应用于二进制除法位数扩展N阶预测-校正迭代算法

提出了一种扩展二进制除法位数的N阶预测-校正迭代算法.该算法每次迭代将除数位长一分为二,直到除数位长与基本除法位长相同.相应地商分前后两步求出,每步中除数高半数位作为除法运算的除数预测商值,低半数位和部分余数形成部分积校正预测值.理论分析并论证了调整值集合为{0,-1,-2},给出了32位以内的各次校正概率曲线图.实验结果表明,本算法与比较除法相比,计算效率可提高3到10倍(取决于基本除法的位长).本算法能得到准确余数,符合IEEE浮点数的舍入规范.

基于硬件的二阶插值单精度函数近似

最简单的初等函数实现方法是查找表,但其只有与简单算术操作相结合才可实现单精度的函数近似;在介绍已有同类研究后,文章提出了一种基于二阶插值的改进查表计算结构,所需查表后的算术操作数据宽度低,不仅减少常数存储ROM面积,并且改善了系统总延迟;此固定结构可适合所有的初等函数的近似查表。

Applications of Computer Aided Modeling Techniques to Complex ICE Components

Design of internal combustion engine (ICE) components is one of the earliest and also the most active areas in which computer aided modeling techniques are applied. Computer aided modeling techniques could provide requisite information for follow up designing segments such as structural analysis, design of technological process and manufacturing etc, and thereby lead to the reduction of product design period and the quality and reliability improvement of ICE components. So the developing situations of ICE components' 2 D drafting, 3 D modeling of ICE, overall CAD of ICE as well as component design expert system etc. are surveyed, which are the typical applications of computer aided modeling techniques in ICE component design process, and some existent problems and tasks are pointed out so as to make some references for the further research work.

Granular Computing for Data Analytics:A Manifesto of Human-Centric Computing

In the plethora of conceptual and algorithmic developments supporting data analytics and system modeling,humancentric pursuits assume a particular position owing to ways they emphasize and realize interaction between users and the data.We advocate that the level of abstraction,which can be flexibly adjusted,is conveniently realized through Granular Computing.Granular Computing is concerned with the development and processing information granules–formal entities which facilitate a way of organizing knowledge about the available data and relationships existing there.This study identifies the principles of Granular Computing,shows how information granules are constructed and subsequently used in describing relationships present among the data.

Similarity-based denoising of point-sampled surfaces

A non-local denoising (NLD) algorithm for point-sampled surfaces (PSSs) is presented based on similarities, including geometry intensity and features of sample points. By using the trilateral filtering operator, the differential signal of each sample point is determined and called "geometry intensity". Based on covariance analysis, a regular grid of geometry intensity of a sample point is constructed, and the geometry-intensity similarity of two points is measured according to their grids. Based on mean shift clustering, the PSSs are clustered in terms of the local geometry-features similarity. The smoothed geometry intensity, i.e., offset distance, of the sample point is estimated according to the two similarities. Using the resulting intensity, the noise component from PSSs is finally removed by adjusting the position of each sample point along its own normal direction. Ex- perimental results demonstrate that the algorithm is robust and can produce a more accurate denoising result while having better feature preservation.

A Practical SSL Server Performance Improvement Algorithm Based on Batch RSA Decryption

The secure socket layer/ transport layer security（SSL/TLS） handshake protocol uses public key cryptographic algorithms such as RSA for key establishment. Typically, public key cryptographic algorithm is computational intensive due to the modular multiplications. Therefore, SSL/TLS servers often become swamped while performing public key decryptions when the simultaneous requests increase quickly. A batch RSA decryption algorithm was proposed. The novel algorithm provides the reasonable response time and optimizes server performance significantly. The decryption speedup is proportional to the batch size b, for instance, the speedup factor is 4, while in Shacham＇s scheme the acceleration rate is only 2.5 when b = 4.

Trinary flip-flops using Savart plate and spatial light modulator for optical computation in multivalued logic

The memory devices in multi-valued logic are of most significance in modem research. This paper deals with the implementation of basic memory devices in multi-valued logic using Savart plate and spatial light modulator （SLM） based optoelectronic circuits. Photons are used here as the carder to speed up the operations. Optical tree architecture （OTA） has been also utilized in the optical interconnection network. We have exploited the advantages of Savart plates, SLMs and OTA and proposed the SLM based high speed JK, D-type and T-type flip-flops in a trinary system.

