Vehicles joint UAVs to acquire and analyze data for topology discovery in large-scale IoT systems

2020 ◽  
Vol 13 (5) ◽  
pp. 1720-1743 ◽  
Author(s):  
Haojun Teng ◽  
Kaoru Ota ◽  
Anfeng Liu ◽  
Tian Wang ◽  
Shaobo Zhang
Keyword(s):  
Large Scale ◽  
Topology Discovery ◽  
Analyze Data

scholarly journals Efficient Doubletree: An Algorithm for Large-Scale Topology Discovery

2013 ◽  
Vol 13 (3) ◽  
pp. 05-12
Author(s):  
Ranjit Nukathati ◽  
Keyword(s):  
Large Scale ◽  
Topology Discovery

scholarly journals Engineering social contagions: Optimal network seeding in the presence of homophily

2013 ◽  
Vol 1 (2) ◽  
pp. 125-153 ◽  
Author(s):  
SINAN ARAL ◽  
LEV MUCHNIK ◽  
ARUN SUNDARARAJAN
Keyword(s):  
Peer Influence ◽  
Large Scale ◽  
Social Conditions ◽  
Data Driven ◽  
Mobile Service ◽  
Simulation Studies ◽  
Optimal Network ◽  
Day By Day ◽  
Overall Effectiveness ◽  
Analyze Data

AbstractWe use data on a real, large-scale social network of 27 million individuals interacting daily, together with the day-by-day adoption of a new mobile service product, to inform, build, and analyze data-driven simulations of the effectiveness of seeding (network targeting) strategies under different social conditions. Three main results emerge from our simulations. First, failure to consider homophily creates significant overestimation of the effectiveness of seeding strategies, casting doubt on conclusions drawn by simulation studies that do not model homophily. Second, seeding is constrained by the small fraction of potential influencers that exist in the network. We find that seeding more than 0.2% of the population is wasteful because the gain from their adoption is lower than the gain from their natural adoption (without seeding). Third, seeding is more effective in the presence of greater social influence. Stronger peer influence creates a greater than additive effect when combined with seeding. Our findings call into question some conventional wisdom about these strategies and suggest that their overall effectiveness may be overestimated.

scholarly journals The Role of The Community in Handling The Covid-19 Pandemic in Indonesia

2021 ◽  
Vol 1 (1) ◽  
pp. 803-810
Author(s):  
Abdul Rohim
Keyword(s):  
Community Participation ◽  
Large Scale ◽  
Virus Disease ◽  
Corona Virus ◽  
Social Restriction ◽  
The City ◽  
Analyze Data

Coronavirus disease is also known as Covid-19 (Corona Virus Disease 2019) and was discovered in the city of Wuhan, China at the end of December 2019. This virus spreads rapidly and has reached almost every country, including Indonesia, in just a few months. As a result, numerous countries have implemented regulations imposing lockdowns to prevent the spread of the Coronavirus. To control the spread of this virus, Indonesia implemented a Large-Scale Social Restriction (PSBB) policy. The method employed in this study is to analyze data from various reading sources. By comparing journals or articles, references are obtained from online publications with diverse studies. This study utilized five journals as references, all of which demonstrated that community participation in preventing the spread of Covid-19 was in a good category. According to the journals reviewed, information regarding the handling of Covid-19 necessitated the participation of all parties to prevent its spread. From the five journals obtained, all of these journals indicate that the role of the community is required in preventing the spread of the Covid-19 virus.

scholarly journals Vocal development in a large-scale crosslinguistic corpus

2019 ◽  
Author(s):  
Meg Cychosz ◽  
Alejandrina Cristia ◽  
Elika Bergelson ◽  
Marisa Casillas ◽  
Gladys Baudet ◽  
...  
Keyword(s):  
Large Scale ◽  
Linguistically Diverse ◽  
Natural Environments ◽  
Cultural Backgrounds ◽  
Fine Grained ◽  
Audio Recordings ◽  
Using Data ◽  
Future Work ◽  
Multiple Languages ◽  
Analyze Data

This study evaluates whether early vocalizations develop in similar ways in children across diverse cultural contexts. We analyze data from daylong audio-recordings of 49 children (1-36 months) from five different language/cultural backgrounds. Citizen scientists annotated these recordings to determine if child vocalizations contained canonical transitions or not (e.g., "ba'' versus "ee''). Results revealed that the proportion of clips reported to contain canonical transitions increased with age. Further, this proportion exceeded 0.15 by around 7 months, replicating and extending previous findings on canonical vocalization development but using data from the natural environments of a culturally and linguistically diverse sample. This work explores how crowdsourcing can be used to annotate corpora, helping establish developmental milestones relevant to multiple languages and cultures. Lower inter-annotator reliability on the crowdsourcing platform, relative to more traditional in-lab expert annotators, means that a larger number of unique annotators and/or annotations are required and that crowdsourcing may not be a suitable method for more fine-grained annotation decisions. Audio clips used for this project are compiled into a large-scale infant vocal corpus that is available for other researchers to use in future work.

