Browsing by Issue Date, starting with "2022-08-18"
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- Powerless sensor for non-intrusive multi-fiber traffic monitoringPublication . Serrador, António; André, SérgioThe rapid expansion of fiber optic networks and services, which sees a large number of circuits enabled and disabled each day, introduces a significant complexity for operators to identify fibers that have and do not have attached clients. The service level agreements prevent operators from disconnecting circuits without absolute assurance that no clients are attached. We propose a non-intrusive multichannel fiber detector to facilitate the operation and maintenance of the optical networks. The optical distribution frame usually does not have any power available, thus, the proposed device operates without batteries and is powered by near field communication (NFC). Device installation does not require fiber disconnection or communication interruption, and introduces less than 1 dB insertion loss to detect optical signals down to -30 dBm. In order to read multiple fiber channel status, an NFC-enabled smartphone is used to power the device and measure the signal levels of each channel.
- A usability study on widget design for selecting boolean operationsPublication . Chambel Lopes, Diogo; Mendes, Helena; Portal, Ricardo; Klerk, Rui de; Nogueira, Isabel; Lopes, DanielApplying the correct set of Boolean operations is a fundamental task in constructive solid geometry (CSG), which is a staple in automated manufacturing systems. Although textual buttons and icons are the most common interfaces to apply such operations, these require an unnecessary cognitive load that hampers the solid modeling process. This study presents VennPad, a novel CSG widget that gathers all Boolean operations under the same user interface control element and is represented as a two-set Venn diagram. Contrary to conventional CSG widgets, VennPad supports a graphical interface that gives simultaneous access to several types of Boolean operations (intersection, union, difference, symmetric difference and split). A usability study was conducted to ascertain whether VennPad is a more natural interface compared to textual buttons and icon-based widgets for different solid modeling tasks. VennPad proved to be an effective interface to perform Boolean operations. Qualitative feedback places VennPad as the preferred interface, but efficiency results are operation dependent, thus, opening the way to new design iterations.
- Oracle for guidance with deep neural networks in reusable launch vehicle landingPublication . Igreja, José; Lemos, Joao MOracles are of paramount importance for Deep Neural Networks training. In this paper, an oracle developed for landing reusable launch vehicles is created from a linearizing feedback control law that can perform a prescribed landing trajectory tracking. The oracle is then used to train a Deep Neural Network that can be used as a guidance system for landing maneuvers. Verification is performed by Monte-Carlo.