Pancreatic function,quality of life and costs at long-term follow-up after acute pancreatitis

AIM:To evaluate long-term endocrine and exocrine pancreatic function,quality of life and health care costs after mild acute pancreatitis and severe acute pancreatitis(SAP).METHODS:Patients prospectively included in 2001-2005 were followed-up after 42(36-53)mo.Pancreatic function was evaluated with laboratory tests,the oral glucose tolerance test(OGTT),fecal elastase-1 and a questionnaire.Short Form(SF)-36,was completed.RESULTS:Fourteen patients with a history of SAP and 26 with mild acute pancreatitis were included.Plasma glucose after OGTT was higher after SAP(9.2 mmol/L vs 7.0 mmol/L,P=0.044).Diabetes mellitus or impaired glucose tolerance in fasting plasma glucose and/or 120 min plasma glucose were more common in SAP patients(11/14 vs 11/25,P=0.037).Sick leave,time until the patients could take up recreational activities and time until they had recovered were all longer after SAP(P <0.001).No significant differences in SF-36 were seen between the groups,or when comparing with age and gender matched reference groups.Total hospital costs,including primary care,follow-up and treatment of complications,were higher after SAP(median€16572 vs €5000,P<0.001).CONCLUSION:Endocrine pancreatic function was affected,especially after severe disease.SAP requires greater resource use with long recovery,but most patients regained a good quality of life.

Multi-objective optimization of rolling schedule based on cost function for tandem cold mill

In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.

Analysis of Cost Functions for Retrieving Sea Surface Salinity

Two kinds of Bayesian-based cost functions (i.e., the unconstrained cost function and parameter-constrained cost function) are investigated for retrieving the sea surface salinity (SSS). In low SSS regions, we have analyzed the sensitivity of the two cost functions to geophysical parameters. The results show that the unconstrained cost function is valid for retrieving several parameters (including SSS, wind speed and significant wave height), and the constrained cost function, which largely depends on the accuracy of reference values, may lead to large retrieval biases. Furthermore, as a retrieval parameter, the sea surface temperature (SST) can re-sult in the divergence of other geophysical parameters in an unconstrained cost function due to the strong sensitivity of brightness temperature to SST. By using the unconstrained cost function and the simulated brightness temperature TB with white noises, the retrieval biases of SSS are discussed with the following two procedures. Procedure a): the simulated TB values are first averaged, and then SSS is retrieved. Procedure b): the SSS is directly retrieved from the simulated TB , and then the retrieved SSS values are aver-aged. The results indicate that, for low SSS and SST distributions, the SSS retrieval by procedure a) has less biases compared with that by procedure b), while the two procedures give almost the same retrieval results for high SSS and SST sea regions.

Competitive analysis of price online inventory problem with cost function

In this paper,a new price is given to the online decision maker at the beginning of each day.The trader must decide how many items to purchase according to the current price.We present three variants and an online algorithm based on cost function.The competitive ratio of the online algorithm is given for each variant,which is a performance measure of an online algorithm.More importantly,we show that the online algorithm is optimal.

Optimal investment with transaction costs based on exponential utility function:a parabolic double obstacle problem

This paper concerns optimal investment problem with proportional transaction costs and finite time horizon based on exponential utility function. Using a partial differential equation approach, we reveal that the problem is equivalent to a parabolic double obstacle problem involving two free boundaries that correspond to the optimal buying and selling policies. Numerical examples are obtained by the binomial method.

Resource Allocation Using SPA Based on Different Cost Functions in Elastic Optical Networks

Routing, modulation and spectrum allocation in elastic optical networks is a problem aiming at increasing the capacity of the network. Many algorithms such as shortest path algorithm can be used as the routing section of this problem. The efficiency of these algorithms is partly based on how the cost of each link is defined. In this study, we considered several basic metrics in cost of network links and compared their effects on the network capacity. In particular, the static costs and the dynamic costs were evaluated and compared. For dynamic scenarios, compared to static scenarios, at least one additional factor, the usage of the links, was added. We further considered a new factor that is based on probability of accommodating the signal at a given time in any given link. The results show that, among them, the shortest path algorithm provides the least blocking probability when the cost is a combination of link length and the abovementioned possibility/usage of the link.

