1 × 4 space switching and simultaneous all-optical wavelength conversion at 2.488Gbit/s using a single monolithically integrated multiwavelength laser

A novel InGaAs/InGaAsP/InP integrated multiwavelength grating cavity laser is presented, which has been used to demonstrate space switching and simultaneous all-optical wavelength conversion at bit rates of 2.488 Gbit/s. This has been achieved using a single monolithically integrated device without the need for post-filtering to separate the converted signal from the input.

Highly flexible all-optical wavelength conversion at 2.488 Gbits/s using a multi-output-wavelength laser

An integrated multiwavelength grating cavity (MGC) laser fabricated by selective area regrowth is demonstrated. In addition to allowing wavelength conversion, the device can perform various important network functions such as space switching and multiplexing. The use of the device for these functions offers several advantages from a wavelength division multiplexing (WDM) network, such as flexibility, reduced component count, size, and the associated cost reduction.

All optical wavelength conversion at 2.488 Gbits/s using the integrated multi grating cavity (MGC) laser

A novel integrated Multi-Wavelength Grating Cavity (MGC) laser has been used for multi-channel wavelength conversion at 2.488 Gbits/s. Functions demonstrated include conversion to multiple wavelengths, WDM multiplexing and 1×4 space switching.

All optical wavelength conversion at 2.488GBits/s using the integrated multi grating cavity (MGC) laser

A novel integrated Multi-Wavelength Grating Cavity (MGC) laser has been used for multi-channel wavelength conversion at 2.488Gbits/s. Functions demonstrated include conversion to multiple wavelengths, WDM multiplexing and 1×4 space switching.

Fast dynamic wavelength and path scheduling in a monolithic 8×8 switch

The control plane is implemented for the first time to allow scheduling and power leveling in a monolithic 8×8 space and wavelength selective cross-connect. 16 dynamic data connections are established within 16μs. © 2013 Optical Society of America.

An evaluation of space time cube representation of spatiotemporal patterns.

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

The Trade-offs with Space Time Cube Representation of Spatiotemporal Patterns

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Fast and correct analysis of such information is important in for instance geospatial and social visualization applications. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a dataset to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap we report on a between-subjects experiment comparing novice users error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the dataset, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users when analyzing complex spatiotemporal patterns.