测中工业循环冷却水及地表水总碱度的测定标准,设计了原位水质总碱度检测流程,并以顺序注射技术为控制滴定流程基础,在连续光谱扫描测量溶液检测过程的条件下,使用酚酞和甲基橙作为指示剂,对水质总碱度进行滴定分析。通过连续光谱扫描对酚酞碱度及甲基橙碱度滴定过程进行监测,以吸光度曲线552 nm处峰值归零作为酚酞碱度滴定临界值判断条件;以吸光度曲线峰值由465 nm偏移至504 nm处作为甲基橙碱度滴定临界值判断条件;分析通过滴加不同剂量酚酞和甲基橙指示剂所得溶液吸光度曲线得出最佳指示剂用量分别为0.01和0.04 mL。该系统利用最小二乘拟合算法建立总碱度测定的回归模型,并对检测系统及检测流程进行优化,实验结果表明,水质总碱度在0.20~25.00 mmol·L-1范围内与盐酸消耗量线性相关,工作曲线拟合系数≥0.994 2;测定总碱度重复性相对标准偏差（RSD）为0.207%~1.151%;废液量≤16 mL;最低检出限为0.03 mmol·L-1;样品加标回收率在97.2%~102.3%之间;与国标法对比实验结果无明显差别。利用连续光谱检测法判断滴定临界值的新方法对于提升水质总碱度检测仪的技术性能具有重要意义,可适用于系统网格化监控地表水、循环冷却水、养殖循环水等多种监测应用平台。     

指数分布族中矩估计序贯置信区间

在矩估计的基础上,对于给定精度(2d)及置信系数(α),建立了对参数函数g(θ) 的一个序贯置信区间估计的程序．并讨论了在一定条件下,当d→0,它的渐近相合性、渐近有效性及有界的最优费用差(EN(d)-n(d))等渐近性质．     

A sequential technique for the control of traffic intensity in Markovian queues

A sequential parameter control technique previously introduced by the author is modified in this paper so as to make it simple in practice. The detailed procedure involving two phases, a warning phase with control limits and a testing phase using an appropriate test is illustrated for a queueing system with an embedded Markov chain. Operating characteristics of the procedure are also examined.     

Enzymatic Determination of Glucose by Optical-Fiber Sensor Sequential Injection Renewable Surface Spectrophotometry

Introduction Determinationofglucoseisrequiredinmedicine industry,foodindustry,clinicaldiagnosisaswellas variousresearchfields.Therefore,intensiveefforts havebeendirectedtothedevelopmentofanalytical methodsfordeterminationofglucose,suchasthose basedonbiose…