Microsoft Technology Licensing, LLC

Janssen Pharmaceutica Nv

Digimarc Corporation

Janssen Pharmaceutica

Cognicity, Inc.

Microsoft Corporation

Bin Benjamin Zhu

Mark J Macielag

Shipeng Li

Li Liu

Yue-Mei Zhang

Philip Michael Pitis

Mark E McDonnell

Haiyan Bian

Sui-Po Zhang

Shu-Chen Lin

Jose Clemente

Kristen Chevalier

Min Feng

John Mabus

Chris Flores

Pete Connolly

Peter J Connolly

Scott L Dax

Yang Yang

Christopher M Flores

Donald William Ludovici

Jia Liu

Mark Andrew Youngman

Rui Guo

Ahmed H Tewfik

Mingde Xia

Ning Xu

Raymond W Colburn

Bart L DeCorte

Wei He

Steven J Coats

Linjun Yang

Gilles C Bignan

Jay M Matthews

Chaozhong Cai

Chun Liang Yuan

Weisheng Li

Yao Zhang

Lin Xu

Josh D Benaloh

Michael Nicholas Greco

Yuan Kong

Rui Zhang

Nathan C Sherman

Daniel J Parks

Bart L De Corte

Aimin Pan

Mitchell D Swanson

Xiaoqing Xu

Kaimin Zhang

Jun Shao

Stephen M Prouty

Matthew J Todd

Marina I Nelen

Erica L Nulton

Maowei Yang

Xuyong Yang

Qiujie Li

Mark E Mcdonnell

Kristen M Chevalier

Yidong Wang

Michael H Parker

Frank Kao-Ping Soong

Heejo Lee

Todd C Henninger

Xiaoming Wang

Brett A Marinelli

Yao Qian

Chang Wen Chen

Guofei Gu

Haidong Zhang

Dongmei Zhang

Feng Xue

Hyunsang Choi

Hai Xin

Xu Yin

Hui Fan

Hai Long

Tierui Chen

Jinhai Wu

Mark M McDonnell

Mark MacIelag

Fei Xue

Weibo Chu

Song Ge

Yuanyuan Tang

He Huang

The text-to-speech audio HIP technique described herein in some embodiments uses different correlated or uncorrelated words or sentences generated via a text-to-speech engine as audio HIP challenges. The technique can apply different effects in the text-to-speech synthesizer speaking a sentence to be used as a HIP challenge string. The different effects can include, for example, spectral frequency warping; vowel duration warping; background addition; echo addition; and varying the time duration between words, among others. In some embodiments the technique varies the set of parameters to prevent using Automated Speech Recognition tools from using previously used audio HIP challenges to learn a model which can then be used to recognize future audio HIP challenges generated by the technique. Additionally, in some embodiments the technique introduces the requirement of semantic understanding in HIP challenges.

Audio human interactive proof based on text-to-speech and semantics

Technologies for distributed single sign-on operable to provide user access to a plurality of services via authentication to a single entity. The distributed single sign-on technologies provide a set of authentication servers and methods for privacy protection based on splitting secret keys and user profiles into secure shares and periodically updating shares among the authentication servers without affecting the underlying secrets. The correctness of the received partial token or partial profiles can be verified with non-interactive zero-knowledge proofs.

Distributed single sign on technologies including privacy protection and proactive updating

This document describes tools associated with symbol entry control functions. In some implementations, the tools identify a first finger that is in tactile contact with a touch screen. The first finger can select a subset of symbols from a plurality of symbols that can be entered via the touch screen. The tools can also identify whether one or more other fingers are in concurrent tactile contact with the first finger on the touch screen. The tools can select an individual symbol from the subset based on whether the one or more other fingers are in concurrent tactile contact with the first finger on the touch screen.

Multi-touch text input

The present invention is directed to benzimidazole derivatives, pharmaceutical compositions containing them and their use in the treatment of disorders and conditions mediated by the CB-1 receptor; more particularly, use in the treatment of disorders and conditions responsive to inverse agonism of the CB-1 receptor. More particularly, the compounds of the present invention are useful in the treatment of metabolic disorders.

