Radio over fibre enabled sensing and communications system for in building

This paper describes work on radio over fiber distributed antenna systems for improving the quality of radio coverage for in-building applications. The DAS network has also been shown to provide improved detection for Gen 2 UHF RFID tags. Using pre-distortion to reduce the problem of the RFID second harmonic, a simple heterogeneous sensing and communications system is demonstrated. © 2011 NOrthumbria University.

Effects of high-order laser distortion products in radio over free-space optical links

RoFSO links are found to be susceptible to high-order laser distortion making conventional SFDR ineffective as a performance indicator. For the first time, peak input power is demonstrated as a service-independent bound on dynamic range. © 2011 OSA.

Binding of radio-iodinated gonadotropin to the ovary of exotic carp (Cyprinus carpio Lin.)

Heterologous murrel gonadotropic hormone (m-GtH) binds to common carp oocyte plasma membrane and enhances steroid secretion. With increasing concentration of radio-labelled hormone the receptor binding is also found to increase linearly up to a certain concentration and then decrease. The [¹²⁵I] murrel GtH binding characteristics to a preparation of common carp ovarian plasma membrane shows saturability with high affinity. Scat chard plot analysis gave dissociation constant (Kd) of 0.81 X 10(super -9) M and maximum binding capacity (MBC) of 22.05 f mole/mg protein.

Modelling of equipment loaded panels for robust control investigations

This paper develops a modelling technique for equipment load panels which directly produces (adequate) models of the underlying dynamics on which to base robust controller design/evaluations. This technique is based on the use of the Lagrange's equations of motion and the resulting models are verified against those produced by a finite Element Method Model.

New food processing equipment

The article presents new food processing equipment for coating and frying. These are predusters, liquid enrobers and applicators for large-particle crumbs.

Automated vision tracking of project related entities

Tracking of project related entities such as construction equipment, materials, and personnel is used to calculate productivity, detect travel path conflicts, enhance the safety on the site, and monitor the project. Radio frequency tracking technologies (Wi-Fi, RFID, UWB) and GPS are commonly used for this purpose. However, on large-scale sites, deploying, maintaining and removing such systems can be costly and time-consuming. In addition, privacy issues with personnel tracking often limits the usability of these technologies on construction sites. This paper presents a vision based tracking framework that holds promise to address these limitations. The framework uses videos from a set of two or more static cameras placed on construction sites. In each camera view, the framework identifies and tracks construction entities providing 2D image coordinates across frames. Combining the 2D coordinates based on the installed camera system (the distance between the cameras and the view angles of them), 3D coordinates are calculated at each frame. The results of each step are presented to illustrate the feasibility of the framework.

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