The role of artificial intelligence, knowledge and wisdom in automatic image understanding

In the paper, the roles of intelligence, knowledge, learning and wisdom are discussed in the context of image content understanding. The known model of automatic image understanding is extended by the role of learning. References to example implementations are also given

Finite element model updating using estimation of distribution algorithm

Finite Element (FE) model updating has been attracting research attentions in structural engineering fields for over 20 years. Its immense importance to the design, construction and maintenance of civil and mechanical structures has been highly recognised. However, many sources of uncertainties may affect the updating results. These uncertainties may be caused by FE modelling errors, measurement noises, signal processing techniques, and so on. Therefore, research efforts on model updating have been focusing on tackling with uncertainties for a long time. Recently, a new type of evolutionary algorithms has been developed to address uncertainty problems, known as Estimation of Distribution Algorithms (EDAs). EDAs are evolutionary algorithms based on estimation and sampling from probabilistic models and able to overcome some of the drawbacks exhibited by traditional genetic algorithms (GAs). In this paper, a numerical steel simple beam is constructed in commercial software ANSYS. The various damage scenarios are simulated and EDAs are employed to identify damages via FE model updating process. The results show that the performances of EDAs for model updating are efficient and reliable

A Prototype-Based Modified DBSCAN for Gene Clustering

AbstractIn this paper, we propose, a novel DBSCAN method to cluster the gene expression data. The main problem of DBSCAN is its quadratic computational complexity. We resolve this drawback by using the prototypes produced from a squared error clustering method such as K-means. Then, the DBSCAN technique is applied efficiently using these prototypes. In our algorithm, during the iterations of DBSCAN, if a point from an uncovered prototype is assigned to a cluster, then all the other points of such prototype belongs to the same cluster. We have carried out excessive experiments on various two dimensional artificial and multi-dimensional biological data. The proposed technique is compared with few existing techniques. It is observed that proposed algorithm outperforms the existing methods

Evolutionary Computation for Global Optimization – Current Trends, Journal of Telecommunications and Information Technology, 2011, nr 4

This article comments on the development of Evolutionary Computation (EC) in the field of global optimization. A brief overview of EC fundamentals is provided together with the discussion of issues of parameter settings and adaptation, advances in the development of theory, new ideas emerging in the EC field and growing availability of massively parallel machines

Cryptographic key Generation Using Fingerprint Biometrics

At the present time progress of communications technologies has resulted to post large amounts of digital data in the media shared among the people, this has necessitated the development of cryptographic techniques to be one of the building blocks for the security of the computer, so that became the encryption feature increasingly important to the security of the computer. This paper proposed a method for generating a key using fingerprint features to ensure the security of the system against hackers. This technical consists of two parts the first is the EPROM memory filled with information of fingerprint after processed by the enhancement, binarization and thinning operations and then 512 numeric values has been extracted. The second part is a set of linear shift registers where every movement for system registers is an address in the memory where the dimensions of memory (8x64), the first three registers give the row address while the registers ordered by two to seven give the column address of EPROM array. The strength of the chain of random numbers which produced by making originating from two different worlds linked to the same user, is a goal makes this technique useful for several uses, such as using output as encryption keys, or use it as a digital series for personal definition for security systems

Optimization and implementation of the wavelet based algorithms for embedded biomedical signal processing

Existing biomedical wavelet based applications exceed the computational, memory and consumption resources of low-complexity embedded systems. In order to make such systems capable to use wavelet transforms, optimization and implementation techniques are proposed. The Real Time QRS Detector and De-noising Filter are developed and implemented in 16-bit fixed point microcontroller achieving 800 Hz sampling rate, occupation of less than 500 bytes of data memory, 99.06% detection accuracy, and 1 mW power consumption. By evaluation of the obtained results it is found that the proposed techniques render negligible degradation in detection accuracy of -0.41% and SNR of -2.8%, behind 2-4 times faster calculation, 2 times less memory usage and 5% energy saving. The same approach can be applied with other signals where the embedded implementation of wavelets can be beneficial