Abstract: A display device includes: a plurality of backlight modules, where each backlight module includes a plurality of light sources capable of emitting light in at least three different colors; a color-filter-less liquid crystal display module including a plurality of pixel units arranged in an array form and a plurality of scanning lines coupled to the pixel units; where the plurality of backlight modules are arranged in parallel with the liquid crystal display module; where an orthogonal projection of each backlight module onto a plane where the liquid crystal display module is located corresponds to at least two rows of pixel units, where the pixel units in one row are along an length extension direction of each scanning line; and a driving circuit coupled to each backlight module and configured to apply a backlight driving signal to each backlight module.

Abstract: A tape includes: a substrate, a conductive adhesive layer disposed on the substrate, and an insulating layer disposed on a part of a bonding surface of the conductive adhesive layer. The insulating layer is configured to insulate the conductive adhesive layer from a conducting part of an object to be bonded.

Abstract: A device and method for preparing a thermosetting bonded magnet are provided, the device includes a compressed air glue feeding tank and a composite-function mold. A feeding end of the compressed air glue feeding tank is connected to the composite-function mold. The composite-function mold includes a housing, the housing is disposed at an upper end and a lower end of the composite-function mold, and the housing includes a polytetrafluoroethylene upper cover and a polytetrafluoroethylene lower cover; the polytetrafluoroethylene upper cover and the polytetrafluoroethylene lower cover are respectively disposed at the upper end and the lower end of composite-function mold. The method uses a silica gel material as a binder for anisotropic magnets, and the selected raw materials and process are suitable for quickly obtaining a uniform magnet slurry. The curing process is controllable, and there is no organic solvent or heating during the mixing process.

Abstract: A device and method for preparing a thermosetting bonded magnet are provided, the device includes a compressed air glue feeding tank and a composite-function mold. A feeding end of the compressed air glue feeding tank is connected to the composite-function mold. The composite-function mold includes a housing, the housing is disposed at an upper end and a lower end of the composite-function mold, and the housing includes a polytetrafluoroethylene upper cover and a polytetrafluoroethylene lower cover; the polytetrafluoroethylene upper cover and the polytetrafluoroethylene lower cover are respectively disposed at the upper end and the lower end of composite-function mold. The method uses a silica gel material as a binder for anisotropic magnets, and the selected raw materials and process are suitable for quickly obtaining a uniform magnet slurry. The curing process is controllable, and there is no organic solvent or heating during the mixing process.

Abstract: A DIMM slot test system without series connection of test board through JTAG and a method thereof are disclosed. A DIMM connector interface of a test board is inserted to a DIMM slot of a circuit board under test, a CPU generates test data or a test signal based on a test signal with JTAG signal format, the CPU transmits test data to a specified CPLD chip through differential pins or IO pins, the specified CPLD chip records the received data as a test result; the CPU transmits the generated test signal to the specified CPLD chip, which then tests power pins or ground pins, reads and records values of the power pins or the ground pins as the test result; the CPU generates and transmits a test result read signal to the specified CPLD chip through the control pins, obtains the test result through data transmission pins.

Abstract: A preparation method of a Mn-MOF-based cold-adapted nanozyme and a preparation method thereof. The method includes: preparing a Mn(CH3COO)3·2H2O solution by fully dissolving a manganese-containing precursor Mn(CH3COO)3·2H2O in a mixed solution of an alcohol and distilled water; wherein the alcohol is ethanol or methanol; preparing a benzenetricarboxylic acid solution by fully dissolving benzenetricarboxylic acid solid in the mixed solution of the alcohol and distilled water; reacting the Mn(CH3COO)3·2H2O solution with the benzenetricarboxylic acid solution sufficiently using co-precipitation; and centrifuging and removing a supernatant to obtain the MnBTC, where the MnBTC is nano-metal-organic framework (nano-MOF) with a particle size of less than 10 nm.

Abstract: The disclosure provides a cloud computing-based adaptive storage layering system and method. The system includes a data node management module, a metadata management module, an adaptive storage layering module, and a pre-aggregated query routing module. According to predefined rules, node capacity is expanded and shrunk, collected queried hit models and scanned file paths are aggregated and sorted, and layering loading and pre-loading are performed on files. Based on the disclosure, an efficient On-Line Analytical Processing (OLAP) query execution engine may be constructed, to deal with complex OLAP queries of various reporting system. Therefore, the execution efficiency of cloud OLAP engines can be significantly enhanced.

Abstract: The disclosure provides a read-write separation and automatic scaling-based cloud arrangement system and method. Thus, a read operation and a write operation are separated. Capacity expansion and capacity reduction are performed on a cluster. All index data is stored in corresponding object storage. A pre-computing module submits resources (memory and CPU) required by a computing task to an automatic scaling module. Resource creation is performed by invoking API corresponding to an infrastructure automated arrangement tool Terraform, to guarantee the operation of a construction task. The automatic scaling module provides two resource expansion strategies, which are based on time and the maximum number of waiting tasks. According to the disclosure, the utilization rate of cloud resources is increased, costs are lowered, and manual intervention is reduced.