Cost Effective Operating Strategy for Unit Commitment and Economic Dispatch of Thermal Power Plants with Cubic Cost Functions Using TLBO Algorithm

This paper deals with a Unit Commitment (UC) problem of a power plant aimed to find the optimal scheduling of the generating units involving cubic cost functions. The problem has non convex generator characteristics, which makes it very hard to handle the corresponding mathematical models. However, Teaching Learning Based Optimization (TLBO) has reached a high efficiency, in terms of solution accuracy and computing time for such non convex problems. Hence, TLBO is applied for scheduling of generators with higher order cost characteristics, and turns out to be computationally solvable. In particular, we represent a model that takes into account the accurate higher order generator cost functions along with ramp limits, and turns to be more general and efficient than those available in the literature. The behavior of the model is analyzed through proposed technique on modified IEEE-24 bus system.

Handover improvement based on cost function and user fairness for cellular relay enhanced LTE networks

In order to optimize handover target selection and achieve better handover performance in cellular relay networks under the long term evolution （LTE） system, a novel handover measurement and decision scheme based on cost function is proposed in the paper. The relay-enhanced network provides user equipment （UE） multiple handover choices from neighbor base stations or relays. This may result in different overhead, resource utility and traffic load which attaches importance to proper handover schemes. Compared with traditional handover measurement and decision schemes, the proposed scheme adopts reference signal receiving quality （RSRQ） in the measurement stage and uses a modified signal cost function considering signal overhead in different handover types and expected long-term throughput of UE. Besides, UE fairness and sector resource utilization are taken into account as well. Theory analysis and simulation results prove that the proposed scheme can enhance cell throughput, decrease handover delay and signal overhead, and improve UE fairness.

Natural Monopoly and Mixed Ownership Reform--Based on Natural Experiment and Cost Function Analysis Method

Despite a multitude of theoretical discussions on China's mixed ownership reform, very few studies have addressed realistic questions concerning the implementation of the reform. The Resolutions of the Third Plenum of the 18 th CPC Central Committee and other reform strategies have outlined the reform of sectors with natural monopoly, including urban public utility sectors. The question is how mixed ownership reform should be carried out in sectors of natural monopoly, or which public utilities sectors should enjoy priority of mixed ownership reform. To answer this question, this paper employs data of large public utility enterprises in China from 1998 to 2008, and estimates the natural monopoly attribute at the industry level and corporate total factor productivity(TFP) using cost function analysis method excluding the impact of product price factor. Based on the difference-indifferences-in-differences(DDD) method of natural experiment, an empirical test is carried out for the relationship among natural monopoly, mixed ownership reform and corporate productivity. Our results suggest that:(1) Statistically, mixed ownership reform cannot significantly increase corporate TFP in sectors with natural monopoly;(2) mixed ownership reform should not be carried out indiscriminately on a nationwide basis and for all public utilities sectors. Such an attempt of reform without distinguishing natural monopoly and the level of competitiveness is fraught with policy uncertainties;(3) relative to sectors with natural monopoly, corporate productivity in competitive sectors after mixed ownership reform will improve more significantly and enjoy greater "policy dividends" of institutional reform. Therefore, mixed ownership reform should be carried out first in competitive sectors.

Composite Cost Function Based Solution to the Unit Commitment Problem

This paper presents a new approach via composite cost function to solve the unit commitment problem. The unit com-mitment problem involves determining the start-up and shut-down schedules for generating units to meet the fore-casted demand at the minimum cost. The commitment schedule must satisfy the other constraints such as the generating limits, spinning reserve, minimum up and down time, ramp level and individual units. The proposed algorithm gives the committed units and economic load dispatch for each specific hour of operation. Numerical simulations were carried out using three cases: four-generator, seven-generator, and ten-generator thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as Dynamic programming, Branch and bound, Ant colony system, and traditional Tabu search. The result demonstrated the accuracy of the proposed method.

