Interest in artificial intelligence (AI)-driven crowd work has increased during the last few years as a line of inquiry that expands upon prior research on microtasking to represent a means of scaling up complex tasks...
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ISBN:
(数字)9798331510886
ISBN:
(纸本)9798331510893
Interest in artificial intelligence (AI)-driven crowd work has increased during the last few years as a line of inquiry that expands upon prior research on microtasking to represent a means of scaling up complex tasks through AI mediation. Despite the increasing attention to the macrotask phenomenon in crowdsourcing, there is a need to understand the processes, elements, and constraints underlying the infrastructural and behavioral aspects in such form of crowd work when involving collaboration. To this end, this paper provides a first attempt to characterize some of the research conducted in this direction to identify important paths for an agenda comprising key drivers, challenges, and prospects for integrating human-centered AI in collaborative crowdsourcing environments.
In Software engineering, context can be understood as the overall set of information used to characterize the situation of an entity. A software system is context-aware if it uses the context to provide relevant infor...
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The evolution of science has been supported by complex computerized infrastructures with growing interest in simulation based experiments. This trend can also be observed in Software engineering. Our capacity of acqui...
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Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory ...
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Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory flow and to evaluate the knowledge of undergraduate students in handling the SIB. To reduce the risks of mortality, length of hospital stay, and infections, SIB is a resource used to ventilate the patient through the inflation of the device, but it is not capable of measuring the ventilatory parameters. Excess ventilation and incorrect handling of the bag can cause lung injury in newborns. Therefore, measuring these parameters can prevent lung injury resulting from inadequate ventilation. Method: This is a cross-sectional and experimental study, with the development of a device SIB that allows the evaluation of variables of neonatal respiratory mechanics that were tested with an artificial lung. It was approved by the Research Ethics Committee and the research was developed in three stages: the first represents the search for scientific articles for the consensus of neonatal ventilatory variables for the construction of the SIB parameters;the second stage depicts the technological development of a device capable of monitoring such variables through the SIB. In the third stage, the content validation of the device with the handling of the SIB was carried out by students of medicine and physiotherapy courses of Brazil. Results: In this work, a device that analyzes the values of the main ventilatory parameters in neonatology was developed and to generate a safety range for the use of the device, curves with a tolerance of 10% up and down were created. All electronic components were coupled to the equipment, with a display that transmits the parameter values. The web page can be used on a cell phone, tablet, computer, or SmartTv, as long as it is connected to the "RespiratorIoT_AP" network. Among the 29 participants in the study, 8 said they were familiar w
Knowledge resource and information system/technology (IS/IT) capability have been considered to improve firm performance, however there is still a gap regarding the sustainability of supply chain to face and recover f...
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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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Speculative Multithreading (SpMT) increases the performance by means of executing multiple threads speculatively to exploit thread-level parallelism. By combining software and hardware approaches, we have improved the...
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Non-adherence to medications is a critical concern since nearly half of patients with chronic illnesses do not follow their prescribed medication regimens, leading to increased mortality, costs, and preventable human ...
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Non-adherence to medications is a critical concern since nearly half of patients with chronic illnesses do not follow their prescribed medication regimens, leading to increased mortality, costs, and preventable human distress. Amongst stage 0-3 breast cancer survivors, adherence to long-term adjuvant endocrine therapy (i.e., Tamoxifen and aromatase inhibitors) is associated with a significant increase in recurrence-free survival. This work aims to develop multi-scale models of medication adherence to understand the significance of different factors influencing adherence across varying time frames. We introduce a computational framework guided by Social Cognitive Theory for multi-scale (daily and weekly) modeling of longitudinal medication adherence. Our models employ both dynamic medication-taking patterns in the recent past (dynamic factors) as well as less frequently changing factors (static factors) for adherence prediction. Additionally, we assess the significance of various factors in influencing adherence behavior across different time scales. Our models outperform traditional machine learning counterparts in both daily and weekly tasks in terms of both accuracy and specificity. Daily models achieved an accuracy of 87.25% (Precision – 92.04%, Recall – 93.15%, Specificity – 77.50%), and weekly models, an accuracy of 76.04% (Precision – 75.83%, Recall – 85.80%, Specificity – 72.30%). Notably, dynamic past medication-taking patterns prove most valuable for predicting daily adherence, while a combination of dynamic and static factors is significant for macro-level weekly adherence patterns. While our models exhibit strong predictive performance, they are constrained by potential cohort-specific biases, reliance on self-reported adherence data, and a limited understanding of the context around non-adherence. Future research will focus on external validation across diverse populations and explore the real-world implementation of sensor-rich systems for a more compre
In this paper we present the architecture for the Personal Autonomic Desktop Manager, a self managing application designed to act on behalf of the user in several aspects: protection, healing, optimization and configu...
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ISBN:
(纸本)9780769531403
In this paper we present the architecture for the Personal Autonomic Desktop Manager, a self managing application designed to act on behalf of the user in several aspects: protection, healing, optimization and configuration. The overall goal of this research is to improve the correlation of the autonomic self* properties and doing so also enhance the overall self-management capacity of the desktop (autonomicity). We introduce the Circulatory Computing (CC) model, a self-managing system initiative based on the biological metaphor of the cardiovascular system, and use its concepts in the design and implementation of the architecture.
Business processes are dynamic and constantly evolving. Contextual elements that had not yet been identified and represented can arise and influence the execution of each process instance in diverse manners. In this s...
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