Results 201 to 210 of about 52,593 (263)
A study of the symptom network structure of internet addiction, non-suicidal self-injury and internalization problems in adolescents and its association with physical activity. [PDF]
Zhu Y, Du Z, Zhang Y, Li X, Meng J.
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Mentorship as a Mechanism for Equity, Retention & Scientific Innovation in Neuroscience-related Careers. [PDF]
Bekele BA +3 more
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Capturing protein-protein interactions in plants: recent advances, challenges, and opportunities. [PDF]
Dickey B +4 more
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An Operational Hybrid SIEM Framework for OT Anomaly Detection. [PDF]
Rahmani J +3 more
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In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network. [PDF]
McClatchy DB +3 more
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Oblivious Routing in IP Networks
IEEE/ACM Transactions on Networking, 2018To optimize the flow of traffic in IP networks, operators do traffic engineering (TE), i.e., tune routing-protocol parameters in response to traffic demands. TE in IP networks typically involves configuring static link weights and splitting traffic between the resulting shortest-paths via the equal-cost-multipath (ECMP) mechanism.
Marco Chiesa +2 more
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Improving IPS by network processors
The Journal of Supercomputing, 2011Many present applications usually require high communication throughputs. Multiprocessor nodes and multicore architectures, as well as programmable NICs (Network Interface Cards) provide new opportunities to take advantage of the available multigigabits per second link bandwidths.
Pablo Cascón +5 more
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An introduction to IP networks
BT Technology Journal, 2000It seems almost impossible to pick up a paper or watch the news without being told about how IP is changing the world. Within the IT business we are often hearing terms such as 'router', 'routeing protocol', 'packet', 'DNS' and 'IP address', but it is not always made clear what these terms actually mean, and how they relate to each other.
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Anomaly detection in IP networks
IEEE Transactions on Signal Processing, 2003Network anomaly detection is a vibrant research area. Researchers have approached this problem using various techniques such as artificial intelligence, machine learning, and state machine modeling. In this paper, we first review these anomaly detection methods and then describe in detail a statistical signal processing technique based on abrupt change
Marina Thottan, Chuanyi Ji
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