scholarly journals Futuristic Cyber-Twin Architecture for 6G Technology to Support Internet of Everything

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Sapna Juneja ◽  
Mamta Gahlan ◽  
Gaurav Dhiman ◽  
Sandeep Kautish
Keyword(s):  
Rapid Growth ◽  
Internet Traffic ◽  
Network Data ◽  
Network Architectures ◽  
Internet Of Everything ◽  
Audio Video ◽  
Digital Assets

With the rapid growth of Internet of Everything, there is a huge rise in the transportable Internet traffic due to which its associated resources have exceptional obstacles which include reliability, security, expandability, security, and portability which the current available network architectures are unable to deal with. In this paper, an IoT centric cyber-physical twin architecture has been proposed for 6G Technology. The cyber-twin technology helps out in serving stronger communication and also contains several features that help out in assisting communication like maintaining a log record of network data and managing all digital assets like images, audio, video, and so forth. These features of the cyber-twin technology enable the proposed network to deal with those exceptional obstacles and make the system more reliable, safe, workable, and adaptable.

scholarly journals Prefetching of Web Objects For Effective Retrieval Process Through Data Mining Techniques

2021 ◽  
Author(s):  
T S Bhagavath Singh ◽  
S Chitra
Keyword(s):  
Data Mining ◽  
Internet Traffic ◽  
Network Architectures ◽  
Retrieval Process ◽  
Data Mining Techniques ◽  
Exponential Increase ◽  
Web Objects ◽  
Innovative Idea ◽  
Web Latency ◽  
Clustered Network

Abstract With the exponential increase of the internet’s user base, performance enhancing network architectures and algorithms has manifested themselves as a requisite. Algorithms for Prefetching and Caching of Web Objects have been observed to effectively minimize user perceived latency. These algorithms are made use of in architectures limited to a particular user. We can further improve the performance of these algorithms by making use of techniques like data mining. We propose an innovative idea of implementing Prefetching and Caching algorithms in a Clustered Network. This will enable all users in a particular cluster to make use of pre-fetched and cached web objects from all other users. The result of simulations indicates a reduction in web latency, internet traffic, and bandwidth consumed.

scholarly journals ADROIT AQUACULTURE SURVEILLANCE SYSTEM

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
Avinash Wilson J ◽  
Anusha P ◽  
Arun P
Keyword(s):  
Internet Of Things ◽  
Rapid Growth ◽  
Mobile Application ◽  
Surveillance System ◽  
Well Being ◽  
Internet Of Everything ◽  
Set Up ◽  
And Control ◽  
Growing Population

Aquaculture is one of the indispensable fields that helps in the chain of nourishment by feeding the world’s growing population, with 93.6 million metric tons to meet the world’s seafood needs by 2030. Internet of Things (IoT) or Internet of Everything is a blooming paradigm that changes the way of interaction with the environment, which has global attention of the industries in its rapid growth. Incorporating the IoT in the observation of seafood cultivating procedures can improve the productivity and supportability while upgrading the business with the next generation technologies. In Aquaculture, a handful of units are set-up in the deep seas, while the majority of the units are set inland. In inland offices, the ocean organisms are cultured in tanks that can change in volumes and materials. In such cases where profitable aquaculture is done, numerous endeavors are taken to augment the well-being of the sea creatures. Here, we are proposing an exceptionally beneficial aquaculture framework, designed for the aquafarming unit employments, for observing the quality of the water, controlling the system’s irregularity and providing real-time updates to the aqua-farmer. The Aqua-Farmer can surveille the units and control the water circulation remotely through a mobile application.

Removing Substrate Background in TEM Microanalysis

1974 ◽  
Vol 32 ◽  
pp. 568-569
Author(s):  
John C. Russ ◽  
Nicholas C. Barbi
Keyword(s):  
Electrical Conductivity ◽  
Rapid Growth ◽  
Organic Film ◽  
Absolute Concentration ◽  
Background Signal ◽  
X Ray ◽  
Elemental Concentrations ◽  
Transmission Electron ◽  
Electron Microscopes ◽  
The Continuum

The rapid growth of interest in attaching energy-dispersive x-ray analysis systems to transmission electron microscopes has centered largely on microanalysis of biological specimens. These are frequently either embedded in plastic or supported by an organic film, which is of great importance as regards stability under the beam since it provides thermal and electrical conductivity from the specimen to the grid.Unfortunately, the supporting medium also produces continuum x-radiation or Bremsstrahlung, which is added to the x-ray spectrum from the sample. It is not difficult to separate the characteristic peaks from the elements in the specimen from the total continuum background, but sometimes it is also necessary to separate the continuum due to the sample from that due to the support. For instance, it is possible to compute relative elemental concentrations in the sample, without standards, based on the relative net characteristic elemental intensities without regard to background; but to calculate absolute concentration, it is necessary to use the background signal itself as a measure of the total excited specimen mass.

