In this paper, we propose an arc-search corrector-predictor interior-point method for solving $P_*(kappa)$-linear complementarity problems. The proposed algorithm searches the optimizers along an ellipse that is an approximation of the central path. The algorithm generates a sequence of iterates in the wide neighborhood of central path introduced by Ai and Zhang. The algorithm does not de...

We developed the Nested Relational Sequence Database System (NRSD System), which is built upon the Nested Relational Sequence Model (NRSM). The NRSM eliminates a substantial amount of redundancy embedded in XML documents and preserves the order of XML data. In this paper, we demonstrate that the storing and querying of XML data are desirable over an NRS relation, which we incorporate an index s...

With the rapid increase in the size of genome sequence databases, the multiple sequence alignment problem is increasingly important and often requires the alignment of a large number of sequences. Beginning in 1975, many heuristic algorithms have been created to improve the speed of computation and the quality of alignment. We introduce a novel approach that is fundamentally distinct from all c...

We present the path sequence storage model, a new logical model for storing XML documents. This model partitions XML data and content according to the document paths; and uses ordered sequences as logical and physical structures. Besides being very compact, this model has a strong impact on the efficiency of XQuery evaluation. Its main advantages are: fast and selective data access plans; intel...

Uncovering problem is one of three main problems of hidden Markov model (HMM), which aims to find out optimal state sequence that is most likely to produce a given observation sequence. Although Viterbi is the best algorithm to solve uncovering problem, I introduce a new viewpoint of how to solve HMM uncovering problem. The proposed algorithm is called longest-path algorithm in which the uncove...