高效可撤销的身份基在线离线加密方案

身份基加密（IBE）需要提供一种有效的成员撤销机制，然而，现有可撤销成员的IBE方案存在密钥更新和加密运算量过大的问题，可能使执行该操作的设备成为系统的瓶颈。将完全子树方法和在线离线技术相结合，通过修改指数逆类型IBE的密钥生成和加密算法，提出了一种高效可撤销的身份基在线离线加密方案。方案利用完全子树方法生成更新钥，使得撤销用户无法获得更新钥，进而失去解密能力；利用在线离线技术，将大部分加密运算在离线阶段进行预处理，使得在线阶段仅执行少量简单计算即可生成密文。与相关知名方案相比，该方案不仅提高密钥生成中心的密钥更新的效率，而且极大减少了轻量级设备的在线加密工作量，适合于轻量级设备保护用户隐私信息。     

基于混合蚁群算法的异质车队低碳VRP研究

针对货运车辆在配送调度过程中产生大量碳排放的问题，建立模型将多种影响碳排放量的因素协同优化。模型中考虑了不同载重量的异质车队，两个节点之间有多条道路的柔性路径，以及车辆重量随卸货而减少的动态负载等因素，以碳排放量、行驶时间和行驶路程为优化目标，并加入了节点需求时间窗、根据速度变化划分路段、交接和卸货时间的约束。提出了一种混合蚁群算法，利用蚁群算法信息素强度更新方式保持群体记忆性，利用粒子群算法的快速收敛特性增加计算效率。通过随机数值算例的仿真优化与对比分析，验证了算法和模型的有效性。     

Delay compensated control of the Stefan problem and robustness to delay mismatch

This paper presents a control design for the one‐phase Stefan problem under actuator delay via a backstepping method. The Stefan problem represents a liquid‐solid phase change phenomenon which describes the time evolution of a material's temperature profile and the interface position. The actuator delay is modeled by a first‐order hyperbolic partial differential equation (PDE), resulting in a cascaded transport‐diffusion PDE system defined on a time‐varying spatial domain described by an ordinary differential equation (ODE). Two nonlinear backstepping transformations are utilized for the control design. The setpoint restriction is given to guarantee a physical constraint on the proposed controller for the melting process. This constraint ensures the exponential convergence of the moving interface to a setpoint and the exponential stability of the temperature equilibrium profile and the delayed controller in the norm. Furthermore, robustness analysis with respect to the delay mismatch between the plant and the controller is studied, which provides analogous results to the exact compensation by restricting the control gain.     

Stochastic polynomial optimization

ABSTRACT

This paper studies stochastic optimization problems with polynomials. We propose an optimization model with sample averages and perturbations. The Lasserre-type Moment-SOS relaxations are used to solve the sample average optimization. Properties of the optimization and its relaxations are studied. Numerical experiments are presented.     

Airline planning and scheduling: Models and solution methodologies

The airline industry is a representative industry with high cost and low profitability. Therefore, airlines should carefully plan their schedules to ensure that overall profit is maximized. We review the literature on airline planning and scheduling and focus on mathematical formulations and solution methodologies. Our research framework is anchored on three major problems in the airline scheduling, namely, fleet assignment, aircraft routing, and crew scheduling. General formulation, widely used solution approaches, and important extensions are presented for each problem and integrated problems. We conclude the review by identifying promising areas for further research.     

