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Platform for predicting a compound’s cardioactivity

The invention is a platform that combines a screening system and machine learning algorithms to investigate and report the cardio-activity related information of a certain compound. Through screening cardiac tissue strips, the platform determines whether a compound is cardio-active or not, as well as the associated cardio-active mechanism based on a drug library that is automatically developed. Such information is crucial for the drug development process, especially for evidence based decisions.

A simple, accurate and inexpensive device pointing system using head tilt gesturing

Current device pointing systems, which control the movement of cursors on screens, suffer from several drawbacks which often preclude their use by individuals with special needs or medical conditions. This UCI invention describes a simple, inexpensive “head mouse” that, in combination with proprietary software, tracks the position of the head relative to the body, allowing for full control of a pointing device.

Predictive Optimization Of Pharmeceutical Efficacy

UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a machine learning platform to virtually screen combinatorial drug therapies.

Reducing Computational Complexity of Training Algorithms for Artificial Neural Networks

Researchers at UCLA have developed a novel mathematical theorem to revolutionize the training of large-scale artificial neural networks (ANN).

TSV coupling mitigation coding techniques in 3D-ICs

Three-dimensional network-on-chip (NoC) designs are a crucial aspect of 3D integrated circuit platforms, though they suffer from unwanted and often detrimental effects due to coupling between their vertical through-silicon via (TSV) connections. Recently, researchers at UCI have developed algorithm-based techniques to mitigate such TSV-to-TSV coupling, capable of >90% reduction of such interactions.

Query-Based Graph Data Reduction

The invention is a set of algorithms that can reduce the amount of graph data for specific applications, based on the type of queries that the graph data needs to answer. Reducing graph data size for certain applications allows them to be run efficiently on devices with limited storage and/or bandwidth.

GPS-Based Miniature Oceanographic Wave Measuring Buoy System

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.

Automated Reconstruction Of The Cardiac Chambers From MRI

This is a fast, fully automated method to accurately model a patient’s left heart ventricle via machine learning algorithms.

ParBreZo - a rapid, high-resolution flood inundation modeling software

By mid-century, flooding is predicted to cause annual losses of $52 billion. The ParBreZo v.8.0 software developed at UCI can predict flood inundation at better than 30 feet resolution, and within a short span of time. These predictions will help plan and prepare for future floods, respond intelligently to on-going flooding, and learn from past floods.

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.

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