This chapter reviews the key academic research on data quality (DQ) and Information Quality (IQ) (used interchangeably in this chapter) in asset management, combines this with the current DQ problems faced by a
Effective conservation requires understanding the behavior of the targeted species. However, some species can be difficult to observe in the wild, which is why GPS collars and other telemetry devices can be used to “observe” these animals remotely. Combined with classification models, data collected...
Section 4 discusses the findings in the context of existing literature. Finally, Sect. 5 concludes with key insights, limitations, and recommendations for future research. Methods Data source and study design This study utilized longitudinal data from Ethiopia's Young Lives of Young cohort (YLCS),...
Learning from noisy data is a challenging task for data mining research. In this paper, we argue that for noisy data both global bagging strategy and local bagging strategy su er from their own inherent disadvantages and thus cannot form accurate prediction models. Consequently, we present a ...
The Smart Oil Sensor is a fully embedded device supporting signal generation and data acquisition, processing of measured signals, automatic classification of oil state, and multiple communications protocols. This allows the sensor to operate autonomously, identifying changes in fluid quality state...
12Though the data collected (and used) for Concluding remarks and research directions In this paper we have described our approach to Web Labour Market Intelligence along with three real-life application scenarios, focusing on the realisation of a machine learning model for classifying job vacancies....
This paper proposes a new approach based on the Kullback-Leibler data for classifying inspectors by panel tests. A method of deciding the same size in the test inspection lot with given risks is also suggested. The recommended procedure is simple, practical and relatively effective.doi:10.1080/...
Statistical methods enable long-term, extensive research and can handle large volumes of data, making them the most effective tools for studying crop growth responses in the context of historical climate change (von Bloh et al., 2023, Srivastava et al., 2022). The current methods and standards...
methodology, including data preprocessing, model development, and evaluation metrics. Section 3 presents the results and analysis. Section 4 discusses the findings in the context of existing literature. Finally, Sect. 5 concludes with key insights, limitations, and recommendations for future research. ...
This research is supported by NSF 60373108. Preview Unable to display preview.Download preview PDF. References Chu, F., Zaniolo, C.: Fast and Light Boosting for Adaptive Mining of Data Streams. In: Dai, H., Srikant, R., Zhang, C. (eds.) PAKDD 2004. LNCS (LNAI), vol. 3056, Springe...