Enabling Operator Decision-Making to Increase the Efficiency of Operator-led Collaborative Teams in Operating Centres

Operating Centre control rooms are large rooms where trained operators remotely supervise data centre equipment. Operators aim to maintain the connectivity and computer services modern society relies on. They provide services to their organizations or government or industry clients including forming and monitoring tactical teams that solve time-critical computing issues. Their daily activities include monitoring and responding to alerts, while simultaneously participating in multiple distributed teams where the role of the operator is to ensure progress towards a problem's resolution.

Advancing Data Science Research (Cohort #2)

Enormous quantities of machine-readable data, measured in many terabytes, are readily available. The sources include the world-wide web, publicly available databases, raw experimental data, unannotated genomic sequences generated by biochemical tools, and so on. However, data does not necessarily equal useful information. More often than not, the data has to be intelligently processed, interpreted, transformed, and then integrated into unified repositories.

Mechanisms and Algorithms for Optimal Use of Inter-Clouds

Cloud computing is one of the pillars of the modern computing infrastructure mainly because it allows the procurement of computing services on a pay-as-you-go basis. However, despite the many benefits offered by cloud computing, it has several significant drawbacks such as data lock-in, lack of universal geographic proximity, risk of service outages, and variable cost structures.

Applying low latency touch sensor technology to mobile devices Year Two

When a user makes an input to a computer, there is a necessary delay before the computer is able to respond. For mouse-based computers, responding within 100ms was sufficient to appear ‘immediate’. In touch-based systems, latency is more apparent, represented as a physical separation between the finger and the object moved onscreen. Technologies capable of immediate (1ms) reporting of input to the computer are being developed by Tactual Labs. Such sensors hold the key to the elimination of lag in the user interface.

Realistic character skinning in a gaming environment

We propose to tackle a challenging problem in computer graphics called 'skinning'. A skinning technique consists in animating the skin of a 3D virtual character. In our context we seek a method specifically targeted to computer games. Therefore our goal is to develop a skinning method as visually plausible as possible with real-time performance. We recently introduced a method called implicit skinning, this technique produces the effect of skin contact and fold at joints in real-time.

Automated optimization of robotic tasks and transitions using graph-based approaches

In recent years, machining with robots has become a trend in the manufacturing industry. The concept offers an economical solution for medium to low accuracy machining applications. However, due to the complexity of the robot kinematics, planning for these paths is challenging. Jabez Technologies has developed a semi-graphical approach that can program large robot-paths. This approach has been very well received by the industry and has proven to be extremely robust in practice. However, this approach is semi-automatic and cannot work without user input.

Efficient Computational Methods for Understanding Back Move-ment and Pain from Dynamic Data Modeling

This project uses machine learning algorithms to better understand back movement and low back pain. We apply supervised learning time series algorithms to data collected from Backtracks’ wearable de-vice — which consists of a malleable think curve that reads data collected from the participants’ spine movements. At each time step, such movements are represented as a curve; the dynamic evolution of this curve in time represents an individual’s spinal movements.

Efficient Computational Methods for Understanding Back Move-ment and Pain from Dynamic Data Modeling

This project uses machine learning algorithms to better understand back movement and low back pain. We apply supervised learning time series algorithms to data collected from Backtracks’ wearable de-vice — which consists of a malleable think curve that reads data collected from the participants’ spine movements. At each time step, such movements are represented as a curve; the dynamic evolution of this curve in time represents an individual’s spinal movements.

Development of design algorithms for WDM network modernization

The rapid technological evolution of telecommunication networks demands service providers to regularly update their technology, with the aim of remaining competitive in the marketplace. However, upgrading the technology in a network is not a trivial task. When modernizing a network, the existing infrastructure and network components need to be taken into account. The design exercise must not only take into consideration the overall desired functionality and capacity but also the existing network properties.

Development of algorithms for scheduling WDM network migrations

The rapid technological evolution of telecommunication networks demands service providers to regularly update their technology, with the aim of remaining competitive in the marketplace. However, upgrading the technology in a network is not a trivial task. New hardware components need to be installed in the network and during the installation, network connectivity may be temporary compromised.

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