SEMI-FRAGILE WATERMARKING ALGORITHM FOR IMAGE TAMPERS LOCALIZATION AND RECOVERY

Two watermarks are embedded into the original image. One is the authentication watermark generated by secret key, which is embedded into the sub-LSB （Least Significant Bit） of the original image for tamper localization; the other is the recovery watermark for tamper recovering. The original image is divided into 8 x 8 blocks and each block is transformed by Discrete Cosine Transform （DCT）. For each block, some lower frequency DCT coefficients are chosen to be quantized and binary encoded so as to gain the recovery watermark of each block, and the recovery watermark is embedded into the LSB of another block by chaos encryption and authentication chain technology. After the two watermarks being detected, the location of any minute changes in image can be detected, and the tampered image data can be recovered effectively. In the paper, the number of coefficients and their bit lengths are carefully chosen in order to satisfy with the payload of each block and gain the capability of self-recovering. The proposed algorithm can well resist against possible forged attacks. Experimental results show that the watermark generated by the proposed algorithm is sensitive to tiny changes in images, and it has higher accuracy of tamper localization and good capability of the tamper recovery.

An all-optical scheme of signed digit binary addition based on optical non-linear material

We propose a new integrated method which covers addition of any two signed digit numbers in all-optical domain. To implement this scheme we have exploited some photo-refractive characters of optical non-linear materials,which may experience 0.1-0.2dB attenuation loss as silica is used as non-linear medium. Moreover,the attenuation loss may be reduced to 0.001 dB/m if we consider the use of slow light at 1.56μm.

An Efficient Algorithm for Discovering Co-occurrence Concepts Through Pathfinder Paradigm

The Pathfinder paradigm has been used in generating and analyzing graph models that support clustering similar concepts and minimum-cost paths to provide an associative network structure within a domain. The co-occurrence pathfinder network （ CPFN ） extends the traditional pathfinder paradigm so that co-occurring concepts can be calculated at each sampling time. Existing algorithms take O（n（s）） time to calculate the pathfinder network （PFN） at each sampling time for a non-completed input graph of a CPFN （r = ∞, q = n - 1）, where n is the number of nodes in the input graph, r is the Minkowski exponent and q is the maximum number of links considered in finding a minimum cost path between vertices. To reduce the complexity of calculating the CPFN, we propose a greedy based algorithm, MEC（G） algorithm, which takes shortcuts to avoid unnecessary steps in the existing algorithms, to correctly calculate a CPFN （r = ∞, q= n - 1） in O（klogk） time where k is the number of edges of the input graph. Our example demonstrates the efficiency and correctness of the proposed MEC（G） algorithm, confirming our mathematic analysis on this algorithm.

Image Series Segmentation and Improved MC Algorithm

A semiautomatic segmentation method based on active contour is proposed for computed tomography (CT) image series. First, to get initial contour, one image slice was segmented exactly by C-V method based on Mumford-Shah model. Next, the computer will segment the nearby slice automatically using the snake model one by one. During segmenting of image slices, former slice boundary, as next slice initial contour, may cross over next slice real boundary and never return to right position. To avoid contour skipping over, the distance variance between two slices is evaluated by an threshold, which decides whether to initiate again. Moreover, a new improved marching cubes (MC) algorithm based on 2D images series segmentation boundary is given for 3D image reconstruction. Compared with the standard method, the proposed algorithm reduces detecting time and needs less storing memory. The effectiveness and capabilities of the algorithm were illustrated by experimental results.

SVM with discriminative dynamic time alignment

In the past several years, support vector machines （SVM） have achieved a huge success in many fields, especially in pattern recognition. But the standard SVM cannot deal with length-variable vectors, which is one severe obstacle for its applications to some important areas, such as speech recognition and part-of-speech tagging. The paper proposed a novel SVM with discriminative dynamic time alignment （ DDTA - SVM） to solve this problem. When training DDTA - SVM classifier, according to the category information of the training sampies, different time alignment strategies were adopted to manipulate them in the kernel functions, which contributed to great improvement for training speed and generalization capability of the classifier. Since the alignment operator was embedded in kernel functions, the training algorithms of standard SVM were still compatible in DDTA- SVM. In order to increase the reliability of the classification, a new classification algorithm was suggested. The preliminary experimental results on Chinese confusable syllables speech classification task show that DDTA- SVM obtains faster convergence speed and better classification performance than dynamic time alignment kernel SVM （ DTAK - SVM）. Moreover, DDTA - SVM also gives higher classification precision compared to the conventional HMM. This proves that the proposed method is effective, especially for confusable length - variable pattern classification tasks

A Two-Stage Method for an Approximate Calculation of Statically Indeterminate Trusses

