The smooth fractionator

A modification of the general fractionator sampling technique called the smooth fractionator is presented. It may be used in almost every situation in which sampling is performed from distinct items that are uniquely defined, often they are physically separated items or clusters like pieces, blocks, slabs, sections, etc. To each item is associated a ‘guesstimate’ or an associated variable with a more‐or‐less close – and possibly biased ? relationship to the content of the item. The smooth fractionator is systematic sampling among the items arranged according to the guesstimates in a unique, symmetric sequence with one peak and minimal jumps. The smooth fractionator is both very simple to implement and so efficient that it should probably always be used unless the natural sequence of the sampling items is equally smooth. So far, there is no theory for the prediction of the efficiency of smooth fractionator designs in general, and their properties are therefore illustrated with a range of real and simulated examples. At the cost of a slightly more elaborate sampling scheme, it is, however, always possible to obtain an unbiased estimate of the real precision and of some of the variance components. The only real practical problem for always obtaining a high precision with the smooth fractionator is specimen inhomogeneity, but that is detectable at almost no extra cost. With careful designs and for sample sizes of about 10, the sampling variation for the primary, smooth fractionator sampling step may in practice often be small enough to be ignored.     

An efficient IP address lookup algorithm based on a small balanced tree using entry reduction

Due to a tremendous increase in internet traffic, backbone routers must have the capability to forward massive incoming packets at several gigabits per second. IP address lookup is one of the most challenging tasks for high-speed packet forwarding. Some high-end routers have been implemented with hardware parallelism using ternary content addressable memory (TCAM). However, TCAM is much more expensive in terms of circuit complexity as well as power consumption. Therefore, efficient algorithmic solutions are essentially required to be implemented using network processors as low cost solutions.Among the state-of-the-art algorithms for IP address lookup, a binary search based on a balanced tree is effective in providing a low-cost solution. In order to construct a balanced search tree, the prefixes with the nesting relationship should be converted into completely disjointed prefixes. A leaf-pushing technique is very useful to eliminate the nesting relationship among prefixes [V. Srinivasan, G. Varghese, Fast address lookups using controlled prefix expansion, ACM Transactions on Computer Systems 17 (1) (1999) 1-40]. However, it creates duplicate prefixes, thus expanding the search tree.This paper proposes an efficient IP address lookup algorithm based on a small balanced tree using entry reduction. The leaf-pushing technique is used for creating the completely disjointed entries. In the leaf-pushed prefixes, there are numerous pairs of adjacent prefixes with similarities in prefix strings and output ports. The number of entries can be significantly reduced by the use of a new entry reduction method which merges pairs with these similar prefixes. After sorting the reduced disjointed entries, a small balanced tree is constructed with a very small node size. Based on this small balanced tree, a native binary search can be effectively used in address lookup issue. In addition, we propose a new multi-way search algorithm to improve a binary search for IPv4 address lookup. As a result, the proposed algorithms offer excellent lookup performance along with reduced memory requirements. Besides, these provide good scalability for large amounts of routing data and for the address migration toward IPv6. Using both various IPv4 and IPv6 routing data, the performance evaluation results demonstrate that the proposed algorithms have better performance in terms of lookup speed, memory requirement and scalability for the growth of entries and IPv6, as compared with other algorithms based on a binary search.     

A balanced solution of a fuzzy soft set based decision making problem in medical science

The purpose of this paper is two folded. Firstly, the concept of mean potentiality approach (MPA) has been developed and an algorithm based on this new approach has been proposed to get a balanced solution of a fuzzy soft set based decision making problem. Secondly, a parameter reduction procedure based on relational algebra with the help of the balanced algorithm of mean potentiality approach has been used to reduce the choice parameter set in the parlance of fuzzy soft set theory and it is justified to the problems of diagnosis of a disease from the myriad of symptoms from medical science. Moreover the feasibility of this proposed method is demonstrated by comparing with Analytical Hierarchy Process (AHP), Naive Bayes classification method and Feng's method.     

