In this paper, naive Bayesian and C4.5 Decision Tree Classifiers(DTC) are successively applied in materials informatics to classify the engineering materials into different classes for the selection of materials that suit the input design specifications.Here, the classifiers are analyzed individually and their performance evaluation is analyzed with confusion matrix predictive parameters and standard measures, the classification results are analyzed on different class of materials. Comparison of classifiers has found that naive Bayesian classifier is more accurate and better than the C4.5 DTC. The knowledge discovered by the naive Bayesian classifier can be employed for decision making in materials selection in manufacturing industries.

In this paper, we present a novel device concept and interactions, using paper like rollable displays. Concept is designed for devices like mobile phones, tablets, e-ink readers, etc. which have one side and dual side rollable screens. Sensors are used to identify physical modes of device and also visible regions in a physical mode. Latest advances in silicon technology will aid in device packaging with IC chips, camera, battery, etc. Device concept is evaluated using low-fidelity prototypes and evaluation results show that interactions based on physical rolling fare well on novelty and usability aspects.

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