Research Paper Computer Science

Research Paper Computer Science-57
Solutions to these issues come from a variety of fields, making this area – called computer-supported collaborative work – an interdisciplinary field.

Solutions to these issues come from a variety of fields, making this area – called computer-supported collaborative work – an interdisciplinary field.At UNC, we are looking at graphics techniques to support telepresence; architectures and abstractions to support scalable, efficient, multi-device collaboration; data mining techniques to make collaboration-related inferences and recommendations; and environments to support collaborative software engineering and distance education.

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Traditional computer science has assumed that a single user interacts with a computer program at any one time.

A whole range of issues emerge when you decide to violate this fundamental assumption by allowing multiple, distributed users to simultaneously communicate with a program to collaborate with each other.

The goal of computer vision is to extract information from visual data and help computers understand the visual world.

Vision algorithms increasingly impact our everyday lives.

The advances in high-throughput genotyping and sequencing have generated massive amounts of data that allow genome-wide analysis to be performed at much finer resolution than before, but at the same time posed great computational challenges.

We have investigated a wide range of problems including haplotype inference, imputation, genome-wide association study, alternative splicing analysis, copy number variation detection, methylation, genome annotation and visualization.

These tradeoffs need to be explicitly accounted for when designing control algorithms that use such sensors.

The distributed and multicore processing platforms on which control algorithms are implemented today also defy the traditional view of a centralized controller that has a synchronized access to all sensors, can compute all control inputs instantaneously, and can provide all actuations synchronously.

As we are rapidly moving towards the design of autonomous systems, such a disciplined approach towards the design and implementation of control algorithms, as promoted by CPS, is increasingly becoming important.

The presence of complex sensors, like cameras, radars, and lidars – that are today common in autonomous cars, drones, or robots – introduce large processing delays, and offer different tradeoffs between accuracy, delay and resource requirements.

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