基于MATLAB的最大误差双圆弧逼近曲线的算法及实现

分析了不同半径的圆弧与曲率连续单调变化的曲线相切的几何关系,讨论了连续相切圆弧以允差逼近曲线的算法,理论上使得圆弧逼近的段数达到最少,并保证了光滑连接。基于Matlab采用一维搜索和优化相结合的方法进行程序的编制求解节点,算法简单,可靠,数控程序段数少,程序运行更快速高效。     

MQL深孔钻削中关键因素的最适化研究

采用了微量润滑技术的钻削在长距或小孔径的条件下有必要对所供给的油雾和压缩空气进行最佳化分析.本文首先对切削变形与切削热分布的总能量进行了分析,并在把普通钻削过程中油雾假设为稳态可压缩绝热紊流状态的假设条件下,通过分析得到油膜厚度、气流速度、压缩空气温度和刀具平均温度等重要影响参数的相互关系.最后,给出微量润滑钻削条件下,切削过程中所需的油膜和压缩空气的最佳容量.     

Two-commodity reliability evaluation of a stochastic-flow network with varying capacity weight in terms of minimal paths

A real-life manufacturing system can be modeled as a stochastic-flow network in which nodes stand for the machine stations, and arcs stand for the shipping media. In terms of minimal paths (MPs), this paper presents a stochastic-flow network model with four characteristics: (1) both nodes and arcs have multiple possible capacities, and may fail; (2) each component (arc/node) has both capacity and cost attributes; (3) two-commodity are proceeded; and (4) the capacity weight varies with arcs, nodes, and types of commodity. We study the possibility of two-commodity to be transmitted through this network simultaneously under the budget constraint. Such a possibility is named as the system reliability. The MPs play the role of media to describe the relationship among flow assignments and capacity vectors. Subsequently, a simple algorithm, in terms of MPs, is proposed to evaluate the system reliability. From the capacity management and decision making viewpoints, managers may adopt the system reliability as a performance index to measure the system capacity and finally to determine if it meets the customers’ orders or not.     

Distance metric learning by minimal distance maximization

Classic linear dimensionality reduction (LDR) methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are known not to be robust against outliers. Following a systematic analysis of the multi-class LDR problem in a unified framework, we propose a new algorithm, called minimal distance maximization (MDM), to address the non-robustness issue. The principle behind MDM is to maximize the minimal between-class distance in the output space. MDM is formulated as a semi-definite program (SDP), and its dual problem reveals a close connection to “weighted” LDR methods. A soft version of MDM, in which LDA is subsumed as a special case, is also developed to deal with overlapping centroids. Finally, we drop the homoscedastic Gaussian assumption made in MDM by extending it in a non-parametric way, along with a gradient-based convex approximation algorithm to significantly reduce the complexity of the original SDP. The effectiveness of our proposed methods are validated on two UCI datasets and two face datasets.     

Extension of some MAP results to transient MAPs and Markovian binary trees

In this work we extend previous results on moment-based characterization and minimal representation of stationary Markovian arrival processes (MAPs) and rational arrival processes (RAPs) to transient Markovian arrival processes (TMAPs) and Markovian binary trees (MBTs).     

Comparing endoscopic systems on two simulated tasks

Endoscopes are slender instruments for performing medical procedures through small incisions or natural body orifices. Three experiments examined the performance effects of various endoscope systems when naive participants executed tasks in a bladder-like environment. The systems involved a direct endoscope, requiring the user to look through a lens at the outer part of the endoscope, and a video endoscope that picks up the image via a camera attached to the endoscope and displays it on a video monitor. The results indicate that the participants performed the tasks better with video than with direct endoscopes, and showed more transfer of practice with video endoscopic surgery from a small to a large task environment than vice versa. The optimal position of the monitor with video endoscopic surgery appeared to involve a reasonable angle relative to the operating area (45° was used). Performance was less at a greater angle (90°), but also at a small angle (10°). It did not matter whether the monitor was located left, right or above the operating area. As performance did not fully transfer to differently sized task environments, endoscopists should initially train with task environments of different, and especially small, sizes.     

Graph theory augmented math programming approach to identify minimal reaction sets in metabolic networks

Bioprocesses are of growing importance as an avenue to produce chemicals. Microorganisms containing only desired catalytic and replication capabilities in their metabolic pathways are expected to offer efficient processes for chemical production. Realizing such minimal cells is the holy grail of metabolic engineering. In this paper, we propose a new method that combines graph-theoretic approaches with mixed-integer liner programming (MILP) to design metabolic networks with minimal reactions. Existing MILP based computational approaches are computationally complex especially for large networks. The proposed graph-theoretic approach offers an efficient divide-and-conquer strategy using the MILP formulation on sub-networks rather than considering the whole network monolithically. In addition to the resulting improvement in computational complexity, the proposed method also aids in identifying the key reactions to be knocked-out in order to achieve the minimal cell. The efficacy of the proposed approach is demonstrated using three case studies from two organisms, Escherichia coli and Saccharomyces cerevisiae.     

A new algorithm for a recursive construction of the minimal interpolation space

In this work, we introduce a new interpolation algorithm, based on a recursive method for computing Lagrange interpolants. This algorithm allows to construct recursively the minimal interpolation space (see [1]) with respect to a finite set of points. We also extend this recursive method to the osculatory interpolation problem.     

二维网格中基于最小通路区的自适应和最小容错路由算法

网格结构是并行与分布式处理中最流行的一种网络拓扑结构。在存在故障的情况下，如何设计具有最优性的容错路由算法一直是研究的热，点问题。本文研究了采用故障块模型的二维网格的最小路由问题，提出存在最小通路的一个充分必要条件。基于最小通路区（RMP）的概念，提出一种自适应的最小容错路由算法。如果源节点和目的节点之间存在最小通路区，则在最小通路区中进行自适应最小容错路由；反之，则采用多阶段最小容错路由。主要思想就是在存在故障的情况下，尽量保证路由算法能走最短路径。因为只要求知道每个节点的局部信息，故算法是分布式的。     

Mining border descriptions of emerging patterns from dataset pairs

The mining of changes or differences or other comparative patterns from a pair of datasets is an interesting problem. This paper is focused on the mining of one type of comparative pattern called emerging patterns. Emerging patterns are denoted by EPs and are defined as patterns for which support increases from one dataset to the other with a big ratio. The number of EPs is sometimes huge. To provide a good structure for and to reduce the size of mining results, we use borders to concisely describe large collections of EPs in a lossless way. Such a border consists of only the minimal (under set inclusion) and the maximal EPs in the collection. We also present an algorithm for efficiently computing the borders of some desired EPs by manipulating the input borders only. Our experience with many datasets in the UCI Repository and recent cancer diagnosis datasets demonstrated that: Both the EP pattern type and our algorithm are useful for building accurate classifiers and useful for mining multifactor interactions, for example, minimal gene groups potentially responsible for the development of cancer.