Stochastic collocation-based nonlinear analysis of concrete bridges with uncertain parameters

This paper focuses on the stochastic response of concrete bridges considering uncertainty in bearing and abutment stiffness. A multi-span simply supported bridge with concrete girders is selected. A 3D-dimensional model is prepared, and nonlinear response history analyses are performed. For the numerical dynamic simulation, the non-sampling stochastic method based on generalized polynomial chaos (gPC) expansion is utilised. The uncertain parameters include the vertical and shear stiffness of bearings and the lateral stiffness of abutments are presented by the truncated gPC expansions. Furthermore, the system response such as base shear, acceleration, velocity and displacement in different columns is presented by gPC expansion with unknown deterministic coefficients. The stochastic Galerkin projection is employed to calculate a set of deterministic equations. A non-intrusive solution, as a set of collocation points, determines the unknown gPC coefficients of the system response and the results are compared with Monte Carlo simulations. The key advantage of spectral discretization is the combination of the mentioned method with the spatial discretization, e.g. finite element model. This study also emphasises the accuracy in results and time efficiency of the proposed non-sampling method for uncertainty quantification of stochastic systems comparing to sampling procedure (e.g. Monte Carlo simulation).     

埋地管道腐蚀防护--防腐层与阴极保护存在的问题分析

在埋地管道研究工作中,关于其腐蚀的防护一直是研究的焦点问题,但现阶段常用的防护手段多为防腐层与阴极防护。为此,在文中主要对二者的保护措施展开了相应地阐述,并重点分析了2种保护手段存在的问题,旨在为后续的管道防腐研究提供相应的参考。     

基于伪布尔模型和启发式算法求解无容量设施选址问题

采用伪布尔模型和启发式算法来求解无容量设施选址问题。首先给出了问题的伪布尔(pseudo-Boolean)表示，然后基于Khumawala规则对问题进行预处理，最后提出两种启发式分支准则来求解问题。实验结果表明所提算法简单有效。     

Optimal design of Raman fibre amplifier based on terminal value optimization strategy and shuffled frog leaping algorithm

This paper introduces an evolutionary algorithm, Shuffled Frog Leaping Algorithm (SFLA), to solve the optimization problem in designing the multi-pumped Raman Fibre Amplifier (RFA). SFLA is a powerful optimizer tool because of its efficient mathematical expressions and global search capability. We utilize SFLA to determine the optimal pump wavelengths and pump powers by minimizing the gain ripple of RFA. To accelerate calculations, a terminal value optimization strategy (TVOS) is incorporated into the evolution of SFLA. This proposed strategy takes the terminal power values of pumps as the decision variables in optimization. Then, the optimal original power values of the pumps are obtained by solving the Power Coupled Equations once, without using the traditional method of repetitive guesses.The combination of SFLA and TVOS enhances the efficiency of optimization and accelerates calculation, while satisfying the design requirements of RFA.The simulation results show that nearly 65% of computational time has been saved compared with the traditional average power analysis. The 4-pumped C+L band of backward multi-pumped RFA with the average net gain of 0 dB, 1 dB and 2 dB are designed individually, where the gain ripple is less than 0.64 dB. The combination of SFLA and TVOS enhance the optimization efficiency and improve the performance of RFA with good gain profile.     

Combinatorial Immunophenotyping of Cell Populations with an Electronic Antibody Microarray

Immunophenotyping is widely used to characterize cell populations in basic research and to diagnose diseases from surface biomarkers in the clinic. This process usually requires complex instruments such as flow cytometers or fluorescence microscopes, which are typically housed in centralized laboratories. Microfluidics are combined with an integrated electrical sensor network to create an antibody microarray for label‐free cell immunophenotyping against multiple antigens. The device works by fractionating the sample via capturing target subpopulations in an array of microfluidic chambers functionalized against different antigens and by electrically quantifying the cell capture statistics through a network of code‐multiplexed electrical sensors. Through a combinatorial arrangement of antibody sequences along different microfluidic paths, the device can measure the prevalence of different cell subpopulations in a sample from computational analysis of the electrical output signal. The device performance is characterized by analyzing heterogeneous samples of mixed tumor cell populations and then the technique is applied to determine leukocyte subpopulations in blood samples and the results are validated against complete blood cell count and flow cytometry results. Label‐free immunophenotyping of cell populations against multiple targets on a disposable electronic chip presents opportunities in global health and telemedicine applications for cell‐based diagnostics and health monitoring.