Abstract: Methods, systems and apparatuses, including computer programs encoded on computer storage media, are provided for generating prediction models related to targeting and acquiring customers. Thousands of variables of historical data, including data for prospects and external data, are used to train the prediction models. The variables are pre-processed, then sensitivity analysis is performed on the input variables with respect to the target. The variables with the most influence on the target are selected and added to the feature set used for training a prediction model.

Abstract: A method for fetching a content from a web server to a client device is disclosed, using tunnel devices serving as intermediate devices. The client device accesses an acceleration server to receive a list of available tunnel devices. The requested content is partitioned into slices, and the client device sends a request for the slices to the available tunnel devices. The tunnel devices in turn fetch the slices from the data server, and send the slices to the client device, where the content is reconstructed from the received slices. A client device may also serve as a tunnel device, serving as an intermediate device to other client devices. Similarly, a tunnel device may also serve as a client device for fetching content from a data server. The selection of tunnel devices to be used by a client device may be in the acceleration server, in the client device, or in both.

Abstract: Technologies for unsupervised data classification include a computing device that generates a high dimensional profile for each column of a data store that is indicative of topological features of the column. The computing device also analyzes each column using multiple predetermined profiling rules and generates an initial classification for the columns based on profiling rule results. The initial classification may be applied to related columns based on clustering of the columns using the high dimensional profile. The computing device may train a machine learning model based on the initial classification and the high dimensional profile. Input features for training may include the profiling rule results and the high dimensional profile. Classifications may be provided to client devices via a predetermined interface. Other embodiments are described and claimed.

Abstract: The present invention relates to a method of reading out information from a data carrier and to a data carrier utilizing the concept of structured-illumination microscopy or saturated structured-illumination microscopy.

Abstract: Techniques for predicting an amount of at least one biomaterial produced or consumed by a biological system in a bioreactor are provided. Process conditions and metabolite concentrations are measured for the biological system as a function of time. Metabolic rates for the biological system, including specific consumption rates of metabolites and specific production rates of metabolites are determined. The process conditions and the metabolic rates are provided to a hybrid system model configured to predict production of the biomaterial. The hybrid system model includes a kinetic growth model configured to estimate cell growth as a function of time and a metabolic condition model based on metabolite specific consumption or secretion rates and select process conditions, wherein the metabolic condition model is configured to classify the biological system into a metabolic state. An amount of the biomaterial based on the hybrid system model is predicted.

Abstract: A method for retrieving a file system entity at a presence of snapshot restore in a history of the file system entity , the method may include (i) receiving a request to obtain a content of the file system entity (FSE) at a certain point in time (PIT); and (ii) retrieving the content of the FSE at the certain point in time, wherein the retrieving comprises searching for FSE content segments to be included in a response to the request, wherein each FSE content segment has a write time that does not exceed the certain PIT, each FSE content segment is not included in a relevant blind period of time that is associated with a reversible snapshot restore operation, and fulfills another timing criterion.

Abstract: Provided are systems, methods, and computer-program products for identifying a media content stream when the media content stream is playing an unscheduled media segment. A computing device may receive a plurality of media content streams, where at least two of the plurality of media content streams concurrently includes a same unscheduled media segment. The computing device may determine that the media display device is playing the unscheduled media segment by examining the media content available at the current time in each of the plurality of media content streams. The computing device may determine identification information from the media content included in the media content stream. The computing device may determine contextually-related content, which may be disabled while the unscheduled media segment is being played by the media display device. The computing device may display the media content stream and the contextually-related content after the unscheduled media segment has been played.

Abstract: A method for contention reduced update of one or more storage system parameters, the method may include (i) concurrently monitoring the one or more storage system parameters (SSPs) by compute entities (CEs); wherein the concurrently monitoring comprises updating, by the CEs, local counters allocated to different SSPs; (ii) updating, by the CEs, sets of shared counter fields with values of the local counters, wherein different sets are allocated to different SSPs; wherein an updating of a set of a shared counter fields by an CE comprises selecting a shared counter field of the set by the CE; and (iii) calculating values of the different SSPs, wherein a calculating of a value of a SSP is based on at least one value of at least one shared counter field of a set that is allocated to the SSP.

Abstract: A development system with automatic upgrade function and an automatic upgrade method of a development system are provided. The development system includes a memory apparatus and a processor. The memory apparatus stores multiple application modules, an application software upgrade method package, and multiple software packages corresponding to the application modules. The processor is coupled to the memory apparatus and executes the application software upgrade method package to execute an upgrade development system program, where the processor analyzes versions of the software packages, maintains a software package list according to an analysis result, reads a software repository according to the software package list to obtain a software package in a new version, and installs the software package in the new version to upgrade at least one of the application modules.

Abstract: An automated service arrangement and execution system and an automated service arrangement and execution method are provided. The automated service arrangement and execution system includes a storage device and a processor. The storage device stores a data relationship obtaining and parsing module, a calling route planning module, and an execution module. The processor executes multiple modules and receives request data for executing an application programming interface (API). The data relationship obtaining and parsing module creates a calling model according to the request data. The calling model includes multiple API objects and the API, and the calling route planning module establishes a calling path according to the API objects and relationship information between respective multiple input data of the API and input data sources. The execution module executes the API objects and the API in the calling model according to the calling path to generate an execution result of the API.

