thus, demonstrating a high test-retest reliability and the practicality of our craving detection method. In addition, the classification performance was further enhanced by using both datasets of the first and second experiments to train the classifiers, suggesting that an individually customized game craving detection system with high accuracy can...
≃ 3 . 9 c m - 1 ). This study employs physics-based metrics and loss functions to identify promising dimension-reduction techniques and reduce at-sensor radiance reconstruction error. The derived RT model shows an overall RMSE of less than 1 K across reflective to emissive grey-body emissivity profiles.
dataset was used to present these practical tests and their impact on model selection.
activity understanding. A distinctive aspect of this research is the special attention paid to the role of semantics within the robot perception and decision-making processes. The obtained results have improved the robot capabilities in terms of efficiency, autonomy, and usefulness, as reported in our publications.
s t-test). The results also showed that classification results improved with the number of subjects in the training data. With a sample size that approached 1000 subjects, classifications results characterized as area under the receiver operating curve (AUC) approached 1.0, indicating very high sensitivity and specificity.
In recent years, Energy Efficiency (EE) has become a critical design metric for cellular systems. In order to achieve EE, a fine balance between throughput and fairness must also be ensured. To this end, in this paper we have presented various resource block (RB) allocation schemes in relay-assisted Long Term Evolution-Advanced (LTE-A) networks. Dr...
Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate distance measurements. Although promising, UWB devices also suffer from the classic problems found when working in indoor scenarios, especial...
at large.
Subject counting systems are extensively used in ambient intelligence applications, such as smart home, smart building and smart retail scenarios. In this paper, we investigate the problem of transforming an unmodified WiFi radio infrastructure into a flexible sensing system for passive subject counting. We first introduce the multi-dimensional cha...
Analysis of high-dimensional data is a challenge in machine learning and data mining. Feature selection plays an important role in dealing with high-dimensional data for improvement of predictive accuracy, as well as better interpretation of the data. Frequently used evaluation functions for feature selection include resampling methods such as cros...
