Electronic and magnetic properties of Ti(2)O(3), Cr(2)O(3), and Fe(2)O(3) calculated by the screened exchange hybrid density functional.

The electronic and magnetic properties of the transition metal sesqui-oxides Cr(2)O(3), Ti(2)O(3), and Fe(2)O(3) have been calculated using the screened exchange (sX) hybrid density functional. This functional is found to give a band structure, bandgap, and magnetic moment in better agreement with experiment than the local density approximation (LDA) or the LDA+U methods. Ti(2)O(3) is found to be a spin-paired insulator with a bandgap of 0.22 eV in the Ti d orbitals. Cr(2)O(3) in its anti-ferromagnetic phase is an intermediate charge transfer Mott-Hubbard insulator with an indirect bandgap of 3.31 eV. Fe(2)O(3), with anti-ferromagnetic order, is found to be a wide bandgap charge transfer semiconductor with a 2.41 eV gap. Interestingly sX outperforms the HSE functional for the bandgaps of these oxides.

Automated 3D Vision Tracking for Project Control Support

On-site tracking in open construction sites is often difficult because of the large amounts of items that are present and need to be tracked. Additionally, the amounts of occlusions/obstructions present create a highly complex tracking environment. Existing tracking methods are based mainly on Radio Frequency technologies, including Global Positioning Systems (GPS), Radio Frequency Identification (RFID), Bluetooth and Wireless Fidelity (Wi-Fi, Ultra-Wideband, etc). These methods require considerable amounts of pre-processing time since they need to manually deploy tags and keep record of the items they are placed on. In construction sites with numerous entities, tags installation, maintenance and decommissioning become an issue since it increases the cost and time needed to implement these tracking methods. This paper presents a novel method for open site tracking with construction cameras based on machine vision. According to this method, video feed is collected from on site video cameras, and the user selects the entity he wishes to track. The entity is tracked in each video using 2D vision tracking. Epipolar geometry is then used to calculate the depth of the marked area to provide the 3D location of the entity. This method addresses the limitations of radio frequency methods by being unobtrusive and using inexpensive, and easy to deploy equipment. The method has been implemented in a C++ prototype and preliminary results indicate its effectiveness