Abstract: A system and a method for parameter optimization with adaptive search space and a user interface using the same are provided. The system includes a data acquisition unit, an adaptive adjustment unit and an optimization search unit. The data acquisition unit obtains a set of executed values of several operating parameters and a target parameter. The adaptive adjustment unit includes a parameter space transformer and a search range definer. The parameter space transformer performs a space transformation on a parameter space of the operating parameters according to the executed values. The search range definer defines a parameter search range in a transformed parameter space based on the sets of the executed values. The optimization search unit takes the parameter search range as a limiting condition and takes optimizing the target parameter as a target to search for a set of recommended values of the operating parameters.

Abstract: A modular planting material for natural turf in sports field and its manufacturing process, the material is consist of a far-infrared mineral substrate, a multi-biochar, and a polysaccharide polymer; wherein the far-infrared mineral substrate is composed of SiO2, ZnO, CaO, Al2O3, Fe2O3, K2O, MgO, TiO2, CeO2, La2O3, pulverized fuel ash 1, and raw carbon powder; the multi-biochar is composed of rice husk, oil millet husk, and oil millet stalk; the polysaccharide polymer is composed of polyuronic acid, sodium salt, and cellulose; The present invention let 75˜85% far-infrared mineral substrate, 10-20% multi-biochar, and 2˜5% polysaccharide polymer be mixed, stirred, dried, heated and pressed into shape, high temperature sterilized and molded, and cooled and pressed, then cut to form a natural turf modular planting material. Since the modular planting material has many pores, it has the feature of water retention, air permeability and promoting the growth of the beneficial bacteria and the plants.

Abstract: In one embodiment, a method selects a percentage of a plurality hosts that are coupled together via a network fabric and calculates a number of workloads needed for the percentage of hosts based on a benchmark test to run. A plurality of data compute nodes are configured on one or more host pairs in the percentage of the plurality of hosts to send and receive the number of workloads through the network fabric to perform the benchmark test. A set of measurements is received for sending and receiving the workloads through the network fabric using the plurality of data compute nodes. The method increases the percentage of the plurality of hosts until the set of measurements fails a criteria or the percentage of the plurality of hosts is all of the plurality of hosts.

Abstract: Exemplary methods, apparatuses, and systems include receiving time series data for each of a plurality of performance metrics. The time series data is sorted into buckets based upon an amount of variation of time series data values for each performance metric. The time series data in each bucket is divided into first and second clusters of time series data points. The bucket having the greatest distance between clusters is used to determine a performance metric having a greatest distance between clusters. The performance metric having the greatest distance between clusters is reported as a potential root cause of a performance issue.

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: Exemplary methods, apparatuses, and systems include receiving time series data for each of a plurality of performance metrics. The time series data is sorted into buckets based upon an amount of variation of time series data values for each performance metric. The time series data in each bucket is divided into first and second clusters of time series data points. The bucket having the greatest distance between clusters is used to determine a performance metric having a greatest distance between clusters. The performance metric having the greatest distance between clusters is reported as a potential root cause of a performance issue.

Abstract: In one embodiment, a method selects a percentage of a plurality hosts that are coupled together via a network fabric and calculates a number of workloads needed for the percentage of hosts based on a benchmark test to run. A plurality of data compute nodes are configured on one or more host pairs in the percentage of the plurality of hosts to send and receive the number of workloads through the network fabric to perform the benchmark test. A set of measurements is received for sending and receiving the workloads through the network fabric using the plurality of data compute nodes. The method increases the percentage of the plurality of hosts until the set of measurements fails a criteria or the percentage of the plurality of hosts is all of the plurality of hosts.

Abstract: A tuning engine for a virtualized computing system is described that periodically collect performance metrics from the virtualized computing system, and detects whether a change in system state has occurred based on the collected metrics. The tuning engine may determine whether the virtualized computing system is densely virtualized, and accordingly modify operations and configuration settings of various components in charge of handling networking for the virtualized computing system.

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: A tuning engine for a virtualized computing system is described that periodically collect performance metrics from the virtualized computing system, and detects whether a change in system state has occurred based on the collected metrics. The tuning engine may determine whether the virtualized computing system is densely virtualized, and accordingly modify operations and configuration settings of various components in charge of handling networking for the virtualized computing system.

Abstract: An anti-scattering structure which comprises a substrate having a first surface; and a polymer layer of a urea as an anti-scattering layer.

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: Some embodiments provide a queue management system that efficiently and dynamically manages multiple queues that process traffic to and from multiple virtual machines (VMs) executing on a host. This system manages the queues by (1) breaking up the queues into different priority pools with the higher priority pools reserved for particular types of traffic or VM (e.g., traffic for VMs that need low latency), (2) dynamically adjusting the number of queues in each pool (i.e., dynamically adjusting the size of the pools), (3) dynamically reassigning a VM to a new queue based on one or more optimization criteria (e.g., criteria relating to the underutilization or overutilization of the queue).

Abstract: An antenna selection method includes respectively utilizing each antenna of a plurality of antennas to receive a plurality of transmission signals from a plurality of stations to generate a plurality of reception signals, respectively estimating a plurality of signal quality indicators corresponding to the plurality of stations according to the plurality of reception signals for each of the plurality of antennas, calculating a weighted sum of the plurality of corresponding signal quality indicators to generate a calculation result for each of the plurality of antennas, and selecting a receiving antenna from the plurality of antennas according to the corresponding calculation result of each of the plurality of antennas.

Abstract: An antenna selection method includes respectively utilizing each antenna of a plurality of antennas to receive a plurality of transmission signals from a plurality of stations to generate a plurality of reception signals, respectively estimating a plurality of signal quality indicators corresponding to the plurality of stations according to the plurality of reception signals for each of the plurality of antennas, calculating a weighted sum of the plurality of corresponding signal quality indicators to generate a calculation result for each of the plurality of antennas, and selecting a receiving antenna from the plurality of antennas according to the corresponding calculation result of each of the plurality of antennas.

Abstract: A photosensitive button structure includes a button body and a photosensitive layer. The photosensitive layer is disposed on a bottom side of the button body, and has a plurality of words and pictures formed thereon. Whereby, the photosensitive layer produces a first color change by absorbing light from one angle, and then produces a second color change or more than two color changes by absorbing light from another angle, in order to produce a dual mode visual effect. The present invention solves problems and the defects of the traditional button having only one fixed color, and that the color of the traditional button can only be changed once, because the photosensitive layer can absorb light from different angles. Hence, the present invention not only improves the appearance of the button body, but can also show more than two color changes of any words or pictures on the button structure.