Data aggregation

The massively parallel approach adopted in the Connection Machine has been termed data parallel. Whereas a uniprocessor must sequentially step through large amounts of data, a data parallel machine moves processors to the data. Aggregate memory to processor bandwidth in the Connection Machine is more than 700 megabytes per second. 

WASH-1400 is a fundamental document for PRA methodology. The data appendixes contain a great deal of useful information on methods of data assessment. A large number of sources for data are considered, and very general failure rate estimates will produce only gross approximations. Since the advent of data collection schemes across and within plants, the WASH-1400 data are solely useful as a constituent to a data aggregation process or as widely bounded figures that provide a basis for comparison. 

In order to improve the policy relevanee of the results, it is necessary to aggregate the indicators analysed to one final result, e.g. a sustainability index. Data aggregation currently faees the faet that there is no commonly accepted methodology to alleviate the problem of evaluating and summarising the environmental indicator data. 

Data Integration Data Aggregation Data Quality Data Storage/Access... 

Data aggregation over time only for monitoring stations at Tier 1, and data aggregation over all monitoring stations and time within a defined area (groundwater body) at Tier 2. 

Data aggregation over monitoring stations with an associated surface water system. 

It is important to note data aggregation and storage issues because large-scale collaborative efforts require similar nature of databases. 

It was therefore decided to develop a comparative methodology which would circumvent the limitations of other rapid comparative methods and which would enable data aggregation from several studies. Ideally, this method should not require the presentation of an excessive number of samples in each new analysis, which would amount to running the evaluation on the full product set again. Besides, this methodology should be possibly performed by subjects without special training, as in free sorting. 

As PSP was initially imagined as a way to aggregate data from separate evaluations, we conducted a third study in order to assess the feasibility of PSP data aggregation. 

PSP seems to be a promising methodology. For the first time it offers clear perspectives for routine sensory analysis of water samples. PSP methodology yielded promising results and should ultimately enable the sensory characteristics of a given product to be determined as well as limiting the number of samples to taste. In addition, PSP allows data aggregation. 

To better understand the behavior of the above categories and to check the validity of the fleet data aggregation for estimatation of the number of failures, we select three random sample data from the data set and apply the same procedure as discussed earlier. The first random data consists of 26 random units and the second and third consist of 25 and 21 random units, respectively. The behavior of ETNF along with the actual total operational time (with/without censoring age) are plotted in Figures 6, 7, and 8, respectively. Results show similar behavior as in the first case (for analysis of all components, see Fig. 5). 

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