Is a Single Product Cost Function Appropriate for Institutions of Higher Education？ Empirical Evidence From China＇s Research Universities＊

Many studies exist in the literature of scale and scope economies in institutions of higher education employing multi-product cost functions of quadratic, constant elasticity substitution （CES）, or hybrid translog form. A single product cost function is normally considered inadequate and yield distorted results. Both quadratic and single product cost functions have been applied to university data from China＇s Ministry of Education （MOE）. This study compares those two methods and their statistical results and finds that ray economies of scale from these two cost functions are quite similar though the single product cost function which can not be used to calculate product-specific economies of scale or economies of scope.

A Reliable and Secure Smart Grid Communication Network Using a Comprehensive Cost Function

SG （smart grids） is an intelligent power grid in which the diverse nodes should communicate different types of information which have different communication requirements with CS （control stations）. There exist several RATs （radio access technologies）, with diversification in quality of service character which respect to the SG nodes communication requirements. On the other side, spectrum is becoming a rare source and its demands request is increasing exponentially. Therefore, resource allocation to support different types of SG nodes should be elaborated so that the resource efficiency is maximized while the SG communication requirements are respected. Using a CF （cost function） based on the SG node requirements and RATs characteristics to find the desirability value of every RATs for a certain node type accomplish this goal in combination with prioritizing the different SG nodes types based on SG goals by creating a priority table for RATs and different SG node types. The main node communication requirements are formulized to be used in the CF in this paper. The numerical results show that the proposed method defines the desirability value of each RAT for a certain SG node type that helps to make a priority table by using the SG node prioritization table.

Functional Sustainability of a Flight Dynamics Control System for Stable Hovering Flight of an Unmanned Aerial Vehicle(UAV),such as in Agricultural Applications:Mathematical Modeling and Simulation

The simulation of a control system for the longitudinal axis of the rotary or fixed-wing unmanned aerial vehicles(UAVs)is demonstrated in this study.The control unit includes design considerations of two controllers to provide robust stability,tracking of the proposed linear dynamics,an adequate set of proportional-integral-derivative(PID)controller gains,and a minimal cost function.The PID control and linear quadratic regulator(LQR)with or without full-state-observer were evaluated.An optimal control system is assumed to provide fast rise and settling time,minimize overshoot,and eliminate the steady-state error.The effectiveness of this approach was verified by a linear model of the UAV aircraft in the semi-dynamic simulation platform of Matlab/Simulink,in which the open-loop system was assessed in terms of flight robustness and reference tracking.The experimental results show that the proposed controllers effectively improve the configuration of the control system of the plant,maintain the sustainability of the dynamic flight model stability,and diminish the flight controller errors.The LQR provides robust stability,but it is not optimal in the transient phase of particular plant output.The PID control system can adjust the controller’s gains for optimal hovering(or stable slow flight)and is especially useful for the tracking system.Finally,comparing aircraft stability using PID and LQR controllers shows that the latter has less overshoot and a shorter settling time;in addition,all proposed controllers can be practically deployed as one UAV’s system,which can be handled as an exemplary model of the UAV flight management system.

智能制造的生产成本属性异变及边际成本递减律

智能科技革命驱动的智能制造,是新时期推进制造强国建设的不二选项。智能制造以工业智能体取代人力作业,采用“车间智能体+镜像网络”的单要素虚实融合生产模式,这将带来迥异于传统制造业的生产特征和成本属性,进而改变成本函数形态。比较研究发现,智能制造具有“高固定成本、弱可变成本”属性,并据此推导出随产量弱增长的弱成本函数,以及相应产生的边际成本递减规律。智能制造边际成本递减律,主要源于智能制造的单要素虚实融合生产模式对可变成本的冲淡与弱化效应。从政策层面,建议有序开展智能制造系统的众筹建造模式,积极推行智能制造系统的产能共享模式,尽早谋划智能时代产业工人的全新就业模式,大力引导消费者不断介入生产活动,实现消费者向“消产者”的身份转变。

基于资源感知的多域服务功能链编排成本优化

网络功能虚拟化技术的兴起使得实例化为服务功能链(SFC)的网络服务能够共享基底网络,缓解了传统网络体系结构僵化的问题.然而,网络中大量服务请求给多域SFC编排带来了新的挑战.首先由于域内网络资源信息及内部策略的保密性,使得多域SFC的编排更为复杂.其次多域SFC编排要确定最佳候选编排域集,先前的研究较少考虑域间负载的均衡性,对服务接受率造成了消极影响.此外跨网络域编排服务请求对服务的成本和响应时间提出了更严格的要求.为解决上述挑战,在本文中,我们首先针对多域网络隐私性需求,提出了域级图的构造方法;然后基于域间负载均衡提出了域权重的计算方法进行SFC编排域的选择;最后,针对多域网络成本和响应时间需求,提出编排算法.实验结果表明,提出的算法有效地权衡了平均服务成本和接受率,并且在服务平均响应时间方面也得到了优化.

