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Reducing Electrical Current Variations in Phase-Locked Loop Systems

Researchers at the University of California, Davis have developed a method of eliminating electrical current mismatches in the charge pumps of phase-locked loops (PLL) systems - thereby increasing their power efficiency and phase detection capabilities.

Systems and Methods for Sound-Enhanced Meeting Platforms

Computer-based, internet-connected, audio/video meeting platforms have become pervasive worldwide, especially since the 2020 emergence of the COVID-19 pandemic lockdown. These meeting platforms include Cisco Webex, Google Meet, GoTo, Microsoft Teams, and Zoom. However, those popular platforms are optimized for meetings in which all the participants are attending the meeting online, individually. Accordingly, those platforms have shortcomings when used for hybrid meetings in which some participants are attending together in-person and others attending online. Also, the existing platforms are problematic for large meetings in big rooms (e.g. classrooms) in which most or all of the participants are in-person. To address those suboptimal meet platform situations, researchers at UC Berkeley conceived systems, methods, algorithms and other software for a meeting platform that's optimized for hybrid meetings and large in-person meetings. The Berkeley meeting platform offers a user experience that's familiar to users of the conventional meeting platforms. Also, the Berkeley platform doesn't require any specialized participant hardware or specialized physical room infrastructure (beyond standard internet connectivity).

Embedded Power Amplifier

Researchers at the University of California, Davis have developed an amplifier technology that boosts power output in order to improve data transmission speeds for high-frequency communications.

Absorptive Microwave Bandpass Filters

Researchers at the University of California, Davis have developed absorptive bandpass filters that enable improved passband flatness and good impedance matching both in-band and out-of-band.

Contextual Augmentation Using Scene Graphs

Spatial computing experiences are constrained by the real-world surroundings of the user.  In such experiences, augmenting virtual objects to existing scenes require a contextual approach, where geometrical conflicts are avoided, and functional and plausible relationships to other objects are maintained in the target environment.  Yet, due to the complexity and diversity of user environments, automatically calculating ideal positions of virtual content that is adaptive to the context of the scene is considered a challenging task.    UC researchers have developed a framework which augments scenes with virtual objects using an explicit generative model to learn topological relationship from priors extracted from a real-world and/or synthetic 3D datasets.  Primarily designed for spatial computing applications, SceneGen extracts features from rooms into a novel spatial representation which encapsulates positional and orientational relationships of a scene which captures pairwise topology between objects, object groups, and the room.  The AR application iteratively augments objects by sampling positions and orientations across a room to create a probabilistic heat map of where the object can be placed.  By placing objects in poses where the spatial relationships are likely, we are able to augment scenes that are realistic. 

A Fully Integrated Stretchable Sensor Arrays for Wearable Sign Language Translation To Voice

UCLA researchers in the Department of Bioengineering have developed a novel machine learning assisted wearable sensor system for the direct translation of sign language into voice with high performance.

New And Integrated Method For Continuous Auditory Brain Stimulation

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).

Vibration Sensing and Long-Distance Sounding with THz Waves

UCLA researchers in the Department of Electrical and Computer Engineering have developed a terahertz (THz) detector that utilizes the micro-Doppler effect to detect vibrations and long-distance sounds.

Decision Making Spike Time Dependent Plasticity (STDP) Based Neuronal Network Learning

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").

Deep Learning Network and Compression Framework over Limited Bandwidth Network Links

Researchers at the University of California, Davis have developed a technology that enables the quantization of discrete wavelet transformed coefficients to reduce bandwidth for cloud-based storage applications. 

Compact Ion Gun for Ion Trap Surface Treatment in Quantum Information Processing Architectures

Electromagnetic noise from surfaces is one of the limiting factors for the performance of solid state and trapped ion quantum information processing architectures. This noise introduces gate errors and reduces the coherence time of the systems. Accordingly, there is great commercial interest in reducing the electromagnetic noise generated at the surface of these systems.Surface treatment using ion bombardment has shown to reduce electromagnetic surface noise by two orders of magnitude. In this procedure ions usually from noble gasses are accelerated towards the surface with energies of 300eV to 2keV. Until recently, commercial ion guns have been repurposed for surface cleaning. While these guns can supply the ion flux and energy required to prepare the surface with the desired quality, they are bulky and limit the laser access, making them incompatible with the requirements for ion trap quantum computing.To address this limitation, UC Berkeley researchers have developed an ion gun that enables in-situ surface treatment without sacrificing high optical access, enabling in situ use with a quantum information processor.

Energy Efficient and Scalable Reconfigurable All-to-All Switching Architecture

Researchers at the University of California, Davis have developed a hierarchical optical switch architecture that is low latency and energy efficient.

Higher-Speed and More Energy-Efficient Signal Processing Platform for Neural Networks

Researchers at the University of California, Davis have developed a nanophotonic-based platform for signal processing and optical computing in algorithm-based neural networks that is faster and more energy-efficient than current technologies.

Privacy Preserving Stream Analytics

UCLA researchers in the Department of Computer Science have developed a new privacy preserving mechanism for stream analytics.

Field Effect Bipolar Transistor

Researchers at the University of California have developed a field effect bipolar transistor (FEBT) on a unilateral silicon substrate using CMOS/BiCMOS technology for use in switching and amplification of electric signals and as a 1-transistor memory cell for storing information in a suitable circuit.

Nonlinearity Factorization for Up-Conversion Mixer Linearity Analysis

Researchers at the University of California, Davis have developed a nonlinearity factorization scheme/method to fully characterize the time-varying behavior of switching stages with low intermediate frequency (IF).

Passive Coupling Balance Scheme for Long Traveling Complex Differential Signals

Researchers at the University of California, Davis have developed a passive coupling balance technique to suppress signal mismatches for long traveling N-pair complex differential signals.

SpeakQL: Towards Speech-driven Multi-Modal Querying

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.

Vertical Cavity Surface-Emitting Lasers with Continuous Wave Operation

An m-plane VCSEL with an active region that has thick quantum wells and operation in continuous wave.

A Digital Polar and a ZVS Contour Based Hybrid Power Amplifier

Researchers in the UCLA Department of Electrical Engineering have created a hybrid digital polar and zero switching voltage (ZVS) contour power amplifier, offering higher efficiency for up to 36 dB peak-to-average ratio.

Energy-Efficient All-Optical Nanophotonic Computing

Researchers at the University of California, Davis, have developed a new computing and signal processing platform based on nanophotonics and nanoelectronics to decrease power consumption and improve overall computing speed with all-optical inputs and outputs.

3D Magnetic Topological Structures for Information Storage

Researchers at the University of California, Davis, have developed a new way to directly create 3-dimensional topological magnetic structures that allows for efficient information storage with potentially low energy dissipation.

Integrated Antennas And Phased Arrays With Mode-Fee Electromagnetic Bandgap Materials

The invention is a multifunctional electromagnetic structure that enhances antennas performance significantly. Built using an electromagnetic bandgap material, it eliminates scan blindness for phased array structures, along all scan directions. The invention simultaneously improves the radiation pattern as well.

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