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Day 2 Tue, August 02, 2022, 2022
In this study, the hole cleaning qualities of mud samples formulated with tigernut derivatives – starch and fibre – as additives were determined by adding drill cuttings as impurities and evaluating the Carrying Capacity Index (CCI) as well as ...
D. Jimmy, E. Wami, Michael Ifeanyi Ogba
semanticscholar +1 more source
In this study, the hole cleaning qualities of mud samples formulated with tigernut derivatives – starch and fibre – as additives were determined by adding drill cuttings as impurities and evaluating the Carrying Capacity Index (CCI) as well as ...
D. Jimmy, E. Wami, Michael Ifeanyi Ogba
semanticscholar +1 more source
Data quality and data cleaning
Proceedings of the 2003 ACM SIGMOD international conference on Management of data, 2003Data quality is a serious concern in any data-driven enterprise, often creating misleading findings during data mining, and causing process disruptions in operational databases. The manifestations of data quality problems can be very expensive- "losing" customers, "misplacing" billions of dollars worth of equipment, misallocated resources due to ...
Theodore Johnson, Tamraparni Dasu
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Quality of cleaning quantified
Building and Environment, 1994Abstract Guidelines for evaluating concentration of dust on non-textile furniture and floors, and carpets are suggested, based on a source control approach. They are based on experience from about 5000 single surface dust samples in Scandinavia, mainly from offices. A sampling strategy is formulated, and simple decision rules for compliance are given.
Thomas Schneider +3 more
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Cleaning uncertain data with quality guarantees
Proceedings of the VLDB Endowment, 2008Uncertain or imprecise data are pervasive in applications like location-based services, sensor monitoring, and data collection and integration. For these applications, probabilistic databases can be used to store uncertain data, and querying facilities are provided to yield answers with statistical confidence. Given
Reynold Cheng, Jinchuan Chen, Xike Xie
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Data cleaning and machine learning: a systematic literature review
International Conference on Automated Software Engineering, 2023Machine Learning (ML) is integrated into a growing number of systems for various applications. Because the performance of an ML model is highly dependent on the quality of the data it has been trained on, there is a growing interest in approaches to ...
Pierre-Olivier Côté +4 more
semanticscholar +1 more source
The TQM Magazine, 1991
The author identifies a link between the environment and the wider issue of corporate quality, based on ideas developed within TDG, the parent company for logistics and hire companies (transport companies) around much of the world. Argues that environmental good practice can be built into the activities of a company without additional bureauracracy ...
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The author identifies a link between the environment and the wider issue of corporate quality, based on ideas developed within TDG, the parent company for logistics and hire companies (transport companies) around much of the world. Argues that environmental good practice can be built into the activities of a company without additional bureauracracy ...
openaire +1 more source
Quality Control in Soil Cleaning
1986For quality control of cleaned soil the following points of procedure must be adhered to in the order given: 1. The quality of the bulk of a cleaned soil has to be defined. 2. The type of control procedure has to be laid down. 3. The demands of cleanness to be met by samples (as opposed to the bulk) have to be specified.
P. Defize, P. J. F. Nooijen, R. Bosman
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Data Cleaning for Power Quality Monitoring
2013 Fourth International Conference on Networking and Distributed Computing, 2013Power quality issues are becoming more critical for high-tech enterprises and grid companies. Many power quality monitoring systems are deployed in recent years. Advanced analysis of monitoring data is not widely applied due to the lackness of data management.
Zijing Yang +5 more
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Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning
International Conference on Machine LearningRecent studies show that in supervised fine-tuning (SFT) of large language models (LLMs), data quality matters more than quantity. While most data cleaning methods concentrate on filtering entire samples, the quality of individual tokens within a sample ...
Jinlong Pang +6 more
semanticscholar +1 more source
Optics and lasers in engineering, 2018
Comparing with the trepanning technology, cooling hole could be processed based on the percussion drilling with higher processing efficiency. However, it is widely believed that the ablating precision of hole is lower for percussion drilling than for ...
Wanqin Zhao, Zhishui Yu
semanticscholar +1 more source
Comparing with the trepanning technology, cooling hole could be processed based on the percussion drilling with higher processing efficiency. However, it is widely believed that the ablating precision of hole is lower for percussion drilling than for ...
Wanqin Zhao, Zhishui Yu
semanticscholar +1 more source