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Search And Recommendation Process For Identifying Useful Boundaries In Virtual Communication Settings

Advances in Augmented and Virtual Reality (AR/VR) headsets and displays have introduced alternative systems of immersive and context aware communications platforms.  However, one key factor that can cause a major bottleneck in future AR/VR communication is the limited space surrounding the user in the real world.  In Augmented Reality, unlimited spatial data can be imported to the user’s current surrounding.  Many of these virtual objects do not hold spatial limitations to themselves and are only restricted to the user’s real world surrounding constraints.  They can be visualized, augmented and placed anywhere necessary in the space, as long as they are within the users’ environmental boundaries.   However, this one-way spatial limitation between virtual and real objects does not always apply in communication applications where two or more users, all having spatial discrete constraints, are interacting with each other in a spatial setting.  All parties of the tele-conference (or other communication methods) hold unique spatial limitations (room size, furniture settings, etc.) and consequently their virtual doubles or Avatars may not be able practice the same spatial relationship and arrangement between the real-world spaces and their corresponding boundaries for all parties.  This would result in misalignment of head and body gestures, spatial sound errors and other micro expression errors due to the incorrect positioning of each member of the virtual call.   UC researchers have developed a search and recommendation process which can identify mutual accessible boundaries of all the parties of a communication setting (AR conference calls, virtual calls, tele-immersion, etc.) and provide each user the exact location to position itself and where to move surrounding objects so that all parties of the call can hold a similar spatial relationship to each other with minimum effort.  Such process would allow all members of the virtual call to augment other members in their own spaces, by considering the spatial limitations of all participants in the virtual/augmented reality call.    The process facilitates promoting remote communication in all consumer levels, in both commercial and personal settings.  It would also benefit remote workplace procedures, allowing workers and employees to communicate efficiently together, without accessing large commercial spaces.  Preserving micro-gestures and expressions in another feature of this process, maintaining different attributions of social interactions and effective communications.

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 Battery-Less Wirelessly Powered Frequency-Swept Spectroscopy Sensor

UCLA researchers in the Department of Electrical and Computer Engineering have developed a wirelessly powered frequency-swept spectroscopy sensor.

Development of a CMOS-Compatible, Nano-photonic, Laser

Researchers at the University of California, Davis have developed a new class of lasers and amplifiers that uses a CMOS-compatible electronics platform - and can also be applied to nano-amplifiers and nano-lasers applications.

Low Complexity Maximum-Likelihood Decoding of Cyclic Codes

UCLA researchers in the Department of Electrical and Computer Engineering have developed a low complexity decoding algorithm of cyclic codes with better performance and lower latency than current approaches.

Multi-Wavelength, Laser Array

Researchers at the University of California, Davis have developed a multi-wavelength, laser array that generates more precise wavelengths than current technologies. The array also delivers narrow linewidths and can operate athermally.

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.

Digital Spur Cancellation Of Fractional Frequency Synthesizer

UCLA researchers in the Department of Electrical and Computer Engineering have developed a digital spur cancellation technique for frequency synthesizers used in clock synchronization.

Security Key Generation Technique for Inter-Vehicular Visible Light Communication

The invention is a technique that provides a novel, reliable and secure cryptography solution for inter-vehicular visible light communication. Through combining unique data as the road roughness and the driving behavior, a symmetric security key is generated for both communicating vehicles. As the data used is unique to the communicating vehicles only, the generated keys are thus unique, securing a reliable communication channel between both vehicles.