Abstract: An embodiment of the present invention discloses a computing resource configuration method and device for enterprise cloudification. The method comprises the following steps: obtaining parameters configured by a user through a configuration page, wherein the parameters include a proportion of a bidding instance to an on-demand instance; determining a total amount of computing resources required by a computing task after the computing task is obtained; determining the computing resources corresponding to the bidding instance and the computing resources corresponding to the on-demand instance based on existing computing resources, the total amount of the computing resources and the proportion; and applying for the computing resources from a cloud provider based on the computing resources corresponding to the bidding instance and the computing resources corresponding to the on-demand instance. Big data is computed in a bidding instance mode so that the total cost of the computing resources is greatly reduced.

Abstract: The pre-checking method and a pre-checking system based on the OLAP pre-calculation model includes: acquiring a target query statement; querying for a model matching the target query statement in preset N query models one by one, and collecting a query log at the same time; performing analysis on the query log, and judging whether a matching model exists among the N query models according to the result of analysis; and, if no matching model exists, determining modification information for modifying the pre-selected model according to the result of analysis, the target query statement, and the data model set by the user. The pre-checking system includes an acquisition module, a query engine, and a query checking module. Whether a matching model exists can be ascertained timely by performing a pre-query in N models in advance. Thus, it is unnecessary to build models and perform query check repeatedly.

Abstract: A method includes: acquiring unit computation cost and unit storage cost of a currently used cloud computation server in unit time; acquiring all historical query statements of a target user, extracting common characteristics of all the historical query statements, and determining query indexes corresponding to the historical query statements according to the common characteristics; determining query cost of each query index according to the frequency and time of querying a database through the query index and the used computation resources; determining a plurality of current query indexes corresponding to the current query statement based on the acquired current query statement of the target user; determining the total cost corresponding to each current query index according to the plurality of current query indexes through the unit computation cost, the unit storage cost, and the computation resource usage amount and usage time; and recommending a target query index to the target user.

Abstract: The present invention discloses a data query method, device and equipment and a storage medium. A data query method comprises the following steps: receiving an MDX query statement; acquiring related information of measurement and dimension in the MDX query statement; and performing query according to the related information of measurement and dimension to obtain a query result. According to the present invention, an MDX expression is computed by extracting the related information of measurement and dimension and utilizing a distributed computing framework, so that the data analysis efficiency is greatly improved.

Abstract: This application discloses a precomputation method and apparatus for continuous iterative optimization. The precomputation method for continuous iterative optimization includes: determining a query task corresponding to each of a plurality of time periods; and continuously performing multiple rounds of optimization on a precomputation model according to the query task corresponding to each time period. According to this application, the precomputation model is continuously optimized, so that the performance of the precomputation model is improved. Therefore, the technical problem of poor performance caused by long-term non-tuning of the precomputation model can be avoided.

Abstract: The present invention discloses a method and a system for hybrid query based on a cloud analysis scene, and a storage medium. The method comprises the following steps: obtaining query information, and obtaining an index thereof based on the query information; obtaining meta-information of the index based on pre-computation, and comparing the obtained meta-information with the meta-information of an aggregate index; and determining a query mode corresponding to the meta-information based on a comparison result, the query mode including a query mode of storage-computation separation or a MPP architecture. The present invention solves the technical problem that in an ultra-high-dimensional environment, how to enable a pre-computation query system to most efficiently and more stably utilize the pre-computation result to respond to the query of a client most quickly and avoid generating a large amount of redundant data.

Abstract: The present invention discloses a method and a device for processing information by batch-stream fusion, and a storage medium. The method comprises the following steps: Obtaining an index based on an input query statement; extracting a pre-computed index data segment based on the index as a query result; and extracting a re-computed index data segment to update the query result. The present invention solves the technical problem that real-time data and offline data are difficult to fuse and analyze.

Abstract: The cloud cost-based resource deployment system and method includes a dynamic deployment strategy module, a resource life cycle management module, and an automatic resource operation and maintenance module. The dynamic deployment strategy module automatically analyzes and combines resource deployment schemes. The resource life cycle management module docks with Application Program Interface (API) of various public clouds, and internally provides standardized and unified interfaces. The automatic resource operation and maintenance module modifies the resources in real time through the public cloud API and a manner of remotely connecting to infrastructure resources. Unified and efficient management on a plurality of public clouds is performed. For cloud resources, deployment strategy can be automatically adjusted for different operation systems, so that the public clouds can be efficiently used with a low cost.

Abstract: This application discloses a method and apparatus for scoring a precomputation model, a device, and a storage medium. The method includes: calculating, in a plurality of precomputation models, a score when each precomputation model executes a same query load; determining the precomputation model with the largest score as a target precomputation model according to the score of each precomputation model; and using the target precomputation model for query calculation. According to this application, the precomputation model may be quantitatively scored, so that horizontal comparison is conveniently performed when different precomputation models execute query tasks of the same load. Therefore, a user can conveniently select different precomputation models for query calculation.