Citrix Systems, Inc.

Other

Nsfocus Information Technology Co., Ltd.

Harvey Woodworking Technology (nanjing) Co., Ltd.

Crrc Nanjing Puzhen Haitai Brake Equipment Co., Ltd.

Jian Ding

Daowen Wei

Hengbo Wang

Feng Tao

Yanjun Su

Manbinder Pal Singh

Yang Li

Li Ping Yang

Arnav Akhoury

Nandikotkur Achyuth

Dong Xu

Divyansh Deora

Qing Qi

Huazhong Sun

Yongjun Lu

Jinzong Yang

Qinghai Xu

Xiaogang Qin

Dingyi Hong

Mingchu Gu

Hongde Xu

Jian Piao

Yurong Wang

Zhen Zhou

Xingjun Lu

Zhanxia Lv

Sheng-Chi Zhang

Yuchun Song

Baichuan Nie

Jianpeng Sun

Jinping Liu

Jinjun Lu

Yinhu Liu

Shen Xing

Ming Ma

Yunzhe Du

Zhengzhuan Yang

Liangliang Cai

A device for pressing materials guided by rollers for a carpentry cutting includes a device body, two base body fixing blocks, an adjustment mechanism and two pressing mechanisms. The device body includes a fist base body and a second base body. The two base body fixing blocks are arranged to press both sides of the base body, respectively. The adjustment mechanism includes a pushing mechanism configured to move the two pressing mechanisms along a direction from the first base body toward the second base body, two compressing mechanisms configured to compress a play between the first base body and the pressing mechanisms and a reset mechanism. Each of the pressing mechanisms includes a roller fixing block connected with the sliding block, and two rollers with a same rolling direction, the two rollers are respectively mounted on both sides of the roller fixing block.

Device for pressing materials guided by rollers for carpentry cutting

A method for video frame analysis includes determining a first dissimilarity metric and a second dissimilarity metric. The first dissimilarity metric may correspond to a first difference between a first foreground of a first key frame in a video and a second foreground of a second key frame following the first key frame in the video. The second dissimilarity metric may correspond to a second difference between the second foreground of the second key frame and a third foreground of a third key frame following the second key frame in the video. A playback of the video may be generated based on the first dissimilarity metric and the second dissimilarity metric. Related systems and computer program products are also provided.

Video frame analysis for targeted video browsing

Described embodiments provide systems and methods for defining a clip within a recording. A device may generate a recording of a session of a user via which a plurality of applications is accessible. The device may detect a transition of an application of the plurality of applications in a foreground of the session. The device may identify, from the recording, a frame corresponding to the transition in the foreground. The device may store an identification of the frame corresponding to the transition to define a clip of the user within the recording using the application in the session.

Extracting clips of application use from recordings of sessions

Methods and systems for using machine learning to provide application recommendations are described herein. A computing device may capture a first edge frame of a first application displayed at the computing device. The computing device may apply machine learning to the first edge frame of the first application to identify a context tag. The computing device may identify applications subsequently accessed in a sequential manner after accessing the first application in a context corresponding to the identified context tag, where each of the applications corresponds to a context level score. The computing device may identify a second application, which may have a higher context level score than remaining applications. Along with the first application, the computing device may display a selectable interface element corresponding to the second application, and selection of the selectable interface element may cause display of an application list that includes the second application.

Contextual application switch based on user behaviors

Typically, when a user switches sessions between devices, the user authenticates the sessions by providing user account information, password, and/or pin code input or other credentials. However, when the user is frequently switching sessions between devices, authenticating sessions may result in the user reducing or even stopping switching across mobile devices. Systems and methods according to this disclosure provide automatic session roaming across mobile devices using proximity authentication. Upon detecting an indication to initiate session roaming, the source device automatically roams the session on the source device to a target device based on a proximity of the source device to the target device. The session is handed off from the source device to the target device as an authenticated user session.

Distance based session roaming

Methods and systems for determining information of applications are described herein. A computing device may receive, from one or more client devices, data indicating application usage events. The computing device may determine, based on the data, popular applications that a target user regularly uses. The computing device may determine, based on the data, recommended applications that users similar to the target user regularly use. The computing device may determine, based on the popular applications and/or the recommended applications, a collection of applications for the target user. The collection of applications may be displayed on a user interface of a client device associated with the target user for expedited access of interested applications.