scholarly journals Evaluation of a Large-Scale Topology Discovery Algorithm

2006 ◽  
pp. 193-204 ◽  
Author(s):  
Benoit Donnet ◽  
Bradley Huffaker ◽  
Timur Friedman ◽  
kc claffy
Keyword(s):  
Large Scale ◽  
Topology Discovery

The Paradoxes of Big Data

2015 ◽  
Vol 743 ◽  
pp. 603-606
Author(s):  
Xin Xing Liu ◽  
Xing Wu ◽  
Shu Ji Dai
Keyword(s):  
Big Data ◽  
Large Scale ◽  
New World ◽  
The Internet ◽  
Analyze Data

The era of Big Data poses a big challenge to our way of living and thinking. Big Data refers to things which can do at a large scale but cannot be done at a smaller size. There are many paradoxes of Big Data: In this new world far more data can be analyzed, though using all the data can make the datum messy and lose some accuracy, sometimes reach better conclusions. As massive quantities of information produced by and about people and their interactions exposed on the Internet, will large scale search and analyze data help people create better services, goods and tools or it just lead to privacy incursions and invasive marketing? In this article, we offer three main provocations, based on our analysis we have constructed some models to help explain the amazing contradiction in Big Data.

scholarly journals Data architecture for a large-scale neuroscience collaboration

2019 ◽  
Author(s):  
◽  
Niccolò Bonacchi ◽  
Gaelle Chapuis ◽  
Anne Churchland ◽  
Kenneth D. Harris ◽  
...  
Keyword(s):  
Large Scale ◽  
Modular Architecture ◽  
Web Based ◽  
Data Architecture ◽  
Graphical Summary ◽  
Geographically Distributed ◽  
Data Files ◽  
Recorded Data ◽  
New Framework ◽  
Analyze Data

AbstractEffective data management is a major challenge for neuroscience labs, and even greater for collaborative projects. In the International Brain laboratory (IBL), ten experimental labs spanning 7 geographically distributed sites measure neural activity across the brains of mice making perceptual decisions. Here, we report a novel, modular architecture that allows users to contribute, access, and analyze data across this collaboration. Users contribute data using a web-based electronic lab notebook (Alyx), which automatically registers recorded data files and uploads them to a central server. Users access data with a lightweight interface, the Open Neurophysiology Environment (ONE), which searches data from all labs and loads it into MATLAB or Python. To analyze data, we have developed pipelines based on DataJoint, which automatically populate a website displaying a graphical summary of results to date. This architecture provides a new framework to contribute, access and analyze data, surmounting many challenges currently faced by neuroscientists.

Testing Conceptual Frameworks of Nonexperimental Program Evaluation Designs Using Structural Equation Modeling

2011 ◽  
Vol 32 (4) ◽  
pp. 480-493 ◽  
Author(s):  
Omolola A. Adedokun ◽  
Amy L. Childress ◽  
Wilella D. Burgess
Keyword(s):  
Program Evaluation ◽  
Structural Equation Modeling ◽  
Program Implementation ◽  
Structural Equation ◽  
Large Scale ◽  
Conceptual Models ◽  
Equation Modeling ◽  
Experimental Program ◽  
Quasi Experimental ◽  
Analyze Data

A theory-driven approach to evaluation (TDE) emphasizes the development and empirical testing of conceptual models to understand the processes and mechanisms through which programs achieve their intended goals. However, most reported applications of TDE are limited to large-scale experimental/quasi-experimental program evaluation designs. Very few (limited) examples of the relevance of TDE to nonexperimental program evaluation designs exist in literature. Using the method of structural equation modeling to analyze data from the Interns for Indiana (IfI) program, this study demonstrates how evaluation practitioners can test logical and sequential relationships among tiers of outcomes of nonexperimental programs, especially programs with limited datasets. The study also describes how the empirical feedback can be used to understand program dynamics and improve program implementation and evaluation.

scholarly journals Who is fighting with whom? How ethnic origin shapes friendship, dislike, and physical violence relations in German secondary schools

2019 ◽  
Author(s):  
Mark Wittek ◽  
Clemens Kroneberg ◽  
Kathrin Lämmermann
Keyword(s):  
Large Scale ◽  
Physical Violence ◽  
Ethnic Origin ◽  
Ethnic Violence ◽  
Seventh Graders ◽  
Friendship Networks ◽  
Friendship Network ◽  
Multiple Networks ◽  
Analyze Data

This study examines the role of ethnic background for friendship, dislike, and violence networks in secondary school. We analyze data on multiple networks from a large-scale study of more than 2500 seventh-graders in Germany. In addition to ethnic homophily in friendship networks, our results reveal a tendency among students to dislike ethnic outgroup members (ethnic heterophobia). However, students are more likely to engage in violence towards same-ethnic peers than outgroup members. This is partly due to the greater prevalence of violence among students who are close in the friendship network and students who spend time together outside of school. Moreover, schools marked by stronger ethnic homophily in friendships tend to display higher levels of ethnic heterophobia but exhibit higher levels of intra-ethnic rather than inter-ethnic violence.

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