Containing epidemics in a local cluster via antidote distribution and partial quarantine

2021 ◽  
Vol 104 (3) ◽  
Author(s):  
Zhenqi Lu ◽  
Johan Wahlström ◽  
Arye Nehorai
Keyword(s):  
Local Cluster

Chemical Bonds Properties and Spontaneous Polarization of Orthogonal SrBi2Ta2O9 Crystals

2016 ◽  
Vol 848 ◽  
pp. 688-695
Author(s):  
Xiao Hong Xiao ◽  
Shi Chun Li
Keyword(s):  
Spontaneous Polarization ◽  
Cluster Structure ◽  
Chemical Bonds ◽  
Local Cluster ◽  
Valence Electron Density ◽  
Effective Valence ◽  
Individual Bond ◽  
Atomic Coordination ◽  
Experimental Values ◽  
The Individual

The bonds structure, atomic coordination situation and local cluster structure in SrBi2Ta2O9 were analyzed by means of the Atomic Environment Calculation (AEC), and then the SrBi2Ta2O9 crystal was decomposed into 20 pseudo-binary crystals with the crystal decomposition method. The chemical bonds properties, such as effective valence electron density and iconicity of the individual bond were calculated by the dielectric chemical bonds theory. And the correlation between chemical bonds properties and spontaneous polarization of the bismuth layered ferroelectrics was established. Finally, the spontaneous polarization in ferroelectric SrBi2Ta2O9 and other relevant ferroelectrics were calculated, which are in good agreement with the experimental values and other theoretical calculated values.

scholarly journals Spectra of Local Cluster Flows on Open Chain of Contours

2018 ◽  
Vol 11 (3) ◽  
pp. 628-644 ◽  
Author(s):  
Alexander Pavlovich Buslaev ◽  
Alexander G Tatashev
Keyword(s):  
Dynamical System ◽  
Unit Length ◽  
Self Organization ◽  
Similar System ◽  
Open Chain ◽  
Local Cluster ◽  
Closed Chain

A dynamical system is considered. This dynamical system is a flow of clusters with the same length $l$ on contours of unit length connected into open chain. A similar system such that contours of this system are connected into closed chain was considered earlier. It has been found that, in the case of closed chain of contours, the dynamical system has a spectrum of velocity and mode periodicity consisted of more than one component. In this paper, it has been shown that, in the case of open chain, the spectrum of cluster velocity and mode periodicity contains only one component.The conditions of self-organization and the dependence of cluster velocity on load $l$ is developed.

Local cluster formation in a cobalt melt during the cooling process

2001 ◽  
Vol 65 (3) ◽  
Author(s):  
Li Hui ◽  
Wang Guanghou ◽  
Bian Xiufang ◽  
Ding Feng
Keyword(s):  
Cluster Formation ◽  
Cooling Process ◽  
Local Cluster

scholarly journals Local Clusters as “Building Blocks” for Smart Specialization Strategies: A Dynamic SWOT Analysis Application in the Case of San Diego (US)

2019 ◽  
Vol 11 (19) ◽  
pp. 5541
Author(s):  
Carmelina Bevilacqua ◽  
Ilaria Giada Anversa ◽  
Gianmarco Cantafio ◽  
Pasquale Pizzimenti
Keyword(s):  
Conceptual Framework ◽  
Economic System ◽  
San Diego ◽  
Swot Analysis ◽  
Building Blocks ◽  
Business Environment ◽  
Data Set ◽  
Local Cluster ◽  
Smart Specialization

The paper aimed at exploring the role of local industrial clusters as a part of an important evidence-based pathway for operationalizing smart specialization policy. Hitherto, the scientific debate has been largely focused on the relationship of clusters with the local business environment to boost competitiveness and has mostly searched for the operationalization of smart specialization policy in economically successful regions. However, the understanding of the role of local clusters (LCs), in terms of cluster industries that serve local businesses and residents, as potential “building-blocks” of Smart Specialization Strategies (S3) still lacks interpretive studies. We proposed a conceptual framework to unveil those factors of LCs that may be enhanced in the S3 policy design, around the concepts of adaptiveness and responsiveness to structural and influencing features of a local economic system. The distinction between Local and Traded clusters, applied in the US context, allows the identification of Local Cluster performance because of the availability of a robust data set. Accordingly, a tool is proposed to investigate those factors that are likely empowering smart specialization strategies: The dynamic SWOT analysis on the case of San Diego provides interesting insights toward building this conceptual framework. The findings may help explain how to relate LCs with smart specialization as building-blocks, based on potential risks and opportunities associated with the local economic system.

scholarly journals A Trustworthy SIoT Aware Mechanism as an Enabler for Citizen Services in Smart Cities

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 918 ◽  
Author(s):  
Ateeq Ur Rehman ◽  
Rizwan Ali Naqvi ◽  
Abdul Rehman ◽  
Anand Paul ◽  
Muhammad Tariq Sadiq ◽  
...  
Keyword(s):  
Social Networks ◽  
Information And Communication Technologies ◽  
Online Social Networks ◽  
Information Technologies ◽  
Smart Cities ◽  
Trust Model ◽  
Human Interaction ◽  
Opinion Leaders ◽  
Local Cluster ◽  
Information And Communication

