基于词法特征的恶意域名快速检测算法

针对互联网中恶意域名攻击事件频发，现有域名检测方法实时性不强的问题，提出一种基于词法特征的恶意域名快速检测算法。该算法根据恶意域名的特点，首先将所有待测域名按照长度进行正则化处理后赋予权值；然后利用聚类算法将待测域名划分成多个小组，并利用改进的堆排序算法按照组内权值总和计算各域名小组优先级，根据优先级降序依次计算各域名小组中每一域名与黑名单上域名之间的编辑距离；最后依据编辑距离值快速判定恶意域名。算法运行结果表明，基于词法特征的恶意域名快速检测算法与单一使用域名语义和单一使用域名词法的恶意域名检测算法相比，准确率分别提高1.7%与2.5%，检测速率分别提高13.9%与6.8%，具有更高的准确率和实时性。     

Distributed Control Strategy with Smith's Predictor in a Pilot-Scale Diabatic Distillation Unit

Intrinsic characteristics of distillation such as dead time and high nonlinearities do not allow the complete elimination of transient times when any external disturbance or set-point change occurs. Thus, aiming at the use of easy-tuning systems, a distributed-action control in trays of a diabatic distillation unit with Smith's predictor was implemented in the Simulink environment to further reduce transient times and out-of-specification product. The distributed-action strategy with Smith's predictor led to a reduction of 33.3 min (33 %) in the transient time of the top temperature control loop and 66 % in out-of-specification product, when compared with the conventional strategy, and thus is shown to be an efficient approach to increasing the productivity of distillation plants.     

偏高岭土-矿渣-磷渣地聚合物配比性能的研究

通过正交实验的方法，以地聚合物稠度、凝结时间、胶砂强度为研究依据，以偏高岭土、矿渣、磷渣、碱激发剂用量为研究对象，每个因素取3个水平，分析4个因素在各自水平上对地聚合物性能的影响。试验结果表明，偏高岭土用量是地聚合物稠度的最主要影响因素；偏高岭土和碱激发剂用量是初凝时间的主要影响因素，磷渣和偏高岭土用量是终凝时间的主要影响因素；偏高岭土用量是3 d 抗压强度的主要影响因素，矿渣用量是28 d 抗压强度的主要影响因素。按30%偏高岭土-40%矿渣-30%磷渣-10%碱激发剂制备的地聚合物具有良好的抗碳化性能，但收缩率较普通硅酸盐水泥高。     

Two-echelon multi-product multi-constraint product returns inventory model with permissible delay in payments and variable lead time

Supply chain is not limited to delivering products to the end-costumers since the defective products that are returned back to the producers by the consumers. The producers should be superior knowledge to utilize the return products effectively so as to maintain our natural resources and to provide better service to customers. In this paper, a distributor and a warehouse consisting of a serviceable part and a recoverable part supply chain problem is considered in which there are several products, the distributor has limited space capacity and budget to purchase all products. In this supply chain, the defective products are returned back to the warehouse by the distributor and the warehouse recovered those defective products into perfect products having the same value as the procured products. The lead-time of receiving products from a warehouse to a distributor is a variable which is controllable by adding extra crashing cost. For each product, a fraction of the shortage is backordered and the rest are lost. A mathematical model is employed in this study for optimizing the order quantity, lead time and total number of deliveries with the objective of minimizing system total cost. We show that the model of this problem is a constrained non-linear programme and present a simple Lagrangian multiplier technique to solve it. Numerical and sensitivity analysis are given to show the applicability of the proposed model in real-world product returns inventory problems.     

Profit maximization of TSP through a hybrid algorithm

Here a new model of Traveling Salesman Problem (TSP) with uncertain parameters is formulated and solved using a hybrid algorithm. For this TSP, there are some fixed number of cities and the costs and time durations for traveling from one city to another are known. Here a Traveling Salesman (TS) visits and spends some time in each city for selling the company’s product. The return and expenditure at each city are dependent on the time spent by the TS at that city and these are given in functional forms of t. The total time limit for the entire tour is fixed and known. Now, the problem for the TS is to identify a tour program and also to determine the stay time at each city so that total profit out of the system is maximum. Here the model is solved by a hybrid method combining the Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The problem is divided into two subproblems where ACO and PSO are used successively iteratively in a generation using one’s result for the other. Numerical experiments are performed to illustrate the models. Some behavioral studies of the models and convergences of the proposed hybrid algorithm with respect to iteration numbers and cost matrix sizes are presented.     

