Maritime authorities (MA) must track fishing vessels to ensure that fishing activities are limited to permitted areas. If illegal fishing is suspected, resources must be allocated to intercept and inspect the vessels....
Maritime authorities (MA) must track fishing vessels to ensure that fishing activities are limited to permitted areas. If illegal fishing is suspected, resources must be allocated to intercept and inspect the vessels. Thus, a false flag by the MA is costly, so it is important to use accurate detection methods. We compare the accuracy and computational time of the main approaches for detecting fishing activities described in the literature, using the Global Fishing Watch (GFW) dataset. We find that Long Short-Term Memory (LSTM) neural networks achieves an optimal accuracy of 1.00, while the random forest approach comes second with an accuracy of 0.87. Given the high cost of mistakes for MA, we conclude that the LSTM's high computational cost is worthwhile.
Recent Artificial Intelligence advancements raise concerns about the future of work, particularly technological unemployment. Studies show automation's impact, but tools like ChatGPT disrupt even traditionally sec...
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ISBN:
(数字)9781665410205
ISBN:
(纸本)9781665410212
Recent Artificial Intelligence advancements raise concerns about the future of work, particularly technological unemployment. Studies show automation's impact, but tools like ChatGPT disrupt even traditionally secure professions like programming. In this study, we reevaluate AI's effects using a method to assess the impact of Generative AI technologies on occupations to understand the potential effects of Generative AI systems on software development work. Valuable insights were obtained by gathering the view of a group of workers, primarily composed of developers who are starting their careers, regarding the impact of these technologies on the tasks they perform to provide a comprehensive understanding of the implications of Generative AI for software development. Results show that all programming tasks performed by these workers would experience some impact by Generative AI -65% of the tasks being considerably impacted, 12% moderately impacted, and 18% minimally impacted. This analysis highlights the substantial influence of Generative AI technologies on software development, mainly affecting those in the early stages of their career. The results of this work contribute to the academic community with valuable information. Policymakers can also use this information, as this work provides a comprehensive view of the impacts of Generative AI on software developers, considering their direct impact on job tasks.
This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requ...
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ISBN:
(纸本)9781450311786
This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requires analyzing all combinations of candidate projects, which is unfeasible when more than a few alternatives are available. We have used a multiobjective genetic algorithm to partially explore the search space of project combinations and select the most effective ones. We present an experimental study based on four project selection problems that compares the results found by the genetic algorithm to those yielded by a non-systematic search procedure. Results show evidence that the project selection technique can be used in large-scale scenarios and that GA presents better results than simpler search strategy. Copyright is held by the author/owner(s).
Since 2016, the demand for remote work has grown by nearly 400%, with 3.5 million remote job vacancies posted, and it is expected to continue to grow in the coming years. Therefore, one of the challenges in advancing ...
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ISBN:
(数字)9781665410205
ISBN:
(纸本)9781665410212
Since 2016, the demand for remote work has grown by nearly 400%, with 3.5 million remote job vacancies posted, and it is expected to continue to grow in the coming years. Therefore, one of the challenges in advancing remote work is fostering innovation, particularly serendipity, in a remote workforce. This fortunate discovery can pave the way for technological advancements, new business strategies, or even scientific revolutions. However, creating moments of serendipity in a remote work environment is a significant challenge. Thus, finding the right approach to stimulate serendipity in a remote work environment is an ever-evolving challenge. Therefore, this work aims to understand the possibilities of serendipity that collaboration tools used in remote work can support. The methodology used for this work was a Rapid Review. First, we explore the factors related to serendipity in physical offices, for which we identified twenty-three elements. Next, we compiled 38 strategies for remote work that were found to promote serendipity, which we organized in a framework for better observation. Our findings can serve as a starting point for designing new tools and identifying existing software and tools that already play a supportive role.
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.
Future-related studies are key in identifying and predicting emerging technologies, fostering innovation, and driving scientific progress. Games have increasingly served as a tool to engage researchers in Technology F...
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ISBN:
(数字)9781665410205
ISBN:
(纸本)9781665410212
Future-related studies are key in identifying and predicting emerging technologies, fostering innovation, and driving scientific progress. Games have increasingly served as a tool to engage researchers in Technology Forecasting and Foresight activities, presenting a gamified approach to gather, analyze, and synthesize information to allow future foresight. In this work, we use the Rapid Review methodology to analyze the scientific literature and explore the use of games as tools for Technology Forecasting and Foresight. We analyzed and categorized the articles by theme and type of study, identifying the areas where games can be most beneficial to guide professionals performing Technology Forecasting and Foresight, helping companies and governments better understand the future. The empirical evidence found provides a comprehensive understanding of how games can enhance foresight activities and contribute to the success of Technology Forecasting and Foresight initiatives. Our analysis also provides insights for future research about gamified strategies in Foresight.
作者:
De Brito, Halisson MatosStrauch, JuliaDe Souza, Jano MoreiraOsthoff, CarlaCOPPE/UFRJ
Systems Engineering and Computer Science Program Federal University of Rio de Janeiro PO Box 68511 ZIP Code: 21945-970 Rio de Janeiro RJ Brazil ENCE /IBGE
National School of Statistical Sciences 106 S. 401 ZIP Code: 20231-050 R. André Cavalcanti Rio de Janeiro RJ Brazil LNCC
National Laboratory for Scientific Computing Av. Getulio 333 Quitandinha Vargas Petrópolis RJ Brazil IM/UFRJ
Institute of Mathematics Federal University of Rio de Janeiro PO Box 68511 ZIP Code: 21945-970 Rio de Janeiro RJ Brazil
This paper presents MODENA, an architecture for scientific models management using Computational Grid platform. This architecture is comprised of two systems: ModManager and ModRunner. ModManager deals with knowledge ...
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This paper presents MODENA, an architecture for scientific models management using Computational Grid platform. This architecture is comprised of two systems: ModManager and ModRunner. ModManager deals with knowledge management about scientific models, acting as a scientific models library allowing for cataloguing, searching, reutilization and generation of new models. To achieve this, a metamodel is proposed to classify models, in order to support the organization, searching and retrieving of models. ModRunner manages the execution of models in a Grid environment allowing for model composition to generate a scientific Grid Workflow to be executed by distributed services offered by Grid Services. An initial prototype of ModManager is presented.
The main knowledge management challenges are to capture, store and reuse contextual knowledge generated during interactions that occur daily in an organization. In this paper, we propose an activity context-aware arch...
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The main knowledge management challenges are to capture, store and reuse contextual knowledge generated during interactions that occur daily in an organization. In this paper, we propose an activity context-aware architecture to support knowledge management in working processes. The required features for this architecture are processing, reasoning and sharing contextual knowledge involving information about activities performed. We also present results from evaluation of our proposal — A-CoBrA — for a specific domain.
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