Employing optimized combinations of one-class classifiers for automated currency validation

Automated currency validation requires a decision to be made regarding the authenticity of a banknote presented to the validation system. This decision often has to be made with little or no information regarding the characteristics of possible counterfeits as is the case for issues of new currency. A method for automated currency validation is presented which segments the whole banknote into different regions, builds individual classifiers on each region and then combines a small subset of the region specific classifiers to provide an overall decision. The segmentation and combination of region specific classifiers to provide optimized false positive and false negative rates is achieved by employing a genetic algorithm. Experiments based on high value notes of Sterling currency were carried out to assess the effectiveness of the proposed solution.     

Quadtree-based genetic algorithm and its applications to computer vision

Many computer vision problems can be formulated as optimization problems. Presented in this paper is a new framework based on the quadtree-based genetic algorithm that can be applied to solve many of these problems. The proposed algorithm incorporates the quadtree structure into the conventional genetic algorithm. The solutions of image-related problems are encoded through encoding the corresponding quadtrees, and therefore, the 2D locality within a solution can be preserved. Examples addressed using the proposed framework include image segmentation, stereo vision, and motion estimation. In all cases, encouraging results are obtained.     

GLU♮ embedded in C++: a marriage between multidimensional and object‐oriented programming

The embedding of a small but expressive language of multidimensional functional programming in a well known and widely used language of object‐oriented programming leads to the combination of two radically different programming models. In this paper, we formally define the syntax and semantics of GLU^?, which can be thought of as the multidimensional core of Lucid and GLU, and we describe its implementation as a language embedded in C++. With the aid of a few examples, we argue that the marriage of the two programming models is not only compatible and natural, but also that it produces a new and interesting hybrid language. Copyright © 2004 John Wiley & Sons, Ltd.     

遗传算法在CDMA网络基站分布规划中的应用

CDMA网络的基站分布规划属于多目标组合优化问题，为此在遗传算法的基础上提出了一种基于成本控制的CDMA网络基站分布规划算法。该算法综合考虑了在CDAM网络规划实际工程中的多种规划目标和要求，能够找到符合CDMA网络建设需要的基站分布方案。     

MSP-G320240DBCW-211N大规模点阵式LCD与PIC单片机接口技术

介绍了大规模点阵式液晶显示器MSP-G320240DBCW-211N的特点及其与PIC18F6620单片机的接口技术，提出了应用过程中可能遇到的问题和解决方法．给出相关的C程序设计并在研制的智能光电检测仪器上得以成功地应用。     

建筑工程投标报价优选模型

通过建立区间二次规划数学模型、灰色模型、多目标规划等模型，建立材料价格和用量的选择模型，提供投标单位一种便捷的调整工程造价和控制造价的手段。     

A note on the variance of rank-based selection strategies for genetic algorithms and genetic programming

This paper evaluates different forms of rank-based selection that are used with genetic algorithms and genetic programming. Many types of rank based selection have exactly the same expected value in terms of the sampling rate allocated to each member of the population. However, the variance associated with that sampling rate can vary depending on how selection is implemented. We examine two forms of tournament selection and compare these to linear rank-based selection using an explicit formula. Because selective pressure has a direct impact on population diversity, we also examine the interaction between selective pressure and different mutation strategies.     

Genetic programming of conventional features to detect seizure precursors

This paper presents an application of genetic programming (GP) to optimally select and fuse conventional features (C-features) for the detection of epileptic waveforms within intracranial electroencephalogram (IEEG) recordings that precede seizures, known as seizure precursors. Evidence suggests that seizure precursors may localize regions important to seizure generation on the IEEG and epilepsy treatment. However, current methods to detect epileptic precursors lack a sound approach to automatically select and combine C-features that best distinguish epileptic events from background, relying on visual review predominantly. This work suggests GP as an optimal alternative to create a single feature after evaluating the performance of a binary detector that uses: (1) genetically programmed features; (2) features selected via GP; (3) forward sequentially selected features; and (4) visually selected features. Results demonstrate that a detector with a genetically programmed feature outperforms the other three approaches, achieving over 78.5% positive predictive value, 83.5% sensitivity, and 93% specificity at the 95% level of confidence.     

The Lambda Library: unnamed functions in C++

The Lambda Library (LL) adds a form of lambda functions to C++, which are common in functional programming languages. The LL is implemented as a template library using standard C++; thus no language extensions or preprocessing is required. The LL consists of a rich set of tools for defining unnamed functions. In particular these unnamed functions work seamlessly with the generic algorithms in the C++ Standard Library. The LL offers significant improvements, in terms of generality and ease of use, compared to the current tools in the C++ Standard Library. Copyright © 2003 John Wiley & Sons, Ltd.     

Metric-based reasoning about pseudocode design in the partial metrics system

The goal of the PMS project is to produce an environment in which the intelligent online assessment of the design for large-scale ADA programming projects is provided. The focus is on the representation of knowledge about the design process for an individual module. Changes in pseudocode complexity are measured in terms of partial metrics. These metrics can take the designers inferences about the pseudocode program structure into account when assessing module complexity. Next, a model of the stepwise refinement process is given which demonstrates how pseudocode elaboration decisions can be modelled in partial metric terms. Finally, the decisions associated with each refinement step for 17 example refinements taken from the computer science literature are described using partial metrics.