The exponential increase of availability of digital data and the necessity to process it in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it. Traditionally data mining has used a data warehousing model of gathering all data into a central site, and then running an algorithm upon that data. Such a centralized approach is fundamenta...

Distributed simulation is an enabling concept to support the networked interaction of models and real world elements that are geographically distributed. This technology has brought a new set of challenging problems to solve, such as Data Distribution Management (DDM). The aim of DDM is to limit and control the volume of the data exchanged during a distributed simulation, and reduce the process...

Human dental pulp cells have been known to have the stem cell features such as self-renewal and multipotency. These cells are differentiated into hard tissue by addition of proper cytokines and biomaterials. Hydroxyapatite-tricalcium phosphates (HA-TCPs) are essential components of hard tissue and generally used as a biocompatible material in tissue engineering of bone. Demineralized dentin mat...

BACKGROUND Following the 1988 World Health Assembly resolution to eradicate polio, the government of Nigeria, with support from partners, has been implementing several rounds of supplementary immunization activities (SIAs) each year. In addition to the technical requirements, the success of the polio eradication initiative depends on timely provision of adequate financial resources. Disbursemen...

This paper considers some permutation flow shop scheduling problems with a learning effect on no-idle dominant machines. The objective is to minimize maximum completion time. This objective is considered under following dominant machines constraint: idm, ddm, idm–ddm and ddm–idm. We present a polynomial-time solution algorithm for each of the above cases. 2006 Elsevier Inc. All rights reserved.

OBJECTIVE The aim of this manuscript is to provide a review of contemporary research and applications on dynamic decision making (DDM). BACKGROUND Since early DDM studies, there has been little systematic progress in understanding decision making in complex, dynamic systems. Our review contributes to better understanding of decision making processes in dynamic tasks. METHOD We discuss new r...

11-Deoxy-16,16-dimethyl PGE(2) (DDM-PGE(2)) protects renal proximal tubule epithelial cells (LLC-PK(1)) against the toxicity induced by 2,3,5-tris(glutathion-S-yl)hydroquinone (TGHQ), a potent nephrotoxic and nephrocarcinogenic metabolite of hydroquinone. We have now determined the ability of DDM-PGE(2) to protect against other renal toxicants and report that DDM-PGE(2) only protects against on...

Distributed data mining (DDM) which often utilizes autonomous agents is a process to extract globally interesting associations, classifiers, clusters, and other patterns from distributed data. As datasets double in size every year, moving the data repeatedly to distant CPUs brings about high communication cost. In this paper, data cloud is utilized to implement DDM in order to move the data rat...

Driving Decision-making Mechanism (DDM) is identified as the key technology to ensure the driving safety of autonomous vehicle, which is mainly influenced by vehicle states and road conditions. However, previous studies have seldom considered road conditions and their coupled effects on driving decisions. Therefore, road conditions are introduced into DDM in this paper, and are based on a Suppo...