Unsupervised WiFi-Enabled Device-User Association for Personalized Location-Based Services

With the emergence of the Internet of Things in smart homes and buildings, determining the identity and mobility of people are key to realizing personalized, context-aware and location-based services - such as adjusting lights and temperature as well as setting preferences of electronic devices in the vicinity. Conventional electronic user identification approaches either require proactive cooperation by users or deployment of dedicated infrastructure. Consequently, existing approaches are intrusive, inconvenient, or expensive to ubiquitously implement. For example: biometric identification requires specific hardware and physical interaction; and vision-based (video) approaches need favorable lighting and introduce privacy issues. To address this situation, researchers at UC Berkeley developed an identification system that uses existing, pervasive WiFi infrastructure and users' WiFi-enabled devices. The innovative Berkeley technology cleverly leverages attributes such as the MAC address and RSS of users' WiFi-enabled devices. Furthermore, the Berkeley approach is facilitated by an unsupervised learning scheme that maps each user identification with associated WiFi-enabled devices. This technology could serve as a vital underpinning for practical personalized context-aware and location-based services in the era of the Internet of Things.

Quarter-Rate Serial Link Receiver with Low Aperture Delay Samplers for High Data Rate Applications

Researchers at the University of California, Davis have developed a quarter-rate serial link receiver with low aperture delay samplers for use in high-speed serial link interconnects in network systems. This receiver decreases the parasitic capacitances that result from threshold adjustments and can drastically decrease the amount of power required for high data rate applications.

Robust High Speed Analog QAM Demodulator for Advanced Wireless Applications

Wireless applications are witnessing major advancement in fields like virtual reality and cellular phones, thus requiring much higher data transfer speed. This technology is a novel architecture for wireless receivers that accommodates such targeted high data rates, while maintaining a cost efficient design; power efficient while still utilizing simple circuits design, through replacing complicated digital blocks with innovative analog ones.

Multiple-Input Multiple-Output (MIMO) Communication System Using Reconfigurable Antennas

Multiple-Input Multiple-Output (MIMO) communication systems, which increase communication speed and signal quality using multi-path propagation, have become an essential part of modern wireless communication such as Wi-Fi and 4G mobile internet connectivity. UCI inventors have developed a wireless communication system architecture that, by using reconfigurable antennas, improves the data throughput capacity and lowers implementation cost and complexity for MIMO communication systems.

Silicon Based Chirped Grating Emitter for Uniform Power Emission

Researchers at the University of California, Davis, have developed a chirped grating emitter with ultra-sharp instantaneous field of view (IFOV) for optical beam-steering applications.

Hollow Plastic Waveguide ("Wave Cable") Based High Speed And Low Power Data Center Inter-Server Link

UCLA researchers in the department of Electrical Engineering have developed a novel and inexpensive plastic interconnect for high efficiency communication within data centers.

A Technique For Securing Key-Value Stores Against Malicious Servers

The advent of the Internet of Things (IoT) has drastically increased the potential scale and scope of destruction hackers can cause. Cloud servers now control and monitor devices such as cars, smart home controls, fitness trackers, medical monitoring systems. These cloud-based devices are at risk, however, in that if they become compromised, third parties could gain full control of all devices and stored information associated with that server. UCI researchers have developed the FIDELIUS system, a technique for secure communication and information storage.

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.

Method Of Localizing Breakdown In High Power Rf Network

Researchers in the Department of Physics have developed a method for detecting localized electrical breakdowns in high power RF networks.

A Circuit-Based Scalable and Low-Complex Optical Datacenter Network

The ever‐increasing bandwidth requirements of modern datacenters have led researchers to propose networks based upon optical circuit switches, but these proposals face significant deployment challenges. In particular, previous proposals dynamically configure circuit switches in response to changes in workload, requiring network‐wide demand estimation, centralized circuit assignment, and tight time synchronization between various network elements— resulting in a complex and unwieldy control plane. Moreover, limitations in the technologies underlying the individual circuit switches restrict both the rate at which they can be reconfigured and the scale of the network that can be constructed; a new approach is necessary.

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.

Monitor Alarm Fatigue Allevation By SuperAlarms - Predictive Combination Of Alarms

UCLA researchers in the Department of Neurosurgery have developed a method that is capable of mining a collection of monitor alarms to search for specific combinations of encoded monitor alarms to predict certain adverse event, such as in-hospital code blue arrests or other target events.

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