scholarly journals A Collaborative Coding Framework of RS and H.264

2017 ◽  
Author(s):  
Jiejun Hu ◽  
Xilong Che
Keyword(s):  
Collaborative Coding

Complex-valued receiver for multiuser collaborative coding schemes

1995 ◽  
Vol 31 (5) ◽  
pp. 341-342 ◽  
Author(s):  
F.H. Ali ◽  
S.A.G. Chandler ◽  
S. Soysa
Keyword(s):  
Coding Schemes ◽  
Complex Valued ◽  
Collaborative Coding

scholarly journals HESS Opinions: Repeatable research: what hydrologists can learn from the Duke cancer research scandal

2016 ◽  
Vol 20 (9) ◽  
pp. 3739-3743 ◽  
Author(s):  
Michael N. Fienen ◽  
Mark Bakker
Keyword(s):  
Cancer Research ◽  
Data Analysis ◽  
Data Management ◽  
Open Source ◽  
Modeling Effort ◽  
Cancer Study ◽  
The Past ◽  
Duke University ◽  
Collaborative Coding

Abstract. In the past decade, difficulties encountered in reproducing the results of a cancer study at Duke University resulted in a scandal and an investigation which concluded that tools used for data management, analysis, and modeling were inappropriate for the documentation of the study, let alone the reproduction of the results. New protocols were developed which require that data analysis and modeling be carried out with scripts that can be used to reproduce the results and are a record of all decisions and interpretations made during an analysis or a modeling effort. In the hydrological sciences, we face similar challenges and need to develop similar standards for transparency and repeatability of results. A promising route is to start making use of open-source languages (such as R and Python) to write scripts and to use collaborative coding environments (such as Git) to share our codes for inspection and use by the hydrological community. An important side-benefit to adopting such protocols is consistency and efficiency among collaborators.

scholarly journals BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Dengcheng Yan ◽  
Zhen Shao ◽  
Yiwen Zhang ◽  
Bin Qi
Keyword(s):  
Large Scale ◽  
Driving Forces ◽  
Research Direction ◽  
Technical System ◽  
Bipartite Network ◽  
Ranking Methods ◽  
Critical Nodes ◽  
Ranking Score ◽  
Complex Technical System ◽  
Collaborative Coding

With the wide adoption of social collaborative coding, more and more developers participate and collaborate on platforms such as GitHub through rich social and technical relationships, forming a large-scale complex technical system. Like the functionalities of critical nodes in other complex systems, influential developers and projects usually play an important role in driving this technical system to more optimized states with higher efficiency for software development, which makes it a meaningful research direction on identifying influential developers and projects in social collaborative coding platforms. However, traditional ranking methods seldom take into account the continuous interactions and the driving forces of human dynamics. In this paper, we combine the bursty interactions and the bipartite network structure between developers and projects and propose the BurstBiRank model. Firstly, the burstiness between each pair of developers and projects is calculated. Secondly, a weighted developer-project bipartite network is constructed using the burstiness as weight. Finally, an iterative score diffusion process is applied to this bipartite network and a final ranking score is obtained at the stationary state. The real-world case study on GitHub demonstrates the effectiveness of our proposed BurstBiRank and the outperformance of traditional ranking methods.

Design framework enhancing developer experience in collaborative coding environment

2015 ◽  
Author(s):  
Jarmo Palviainen ◽  
Terhi Kilamo ◽  
Johannes Koskinen ◽  
Janne Lautamäki ◽  
Tommi Mikkonen ◽  
...  
Keyword(s):  
Design Framework ◽  
Collaborative Coding

Capacity oft-user collaborative coding multiple-access scheme operating over noisy channel

1989 ◽  
Vol 25 (11) ◽  
pp. 742-744 ◽  
Author(s):  
B. Honary ◽  
F. Ali ◽  
M. Darnell
Keyword(s):  
Multiple Access ◽  
Noisy Channel ◽  
Access Scheme ◽  
Collaborative Coding

Fostering Computational Thinking in Homes and Other Informal Learning Spaces

2021 ◽  
pp. 158-175
Author(s):  
Madhu Govind
Keyword(s):  
Informal Learning ◽  
Computational Thinking ◽  
After School Programs ◽  
Family Context ◽  
After School ◽  
Learning Spaces ◽  
School Programs ◽  
Family Friendly ◽  
The Family ◽  
Collaborative Coding

This chapter provides theoretical and practical insights for fostering children's computational thinking (CT) in homes and other family-friendly spaces such as libraries, museums, and after-school programs. The family context—the kinds of roles, interactions, and opportunities afforded by parents, caregivers, and siblings—is essential for understanding how young children learn and engage in CT. This work is informed by research on how everyday activities and educational technologies (and the contexts in which they are used) can be designed to promote opportunities for CT and family engagement. This chapter discusses ways to support children's CT by co-engaging family members in collaborative coding activities in homes and other informal learning spaces.

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