Unification of Filled Function and Tunnelling Function in Global Optimization

In this paper, two auxiliary functions for global optimization are proposed. These two auxiliary functions possess all characters of tunnelling functions and filled functions under certain general assumptions. Thus, they can be considered as the unification of filled function and tunnelling function. Moreover, the process of tunneling or filling for global optimization can be unified as the minimization of such auxiliary functions. Result of numerical experiments shows that such two auxiliary functions are effective.

Determination of phenolic whitening agents in cosmetics by micellar electrokinetic capillary chromatography with amperometric detection

A sensitive method for simultaneous determination of six phenolic whitening agents, including arbutin, phenol, resorcinol, hydroquinone, kojic acid, and salicylic acid in cosmetics has been developed using micellar electrokinetic capillary chromatography with amperometric detection （MECC-AD）. Effects of several factors, such as the pH value and concentration of running buffer, potential applied to the working electrode, separation voltage, and injection time were investigated to obtain optimum conditions for separation and detection. With a 75 cm long fused-silica capillary tube, well-defined separation of six phenolic compounds was achieved in 10 mmol/L SDS/40 mmol/L H3BO3-Na2B407 running buffer （pH 9.0）. Good linear relationship was obtained for each analyte over three orders of magnitude with correlation coefficients （r2） between 0.9985 and 0.9994, and the detection limit （S/N = 3） ranged from 0.04 p^g/mL to 0.45 p^g/mL. The proposed method has been successfully applied for the determination of phenolic whitening agents in real cosmetic samples with satisfactory results, providing an alternative monitoring method for cosmetics safety regulation.

高速气流作用下自燃箔片云团的辐射特性计算与实验研究（英文）

目的:当自燃箔片云团在空气中扩散时,自燃箔片云团之间存在大量的对辐射的遮挡、吸收和反射作用,并且箔片与空气之间也会发生相互作用,这使得辐射传输计算变得更加复杂。本文旨在计算自燃箔片云团的辐射特性并生成辐射图像。创新点:建立自燃箔片云团的辐射计算模型和燃烧模型,并得到辐射图像和光谱特性曲线。方法:1.针对辐射的传输特点,建立一种基于反向路径采样的辐射计算模型;该模型假设探测器按照辐射的反向均匀向外发射光线,采样统计各光线的路径后,正向计算探测器接收到的光线数量与强度。2.考虑箔片表面的多孔结构对活性金属燃烧反应速率的影响并建立箔片的自燃模型;将计算结果与实验数据进行对比,验证该模型的准确性。3.计算得到箔片云团的光谱分布并生成辐射图像。结论:1.箔片燃烧后温度迅速攀升,并在1.3 s左右达到最大值;随后,温度缓慢下降,并在6s左右下降到接近环境温度。2.箔条云扩散后呈椭圆形,扩散区随着时间的推移逐渐扩大,且亮度中心向后移动。3.箔条云的光谱辐射强度极大点位于波长1.4、1.9、3.1、4.3和8.0μm处,并且在3.1μm时达到最大值。

Optimization Methods for Mixed Integer Weakly Concave Programming Problems

In this paper,we consider a class of mixed integer weakly concave programming problems(MIWCPP)consisting of minimizing a difference of a quadratic function and a convex function.A new necessary global optimality conditions for MIWCPP is presented in this paper.A new local optimization method for MIWCPP is designed based on the necessary global optimality conditions,which is different from the traditional local optimization method.A global optimization method is proposed by combining some auxiliary functions and the new local optimization method.Furthermore,numerical examples are also presented to show that the proposed global optimization method for MIWCPP is efficient.

Discrete Global Optimization Problems with a Modified Discrete Filled Function

This paper considers discrete global optimization problems.The traditional definition of the discrete filled function is modified in this paper.Based on the modified definition,a new discrete filled function is presented and an algorithm for discrete global optimization is developed from the discrete filled function.Numerical experiments reported in this paper on several test problems with up to 200 variables have demonstrated the efficiency of the algorithm.