The paper presents the principles of a method, which in two simple stages makes possible to carry out the statically calculation of values of forces acting in the fiat static indeterminate trusses. In each stage, it is considered the static determinate truss, scheme of which is obtained after remove the suitable number of members from the basic static indeterminate truss. The both intermediate statically determinate trusses are of the same clear span and they are loaded by forces of half values applied to the corresponding truss nodes. The method applies one of the typical procedures of calculation of the statically determinate trusses and then it is applied in an appropriate way the rule of superposition for obtaining the final values of forces acting in particular members of the basic truss. The values of forces calculated in this way are of a very close approximation to the force values determined in the special and complex ways being considered as the exact calculation methods. The proposed method can be useful mostly but not only for the initial structural design of such systems. The simplicity of the two-stage method justifies an assumption that it can be relatively easy and worthy to adjust to the requirements of the computer aided technology of statically calculation of the complex forms of trusses.

A High-accuracy Approach to Pronunciation Prediction for Out-of-vocabulary English Word

Letter-to-Sound conversion is one of the fundamental issues in text-to-speech synthesis. In this paper, we address an approach to automatic prediction of word pronunciation. This approach combines example-based learning and dynamic-programming searching to predict sub-word pronunciation. Word pronunciation is formed by concatenating sub-word pronunciations. We conducted comparative experiments over a large-scale English dictionary. Experimental results show that this approach can achieve accuracy of 70.1%, which outperforms those published results.

Improved Genetic Algorithm Application in Textile Defect Detection

Based on an efficient improved genetic algorithm, a pattern recognition approach is represented for textile defects inspection. An image process is developed to automatically detect the drawbacks on textile caused by three circumstances： break, dual, and jump of yams. By statistic method, some texture feature values of the image with defects points can be achieved. Therefore, the textile defects are classified properly. The advanced process of the defect image is done. Image segmentation is realized by an improved genetic algorithm to detect the defects. This method can be used to automatically classify and detect textile defects. According to different users＇ requirements, different types of textile material can be detected.

An efficient shortest path approach for social networks based on community structure

Finding the shortest path （SP） in a large-scale network analysis between any two nodes is a tough but very significant task. The SP can help us to analyze the information spreading performance and research the latent relationship in the weighted social network, and so on. As the size of the social network increases, the traditional SP algorithms have poor performance and there is not a suitable algorithm for weighted social network. Some features of the network analysis are beneficial to solve this problem, and community structure ignored by the traditional methods is one of the most important features. In this paper, we propose a shortest path algorithm based on community detection （SPCD） by integrating community detection algorithm with traditional search methods. SPCD constructs a community graph by using community structure to narrow the searching scope. The algorithm presented improves the time efficiency and maintains the accuracy scale of the SR Experimental results on five real-world networks demonstrate the effectiveness of the proposed methods for the SP problem.

Method for improving RLS algorithms

The recursive least-square (RLS) algorithm has been extensively used in adaptive identification, prediction, filtering, and many other fields. This paper proposes adding a second-difference term to the standard recurrent formula to create a novel method for improving tracing capabilities. Test results show that this can greatly improve the convergence capability of RLS algorithms.

Collaborative work model based on peer-to-peer network

In this paper, we incorporated peer-to-peer (P2P) concept with agent technology and put forward a collaborative work model based on peer-to-peer network (P2PCWM) after investigating into business demands of modern enterprises and problems prevailing in mainstream collaborative work systems based on central server. Theoretically, the P2PCWM can effectively overcome the problems in a conventional system with a central server and meet the practical demands of modern businesses. It is distinguished from other systems by its features of equality, openness, promptness, fairness, expandability and convenience.

Measuring the effectiveness of methods for evaluating noise jammers

Reliable evaluations of a noise jammer's effectiveness are necessary to properly design, manufacture, and operate one, so it is important to have an evaluation model. Based on their characteristics and principles, relevant factors were classified in terms of their contribution to a unit's effectiveness. In this way an evaluation index system was established. In the proposed mathematical model a noise jammer is analyzed by combining the model of system effectiveness with the method of analytic hierarchical process. A simulation of underwater acoustic countermeasures was used to test the rationality and feasibility of the model. The results showed that this model is an effective way to solve the challenge of evaluating the effectiveness of non-offensive weapons under single working phase.

The Syntax of Lattice-Valued Propositional Logic System lp(X)

Lattice-valued logic plays an important role in multi-valued logic systems. A lattice valued logic system lp(X) is constructed. The syntax of lp(X) is discussed. It may be more convenient in application and study especially in the case that the valuation domain is finite lattice implication algebra.