Abstract: Aspects of the disclosure are directed to an approach for training a multivariate time series forecasting model using linear regression and ARIMA. The training may be performed by accessing data stored in a data warehouse using structure query language commands. The disclosure further provides for forecasting utilizing the trained model.

Abstract: A method includes receiving a point data anomaly detection query from a user. The query requests the data processing hardware to determine a quantity of anomalous point data values in a set of point data values. The method includes training a model using the set of point data values. For at least one respective point data value in the set of point data values, the method includes determining, using the trained model, a variance value for the respective point data value and determining that the variance value satisfies a threshold value. Based on the variance value satisfying the threshold value, the method includes determining that the respective point data value is an anomalous point data value. The method includes reporting the determined anomalous point data value to the user.

Abstract: Some embodiments provide a method of identifying packet latency in a software defined datacenter (SDDC) that includes a network and multiple host computers executing multiple machines. At a first host computer, the method identifies and stores (i) multiple time values associated with several packet processing operations performed on a particular packet sent by a first machine executing on the first host computer, and (ii) a time value associated with packet transmission through the SDDC network from the first host computer to a second host computer that is a destination of the particular packet. The method provides the stored time values to a set of one or more controllers to process to identify multiple latencies experienced by multiple packets processed in the SDDC.

Abstract: The present disclosure discloses a fracture repair device realizing transition from mechanical fixation (association of osteosynthesis, AO) to biological fixation (biological osteosynthesis, BO), including: a bone repair instrument, wherein auxiliary components are arranged at positions, close to a repaired bone surface, of the bone repair instrument, and each auxiliary component is made of a degradable metal material or a composite material thereof or a degradable polymeric material. The device of the present disclosure only has the advantages of AO rigid mechanical fixation, but also can effectively improve the defects of bone disconnection, fixed segment osteoporosis, re-fracture after defixation, etc., frequently occurring under AO rigid mechanical fixation, realizing transition from mechanical fixation (association of osteosynthesis, AO) to biological fixation (biological osteosynthesis, BO) during bone fixation or repair.

Abstract: The present application discloses a thin-film transistor, a display panel, and an electronic device. The thin-film transistor includes a gate, a gate insulating layer, and a semiconductor layer sequentially disposed from an inside to an outside along a radial direction. The thin-film transistor further includes a source and a drain disposed on a side of the semiconductor layer and arranged at intervals, and the source and the drain are connected to the semiconductor layer.

Abstract: The present application discloses a display panel. The display panel includes a plurality of light emitting devices distributed in an array, wherein each light-emitting device includes an upper light emitting surface and a side light emitting surface configured to transmit light, and wherein the side light emitting surface is provided with a reflective layer; a plurality of light emitting devices includes a plurality of light emitting devices with different colors, and the reflective layer on the light emitting device with one color is configured to reflect light emitted by the color light emitting devices with another colors.

Abstract: A display panel and an electronic device are provided. The display panel includes a plurality of scan lines, a plurality of data lines, and a plurality of sub-pixel units. Wherein, every N adjacent rows of the sub-pixel units share a same scan line. Every N adjacent strips of the data lines correspond to the sub-pixel units in a same column. In the sub-pixel units in a same column, every N adjacent rows of the sub-pixel units form a pixel group. The sub-pixel units in each pixel group are connected to N strips of the data lines in a one-to-one correspondence. N is a positive integer greater than or equal to four.

Abstract: The application discloses a thin film transistor and a light-emitting diode (LED) backplane. The thin film transistor includes: a first gate, a first insulating layer, a first source, a semiconductor layer, a first drain, a second insulating layer, and a second gate; the first insulating layer covers the first gate; the first source, the semiconductor layer, and the first drain are all disposed at a side of the first insulating layer away from the first gate; the second insulating layer covers the first drain, the semiconductor layer, and the first source; and the second gate is disposed on a surface of a side of the second insulating layer away from the first gate, wherein the first source, the semiconductor layer, and the first drain jointly constitute a vertical channel structure.

Abstract: Some embodiments provide a method for performing data traffic monitoring. The method processes a packet through a packet processing pipeline that includes multiple stages. At a filtering stage, the method tags the packet with a set of monitoring actions for subsequent stages to perform on the packet based on a determination that the packet matches a particular filter. For each stage of a set of packet processing stages subsequent to the filtering stage, the method (i) executes any monitoring actions specified for the stage to perform on the packet and (ii) sends the packet to a next stage in the packet processing pipeline.

Abstract: A driver substrate and a display panel are disclosed. The driver substrate includes a base substrate and a flexible circuit board. The base substrate has a first bonding portion. The flexible circuit board is disposed on a bonding surface of the first bonding portion and bends from the bonding surface to a side of the first bonding portion away from the bonding surface. The flexible circuit board includes a bent portion, an anti-scratch structure is disposed between the bent portion and the first bonding portion, and the bent portion is attached to the anti-scratch structure.

