Search Results for "speed"

...Due to its light-weight architecture, high performance and rich feature set together with its deep integration with Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage, high-speed data ingestion and complex data analysis in the IoT industrial fields. In the scene of factories, there are tens of devices under LAN network. IoTDB can be installed on a local controller server in the factory to receive data from those devices. The local controller server (normal PC or workstation) with IoTDB can provide the ability to persist data and query data with SQL-like interface. ...

Alluxio is the world’s first open source data orchestration technology for analytics and AI for the cloud. It bridges the gap between computation frameworks and storage systems, bringing data from the storage tier closer to the data driven applications. This enables applications to connect to numerous storage systems through a common interface. It makes data local, more accessible and as elastic as compute.

...Large set of built-in Semantic Types (extensible via JSON defined plugins). Extensive Profiling metrics (e.g. Min, Max, Distinct, signatures, …) Sufficiently fast to be used inline. See Speed notes below. Minimal false positives for Semantic type detection. See Performance notes below. Usable in either Streaming, Bulk or Record mode. Broad country/language support - including US, Canada, Mexico, Brazil, UK, Australia, much of Europe, Japan and China. Support for sharded analysis (i.e. Analysis results can be merged) Once stream is profiled then subsequent samples can be validated and/or new samples can be generated.

...It contains a variant of Tight encoding that is tuned for maximum performance and compression with 3D applications (VirtualGL), video, and other image-intensive workloads. TurboVNC, in combination with VirtualGL, provides a complete solution for remotely displaying 3D applications with interactive performance. TurboVNC's high-speed encoding methods have been adopted by TigerVNC and libvncserver, and TurboVNC is also compatible with any other TightVNC derivative. TurboVNC forked from TightVNC in 2004 and still covers all of the TightVNC 1.3.x features, but TurboVNC contains numerous feature enhancements and bug fixes relative to TightVNC, and it compresses 3D and video workloads much better than TightVNC while using generally only 5-20% of the CPU time of the latter. ...

...The data structures tend to change over time, or not be known in advance, working with them must be maintained; 3. All routine work ETL should be automated wherever possible; 4. Compiling the code on the fly bail speed and reserve for the optimization; 5. Sophisticated class hierarchy guarantee easy connection of other open source solutions.

DATAGYM enables data scientists and machine learning experts to label images up to 10x faster. AI-assisted annotation tools reduce manual labeling effort, give you more time to finetune ML models and speed up your go to market of new products. Accelerate your computer vision projects by cutting down data preparation time up to 50%. A machine learning model is only as good as its training data. DATAGYM is an end-to-end workbench to create, annotate, manage, and export the right training data for your computer vision models. Your image data can be imported into DATAGYM from your local machine, from any public image URL or directly from an AWS cloud S3 bucket. ...

As of 2018-06-28, this project has moved to https://github.com/AdamaJava. This copy of the code will remain but all new code updates and releases will be from the new site. Java code developed by the Australian ICGC team for operating on next-generation sequencing data. This code is currently being maintained and expanded by the QIMR Berghofer Genome Informatics team (http://www.qimrberghofer.edu.au/lab/genome-informatics/) More details and documentation can be found on the...

It's a "Hello World" implementation of SOM (Self-Organizing Map) of Teuvo Kohonen, otherwise called as the Kohonen map or Kohonen artificial neural networks.

...It is particularly useful for users that generate ns-2 trace files with other tools such as VanetMobiSim or SUMO (Simulation of Urban Mobility). With ns-2 Trace Toolkit, users can debug their trace files by generating histograms for: (1) node speed, (2) node x-position, and (3) node y-position. These histograms can give hits about concentration of nodes. Additionally, the tool allows users to simulate the movement of the nodes, in different modes: step-by-step and continue motion. During the simulation, the information of each node (speed and position) is shown. Finally, basic manipulation of trace files are also available in the tool. ...

MotoHUD is a Heads Up Display System designed specifically for motorcycles. Drive your bike without taking your eyes off the road. Tachometer, speed, trip meter, mp3s and other great features are provided by MotoHUD.