Introduction To The Special Section On Edge/Fog Computing For Infectious Disease Intelligence

Kaijian Xia; Wenbing Zhao; Alireza Jolfaei; Tamer Ozsu

doi:10.1145/3494119

Introduction To The Special Section On Edge/Fog Computing For Infectious Disease Intelligence

ACM Transactions on Internet Technology ◽

10.1145/3494119 ◽

2022 ◽

Vol 22 (3) ◽

pp. 1-2

Author(s):

Kaijian Xia ◽

Wenbing Zhao ◽

Alireza Jolfaei ◽

Tamer Ozsu

Keyword(s):

Infectious Disease ◽

Special Section ◽

Fog Computing

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Guest editorial: Introduction to the Special Section on Load Balancing of Sensory Data for IoT Deep Learning Applications with Edge/Fog Computing (VSI-lbdl)

Computers & Electrical Engineering ◽

10.1016/j.compeleceng.2021.107332 ◽

2021 ◽

Vol 93 ◽

pp. 107332

Author(s):

Bhisham Sharma ◽

Deepika Koundal ◽

Raman Singh

Keyword(s):

Deep Learning ◽

Load Balancing ◽

Guest Editorial ◽

Special Section ◽

Fog Computing ◽

Editorial Introduction ◽

Sensory Data

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A Blockchain and FOT (Fog of Things) based system and method for predicting an Infectious disease transmitted by a virulent respiratory virus

10.21203/rs.3.rs-100784/v1 ◽

2020 ◽

Author(s):

Naveen Tewari ◽

Rajeev Kumar

Keyword(s):

Infectious Disease ◽

Internet Of Things ◽

Data Centers ◽

Respiratory Virus ◽

Fog Computing ◽

Patent Office ◽

Human Beings ◽

Cloud Data ◽

Cloud Data Centers ◽

To Receive

Abstract The present research is generally related to a system and method for predicting an infectious disease such as COVID-19 transmitted by a virulent respiratory virus. Disclosed are a system and method for predicting an infectious disease transmitted by a virulent respiratory virus. The system includes a plurality of Internet of Things (IoT) sensors, a plurality of fog node devices, and a plurality of computing devices in cloud data centers. The IoT sensors are configured to be coupled to a plurality of human beings to generate a health dataset. The fog node devices are associated with a fog layer to receive the health dataset from the IoT sensors to process and to store the health dataset over a blockchain network. The fog node devices process the health dataset at the fog layer by performing a fog computing. The computing devices and cloud data centers receive the processed health dataset from the of fog node devices over the blockchain network. This research is also filed for patent in Indian Patent Office with application number – 202011021969.

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Introduction to the Special Section on Inference for Infectious Disease Dynamics

Statistical Science ◽

10.1214/18-sts331i ◽

2018 ◽

Vol 33 (1) ◽

pp. 1-3

Author(s):

Theodore Kypraios ◽

Vladimir N. Minin

Keyword(s):

Infectious Disease ◽

Special Section ◽

Disease Dynamics ◽

Infectious Disease Dynamics

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IEEE Access Special Section Editorial: Green Cloud and Fog Computing: Energy Efficiency and Sustainability Aware Infrastructures, Protocols, and Applications

IEEE Access ◽

10.1109/access.2018.2805543 ◽

2018 ◽

Vol 6 ◽

pp. 12280-12283 ◽

Cited By ~ 2

Author(s):

Minhaj Ahmad Khan ◽

Tariq Umer ◽

Samee U. Khan ◽

Shui Yu ◽

Abderrezak Rachedi

Keyword(s):

Energy Efficiency ◽

Special Section ◽

Fog Computing ◽

Green Cloud

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IEEE Access Special Section Editorial: Sustainable Infrastructures, Protocols, and Research Challenges for FOG Computing

IEEE Access ◽

10.1109/access.2020.3000845 ◽

2020 ◽

Vol 8 ◽

pp. 110943-110946

Author(s):

Mithun Mukherjee ◽

Maria Gorlatova ◽

James Gross ◽

Mohammad Aazam

Keyword(s):

Special Section ◽

Fog Computing ◽

Research Challenges

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Tissue section lifting for electron microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100081292 ◽

1978 ◽

Vol 36 (2) ◽

pp. 86-87

Author(s):

Adrian F. van Dellen

Keyword(s):

Infectious Disease ◽

Electron Microscopy ◽

Tissue Culture ◽

Organ System ◽

Surrounding Tissue ◽

Paraffin Sections ◽

Surface Areas ◽

Specific Determination ◽

High Degree ◽

Accuracy And Repeatability

The morphologic pathologist may require information on the ultrastructure of a non-specific lesion seen under the light microscope before he can make a specific determination. Such lesions, when caused by infectious disease agents, may be sparsely distributed in any organ system. Tissue culture systems, too, may only have widely dispersed foci suitable for ultrastructural study. In these situations, when only a few, small foci in large tissue areas are useful for electron microscopy, it is advantageous to employ a methodology which rapidly selects a single tissue focus that is expected to yield beneficial ultrastructural data from amongst the surrounding tissue. This is in essence what "LIFTING" accomplishes. We have developed LIFTING to a high degree of accuracy and repeatability utilizing the Microlift (Fig 1), and have successfully applied it to tissue culture monolayers, histologic paraffin sections, and tissue blocks with large surface areas that had been initially fixed for either light or electron microscopy.

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