Previous research described the use of machine learning algorithms to predict aircraft fuel consumption. This technique, known as Virtual Sensors, models fuel consumption as a function of aircraft Flight Operations Quality Assurance (FOQA) data. FOQA data consist of a large number of measurements that are already recorded by many commercial airlines. The predictive model is used for anomaly det...

Urban water managers rely heavily on forecasts of water consumption to determine management decisions and investment choices. Typical forecasts rely on simple models whose criteria for selection has little to do with their performance in predicting out-ofsample consumption levels. We demonstrate this issue by comparing forecast models selected on the basis of their ability to perform well in-sa...

The implementation of the village community empowerment program around national border areas is faced a unique environment with complex problems. purpose study to highlight and explore supporting inhibiting factors program. type this was descriptive-qualitative. Data were collected through interviews, document searches, observation. data then processed, analysed, concluded. Results showed that ...

Massive upsurge in cloud resource usage stave off service availability resulting into outages, contention, and excessive power-consumption. The existing approaches have addressed this challenge by providing multi-cloud, VM migration, running multiple replicas of each which accounts for high expenses data centre (CDC). In context, a novel Significance Ranking Resource Estimation based High Avail...

The list-ranking problem is considered for parallel computers which communicate through an interconnection network. Each PU holds k nodes of a set of singly linked lists. An easy randomized algorithm gives a considerable improvement over earlier ones. For a large class of networks, the algorithm takes only twice the number of steps required by a k-k routing. The only conditions are that: (1) k ...

Recommender systems have become a vital tool to identify items for users based on personalized preferences. The ranking or item recommendation generates ranked list of the users. Clustering methods offer better scalability than collaborative filtering (CF) since they make predictions within small clusters. major challenges recommender are accuracy and scalability. Traditionally, centralized fra...