Towards a Practical Pedestrian Distraction Detection Framework using Wearables

Pedestrian safety continues to be a significant concern in urban communities and pedestrian distraction is emerging as one of the main causes of grave and fatal accidents involving pedestrians. The advent of sophisticated mobile and wearable devices, equipped with high-precision on-board sensors capable of measuring fine-grained user movements and context, provides a tremendous opportunity for designing effective pedestrian safety systems and applications. Accurate and efficient recognition of pedestrian distractions in real-time given the memory, computation and communication limitations of these devices, however, remains the key technical challenge in the design of such systems. Earlier research efforts in pedestrian distraction detection using data available from mobile and wearable devices have primarily focused only on achieving high detection accuracy, resulting in designs that are either resource intensive and unsuitable for implementation on mainstream mobile devices, or computationally slow and not useful for real-time pedestrian safety applications, or require specialized hardware and less likely to be adopted by most users. In the quest for a pedestrian safety system that achieves a favorable balance between computational efficiency, detection accuracy, and energy consumption, this paper makes the following main contributions: (i) design of a novel complex activity recognition framework which employs motion data available from users' mobile and wearable devices and a lightweight frequency matching approach to accurately and efficiently recognize complex distraction related activities, and (ii) a comprehensive comparative evaluation of the proposed framework with well-known complex activity recognition techniques in the literature with the help of data collected from human subject pedestrians and prototype implementations on commercially-available mobile and wearable devices

Molecular modeling of an antigenic complex between a viral peptide and a class I major histocompatibility glycoprotein

Computer simulation of the conformations of short antigenic peptides (&lo residues) either free or bound to their receptor, the major histocompatibility complex (MHC)- encoded glycoprotein H-2 Ld, was employed to explain experimentally determined differences in the antigenic activities within a set of related peptides. Starting for each sequence from the most probable conformations disclosed by a pattern-recognition technique, several energyminimized structures were subjected to molecular dynamics simulations (MD) either in vacuo or solvated by water molecules. Notably, antigenic potencies were found to correlate to the peptides propensity to form and maintain an overall a-helical conformation through regular i,i + 4 hydrogen bonds. Accordingly, less active or inactive peptides showed a strong tendency to form i,i+3 hydrogen bonds at their Nterminal end. Experimental data documented that the C-terminal residue is critical for interaction of the peptide with H-2 Ld. This finding could be satisfactorily explained by a 3-D Q.S.A.R. analysis postulating interactions between ligand and receptor by hydrophobic forces. A 3-D model is proposed for the complex between a high-affinity nonapeptide and the H- 2 Ld receptor. First, the H-2 Ld molecule was built from X-ray coordinates of two homologous proteins: HLA-A2 and HLA-Aw68, energyminimized and studied by MD simulations. With HLA-A2 as template, the only realistic simulation was achieved for a solvated model with minor deviations of the MD mean structure from the X-ray conformation. Water simulation of the H-2 Ld protein in complex with the antigenic nonapeptide was then achieved with the template- derived optimal parameters. The bound peptide retains mainly its a-helical conformation and binds to hydrophobic residues of H-2 Ld that correspond to highly polymorphic positions of MHC proteins. The orientation of the nonapeptide in the binding cleft is in accordance with the experimentally determined distribution of its MHC receptor-binding residues (agretope residues). Thus, computer simulation was successfully employed to explain functional data and predicts a-helical conformation for the bound peptid