Systems and methods for expedited access to applications

Techniques are disclosed for providing messaging participant identity leak prevention. An example methodology implementing the techniques includes, receiving, by a computing device, a message from a sender to a recipient via a software application running on the computing device, the software application having a non-confidential messaging view and a confidential messaging view. The method also includes determining a message type of the message, the message type is one of a non-confidential message or a confidential message, and displaying the message in the confidential messaging view of the software application in response to a determination that the message type indicates a confidential message, the confidential messaging view being distinct from the non-confidential messaging view, wherein messaging participant identity information is obfuscated in the display of the message in the confidential messaging view.

Identity leak prevention

Described embodiments provide systems and methods for balancing user sessions using load pattern forecasting are provided here. A device can determine a pattern of load distribution for a session prior to establishment of the session on a server of a computing environment. The pattern can be indicative of load on a server to run the session for a range of time. The device can determine an amount of usage of the plurality of servers on a per server basis. The usage can be indicative of sessions to be run on individual servers for the range of time. The device can select one of the plurality of servers on which to run the session based on a comparison of the pattern of load distribution for the session and the determined amounts of usage of the plurality servers. The device can assign the session to the selected server of the computing environment to balance resource usage across the computing environment.

Load balancing of computing sessions with load patterns

A system and method that automatically terminates an application. A method includes monitoring activity data points for an application launched by a client device within a workspace environment. The activity data points may include user interactions with a physical interface component. State data for each file associated with the application is monitored and, if a determination is made that the application is inactive based on the activity data points, the method determines if a file associated with the application includes unsaved content based on state data. If it is determined that no files for the application include unsaved content, the method forecasts whether the application will be inactive for a future period based on the activity data. The application is terminated if it is determined that no files for the application include unsaved content and the application is forecast to be inactive.

Auto termination of applications based on application and user activity

A computing device may include a display, and a processor coupled to the display and configured to generate a GUI current screen on the display. The GUI current screen may include a first window and a second window docked to the first window, the second window overlapping the first window. The processor may be configured to determine an interaction region in the first window based upon user input in the first window, determine a ratio of overlap between the first window and the second window, and resize the second window based upon the ratio of overlap and so that the second window does not overlap the interaction region.

Computing device with window docking and related systems and methods

The systems and methods discussed herein provide for intelligent identification of applications or tasks to be utilized or performed by a user based on a variety of variables that provide relevant context. In some implementations, applications may be pre-launched or instantiated prior to a user requesting to execute the application, reducing user experience latency and avoiding incorrect application launch. User behavior patterns, location, time of day, user events, etc. may be utilized to identify and recommend or pre-launch relevant applications that should or can be used at any given instance. In some implementations, deep linking may be used to pre-launch or suggest specific tasks to be performed within an application.

Systems and methods for intelligent application instantiation

Methods and systems for performing real time digital content concealment are described herein. A computing device may, in response to detecting a user within view of an image capture device of a client device, perform a first type of text recognition on a first region of digital content and a second type of text recognition on a second region of the digital content, where the first type of text recognition is determined based on a first type of content items contained in the first region and the second type of text recognition is determined based on a second type of content items contained in the second region. Based at least in part on rules corresponding to the user, the computing device may determine content items within the digital content to be concealed, and may modify the digital content to conceal the content items.

Real time digital content concealment

One disclosed method involves determining first data indicative of a context of one or more client devices in response to access of a first file by the one or more client devices, and determining, subsequent to the access of the first file by the one or more client devices, second data indicative of a current context of a first client device. Based at least in part on the first data and the second data being of a first context type, at least one command is generated that causes the first client device to present an indication that the first file is available for access.

Intelligent file access system

In some implementations, a method may involve determining first feature vectors for a plurality of data items accessed by a user of one or more client devices, the first feature vectors representing first contextual data about the one or more client devices at times that respective data items of the plurality of data items were accessed, the plurality of data items including a first data item. A predictive model, configured to classify input feature vectors into context types, may be used to determine that the first feature vector for the first data item is classified as a first context type. A second feature vector representing second contextual data about a first client device operated by the user may be determined and the predictive model may be used to determined that the second feature vector is classified as the first context type. Based at least in part on the first and second feature vectors being classified as the first context type and the first and second data items being of a first data item type, the first client device may be caused to present the second data item.

Context-based notification processing system

Growing community of inventors

Nanjing, China

Jian Ding