نتایج جستجو برای: data cleaning
تعداد نتایج: 2424654 فیلتر نتایج به سال:
Fouling is an age-old problem in many process industries. It is responsible for large energy and throughput losses, resulting in financial penalties and negative environmental impact. One effective mitigation strategy is the regular cleaning of fouled heat transfer devices. Optimization tools can be used to schedule the timing of cleaning actions in order to minimize the cost of fouling and imp...
This study compared the efficacy of an antimicrobial mouthrinse (0.12% chlorhexidine gluconate) plus toothbrushing (mouthrinse group), mechanical interdental cleaning plus toothbrushing (mechanical group), and toothbrushing alone (control group), at reducing and preventing interdental gingival inflammation. 92 male subjects were examined for interdental inflammation using the Eastman interdenta...
Biofouling is detrimental to the hydrodynamic performance of ships. In spite of advances in hull coating technology, a ship must usually undergo underwater hull cleaning to remove biofouling during her in-service time. However, some cleaning practices may also lead to decreased lifetime of the fouling-control coating. Therefore, cleaning forces should be minimized, according to the adhesion str...
OBJECTIVE Most reusable biopsy forceps and all of the currently available single-use biopsy forceps do not have a port that allows fluid flow down the inner tubular shaft of the device. Reusable biopsy forceps are widely used and reprocessed in healthcare facilities, and single-use biopsy forceps are reprocessed either in-house (eg, in Canada and Japan) or by third-party reprocessors (eg, in th...
Traditionally, data cleaning has been performed as a pre-processing task: after all data are selected for a study (or application), they are cleaned and loaded into a database or data warehouse. In this paper, we argue that data cleaning should be an integral part of data exploration. Especially for complex, spatio-temporal data, it is only by exploring a dataset that one can discover which con...
Data cleaning is often an important step to ensure that predictive models, such as regression and classification, are not affected by systematic errors such as inconsistent, out-of-date, or outlier data. Identifying dirty data is often a manual and iterative process, and can be challenging on large datasets. However, many data cleaning workflows can introduce subtle biases into the training pro...
Actually the growing volume of data provided by different sources some times may present inconsistencies, the data could be incomplete with lack of values or containing aggregate data, noisy containing errors or outliers, etc. Then data cleaning consist in filling missing values, smooth noisy data, identify or remove outliers and resolve inconsistencies. In more general definition, data cleanin...
In order for an enterprise to gain insight into its internal business and the changing outside environment, it is essential to provide the relevant data for in-depth analysis. Enterprise data is usually scattered across departments and geographic regions, and is often inconsistent. Data scientists spend the majority of their time finding, preparing, integrating, and cleaning relevant data sets....
RATIONALE Cleaning tasks may imply exposure to chemical agents with potential harmful effects to the respiratory system, and increased risk of asthma and respiratory symptoms among professional cleaners and in persons cleaning at home has been reported. The long-term consequences of cleaning agents on respiratory health are, however, not well described. OBJECTIVES This paper aims to investiga...
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