A complete lookup table for marching cubes

The well-known marching cubes method is used to generate isosurfaces from volume data or data on a 3D rectilinear grid.To do so,it refers to a lookup table to decide on the possible configurations of the isosurface within a given cube,assuming we know whether each vertex lies inside or outside the surface.However,the vertex values alone do not uniquely determine how the isosurface may pass through the cube,and in particular how it cuts each face of the cube.Earlier lookup tables are deficient in various respects.The possible combinations of the different configurations of such ambiguous faces are used in this paper to find a complete and correct lookup table.Isosurfaces generated using the new lookup table here are guaranteed to be watertight.     

区间表的快速查找算法

区间表(表中每一元素表示的是一个范围的数据)的查找是一个常见的问题,在表的长度较小或要查找元素的数量不多的情况下,折半查找是一种不错并且容易实现的算法。但在某些特殊的行业(如电信业)由于要对长度较大的表进行数量巨大的元素的查找,就不得不考虑它的执行效率。在广东电信公用电话管理中心从事的“签约分销商售卡话务”统计中,巧用哈希表来实现大量数据在众多签约分销商售卡记录中的数据查找,将整个查找的总长度较折半查找降低了一个数量级,大大提高了数据查找的效率。     

Efficient lookup table based camera pose estimation for augmented reality

Until now, exising camera pose estimation methods for the widely used square marker‐based augmented reality (AR) are either highly sensitive to noise or much time consuming, and developers have to work hard to find the proper trade‐off between computational speed and quality in mobile AR applications where computational resources are limited. The major difficulty is that only the four corner points of the square AR marker are available, and no redundant point correspondences can be used for a stable estimation. To solve this problem, an efficient lookup table (LUT)‐based non‐iterative solution is presented in this paper that achieves high stability in the presence of noise better than the most robust and accurate iterative solutions in the field, with the same level of accuracy and a much lower computational complexity. Our central idea consists of extracting a key parameter β from the camera pose and creating a LUT for β by taking the symmetrical structure of the square marker into account, thereby exploiting additional information. Copyright © 2011 John Wiley & Sons, Ltd.     

对路由表结构和查找算法的研究

随着网络流量的指数性增长,每秒能够传输10G以上比特的光纤骨干网络大量投入使用,但是大部分骨干路由器无法相应达到每秒转发百万个分组的高速,成为网络瓶颈。分组转发性能由多种因素决定,其中路由查找算法是关键。综述了近年来在路由表数据结构和查找算法的研究方面的最新进展,并对一种较先进的转发表结构进行了重点分析。     

Fast and deterministic hash table lookup using discriminative bloom filters

Hash tables are widely used in network applications, as they can achieve O(1) query, insert, and delete operations at moderate loads. However, at high loads, collisions are prevalent in the table, which increases the access time and induces non-deterministic performance. Slow rates and non-determinism can considerably hurt the performance and scalability of hash tables in the multi-threaded parallel systems such as ASIC/FPGA and multi-core. So it is critical to keep the hash operations faster and more deterministic.This paper presents a novel fast collision-free hashing scheme using Discriminative Bloom Filters (DBFs) to achieve fast and deterministic hash table lookup. DBF is a compact summary stored in on-chip memory. It is composed of an array of parallel Bloom filters organized by the discriminator. Each element lookup performs parallel membership checks on the on-chip DBF to produce a possible discriminator value. Then, the element plus the discriminator value is hashed to a possible bucket in an off-chip hash table for validating the match. This DBF-based scheme requires one off-chip memory access per lookup as well as less off-chip memory usage. Experiments show that our scheme achieves up to 8.5-fold reduction in the number of off-chip memory accesses per lookup than previous schemes.     

基于混沌动态搜索的数字图像加密算法

利用了混沌系统的伪随机性和遍历性,提出了一种新的两个一维混沌映射的动态查找表的数字图像加密算法.该算法在加密过程中,一个混沌映射作为干扰源,克服了单个一维混沌系统周期短、精度低的缺点.同时引入了反馈,动态的改变查找表,克服了静态查询密丈分布不均匀缺点.理论分析与实验结果表明,该算法的安全性明显增强,加密速度也有所提高且对已有的攻击方法有了更强的抵抗能力.     

