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OHSUMED-CA-3187-1L primary and secondary data sets (k = 2,339)

Primary Data And Secondary Data Examples

Primary Data And Secondary Data Examples

... other primary secondary examples of the workstations in their product or a ...of primary and children are a discussion with another purpose like the definition of the ...to data ...
Secondary uses of clinical data in primary care

Secondary uses of clinical data in primary care

... management The Association of American Medical Colleges (AAMC) sent out a request for collaboration among academic medical centres. The requests focused on chronic diseases such as diabetes, asthma and osteoarthritis. ...

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primary and secondary processes, formation of H 2 S,

primary and secondary processes, formation of H 2 S,

... iii) Stability of photoproduct 10 Product 10 was produced by reduction of peptide 1 with DTT and purified by HPLC. 1 In a first experiment, peptide 10 was incubated in air-saturated solution at 40 o C overnight at either ...

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Transparent Practices: Primary and Secondary Data in Business Ethics Dissertations

Transparent Practices: Primary and Secondary Data in Business Ethics Dissertations

... other secondary data to, among other things, reduce the cost (monetary and political) of collecting primary data, and enhance (or refute) the conclu- sions derived from primary ...

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Secondary headaches: secondary or still primary?

Secondary headaches: secondary or still primary?

... The IHS defines post-craniotomy headache (ICHD-II 5.7) as (i) occurring in the area of the surgery and (ii) devel- oping within 7 days after craniotomy, which was per- formed, for non-traumatic head pathology. Its ...

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Novel Techniques for Processing Unstructured Data Sets Roger Chamberlain Ron K. Cytron

Novel Techniques for Processing Unstructured Data Sets Roger Chamberlain Ron K. Cytron

... Primary Data Figure 8. Data flow diagram. The primary data store and the semantic annotation store are both (at their core) file systems that are retained on sets of coordinated ...

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Bridging the Business Data Divide: Insights into Primary and Secondary Data Use by Business Researchers

Bridging the Business Data Divide: Insights into Primary and Secondary Data Use by Business Researchers

... and data specialists who develop data collections to support academic programs in their institutions will need to work closely with disciplinary faculty in accounting, finance, or other subfields that rely ...

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Tools and Data. for School Self-evaluation. For Secondary, Primary and Special Schools

Tools and Data. for School Self-evaluation. For Secondary, Primary and Special Schools

... and data in support of schools’ self-evaluation work: The evaluation tools and data are developed according to the PI ...and data with flexibility to align with their own SSE mechanism and ...

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From interval-valued data to general type-2 fuzzy sets

From interval-valued data to general type-2 fuzzy sets

... T1 sets to produce a zGT2 FS that represents the inter-expert uncertainty as detailed in Section ...the secondary membership domain is divided into four levels, one for each level of agreement between the ...

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From interval valued data to general type 2 fuzzy sets

From interval valued data to general type 2 fuzzy sets

... T1 sets to produce a zGT2 FS that represents the inter-expert uncertainty as detailed in Section ...the secondary membership domain is divided into four levels, one for each level of agreement between the ...

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Calcium (Ca 2+ ) is a ubiquitous primary

Calcium (Ca 2+ ) is a ubiquitous primary

... (Ca 2+ ) signaling is an essential process in all cells that is maintained by a plethora of channels, pumps, transporters, receptors, and intracellular Ca 2+ sequestering ...cytosolic ...

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A hybrid algorithm for k-medoid clustering of large data sets

A hybrid algorithm for k-medoid clustering of large data sets

... Unlike some other k-medoid clustering algorithms which typically have time complexity of O(nz) per iteration, our heuristic only requires O(ipn), where i is the iterat[r] ...

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Analysis of K Mean Clustering For Various Data Sets In MATLAB

Analysis of K Mean Clustering For Various Data Sets In MATLAB

... the data. These are some data mining techniques related to classification, clustering, and association ...rating K-minerals are a specific way of cluster observations. "K" indicates the number ...

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Privacy-Preserving k-NN for Small and Large Data Sets

Privacy-Preserving k-NN for Small and Large Data Sets

... in k- NN queries to enable clustering, classification and outlier- detection ...preserving k-NN are costly and can only be realistically ap- plied to small data ...for k-NN queries queries for ...

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SAFETY DATA SHEET 1L SUPER TOILET CLEANER

SAFETY DATA SHEET 1L SUPER TOILET CLEANER

... SECTION 7: HANDLING AND STORAGE 7.1. Precautions for safe handling Provide good ventilation. Avoid contact with skin and eyes. Wear protective clothing as described in Section 8 of this safety data sheet. Good ...

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Completely separating systems of k-sets for  k −1

Completely separating systems of k-sets for k −1

... Assume that A shares 3-points with another full row, say Z 1 , which contains the 3-points f ghij. There is one way to completely separate these in four other blocks. There must be at least two other distinct 3-points in ...

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Join and Meet Operations for Type-2 Fuzzy Sets with Nonconvex Secondary Memberships

Join and Meet Operations for Type-2 Fuzzy Sets with Nonconvex Secondary Memberships

... fuzzy sets with arbitrary secondary memberships, which can be non-convex and/or non-normal type-1 fuzzy ...fuzzy sets presented in [1], where the secondary grades can be ...fuzzy sets ...

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Clustering for binary data sets by using genetic algorithm incremental K means

Clustering for binary data sets by using genetic algorithm incremental K means

... of data that were collected by individuals, organizations or either firms has triggered the initiative to process and analyse this type of ...clusters, K maybe known or ...

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Extensions to the k-means Algorithm for Clustering Large Data Sets with Categorical Values

Extensions to the k-means Algorithm for Clustering Large Data Sets with Categorical Values

... the k-means paradigm to cluster data having categorical values. The k-modes algorithm (Huang, 1997b) extends the k-means paradigm to cluster categorical data by using (1) a simple ...

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Modified global k-means algorithm for clustering in gene expression data sets

Modified global k-means algorithm for clustering in gene expression data sets

... expression data sets. Clustering in gene expression data sets is a challenging ...problems. k-means algorithm and its different variations are among those algorithms which still ...

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