The invention is related to a sphere of mobile advertisement. The user wearable device for video information and advertising material demonstration represented by a user wearable personal item is equipped with multimedia device comprising the display placed on the front wall of the personal item and electrically connected with the processor unit placed inside the personal item and connected to the power unit. The processor unit is designed as microprocessor board represented by single-chip BLUETOOTH controller with integrated processor functioning as a processor and signal reception unit in the wireless communication mode with a mobile communication device. The display is designed as a flexible film OLED panel placed in the pocket on the font side of the personal item, which can be closed and whose front wall is made of transparent material.

An error correction and fault tolerance method and system for an array of disks is presented. The array comprises k+5 disks, where k disks store user data and 5 disks store computed parity. The present invention further comprises a method and a system for reconstituting the original content of each of the k+5 disks, when up to 5 disks have been lost, wherein the number of disks at unknown locations is E and the number of disks wherein the location of the disks is known is Z. All combinations of faulty disks wherein Z+2×E≤4 are reconstituted. Some combinations of faulty disks wherein Z+2×E≥5 are either reconstituted, or errors are limited to a small list.

Some aspects include a method for synchronizing at least two devices, including: connecting the at least two devices using an application executed on each of the at least two devices, wherein: a same media is executed in synchronization by the at least two devices using the application; and an input received by the application executed on a first device of the at least two devices actuates a same response on the at least two devices.

In an embodiment, agricultural intelligence computer system stores a digital model of nutrient content in soil which includes a plurality of values and expressions that define transformations of or relationships between the values and produce estimates of nutrient content values in soil. The agricultural intelligence computer receives nutrient content measurement values for a particular field at a particular time. The agricultural intelligence computer system uses the digital model of nutrient content to compute a nutrient content value for the particular field at the particular time. The agricultural intelligence computer system identifies a modeling uncertainty corresponding to the computed nutrient content value and a measurement uncertainty corresponding to the received measurement values. Based on the identified uncertainties, the modeled nutrient content value, and the received measurement values, the agricultural intelligence computer system computes an assimilated nutrient content value.

File access statistics associated with a content file are maintained by a file tier agent of a secondary storage system. The content file is accessible via a primary storage system. A target storage tier corresponding to the file access statistics associated with the content file is determined according to one or more policies. At least a portion of data of the content file is migrated to the determined storage tier while accessibility of the content file via the primary storage system is maintained.

In a method for dynamically binding data in an application, an expression describing a relation between a first property of a first data of the application to a first property of a second data of the application is received. A binding is created between the first data and the second data based on the relation. A change is propagated to the first property of the second data based on a change to the first property of the first data. The receiving the expression and the creating the binding are repeated to create a plurality of bindings based on a plurality of expressions, and the receiving the expression and the creating the binding occur dynamically during an execution of the application.

A medical device comprises a control system, processing modules, and a wire bundle connecting the control system to the processing modules, the wire bundle comprising control lines and data lines. Each processing module is coupled to a respective set of sensors arranged to interface with a biological tissue site, the sensors being configured to capture analog physiological signals generated from the biological tissue site. The control system is configured to generate a control signal on the control lines to initiate a data collection cycle by the processing modules. In response to the control signal, each processing module is configured to perform a respective data collection process which comprises (i) capturing and processing an analog physiological signal on each enabled sensor to generate a data sample for each analog physiological signal captured on each enabled sensor, and (ii) outputting data samples to the control system on the data lines.

A medical device comprises a control system, processing modules, and a wire bundle connecting the control system to the processing modules, the wire bundle comprising control lines and data lines. Each processing module is coupled to a respective set of sensors arranged to interface with a biological tissue site, the sensors being configured to capture analog physiological signals generated from the biological tissue site. The control system is configured to generate a control signal on the control lines to initiate a data collection cycle by the processing modules. In response to the control signal, each processing module is configured to perform a respective data collection process which comprises (i) capturing and processing an analog physiological signal on each enabled sensor to generate a data sample for each analog physiological signal captured on each enabled sensor, and (ii) outputting data samples to the control system on the data lines.

An improved buffer for networking and other computing devices comprises multiple memory instances, each having a distinct set of entries. Transport data units (“TDUs”) are divided into storage data units (“SDUs”), and each SDU is stored within a separate entry of a separate memory instance in a logical bank. One or more grids of the memory instances are organized into overlapping logical banks. The logical banks are arranged into views. Different destinations or other entities are assigned different views of the buffer. A memory instance may be shared between logical banks in different views. When overlapping logical banks are accessed concurrently, data in a memory instance that they share may be recovered using a parity SDU in another memory instance. The shared buffering enables more efficient buffer usage in a network device with a traffic manager shared amongst egress bocks. Example read and write algorithms for such buffers are disclosed.

Systems and methods for determining the impact of a modification made to an API is provided. The system may include an association rule learning subsystem and a recommender subsystem. The association rule learning subsystem may receive input from an API, a metadata processor and a plurality of production logs. The API may include a plurality of API elements. The association rule learning subsystem may link each API element with one or more data elements retrieved by the metadata processors based on data retrieved from the plurality of production logs. The association rule learning subsystem may create and output a tree of API elements and linked data elements. A recommender subsystem may receive the tree. The recommender subsystem may prioritize the data elements included in the tree based on data element severity, data element frequency and data element complexity. The recommender subsystem may select a prioritized subset of the data elements.