Machine Learning on Minimizing Irrigation Water for Lawns

Water front study for spot irrigation

Alfalfa Sprout Irrigation Water

Salmonella has been associated with a number of recent outbreaks of foodborne illness involving sprouted seeds. In this research, we addressed the design of sensor components intended for use in a fully automated detection system. A real−time PCR assay was developed to detect Salmonella in sprout irrigation water. Specific detection was achieved by targeting a region of the invasion gene, invA....

A Hybrid Machine Learning Method for Intrusion Detection

Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...

Machine learning algorithms for time series in financial markets

This research is related to the usefulness of different machine learning methods in forecasting time series on financial markets. The main issue in this field is that economic managers and scientific society are still longing for more accurate forecasting algorithms. Fulfilling this request leads to an increase in forecasting quality and, therefore, more profitability and efficiency. In this pa...

Deficit irrigation for reducing agricultural water use.

At present and more so in the future, irrigated agriculture will take place under water scarcity. Insufficient water supply for irrigation will be the norm rather than the exception, and irrigation management will shift from emphasizing production per unit area towards maximizing the production per unit of water consumed, the water productivity. To cope with scarce supplies, deficit irrigation,...