In the recent era, new information technologies have a significant impact on social networks. Initial integration of information and communication technologies (ICT) into city operations has promoted information city, ease of communication and principles of smart communities. Subsequently, the idea of the Internet of Things (IoT) with the specific focus of social IoT (SIoT) has contributed towards the smart cities (SC), which support the city operations with minimal human interaction. The user-generated data obtained by SIoT can be exploited to produce new useful information for creating citizen-centered smart services for SC. The aim of this research is twofold. Firstly, we used the concept of local and global trust to provide new services in SC based on popular online social networks (OSN) data used by the citizens. Secondly, the sustainability of the three different OSN is assessed. This paper investigates the social network domain with regard to the SC. Although in SC, OSN are increasing day by day, there is still an unresolved issue of trust among their users and also OSN are not much sustainable. In this research, we are analyzing the sustainability of different OSN for the SC. We employ datasets of three different social networks for our analyses. A local trust model is used to identify the central user within the local cluster while the global trust-based framework is used to identify the opinion leaders. Our analysis based on the datasets of Facebook, Twitter, and Slashdot unveil that filtration of these central-local users and opinion leaders result in the dispersion and significant reduction in a network. A novel model is being developed that outlines the relationship between local and global trust for the protection of OSN users in SC. Furthermore, the proposed mechanism uses the data posted by citizens on OSN to propose new services by mitigating the effect of untrusted users.

scholarly journals Wavelet Analysis of Shower Track Distribution in High-Energy Nucleus-Nucleus Collisions

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Provash Mali ◽  
Soumya Sarkar ◽  
Amitabha Mukhopadhyay ◽  
Gurmukh Singh
Keyword(s):  
Wavelet Analysis ◽  
Cluster Formation ◽  
High Energy ◽  
Multiparticle Production ◽  
Quantum Molecular Dynamics ◽  
Emission Data ◽  
Local Cluster ◽  
Local Maxima ◽  
A Charge ◽  
Bose Einstein

A continuous wavelet analysis is performed for pattern recognition of charged particle emission data in28Si-Ag/Br interaction at 14.5A GeV and in32S-Ag/Br interaction at 200A GeV. Making use of the event-wise local maxima present in the scalograms, we try to identify the collective behavior in multiparticle production, if there is any. For the first time, the wavelet results are compared with a model prediction based on the ultrarelativistic quantum molecular dynamics (UrQMD), where we adopt a charge reassignment algorithm to modify the UrQMD events to mimic the Bose-Einstein type of correlation among identical mesons—a feature known to be the most dominating factor responsible for local cluster formation. Statistically significant deviations between the experiment and the simulation are interpreted in terms of nontrivial dynamics of multiparticle production.

Local Cluster Neural Network Chip for Control

2005 ◽  
pp. 116-119 ◽  
Author(s):  
Liang Zhang ◽  
Joaquin Sitte ◽  
Ulrich Rueckert
Keyword(s):  
Neural Network ◽  
Local Cluster

scholarly journals Nonlinear multidimensional scaling and visualization of earthquake clusters over space, time and feature space

2005 ◽  
Vol 12 (1) ◽  
pp. 117-128 ◽  
Author(s):  
W. Dzwinel ◽  
D. A. Yuen ◽  
K. Boryczko ◽  
Y. Ben-Zion ◽  
S. Yoshioka ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
Synthetic Data ◽  
Feature Space ◽  
Seismic Events ◽  
Agglomerative Clustering ◽  
Local Cluster ◽  
Small Magnitude ◽  
Earthquake Parameters ◽  
Dimensional Scaling ◽  
Multi Dimensional Scaling

Abstract. We present a novel technique based on a multi-resolutional clustering and nonlinear multi-dimensional scaling of earthquake patterns to investigate observed and synthetic seismic catalogs. The observed data represent seismic activities around the Japanese islands during 1997-2003. The synthetic data were generated by numerical simulations for various cases of a heterogeneous fault governed by 3-D elastic dislocation and power-law creep. At the highest resolution, we analyze the local cluster structures in the data space of seismic events for the two types of catalogs by using an agglomerative clustering algorithm. We demonstrate that small magnitude events produce local spatio-temporal patches delineating neighboring large events. Seismic events, quantized in space and time, generate the multi-dimensional feature space characterized by the earthquake parameters. Using a non-hierarchical clustering algorithm and nonlinear multi-dimensional scaling, we explore the multitudinous earthquakes by real-time 3-D visualization and inspection of the multivariate clusters. At the spatial resolutions characteristic of the earthquake parameters, all of the ongoing seismicity both before and after the largest events accumulates to a global structure consisting of a few separate clusters in the feature space. We show that by combining the results of clustering in both low and high resolution spaces, we can recognize precursory events more precisely and unravel vital information that cannot be discerned at a single resolution.

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