基于亚像素边缘定位点查找表的检测算法

提出了一种新型的测量图像快速亚像素边缘检测方法。首先通过计算机模拟仿真,找出图像边缘处灰度落差与边缘点偏移之间的规律性,建立了一个由灰度落差得到边缘亚像素定位点的查找表;然后结合改进的Sobel检测算子和十字窗检测法将图像边缘检测精度达到像素级,并应用查找表实现了亚像素级的检测精度。实验表明:该方法不仅得到了较高的检测精度,定位精度为0.3pixels,而且可以大大地提高检测速度。     

Medial axis lookup table and test neighborhood computation for 3D chamfer norms

Chamfer distances are discrete distances based on the propagation of local distances, or weights, defined in a mask. The medial axis, i.e. the centers of maximal balls (balls which are not contained in any other ball), is a powerful tool for shape representation and analysis. The extraction of maximal disks is performed in the general case by testing the inclusion of a ball in a local neighborhood with covering relations usually represented by lookup tables.The proposed method determines if a mask induces a norm and in this case, computes the lookup tables and the test neighborhood based on geometric properties of the balls of chamfer norms, represented as H-polytopes. The method does not need to repeatedly scan the image space, and improves the computation time of both the test neighborhood detection and the lookup table computation.     

基于对照表以及语义相关性之简繁汉字转换

目前使用的汉字有简体和繁体两大形式：中国大陆和新加坡等地使用简体字,我国港澳台地区和部分海外华人社区使用繁体字。其中大多数简体字的意义和用法与对应的繁体字是一样的,具有一一对应关系,这种情况通过查找简繁对照表就可以正确处理。然而,还有相当一部分简体字对应多个繁体字,这是简繁字转换的重点和难点。基于此背景提出基于对照表以及语义相关性的简繁汉字转换方法。在教育部语信司及中国中文信息学会联合举办的一对多简繁转换评测中,此一对多简繁转换系统以95.6%的准确率排名第一。     

基于多层混合结构的IPv6路由表查找算法

针对现有的大多IPv6路由表查找算法采用各种优化手段提高查找性能,却使得路由更新需要重构整个路由表的问题,提出基于多层混合结构的IPv6路由表查找算法。该算法在第一层借鉴最优查找树的优点,把前缀1~16位的不同取值按其在路由表中出现的概率降序存储在线性表中,在第二、三层把前缀的17~32位和33~48位分别用二叉平衡树组织,在第四层把49~64位使用线性表组织。实验结果表明,该算法查找速度快,占用内存少,动态增量更新速度快。     

Symbol spotting in vectorized technical drawings through a lookup table of region strings

In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes.     

A genetic algorithm based lookup table approach for optimal stepping sequence of open-loop stepper motor systems

Stepper motor driven systems are widely used in industrial applications. They are mainly used for their low cost open-loop high performance. However, as dynamic systems need to be increasingly faster and their motion more precise, it is important to have an open-loop system which is accurate and reliable. In this paper, we present a novel technique in which a genetic algorithm (GA) based lookup table approach is used to find the optimal stepping sequence of an open-loop stepper motor system. The optimal sequence objective is to minimize residual vibration and to accurately follow trajectory. A genetic algorithm is used to find the best stepping sequence which minimizes the error and improves the system performance. Numerical simulation has showed the effectiveness of our approach to improve the system performance for both position and velocity. The optimized system reduced the residual vibration and was able to follow the trajectory with minimal error.     

VIBEX: an expert system for vibration fault diagnosis of rotating machinery using decision tree and decision table

This paper proposes an expert system called VIBEX (VIBration EXpert) to aid plant operators in diagnosing the cause of abnormal vibration for rotating machinery. In order to automatize the diagnosis, a decision table based on the cause-symptom matrix is used as a probabilistic method for diagnosing abnormal vibration. Also a decision tree is used as the acquisition of structured knowledge in the form of concepts is introduced to build a knowledge base which is indispensable for vibration expert systems. The decision tree is a technique used for building knowledge-based systems by the inductive inference from examples and plays a role itself as a vibration diagnostic tool. The proposed system has been successfully implemented on Microsoft Windows environment and is written in Microsoft Visual Basic and Visual C++. To validate the system performance, the diagnostic system was tested with some examples using the two diagnostic methods.     

Real-time fault diagnosis [robot fault diagnosis]

This article presents a number of complementary algorithms for detecting faults on-board operating robots, where a fault is defined as a deviation from expected behavior. The algorithms focus on faults that cannot directly be detected from current sensor values but require inference from a sequence of time-varying sensor values. Each algorithm provides an independent improvement over the basic approach. These improvements are not mutually exclusive, and the algorithms may be combined to suit the application domain. All the approaches presented require dynamic models representing the behavior of each of the fault and operational states. These models can be built from analytical models of the robot dynamics, data from simulation, or from the real robot. All the approaches presented detect faults from a finite number of known fault conditions, although there may potentially be a very large number of these faults.     

