Concurrent Firing Light Detection and Ranging System for Autonomous Vehicles

We proposed a light detection and ranging (LIDAR) system that changes the measurement strategy from a LIDAR system of sequential emission and measuring method to a concurrent firing measuring method. The proposed LIDAR was a 3D scanning LIDAR method that consisted of 128 output channels in one vertical line in the measurement direction and concurrently measured the distance for each of these 128 channels. The scanning LIDAR emitted 128 laser pulse streams encoded by carrier-hopping prime code (CHPC) technology with identification and checksum. When the reflected pulse stream was received and demodulated, the emission channel could be recognized. This information could be used to estimate the time when the laser pulse stream was emitted and calculate the distance to the object reflecting the laser. By using the identification of the received reflected wave, even if several positions were measured at the same time, the measurement position could be recognized after the reception. Extensive simulations indicated that the proposed LIDAR could provide autonomous vehicles or autonomous walking robots with good distance images to recognize the environment ahead.

Notating disfluencies and temporal deviations in music and arrhythmia

Expressive music performance and cardiac arrhythmia can be viewed as deformations of, or deviations from, an underlying pulse stream. I propose that the results of these pulse displacements can be treated as actual rhythms and represented accurately via a literal application of common music notation, which encodes proportional relations among duration categories, and figural and metric groupings. I apply the theory to recorded music containing extreme timing deviations and to electrocardiographic (ECG) recordings of cardiac arrhythmias. The rhythm transcriptions are based on rigorous computer-assisted quantitative measurements of onset timings and durations. The root-mean-square error ranges for the rhythm transcriptions were (19.1, 87.4) ms for the music samples and (24.8, 53.0) ms for the arrhythmia examples. For the performed music, the representation makes concrete the gap between the score and performance. For the arrhythmia ECGs, the transcriptions show rhythmic patterns evolving through time, progressions which are obscured by predominant individual beat morphology- and frequency-based representations. To make tangible the similarities between cardiac and music rhythms, I match the heart rhythms to music with similar rhythms to form assemblage pieces. The use of music notation leads to representations that enable formal comparisons and automated as well as human-readable analysis of the time structures of performed music and of arrhythmia ECG sequences beyond what is currently possible.