刮膜式分子蒸馏器液体停留时间分布及壁面结构优化

在刮膜式分子蒸馏器中,可以通过液体的停留时间分布反映物料蒸发分离特性,研究其规律对改进蒸馏器内的流场结构、优化操作参数和装置的设计都具有重要意义。今采用计算流体力学的方法,建立三维CFD模型,研究了进料速率和转子转速对停留时间分布规律的影响,并且与实验值进行对比验证;对蒸馏器壁面进行了优化,包括水平圆环、倾斜圆环和网状圆环三种优化壁面,并且对其分别进行模拟计算和实验验证。模拟结果显示出与实验结果相同的规律。结果表明,在研究范围内,停留时间随着进料速率的增大而减小;随着转子转速的增大,停留时间先增大,达到一定转速后,停留时间反而减小。经过壁面优化以后,在相同的进料速率和转子转速下,水平圆环壁面和网状圆环壁面的停留时间得到延长,倾斜圆环壁面的停留时间适当缩短;壁面湍动程度增大,有利于传质传热,提高了分离效率。     

Indirect adaptive control of nonlinear system via dynamic multilayer neural networks with multi‐time scales

This paper deals with adaptive nonlinear identification and trajectory tracking problem via dynamic multilayer neural network with different time scales. By means of a Lyapunov‐like analysis, we determine stability conditions for the on‐line identification. Then, a sliding mode controller is designed for trajectory tracking with consideration of the modeling error and disturbance. The main contributions of the paper lie in the following aspects. First, we extend our prior identification results of single‐layer dynamic neural networks with multi‐time scales to those of multilayer case. Second, the e‐modification in standard use in adaptive control is introduced in the on‐line update laws to guarantee bounded weights and bounded identification errors. Third, the potential singularity problem in controller design is solved by using new update laws for the NN weights so that the control signal is guaranteed bounded. The stability of proposed controller is proved by using Lyapunov function. Simulation results demonstrate the effectiveness of the proposed algorithm. Copyright © 2014 John Wiley & Sons, Ltd.     

Salmonella in table eggs from farm to retail – When is cooling required?

Storage time and temperature are known to be important factors in determining Salmonella growth in table eggs. It is assumed that growth of Salmonella within eggs starts when the egg yolk membrane breaks down, allowing Salmonella to enter and grow. The length of time for which the yolk membrane remains intact is time and temperature dependent.The present study addresses the question whether the current legal requirement in Germany to cool table eggs marketed 18 days after laying needs to be updated. Detailed data on the current storage and transport conditions in Germany were collected. On the basis of these data, typical combinations of temperature and time were selected. For these different time-temperature scenarios, the consequences regarding the probability of growth of Salmonella Enteritidis inside the eggs were calculated. A probabilistic model consisting of nine modules reflecting storage/transport stages from farm to retail in Germany was used to calculate whether the yolk membrane remains intact during the individual steps. Growth of Salmonella was simulated without cooling (room temperature) as well as with two different cooling scenarios (4–6 °C and 8–12 °C), which are temperature ranges used in Germany by various retailers. Simulations of these scenarios resulted in relative low numbers of eggs with Salmonella growth until purchase (89 out of 50,000 eggs in the uncooled scenario, 10 out of 50,000 eggs stored at 8–12 °C and 5 out of 50,000 eggs stored at 4–6 °C). These results show that for an average egg trading time of 7.5 days, as was observed for Germany, the probability for the consumer to purchase eggs where no Salmonella growth has started and yolk membrane integrity still exists is high. However, the model supports the necessity for egg cooling after the yolk membrane integrity time is exhausted. Furthermore, the model shows clearly that cooling will extend the time period before the egg yolk membrane breaks down. According to our results, the requirement to cool eggs from the 18th day onwards after laying, as required by legislation in Germany, is reasonable, as it matches the time point of the yolk membrane breakdown for the average egg kept at 18–20 °C. Therefore, continuation of this regulation is strongly supported.     

Liquid yield from juniper and mesquite bio‐fuel gasification

Mesquite (Prosopis glandulosa) and redberry juniper (Juniperus pinchotii) are two woody species which dominate uncultivated lands in the south central Great Plains, USA (Texas, Oklahoma) and may have potential for bioenergy utilization. In this study, these two biomasses were gasified in an adiabatic, updraft fixed‐bed gasifier using air as medium. The products include low heating value gas and liquid tar yield. The effects of fuel moisture content and the equivalence ratio (ER) on liquid yields including heavy tar and light tar and higher heating value (HHV) of the producer gas were investigated. It was found that updraft gasifiers produce a large amount of tar, in a range of 100 g/Nm³ of gas produced. As the equivalence ratio (ER) increased (i.e. more rich char conditions), peak temperature (T_peak) within the bed decreased due to the lesser partial oxidization. The liquid yield showed peak value with change in moisture content between 6 and 24%. Heavy tar is a very high quality fuel with a higher heating value of over 29 MJ/kg on a dry, ash‐free (DAF) basis which is a slightly higher than that of ethanol. Copyright © 2015 John Wiley & Sons, Ltd.