scholarly journals Drawing impossible boundaries: field delineation of Social Network Science

2020 ◽  
Vol 125 (3) ◽  
pp. 2841-2876
Author(s):  
Haiko Lietz
Keyword(s):  
Social Network ◽  
Large Scale ◽  
Network Science ◽  
Face Validity ◽  
Size Distributions ◽  
Retrieval Method ◽  
Science Field ◽  
Cultural Systems ◽  
Field Heterogeneity ◽  
And Performance

Abstract“Big” digital behavioral data increasingly allows large-scale and high-resolution analyses of the behavior and performance of persons or aggregated identities in whole fields. Often the desired system of study is only a subset of a larger database. The task of drawing a field boundary is complicated because socio-cultural systems are highly overlapping. Here, I propose a sociologically enhanced information retrieval method to delineate fields that is based on the reproductive mechanism of fields, able to account for field heterogeneity, and generally applicable also outside scientometric, e.g., in social media, contexts. The method is demonstrated in a delineation of the multidisciplinary and very heterogeneous Social Network Science field using the Web of Science database. The field consists of 25,760 publications and has a historical dimension (1916–2012). This set has high face validity and exhibits expected statistical properties like systemic growth and power law size distributions. Data is clean and disambiguated. The dataset with 45,580 author names and 23,026 linguistic concepts is publically available and supposed to enable high-quality analyses of an evolving complex socio-cultural system.

scholarly journals The Youth Digital Skills Indicator: Report on the conceptualisation and development of the ySKILLS digital skills measure

2021 ◽  
Author(s):  
AISDL
Keyword(s):  
Large Scale ◽  
Full Range ◽  
Face Validity ◽  
Measurement Tool ◽  
Four Dimensions ◽  
Information Navigation ◽  
Wide Range ◽  
Digital Skills ◽  
Digital Knowledge ◽  
And Performance

This report presents the youth Digital Skills Indicator (yDSI), a unique, extensively crossnationally validated measurement tool with 31 items, distributed over digital skills and digital knowledge questions, that can be used for large-scale population research. The yDSI is the only measurement tool for youth digital skills that has been tested using the full range of validation practices. Over a period of six months, consultation with experts (face validity), cognitive interviews (content validity), pilot surveys (construct validity) and performance tests (criterion validity) with young people were conducted in a wide range of European countries. A review of the literature led to a framework identifying four dimensions that constitute digital skills: (1) technical and operational skills; (2) information navigation and processing skills; (3) communication and interaction skills; and (4) content creation and production skills.

scholarly journals Review of Battery Management Systems (BMS) Development and Industrial Standards

Technologies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 28
Author(s):  
Hossam A. Gabbar ◽  
Ahmed M. Othman ◽  
Muhammad R. Abdussami
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Storage System ◽  
Energy Storage System ◽  
Battery Management System ◽  
Battery Management ◽  
Electrical Power System ◽  
Safety Aspects ◽  
And Performance

The evolving global landscape for electrical distribution and use created a need area for energy storage systems (ESS), making them among the fastest growing electrical power system products. A key element in any energy storage system is the capability to monitor, control, and optimize performance of an individual or multiple battery modules in an energy storage system and the ability to control the disconnection of the module(s) from the system in the event of abnormal conditions. This management scheme is known as “battery management system (BMS)”, which is one of the essential units in electrical equipment. BMS reacts with external events, as well with as an internal event. It is used to improve the battery performance with proper safety measures within a system. Therefore, a safe BMS is the prerequisite for operating an electrical system. This report analyzes the details of BMS for electric transportation and large-scale (stationary) energy storage. The analysis includes different aspects of BMS covering testing, component, functionalities, topology, operation, architecture, and BMS safety aspects. Additionally, current related standards and codes related to BMS are also reviewed. The report investigates BMS safety aspects, battery technology, regulation needs, and offer recommendations. It further studies current gaps in respect to the safety requirements and performance requirements of BMS by focusing mainly on the electric transportation and stationary application. The report further provides a framework for developing a new standard on BMS, especially on BMS safety and operational risk. In conclusion, four main areas of (1) BMS construction, (2) Operation Parameters, (3) BMS Integration, and (4) Installation for improvement of BMS safety and performance are identified, and detailed recommendations were provided for each area. It is recommended that a technical review of the BMS be performed for transportation electrification and large-scale (stationary) applications. A comprehensive evaluation of the components, architectures, and safety risks applicable to BMS operation is also presented.

A Scalable Redefined Stochastic Blockmodel

2021 ◽  
Vol 15 (3) ◽  
pp. 1-28
Author(s):  
Xueyan Liu ◽  
Bo Yang ◽  
Hechang Chen ◽  
Katarzyna Musial ◽  
Hongxu Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Network Science ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Real World Data ◽  
Computational Overhead ◽  
Stochastic Blockmodel ◽  
Np Hard Problem ◽  
Large Scale Networks ◽  
The Cost

Stochastic blockmodel (SBM) is a widely used statistical network representation model, with good interpretability, expressiveness, generalization, and flexibility, which has become prevalent and important in the field of network science over the last years. However, learning an optimal SBM for a given network is an NP-hard problem. This results in significant limitations when it comes to applications of SBMs in large-scale networks, because of the significant computational overhead of existing SBM models, as well as their learning methods. Reducing the cost of SBM learning and making it scalable for handling large-scale networks, while maintaining the good theoretical properties of SBM, remains an unresolved problem. In this work, we address this challenging task from a novel perspective of model redefinition. We propose a novel redefined SBM with Poisson distribution and its block-wise learning algorithm that can efficiently analyse large-scale networks. Extensive validation conducted on both artificial and real-world data shows that our proposed method significantly outperforms the state-of-the-art methods in terms of a reasonable trade-off between accuracy and scalability. 1

scholarly journals Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions

PLoS ONE ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. e0146220 ◽  
Author(s):  
Aleksandra do Socorro da Silva ◽  
Silvana Rossy de Brito ◽  
Nandamudi Lankalapalli Vijaykumar ◽  
Cláudio Alex Jorge da Rocha ◽  
Maurílio de Abreu Monteiro ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Large Scale ◽  
Information And Communication
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