Abstract: The present disclosure provides a fluorescence image registration method, the method includes: acquiring a fluorescence image of a biochip; selecting a preset local region of the fluorescence image; acquiring a position of a minimum value of a sum of brightness values of pixels in a first direction and a second direction, and obtaining pixel-level registration points; dividing the pixel-level registration points into non-defective pixels and defective pixels; if the fluorescence image meets the preset standard, correcting positions of the defective pixels according to positions of the non-defective pixels; acquiring a position of a center of gravity of image points of fluorescent molecules according to a center of gravity method; fitting straight lines in the first direction and the second direction respectively according to the position of the center of gravity; and acquiring boundary points of the fluorescence image and calculating the positions of the boundary points.

Abstract: Disclosed are a low-cost high-efficiency drip irrigation system for a cotton field and a use method thereof. The drip irrigation system for a cotton field includes a filtering device and a water supply device; wherein the filtering device adopts different types of single filtering devices or combined filtering devices according to different water source types; the water supply device includes multiple stages of main pipes, submain pipes and laterals; the laterals (a drip irrigation tape with labyrinth on one side or a drip irrigation tape inlaid with emitters inside) are laid on the surface of the ground and located below a mulch film. The drip irrigation system adopts the design of large flow (1.5-3.4 L/h), slightly larger pipe diameter (>75 mm), low water pressure (operating pressure of drip irrigation tape being 0.03-0.07 MPa) and suitable drip irrigation uniformity (80%-90%).

Abstract: Described herein are systems, methods, and software to manage multi-type storage in a cluster computing environment. In one example, a host can identify health and performance information at a first time for each local data store on the host and a hyperconverged data store available to the host. The host can further identify health and performance information associated with the data stores at a second time and can compare the health and performance information at the first time and the second time to identify differences in the information. The host then communicates the differences to a second host in the computing environment.

Abstract: Embodiments of the present disclosure relate to a method, system and computer program product for semantic search based on a graph database. In some embodiments, a method is disclosed. According to the method, the user jobs of a user are obtained from a first software product. Based on the user jobs, target test cases are selected from a plurality of test cases associated with the first software product and a second software product. The target test cases are applied to the first software product and the second software product, and in accordance with a determination that a result of applying the target test cases satisfies a predetermined criterion, an instruction is provided to indicate migrating from the first software product to the second software product. In other embodiments, a system and a computer program product are disclosed.

Abstract: At least one processor identifies dependency relationships among libraries in a repository of libraries. Using the dependency relationships among libraries, at least one machine learning model can be created that predicts with a confidence value a dependency between a given library and a target library. An L layer tree-like graph can be created, using the dependency relationships among libraries and an application package. L can be configurable. Versions of the libraries to use can be determined by running the at least one machine learning model for each pair of nodes having a dependency relationship in the L layer tree-like graph, the at least one machine learning model identifying the dependency relationship with a confidence value, where pairs of nodes having largest confidence values are selected as the versions of the libraries to use in the application package.

Abstract: The disclosure relates to processing application programming interface (API) requests. Embodiments include receiving, at an API wrapper, from a first caller, a first call to an API and sending the first call to the API. Embodiments include receiving, by the API wrapper, from one or more second callers, a second one or more calls to the API prior to receiving a response from the API to the first call. Embodiments include receiving, by the API wrapper, the response from the API to the first call and responding to the first call from the first caller with the response from the API to the first call. Embodiments include responding, by the API wrapper, to the second one or more calls from the one or more second callers with the response from the API to the first call without sending the second one or more calls to the API.

Abstract: The disclosure provides automated update notifications. Embodiments include receiving, by a cloud provider, a request to manage updates for a computing device communicating with the cloud provider via a network. Embodiments include registering an agent at the computing device with the cloud provider as a recipient for an automated update notification based on configuration details of the computing device and detection of an update item related to an aspect of the configuration details. Embodiments include identifying, by the agent, the configuration details of the computing device, the configuration details comprising details of a hardware configuration of the computing device and a software configuration of the computing device. Embodiments include monitoring one or more databases for the update item. Embodiments include transmitting the automated update notification to the agent based on detection of the update item in the one or more databases.

Abstract: The current document is directed to methods and subsystems that manage submitted code changes for processing by continuous-integration/continuous-delivery/deployment systems. In disclosed implementations, code changes are processed as quickly as possible, when the code changes are flagged as being urgent. Non-urgent code changes are evaluated for the possibility of merging the non-urgent code changes with additional, subsequently submitted code changes in order to more efficiently employ computational resources needed for processing the code changes. When there is a code change, waiting for processing, with which a submitted code change can be merged, the submitted code change is merged with the waiting code change so that the merged code changes can be together verified.

Abstract: Example methods and systems associated with dynamic configuration of a statistics endpoint in a virtualized computing environment have been disclosed. One example method includes in response to receiving a first request, by a host in the virtualized computing environment, accepting a configuration file specified in the first request; in response to receiving a second request, by the host, parsing a rule based on the configuration file and collecting statistics based on the rule; processing, by the host, the statistics collected based on the rule; and sending, by the host, the processed statistics to a monitoring terminal.