An analytical study on optimizing the lookup performance of distributed hash table systems under churn

The phenomenon of system churn degrades the lookup performance of distributed hash table (DHT) systems greatly. To handle the churn, a number of approaches have been proposed to date. However, there is a lack of theoretical analysis to direct how to make design choices under different churn rates and how to configure their parameters optimally. In this paper, we analytically study three important aspects on optimizing DHT lookup performance under churn, i.e. lookup strategy, lookup parallelism and lookup key replication. Our objective is to build a theoretical basis for designers to make better design choices in the future. We first compare the performance of two representative lookup strategies—recursive routing and iterative routing—and explore the existence of better alternatives. Then we study the effectiveness of lookup parallelism in systems with different churn rates and show how to select the optimal degree of parallelism. Owing to the importance of key replication on lookup performance, we also analyze the reliability of the replicated key under two different replication policies, and show how to perform proper configuration. Besides the analytical study, our results are also validated by simulation, and Kad is taken as a case to show the meaningfulness of our analysis. Copyright © 2007 John Wiley & Sons, Ltd.     

A rough set-based fault ranking prototype system for fault diagnosis

Fault diagnosis is a complex and difficult problem that concerns effective decision-making. Carrying out timely system diagnosis whenever a fault symptom is detected would help to reduce system down time and improve the overall productivity. Due to the knowledge and experience intensive nature of fault diagnosis, the diagnostic result very much depends on the preference of the decision makers on the hidden relations between possible faults and the presented symptom. In other words, fault diagnosis is to rank the possible faults accordingly to give the engineer a practical priority to carry out the maintenance work in an efficient and orderly manner. This paper presents a rough set-based prototype system that aims at ranking the possible faults for fault diagnosis. The novel approach engages rough theory as a knowledge extraction tool to work on the past diagnostic records, which is registered in a pair-wise comparison table. It attempts to extract a set of minimal diagnostic rules encoding the preference pattern of decision-making by domain experts. By means of the knowledge acquired, the ordering of possible faults for failure symptom can then be determined. The prototype system also incorporates a self-learning ability to accumulate the diagnostic knowledge. A case study is used to illustrate the functionality of the developed prototype. Result shows that the ranking outcome of the possible faults is reasonable and sensible.     

Rollout strategies for sequential fault diagnosis

Test sequencing is a binary identification problem wherein one needs to develop a minimal expected cost testing procedure to determine which one of a finite number of possible failure sources, if any, is present. The problem can be solved optimally using dynamic programming or AND/OR graph search methods (AO/sup */, CF, and HS). However, for large systems, the associated computation with dynamic programming or AND/OR graph search methods is substantial, due to the rapidly increasing number of OR nodes (denoting ambiguity states) and AND nodes (denoting tests) in the search graph. In order to overcome the computational explosion, the one-step or multistep lookahead heuristic algorithms have been developed to solve the test sequencing problem. In this paper, we propose to apply rollout strategies, which can be combined with the one-step or multistep lookahead heuristic algorithms, in a computationally more efficient manner than the optimal strategies, to obtain solutions superior to those using the one-step or multistep lookahead heuristic algorithms. The rollout strategies are illustrated and tested using a range of real-world systems. We show computational results, which suggest that the information-heuristic based rollout policies are significantly better than other rollout policies based on Huffman coding and entropy.     

Input design for active fault diagnosis

Reliably diagnosing faults and malfunctions has become increasingly challenging in modern technical systems because of their growing complexity as well as increasingly stringent requirements on safety, availability, and high-performance operation. Traditional methods for fault detection and diagnosis rely on nominal input–output data, which can contain insufficient information to support reliable conclusions. Recent years have witnessed a growing interest in active fault diagnosis, which addresses this issue by injecting input signals specifically designed to reveal the fault status of the system. This paper provides an overview of state-of-the-art methods for input design for active fault diagnosis and discusses the primary considerations in the formulation and solution of the input-design problem. We also discuss the primary challenges and suggest avenues for future research in this rapidly evolving field.     

故障诊断的信息融合方法

对基于信息融合的故障诊断方法进行综述．首先简要阐述信息融合的基本概念以及信息融合与故障诊断的关系;然后介绍贝叶斯定理融合故障诊断、模糊融合故障诊断、证据理论融合故障诊断、神经网络融合故障诊断和集成信息融合故障诊断方法的诊断原理与步骤。并分析其特点和局限性;最后给出了信息融合故障诊断研究的若干发展方向．