An Efficient Message Dissemination Scheme for Minimizing DeliveryDelay in Delay Tolerant Networks

Delay tolerant networks （DTNs） are a kind of sparse and highly mobile wireless networks, where no stableconnectivity guarantee can be assumed. Most DTN users have several points of interest （PoIs）, and they enjoy disseminatingmessages to the other users of the same PoI through WiFi. In DTNs, some time-sensitive messages （disaster warnings, searchnotices, etc.） need to be rapidly propagated among specific users or areas. Therefore, finding a path from the source tothe destination with the shortest delay is the key problem. Taking the dissemination cost into consideration, we proposean efficient message dissemination strategy for minimizing delivery delay （MDMD） in DTNs, which first defines the user＇sactiveness according to the transiting habit among different PoIs. Furthermore, depending on the activeness, an optimaluser in each PoI is selected to constitute the path with the shortest delay. Finally, the MDMD with inactive state （on theway between PoIs） is further proposed to enhance the applicability. Simulation results show that, compared with otherdissemination strategies, MDMD achieves the lowest average delay, and the comparable average hopcounts, on the premisethat the delivery ratio is guaranteed to be 100% by the sufficient simulation time.

A Buffer Scheduling Method Based on Message Priority in Delay Tolerant Networks

Routing protocols in delay tolerant networks usually utilize multiple message copies to guarantee the message delivery, in order to overcome unpredictable node mobility and easily-interrupted connections. A store-carry-and-forward paradigm was also proposed to further improve the message delivery. However, excessive message copies lead to the shortage of buffer and bandwidth. The spray and wait routing protocol has been proposed to reduce the network overload caused by the buffer and transmission of unrestricted message copies. However, when a node＇s buffer is quite constrained, there still exist congestion problems. In this paper, we propose a message scheduling and drop strategy on spray and wait routing protocol （SDSRP）. To improve the delivery ratio, first of all, SDSRP calculates the priority of each message by evaluating the impact of both replicating and dropping a message copy on delivery ratio. Subsequently, scheduling and drop decisions are made according to the priority. In order to further increase delivery ratio, we propose an improved message scheduling and drop strategy on spray and wait routing protocol （ISDSRP） through enhancing the accuracy of estimating parameters. Finally, we conduct extensive simulations based on synthetic and real traces in ONE. The results show that compared with other buffer management strategies, ISDSRP and SDSRP achieve higher delivery ratio, similar average hopcounts, and lower overhead ratio.

Distributed Game-Theoretical D2D-Enabled Task Offloading in Mobile Edge Computing

Mobile Edge Computing(MEC)has been envisioned as a promising distributed computing paradigm where mobile users offload their tasks to edge nodes to decrease the cost of energy and computation.However,most of the existing studies only consider the congestion of wireless channels as a crucial factor affecting the strategy-making process,while ignoring the impact of offloading among edge nodes.In addition,centralized task offloading strategies result in enormous computation complexity in center nodes.Along this line,we take both the congestion of wireless channels and the offloading among multiple edge nodes into consideration to enrich users'offloading strategies and propose the Parallel User Selection Algorithm(PUS)and Single User Selection Algorithm(SUS)to substantially accelerate the convergence.More practically,we extend the users'offloading strategies to take into account idle devices and cloud services,which considers the potential computing resources at the edge.Furthermore,we construct a potential game in which each user selfishly seeks an optimal strategy to minimize its cost of latency and energy based on acceptable latency,and find the potential function to prove the existence of Nash equilibrium(NE).Additionally,we update PUS to accelerate its convergence and illustrate its performance through the experimental results of three real datasets,and the updated PUS effectively decreases the total cost and reaches Nash equilibrium.

Novel Global Optimization Algorithm with a Space-Filling Curve and Integral Function

In this study,we consider the global optimization problem in a hypercube.We use a class of series to construct a curve in a hypercube,which can fill the hypercube,and we present an integral function on the curve.Based on the integral function,we propose an algorithm for solving the global optimization problem.Then,we perform a convergence analysis and numerical experiments to demonstrate the effectiveness of the proposed algorithm.