Digital Commons Network^™

Determining Optimal Wireless Propagation Model For A Region And Wavelength, Yi-Fan Chen, Georgios Roumpos, Boon-Lock Yeo, Peter Yung Sen Chen

Defensive Publications Series

Generally, the present disclosure is directed to determining an optimal wireless propagation model for a given region and wavelength. 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 wireless propagation model for a region based on terrain data for the region.

Intelligent Ordering Of Repeated Fields, Gang Wang, Haskell Garon

Defensive Publications Series

Generally, the present disclosure is directed to choosing an optimal order for options within a repeated field. 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 order for options within a repeated field based on interaction data with the repeated field.

Identifying Sources Of A Change In Metrics Of A Stack Of Servers, Kyle Loveless

Defensive Publications Series

Generally, the present disclosure is directed to identifying a source of a change in one or more metrics of one or more servers. 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 contribution from a component within a stack of one or more servers based on one or more states of the component.

Automatically Scaling Multi-Tenant Machine Learning, Steven J. Ross, Christopher Olston, Noah Fiedel

Defensive Publications Series

Generally, the present disclosure is directed to optimizing use of computing resources in a 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 task allocation for a job serving a plurality of machine-learned models based on current system state and queries per second (QPS) data for the plurality of models. Alternatively, the tasks can be allocated according to one or more rules (e.g., a new task is allocated to a job until the compute usage for the job falls below a scaling threshold). …

Legal Precedent Mining With Machine Learning, Alexandros Salazar

Defensive Publications Series

Generally, the present disclosure is directed to gathering legal precedent from a corpus of law. 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 decision data from a court decision based on the court decision (e.g., a textual copy of the court decision).

Determining Validity Of A Point Of Interest Based On Existing Data, Melanie L. Donny-Clark, Jingyu Zhou, Shuang Qu

Defensive Publications Series

Generally, the present disclosure is directed to determining whether or not a point of interest is valid based on existing data. 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 a point of interest being valid based on ‘clues’ gathered from existing data.

Extracting Point Of Interest Information From Query Logs, Melanie L. Donny-Clark, Jing Dai

Defensive Publications Series

Generally, the present disclosure is directed to extracting information about a point of interest from one or more query logs. 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 local intent for a query based on content of the query.

Correcting Image Anomalies Using Machine Learning, Nick Felker

Defensive Publications Series

Generally, the present disclosure is directed to correcting anomalies in an image. 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 correct one or more anomalies in an image based on image data from an image.

Fitness Program For User-Defined Goals, Nick Felker

Defensive Publications Series

Generally, the present disclosure is directed to a fitness program tailored to 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 generate a goal-oriented fitness program to a user based on user physiological and or fitness data.

User Interface And Application Programming Interface For Explaining Personalized Machine-Learned Model Outputs, N/A

Defensive Publications Series

Generally, the present disclosure is directed to systems and methods that enable explanation of personalized machine-learned model outputs. For example, the systems and methods of the present disclosure can include or leverage a user interface and/or an application programming interface (API) to enable explanation of model outputs. According to one aspect, the present disclosure provides a principled way of discovering which actions or range of actions that the user took contributed to a particular output that the model predicted at later time. This allows, for example, an application that employs the personalized model to describe to the user which actions …

Providing Reader Assistance Based On Reader Interaction, Nick Felker

Defensive Publications Series

Generally, the present disclosure is directed to assisting users of 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 provide assistance for one or more content items in an electronic document to a user of the electronic document based on the user’s interaction with the electronic document.

Machine Learning To Predict Advertisement Targeting Solutions, Zachary Garrett

Defensive Publications Series

Generally, the present disclosure is directed to using machine learning to predict advertisement targeting solutions. 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 optimal advertisement target solutions such as, for example, keyword word sets, negative word sets, location restrictions, bid adjustments, and/or schedules based on product data such as, for example, advertisement content (e.g., ad creatives text), seed keywords, images of the product, and/or advertiser metadata.

