Random Multi Hazard Resilience Modeling of Engineered Systems and Critical Infrastructure

The hest for technological advancement in mobile communication is due to augmentation of wireless user. The deployment of 5G mobile communication is less than 4G mobile communication due to challenges in security like cyberwarfare, espionage, critical infrastructure threats. Nevertheless, critic of neurological discomforts, tissue damage in living organisms occur in the existence of EMF radiation. Also, physical scarcity for spectral efficiency arises due to ubiquitous data traffic. Inspite of these disputes data rate, low latency, device to device communication is also a challenge. In this paper we provide a survey on radiation effects, security threats, traffic management.

Download Full-text

Critical Infrastructure Assurance: Electric Power Reliability

10.21236/ada374150 ◽

1999 ◽

Author(s):

Maximilian K. Bremer ◽

Daniel Feliz ◽

Troy Perry

Keyword(s):

Electric Power ◽

Critical Infrastructure ◽

Power Reliability

Download Full-text

Principles and Algorithms for Natural and Engineered Systems

10.21236/ada619896 ◽

2014 ◽

Author(s):

Perinkulam S. Krishnaprasad

Keyword(s):

Engineered Systems

Download Full-text

Critical Infrastructure: Making It Private or Public An Institutional Economic Discussion on the Example of Transport Infrastructure

SSRN Electronic Journal ◽

10.2139/ssrn.2628367 ◽

2015 ◽

Cited By ~ 1

Author(s):

Isabella Geis ◽

Wolfgang H. Schulz

Keyword(s):

Critical Infrastructure ◽

Transport Infrastructure ◽

Institutional Economic

Download Full-text

Novel biological removal of hazardous chemicals at trace levels

Water Science & Technology ◽

10.2166/wst.2000.0238 ◽

2000 ◽

Vol 42 (12) ◽

pp. 49-60 ◽

Cited By ~ 4

Author(s):

P.L. McCarty

Keyword(s):

Plug Flow ◽

Chlorinated Solvents ◽

Biological Removal ◽

Sanitary Landfills ◽

Low Levels ◽

Trace Chemicals ◽

Engineered Systems ◽

Biological Methods ◽

Aerobic And Anaerobic ◽

Flow Treatment

Of recent concern is the removal of toxic compounds in wastewaters, soils, and groundwater to concentrations in the low microgram per litre level or less. Threshold limits to bioremediation exist and must be considered in biological treatment schemes to achieve such limits. These limits may be related to reaction kinetics or thermodynamics. Techniques for removing compounds below threshold levels exist that rely on appropriate approaches such as plug flow treatment. Novel biological methods exist for removal of refractory contaminants to low levels. Examples are provided for removal of trace levels of chlorinated solvents, such as tetrachloroethene (PCE) and trichloroethene (TCE), that employ dehalorespiration under anaerobic conditions or cometabolism under aerobic conditions. These approaches are currently being used in engineered systems or through natural attenuation for remediation of soils and groundwater. Successful results offer insights for similar removals of trace chemicals in both aerobic and anaerobic biological systems for treatment of wastewaters and sanitary landfills.

Download Full-text

Proceedings of the 2019 ACM International Symposium on Blockchain and Secure Critical Infrastructure - BSCI '19

10.1145/3327960 ◽

2019 ◽

Keyword(s):

International Symposium ◽

Critical Infrastructure

Download Full-text

Perception

10.1093/oso/9780199674923.003.0025 ◽

2018 ◽

Author(s):

Joel Z. Leibo ◽

Tomaso Poggio

Keyword(s):

Computational Neuroscience ◽

Feature Detection ◽

Pedestrian Detection ◽

Detection Systems ◽

Catching Up ◽

Feature Detectors ◽

Recognition Systems ◽

Engineered Systems ◽

Perceptual Systems ◽

The Brain

This chapter provides an overview of biological perceptual systems and their underlying computational principles focusing on the sensory sheets of the retina and cochlea and exploring how complex feature detection emerges by combining simple feature detectors in a hierarchical fashion. We also explore how the microcircuits of the neocortex implement such schemes pointing out similarities to progress in the field of machine vision driven deep learning algorithms. We see signs that engineered systems are catching up with the brain. For example, vision-based pedestrian detection systems are now accurate enough to be installed as safety devices in (for now) human-driven vehicles and the speech recognition systems embedded in smartphones have become increasingly impressive. While not being entirely biologically based, we note that computational neuroscience, as described in this chapter, makes up a considerable portion of such systems’ intellectual pedigree.

Download Full-text