Ultra-wideband cognitive interrogator network for indoor location tracking - part 1: system architecture and network performance analysis

We explore the potential application of cognitive interrogator network (CIN) in remote monitoring of mobile subjects in domestic environments, where the ultra-wideband radio frequency identification (UWB-RFID) technique is considered for accurate source localization. We first present the CIN architecture in which the central base station (BS) continuously and intelligently customizes the illumination modes of the distributed transceivers in response to the systempsilas changing knowledge of the channel conditions and subject movements. Subsequently, the analytical results of the locating probability and time-of-arrival (TOA) estimation uncertainty for a large-scale CIN with randomly distributed interrogators are derived based upon the implemented cognitive intelligences. Finally, numerical examples are used to demonstrate the key effects of the proposed cognitions on the system performance

Empirical performance of RSSI-based Monte Carlo localisation for active RFID patient tracking systems

The range of potential applications for indoor and campus based personnel localisation has led researchers to create a wide spectrum of different algorithmic approaches and systems. However, the majority of the proposed systems overlook the unique radio environment presented by the human body leading to systematic errors and inaccuracies when deployed in this context. In this paper RSSI-based Monte Carlo Localisation was implemented using commercial 868 MHz off the shelf hardware and empirical data was gathered across a relatively large number of scenarios within a single indoor office environment. This data showed that the body shadowing effect caused by the human body introduced path skew into location estimates. It was also shown that, by using two body-worn nodes in concert, the effect of body shadowing can be mitigated by averaging the estimated position of the two nodes worn on either side of the body. © Springer Science+Business Media, LLC 2012.

Localization Algorithm Performance in Ultra Low Power Active RFID Based Patient Tracking

Indoor personnel localization research has generated a range of potential techniques and algorithms. However, these typically do not account for the influence of the user's body upon the radio channel. In this paper an active RFID based patient tracking system is demonstrated and three localization algorithms are used to estimate the location of a user within a modern office building. It is shown that disregarding body effects reduces the accuracy of the algorithms' location estimates and that body shadowing effects create a systematic position error that estimates the user's location as closer to the RFID reader that the active tag has line of sight to.

Dual-tracking multi-constellation GNSS front-end for high-performance receiver applications

This paper presents the design and implementation of a dual–tracking Radio Frequency (RF) front–end for a multi–constellation Global Navigation Satellite Systems (GNSS) receiver. The RF frond–end is based on the direct RF conversion architecture, which employs sub–Nyquist sampling (also known as subsampling) at RF. The dual–tracking RF front–end is composed of a few RF components that are duplicated to form the two RF channels. Employing a dual–channel Analogue–to–Digital Converter (ADC) enables synchronisation of the RF channels and minimises the errors resulting from the differences in the satellite clocks and the propagation delay between the two RF channels. The digitised GNSS signals are processed by two separate acquisition and tracking engines that are driven by the front–end’s master clock. This setup provides two synchronised receivers that are integrated onto one piece of hardware. The hardware is intended to be used for research applications such as multipath mitigation, scintillation assessment, and advanced satellite clock and spatial frame transformation modelling.

Wearing a sports compression garment on the performance of visuomotor tracking following eccentric exercise : a pilot study

Clinical compression garments have been shown to improve functional control in patients with motor impairments, however, investigation in functional control has not been observed whilst wearing sports compression garments. This pilot study assessed motor control changes in the bicep brachii muscle following a bout of eccentric exercise designed to induce delayed onset muscle soreness for intervals up to 14 days after exercise. Eight male participants performed 35 maximal isokinetic eccentric extensions at 90° s−1. Participants where then randomly divided into one of two groups to perform a one-dimensional elbow flexion/extension visuomotor tracking task; one group wore a sports compression garment during the task, the other acted as control (no garment). The group who wore the compression garment performed the tracking task significantly better immediately post-exercise, and at days 1, 2 and 3 post-exercise (p ≤ 0.05). Non-significant but large and moderate effects sizes (ES), in tracking, were found between the two groups on day 5 (ES = 1.3) and day 7 (ES = 0.7), respectively. Further research is necessary to elucidate these preliminary findings, however, the results suggest that the wearing of sports compression garments post-eccentric exercise has a positive effect on functional motor control.

