Design of agile supply chain assessment model and its case study in an Indian automotive components manufacturing organization

Agile Manufacturing (AM) paradigm is fast instilled in modern organizations. AM enables an organization to evolve products and services quickly and economically in response to the customers’ dynamic demands. The effectiveness of AM is largely determined by the performance of Agile Supply Chains (ASC). In order to assess their performance, an ASC assessment model was reported in this research paper. This model is encompassed with agile supply chain attributes whose performance levels need to be determined for assessing the overall ASC performance of the organization. The computation was performed using fuzzy logic approach. The working of this model was examined by conducting a case study in an Indian automotive components manufacturing organization. The experience gained by conducting this case study favored the use of a computerized system which will ensure accuracy of computations involving fuzzy logic.     

Review of coupling methods for non-matching meshes

Domain decomposition is nowadays a common way to speed up complex computations. However, the discrete meshes used in the different domains do not have to match at their common interface, especially when different physical fields are involved such as in fluid-structure interaction computations. Exchange of information over this interface is therefore no longer trivial. In this paper six methods that can deal with the information transfer between non-matching meshes in fluid-structure interaction computations are compared for different criteria. This is done for analytical test cases as well as a quasi-1D fluid-structure interaction problem. Two methods based on radial basis functions, one with compact support and one using thin plate splines, are favoured over the other methods because of their high accuracy and efficiency.     

A way to improve an architecture of neural network classifier for remote sensing applications

Recent results in neural network research have demonstrated their utility in a variety of application areas. Neural networks are able to achieve a very high performance, and classification accuracy in real world applications such as handwritten character recognition, remote sensing images, vision, robotic. Network performance greatly depends not only on the input/output data, but also on its architecture. Most of neural network applications have been developed using anad hoc approach resulting in poor efficiency and performance. In this paper, a development method of neural network applications is presented, and illustrated with a neural classifier of remote sensing images. It is shown how to create in an iterative way a neural classifier architecture, and how to refine a network organization using performance evaluation criteria.     

多解析度自适应零块判决算法

在视频会议等应用中,视频编码的速度是保证系统实时性的关键.为了减小视频编码的运算量并提高系统的整体性能,提出了多解析度的自适应零块发现判决算法.多解析度通过对图像的子采样从而大幅度降低了搜索最佳匹配块的次数;而自适应的零块判决算法使得运动搜索速度收敛的更快,在不影响图像质量的前提下提高了编码的效率,并且减少了后续模块(DCT、量化等)所占用的时间.利用H.263算法进行了测试,结果显示在图像主客观质量基本不变的前提下,编码时间最多减少了近40%.     

基于结构网格的高超声速流动大规模并行数值模拟研究

本文采用MPI消息传递模式自主开发出适用于高超声速流动数值模拟的并行计算软件,该软件以三维Navier-Stokes方程为基本控制方程来求解层流问题,应用基于结构网格的有限体积法对计算域进行离散,采用AUSMPW+格式求解对流通量,利用MUSCL插值方法获得高阶精度,时间格式上采用LU-SGS方法进行时间迭代以加快求解定常流动的收敛过程。在高性能计算机上针对不同高超声速流动进行大规模并行计算的结果表明,所开发的CFD并行计算软件具有较高的并行计算效率,为高超声速飞行器气动力/热的准确预测提供了高效工具。     

Intervening variables and constraint approximations in safety index and failure probability calculations

The emphasis of this paper is on developing suitable intervening variables and constraint approximations for structural reliability analysis. Traditionally, these procedures are used in structural optimization, whereas this research work adopts these concepts to safety index and failure probability computations. The use of these concepts enables the development of an efficient and stable iteration algorithm for identifying the most probable failure points (MPPs) of the limit state functions. An approximate second-order failure probability is calculated at this MPP with no extra computations of the limit state function and gradients. The efficiency and accuracy of the proposed algorithm are demonstrated by several examples with highly nonlinear, complex, explicit/implicit performance functions.     

Role of involutive criteria in computing Boolean Gröbner bases

In this paper, effectiveness of using four criteria in an involutive algorithm based on the Pommaret division for construction of Boolean Gröbner bases is studied. One of the results of this study is the observation that the role of the criteria in computations in Boolean rings is much less than that in computations in an ordinary ring of polynomials over the field of integers. Another conclusion of this study is that the efficiency of the second and/or third criteria is higher than that of the two others.     

The choice of a method for processing the matrix of paired comparisons according to simplicity and accuracy Criteria

Using simulation, the accuracy of computations of the components of an eigenvector of the matrix of paired comparisons 3 × 3 is analyzed by different approximate methods. Their complexities are estimated. An efficient method for processing matrices of paired comparisons is chosen according to the simplicity and accuracy criteria.     