Abstract: Example methods and systems for request handling with automatic scheduling are described. In one example, a computer system may receive, from multiple client devices, respective multiple requests that are generated and sent according to a first set of control parameters. Based on the multiple requests, request characteristic(s) may be monitored to determine whether an automatic scheduling condition is satisfied. In response to determination that the automatic scheduling condition is satisfied, the computer system may assign a second set of control parameters to the respective client devices and instruct the client devices to generate and send respective multiple subsequent requests according to the second set of control parameters to cause a modification of the request characteristic(s).

Abstract: The health of a distributed storage system provided by a virtualized computing environment may be evaluated. The evaluation techniques categorize health issues based on at least three categories (e.g., storage data availability and accessibility, storage data performance, and storage space utilization and efficiency), and provide priority levels for the health issues within each category. In this manner, a more user-oriented approach is provided wherein in addition to identifying health issues, the priority/urgency level of the health issue(s) can be provided so as to guide the user (such as a system administrator) in determining an appropriate remedial action to perform and when such remedial action should be performed to address health issues.

Abstract: Intelligent capacity planning is provided for storage in a hyperconverged infrastructure environment. The storage may be a logical storage unit that is supported by storage space of a plurality of hardware disks in a virtualized computing environment. Failure predictions can be obtained for each individual hardware disk, and a failure prediction for a number of hardware disk in a hardware disk set can also be obtained. A failure prediction and/or a reduced availability prediction for the logical storage unit can be generated based at least on a configuration state of the logical storage unit, a prediction for one or more hardware disks of the logical storage unit, and a prediction time. Predictions based on what-if operations are also able to be generated.

Abstract: Intelligent capacity planning is provided for storage in a hyperconverged infrastructure environment. The storage may be a logical storage unit that is supported by storage space of a plurality of hardware disks in a virtualized computing environment. Failure predictions can be obtained for each individual hardware disk, and a failure prediction for a number of hardware disk in a hardware disk set can also be obtained. A failure prediction and/or a reduced availability prediction for the logical storage unit can be generated based at least on a configuration state of the logical storage unit, a prediction for one or more hardware disks of the logical storage unit, and a prediction time. Predictions based on what-if operations are also able to be generated.

Abstract: An analytics portal, having a machine learning model, is deployed at an edge device in a virtualized computing environment. The machine learning model may be trained internally in the virtualized computing environment or via trained models received via an external network such as a cloud. The analytics portal is in an active mode, while another analytics portal at another host or edge device in the virtualized computing environment is in a passive mode. An election process may be used to change an analytics portal from the active mode to the passive mode. A failover process is also available to transition the passive analytics portal to the active mode, in response to a failure of the current active analytics portal.

Abstract: Described herein are systems, methods, and software to generate user interfaces to indicate software-defined storage information in view of available hardware resources. In one example, a user interface service may obtain enclosure information associated with enclosures in a computing environment and may determine a storage overview for the plurality of enclosures based on the enclosure information. The user interface service may further determine a function for each storage device in the storage overview in relation to a software-defined storage configuration for the computing environment and generate a user interface to indicate the storage overview with the function for each storage device in the plurality of enclosures.

Abstract: A troubleshooting technique provides faster and more efficient troubleshooting of issues in a distributed system, such as a distributed storage system provided by a virtualized computing environment. The distributed system includes a plurality of hosts arranged in a cluster. The troubleshooting technique uses cluster-wide correlation analysis to identify potential causes of a particular issue in the distributed system, and executes workflows to remedy the particular issue.

Abstract: The disclosure relates to processing application programming interface (API) requests. Embodiments include receiving, at an API wrapper, from a first caller, a first call to an API and sending the first call to the API. Embodiments include receiving, by the API wrapper, from one or more second callers, a second one or more calls to the API prior to receiving a response from the API to the first call. Embodiments include receiving, by the API wrapper, the response from the API to the first call and responding to the first call from the first caller with the response from the API to the first call. Embodiments include responding, by the API wrapper, to the second one or more calls from the one or more second callers with the response from the API to the first call without sending the second one or more calls to the API.

Abstract: A method to migrate a cluster's hosts and virtual machines from virtual standard switches to a virtual distributed switch includes creating distributed port groups on the virtual distributed switch, where properties of the distributed port groups are automatically replicated to host proxy switches on the hosts. The method further includes configuring the distributed port group with ephemeral binding so port binding of the distributed port group is configurable through a host in the cluster even when an infrastructure virtual machine that manages the cluster is down, determining (or receiving user input indicating) the infrastructure virtual machine is on the host, and issuing a call to the host to migrate (1) the infrastructure virtual machine to the distributed port group and (2) one or more physical network interface cards of the host to the virtual distributed switch.

Abstract: A troubleshooting technique provides faster and more efficient troubleshooting of issues in a distributed system, such as a distributed storage system provided by a virtualized computing environment. The distributed system includes a plurality of hosts arranged in a cluster. The troubleshooting technique uses cluster-wide correlation analysis to identify potential causes of a particular issue in the distributed system, and executes workflows to remedy the particular issue.