Benzimidazole derivatives useful as CB-1 inverse agonists

Described is an optimistic fair payment protocol in electronic commerce that provides fair payment while resisting an unconscious double spending attack and other attacks. A buyer receives encrypted e-goods from a merchant, and sends payment to the merchant. If decryption information is not received in exchange for the payment, or the decryption information does not render the e-goods useable, the buyer launches a dispute with a third party dispute resolution service. If the decryption information is received and renders the e-goods useable, the buyer determines whether the e-goods are valid, according to a corresponding description. If not valid, the buyer launches a dispute and provides the e-goods and the description. The third party uses the description to evaluate the validity of the goods to determine whether to refund the payment to the buyer or release it to the merchant.

Fair payment protocol with semi-trusted third party

Technologies for a human computation framework suitable for answering common sense questions that are difficult for computers to answer but easy for humans to answer. The technologies support solving general common sense problems without a priori knowledge of the problems; support for determining whether an answer is from a bot or human so as to screen out spurious answers from bots; support for distilling answers collected from human users to ensure high quality solutions to the questions asked; and support for preventing malicious elements in or out of the system from attacking other system elements or contaminating the solutions produced by the system, and preventing users from being compensated without contributing answers.

Comprehensive human computation framework

Techniques for an image-based CAPTCHA for object recognition are described. The disclosure describes adding images to a database by collecting images by querying descriptive keywords to an image search engine or crawling images from the Internet. The disclosure describes generating the image-based CAPTCHA. The image is retrieved from the database, along with objects having significant values. An object is cropped from its image. The portion on the image where the object has been cropped is filled with image inpainting. The process obtains other objects from the database. The object is mixed among the other objects to from a set of candidate objects. A user is asked to select 'the object' from the set of candidate objects that fits or matches the image. The image-based CAPTCHA evaluates whether a response, the selection, is from a human or a bot.

Image-based CAPTCHA exploiting context in object recognition

Techniques for generating, updating, and transmitting a structure-based data representation of a document are described herein. The structure-based adaptive document caching techniques may effectively eliminate redundancy in data transmission by exploiting structures of the document to be transmitted. The described techniques partitions a document into a sequence of structures, differentiate between cache-worthy structures and cache-unworthy structures, and generating a structure-based data representation of the document. The techniques may transmit updated structures and instructions, instead of all data of the document, to update previously cached structures at a client device; thereby resulting in higher cache hit rates.

Structure-based adaptive document caching

A trust level of an account is determined at least partly based on a degree of the memorability of an email address associated with the account. Additional features such as those based on the domain of the email address and those from the additional information such as name, phone number, and address associated with the account may also be used to determine the trust level of the account. A machine learning process may be used to learn a classification model based on one or more features that distinguish a malicious account from a benign account from training data. The classification model is used to determine a trust level of the account, and/or if the account is malicious or benign, and may be continuously improved by incrementally adapting or improving the model with new accounts.

Machine-learning based classification of user accounts based on email addresses and other account information

The techniques described herein use training data to train classification models to detect malicious Uniform Resource Locators (URLs) that target authentic resources (e.g., Web page, Web site, or other network locations accessed via a URL). The techniques train the classification models using one or more machine learning algorithms. The training data may include known benign URLs and known malicious URLs (e.g., training URLs) that are associated with a target authentic resource. The techniques then use the trained classification models to determine whether an unknown URL is a malicious URL. The malicious URL determination may be based on one or more lexical features (e.g., brand name edit distances for a domain and path of the URL) and/or site/page features (e.g., a domain age and a domain confidence level) extracted.

Malicious uniform resource locator detection

Technologies for distributed single sign-on operable to provide user access to a plurality of services via authentication to a single entity. The distributed single sign-on technologies provide a set of authentication servers and methods for privacy protection based on splitting secret, keys and user profiles into secure shares and periodically updating shares among the authentication servers without affecting the underlying secrets. The correctness of the received partial token or partial profiles can be verified with non-interactive zero-knowledge proofs.

Disclosed are compounds, compositions and methods for treating various diseases, syndromes, conditions and disorders, including pain. Such compounds are represented by Formula (I) as follows: wherein A, L, R, R, R, and Rare defined herein.

Cold menthol receptor antagonists

Growing community of inventors

Edina, MN, United States of America

Bin Benjamin Zhu