Shared Network Arrays as an Abstraction of Network Code from Game Code Logic

2016 ◽  
pp. 243-250
Keyword(s):  
Network Code ◽  
Shared Network

Learning Conversation and Shared Network Leadership

2010 ◽  
Vol 9 (4) ◽  
pp. 181-194 ◽  
Author(s):  
Jürgen Weibler ◽  
Sigrid Rohn-Endres
Keyword(s):  
Qualitative Research ◽  
Grounded Theory ◽  
Social Network ◽  
Interorganizational Networks ◽  
Original Network ◽  
High Quality ◽  
Qualitative Research Design ◽  
Collective Processes ◽  
Shared Network ◽  
Practical Implications

This paper develops an understanding of how shared leadership emerges in social network interactions. On the basis of a qualitative research design (grounded theory methodology – GTM) our study in two interorganizational networks offers insights into the interplay between structures, individuals, and the collective for the emergence of shared network leadership (SNL). The network-specific Gestalt of SNL appears as a pattern of collective and individual leadership activities unified under the roof of a highly developed learning conversation. More importantly, our findings support the idea that individual network leadership would not emerge without embeddedness in certain high-quality collective processes of relating and dialogue. Both theoretical and practical implications of this original network leadership perspective are discussed.

Dynamic Spectrum Access to the Combined Resource of Commercial and Public Safety Bands Based on a WCDMA Shared Network

2009 ◽  
Vol E92-B (12) ◽  
pp. 3581-3585
Author(s):  
Hyoungsuk JEON ◽  
Sooyeol IM ◽  
Youmin KIM ◽  
Seunghee KIM ◽  
Jinup KIM ◽  
...  
Keyword(s):  
Public Safety ◽  
Dynamic Spectrum Access ◽  
Dynamic Spectrum ◽  
Spectrum Access ◽  
Shared Network

scholarly journals INSTANCE – the Italian seismic dataset for machine learning

2021 ◽  
Vol 13 (12) ◽  
pp. 5509-5544
Author(s):  
Alberto Michelini ◽  
Spina Cianetti ◽  
Sonja Gaviano ◽  
Carlo Giunchi ◽  
Dario Jozinović ◽  
...  
Keyword(s):  
Machine Learning ◽  
Transfer Functions ◽  
Strong Motion ◽  
Network Code ◽  
Waveform Data ◽  
Magnitude Range ◽  
Comprehensive Information ◽  
Selection For ◽  
Learning Analysis ◽  
Italian Earthquake

Abstract. The Italian earthquake waveform data are collected here in a dataset suited for machine learning analysis (ML) applications. The dataset consists of nearly 1.2 million three-component (3C) waveform traces from about 50 000 earthquakes and more than 130 000 noise 3C waveform traces, for a total of about 43 000 h of data and an average of 21 3C traces provided per event. The earthquake list is based on the Italian Seismic Bulletin (http://terremoti.ingv.it/bsi, last access: 15 February 2020​​​​​​​) of the Istituto Nazionale di Geofisica e Vulcanologia between January 2005 and January 2020, and it includes events in the magnitude range between 0.0 and 6.5. The waveform data have been recorded primarily by the Italian National Seismic Network (network code IV) and include both weak- (HH, EH channels) and strong-motion (HN channels) recordings. All the waveform traces have a length of 120 s, are sampled at 100 Hz, and are provided both in counts and ground motion physical units after deconvolution of the instrument transfer functions. The waveform dataset is accompanied by metadata consisting of more than 100 parameters providing comprehensive information on the earthquake source, the recording stations, the trace features, and other derived quantities. This rich set of metadata allows the users to target the data selection for their own purposes. Much of these metadata can be used as labels in ML analysis or for other studies. The dataset, assembled in HDF5 format, is available at http://doi.org/10.13127/instance (Michelini et al., 2021).

Network Code Division Multiplexing for Wireless Relay Networks

2015 ◽  
Vol 14 (10) ◽  
pp. 5736-5749 ◽  
Author(s):  
Jing Yue ◽  
Zihuai Lin ◽  
Branka Vucetic ◽  
Guoqiang Mao ◽  
Ming Xiao ◽  
...  
Keyword(s):  
Relay Networks ◽  
Network Code ◽  
Wireless Relay Networks ◽  
Wireless Relay ◽  
Code Division Multiplexing

Flawed Security of Social Network of Things

2018 ◽  
pp. 65-86
Author(s):  
Rohit Anand ◽  
Akash Sinha ◽  
Abhishek Bhardwaj ◽  
Aswin Sreeraj
Keyword(s):  
Social Network ◽  
Real World ◽  
Personal Data ◽  
Dynamic Structure ◽  
Security And Privacy ◽  
Human Intervention ◽  
Security Measures ◽  
The Social ◽  
Data Capturing ◽  
Shared Network

This chapter deals with the security flaws of social network of things. The network of things (NoT) is a dynamic structure that is basically an interface of real world and virtual world having capabilities of collection and sharing data over a shared network. The social network of things (SNoT) is a versatile way of connecting virtual and real world. Like any other device connected to internet, objects in SNoT are also vulnerable to the various security and privacy attacks. Generally, to secure Social Network of Things in which human intervention is absent, data capturing devices must be avoided. Types of security attacks that are huge threats to NoT as well as SNoT will be discussed in the chapter. The huge collection of information without necessary security measures allows an intruder to misuse the personal data of owner. Different types of attacks with reference to the different layers are also discussed in detail. The best possible potential solutions for the security of devices in SNoT will be considered.

Cloud Computing

2018 ◽  
pp. 233-259
Author(s):  
Shailendra Singh ◽  
Sunita Gond
Keyword(s):  
Cloud Computing ◽  
Cloud Services ◽  
Educational Institutions ◽  
Personal Computing ◽  
The World ◽  
Long Time ◽  
The Cost ◽  
Shared Network ◽  
Cloud Users ◽  
Distributed And Parallel Computing

As this is the age of technology and every day we are receiving the news about growing popularity of internet and its applications. Cloud computing is an emerging paradigm of today that is rapidly accepted by the industry/organizations/educational institutions etc. for various applications and purpose. As computing is related to distributed and parallel computing which are from a very long time in the market, but today is the world of cloud computing that reduces the cost of computing by focusing on personal computing to data center computing. Cloud computing architecture and standard provide a unique way for delivering computation services to cloud users. It is having a simple API (Application Platform Interface) to users for accessing storage, platform and hardware by paying-as-per-use basis. Services provided by cloud computing is as same as other utility oriented services like electricity bill, water, telephone etc. over shared network. There are many cloud services providers in the market for providing services like Google, Microsoft, Manjrasoft Aneka, etc.

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