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Articles 3211 - 3240 of 160810
Full-Text Articles in Entire DC Network
Disloyal Order, Marissa Dillon
Disloyal Order, Marissa Dillon
Fishladder: A Student Journal of Art and Writing
No abstract provided.
How To Read Between The Lines, Allison Poschke
How To Read Between The Lines, Allison Poschke
Fishladder: A Student Journal of Art and Writing
No abstract provided.
Tl;Dr, Kenzie Mclain
Tl;Dr, Kenzie Mclain
Fishladder: A Student Journal of Art and Writing
No abstract provided.
Buggin' Out, Robert Manquen
Buggin' Out, Robert Manquen
Fishladder: A Student Journal of Art and Writing
No abstract provided.
Letter From The Editors, Jacob Guajardo, Jackie Vega
Letter From The Editors, Jacob Guajardo, Jackie Vega
Fishladder: A Student Journal of Art and Writing
No abstract provided.
Identifying Impaired State For A Driver, Catherine Cardinal, Cliff Sze
Identifying Impaired State For A Driver, Catherine Cardinal, Cliff Sze
Defensive Publications Series
Generally, the present disclosure is directed to improving driver safety by identifying impaired drivers. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a driver’s impairment state based on driving data.
The Imp Of The Perverse, John Emil Vincent
No Story, No Myth, Jonathan Lamb
Are You My Internal Object?, Sharif Youssef
An Impossible Ideal: Motherhood In Eighteenth-Century Britain, Jessica Hanselman Gray
An Impossible Ideal: Motherhood In Eighteenth-Century Britain, Jessica Hanselman Gray
Criticism
No abstract provided.
Contributors, Antipodes Editors
Determining High-Level Topical Annotations For A Conversation, N/A
Determining High-Level Topical Annotations For A Conversation, N/A
Defensive Publications Series
Generally, the present disclosure is directed to annotating a conversation with high-level topical annotations. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict topical annotations for a conversation based on audio data from the conversation.
Determining Projection Format For A Video, N/A
Determining Projection Format For A Video, N/A
Defensive Publications Series
Generally, the present disclosure is directed to determining one or more projection formats for a video. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a projection format for a segment of a video based on image data extracted from the video.
Recommending Items For Deletion Based On Item Quality And Usage, N/A
Recommending Items For Deletion Based On Item Quality And Usage, N/A
Defensive Publications Series
Generally, the present disclosure is directed to recommending items stored in a data storage system for deletion. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a likelihood of deletion for an item based on item data and user interaction data for one or more items.
Using Customer Support Interaction Data To Estimate Customer Satisfaction, N/A
Using Customer Support Interaction Data To Estimate Customer Satisfaction, N/A
Defensive Publications Series
Generally, the present disclosure is directed to using customer support interaction data to estimate customer satisfaction. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a customer satisfaction score based on customer interaction data.
Determining Priority Value Of Processes Based On Usage History, Neil Dhillon, Tanmay Wadhwa
Determining Priority Value Of Processes Based On Usage History, Neil Dhillon, Tanmay Wadhwa
Defensive Publications Series
Generally, the present disclosure is directed to determining optimal priority values for one or more processes in a computing system. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict an optimal priority value for a process based on system data and/or process data.
Semi-Supervised Classification Using Object Metadata, Dave Feltenberger
Semi-Supervised Classification Using Object Metadata, Dave Feltenberger
Defensive Publications Series
Generally, the present disclosure is directed to classification of data objects (e.g. documents, images, graphs, etc.). In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to classify a data object based on object data and/or metadata associated with the object.
Optimizing Route Guidance To Preserve User Loyalty, Thomas Price
Optimizing Route Guidance To Preserve User Loyalty, Thomas Price
Defensive Publications Series
Generally, the present disclosure is directed to optimizing route guidance in a navigation or ride share service to preserve user loyalty. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict likelihood of user abandonment based on user data and/or route data.
Classifying A User As Driver Or Passenger In A Vehicle Using Machine Learning, Thomas Price
Classifying A User As Driver Or Passenger In A Vehicle Using Machine Learning, Thomas Price
Defensive Publications Series
Generally, the present disclosure is directed to classifying a user as driver or passenger in a vehicle using machine learning. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a user type based on device usage data and/or device sensor data.
Determining Optimal Dimming Of Displays, N/A
Determining Optimal Dimming Of Displays, N/A
Defensive Publications Series
Generally, the present disclosure is directed to dimming a display to reduce power consumption and/or improve security of a device. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predictively dim a display connected to a device based on usage data and/or sensor data available from the device and/or signals derived from the usage data and/or sensor data.
Weighting Knowledge Sources To Facilitate User Input, N/A
Weighting Knowledge Sources To Facilitate User Input, N/A
Defensive Publications Series
Generally, the present disclosure is directed to weighting one or more knowledge sources used to determine user input. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a weight for a knowledge source based on user input data and/or output of one or more knowledge sources.
Learning Weights For Smart Navigation Planning, N/A
Learning Weights For Smart Navigation Planning, N/A
Defensive Publications Series
Generally, the present disclosure is directed to learning costs or weights associated with elements used in navigation planning. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a travel cost or weight associated with an element based on properties of the element and/or time data and/or weather data.
Routing Audio Output To Provide Inadvertently Muted Audio Output To A User, N/A
Routing Audio Output To Provide Inadvertently Muted Audio Output To A User, N/A
Defensive Publications Series
Generally, the present disclosure is directed to routing audio output to increase the likelihood that a user hears the audio output. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict an output channel for audio output based on audio output data such as connection data, audio data, and/or user interaction data.
Context-Dependent Account Selection, N/A
Context-Dependent Account Selection, N/A
Defensive Publications Series
Generally, the present disclosure is directed to selecting a user account out of one or more user accounts for a user. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a user account for a user based on context data.
Electronic Document Navigation Assistance Using Markings And/Or Non-Uniform Scrolling, N/A
Electronic Document Navigation Assistance Using Markings And/Or Non-Uniform Scrolling, N/A
Defensive Publications Series
Generally, the present disclosure is directed to assisting in navigation within an electronic document. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a location within an electronic document to be marked based on user interaction with the electronic document.
Retrospective User Input Inference And Correction, N/A
Retrospective User Input Inference And Correction, N/A
Defensive Publications Series
Generally, the present disclosure is directed to retrospective user input inference and/or correction. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict intended user input based on actual user input.
Machine Learning To Dissipate A Cyclone, N/A
Machine Learning To Dissipate A Cyclone, N/A
Defensive Publications Series
Generally, the present disclosure is directed to using machine learning to dissipate or otherwise combat a cyclone. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict characteristics of a cyclone (or infant cyclone which can be referred to as a cyclet) such as location, path, strength, number of anti-cyclone devices needed to combat the cyclone, positioning of the anti-cyclone devices, etc. based on information descriptive of the cyclone including imagery of the cyclone or other collected data such as, for example, wind speed and …
Mechanism For Queuing Livestream Content In A Media Content Display Queue, Ruxandra Davies, Justin Lewis
Mechanism For Queuing Livestream Content In A Media Content Display Queue, Ruxandra Davies, Justin Lewis
Defensive Publications Series
A mechanism is provided to queue live content items in a playlist by including timestamps corresponding to a start time and end time of a content item. A livestream may be added to a playlist that includes a timestamp and content items from the playlist may be provided to a user. Subsequently, a content item service may determine a user may not reach a livestream on time. The content item service may generate a notification to be presented to the user in a user interface that includes selectable icons representing actions that may be performed on the content items. In …