Building Scalable Virtual Communities — Infrastructure Requirements and Computational Costs

2005 ◽  
pp. 68-83 ◽  
Author(s):  
Omer F. Rana ◽  
Asif Akram ◽  
Steven J. Lynden
Keyword(s):  
Virtual Communities ◽  
Computational Costs

The Challenge of Evaluating Virtual Communities of Practice: A Systematic Mapping Study

10.28945/4505 ◽  
2020 ◽  
Vol 15 ◽  
pp. 039-064
Author(s):  
Rogerio Ferreira da Silva ◽  
Itana Maria de Souza Gimenes ◽  
José Carlos Maldonado
Keyword(s):  
Communities Of Practice ◽  
Virtual Communities ◽  
Evaluation Process ◽  
Evaluation Methods ◽  
Systematic Mapping Study ◽  
Research Gaps ◽  
Systematic Mapping ◽  
Research Questions ◽  
Virtual Communities Of Practice ◽  
Selection Of

Aim/Purpose: This paper presents a study of Virtual Communities of Practice (VCoP) evaluation methods that aims to identify their current status and impact on knowledge sharing. The purposes of the study are as follows: (i) to identify trends and research gaps in VCoP evaluation methods; and, (ii) to assist researchers to position new research activities in this domain. Background: VCoP have become a popular knowledge sharing mechanism for both individuals and organizations. Their evaluation process is complex; however, it is recognized as an essential means to provide evidences of community effectiveness. Moreover, VCoP have introduced additional features to face to face Communities of Practice (CoP) that need to be taken into account in evaluation processes, such as geographical dispersion. The fact that VCoP rely on Information and Communication Technologies (ICT) to execute their practices as well as storing artifacts virtually makes more consistent data analysis possible; thus, the evaluation process can apply automatic data gathering and analysis. Methodology: A systematic mapping study, based on five research questions, was carried out in order to analyze existing studies about VCoP evaluation methods and frameworks. The mapping included searching five research databases resulting in the selection of 1,417 papers over which a formal analysis process was applied. This process led to the preliminary selection of 39 primary studies for complete reading. After reading them, we select 28 relevant primary studies from which data was extracted and synthesized to answer the proposed research questions. Contribution: The authors of the primary studies analyzed along this systematic mapping propose a set of methods and strategies for evaluating VCoP, such as frameworks, processes and maturity models. Our main contribution is the identification of some research gaps present in the body of studies, in order to stimulate projects that can improve VCoP evaluation methods and support its important role in social learning. Findings: The systematic mapping led to the conclusion that most of the approaches for VCoP evaluation do not consider the combination of data structured and unstructured metrics. In addition, there is a lack of guidelines to support community operators’ actions based on evaluation metrics.

THE NEW ALGORITHM OF SOLVING HARMONIC BALANCE EQUATIONS

2019 ◽  
Author(s):  
Vladimir Lantsov ◽  
A. Papulina
Keyword(s):  
Harmonic Balance ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Balance Equations ◽  
Model Order ◽  
Cad Systems ◽  
Computational Costs ◽  
Reduction Methods ◽  
Model Equations

The new algorithm of solving harmonic balance equations which used in electronic CAD systems is presented. The new algorithm is based on implementation to harmonic balance equations the ideas of model order reduction methods. This algorithm allows significantly reduce the size of memory for storing of model equations and reduce of computational costs.

Identification, Prediction and Data Analysis of Noncoding RNAs: A Review

2019 ◽  
Vol 15 (3) ◽  
pp. 216-230 ◽  
Author(s):  
Abbasali Emamjomeh ◽  
Javad Zahiri ◽  
Mehrdad Asadian ◽  
Mehrdad Behmanesh ◽  
Barat A. Fakheri ◽  
...  
Keyword(s):  
Computational Methods ◽  
State Of The Art ◽  
Noncoding Rnas ◽  
Research Field ◽  
Design Strategies ◽  
Structural Prediction ◽  
Computational Costs ◽  
Cellular Processes ◽  
Laboratory Techniques ◽  
Fast Prediction