Using Image Recognition To Control Devices, Johan Ulrich Lewin Jessen, Morten Just Petersen

Defensive Publications Series

Generally, the present disclosure is directed to using image recognition to control devices. 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 appropriate user interface to control one or more remotely controllable appliances based on image data.

Generating Icons For Applications In An Applications Marketplace, Jun Hong

Defensive Publications Series

Generally, the present disclosure is directed to generating one or more icons for one or more applications in an applications marketplace. 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 generate an icon for an application based on one or more icons for existing applications.

Machine Learning To Disable Applications From Using Background Resources Except At Appropriate Times, Thomas Price, Eytan Lerba

Defensive Publications Series

Generally, the present disclosure is directed to disabling computing applications from using background resources (e.g., processing or data transmission) except at appropriate times (e.g., times when the user is likely to use the electronic 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 predict an appropriate time for an application to use resources based on device usage data.

Machine Learning To Select Best Network Access Point, Thomas Price, Eytan Lerba

Defensive Publications Series

Generally, the present disclosure is directed to selecting a best network access point when multiple are available (e.g., including cell towers, WiFi access points, 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 predict a best network access point based on device usage data.

Rethinking The Potential Of Documentation Of Culture As A Data Gathering Practice, Tomasz Umerle

Proceedings from the Document Academy

In this article, I examine the documentation of culture (DoC). This is the practice of gathering and producing the information and data relevant to intangible cultural phenomena. DoC is generally practiced by teams of documentalists generally outside GLAM institutions (i.e., galleries, libraries, archives and museums). As such, it differs from the preservation and description of concrete objects of cultural heritage done within those institutions. I examine how DoC finds it increasingly difficult to clearly define and communicate its role: a) in relation to LIS; b) to the broader academic community; and c) in digital age of information overload. In this …

Before The Antelope: Robert Pagès On Documents, Michael K. Buckland

Proceedings from the Document Academy

In 1951 Suzanne Briet wrote, with minimal explanation, that an antelope could become a document. In 1948 Robert Pagès (1919-2007) published an explanation of the same and related ideas. Textual and other graphic documents are about something, hence descriptive and derived. Animals and other objects are informative because they are illustrative of themselves either as specimens of a class (tokens of a type) or simply as particular individuals (“autodocuments”). Pagès’ career and ideas are briefly discussed.

Promoting Trustworthiness And Discoverability In An S-Town Of Osn Documents, Laurie J. Bonnici

Proceedings from the Document Academy

The realm of online social networks (OSN) has evolved rapidly over the last decade. While literature has primarily focused on Twitter, Facebook presents a unique forum for seeking secondhand knowledge on highly specialized topics including life-threatening medical conditions. Cognitive authority expressed through accounts of personal experiences augments authoritative resources that often are inaccessible or non-existent. OSN posts in Facebook groups appear as a plethora of documents thrown upon the virtual floor, disorganized and unsearchable. This paper offers ideas of what could be possible when interaction design (Ixd) is applied to Facebook groups to promote trustworthiness and discoverability for the information …

The Spider: Anaylsis Of An Automaton, Susannah N. Munson

Proceedings from the Document Academy

[Editors' note: This paper is the 2017 winner of the Student Paper Award in Document(ation) Studies, http://documentacademy.org/award. Susannah Munson wrote the paper as a Kent State University, School of Information, Museum Studies student.]

The physical objects that surround us document vast amounts of information about themselves, their histories, and their roles in broader social and cultural contexts. To reveal this sometimes hidden information, we examine these objects through analytical frameworks that go beyond descriptive accounts to explore how an object existed and was culturally understood throughout its history. Document phenomenology (Gorichanaz and Latham, 2016), conceived in two Acts, …

Configuring Alarm Setting Using Machine Learning, Thomas Price, Eytan Lerba

Defensive Publications Series

Generally, the present disclosure is directed to configuring the initial time set in an alarm 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 a time to set an alarm based on historical alarm records and/or other contextual data.

