Vol. 1 No. 1 (2007)

Rural Next Generation Networks (R-NGN) technology allows Internet protocol (IP) based systems to be used in rural areas. This paper reports a testbed of R-NGN that uses low cost Ethernet radio links, combined with media gateways and a softswitch. The network consists of point-to-point IP Ethernet 2.4 GHz wireless link, IP switches and gateways in each community, standard copper wires and telephone sets for users. It uses low power consumption, and suitable for low density users. This combination allows low cost systems as well as multiservices (voice, data, and multimedia) for rural…

A new approach for detecting faces in a digital image with unconstrained background has been developed. The approach is composed of three phases: segmentation phase, filtering phase and localization phase. In the segmentation phase, we utilized both training and non-training methods, which are implemented in user selectable color space. In the filtering phase, Minkowski addition-based objects removal has been used for image cleaning. In the last phase, an image processing method and a data mining method are employed for grouping and localizing objects, combined with geometric-based image…

There are two categories of well-known approach (as basic principle of classification process) for learning structure of Bayesian Network (BN) in data mining (DM): scoring-based and constraint-based algorithms. Inspired by those approaches, we present a new CB* algorithm that is developed by considering four related algorithms: K2, PC, CB, and BC. The improvement obtained by our algorithm is derived from the strength of its primitives in the process of learning structure of BN. Specifically, CB* algorithm is appropriate for incomplete databases (having missing value), and without any prior…

Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of data, computational and I/O cost. Additionally, the recursive mining process to mine these structures is also too voracious in memory resources. In this paper, we describe a more efficient algorithm for mining complete frequent itemsets from transactional databases. The suggested algorithm is partially based on FP-tree hypothesis and extracts…

Neuro-fuzzy system has been shown to provide a good performance on chromosome classification but does not offer a simple method to obtain the accurate parameter values required to yield the best recognition rate. This paper presents a neuro-fuzzy system where its parameters can be automatically adjusted using genetic algorithms. The approach combines the advantages of fuzzy logic theory, neural networks, and genetic algorithms. The structure consists of a four layer feed-forward neural network that uses a GBell membership function as the output function. The proposed methodology has been…