An importance learning method for non-probabilistic reliability analysis and optimization

With the time-consuming computations incurred by nested double-loop strategy and multiple performance functions, the enhancement of computational efficiency for the non-probabilistic reliability estimation and optimization is a challenging problem in the assessment of structural safety. In this study, a novel importance learning method (ILM) is proposed on the basis of active learning technique using Kriging metamodel, which builds the Kriging model accurately and efficiently by considering the influence of the most concerned point. To further accelerate the convergence rate of non-probabilistic reliability analysis, a new stopping criterion is constructed to ensure accuracy of the Kriging model. For solving the non-probabilistic reliability-based design optimization (NRBDO) problems with multiple non-probabilistic constraints, a new active learning function is further developed based upon the ILM for dealing with this problem efficiently. The proposed ILM is verified by two non-probabilistic reliability estimation examples and three NRBDO examples. Comparing with the existing active learning methods, the optimal results calculated by the proposed ILM show high performance in terms of efficiency and accuracy.

     

基于BP-NN和遗传算法的高速公路交通量预测

高速公路交通量预测对于高速公路建设和管理具有重要的指导作用,针对传统预测方法准确性低、预测时间长等问题,提出了将BP神经网络和遗传算法有机结合起来的遗传—神经网络预测模型,并且在实现过程中通过对两种算法的改进,进一步提高预测的效率和准确性,最终通过实验数据验证了该算法具有优良性能。     

Relaxing instance boundaries for the search of splitting points of numerical attributes in classification trees

We propose a simple heuristic partition method (HPM) of classification tree to improve efficiency in the search for splitting points of numerical attributes. The proposal is motivated by the idea that the selection process of candidates in the splitting point selection can be made more flexible as to achieve a faster computation while retaining classification accuracy. We compare the performance of the HPM against Fayyad’s method, as the latter is the improved version of the standard C4.5 algorithm on the search of splitting points. We demonstrate that HPM is more efficient, in some cases by as much as 50%, while producing essentially the same classification for six different data sets. Our result supports the relaxation of instance boundaries (RIB) as a valid approach that can be explored to achieve more efficient computations.     

Pipelined architecture for real-time cost-optimized extraction of visual primitives based on FPGAs

This paper presents an architecture for the extraction of visual primitives on chip: energy, orientation, disparity, and optical flow. This cost-optimized architecture processes in real time high-resolution images for real-life applications. In fact, we present a versatile architecture that may be customized for different performance requirements depending on the target application. In this case, dedicated hardware and its potential on-chip implementation on FPGA devices become an efficient solution. We have developed a multi-scale approach for the computation of the gradient-based primitives. Gradient-based methods are very popular in the literature because they provide a very competitive accuracy vs. efficiency trade-off. The hardware implementation of the system is performed using superscalar fine-grain pipelines to exploit the maximum degree of parallelism provided by the FPGA. The system reaches 350 and 270 VGA frames per second (fps) for the disparity and optical flow computations respectively in their mono-scale version and up to 32 fps for the multi-scale scheme extracting all the described features in parallel. In this work we also analyze the performance in accuracy and hardware resources of the proposed implementation.     

High-Resolution Finite Volume Methods on Unstructured Grids for Turbulence and Aeroacoustics

In this paper we focus on the application of a higher-order finite volume method for the resolution of Computational Aeroacoustics problems. In particular, we present the application of a finite volume method based in Moving Least Squares approximations in the context of a hybrid approach for low Mach number flows. In this case, the acoustic and aerodynamic fields can be computed separately. We focus on two kinds of computations: turbulent flow and aeroacoustics in complex geometries. Both fields require very accurate methods to capture the fine features of the flow, small scales in the case of turbulent flows and very low-amplitude acoustic waves in the case of aeroacoustics. On the other hand, the use of unstructured grids is interesting for real engineering applications, but unfortunately, the accuracy and efficiency of the numerical methods developed for unstructured grids is far to reach the performance of those methods developed for structured grids. In this context, we propose the FV-MLS method as a tool for accurate CAA computations on unstructured grids.     

Performance Criteria for Constrained Nonlinear Programming Codes

A set of performance criteria for evaluating optimization software with respect to efficiency, reliability, and accuracy is presented and discussed. A numerical comparison of five constrained nonlinear programming codes is described, which was carried out in order to test the usefulness and general applicability of the proposed performance criteria. The results of the numerical comparison are discussed, and the proposed criteria are compared to the criteria traditionally used in comparative evaluations of nonlinear programming codes, with particular reference to machine dependence and the applicability to test problems with unknown solutions. A separate small scale computational experiment is described which was carried out specifically to test the machine dependence of the criteria. The observed deficiencies of the proposed new criteria are also discussed.     

