Researchers from UC San Diego have developed RadSenNet, a new approach of sequential fusing of information from radars and cameras. The key idea of sequential fusion is to fundamentally shift the center of focus in radar-camera fusion systems from cameras to radars. This shift enables their invention (RadSegNet) to achieve all-weather perception benefits of radar sensing. Keeping radars as the primary modality ensures reliability in all situations including occlusions, longrange and bad weather.

 Researchers from UC San Diego developed Pointillism, a system that enables radars to overcome the challenges posed by specular reflections, sparsity and noise in the radar point clouds, to provide high-fidelity perception of the scene with 3D bounding boxes. Pointillism consists of multiple low-resolution radars placed in a optimal fashion to maximize the spatial diversity and scene information. Pointillism combines this spatial diversity with novel multi-radar fusion algorithms to tackle the problem of specular reflections, sparsity and noise in radar point clouds. Building upon the hardware and algorithms, Pointillism also introduces a novel data-driven approach that enables the detection of multiple dynamic objects in the scene, with their accurate location, orientation and 3D dimensions. Furthermore, Pointillism enables such perception even in inclement weather, thereby paving a way for radar to be the main-stream sensor for autonomous perception.

Various examples of delivering continuous auditory stimulation of various kinds (sometimes referred to by the term “entrainment”) have been proposed to modulate brainwaves for therapeutic effect. Current methods of delivering continuous auditory stimulation typically present noises (in the form of clicks, tones, pulses) embedded in music. By modulating the user’s existing audial environment to embed continuous auditory sound stimulation, this technology creates a more tolerable and user-friendly experience that enables prolonged therapeutic stimulation for such neurodegenerative disorders as Alzheimer’s, Parkinson’s and Chronic Traumatic Encephalopathy (CTE).

Biologically inspired neural networks are capable of performing sophisticated information processing. Information processing by the brain is multilayered and involves many sequential steps before sensory information can be interpreted and translated into a behavior or action. What makes this cascade powerful is its ability to learn and respond to an ever changing environment based on patterns. Eventually, information gathered from the senses may reach decision centers (such as lateral intra parietal cortex) that govern behavior and are under the influence of reward signals. While a great deal of research has gone into understanding mechanisms of learning at the cellular level, there is still much to discover regarding how learning at the cellular level gives rise to learning on the level of animal behavior. One of the most promising mechanisms of synaptic change for learning is spike time dependent plasticity ("STDP").

Automatic speech recognition (ASR) systems currently in use work well for routine tasks such as posing a question to SIRI (Apple) or Alexa (Amazon), but do not interface with more complex datasets. Complex datasets take into account when the user considers a speech-driven system to query structured data, but these require new approaches. Some of these approaches have used new querying modalities such as visual, touch-based and natural language interfaces (NLIs) whereby user commands are translated into the Structured Query Language (SQL). Unfortunately these new proposals are not suitable for complex datasets.

Oceanic monitoring helps coastal communities, economies, and ecosystems thrive. The coastlines and open oceans prove to be very important to maritime countries for recreation, mineral and energy exploitation, shipping, weather forecasting and national security. As solar power, GPS, and telecomm improvements have been made, directional wave buoys have emerged and set the standard in wave monitoring. Non-directional and directional wave measurements are of high interest to users because of the importance of wave monitoring for successful marine operations. Wave data and climatological information derived from the data are also used for a variety of engineering and scientific applications.

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To achieve maximum SNR and minimum interference, phased array antennas have gained popularity in high-capacity communication networks as an electronically steerable alternative to fixed-direction antenna. Fixed direction antennas have a high installation cost though as beam alignment must be very precise to maintain high SNR. Coupled with this high installation cost is the unavoidable alignment issues that arise with building sway under wind loading conditions. What is needed is an adaptive technique based on phased array antenna which will accommodate off angle RF signals at the receive side of the communications link.

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