Engaging Learners Across the Globe: Fun and Education Global Network

Dennis Baffour‐Awuah

doi:10.1080/00094056.2021.2000307

Indymedia (r)evolution: The global network & rise of one Indymedia center

PsycEXTRA Dataset ◽

10.1037/e628672012-302 ◽

2003 ◽

Author(s):

S. Meinrath ◽

M. Lehman ◽

T. Steinlage ◽

B. Hagy

Keyword(s):

Global Network

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A Survey on Internet of Things : Applications and Layered Wise Security Issues

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit195624 ◽

2019 ◽

pp. 171-180

Author(s):

Uppuluri Sirisha ◽

G. Lakshme Eswari

Keyword(s):

Quality Of Life ◽

Internet Of Things ◽

Security And Privacy ◽

Global Network ◽

Business Growth ◽

Paper Briefly ◽

Smart Meters ◽

Security Issues ◽

Data Points

This paper briefly introduces Internet of Things(IOT) as a intellectual connectivity among the physical objects or devices which are gaining massive increase in the fields like efficiency, quality of life and business growth. IOT is a global network which is interconnecting around 46 million smart meters in U.S. alone with 1.1 billion data points per day[1]. The total installation base of IOT connecting devices would increase to 75.44 billion globally by 2025 with a increase in growth in business, productivity, government efficiency, lifestyle, etc., This paper familiarizes the serious concern such as effective security and privacy to ensure exact and accurate confidentiality, integrity, authentication access control among the devices.

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FLUCTUATIONS IN GEOMAGNETIC SECULAR VARIATION RATE ACCORDING TO DATA FROM THE GLOBAL NETWORK OF MAGNETIC OBSERVATORIES

Геология и геофизика ◽

10.15372/gig20160310 ◽

2016 ◽

Vol 57 (3) ◽

Keyword(s):

Secular Variation ◽

Global Network ◽

Geomagnetic Secular Variation ◽

Variation Rate ◽

Magnetic Observatories

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Document- and Keyword-based Author Co-citation Analysis

Data and Information Management ◽

10.2478/dim-2018-0009 ◽

2018 ◽

Vol 2 (2) ◽

pp. 70-82 ◽

Cited By ~ 2

Author(s):

Binglu Wang ◽

Yi Bu ◽

Win-bin Huang

Keyword(s):

Citation Analysis ◽

Semantic Similarity ◽

Method Validation ◽

New Method ◽

Global Network ◽

Network Visualization ◽

Knowledge Domain ◽

Knowledge Domains ◽

Domain Mapping ◽

The Relationship

AbstractIn the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.

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