Digital Commons Network^™

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

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

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

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

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

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

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

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

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

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

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

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

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 …

A Qualitative Examination Of The Listening Effort Experience Of Adults With Hearing Loss, Alison Marinelli

Doctoral Dissertations

Increased effort and fatigue are common complaints of individuals with hearing loss, however the listening effort (LE) experience from the patient perspective is not well understood. Current models note the importance of cognitive factors in LE. Research, that is largely quantitative in nature, has shown equivocal findings regarding auditory signals that may cause increased LE, technologies that may ameliorate the LE experience, and the effects of LE on sensory systems. Very limited work has explored the personal aspects of LE. As a whole, however, investigations of LE fail to define the experience from the patient’s view or offer suggestions for …

How Do You Like Me Now? An Examination Of College Students’ Use Of Social Media Sites, James D. Wheeler Iii

Honors Program Theses and Projects

The digital era and the rise of new technology within everyday experiences has led young adults to seek out social media sites as a means of socializing, identity building, self-expression, and seeking validation from peers and friends. The previous work of scholars expresses how social media sites have become a predominate form of communication amongst young adults, and are a social hub for establishing communities that foster particular ideals and online behavior of ‘digital natives’ (those born right before and after the general introduction of digital technologies). This research project contextualizes young adults’ use and behaviors on social media by …

Erosion In Extruder Flows: Analytical And Numerical Study, Miron Kaufman, Petru S. Fodor

Physics Faculty Publications

© 2017 Author(s). We consider the erosion of particles (e.g. carbonblack agglomerates) advected by the polymeric flow in a single screw extruder. We assume a particle to be made of primary fragments bound together. In the erosion process a primary fragment breaks out of a given particle. Particles disperse because of the shear stresses imparted by the fluid. The time evolution of the numbers of particles of different sizes is described by the Bateman coupled differential equations developed a century ago to model radioactivity. Using the particle size distribution we compute an entropic fragmentation index which varies from 0 for …

Dell Doc 8, 2017.12.14 Del Sc Decision

Related Documents for Professor Thompson's book Corporate Valuation in M&A

No abstract provided.

Similar Ultrafast Dynamics Of Several Dissimilar Dirac And Weyl Semimetals, Christopher P. Weber, Bryan S. Berggren, Madison G. Masten, Thomas C. Ogloza, Skylar Deckoff-Jones, Julien Madéo, Michael K. L. Man, Keshav M. Dani, Lingxiao Zhao, Genfu Chen, Jinyu Liu, Zhiqiang Mao, Leslie M. Schoop, Bettina V. Lotsch, Stuart S. P. Parkin, Mazhar Ali

Physics

Recent years have seen the rapid discovery of solids whose low-energy electrons have a massless, linear dispersion, such as Weyl, line-node, and Dirac semimetals. The remarkable optical properties predicted in these materials show their versatile potential for optoelectronic uses. However, little is known of their response in the picoseconds after absorbing a photon. Here, we measure the ultrafast dynamics of four materials that share non-trivial band structure topology but that differ chemically, structurally, and in their low-energy band structures: ZrSiS, which hosts a Dirac line node and Dirac points; TaAs and NbP, which are Weyl semimetals; and Sr_{1–y …}

Winter Commencement: December 14-15, 2017, University Of North Dakota

UND Commencement Programs

UND Winter Commencement program from December 14 and 15, 2017.

The Impact Of Song And Movement On Kindergarten Sight Word Acquisition, Katy Martin

Theses and Dissertations

The purpose of this naturalistic, qualitative study was to document the impact that song and movement had on kindergarten sight word acquisition. To investigate this, 18 kindergarten students were taught 20 new sight words using songs and movement over the course of four weeks. Data was systematically collected and analyzed to determine the specific benefits that song and movement had on kindergartner's sight word learning in regard to automaticity, motivation, and engagement. The kindergarten students were administered a pre-and post-sight word assessment along with a pre-and post-song and movement motivation and engagement student survey. Throughout the study, a qualitative journal …

A Statistical Study Of Student Success In The Bgsu Honors College, Sarah Hercules

Honors Projects

Higher education has long tried to find the best measures to predict student success. Different colleges often have different guidelines, requiring different criteria to be evaluated. The BGSU Honors College has struggled with retention and recruitment of underrepresented students with their current admission criteria. This analysis studies different measures of student success such as BGSU GPA and number of completed Honors credits for high-achieving BGSU students who enrolled from Fall 2013 through Fall 2016 to find the best predictors of student success through regression analysis. Throughout this paper, the impact of ethnicity, gender, the college of a student’s program, high …

Soft Foam Robot With Caterpillar-Inspired Gait Regimes For Terrestrial Locomotion, Cassandra M. Donatelli, Zachary T. Serlin, Piers Echols-Jones, Anthony E. Scibelli, Alexandra Cohen, Jeanne-Marie Musca, Shane Rozen-Levy, David Buckingham, Robert White, Barry A. Trimmer