Abstract: Example methods and systems to perform flow cache information update(s) for packet processing are described. In one example, a network element may configure flow cache information specifying a set of actions based on a sequence of stages that is executable during slow-path packet processing. The network element may configure dependency information specifying execution dependence or independence among the set of actions during fast-path packet processing. In response to detecting a configuration change associated with stage(s) from the sequence of stages, the network element may identify first action(s) affected by the configuration change and second action(s) not affected by the configuration change. This way, a granular update may be performed to the flow cache information by updating the at least one first action, but not the at least one second action.

Abstract: The present application discloses a backlight module and a display device. The backlight module includes a substrate, a plurality of LED chips, and a sealant layer. The plurality of LED chips are arranged on the substrate at intervals, and the sealant layer is arranged on the substrate and covers the plurality of LED chips; the sealant layer is provided with a plurality of recesses on a side away from the LED chips, and the plurality of recesses is arranged above the plurality of LED chips in a one-to-one correspondence to the plurality of LED chips, so that light directly above the LED chips is opened to surroundings, and side light emission of the LED chips is increased, thereby increasing brightness of an area between adjacent ones of the LED chips, thus reducing a probability of dark shadows occurring.

Abstract: Some embodiments provide a method for performing data traffic monitoring. The method processes a packet through a packet processing pipeline that includes multiple stages. At a filtering stage, the method tags the packet with a set of monitoring actions for subsequent stages to perform on the packet based on a determination that the packet matches a particular filter. For each stage of a set of packet processing stages subsequent to the filtering stage, the method (i) executes any monitoring actions specified for the stage to perform on the packet and (ii) sends the packet to a next stage in the packet processing pipeline.

Abstract: Example methods and systems for state consistency monitoring in a network environment are described. In one example, a computer system may identify association chain(s) that associate (a) first state information associated with one or more first network entities residing on a first plane with (b) second state information associated with one or more second network entities residing on a second plane. Based on the association chain(s), a consistency check may be performed to compare multiple first fields of the first state information with multiple second fields of the second state information. In response to determination that there is a state inconsistency based on the consistency check, a remediation action to address the state inconsistency by generating and sending at least one of the following: a notification to a user, and a remediation request to a particular first network entity residing on the first plane or a particular second network entity residing on the second plane.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that creates a machine learning model with k-means clustering. In some implementations, an instruction to create a model is obtained. A data set including geographic data and non-geographic data is received. The data set includes multiple data entries. Geographic centroids are determined from the geographic data. The data set is analyzed to obtain statistics of the data set. Transformed data is generated from the data set, the statistics, and the geographic centroids. A model is generated with the transformed data, the model indicating multiple data groupings.

Abstract: A backlight source and a manufacturing method thereof are provided. The backlight source includes a first substrate, a plurality of light sources, a driving circuit layer, and a conductive line. The light sources are distributed on an upper surface of the first substrate. The second substrate is disposed opposite to the first substrate. The driving circuit layer is disposed on a surface of a side of the second substrate away from the first substrate. An end of the conductive line is connected to one of the light sources, and another end of the conductive line is bonded to the driving circuit layer.

Abstract: A splicing type light board and a display device are provided with a first LED light board and a second LED light board; a first end of the first LED light board near a first signal input terminal, and a second end away from the first signal input terminal; a first end of the second LED light board near a second signal input terminal, and a second end away from the second signal input terminal; and the first end of the first LED light board connecting the first end of the second LED light board or the second end of the first LED light board connecting the second end of the second LED light board.

Abstract: A method for time series forecasting includes receiving a time series forecasting query from a user requesting the data processing hardware to perform a plurality of time series forecasts. Each time series forecast is a forecast of future data based on respective current data. Simultaneously, for each time series forecast of the plurality of time series forecasts requested by the time series forecasting query, the method includes training a plurality of models for the respective time series forecast. The method also includes determining which model of the plurality of models best fits the respective time series forecast and forecasting the future data based on the determined best fitting model and the respective current data. The method also includes returning, to the user, the forecasted future data for each of the plurality of time series forecasts request by the timer series forecasting query.

Abstract: A method for forecasting time-series data, when executed by data processing hardware, causes the data processing hardware to perform operations including receiving a time series forecasting query from a user requesting a time series forecast forecasting future data based on a set of current time-series data. The operations include obtaining, from the set of current time-series data, a set of training data. The operations include training, using a first portion of the set of training data, a first sub-model of a forecasting model and training, using a second portion of the set of training data, a second sub-model of the forecasting model. The second portion is different than the first portion. The operations include forecasting, using the forecasting model, the future data based on the set of current time-series data and returning, to the user, the forecasted future data for the time series forecast.

Abstract: The present application provides a resource scheduling method and apparatus, an electronic device, and a computer readable storage medium. The method includes: selecting an optimal path from a pre-constructed resource label forest according to a weight of a path in a resource label tree in the resource label forest; and scheduling a task to a third node through which the optimal path passes. The resource label forest includes the at least one resource label tree, and each path of which includes a first node, a second node and the third node in an order from a root node to leaf nodes.