Dynamic Pricing for Cloud Service Negotiation

Big players in cloud service market like Microsoft, Amazon and Google keeps changing their service price. Increasing cloud service offerings have motivated cloud providers to develop cloud service marketplaces such as AWS, Google Apps and CloudSurfing. However, these marketplaces lack dynamic pricing mechanism. The idea of dynamic pricing in the cloud services market has emerged…

Protocols for agent-based autonomous negotiations: A review

Autonomous negotiation needs certain protocol, a set of rules that defines the interaction boundaries between negotiating agents. This paper aims to allow readers, particularly agent-based autonomous negotiation designers to understand and differentiate various agent-based negotiation protocols. This paper reviews one-to-one, concurrent one-to-many and many-to-many negotiation protocols that are divided into general, Alternative-offers and auctions-based protocols.…

Myhealthykids: Intelligent obesity intervention system for primary school children

Sedentary lifestyles and unhealthy diet are the main reasons of childhood obesity. This paper presents MyHealthyKids: Intelligent Web-mobile Children Obesity Intervention System for Primary School to manage and reduce the problems. The main objective of the system is to prevent and to reduce childhood obesity cases that are currently increasing in primary schools in Malaysia.…

A hybrid approach using Naïve Bayes and Genetic Algorithm for childhood obesity prediction

Naïve Bayes is a data mining technique that has been used by many researchers for predictions in various domains. This paper presents a framework of a hybrid approach using Naïve Bayes for prediction and Genetic Algorithm for parameter optimization. This framework is a solution applied to the childhood obesity prediction problem that has a small…

Hybrid Approaches Using Decision Tree, Naive Bayes, Means and Euclidean Distances for Childhood Obesity Prediction

Even by using the data mining, many weaknesses still existed in childhood obesity prediction and it is still far from achieving perfect prediction. This paper studies previous steps involved in childhood obesity prediction using different data mining techniques and proposed hybrid approaches to improve the accuracy of the prediction. The steps taken in this study…

Parameter Identification and Selection for Childhood Obesity Prediction Using Data Mining

The accurate identification and selection of useful parameters for childhood obesity prediction are very important. This study aims to identify childhood obesity prediction parameters for children in Malaysia, and presents the methods used to identify and select the parameters from the children's attributes, lifestyle, family, and environment. The study comprises four stages: risk factor review,…

Implementation of Hybrid Naive Bayesian-Decision Tree for Childhood Obesity Predictions

Data mining techniques have been used by past researchers to predict childhood obesity, but the results are still inadequate. The purposes of this paper are to use significant parameters for childhood obesity prediction, to study suitable data mining techniques for childhood obesity predictions, and to propose a hybrid data mining technique. The proposed technique is…