Combining multiple tracking algorithms for improved general performance

Automated tracking of objects through a sequence of images has remained one of the difficult problems in computer vision. Numerous algorithms and techniques have been proposed for this task. Some algorithms perform well in restricted environments, such as tracking using stationary cameras, but a general solution is not currently available. A frequent problem is that when an algorithm is refined for one application, it becomes unsuitable for other applications. This paper proposes a general tracking system based on a different approach. Rather than refine one algorithm for a specific tracking task, two tracking algorithms are employed, and used to correct each other during the tracking task. By choosing the two algorithms such that they have complementary failure modes, a robust algorithm is created without increased specialisation.

Executive Stock Ownership and Performance: Tracking Faint Traces

We examine the relation between managers' financial interests and firm performance. Since the relation could go in either direction, we cast the analysis in a simultaneous equations framework. For firms involved in acquisitions, we find that acquisition performance and Tobin's Q ratios affect the size of managers' stockholdings. We find no evidence, however, that larger stockholdings lead to better performance. Perhaps management is effectively disciplined by competition in product and labor markets. Alternatively, it may not be necessary for top executives to own stock to the residual claimants. And finally, higher ownership might multiply the opportunities to appropriate corporate wealth.

Can you see me thinking (about my answers)? Using eye-tracking to illuminate developmental differences in monitoring and control skills and their relation to performance

This study focuses on relations between 7- and 9-year-old children’s and adults’ metacognitive monitoring and control processes. In addition to explicit confidence judgments (CJ), data for participants’ control behavior during learning and recall as well as implicit CJs were collected with an eye-tracking device (Tobii 1750). Results revealed developmental progression in both accuracy of implicit and explicit monitoring across age groups. In addition, efficiency of learning and recall strategies increases with age, as older participants allocate more fixation time to critical information and less time to peripheral or potentially interfering information. Correlational analyses, recall performance, metacognitive monitoring, and controlling indicate significant interrelations between all of these measures, with varying patterns of correlations within age groups. Results are discussed in regard to the intricate relationship between monitoring and recall and their relation to performance.

Vision-based tracking for sports performance analysis

With the world of professional sports shifting towards employing better sport analytics, the demand for vision-based performance analysis is growing increasingly in recent years. In addition, the nature of many sports does not allow the use of any kind of sensors or other wearable markers attached to players for monitoring their performances during competitions. This provides a potential application of systematic observations such as tracking information of the players to help coaches to develop their visual skills and perceptual awareness needed to make decisions about team strategy or training plans. My PhD project is part of a bigger ongoing project between sport scientists and computer scientists involving also industry partners and sports organisations. The overall idea is to investigate the contribution technology can make to the analysis of sports performance on the example of team sports such as rugby, football or hockey. A particular focus is on vision-based tracking, so that information about the location and dynamics of the players can be gained without any additional sensors on the players. To start with, prior approaches on visual tracking are extensively reviewed and analysed. In this thesis, methods to deal with the difficulties in visual tracking to handle the target appearance changes caused by intrinsic (e.g. pose variation) and extrinsic factors, such as occlusion, are proposed. This analysis highlights the importance of the proposed visual tracking algorithms, which reflect these challenges and suggest robust and accurate frameworks to estimate the target state in a complex tracking scenario such as a sports scene, thereby facilitating the tracking process. Next, a framework for continuously tracking multiple targets is proposed. Compared to single target tracking, multi-target tracking such as tracking the players on a sports field, poses additional difficulties, namely data association, which needs to be addressed. Here, the aim is to locate all targets of interest, inferring their trajectories and deciding which observation corresponds to which target trajectory is. In this thesis, an efficient framework is proposed to handle this particular problem, especially in sport scenes, where the players of the same team tend to look similar and exhibit complex interactions and unpredictable movements resulting in matching ambiguity between the players. The presented approach is also evaluated on different sports datasets and shows promising results. Finally, information from the proposed tracking system is utilised as the basic input for further higher level performance analysis such as tactics and team formations, which can help coaches to design a better training plan. Due to the continuous nature of many team sports (e.g. soccer, hockey), it is not straightforward to infer the high-level team behaviours, such as players’ interaction. The proposed framework relies on two distinct levels of performance analysis: low-level performance analysis, such as identifying players positions on the play field, as well as a high-level analysis, where the aim is to estimate the density of player locations or detecting their possible interaction group. The related experiments show the proposed approach can effectively explore this high-level information, which has many potential applications.