DNA测序首段信号数据特别处理方法研究

针对荧光标记毛细管电泳DNA测序开始一段序列的信号杂乱特性以及不同碱基通道信号间的相对偏移问题,提出了一种用于首段信号特别处理的电泳迁移率自适应校正方法。分析设计基于四通道首段信号间峰重叠程度估计的运筹决策目标函数,通过目标函数动态寻优计算确定不同碱基通道信号的相对偏移系数,从而实现DNA测序首段信号的相对偏移校正,为提高首段信号碱基的合理判读及后续DNA精准排序提供了可靠的过程数据。

基于TOPSIS优化永磁同步电机预测控制成本函数

针对多目标约束条件下,为永磁同步电机预测控制算法成本函数选择适当的权重因子,提出了一种逼近理想解排序法(TOPSIS)优化成本函数的优选顺序方法改进权重因子的选择。首先,采用TOPSIS选择一个最接近理想控制动作的正解和最远离理想控制动作的负解,对成本函数中的控制变量进行优先级排序,以确保在每个采样持续时间内选择最佳控制措施。其次,根据上一时刻的最优控制状态,将预测的下一个切换时刻状态用于成本函数优化,从而减少了预测控制算法的计算持续时间。仿真和实验结果表明:与传统预测控制方法相比,基于TOPSIS的预测控制在具有较小开关频率的稳定操作下降低了电磁转矩和磁链的纹波,并且能够有效抑制电流脉动,降低算法的复杂度和计算量,提高了永磁同步电机控制系统在实际中的运行性能。

基于组合代价函数的智能汽车轨迹规划

针对智能汽车在多车道公路场景行驶中的安全性、舒适性问题,提出一种基于组合代价函数的轨迹规划方法。利用Frenet坐标系分别求解车辆的横向和纵向运动轨迹,通过五次多项式拟合生成候选轨迹集;以危险程度和轨迹偏离程度为基准,以车辆在多车道公路行驶中的安全性、舒适性为目标,设计一种新的代价函数组合,通过求解代价函数从而选择最优轨迹。仿真结果表明:该方法能够使车辆在三车道动态公路场景中实现跟车与变道。

基于改进哈里斯鹰算法的无人飞行器路径规划

针对无人飞行器三维路径规划问题,提出一种基于哈里斯鹰优化(Harris hawks optimization,HHO)算法的无人飞行器三维路径规划算法。首先根据路径规划代价指标和无人飞行器自身性能,建立路径规划模型确立代价函数和约束条件。接着针对传统HHO算法的不足,引入非线性能量因子来平衡全局搜索和局部搜索的关系,使算法避免陷入局部最小值;引入混沌映射对HHO算法进行初始化种群并对其进行局部混沌搜索,增强算法种群多样性和搜索能力。最后通过仿真实验证明,改进的哈里斯鹰优化(improvement Harris hawks optimization,IHHO)算法可以有效规划出安全的无人飞行器航线,并且能够跳出局部最小值和具备较优的收敛速度。

基于GPSSA算法的无人机中继通信航迹规划方法研究

目前针对无人机中继通信航迹的规划方法未考虑航迹规划中存在的约束条件及代价函数,导致得到的规划航迹中断概率、通信误码率偏高.针对上述问题,提出一种基于改进麻雀算法的无人机中继航迹规划方法.根据无人机任务区信息和通信环境,建立通信障碍代价模型,通过真实约束,建立约束函数和代价函数,将其应用到麻雀搜索算法中,设计总体的航迹寻优规划流程,并应用仿真实验验证所提出的改进麻雀优化方法的有效性,实验结果表明,在不同的转角约束条件下,设计方法得到的航迹中断概率、通信误码率均有一定降低.