Geographic data are characterized by huge volumes, lack of standards, multiplicity of data sources, multiscale requirements, and variability in time. These characteristics make geographic information complex and uncertain. At the same time, the important growth of the quantity of data manipulated and the necessity to make rapid decisions imposed the appearance and the great progress of new tool...

traditional leveraging statistical methods for analyzing today’s large volumes of spatial data have high computational burdens. to eliminate the deficiency, relatively modern data mining techniques have been recently applied in different spatial analysis tasks with the purpose of autonomous knowledge extraction from high-volume spatial data. fortunately, geospatial data is considered a proper s...

This paper proposes a new method for geographical simulation by applying data mining techniques to cellular automata. CA has strong capabilities in simulating complex systems. The core of CA is how to define transition rules. There are no good methods for defining these transition rules. They are usually defined by using heuristic methods and thus subject to uncertainties. Mathematical equation...

In this paper it is tested which of the various alternative approaches for constructing knowledge spillover pools suggested in existing literature measures the extent to which a rm can costlessly receive external knowledge best. Since knowledge spillovers are unmeasurable, a `goodness of t' measure is constructed using innovation survey data. It turns out that measures of the uncentered correla...

the rapid growing of information technology (it) motivates and makes competitive advantages in health care industry. nowadays, many hospitals try to build a successful customer relationship management (crm) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. many hospitals have large data warehouses containing customer ...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers need...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers nee...

ontology is a requirement engineering product and the key to knowledge discovery. it includes the terminology to describe a set of facts, assumptions, and relations with which the detailed meanings of vocabularies among communities can be determined. this is a qualitative content analysis research. this study has made use of ontology for the first time to discover the knowledge of vaccine in ir...

Despite enormous efforts in quantification, our understanding of many of the Earth’s systems remains non-axiomatic; the systems are ‘open’ and consequently it is not possible to deduce all outcomes from known laws. Science must therefore adopt a manner that encourages the creation or uncovering of new knowledge (Baker, 1999; Takatsuka & Gahegan, 2001). For this reason aloneand completely uncou...

background and objectives: arteriovenous fistula is a popular vascular access method for surgical treatmentof hemodialysis patients. the method, however, is associated with a high rate of early failure varying in the range of 20-60%. predicting early arteriovenous fistula failure and its risk factors can help reduce its incidence, its hospitalization rate, and associated costs. in this study, w...