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Anchor Based Sequence Clustering Algorithm for Efficient & Accurate Motif Discovery

A new strategy for speeding up motif discovery, an anchor based sequence clustering algorithm (ASC) that works significantly faster and with greater accuracy than current motif finding algorithms.

Developing Physics-Based High-Resolution Head And Neck Biomechanical Models

UCLA researchers in the Department of Radiation Oncology at the David Geffen School of Medicine have developed a new computational method to model head and neck movements during medical imaging/treatment procedures.

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.

Three-Dimensional NoC Reliability Evaluation Automated Tool (TREAT)

The invention is a reliability analysis framework designed specifically and uniquely for 3D Network-on-Chip platforms. Following an innovative methodology together with accurate modeling for smart dynamic faults injection, the invention can effectively be used to avoid costly redesigns through assessments at earlier design stages.

Automated And Unsupervised Method For Electroencephalogram Artifact Minimazation And Rejection

UCLA researchers have developed an automated and unsupervised digital signal processing method to quickly and efficiently minimize and reject artifacts from scalp Electroencephalogram (EEG) and intracranial EEG recordings.

Mechanical Process For Creating Particles Using Two Plates

UCLA researchers in the Department of Chemistry and Biochemistry & Physics and Astronomy have developed a novel method to lithograph two polished solid surfaces by using a simple mechanical alignment jig with piezoelectric control and a method of pressing them together and solidifying a material.

Robust Visual-Inertial Sensor Fusion For Navigation, Localization, Mapping, And 3D Reconstruction

UCLA researchers in the Computer Science Department have invented a novel model for a visual-inertial system (VINS) for navigation, localization, mapping, and 3D reconstruction applications.

Dsp-Sift: Domain-Size Pooling For Image Descriptors For Image Matching And Other Applications

UCLA researchers in the Computer Science Department have invented a novel modification to the scale-invariant feature transform (SIFT) algorithm that shows significant improvement for computer vision applications.

Determining Oil Well Connectivity Using Nanoparticles

UCLA researchers in the Department of Chemistry & Biochemistry, Department of Math, and California NanoSystems Institute (CNSI) have designed methods and systems for monitoring and testing underground wells using sampled nanowires.

Clinical Operations Management And Patient Analytics System (C.O.M.P.A.S.)

The C.O.M.P.A.S. system is a suite of software tools designed to improve the efficiency of outpatient health clinics. The software displays a HIPPA-compliant, real-time map of clinic operations and regularly computes clinic efficiency metrics, which are useful in guiding decisions for improvements, both in clinic organization and in patient experience. The C.O.M.P.A.S. suite turns medical clinics into SMART clinics.

Grouping Algorithm For Touchscreen Finger Position Detection

UCLA researchers in the Department of Electrical Engineering developed a new grouping algorithm for touchscreen finger position detection.

A Method Of Computational Image Analysis For Predicting Tissue Infarction After Acute Ischemic Stroke

UCLA researchers in the Departments of Radiological Sciences and Neurology have designed an algorithm to predict tissue infarctions using pre-therapy magnetic resonance (MR) perfusion-weighted images (pre-PWIs) acquired from patients with acute ischemic stroke. The predictions generated by the algorithm provide information that may assist in physicians’ treatment decisions.

Automatic Role Based User Provisioning for Epic’s Electronic Medical Record (EMR) System

Researchers at the University of California, Davis have developed web based software called OPAL to automate the user provisioning process for Epic’s EMR system. The technology handles new access requests, account renewals and access revokes with zero or minimal input from the end user. The software interfaces with multiple health system enterprise systems to validate employment status, verify provider credentials, automatically determine the appropriate level of access for users and create those accounts within Epic.

Wearable Monitoring System Better Understands Autism Spectrum Disorder

Researchers at the University of California, Davis have developed a wearable monitoring system to better understand the emotional dysregulation that an individual with an autism spectrum disorder (ASD) may encounter.

Weather Augmented Risk Determination (WARD) System

The inventors have created software for construction project management. The Weather Augmented Risk Determination (WARD) System uses historic weather data and forecasts to determine probability of weather related work stoppage and probabilistic information on labor productivity and project duration.

Energy Efficient Trigger Word Detection via Accelerometer Data

Researchers at the University of California, Davis have developed an energy-efficient voice monitoring technique for smart devices, such as smartphones and wearables, based on accelerometer data.

Super Alarm – A Learning Software for Prevention of Alarm Fatigue

A robust learning software platform capable of combining both patient physiologic monitor alarms and data in EMR (e.g., laboratory tests) to more precisely monitor patients.

Software for Optimal Presentation Of Imagery On Multi-Plane Displays

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Method And System For Diagnosing And Training Cognitive Fitness And Targeted Neural Network Function Underlying Cognitive Fitness In An Integrated...

This invention is a novel video game that integrates cognitive and neural training in real-time to improve cognitive function.

Software for auto-generation of text reports from radiology studies

Imaging machines used for radiology studies often export data (such as vascular velocities, bone densitometry, radiation dose, etc.) as characters stored in image format. Radiologists are expected to interpret this data and also store it in their text-based reports of the studies. This is usually accomplished by dictating the data into the text report or copying it by typing it. However, these methods are error-prone and time-intensive.

UCSF Chimera: Molecular Modeling Software for Visualization and Analysis of Molecular Structures

This invention consists of software that facilitates modeling and interactive visualization of molecular structures and related data.

Software for Differential Dynamic Microscopy (DDMCalc)

A MATLAB code for performing differential dynamic microscopy (DDM).

Forest Convolutional Neural Networks

In machine learning, a convolutional neural network (CNN) is a type of feed-forward artificial neural network where the individual neurons are tiled in such a way that they respond to overlapping regions in the visual field. They are widely used to model image and video recognition, being a powerful tool for different vision problems. Compared to other image classification algorithms, convolutional neural networks use relatively little pre-processing. This means that the network is responsible for learning the filters that in traditional algorithms were hand-engineered. Despite major reductions in error, current implementations of CNN models still leave significant room for improvement due to the lack of transparency and flexibility in architecture design.

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