Abstract: The present disclosure provides a high-performance data lake system and a data storage method. The data storage method includes the following steps: S1: converting a file into a file stream; S2: converting the file stream into an array in which multiple subarrays are nested; and S3: converting the array into a resilient distributed dataset (RDD), and storing the RDD to a storage layer of a data lake. The present disclosure provides a nested field structure, which lays the foundation for parallel processing in reading, and effectively improves read performance. Furthermore, the present disclosure flexibly generates a number of nested subarrays according to hardware cores, such that the data lake achieves better extension performance, and can keep optimal writing efficiency for different users.

Abstract: The present invention provides an omnidirectional distance measuring device that covers a wide detection range and does not require adjustment of each of the detection areas of a plurality of distance measuring sensors. In the omnidirectional distance measuring device, a plurality of distance measuring sensors that measure a distance to a target are disposed radially around a central axis so as to be close to each other. The plurality of distance measuring sensors are integrally configured such that a detection center direction of each of the plurality of distance measuring sensors is inclined by a predetermined angle from a plane perpendicular to the central axis. As the distance measuring sensor, a TOF sensor that measures a distance based on a flight time of light or a stereo camera that measures a distance using parallax of a pair of cameras is used.

Abstract: A method for lock metadata re-balancing upon an expansion of a storage system, the method may include instructing multiple compute entities, by an expansion manager and during a first phase of the lock metadata re-balancing, to acquire locks by using: (a) a current translation function for linking addresses of current lock metadata units (LMUs) to identifiers of stored entities; wherein the current translation function is based on a size of a current storage space allocated to the lock metadata; and (b) a next translation function for linking addresses of new LMUs to identifiers of stored entities; wherein the new translation function is based on a size of a new storage space allocated to the lock metadata; wherein the current space is expanded during the expansion of the storage system to provide the next storage space.

Abstract: A method for determining size information related one or more snapshots related to file systems stored in a storage system, the method may include (a) sampling one or more combinations of points in time and logical spaces, the logical spaces are associated with the one or more file systems to provide sampled combinations of sampled portions of file system entities (FSEs) and sampled points in time; (b) searching for relevant snapshots that are relevant to the sampled combinations to provide relevant snapshots at the sampled points in time; and (c) determining physical sizes of the relevant snapshots at the sampled point in time; wherein a number of samples per sampled FSE is indicative of a size of the sampled FSEs.

Abstract: An intercept engine is installed on a computer and includes an intercept filter adapted to intercept selected commands transmitted between a file system and a storage device. The intercept engine also includes an intercept manager adapted to transmit to the intercept filter one or more primitives, wherein each primitive includes device information specifying a device, wherein a command directed to the specified device is to be intercepted, command type information specifying a type of command to be intercepted, and follow-up action information specifying an action to be performed after the command has been intercepted. A primitive may also include default action information specifying an action to be performed with respect to the command if a communication between the intercept filter and the intercept manager is interrupted. The intercept engine intercepts commands transmitted between the file system and the storage device in accordance with the one or more primitives.

Abstract: A version management system and method are provided. The version management system includes a cloud server and a local server. When a first cloud application programming interface of a first local application programming interface corresponding to a first tenant is updated from a first version to a second version, a cloud version update module publishes first configuration data to be version updated to a configuration repository. When the cloud version update module judges that the first local application programming interface is updated from the first version to the second version through a local version update module, the cloud version update module updates a cloud version correspondence table. When the cloud server calls the first cloud application programming interface, a cloud configuration management module loads the first configuration data to be version updated, so that the cloud server executes the second version of the first cloud application programming interface.

Abstract: Systems and methods of performing identity verification across different geographical or jurisdictional regions are provided. In one exemplary embodiment, a method by a first network node comprises sending, by the first network node located in a first geographical or jurisdictional region, to a second network node located in a second geographical or jurisdictional region, an indication of an identity verification associated with a certain identity based on personally identifiable information of that identity received by the first network node from the second network node. Further, the identity verification is determined based on whether the PII data of the certain identity corresponds to PII data of at least one of a plurality of identities associated with the first region and stored in one or more databases located in the first region and on identity verification rule(s) associated with the first region.

Abstract: The systems and methods described herein analyze one or more selected data sources in their entirety and determine data relationships, using a single-branch approach. Indexes are created based on the determined data relationships, and data from the one or more data sets is imported into the indexes and stored in a back-end storage system. Once the data is analyzed and stored in the indexes, a user can submit a request for a data visualization. In response to the request, the system automatically generates (e.g., builds) and displays the requested data visualization to the user. In some examples, the user may request a modification of the data visualization such as changing the timeframe shown in the data visualization or adding/removing data associated with a particular parameter, and the system will automatically generate the modified data visualization for the user.

Abstract: A biological detection device includes a signal acquirer that acquires a signal including a heartbeat, an analyzer that performs a frequency analysis of the signal to generate a spectrogram, an integrated value calculator that integrates energy of a heartbeat frequency component, which is a frequency component corresponding to the heartbeat, among frequency components of the signal shown by the spectrogram and calculates an integrated value, a peak specifier that specifies peaks, which are maximum values, in the integrated value, a peak set generator that combines, among the peaks, a first peak and a second peak, which occurs in a later time than the first peak, and generates a peak set, and a selector that selects, from the peak set, a sequence having highest likelihood in a maximum likelihood estimation method.

Abstract: An unmanned aerial vehicle-based data collection and distribution system includes a source of animal data that can be transmitted electronically. The source of animal data includes at least one sensor. The animal data is collected from at least one target individual. The system also includes an unmanned aerial vehicle that receives the animal data from the source of animal data as a first set of received animal data and a home station that receives the first set of received animal data. Characteristically, the unmanned aerial vehicle includes a transceiver operable to receive signals from the source of animal data and to send control signals to the source of animal data.