35%
06.10.2019
or more sophisticated tools such as Burp Suite [3]. Figures 4 and 5 show how these tools can capture entire web sessions.
Figure 3: Anatomy of a web session
35%
09.06.2018
background process waiting for its time to act. With
> SELECT * FROM __InstanceModiFicationEvent WITHIN 5 WHERE TargetInstance ISA "Win32_Service" AND Target Instance.State="Stopped"
such events could
35%
13.06.2016
/O interfaces.
Figure 1 shows an Intel communications platform that features the Intel Xeon Processor E5-2658 and E5-2448L with the Intel Communications Chipset 89xx Development Kit
35%
26.01.2025
.
Fugaku was first on the June 2020 list at 13,400 TFLOPS. The previous system, Summit, achieved only 2,925.75 TFLOPS. Fugaku's results went up a little on the next list (November 2020), at almost 5.5 times
35%
14.11.2013
] or from the sources [5] for all major platforms, and is described in great detail on the project page. After installing the necessary packages and creating an OpenNebula user, oneadmin, you then need
35%
27.09.2024
component, targets larger infrastructures, and only makes sense in environments with more than eight nodes.
Infos
KubeVirt: https://kubevirt.io
Elemental toolkit: https://github.com
35%
30.01.2024
://ralph.allegro.tech
docker-compose configuration: https://github.com/allegro/ralph/tree/ng/contrib/
Extension code: https://ralph-ng.readthedocs.io/en/stable/installation/installation/
Ralph online demo: https
35%
01.06.2024
; the US National Institute of Standards and Technology (NIST) has published guidelines for the use of RFID technology, as well [5]. Finally, do not forget that RFID systems sometimes generate tracking
35%
03.08.2023
limited. In fact, the current version of Project Koku is only interesting for Red Hat users.
Infos
Project Koku: https://project-koku.github.io
Getting started with Koku: https://github.com/project-koku/koku-ui#getting-started
35%
18.07.2013
. Many companies are finding Hadoop to be the new corporate HPC for big data.
Infos
Apache Hadoop: http://hadoop.apache.org/
MapReduce: Simplified Data Processing on Large Clusters : http://research.google.com
