Over the past decades, the use of digital technologies to support participatory urban planning and design has been repeatedly described as a crucial instrument and critical building block for tackling historical probl...
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ISBN:
(纸本)9781728165974;9781728165981
Over the past decades, the use of digital technologies to support participatory urban planning and design has been repeatedly described as a crucial instrument and critical building block for tackling historical problems of participation in such processes. Social media, e-participation platforms, and crowdsourcing applications are examples of technologies that can involve citizens in decision-making processes and thus leverage the benefits of collective intelligence. However, despite the extensive use of social media platforms, old problems related to engagement and participation still occur in digital initiatives. Successful collaboration examples between citizens, policymakers, and strategic stakeholders are still scarce based on online social practices. This study aims to introduce a collective intelligence model, which combines crowdsourcing and social storytelling to support participatory urban planning and design from a bottom-up perspective. The paper concludes by discussing a scenario where citizens can engage in mapping, taking photos, sending ideas, or even creating collective stories about their university issues in a post-pandemic future.
Over the past decade, online crowdsourcing has established itself as an emerging paradigm that industry and government have been using to harness the cognitive abilities of a multitude of users distributed around the ...
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ISBN:
(数字)9781728185262
ISBN:
(纸本)9781728185279
Over the past decade, online crowdsourcing has established itself as an emerging paradigm that industry and government have been using to harness the cognitive abilities of a multitude of users distributed around the world. In this context, microtask crowdsourcing has become the method of choice for addressing a wide range of diverse problems. Microtasks typically require a minimum of time and cognitive effort, but combined individual efforts have made it possible to accomplish great achievements. The goal of this paper is to contribute to the ongoing effort of understanding whether the same success that microtask crowdsourcing has achieved in other domains can be obtained in the field of social news curation. In particular, we ask whether it is possible to turn online news curation, typically a social and collaborative activity on the Web, into a model in which curatorial activities are mapped into microtasks to be performed by a crowd of online users.
Software development depends on diverse technologies and methods and as a result, software development teams often handle issues in which team members are not experts. In order to address this lack of expertise, devel...
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It is expected that managing process variations and organizing process domain knowledge in a reusable way can provide support to handle complexity in software process definition. In this context, the purpose of this p...
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Software processes have been the focus of discussion in literature, but defining a software process remains a challenge. The Software Process Line (SPrL) technique offers a systematic process reuse approach that ident...
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ISBN:
(纸本)9781728104386
Software processes have been the focus of discussion in literature, but defining a software process remains a challenge. The Software Process Line (SPrL) technique offers a systematic process reuse approach that identifies processes' similarities and variability. This study aims to characterize the state-of-the-art of the software process definition using SPrL. A Systematic Literature Review (SLR) was conducted and 26 papers were identified to be studied in depth. The results indicate a concentration of approaches that use mapping/rules techniques to support variability resolution and the need for integrated supporting tools. In addition, three problems that affect the software process definition using SPrL were observed: (1) low understanding of SPrL models complexity and their impact, (2) lack of understanding about the impacts of the defined software process, and (3) experts' knowledge dependence issues in decision-making to solve variability.
The extreme learning machine (ELM) is known for being a fast learning neural model. This work presents a performance comparison between ELM and the WiSARD weightless neural network model, regarding training and testin...
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Context: Several code guidelines aim at providing a common perspective on the readability and comprehensibility of source code. However, in many cases, they are contradictory on how to improve these quality characteri...
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ISBN:
(纸本)9789873806988
Context: Several code guidelines aim at providing a common perspective on the readability and comprehensibility of source code. However, in many cases, they are contradictory on how to improve these quality characteristics. Objective: To analyze the influence of three contradictory source code attributes - indentation spacing, identifier length and code size - on the source code reada-bility and comprehensibility, interpreting whether programming experience and domain knowledge can support explaining these contradictions. Method: To per-form an empirical study with software developers collecting quantitative (Likert scale) and qualitative data to assess the readability and comprehensibility of de-velopers regarding Python snippets. To observe eventual perceptions contradic-tions and whether their levels of experience and knowledge have something to do with such contrary results. Results: Regardless their programming experience, 4-spaces indentation dominated the readability preference of participants. While the readability and comprehensibility preferences towards long and complete-word identifiers were mostly true for both novice/experts, developers with more experience and low domain knowledge level seemed to be more affected by the length of identifiers. Furthermore, while all participants showed more positive comprehensibility perceptions for Pythin snippets with more lines of code, their readability perceptions regardnig code size were contradictory since the less experienced participants preferred more lines of code and the more experienced ones prefer fewer lines. Conclusion: The results presented in the technical literature seemed to be caused by the interchangeable use of the readability and comprehensibility concepts. Further investigation is still needed to observe whether other confounding factors might support the explanation of such contrary results.
The ubiquity of smartphones creates great opportunities for participatory sensing, where people can implicitly contribute observations about their local environments through sensors such as cameras and accelerometers....
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The ubiquity of smartphones creates great opportunities for participatory sensing, where people can implicitly contribute observations about their local environments through sensors such as cameras and accelerometers. The collected data can then be aggregated and used to benefit the crowd in some way. In this paper, we report on the current development of Sherlock, a device capable of automatically detecting the presence of people in localities through evidences left by smartphones called probe requests, without any user intervention. To validate the proposed mechanism implemented in the device, we performed an experiment with ten participants in six rounds where it was possible to automatically detect 41 presence events, of which 66% could be detected within less than 30s. The implicit crowdsourcing mechanism behind this approach may allow real-time monitoring of people flows in public environments, which can enable, among other things, energy systems to be automatically orchestrated according to demand, reducing associated costs.
Link Prediction is a classic social networks analysis problem. Knowing in advance future actions in social network can help, for example, agents decision. Link Prediction techniques are based on metrics that have diff...
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ISBN:
(纸本)9781509019168
Link Prediction is a classic social networks analysis problem. Knowing in advance future actions in social network can help, for example, agents decision. Link Prediction techniques are based on metrics that have different approaches. In this paper, we model a multi-relational scientific social network to assess the impact of content extraction on topological metrics. Thus, a metric composed of topological and semantic approach is proposed to solve link prediction problem. The results were compared with those presented by Katz metric.
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