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Proposal - start [kondor.etf.rs]

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Success criteria:<br />

• Opinion of beneficiaries on the need for the generated applications, based on their<br />

knowledge about where the major unknowns are<br />

• Opinion of beneficiaries about the functionalities provided<br />

• Opinion of beneficiaries about optimal values of paramete<strong>rs</strong> involved.<br />

Objective 2: To develop the system architecture, to determine the functionalities of all<br />

building blocks, and to develop hardware (HW), communications, and software (SW)<br />

requirements.<br />

All details related to hardware, software, and communications have to be developed. Software<br />

details include issues like data mining, semantic web, and concept modelling. Details imply<br />

algorithm, procedures, and the operating system. The suggested DiaMus HW module will<br />

acquire various physical quantities using remote senso<strong>rs</strong>. The interpretation of acquired data<br />

is a demanding task, which requires a skilled expert.<br />

The main objective is to develop a system (software platform) for automatic signal<br />

processing, pattern recognition and final interpretation of processed data. SW platform is<br />

determined by the data acquisition process, mode of communication with HW module and<br />

methods used for signal processing and data interpretation. On that basis a suitable data<br />

model, GUI, report contents and views will be specified.<br />

All measurements will be performed in controlled laboratory conditions that will enable the<br />

construction of the knowledge database.<br />

Success criteria:<br />

• Potential speed of processing and communications,<br />

• Software and hardware architecture which permits easy expandability<br />

• Compatibility with existing platforms<br />

Objective 3: Adding intelligence to the system (for all six types of AW, for a relatively<br />

large number of application scenario, to define CSP and EAP paramete<strong>rs</strong>, and to<br />

develop related KEP procedures, appropriate CEA algorithms, and business-oriented<br />

RRG generato<strong>rs</strong>)<br />

For all use cases mentioned, specific algorithms, procedures, and operating system routines<br />

will be defined, to incorporate elements of artificial intelligence (AI), using the concept<br />

modelling (CM) approach (coauthored by the membe<strong>rs</strong> of this consortium, A Survey of<br />

Concept Modelling, submitted to IEEE Computer, 2009, and given in Appendix 4). For all of<br />

them, optimal values of related paramete<strong>rs</strong> will be determined and built into the algorithms,

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