A risk prediction model for software project management based on similarity analysis of context histories

Filippetto, Alexsandro; Lima, Robson; Barbosa, Jorge Luís Victória

doi:10.1016/j.infsof.2020.106497

Cited by 86 publications

(51 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Vital sign analysis may support health-related decision making. In this sense, the vital signs collected by applications can be formatted as contexts (D'Avila et al 2020), stored in chronological databases Barbosa 2019, 2020), and used for context predictions (da Rosa et al 2016;Filippetto et al 2021). Based on these databases, researchers can design tests of analytical techniques to verify their real effectiveness in assisting health systems.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A computational model for adaptive recording of vital signs through context histories

Aranda

Bavaresco

Carvalho

et al. 2021

J Ambient Intell Human Comput

Self Cite

View full text Add to dashboard Cite

Wearable devices emerged from the advancement of communication technology and the miniaturization of electronic components. These devices periodically monitor the user's vital signs and generally have a short battery life. This work introduces ODIN, a model for optimized vital signs collection based on adaptive rules. Analyzing vital sign values requires preciseness, so the adaption of these collected data allows a personalized analysis of the user's health condition. The comparison with related works indicates that ODIN is the only model that presents context-aware-adaptive vital signs collection. The implementation of a prototype allowed to perform three evaluations of ODIN. The first evaluation used simulations in different scenarios, with the adaptive approach increasing battery life by 119% through the analysis of input data compared to data collection without adaptivity. The second evaluation applied the prototype to a database of real physiologic data, which allowed reduced data collection when the user has regular vital signs. This reduction optimized battery consumption by 66% compared to collection without adaptivity. Finally, the third evaluation applied ODIN through an Arduino and a heart rate monitor (Polar H7). The average power saved across mobile devices was 21%. Consequently, the adaptive strategy presented in this work allows the optimization of computational resources during the collection and analysis of vital signs. This optimization occurs because of the reduction in energy expenditure and the reduction in the amount of data that needs to be collected and stored.

show abstract

Section: Related Workmentioning

confidence: 99%

“… 2016 ; Filippetto et al. 2021 ). Based on these databases, researchers can design tests of analytical techniques to verify their real effectiveness in assisting health systems.…”

Section: Related Workmentioning

confidence: 99%

A computational model for adaptive recording of vital signs through context histories

Aranda

Bavaresco

Carvalho

et al. 2021

J Ambient Intell Human Comput

Self Cite

View full text Add to dashboard Cite

show abstract

“…This new research area received the name of Context Histories [37], [38], [39], [40] or Trails [41], [42]. This kind of data organization allows the exploration of advance strategies to data analysis, such as, profile management [43], [44], [45], [46], [47], pattern analysis [48], context prediction [49] and similarity analysis [50], [51]. All these strategies allowed the use of Learning Analytics [52], [53].…”

Section: Context-aware Ubiquitous Learningmentioning

confidence: 99%

ULearnEnglish: An open Ubiquitous System for Assisting in the English Vocabulary Learning

Silva¹,

EGdA²,

Rodríguez‐Sánchez³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Language learners often face communication problems when they need to express themselves and do not have this ability. On the other hand, continuous advances in technology create new opportunities to improve second language (L2) acquisition through context-aware ubiquitous learning (CAUL) technology. Since vocabulary is the foundation of all language acquisition, this article presents the ULearnEnglish, an open-source system to allow ubiquitous English learning focused on incidental vocabulary acquisition. To evaluate the proposal, 15 learners used the system developed, and 10 answered a survey based on the Technology Acceptance Model (TAM). Results indicate a favorable response to the use of the learner context to assist them in their learning. The ULearnEnglish achieved an acceptance of 78.66% for the perception of the utility, 96% for the perception of ease of use, 86% for user context assessment, and 88% for ubiquity. This study presented a positive response in using the location of users to assist their learning. Among the main contributions, this study demonstrates an opportunity for ubiquity use in future research in language learning. Also, furthers studies can use the source available to evolve the model and system.

show abstract

“…Future work will explore the use of Context Histories to organize the data produced during the workshops, allowing the use of these data to include intelligence in patient care environments. In this sense, the project will explore advanced data analysis strategies such as pattern analysis [61], context prediction [62], learning analytics [63,64], and similarity and similarity analysis [65,66]. These strategies for handling context histories will be applied in the analysis of project data, mainly enabling prediction, personalization and content recommendation to improve the user experience.…”

Section: Final Remarksmentioning

confidence: 99%

Learning and Well-being in Educational Practices with Children and Adolescents Undergoing Cancer Treatment

Santos¹,

Barbosa²,

Neto³

et al. 2021

Preprint

View full text Add to dashboard Cite

The use of Information Communication Technologies (ICT) in education brings up new possibilities of promoting the learning and health experiences. In this sense, education contexts of 21st century must consider these two areas of knowledge, especially their integration. This article presents learning practices developed with mobile devices and games, in order to improve learning and well-being in children and adolescents undergoing cancer treatment in non-formal educational setting. The methodology is based on qualitative case studies with content-based data analysis, involving informal interviews and observation methods. The study considers data from 5 patients who participated in the research between 2015 and 2019. The results demonstrate a positive influence of the practices with mobile technologies and games in terms of learning and in the well-being feeling of patients during the treatment.

show abstract

A risk prediction model for software project management based on similarity analysis of context histories

Cited by 86 publications

References 15 publications

A computational model for adaptive recording of vital signs through context histories

A computational model for adaptive recording of vital signs through context histories

ULearnEnglish: An open Ubiquitous System for Assisting in the English Vocabulary Learning

Learning and Well-being in Educational Practices with Children and Adolescents Undergoing Cancer Treatment

Contact Info

Product

Resources

About