Beyond being facilitators of human interactions, social networks have become an interesting target of research, providing rich information for studying and modeling user’s behavior. Identification of personality-related indicators encrypted in Facebook profiles and activities are of special concern in our current research efforts. This paper explores the feasibility of modeling user personality...

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored...

This paper proposes an approach to active fault tolerant control (AFTC) of a variable-speed wind turbine subject to actuator faults. The actuator faults in the turbine pitch system and generator system are considered in this work. Takagi-Sugeno (T-S) fuzzy modeling of the combined driver train, pitch and generator systems is proposed to account for nonlinearities in the dynamics. Moving horizon...

OBJECTIVE To increase discriminatory accuracy (DA) for emergency cesarean sections (ECSs). STUDY DESIGN We prospectively collected data on and studied all 6,157 births occurring in 2014 at four public hospitals located in three different autonomous communities of Spain. To identify risk factors (RFs) for ECS, we used likelihood ratios and logistic regression, fitted a classification tree (CTR...

As computational fluid dynamics techniques and tools become widely accepted for realworld practice today, it is intriguing to ask: what areas can it be utilized to its potential in the future. Some promising areas include design optimization and exploration of fluid dynamics phenomena (the concept of numerical wind tunnel), in which both have the common feature where some parameters are varied ...

Predictive data mining is the process of automatically creating a classification model from a set of examples, called the training set, which belongs to a set of classes. Once a model is created, it can be used to automatically predict the class of other unclassified examples. Some datasets encountered in real life applications have skewed class distributions. Many predictive modeling systems a...

Predictive modeling has become a practical research tool in homogeneous catalysis. It can help to pinpoint 'good regions' in the catalyst space, narrowing the search for the optimal catalyst for a given reaction. Just like any other new idea, in silico catalyst optimization is accepted by some researchers and met with skepticism by others. The basic requirements for good predictive models are a...

Lectins are a diverse type of glycoproteins or carbohydrate-binding proteins that have a wide distribution to various species. They can specially identify and exclusively bind to a certain kind of saccharide groups. Cancerlectins are a group of lectins that are closely related to cancer and play a major role in the initiation, survival, growth, metastasis and spread of tumor. Several computatio...

Large-scale data applications are increasingly a part of daily life. For example, the GPS in your phone that can tell you the fastest way to the airport incorporating real-time traffic data, Netflix suggests movies based on your entire viewing history, and the spam filters in email software learn individual spam preferences. Some of these applications rely on methodologies that are more ‘data h...

The success of prediction models for business purposes should not be measured by their accuracy only. Their evaluation should also take into account the higher importance of precise prediction for “valuable” customers. We illustrate this idea through the example of churn modeling in telecommunications, where it is obviously much more important to identify potential churn among valuable customer...