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Classification of pulsars with Dirichlet process Gaussian mixture model

This work uses Dirichlet process Gaussian mixture model (DPGMM), an unsupervised machine learning algorithm, for analyzing the distribution of pulsar families in the parameter space of period and period derivative and compares the average values of the characteristic age, magnetic dipole field strength, surface temperature and transverse velocity of all discovered clusters.
arXiv (opens in a new tab)

Collective Success Measure and Analysis in Gamification

It is observed that clusters are affected by the structural breaks that is occurred in the first two dates at almost the same rate, and after the third structural break, they are inversely affected depending on the their average performance level.
IEEE (opens in a new tab)

A tangible user interface for air drum game

A reliable and real time tangible user interface system developed for the air drum game which is used both for game and computer based training programs is presented and its performance has been reported.
IEEE (opens in a new tab)

Comparative Assessment of Pulsar Families using GMM and DPGMM

The clustering performance of models with respect to silhouette coefficients is compared and apparently, DPGMM performs, once again, better than GMM in discriminating selected pulsar families.
IEEE (opens in a new tab)

Application of pesticide using unmanned aerial vehicle

It was aimed to use unmanned aerial vehicle (UAV) that is able to fly on and spray farmland autonomously and it was verified that the the equipment to be mounted on the UAV works properly in real time and real world.
IEEE (opens in a new tab)
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