Though recently they have fallen into some disrepute, genome-wide association studies (GWAS) have been formulated and applied to understanding essential hypertension. The principal goal here is to use data gathered in a GWAS to gauge the extent to which SNPs and their interactions with other features can be combined to predict mean arterial blood pressure (MAP) in 3138 pre-menopausal and natura...

Trajectory and intention prediction of traffic participants is an important task in automated driving and crucial for safe interaction with the environment. In this paper, we present a new approach to vehicle trajectory prediction based on automatically generated maps containing statistical information about the behavior of traffic participants in a given area. These maps are generated based on...

Discovering new drugs for disease treatment is challenging, requiring a multidisciplinary effort as well time, and resources. With view to improving hit discovery lead compound identification, machine learning (ML) approaches are being increasingly used in the decision-making process. Although number of ML-based studies have been published, most only report fragments wider range bioactivities w...

This work compares the accuracy of fundamental frequency and formant frequency estimation methods and maximum a posteriori (MAP) prediction from MFCC vectors with hand-corrected references. Five fundamental frequency estimation methods are compared to fundamental frequency prediction from MFCC vectors in both clean and noisy speech. Similarly, three formant frequency estimation and prediction m...

This paper presents a new approach for predicting software faults by means of two-level clustering with unknown number of clusters. We employed Self-Organizing Map method and our proposed clustering approach in the first and second level, respectively, to classify historical and development data into clusters. Next we applied the Radial-Basis Function Network to predict software faults occurred...

Link prediction is an important research direction in the field of Social Network Analysis. The significance of this research area is crucial especially in the fields of network evolution analysis and recommender system in online social networks as well as e-commerce sites. This paper aims at predicting the hidden links that are likely to occur in near future. The possibility of formation of li...

Thanks to the frequency hopping nature of Bluetooth, sniffing Bluetooth traffic with low-cost devices has been considered as a challenging problem. To this end, BlueEar, state-of-the-art system two radios proposes set novel machine learning-based subchannel classification techniques for adaptive (AFH) map prediction by collecting packet statistics and spectrum sensing. However, there is no expl...