Comparison of two algorithms for solving STIFF differential equations

Many algorithms are available for solving differential equations. Of these, two methods—GEAR and STIFF3, which were developed specifically for stiff differential equations, are compared based on their performance on five test problems. The performance criteria are both accuracy of the numerical solution and efficiency of the method. The results indicate that GEAR, although the older of the two methods, is the preferred algorithm, for stiff differential equations.     

Design, Analysis and Performance Evaluation of Group Key Establishment in Wireless Sensor Networks

Wireless sensor networks are comprised of a vast number of ultra-small autonomous computing, communication and sensing devices, with restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Such networks can be very useful in practice, e.g. in the local monitoring of ambient conditions and reporting them to a control center. In this paper we propose a new lightweight, distributed group key establishment protocol suitable for such energy constrained networks. Our approach basically trade-offs complex message exchanges by performing some amount of additional local computations. The extra computations are simple for the devices to implement and are evenly distributed across the participants of the network leading to good energy balance. We evaluate the performance our protocol in comparison to existing group key establishment protocols both in simulated and real environments. The intractability of all protocols is based on the Diffie-Hellman problem and we used its elliptic curve analog in our experiments. Our findings basically indicate the feasibility of implementing our protocol in real sensor network devices and highlight the advantages and disadvantages of each approach given the available technology and the corresponding efficiency (energy, time) criteria.     

Locating circuit bodies and documenting routing graphs

The paper considers the organization of correct iterative computations in problem-oriented systems with graph models of the application domain. The efficiency of the proposed method is confirmed by experimental data.Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 21–31, September–October, 1991.     

Performance modeling of pipelined linear algebra architectures on FPGAs

The potential design space of FPGA accelerators is very large. The factors that define performance of a particular implementation include the architecture design, number of pipelines, and memory bandwidth. In this paper we present a mathematical model that, based on these factors, calculates the computation time of pipelined FPGA accelerators and allows for quick exploration of the design space without any implementation or simulation. We evaluate the model and its ability to identify design bottlenecks and improve performance. Being the core of many compute-intensive applications, linear algebra computations are the main contributors to their total execution time. Hence, five relevant linear algebra computations are selected, analyzed, and the accuracy of the model is validated against implemented designs.     

Intellectual capital evaluation using fuzzy cognitive maps: A scenario-based development planning

Evaluation of Intellectual Capital (IC) is a vital phenomenon for various organizations in order to determine the value of the organization, to improve the control system and to assist strategic planning and decision-making. This study presents a new model in which the interactions between the IC components are considered in the evaluation and development planning process. This, in turn, would enhance the accuracy in evaluating IC and would aid managers in establishing a development plan for IC. In other words, this study tackles the common problem of the inner correlation between IC components by using fuzzy logic, which bears concrete results. The procedure starts with studying numerous criteria proposed for measuring IC drawn from the literature and selecting the most frequently used ones. Then, the selected criteria are refined through a questionnaire based on their relevance to the organization in which we want to evaluate IC. Interactions among IC criteria are captured with the help of Fuzzy Cognitive Maps (FCMs). The present study is the first that uses FCMs method for evaluating IC. After the influence of each criterion over the others is identified, several scenarios are developed and analyzed in order to realize their efficiency and effectiveness for IC development. The results reveal that improving IC criteria with maximum influence over others, does not necessarily lead to the development of IC and investigations are required to establish the development plan.     

Information-theoretical secure verifiable secret sharing with vector space access structures over bilinear groups and its applications

As a basic tool, Verifiable Secret Sharing (VSS) has wide applications in distributed cryptosystems as well as secure multi-party computations. A number of VSS schemes for sharing a secret from a finite field, both on threshold access structures and on general access structures, have been available. In this paper, we investigate the verifiably sharing of a secret that is a random element from a bilinear group on vector space access structures. For this purpose, we present an information-theoretical secure VSS scheme, and then convert it to a modified one with improved efficiency. The performance and the security of the proposed schemes are analyzed in detail. Two examples are given to illustrate the applications of our proposed VSS schemes. One is the secure sharing of an organization’s private key in Boneh and Franklin’s identity-based encryption system, and the other is the distributed key generation and distributed decryption for bilinear ElGamal encryption system, both with vector space access structures.