Educating Patients about Behavioral Interventions and Exercises for Musculoskeletal Lower Back Pain

Low back pain (LBP) is a common problem which affects all genders and most ages. It results in considerable direct and indirect costs, and these costs are financial, workforce and social. The majority of lower back pain occurs due to a musculoskeletal etiology and often presents to the primary care physician. We worked with local physicians, chiropractors, physical therapists, and athletic trainers to develop exercises and behavioral modifications that patients can do to improve lower back pain symptoms.https://scholarworks.uvm.edu/fmclerk/1273/thumbnail.jp

Towards Graphene Remote Plasma Interfacial Growth and Auger Spectra Simulation

Graphene, the single layer of carbon atoms which form a honeycomb lattice, has excellent physical properties that make it an well known material for fundamental and applied research. A surface sensitive technique known as Auger electron spectroscopy is ideal for studying graphene due to the thickness of the graphene. A complete understanding of how the various peak in the graphene Auger spectra occur is not yet available. Towards explaining these peaks a simulation which predicts the Auger energies of neutral free carbon has been scripted. Growth of graphene which is mostly likely to see the greatest implementation in industry occurs in chemical vapor deposition systems. In order to avoid time-consuming and potentially damaging transfer processes, a type of graphene growth which occurs at the interface of a nickel catalyst and the underlying substrate which requires no transfer is experimented with. Here, growths have occurred on a remote plasma inductively coupled plasma chemical vapor deposition system at various gas ratios of methane to hydrogen, temperatures, and plasma conditions to explore growth optimization. The growths are subsequently analyzed using Raman spectroscopy, X-Ray photoelectron spectroscopy, and Auger electron spectroscopy. In general growths without plasma tended to be more graphite like and growths with plasma tended to be more diamond like

Method Of Block Chain Verification To Authenticate Advertising Payment Chains

A block chain method of verification to authenticate advertising payment chains is disclosed. The online advertisement transactions are registered on a public ledger so that the middle reselling layers are available. Cryptographic validation is used here. The information in the public ledger could be used to establish reselling nodes between advertisers and content publishers. The computation is done either by the advertisement network or the advertisers themselves. The method is intended to establish valid ownership chains for advertising. The advantages of the method are that this method can be performed across the entire advertisement ecosystem and there is no restriction to any central owner or authentication committee to map buyers to sellers. Through this, at any given time a buyer could also validate acceptable buyers and could either remove or block nodes to those the buyer wants to permanently blacklist

Click-to-call conversion measurement based on transcribing conversation

The conversion metric, which is the ratio of sales (or other predefined result) to advertisement impressions or clicks, is a key measure for advertisers to assess the value derived from digital advertising. In click-to-call ads, which show a link for mobile users to initiate a call to an advertiser, conversions, if any, occur over the phone after the user clicks the ad. Conversions that occur over the phone are difficult to document, in turn making it difficult to accurately measure the conversion metric. This disclosure describes use of machine learning techniques to transcribe, with user and advertiser permission, the call between a user and an advertiser and to use the transcript to determine conversions that happen during the call

Increased Efficiency In Ad Modeling Through Adveritser Analytic Power-User Analysis

Increased efficiency in modeling through analytic power user analysis is introduced in this publication. The analytic power user analysis includes identifying a first set of users from a global set of users. The first set of users is generally characterized as proficient, relative to the global set, in setting up and/or tracking a content item. Interactions of the first set of users are analyzed to determine interactions or information associated with interactions that distinguish the first set of users from the global set. A second set of users are identified based on the distinguishing interactions or associated information. Performance data associated with the second set of users is used for analysis and modeling improvement

Spam Detection For Outgoing And Incoming Calls

System and method are disclosed to detect spam in outgoing or incoming calls on a telephone device. The system includes a server running a machine-learning algorithm coupled to a spam detection service running on the device that detects spam during an outgoing or incoming call. When the user places a call; the device listens to the conversation and extracts identifiable characteristics through acoustic characterization. These characteristics constituting a signature are received by the spam detection service to identify spam. If a spam call is detected, the user is warned through an audio cue during the call and ends the call. If spam is not detected, the user continues the conversation. After the call, user is allowed to assign a spam rating. The spam rating and acoustic signature entry are sent to the server to improve the machine learning algorithm. The disclosed method of detecting spam calls helps users save money

Preventing reverse engineering of black-box classifiers

Machine learning (ML) models trained for various purposes are generally kept confidential, e.g., due to their commercial value, proprietary nature of training data, etc. Therefore, commercial cloud-based machine-learning service providers protect their ML models even as they provide one or more services to customers that employ ML models. For example, a service enables a customer to upload an observation, e.g., an image, and receive a label for the observation, generated by a ML model that’s trained to determine labels for images. Recent research has shown that given a sufficient number of observations and returned labels, it is possible to reverse engineer the ML model that generated the labels. This disclosure presents techniques that thwart reverse-engineering efforts, e.g., by adversarial actors, by returning, for a small fraction of input queries, not a true but a near-true class label

Client-Side Link Selection Validation

A method for reducing unintentional user clicks due to reflow and clickjacking in mobile apps. Links in electronic documents such as web pages may be marked as special or protected. When a protected link is present, the document presentation environment prevents selection of links that exhibit untrustworthy behavior, which might have been clicked by accident in an attempt to select the protected link. Examples of untrustworthy behavior include repositioning the link just prior to the link selection or presenting the link in a transparent manner

Conversational hierarchy for interaction with virtual assistant

User interfaces for conversations, e.g., with virtual assistants, typically model conversation as a back-and-forth exchange between participants, e.g., without regard to the type or topic of conversation. Under this user interface, a filter, refinement, or query by the user is added as a new inline block or a full-page refresh, making the user interface cumbersome to use. This disclosure describes techniques that model conversation as a hierarchy, e.g., with major and minor conversational turns. The user interface is designed around this hierarchy, and a flow between the front-end and the back-end of conversations informs user interactions and client-side page interactions