Numerical simulation of land subsidence and verification of its character for an iron mine using sublevel caving

Combined with a digital bored photography system and in-situ statistics concerning the joints and fissures of both ore-body and surrounding rock,a 2D discrete model was constructed using UDEC.The stress field and displacement field changes of different sublevel stoping systems were also studied.Changes in the overlying rock strata settlement pattern has been analyzed and validated by in-situ monitoring data.The results show that:in the caving process,there exists an obvious delay and jump for the overlying rock strata displacement over time,and a stable arch can be formed in the process of caving,which leads to hidden goafs.Disturbed by the mining activity,a stress increase occurred in both the hanging wall and the foot wall,demonstrating a hump-shaped distribution pattern.From the comparison between simulation results and in-situ monitoring results,land subsidence shows a slow-development,suddenfailure,slow-development cycle pattern,which leads eventually to a stable state.This pattern validates the existence of balanced arch and hidden goafs.     

Robust procedures in multiple regression: P-subsets and a computational proposal

A number of robust and diagnostic techniques for the linear regression are in terms of p-dimensional subsets of the original sample. In a sample of size n this leads to consider ⁿ C _p subsets. To reduce the computational burden, a limited number of subsets can be selected by means of a sub-sampling scheme. In this paper we suggest and discuss the use of a Balanced Incomplete Block design plan.     

基于BSC-AHP的绩效评估模型研究与实现

为了解决企业战略目标执行难的问题,提升绩效评估合理性。笔者在深入研究现存理论和方法的基础上,采用平衡记分卡理论从企业战略目标中提取关键评估指标,并提出了用分解矩阵的方法将评估指标分解到各评估对象。最后引用层次分析法确定各指标权重。建立了引导、鼓励员工工作向有利于企业战略的执行与控制的绩效评估指标体系和评价模型。开发的系统在某印刷企业得到应用并取得良好效果,有效证明了模型的可行性和科学性。     

无人机侧向系统LPV 模型降阶

无人机线性参变(LPV)模型能准确描述其非线性动态特性,但初始建立的LPV模型阶数较高,控制过程计算量较大.为此,提出一种基于平衡截断的LPV模型降阶方法.首先给出LPV系统的适定性、稳定性和平衡实现的定义;然后,提出LPV模型的平衡截断降阶方法.针对无人机侧向系统LTI模型,通过多项式拟合来建立LPV模型,并实现模型降阶.仿真结果表明,降阶模型的阶跃响应满足输出响应的精度要求.     

The balanced traveling salesmanproblem

In this paper we introduce the balanced traveling salesman problem (BTSP), which can be used to model optimization problems where equitable distribution of resources are important. BTSP is obviously NP-hard. Efficient heuristic algorithms are presented to solve the problem along with extensive computational results using benchmark problems from TSPLIB and random instances. Our algorithms produced provably optimal solutions for several test instances. Application of the model in solving the nozzle guide vane assembly problem related to the maintenance of aircraft engines is also discussed.     

Effective allocation of customers to distribution centres: A multiple ant colony optimization approach

The global and competitive business environment has identified the importance of a quick and efficient service towards the customers in the past few decades. Distribution centre (DC) plays an important role in maintaining the uninterrupted flow of goods and materials between the manufacturer and customers. The performance of the supply chain network can be easily improved by an effective or balanced allocation of customers to DCs. Improper or unbalanced allocation of customers can lead to the under- or overutilization of facilities and can further deteriorate the customer service. Performance of the DC can be judged on the basis of its ability to provide the right goods, at the right time and at the right place. The lead time or transit time to deliver the goods to the customers is an important parameter for the measuring the efficiency and effectiveness of a particular DC in a supply chain. In this paper, a multiple ant colony optimization (MACO) approach is discussed in an effort to design a balanced and efficient supply chain network that maintains the best balance of transit time and customers service. The focus of this paper is on the effective allocation of the customers to the DCs with the two-fold objective of minimization of the transit time and degree of imbalance of the DCs. MACO technique is a modified form of the traditional ant colony system, where multiple ant colonies cooperate with each other to find the best possible customer allocation pattern for the DC. The proposed technique shows better performance because of its nature of considering both positive and negative feedback in search of optimum or near-optimum results. The developed algorithm based on the proposed approach is tested on a real practical problem and the results are discussed in this paper.     

光纤无线电系统中的新型探测法研究

光纤无线电系统利用光载波携带毫米波信号在中心站和基站之间构成上行和下行传输链路,能够满足宽带无线接入系统的需求.利用光外差的方法产生毫米波信号是光载毫米波最简单和直接的方式.分析了在光纤无线电系统中利用光纤布拉格光栅从可调谐激光器中反射出两束相位近似相等的相干光,采用平衡探测产生了毫米波信号,降低了相位噪声和强度噪声对产生的毫米波信号的影响.