Background:Noncoding RNAs (ncRNAs) which play an important role in various cellular processes are important in medicine as well as in drug design strategies. Different studies have shown that ncRNAs are dis-regulated in cancer cells and play an important role in human tumorigenesis. Therefore, it is important to identify and predict such molecules by experimental and computational methods, respectively. However, to avoid expensive experimental methods, computational algorithms have been developed for accurately and fast prediction of ncRNAs.Objective:The aim of this review was to introduce the experimental and computational methods to identify and predict ncRNAs structure. Also, we explained the ncRNA’s roles in cellular processes and drugs design, briefly.Method:In this survey, we will introduce ncRNAs and their roles in biological and medicinal processes. Then, some important laboratory techniques will be studied to identify ncRNAs. Finally, the state-of-the-art models and algorithms will be introduced along with important tools and databases.Results:The results showed that the integration of experimental and computational approaches improves to identify ncRNAs. Moreover, the high accurate databases, algorithms and tools were compared to predict the ncRNAs.Conclusion:ncRNAs prediction is an exciting research field, but there are different difficulties. It requires accurate and reliable algorithms and tools. Also, it should be mentioned that computational costs of such algorithm including running time and usage memory are very important. Finally, some suggestions were presented to improve computational methods of ncRNAs gene and structural prediction.

Social Media and the Transformation of Healthcare: A Viewpoint (Preprint)

2020 ◽  
Author(s):  
Ella Forgie ◽  
Hollis Lai ◽  
Bo Cao ◽  
Eleni Stroulia ◽  
Andrew James Greenshaw ◽  
...  
Keyword(s):  
Social Media ◽  
Health Information ◽  
Information Seeking ◽  
Virtual Communities ◽  
Community Support ◽  
Security And Privacy ◽  
Support Network ◽  
Full Potential ◽  
Physician Patient Relationship ◽  
Mediation Effects

UNSTRUCTURED As many as 80% of internet users seek health information online. The social determinants of health (SDoH) are intimately related to who has access to the internet and healthcare as a whole. Those who face more barriers to care are more likely to benefit from accessing health information online, granted the information they are retrieving is accurate. Virtual communities on social media platforms are particularly interesting as venues for seeking health information online because peers have been shown to influence health behaviour more than almost anything else. Thus, it is important to recognize the potential of social media to have positive mediation effects on health, so long as any negative mediation effects are reconcilable. As a positive mediator of health, social media can be used as a direct or indirect mode of communication between physicians and patients, a venue for health promotion and health information, and a community support network. False or misleading content, social contagion, confirmation bias, and security and privacy concerns must be mitigated in order to realize full potential of social media as a positive mediator of health. In any case, it is clear that the intersections between the SDoH, social media, and health are intimate, and they must be taken into consideration by physicians. Here, we argue that a paradigm shift in the physician-patient relationship is warranted, one where physicians: a) acknowledge the impacts of the SDoH on information-seeking behaviour, b) recognize the positive and negative roles of social media as a mediator of health through the lens of the SDoH, and c) use social media to catalyze positive changes in the standard of care.

scholarly journals Performance of Adaptive Unstructured Mesh Modelling in Idealized Advection Cases over Steep Terrains

Atmosphere ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 444 ◽  
Author(s):  
Jinxi Li ◽  
Jie Zheng ◽  
Jiang Zhu ◽  
Fangxin Fang ◽  
Christopher. Pain ◽  
...  
Keyword(s):  
Unstructured Mesh ◽  
Computational Cost ◽  
Adaptive Mesh ◽  
Galerkin Finite Element Method ◽  
Adaptive Meshes ◽  
Galerkin Finite Element ◽  
Computational Costs ◽  
Cut Cell ◽  
Discontinuous Galerkin Finite Element ◽  
Terrain Following

Advection errors are common in basic terrain-following (TF) coordinates. Numerous methods, including the hybrid TF coordinate and smoothing vertical layers, have been proposed to reduce the advection errors. Advection errors are affected by the directions of velocity fields and the complexity of the terrain. In this study, an unstructured adaptive mesh together with the discontinuous Galerkin finite element method is employed to reduce advection errors over steep terrains. To test the capability of adaptive meshes, five two-dimensional (2D) idealized tests are conducted. Then, the results of adaptive meshes are compared with those of cut-cell and TF meshes. The results show that using adaptive meshes reduces the advection errors by one to two orders of magnitude compared to the cut-cell and TF meshes regardless of variations in velocity directions or terrain complexity. Furthermore, adaptive meshes can reduce the advection errors when the tracer moves tangentially along the terrain surface and allows the terrain to be represented without incurring in severe dispersion. Finally, the computational cost is analyzed. To achieve a given tagging criterion level, the adaptive mesh requires fewer nodes, smaller minimum mesh sizes, less runtime and lower proportion between the node numbers used for resolving the tracer and each wavelength than cut-cell and TF meshes, thus reducing the computational costs.

