BASE: A bacteria foraging algorithm for cell formation with sequence data

A cellular manufacturing system (CMS) is considered an efficient production strategy for batch type production. A CMS relies on the principle of grouping machines into machine cells and grouping parts into part families on the basis of pertinent similarity measures. The bacteria foraging algorithm (BFA) is a newly developed computation technique extracted from the social foraging behavior of Escherichia coli (E. coli) bacteria. Ever since Kevin M. Passino invented the BFA, one of the main challenges has been employment of the algorithm to problem areas other than those for which the algorithm was proposed. This research work studies the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem considering the operation sequence. In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. In this paper, an attempt is made to solve the CF problem, while taking into consideration the number of voids in the cells and the number of inter-cell travels based on operational sequences of the parts visited by the machines. The BFA is suggested to create machine cells and part families. The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. The results show better performance of the proposed algorithm.     

KISTCM: knowledge discovery system for traditional Chinese medicine

Objective: Traditional Chinese Medicine (TCM) provides an alternative method for achieving and maintaining good health. Due to the increasing prevalence of TCM and the large volume of TCM data accumulated though thousands of years, there is an urgent need to efficiently and effectively explore this information and its hidden rules with knowledge discovery in database (KDD) techniques. This paper describes the design and development of a knowledge discovery system for TCM as well as the newly proposed KDD techniques integrated in this system.     

2009多国仪器仪表展览会流量仪表评估

简要介绍了2009年多国仪器仪表展览会(MICONEX2009)上流量仪表参展商概况、12大类参展流量仪表所占比例,并分析评述了展品及其亮点,如新流量测最原理的激光流量计,向小流量低流速方向延伸的超声流量计、超声热黾表和超声水表,能测量液体的MEMS(微机电系统)制的热式流量计,可代替机械式的MEMS家用/商用燃气表,高阶椭圆齿轮流量计等.     

基于窗函数的FIR数字滤波器的优化及Matlab实现

窗函数法是设计数字滤波器的一种方法。简要介绍了如何利用窗函数进行FIR数字滤波器的设计,以及分析各种不同窗形式对滤波器性能的影响。最后运用Matlab进行仿真比较。     

网络攻击与防范研究

随着信息时代的到来,越来越多的企业或个人逐步意识到信息安全防护的重要性。计算机网络、数据通信、电子商务、办公自动化等领域需要解决信息安全问题。如何保护企业或个人的信息系统免遭非法入侵？对目前计算机网络存在的网络攻击方法进行了分析,从发现正确的目标到执行攻击,并提出相应的防范措施。     

社保网络信息安全防护

本文针对各种威胁社保网络安全的多种因素,进行有的放矢地构建相应策略,综合立体地进行网络安全防护,构建了一个多方面考虑的安全网络,这样社保部门在保护计算机网络设备安全和计算机网络系统安全的同时也保护了数据的安全,为构建和谐社会贡献力量。     

An efficient secure proxy verifiably encrypted signature scheme

Verifiably encrypted signature is an important cryptographic primitive, it can convince a verifier that a given ciphertext is an encryption of signature on a given message. It is often used as a building block to construct an optimistic fair exchange. In this paper, we propose a new concept: a proxy verifiably encrypted signature scheme, by combining proxy signature with a verifiably encrypted signature. And we formalize security model of proxy verifiably encrypted signature. After a detail construction is given, we show that the proposed scheme is provably secure in the random oracle model. The security of the scheme is related to the computational Diffie–Hellman problem.     

Quarter Load Threshold (QLT) flow control for wormhole switching in mesh-based Network-on-Chip

The fact that latency increases abruptly once the on-chip network is saturated indicates that it is necessary to devise an effective flow control strategy. Through tracing the status of the network buffer space we found that the payload of the on-chip network cannot get beyond an upper bound to avoid vicious congestion. Specifically, quarter of the total network buffer space is such a threshold, which is termed Quarter Load Threshold (QLT). Based on this fact we present the Quarter Load Threshold (QLT) flow control strategy. The performance of the proposed strategy is evaluated by the open source simulator Noxim [Noxim: Network-on-Chip Simulator, http://sourceforge.net/projects/noxim, 2008]. Simulation results show that the on-chip network runs smoothly and no serious congestion is encountered any more.     

Robust Calibration for Localization in Clustered Wireless Sensor Networks

This paper presents a robust calibration procedure for clustered wireless sensor networks. Accurate calibration of between-node distances is one crucial step in localizing sensor nodes in an ad-hoc sensor network. The calibration problem is formulated as a parameter estimation problem using a linear calibration model. For reducing or eliminating the unwanted influence of measurement corruptions or outliers on parameter estimation, which may be caused by sensor or communication failures, a robust regression estimator such as the least-trimmed squares (LTS) estimator is a natural choice. Despite the availability of the FAST-LTS routine in several statistical packages (e.g., R, S-PLUS, SAS), applying it to the sensor network calibration is not a simple task. To use the FAST-LTS, one needs to input a trimming parameter, which is a function of the sensor redundancy in a network. Computing the redundancy degree and subsequently solving the LTS estimation both turn out to be computationally demanding. Our research aims at utilizing some cluster structure in a network configuration in order to do robust estimation more efficiently. We present two algorithms that compute the exact value and a lower bound of the redundancy degree, respectively, and an algorithm that computes the LTS estimation. Two examples are presented to illustrate how the proposed methods help alleviate the computational demands associated with robust estimation and thus facilitate robust calibration in a sensor network.     

Skew detection in document images based on rectangular active contour

The digitalization processes of documents produce frequently images with small rotation angles. The skew angles in document images degrade the performance of optical character recognition (OCR) tools. Therefore, skew detection of document images plays an important role in automatic document analysis systems. In this paper, we propose a Rectangular Active Contour Model (RAC Model) for content region detection and skew angle calculation by imposing a rectangular shape constraint on the zero-level set in Chan–Vese Model (C-V Model) according to the rectangular feature of content regions in document images. Our algorithm differs from other skew detection methods in that it does not rely on local image features. Instead, it uses global image features and shape constraint to obtain a strong robustness in detecting skew angles of document images. We experimented on different types of document images. Comparing the results with other skew detection algorithms, our algorithm is more accurate in detecting the skews of the complex document images with different fonts, tables, illustrations, and layouts. We do not need to pre-process the original image, even if it is noisy, and at the same time the rectangular content region of a document image is also detected.