Dysarthric Sentence Intelligibility

1998 ◽  
Vol 41 (6) ◽  
pp. 1282-1293 ◽  
Author(s):  
Jane Mertz Garcia ◽  
Paul A. Dagenais
Keyword(s):  
Speech Intelligibility ◽  
Presentation Mode ◽  
Contextual Influences ◽  
Motor Functioning ◽  
Video Presentation ◽  
Independent Information ◽  
Communicative Process ◽  
Presentation Formats ◽  
Sentence Intelligibility ◽  
Audio Video

This study examined changes in the sentence intelligibility scores of speakers with dysarthria in association with different signal-independent factors (contextual influences). This investigation focused on the presence or absence of iconic gestures while speaking sentences with low or high semantic predictiveness. The speakers were 4 individuals with dysarthria, who varied from one another in terms of their level of speech intelligibility impairment, gestural abilities, and overall level of motor functioning. Ninety-six inexperienced listeners (24 assigned to each speaker) orthographically transcribed 16 test sentences presented in an audio + video or audio-only format. The sentences had either low or high semantic predictiveness and were spoken by each speaker with and without the corresponding gestures. The effects of signal-independent factors (presence or absence of iconic gestures, low or high semantic predictiveness, and audio + video or audio-only presentation formats) were analyzed for individual speakers. Not all signal-independent information benefited speakers similarly. Results indicated that use of gestures and high semantic predictiveness improved sentence intelligibility for 2 speakers. The other 2 speakers benefited from high predictive messages. The audio + video presentation mode enhanced listener understanding for all speakers, although there were interactions related to specific speaking situations. Overall, the contributions of relevant signal-independent information were greater for the speakers with more severely impaired intelligibility. The results are discussed in terms of understanding the contribution of signal-independent factors to the communicative process.

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data

The Multilevel p2 Model

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders
Keyword(s):  
Social Network ◽  
Network Data ◽  
Mcmc Algorithm ◽  
Independent Observation ◽  
Single Observation ◽  
Multiple Networks ◽  
Social Network Data ◽  
Multiple Observations ◽  
Practical Support ◽  
The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

Collection of Ego-Centered Network Data with Computer-Assisted Interviews

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Joachim Gerich ◽  
Roland Lehner
Keyword(s):  
Survey Methods ◽  
A Priori ◽  
Dynamic Structure ◽  
Computer Assisted ◽  
Network Data ◽  
Great Effort ◽  
Self Administration ◽  
Face To Face ◽  
Full Network

Although ego-centered network data provide information that is limited in various ways as compared with full network data, an ego-centered design can be used without the need for a priori and researcher-defined network borders. Moreover, ego-centered network data can be obtained with traditional survey methods. However, due to the dynamic structure of the questionnaires involved, a great effort is required on the part of either respondents (with self-administration) or interviewers (with face-to-face interviews). As an alternative, we will show the advantages of using CASI (computer-assisted self-administered interview) methods for the collection of ego-centered network data as applied in a study on the role of social networks in substance use among college students.

Positional Estimation Within a Latent Space Model for Networks

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Susan Shortreed ◽  
Mark S. Handcock ◽  
Peter Hoff
Keyword(s):  
Random Effects ◽  
Network Data ◽  
Random Effects Models ◽  
Space Model ◽  
Network Analyses ◽  
Recent Advances ◽  
Latent Space ◽  
Latent Space Model ◽  
Modeling Data

Recent advances in latent space and related random effects models hold much promise for representing network data. The inherent dependency between ties in a network makes modeling data of this type difficult. In this article we consider a recently developed latent space model that is particularly appropriate for the visualization of networks. We suggest a new estimator of the latent positions and perform two network analyses, comparing four alternative estimators. We demonstrate a method of checking the validity of the positional estimates. These estimators are implemented via a package in the freeware statistical language R. The package allows researchers to efficiently fit the latent space model to data and to visualize the results.

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