The Impact of Open Source Intelligence on Cybersecurity

Author(s):  
Alastair Paterson ◽  
James Chappell
MIS Quarterly ◽  
2019 ◽  
Vol 43 (3) ◽  
pp. 951-976
Author(s):  
Likoebe M. Maruping ◽  
◽  
Sherae L. Daniel ◽  
Marcelo Cataldo ◽  
◽  
...  

Author(s):  
Erin Polka ◽  
Ellen Childs ◽  
Alexa Friedman ◽  
Kathryn S. Tomsho ◽  
Birgit Claus Henn ◽  
...  

Sharing individualized results with health study participants, a practice we and others refer to as “report-back,” ensures participant access to exposure and health information and may promote health equity. However, the practice of report-back and the content shared is often limited by the time-intensive process of personalizing reports. Software tools that automate creation of individualized reports have been built for specific studies, but are largely not open-source or broadly modifiable. We created an open-source and generalizable tool, called the Macro for the Compilation of Report-backs (MCR), to automate compilation of health study reports. We piloted MCR in two environmental exposure studies in Massachusetts, USA, and interviewed research team members (n = 7) about the impact of MCR on the report-back process. Researchers using MCR created more detailed reports than during manual report-back, including more individualized numerical, text, and graphical results. Using MCR, researchers saved time producing draft and final reports. Researchers also reported feeling more creative in the design process and more confident in report-back quality control. While MCR does not expedite the entire report-back process, we hope that this open-source tool reduces the barriers to personalizing health study reports, promotes more equitable access to individualized data, and advances self-determination among participants.


Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1791
Author(s):  
Carmen Fattore ◽  
Nicodemo Abate ◽  
Farid Faridani ◽  
Nicola Masini ◽  
Rosa Lasaponara

In recent years, the impact of Climate change, anthropogenic and natural hazards (such as earthquakes, landslides, floods, tsunamis, fires) has dramatically increased and adversely affected modern and past human buildings including outstanding cultural properties and UNESCO heritage sites. Research about protection/monitoring of cultural heritage is crucial to preserve our cultural properties and (with them also) our history and identity. This paper is focused on the use of the open-source Google Earth Engine tool herein used to analyze flood and fire events which affected the area of Metaponto (southern Italy), near the homonymous Greek-Roman archaeological site. The use of the Google Earth Engine has allowed the supervised and unsupervised classification of areas affected by flooding (2013–2020) and fire (2017) in the past years, obtaining remarkable results and useful information for setting up strategies to mitigate damage and support the preservation of areas and landscape rich in cultural and natural heritage.


2015 ◽  
Vol 19 (4) ◽  
pp. 791-813 ◽  
Author(s):  
Zilia Iskoujina ◽  
Joanne Roberts

Purpose – This paper aims to add to the understanding of knowledge sharing in online communities through an investigation of the relationship between individual participant’s motivations and management in open source software (OSS) communities. Drawing on a review of literature concerning knowledge sharing in organisations, the factors that motivate participants to share their knowledge in OSS communities, and the management of such communities, it is hypothesised that the quality of management influences the extent to which the motivations of members actually result in knowledge sharing. Design/methodology/approach – To test the hypothesis, quantitative data were collected through an online questionnaire survey of OSS web developers with the aim of gathering respondents’ opinions concerning knowledge sharing, motivations to share knowledge and satisfaction with the management of OSS projects. Factor analysis, descriptive analysis, correlation analysis and regression analysis were used to explore the survey data. Findings – The analysis of the data reveals that the individual participant’s satisfaction with the management of an OSS project is an important factor influencing the extent of their personal contribution to a community. Originality/value – Little attention has been devoted to understanding the impact of management in OSS communities. Focused on OSS developers specialising in web development, the findings of this paper offer an important original contribution to understanding the connections between individual members’ satisfaction with management and their motivations to contribute to an OSS project. The findings reveal that motivations to share knowledge in online communities are influenced by the quality of management. Consequently, the findings suggest that appropriate management can enhance knowledge sharing in OSS projects and online communities, and organisations more generally.


Author(s):  
Mr. Kiran Mudaraddi

The paper presents a deep learning-based methodology for detecting social distancing in order to assess the distance between people in order to mitigate the impact of the coronavirus pandemic. The input was a video frame from the camera, and the open-source object detection was pre-trained. The outcome demonstrates that the suggested method is capable of determining the social distancing measures between many participants in a video.


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