Engineering Faculty Articles and Research

Caterpillars are the soft bodied larvae of lepidopteran insects. They have evolved to occupy an extremely diverse range of natural environments and to locomote in complex three-dimensional structures without articulated joint or hydrostatic control. These animals make excellent bio-inspiration for the field of soft robotics because of their diversity and adaptability. In this paper, we present SquMA Bot, a caterpillar-inspired soft robot. The robot's body is primarily composed of a soft viscoelastic foam, and it is actuated using a motor-tendon system. SquMA Bot is able to mimic the inching gait of a caterpillar and can use its flexible body to …

Observation Of Top Quark Production In Proton-Nucleus Collisions, A. M. Sirunyan, The Cms Collaboration, M. M. Baarmand, Vallary Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva

Aerospace, Physics, and Space Science Faculty Publications

The first observation of top quark production in proton-nucleus collisions is reported using proton-lead data collected by the CMS experiment at the CERN LHC at a nucleon-nucleon center-of-mass energy of psNN 8.16 TeV. The measurement is performed using events with exactly one isolated electron or muon candidate and at least four jets. The data sample corresponds to an integrated luminosity of 174 nb−1. The significance of the t¯t signal against the background-only hypothesis is above 5 standard deviations. The measured cross section is σ ¯ 45 8 nb, consistent with predictions from perturbative quantum chromodynamics.

The Influence Of Participation In The Leveled Literacy Intervention Program On The Sustained Literacy Achievement For Students In Grades One Through Threev, Veronica Anne Glover

Seton Hall University Dissertations and Theses (ETDs)

This study evaluated the efficacy of Fountas & Pinnell’s Leveled Literacy Intervention (LLI) program and its effect on struggling readers in the first grade, as well as the sustaining effects of the intervention over a two-year period. The students in the study attended an elementary school in a Central New Jersey public school district and received the LLI supplemental pull out reading program five days a week for 30 to 45 minutes per session as prescribed. The study hypothesized that the LLI program would have a significant effect on the reading progress of struggling first-grade students in the districts’ first …

Information Security Collaboration Formation In Organisations, Safa N Sohrabi, C Maple, T Watson, Sm Furnell

School of Engineering, Computing and Mathematics

Collaboration between employees in the domain of information security efficiently mitigates the effect of information security attacks on organisations. Collaboration means working together to do or to fulfil a shared goal, the target of which in this paper is the protection of the information assets in organisations. Information Security Collaboration (ISC) aims to aggregate the employees’ contribution against information security threats. This study clarifies how ISC is to be developed and how it helps to reduce the effect of attacks. The socialisation of collaboration in the domain of information security applies two essential theories: Social Bond Theory (SBT) and the …

Hodge Theory On Transversely Symplectic Foliations, Yi Lin

Mathematical Sciences: Faculty Publications

In this paper, we develop symplectic Hodge theory on transversely symplectic foliations. In particular, we establish the symplectic dδ-lemma for any such foliations with the (transverse) s-Lefschetz property. As transversely symplectic foliations include many geometric structures, such as contact manifolds, co-symplectic manifolds, symplectic orbifolds, and symplectic quasi-folds as special examples, our work provides a unifying treatment of symplectic Hodge theory in these geometries.

As an application, we show that on compact K-contact manifolds, the s-Lefschetz property implies a general result on the vanishing of cup products, and that the cup length of a 2n+1 dimensional compact K-contact manifold with the …

Analysing The Sentiment Expressed By Political Audiences On Twitter: The Case Of The 2017 Uk General Election, M Plummer, Ma Palomino, Gl Masala

School of Engineering, Computing and Mathematics

A significant amount of research on the intersection of sentiment analysis and social media platforms has been published in the past few years. While previous studies have focused on methods to identify the polarity of online posts, little has been done in terms of using the impact of such posts to enhance the discovery and description of trends in real time. Here, we present a tool for the retrieval and analysis of microblogging posts in real time. We have gathered a large sample of tweets related to the 2017 UK General Election. We introduce a novel classification of the polarity …

Configuring An Application Based On Settings In Similar Applications, N/A

Defensive Publications Series

Generally, the present disclosure is directed to configuring settings in an application, such as an application on 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 predict a value for a setting in an application based on values of one or more settings in one or more similar applications.

Generating A User-Specific Reduced Content Webpage, N/A

Defensive Publications Series

Generally, the present disclosure is directed to generating a user-specific reduced content webpage that is tailored 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 content on a webpage that is relevant to and/or irrelevant to a user based on the content of the webpage.

Identifying And Determining Trustworthiness Of A Machine-Learned Model, N/A

Defensive Publications Series

Generally, the present disclosure is directed to identifying and determining trustworthiness of a production machine-learned model. 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 identify a production machine-learned model output within a production system and/or trustworthiness of the production machine-learned model based on the context in which the production machine-learned model is provided.