We develop fraud detection and user authentication classifiers for mobile keystroke and haptic patterns, achieving 84% accuracy, 90% recall, and 81% precision within one model architecture, and 99% recall and 83% precision across all models. In addition to proposing these models that outperform existing touch dynamics authentication models, we present a secure, space-efficient, and extensible f...

An Optimization Framework for Solving Capacitated Multi-level Lot-sizing Problems with Backlogging Tao Wu†, Leyuan Shi†,>, Joseph Geunes‡, Kerem Akartunalı∗ † Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706 ‡ Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611 ∗ Department of Management Science, Univ...

This paper proposes a mixed integer programming formulation for modeling the capacitated multi-level lot sizing problem with both backlogging and setup carryover. Based on the model formulation, a progressive time-oriented decomposition heuristic framework is then proposed, where improvement and construction heuristics are effectively combined, therefore efficiently avoiding the weaknesses asso...