Machine Learning To Select Media Playback Volume, Thomas Price, Eytan Lerba

Defensive Publications Series

Generally, the present disclosure is directed to setting a media playback volume of an electronic 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 predict an appropriate media playback volume based on device usage data.

Machine Learning To Select Input Language On A Software Keyboard, Thomas Price, Eytan Lerba

Defensive Publications Series

Generally, the present disclosure is directed to selecting an input language on a software keyboard. 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 input language for a keyboard based on device usage data.

Machine Learning To Select Screen Brightness Level, Thomas Price, Eytan Lerba

Defensive Publications Series

Generally, the present disclosure is directed to setting a brightness of a screen of an electronic device (e.g., during media viewing or media playback). 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 appropriate screen brightness level based on device usage data.

Machine Learning To Automatically Lock Device Screen At Opportune Time, Thomas Price, Eytan Lerba

Defensive Publications Series

Generally, the present disclosure is directed to determining when to lock a screen of an electronic device such as, for example, a smartphone. 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 appropriate lock screen behavior based on device usage data.

Generating Travel Itineraries Based On Travel History Of Similar Users, Alexandre Chinien

Defensive Publications Series

Generally, the present disclosure is directed to generating a travel itinerary for a user based on travel history of similar users. 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 generate a travel itinerary for a user based on travel history data from one or more users.

The Development And Use Of The Component Timed-Up-And-Go Test To Determine Basic Prosthetic Mobility In People With Lower Limb Amputation, Sheila Marie Clemens

Open Access Dissertations

Lower limb amputation (LLA) is a devastating event for an individual, often disrupting several aspects of life and, at least initially, upsetting the order of their daily routine. Lower limb amputation places a person at increased risk for secondary medical conditions, like joint degeneration and low back pain, related to use of a prosthesis. Additionally, an increased risk for falls may illicit loss of confidence, and have a detrimental effect on social interactions and quality of life (QoL). The use of outcome measures to assess whether applied interventions are effective can help to focus care and provide guidance to clinicians …

Study Of Selected Issues Of Solid-State Electrochemical Energy Storage, Yuchen Wang

Open Access Dissertations

The present dissertation focuses on three different topics of supercapacitor (SC) technology: 1) combination of galvanic cell components into SCs to mitigate the problem of self-discharge, 2) development of an all-solid-state SC/battery based on a superionic ceramic electrolyte and 3) mechanical-electrochemical study of a composite structural SC. A new hybrid supercapacitor SC with the galvanic cell materials is proposed to mitigate the self-discharge problem and to increase the storage-life. The galvanic cell components in the hybrid SC can provide a micro-current to compensate the self-discharge current. The hybrid SC was fabricated with active carbon electrodes, a polyvinylidene fluoride (PVDF)/lithium trifluoromethanesulfonate …

Early Eye Development, Dave Larsen

College of Arts and Sciences Newsroom

University of Dayton biologist Amit Singh is studying early eye development in fruit flies to understand the molecular basis of retinal disease and birth defects in the human eye under a new $439,499 grant from the National Institutes of Health.

The Mobile Shopping Engagement: Surveys’ Review And Empirical Study, Eftychia Gkiolnta, Vaggelis Saprikis, Maro Vlachopoulou

Journal of Marketing and Consumer Behaviour in Emerging Markets

Mobile shopping (m-shopping) has become extremely signifi cant for both marketing and retail selling. Despite the fact that m-shopping has evolved into a popular alternative approach for purchasing products and services worldwide, the research regarding the extent of its adoption is still on a mediocre level and in certain countries, such as Greece, is rather limited. It is highly important to analyze and fully comprehend several factors that infl uence the acceptance of mobile technologies by consumers in order to motivate and support sellers’ mobile strategy. The objective of this research is to approach the factors that affect m-shopping with …