scholarly journals Very Fast and Accurate Procedure for the Characterization of Photovoltaic Panels from Datasheet Information

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Antonino Laudani ◽  
Francesco Riganti Fulginei ◽  
Alessandro Salvini ◽  
Gabriele Maria Lozito ◽  
Salvatore Coco
Keyword(s):  
Numerical Methods ◽  
Search Space ◽  
Extraction Process ◽  
Reduced Form ◽  
Photovoltaic Panels ◽  
Approximation Techniques ◽  
Computational Costs ◽  
Minimization Technique ◽  
Accurate Procedure

In recent years several numerical methods have been proposed to identify the five-parameter model of photovoltaic panels from manufacturer datasheets also by introducing simplification or approximation techniques. In this paper we present a fast and accurate procedure for obtaining the parameters of the five-parameter model by starting from its reduced form. The procedure allows characterizing, in few seconds, thousands of photovoltaic panels present on the standard databases. It introduces and takes advantage of further important mathematical considerations without any model simplifications or data approximations. In particular the five parameters are divided in two groups, independent and dependent parameters, in order to reduce the dimensions of the search space. The partitioning of the parameters provides a strong advantage in terms of convergence, computational costs, and execution time of the present approach. Validations on thousands of photovoltaic panels are presented that show how it is possible to make easy and efficient the extraction process of the five parameters, without taking care of choosing a specific solver algorithm but simply by using any deterministic optimization/minimization technique.

scholarly journals Echo chamber detection and analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giacomo Villa ◽  
Gabriella Pasi ◽  
Marco Viviani
Keyword(s):  
Social Media ◽  
Community Detection ◽  
Virtual Communities ◽  
Selective Exposure ◽  
Social Needs ◽  
News Sources ◽  
Detection Strategy ◽  
Echo Chambers ◽  
Echo Chamber ◽  
Content Aware

AbstractSocial media allow to fulfill perceived social needs such as connecting with friends or other individuals with similar interests into virtual communities; they have also become essential as news sources, microblogging platforms, in particular, in a variety of contexts including that of health. However, due to the homophily property and selective exposure to information, social media have the tendency to create distinct groups of individuals whose ideas are highly polarized around certain topics. In these groups, a.k.a. echo chambers, people only "hear their own voice,” and divergent visions are no longer taken into account. This article focuses on the study of the echo chamber phenomenon in the context of the COVID-19 pandemic, by considering both the relationships connecting individuals and semantic aspects related to the content they share over Twitter. To this aim, we propose an approach based on the application of a community detection strategy to distinct topology- and content-aware representations of the COVID-19 conversation graph. Then, we assess and analyze the controversy and homogeneity among the different polarized groups obtained. The evaluations of the approach are carried out on a dataset of tweets related to COVID-19 collected between January and March 2020.

Arising of Informal Women's Learn-to-code Communities

2021 ◽  
Vol 21 (2) ◽  
pp. 1-24
Author(s):  
Louise Ann Lyon ◽  
Chelsea Clayton
Keyword(s):  
Learning Community ◽  
Virtual Communities ◽  
Point Of View ◽  
Customer Relationship ◽  
Activity System ◽  
Learning Group ◽  
Management Platform ◽  
High Level ◽  
Verbal Encouragement ◽  
Activity Systems Analysis

Female-focused, grassroots communities purporting to help women learn to code are popping up in a variety of settings, indicating the motivation on the part of the participants to evade male-dominated settings while learning. However, little is known about how these groups function as an activity system. With current technology enabling the forming of virtual communities and the meteoric rise in use of the Salesforce CRM (customer relationship management) platform, a group of women have formed a coaching and learning community designed to help women move from Salesforce administrators to software developers through learning to code. We used activity systems analysis (ASA) to investigate this real-world instance of the larger phenomenon using an ethnographic approach. We used ASA to organize and make sense of the data by first creating a table listing the points on the activity system triangle (subject, rules, object, etc.) and filling in the points of the triangle based on the design of the coaching and learning group as described by participants; this gave us a high-level view of the activity system. To understand the subjects’ point of view of the system, we then created a new column in the table to fill in themes that emerged from our qualitative data analysis organized by dimension of the activity system. This process enabled us to capture the activity and the voices of participants as well as tensions that had emerged in the system. Findings show a range of outcomes, from participants crediting the group as a kickstart to the journey to successfully landing a job as a developer to members stalling in their progress after involvement. Results also show that purposeful tensions of welcoming novice questions and offering unsolicited verbal encouragement built into the activity system create a welcoming, safe environment for women learning to code.

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